2025-10-27 11:12:37.381343: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:12:37.394225: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761559957.407906  522138 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761559957.412212  522138 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761559957.423473  522138 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761559957.423516  522138 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761559957.423519  522138 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761559957.423522  522138 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:12:37.427025: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/tune/impl/tuner_internal.py:144: RayDeprecationWarning: The `RunConfig` class should be imported from `ray.tune` when passing it to the Tuner. Please update your imports. See this issue for more context and migration options: https://github.com/ray-project/ray/issues/49454. Disable these warnings by setting the environment variable: RAY_TRAIN_ENABLE_V2_MIGRATION_WARNINGS=0
  _log_deprecation_warning(
2025-10-27 11:12:54,765	INFO worker.py:1927 -- Started a local Ray instance.
2025-10-27 11:12:55,418	INFO tune.py:253 -- Initializing Ray automatically. For cluster usage or custom Ray initialization, call `ray.init(...)` before `Tuner(...)`.
2025-10-27 11:12:55,485	INFO trial.py:182 -- Creating a new dirname dir_815ce_7ae0 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,487	INFO trial.py:182 -- Creating a new dirname dir_815ce_fcaa because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,491	INFO trial.py:182 -- Creating a new dirname dir_815ce_97e3 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,495	INFO trial.py:182 -- Creating a new dirname dir_815ce_e462 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,497	INFO trial.py:182 -- Creating a new dirname dir_815ce_2a0a because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,499	INFO trial.py:182 -- Creating a new dirname dir_815ce_f132 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,501	INFO trial.py:182 -- Creating a new dirname dir_815ce_8b50 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,504	INFO trial.py:182 -- Creating a new dirname dir_815ce_354e because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,508	INFO trial.py:182 -- Creating a new dirname dir_815ce_b645 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,511	INFO trial.py:182 -- Creating a new dirname dir_815ce_ecfe because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,513	INFO trial.py:182 -- Creating a new dirname dir_815ce_1a33 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,516	INFO trial.py:182 -- Creating a new dirname dir_815ce_3a0a because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,519	INFO trial.py:182 -- Creating a new dirname dir_815ce_6db5 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,522	INFO trial.py:182 -- Creating a new dirname dir_815ce_c1c3 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,526	INFO trial.py:182 -- Creating a new dirname dir_815ce_f5c7 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,529	INFO trial.py:182 -- Creating a new dirname dir_815ce_2dc3 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,534	INFO trial.py:182 -- Creating a new dirname dir_815ce_cbf5 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,538	INFO trial.py:182 -- Creating a new dirname dir_815ce_f080 because trial dirname 'dir_815ce' already exists.
2025-10-27 11:12:55,541	INFO trial.py:182 -- Creating a new dirname dir_815ce_741c because trial dirname 'dir_815ce' already exists.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
Se lanza la búsqueda de hiperparámetros óptimos del modelo.
╭───────────────────────────────────────────────────────────────────╮
│ Configuration for experiment     XGBoost_hyperparameters_tuning   │
├───────────────────────────────────────────────────────────────────┤
│ Search algorithm                 BasicVariantGenerator            │
│ Scheduler                        AsyncHyperBandScheduler          │
│ Number of trials                 20                               │
╰───────────────────────────────────────────────────────────────────╯

View detailed results here: /mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_C/case_C_XGB_acc_gyr_17_classes/XGBoost_hyperparameters_tuning
To visualize your results with TensorBoard, run: `tensorboard --logdir /tmp/ray/session_2025-10-27_11-12-53_041501_522138/artifacts/2025-10-27_11-12-55/XGBoost_hyperparameters_tuning/driver_artifacts`

Trial status: 20 PENDING
Current time: 2025-10-27 11:12:55. Total running time: 0s
Logical resource usage: 0/20 CPUs, 0/1 GPUs (0.0/1.0 accelerator_type:G)
╭──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ Trial name     status       num_boost_round     max_depth     learning_rate     subsample     colsample_bytree      gamma     min_child_weight     reg_alpha     reg_lambda     random_state │
├──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ trial_815ce    PENDING                  591             3        0.0085005       0.528068             0.538545   27.6444                    84       2.77301        5.6084              9789 │
│ trial_815ce    PENDING                  682             2        0.0146801       0.785254             0.713742   28.1164                   148     230.112          6.03871             4262 │
│ trial_815ce    PENDING                  291             2        0.0124667       0.824162             0.57164     5.27421                   62      12.8313       296.871               7779 │
│ trial_815ce    PENDING                  373             2        0.00615249      0.817785             0.660271   13.2957                   157      21.6249       164.981               7724 │
│ trial_815ce    PENDING                  718             3        0.0132957       0.580279             0.509772   29.263                    112      36.2913        67.778               6110 │
│ trial_815ce    PENDING                  626             2        0.0197307       0.760867             0.834172   29.7125                    95     297.768         97.9173               518 │
│ trial_815ce    PENDING                  647             2        0.0191399       0.637997             0.641773   14.3746                   139      72.7003       158.825               5669 │
│ trial_815ce    PENDING                  284             2        0.00785538      0.70404              0.765188   29.8994                   171       2.05829       32.3756              7624 │
│ trial_815ce    PENDING                  402             3        0.0183588       0.507052             0.829074    6.27376                   78      10.5642       623.61                7375 │
│ trial_815ce    PENDING                  756             2        0.0198547       0.539038             0.656365    9.29435                   97      16.981         42.2814              4597 │
│ trial_815ce    PENDING                  743             3        0.00571989      0.512015             0.664965   21.0431                   119      20.2153       476.006               5012 │
│ trial_815ce    PENDING                  445             2        0.011522        0.543758             0.820794   11.8266                   144       2.06773      886.585               5060 │
│ trial_815ce    PENDING                  714             3        0.0184111       0.611159             0.652786    8.01805                   76      15.9429        41.985                274 │
│ trial_815ce    PENDING                  735             2        0.0129654       0.753519             0.546044    7.53437                  109      77.9489       132.385               2413 │
│ trial_815ce    PENDING                  789             3        0.0171509       0.536051             0.50909    24.0376                    63     939.294        903.31                3632 │
│ trial_815ce    PENDING                  224             3        0.0188875       0.765795             0.63462    23.754                    147     293.798        248.333               8671 │
│ trial_815ce    PENDING                  467             3        0.019242        0.80582              0.523636   10.4785                   156      43.0216        47.2207              9252 │
│ trial_815ce    PENDING                  598             3        0.0135708       0.623241             0.761129   14.8588                    71       1.37779       20.6734              6349 │
│ trial_815ce    PENDING                  567             2        0.00814755      0.728638             0.827736    9.36595                  126      57.4077        13.7875              8719 │
│ trial_815ce    PENDING                  217             2        0.0148705       0.565127             0.574846   24.1135                   101     145.722          6.90155             4616 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.52364 │
│ gamma                        10.4785 │
│ learning_rate                0.01924 │
│ max_depth                          3 │
│ min_child_weight                 156 │
│ num_boost_round                  467 │
│ random_state                    9252 │
│ reg_alpha                    43.0216 │
│ reg_lambda                   47.2207 │
│ subsample                    0.80582 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.65637 │
│ gamma                        9.29435 │
│ learning_rate                0.01985 │
│ max_depth                          2 │
│ min_child_weight                  97 │
│ num_boost_round                  756 │
│ random_state                    4597 │
│ reg_alpha                     16.981 │
│ reg_lambda                   42.2814 │
│ subsample                    0.53904 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.50977 │
│ gamma                         29.263 │
│ learning_rate                 0.0133 │
│ max_depth                          3 │
│ min_child_weight                 112 │
│ num_boost_round                  718 │
│ random_state                    6110 │
│ reg_alpha                    36.2913 │
│ reg_lambda                    67.778 │
│ subsample                    0.58028 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.57164 │
│ gamma                        5.27421 │
│ learning_rate                0.01247 │
│ max_depth                          2 │
│ min_child_weight                  62 │
│ num_boost_round                  291 │
│ random_state                    7779 │
│ reg_alpha                    12.8313 │
│ reg_lambda                   296.871 │
│ subsample                    0.82416 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.82774 │
│ gamma                        9.36595 │
│ learning_rate                0.00815 │
│ max_depth                          2 │
│ min_child_weight                 126 │
│ num_boost_round                  567 │
│ random_state                    8719 │
│ reg_alpha                    57.4077 │
│ reg_lambda                   13.7875 │
│ subsample                    0.72864 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.71374 │
│ gamma                        28.1164 │
│ learning_rate                0.01468 │
│ max_depth                          2 │
│ min_child_weight                 148 │
│ num_boost_round                  682 │
│ random_state                    4262 │
│ reg_alpha                    230.112 │
│ reg_lambda                   6.03871 │
│ subsample                    0.78525 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.76113 │
│ gamma                        14.8588 │
│ learning_rate                0.01357 │
│ max_depth                          3 │
│ min_child_weight                  71 │
│ num_boost_round                  598 │
│ random_state                    6349 │
│ reg_alpha                    1.37779 │
│ reg_lambda                   20.6734 │
│ subsample                    0.62324 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.57485 │
│ gamma                        24.1135 │
│ learning_rate                0.01487 │
│ max_depth                          2 │
│ min_child_weight                 101 │
│ num_boost_round                  217 │
│ random_state                    4616 │
│ reg_alpha                    145.722 │
│ reg_lambda                   6.90155 │
│ subsample                    0.56513 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.53854 │
│ gamma                        27.6444 │
│ learning_rate                 0.0085 │
│ max_depth                          3 │
│ min_child_weight                  84 │
│ num_boost_round                  591 │
│ random_state                    9789 │
│ reg_alpha                    2.77301 │
│ reg_lambda                    5.6084 │
│ subsample                    0.52807 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.83417 │
│ gamma                        29.7125 │
│ learning_rate                0.01973 │
│ max_depth                          2 │
│ min_child_weight                  95 │
│ num_boost_round                  626 │
│ random_state                     518 │
│ reg_alpha                    297.768 │
│ reg_lambda                   97.9173 │
│ subsample                    0.76087 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.82907 │
│ gamma                        6.27376 │
│ learning_rate                0.01836 │
│ max_depth                          3 │
│ min_child_weight                  78 │
│ num_boost_round                  402 │
│ random_state                    7375 │
│ reg_alpha                    10.5642 │
│ reg_lambda                    623.61 │
│ subsample                    0.50705 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.82079 │
│ gamma                        11.8266 │
│ learning_rate                0.01152 │
│ max_depth                          2 │
│ min_child_weight                 144 │
│ num_boost_round                  445 │
│ random_state                    5060 │
│ reg_alpha                    2.06773 │
│ reg_lambda                   886.585 │
│ subsample                    0.54376 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.54604 │
│ gamma                        7.53437 │
│ learning_rate                0.01297 │
│ max_depth                          2 │
│ min_child_weight                 109 │
│ num_boost_round                  735 │
│ random_state                    2413 │
│ reg_alpha                    77.9489 │
│ reg_lambda                   132.385 │
│ subsample                    0.75352 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.63462 │
│ gamma                         23.754 │
│ learning_rate                0.01889 │
│ max_depth                          3 │
│ min_child_weight                 147 │
│ num_boost_round                  224 │
│ random_state                    8671 │
│ reg_alpha                    293.798 │
│ reg_lambda                   248.333 │
│ subsample                     0.7658 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.76519 │
│ gamma                        29.8994 │
│ learning_rate                0.00786 │
│ max_depth                          2 │
│ min_child_weight                 171 │
│ num_boost_round                  284 │
│ random_state                    7624 │
│ reg_alpha                    2.05829 │
│ reg_lambda                   32.3756 │
│ subsample                    0.70404 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.66027 │
│ gamma                        13.2957 │
│ learning_rate                0.00615 │
│ max_depth                          2 │
│ min_child_weight                 157 │
│ num_boost_round                  373 │
│ random_state                    7724 │
│ reg_alpha                    21.6249 │
│ reg_lambda                   164.981 │
│ subsample                    0.81778 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.66497 │
│ gamma                        21.0432 │
│ learning_rate                0.00572 │
│ max_depth                          3 │
│ min_child_weight                 119 │
│ num_boost_round                  743 │
│ random_state                    5012 │
│ reg_alpha                    20.2153 │
│ reg_lambda                   476.006 │
│ subsample                    0.51201 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.65279 │
│ gamma                        8.01805 │
│ learning_rate                0.01841 │
│ max_depth                          3 │
│ min_child_weight                  76 │
│ num_boost_round                  714 │
│ random_state                     274 │
│ reg_alpha                    15.9429 │
│ reg_lambda                    41.985 │
│ subsample                    0.61116 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
[36m(train_xgb_ray_tune pid=524079)[0m 2025-10-27 11:12:58.984679: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
[36m(train_xgb_ray_tune pid=524075)[0m 2025-10-27 11:12:59.027909: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
[36m(train_xgb_ray_tune pid=524075)[0m WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
[36m(train_xgb_ray_tune pid=524075)[0m E0000 00:00:1761559979.055718  525229 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
[36m(train_xgb_ray_tune pid=524075)[0m E0000 00:00:1761559979.063734  525229 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
[36m(train_xgb_ray_tune pid=524075)[0m W0000 00:00:1761559979.084324  525229 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
[36m(train_xgb_ray_tune pid=524075)[0m W0000 00:00:1761559979.084366  525229 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
[36m(train_xgb_ray_tune pid=524075)[0m W0000 00:00:1761559979.084368  525229 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
[36m(train_xgb_ray_tune pid=524075)[0m W0000 00:00:1761559979.084370  525229 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
[36m(train_xgb_ray_tune pid=524075)[0m 2025-10-27 11:12:59.090268: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
[36m(train_xgb_ray_tune pid=524075)[0m To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.50909 │
│ gamma                        24.0376 │
│ learning_rate                0.01715 │
│ max_depth                          3 │
│ min_child_weight                  63 │
│ num_boost_round                  789 │
│ random_state                    3632 │
│ reg_alpha                    939.294 │
│ reg_lambda                    903.31 │
│ subsample                    0.53605 │
╰──────────────────────────────────────╯
Trial trial_815ce started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_815ce config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.64177 │
│ gamma                        14.3746 │
│ learning_rate                0.01914 │
│ max_depth                          2 │
│ min_child_weight                 139 │
│ num_boost_round                  647 │
│ random_state                    5669 │
│ reg_alpha                    72.7003 │
│ reg_lambda                   158.825 │
│ subsample                      0.638 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=524075)[0m [0]	train-mlogloss:2.68675	validation-mlogloss:2.68598
[36m(train_xgb_ray_tune pid=524075)[0m [1]	train-mlogloss:2.66636	validation-mlogloss:2.66458
[36m(train_xgb_ray_tune pid=524079)[0m [0]	train-mlogloss:2.68698	validation-mlogloss:2.68716
[36m(train_xgb_ray_tune pid=524075)[0m [2]	train-mlogloss:2.64724	validation-mlogloss:2.64494
[36m(train_xgb_ray_tune pid=524044)[0m [0]	train-mlogloss:2.69893	validation-mlogloss:2.69916
[36m(train_xgb_ray_tune pid=524079)[0m [1]	train-mlogloss:2.66431	validation-mlogloss:2.66495
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[36m(train_xgb_ray_tune pid=524065)[0m [7]	train-mlogloss:2.66623	validation-mlogloss:2.66594
[36m(train_xgb_ray_tune pid=524078)[0m [16]	train-mlogloss:2.55969	validation-mlogloss:2.55776
[36m(train_xgb_ray_tune pid=524063)[0m [7]	train-mlogloss:2.66516	validation-mlogloss:2.66409
[36m(train_xgb_ray_tune pid=524080)[0m [5]	train-mlogloss:2.57338	validation-mlogloss:2.57489
[36m(train_xgb_ray_tune pid=524075)[0m [17]	train-mlogloss:2.39039	validation-mlogloss:2.38878
[36m(train_xgb_ray_tune pid=524081)[0m [6]	train-mlogloss:2.63596	validation-mlogloss:2.63447
[36m(train_xgb_ray_tune pid=524076)[0m [5]	train-mlogloss:2.68669	validation-mlogloss:2.68644
[36m(train_xgb_ray_tune pid=524046)[0m [13]	train-mlogloss:2.54642	validation-mlogloss:2.54779
[36m(train_xgb_ray_tune pid=524074)[0m [6]	train-mlogloss:2.69136	validation-mlogloss:2.69112
[36m(train_xgb_ray_tune pid=524079)[0m [13]	train-mlogloss:2.44536	validation-mlogloss:2.44952
[36m(train_xgb_ray_tune pid=524077)[0m [4]	train-mlogloss:2.61162	validation-mlogloss:2.61525
[36m(train_xgb_ray_tune pid=524060)[0m [10]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=524032)[0m [7]	train-mlogloss:2.61218	validation-mlogloss:2.61328
[36m(train_xgb_ray_tune pid=524045)[0m [6]	train-mlogloss:2.63003	validation-mlogloss:2.62833
[36m(train_xgb_ray_tune pid=524081)[0m [7]	train-mlogloss:2.62660	validation-mlogloss:2.62483
[36m(train_xgb_ray_tune pid=524038)[0m [5]	train-mlogloss:2.65925	validation-mlogloss:2.65833
[36m(train_xgb_ray_tune pid=524044)[0m [16]	train-mlogloss:2.56019	validation-mlogloss:2.55925
[36m(train_xgb_ray_tune pid=524063)[0m [8]	train-mlogloss:2.66017	validation-mlogloss:2.65891
[36m(train_xgb_ray_tune pid=524073)[0m [7]	train-mlogloss:2.65160	validation-mlogloss:2.65084
[36m(train_xgb_ray_tune pid=524066)[0m [7]	train-mlogloss:2.60821	validation-mlogloss:2.60773
[36m(train_xgb_ray_tune pid=524064)[0m [7]	train-mlogloss:2.63939	validation-mlogloss:2.63940
[36m(train_xgb_ray_tune pid=524065)[0m [8]	train-mlogloss:2.66087	validation-mlogloss:2.66059
[36m(train_xgb_ray_tune pid=524078)[0m [17]	train-mlogloss:2.55168	validation-mlogloss:2.54955
[36m(train_xgb_ray_tune pid=524072)[0m [9]	train-mlogloss:2.59236	validation-mlogloss:2.59068
[36m(train_xgb_ray_tune pid=524075)[0m [18]	train-mlogloss:2.37627	validation-mlogloss:2.37418
[36m(train_xgb_ray_tune pid=524060)[0m [11]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=524076)[0m [6]	train-mlogloss:2.68316	validation-mlogloss:2.68283
[36m(train_xgb_ray_tune pid=524046)[0m [14]	train-mlogloss:2.53607	validation-mlogloss:2.53745
[36m(train_xgb_ray_tune pid=524074)[0m [7]	train-mlogloss:2.68911	validation-mlogloss:2.68882
[36m(train_xgb_ray_tune pid=524079)[0m [14]	train-mlogloss:2.42984	validation-mlogloss:2.43405
[36m(train_xgb_ray_tune pid=524072)[0m [10]	train-mlogloss:2.58224	validation-mlogloss:2.58074
[36m(train_xgb_ray_tune pid=524078)[0m [18]	train-mlogloss:2.54410	validation-mlogloss:2.54190
[36m(train_xgb_ray_tune pid=524080)[0m [6]	train-mlogloss:2.55359	validation-mlogloss:2.55554
[36m(train_xgb_ray_tune pid=524038)[0m [6]	train-mlogloss:2.65189	validation-mlogloss:2.65072
[36m(train_xgb_ray_tune pid=524032)[0m [8]	train-mlogloss:2.60098	validation-mlogloss:2.60241
[36m(train_xgb_ray_tune pid=524045)[0m [7]	train-mlogloss:2.62006	validation-mlogloss:2.61810
[36m(train_xgb_ray_tune pid=524081)[0m [8]	train-mlogloss:2.61686	validation-mlogloss:2.61485
[36m(train_xgb_ray_tune pid=524060)[0m [12]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=524044)[0m [17]	train-mlogloss:2.55213	validation-mlogloss:2.55104
[36m(train_xgb_ray_tune pid=524063)[0m [9]	train-mlogloss:2.65481	validation-mlogloss:2.65337
[36m(train_xgb_ray_tune pid=524066)[0m [8]	train-mlogloss:2.59649	validation-mlogloss:2.59606
[36m(train_xgb_ray_tune pid=524064)[0m [8]	train-mlogloss:2.63117	validation-mlogloss:2.63093
[36m(train_xgb_ray_tune pid=524065)[0m [9]	train-mlogloss:2.65554	validation-mlogloss:2.65520
[36m(train_xgb_ray_tune pid=524074)[0m [8]	train-mlogloss:2.68682	validation-mlogloss:2.68650
[36m(train_xgb_ray_tune pid=524077)[0m [5]	train-mlogloss:2.59372	validation-mlogloss:2.59852
[36m(train_xgb_ray_tune pid=524075)[0m [19]	train-mlogloss:2.36344	validation-mlogloss:2.36125
[36m(train_xgb_ray_tune pid=524060)[0m [13]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=524038)[0m [7]	train-mlogloss:2.64454	validation-mlogloss:2.64316
[36m(train_xgb_ray_tune pid=524076)[0m [7]	train-mlogloss:2.67974	validation-mlogloss:2.67939
[36m(train_xgb_ray_tune pid=524046)[0m [15]	train-mlogloss:2.52570	validation-mlogloss:2.52700
[36m(train_xgb_ray_tune pid=524073)[0m [8]	train-mlogloss:2.64480	validation-mlogloss:2.64394
[36m(train_xgb_ray_tune pid=524065)[0m [10]	train-mlogloss:2.65018	validation-mlogloss:2.64979
[36m(train_xgb_ray_tune pid=524079)[0m [15]	train-mlogloss:2.41387	validation-mlogloss:2.41790
[36m(train_xgb_ray_tune pid=524072)[0m [11]	train-mlogloss:2.57169	validation-mlogloss:2.56992
[36m(train_xgb_ray_tune pid=524045)[0m [8]	train-mlogloss:2.61016	validation-mlogloss:2.60809
[36m(train_xgb_ray_tune pid=524081)[0m [9]	train-mlogloss:2.60715	validation-mlogloss:2.60500
[36m(train_xgb_ray_tune pid=524063)[0m [10]	train-mlogloss:2.64958	validation-mlogloss:2.64799
[36m(train_xgb_ray_tune pid=524064)[0m [9]	train-mlogloss:2.62270	validation-mlogloss:2.62249
[36m(train_xgb_ray_tune pid=524078)[0m [19]	train-mlogloss:2.53676	validation-mlogloss:2.53451
[36m(train_xgb_ray_tune pid=524080)[0m [7]	train-mlogloss:2.53408	validation-mlogloss:2.53652
[36m(train_xgb_ray_tune pid=524044)[0m [18]	train-mlogloss:2.54419	validation-mlogloss:2.54304
[36m(train_xgb_ray_tune pid=524066)[0m [9]	train-mlogloss:2.58474	validation-mlogloss:2.58429
[36m(train_xgb_ray_tune pid=524032)[0m [9]	train-mlogloss:2.59007	validation-mlogloss:2.59156
[36m(train_xgb_ray_tune pid=524075)[0m [20]	train-mlogloss:2.34955	validation-mlogloss:2.34730
[36m(train_xgb_ray_tune pid=524060)[0m [14]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=524038)[0m [8]	train-mlogloss:2.63729	validation-mlogloss:2.63575
[36m(train_xgb_ray_tune pid=524076)[0m [8]	train-mlogloss:2.67627	validation-mlogloss:2.67585
[36m(train_xgb_ray_tune pid=524046)[0m [16]	train-mlogloss:2.51500	validation-mlogloss:2.51634
[36m(train_xgb_ray_tune pid=524065)[0m [11]	train-mlogloss:2.64505	validation-mlogloss:2.64468
[36m(train_xgb_ray_tune pid=524074)[0m [9]	train-mlogloss:2.68443	validation-mlogloss:2.68408
[36m(train_xgb_ray_tune pid=524077)[0m [6]	train-mlogloss:2.57554	validation-mlogloss:2.58065
[36m(train_xgb_ray_tune pid=524072)[0m [12]	train-mlogloss:2.56200	validation-mlogloss:2.56001
[36m(train_xgb_ray_tune pid=524045)[0m [9]	train-mlogloss:2.60098	validation-mlogloss:2.59876
[36m(train_xgb_ray_tune pid=524081)[0m [10]	train-mlogloss:2.59766	validation-mlogloss:2.59520
[36m(train_xgb_ray_tune pid=524060)[0m [15]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=524044)[0m [19]	train-mlogloss:2.53610	validation-mlogloss:2.53487
[36m(train_xgb_ray_tune pid=524063)[0m [11]	train-mlogloss:2.64524	validation-mlogloss:2.64365
[36m(train_xgb_ray_tune pid=524073)[0m [9]	train-mlogloss:2.63806	validation-mlogloss:2.63713
[36m(train_xgb_ray_tune pid=524066)[0m [10]	train-mlogloss:2.57365	validation-mlogloss:2.57300
[36m(train_xgb_ray_tune pid=524064)[0m [10]	train-mlogloss:2.61468	validation-mlogloss:2.61428
[36m(train_xgb_ray_tune pid=524079)[0m [16]	train-mlogloss:2.39826	validation-mlogloss:2.40231
[36m(train_xgb_ray_tune pid=524072)[0m [13]	train-mlogloss:2.55265	validation-mlogloss:2.55063
[36m(train_xgb_ray_tune pid=524032)[0m [10]	train-mlogloss:2.57952	validation-mlogloss:2.58160
[36m(train_xgb_ray_tune pid=524045)[0m [10]	train-mlogloss:2.59238	validation-mlogloss:2.59003
[36m(train_xgb_ray_tune pid=524080)[0m [8]	train-mlogloss:2.51434	validation-mlogloss:2.51710
[36m(train_xgb_ray_tune pid=524075)[0m [21]	train-mlogloss:2.33700	validation-mlogloss:2.33494
[36m(train_xgb_ray_tune pid=524060)[0m [16]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=524038)[0m [9]	train-mlogloss:2.62992	validation-mlogloss:2.62836
[36m(train_xgb_ray_tune pid=524076)[0m [9]	train-mlogloss:2.67282	validation-mlogloss:2.67233
[36m(train_xgb_ray_tune pid=524046)[0m [17]	train-mlogloss:2.50491	validation-mlogloss:2.50655
[36m(train_xgb_ray_tune pid=524065)[0m [12]	train-mlogloss:2.64005	validation-mlogloss:2.63958
[36m(train_xgb_ray_tune pid=524074)[0m [10]	train-mlogloss:2.68211	validation-mlogloss:2.68180
[36m(train_xgb_ray_tune pid=524078)[0m [20]	train-mlogloss:2.52886	validation-mlogloss:2.52671
[36m(train_xgb_ray_tune pid=524077)[0m [7]	train-mlogloss:2.55771	validation-mlogloss:2.56311
[36m(train_xgb_ray_tune pid=524081)[0m [11]	train-mlogloss:2.58836	validation-mlogloss:2.58570
[36m(train_xgb_ray_tune pid=524060)[0m [17]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=524044)[0m [20]	train-mlogloss:2.52833	validation-mlogloss:2.52696
[36m(train_xgb_ray_tune pid=524063)[0m [12]	train-mlogloss:2.64033	validation-mlogloss:2.63881
[36m(train_xgb_ray_tune pid=524073)[0m [10]	train-mlogloss:2.63131	validation-mlogloss:2.63028
[36m(train_xgb_ray_tune pid=524066)[0m [11]	train-mlogloss:2.56262	validation-mlogloss:2.56167
[36m(train_xgb_ray_tune pid=524064)[0m [11]	train-mlogloss:2.60648	validation-mlogloss:2.60617
[36m(train_xgb_ray_tune pid=524079)[0m [17]	train-mlogloss:2.38316	validation-mlogloss:2.38691
[36m(train_xgb_ray_tune pid=524072)[0m [14]	train-mlogloss:2.54333	validation-mlogloss:2.54128
[36m(train_xgb_ray_tune pid=524075)[0m [22]	train-mlogloss:2.32397	validation-mlogloss:2.32189
[36m(train_xgb_ray_tune pid=524078)[0m [21]	train-mlogloss:2.52133	validation-mlogloss:2.51937
[36m(train_xgb_ray_tune pid=524032)[0m [11]	train-mlogloss:2.56879	validation-mlogloss:2.57115
[36m(train_xgb_ray_tune pid=524045)[0m [11]	train-mlogloss:2.58277	validation-mlogloss:2.58013
[36m(train_xgb_ray_tune pid=524080)[0m [9]	train-mlogloss:2.49576	validation-mlogloss:2.49977
[36m(train_xgb_ray_tune pid=524060)[0m [18]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=524038)[0m [10]	train-mlogloss:2.62275	validation-mlogloss:2.62095
[36m(train_xgb_ray_tune pid=524076)[0m [10]	train-mlogloss:2.66934	validation-mlogloss:2.66877
[36m(train_xgb_ray_tune pid=524063)[0m [13]	train-mlogloss:2.63544	validation-mlogloss:2.63367
[36m(train_xgb_ray_tune pid=524046)[0m [18]	train-mlogloss:2.49525	validation-mlogloss:2.49700
[36m(train_xgb_ray_tune pid=524064)[0m [12]	train-mlogloss:2.59827	validation-mlogloss:2.59811
[36m(train_xgb_ray_tune pid=524065)[0m [13]	train-mlogloss:2.63513	validation-mlogloss:2.63457
[36m(train_xgb_ray_tune pid=524074)[0m [11]	train-mlogloss:2.67980	validation-mlogloss:2.67944
[36m(train_xgb_ray_tune pid=524081)[0m [12]	train-mlogloss:2.57894	validation-mlogloss:2.57591
[36m(train_xgb_ray_tune pid=524072)[0m [15]	train-mlogloss:2.53469	validation-mlogloss:2.53242
[36m(train_xgb_ray_tune pid=524066)[0m [12]	train-mlogloss:2.55115	validation-mlogloss:2.55005
[36m(train_xgb_ray_tune pid=524045)[0m [12]	train-mlogloss:2.57394	validation-mlogloss:2.57106
[36m(train_xgb_ray_tune pid=524075)[0m [23]	train-mlogloss:2.31072	validation-mlogloss:2.30864
[36m(train_xgb_ray_tune pid=524060)[0m [19]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=524038)[0m [11]	train-mlogloss:2.61594	validation-mlogloss:2.61387
[36m(train_xgb_ray_tune pid=524044)[0m [21]	train-mlogloss:2.52051	validation-mlogloss:2.51895
[36m(train_xgb_ray_tune pid=524076)[0m [11]	train-mlogloss:2.66582	validation-mlogloss:2.66519
[36m(train_xgb_ray_tune pid=524073)[0m [11]	train-mlogloss:2.62467	validation-mlogloss:2.62354
[36m(train_xgb_ray_tune pid=524065)[0m [14]	train-mlogloss:2.63026	validation-mlogloss:2.62973
[36m(train_xgb_ray_tune pid=524079)[0m [18]	train-mlogloss:2.36957	validation-mlogloss:2.37386
[36m(train_xgb_ray_tune pid=524078)[0m [22]	train-mlogloss:2.51421	validation-mlogloss:2.51221
[36m(train_xgb_ray_tune pid=524077)[0m [8]	train-mlogloss:2.54164	validation-mlogloss:2.54756
[36m(train_xgb_ray_tune pid=524074)[0m [12]	train-mlogloss:2.67746	validation-mlogloss:2.67704
[36m(train_xgb_ray_tune pid=524032)[0m [12]	train-mlogloss:2.55815	validation-mlogloss:2.56044
[36m(train_xgb_ray_tune pid=524080)[0m [10]	train-mlogloss:2.47813	validation-mlogloss:2.48240
[36m(train_xgb_ray_tune pid=524081)[0m [13]	train-mlogloss:2.57038	validation-mlogloss:2.56719
[36m(train_xgb_ray_tune pid=524060)[0m [20]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=524063)[0m [14]	train-mlogloss:2.63061	validation-mlogloss:2.62872
[36m(train_xgb_ray_tune pid=524046)[0m [19]	train-mlogloss:2.48532	validation-mlogloss:2.48719
[36m(train_xgb_ray_tune pid=524064)[0m [13]	train-mlogloss:2.59002	validation-mlogloss:2.58978
[36m(train_xgb_ray_tune pid=524072)[0m [16]	train-mlogloss:2.52569	validation-mlogloss:2.52346
[36m(train_xgb_ray_tune pid=524075)[0m [24]	train-mlogloss:2.29939	validation-mlogloss:2.29776
[36m(train_xgb_ray_tune pid=524038)[0m [12]	train-mlogloss:2.60917	validation-mlogloss:2.60702
[36m(train_xgb_ray_tune pid=524044)[0m [22]	train-mlogloss:2.51282	validation-mlogloss:2.51110
[36m(train_xgb_ray_tune pid=524066)[0m [13]	train-mlogloss:2.53992	validation-mlogloss:2.53864
[36m(train_xgb_ray_tune pid=524065)[0m [15]	train-mlogloss:2.62544	validation-mlogloss:2.62484

Trial trial_815ce finished iteration 1 at 2025-10-27 11:13:07. Total running time: 12s
[36m(train_xgb_ray_tune pid=524060)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454
[36m(train_xgb_ray_tune pid=524060)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=524066)[0m 2025-10-27 11:12:59.388157: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.[32m [repeated 19x across cluster] (Ray deduplicates logs by default. Set RAY_DEDUP_LOGS=0 to disable log deduplication, or see https://docs.ray.io/en/master/ray-observability/user-guides/configure-logging.html#log-deduplication for more options.)[0m
[36m(train_xgb_ray_tune pid=524066)[0m 2025-10-27 11:12:59.412092: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered[32m [repeated 19x across cluster][0m
[36m(train_xgb_ray_tune pid=524066)[0m WARNING: All log messages before absl::InitializeLog() is called are written to STDERR[32m [repeated 19x across cluster][0m
[36m(train_xgb_ray_tune pid=524066)[0m E0000 00:00:1761559979.443453  525363 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered[32m [repeated 19x across cluster][0m
[36m(train_xgb_ray_tune pid=524066)[0m E0000 00:00:1761559979.452127  525363 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered[32m [repeated 19x across cluster][0m
[36m(train_xgb_ray_tune pid=524066)[0m W0000 00:00:1761559979.475312  525363 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.[32m [repeated 76x across cluster][0m
[36m(train_xgb_ray_tune pid=524066)[0m 2025-10-27 11:12:59.481999: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.[32m [repeated 19x across cluster][0m
[36m(train_xgb_ray_tune pid=524066)[0m To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.[32m [repeated 19x across cluster][0m
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s              8.6632 │
│ time_total_s                  8.6632 │
│ training_iteration                 1 │
│ validation_accuracy          0.06818 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=524045)[0m [13]	train-mlogloss:2.56444	validation-mlogloss:2.56139
[36m(train_xgb_ray_tune pid=524080)[0m [11]	train-mlogloss:2.45998	validation-mlogloss:2.46431
[36m(train_xgb_ray_tune pid=524076)[0m [12]	train-mlogloss:2.66254	validation-mlogloss:2.66176
[36m(train_xgb_ray_tune pid=524063)[0m [15]	train-mlogloss:2.62560	validation-mlogloss:2.62361
[36m(train_xgb_ray_tune pid=524073)[0m [12]	train-mlogloss:2.61809	validation-mlogloss:2.61698

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:13:07. Total running time: 12s
[36m(train_xgb_ray_tune pid=524064)[0m [14]	train-mlogloss:2.58209	validation-mlogloss:2.58166
[36m(train_xgb_ray_tune pid=524074)[0m [13]	train-mlogloss:2.67519	validation-mlogloss:2.67468
[36m(train_xgb_ray_tune pid=524079)[0m [19]	train-mlogloss:2.35488	validation-mlogloss:2.35989
[36m(train_xgb_ray_tune pid=524078)[0m [23]	train-mlogloss:2.50687	validation-mlogloss:2.50504
[36m(train_xgb_ray_tune pid=524077)[0m [9]	train-mlogloss:2.52563	validation-mlogloss:2.53249
[36m(train_xgb_ray_tune pid=524072)[0m [17]	train-mlogloss:2.51750	validation-mlogloss:2.51530
[36m(train_xgb_ray_tune pid=524032)[0m [13]	train-mlogloss:2.54743	validation-mlogloss:2.54978
[36m(train_xgb_ray_tune pid=524081)[0m [14]	train-mlogloss:2.56174	validation-mlogloss:2.55859
[36m(train_xgb_ray_tune pid=524045)[0m [14]	train-mlogloss:2.55554	validation-mlogloss:2.55253
[36m(train_xgb_ray_tune pid=524075)[0m [25]	train-mlogloss:2.28687	validation-mlogloss:2.28539
[36m(train_xgb_ray_tune pid=524044)[0m [23]	train-mlogloss:2.50512	validation-mlogloss:2.50315
[36m(train_xgb_ray_tune pid=524076)[0m [13]	train-mlogloss:2.65918	validation-mlogloss:2.65833
[36m(train_xgb_ray_tune pid=524046)[0m [20]	train-mlogloss:2.47542	validation-mlogloss:2.47702
[36m(train_xgb_ray_tune pid=524066)[0m [14]	train-mlogloss:2.52901	validation-mlogloss:2.52747
[36m(train_xgb_ray_tune pid=524065)[0m [16]	train-mlogloss:2.62038	validation-mlogloss:2.61977
[36m(train_xgb_ray_tune pid=524038)[0m [13]	train-mlogloss:2.60224	validation-mlogloss:2.59988
[36m(train_xgb_ray_tune pid=524064)[0m [15]	train-mlogloss:2.57441	validation-mlogloss:2.57365
[36m(train_xgb_ray_tune pid=524032)[0m [14]	train-mlogloss:2.53788	validation-mlogloss:2.54061
[36m(train_xgb_ray_tune pid=524080)[0m [12]	train-mlogloss:2.44309	validation-mlogloss:2.44741
[36m(train_xgb_ray_tune pid=524075)[0m [26]	train-mlogloss:2.27463	validation-mlogloss:2.27301
[36m(train_xgb_ray_tune pid=524081)[0m [15]	train-mlogloss:2.55267	validation-mlogloss:2.54954
[36m(train_xgb_ray_tune pid=524063)[0m [16]	train-mlogloss:2.62072	validation-mlogloss:2.61855
[36m(train_xgb_ray_tune pid=524066)[0m [15]	train-mlogloss:2.51792	validation-mlogloss:2.51638
[36m(train_xgb_ray_tune pid=524074)[0m [14]	train-mlogloss:2.67284	validation-mlogloss:2.67232
[36m(train_xgb_ray_tune pid=524079)[0m [20]	train-mlogloss:2.34155	validation-mlogloss:2.34679
[36m(train_xgb_ray_tune pid=524078)[0m [24]	train-mlogloss:2.49951	validation-mlogloss:2.49759
[36m(train_xgb_ray_tune pid=524077)[0m [10]	train-mlogloss:2.50828	validation-mlogloss:2.51555
[36m(train_xgb_ray_tune pid=524072)[0m [18]	train-mlogloss:2.50890	validation-mlogloss:2.50664
[36m(train_xgb_ray_tune pid=524045)[0m [15]	train-mlogloss:2.54731	validation-mlogloss:2.54427
[36m(train_xgb_ray_tune pid=524046)[0m [21]	train-mlogloss:2.46635	validation-mlogloss:2.46843
[36m(train_xgb_ray_tune pid=524044)[0m [24]	train-mlogloss:2.49758	validation-mlogloss:2.49556
[36m(train_xgb_ray_tune pid=524073)[0m [13]	train-mlogloss:2.61149	validation-mlogloss:2.61036
[36m(train_xgb_ray_tune pid=524065)[0m [17]	train-mlogloss:2.61546	validation-mlogloss:2.61480
[36m(train_xgb_ray_tune pid=524038)[0m [14]	train-mlogloss:2.59553	validation-mlogloss:2.59310
[36m(train_xgb_ray_tune pid=524076)[0m [14]	train-mlogloss:2.65576	validation-mlogloss:2.65483
[36m(train_xgb_ray_tune pid=524063)[0m [17]	train-mlogloss:2.61642	validation-mlogloss:2.61401
[36m(train_xgb_ray_tune pid=524066)[0m [16]	train-mlogloss:2.50754	validation-mlogloss:2.50597
[36m(train_xgb_ray_tune pid=524064)[0m [16]	train-mlogloss:2.56685	validation-mlogloss:2.56600
[36m(train_xgb_ray_tune pid=524074)[0m [15]	train-mlogloss:2.67054	validation-mlogloss:2.66989
[36m(train_xgb_ray_tune pid=524078)[0m [25]	train-mlogloss:2.49259	validation-mlogloss:2.49061
[36m(train_xgb_ray_tune pid=524072)[0m [19]	train-mlogloss:2.50049	validation-mlogloss:2.49791
[36m(train_xgb_ray_tune pid=524075)[0m [27]	train-mlogloss:2.26279	validation-mlogloss:2.26140
[36m(train_xgb_ray_tune pid=524081)[0m [16]	train-mlogloss:2.54439	validation-mlogloss:2.54122
[36m(train_xgb_ray_tune pid=524045)[0m [16]	train-mlogloss:2.53940	validation-mlogloss:2.53640
[36m(train_xgb_ray_tune pid=524080)[0m [13]	train-mlogloss:2.42587	validation-mlogloss:2.43051
[36m(train_xgb_ray_tune pid=524079)[0m [21]	train-mlogloss:2.32798	validation-mlogloss:2.33339
[36m(train_xgb_ray_tune pid=524032)[0m [15]	train-mlogloss:2.52703	validation-mlogloss:2.52991
[36m(train_xgb_ray_tune pid=524038)[0m [15]	train-mlogloss:2.58911	validation-mlogloss:2.58650
[36m(train_xgb_ray_tune pid=524044)[0m [25]	train-mlogloss:2.49023	validation-mlogloss:2.48818
[36m(train_xgb_ray_tune pid=524076)[0m [15]	train-mlogloss:2.65234	validation-mlogloss:2.65142
[36m(train_xgb_ray_tune pid=524063)[0m [18]	train-mlogloss:2.61192	validation-mlogloss:2.60937
[36m(train_xgb_ray_tune pid=524046)[0m [22]	train-mlogloss:2.45701	validation-mlogloss:2.45915
[36m(train_xgb_ray_tune pid=524073)[0m [14]	train-mlogloss:2.60481	validation-mlogloss:2.60372
[36m(train_xgb_ray_tune pid=524064)[0m [17]	train-mlogloss:2.55904	validation-mlogloss:2.55811
[36m(train_xgb_ray_tune pid=524065)[0m [18]	train-mlogloss:2.61071	validation-mlogloss:2.61005
[36m(train_xgb_ray_tune pid=524074)[0m [16]	train-mlogloss:2.66821	validation-mlogloss:2.66754
[36m(train_xgb_ray_tune pid=524078)[0m [26]	train-mlogloss:2.48575	validation-mlogloss:2.48353
[36m(train_xgb_ray_tune pid=524077)[0m [11]	train-mlogloss:2.49234	validation-mlogloss:2.50026
[36m(train_xgb_ray_tune pid=524032)[0m [16]	train-mlogloss:2.51699	validation-mlogloss:2.52015
[36m(train_xgb_ray_tune pid=524045)[0m [17]	train-mlogloss:2.53141	validation-mlogloss:2.52826
[36m(train_xgb_ray_tune pid=524075)[0m [28]	train-mlogloss:2.25126	validation-mlogloss:2.24974
[36m(train_xgb_ray_tune pid=524081)[0m [17]	train-mlogloss:2.53570	validation-mlogloss:2.53246
[36m(train_xgb_ray_tune pid=524038)[0m [16]	train-mlogloss:2.58307	validation-mlogloss:2.58035
[36m(train_xgb_ray_tune pid=524046)[0m [23]	train-mlogloss:2.44828	validation-mlogloss:2.45070
[36m(train_xgb_ray_tune pid=524066)[0m [17]	train-mlogloss:2.49685	validation-mlogloss:2.49511
[36m(train_xgb_ray_tune pid=524065)[0m [19]	train-mlogloss:2.60570	validation-mlogloss:2.60498
[36m(train_xgb_ray_tune pid=524079)[0m [22]	train-mlogloss:2.31442	validation-mlogloss:2.32059
[36m(train_xgb_ray_tune pid=524072)[0m [20]	train-mlogloss:2.49194	validation-mlogloss:2.48902
[36m(train_xgb_ray_tune pid=524080)[0m [14]	train-mlogloss:2.40917	validation-mlogloss:2.41432
[36m(train_xgb_ray_tune pid=524044)[0m [26]	train-mlogloss:2.48309	validation-mlogloss:2.48116
[36m(train_xgb_ray_tune pid=524076)[0m [16]	train-mlogloss:2.64898	validation-mlogloss:2.64800
[36m(train_xgb_ray_tune pid=524081)[0m [18]	train-mlogloss:2.52696	validation-mlogloss:2.52375
[36m(train_xgb_ray_tune pid=524063)[0m [19]	train-mlogloss:2.60731	validation-mlogloss:2.60464
[36m(train_xgb_ray_tune pid=524073)[0m [15]	train-mlogloss:2.59827	validation-mlogloss:2.59703
[36m(train_xgb_ray_tune pid=524066)[0m [18]	train-mlogloss:2.48648	validation-mlogloss:2.48465
[36m(train_xgb_ray_tune pid=524064)[0m [18]	train-mlogloss:2.55129	validation-mlogloss:2.55018
[36m(train_xgb_ray_tune pid=524074)[0m [17]	train-mlogloss:2.66594	validation-mlogloss:2.66521
[36m(train_xgb_ray_tune pid=524078)[0m [27]	train-mlogloss:2.47845	validation-mlogloss:2.47615
[36m(train_xgb_ray_tune pid=524077)[0m [12]	train-mlogloss:2.47670	validation-mlogloss:2.48559
[36m(train_xgb_ray_tune pid=524072)[0m [21]	train-mlogloss:2.48342	validation-mlogloss:2.48023
[36m(train_xgb_ray_tune pid=524045)[0m [18]	train-mlogloss:2.52405	validation-mlogloss:2.52078
[36m(train_xgb_ray_tune pid=524038)[0m [17]	train-mlogloss:2.57731	validation-mlogloss:2.57429
[36m(train_xgb_ray_tune pid=524046)[0m [24]	train-mlogloss:2.43923	validation-mlogloss:2.44211
[36m(train_xgb_ray_tune pid=524065)[0m [20]	train-mlogloss:2.60079	validation-mlogloss:2.60011
[36m(train_xgb_ray_tune pid=524032)[0m [17]	train-mlogloss:2.50741	validation-mlogloss:2.51064
[36m(train_xgb_ray_tune pid=524080)[0m [15]	train-mlogloss:2.39247	validation-mlogloss:2.39743
[36m(train_xgb_ray_tune pid=524075)[0m [29]	train-mlogloss:2.23981	validation-mlogloss:2.23836
[36m(train_xgb_ray_tune pid=524044)[0m [27]	train-mlogloss:2.47624	validation-mlogloss:2.47434
[36m(train_xgb_ray_tune pid=524076)[0m [17]	train-mlogloss:2.64559	validation-mlogloss:2.64463
[36m(train_xgb_ray_tune pid=524063)[0m [20]	train-mlogloss:2.60269	validation-mlogloss:2.59995
[36m(train_xgb_ray_tune pid=524066)[0m [19]	train-mlogloss:2.47612	validation-mlogloss:2.47414
[36m(train_xgb_ray_tune pid=524064)[0m [19]	train-mlogloss:2.54409	validation-mlogloss:2.54258
[36m(train_xgb_ray_tune pid=524079)[0m [23]	train-mlogloss:2.30104	validation-mlogloss:2.30740
[36m(train_xgb_ray_tune pid=524078)[0m [28]	train-mlogloss:2.47142	validation-mlogloss:2.46896
[36m(train_xgb_ray_tune pid=524072)[0m [22]	train-mlogloss:2.47484	validation-mlogloss:2.47166
[36m(train_xgb_ray_tune pid=524081)[0m [19]	train-mlogloss:2.51837	validation-mlogloss:2.51481
[36m(train_xgb_ray_tune pid=524074)[0m [18]	train-mlogloss:2.66368	validation-mlogloss:2.66292
[36m(train_xgb_ray_tune pid=524045)[0m [19]	train-mlogloss:2.51657	validation-mlogloss:2.51320
[36m(train_xgb_ray_tune pid=524038)[0m [18]	train-mlogloss:2.57125	validation-mlogloss:2.56813
[36m(train_xgb_ray_tune pid=524065)[0m [21]	train-mlogloss:2.59601	validation-mlogloss:2.59525
[36m(train_xgb_ray_tune pid=524075)[0m [30]	train-mlogloss:2.22851	validation-mlogloss:2.22677
[36m(train_xgb_ray_tune pid=524044)[0m [28]	train-mlogloss:2.46896	validation-mlogloss:2.46712
[36m(train_xgb_ray_tune pid=524076)[0m [18]	train-mlogloss:2.64224	validation-mlogloss:2.64121
[36m(train_xgb_ray_tune pid=524063)[0m [21]	train-mlogloss:2.59817	validation-mlogloss:2.59530
[36m(train_xgb_ray_tune pid=524046)[0m [25]	train-mlogloss:2.43009	validation-mlogloss:2.43310
[36m(train_xgb_ray_tune pid=524073)[0m [16]	train-mlogloss:2.59183	validation-mlogloss:2.59051
[36m(train_xgb_ray_tune pid=524078)[0m [29]	train-mlogloss:2.46455	validation-mlogloss:2.46205
[36m(train_xgb_ray_tune pid=524077)[0m [13]	train-mlogloss:2.46092	validation-mlogloss:2.47010
[36m(train_xgb_ray_tune pid=524032)[0m [18]	train-mlogloss:2.49727	validation-mlogloss:2.50108
[36m(train_xgb_ray_tune pid=524066)[0m [20]	train-mlogloss:2.46601	validation-mlogloss:2.46399
[36m(train_xgb_ray_tune pid=524045)[0m [20]	train-mlogloss:2.50981	validation-mlogloss:2.50638
[36m(train_xgb_ray_tune pid=524080)[0m [16]	train-mlogloss:2.37667	validation-mlogloss:2.38202
[36m(train_xgb_ray_tune pid=524081)[0m [20]	train-mlogloss:2.51000	validation-mlogloss:2.50632
[36m(train_xgb_ray_tune pid=524038)[0m [19]	train-mlogloss:2.56537	validation-mlogloss:2.56216
[36m(train_xgb_ray_tune pid=524064)[0m [20]	train-mlogloss:2.53701	validation-mlogloss:2.53532
[36m(train_xgb_ray_tune pid=524065)[0m [22]	train-mlogloss:2.59112	validation-mlogloss:2.59027
[36m(train_xgb_ray_tune pid=524074)[0m [19]	train-mlogloss:2.66145	validation-mlogloss:2.66071
[36m(train_xgb_ray_tune pid=524079)[0m [24]	train-mlogloss:2.28804	validation-mlogloss:2.29525
[36m(train_xgb_ray_tune pid=524072)[0m [23]	train-mlogloss:2.46646	validation-mlogloss:2.46324
[36m(train_xgb_ray_tune pid=524032)[0m [19]	train-mlogloss:2.48777	validation-mlogloss:2.49202
[36m(train_xgb_ray_tune pid=524045)[0m [21]	train-mlogloss:2.50261	validation-mlogloss:2.49918
[36m(train_xgb_ray_tune pid=524075)[0m [31]	train-mlogloss:2.21735	validation-mlogloss:2.21584
[36m(train_xgb_ray_tune pid=524081)[0m [21]	train-mlogloss:2.50178	validation-mlogloss:2.49803
[36m(train_xgb_ray_tune pid=524038)[0m [20]	train-mlogloss:2.55942	validation-mlogloss:2.55607
[36m(train_xgb_ray_tune pid=524044)[0m [29]	train-mlogloss:2.46186	validation-mlogloss:2.45995
[36m(train_xgb_ray_tune pid=524076)[0m [19]	train-mlogloss:2.63878	validation-mlogloss:2.63770
[36m(train_xgb_ray_tune pid=524063)[0m [22]	train-mlogloss:2.59351	validation-mlogloss:2.59046
[36m(train_xgb_ray_tune pid=524046)[0m [26]	train-mlogloss:2.42110	validation-mlogloss:2.42429
[36m(train_xgb_ray_tune pid=524073)[0m [17]	train-mlogloss:2.58537	validation-mlogloss:2.58397
[36m(train_xgb_ray_tune pid=524066)[0m [21]	train-mlogloss:2.45589	validation-mlogloss:2.45378
[36m(train_xgb_ray_tune pid=524064)[0m [21]	train-mlogloss:2.52972	validation-mlogloss:2.52776
[36m(train_xgb_ray_tune pid=524065)[0m [23]	train-mlogloss:2.58648	validation-mlogloss:2.58558
[36m(train_xgb_ray_tune pid=524074)[0m [20]	train-mlogloss:2.65914	validation-mlogloss:2.65836
[36m(train_xgb_ray_tune pid=524078)[0m [30]	train-mlogloss:2.45771	validation-mlogloss:2.45517
[36m(train_xgb_ray_tune pid=524077)[0m [14]	train-mlogloss:2.44556	validation-mlogloss:2.45515
[36m(train_xgb_ray_tune pid=524072)[0m [24]	train-mlogloss:2.45913	validation-mlogloss:2.45577
[36m(train_xgb_ray_tune pid=524080)[0m [17]	train-mlogloss:2.36061	validation-mlogloss:2.36677
[36m(train_xgb_ray_tune pid=524075)[0m [32]	train-mlogloss:2.20705	validation-mlogloss:2.20510
[36m(train_xgb_ray_tune pid=524038)[0m [21]	train-mlogloss:2.55386	validation-mlogloss:2.55024
[36m(train_xgb_ray_tune pid=524044)[0m [30]	train-mlogloss:2.45484	validation-mlogloss:2.45297
[36m(train_xgb_ray_tune pid=524076)[0m [20]	train-mlogloss:2.63546	validation-mlogloss:2.63430
[36m(train_xgb_ray_tune pid=524063)[0m [23]	train-mlogloss:2.58935	validation-mlogloss:2.58609
[36m(train_xgb_ray_tune pid=524066)[0m [22]	train-mlogloss:2.44611	validation-mlogloss:2.44383
[36m(train_xgb_ray_tune pid=524064)[0m [22]	train-mlogloss:2.52250	validation-mlogloss:2.52046
[36m(train_xgb_ray_tune pid=524079)[0m [25]	train-mlogloss:2.27548	validation-mlogloss:2.28302
[36m(train_xgb_ray_tune pid=524078)[0m [31]	train-mlogloss:2.45096	validation-mlogloss:2.44842
[36m(train_xgb_ray_tune pid=524072)[0m [25]	train-mlogloss:2.45134	validation-mlogloss:2.44799
[36m(train_xgb_ray_tune pid=524081)[0m [22]	train-mlogloss:2.49351	validation-mlogloss:2.48943
[36m(train_xgb_ray_tune pid=524032)[0m [20]	train-mlogloss:2.47842	validation-mlogloss:2.48322
[36m(train_xgb_ray_tune pid=524045)[0m [22]	train-mlogloss:2.49550	validation-mlogloss:2.49192
[36m(train_xgb_ray_tune pid=524038)[0m [22]	train-mlogloss:2.54798	validation-mlogloss:2.54408
[36m(train_xgb_ray_tune pid=524046)[0m [27]	train-mlogloss:2.41236	validation-mlogloss:2.41570
[36m(train_xgb_ray_tune pid=524073)[0m [18]	train-mlogloss:2.57893	validation-mlogloss:2.57745
[36m(train_xgb_ray_tune pid=524065)[0m [24]	train-mlogloss:2.58198	validation-mlogloss:2.58095
[36m(train_xgb_ray_tune pid=524074)[0m [21]	train-mlogloss:2.65685	validation-mlogloss:2.65602
[36m(train_xgb_ray_tune pid=524044)[0m [31]	train-mlogloss:2.44769	validation-mlogloss:2.44552
[36m(train_xgb_ray_tune pid=524080)[0m [18]	train-mlogloss:2.34563	validation-mlogloss:2.35187
[36m(train_xgb_ray_tune pid=524075)[0m [33]	train-mlogloss:2.19626	validation-mlogloss:2.19437
[36m(train_xgb_ray_tune pid=524081)[0m [23]	train-mlogloss:2.48558	validation-mlogloss:2.48146
[36m(train_xgb_ray_tune pid=524076)[0m [21]	train-mlogloss:2.63220	validation-mlogloss:2.63096
[36m(train_xgb_ray_tune pid=524063)[0m [24]	train-mlogloss:2.58500	validation-mlogloss:2.58155
[36m(train_xgb_ray_tune pid=524066)[0m [23]	train-mlogloss:2.43640	validation-mlogloss:2.43419
[36m(train_xgb_ray_tune pid=524064)[0m [23]	train-mlogloss:2.51541	validation-mlogloss:2.51328
[36m(train_xgb_ray_tune pid=524079)[0m [26]	train-mlogloss:2.26289	validation-mlogloss:2.27141
[36m(train_xgb_ray_tune pid=524078)[0m [32]	train-mlogloss:2.44414	validation-mlogloss:2.44150
[36m(train_xgb_ray_tune pid=524077)[0m [15]	train-mlogloss:2.43061	validation-mlogloss:2.44040
[36m(train_xgb_ray_tune pid=524072)[0m [26]	train-mlogloss:2.44378	validation-mlogloss:2.44017
[36m(train_xgb_ray_tune pid=524032)[0m [21]	train-mlogloss:2.46891	validation-mlogloss:2.47430
[36m(train_xgb_ray_tune pid=524045)[0m [23]	train-mlogloss:2.48853	validation-mlogloss:2.48504
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[36m(train_xgb_ray_tune pid=524063)[0m [97]	train-mlogloss:2.37155	validation-mlogloss:2.36108
[36m(train_xgb_ray_tune pid=524064)[0m [89]	train-mlogloss:2.15477	validation-mlogloss:2.15159
[36m(train_xgb_ray_tune pid=524065)[0m [93]	train-mlogloss:2.30924	validation-mlogloss:2.30659
[36m(train_xgb_ray_tune pid=524078)[0m [96]	train-mlogloss:2.12866	validation-mlogloss:2.12802
[36m(train_xgb_ray_tune pid=524072)[0m [100]	train-mlogloss:2.13330	validation-mlogloss:2.12307
[36m(train_xgb_ray_tune pid=524045)[0m [96]	train-mlogloss:2.19503	validation-mlogloss:2.18524
[36m(train_xgb_ray_tune pid=524075)[0m [97]	train-mlogloss:1.77437	validation-mlogloss:1.77478
[36m(train_xgb_ray_tune pid=524077)[0m [62]	train-mlogloss:1.96154	validation-mlogloss:1.98948
[36m(train_xgb_ray_tune pid=524032)[0m [75]	train-mlogloss:2.09389	validation-mlogloss:2.10990
[36m(train_xgb_ray_tune pid=524080)[0m [68]	train-mlogloss:1.85557	validation-mlogloss:1.87801
[36m(train_xgb_ray_tune pid=524081)[0m [89]	train-mlogloss:2.10174	validation-mlogloss:2.09658
[36m(train_xgb_ray_tune pid=524038)[0m [103]	train-mlogloss:2.31960	validation-mlogloss:2.30554
[36m(train_xgb_ray_tune pid=524044)[0m [96]	train-mlogloss:2.09054	validation-mlogloss:2.08667
[36m(train_xgb_ray_tune pid=524076)[0m [87]	train-mlogloss:2.43425	validation-mlogloss:2.42893
[36m(train_xgb_ray_tune pid=524063)[0m [98]	train-mlogloss:2.37016	validation-mlogloss:2.35957
[36m(train_xgb_ray_tune pid=524046)[0m [87]	train-mlogloss:2.03230	validation-mlogloss:2.03421
[36m(train_xgb_ray_tune pid=524073)[0m [71]	train-mlogloss:2.28819	validation-mlogloss:2.28594
[36m(train_xgb_ray_tune pid=524066)[0m [89]	train-mlogloss:2.01302	validation-mlogloss:2.00571
[36m(train_xgb_ray_tune pid=524074)[0m [83]	train-mlogloss:2.52440	validation-mlogloss:2.52050
[36m(train_xgb_ray_tune pid=524079)[0m [77]	train-mlogloss:1.84340	validation-mlogloss:1.86376
[36m(train_xgb_ray_tune pid=524072)[0m [101]	train-mlogloss:2.13082	validation-mlogloss:2.12061
[36m(train_xgb_ray_tune pid=524078)[0m [97]	train-mlogloss:2.12489	validation-mlogloss:2.12431
[36m(train_xgb_ray_tune pid=524045)[0m [97]	train-mlogloss:2.19238	validation-mlogloss:2.18246
[36m(train_xgb_ray_tune pid=524075)[0m [98]	train-mlogloss:1.77034	validation-mlogloss:1.77083
[36m(train_xgb_ray_tune pid=524081)[0m [90]	train-mlogloss:2.09763	validation-mlogloss:2.09254
[36m(train_xgb_ray_tune pid=524038)[0m [104]	train-mlogloss:2.31859	validation-mlogloss:2.30440
[36m(train_xgb_ray_tune pid=524064)[0m [90]	train-mlogloss:2.15066	validation-mlogloss:2.14752
[36m(train_xgb_ray_tune pid=524065)[0m [94]	train-mlogloss:2.30588	validation-mlogloss:2.30316
[36m(train_xgb_ray_tune pid=524072)[0m [102]	train-mlogloss:2.12828	validation-mlogloss:2.11803
[36m(train_xgb_ray_tune pid=524032)[0m [76]	train-mlogloss:2.08857	validation-mlogloss:2.10489
[36m(train_xgb_ray_tune pid=524080)[0m [69]	train-mlogloss:1.84924	validation-mlogloss:1.87173
[36m(train_xgb_ray_tune pid=524038)[0m [105]	train-mlogloss:2.31760	validation-mlogloss:2.30331
[36m(train_xgb_ray_tune pid=524044)[0m [97]	train-mlogloss:2.08627	validation-mlogloss:2.08249
[36m(train_xgb_ray_tune pid=524076)[0m [88]	train-mlogloss:2.43158	validation-mlogloss:2.42621
[36m(train_xgb_ray_tune pid=524063)[0m [99]	train-mlogloss:2.36812	validation-mlogloss:2.35753
[36m(train_xgb_ray_tune pid=524046)[0m [88]	train-mlogloss:2.02776	validation-mlogloss:2.02973
[36m(train_xgb_ray_tune pid=524073)[0m [72]	train-mlogloss:2.28340	validation-mlogloss:2.28098
[36m(train_xgb_ray_tune pid=524066)[0m [90]	train-mlogloss:2.00898	validation-mlogloss:2.00176
[36m(train_xgb_ray_tune pid=524064)[0m [91]	train-mlogloss:2.14655	validation-mlogloss:2.14349
[36m(train_xgb_ray_tune pid=524065)[0m [95]	train-mlogloss:2.30275	validation-mlogloss:2.30000
[36m(train_xgb_ray_tune pid=524074)[0m [84]	train-mlogloss:2.52241	validation-mlogloss:2.51849
[36m(train_xgb_ray_tune pid=524079)[0m [78]	train-mlogloss:1.83805	validation-mlogloss:1.85821
[36m(train_xgb_ray_tune pid=524078)[0m [98]	train-mlogloss:2.12128	validation-mlogloss:2.12091
[36m(train_xgb_ray_tune pid=524077)[0m [63]	train-mlogloss:1.95490	validation-mlogloss:1.98330
[36m(train_xgb_ray_tune pid=524045)[0m [98]	train-mlogloss:2.18998	validation-mlogloss:2.17992
[36m(train_xgb_ray_tune pid=524072)[0m [103]	train-mlogloss:2.12576	validation-mlogloss:2.11544
[36m(train_xgb_ray_tune pid=524075)[0m [99]	train-mlogloss:1.76622	validation-mlogloss:1.76680
[36m(train_xgb_ray_tune pid=524081)[0m [91]	train-mlogloss:2.09367	validation-mlogloss:2.08856
[36m(train_xgb_ray_tune pid=524038)[0m [106]	train-mlogloss:2.31618	validation-mlogloss:2.30180
[36m(train_xgb_ray_tune pid=524044)[0m [98]	train-mlogloss:2.08216	validation-mlogloss:2.07840
[36m(train_xgb_ray_tune pid=524076)[0m [89]	train-mlogloss:2.42887	validation-mlogloss:2.42348
[36m(train_xgb_ray_tune pid=524063)[0m [100]	train-mlogloss:2.36665	validation-mlogloss:2.35596
[36m(train_xgb_ray_tune pid=524066)[0m [91]	train-mlogloss:2.00469	validation-mlogloss:1.99733
[36m(train_xgb_ray_tune pid=524074)[0m [85]	train-mlogloss:2.52045	validation-mlogloss:2.51645
[36m(train_xgb_ray_tune pid=524077)[0m [64]	train-mlogloss:1.94805	validation-mlogloss:1.97663
[36m(train_xgb_ray_tune pid=524046)[0m [89]	train-mlogloss:2.02346	validation-mlogloss:2.02518
[36m(train_xgb_ray_tune pid=524065)[0m [96]	train-mlogloss:2.29943	validation-mlogloss:2.29672
[36m(train_xgb_ray_tune pid=524078)[0m [99]	train-mlogloss:2.11766	validation-mlogloss:2.11736
[36m(train_xgb_ray_tune pid=524045)[0m [99]	train-mlogloss:2.18747	validation-mlogloss:2.17735
[36m(train_xgb_ray_tune pid=524063)[0m [101]	train-mlogloss:2.36515	validation-mlogloss:2.35432
[36m(train_xgb_ray_tune pid=524073)[0m [73]	train-mlogloss:2.27873	validation-mlogloss:2.27623
[36m(train_xgb_ray_tune pid=524079)[0m [79]	train-mlogloss:1.83287	validation-mlogloss:1.85295
[36m(train_xgb_ray_tune pid=524072)[0m [104]	train-mlogloss:2.12330	validation-mlogloss:2.11296
[36m(train_xgb_ray_tune pid=524032)[0m [77]	train-mlogloss:2.08367	validation-mlogloss:2.10032
[36m(train_xgb_ray_tune pid=524080)[0m [70]	train-mlogloss:1.84294	validation-mlogloss:1.86588
[36m(train_xgb_ray_tune pid=524075)[0m [100]	train-mlogloss:1.76242	validation-mlogloss:1.76285
[36m(train_xgb_ray_tune pid=524081)[0m [92]	train-mlogloss:2.08953	validation-mlogloss:2.08437
[36m(train_xgb_ray_tune pid=524038)[0m [107]	train-mlogloss:2.31460	validation-mlogloss:2.30016
[36m(train_xgb_ray_tune pid=524076)[0m [90]	train-mlogloss:2.42615	validation-mlogloss:2.42069
[36m(train_xgb_ray_tune pid=524066)[0m [92]	train-mlogloss:2.00027	validation-mlogloss:1.99294
[36m(train_xgb_ray_tune pid=524064)[0m [92]	train-mlogloss:2.14238	validation-mlogloss:2.13921
[36m(train_xgb_ray_tune pid=524045)[0m [100]	train-mlogloss:2.18499	validation-mlogloss:2.17483
[36m(train_xgb_ray_tune pid=524044)[0m [99]	train-mlogloss:2.07790	validation-mlogloss:2.07417
[36m(train_xgb_ray_tune pid=524063)[0m [102]	train-mlogloss:2.36357	validation-mlogloss:2.35262
[36m(train_xgb_ray_tune pid=524046)[0m [90]	train-mlogloss:2.01915	validation-mlogloss:2.02098
[36m(train_xgb_ray_tune pid=524065)[0m [97]	train-mlogloss:2.29615	validation-mlogloss:2.29343
[36m(train_xgb_ray_tune pid=524074)[0m [86]	train-mlogloss:2.51849	validation-mlogloss:2.51446
[36m(train_xgb_ray_tune pid=524079)[0m [80]	train-mlogloss:1.82757	validation-mlogloss:1.84749
[36m(train_xgb_ray_tune pid=524078)[0m [100]	train-mlogloss:2.11410	validation-mlogloss:2.11385
[36m(train_xgb_ray_tune pid=524077)[0m [65]	train-mlogloss:1.94157	validation-mlogloss:1.97038
[36m(train_xgb_ray_tune pid=524072)[0m [105]	train-mlogloss:2.12072	validation-mlogloss:2.11047
[36m(train_xgb_ray_tune pid=524032)[0m [78]	train-mlogloss:2.07860	validation-mlogloss:2.09549
[36m(train_xgb_ray_tune pid=524080)[0m [71]	train-mlogloss:1.83678	validation-mlogloss:1.86006
[36m(train_xgb_ray_tune pid=524075)[0m [101]	train-mlogloss:1.75842	validation-mlogloss:1.75891
[36m(train_xgb_ray_tune pid=524081)[0m [93]	train-mlogloss:2.08526	validation-mlogloss:2.08016
[36m(train_xgb_ray_tune pid=524038)[0m [108]	train-mlogloss:2.31367	validation-mlogloss:2.29918
[36m(train_xgb_ray_tune pid=524076)[0m [91]	train-mlogloss:2.42363	validation-mlogloss:2.41804
[36m(train_xgb_ray_tune pid=524063)[0m [103]	train-mlogloss:2.36235	validation-mlogloss:2.35133
[36m(train_xgb_ray_tune pid=524073)[0m [74]	train-mlogloss:2.27414	validation-mlogloss:2.27163
[36m(train_xgb_ray_tune pid=524066)[0m [93]	train-mlogloss:1.99621	validation-mlogloss:1.98885
[36m(train_xgb_ray_tune pid=524064)[0m [93]	train-mlogloss:2.13826	validation-mlogloss:2.13505
[36m(train_xgb_ray_tune pid=524074)[0m [87]	train-mlogloss:2.51644	validation-mlogloss:2.51238
[36m(train_xgb_ray_tune pid=524072)[0m [106]	train-mlogloss:2.11821	validation-mlogloss:2.10779

Trial status: 19 RUNNING | 1 TERMINATED
Current time: 2025-10-27 11:13:25. Total running time: 30s
Logical resource usage: 19.0/20 CPUs, 0/1 GPUs (0.0/1.0 accelerator_type:G)
╭────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ Trial name     status         num_boost_round     max_depth     learning_rate     subsample     colsample_bytree      gamma     min_child_weight     reg_alpha     reg_lambda     random_state     iter     total time (s)     validation_accuracy │
├────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ trial_815ce    RUNNING                    591             3        0.0085005       0.528068             0.538545   27.6444                    84       2.77301        5.6084              9789                                                     │
│ trial_815ce    RUNNING                    682             2        0.0146801       0.785254             0.713742   28.1164                   148     230.112          6.03871             4262                                                     │
│ trial_815ce    RUNNING                    291             2        0.0124667       0.824162             0.57164     5.27421                   62      12.8313       296.871               7779                                                     │
│ trial_815ce    RUNNING                    373             2        0.00615249      0.817785             0.660271   13.2957                   157      21.6249       164.981               7724                                                     │
│ trial_815ce    RUNNING                    718             3        0.0132957       0.580279             0.509772   29.263                    112      36.2913        67.778               6110                                                     │
│ trial_815ce    RUNNING                    626             2        0.0197307       0.760867             0.834172   29.7125                    95     297.768         97.9173               518                                                     │
│ trial_815ce    RUNNING                    647             2        0.0191399       0.637997             0.641773   14.3746                   139      72.7003       158.825               5669                                                     │
│ trial_815ce    RUNNING                    284             2        0.00785538      0.70404              0.765188   29.8994                   171       2.05829       32.3756              7624                                                     │
│ trial_815ce    RUNNING                    402             3        0.0183588       0.507052             0.829074    6.27376                   78      10.5642       623.61                7375                                                     │
│ trial_815ce    RUNNING                    756             2        0.0198547       0.539038             0.656365    9.29435                   97      16.981         42.2814              4597                                                     │
│ trial_815ce    RUNNING                    743             3        0.00571989      0.512015             0.664965   21.0431                   119      20.2153       476.006               5012                                                     │
│ trial_815ce    RUNNING                    445             2        0.011522        0.543758             0.820794   11.8266                   144       2.06773      886.585               5060                                                     │
│ trial_815ce    RUNNING                    714             3        0.0184111       0.611159             0.652786    8.01805                   76      15.9429        41.985                274                                                     │
│ trial_815ce    RUNNING                    735             2        0.0129654       0.753519             0.546044    7.53437                  109      77.9489       132.385               2413                                                     │
│ trial_815ce    RUNNING                    224             3        0.0188875       0.765795             0.63462    23.754                    147     293.798        248.333               8671                                                     │
│ trial_815ce    RUNNING                    467             3        0.019242        0.80582              0.523636   10.4785                   156      43.0216        47.2207              9252                                                     │
│ trial_815ce    RUNNING                    598             3        0.0135708       0.623241             0.761129   14.8588                    71       1.37779       20.6734              6349                                                     │
│ trial_815ce    RUNNING                    567             2        0.00814755      0.728638             0.827736    9.36595                  126      57.4077        13.7875              8719                                                     │
│ trial_815ce    RUNNING                    217             2        0.0148705       0.565127             0.574846   24.1135                   101     145.722          6.90155             4616                                                     │
│ trial_815ce    TERMINATED                 789             3        0.0171509       0.536051             0.50909    24.0376                    63     939.294        903.31                3632        1             8.6632               0.0681818 │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=524045)[0m [101]	train-mlogloss:2.18259	validation-mlogloss:2.17244
[36m(train_xgb_ray_tune pid=524038)[0m [109]	train-mlogloss:2.31227	validation-mlogloss:2.29772
[36m(train_xgb_ray_tune pid=524044)[0m [100]	train-mlogloss:2.07370	validation-mlogloss:2.06985
[36m(train_xgb_ray_tune pid=524063)[0m [104]	train-mlogloss:2.36057	validation-mlogloss:2.34946
[36m(train_xgb_ray_tune pid=524046)[0m [91]	train-mlogloss:2.01496	validation-mlogloss:2.01660
[36m(train_xgb_ray_tune pid=524065)[0m [98]	train-mlogloss:2.29297	validation-mlogloss:2.29024
[36m(train_xgb_ray_tune pid=524079)[0m [81]	train-mlogloss:1.82224	validation-mlogloss:1.84209
[36m(train_xgb_ray_tune pid=524078)[0m [101]	train-mlogloss:2.11057	validation-mlogloss:2.11058
[36m(train_xgb_ray_tune pid=524066)[0m [94]	train-mlogloss:1.99207	validation-mlogloss:1.98466
[36m(train_xgb_ray_tune pid=524032)[0m [79]	train-mlogloss:2.07360	validation-mlogloss:2.09050
[36m(train_xgb_ray_tune pid=524045)[0m [102]	train-mlogloss:2.18031	validation-mlogloss:2.17014
[36m(train_xgb_ray_tune pid=524080)[0m [72]	train-mlogloss:1.83082	validation-mlogloss:1.85411
[36m(train_xgb_ray_tune pid=524075)[0m [102]	train-mlogloss:1.75439	validation-mlogloss:1.75498
[36m(train_xgb_ray_tune pid=524081)[0m [94]	train-mlogloss:2.08135	validation-mlogloss:2.07644
[36m(train_xgb_ray_tune pid=524038)[0m [110]	train-mlogloss:2.31102	validation-mlogloss:2.29637
[36m(train_xgb_ray_tune pid=524076)[0m [92]	train-mlogloss:2.42096	validation-mlogloss:2.41526
[36m(train_xgb_ray_tune pid=524063)[0m [105]	train-mlogloss:2.35919	validation-mlogloss:2.34790
[36m(train_xgb_ray_tune pid=524073)[0m [75]	train-mlogloss:2.26955	validation-mlogloss:2.26715
[36m(train_xgb_ray_tune pid=524064)[0m [94]	train-mlogloss:2.13426	validation-mlogloss:2.13105
[36m(train_xgb_ray_tune pid=524065)[0m [99]	train-mlogloss:2.28981	validation-mlogloss:2.28702
[36m(train_xgb_ray_tune pid=524074)[0m [88]	train-mlogloss:2.51446	validation-mlogloss:2.51033
[36m(train_xgb_ray_tune pid=524078)[0m [102]	train-mlogloss:2.10719	validation-mlogloss:2.10719
[36m(train_xgb_ray_tune pid=524077)[0m [66]	train-mlogloss:1.93514	validation-mlogloss:1.96420
[36m(train_xgb_ray_tune pid=524072)[0m [107]	train-mlogloss:2.11591	validation-mlogloss:2.10538
[36m(train_xgb_ray_tune pid=524044)[0m [101]	train-mlogloss:2.06978	validation-mlogloss:2.06591
[36m(train_xgb_ray_tune pid=524046)[0m [92]	train-mlogloss:2.01069	validation-mlogloss:2.01225
[36m(train_xgb_ray_tune pid=524066)[0m [95]	train-mlogloss:1.98789	validation-mlogloss:1.98038
[36m(train_xgb_ray_tune pid=524064)[0m [95]	train-mlogloss:2.13027	validation-mlogloss:2.12706
[36m(train_xgb_ray_tune pid=524079)[0m [82]	train-mlogloss:1.81715	validation-mlogloss:1.83721
[36m(train_xgb_ray_tune pid=524072)[0m [108]	train-mlogloss:2.11371	validation-mlogloss:2.10311
[36m(train_xgb_ray_tune pid=524045)[0m [103]	train-mlogloss:2.17803	validation-mlogloss:2.16775
[36m(train_xgb_ray_tune pid=524038)[0m [111]	train-mlogloss:2.31021	validation-mlogloss:2.29548
[36m(train_xgb_ray_tune pid=524076)[0m [93]	train-mlogloss:2.41835	validation-mlogloss:2.41256
[36m(train_xgb_ray_tune pid=524063)[0m [106]	train-mlogloss:2.35740	validation-mlogloss:2.34607
[36m(train_xgb_ray_tune pid=524073)[0m [76]	train-mlogloss:2.26491	validation-mlogloss:2.26244
[36m(train_xgb_ray_tune pid=524081)[0m [95]	train-mlogloss:2.07719	validation-mlogloss:2.07222
[36m(train_xgb_ray_tune pid=524032)[0m [80]	train-mlogloss:2.06866	validation-mlogloss:2.08584
[36m(train_xgb_ray_tune pid=524080)[0m [73]	train-mlogloss:1.82457	validation-mlogloss:1.84821
[36m(train_xgb_ray_tune pid=524075)[0m [103]	train-mlogloss:1.75030	validation-mlogloss:1.75100
[36m(train_xgb_ray_tune pid=524038)[0m [112]	train-mlogloss:2.30907	validation-mlogloss:2.29431
[36m(train_xgb_ray_tune pid=524044)[0m [102]	train-mlogloss:2.06575	validation-mlogloss:2.06194
[36m(train_xgb_ray_tune pid=524063)[0m [107]	train-mlogloss:2.35604	validation-mlogloss:2.34458
[36m(train_xgb_ray_tune pid=524066)[0m [96]	train-mlogloss:1.98381	validation-mlogloss:1.97631
[36m(train_xgb_ray_tune pid=524064)[0m [96]	train-mlogloss:2.12624	validation-mlogloss:2.12305
[36m(train_xgb_ray_tune pid=524065)[0m [100]	train-mlogloss:2.28657	validation-mlogloss:2.28367
[36m(train_xgb_ray_tune pid=524074)[0m [89]	train-mlogloss:2.51250	validation-mlogloss:2.50834
[36m(train_xgb_ray_tune pid=524079)[0m [83]	train-mlogloss:1.81208	validation-mlogloss:1.83219
[36m(train_xgb_ray_tune pid=524078)[0m [103]	train-mlogloss:2.10367	validation-mlogloss:2.10353
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[36m(train_xgb_ray_tune pid=524044)[0m [181]	train-mlogloss:1.82084	validation-mlogloss:1.81980
[36m(train_xgb_ray_tune pid=524076)[0m [175]	train-mlogloss:2.22598	validation-mlogloss:2.21577
[36m(train_xgb_ray_tune pid=524066)[0m [178]	train-mlogloss:1.75897	validation-mlogloss:1.75265
[36m(train_xgb_ray_tune pid=524064)[0m [174]	train-mlogloss:1.88693	validation-mlogloss:1.88436
[36m(train_xgb_ray_tune pid=524065)[0m [183]	train-mlogloss:2.06896	validation-mlogloss:2.06646
[36m(train_xgb_ray_tune pid=524074)[0m [165]	train-mlogloss:2.37526	validation-mlogloss:2.36695
[36m(train_xgb_ray_tune pid=524079)[0m [147]	train-mlogloss:1.58684	validation-mlogloss:1.61227
[36m(train_xgb_ray_tune pid=524045)[0m [208]	train-mlogloss:2.05492	validation-mlogloss:2.04223
[36m(train_xgb_ray_tune pid=524080)[0m [135]	train-mlogloss:1.56481	validation-mlogloss:1.60081
[36m(train_xgb_ray_tune pid=524081)[0m [173]	train-mlogloss:1.84421	validation-mlogloss:1.84004
[36m(train_xgb_ray_tune pid=524038)[0m [227]	train-mlogloss:2.25825	validation-mlogloss:2.24110
[36m(train_xgb_ray_tune pid=524044)[0m [182]	train-mlogloss:1.81849	validation-mlogloss:1.81750
[36m(train_xgb_ray_tune pid=524063)[0m [218]	train-mlogloss:2.26356	validation-mlogloss:2.24810
[36m(train_xgb_ray_tune pid=524046)[0m [164]	train-mlogloss:1.78971	validation-mlogloss:1.79041
[36m(train_xgb_ray_tune pid=524073)[0m [141]	train-mlogloss:2.01904	validation-mlogloss:2.01700
[36m(train_xgb_ray_tune pid=524066)[0m [179]	train-mlogloss:1.75742	validation-mlogloss:1.75116
[36m(train_xgb_ray_tune pid=524078)[0m [182]	train-mlogloss:1.88747	validation-mlogloss:1.88828
[36m(train_xgb_ray_tune pid=524077)[0m [127]	train-mlogloss:1.64650	validation-mlogloss:1.68498
[36m(train_xgb_ray_tune pid=524072)[0m [209]	train-mlogloss:1.99041	validation-mlogloss:1.97727
[36m(train_xgb_ray_tune pid=524032)[0m [147]	train-mlogloss:1.81810	validation-mlogloss:1.83869
[36m(train_xgb_ray_tune pid=524076)[0m [176]	train-mlogloss:2.22396	validation-mlogloss:2.21374
[36m(train_xgb_ray_tune pid=524065)[0m [184]	train-mlogloss:2.06680	validation-mlogloss:2.06432
[36m(train_xgb_ray_tune pid=524074)[0m [166]	train-mlogloss:2.37364	validation-mlogloss:2.36531
[36m(train_xgb_ray_tune pid=524075)[0m [183]	train-mlogloss:1.54142	validation-mlogloss:1.55334
[36m(train_xgb_ray_tune pid=524063)[0m [219]	train-mlogloss:2.26315	validation-mlogloss:2.24764
[36m(train_xgb_ray_tune pid=524064)[0m [175]	train-mlogloss:1.88453	validation-mlogloss:1.88192
[36m(train_xgb_ray_tune pid=524072)[0m [210]	train-mlogloss:1.98985	validation-mlogloss:1.97675
[36m(train_xgb_ray_tune pid=524045)[0m [209]	train-mlogloss:2.05440	validation-mlogloss:2.04173
[36m(train_xgb_ray_tune pid=524081)[0m [174]	train-mlogloss:1.84197	validation-mlogloss:1.83791
[36m(train_xgb_ray_tune pid=524038)[0m [228]	train-mlogloss:2.25796	validation-mlogloss:2.24082
[36m(train_xgb_ray_tune pid=524044)[0m [183]	train-mlogloss:1.81609	validation-mlogloss:1.81512
[36m(train_xgb_ray_tune pid=524063)[0m [220]	train-mlogloss:2.26273	validation-mlogloss:2.24716
[36m(train_xgb_ray_tune pid=524046)[0m [165]	train-mlogloss:1.78760	validation-mlogloss:1.78825
[36m(train_xgb_ray_tune pid=524079)[0m [148]	train-mlogloss:1.58462	validation-mlogloss:1.61031
[36m(train_xgb_ray_tune pid=524078)[0m [183]	train-mlogloss:1.88533	validation-mlogloss:1.88617
[36m(train_xgb_ray_tune pid=524077)[0m [128]	train-mlogloss:1.64283	validation-mlogloss:1.68166
[36m(train_xgb_ray_tune pid=524032)[0m [148]	train-mlogloss:1.81534	validation-mlogloss:1.83580
[36m(train_xgb_ray_tune pid=524045)[0m [210]	train-mlogloss:2.05366	validation-mlogloss:2.04094
[36m(train_xgb_ray_tune pid=524080)[0m [136]	train-mlogloss:1.56195	validation-mlogloss:1.59811
[36m(train_xgb_ray_tune pid=524075)[0m [184]	train-mlogloss:1.53960	validation-mlogloss:1.55183
[36m(train_xgb_ray_tune pid=524038)[0m [229]	train-mlogloss:2.25780	validation-mlogloss:2.24061
[36m(train_xgb_ray_tune pid=524076)[0m [177]	train-mlogloss:2.22189	validation-mlogloss:2.21165
[36m(train_xgb_ray_tune pid=524063)[0m [221]	train-mlogloss:2.26245	validation-mlogloss:2.24685
[36m(train_xgb_ray_tune pid=524073)[0m [142]	train-mlogloss:2.01591	validation-mlogloss:2.01385
[36m(train_xgb_ray_tune pid=524066)[0m [180]	train-mlogloss:1.75583	validation-mlogloss:1.74950
[36m(train_xgb_ray_tune pid=524064)[0m [176]	train-mlogloss:1.88224	validation-mlogloss:1.87954
[36m(train_xgb_ray_tune pid=524065)[0m [185]	train-mlogloss:2.06462	validation-mlogloss:2.06219
[36m(train_xgb_ray_tune pid=524074)[0m [167]	train-mlogloss:2.37207	validation-mlogloss:2.36373
[36m(train_xgb_ray_tune pid=524072)[0m [211]	train-mlogloss:1.98921	validation-mlogloss:1.97618
[36m(train_xgb_ray_tune pid=524079)[0m [149]	train-mlogloss:1.58229	validation-mlogloss:1.60812
[36m(train_xgb_ray_tune pid=524078)[0m [184]	train-mlogloss:1.88320	validation-mlogloss:1.88404
[36m(train_xgb_ray_tune pid=524046)[0m [166]	train-mlogloss:1.78539	validation-mlogloss:1.78617
[36m(train_xgb_ray_tune pid=524045)[0m [211]	train-mlogloss:2.05324	validation-mlogloss:2.04051
[36m(train_xgb_ray_tune pid=524081)[0m [175]	train-mlogloss:1.83979	validation-mlogloss:1.83567
[36m(train_xgb_ray_tune pid=524038)[0m [230]	train-mlogloss:2.25780	validation-mlogloss:2.24061
[36m(train_xgb_ray_tune pid=524044)[0m [184]	train-mlogloss:1.81379	validation-mlogloss:1.81293
[36m(train_xgb_ray_tune pid=524063)[0m [222]	train-mlogloss:2.26216	validation-mlogloss:2.24659
[36m(train_xgb_ray_tune pid=524066)[0m [181]	train-mlogloss:1.75409	validation-mlogloss:1.74771
[36m(train_xgb_ray_tune pid=524065)[0m [186]	train-mlogloss:2.06247	validation-mlogloss:2.05999
[36m(train_xgb_ray_tune pid=524074)[0m [168]	train-mlogloss:2.37045	validation-mlogloss:2.36211
[36m(train_xgb_ray_tune pid=524077)[0m [129]	train-mlogloss:1.63951	validation-mlogloss:1.67833
[36m(train_xgb_ray_tune pid=524072)[0m [212]	train-mlogloss:1.98876	validation-mlogloss:1.97569
[36m(train_xgb_ray_tune pid=524076)[0m [178]	train-mlogloss:2.21985	validation-mlogloss:2.20961
[36m(train_xgb_ray_tune pid=524064)[0m [177]	train-mlogloss:1.88000	validation-mlogloss:1.87729
[36m(train_xgb_ray_tune pid=524032)[0m [149]	train-mlogloss:1.81253	validation-mlogloss:1.83304
[36m(train_xgb_ray_tune pid=524075)[0m [185]	train-mlogloss:1.53783	validation-mlogloss:1.55019
[36m(train_xgb_ray_tune pid=524045)[0m [212]	train-mlogloss:2.05261	validation-mlogloss:2.03995
[36m(train_xgb_ray_tune pid=524080)[0m [137]	train-mlogloss:1.55923	validation-mlogloss:1.59553
[36m(train_xgb_ray_tune pid=524081)[0m [176]	train-mlogloss:1.83773	validation-mlogloss:1.83354
[36m(train_xgb_ray_tune pid=524038)[0m [231]	train-mlogloss:2.25780	validation-mlogloss:2.24061
[36m(train_xgb_ray_tune pid=524044)[0m [185]	train-mlogloss:1.81144	validation-mlogloss:1.81056
[36m(train_xgb_ray_tune pid=524063)[0m [223]	train-mlogloss:2.26175	validation-mlogloss:2.24619
[36m(train_xgb_ray_tune pid=524046)[0m [167]	train-mlogloss:1.78346	validation-mlogloss:1.78433
[36m(train_xgb_ray_tune pid=524073)[0m [143]	train-mlogloss:2.01276	validation-mlogloss:2.01066
[36m(train_xgb_ray_tune pid=524066)[0m [182]	train-mlogloss:1.75257	validation-mlogloss:1.74609
[36m(train_xgb_ray_tune pid=524065)[0m [187]	train-mlogloss:2.06028	validation-mlogloss:2.05787
[36m(train_xgb_ray_tune pid=524079)[0m [150]	train-mlogloss:1.57995	validation-mlogloss:1.60592
[36m(train_xgb_ray_tune pid=524078)[0m [185]	train-mlogloss:1.88110	validation-mlogloss:1.88198
[36m(train_xgb_ray_tune pid=524072)[0m [213]	train-mlogloss:1.98795	validation-mlogloss:1.97503
[36m(train_xgb_ray_tune pid=524032)[0m [150]	train-mlogloss:1.80992	validation-mlogloss:1.83048
[36m(train_xgb_ray_tune pid=524045)[0m [213]	train-mlogloss:2.05217	validation-mlogloss:2.03952
[36m(train_xgb_ray_tune pid=524075)[0m [186]	train-mlogloss:1.53608	validation-mlogloss:1.54877
[36m(train_xgb_ray_tune pid=524081)[0m [177]	train-mlogloss:1.83553	validation-mlogloss:1.83139
[36m(train_xgb_ray_tune pid=524038)[0m [232]	train-mlogloss:2.25780	validation-mlogloss:2.24061
[36m(train_xgb_ray_tune pid=524076)[0m [179]	train-mlogloss:2.21781	validation-mlogloss:2.20745
[36m(train_xgb_ray_tune pid=524064)[0m [178]	train-mlogloss:1.87769	validation-mlogloss:1.87515
[36m(train_xgb_ray_tune pid=524074)[0m [169]	train-mlogloss:2.36878	validation-mlogloss:2.36039
[36m(train_xgb_ray_tune pid=524077)[0m [130]	train-mlogloss:1.63612	validation-mlogloss:1.67507
[36m(train_xgb_ray_tune pid=524072)[0m [214]	train-mlogloss:1.98739	validation-mlogloss:1.97442
[36m(train_xgb_ray_tune pid=524045)[0m [214]	train-mlogloss:2.05154	validation-mlogloss:2.03887
[36m(train_xgb_ray_tune pid=524080)[0m [138]	train-mlogloss:1.55651	validation-mlogloss:1.59304
[36m(train_xgb_ray_tune pid=524038)[0m [233]	train-mlogloss:2.25780	validation-mlogloss:2.24061
[36m(train_xgb_ray_tune pid=524044)[0m [186]	train-mlogloss:1.80910	validation-mlogloss:1.80827
[36m(train_xgb_ray_tune pid=524046)[0m [168]	train-mlogloss:1.78126	validation-mlogloss:1.78215
[36m(train_xgb_ray_tune pid=524073)[0m [144]	train-mlogloss:2.00976	validation-mlogloss:2.00766
[36m(train_xgb_ray_tune pid=524066)[0m [183]	train-mlogloss:1.75080	validation-mlogloss:1.74441
[36m(train_xgb_ray_tune pid=524065)[0m [188]	train-mlogloss:2.05820	validation-mlogloss:2.05579
[36m(train_xgb_ray_tune pid=524074)[0m [170]	train-mlogloss:2.36720	validation-mlogloss:2.35874
[36m(train_xgb_ray_tune pid=524079)[0m [151]	train-mlogloss:1.57771	validation-mlogloss:1.60381
[36m(train_xgb_ray_tune pid=524063)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454
[36m(train_xgb_ray_tune pid=524063)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=524078)[0m [186]	train-mlogloss:1.87912	validation-mlogloss:1.87993
[36m(train_xgb_ray_tune pid=524072)[0m [215]	train-mlogloss:1.98705	validation-mlogloss:1.97409
[36m(train_xgb_ray_tune pid=524081)[0m [178]	train-mlogloss:1.83340	validation-mlogloss:1.82928
[36m(train_xgb_ray_tune pid=524032)[0m [151]	train-mlogloss:1.80718	validation-mlogloss:1.82776
[36m(train_xgb_ray_tune pid=524045)[0m [215]	train-mlogloss:2.05120	validation-mlogloss:2.03857
[36m(train_xgb_ray_tune pid=524075)[0m [187]	train-mlogloss:1.53432	validation-mlogloss:1.54733
[36m(train_xgb_ray_tune pid=524038)[0m [234]	train-mlogloss:2.25780	validation-mlogloss:2.24061
[36m(train_xgb_ray_tune pid=524076)[0m [180]	train-mlogloss:2.21583	validation-mlogloss:2.20545
[36m(train_xgb_ray_tune pid=524046)[0m [169]	train-mlogloss:1.77927	validation-mlogloss:1.78004
[36m(train_xgb_ray_tune pid=524066)[0m [184]	train-mlogloss:1.74932	validation-mlogloss:1.74304
[36m(train_xgb_ray_tune pid=524064)[0m [179]	train-mlogloss:1.87530	validation-mlogloss:1.87276
[36m(train_xgb_ray_tune pid=524078)[0m [187]	train-mlogloss:1.87699	validation-mlogloss:1.87781
[36m(train_xgb_ray_tune pid=524077)[0m [131]	train-mlogloss:1.63278	validation-mlogloss:1.67171
[36m(train_xgb_ray_tune pid=524072)[0m [216]	train-mlogloss:1.98681	validation-mlogloss:1.97389
[36m(train_xgb_ray_tune pid=524044)[0m [187]	train-mlogloss:1.80672	validation-mlogloss:1.80595
[36m(train_xgb_ray_tune pid=524065)[0m [189]	train-mlogloss:2.05612	validation-mlogloss:2.05374
[36m(train_xgb_ray_tune pid=524032)[0m [152]	train-mlogloss:1.80447	validation-mlogloss:1.82518
[36m(train_xgb_ray_tune pid=524045)[0m [216]	train-mlogloss:2.05067	validation-mlogloss:2.03799
[36m(train_xgb_ray_tune pid=524080)[0m [139]	train-mlogloss:1.55362	validation-mlogloss:1.59040
[36m(train_xgb_ray_tune pid=524075)[0m [188]	train-mlogloss:1.53265	validation-mlogloss:1.54591
[36m(train_xgb_ray_tune pid=524081)[0m [179]	train-mlogloss:1.83124	validation-mlogloss:1.82716
[36m(train_xgb_ray_tune pid=524038)[0m [235]	train-mlogloss:2.25755	validation-mlogloss:2.24038
[36m(train_xgb_ray_tune pid=524076)[0m [181]	train-mlogloss:2.21380	validation-mlogloss:2.20336
[36m(train_xgb_ray_tune pid=524046)[0m [170]	train-mlogloss:1.77725	validation-mlogloss:1.77812
[36m(train_xgb_ray_tune pid=524073)[0m [145]	train-mlogloss:2.00669	validation-mlogloss:2.00467
[36m(train_xgb_ray_tune pid=524064)[0m [180]	train-mlogloss:1.87293	validation-mlogloss:1.87046
[36m(train_xgb_ray_tune pid=524074)[0m [171]	train-mlogloss:2.36553	validation-mlogloss:2.35702
[36m(train_xgb_ray_tune pid=524079)[0m [152]	train-mlogloss:1.57544	validation-mlogloss:1.60187
[36m(train_xgb_ray_tune pid=524078)[0m [188]	train-mlogloss:1.87494	validation-mlogloss:1.87563
[36m(train_xgb_ray_tune pid=524045)[0m [217]	train-mlogloss:2.05017	validation-mlogloss:2.03749
[36m(train_xgb_ray_tune pid=524080)[0m [140]	train-mlogloss:1.55089	validation-mlogloss:1.58797
[36m(train_xgb_ray_tune pid=524075)[0m [189]	train-mlogloss:1.53099	validation-mlogloss:1.54451
[36m(train_xgb_ray_tune pid=524081)[0m [180]	train-mlogloss:1.82918	validation-mlogloss:1.82515
[36m(train_xgb_ray_tune pid=524038)[0m [236]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524044)[0m [188]	train-mlogloss:1.80451	validation-mlogloss:1.80382
[36m(train_xgb_ray_tune pid=524073)[0m [146]	train-mlogloss:2.00360	validation-mlogloss:2.00174
[36m(train_xgb_ray_tune pid=524066)[0m [185]	train-mlogloss:1.74773	validation-mlogloss:1.74148
[36m(train_xgb_ray_tune pid=524064)[0m [181]	train-mlogloss:1.87055	validation-mlogloss:1.86810
[36m(train_xgb_ray_tune pid=524065)[0m [190]	train-mlogloss:2.05401	validation-mlogloss:2.05159
[36m(train_xgb_ray_tune pid=524074)[0m [172]	train-mlogloss:2.36385	validation-mlogloss:2.35530
[36m(train_xgb_ray_tune pid=524077)[0m [132]	train-mlogloss:1.62947	validation-mlogloss:1.66857

Trial trial_815ce finished iteration 1 at 2025-10-27 11:13:46. Total running time: 50s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             47.3779 │
│ time_total_s                 47.3779 │
│ training_iteration                 1 │
│ validation_accuracy          0.40494 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=524032)[0m [153]	train-mlogloss:1.80178	validation-mlogloss:1.82246
[36m(train_xgb_ray_tune pid=524045)[0m [218]	train-mlogloss:2.04948	validation-mlogloss:2.03682
[36m(train_xgb_ray_tune pid=524081)[0m [181]	train-mlogloss:1.82702	validation-mlogloss:1.82286
[36m(train_xgb_ray_tune pid=524038)[0m [237]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524076)[0m [182]	train-mlogloss:2.21182	validation-mlogloss:2.20137
[36m(train_xgb_ray_tune pid=524046)[0m [171]	train-mlogloss:1.77516	validation-mlogloss:1.77588
[36m(train_xgb_ray_tune pid=524066)[0m [186]	train-mlogloss:1.74624	validation-mlogloss:1.73997
[36m(train_xgb_ray_tune pid=524065)[0m [191]	train-mlogloss:2.05188	validation-mlogloss:2.04953
[36m(train_xgb_ray_tune pid=524079)[0m [153]	train-mlogloss:1.57317	validation-mlogloss:1.59962
[36m(train_xgb_ray_tune pid=524078)[0m [189]	train-mlogloss:1.87283	validation-mlogloss:1.87358
[36m(train_xgb_ray_tune pid=524075)[0m [190]	train-mlogloss:1.52931	validation-mlogloss:1.54299
[36m(train_xgb_ray_tune pid=524044)[0m [189]	train-mlogloss:1.80228	validation-mlogloss:1.80155

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:13:46. Total running time: 50s
[36m(train_xgb_ray_tune pid=524045)[0m [219]	train-mlogloss:2.04895	validation-mlogloss:2.03637
[36m(train_xgb_ray_tune pid=524080)[0m [141]	train-mlogloss:1.54817	validation-mlogloss:1.58541
[36m(train_xgb_ray_tune pid=524038)[0m [238]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524076)[0m [183]	train-mlogloss:2.20985	validation-mlogloss:2.19931
[36m(train_xgb_ray_tune pid=524046)[0m [172]	train-mlogloss:1.77305	validation-mlogloss:1.77374
[36m(train_xgb_ray_tune pid=524073)[0m [147]	train-mlogloss:2.00073	validation-mlogloss:1.99882
[36m(train_xgb_ray_tune pid=524066)[0m [187]	train-mlogloss:1.74485	validation-mlogloss:1.73862
[36m(train_xgb_ray_tune pid=524064)[0m [182]	train-mlogloss:1.86815	validation-mlogloss:1.86575
[36m(train_xgb_ray_tune pid=524074)[0m [173]	train-mlogloss:2.36217	validation-mlogloss:2.35358
[36m(train_xgb_ray_tune pid=524079)[0m [154]	train-mlogloss:1.57094	validation-mlogloss:1.59756
[36m(train_xgb_ray_tune pid=524078)[0m [190]	train-mlogloss:1.87081	validation-mlogloss:1.87158
[36m(train_xgb_ray_tune pid=524077)[0m [133]	train-mlogloss:1.62626	validation-mlogloss:1.66542
[36m(train_xgb_ray_tune pid=524032)[0m [154]	train-mlogloss:1.79919	validation-mlogloss:1.81983
[36m(train_xgb_ray_tune pid=524065)[0m [192]	train-mlogloss:2.04974	validation-mlogloss:2.04734
[36m(train_xgb_ray_tune pid=524081)[0m [182]	train-mlogloss:1.82499	validation-mlogloss:1.82090
[36m(train_xgb_ray_tune pid=524045)[0m [220]	train-mlogloss:2.04834	validation-mlogloss:2.03570
[36m(train_xgb_ray_tune pid=524075)[0m [191]	train-mlogloss:1.52760	validation-mlogloss:1.54150
[36m(train_xgb_ray_tune pid=524038)[0m [239]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524044)[0m [190]	train-mlogloss:1.79995	validation-mlogloss:1.79927
[36m(train_xgb_ray_tune pid=524076)[0m [184]	train-mlogloss:2.20790	validation-mlogloss:2.19733
[36m(train_xgb_ray_tune pid=524046)[0m [173]	train-mlogloss:1.77105	validation-mlogloss:1.77165
[36m(train_xgb_ray_tune pid=524066)[0m [188]	train-mlogloss:1.74340	validation-mlogloss:1.73722
[36m(train_xgb_ray_tune pid=524072)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454
[36m(train_xgb_ray_tune pid=524072)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=524064)[0m [183]	train-mlogloss:1.86589	validation-mlogloss:1.86351
[36m(train_xgb_ray_tune pid=524074)[0m [174]	train-mlogloss:2.36060	validation-mlogloss:2.35196
[36m(train_xgb_ray_tune pid=524078)[0m [191]	train-mlogloss:1.86875	validation-mlogloss:1.86945
[36m(train_xgb_ray_tune pid=524079)[0m [155]	train-mlogloss:1.56868	validation-mlogloss:1.59557

Trial trial_815ce finished iteration 1 at 2025-10-27 11:13:46. Total running time: 51s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             47.8721 │
│ time_total_s                 47.8721 │
│ training_iteration                 1 │
│ validation_accuracy          0.44308 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:13:46. Total running time: 51s
[36m(train_xgb_ray_tune pid=524032)[0m [155]	train-mlogloss:1.79652	validation-mlogloss:1.81713
[36m(train_xgb_ray_tune pid=524045)[0m [221]	train-mlogloss:2.04792	validation-mlogloss:2.03531
[36m(train_xgb_ray_tune pid=524080)[0m [142]	train-mlogloss:1.54529	validation-mlogloss:1.58290
[36m(train_xgb_ray_tune pid=524075)[0m [192]	train-mlogloss:1.52590	validation-mlogloss:1.53998
[36m(train_xgb_ray_tune pid=524081)[0m [183]	train-mlogloss:1.82290	validation-mlogloss:1.81878
[36m(train_xgb_ray_tune pid=524038)[0m [240]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524044)[0m [191]	train-mlogloss:1.79768	validation-mlogloss:1.79704
[36m(train_xgb_ray_tune pid=524073)[0m [148]	train-mlogloss:1.99785	validation-mlogloss:1.99600
[36m(train_xgb_ray_tune pid=524066)[0m [189]	train-mlogloss:1.74196	validation-mlogloss:1.73575
[36m(train_xgb_ray_tune pid=524065)[0m [193]	train-mlogloss:2.04762	validation-mlogloss:2.04518
[36m(train_xgb_ray_tune pid=524077)[0m [134]	train-mlogloss:1.62310	validation-mlogloss:1.66238
[36m(train_xgb_ray_tune pid=524074)[0m [175]	train-mlogloss:2.35904	validation-mlogloss:2.35036
[36m(train_xgb_ray_tune pid=524076)[0m [185]	train-mlogloss:2.20594	validation-mlogloss:2.19537
[36m(train_xgb_ray_tune pid=524045)[0m [222]	train-mlogloss:2.04768	validation-mlogloss:2.03505
[36m(train_xgb_ray_tune pid=524078)[0m [192]	train-mlogloss:1.86666	validation-mlogloss:1.86740
[36m(train_xgb_ray_tune pid=524032)[0m [156]	train-mlogloss:1.79391	validation-mlogloss:1.81455
[36m(train_xgb_ray_tune pid=524080)[0m [143]	train-mlogloss:1.54244	validation-mlogloss:1.58055
[36m(train_xgb_ray_tune pid=524081)[0m [184]	train-mlogloss:1.82092	validation-mlogloss:1.81683
[36m(train_xgb_ray_tune pid=524038)[0m [241]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524044)[0m [192]	train-mlogloss:1.79546	validation-mlogloss:1.79487
[36m(train_xgb_ray_tune pid=524046)[0m [174]	train-mlogloss:1.76896	validation-mlogloss:1.76965
[36m(train_xgb_ray_tune pid=524073)[0m [149]	train-mlogloss:1.99479	validation-mlogloss:1.99293
[36m(train_xgb_ray_tune pid=524066)[0m [190]	train-mlogloss:1.74047	validation-mlogloss:1.73427
[36m(train_xgb_ray_tune pid=524064)[0m [184]	train-mlogloss:1.86364	validation-mlogloss:1.86129
[36m(train_xgb_ray_tune pid=524065)[0m [194]	train-mlogloss:2.04550	validation-mlogloss:2.04317
[36m(train_xgb_ray_tune pid=524079)[0m [156]	train-mlogloss:1.56648	validation-mlogloss:1.59339
[36m(train_xgb_ray_tune pid=524077)[0m [135]	train-mlogloss:1.61970	validation-mlogloss:1.65924
[36m(train_xgb_ray_tune pid=524045)[0m [223]	train-mlogloss:2.04735	validation-mlogloss:2.03473
[36m(train_xgb_ray_tune pid=524045)[0m [224]	train-mlogloss:2.04677	validation-mlogloss:2.03416
[36m(train_xgb_ray_tune pid=524075)[0m [193]	train-mlogloss:1.52437	validation-mlogloss:1.53866
[36m(train_xgb_ray_tune pid=524038)[0m [242]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524076)[0m [186]	train-mlogloss:2.20398	validation-mlogloss:2.19334
[36m(train_xgb_ray_tune pid=524046)[0m [175]	train-mlogloss:1.76699	validation-mlogloss:1.76777
[36m(train_xgb_ray_tune pid=524066)[0m [191]	train-mlogloss:1.73887	validation-mlogloss:1.73273
[36m(train_xgb_ray_tune pid=524064)[0m [185]	train-mlogloss:1.86142	validation-mlogloss:1.85900
[36m(train_xgb_ray_tune pid=524065)[0m [195]	train-mlogloss:2.04337	validation-mlogloss:2.04097
[36m(train_xgb_ray_tune pid=524074)[0m [176]	train-mlogloss:2.35739	validation-mlogloss:2.34866
[36m(train_xgb_ray_tune pid=524078)[0m [193]	train-mlogloss:1.86465	validation-mlogloss:1.86542
[36m(train_xgb_ray_tune pid=524081)[0m [185]	train-mlogloss:1.81891	validation-mlogloss:1.81482
[36m(train_xgb_ray_tune pid=524038)[0m [243]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524032)[0m [157]	train-mlogloss:1.79142	validation-mlogloss:1.81189
[36m(train_xgb_ray_tune pid=524079)[0m [157]	train-mlogloss:1.56431	validation-mlogloss:1.59146
[36m(train_xgb_ray_tune pid=524044)[0m [193]	train-mlogloss:1.79323	validation-mlogloss:1.79271
[36m(train_xgb_ray_tune pid=524045)[0m [225]	train-mlogloss:2.04655	validation-mlogloss:2.03396
[36m(train_xgb_ray_tune pid=524080)[0m [144]	train-mlogloss:1.53981	validation-mlogloss:1.57800
[36m(train_xgb_ray_tune pid=524075)[0m [194]	train-mlogloss:1.52279	validation-mlogloss:1.53724
[36m(train_xgb_ray_tune pid=524038)[0m [244]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524076)[0m [187]	train-mlogloss:2.20192	validation-mlogloss:2.19128
[36m(train_xgb_ray_tune pid=524073)[0m [150]	train-mlogloss:1.99183	validation-mlogloss:1.99012
[36m(train_xgb_ray_tune pid=524066)[0m [192]	train-mlogloss:1.73729	validation-mlogloss:1.73117
[36m(train_xgb_ray_tune pid=524064)[0m [186]	train-mlogloss:1.85915	validation-mlogloss:1.85682
[36m(train_xgb_ray_tune pid=524065)[0m [196]	train-mlogloss:2.04138	validation-mlogloss:2.03892
[36m(train_xgb_ray_tune pid=524074)[0m [177]	train-mlogloss:2.35583	validation-mlogloss:2.34704
[36m(train_xgb_ray_tune pid=524078)[0m [194]	train-mlogloss:1.86272	validation-mlogloss:1.86350
[36m(train_xgb_ray_tune pid=524077)[0m [136]	train-mlogloss:1.61647	validation-mlogloss:1.65635
[36m(train_xgb_ray_tune pid=524032)[0m [158]	train-mlogloss:1.78885	validation-mlogloss:1.80943
[36m(train_xgb_ray_tune pid=524045)[0m [226]	train-mlogloss:2.04621	validation-mlogloss:2.03362
[36m(train_xgb_ray_tune pid=524080)[0m [145]	train-mlogloss:1.53711	validation-mlogloss:1.57559
[36m(train_xgb_ray_tune pid=524081)[0m [186]	train-mlogloss:1.81693	validation-mlogloss:1.81280
[36m(train_xgb_ray_tune pid=524038)[0m [245]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524044)[0m [194]	train-mlogloss:1.79105	validation-mlogloss:1.79052
[36m(train_xgb_ray_tune pid=524076)[0m [188]	train-mlogloss:2.19997	validation-mlogloss:2.18935
[36m(train_xgb_ray_tune pid=524046)[0m [176]	train-mlogloss:1.76506	validation-mlogloss:1.76600
[36m(train_xgb_ray_tune pid=524066)[0m [193]	train-mlogloss:1.73574	validation-mlogloss:1.72965
[36m(train_xgb_ray_tune pid=524079)[0m [158]	train-mlogloss:1.56207	validation-mlogloss:1.58934
[36m(train_xgb_ray_tune pid=524077)[0m [137]	train-mlogloss:1.61344	validation-mlogloss:1.65345
[36m(train_xgb_ray_tune pid=524045)[0m [227]	train-mlogloss:2.04588	validation-mlogloss:2.03330
[36m(train_xgb_ray_tune pid=524080)[0m [146]	train-mlogloss:1.53453	validation-mlogloss:1.57310
[36m(train_xgb_ray_tune pid=524075)[0m [195]	train-mlogloss:1.52125	validation-mlogloss:1.53592
[36m(train_xgb_ray_tune pid=524046)[0m [177]	train-mlogloss:1.76285	validation-mlogloss:1.76380
[36m(train_xgb_ray_tune pid=524073)[0m [151]	train-mlogloss:1.98880	validation-mlogloss:1.98721
[36m(train_xgb_ray_tune pid=524064)[0m [187]	train-mlogloss:1.85687	validation-mlogloss:1.85462
[36m(train_xgb_ray_tune pid=524065)[0m [197]	train-mlogloss:2.03932	validation-mlogloss:2.03683
[36m(train_xgb_ray_tune pid=524074)[0m [178]	train-mlogloss:2.35420	validation-mlogloss:2.34536
[36m(train_xgb_ray_tune pid=524079)[0m [159]	train-mlogloss:1.55998	validation-mlogloss:1.58737
[36m(train_xgb_ray_tune pid=524078)[0m [195]	train-mlogloss:1.86061	validation-mlogloss:1.86140
[36m(train_xgb_ray_tune pid=524081)[0m [187]	train-mlogloss:1.81494	validation-mlogloss:1.81083
[36m(train_xgb_ray_tune pid=524038)[0m [246]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524077)[0m [138]	train-mlogloss:1.61026	validation-mlogloss:1.65039
[36m(train_xgb_ray_tune pid=524076)[0m [189]	train-mlogloss:2.19797	validation-mlogloss:2.18727
[36m(train_xgb_ray_tune pid=524032)[0m [159]	train-mlogloss:1.78624	validation-mlogloss:1.80675
[36m(train_xgb_ray_tune pid=524045)[0m [228]	train-mlogloss:2.04532	validation-mlogloss:2.03280
[36m(train_xgb_ray_tune pid=524075)[0m [196]	train-mlogloss:1.51972	validation-mlogloss:1.53438
[36m(train_xgb_ray_tune pid=524038)[0m [247]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524044)[0m [195]	train-mlogloss:1.78881	validation-mlogloss:1.78833
[36m(train_xgb_ray_tune pid=524046)[0m [178]	train-mlogloss:1.76094	validation-mlogloss:1.76199
[36m(train_xgb_ray_tune pid=524066)[0m [194]	train-mlogloss:1.73439	validation-mlogloss:1.72823
[36m(train_xgb_ray_tune pid=524064)[0m [188]	train-mlogloss:1.85461	validation-mlogloss:1.85231
[36m(train_xgb_ray_tune pid=524065)[0m [198]	train-mlogloss:2.03727	validation-mlogloss:2.03478
[36m(train_xgb_ray_tune pid=524045)[0m [229]	train-mlogloss:2.04500	validation-mlogloss:2.03255
[36m(train_xgb_ray_tune pid=524080)[0m [147]	train-mlogloss:1.53179	validation-mlogloss:1.57049
[36m(train_xgb_ray_tune pid=524075)[0m [197]	train-mlogloss:1.51826	validation-mlogloss:1.53308
[36m(train_xgb_ray_tune pid=524081)[0m [188]	train-mlogloss:1.81288	validation-mlogloss:1.80886
[36m(train_xgb_ray_tune pid=524038)[0m [248]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524044)[0m [196]	train-mlogloss:1.78661	validation-mlogloss:1.78617
[36m(train_xgb_ray_tune pid=524076)[0m [190]	train-mlogloss:2.19596	validation-mlogloss:2.18521
[36m(train_xgb_ray_tune pid=524073)[0m [152]	train-mlogloss:1.98602	validation-mlogloss:1.98444
[36m(train_xgb_ray_tune pid=524066)[0m [195]	train-mlogloss:1.73301	validation-mlogloss:1.72692
[36m(train_xgb_ray_tune pid=524065)[0m [199]	train-mlogloss:2.03519	validation-mlogloss:2.03270
[36m(train_xgb_ray_tune pid=524074)[0m [179]	train-mlogloss:2.35261	validation-mlogloss:2.34370
[36m(train_xgb_ray_tune pid=524079)[0m [160]	train-mlogloss:1.55797	validation-mlogloss:1.58537
[36m(train_xgb_ray_tune pid=524078)[0m [196]	train-mlogloss:1.85859	validation-mlogloss:1.85940
[36m(train_xgb_ray_tune pid=524077)[0m [139]	train-mlogloss:1.60728	validation-mlogloss:1.64755
[36m(train_xgb_ray_tune pid=524032)[0m [160]	train-mlogloss:1.78355	validation-mlogloss:1.80421
[36m(train_xgb_ray_tune pid=524045)[0m [230]	train-mlogloss:2.04451	validation-mlogloss:2.03210
[36m(train_xgb_ray_tune pid=524080)[0m [148]	train-mlogloss:1.52924	validation-mlogloss:1.56801
[36m(train_xgb_ray_tune pid=524081)[0m [189]	train-mlogloss:1.81088	validation-mlogloss:1.80693
[36m(train_xgb_ray_tune pid=524038)[0m [249]	train-mlogloss:2.25725	validation-mlogloss:2.24008
[36m(train_xgb_ray_tune pid=524046)[0m [179]	train-mlogloss:1.75899	validation-mlogloss:1.76008
[36m(train_xgb_ray_tune pid=524066)[0m [196]	train-mlogloss:1.73168	validation-mlogloss:1.72576
[36m(train_xgb_ray_tune pid=524064)[0m [189]	train-mlogloss:1.85256	validation-mlogloss:1.85024
[36m(train_xgb_ray_tune pid=524065)[0m [200]	train-mlogloss:2.03315	validation-mlogloss:2.03062
[36m(train_xgb_ray_tune pid=524074)[0m [180]	train-mlogloss:2.35104	validation-mlogloss:2.34209
[36m(train_xgb_ray_tune pid=524079)[0m [161]	train-mlogloss:1.55575	validation-mlogloss:1.58333
[36m(train_xgb_ray_tune pid=524078)[0m [197]	train-mlogloss:1.85669	validation-mlogloss:1.85752
[36m(train_xgb_ray_tune pid=524075)[0m [198]	train-mlogloss:1.51665	validation-mlogloss:1.53159
[36m(train_xgb_ray_tune pid=524076)[0m [191]	train-mlogloss:2.19407	validation-mlogloss:2.18329
[36m(train_xgb_ray_tune pid=524073)[0m [153]	train-mlogloss:1.98314	validation-mlogloss:1.98149
[36m(train_xgb_ray_tune pid=524032)[0m [161]	train-mlogloss:1.78103	validation-mlogloss:1.80168
[36m(train_xgb_ray_tune pid=524045)[0m [231]	train-mlogloss:2.04390	validation-mlogloss:2.03147
[36m(train_xgb_ray_tune pid=524081)[0m [190]	train-mlogloss:1.80894	validation-mlogloss:1.80508
[36m(train_xgb_ray_tune pid=524038)[0m [250]	train-mlogloss:2.25657	validation-mlogloss:2.23945
[36m(train_xgb_ray_tune pid=524044)[0m [197]	train-mlogloss:1.78449	validation-mlogloss:1.78407
[36m(train_xgb_ray_tune pid=524046)[0m [180]	train-mlogloss:1.75721	validation-mlogloss:1.75829
[36m(train_xgb_ray_tune pid=524064)[0m [190]	train-mlogloss:1.85028	validation-mlogloss:1.84813
[36m(train_xgb_ray_tune pid=524074)[0m [181]	train-mlogloss:2.34936	validation-mlogloss:2.34039
[36m(train_xgb_ray_tune pid=524079)[0m [162]	train-mlogloss:1.55364	validation-mlogloss:1.58125
[36m(train_xgb_ray_tune pid=524077)[0m [140]	train-mlogloss:1.60422	validation-mlogloss:1.64464
[36m(train_xgb_ray_tune pid=524075)[0m [199]	train-mlogloss:1.51502	validation-mlogloss:1.53019
[36m(train_xgb_ray_tune pid=524066)[0m [197]	train-mlogloss:1.73049	validation-mlogloss:1.72464
[36m(train_xgb_ray_tune pid=524065)[0m [201]	train-mlogloss:2.03108	validation-mlogloss:2.02857
[36m(train_xgb_ray_tune pid=524078)[0m [198]	train-mlogloss:1.85470	validation-mlogloss:1.85558
[36m(train_xgb_ray_tune pid=524080)[0m [149]	train-mlogloss:1.52662	validation-mlogloss:1.56575
[36m(train_xgb_ray_tune pid=524045)[0m [232]	train-mlogloss:2.04359	validation-mlogloss:2.03122
[36m(train_xgb_ray_tune pid=524081)[0m [191]	train-mlogloss:1.80701	validation-mlogloss:1.80322
[36m(train_xgb_ray_tune pid=524038)[0m [251]	train-mlogloss:2.25657	validation-mlogloss:2.23945
[36m(train_xgb_ray_tune pid=524044)[0m [198]	train-mlogloss:1.78236	validation-mlogloss:1.78191
[36m(train_xgb_ray_tune pid=524076)[0m [192]	train-mlogloss:2.19209	validation-mlogloss:2.18131
[36m(train_xgb_ray_tune pid=524073)[0m [154]	train-mlogloss:1.98017	validation-mlogloss:1.97843
[36m(train_xgb_ray_tune pid=524078)[0m [199]	train-mlogloss:1.85278	validation-mlogloss:1.85363
[36m(train_xgb_ray_tune pid=524075)[0m [200]	train-mlogloss:1.51354	validation-mlogloss:1.52880
[36m(train_xgb_ray_tune pid=524032)[0m [162]	train-mlogloss:1.77860	validation-mlogloss:1.79924
[36m(train_xgb_ray_tune pid=524064)[0m [191]	train-mlogloss:1.84789	validation-mlogloss:1.84573
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[36m(train_xgb_ray_tune pid=524045)[0m [274]	train-mlogloss:2.03450	validation-mlogloss:2.02219
[36m(train_xgb_ray_tune pid=524038)[0m [295]	train-mlogloss:2.25513	validation-mlogloss:2.23793
[36m(train_xgb_ray_tune pid=524078)[0m [231]	train-mlogloss:1.79544	validation-mlogloss:1.79714
[36m(train_xgb_ray_tune pid=524032)[0m [190]	train-mlogloss:1.71486	validation-mlogloss:1.73636
[36m(train_xgb_ray_tune pid=524080)[0m [173]	train-mlogloss:1.47264	validation-mlogloss:1.51677
[36m(train_xgb_ray_tune pid=524075)[0m [231]	train-mlogloss:1.47252	validation-mlogloss:1.49201
[36m(train_xgb_ray_tune pid=524038)[0m [296]	train-mlogloss:2.25513	validation-mlogloss:2.23793
[36m(train_xgb_ray_tune pid=524076)[0m [222]	train-mlogloss:2.13648	validation-mlogloss:2.12471
[36m(train_xgb_ray_tune pid=524046)[0m [210]	train-mlogloss:1.71022	validation-mlogloss:1.71087
[36m(train_xgb_ray_tune pid=524066)[0m [233]	train-mlogloss:1.68852	validation-mlogloss:1.68496
[36m(train_xgb_ray_tune pid=524064)[0m [222]	train-mlogloss:1.78623	validation-mlogloss:1.78443
[36m(train_xgb_ray_tune pid=524065)[0m [233]	train-mlogloss:1.97034	validation-mlogloss:1.96828
[36m(train_xgb_ray_tune pid=524074)[0m [211]	train-mlogloss:2.30333	validation-mlogloss:2.29322
[36m(train_xgb_ray_tune pid=524079)[0m [187]	train-mlogloss:1.50814	validation-mlogloss:1.53863
[36m(train_xgb_ray_tune pid=524077)[0m [163]	train-mlogloss:1.54092	validation-mlogloss:1.58500
[36m(train_xgb_ray_tune pid=524045)[0m [275]	train-mlogloss:2.03450	validation-mlogloss:2.02219
[36m(train_xgb_ray_tune pid=524081)[0m [224]	train-mlogloss:1.74867	validation-mlogloss:1.74605
[36m(train_xgb_ray_tune pid=524044)[0m [228]	train-mlogloss:1.72326	validation-mlogloss:1.72533
[36m(train_xgb_ray_tune pid=524032)[0m [191]	train-mlogloss:1.71281	validation-mlogloss:1.73436
[36m(train_xgb_ray_tune pid=524075)[0m [232]	train-mlogloss:1.47128	validation-mlogloss:1.49082
[36m(train_xgb_ray_tune pid=524038)[0m [297]	train-mlogloss:2.25513	validation-mlogloss:2.23793
[36m(train_xgb_ray_tune pid=524076)[0m [223]	train-mlogloss:2.13476	validation-mlogloss:2.12295
[36m(train_xgb_ray_tune pid=524046)[0m [211]	train-mlogloss:1.70898	validation-mlogloss:1.70957
[36m(train_xgb_ray_tune pid=524073)[0m [178]	train-mlogloss:1.91557	validation-mlogloss:1.91411
[36m(train_xgb_ray_tune pid=524066)[0m [234]	train-mlogloss:1.68737	validation-mlogloss:1.68386
[36m(train_xgb_ray_tune pid=524064)[0m [223]	train-mlogloss:1.78439	validation-mlogloss:1.78264
[36m(train_xgb_ray_tune pid=524078)[0m [232]	train-mlogloss:1.79383	validation-mlogloss:1.79554
[36m(train_xgb_ray_tune pid=524045)[0m [276]	train-mlogloss:2.03423	validation-mlogloss:2.02193
[36m(train_xgb_ray_tune pid=524080)[0m [174]	train-mlogloss:1.47059	validation-mlogloss:1.51494
[36m(train_xgb_ray_tune pid=524075)[0m [233]	train-mlogloss:1.47003	validation-mlogloss:1.48975
[36m(train_xgb_ray_tune pid=524081)[0m [225]	train-mlogloss:1.74711	validation-mlogloss:1.74443
[36m(train_xgb_ray_tune pid=524038)[0m [298]	train-mlogloss:2.25498	validation-mlogloss:2.23777
[36m(train_xgb_ray_tune pid=524044)[0m [229]	train-mlogloss:1.72155	validation-mlogloss:1.72377
[36m(train_xgb_ray_tune pid=524076)[0m [224]	train-mlogloss:2.13297	validation-mlogloss:2.12107
[36m(train_xgb_ray_tune pid=524066)[0m [235]	train-mlogloss:1.68669	validation-mlogloss:1.68323
[36m(train_xgb_ray_tune pid=524065)[0m [234]	train-mlogloss:1.96854	validation-mlogloss:1.96651
[36m(train_xgb_ray_tune pid=524074)[0m [212]	train-mlogloss:2.30183	validation-mlogloss:2.29166
[36m(train_xgb_ray_tune pid=524079)[0m [188]	train-mlogloss:1.50646	validation-mlogloss:1.53705
[36m(train_xgb_ray_tune pid=524078)[0m [233]	train-mlogloss:1.79222	validation-mlogloss:1.79391
[36m(train_xgb_ray_tune pid=524077)[0m [164]	train-mlogloss:1.53851	validation-mlogloss:1.58287
[36m(train_xgb_ray_tune pid=524032)[0m [192]	train-mlogloss:1.71078	validation-mlogloss:1.73230
[36m(train_xgb_ray_tune pid=524045)[0m [277]	train-mlogloss:2.03405	validation-mlogloss:2.02173
[36m(train_xgb_ray_tune pid=524080)[0m [175]	train-mlogloss:1.46849	validation-mlogloss:1.51317
[36m(train_xgb_ray_tune pid=524038)[0m [299]	train-mlogloss:2.25498	validation-mlogloss:2.23777
[36m(train_xgb_ray_tune pid=524046)[0m [212]	train-mlogloss:1.70782	validation-mlogloss:1.70850
[36m(train_xgb_ray_tune pid=524073)[0m [179]	train-mlogloss:1.91300	validation-mlogloss:1.91151
[36m(train_xgb_ray_tune pid=524064)[0m [224]	train-mlogloss:1.78258	validation-mlogloss:1.78089
[36m(train_xgb_ray_tune pid=524065)[0m [235]	train-mlogloss:1.96679	validation-mlogloss:1.96467
[36m(train_xgb_ray_tune pid=524079)[0m [189]	train-mlogloss:1.50498	validation-mlogloss:1.53570
[36m(train_xgb_ray_tune pid=524078)[0m [234]	train-mlogloss:1.79057	validation-mlogloss:1.79232
[36m(train_xgb_ray_tune pid=524081)[0m [226]	train-mlogloss:1.74555	validation-mlogloss:1.74301
[36m(train_xgb_ray_tune pid=524074)[0m [213]	train-mlogloss:2.30034	validation-mlogloss:2.29012
[36m(train_xgb_ray_tune pid=524032)[0m [193]	train-mlogloss:1.70873	validation-mlogloss:1.73026
[36m(train_xgb_ray_tune pid=524045)[0m [278]	train-mlogloss:2.03397	validation-mlogloss:2.02163
[36m(train_xgb_ray_tune pid=524038)[0m [300]	train-mlogloss:2.25498	validation-mlogloss:2.23777
[36m(train_xgb_ray_tune pid=524044)[0m [230]	train-mlogloss:1.71977	validation-mlogloss:1.72204
[36m(train_xgb_ray_tune pid=524076)[0m [225]	train-mlogloss:2.13117	validation-mlogloss:2.11938
[36m(train_xgb_ray_tune pid=524066)[0m [236]	train-mlogloss:1.68562	validation-mlogloss:1.68217
[36m(train_xgb_ray_tune pid=524077)[0m [165]	train-mlogloss:1.53601	validation-mlogloss:1.58053
[36m(train_xgb_ray_tune pid=524075)[0m [234]	train-mlogloss:1.46888	validation-mlogloss:1.48876
[36m(train_xgb_ray_tune pid=524045)[0m [279]	train-mlogloss:2.03379	validation-mlogloss:2.02146
[36m(train_xgb_ray_tune pid=524080)[0m [176]	train-mlogloss:1.46654	validation-mlogloss:1.51147
[36m(train_xgb_ray_tune pid=524038)[0m [301]	train-mlogloss:2.25498	validation-mlogloss:2.23777
[36m(train_xgb_ray_tune pid=524046)[0m [213]	train-mlogloss:1.70648	validation-mlogloss:1.70718
[36m(train_xgb_ray_tune pid=524073)[0m [180]	train-mlogloss:1.91052	validation-mlogloss:1.90902
[36m(train_xgb_ray_tune pid=524064)[0m [225]	train-mlogloss:1.78075	validation-mlogloss:1.77920
[36m(train_xgb_ray_tune pid=524065)[0m [236]	train-mlogloss:1.96506	validation-mlogloss:1.96296
[36m(train_xgb_ray_tune pid=524074)[0m [214]	train-mlogloss:2.29894	validation-mlogloss:2.28864
[36m(train_xgb_ray_tune pid=524078)[0m [235]	train-mlogloss:1.78896	validation-mlogloss:1.79067
[36m(train_xgb_ray_tune pid=524032)[0m [194]	train-mlogloss:1.70663	validation-mlogloss:1.72825
[36m(train_xgb_ray_tune pid=524075)[0m [235]	train-mlogloss:1.46784	validation-mlogloss:1.48786
[36m(train_xgb_ray_tune pid=524081)[0m [227]	train-mlogloss:1.74399	validation-mlogloss:1.74145
[36m(train_xgb_ray_tune pid=524038)[0m [302]	train-mlogloss:2.25498	validation-mlogloss:2.23777
[36m(train_xgb_ray_tune pid=524044)[0m [231]	train-mlogloss:1.71796	validation-mlogloss:1.72031
[36m(train_xgb_ray_tune pid=524076)[0m [226]	train-mlogloss:2.12944	validation-mlogloss:2.11766
[36m(train_xgb_ray_tune pid=524046)[0m [214]	train-mlogloss:1.70512	validation-mlogloss:1.70592
[36m(train_xgb_ray_tune pid=524066)[0m [237]	train-mlogloss:1.68466	validation-mlogloss:1.68131
[36m(train_xgb_ray_tune pid=524074)[0m [215]	train-mlogloss:2.29745	validation-mlogloss:2.28711
[36m(train_xgb_ray_tune pid=524079)[0m [190]	train-mlogloss:1.50354	validation-mlogloss:1.53432
[36m(train_xgb_ray_tune pid=524077)[0m [166]	train-mlogloss:1.53357	validation-mlogloss:1.57829
[36m(train_xgb_ray_tune pid=524045)[0m [280]	train-mlogloss:2.03370	validation-mlogloss:2.02136
[36m(train_xgb_ray_tune pid=524080)[0m [177]	train-mlogloss:1.46454	validation-mlogloss:1.51001
[36m(train_xgb_ray_tune pid=524032)[0m [195]	train-mlogloss:1.70459	validation-mlogloss:1.72614
[36m(train_xgb_ray_tune pid=524045)[0m [281]	train-mlogloss:2.03370	validation-mlogloss:2.02136
[36m(train_xgb_ray_tune pid=524081)[0m [228]	train-mlogloss:1.74241	validation-mlogloss:1.73985
[36m(train_xgb_ray_tune pid=524038)[0m [303]	train-mlogloss:2.25498	validation-mlogloss:2.23777
[36m(train_xgb_ray_tune pid=524076)[0m [227]	train-mlogloss:2.12770	validation-mlogloss:2.11600
[36m(train_xgb_ray_tune pid=524046)[0m [215]	train-mlogloss:1.70394	validation-mlogloss:1.70471
[36m(train_xgb_ray_tune pid=524073)[0m [181]	train-mlogloss:1.90806	validation-mlogloss:1.90656
[36m(train_xgb_ray_tune pid=524066)[0m [238]	train-mlogloss:1.68375	validation-mlogloss:1.68040
[36m(train_xgb_ray_tune pid=524064)[0m [226]	train-mlogloss:1.77891	validation-mlogloss:1.77746
[36m(train_xgb_ray_tune pid=524065)[0m [237]	train-mlogloss:1.96328	validation-mlogloss:1.96122
[36m(train_xgb_ray_tune pid=524074)[0m [216]	train-mlogloss:2.29595	validation-mlogloss:2.28554
[36m(train_xgb_ray_tune pid=524078)[0m [236]	train-mlogloss:1.78735	validation-mlogloss:1.78904
[36m(train_xgb_ray_tune pid=524044)[0m [232]	train-mlogloss:1.71627	validation-mlogloss:1.71866
[36m(train_xgb_ray_tune pid=524032)[0m [196]	train-mlogloss:1.70251	validation-mlogloss:1.72409
[36m(train_xgb_ray_tune pid=524045)[0m [282]	train-mlogloss:2.03361	validation-mlogloss:2.02126
[36m(train_xgb_ray_tune pid=524080)[0m [178]	train-mlogloss:1.46265	validation-mlogloss:1.50846
[36m(train_xgb_ray_tune pid=524075)[0m [236]	train-mlogloss:1.46679	validation-mlogloss:1.48689
[36m(train_xgb_ray_tune pid=524038)[0m [304]	train-mlogloss:2.25498	validation-mlogloss:2.23777
[36m(train_xgb_ray_tune pid=524038)[0m [305]	train-mlogloss:2.25498	validation-mlogloss:2.23777
[36m(train_xgb_ray_tune pid=524046)[0m [216]	train-mlogloss:1.70280	validation-mlogloss:1.70349
[36m(train_xgb_ray_tune pid=524066)[0m [239]	train-mlogloss:1.68292	validation-mlogloss:1.67966
[36m(train_xgb_ray_tune pid=524064)[0m [227]	train-mlogloss:1.77708	validation-mlogloss:1.77566
[36m(train_xgb_ray_tune pid=524065)[0m [238]	train-mlogloss:1.96153	validation-mlogloss:1.95947
[36m(train_xgb_ray_tune pid=524079)[0m [191]	train-mlogloss:1.50214	validation-mlogloss:1.53300
[36m(train_xgb_ray_tune pid=524078)[0m [237]	train-mlogloss:1.78570	validation-mlogloss:1.78745
[36m(train_xgb_ray_tune pid=524077)[0m [167]	train-mlogloss:1.53115	validation-mlogloss:1.57606
[36m(train_xgb_ray_tune pid=524045)[0m [283]	train-mlogloss:2.03343	validation-mlogloss:2.02105
[36m(train_xgb_ray_tune pid=524075)[0m [237]	train-mlogloss:1.46577	validation-mlogloss:1.48586
[36m(train_xgb_ray_tune pid=524081)[0m [229]	train-mlogloss:1.74083	validation-mlogloss:1.73832
[36m(train_xgb_ray_tune pid=524038)[0m [306]	train-mlogloss:2.25498	validation-mlogloss:2.23777
[36m(train_xgb_ray_tune pid=524044)[0m [233]	train-mlogloss:1.71451	validation-mlogloss:1.71706
[36m(train_xgb_ray_tune pid=524076)[0m [228]	train-mlogloss:2.12604	validation-mlogloss:2.11431
[36m(train_xgb_ray_tune pid=524046)[0m [217]	train-mlogloss:1.70165	validation-mlogloss:1.70229
[36m(train_xgb_ray_tune pid=524073)[0m [182]	train-mlogloss:1.90553	validation-mlogloss:1.90408
[36m(train_xgb_ray_tune pid=524074)[0m [217]	train-mlogloss:2.29448	validation-mlogloss:2.28403
[36m(train_xgb_ray_tune pid=524079)[0m [192]	train-mlogloss:1.50076	validation-mlogloss:1.53171
[36m(train_xgb_ray_tune pid=524078)[0m [238]	train-mlogloss:1.78401	validation-mlogloss:1.78583
[36m(train_xgb_ray_tune pid=524077)[0m [168]	train-mlogloss:1.52887	validation-mlogloss:1.57399
[36m(train_xgb_ray_tune pid=524032)[0m [197]	train-mlogloss:1.70055	validation-mlogloss:1.72218
[36m(train_xgb_ray_tune pid=524045)[0m [284]	train-mlogloss:2.03343	validation-mlogloss:2.02105
[36m(train_xgb_ray_tune pid=524080)[0m [179]	train-mlogloss:1.46069	validation-mlogloss:1.50671
[36m(train_xgb_ray_tune pid=524081)[0m [230]	train-mlogloss:1.73923	validation-mlogloss:1.73671
[36m(train_xgb_ray_tune pid=524038)[0m [307]	train-mlogloss:2.25498	validation-mlogloss:2.23777
[36m(train_xgb_ray_tune pid=524044)[0m [234]	train-mlogloss:1.71270	validation-mlogloss:1.71532
[36m(train_xgb_ray_tune pid=524076)[0m [229]	train-mlogloss:2.12434	validation-mlogloss:2.11262
[36m(train_xgb_ray_tune pid=524066)[0m [240]	train-mlogloss:1.68226	validation-mlogloss:1.67900
[36m(train_xgb_ray_tune pid=524064)[0m [228]	train-mlogloss:1.77534	validation-mlogloss:1.77398
[36m(train_xgb_ray_tune pid=524065)[0m [239]	train-mlogloss:1.95982	validation-mlogloss:1.95770
[36m(train_xgb_ray_tune pid=524074)[0m [218]	train-mlogloss:2.29302	validation-mlogloss:2.28252
[36m(train_xgb_ray_tune pid=524079)[0m [193]	train-mlogloss:1.49929	validation-mlogloss:1.53038
[36m(train_xgb_ray_tune pid=524078)[0m [239]	train-mlogloss:1.78239	validation-mlogloss:1.78426
[36m(train_xgb_ray_tune pid=524046)[0m [218]	train-mlogloss:1.70057	validation-mlogloss:1.70122
[36m(train_xgb_ray_tune pid=524066)[0m [241]	train-mlogloss:1.68128	validation-mlogloss:1.67812
[36m(train_xgb_ray_tune pid=524032)[0m [198]	train-mlogloss:1.69867	validation-mlogloss:1.72032
[36m(train_xgb_ray_tune pid=524045)[0m [285]	train-mlogloss:2.03343	validation-mlogloss:2.02105
[36m(train_xgb_ray_tune pid=524080)[0m [180]	train-mlogloss:1.45884	validation-mlogloss:1.50502
[36m(train_xgb_ray_tune pid=524075)[0m [238]	train-mlogloss:1.46462	validation-mlogloss:1.48484
[36m(train_xgb_ray_tune pid=524038)[0m [308]	train-mlogloss:2.25469	validation-mlogloss:2.23751
[36m(train_xgb_ray_tune pid=524044)[0m [235]	train-mlogloss:1.71096	validation-mlogloss:1.71379
[36m(train_xgb_ray_tune pid=524073)[0m [183]	train-mlogloss:1.90309	validation-mlogloss:1.90177
[36m(train_xgb_ray_tune pid=524065)[0m [240]	train-mlogloss:1.95810	validation-mlogloss:1.95598
[36m(train_xgb_ray_tune pid=524074)[0m [219]	train-mlogloss:2.29161	validation-mlogloss:2.28109
[36m(train_xgb_ray_tune pid=524078)[0m [240]	train-mlogloss:1.78078	validation-mlogloss:1.78268
[36m(train_xgb_ray_tune pid=524077)[0m [169]	train-mlogloss:1.52658	validation-mlogloss:1.57172
[36m(train_xgb_ray_tune pid=524064)[0m [229]	train-mlogloss:1.77370	validation-mlogloss:1.77237
[36m(train_xgb_ray_tune pid=524081)[0m [231]	train-mlogloss:1.73777	validation-mlogloss:1.73529
[36m(train_xgb_ray_tune pid=524066)[0m [242]	train-mlogloss:1.68053	validation-mlogloss:1.67746
[36m(train_xgb_ray_tune pid=524079)[0m [194]	train-mlogloss:1.49781	validation-mlogloss:1.52896
[36m(train_xgb_ray_tune pid=524045)[0m [286]	train-mlogloss:2.03343	validation-mlogloss:2.02105
[36m(train_xgb_ray_tune pid=524075)[0m [239]	train-mlogloss:1.46348	validation-mlogloss:1.48382
[36m(train_xgb_ray_tune pid=524038)[0m [309]	train-mlogloss:2.25454	validation-mlogloss:2.23740

Trial status: 17 RUNNING | 3 TERMINATED
Current time: 2025-10-27 11:13:55. Total running time: 1min 0s
Logical resource usage: 17.0/20 CPUs, 0/1 GPUs (0.0/1.0 accelerator_type:G)
[36m(train_xgb_ray_tune pid=524044)[0m [236]	train-mlogloss:1.70927	validation-mlogloss:1.71211
╭────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ Trial name     status         num_boost_round     max_depth     learning_rate     subsample     colsample_bytree      gamma     min_child_weight     reg_alpha     reg_lambda     random_state     iter     total time (s)     validation_accuracy │
├────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ trial_815ce    RUNNING                    591             3        0.0085005       0.528068             0.538545   27.6444                    84       2.77301        5.6084              9789                                                     │
│ trial_815ce    RUNNING                    682             2        0.0146801       0.785254             0.713742   28.1164                   148     230.112          6.03871             4262                                                     │
│ trial_815ce    RUNNING                    291             2        0.0124667       0.824162             0.57164     5.27421                   62      12.8313       296.871               7779                                                     │
│ trial_815ce    RUNNING                    373             2        0.00615249      0.817785             0.660271   13.2957                   157      21.6249       164.981               7724                                                     │
│ trial_815ce    RUNNING                    718             3        0.0132957       0.580279             0.509772   29.263                    112      36.2913        67.778               6110                                                     │
│ trial_815ce    RUNNING                    626             2        0.0197307       0.760867             0.834172   29.7125                    95     297.768         97.9173               518                                                     │
│ trial_815ce    RUNNING                    647             2        0.0191399       0.637997             0.641773   14.3746                   139      72.7003       158.825               5669                                                     │
│ trial_815ce    RUNNING                    284             2        0.00785538      0.70404              0.765188   29.8994                   171       2.05829       32.3756              7624                                                     │
│ trial_815ce    RUNNING                    402             3        0.0183588       0.507052             0.829074    6.27376                   78      10.5642       623.61                7375                                                     │
│ trial_815ce    RUNNING                    756             2        0.0198547       0.539038             0.656365    9.29435                   97      16.981         42.2814              4597                                                     │
│ trial_815ce    RUNNING                    743             3        0.00571989      0.512015             0.664965   21.0431                   119      20.2153       476.006               5012                                                     │
│ trial_815ce    RUNNING                    445             2        0.011522        0.543758             0.820794   11.8266                   144       2.06773      886.585               5060                                                     │
│ trial_815ce    RUNNING                    714             3        0.0184111       0.611159             0.652786    8.01805                   76      15.9429        41.985                274                                                     │
│ trial_815ce    RUNNING                    735             2        0.0129654       0.753519             0.546044    7.53437                  109      77.9489       132.385               2413                                                     │
│ trial_815ce    RUNNING                    467             3        0.019242        0.80582              0.523636   10.4785                   156      43.0216        47.2207              9252                                                     │
│ trial_815ce    RUNNING                    598             3        0.0135708       0.623241             0.761129   14.8588                    71       1.37779       20.6734              6349                                                     │
│ trial_815ce    RUNNING                    567             2        0.00814755      0.728638             0.827736    9.36595                  126      57.4077        13.7875              8719                                                     │
│ trial_815ce    TERMINATED                 789             3        0.0171509       0.536051             0.50909    24.0376                    63     939.294        903.31                3632        1             8.6632               0.0681818 │
│ trial_815ce    TERMINATED                 224             3        0.0188875       0.765795             0.63462    23.754                    147     293.798        248.333               8671        1            47.3779               0.404941  │
│ trial_815ce    TERMINATED                 217             2        0.0148705       0.565127             0.574846   24.1135                   101     145.722          6.90155             4616        1            47.8721               0.443083  │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=524076)[0m [230]	train-mlogloss:2.12263	validation-mlogloss:2.11088
[36m(train_xgb_ray_tune pid=524046)[0m [219]	train-mlogloss:1.69935	validation-mlogloss:1.70005
[36m(train_xgb_ray_tune pid=524065)[0m [241]	train-mlogloss:1.95641	validation-mlogloss:1.95429
[36m(train_xgb_ray_tune pid=524074)[0m [220]	train-mlogloss:2.29018	validation-mlogloss:2.27956
[36m(train_xgb_ray_tune pid=524078)[0m [241]	train-mlogloss:1.77921	validation-mlogloss:1.78111
[36m(train_xgb_ray_tune pid=524032)[0m [199]	train-mlogloss:1.69667	validation-mlogloss:1.71829
[36m(train_xgb_ray_tune pid=524045)[0m [287]	train-mlogloss:2.03343	validation-mlogloss:2.02105
[36m(train_xgb_ray_tune pid=524045)[0m [288]	train-mlogloss:2.03343	validation-mlogloss:2.02105
[36m(train_xgb_ray_tune pid=524080)[0m [181]	train-mlogloss:1.45698	validation-mlogloss:1.50337
[36m(train_xgb_ray_tune pid=524081)[0m [232]	train-mlogloss:1.73627	validation-mlogloss:1.73388
[36m(train_xgb_ray_tune pid=524038)[0m [310]	train-mlogloss:2.25454	validation-mlogloss:2.23740
[36m(train_xgb_ray_tune pid=524076)[0m [231]	train-mlogloss:2.12090	validation-mlogloss:2.10915
[36m(train_xgb_ray_tune pid=524046)[0m [220]	train-mlogloss:1.69807	validation-mlogloss:1.69885
[36m(train_xgb_ray_tune pid=524073)[0m [184]	train-mlogloss:1.90071	validation-mlogloss:1.89941
[36m(train_xgb_ray_tune pid=524066)[0m [243]	train-mlogloss:1.67967	validation-mlogloss:1.67677
[36m(train_xgb_ray_tune pid=524064)[0m [230]	train-mlogloss:1.77196	validation-mlogloss:1.77067
[36m(train_xgb_ray_tune pid=524065)[0m [242]	train-mlogloss:1.95467	validation-mlogloss:1.95250
[36m(train_xgb_ray_tune pid=524079)[0m [195]	train-mlogloss:1.49627	validation-mlogloss:1.52744
[36m(train_xgb_ray_tune pid=524078)[0m [242]	train-mlogloss:1.77769	validation-mlogloss:1.77962
[36m(train_xgb_ray_tune pid=524077)[0m [170]	train-mlogloss:1.52421	validation-mlogloss:1.56963
[36m(train_xgb_ray_tune pid=524075)[0m [240]	train-mlogloss:1.46238	validation-mlogloss:1.48278
[36m(train_xgb_ray_tune pid=524074)[0m [221]	train-mlogloss:2.28876	validation-mlogloss:2.27810
[36m(train_xgb_ray_tune pid=524032)[0m [200]	train-mlogloss:1.69478	validation-mlogloss:1.71644
[36m(train_xgb_ray_tune pid=524045)[0m [289]	train-mlogloss:2.03334	validation-mlogloss:2.02096
[36m(train_xgb_ray_tune pid=524075)[0m [241]	train-mlogloss:1.46125	validation-mlogloss:1.48172
[36m(train_xgb_ray_tune pid=524038)[0m [311]	train-mlogloss:2.25454	validation-mlogloss:2.23740
[36m(train_xgb_ray_tune pid=524044)[0m [237]	train-mlogloss:1.70754	validation-mlogloss:1.71040
[36m(train_xgb_ray_tune pid=524073)[0m [185]	train-mlogloss:1.89824	validation-mlogloss:1.89707
[36m(train_xgb_ray_tune pid=524066)[0m [244]	train-mlogloss:1.67898	validation-mlogloss:1.67606
[36m(train_xgb_ray_tune pid=524064)[0m [231]	train-mlogloss:1.77025	validation-mlogloss:1.76896
[36m(train_xgb_ray_tune pid=524079)[0m [196]	train-mlogloss:1.49496	validation-mlogloss:1.52597
[36m(train_xgb_ray_tune pid=524038)[0m [312]	train-mlogloss:2.25454	validation-mlogloss:2.23740
[36m(train_xgb_ray_tune pid=524081)[0m [233]	train-mlogloss:1.73475	validation-mlogloss:1.73246
[36m(train_xgb_ray_tune pid=524080)[0m [182]	train-mlogloss:1.45520	validation-mlogloss:1.50176
[36m(train_xgb_ray_tune pid=524046)[0m [221]	train-mlogloss:1.69672	validation-mlogloss:1.69759
[36m(train_xgb_ray_tune pid=524065)[0m [243]	train-mlogloss:1.95301	validation-mlogloss:1.95079
[36m(train_xgb_ray_tune pid=524078)[0m [243]	train-mlogloss:1.77615	validation-mlogloss:1.77812
[36m(train_xgb_ray_tune pid=524045)[0m [290]	train-mlogloss:2.03334	validation-mlogloss:2.02096
[36m(train_xgb_ray_tune pid=524038)[0m [313]	train-mlogloss:2.25454	validation-mlogloss:2.23740
[36m(train_xgb_ray_tune pid=524044)[0m [238]	train-mlogloss:1.70581	validation-mlogloss:1.70884
[36m(train_xgb_ray_tune pid=524076)[0m [232]	train-mlogloss:2.11919	validation-mlogloss:2.10741
[36m(train_xgb_ray_tune pid=524066)[0m [245]	train-mlogloss:1.67816	validation-mlogloss:1.67527
[36m(train_xgb_ray_tune pid=524064)[0m [232]	train-mlogloss:1.76855	validation-mlogloss:1.76729
[36m(train_xgb_ray_tune pid=524074)[0m [222]	train-mlogloss:2.28728	validation-mlogloss:2.27658
[36m(train_xgb_ray_tune pid=524077)[0m [171]	train-mlogloss:1.52182	validation-mlogloss:1.56745
[36m(train_xgb_ray_tune pid=524032)[0m [201]	train-mlogloss:1.69278	validation-mlogloss:1.71437
[36m(train_xgb_ray_tune pid=524045)[0m [291]	train-mlogloss:2.03334	validation-mlogloss:2.02096
[36m(train_xgb_ray_tune pid=524080)[0m [183]	train-mlogloss:1.45348	validation-mlogloss:1.50025
[36m(train_xgb_ray_tune pid=524075)[0m [242]	train-mlogloss:1.46012	validation-mlogloss:1.48067
[36m(train_xgb_ray_tune pid=524081)[0m [234]	train-mlogloss:1.73318	validation-mlogloss:1.73101
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[36m(train_xgb_ray_tune pid=524044)[0m [239]	train-mlogloss:1.70413	validation-mlogloss:1.70735
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[36m(train_xgb_ray_tune pid=524046)[0m [222]	train-mlogloss:1.69548	validation-mlogloss:1.69639
[36m(train_xgb_ray_tune pid=524073)[0m [186]	train-mlogloss:1.89565	validation-mlogloss:1.89461
[36m(train_xgb_ray_tune pid=524066)[0m [246]	train-mlogloss:1.67758	validation-mlogloss:1.67464
[36m(train_xgb_ray_tune pid=524065)[0m [244]	train-mlogloss:1.95125	validation-mlogloss:1.94906
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[36m(train_xgb_ray_tune pid=524079)[0m [197]	train-mlogloss:1.49355	validation-mlogloss:1.52474
[36m(train_xgb_ray_tune pid=524078)[0m [244]	train-mlogloss:1.77460	validation-mlogloss:1.77651
[36m(train_xgb_ray_tune pid=524038)[0m [315]	train-mlogloss:2.25439	validation-mlogloss:2.23722
[36m(train_xgb_ray_tune pid=524032)[0m [202]	train-mlogloss:1.69089	validation-mlogloss:1.71251
[36m(train_xgb_ray_tune pid=524045)[0m [292]	train-mlogloss:2.03326	validation-mlogloss:2.02086
[36m(train_xgb_ray_tune pid=524075)[0m [243]	train-mlogloss:1.45913	validation-mlogloss:1.47980
[36m(train_xgb_ray_tune pid=524046)[0m [223]	train-mlogloss:1.69431	validation-mlogloss:1.69517
[36m(train_xgb_ray_tune pid=524073)[0m [187]	train-mlogloss:1.89331	validation-mlogloss:1.89229
[36m(train_xgb_ray_tune pid=524066)[0m [247]	train-mlogloss:1.67671	validation-mlogloss:1.67380
[36m(train_xgb_ray_tune pid=524064)[0m [233]	train-mlogloss:1.76684	validation-mlogloss:1.76561
[36m(train_xgb_ray_tune pid=524065)[0m [245]	train-mlogloss:1.94958	validation-mlogloss:1.94736
[36m(train_xgb_ray_tune pid=524079)[0m [198]	train-mlogloss:1.49207	validation-mlogloss:1.52335
[36m(train_xgb_ray_tune pid=524078)[0m [245]	train-mlogloss:1.77304	validation-mlogloss:1.77493
[36m(train_xgb_ray_tune pid=524077)[0m [172]	train-mlogloss:1.51951	validation-mlogloss:1.56549
[36m(train_xgb_ray_tune pid=524081)[0m [235]	train-mlogloss:1.73173	validation-mlogloss:1.72954
[36m(train_xgb_ray_tune pid=524038)[0m [316]	train-mlogloss:2.25439	validation-mlogloss:2.23722
[36m(train_xgb_ray_tune pid=524032)[0m [203]	train-mlogloss:1.68890	validation-mlogloss:1.71044
[36m(train_xgb_ray_tune pid=524045)[0m [293]	train-mlogloss:2.03326	validation-mlogloss:2.02086
[36m(train_xgb_ray_tune pid=524080)[0m [184]	train-mlogloss:1.45182	validation-mlogloss:1.49876
[36m(train_xgb_ray_tune pid=524044)[0m [240]	train-mlogloss:1.70241	validation-mlogloss:1.70570
[36m(train_xgb_ray_tune pid=524076)[0m [234]	train-mlogloss:2.11589	validation-mlogloss:2.10412
[36m(train_xgb_ray_tune pid=524046)[0m [224]	train-mlogloss:1.69304	validation-mlogloss:1.69392
[36m(train_xgb_ray_tune pid=524066)[0m [248]	train-mlogloss:1.67587	validation-mlogloss:1.67305
[36m(train_xgb_ray_tune pid=524064)[0m [234]	train-mlogloss:1.76508	validation-mlogloss:1.76394
[36m(train_xgb_ray_tune pid=524065)[0m [246]	train-mlogloss:1.94789	validation-mlogloss:1.94573
[36m(train_xgb_ray_tune pid=524074)[0m [224]	train-mlogloss:2.28435	validation-mlogloss:2.27353
[36m(train_xgb_ray_tune pid=524045)[0m [294]	train-mlogloss:2.03326	validation-mlogloss:2.02086
[36m(train_xgb_ray_tune pid=524075)[0m [244]	train-mlogloss:1.45806	validation-mlogloss:1.47890
[36m(train_xgb_ray_tune pid=524038)[0m [317]	train-mlogloss:2.25439	validation-mlogloss:2.23722
[36m(train_xgb_ray_tune pid=524032)[0m [204]	train-mlogloss:1.68685	validation-mlogloss:1.70836
[36m(train_xgb_ray_tune pid=524045)[0m [295]	train-mlogloss:2.03309	validation-mlogloss:2.02070
[36m(train_xgb_ray_tune pid=524081)[0m [236]	train-mlogloss:1.73023	validation-mlogloss:1.72812
[36m(train_xgb_ray_tune pid=524038)[0m [318]	train-mlogloss:2.25439	validation-mlogloss:2.23722
[36m(train_xgb_ray_tune pid=524044)[0m [241]	train-mlogloss:1.70076	validation-mlogloss:1.70425
[36m(train_xgb_ray_tune pid=524076)[0m [235]	train-mlogloss:2.11431	validation-mlogloss:2.10252
[36m(train_xgb_ray_tune pid=524046)[0m [225]	train-mlogloss:1.69179	validation-mlogloss:1.69274
[36m(train_xgb_ray_tune pid=524073)[0m [188]	train-mlogloss:1.89089	validation-mlogloss:1.88997
[36m(train_xgb_ray_tune pid=524066)[0m [249]	train-mlogloss:1.67505	validation-mlogloss:1.67226
[36m(train_xgb_ray_tune pid=524065)[0m [247]	train-mlogloss:1.94623	validation-mlogloss:1.94414
[36m(train_xgb_ray_tune pid=524074)[0m [225]	train-mlogloss:2.28294	validation-mlogloss:2.27209
[36m(train_xgb_ray_tune pid=524079)[0m [199]	train-mlogloss:1.49067	validation-mlogloss:1.52196
[36m(train_xgb_ray_tune pid=524078)[0m [246]	train-mlogloss:1.77156	validation-mlogloss:1.77348
[36m(train_xgb_ray_tune pid=524077)[0m [173]	train-mlogloss:1.51710	validation-mlogloss:1.56335
[36m(train_xgb_ray_tune pid=524045)[0m [296]	train-mlogloss:2.03300	validation-mlogloss:2.02059
[36m(train_xgb_ray_tune pid=524080)[0m [185]	train-mlogloss:1.44991	validation-mlogloss:1.49695
[36m(train_xgb_ray_tune pid=524075)[0m [245]	train-mlogloss:1.45704	validation-mlogloss:1.47804
[36m(train_xgb_ray_tune pid=524081)[0m [237]	train-mlogloss:1.72875	validation-mlogloss:1.72668
[36m(train_xgb_ray_tune pid=524038)[0m [319]	train-mlogloss:2.25425	validation-mlogloss:2.23709
[36m(train_xgb_ray_tune pid=524076)[0m [236]	train-mlogloss:2.11258	validation-mlogloss:2.10075
[36m(train_xgb_ray_tune pid=524073)[0m [189]	train-mlogloss:1.88844	validation-mlogloss:1.88759
[36m(train_xgb_ray_tune pid=524066)[0m [250]	train-mlogloss:1.67425	validation-mlogloss:1.67151
[36m(train_xgb_ray_tune pid=524064)[0m [235]	train-mlogloss:1.76336	validation-mlogloss:1.76227
[36m(train_xgb_ray_tune pid=524065)[0m [248]	train-mlogloss:1.94459	validation-mlogloss:1.94251
[36m(train_xgb_ray_tune pid=524078)[0m [247]	train-mlogloss:1.77009	validation-mlogloss:1.77201
[36m(train_xgb_ray_tune pid=524077)[0m [174]	train-mlogloss:1.51486	validation-mlogloss:1.56133
[36m(train_xgb_ray_tune pid=524032)[0m [205]	train-mlogloss:1.68497	validation-mlogloss:1.70653
[36m(train_xgb_ray_tune pid=524045)[0m [297]	train-mlogloss:2.03300	validation-mlogloss:2.02059
[36m(train_xgb_ray_tune pid=524080)[0m [186]	train-mlogloss:1.44820	validation-mlogloss:1.49524
[36m(train_xgb_ray_tune pid=524081)[0m [238]	train-mlogloss:1.72726	validation-mlogloss:1.72523
[36m(train_xgb_ray_tune pid=524038)[0m [320]	train-mlogloss:2.25425	validation-mlogloss:2.23709
[36m(train_xgb_ray_tune pid=524044)[0m [242]	train-mlogloss:1.69905	validation-mlogloss:1.70265
[36m(train_xgb_ray_tune pid=524076)[0m [237]	train-mlogloss:2.11094	validation-mlogloss:2.09915
[36m(train_xgb_ray_tune pid=524046)[0m [226]	train-mlogloss:1.69051	validation-mlogloss:1.69142
[36m(train_xgb_ray_tune pid=524066)[0m [251]	train-mlogloss:1.67356	validation-mlogloss:1.67078
[36m(train_xgb_ray_tune pid=524064)[0m [236]	train-mlogloss:1.76169	validation-mlogloss:1.76063
[36m(train_xgb_ray_tune pid=524074)[0m [226]	train-mlogloss:2.28147	validation-mlogloss:2.27062
[36m(train_xgb_ray_tune pid=524079)[0m [200]	train-mlogloss:1.48929	validation-mlogloss:1.52063
[36m(train_xgb_ray_tune pid=524078)[0m [248]	train-mlogloss:1.76858	validation-mlogloss:1.77054
[36m(train_xgb_ray_tune pid=524075)[0m [246]	train-mlogloss:1.45599	validation-mlogloss:1.47715
[36m(train_xgb_ray_tune pid=524032)[0m [206]	train-mlogloss:1.68315	validation-mlogloss:1.70467
[36m(train_xgb_ray_tune pid=524045)[0m [298]	train-mlogloss:2.03281	validation-mlogloss:2.02036
[36m(train_xgb_ray_tune pid=524080)[0m [187]	train-mlogloss:1.44641	validation-mlogloss:1.49380
[36m(train_xgb_ray_tune pid=524038)[0m [321]	train-mlogloss:2.25425	validation-mlogloss:2.23709
[36m(train_xgb_ray_tune pid=524044)[0m [243]	train-mlogloss:1.69737	validation-mlogloss:1.70102
[36m(train_xgb_ray_tune pid=524076)[0m [238]	train-mlogloss:2.10934	validation-mlogloss:2.09743
[36m(train_xgb_ray_tune pid=524046)[0m [227]	train-mlogloss:1.68942	validation-mlogloss:1.69037
[36m(train_xgb_ray_tune pid=524073)[0m [190]	train-mlogloss:1.88598	validation-mlogloss:1.88525
[36m(train_xgb_ray_tune pid=524065)[0m [249]	train-mlogloss:1.94295	validation-mlogloss:1.94094
[36m(train_xgb_ray_tune pid=524079)[0m [201]	train-mlogloss:1.48801	validation-mlogloss:1.51937
[36m(train_xgb_ray_tune pid=524077)[0m [175]	train-mlogloss:1.51251	validation-mlogloss:1.55920
[36m(train_xgb_ray_tune pid=524074)[0m [227]	train-mlogloss:2.28006	validation-mlogloss:2.26918
[36m(train_xgb_ray_tune pid=524081)[0m [239]	train-mlogloss:1.72581	validation-mlogloss:1.72384
[36m(train_xgb_ray_tune pid=524066)[0m [252]	train-mlogloss:1.67296	validation-mlogloss:1.67016
[36m(train_xgb_ray_tune pid=524045)[0m [299]	train-mlogloss:2.03273	validation-mlogloss:2.02026
[36m(train_xgb_ray_tune pid=524080)[0m [188]	train-mlogloss:1.44475	validation-mlogloss:1.49229
[36m(train_xgb_ray_tune pid=524075)[0m [247]	train-mlogloss:1.45502	validation-mlogloss:1.47621
[36m(train_xgb_ray_tune pid=524038)[0m [322]	train-mlogloss:2.25425	validation-mlogloss:2.23709
[36m(train_xgb_ray_tune pid=524046)[0m [228]	train-mlogloss:1.68828	validation-mlogloss:1.68930
[36m(train_xgb_ray_tune pid=524064)[0m [237]	train-mlogloss:1.75997	validation-mlogloss:1.75891
[36m(train_xgb_ray_tune pid=524065)[0m [250]	train-mlogloss:1.94131	validation-mlogloss:1.93936
[36m(train_xgb_ray_tune pid=524078)[0m [249]	train-mlogloss:1.76706	validation-mlogloss:1.76904
[36m(train_xgb_ray_tune pid=524032)[0m [207]	train-mlogloss:1.68131	validation-mlogloss:1.70281
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[36m(train_xgb_ray_tune pid=524044)[0m [290]	train-mlogloss:1.62771	validation-mlogloss:1.63620
[36m(train_xgb_ray_tune pid=524046)[0m [284]	train-mlogloss:1.64269	validation-mlogloss:1.64542
[36m(train_xgb_ray_tune pid=524066)[0m [318]	train-mlogloss:1.64038	validation-mlogloss:1.63913
[36m(train_xgb_ray_tune pid=524074)[0m [274]	train-mlogloss:2.21614	validation-mlogloss:2.20366
[36m(train_xgb_ray_tune pid=524079)[0m [246]	train-mlogloss:1.43865	validation-mlogloss:1.47400
[36m(train_xgb_ray_tune pid=524078)[0m [296]	train-mlogloss:1.70408	validation-mlogloss:1.70841
[36m(train_xgb_ray_tune pid=524077)[0m [211]	train-mlogloss:1.44301	validation-mlogloss:1.49618
[36m(train_xgb_ray_tune pid=524038)[0m [393]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524032)[0m [251]	train-mlogloss:1.60978	validation-mlogloss:1.63201
[36m(train_xgb_ray_tune pid=524064)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454
[36m(train_xgb_ray_tune pid=524064)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=524045)[0m [375]	train-mlogloss:2.02859	validation-mlogloss:2.01603
[36m(train_xgb_ray_tune pid=524075)[0m [296]	train-mlogloss:1.41423	validation-mlogloss:1.44042
[36m(train_xgb_ray_tune pid=524038)[0m [394]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524076)[0m [287]	train-mlogloss:2.03263	validation-mlogloss:2.01977
[36m(train_xgb_ray_tune pid=524046)[0m [285]	train-mlogloss:1.64215	validation-mlogloss:1.64489
[36m(train_xgb_ray_tune pid=524073)[0m [230]	train-mlogloss:1.80091	validation-mlogloss:1.80169
[36m(train_xgb_ray_tune pid=524065)[0m [297]	train-mlogloss:1.86916	validation-mlogloss:1.86802
[36m(train_xgb_ray_tune pid=524079)[0m [247]	train-mlogloss:1.43790	validation-mlogloss:1.47327
[36m(train_xgb_ray_tune pid=524078)[0m [297]	train-mlogloss:1.70293	validation-mlogloss:1.70733
[36m(train_xgb_ray_tune pid=524077)[0m [212]	train-mlogloss:1.44137	validation-mlogloss:1.49459
[36m(train_xgb_ray_tune pid=524081)[0m [291]	train-mlogloss:1.66071	validation-mlogloss:1.66143
[36m(train_xgb_ray_tune pid=524066)[0m [319]	train-mlogloss:1.64002	validation-mlogloss:1.63882
[36m(train_xgb_ray_tune pid=524032)[0m [252]	train-mlogloss:1.60828	validation-mlogloss:1.63039
[36m(train_xgb_ray_tune pid=524045)[0m [376]	train-mlogloss:2.02859	validation-mlogloss:2.01603
[36m(train_xgb_ray_tune pid=524080)[0m [230]	train-mlogloss:1.38304	validation-mlogloss:1.43995
[36m(train_xgb_ray_tune pid=524038)[0m [395]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524076)[0m [288]	train-mlogloss:2.03119	validation-mlogloss:2.01833
[36m(train_xgb_ray_tune pid=524046)[0m [286]	train-mlogloss:1.64156	validation-mlogloss:1.64431
[36m(train_xgb_ray_tune pid=524073)[0m [231]	train-mlogloss:1.79911	validation-mlogloss:1.79996
[36m(train_xgb_ray_tune pid=524065)[0m [298]	train-mlogloss:1.86772	validation-mlogloss:1.86659
[36m(train_xgb_ray_tune pid=524074)[0m [275]	train-mlogloss:2.21485	validation-mlogloss:2.20231
[36m(train_xgb_ray_tune pid=524045)[0m [377]	train-mlogloss:2.02859	validation-mlogloss:2.01603
[36m(train_xgb_ray_tune pid=524075)[0m [297]	train-mlogloss:1.41351	validation-mlogloss:1.43976
[36m(train_xgb_ray_tune pid=524081)[0m [292]	train-mlogloss:1.65962	validation-mlogloss:1.66037
[36m(train_xgb_ray_tune pid=524038)[0m [396]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524076)[0m [289]	train-mlogloss:2.02985	validation-mlogloss:2.01690
[36m(train_xgb_ray_tune pid=524046)[0m [287]	train-mlogloss:1.64093	validation-mlogloss:1.64375
[36m(train_xgb_ray_tune pid=524066)[0m [320]	train-mlogloss:1.63984	validation-mlogloss:1.63872
[36m(train_xgb_ray_tune pid=524065)[0m [299]	train-mlogloss:1.86628	validation-mlogloss:1.86520
[36m(train_xgb_ray_tune pid=524074)[0m [276]	train-mlogloss:2.21362	validation-mlogloss:2.20102
[36m(train_xgb_ray_tune pid=524079)[0m [248]	train-mlogloss:1.43722	validation-mlogloss:1.47250
[36m(train_xgb_ray_tune pid=524078)[0m [298]	train-mlogloss:1.70174	validation-mlogloss:1.70619
[36m(train_xgb_ray_tune pid=524077)[0m [213]	train-mlogloss:1.43968	validation-mlogloss:1.49324

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:07. Total running time: 1min 11s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             68.5358 │
│ time_total_s                 68.5358 │
│ training_iteration                 1 │
│ validation_accuracy          0.48854 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:07. Total running time: 1min 11s
[36m(train_xgb_ray_tune pid=524032)[0m [253]	train-mlogloss:1.60698	validation-mlogloss:1.62904
[36m(train_xgb_ray_tune pid=524045)[0m [378]	train-mlogloss:2.02859	validation-mlogloss:2.01603
[36m(train_xgb_ray_tune pid=524080)[0m [231]	train-mlogloss:1.38181	validation-mlogloss:1.43899
[36m(train_xgb_ray_tune pid=524075)[0m [298]	train-mlogloss:1.41281	validation-mlogloss:1.43918
[36m(train_xgb_ray_tune pid=524081)[0m [293]	train-mlogloss:1.65853	validation-mlogloss:1.65942
[36m(train_xgb_ray_tune pid=524038)[0m [397]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524076)[0m [290]	train-mlogloss:2.02836	validation-mlogloss:2.01545
[36m(train_xgb_ray_tune pid=524046)[0m [288]	train-mlogloss:1.64052	validation-mlogloss:1.64333
[36m(train_xgb_ray_tune pid=524073)[0m [232]	train-mlogloss:1.79711	validation-mlogloss:1.79809
[36m(train_xgb_ray_tune pid=524066)[0m [321]	train-mlogloss:1.63956	validation-mlogloss:1.63842
[36m(train_xgb_ray_tune pid=524065)[0m [300]	train-mlogloss:1.86493	validation-mlogloss:1.86390
[36m(train_xgb_ray_tune pid=524074)[0m [277]	train-mlogloss:2.21236	validation-mlogloss:2.19975
[36m(train_xgb_ray_tune pid=524079)[0m [249]	train-mlogloss:1.43647	validation-mlogloss:1.47176
[36m(train_xgb_ray_tune pid=524078)[0m [299]	train-mlogloss:1.70052	validation-mlogloss:1.70500
[36m(train_xgb_ray_tune pid=524032)[0m [254]	train-mlogloss:1.60559	validation-mlogloss:1.62765
[36m(train_xgb_ray_tune pid=524045)[0m [379]	train-mlogloss:2.02859	validation-mlogloss:2.01603
[36m(train_xgb_ray_tune pid=524080)[0m [232]	train-mlogloss:1.38078	validation-mlogloss:1.43809
[36m(train_xgb_ray_tune pid=524075)[0m [299]	train-mlogloss:1.41223	validation-mlogloss:1.43872
[36m(train_xgb_ray_tune pid=524081)[0m [294]	train-mlogloss:1.65750	validation-mlogloss:1.65847
[36m(train_xgb_ray_tune pid=524038)[0m [398]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524076)[0m [291]	train-mlogloss:2.02682	validation-mlogloss:2.01399
[36m(train_xgb_ray_tune pid=524046)[0m [289]	train-mlogloss:1.63998	validation-mlogloss:1.64283
[36m(train_xgb_ray_tune pid=524073)[0m [233]	train-mlogloss:1.79522	validation-mlogloss:1.79620
[36m(train_xgb_ray_tune pid=524066)[0m [322]	train-mlogloss:1.63934	validation-mlogloss:1.63821
[36m(train_xgb_ray_tune pid=524065)[0m [301]	train-mlogloss:1.86356	validation-mlogloss:1.86252
[36m(train_xgb_ray_tune pid=524074)[0m [278]	train-mlogloss:2.21109	validation-mlogloss:2.19845
[36m(train_xgb_ray_tune pid=524077)[0m [214]	train-mlogloss:1.43810	validation-mlogloss:1.49178
[36m(train_xgb_ray_tune pid=524045)[0m [380]	train-mlogloss:2.02859	validation-mlogloss:2.01603
[36m(train_xgb_ray_tune pid=524080)[0m [233]	train-mlogloss:1.37955	validation-mlogloss:1.43715
[36m(train_xgb_ray_tune pid=524081)[0m [295]	train-mlogloss:1.65641	validation-mlogloss:1.65747
[36m(train_xgb_ray_tune pid=524038)[0m [399]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524038)[0m [400]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524046)[0m [290]	train-mlogloss:1.63950	validation-mlogloss:1.64233
[36m(train_xgb_ray_tune pid=524066)[0m [323]	train-mlogloss:1.63896	validation-mlogloss:1.63781
[36m(train_xgb_ray_tune pid=524065)[0m [302]	train-mlogloss:1.86220	validation-mlogloss:1.86111
[36m(train_xgb_ray_tune pid=524074)[0m [279]	train-mlogloss:2.20977	validation-mlogloss:2.19706
[36m(train_xgb_ray_tune pid=524079)[0m [250]	train-mlogloss:1.43558	validation-mlogloss:1.47099
[36m(train_xgb_ray_tune pid=524078)[0m [300]	train-mlogloss:1.69932	validation-mlogloss:1.70387
[36m(train_xgb_ray_tune pid=524077)[0m [215]	train-mlogloss:1.43650	validation-mlogloss:1.49043
[36m(train_xgb_ray_tune pid=524032)[0m [255]	train-mlogloss:1.60425	validation-mlogloss:1.62633
[36m(train_xgb_ray_tune pid=524045)[0m [381]	train-mlogloss:2.02859	validation-mlogloss:2.01603
[36m(train_xgb_ray_tune pid=524080)[0m [234]	train-mlogloss:1.37842	validation-mlogloss:1.43631
[36m(train_xgb_ray_tune pid=524044)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454
[36m(train_xgb_ray_tune pid=524044)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=524075)[0m [300]	train-mlogloss:1.41150	validation-mlogloss:1.43829
[36m(train_xgb_ray_tune pid=524081)[0m [296]	train-mlogloss:1.65537	validation-mlogloss:1.65653
[36m(train_xgb_ray_tune pid=524038)[0m [401]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524076)[0m [292]	train-mlogloss:2.02540	validation-mlogloss:2.01258
[36m(train_xgb_ray_tune pid=524046)[0m [291]	train-mlogloss:1.63892	validation-mlogloss:1.64175
[36m(train_xgb_ray_tune pid=524073)[0m [234]	train-mlogloss:1.79339	validation-mlogloss:1.79441
[36m(train_xgb_ray_tune pid=524066)[0m [324]	train-mlogloss:1.63874	validation-mlogloss:1.63755
[36m(train_xgb_ray_tune pid=524079)[0m [251]	train-mlogloss:1.43477	validation-mlogloss:1.47032
[36m(train_xgb_ray_tune pid=524078)[0m [301]	train-mlogloss:1.69821	validation-mlogloss:1.70275
[36m(train_xgb_ray_tune pid=524032)[0m [256]	train-mlogloss:1.60287	validation-mlogloss:1.62492
[36m(train_xgb_ray_tune pid=524045)[0m [382]	train-mlogloss:2.02859	validation-mlogloss:2.01603
[36m(train_xgb_ray_tune pid=524075)[0m [301]	train-mlogloss:1.41086	validation-mlogloss:1.43764
[36m(train_xgb_ray_tune pid=524038)[0m [402]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524076)[0m [293]	train-mlogloss:2.02396	validation-mlogloss:2.01109
[36m(train_xgb_ray_tune pid=524046)[0m [292]	train-mlogloss:1.63835	validation-mlogloss:1.64114
[36m(train_xgb_ray_tune pid=524066)[0m [325]	train-mlogloss:1.63847	validation-mlogloss:1.63729
[36m(train_xgb_ray_tune pid=524065)[0m [303]	train-mlogloss:1.86076	validation-mlogloss:1.85970
[36m(train_xgb_ray_tune pid=524065)[0m [304]	train-mlogloss:1.85936	validation-mlogloss:1.85833
[36m(train_xgb_ray_tune pid=524074)[0m [280]	train-mlogloss:2.20852	validation-mlogloss:2.19576
[36m(train_xgb_ray_tune pid=524078)[0m [302]	train-mlogloss:1.69693	validation-mlogloss:1.70158
[36m(train_xgb_ray_tune pid=524077)[0m [216]	train-mlogloss:1.43497	validation-mlogloss:1.48911
[36m(train_xgb_ray_tune pid=524081)[0m [297]	train-mlogloss:1.65428	validation-mlogloss:1.65549
[36m(train_xgb_ray_tune pid=524079)[0m [252]	train-mlogloss:1.43399	validation-mlogloss:1.46969
[36m(train_xgb_ray_tune pid=524045)[0m [383]	train-mlogloss:2.02859	validation-mlogloss:2.01603
[36m(train_xgb_ray_tune pid=524080)[0m [235]	train-mlogloss:1.37736	validation-mlogloss:1.43539
[36m(train_xgb_ray_tune pid=524038)[0m [403]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524077)[0m [217]	train-mlogloss:1.43335	validation-mlogloss:1.48777
[36m(train_xgb_ray_tune pid=524032)[0m [257]	train-mlogloss:1.60142	validation-mlogloss:1.62345
[36m(train_xgb_ray_tune pid=524045)[0m [384]	train-mlogloss:2.02841	validation-mlogloss:2.01581
[36m(train_xgb_ray_tune pid=524038)[0m [404]	train-mlogloss:2.25130	validation-mlogloss:2.23412
[36m(train_xgb_ray_tune pid=524076)[0m [294]	train-mlogloss:2.02251	validation-mlogloss:2.00967
[36m(train_xgb_ray_tune pid=524046)[0m [293]	train-mlogloss:1.63784	validation-mlogloss:1.64065
[36m(train_xgb_ray_tune pid=524073)[0m [235]	train-mlogloss:1.79154	validation-mlogloss:1.79256
[36m(train_xgb_ray_tune pid=524066)[0m [326]	train-mlogloss:1.63813	validation-mlogloss:1.63701
[36m(train_xgb_ray_tune pid=524065)[0m [305]	train-mlogloss:1.85802	validation-mlogloss:1.85692
[36m(train_xgb_ray_tune pid=524074)[0m [281]	train-mlogloss:2.20724	validation-mlogloss:2.19444
[36m(train_xgb_ray_tune pid=524078)[0m [303]	train-mlogloss:1.69575	validation-mlogloss:1.70048
[36m(train_xgb_ray_tune pid=524075)[0m [302]	train-mlogloss:1.41022	validation-mlogloss:1.43716
[36m(train_xgb_ray_tune pid=524081)[0m [298]	train-mlogloss:1.65320	validation-mlogloss:1.65451
[36m(train_xgb_ray_tune pid=524046)[0m [294]	train-mlogloss:1.63742	validation-mlogloss:1.64020
[36m(train_xgb_ray_tune pid=524045)[0m [385]	train-mlogloss:2.02841	validation-mlogloss:2.01581
[36m(train_xgb_ray_tune pid=524080)[0m [236]	train-mlogloss:1.37626	validation-mlogloss:1.43452
[36m(train_xgb_ray_tune pid=524046)[0m [295]	train-mlogloss:1.63691	validation-mlogloss:1.63965
[36m(train_xgb_ray_tune pid=524066)[0m [327]	train-mlogloss:1.63796	validation-mlogloss:1.63682
[36m(train_xgb_ray_tune pid=524065)[0m [306]	train-mlogloss:1.85667	validation-mlogloss:1.85560
[36m(train_xgb_ray_tune pid=524074)[0m [282]	train-mlogloss:2.20603	validation-mlogloss:2.19320
[36m(train_xgb_ray_tune pid=524079)[0m [253]	train-mlogloss:1.43311	validation-mlogloss:1.46889
[36m(train_xgb_ray_tune pid=524077)[0m [218]	train-mlogloss:1.43176	validation-mlogloss:1.48661
[36m(train_xgb_ray_tune pid=524076)[0m [295]	train-mlogloss:2.02113	validation-mlogloss:2.00826

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:08. Total running time: 1min 13s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             69.7763 │
│ time_total_s                 69.7763 │
│ training_iteration                 1 │
│ validation_accuracy          0.50059 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=524032)[0m [258]	train-mlogloss:1.60003	validation-mlogloss:1.62214

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:08. Total running time: 1min 13s
[36m(train_xgb_ray_tune pid=524045)[0m [386]	train-mlogloss:2.02832	validation-mlogloss:2.01576
[36m(train_xgb_ray_tune pid=524075)[0m [303]	train-mlogloss:1.40954	validation-mlogloss:1.43653
[36m(train_xgb_ray_tune pid=524081)[0m [299]	train-mlogloss:1.65215	validation-mlogloss:1.65351
[36m(train_xgb_ray_tune pid=524076)[0m [296]	train-mlogloss:2.01977	validation-mlogloss:2.00690
[36m(train_xgb_ray_tune pid=524046)[0m [296]	train-mlogloss:1.63649	validation-mlogloss:1.63929
[36m(train_xgb_ray_tune pid=524073)[0m [236]	train-mlogloss:1.78955	validation-mlogloss:1.79070
[36m(train_xgb_ray_tune pid=524066)[0m [328]	train-mlogloss:1.63778	validation-mlogloss:1.63661
[36m(train_xgb_ray_tune pid=524065)[0m [307]	train-mlogloss:1.85530	validation-mlogloss:1.85420
[36m(train_xgb_ray_tune pid=524079)[0m [254]	train-mlogloss:1.43229	validation-mlogloss:1.46826
[36m(train_xgb_ray_tune pid=524078)[0m [304]	train-mlogloss:1.69462	validation-mlogloss:1.69940
[36m(train_xgb_ray_tune pid=524045)[0m [387]	train-mlogloss:2.02832	validation-mlogloss:2.01576
[36m(train_xgb_ray_tune pid=524080)[0m [237]	train-mlogloss:1.37495	validation-mlogloss:1.43347
[36m(train_xgb_ray_tune pid=524075)[0m [304]	train-mlogloss:1.40903	validation-mlogloss:1.43602
[36m(train_xgb_ray_tune pid=524081)[0m [300]	train-mlogloss:1.65109	validation-mlogloss:1.65249
[36m(train_xgb_ray_tune pid=524076)[0m [297]	train-mlogloss:2.01832	validation-mlogloss:2.00534
[36m(train_xgb_ray_tune pid=524046)[0m [297]	train-mlogloss:1.63602	validation-mlogloss:1.63892
[36m(train_xgb_ray_tune pid=524066)[0m [329]	train-mlogloss:1.63747	validation-mlogloss:1.63629
[36m(train_xgb_ray_tune pid=524065)[0m [308]	train-mlogloss:1.85393	validation-mlogloss:1.85295
[36m(train_xgb_ray_tune pid=524074)[0m [283]	train-mlogloss:2.20475	validation-mlogloss:2.19187
[36m(train_xgb_ray_tune pid=524078)[0m [305]	train-mlogloss:1.69352	validation-mlogloss:1.69833
[36m(train_xgb_ray_tune pid=524077)[0m [219]	train-mlogloss:1.43022	validation-mlogloss:1.48506
[36m(train_xgb_ray_tune pid=524032)[0m [259]	train-mlogloss:1.59877	validation-mlogloss:1.62083
[36m(train_xgb_ray_tune pid=524045)[0m [388]	train-mlogloss:2.02832	validation-mlogloss:2.01576
[36m(train_xgb_ray_tune pid=524046)[0m [298]	train-mlogloss:1.63542	validation-mlogloss:1.63830
[36m(train_xgb_ray_tune pid=524073)[0m [237]	train-mlogloss:1.78771	validation-mlogloss:1.78891
[36m(train_xgb_ray_tune pid=524079)[0m [255]	train-mlogloss:1.43153	validation-mlogloss:1.46760
[36m(train_xgb_ray_tune pid=524081)[0m [301]	train-mlogloss:1.65006	validation-mlogloss:1.65151
[36m(train_xgb_ray_tune pid=524045)[0m [389]	train-mlogloss:2.02824	validation-mlogloss:2.01566
[36m(train_xgb_ray_tune pid=524075)[0m [305]	train-mlogloss:1.40838	validation-mlogloss:1.43540
[36m(train_xgb_ray_tune pid=524081)[0m [302]	train-mlogloss:1.64896	validation-mlogloss:1.65055
[36m(train_xgb_ray_tune pid=524076)[0m [298]	train-mlogloss:2.01689	validation-mlogloss:2.00389
[36m(train_xgb_ray_tune pid=524046)[0m [299]	train-mlogloss:1.63495	validation-mlogloss:1.63785
[36m(train_xgb_ray_tune pid=524066)[0m [330]	train-mlogloss:1.63717	validation-mlogloss:1.63605
[36m(train_xgb_ray_tune pid=524065)[0m [309]	train-mlogloss:1.85258	validation-mlogloss:1.85164
[36m(train_xgb_ray_tune pid=524074)[0m [284]	train-mlogloss:2.20346	validation-mlogloss:2.19054
[36m(train_xgb_ray_tune pid=524078)[0m [306]	train-mlogloss:1.69234	validation-mlogloss:1.69721
[36m(train_xgb_ray_tune pid=524032)[0m [260]	train-mlogloss:1.59744	validation-mlogloss:1.61954
[36m(train_xgb_ray_tune pid=524045)[0m [390]	train-mlogloss:2.02815	validation-mlogloss:2.01555
[36m(train_xgb_ray_tune pid=524080)[0m [238]	train-mlogloss:1.37386	validation-mlogloss:1.43255
[36m(train_xgb_ray_tune pid=524076)[0m [299]	train-mlogloss:2.01549	validation-mlogloss:2.00246
[36m(train_xgb_ray_tune pid=524046)[0m [300]	train-mlogloss:1.63452	validation-mlogloss:1.63746
[36m(train_xgb_ray_tune pid=524073)[0m [238]	train-mlogloss:1.78589	validation-mlogloss:1.78717
[36m(train_xgb_ray_tune pid=524066)[0m [331]	train-mlogloss:1.63677	validation-mlogloss:1.63568
[36m(train_xgb_ray_tune pid=524066)[0m [332]	train-mlogloss:1.63656	validation-mlogloss:1.63549
[36m(train_xgb_ray_tune pid=524065)[0m [310]	train-mlogloss:1.85118	validation-mlogloss:1.85025
[36m(train_xgb_ray_tune pid=524074)[0m [285]	train-mlogloss:2.20213	validation-mlogloss:2.18917
[36m(train_xgb_ray_tune pid=524079)[0m [256]	train-mlogloss:1.43079	validation-mlogloss:1.46686
[36m(train_xgb_ray_tune pid=524077)[0m [220]	train-mlogloss:1.42858	validation-mlogloss:1.48361
[36m(train_xgb_ray_tune pid=524081)[0m [303]	train-mlogloss:1.64799	validation-mlogloss:1.64969
[36m(train_xgb_ray_tune pid=524065)[0m [311]	train-mlogloss:1.84977	validation-mlogloss:1.84890
[36m(train_xgb_ray_tune pid=524077)[0m [221]	train-mlogloss:1.42702	validation-mlogloss:1.48235
[36m(train_xgb_ray_tune pid=524078)[0m [307]	train-mlogloss:1.69121	validation-mlogloss:1.69612
[36m(train_xgb_ray_tune pid=524032)[0m [261]	train-mlogloss:1.59615	validation-mlogloss:1.61827
[36m(train_xgb_ray_tune pid=524045)[0m [391]	train-mlogloss:2.02815	validation-mlogloss:2.01555
[36m(train_xgb_ray_tune pid=524080)[0m [239]	train-mlogloss:1.37267	validation-mlogloss:1.43143
[36m(train_xgb_ray_tune pid=524075)[0m [306]	train-mlogloss:1.40783	validation-mlogloss:1.43494
[36m(train_xgb_ray_tune pid=524076)[0m [300]	train-mlogloss:2.01402	validation-mlogloss:2.00101
[36m(train_xgb_ray_tune pid=524046)[0m [301]	train-mlogloss:1.63411	validation-mlogloss:1.63710
[36m(train_xgb_ray_tune pid=524066)[0m [333]	train-mlogloss:1.63627	validation-mlogloss:1.63522
[36m(train_xgb_ray_tune pid=524065)[0m [312]	train-mlogloss:1.84848	validation-mlogloss:1.84762
[36m(train_xgb_ray_tune pid=524074)[0m [286]	train-mlogloss:2.20085	validation-mlogloss:2.18790
[36m(train_xgb_ray_tune pid=524079)[0m [257]	train-mlogloss:1.42994	validation-mlogloss:1.46606
[36m(train_xgb_ray_tune pid=524078)[0m [308]	train-mlogloss:1.69004	validation-mlogloss:1.69494
[36m(train_xgb_ray_tune pid=524045)[0m [392]	train-mlogloss:2.02815	validation-mlogloss:2.01555
[36m(train_xgb_ray_tune pid=524075)[0m [307]	train-mlogloss:1.40721	validation-mlogloss:1.43434
[36m(train_xgb_ray_tune pid=524081)[0m [304]	train-mlogloss:1.64695	validation-mlogloss:1.64868
[36m(train_xgb_ray_tune pid=524076)[0m [301]	train-mlogloss:2.01251	validation-mlogloss:1.99951
[36m(train_xgb_ray_tune pid=524046)[0m [302]	train-mlogloss:1.63356	validation-mlogloss:1.63656
[36m(train_xgb_ray_tune pid=524073)[0m [239]	train-mlogloss:1.78406	validation-mlogloss:1.78545
[36m(train_xgb_ray_tune pid=524066)[0m [334]	train-mlogloss:1.63602	validation-mlogloss:1.63497
[36m(train_xgb_ray_tune pid=524065)[0m [313]	train-mlogloss:1.84713	validation-mlogloss:1.84631
[36m(train_xgb_ray_tune pid=524074)[0m [287]	train-mlogloss:2.19962	validation-mlogloss:2.18666
[36m(train_xgb_ray_tune pid=524077)[0m [222]	train-mlogloss:1.42554	validation-mlogloss:1.48109
[36m(train_xgb_ray_tune pid=524078)[0m [309]	train-mlogloss:1.68888	validation-mlogloss:1.69389
[36m(train_xgb_ray_tune pid=524032)[0m [262]	train-mlogloss:1.59487	validation-mlogloss:1.61698
[36m(train_xgb_ray_tune pid=524045)[0m [393]	train-mlogloss:2.02807	validation-mlogloss:2.01547
[36m(train_xgb_ray_tune pid=524080)[0m [240]	train-mlogloss:1.37150	validation-mlogloss:1.43036
[36m(train_xgb_ray_tune pid=524075)[0m [308]	train-mlogloss:1.40660	validation-mlogloss:1.43389
[36m(train_xgb_ray_tune pid=524081)[0m [305]	train-mlogloss:1.64591	validation-mlogloss:1.64765
[36m(train_xgb_ray_tune pid=524076)[0m [302]	train-mlogloss:2.01113	validation-mlogloss:1.99815
[36m(train_xgb_ray_tune pid=524046)[0m [303]	train-mlogloss:1.63302	validation-mlogloss:1.63603
[36m(train_xgb_ray_tune pid=524066)[0m [335]	train-mlogloss:1.63576	validation-mlogloss:1.63471
[36m(train_xgb_ray_tune pid=524065)[0m [314]	train-mlogloss:1.84578	validation-mlogloss:1.84492
[36m(train_xgb_ray_tune pid=524079)[0m [258]	train-mlogloss:1.42933	validation-mlogloss:1.46552
[36m(train_xgb_ray_tune pid=524078)[0m [310]	train-mlogloss:1.68777	validation-mlogloss:1.69277
[36m(train_xgb_ray_tune pid=524077)[0m [223]	train-mlogloss:1.42400	validation-mlogloss:1.47964
[36m(train_xgb_ray_tune pid=524076)[0m [303]	train-mlogloss:2.00977	validation-mlogloss:1.99682
[36m(train_xgb_ray_tune pid=524074)[0m [288]	train-mlogloss:2.19838	validation-mlogloss:2.18536
[36m(train_xgb_ray_tune pid=524045)[0m [394]	train-mlogloss:2.02798	validation-mlogloss:2.01536
[36m(train_xgb_ray_tune pid=524076)[0m [304]	train-mlogloss:2.00838	validation-mlogloss:1.99544
[36m(train_xgb_ray_tune pid=524046)[0m [304]	train-mlogloss:1.63264	validation-mlogloss:1.63565
[36m(train_xgb_ray_tune pid=524073)[0m [240]	train-mlogloss:1.78229	validation-mlogloss:1.78373
[36m(train_xgb_ray_tune pid=524066)[0m [336]	train-mlogloss:1.63545	validation-mlogloss:1.63442
[36m(train_xgb_ray_tune pid=524065)[0m [315]	train-mlogloss:1.84444	validation-mlogloss:1.84365
[36m(train_xgb_ray_tune pid=524079)[0m [259]	train-mlogloss:1.42853	validation-mlogloss:1.46487
[36m(train_xgb_ray_tune pid=524078)[0m [311]	train-mlogloss:1.68662	validation-mlogloss:1.69168
[36m(train_xgb_ray_tune pid=524077)[0m [224]	train-mlogloss:1.42255	validation-mlogloss:1.47816
[36m(train_xgb_ray_tune pid=524032)[0m [263]	train-mlogloss:1.59357	validation-mlogloss:1.61569
[36m(train_xgb_ray_tune pid=524080)[0m [241]	train-mlogloss:1.37046	validation-mlogloss:1.42943
[36m(train_xgb_ray_tune pid=524045)[0m [395]	train-mlogloss:2.02798	validation-mlogloss:2.01536
[36m(train_xgb_ray_tune pid=524075)[0m [309]	train-mlogloss:1.40599	validation-mlogloss:1.43360
[36m(train_xgb_ray_tune pid=524081)[0m [306]	train-mlogloss:1.64497	validation-mlogloss:1.64679
[36m(train_xgb_ray_tune pid=524076)[0m [305]	train-mlogloss:2.00703	validation-mlogloss:1.99405
[36m(train_xgb_ray_tune pid=524073)[0m [241]	train-mlogloss:1.78043	validation-mlogloss:1.78202
[36m(train_xgb_ray_tune pid=524066)[0m [337]	train-mlogloss:1.63508	validation-mlogloss:1.63406
[36m(train_xgb_ray_tune pid=524066)[0m [338]	train-mlogloss:1.63483	validation-mlogloss:1.63380
[36m(train_xgb_ray_tune pid=524065)[0m [316]	train-mlogloss:1.84312	validation-mlogloss:1.84240
[36m(train_xgb_ray_tune pid=524074)[0m [289]	train-mlogloss:2.19709	validation-mlogloss:2.18400
[36m(train_xgb_ray_tune pid=524078)[0m [312]	train-mlogloss:1.68548	validation-mlogloss:1.69052
[36m(train_xgb_ray_tune pid=524077)[0m [225]	train-mlogloss:1.42104	validation-mlogloss:1.47678
[36m(train_xgb_ray_tune pid=524046)[0m [305]	train-mlogloss:1.63226	validation-mlogloss:1.63529
[36m(train_xgb_ray_tune pid=524032)[0m [264]	train-mlogloss:1.59244	validation-mlogloss:1.61450
[36m(train_xgb_ray_tune pid=524045)[0m [396]	train-mlogloss:2.02798	validation-mlogloss:2.01536
[36m(train_xgb_ray_tune pid=524080)[0m [242]	train-mlogloss:1.36942	validation-mlogloss:1.42867
[36m(train_xgb_ray_tune pid=524075)[0m [310]	train-mlogloss:1.40537	validation-mlogloss:1.43328
[36m(train_xgb_ray_tune pid=524081)[0m [307]	train-mlogloss:1.64398	validation-mlogloss:1.64590
[36m(train_xgb_ray_tune pid=524076)[0m [306]	train-mlogloss:2.00565	validation-mlogloss:1.99277
[36m(train_xgb_ray_tune pid=524066)[0m [339]	train-mlogloss:1.63453	validation-mlogloss:1.63350
[36m(train_xgb_ray_tune pid=524065)[0m [317]	train-mlogloss:1.84183	validation-mlogloss:1.84106
[36m(train_xgb_ray_tune pid=524074)[0m [290]	train-mlogloss:2.19590	validation-mlogloss:2.18276
[36m(train_xgb_ray_tune pid=524079)[0m [260]	train-mlogloss:1.42777	validation-mlogloss:1.46436
[36m(train_xgb_ray_tune pid=524078)[0m [313]	train-mlogloss:1.68434	validation-mlogloss:1.68936
[36m(train_xgb_ray_tune pid=524077)[0m [226]	train-mlogloss:1.41950	validation-mlogloss:1.47540
[36m(train_xgb_ray_tune pid=524046)[0m [306]	train-mlogloss:1.63175	validation-mlogloss:1.63477

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:09. Total running time: 1min 14s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             70.9399 │
│ time_total_s                 70.9399 │
│ training_iteration                 1 │
│ validation_accuracy          0.40277 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=524045)[0m [397]	train-mlogloss:2.02798	validation-mlogloss:2.01536
[36m(train_xgb_ray_tune pid=524065)[0m [318]	train-mlogloss:1.84050	validation-mlogloss:1.83978

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:09. Total running time: 1min 14s
[36m(train_xgb_ray_tune pid=524032)[0m [265]	train-mlogloss:1.59106	validation-mlogloss:1.61322
[36m(train_xgb_ray_tune pid=524045)[0m [398]	train-mlogloss:2.02789	validation-mlogloss:2.01529
[36m(train_xgb_ray_tune pid=524075)[0m [311]	train-mlogloss:1.40482	validation-mlogloss:1.43274
[36m(train_xgb_ray_tune pid=524081)[0m [308]	train-mlogloss:1.64303	validation-mlogloss:1.64496
[36m(train_xgb_ray_tune pid=524076)[0m [307]	train-mlogloss:2.00422	validation-mlogloss:1.99133
[36m(train_xgb_ray_tune pid=524046)[0m [307]	train-mlogloss:1.63140	validation-mlogloss:1.63439
[36m(train_xgb_ray_tune pid=524073)[0m [242]	train-mlogloss:1.77877	validation-mlogloss:1.78043
[36m(train_xgb_ray_tune pid=524066)[0m [340]	train-mlogloss:1.63433	validation-mlogloss:1.63332
[36m(train_xgb_ray_tune pid=524074)[0m [291]	train-mlogloss:2.19462	validation-mlogloss:2.18148
[36m(train_xgb_ray_tune pid=524079)[0m [261]	train-mlogloss:1.42709	validation-mlogloss:1.46379
[36m(train_xgb_ray_tune pid=524078)[0m [314]	train-mlogloss:1.68322	validation-mlogloss:1.68830
[36m(train_xgb_ray_tune pid=524077)[0m [227]	train-mlogloss:1.41786	validation-mlogloss:1.47404
[36m(train_xgb_ray_tune pid=524066)[0m [341]	train-mlogloss:1.63407	validation-mlogloss:1.63305
[36m(train_xgb_ray_tune pid=524032)[0m [266]	train-mlogloss:1.58970	validation-mlogloss:1.61190
[36m(train_xgb_ray_tune pid=524045)[0m [399]	train-mlogloss:2.02780	validation-mlogloss:2.01523
[36m(train_xgb_ray_tune pid=524080)[0m [243]	train-mlogloss:1.36826	validation-mlogloss:1.42758
[36m(train_xgb_ray_tune pid=524075)[0m [312]	train-mlogloss:1.40428	validation-mlogloss:1.43228
[36m(train_xgb_ray_tune pid=524076)[0m [308]	train-mlogloss:2.00277	validation-mlogloss:1.98990
[36m(train_xgb_ray_tune pid=524046)[0m [308]	train-mlogloss:1.63100	validation-mlogloss:1.63395
[36m(train_xgb_ray_tune pid=524066)[0m [342]	train-mlogloss:1.63384	validation-mlogloss:1.63284
[36m(train_xgb_ray_tune pid=524065)[0m [319]	train-mlogloss:1.83917	validation-mlogloss:1.83849
[36m(train_xgb_ray_tune pid=524079)[0m [262]	train-mlogloss:1.42642	validation-mlogloss:1.46329
[36m(train_xgb_ray_tune pid=524078)[0m [315]	train-mlogloss:1.68218	validation-mlogloss:1.68722
[36m(train_xgb_ray_tune pid=524074)[0m [292]	train-mlogloss:2.19333	validation-mlogloss:2.18018
[36m(train_xgb_ray_tune pid=524077)[0m [228]	train-mlogloss:1.41642	validation-mlogloss:1.47272
[36m(train_xgb_ray_tune pid=524045)[0m [400]	train-mlogloss:2.02780	validation-mlogloss:2.01523
[36m(train_xgb_ray_tune pid=524080)[0m [244]	train-mlogloss:1.36721	validation-mlogloss:1.42664
[36m(train_xgb_ray_tune pid=524075)[0m [313]	train-mlogloss:1.40368	validation-mlogloss:1.43169
[36m(train_xgb_ray_tune pid=524081)[0m [309]	train-mlogloss:1.64204	validation-mlogloss:1.64396
[36m(train_xgb_ray_tune pid=524076)[0m [309]	train-mlogloss:2.00138	validation-mlogloss:1.98842
[36m(train_xgb_ray_tune pid=524046)[0m [309]	train-mlogloss:1.63053	validation-mlogloss:1.63346
[36m(train_xgb_ray_tune pid=524046)[0m [310]	train-mlogloss:1.63004	validation-mlogloss:1.63298
[36m(train_xgb_ray_tune pid=524073)[0m [243]	train-mlogloss:1.77702	validation-mlogloss:1.77872
[36m(train_xgb_ray_tune pid=524066)[0m [343]	train-mlogloss:1.63352	validation-mlogloss:1.63257
[36m(train_xgb_ray_tune pid=524065)[0m [320]	train-mlogloss:1.83783	validation-mlogloss:1.83717
[36m(train_xgb_ray_tune pid=524032)[0m [267]	train-mlogloss:1.58836	validation-mlogloss:1.61063
[36m(train_xgb_ray_tune pid=524045)[0m [401]	train-mlogloss:2.02780	validation-mlogloss:2.01523
[36m(train_xgb_ray_tune pid=524075)[0m [314]	train-mlogloss:1.40298	validation-mlogloss:1.43110
[36m(train_xgb_ray_tune pid=524081)[0m [310]	train-mlogloss:1.64110	validation-mlogloss:1.64308
[36m(train_xgb_ray_tune pid=524076)[0m [310]	train-mlogloss:2.00010	validation-mlogloss:1.98711
[36m(train_xgb_ray_tune pid=524046)[0m [311]	train-mlogloss:1.62964	validation-mlogloss:1.63263
[36m(train_xgb_ray_tune pid=524066)[0m [344]	train-mlogloss:1.63323	validation-mlogloss:1.63230
[36m(train_xgb_ray_tune pid=524066)[0m [345]	train-mlogloss:1.63293	validation-mlogloss:1.63203
[36m(train_xgb_ray_tune pid=524074)[0m [293]	train-mlogloss:2.19211	validation-mlogloss:2.17894
[36m(train_xgb_ray_tune pid=524079)[0m [263]	train-mlogloss:1.42564	validation-mlogloss:1.46247
[36m(train_xgb_ray_tune pid=524078)[0m [316]	train-mlogloss:1.68113	validation-mlogloss:1.68620
[36m(train_xgb_ray_tune pid=524077)[0m [229]	train-mlogloss:1.41500	validation-mlogloss:1.47143
[36m(train_xgb_ray_tune pid=524032)[0m [268]	train-mlogloss:1.58702	validation-mlogloss:1.60931
[36m(train_xgb_ray_tune pid=524045)[0m [402]	train-mlogloss:2.02780	validation-mlogloss:2.01523
[36m(train_xgb_ray_tune pid=524080)[0m [245]	train-mlogloss:1.36623	validation-mlogloss:1.42561
[36m(train_xgb_ray_tune pid=524075)[0m [315]	train-mlogloss:1.40242	validation-mlogloss:1.43062
[36m(train_xgb_ray_tune pid=524075)[0m [316]	train-mlogloss:1.40192	validation-mlogloss:1.43029
[36m(train_xgb_ray_tune pid=524046)[0m [312]	train-mlogloss:1.62926	validation-mlogloss:1.63224
[36m(train_xgb_ray_tune pid=524073)[0m [244]	train-mlogloss:1.77534	validation-mlogloss:1.77700
[36m(train_xgb_ray_tune pid=524066)[0m [346]	train-mlogloss:1.63269	validation-mlogloss:1.63178
[36m(train_xgb_ray_tune pid=524065)[0m [321]	train-mlogloss:1.83658	validation-mlogloss:1.83594
[36m(train_xgb_ray_tune pid=524079)[0m [264]	train-mlogloss:1.42500	validation-mlogloss:1.46187
[36m(train_xgb_ray_tune pid=524078)[0m [317]	train-mlogloss:1.68005	validation-mlogloss:1.68516
[36m(train_xgb_ray_tune pid=524077)[0m [230]	train-mlogloss:1.41358	validation-mlogloss:1.47024
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[36m(train_xgb_ray_tune pid=524046)[0m [416]	train-mlogloss:1.60020	validation-mlogloss:1.60448
[36m(train_xgb_ray_tune pid=524046)[0m [417]	train-mlogloss:1.60005	validation-mlogloss:1.60435
[36m(train_xgb_ray_tune pid=524073)[0m [307]	train-mlogloss:1.67934	validation-mlogloss:1.68493
[36m(train_xgb_ray_tune pid=524066)[0m [429]	train-mlogloss:1.62126	validation-mlogloss:1.62152
[36m(train_xgb_ray_tune pid=524074)[0m [354]	train-mlogloss:2.12190	validation-mlogloss:2.10708
[36m(train_xgb_ray_tune pid=524079)[0m [338]	train-mlogloss:1.39349	validation-mlogloss:1.43360
[36m(train_xgb_ray_tune pid=524078)[0m [398]	train-mlogloss:1.60458	validation-mlogloss:1.61397
[36m(train_xgb_ray_tune pid=524077)[0m [291]	train-mlogloss:1.34429	validation-mlogloss:1.41083
[36m(train_xgb_ray_tune pid=524075)[0m [411]	train-mlogloss:1.36987	validation-mlogloss:1.40455
[36m(train_xgb_ray_tune pid=524032)[0m [324]	train-mlogloss:1.52644	validation-mlogloss:1.55025
[36m(train_xgb_ray_tune pid=524045)[0m [488]	train-mlogloss:2.02534	validation-mlogloss:2.01268
[36m(train_xgb_ray_tune pid=524080)[0m [314]	train-mlogloss:1.31101	validation-mlogloss:1.38148
[36m(train_xgb_ray_tune pid=524075)[0m [412]	train-mlogloss:1.36971	validation-mlogloss:1.40442
[36m(train_xgb_ray_tune pid=524046)[0m [418]	train-mlogloss:1.59989	validation-mlogloss:1.60424
[36m(train_xgb_ray_tune pid=524073)[0m [308]	train-mlogloss:1.67810	validation-mlogloss:1.68373
[36m(train_xgb_ray_tune pid=524066)[0m [430]	train-mlogloss:1.62117	validation-mlogloss:1.62149
[36m(train_xgb_ray_tune pid=524078)[0m [399]	train-mlogloss:1.60378	validation-mlogloss:1.61319
[36m(train_xgb_ray_tune pid=524077)[0m [292]	train-mlogloss:1.34334	validation-mlogloss:1.41008
[36m(train_xgb_ray_tune pid=524081)[0m [380]	train-mlogloss:1.58470	validation-mlogloss:1.59059
[36m(train_xgb_ray_tune pid=524046)[0m [419]	train-mlogloss:1.59973	validation-mlogloss:1.60405
[36m(train_xgb_ray_tune pid=524079)[0m [339]	train-mlogloss:1.39317	validation-mlogloss:1.43324
[36m(train_xgb_ray_tune pid=524045)[0m [489]	train-mlogloss:2.02534	validation-mlogloss:2.01268
[36m(train_xgb_ray_tune pid=524080)[0m [315]	train-mlogloss:1.31044	validation-mlogloss:1.38105
[36m(train_xgb_ray_tune pid=524075)[0m [413]	train-mlogloss:1.36947	validation-mlogloss:1.40427
[36m(train_xgb_ray_tune pid=524076)[0m [385]	train-mlogloss:1.90834	validation-mlogloss:1.89557
[36m(train_xgb_ray_tune pid=524046)[0m [420]	train-mlogloss:1.59952	validation-mlogloss:1.60379
[36m(train_xgb_ray_tune pid=524073)[0m [309]	train-mlogloss:1.67688	validation-mlogloss:1.68250
[36m(train_xgb_ray_tune pid=524066)[0m [431]	train-mlogloss:1.62113	validation-mlogloss:1.62148
[36m(train_xgb_ray_tune pid=524074)[0m [355]	train-mlogloss:2.12080	validation-mlogloss:2.10594
[36m(train_xgb_ray_tune pid=524078)[0m [400]	train-mlogloss:1.60301	validation-mlogloss:1.61245
[36m(train_xgb_ray_tune pid=524077)[0m [293]	train-mlogloss:1.34246	validation-mlogloss:1.40940
[36m(train_xgb_ray_tune pid=524032)[0m [325]	train-mlogloss:1.52545	validation-mlogloss:1.54928
[36m(train_xgb_ray_tune pid=524075)[0m [414]	train-mlogloss:1.36935	validation-mlogloss:1.40418
[36m(train_xgb_ray_tune pid=524045)[0m [490]	train-mlogloss:2.02534	validation-mlogloss:2.01268
[36m(train_xgb_ray_tune pid=524080)[0m [316]	train-mlogloss:1.30988	validation-mlogloss:1.38062
[36m(train_xgb_ray_tune pid=524079)[0m [340]	train-mlogloss:1.39296	validation-mlogloss:1.43304
[36m(train_xgb_ray_tune pid=524045)[0m [491]	train-mlogloss:2.02534	validation-mlogloss:2.01268
[36m(train_xgb_ray_tune pid=524080)[0m [317]	train-mlogloss:1.30936	validation-mlogloss:1.38022
[36m(train_xgb_ray_tune pid=524075)[0m [415]	train-mlogloss:1.36911	validation-mlogloss:1.40395
[36m(train_xgb_ray_tune pid=524081)[0m [381]	train-mlogloss:1.58404	validation-mlogloss:1.59011
[36m(train_xgb_ray_tune pid=524076)[0m [386]	train-mlogloss:1.90720	validation-mlogloss:1.89446
[36m(train_xgb_ray_tune pid=524046)[0m [421]	train-mlogloss:1.59924	validation-mlogloss:1.60348
[36m(train_xgb_ray_tune pid=524046)[0m [422]	train-mlogloss:1.59918	validation-mlogloss:1.60343
[36m(train_xgb_ray_tune pid=524073)[0m [310]	train-mlogloss:1.67557	validation-mlogloss:1.68126
[36m(train_xgb_ray_tune pid=524066)[0m [432]	train-mlogloss:1.62108	validation-mlogloss:1.62144
[36m(train_xgb_ray_tune pid=524074)[0m [356]	train-mlogloss:2.11972	validation-mlogloss:2.10486
[36m(train_xgb_ray_tune pid=524078)[0m [401]	train-mlogloss:1.60222	validation-mlogloss:1.61167
[36m(train_xgb_ray_tune pid=524077)[0m [294]	train-mlogloss:1.34146	validation-mlogloss:1.40868
[36m(train_xgb_ray_tune pid=524032)[0m [326]	train-mlogloss:1.52452	validation-mlogloss:1.54845
[36m(train_xgb_ray_tune pid=524045)[0m [492]	train-mlogloss:2.02534	validation-mlogloss:2.01268
[36m(train_xgb_ray_tune pid=524080)[0m [318]	train-mlogloss:1.30878	validation-mlogloss:1.37980
[36m(train_xgb_ray_tune pid=524075)[0m [416]	train-mlogloss:1.36894	validation-mlogloss:1.40385
[36m(train_xgb_ray_tune pid=524075)[0m [417]	train-mlogloss:1.36879	validation-mlogloss:1.40373
[36m(train_xgb_ray_tune pid=524081)[0m [382]	train-mlogloss:1.58346	validation-mlogloss:1.58954
[36m(train_xgb_ray_tune pid=524046)[0m [423]	train-mlogloss:1.59908	validation-mlogloss:1.60331
[36m(train_xgb_ray_tune pid=524073)[0m [311]	train-mlogloss:1.67437	validation-mlogloss:1.68017
[36m(train_xgb_ray_tune pid=524066)[0m [433]	train-mlogloss:1.62099	validation-mlogloss:1.62135
[36m(train_xgb_ray_tune pid=524079)[0m [341]	train-mlogloss:1.39268	validation-mlogloss:1.43277
[36m(train_xgb_ray_tune pid=524078)[0m [402]	train-mlogloss:1.60144	validation-mlogloss:1.61093
[36m(train_xgb_ray_tune pid=524077)[0m [295]	train-mlogloss:1.34061	validation-mlogloss:1.40781
[36m(train_xgb_ray_tune pid=524032)[0m [327]	train-mlogloss:1.52367	validation-mlogloss:1.54764
[36m(train_xgb_ray_tune pid=524065)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 2x across cluster][0m
[36m(train_xgb_ray_tune pid=524065)[0m   _log_deprecation_warning([32m [repeated 2x across cluster][0m
[36m(train_xgb_ray_tune pid=524045)[0m [493]	train-mlogloss:2.02515	validation-mlogloss:2.01246
[36m(train_xgb_ray_tune pid=524080)[0m [319]	train-mlogloss:1.30833	validation-mlogloss:1.37944
[36m(train_xgb_ray_tune pid=524075)[0m [418]	train-mlogloss:1.36859	validation-mlogloss:1.40356
[36m(train_xgb_ray_tune pid=524076)[0m [387]	train-mlogloss:1.90606	validation-mlogloss:1.89330
[36m(train_xgb_ray_tune pid=524046)[0m [424]	train-mlogloss:1.59887	validation-mlogloss:1.60316
[36m(train_xgb_ray_tune pid=524046)[0m [425]	train-mlogloss:1.59883	validation-mlogloss:1.60312
[36m(train_xgb_ray_tune pid=524073)[0m [312]	train-mlogloss:1.67310	validation-mlogloss:1.67894
[36m(train_xgb_ray_tune pid=524066)[0m [434]	train-mlogloss:1.62091	validation-mlogloss:1.62127
[36m(train_xgb_ray_tune pid=524074)[0m [357]	train-mlogloss:2.11863	validation-mlogloss:2.10373
[36m(train_xgb_ray_tune pid=524079)[0m [342]	train-mlogloss:1.39255	validation-mlogloss:1.43264
[36m(train_xgb_ray_tune pid=524078)[0m [403]	train-mlogloss:1.60066	validation-mlogloss:1.61018
[36m(train_xgb_ray_tune pid=524078)[0m [404]	train-mlogloss:1.59993	validation-mlogloss:1.60952
[36m(train_xgb_ray_tune pid=524077)[0m [296]	train-mlogloss:1.33985	validation-mlogloss:1.40714
[36m(train_xgb_ray_tune pid=524081)[0m [383]	train-mlogloss:1.58288	validation-mlogloss:1.58905
[36m(train_xgb_ray_tune pid=524066)[0m [435]	train-mlogloss:1.62081	validation-mlogloss:1.62118
[36m(train_xgb_ray_tune pid=524045)[0m [494]	train-mlogloss:2.02515	validation-mlogloss:2.01246
[36m(train_xgb_ray_tune pid=524080)[0m [320]	train-mlogloss:1.30760	validation-mlogloss:1.37895
[36m(train_xgb_ray_tune pid=524075)[0m [419]	train-mlogloss:1.36840	validation-mlogloss:1.40334
[36m(train_xgb_ray_tune pid=524075)[0m [420]	train-mlogloss:1.36822	validation-mlogloss:1.40316
[36m(train_xgb_ray_tune pid=524076)[0m [388]	train-mlogloss:1.90507	validation-mlogloss:1.89230
[36m(train_xgb_ray_tune pid=524046)[0m [426]	train-mlogloss:1.59877	validation-mlogloss:1.60306
[36m(train_xgb_ray_tune pid=524073)[0m [313]	train-mlogloss:1.67185	validation-mlogloss:1.67767
[36m(train_xgb_ray_tune pid=524074)[0m [358]	train-mlogloss:2.11759	validation-mlogloss:2.10269
[36m(train_xgb_ray_tune pid=524079)[0m [343]	train-mlogloss:1.39226	validation-mlogloss:1.43236
[36m(train_xgb_ray_tune pid=524078)[0m [405]	train-mlogloss:1.59914	validation-mlogloss:1.60880
[36m(train_xgb_ray_tune pid=524077)[0m [297]	train-mlogloss:1.33894	validation-mlogloss:1.40635
[36m(train_xgb_ray_tune pid=524045)[0m [495]	train-mlogloss:2.02488	validation-mlogloss:2.01220
[36m(train_xgb_ray_tune pid=524046)[0m [427]	train-mlogloss:1.59853	validation-mlogloss:1.60280
[36m(train_xgb_ray_tune pid=524066)[0m [436]	train-mlogloss:1.62077	validation-mlogloss:1.62116
[36m(train_xgb_ray_tune pid=524077)[0m [298]	train-mlogloss:1.33816	validation-mlogloss:1.40562
[36m(train_xgb_ray_tune pid=524032)[0m [328]	train-mlogloss:1.52282	validation-mlogloss:1.54680

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:21. Total running time: 1min 25s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             82.5156 │
│ time_total_s                 82.5156 │
│ training_iteration                 1 │
│ validation_accuracy          0.47826 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=524045)[0m [496]	train-mlogloss:2.02488	validation-mlogloss:2.01220
[36m(train_xgb_ray_tune pid=524080)[0m [321]	train-mlogloss:1.30695	validation-mlogloss:1.37844
[36m(train_xgb_ray_tune pid=524075)[0m [421]	train-mlogloss:1.36799	validation-mlogloss:1.40295
[36m(train_xgb_ray_tune pid=524081)[0m [384]	train-mlogloss:1.58228	validation-mlogloss:1.58858
[36m(train_xgb_ray_tune pid=524076)[0m [389]	train-mlogloss:1.90406	validation-mlogloss:1.89133
[36m(train_xgb_ray_tune pid=524046)[0m [428]	train-mlogloss:1.59843	validation-mlogloss:1.60270
[36m(train_xgb_ray_tune pid=524073)[0m [314]	train-mlogloss:1.67064	validation-mlogloss:1.67644
[36m(train_xgb_ray_tune pid=524066)[0m [437]	train-mlogloss:1.62068	validation-mlogloss:1.62110
[36m(train_xgb_ray_tune pid=524079)[0m [344]	train-mlogloss:1.39212	validation-mlogloss:1.43221
[36m(train_xgb_ray_tune pid=524078)[0m [406]	train-mlogloss:1.59834	validation-mlogloss:1.60804
[36m(train_xgb_ray_tune pid=524077)[0m [299]	train-mlogloss:1.33730	validation-mlogloss:1.40489

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:21. Total running time: 1min 25s
[36m(train_xgb_ray_tune pid=524032)[0m [329]	train-mlogloss:1.52188	validation-mlogloss:1.54594
[36m(train_xgb_ray_tune pid=524045)[0m [497]	train-mlogloss:2.02488	validation-mlogloss:2.01220
[36m(train_xgb_ray_tune pid=524080)[0m [322]	train-mlogloss:1.30644	validation-mlogloss:1.37811
[36m(train_xgb_ray_tune pid=524080)[0m [323]	train-mlogloss:1.30592	validation-mlogloss:1.37775
[36m(train_xgb_ray_tune pid=524075)[0m [422]	train-mlogloss:1.36785	validation-mlogloss:1.40279
[36m(train_xgb_ray_tune pid=524081)[0m [385]	train-mlogloss:1.58170	validation-mlogloss:1.58802
[36m(train_xgb_ray_tune pid=524046)[0m [429]	train-mlogloss:1.59838	validation-mlogloss:1.60265
[36m(train_xgb_ray_tune pid=524046)[0m [430]	train-mlogloss:1.59818	validation-mlogloss:1.60247
[36m(train_xgb_ray_tune pid=524073)[0m [315]	train-mlogloss:1.66931	validation-mlogloss:1.67511
[36m(train_xgb_ray_tune pid=524066)[0m [438]	train-mlogloss:1.62054	validation-mlogloss:1.62096
[36m(train_xgb_ray_tune pid=524074)[0m [359]	train-mlogloss:2.11657	validation-mlogloss:2.10167
[36m(train_xgb_ray_tune pid=524079)[0m [345]	train-mlogloss:1.39197	validation-mlogloss:1.43211
[36m(train_xgb_ray_tune pid=524078)[0m [407]	train-mlogloss:1.59759	validation-mlogloss:1.60730
[36m(train_xgb_ray_tune pid=524075)[0m [423]	train-mlogloss:1.36753	validation-mlogloss:1.40259
[36m(train_xgb_ray_tune pid=524077)[0m [300]	train-mlogloss:1.33648	validation-mlogloss:1.40425
[36m(train_xgb_ray_tune pid=524045)[0m [498]	train-mlogloss:2.02488	validation-mlogloss:2.01220
[36m(train_xgb_ray_tune pid=524045)[0m [499]	train-mlogloss:2.02488	validation-mlogloss:2.01220
[36m(train_xgb_ray_tune pid=524080)[0m [324]	train-mlogloss:1.30543	validation-mlogloss:1.37747
[36m(train_xgb_ray_tune pid=524075)[0m [424]	train-mlogloss:1.36733	validation-mlogloss:1.40243
[36m(train_xgb_ray_tune pid=524081)[0m [386]	train-mlogloss:1.58110	validation-mlogloss:1.58753
[36m(train_xgb_ray_tune pid=524076)[0m [390]	train-mlogloss:1.90293	validation-mlogloss:1.89026
[36m(train_xgb_ray_tune pid=524046)[0m [431]	train-mlogloss:1.59808	validation-mlogloss:1.60238
[36m(train_xgb_ray_tune pid=524073)[0m [316]	train-mlogloss:1.66807	validation-mlogloss:1.67387
[36m(train_xgb_ray_tune pid=524066)[0m [439]	train-mlogloss:1.62050	validation-mlogloss:1.62093
[36m(train_xgb_ray_tune pid=524074)[0m [360]	train-mlogloss:2.11551	validation-mlogloss:2.10056
[36m(train_xgb_ray_tune pid=524079)[0m [346]	train-mlogloss:1.39174	validation-mlogloss:1.43197
[36m(train_xgb_ray_tune pid=524078)[0m [408]	train-mlogloss:1.59679	validation-mlogloss:1.60661
[36m(train_xgb_ray_tune pid=524077)[0m [301]	train-mlogloss:1.33566	validation-mlogloss:1.40364
[36m(train_xgb_ray_tune pid=524032)[0m [330]	train-mlogloss:1.52095	validation-mlogloss:1.54497
[36m(train_xgb_ray_tune pid=524045)[0m [500]	train-mlogloss:2.02488	validation-mlogloss:2.01220
[36m(train_xgb_ray_tune pid=524045)[0m [501]	train-mlogloss:2.02488	validation-mlogloss:2.01220
[36m(train_xgb_ray_tune pid=524080)[0m [325]	train-mlogloss:1.30490	validation-mlogloss:1.37709
[36m(train_xgb_ray_tune pid=524075)[0m [425]	train-mlogloss:1.36722	validation-mlogloss:1.40238
[36m(train_xgb_ray_tune pid=524075)[0m [426]	train-mlogloss:1.36704	validation-mlogloss:1.40230
[36m(train_xgb_ray_tune pid=524076)[0m [391]	train-mlogloss:1.90182	validation-mlogloss:1.88918
[36m(train_xgb_ray_tune pid=524046)[0m [432]	train-mlogloss:1.59789	validation-mlogloss:1.60222
[36m(train_xgb_ray_tune pid=524046)[0m [433]	train-mlogloss:1.59773	validation-mlogloss:1.60207
[36m(train_xgb_ray_tune pid=524073)[0m [317]	train-mlogloss:1.66686	validation-mlogloss:1.67273
[36m(train_xgb_ray_tune pid=524066)[0m [440]	train-mlogloss:1.62038	validation-mlogloss:1.62082
[36m(train_xgb_ray_tune pid=524074)[0m [361]	train-mlogloss:2.11442	validation-mlogloss:2.09949
[36m(train_xgb_ray_tune pid=524079)[0m [347]	train-mlogloss:1.39139	validation-mlogloss:1.43166
[36m(train_xgb_ray_tune pid=524078)[0m [409]	train-mlogloss:1.59609	validation-mlogloss:1.60596
[36m(train_xgb_ray_tune pid=524077)[0m [302]	train-mlogloss:1.33479	validation-mlogloss:1.40293
[36m(train_xgb_ray_tune pid=524032)[0m [331]	train-mlogloss:1.52004	validation-mlogloss:1.54411
[36m(train_xgb_ray_tune pid=524045)[0m [502]	train-mlogloss:2.02488	validation-mlogloss:2.01220
[36m(train_xgb_ray_tune pid=524080)[0m [326]	train-mlogloss:1.30441	validation-mlogloss:1.37675
[36m(train_xgb_ray_tune pid=524075)[0m [427]	train-mlogloss:1.36693	validation-mlogloss:1.40221
[36m(train_xgb_ray_tune pid=524081)[0m [387]	train-mlogloss:1.58047	validation-mlogloss:1.58693
[36m(train_xgb_ray_tune pid=524076)[0m [392]	train-mlogloss:1.90070	validation-mlogloss:1.88809
[36m(train_xgb_ray_tune pid=524046)[0m [434]	train-mlogloss:1.59763	validation-mlogloss:1.60202
[36m(train_xgb_ray_tune pid=524073)[0m [318]	train-mlogloss:1.66563	validation-mlogloss:1.67155
[36m(train_xgb_ray_tune pid=524066)[0m [441]	train-mlogloss:1.62038	validation-mlogloss:1.62082
[36m(train_xgb_ray_tune pid=524079)[0m [348]	train-mlogloss:1.39117	validation-mlogloss:1.43149
[36m(train_xgb_ray_tune pid=524078)[0m [410]	train-mlogloss:1.59540	validation-mlogloss:1.60526
[36m(train_xgb_ray_tune pid=524077)[0m [303]	train-mlogloss:1.33392	validation-mlogloss:1.40231
[36m(train_xgb_ray_tune pid=524045)[0m [503]	train-mlogloss:2.02488	validation-mlogloss:2.01220
[36m(train_xgb_ray_tune pid=524078)[0m [411]	train-mlogloss:1.59466	validation-mlogloss:1.60454
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[36m(train_xgb_ray_tune pid=524080)[0m [358]	train-mlogloss:1.29054	validation-mlogloss:1.36651
[36m(train_xgb_ray_tune pid=524075)[0m [464]	train-mlogloss:1.36184	validation-mlogloss:1.39790
[36m(train_xgb_ray_tune pid=524075)[0m [465]	train-mlogloss:1.36174	validation-mlogloss:1.39780
[36m(train_xgb_ray_tune pid=524081)[0m [406]	train-mlogloss:1.56986	validation-mlogloss:1.57728
[36m(train_xgb_ray_tune pid=524046)[0m [474]	train-mlogloss:1.59451	validation-mlogloss:1.59913
[36m(train_xgb_ray_tune pid=524073)[0m [343]	train-mlogloss:1.63699	validation-mlogloss:1.64427
[36m(train_xgb_ray_tune pid=524066)[0m [467]	train-mlogloss:1.61904	validation-mlogloss:1.61974
[36m(train_xgb_ray_tune pid=524078)[0m [439]	train-mlogloss:1.57502	validation-mlogloss:1.58648
[36m(train_xgb_ray_tune pid=524077)[0m [328]	train-mlogloss:1.31475	validation-mlogloss:1.38745
[36m(train_xgb_ray_tune pid=524032)[0m [348]	train-mlogloss:1.50574	validation-mlogloss:1.53056
[36m(train_xgb_ray_tune pid=524045)[0m [545]	train-mlogloss:2.02462	validation-mlogloss:2.01191
[36m(train_xgb_ray_tune pid=524045)[0m [546]	train-mlogloss:2.02454	validation-mlogloss:2.01186
[36m(train_xgb_ray_tune pid=524080)[0m [359]	train-mlogloss:1.29020	validation-mlogloss:1.36631
[36m(train_xgb_ray_tune pid=524075)[0m [466]	train-mlogloss:1.36160	validation-mlogloss:1.39769
[36m(train_xgb_ray_tune pid=524081)[0m [407]	train-mlogloss:1.56940	validation-mlogloss:1.57689
[36m(train_xgb_ray_tune pid=524076)[0m [410]	train-mlogloss:1.88180	validation-mlogloss:1.86944
[36m(train_xgb_ray_tune pid=524046)[0m [475]	train-mlogloss:1.59446	validation-mlogloss:1.59906
[36m(train_xgb_ray_tune pid=524046)[0m [476]	train-mlogloss:1.59431	validation-mlogloss:1.59891
[36m(train_xgb_ray_tune pid=524073)[0m [344]	train-mlogloss:1.63595	validation-mlogloss:1.64335
[36m(train_xgb_ray_tune pid=524066)[0m [468]	train-mlogloss:1.61904	validation-mlogloss:1.61974
[36m(train_xgb_ray_tune pid=524074)[0m [379]	train-mlogloss:2.09571	validation-mlogloss:2.08030
[36m(train_xgb_ray_tune pid=524079)[0m [372]	train-mlogloss:1.38717	validation-mlogloss:1.42813
[36m(train_xgb_ray_tune pid=524078)[0m [440]	train-mlogloss:1.57436	validation-mlogloss:1.58587
[36m(train_xgb_ray_tune pid=524078)[0m [441]	train-mlogloss:1.57373	validation-mlogloss:1.58526
[36m(train_xgb_ray_tune pid=524077)[0m [329]	train-mlogloss:1.31392	validation-mlogloss:1.38692
[36m(train_xgb_ray_tune pid=524080)[0m [360]	train-mlogloss:1.28978	validation-mlogloss:1.36591
[36m(train_xgb_ray_tune pid=524032)[0m [349]	train-mlogloss:1.50506	validation-mlogloss:1.52981
[36m(train_xgb_ray_tune pid=524045)[0m [547]	train-mlogloss:2.02454	validation-mlogloss:2.01186
[36m(train_xgb_ray_tune pid=524045)[0m [548]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524080)[0m [361]	train-mlogloss:1.28936	validation-mlogloss:1.36563
[36m(train_xgb_ray_tune pid=524075)[0m [467]	train-mlogloss:1.36154	validation-mlogloss:1.39763
[36m(train_xgb_ray_tune pid=524075)[0m [468]	train-mlogloss:1.36137	validation-mlogloss:1.39746
[36m(train_xgb_ray_tune pid=524076)[0m [411]	train-mlogloss:1.88077	validation-mlogloss:1.86843
[36m(train_xgb_ray_tune pid=524046)[0m [477]	train-mlogloss:1.59427	validation-mlogloss:1.59888
[36m(train_xgb_ray_tune pid=524046)[0m [478]	train-mlogloss:1.59422	validation-mlogloss:1.59886
[36m(train_xgb_ray_tune pid=524073)[0m [345]	train-mlogloss:1.63494	validation-mlogloss:1.64231
[36m(train_xgb_ray_tune pid=524066)[0m [469]	train-mlogloss:1.61904	validation-mlogloss:1.61974
[36m(train_xgb_ray_tune pid=524074)[0m [380]	train-mlogloss:2.09462	validation-mlogloss:2.07920
[36m(train_xgb_ray_tune pid=524079)[0m [373]	train-mlogloss:1.38699	validation-mlogloss:1.42793
[36m(train_xgb_ray_tune pid=524078)[0m [442]	train-mlogloss:1.57310	validation-mlogloss:1.58468
[36m(train_xgb_ray_tune pid=524077)[0m [330]	train-mlogloss:1.31317	validation-mlogloss:1.38637
[36m(train_xgb_ray_tune pid=524045)[0m [549]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524080)[0m [362]	train-mlogloss:1.28896	validation-mlogloss:1.36531
[36m(train_xgb_ray_tune pid=524075)[0m [469]	train-mlogloss:1.36127	validation-mlogloss:1.39743
[36m(train_xgb_ray_tune pid=524081)[0m [408]	train-mlogloss:1.56893	validation-mlogloss:1.57647
[36m(train_xgb_ray_tune pid=524076)[0m [412]	train-mlogloss:1.87978	validation-mlogloss:1.86744
[36m(train_xgb_ray_tune pid=524046)[0m [479]	train-mlogloss:1.59418	validation-mlogloss:1.59886
[36m(train_xgb_ray_tune pid=524073)[0m [346]	train-mlogloss:1.63377	validation-mlogloss:1.64116
[36m(train_xgb_ray_tune pid=524066)[0m [470]	train-mlogloss:1.61903	validation-mlogloss:1.61974
[36m(train_xgb_ray_tune pid=524079)[0m [374]	train-mlogloss:1.38689	validation-mlogloss:1.42783
[36m(train_xgb_ray_tune pid=524079)[0m [375]	train-mlogloss:1.38671	validation-mlogloss:1.42769
[36m(train_xgb_ray_tune pid=524078)[0m [443]	train-mlogloss:1.57243	validation-mlogloss:1.58402
[36m(train_xgb_ray_tune pid=524077)[0m [331]	train-mlogloss:1.31254	validation-mlogloss:1.38581
[36m(train_xgb_ray_tune pid=524045)[0m [550]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524032)[0m [350]	train-mlogloss:1.50439	validation-mlogloss:1.52910
[36m(train_xgb_ray_tune pid=524045)[0m [551]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524080)[0m [363]	train-mlogloss:1.28866	validation-mlogloss:1.36504
[36m(train_xgb_ray_tune pid=524075)[0m [470]	train-mlogloss:1.36109	validation-mlogloss:1.39733
[36m(train_xgb_ray_tune pid=524075)[0m [471]	train-mlogloss:1.36082	validation-mlogloss:1.39711
[36m(train_xgb_ray_tune pid=524081)[0m [409]	train-mlogloss:1.56829	validation-mlogloss:1.57586
[36m(train_xgb_ray_tune pid=524046)[0m [480]	train-mlogloss:1.59402	validation-mlogloss:1.59872
[36m(train_xgb_ray_tune pid=524046)[0m [481]	train-mlogloss:1.59398	validation-mlogloss:1.59868
[36m(train_xgb_ray_tune pid=524073)[0m [347]	train-mlogloss:1.63275	validation-mlogloss:1.64018
[36m(train_xgb_ray_tune pid=524066)[0m [471]	train-mlogloss:1.61899	validation-mlogloss:1.61972
[36m(train_xgb_ray_tune pid=524074)[0m [381]	train-mlogloss:2.09360	validation-mlogloss:2.07813
[36m(train_xgb_ray_tune pid=524079)[0m [376]	train-mlogloss:1.38659	validation-mlogloss:1.42757
[36m(train_xgb_ray_tune pid=524078)[0m [444]	train-mlogloss:1.57186	validation-mlogloss:1.58349
[36m(train_xgb_ray_tune pid=524077)[0m [332]	train-mlogloss:1.31178	validation-mlogloss:1.38540
[36m(train_xgb_ray_tune pid=524080)[0m [364]	train-mlogloss:1.28822	validation-mlogloss:1.36480
[36m(train_xgb_ray_tune pid=524032)[0m [351]	train-mlogloss:1.50359	validation-mlogloss:1.52841
[36m(train_xgb_ray_tune pid=524045)[0m [552]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524045)[0m [553]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524080)[0m [365]	train-mlogloss:1.28780	validation-mlogloss:1.36446
[36m(train_xgb_ray_tune pid=524075)[0m [472]	train-mlogloss:1.36069	validation-mlogloss:1.39701
[36m(train_xgb_ray_tune pid=524081)[0m [410]	train-mlogloss:1.56781	validation-mlogloss:1.57548
[36m(train_xgb_ray_tune pid=524076)[0m [413]	train-mlogloss:1.87879	validation-mlogloss:1.86642
[36m(train_xgb_ray_tune pid=524046)[0m [482]	train-mlogloss:1.59393	validation-mlogloss:1.59865
[36m(train_xgb_ray_tune pid=524046)[0m [483]	train-mlogloss:1.59383	validation-mlogloss:1.59857
[36m(train_xgb_ray_tune pid=524073)[0m [348]	train-mlogloss:1.63169	validation-mlogloss:1.63925
[36m(train_xgb_ray_tune pid=524066)[0m [472]	train-mlogloss:1.61887	validation-mlogloss:1.61959
[36m(train_xgb_ray_tune pid=524074)[0m [382]	train-mlogloss:2.09253	validation-mlogloss:2.07709
[36m(train_xgb_ray_tune pid=524079)[0m [377]	train-mlogloss:1.38634	validation-mlogloss:1.42732
[36m(train_xgb_ray_tune pid=524079)[0m [378]	train-mlogloss:1.38612	validation-mlogloss:1.42712
[36m(train_xgb_ray_tune pid=524078)[0m [445]	train-mlogloss:1.57119	validation-mlogloss:1.58287
[36m(train_xgb_ray_tune pid=524045)[0m [554]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524045)[0m [555]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524080)[0m [366]	train-mlogloss:1.28741	validation-mlogloss:1.36411
[36m(train_xgb_ray_tune pid=524075)[0m [473]	train-mlogloss:1.36055	validation-mlogloss:1.39686
[36m(train_xgb_ray_tune pid=524075)[0m [474]	train-mlogloss:1.36051	validation-mlogloss:1.39682
[36m(train_xgb_ray_tune pid=524076)[0m [414]	train-mlogloss:1.87782	validation-mlogloss:1.86546
[36m(train_xgb_ray_tune pid=524046)[0m [484]	train-mlogloss:1.59373	validation-mlogloss:1.59848
[36m(train_xgb_ray_tune pid=524073)[0m [349]	train-mlogloss:1.63067	validation-mlogloss:1.63827
[36m(train_xgb_ray_tune pid=524066)[0m [473]	train-mlogloss:1.61887	validation-mlogloss:1.61959
[36m(train_xgb_ray_tune pid=524079)[0m [379]	train-mlogloss:1.38597	validation-mlogloss:1.42695
[36m(train_xgb_ray_tune pid=524078)[0m [446]	train-mlogloss:1.57053	validation-mlogloss:1.58231
[36m(train_xgb_ray_tune pid=524077)[0m [333]	train-mlogloss:1.31119	validation-mlogloss:1.38488
[36m(train_xgb_ray_tune pid=524078)[0m [447]	train-mlogloss:1.56985	validation-mlogloss:1.58170
[36m(train_xgb_ray_tune pid=524079)[0m [380]	train-mlogloss:1.38576	validation-mlogloss:1.42678
[36m(train_xgb_ray_tune pid=524066)[0m [474]	train-mlogloss:1.61887	validation-mlogloss:1.61959
[36m(train_xgb_ray_tune pid=524032)[0m [352]	train-mlogloss:1.50268	validation-mlogloss:1.52748
[36m(train_xgb_ray_tune pid=524081)[0m [411]	train-mlogloss:1.56729	validation-mlogloss:1.57499
[36m(train_xgb_ray_tune pid=524046)[0m [485]	train-mlogloss:1.59368	validation-mlogloss:1.59845
[36m(train_xgb_ray_tune pid=524080)[0m [367]	train-mlogloss:1.28709	validation-mlogloss:1.36395
[36m(train_xgb_ray_tune pid=524074)[0m [383]	train-mlogloss:2.09154	validation-mlogloss:2.07600
[36m(train_xgb_ray_tune pid=524045)[0m [556]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524045)[0m [557]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524080)[0m [368]	train-mlogloss:1.28672	validation-mlogloss:1.36362
[36m(train_xgb_ray_tune pid=524075)[0m [475]	train-mlogloss:1.36042	validation-mlogloss:1.39675
[36m(train_xgb_ray_tune pid=524075)[0m [476]	train-mlogloss:1.36035	validation-mlogloss:1.39672
[36m(train_xgb_ray_tune pid=524076)[0m [415]	train-mlogloss:1.87677	validation-mlogloss:1.86443
[36m(train_xgb_ray_tune pid=524046)[0m [486]	train-mlogloss:1.59364	validation-mlogloss:1.59837
[36m(train_xgb_ray_tune pid=524073)[0m [350]	train-mlogloss:1.62954	validation-mlogloss:1.63718
[36m(train_xgb_ray_tune pid=524066)[0m [475]	train-mlogloss:1.61887	validation-mlogloss:1.61959
[36m(train_xgb_ray_tune pid=524079)[0m [381]	train-mlogloss:1.38565	validation-mlogloss:1.42665
[36m(train_xgb_ray_tune pid=524078)[0m [448]	train-mlogloss:1.56924	validation-mlogloss:1.58111
[36m(train_xgb_ray_tune pid=524077)[0m [334]	train-mlogloss:1.31054	validation-mlogloss:1.38435

Trial status: 13 RUNNING | 7 TERMINATED
Current time: 2025-10-27 11:14:25. Total running time: 1min 30s
Logical resource usage: 13.0/20 CPUs, 0/1 GPUs (0.0/1.0 accelerator_type:G)
╭────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ Trial name     status         num_boost_round     max_depth     learning_rate     subsample     colsample_bytree      gamma     min_child_weight     reg_alpha     reg_lambda     random_state     iter     total time (s)     validation_accuracy │
├────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ trial_815ce    RUNNING                    591             3        0.0085005       0.528068             0.538545   27.6444                    84       2.77301        5.6084              9789                                                     │
│ trial_815ce    RUNNING                    682             2        0.0146801       0.785254             0.713742   28.1164                   148     230.112          6.03871             4262                                                     │
│ trial_815ce    RUNNING                    718             3        0.0132957       0.580279             0.509772   29.263                    112      36.2913        67.778               6110                                                     │
│ trial_815ce    RUNNING                    647             2        0.0191399       0.637997             0.641773   14.3746                   139      72.7003       158.825               5669                                                     │
│ trial_815ce    RUNNING                    402             3        0.0183588       0.507052             0.829074    6.27376                   78      10.5642       623.61                7375                                                     │
│ trial_815ce    RUNNING                    756             2        0.0198547       0.539038             0.656365    9.29435                   97      16.981         42.2814              4597                                                     │
│ trial_815ce    RUNNING                    743             3        0.00571989      0.512015             0.664965   21.0431                   119      20.2153       476.006               5012                                                     │
│ trial_815ce    RUNNING                    445             2        0.011522        0.543758             0.820794   11.8266                   144       2.06773      886.585               5060                                                     │
│ trial_815ce    RUNNING                    714             3        0.0184111       0.611159             0.652786    8.01805                   76      15.9429        41.985                274                                                     │
│ trial_815ce    RUNNING                    735             2        0.0129654       0.753519             0.546044    7.53437                  109      77.9489       132.385               2413                                                     │
│ trial_815ce    RUNNING                    467             3        0.019242        0.80582              0.523636   10.4785                   156      43.0216        47.2207              9252                                                     │
│ trial_815ce    RUNNING                    598             3        0.0135708       0.623241             0.761129   14.8588                    71       1.37779       20.6734              6349                                                     │
│ trial_815ce    RUNNING                    567             2        0.00814755      0.728638             0.827736    9.36595                  126      57.4077        13.7875              8719                                                     │
│ trial_815ce    TERMINATED                 291             2        0.0124667       0.824162             0.57164     5.27421                   62      12.8313       296.871               7779        1            69.7763               0.500593  │
│ trial_815ce    TERMINATED                 373             2        0.00615249      0.817785             0.660271   13.2957                   157      21.6249       164.981               7724        1            82.5157               0.478261  │
│ trial_815ce    TERMINATED                 626             2        0.0197307       0.760867             0.834172   29.7125                    95     297.768         97.9173               518        1            70.9399               0.402767  │
│ trial_815ce    TERMINATED                 284             2        0.00785538      0.70404              0.765188   29.8994                   171       2.05829       32.3756              7624        1            68.5358               0.488538  │
│ trial_815ce    TERMINATED                 789             3        0.0171509       0.536051             0.50909    24.0376                    63     939.294        903.31                3632        1             8.6632               0.0681818 │
│ trial_815ce    TERMINATED                 224             3        0.0188875       0.765795             0.63462    23.754                    147     293.798        248.333               8671        1            47.3779               0.404941  │
│ trial_815ce    TERMINATED                 217             2        0.0148705       0.565127             0.574846   24.1135                   101     145.722          6.90155             4616        1            47.8721               0.443083  │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=524032)[0m [353]	train-mlogloss:1.50196	validation-mlogloss:1.52678
[36m(train_xgb_ray_tune pid=524045)[0m [558]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524080)[0m [369]	train-mlogloss:1.28638	validation-mlogloss:1.36331
[36m(train_xgb_ray_tune pid=524075)[0m [477]	train-mlogloss:1.36021	validation-mlogloss:1.39658
[36m(train_xgb_ray_tune pid=524081)[0m [412]	train-mlogloss:1.56684	validation-mlogloss:1.57456
[36m(train_xgb_ray_tune pid=524046)[0m [487]	train-mlogloss:1.59364	validation-mlogloss:1.59837
[36m(train_xgb_ray_tune pid=524046)[0m [488]	train-mlogloss:1.59350	validation-mlogloss:1.59825
[36m(train_xgb_ray_tune pid=524073)[0m [351]	train-mlogloss:1.62844	validation-mlogloss:1.63611
[36m(train_xgb_ray_tune pid=524066)[0m [476]	train-mlogloss:1.61878	validation-mlogloss:1.61952
[36m(train_xgb_ray_tune pid=524074)[0m [384]	train-mlogloss:2.09055	validation-mlogloss:2.07498
[36m(train_xgb_ray_tune pid=524079)[0m [382]	train-mlogloss:1.38546	validation-mlogloss:1.42640
[36m(train_xgb_ray_tune pid=524079)[0m [383]	train-mlogloss:1.38543	validation-mlogloss:1.42635
[36m(train_xgb_ray_tune pid=524078)[0m [449]	train-mlogloss:1.56859	validation-mlogloss:1.58056
[36m(train_xgb_ray_tune pid=524045)[0m [559]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524032)[0m [354]	train-mlogloss:1.50116	validation-mlogloss:1.52603
[36m(train_xgb_ray_tune pid=524045)[0m [560]	train-mlogloss:2.02437	validation-mlogloss:2.01169
[36m(train_xgb_ray_tune pid=524080)[0m [370]	train-mlogloss:1.28619	validation-mlogloss:1.36322
[36m(train_xgb_ray_tune pid=524080)[0m [371]	train-mlogloss:1.28567	validation-mlogloss:1.36287
[36m(train_xgb_ray_tune pid=524075)[0m [478]	train-mlogloss:1.36016	validation-mlogloss:1.39654
[36m(train_xgb_ray_tune pid=524075)[0m [479]	train-mlogloss:1.36004	validation-mlogloss:1.39647
[36m(train_xgb_ray_tune pid=524081)[0m [413]	train-mlogloss:1.56630	validation-mlogloss:1.57402
[36m(train_xgb_ray_tune pid=524076)[0m [416]	train-mlogloss:1.87576	validation-mlogloss:1.86340
[36m(train_xgb_ray_tune pid=524046)[0m [489]	train-mlogloss:1.59340	validation-mlogloss:1.59820
[36m(train_xgb_ray_tune pid=524046)[0m [490]	train-mlogloss:1.59336	validation-mlogloss:1.59818
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[36m(train_xgb_ray_tune pid=524045)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454
[36m(train_xgb_ray_tune pid=524045)[0m   _log_deprecation_warning(
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[36m(train_xgb_ray_tune pid=524081)[0m [450]	train-mlogloss:1.55062	validation-mlogloss:1.55983
[36m(train_xgb_ray_tune pid=524046)[0m [566]	train-mlogloss:1.59025	validation-mlogloss:1.59552
[36m(train_xgb_ray_tune pid=524046)[0m [567]	train-mlogloss:1.59016	validation-mlogloss:1.59546
[36m(train_xgb_ray_tune pid=524073)[0m [400]	train-mlogloss:1.58357	validation-mlogloss:1.59446
[36m(train_xgb_ray_tune pid=524066)[0m [527]	train-mlogloss:1.61684	validation-mlogloss:1.61760
[36m(train_xgb_ray_tune pid=524074)[0m [418]	train-mlogloss:2.05738	validation-mlogloss:2.04094
[36m(train_xgb_ray_tune pid=524079)[0m [461]	train-mlogloss:1.38003	validation-mlogloss:1.42175
[36m(train_xgb_ray_tune pid=524079)[0m [462]	train-mlogloss:1.37999	validation-mlogloss:1.42170
[36m(train_xgb_ray_tune pid=524078)[0m [505]	train-mlogloss:1.53630	validation-mlogloss:1.55097
[36m(train_xgb_ray_tune pid=524077)[0m [366]	train-mlogloss:1.29115	validation-mlogloss:1.36921
[36m(train_xgb_ray_tune pid=524080)[0m [440]	train-mlogloss:1.26978	validation-mlogloss:1.35156
[36m(train_xgb_ray_tune pid=524080)[0m [441]	train-mlogloss:1.26961	validation-mlogloss:1.35145
[36m(train_xgb_ray_tune pid=524075)[0m [554]	train-mlogloss:1.35418	validation-mlogloss:1.39232
[36m(train_xgb_ray_tune pid=524075)[0m [555]	train-mlogloss:1.35412	validation-mlogloss:1.39233
[36m(train_xgb_ray_tune pid=524081)[0m [451]	train-mlogloss:1.55027	validation-mlogloss:1.55953
[36m(train_xgb_ray_tune pid=524046)[0m [568]	train-mlogloss:1.59012	validation-mlogloss:1.59543
[36m(train_xgb_ray_tune pid=524046)[0m [569]	train-mlogloss:1.59003	validation-mlogloss:1.59536
[36m(train_xgb_ray_tune pid=524073)[0m [401]	train-mlogloss:1.58279	validation-mlogloss:1.59377
[36m(train_xgb_ray_tune pid=524066)[0m [528]	train-mlogloss:1.61680	validation-mlogloss:1.61756
[36m(train_xgb_ray_tune pid=524074)[0m [419]	train-mlogloss:2.05647	validation-mlogloss:2.03998
[36m(train_xgb_ray_tune pid=524079)[0m [463]	train-mlogloss:1.37992	validation-mlogloss:1.42161
[36m(train_xgb_ray_tune pid=524079)[0m [464]	train-mlogloss:1.37990	validation-mlogloss:1.42157
[36m(train_xgb_ray_tune pid=524078)[0m [506]	train-mlogloss:1.53576	validation-mlogloss:1.55045
[36m(train_xgb_ray_tune pid=524078)[0m [507]	train-mlogloss:1.53530	validation-mlogloss:1.55003
[36m(train_xgb_ray_tune pid=524032)[0m [388]	train-mlogloss:1.47924	validation-mlogloss:1.50523

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:31. Total running time: 1min 36s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             93.2442 │
│ time_total_s                 93.2442 │
│ training_iteration                 1 │
│ validation_accuracy          0.41423 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:31. Total running time: 1min 36s
[36m(train_xgb_ray_tune pid=524080)[0m [442]	train-mlogloss:1.26935	validation-mlogloss:1.35129
[36m(train_xgb_ray_tune pid=524075)[0m [556]	train-mlogloss:1.35405	validation-mlogloss:1.39228
[36m(train_xgb_ray_tune pid=524075)[0m [557]	train-mlogloss:1.35403	validation-mlogloss:1.39227
[36m(train_xgb_ray_tune pid=524081)[0m [452]	train-mlogloss:1.54995	validation-mlogloss:1.55921
[36m(train_xgb_ray_tune pid=524046)[0m [570]	train-mlogloss:1.59003	validation-mlogloss:1.59536
[36m(train_xgb_ray_tune pid=524046)[0m [571]	train-mlogloss:1.59003	validation-mlogloss:1.59536
[36m(train_xgb_ray_tune pid=524066)[0m [529]	train-mlogloss:1.61676	validation-mlogloss:1.61752
[36m(train_xgb_ray_tune pid=524074)[0m [420]	train-mlogloss:2.05553	validation-mlogloss:2.03899
[36m(train_xgb_ray_tune pid=524079)[0m [465]	train-mlogloss:1.37987	validation-mlogloss:1.42155
[36m(train_xgb_ray_tune pid=524079)[0m [466]	train-mlogloss:1.37985	validation-mlogloss:1.42151
[36m(train_xgb_ray_tune pid=524078)[0m [508]	train-mlogloss:1.53480	validation-mlogloss:1.54958
[36m(train_xgb_ray_tune pid=524077)[0m [367]	train-mlogloss:1.29058	validation-mlogloss:1.36883
[36m(train_xgb_ray_tune pid=524080)[0m [443]	train-mlogloss:1.26918	validation-mlogloss:1.35115
[36m(train_xgb_ray_tune pid=524032)[0m [389]	train-mlogloss:1.47858	validation-mlogloss:1.50456
[36m(train_xgb_ray_tune pid=524032)[0m [390]	train-mlogloss:1.47801	validation-mlogloss:1.50391
[36m(train_xgb_ray_tune pid=524080)[0m [444]	train-mlogloss:1.26899	validation-mlogloss:1.35104
[36m(train_xgb_ray_tune pid=524075)[0m [558]	train-mlogloss:1.35398	validation-mlogloss:1.39228
[36m(train_xgb_ray_tune pid=524046)[0m [572]	train-mlogloss:1.58998	validation-mlogloss:1.59533
[36m(train_xgb_ray_tune pid=524066)[0m [530]	train-mlogloss:1.61676	validation-mlogloss:1.61752
[36m(train_xgb_ray_tune pid=524066)[0m [531]	train-mlogloss:1.61667	validation-mlogloss:1.61745
[36m(train_xgb_ray_tune pid=524074)[0m [421]	train-mlogloss:2.05459	validation-mlogloss:2.03799
[36m(train_xgb_ray_tune pid=524078)[0m [509]	train-mlogloss:1.53427	validation-mlogloss:1.54912
[36m(train_xgb_ray_tune pid=524077)[0m [368]	train-mlogloss:1.29000	validation-mlogloss:1.36841
[36m(train_xgb_ray_tune pid=524032)[0m [391]	train-mlogloss:1.47748	validation-mlogloss:1.50341
[36m(train_xgb_ray_tune pid=524080)[0m [445]	train-mlogloss:1.26882	validation-mlogloss:1.35094
[36m(train_xgb_ray_tune pid=524080)[0m [446]	train-mlogloss:1.26867	validation-mlogloss:1.35087
[36m(train_xgb_ray_tune pid=524076)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454
[36m(train_xgb_ray_tune pid=524076)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=524075)[0m [559]	train-mlogloss:1.35395	validation-mlogloss:1.39228
[36m(train_xgb_ray_tune pid=524075)[0m [560]	train-mlogloss:1.35391	validation-mlogloss:1.39225
[36m(train_xgb_ray_tune pid=524081)[0m [453]	train-mlogloss:1.54961	validation-mlogloss:1.55890
[36m(train_xgb_ray_tune pid=524046)[0m [573]	train-mlogloss:1.58997	validation-mlogloss:1.59533
[36m(train_xgb_ray_tune pid=524046)[0m [574]	train-mlogloss:1.58988	validation-mlogloss:1.59528
[36m(train_xgb_ray_tune pid=524066)[0m [532]	train-mlogloss:1.61667	validation-mlogloss:1.61745
[36m(train_xgb_ray_tune pid=524074)[0m [422]	train-mlogloss:2.05370	validation-mlogloss:2.03709
[36m(train_xgb_ray_tune pid=524078)[0m [510]	train-mlogloss:1.53374	validation-mlogloss:1.54871
[36m(train_xgb_ray_tune pid=524078)[0m [511]	train-mlogloss:1.53321	validation-mlogloss:1.54824
[36m(train_xgb_ray_tune pid=524077)[0m [369]	train-mlogloss:1.28955	validation-mlogloss:1.36812
[36m(train_xgb_ray_tune pid=524074)[0m [423]	train-mlogloss:2.05267	validation-mlogloss:2.03607

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:32. Total running time: 1min 36s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             93.4895 │
│ time_total_s                 93.4895 │
│ training_iteration                 1 │
│ validation_accuracy          0.47095 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:32. Total running time: 1min 36s
[36m(train_xgb_ray_tune pid=524032)[0m [392]	train-mlogloss:1.47700	validation-mlogloss:1.50289
[36m(train_xgb_ray_tune pid=524080)[0m [447]	train-mlogloss:1.26843	validation-mlogloss:1.35078
[36m(train_xgb_ray_tune pid=524075)[0m [561]	train-mlogloss:1.35391	validation-mlogloss:1.39225
[36m(train_xgb_ray_tune pid=524075)[0m [562]	train-mlogloss:1.35387	validation-mlogloss:1.39221
[36m(train_xgb_ray_tune pid=524081)[0m [454]	train-mlogloss:1.54932	validation-mlogloss:1.55863
[36m(train_xgb_ray_tune pid=524046)[0m [575]	train-mlogloss:1.58988	validation-mlogloss:1.59528
[36m(train_xgb_ray_tune pid=524046)[0m [576]	train-mlogloss:1.58984	validation-mlogloss:1.59524
[36m(train_xgb_ray_tune pid=524066)[0m [533]	train-mlogloss:1.61658	validation-mlogloss:1.61740
[36m(train_xgb_ray_tune pid=524066)[0m [534]	train-mlogloss:1.61658	validation-mlogloss:1.61740
[36m(train_xgb_ray_tune pid=524074)[0m [424]	train-mlogloss:2.05172	validation-mlogloss:2.03517
[36m(train_xgb_ray_tune pid=524078)[0m [512]	train-mlogloss:1.53269	validation-mlogloss:1.54782
[36m(train_xgb_ray_tune pid=524080)[0m [448]	train-mlogloss:1.26820	validation-mlogloss:1.35063
[36m(train_xgb_ray_tune pid=524032)[0m [393]	train-mlogloss:1.47640	validation-mlogloss:1.50238
[36m(train_xgb_ray_tune pid=524032)[0m [394]	train-mlogloss:1.47583	validation-mlogloss:1.50192
[36m(train_xgb_ray_tune pid=524080)[0m [449]	train-mlogloss:1.26809	validation-mlogloss:1.35050
[36m(train_xgb_ray_tune pid=524075)[0m [563]	train-mlogloss:1.35374	validation-mlogloss:1.39208
[36m(train_xgb_ray_tune pid=524075)[0m [564]	train-mlogloss:1.35370	validation-mlogloss:1.39207
[36m(train_xgb_ray_tune pid=524081)[0m [455]	train-mlogloss:1.54901	validation-mlogloss:1.55834
[36m(train_xgb_ray_tune pid=524046)[0m [577]	train-mlogloss:1.58983	validation-mlogloss:1.59524
[36m(train_xgb_ray_tune pid=524046)[0m [578]	train-mlogloss:1.58979	validation-mlogloss:1.59521
[36m(train_xgb_ray_tune pid=524066)[0m [535]	train-mlogloss:1.61650	validation-mlogloss:1.61732
[36m(train_xgb_ray_tune pid=524066)[0m [536]	train-mlogloss:1.61650	validation-mlogloss:1.61732
[36m(train_xgb_ray_tune pid=524074)[0m [425]	train-mlogloss:2.05080	validation-mlogloss:2.03427
[36m(train_xgb_ray_tune pid=524078)[0m [513]	train-mlogloss:1.53217	validation-mlogloss:1.54728
[36m(train_xgb_ray_tune pid=524077)[0m [370]	train-mlogloss:1.28910	validation-mlogloss:1.36788
[36m(train_xgb_ray_tune pid=524080)[0m [450]	train-mlogloss:1.26795	validation-mlogloss:1.35046
[36m(train_xgb_ray_tune pid=524078)[0m [514]	train-mlogloss:1.53162	validation-mlogloss:1.54682
[36m(train_xgb_ray_tune pid=524032)[0m [395]	train-mlogloss:1.47531	validation-mlogloss:1.50136
[36m(train_xgb_ray_tune pid=524080)[0m [451]	train-mlogloss:1.26778	validation-mlogloss:1.35032
[36m(train_xgb_ray_tune pid=524075)[0m [565]	train-mlogloss:1.35365	validation-mlogloss:1.39200
[36m(train_xgb_ray_tune pid=524075)[0m [566]	train-mlogloss:1.35353	validation-mlogloss:1.39194
[36m(train_xgb_ray_tune pid=524081)[0m [456]	train-mlogloss:1.54867	validation-mlogloss:1.55808
[36m(train_xgb_ray_tune pid=524046)[0m [579]	train-mlogloss:1.58974	validation-mlogloss:1.59515
[36m(train_xgb_ray_tune pid=524046)[0m [580]	train-mlogloss:1.58974	validation-mlogloss:1.59515
[36m(train_xgb_ray_tune pid=524066)[0m [537]	train-mlogloss:1.61645	validation-mlogloss:1.61728
[36m(train_xgb_ray_tune pid=524066)[0m [538]	train-mlogloss:1.61636	validation-mlogloss:1.61718
[36m(train_xgb_ray_tune pid=524074)[0m [426]	train-mlogloss:2.04994	validation-mlogloss:2.03338
[36m(train_xgb_ray_tune pid=524074)[0m [427]	train-mlogloss:2.04900	validation-mlogloss:2.03240
[36m(train_xgb_ray_tune pid=524078)[0m [515]	train-mlogloss:1.53107	validation-mlogloss:1.54634
[36m(train_xgb_ray_tune pid=524077)[0m [371]	train-mlogloss:1.28855	validation-mlogloss:1.36743
[36m(train_xgb_ray_tune pid=524032)[0m [396]	train-mlogloss:1.47470	validation-mlogloss:1.50083
[36m(train_xgb_ray_tune pid=524032)[0m [397]	train-mlogloss:1.47410	validation-mlogloss:1.50022
[36m(train_xgb_ray_tune pid=524080)[0m [452]	train-mlogloss:1.26763	validation-mlogloss:1.35019
[36m(train_xgb_ray_tune pid=524080)[0m [453]	train-mlogloss:1.26756	validation-mlogloss:1.35014
[36m(train_xgb_ray_tune pid=524075)[0m [567]	train-mlogloss:1.35343	validation-mlogloss:1.39188
[36m(train_xgb_ray_tune pid=524075)[0m [568]	train-mlogloss:1.35335	validation-mlogloss:1.39183
[36m(train_xgb_ray_tune pid=524081)[0m [457]	train-mlogloss:1.54819	validation-mlogloss:1.55766
[36m(train_xgb_ray_tune pid=524046)[0m [581]	train-mlogloss:1.58970	validation-mlogloss:1.59510
[36m(train_xgb_ray_tune pid=524046)[0m [582]	train-mlogloss:1.58970	validation-mlogloss:1.59510
[36m(train_xgb_ray_tune pid=524066)[0m [539]	train-mlogloss:1.61631	validation-mlogloss:1.61713
[36m(train_xgb_ray_tune pid=524066)[0m [540]	train-mlogloss:1.61631	validation-mlogloss:1.61713
[36m(train_xgb_ray_tune pid=524074)[0m [428]	train-mlogloss:2.04804	validation-mlogloss:2.03150
[36m(train_xgb_ray_tune pid=524078)[0m [516]	train-mlogloss:1.53052	validation-mlogloss:1.54580
[36m(train_xgb_ray_tune pid=524077)[0m [372]	train-mlogloss:1.28816	validation-mlogloss:1.36718

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:32. Total running time: 1min 37s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             94.0104 │
│ time_total_s                 94.0104 │
│ training_iteration                 1 │
│ validation_accuracy          0.51285 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:32. Total running time: 1min 37s
[36m(train_xgb_ray_tune pid=524032)[0m [398]	train-mlogloss:1.47363	validation-mlogloss:1.49979
[36m(train_xgb_ray_tune pid=524080)[0m [454]	train-mlogloss:1.26746	validation-mlogloss:1.35013
[36m(train_xgb_ray_tune pid=524080)[0m [455]	train-mlogloss:1.26736	validation-mlogloss:1.35005
[36m(train_xgb_ray_tune pid=524075)[0m [569]	train-mlogloss:1.35335	validation-mlogloss:1.39183
[36m(train_xgb_ray_tune pid=524075)[0m [570]	train-mlogloss:1.35326	validation-mlogloss:1.39176
[36m(train_xgb_ray_tune pid=524081)[0m [458]	train-mlogloss:1.54787	validation-mlogloss:1.55734
[36m(train_xgb_ray_tune pid=524046)[0m [583]	train-mlogloss:1.58961	validation-mlogloss:1.59501
[36m(train_xgb_ray_tune pid=524046)[0m [584]	train-mlogloss:1.58961	validation-mlogloss:1.59501
[36m(train_xgb_ray_tune pid=524066)[0m [541]	train-mlogloss:1.61627	validation-mlogloss:1.61711
[36m(train_xgb_ray_tune pid=524066)[0m [542]	train-mlogloss:1.61619	validation-mlogloss:1.61703
[36m(train_xgb_ray_tune pid=524074)[0m [429]	train-mlogloss:2.04713	validation-mlogloss:2.03049
[36m(train_xgb_ray_tune pid=524078)[0m [517]	train-mlogloss:1.53001	validation-mlogloss:1.54531
[36m(train_xgb_ray_tune pid=524078)[0m [518]	train-mlogloss:1.52952	validation-mlogloss:1.54486
[36m(train_xgb_ray_tune pid=524077)[0m [373]	train-mlogloss:1.28774	validation-mlogloss:1.36689
[36m(train_xgb_ray_tune pid=524032)[0m [399]	train-mlogloss:1.47309	validation-mlogloss:1.49925
[36m(train_xgb_ray_tune pid=524032)[0m [400]	train-mlogloss:1.47268	validation-mlogloss:1.49889
[36m(train_xgb_ray_tune pid=524080)[0m [456]	train-mlogloss:1.26716	validation-mlogloss:1.34988
[36m(train_xgb_ray_tune pid=524080)[0m [457]	train-mlogloss:1.26701	validation-mlogloss:1.34974
[36m(train_xgb_ray_tune pid=524075)[0m [571]	train-mlogloss:1.35320	validation-mlogloss:1.39173
[36m(train_xgb_ray_tune pid=524075)[0m [572]	train-mlogloss:1.35308	validation-mlogloss:1.39167
[36m(train_xgb_ray_tune pid=524081)[0m [459]	train-mlogloss:1.54752	validation-mlogloss:1.55706
[36m(train_xgb_ray_tune pid=524046)[0m [585]	train-mlogloss:1.58956	validation-mlogloss:1.59498
[36m(train_xgb_ray_tune pid=524046)[0m [586]	train-mlogloss:1.58956	validation-mlogloss:1.59498
[36m(train_xgb_ray_tune pid=524066)[0m [543]	train-mlogloss:1.61614	validation-mlogloss:1.61698
[36m(train_xgb_ray_tune pid=524066)[0m [544]	train-mlogloss:1.61605	validation-mlogloss:1.61687
[36m(train_xgb_ray_tune pid=524074)[0m [430]	train-mlogloss:2.04623	validation-mlogloss:2.02955
[36m(train_xgb_ray_tune pid=524074)[0m [431]	train-mlogloss:2.04533	validation-mlogloss:2.02867
[36m(train_xgb_ray_tune pid=524078)[0m [519]	train-mlogloss:1.52901	validation-mlogloss:1.54444
[36m(train_xgb_ray_tune pid=524077)[0m [374]	train-mlogloss:1.28711	validation-mlogloss:1.36653
[36m(train_xgb_ray_tune pid=524081)[0m [460]	train-mlogloss:1.54724	validation-mlogloss:1.55676
[36m(train_xgb_ray_tune pid=524032)[0m [401]	train-mlogloss:1.47214	validation-mlogloss:1.49837
[36m(train_xgb_ray_tune pid=524080)[0m [458]	train-mlogloss:1.26689	validation-mlogloss:1.34967
[36m(train_xgb_ray_tune pid=524080)[0m [459]	train-mlogloss:1.26677	validation-mlogloss:1.34959
[36m(train_xgb_ray_tune pid=524075)[0m [573]	train-mlogloss:1.35299	validation-mlogloss:1.39158
[36m(train_xgb_ray_tune pid=524081)[0m [461]	train-mlogloss:1.54687	validation-mlogloss:1.55642
[36m(train_xgb_ray_tune pid=524046)[0m [587]	train-mlogloss:1.58952	validation-mlogloss:1.59495
[36m(train_xgb_ray_tune pid=524046)[0m [588]	train-mlogloss:1.58947	validation-mlogloss:1.59491
[36m(train_xgb_ray_tune pid=524066)[0m [545]	train-mlogloss:1.61601	validation-mlogloss:1.61685
[36m(train_xgb_ray_tune pid=524066)[0m [546]	train-mlogloss:1.61596	validation-mlogloss:1.61683
[36m(train_xgb_ray_tune pid=524074)[0m [432]	train-mlogloss:2.04439	validation-mlogloss:2.02774
[36m(train_xgb_ray_tune pid=524078)[0m [520]	train-mlogloss:1.52855	validation-mlogloss:1.54399
[36m(train_xgb_ray_tune pid=524077)[0m [375]	train-mlogloss:1.28650	validation-mlogloss:1.36611
[36m(train_xgb_ray_tune pid=524075)[0m [574]	train-mlogloss:1.35299	validation-mlogloss:1.39158

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:33. Total running time: 1min 37s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             94.5969 │
│ time_total_s                 94.5969 │
│ training_iteration                 1 │
│ validation_accuracy          0.53814 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:33. Total running time: 1min 37s
[36m(train_xgb_ray_tune pid=524032)[0m [402]	train-mlogloss:1.47172	validation-mlogloss:1.49798
[36m(train_xgb_ray_tune pid=524032)[0m [403]	train-mlogloss:1.47121	validation-mlogloss:1.49760
[36m(train_xgb_ray_tune pid=524080)[0m [460]	train-mlogloss:1.26670	validation-mlogloss:1.34955
[36m(train_xgb_ray_tune pid=524075)[0m [575]	train-mlogloss:1.35299	validation-mlogloss:1.39158
[36m(train_xgb_ray_tune pid=524081)[0m [462]	train-mlogloss:1.54657	validation-mlogloss:1.55622
[36m(train_xgb_ray_tune pid=524081)[0m [463]	train-mlogloss:1.54625	validation-mlogloss:1.55593
[36m(train_xgb_ray_tune pid=524046)[0m [589]	train-mlogloss:1.58938	validation-mlogloss:1.59483
[36m(train_xgb_ray_tune pid=524046)[0m [590]	train-mlogloss:1.58933	validation-mlogloss:1.59480
[36m(train_xgb_ray_tune pid=524066)[0m [547]	train-mlogloss:1.61596	validation-mlogloss:1.61683
[36m(train_xgb_ray_tune pid=524066)[0m [548]	train-mlogloss:1.61592	validation-mlogloss:1.61678
[36m(train_xgb_ray_tune pid=524074)[0m [433]	train-mlogloss:2.04350	validation-mlogloss:2.02683
[36m(train_xgb_ray_tune pid=524078)[0m [521]	train-mlogloss:1.52801	validation-mlogloss:1.54352
[36m(train_xgb_ray_tune pid=524078)[0m [522]	train-mlogloss:1.52749	validation-mlogloss:1.54304
[36m(train_xgb_ray_tune pid=524077)[0m [376]	train-mlogloss:1.28597	validation-mlogloss:1.36564
[36m(train_xgb_ray_tune pid=524080)[0m [461]	train-mlogloss:1.26659	validation-mlogloss:1.34947
[36m(train_xgb_ray_tune pid=524075)[0m [576]	train-mlogloss:1.35288	validation-mlogloss:1.39144
[36m(train_xgb_ray_tune pid=524032)[0m [404]	train-mlogloss:1.47071	validation-mlogloss:1.49716
[36m(train_xgb_ray_tune pid=524080)[0m [462]	train-mlogloss:1.26640	validation-mlogloss:1.34932
[36m(train_xgb_ray_tune pid=524075)[0m [577]	train-mlogloss:1.35288	validation-mlogloss:1.39144
[36m(train_xgb_ray_tune pid=524081)[0m [464]	train-mlogloss:1.54584	validation-mlogloss:1.55554
[36m(train_xgb_ray_tune pid=524046)[0m [591]	train-mlogloss:1.58933	validation-mlogloss:1.59480
[36m(train_xgb_ray_tune pid=524046)[0m [592]	train-mlogloss:1.58929	validation-mlogloss:1.59476
[36m(train_xgb_ray_tune pid=524066)[0m [549]	train-mlogloss:1.61588	validation-mlogloss:1.61672
[36m(train_xgb_ray_tune pid=524066)[0m [550]	train-mlogloss:1.61588	validation-mlogloss:1.61672
[36m(train_xgb_ray_tune pid=524074)[0m [434]	train-mlogloss:2.04258	validation-mlogloss:2.02593
[36m(train_xgb_ray_tune pid=524074)[0m [435]	train-mlogloss:2.04168	validation-mlogloss:2.02497
[36m(train_xgb_ray_tune pid=524078)[0m [523]	train-mlogloss:1.52698	validation-mlogloss:1.54264
[36m(train_xgb_ray_tune pid=524077)[0m [377]	train-mlogloss:1.28543	validation-mlogloss:1.36520
[36m(train_xgb_ray_tune pid=524077)[0m [378]	train-mlogloss:1.28501	validation-mlogloss:1.36486
[36m(train_xgb_ray_tune pid=524075)[0m [578]	train-mlogloss:1.35279	validation-mlogloss:1.39133
[36m(train_xgb_ray_tune pid=524081)[0m [465]	train-mlogloss:1.54547	validation-mlogloss:1.55517
[36m(train_xgb_ray_tune pid=524032)[0m [405]	train-mlogloss:1.47016	validation-mlogloss:1.49659
[36m(train_xgb_ray_tune pid=524032)[0m [406]	train-mlogloss:1.46959	validation-mlogloss:1.49597
[36m(train_xgb_ray_tune pid=524080)[0m [463]	train-mlogloss:1.26612	validation-mlogloss:1.34921
[36m(train_xgb_ray_tune pid=524080)[0m [464]	train-mlogloss:1.26604	validation-mlogloss:1.34918
[36m(train_xgb_ray_tune pid=524075)[0m [579]	train-mlogloss:1.35277	validation-mlogloss:1.39130
[36m(train_xgb_ray_tune pid=524075)[0m [580]	train-mlogloss:1.35273	validation-mlogloss:1.39131
[36m(train_xgb_ray_tune pid=524081)[0m [466]	train-mlogloss:1.54508	validation-mlogloss:1.55480
[36m(train_xgb_ray_tune pid=524046)[0m [593]	train-mlogloss:1.58914	validation-mlogloss:1.59464
[36m(train_xgb_ray_tune pid=524046)[0m [594]	train-mlogloss:1.58914	validation-mlogloss:1.59464
[36m(train_xgb_ray_tune pid=524066)[0m [551]	train-mlogloss:1.61588	validation-mlogloss:1.61672
[36m(train_xgb_ray_tune pid=524066)[0m [552]	train-mlogloss:1.61579	validation-mlogloss:1.61662
[36m(train_xgb_ray_tune pid=524074)[0m [436]	train-mlogloss:2.04076	validation-mlogloss:2.02407
[36m(train_xgb_ray_tune pid=524078)[0m [524]	train-mlogloss:1.52648	validation-mlogloss:1.54219
[36m(train_xgb_ray_tune pid=524078)[0m [525]	train-mlogloss:1.52604	validation-mlogloss:1.54176
[36m(train_xgb_ray_tune pid=524077)[0m [379]	train-mlogloss:1.28450	validation-mlogloss:1.36439
[36m(train_xgb_ray_tune pid=524046)[0m [595]	train-mlogloss:1.58914	validation-mlogloss:1.59464
[36m(train_xgb_ray_tune pid=524032)[0m [407]	train-mlogloss:1.46914	validation-mlogloss:1.49558
[36m(train_xgb_ray_tune pid=524032)[0m [408]	train-mlogloss:1.46875	validation-mlogloss:1.49517
[36m(train_xgb_ray_tune pid=524080)[0m [465]	train-mlogloss:1.26591	validation-mlogloss:1.34908
[36m(train_xgb_ray_tune pid=524080)[0m [466]	train-mlogloss:1.26590	validation-mlogloss:1.34907
[36m(train_xgb_ray_tune pid=524075)[0m [581]	train-mlogloss:1.35268	validation-mlogloss:1.39131
[36m(train_xgb_ray_tune pid=524075)[0m [582]	train-mlogloss:1.35256	validation-mlogloss:1.39133
[36m(train_xgb_ray_tune pid=524081)[0m [467]	train-mlogloss:1.54472	validation-mlogloss:1.55448
[36m(train_xgb_ray_tune pid=524081)[0m [468]	train-mlogloss:1.54433	validation-mlogloss:1.55411
[36m(train_xgb_ray_tune pid=524046)[0m [596]	train-mlogloss:1.58910	validation-mlogloss:1.59459
[36m(train_xgb_ray_tune pid=524046)[0m [597]	train-mlogloss:1.58905	validation-mlogloss:1.59451
[36m(train_xgb_ray_tune pid=524066)[0m [553]	train-mlogloss:1.61563	validation-mlogloss:1.61645
[36m(train_xgb_ray_tune pid=524066)[0m [554]	train-mlogloss:1.61558	validation-mlogloss:1.61643
[36m(train_xgb_ray_tune pid=524074)[0m [437]	train-mlogloss:2.03995	validation-mlogloss:2.02324
[36m(train_xgb_ray_tune pid=524074)[0m [438]	train-mlogloss:2.03911	validation-mlogloss:2.02234
[36m(train_xgb_ray_tune pid=524078)[0m [526]	train-mlogloss:1.52556	validation-mlogloss:1.54136
[36m(train_xgb_ray_tune pid=524077)[0m [380]	train-mlogloss:1.28407	validation-mlogloss:1.36403
[36m(train_xgb_ray_tune pid=524077)[0m [381]	train-mlogloss:1.28360	validation-mlogloss:1.36378
[36m(train_xgb_ray_tune pid=524080)[0m [467]	train-mlogloss:1.26581	validation-mlogloss:1.34901
[36m(train_xgb_ray_tune pid=524032)[0m [409]	train-mlogloss:1.46827	validation-mlogloss:1.49473
[36m(train_xgb_ray_tune pid=524080)[0m [468]	train-mlogloss:1.26573	validation-mlogloss:1.34895
[36m(train_xgb_ray_tune pid=524075)[0m [583]	train-mlogloss:1.35238	validation-mlogloss:1.39121
[36m(train_xgb_ray_tune pid=524075)[0m [584]	train-mlogloss:1.35231	validation-mlogloss:1.39118
[36m(train_xgb_ray_tune pid=524081)[0m [469]	train-mlogloss:1.54403	validation-mlogloss:1.55384
[36m(train_xgb_ray_tune pid=524081)[0m [470]	train-mlogloss:1.54374	validation-mlogloss:1.55354
[36m(train_xgb_ray_tune pid=524046)[0m [598]	train-mlogloss:1.58905	validation-mlogloss:1.59451
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[36m(train_xgb_ray_tune pid=524066)[0m [555]	train-mlogloss:1.61554	validation-mlogloss:1.61637
[36m(train_xgb_ray_tune pid=524066)[0m [556]	train-mlogloss:1.61550	validation-mlogloss:1.61634
[36m(train_xgb_ray_tune pid=524074)[0m [439]	train-mlogloss:2.03824	validation-mlogloss:2.02147
[36m(train_xgb_ray_tune pid=524078)[0m [527]	train-mlogloss:1.52513	validation-mlogloss:1.54098
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[36m(train_xgb_ray_tune pid=524077)[0m [382]	train-mlogloss:1.28314	validation-mlogloss:1.36349
[36m(train_xgb_ray_tune pid=524080)[0m [469]	train-mlogloss:1.26560	validation-mlogloss:1.34885
[36m(train_xgb_ray_tune pid=524066)[0m [557]	train-mlogloss:1.61545	validation-mlogloss:1.61629
[36m(train_xgb_ray_tune pid=524074)[0m [440]	train-mlogloss:2.03740	validation-mlogloss:2.02060
[36m(train_xgb_ray_tune pid=524032)[0m [410]	train-mlogloss:1.46790	validation-mlogloss:1.49434
[36m(train_xgb_ray_tune pid=524032)[0m [411]	train-mlogloss:1.46736	validation-mlogloss:1.49379
[36m(train_xgb_ray_tune pid=524080)[0m [470]	train-mlogloss:1.26542	validation-mlogloss:1.34870
[36m(train_xgb_ray_tune pid=524075)[0m [585]	train-mlogloss:1.35221	validation-mlogloss:1.39108
[36m(train_xgb_ray_tune pid=524075)[0m [586]	train-mlogloss:1.35219	validation-mlogloss:1.39106
[36m(train_xgb_ray_tune pid=524081)[0m [471]	train-mlogloss:1.54346	validation-mlogloss:1.55325
[36m(train_xgb_ray_tune pid=524046)[0m [600]	train-mlogloss:1.58905	validation-mlogloss:1.59451
[36m(train_xgb_ray_tune pid=524046)[0m [601]	train-mlogloss:1.58905	validation-mlogloss:1.59451
[36m(train_xgb_ray_tune pid=524066)[0m [558]	train-mlogloss:1.61537	validation-mlogloss:1.61623
[36m(train_xgb_ray_tune pid=524066)[0m [559]	train-mlogloss:1.61528	validation-mlogloss:1.61614
[36m(train_xgb_ray_tune pid=524074)[0m [441]	train-mlogloss:2.03646	validation-mlogloss:2.01970
[36m(train_xgb_ray_tune pid=524078)[0m [529]	train-mlogloss:1.52428	validation-mlogloss:1.54018
[36m(train_xgb_ray_tune pid=524077)[0m [383]	train-mlogloss:1.28269	validation-mlogloss:1.36323
[36m(train_xgb_ray_tune pid=524077)[0m [384]	train-mlogloss:1.28228	validation-mlogloss:1.36286
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[36m(train_xgb_ray_tune pid=524081)[0m [472]	train-mlogloss:1.54313	validation-mlogloss:1.55295
[36m(train_xgb_ray_tune pid=524032)[0m [412]	train-mlogloss:1.46697	validation-mlogloss:1.49335
[36m(train_xgb_ray_tune pid=524080)[0m [472]	train-mlogloss:1.26523	validation-mlogloss:1.34859
[36m(train_xgb_ray_tune pid=524080)[0m [473]	train-mlogloss:1.26517	validation-mlogloss:1.34853
[36m(train_xgb_ray_tune pid=524075)[0m [587]	train-mlogloss:1.35210	validation-mlogloss:1.39098
[36m(train_xgb_ray_tune pid=524075)[0m [588]	train-mlogloss:1.35206	validation-mlogloss:1.39094
[36m(train_xgb_ray_tune pid=524081)[0m [473]	train-mlogloss:1.54276	validation-mlogloss:1.55259
[36m(train_xgb_ray_tune pid=524046)[0m [602]	train-mlogloss:1.58900	validation-mlogloss:1.59447
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[36m(train_xgb_ray_tune pid=524066)[0m [560]	train-mlogloss:1.61524	validation-mlogloss:1.61609
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[36m(train_xgb_ray_tune pid=524074)[0m [442]	train-mlogloss:2.03554	validation-mlogloss:2.01878
[36m(train_xgb_ray_tune pid=524078)[0m [530]	train-mlogloss:1.52384	validation-mlogloss:1.53977
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[36m(train_xgb_ray_tune pid=524077)[0m [385]	train-mlogloss:1.28174	validation-mlogloss:1.36249
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[36m(train_xgb_ray_tune pid=524032)[0m [414]	train-mlogloss:1.46607	validation-mlogloss:1.49249
[36m(train_xgb_ray_tune pid=524080)[0m [474]	train-mlogloss:1.26502	validation-mlogloss:1.34837
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[36m(train_xgb_ray_tune pid=524075)[0m [589]	train-mlogloss:1.35204	validation-mlogloss:1.39094
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[36m(train_xgb_ray_tune pid=524046)[0m [604]	train-mlogloss:1.58895	validation-mlogloss:1.59440
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[36m(train_xgb_ray_tune pid=524066)[0m [562]	train-mlogloss:1.61511	validation-mlogloss:1.61594
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[36m(train_xgb_ray_tune pid=524074)[0m [443]	train-mlogloss:2.03465	validation-mlogloss:2.01783
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[36m(train_xgb_ray_tune pid=524078)[0m [532]	train-mlogloss:1.52299	validation-mlogloss:1.53898
[36m(train_xgb_ray_tune pid=524077)[0m [386]	train-mlogloss:1.28137	validation-mlogloss:1.36224
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[36m(train_xgb_ray_tune pid=524032)[0m [415]	train-mlogloss:1.46571	validation-mlogloss:1.49214
[36m(train_xgb_ray_tune pid=524032)[0m [416]	train-mlogloss:1.46527	validation-mlogloss:1.49172
[36m(train_xgb_ray_tune pid=524080)[0m [476]	train-mlogloss:1.26484	validation-mlogloss:1.34829
[36m(train_xgb_ray_tune pid=524080)[0m [477]	train-mlogloss:1.26471	validation-mlogloss:1.34824
[36m(train_xgb_ray_tune pid=524075)[0m [591]	train-mlogloss:1.35198	validation-mlogloss:1.39088
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[36m(train_xgb_ray_tune pid=524066)[0m [564]	train-mlogloss:1.61502	validation-mlogloss:1.61589
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[36m(train_xgb_ray_tune pid=524077)[0m [388]	train-mlogloss:1.28042	validation-mlogloss:1.36153
[36m(train_xgb_ray_tune pid=524032)[0m [417]	train-mlogloss:1.46478	validation-mlogloss:1.49128
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[36m(train_xgb_ray_tune pid=524075)[0m [593]	train-mlogloss:1.35181	validation-mlogloss:1.39077
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[36m(train_xgb_ray_tune pid=524077)[0m [389]	train-mlogloss:1.28000	validation-mlogloss:1.36120
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[36m(train_xgb_ray_tune pid=524081)[0m [516]	train-mlogloss:1.53193	validation-mlogloss:1.54289
[36m(train_xgb_ray_tune pid=524046)[0m [654]	train-mlogloss:1.58778	validation-mlogloss:1.59329
[36m(train_xgb_ray_tune pid=524046)[0m [655]	train-mlogloss:1.58778	validation-mlogloss:1.59329
[36m(train_xgb_ray_tune pid=524066)[0m [612]	train-mlogloss:1.61387	validation-mlogloss:1.61477
[36m(train_xgb_ray_tune pid=524066)[0m [613]	train-mlogloss:1.61387	validation-mlogloss:1.61477
[36m(train_xgb_ray_tune pid=524074)[0m [477]	train-mlogloss:2.00467	validation-mlogloss:1.98748
[36m(train_xgb_ray_tune pid=524074)[0m [478]	train-mlogloss:2.00382	validation-mlogloss:1.98666
[36m(train_xgb_ray_tune pid=524077)[0m [422]	train-mlogloss:1.26755	validation-mlogloss:1.35186
[36m(train_xgb_ray_tune pid=524077)[0m [423]	train-mlogloss:1.26728	validation-mlogloss:1.35165
[36m(train_xgb_ray_tune pid=524032)[0m [454]	train-mlogloss:1.45054	validation-mlogloss:1.47775
[36m(train_xgb_ray_tune pid=524032)[0m [455]	train-mlogloss:1.45023	validation-mlogloss:1.47742
[36m(train_xgb_ray_tune pid=524080)[0m [525]	train-mlogloss:1.26035	validation-mlogloss:1.34542
[36m(train_xgb_ray_tune pid=524080)[0m [526]	train-mlogloss:1.26029	validation-mlogloss:1.34530
[36m(train_xgb_ray_tune pid=524075)[0m [639]	train-mlogloss:1.34912	validation-mlogloss:1.38878
[36m(train_xgb_ray_tune pid=524075)[0m [640]	train-mlogloss:1.34902	validation-mlogloss:1.38878
[36m(train_xgb_ray_tune pid=524081)[0m [517]	train-mlogloss:1.53171	validation-mlogloss:1.54272
[36m(train_xgb_ray_tune pid=524081)[0m [518]	train-mlogloss:1.53161	validation-mlogloss:1.54261
[36m(train_xgb_ray_tune pid=524046)[0m [656]	train-mlogloss:1.58773	validation-mlogloss:1.59328
[36m(train_xgb_ray_tune pid=524046)[0m [657]	train-mlogloss:1.58773	validation-mlogloss:1.59328
[36m(train_xgb_ray_tune pid=524066)[0m [614]	train-mlogloss:1.61383	validation-mlogloss:1.61475
[36m(train_xgb_ray_tune pid=524066)[0m [615]	train-mlogloss:1.61378	validation-mlogloss:1.61474
[36m(train_xgb_ray_tune pid=524074)[0m [479]	train-mlogloss:2.00297	validation-mlogloss:1.98583
[36m(train_xgb_ray_tune pid=524077)[0m [424]	train-mlogloss:1.26685	validation-mlogloss:1.35137
[36m(train_xgb_ray_tune pid=524032)[0m [456]	train-mlogloss:1.44997	validation-mlogloss:1.47708
[36m(train_xgb_ray_tune pid=524032)[0m [457]	train-mlogloss:1.44971	validation-mlogloss:1.47683
[36m(train_xgb_ray_tune pid=524080)[0m [527]	train-mlogloss:1.26027	validation-mlogloss:1.34531
[36m(train_xgb_ray_tune pid=524080)[0m [528]	train-mlogloss:1.26019	validation-mlogloss:1.34526
[36m(train_xgb_ray_tune pid=524075)[0m [641]	train-mlogloss:1.34900	validation-mlogloss:1.38876
[36m(train_xgb_ray_tune pid=524075)[0m [642]	train-mlogloss:1.34898	validation-mlogloss:1.38876
[36m(train_xgb_ray_tune pid=524081)[0m [519]	train-mlogloss:1.53140	validation-mlogloss:1.54241
[36m(train_xgb_ray_tune pid=524081)[0m [520]	train-mlogloss:1.53120	validation-mlogloss:1.54224
[36m(train_xgb_ray_tune pid=524046)[0m [658]	train-mlogloss:1.58764	validation-mlogloss:1.59321
[36m(train_xgb_ray_tune pid=524046)[0m [659]	train-mlogloss:1.58764	validation-mlogloss:1.59321
[36m(train_xgb_ray_tune pid=524046)[0m [660]	train-mlogloss:1.58759	validation-mlogloss:1.59315
[36m(train_xgb_ray_tune pid=524066)[0m [616]	train-mlogloss:1.61378	validation-mlogloss:1.61474
[36m(train_xgb_ray_tune pid=524066)[0m [617]	train-mlogloss:1.61378	validation-mlogloss:1.61474
[36m(train_xgb_ray_tune pid=524066)[0m [618]	train-mlogloss:1.61378	validation-mlogloss:1.61474
[36m(train_xgb_ray_tune pid=524074)[0m [480]	train-mlogloss:2.00207	validation-mlogloss:1.98493
[36m(train_xgb_ray_tune pid=524074)[0m [481]	train-mlogloss:2.00124	validation-mlogloss:1.98412
[36m(train_xgb_ray_tune pid=524077)[0m [425]	train-mlogloss:1.26650	validation-mlogloss:1.35121
[36m(train_xgb_ray_tune pid=524077)[0m [426]	train-mlogloss:1.26622	validation-mlogloss:1.35097
[36m(train_xgb_ray_tune pid=524032)[0m [458]	train-mlogloss:1.44941	validation-mlogloss:1.47652
[36m(train_xgb_ray_tune pid=524080)[0m [529]	train-mlogloss:1.26012	validation-mlogloss:1.34517
[36m(train_xgb_ray_tune pid=524080)[0m [530]	train-mlogloss:1.26009	validation-mlogloss:1.34515
[36m(train_xgb_ray_tune pid=524075)[0m [643]	train-mlogloss:1.34898	validation-mlogloss:1.38876
[36m(train_xgb_ray_tune pid=524075)[0m [644]	train-mlogloss:1.34890	validation-mlogloss:1.38870
[36m(train_xgb_ray_tune pid=524081)[0m [521]	train-mlogloss:1.53098	validation-mlogloss:1.54209
[36m(train_xgb_ray_tune pid=524081)[0m [522]	train-mlogloss:1.53077	validation-mlogloss:1.54189
[36m(train_xgb_ray_tune pid=524046)[0m [661]	train-mlogloss:1.58759	validation-mlogloss:1.59315
[36m(train_xgb_ray_tune pid=524046)[0m [662]	train-mlogloss:1.58759	validation-mlogloss:1.59315
[36m(train_xgb_ray_tune pid=524066)[0m [619]	train-mlogloss:1.61374	validation-mlogloss:1.61470
[36m(train_xgb_ray_tune pid=524066)[0m [620]	train-mlogloss:1.61374	validation-mlogloss:1.61470
[36m(train_xgb_ray_tune pid=524074)[0m [482]	train-mlogloss:2.00039	validation-mlogloss:1.98329
[36m(train_xgb_ray_tune pid=524077)[0m [427]	train-mlogloss:1.26580	validation-mlogloss:1.35077
[36m(train_xgb_ray_tune pid=524032)[0m [459]	train-mlogloss:1.44910	validation-mlogloss:1.47620
[36m(train_xgb_ray_tune pid=524032)[0m [460]	train-mlogloss:1.44872	validation-mlogloss:1.47586
[36m(train_xgb_ray_tune pid=524080)[0m [531]	train-mlogloss:1.26007	validation-mlogloss:1.34513
[36m(train_xgb_ray_tune pid=524080)[0m [532]	train-mlogloss:1.26007	validation-mlogloss:1.34513
[36m(train_xgb_ray_tune pid=524075)[0m [645]	train-mlogloss:1.34886	validation-mlogloss:1.38869
[36m(train_xgb_ray_tune pid=524075)[0m [646]	train-mlogloss:1.34885	validation-mlogloss:1.38869
[36m(train_xgb_ray_tune pid=524081)[0m [523]	train-mlogloss:1.53054	validation-mlogloss:1.54166
[36m(train_xgb_ray_tune pid=524081)[0m [524]	train-mlogloss:1.53032	validation-mlogloss:1.54146
[36m(train_xgb_ray_tune pid=524046)[0m [663]	train-mlogloss:1.58754	validation-mlogloss:1.59308
[36m(train_xgb_ray_tune pid=524046)[0m [664]	train-mlogloss:1.58754	validation-mlogloss:1.59308
[36m(train_xgb_ray_tune pid=524066)[0m [621]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524066)[0m [622]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524074)[0m [483]	train-mlogloss:1.99953	validation-mlogloss:1.98245
[36m(train_xgb_ray_tune pid=524074)[0m [484]	train-mlogloss:1.99873	validation-mlogloss:1.98164
[36m(train_xgb_ray_tune pid=524077)[0m [428]	train-mlogloss:1.26545	validation-mlogloss:1.35053
[36m(train_xgb_ray_tune pid=524077)[0m [429]	train-mlogloss:1.26518	validation-mlogloss:1.35036
[36m(train_xgb_ray_tune pid=524075)[0m [647]	train-mlogloss:1.34883	validation-mlogloss:1.38867
[36m(train_xgb_ray_tune pid=524032)[0m [461]	train-mlogloss:1.44841	validation-mlogloss:1.47557
[36m(train_xgb_ray_tune pid=524032)[0m [462]	train-mlogloss:1.44810	validation-mlogloss:1.47522
[36m(train_xgb_ray_tune pid=524080)[0m [533]	train-mlogloss:1.26004	validation-mlogloss:1.34512
[36m(train_xgb_ray_tune pid=524080)[0m [534]	train-mlogloss:1.25996	validation-mlogloss:1.34502
[36m(train_xgb_ray_tune pid=524075)[0m [648]	train-mlogloss:1.34875	validation-mlogloss:1.38865
[36m(train_xgb_ray_tune pid=524075)[0m [649]	train-mlogloss:1.34875	validation-mlogloss:1.38865
[36m(train_xgb_ray_tune pid=524081)[0m [525]	train-mlogloss:1.53018	validation-mlogloss:1.54134
[36m(train_xgb_ray_tune pid=524046)[0m [665]	train-mlogloss:1.58754	validation-mlogloss:1.59308
[36m(train_xgb_ray_tune pid=524046)[0m [666]	train-mlogloss:1.58750	validation-mlogloss:1.59305
[36m(train_xgb_ray_tune pid=524066)[0m [623]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524066)[0m [624]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524074)[0m [485]	train-mlogloss:1.99786	validation-mlogloss:1.98077
[36m(train_xgb_ray_tune pid=524077)[0m [430]	train-mlogloss:1.26490	validation-mlogloss:1.35016
[36m(train_xgb_ray_tune pid=524077)[0m [431]	train-mlogloss:1.26452	validation-mlogloss:1.34988
[36m(train_xgb_ray_tune pid=524081)[0m [526]	train-mlogloss:1.52996	validation-mlogloss:1.54114
[36m(train_xgb_ray_tune pid=524066)[0m [625]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524080)[0m [535]	train-mlogloss:1.25987	validation-mlogloss:1.34499
[36m(train_xgb_ray_tune pid=524032)[0m [463]	train-mlogloss:1.44779	validation-mlogloss:1.47491
[36m(train_xgb_ray_tune pid=524032)[0m [464]	train-mlogloss:1.44743	validation-mlogloss:1.47453
[36m(train_xgb_ray_tune pid=524080)[0m [536]	train-mlogloss:1.25984	validation-mlogloss:1.34497
[36m(train_xgb_ray_tune pid=524080)[0m [537]	train-mlogloss:1.25979	validation-mlogloss:1.34494
[36m(train_xgb_ray_tune pid=524075)[0m [650]	train-mlogloss:1.34873	validation-mlogloss:1.38863
[36m(train_xgb_ray_tune pid=524075)[0m [651]	train-mlogloss:1.34869	validation-mlogloss:1.38863
[36m(train_xgb_ray_tune pid=524081)[0m [527]	train-mlogloss:1.52981	validation-mlogloss:1.54098
[36m(train_xgb_ray_tune pid=524046)[0m [667]	train-mlogloss:1.58745	validation-mlogloss:1.59302
[36m(train_xgb_ray_tune pid=524046)[0m [668]	train-mlogloss:1.58745	validation-mlogloss:1.59302
[36m(train_xgb_ray_tune pid=524046)[0m [669]	train-mlogloss:1.58745	validation-mlogloss:1.59302
[36m(train_xgb_ray_tune pid=524066)[0m [626]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524066)[0m [627]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524074)[0m [486]	train-mlogloss:1.99708	validation-mlogloss:1.98000
[36m(train_xgb_ray_tune pid=524074)[0m [487]	train-mlogloss:1.99628	validation-mlogloss:1.97916
[36m(train_xgb_ray_tune pid=524077)[0m [432]	train-mlogloss:1.26435	validation-mlogloss:1.34972
[36m(train_xgb_ray_tune pid=524081)[0m [528]	train-mlogloss:1.52966	validation-mlogloss:1.54084
[36m(train_xgb_ray_tune pid=524032)[0m [465]	train-mlogloss:1.44712	validation-mlogloss:1.47425
[36m(train_xgb_ray_tune pid=524032)[0m [466]	train-mlogloss:1.44693	validation-mlogloss:1.47408
[36m(train_xgb_ray_tune pid=524080)[0m [538]	train-mlogloss:1.25972	validation-mlogloss:1.34490
[36m(train_xgb_ray_tune pid=524080)[0m [539]	train-mlogloss:1.25965	validation-mlogloss:1.34485
[36m(train_xgb_ray_tune pid=524075)[0m [652]	train-mlogloss:1.34868	validation-mlogloss:1.38863
[36m(train_xgb_ray_tune pid=524075)[0m [653]	train-mlogloss:1.34868	validation-mlogloss:1.38863
[36m(train_xgb_ray_tune pid=524081)[0m [529]	train-mlogloss:1.52950	validation-mlogloss:1.54070
[36m(train_xgb_ray_tune pid=524046)[0m [670]	train-mlogloss:1.58745	validation-mlogloss:1.59302
[36m(train_xgb_ray_tune pid=524046)[0m [671]	train-mlogloss:1.58736	validation-mlogloss:1.59292
[36m(train_xgb_ray_tune pid=524078)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=524078)[0m   _log_deprecation_warning([32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=524066)[0m [628]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524066)[0m [629]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524074)[0m [488]	train-mlogloss:1.99549	validation-mlogloss:1.97835
[36m(train_xgb_ray_tune pid=524077)[0m [433]	train-mlogloss:1.26402	validation-mlogloss:1.34953
[36m(train_xgb_ray_tune pid=524077)[0m [434]	train-mlogloss:1.26366	validation-mlogloss:1.34930

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:37. Total running time: 1min 42s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             98.9537 │
│ time_total_s                 98.9537 │
│ training_iteration                 1 │
│ validation_accuracy          0.51621 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=524032)[0m [467]	train-mlogloss:1.44662	validation-mlogloss:1.47378
[36m(train_xgb_ray_tune pid=524032)[0m [468]	train-mlogloss:1.44629	validation-mlogloss:1.47343
[36m(train_xgb_ray_tune pid=524080)[0m [540]	train-mlogloss:1.25950	validation-mlogloss:1.34478
[36m(train_xgb_ray_tune pid=524080)[0m [541]	train-mlogloss:1.25947	validation-mlogloss:1.34476
[36m(train_xgb_ray_tune pid=524075)[0m [654]	train-mlogloss:1.34868	validation-mlogloss:1.38863
[36m(train_xgb_ray_tune pid=524075)[0m [655]	train-mlogloss:1.34868	validation-mlogloss:1.38864
[36m(train_xgb_ray_tune pid=524081)[0m [530]	train-mlogloss:1.52929	validation-mlogloss:1.54048
[36m(train_xgb_ray_tune pid=524081)[0m [531]	train-mlogloss:1.52913	validation-mlogloss:1.54033
[36m(train_xgb_ray_tune pid=524046)[0m [672]	train-mlogloss:1.58736	validation-mlogloss:1.59292
[36m(train_xgb_ray_tune pid=524046)[0m [673]	train-mlogloss:1.58736	validation-mlogloss:1.59292
[36m(train_xgb_ray_tune pid=524066)[0m [630]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524066)[0m [631]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524074)[0m [489]	train-mlogloss:1.99467	validation-mlogloss:1.97748
[36m(train_xgb_ray_tune pid=524074)[0m [490]	train-mlogloss:1.99387	validation-mlogloss:1.97667

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:37. Total running time: 1min 42s
[36m(train_xgb_ray_tune pid=524077)[0m [435]	train-mlogloss:1.26340	validation-mlogloss:1.34915
[36m(train_xgb_ray_tune pid=524077)[0m [436]	train-mlogloss:1.26311	validation-mlogloss:1.34907
[36m(train_xgb_ray_tune pid=524075)[0m [656]	train-mlogloss:1.34864	validation-mlogloss:1.38862
[36m(train_xgb_ray_tune pid=524066)[0m [632]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524032)[0m [469]	train-mlogloss:1.44592	validation-mlogloss:1.47309
[36m(train_xgb_ray_tune pid=524080)[0m [542]	train-mlogloss:1.25940	validation-mlogloss:1.34471
[36m(train_xgb_ray_tune pid=524080)[0m [543]	train-mlogloss:1.25937	validation-mlogloss:1.34469
[36m(train_xgb_ray_tune pid=524080)[0m [544]	train-mlogloss:1.25929	validation-mlogloss:1.34468
[36m(train_xgb_ray_tune pid=524075)[0m [657]	train-mlogloss:1.34856	validation-mlogloss:1.38860
[36m(train_xgb_ray_tune pid=524075)[0m [658]	train-mlogloss:1.34852	validation-mlogloss:1.38857
[36m(train_xgb_ray_tune pid=524081)[0m [532]	train-mlogloss:1.52892	validation-mlogloss:1.54013
[36m(train_xgb_ray_tune pid=524081)[0m [533]	train-mlogloss:1.52864	validation-mlogloss:1.53988
[36m(train_xgb_ray_tune pid=524046)[0m [674]	train-mlogloss:1.58736	validation-mlogloss:1.59292
[36m(train_xgb_ray_tune pid=524046)[0m [675]	train-mlogloss:1.58736	validation-mlogloss:1.59292
[36m(train_xgb_ray_tune pid=524046)[0m [676]	train-mlogloss:1.58736	validation-mlogloss:1.59292
[36m(train_xgb_ray_tune pid=524066)[0m [633]	train-mlogloss:1.61370	validation-mlogloss:1.61468
[36m(train_xgb_ray_tune pid=524066)[0m [634]	train-mlogloss:1.61365	validation-mlogloss:1.61464
[36m(train_xgb_ray_tune pid=524074)[0m [491]	train-mlogloss:1.99301	validation-mlogloss:1.97581
[36m(train_xgb_ray_tune pid=524074)[0m [492]	train-mlogloss:1.99226	validation-mlogloss:1.97503
[36m(train_xgb_ray_tune pid=524077)[0m [437]	train-mlogloss:1.26273	validation-mlogloss:1.34884
[36m(train_xgb_ray_tune pid=524077)[0m [438]	train-mlogloss:1.26252	validation-mlogloss:1.34870
[36m(train_xgb_ray_tune pid=524032)[0m [470]	train-mlogloss:1.44567	validation-mlogloss:1.47282
[36m(train_xgb_ray_tune pid=524032)[0m [471]	train-mlogloss:1.44540	validation-mlogloss:1.47256
[36m(train_xgb_ray_tune pid=524080)[0m [545]	train-mlogloss:1.25924	validation-mlogloss:1.34465
[36m(train_xgb_ray_tune pid=524080)[0m [546]	train-mlogloss:1.25905	validation-mlogloss:1.34442
[36m(train_xgb_ray_tune pid=524075)[0m [659]	train-mlogloss:1.34844	validation-mlogloss:1.38853
[36m(train_xgb_ray_tune pid=524075)[0m [660]	train-mlogloss:1.34842	validation-mlogloss:1.38852
[36m(train_xgb_ray_tune pid=524081)[0m [534]	train-mlogloss:1.52840	validation-mlogloss:1.53967
[36m(train_xgb_ray_tune pid=524081)[0m [535]	train-mlogloss:1.52829	validation-mlogloss:1.53957
[36m(train_xgb_ray_tune pid=524046)[0m [677]	train-mlogloss:1.58731	validation-mlogloss:1.59287
[36m(train_xgb_ray_tune pid=524046)[0m [678]	train-mlogloss:1.58717	validation-mlogloss:1.59268
[36m(train_xgb_ray_tune pid=524066)[0m [635]	train-mlogloss:1.61353	validation-mlogloss:1.61452
[36m(train_xgb_ray_tune pid=524066)[0m [636]	train-mlogloss:1.61348	validation-mlogloss:1.61450
[36m(train_xgb_ray_tune pid=524074)[0m [493]	train-mlogloss:1.99141	validation-mlogloss:1.97419
[36m(train_xgb_ray_tune pid=524077)[0m [439]	train-mlogloss:1.26232	validation-mlogloss:1.34851
[36m(train_xgb_ray_tune pid=524077)[0m [440]	train-mlogloss:1.26193	validation-mlogloss:1.34816
[36m(train_xgb_ray_tune pid=524032)[0m [472]	train-mlogloss:1.44505	validation-mlogloss:1.47220
[36m(train_xgb_ray_tune pid=524081)[0m [536]	train-mlogloss:1.52802	validation-mlogloss:1.53936
[36m(train_xgb_ray_tune pid=524066)[0m [637]	train-mlogloss:1.61348	validation-mlogloss:1.61450
[36m(train_xgb_ray_tune pid=524032)[0m [473]	train-mlogloss:1.44475	validation-mlogloss:1.47192
[36m(train_xgb_ray_tune pid=524080)[0m [547]	train-mlogloss:1.25900	validation-mlogloss:1.34440
[36m(train_xgb_ray_tune pid=524080)[0m [548]	train-mlogloss:1.25898	validation-mlogloss:1.34439
[36m(train_xgb_ray_tune pid=524080)[0m [549]	train-mlogloss:1.25895	validation-mlogloss:1.34438
[36m(train_xgb_ray_tune pid=524075)[0m [661]	train-mlogloss:1.34827	validation-mlogloss:1.38849
[36m(train_xgb_ray_tune pid=524075)[0m [662]	train-mlogloss:1.34822	validation-mlogloss:1.38844
[36m(train_xgb_ray_tune pid=524081)[0m [537]	train-mlogloss:1.52784	validation-mlogloss:1.53920
[36m(train_xgb_ray_tune pid=524081)[0m [538]	train-mlogloss:1.52768	validation-mlogloss:1.53907
[36m(train_xgb_ray_tune pid=524046)[0m [679]	train-mlogloss:1.58717	validation-mlogloss:1.59268
[36m(train_xgb_ray_tune pid=524046)[0m [680]	train-mlogloss:1.58717	validation-mlogloss:1.59268
[36m(train_xgb_ray_tune pid=524066)[0m [638]	train-mlogloss:1.61348	validation-mlogloss:1.61450
[36m(train_xgb_ray_tune pid=524066)[0m [639]	train-mlogloss:1.61344	validation-mlogloss:1.61448
[36m(train_xgb_ray_tune pid=524074)[0m [494]	train-mlogloss:1.99061	validation-mlogloss:1.97340
[36m(train_xgb_ray_tune pid=524074)[0m [495]	train-mlogloss:1.98979	validation-mlogloss:1.97255
[36m(train_xgb_ray_tune pid=524077)[0m [441]	train-mlogloss:1.26178	validation-mlogloss:1.34799
[36m(train_xgb_ray_tune pid=524077)[0m [442]	train-mlogloss:1.26147	validation-mlogloss:1.34787
[36m(train_xgb_ray_tune pid=524032)[0m [474]	train-mlogloss:1.44439	validation-mlogloss:1.47166
[36m(train_xgb_ray_tune pid=524046)[0m [681]	train-mlogloss:1.58712	validation-mlogloss:1.59266
[36m(train_xgb_ray_tune pid=524032)[0m [475]	train-mlogloss:1.44404	validation-mlogloss:1.47140
[36m(train_xgb_ray_tune pid=524080)[0m [550]	train-mlogloss:1.25889	validation-mlogloss:1.34439
[36m(train_xgb_ray_tune pid=524080)[0m [551]	train-mlogloss:1.25885	validation-mlogloss:1.34436
[36m(train_xgb_ray_tune pid=524075)[0m [663]	train-mlogloss:1.34815	validation-mlogloss:1.38832
[36m(train_xgb_ray_tune pid=524075)[0m [664]	train-mlogloss:1.34813	validation-mlogloss:1.38832
[36m(train_xgb_ray_tune pid=524075)[0m [665]	train-mlogloss:1.34804	validation-mlogloss:1.38831
[36m(train_xgb_ray_tune pid=524081)[0m [539]	train-mlogloss:1.52743	validation-mlogloss:1.53884
[36m(train_xgb_ray_tune pid=524081)[0m [540]	train-mlogloss:1.52733	validation-mlogloss:1.53876
[36m(train_xgb_ray_tune pid=524046)[0m [682]	train-mlogloss:1.58703	validation-mlogloss:1.59260
[36m(train_xgb_ray_tune pid=524046)[0m [683]	train-mlogloss:1.58693	validation-mlogloss:1.59250
[36m(train_xgb_ray_tune pid=524066)[0m [640]	train-mlogloss:1.61344	validation-mlogloss:1.61448
[36m(train_xgb_ray_tune pid=524066)[0m [641]	train-mlogloss:1.61344	validation-mlogloss:1.61448
[36m(train_xgb_ray_tune pid=524074)[0m [496]	train-mlogloss:1.98897	validation-mlogloss:1.97169
[36m(train_xgb_ray_tune pid=524074)[0m [497]	train-mlogloss:1.98818	validation-mlogloss:1.97096
[36m(train_xgb_ray_tune pid=524077)[0m [443]	train-mlogloss:1.26127	validation-mlogloss:1.34772
[36m(train_xgb_ray_tune pid=524032)[0m [476]	train-mlogloss:1.44373	validation-mlogloss:1.47111
[36m(train_xgb_ray_tune pid=524066)[0m [642]	train-mlogloss:1.61344	validation-mlogloss:1.61448
[36m(train_xgb_ray_tune pid=524032)[0m [477]	train-mlogloss:1.44346	validation-mlogloss:1.47085
[36m(train_xgb_ray_tune pid=524080)[0m [552]	train-mlogloss:1.25881	validation-mlogloss:1.34434
[36m(train_xgb_ray_tune pid=524080)[0m [553]	train-mlogloss:1.25872	validation-mlogloss:1.34424
[36m(train_xgb_ray_tune pid=524075)[0m [666]	train-mlogloss:1.34798	validation-mlogloss:1.38829
[36m(train_xgb_ray_tune pid=524075)[0m [667]	train-mlogloss:1.34791	validation-mlogloss:1.38827
[36m(train_xgb_ray_tune pid=524081)[0m [541]	train-mlogloss:1.52717	validation-mlogloss:1.53861
[36m(train_xgb_ray_tune pid=524081)[0m [542]	train-mlogloss:1.52707	validation-mlogloss:1.53855
[36m(train_xgb_ray_tune pid=524046)[0m [684]	train-mlogloss:1.58693	validation-mlogloss:1.59250
[36m(train_xgb_ray_tune pid=524046)[0m [685]	train-mlogloss:1.58693	validation-mlogloss:1.59250
[36m(train_xgb_ray_tune pid=524066)[0m [643]	train-mlogloss:1.61344	validation-mlogloss:1.61448
[36m(train_xgb_ray_tune pid=524066)[0m [644]	train-mlogloss:1.61340	validation-mlogloss:1.61444
[36m(train_xgb_ray_tune pid=524074)[0m [498]	train-mlogloss:1.98738	validation-mlogloss:1.97014
[36m(train_xgb_ray_tune pid=524077)[0m [444]	train-mlogloss:1.26099	validation-mlogloss:1.34748
[36m(train_xgb_ray_tune pid=524077)[0m [445]	train-mlogloss:1.26077	validation-mlogloss:1.34746
[36m(train_xgb_ray_tune pid=524032)[0m [478]	train-mlogloss:1.44313	validation-mlogloss:1.47056
[36m(train_xgb_ray_tune pid=524032)[0m [479]	train-mlogloss:1.44279	validation-mlogloss:1.47024
[36m(train_xgb_ray_tune pid=524080)[0m [554]	train-mlogloss:1.25862	validation-mlogloss:1.34422
[36m(train_xgb_ray_tune pid=524080)[0m [555]	train-mlogloss:1.25858	validation-mlogloss:1.34421
[36m(train_xgb_ray_tune pid=524080)[0m [556]	train-mlogloss:1.25851	validation-mlogloss:1.34413
[36m(train_xgb_ray_tune pid=524075)[0m [668]	train-mlogloss:1.34784	validation-mlogloss:1.38824
[36m(train_xgb_ray_tune pid=524075)[0m [669]	train-mlogloss:1.34782	validation-mlogloss:1.38822
[36m(train_xgb_ray_tune pid=524081)[0m [543]	train-mlogloss:1.52683	validation-mlogloss:1.53836
[36m(train_xgb_ray_tune pid=524081)[0m [544]	train-mlogloss:1.52667	validation-mlogloss:1.53824
[36m(train_xgb_ray_tune pid=524046)[0m [686]	train-mlogloss:1.58693	validation-mlogloss:1.59250
[36m(train_xgb_ray_tune pid=524046)[0m [687]	train-mlogloss:1.58693	validation-mlogloss:1.59250
[36m(train_xgb_ray_tune pid=524046)[0m [688]	train-mlogloss:1.58693	validation-mlogloss:1.59250
[36m(train_xgb_ray_tune pid=524066)[0m [645]	train-mlogloss:1.61339	validation-mlogloss:1.61444
[36m(train_xgb_ray_tune pid=524066)[0m [646]	train-mlogloss:1.61339	validation-mlogloss:1.61444
[36m(train_xgb_ray_tune pid=524074)[0m [499]	train-mlogloss:1.98657	validation-mlogloss:1.96933
[36m(train_xgb_ray_tune pid=524074)[0m [500]	train-mlogloss:1.98578	validation-mlogloss:1.96849
[36m(train_xgb_ray_tune pid=524077)[0m [446]	train-mlogloss:1.26048	validation-mlogloss:1.34738
[36m(train_xgb_ray_tune pid=524077)[0m [447]	train-mlogloss:1.26024	validation-mlogloss:1.34720
[36m(train_xgb_ray_tune pid=524032)[0m [480]	train-mlogloss:1.44247	validation-mlogloss:1.46993
[36m(train_xgb_ray_tune pid=524032)[0m [481]	train-mlogloss:1.44222	validation-mlogloss:1.46970
[36m(train_xgb_ray_tune pid=524080)[0m [557]	train-mlogloss:1.25848	validation-mlogloss:1.34412
[36m(train_xgb_ray_tune pid=524080)[0m [558]	train-mlogloss:1.25842	validation-mlogloss:1.34406
[36m(train_xgb_ray_tune pid=524075)[0m [670]	train-mlogloss:1.34775	validation-mlogloss:1.38814
[36m(train_xgb_ray_tune pid=524075)[0m [671]	train-mlogloss:1.34768	validation-mlogloss:1.38806
[36m(train_xgb_ray_tune pid=524081)[0m [545]	train-mlogloss:1.52646	validation-mlogloss:1.53806
[36m(train_xgb_ray_tune pid=524081)[0m [546]	train-mlogloss:1.52630	validation-mlogloss:1.53789
[36m(train_xgb_ray_tune pid=524046)[0m [689]	train-mlogloss:1.58688	validation-mlogloss:1.59244
[36m(train_xgb_ray_tune pid=524046)[0m [690]	train-mlogloss:1.58688	validation-mlogloss:1.59244
[36m(train_xgb_ray_tune pid=524074)[0m [501]	train-mlogloss:1.98497	validation-mlogloss:1.96766
[36m(train_xgb_ray_tune pid=524074)[0m [502]	train-mlogloss:1.98415	validation-mlogloss:1.96684
[36m(train_xgb_ray_tune pid=524077)[0m [448]	train-mlogloss:1.25993	validation-mlogloss:1.34704
[36m(train_xgb_ray_tune pid=524077)[0m [449]	train-mlogloss:1.25971	validation-mlogloss:1.34690
[36m(train_xgb_ray_tune pid=524032)[0m [482]	train-mlogloss:1.44191	validation-mlogloss:1.46944
[36m(train_xgb_ray_tune pid=524032)[0m [483]	train-mlogloss:1.44157	validation-mlogloss:1.46909
[36m(train_xgb_ray_tune pid=524080)[0m [559]	train-mlogloss:1.25831	validation-mlogloss:1.34396
[36m(train_xgb_ray_tune pid=524080)[0m [560]	train-mlogloss:1.25825	validation-mlogloss:1.34395
[36m(train_xgb_ray_tune pid=524080)[0m [561]	train-mlogloss:1.25823	validation-mlogloss:1.34395
[36m(train_xgb_ray_tune pid=524075)[0m [672]	train-mlogloss:1.34761	validation-mlogloss:1.38803
[36m(train_xgb_ray_tune pid=524075)[0m [673]	train-mlogloss:1.34755	validation-mlogloss:1.38797
[36m(train_xgb_ray_tune pid=524081)[0m [547]	train-mlogloss:1.52616	validation-mlogloss:1.53778
[36m(train_xgb_ray_tune pid=524081)[0m [548]	train-mlogloss:1.52600	validation-mlogloss:1.53765
[36m(train_xgb_ray_tune pid=524046)[0m [691]	train-mlogloss:1.58683	validation-mlogloss:1.59240
[36m(train_xgb_ray_tune pid=524046)[0m [692]	train-mlogloss:1.58683	validation-mlogloss:1.59240
[36m(train_xgb_ray_tune pid=524046)[0m [693]	train-mlogloss:1.58683	validation-mlogloss:1.59240
[36m(train_xgb_ray_tune pid=524074)[0m [503]	train-mlogloss:1.98330	validation-mlogloss:1.96602
[36m(train_xgb_ray_tune pid=524077)[0m [450]	train-mlogloss:1.25955	validation-mlogloss:1.34675
[36m(train_xgb_ray_tune pid=524077)[0m [451]	train-mlogloss:1.25938	validation-mlogloss:1.34657
[36m(train_xgb_ray_tune pid=524075)[0m [674]	train-mlogloss:1.34749	validation-mlogloss:1.38793
[36m(train_xgb_ray_tune pid=524032)[0m [484]	train-mlogloss:1.44130	validation-mlogloss:1.46881
[36m(train_xgb_ray_tune pid=524081)[0m [549]	train-mlogloss:1.52586	validation-mlogloss:1.53753
[36m(train_xgb_ray_tune pid=524032)[0m [485]	train-mlogloss:1.44105	validation-mlogloss:1.46856
[36m(train_xgb_ray_tune pid=524032)[0m [486]	train-mlogloss:1.44077	validation-mlogloss:1.46831
[36m(train_xgb_ray_tune pid=524080)[0m [562]	train-mlogloss:1.25818	validation-mlogloss:1.34390
[36m(train_xgb_ray_tune pid=524080)[0m [563]	train-mlogloss:1.25816	validation-mlogloss:1.34386
[36m(train_xgb_ray_tune pid=524075)[0m [675]	train-mlogloss:1.34747	validation-mlogloss:1.38792
[36m(train_xgb_ray_tune pid=524075)[0m [676]	train-mlogloss:1.34745	validation-mlogloss:1.38791
[36m(train_xgb_ray_tune pid=524081)[0m [550]	train-mlogloss:1.52574	validation-mlogloss:1.53741
[36m(train_xgb_ray_tune pid=524081)[0m [551]	train-mlogloss:1.52561	validation-mlogloss:1.53732
[36m(train_xgb_ray_tune pid=524046)[0m [694]	train-mlogloss:1.58683	validation-mlogloss:1.59240
[36m(train_xgb_ray_tune pid=524046)[0m [695]	train-mlogloss:1.58678	validation-mlogloss:1.59234
[36m(train_xgb_ray_tune pid=524074)[0m [504]	train-mlogloss:1.98254	validation-mlogloss:1.96518
[36m(train_xgb_ray_tune pid=524074)[0m [505]	train-mlogloss:1.98180	validation-mlogloss:1.96442
[36m(train_xgb_ray_tune pid=524077)[0m [452]	train-mlogloss:1.25921	validation-mlogloss:1.34650
[36m(train_xgb_ray_tune pid=524077)[0m [453]	train-mlogloss:1.25904	validation-mlogloss:1.34629
[36m(train_xgb_ray_tune pid=524032)[0m [487]	train-mlogloss:1.44055	validation-mlogloss:1.46809
[36m(train_xgb_ray_tune pid=524032)[0m [488]	train-mlogloss:1.44027	validation-mlogloss:1.46780
[36m(train_xgb_ray_tune pid=524080)[0m [564]	train-mlogloss:1.25803	validation-mlogloss:1.34379
[36m(train_xgb_ray_tune pid=524080)[0m [565]	train-mlogloss:1.25798	validation-mlogloss:1.34374
[36m(train_xgb_ray_tune pid=524080)[0m [566]	train-mlogloss:1.25791	validation-mlogloss:1.34371
[36m(train_xgb_ray_tune pid=524075)[0m [677]	train-mlogloss:1.34737	validation-mlogloss:1.38785
[36m(train_xgb_ray_tune pid=524075)[0m [678]	train-mlogloss:1.34736	validation-mlogloss:1.38785
[36m(train_xgb_ray_tune pid=524081)[0m [552]	train-mlogloss:1.52534	validation-mlogloss:1.53704
[36m(train_xgb_ray_tune pid=524081)[0m [553]	train-mlogloss:1.52520	validation-mlogloss:1.53694
[36m(train_xgb_ray_tune pid=524046)[0m [696]	train-mlogloss:1.58678	validation-mlogloss:1.59234
[36m(train_xgb_ray_tune pid=524046)[0m [697]	train-mlogloss:1.58678	validation-mlogloss:1.59234
[36m(train_xgb_ray_tune pid=524046)[0m [698]	train-mlogloss:1.58678	validation-mlogloss:1.59234
[36m(train_xgb_ray_tune pid=524074)[0m [506]	train-mlogloss:1.98098	validation-mlogloss:1.96359
[36m(train_xgb_ray_tune pid=524074)[0m [507]	train-mlogloss:1.98015	validation-mlogloss:1.96277
[36m(train_xgb_ray_tune pid=524077)[0m [454]	train-mlogloss:1.25880	validation-mlogloss:1.34616
[36m(train_xgb_ray_tune pid=524077)[0m [455]	train-mlogloss:1.25858	validation-mlogloss:1.34597
[36m(train_xgb_ray_tune pid=524032)[0m [489]	train-mlogloss:1.43998	validation-mlogloss:1.46753
[36m(train_xgb_ray_tune pid=524080)[0m [567]	train-mlogloss:1.25787	validation-mlogloss:1.34368
[36m(train_xgb_ray_tune pid=524080)[0m [568]	train-mlogloss:1.25785	validation-mlogloss:1.34368
[36m(train_xgb_ray_tune pid=524075)[0m [679]	train-mlogloss:1.34730	validation-mlogloss:1.38782
[36m(train_xgb_ray_tune pid=524075)[0m [680]	train-mlogloss:1.34729	validation-mlogloss:1.38783
[36m(train_xgb_ray_tune pid=524081)[0m [554]	train-mlogloss:1.52508	validation-mlogloss:1.53679
[36m(train_xgb_ray_tune pid=524081)[0m [555]	train-mlogloss:1.52493	validation-mlogloss:1.53666
[36m(train_xgb_ray_tune pid=524046)[0m [699]	train-mlogloss:1.58678	validation-mlogloss:1.59234
[36m(train_xgb_ray_tune pid=524046)[0m [700]	train-mlogloss:1.58678	validation-mlogloss:1.59234
[36m(train_xgb_ray_tune pid=524074)[0m [508]	train-mlogloss:1.97937	validation-mlogloss:1.96191
[36m(train_xgb_ray_tune pid=524077)[0m [456]	train-mlogloss:1.25838	validation-mlogloss:1.34575
[36m(train_xgb_ray_tune pid=524077)[0m [457]	train-mlogloss:1.25812	validation-mlogloss:1.34558
[36m(train_xgb_ray_tune pid=524032)[0m [490]	train-mlogloss:1.43973	validation-mlogloss:1.46723
[36m(train_xgb_ray_tune pid=524075)[0m [681]	train-mlogloss:1.34729	validation-mlogloss:1.38783
[36m(train_xgb_ray_tune pid=524046)[0m [701]	train-mlogloss:1.58678	validation-mlogloss:1.59234
[36m(train_xgb_ray_tune pid=524032)[0m [491]	train-mlogloss:1.43955	validation-mlogloss:1.46702
[36m(train_xgb_ray_tune pid=524032)[0m [492]	train-mlogloss:1.43928	validation-mlogloss:1.46673
[36m(train_xgb_ray_tune pid=524080)[0m [569]	train-mlogloss:1.25780	validation-mlogloss:1.34365
[36m(train_xgb_ray_tune pid=524080)[0m [570]	train-mlogloss:1.25773	validation-mlogloss:1.34363
[36m(train_xgb_ray_tune pid=524080)[0m [571]	train-mlogloss:1.25773	validation-mlogloss:1.34363
[36m(train_xgb_ray_tune pid=524075)[0m [682]	train-mlogloss:1.34723	validation-mlogloss:1.38773
[36m(train_xgb_ray_tune pid=524075)[0m [683]	train-mlogloss:1.34719	validation-mlogloss:1.38774
[36m(train_xgb_ray_tune pid=524081)[0m [556]	train-mlogloss:1.52485	validation-mlogloss:1.53661
[36m(train_xgb_ray_tune pid=524081)[0m [557]	train-mlogloss:1.52474	validation-mlogloss:1.53652
[36m(train_xgb_ray_tune pid=524046)[0m [702]	train-mlogloss:1.58673	validation-mlogloss:1.59229
[36m(train_xgb_ray_tune pid=524046)[0m [703]	train-mlogloss:1.58673	validation-mlogloss:1.59229
[36m(train_xgb_ray_tune pid=524074)[0m [509]	train-mlogloss:1.97863	validation-mlogloss:1.96112
[36m(train_xgb_ray_tune pid=524074)[0m [510]	train-mlogloss:1.97784	validation-mlogloss:1.96031
[36m(train_xgb_ray_tune pid=524077)[0m [458]	train-mlogloss:1.25781	validation-mlogloss:1.34538
[36m(train_xgb_ray_tune pid=524077)[0m [459]	train-mlogloss:1.25767	validation-mlogloss:1.34525

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:39. Total running time: 1min 43s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             100.063 │
│ time_total_s                 100.063 │
│ training_iteration                 1 │
│ validation_accuracy          0.47668 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:39. Total running time: 1min 43s
[36m(train_xgb_ray_tune pid=524032)[0m [493]	train-mlogloss:1.43885	validation-mlogloss:1.46636
[36m(train_xgb_ray_tune pid=524080)[0m [572]	train-mlogloss:1.25770	validation-mlogloss:1.34361
[36m(train_xgb_ray_tune pid=524080)[0m [573]	train-mlogloss:1.25766	validation-mlogloss:1.34360
[36m(train_xgb_ray_tune pid=524075)[0m [684]	train-mlogloss:1.34713	validation-mlogloss:1.38770
[36m(train_xgb_ray_tune pid=524075)[0m [685]	train-mlogloss:1.34705	validation-mlogloss:1.38763
[36m(train_xgb_ray_tune pid=524081)[0m [558]	train-mlogloss:1.52458	validation-mlogloss:1.53636
[36m(train_xgb_ray_tune pid=524081)[0m [559]	train-mlogloss:1.52446	validation-mlogloss:1.53621
[36m(train_xgb_ray_tune pid=524046)[0m [704]	train-mlogloss:1.58673	validation-mlogloss:1.59229
[36m(train_xgb_ray_tune pid=524046)[0m [705]	train-mlogloss:1.58673	validation-mlogloss:1.59229
[36m(train_xgb_ray_tune pid=524074)[0m [511]	train-mlogloss:1.97705	validation-mlogloss:1.95951
[36m(train_xgb_ray_tune pid=524074)[0m [512]	train-mlogloss:1.97625	validation-mlogloss:1.95872
[36m(train_xgb_ray_tune pid=524077)[0m [460]	train-mlogloss:1.25749	validation-mlogloss:1.34517
[36m(train_xgb_ray_tune pid=524077)[0m [461]	train-mlogloss:1.25734	validation-mlogloss:1.34510
[36m(train_xgb_ray_tune pid=524032)[0m [494]	train-mlogloss:1.43854	validation-mlogloss:1.46607
[36m(train_xgb_ray_tune pid=524081)[0m [560]	train-mlogloss:1.52430	validation-mlogloss:1.53607
[36m(train_xgb_ray_tune pid=524032)[0m [495]	train-mlogloss:1.43825	validation-mlogloss:1.46580
[36m(train_xgb_ray_tune pid=524032)[0m [496]	train-mlogloss:1.43804	validation-mlogloss:1.46562
[36m(train_xgb_ray_tune pid=524080)[0m [574]	train-mlogloss:1.25766	validation-mlogloss:1.34360
[36m(train_xgb_ray_tune pid=524080)[0m [575]	train-mlogloss:1.25760	validation-mlogloss:1.34360
[36m(train_xgb_ray_tune pid=524080)[0m [576]	train-mlogloss:1.25758	validation-mlogloss:1.34360
[36m(train_xgb_ray_tune pid=524075)[0m [686]	train-mlogloss:1.34705	validation-mlogloss:1.38763
[36m(train_xgb_ray_tune pid=524075)[0m [687]	train-mlogloss:1.34703	validation-mlogloss:1.38763
[36m(train_xgb_ray_tune pid=524075)[0m [688]	train-mlogloss:1.34703	validation-mlogloss:1.38763
[36m(train_xgb_ray_tune pid=524081)[0m [561]	train-mlogloss:1.52415	validation-mlogloss:1.53589
[36m(train_xgb_ray_tune pid=524081)[0m [562]	train-mlogloss:1.52390	validation-mlogloss:1.53567
[36m(train_xgb_ray_tune pid=524046)[0m [706]	train-mlogloss:1.58668	validation-mlogloss:1.59225
[36m(train_xgb_ray_tune pid=524046)[0m [707]	train-mlogloss:1.58668	validation-mlogloss:1.59225
[36m(train_xgb_ray_tune pid=524046)[0m [708]	train-mlogloss:1.58668	validation-mlogloss:1.59225
[36m(train_xgb_ray_tune pid=524074)[0m [513]	train-mlogloss:1.97545	validation-mlogloss:1.95793
[36m(train_xgb_ray_tune pid=524077)[0m [462]	train-mlogloss:1.25714	validation-mlogloss:1.34491
[36m(train_xgb_ray_tune pid=524077)[0m [463]	train-mlogloss:1.25700	validation-mlogloss:1.34485
[36m(train_xgb_ray_tune pid=524032)[0m [497]	train-mlogloss:1.43780	validation-mlogloss:1.46538
[36m(train_xgb_ray_tune pid=524032)[0m [498]	train-mlogloss:1.43766	validation-mlogloss:1.46526
[36m(train_xgb_ray_tune pid=524080)[0m [577]	train-mlogloss:1.25750	validation-mlogloss:1.34356
[36m(train_xgb_ray_tune pid=524080)[0m [578]	train-mlogloss:1.25743	validation-mlogloss:1.34354
[36m(train_xgb_ray_tune pid=524075)[0m [689]	train-mlogloss:1.34699	validation-mlogloss:1.38760
[36m(train_xgb_ray_tune pid=524075)[0m [690]	train-mlogloss:1.34698	validation-mlogloss:1.38760
[36m(train_xgb_ray_tune pid=524081)[0m [563]	train-mlogloss:1.52375	validation-mlogloss:1.53552
[36m(train_xgb_ray_tune pid=524081)[0m [564]	train-mlogloss:1.52359	validation-mlogloss:1.53540
[36m(train_xgb_ray_tune pid=524046)[0m [709]	train-mlogloss:1.58667	validation-mlogloss:1.59225
[36m(train_xgb_ray_tune pid=524046)[0m [710]	train-mlogloss:1.58667	validation-mlogloss:1.59225
[36m(train_xgb_ray_tune pid=524046)[0m [711]	train-mlogloss:1.58662	validation-mlogloss:1.59221
[36m(train_xgb_ray_tune pid=524074)[0m [514]	train-mlogloss:1.97464	validation-mlogloss:1.95713
[36m(train_xgb_ray_tune pid=524074)[0m [515]	train-mlogloss:1.97388	validation-mlogloss:1.95634
[36m(train_xgb_ray_tune pid=524077)[0m [464]	train-mlogloss:1.25674	validation-mlogloss:1.34460
[36m(train_xgb_ray_tune pid=524077)[0m [465]	train-mlogloss:1.25663	validation-mlogloss:1.34448
[36m(train_xgb_ray_tune pid=524032)[0m [499]	train-mlogloss:1.43740	validation-mlogloss:1.46496
[36m(train_xgb_ray_tune pid=524032)[0m [500]	train-mlogloss:1.43719	validation-mlogloss:1.46479
[36m(train_xgb_ray_tune pid=524080)[0m [579]	train-mlogloss:1.25731	validation-mlogloss:1.34339
[36m(train_xgb_ray_tune pid=524080)[0m [580]	train-mlogloss:1.25726	validation-mlogloss:1.34338
[36m(train_xgb_ray_tune pid=524080)[0m [581]	train-mlogloss:1.25717	validation-mlogloss:1.34328
[36m(train_xgb_ray_tune pid=524075)[0m [691]	train-mlogloss:1.34694	validation-mlogloss:1.38754
[36m(train_xgb_ray_tune pid=524075)[0m [692]	train-mlogloss:1.34688	validation-mlogloss:1.38749
[36m(train_xgb_ray_tune pid=524075)[0m [693]	train-mlogloss:1.34686	validation-mlogloss:1.38750
[36m(train_xgb_ray_tune pid=524081)[0m [565]	train-mlogloss:1.52348	validation-mlogloss:1.53530
[36m(train_xgb_ray_tune pid=524081)[0m [566]	train-mlogloss:1.52335	validation-mlogloss:1.53519
[36m(train_xgb_ray_tune pid=524046)[0m [712]	train-mlogloss:1.58662	validation-mlogloss:1.59221
[36m(train_xgb_ray_tune pid=524046)[0m [713]	train-mlogloss:1.58662	validation-mlogloss:1.59221
[36m(train_xgb_ray_tune pid=524074)[0m [516]	train-mlogloss:1.97311	validation-mlogloss:1.95552
[36m(train_xgb_ray_tune pid=524074)[0m [517]	train-mlogloss:1.97234	validation-mlogloss:1.95474
[36m(train_xgb_ray_tune pid=524077)[0m [466]	train-mlogloss:1.25647	validation-mlogloss:1.34442
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[36m(train_xgb_ray_tune pid=524032)[0m [501]	train-mlogloss:1.43692	validation-mlogloss:1.46456
[36m(train_xgb_ray_tune pid=524032)[0m [502]	train-mlogloss:1.43668	validation-mlogloss:1.46432
[36m(train_xgb_ray_tune pid=524080)[0m [582]	train-mlogloss:1.25712	validation-mlogloss:1.34320
[36m(train_xgb_ray_tune pid=524080)[0m [583]	train-mlogloss:1.25712	validation-mlogloss:1.34320
[36m(train_xgb_ray_tune pid=524075)[0m [694]	train-mlogloss:1.34683	validation-mlogloss:1.38747
[36m(train_xgb_ray_tune pid=524075)[0m [695]	train-mlogloss:1.34676	validation-mlogloss:1.38746
[36m(train_xgb_ray_tune pid=524081)[0m [567]	train-mlogloss:1.52324	validation-mlogloss:1.53511
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[36m(train_xgb_ray_tune pid=524081)[0m [569]	train-mlogloss:1.52312	validation-mlogloss:1.53498
[36m(train_xgb_ray_tune pid=524046)[0m [714]	train-mlogloss:1.58657	validation-mlogloss:1.59217
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[36m(train_xgb_ray_tune pid=524046)[0m [716]	train-mlogloss:1.58657	validation-mlogloss:1.59217
[36m(train_xgb_ray_tune pid=524074)[0m [518]	train-mlogloss:1.97160	validation-mlogloss:1.95401
[36m(train_xgb_ray_tune pid=524074)[0m [519]	train-mlogloss:1.97080	validation-mlogloss:1.95325
[36m(train_xgb_ray_tune pid=524077)[0m [468]	train-mlogloss:1.25610	validation-mlogloss:1.34419
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[36m(train_xgb_ray_tune pid=524032)[0m [503]	train-mlogloss:1.43650	validation-mlogloss:1.46413
[36m(train_xgb_ray_tune pid=524032)[0m [504]	train-mlogloss:1.43625	validation-mlogloss:1.46386
[36m(train_xgb_ray_tune pid=524032)[0m [505]	train-mlogloss:1.43612	validation-mlogloss:1.46373
[36m(train_xgb_ray_tune pid=524080)[0m [584]	train-mlogloss:1.25710	validation-mlogloss:1.34318
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[36m(train_xgb_ray_tune pid=524080)[0m [586]	train-mlogloss:1.25685	validation-mlogloss:1.34300
[36m(train_xgb_ray_tune pid=524075)[0m [696]	train-mlogloss:1.34674	validation-mlogloss:1.38744
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[36m(train_xgb_ray_tune pid=524081)[0m [570]	train-mlogloss:1.52301	validation-mlogloss:1.53489
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[36m(train_xgb_ray_tune pid=524046)[0m [717]	train-mlogloss:1.58653	validation-mlogloss:1.59213
[36m(train_xgb_ray_tune pid=524074)[0m [520]	train-mlogloss:1.96999	validation-mlogloss:1.95244
[36m(train_xgb_ray_tune pid=524074)[0m [521]	train-mlogloss:1.96924	validation-mlogloss:1.95169
[36m(train_xgb_ray_tune pid=524077)[0m [470]	train-mlogloss:1.25567	validation-mlogloss:1.34377
[36m(train_xgb_ray_tune pid=524077)[0m [471]	train-mlogloss:1.25542	validation-mlogloss:1.34363
[36m(train_xgb_ray_tune pid=524032)[0m [506]	train-mlogloss:1.43583	validation-mlogloss:1.46345
[36m(train_xgb_ray_tune pid=524032)[0m [507]	train-mlogloss:1.43560	validation-mlogloss:1.46320
[36m(train_xgb_ray_tune pid=524080)[0m [587]	train-mlogloss:1.25685	validation-mlogloss:1.34301
[36m(train_xgb_ray_tune pid=524080)[0m [588]	train-mlogloss:1.25675	validation-mlogloss:1.34294
[36m(train_xgb_ray_tune pid=524075)[0m [699]	train-mlogloss:1.34660	validation-mlogloss:1.38734
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[36m(train_xgb_ray_tune pid=524081)[0m [572]	train-mlogloss:1.52275	validation-mlogloss:1.53463
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[36m(train_xgb_ray_tune pid=524081)[0m [574]	train-mlogloss:1.52251	validation-mlogloss:1.53442
[36m(train_xgb_ray_tune pid=524074)[0m [522]	train-mlogloss:1.96848	validation-mlogloss:1.95092
[36m(train_xgb_ray_tune pid=524074)[0m [523]	train-mlogloss:1.96767	validation-mlogloss:1.95013
[36m(train_xgb_ray_tune pid=524077)[0m [472]	train-mlogloss:1.25520	validation-mlogloss:1.34348
[36m(train_xgb_ray_tune pid=524077)[0m [473]	train-mlogloss:1.25486	validation-mlogloss:1.34325
[36m(train_xgb_ray_tune pid=524080)[0m [589]	train-mlogloss:1.25671	validation-mlogloss:1.34294
[36m(train_xgb_ray_tune pid=524032)[0m [508]	train-mlogloss:1.43536	validation-mlogloss:1.46300
[36m(train_xgb_ray_tune pid=524032)[0m [509]	train-mlogloss:1.43515	validation-mlogloss:1.46281
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[36m(train_xgb_ray_tune pid=524075)[0m [702]	train-mlogloss:1.34638	validation-mlogloss:1.38717
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[36m(train_xgb_ray_tune pid=524074)[0m [524]	train-mlogloss:1.96689	validation-mlogloss:1.94936
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[36m(train_xgb_ray_tune pid=524032)[0m [510]	train-mlogloss:1.43490	validation-mlogloss:1.46261
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[36m(train_xgb_ray_tune pid=524032)[0m [512]	train-mlogloss:1.43449	validation-mlogloss:1.46222
[36m(train_xgb_ray_tune pid=524080)[0m [592]	train-mlogloss:1.25646	validation-mlogloss:1.34287
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[36m(train_xgb_ray_tune pid=524075)[0m [704]	train-mlogloss:1.34634	validation-mlogloss:1.38712
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[36m(train_xgb_ray_tune pid=524074)[0m [525]	train-mlogloss:1.96613	validation-mlogloss:1.94863
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[36m(train_xgb_ray_tune pid=524077)[0m [477]	train-mlogloss:1.25442	validation-mlogloss:1.34290
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[36m(train_xgb_ray_tune pid=524032)[0m [513]	train-mlogloss:1.43426	validation-mlogloss:1.46201
[36m(train_xgb_ray_tune pid=524032)[0m [514]	train-mlogloss:1.43408	validation-mlogloss:1.46191
[36m(train_xgb_ray_tune pid=524080)[0m [595]	train-mlogloss:1.25615	validation-mlogloss:1.34272
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[36m(train_xgb_ray_tune pid=524075)[0m [707]	train-mlogloss:1.34627	validation-mlogloss:1.38711
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[36m(train_xgb_ray_tune pid=524077)[0m [479]	train-mlogloss:1.25412	validation-mlogloss:1.34275
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[36m(train_xgb_ray_tune pid=524075)[0m [710]	train-mlogloss:1.34625	validation-mlogloss:1.38709
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[36m(train_xgb_ray_tune pid=524074)[0m [529]	train-mlogloss:1.96317	validation-mlogloss:1.94561
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[36m(train_xgb_ray_tune pid=524077)[0m [481]	train-mlogloss:1.25393	validation-mlogloss:1.34265
[36m(train_xgb_ray_tune pid=524077)[0m [482]	train-mlogloss:1.25379	validation-mlogloss:1.34253
[36m(train_xgb_ray_tune pid=524077)[0m [483]	train-mlogloss:1.25362	validation-mlogloss:1.34239
[36m(train_xgb_ray_tune pid=524032)[0m [517]	train-mlogloss:1.43342	validation-mlogloss:1.46129
[36m(train_xgb_ray_tune pid=524032)[0m [518]	train-mlogloss:1.43325	validation-mlogloss:1.46108
[36m(train_xgb_ray_tune pid=524032)[0m [519]	train-mlogloss:1.43303	validation-mlogloss:1.46082
[36m(train_xgb_ray_tune pid=524080)[0m [600]	train-mlogloss:1.25595	validation-mlogloss:1.34266
[36m(train_xgb_ray_tune pid=524080)[0m [601]	train-mlogloss:1.25595	validation-mlogloss:1.34266
[36m(train_xgb_ray_tune pid=524075)[0m [712]	train-mlogloss:1.34621	validation-mlogloss:1.38706
[36m(train_xgb_ray_tune pid=524075)[0m [713]	train-mlogloss:1.34618	validation-mlogloss:1.38705
[36m(train_xgb_ray_tune pid=524075)[0m [714]	train-mlogloss:1.34618	validation-mlogloss:1.38705
[36m(train_xgb_ray_tune pid=524081)[0m [585]	train-mlogloss:1.52122	validation-mlogloss:1.53318
[36m(train_xgb_ray_tune pid=524081)[0m [586]	train-mlogloss:1.52107	validation-mlogloss:1.53305
[36m(train_xgb_ray_tune pid=524074)[0m [531]	train-mlogloss:1.96164	validation-mlogloss:1.94415
[36m(train_xgb_ray_tune pid=524077)[0m [484]	train-mlogloss:1.25345	validation-mlogloss:1.34224
[36m(train_xgb_ray_tune pid=524077)[0m [485]	train-mlogloss:1.25331	validation-mlogloss:1.34220
[36m(train_xgb_ray_tune pid=524080)[0m [602]	train-mlogloss:1.25590	validation-mlogloss:1.34263

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:40. Total running time: 1min 44s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             101.691 │
│ time_total_s                 101.691 │
│ training_iteration                 1 │
│ validation_accuracy          0.48696 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:40. Total running time: 1min 44s
[36m(train_xgb_ray_tune pid=524032)[0m [520]	train-mlogloss:1.43287	validation-mlogloss:1.46070
[36m(train_xgb_ray_tune pid=524032)[0m [521]	train-mlogloss:1.43267	validation-mlogloss:1.46052
[36m(train_xgb_ray_tune pid=524080)[0m [603]	train-mlogloss:1.25580	validation-mlogloss:1.34257
[36m(train_xgb_ray_tune pid=524080)[0m [604]	train-mlogloss:1.25578	validation-mlogloss:1.34257
[36m(train_xgb_ray_tune pid=524075)[0m [715]	train-mlogloss:1.34615	validation-mlogloss:1.38702
[36m(train_xgb_ray_tune pid=524075)[0m [716]	train-mlogloss:1.34612	validation-mlogloss:1.38702
[36m(train_xgb_ray_tune pid=524075)[0m [717]	train-mlogloss:1.34612	validation-mlogloss:1.38702
[36m(train_xgb_ray_tune pid=524081)[0m [587]	train-mlogloss:1.52097	validation-mlogloss:1.53299
[36m(train_xgb_ray_tune pid=524081)[0m [588]	train-mlogloss:1.52087	validation-mlogloss:1.53290
[36m(train_xgb_ray_tune pid=524081)[0m [589]	train-mlogloss:1.52078	validation-mlogloss:1.53282
[36m(train_xgb_ray_tune pid=524074)[0m [532]	train-mlogloss:1.96089	validation-mlogloss:1.94339
[36m(train_xgb_ray_tune pid=524074)[0m [533]	train-mlogloss:1.96017	validation-mlogloss:1.94271
[36m(train_xgb_ray_tune pid=524077)[0m [486]	train-mlogloss:1.25300	validation-mlogloss:1.34193
[36m(train_xgb_ray_tune pid=524077)[0m [487]	train-mlogloss:1.25268	validation-mlogloss:1.34180
[36m(train_xgb_ray_tune pid=524032)[0m [522]	train-mlogloss:1.43252	validation-mlogloss:1.46035
[36m(train_xgb_ray_tune pid=524032)[0m [523]	train-mlogloss:1.43228	validation-mlogloss:1.46014
[36m(train_xgb_ray_tune pid=524032)[0m [524]	train-mlogloss:1.43211	validation-mlogloss:1.46004
[36m(train_xgb_ray_tune pid=524080)[0m [605]	train-mlogloss:1.25571	validation-mlogloss:1.34248
[36m(train_xgb_ray_tune pid=524080)[0m [606]	train-mlogloss:1.25564	validation-mlogloss:1.34245
[36m(train_xgb_ray_tune pid=524080)[0m [607]	train-mlogloss:1.25555	validation-mlogloss:1.34241
[36m(train_xgb_ray_tune pid=524075)[0m [718]	train-mlogloss:1.34612	validation-mlogloss:1.38702
[36m(train_xgb_ray_tune pid=524075)[0m [719]	train-mlogloss:1.34610	validation-mlogloss:1.38702
[36m(train_xgb_ray_tune pid=524081)[0m [590]	train-mlogloss:1.52070	validation-mlogloss:1.53274
[36m(train_xgb_ray_tune pid=524081)[0m [591]	train-mlogloss:1.52053	validation-mlogloss:1.53258
[36m(train_xgb_ray_tune pid=524074)[0m [534]	train-mlogloss:1.95942	validation-mlogloss:1.94194
[36m(train_xgb_ray_tune pid=524074)[0m [535]	train-mlogloss:1.95863	validation-mlogloss:1.94120
[36m(train_xgb_ray_tune pid=524077)[0m [488]	train-mlogloss:1.25259	validation-mlogloss:1.34171
[36m(train_xgb_ray_tune pid=524077)[0m [489]	train-mlogloss:1.25232	validation-mlogloss:1.34157
[36m(train_xgb_ray_tune pid=524075)[0m [720]	train-mlogloss:1.34610	validation-mlogloss:1.38703
[36m(train_xgb_ray_tune pid=524032)[0m [525]	train-mlogloss:1.43188	validation-mlogloss:1.45982
[36m(train_xgb_ray_tune pid=524032)[0m [526]	train-mlogloss:1.43176	validation-mlogloss:1.45971
[36m(train_xgb_ray_tune pid=524080)[0m [608]	train-mlogloss:1.25553	validation-mlogloss:1.34241
[36m(train_xgb_ray_tune pid=524080)[0m [609]	train-mlogloss:1.25544	validation-mlogloss:1.34240
[36m(train_xgb_ray_tune pid=524080)[0m [610]	train-mlogloss:1.25536	validation-mlogloss:1.34232
[36m(train_xgb_ray_tune pid=524075)[0m [721]	train-mlogloss:1.34602	validation-mlogloss:1.38693
[36m(train_xgb_ray_tune pid=524075)[0m [722]	train-mlogloss:1.34602	validation-mlogloss:1.38693
[36m(train_xgb_ray_tune pid=524081)[0m [592]	train-mlogloss:1.52041	validation-mlogloss:1.53248
[36m(train_xgb_ray_tune pid=524081)[0m [593]	train-mlogloss:1.52022	validation-mlogloss:1.53235
[36m(train_xgb_ray_tune pid=524081)[0m [594]	train-mlogloss:1.52010	validation-mlogloss:1.53227
[36m(train_xgb_ray_tune pid=524074)[0m [536]	train-mlogloss:1.95789	validation-mlogloss:1.94045
[36m(train_xgb_ray_tune pid=524074)[0m [537]	train-mlogloss:1.95715	validation-mlogloss:1.93967
[36m(train_xgb_ray_tune pid=524077)[0m [490]	train-mlogloss:1.25217	validation-mlogloss:1.34143
[36m(train_xgb_ray_tune pid=524077)[0m [491]	train-mlogloss:1.25194	validation-mlogloss:1.34122
[36m(train_xgb_ray_tune pid=524077)[0m [492]	train-mlogloss:1.25186	validation-mlogloss:1.34119
[36m(train_xgb_ray_tune pid=524032)[0m [527]	train-mlogloss:1.43158	validation-mlogloss:1.45950
[36m(train_xgb_ray_tune pid=524032)[0m [528]	train-mlogloss:1.43139	validation-mlogloss:1.45933
[36m(train_xgb_ray_tune pid=524032)[0m [529]	train-mlogloss:1.43118	validation-mlogloss:1.45919
[36m(train_xgb_ray_tune pid=524080)[0m [611]	train-mlogloss:1.25536	validation-mlogloss:1.34232
[36m(train_xgb_ray_tune pid=524080)[0m [612]	train-mlogloss:1.25533	validation-mlogloss:1.34229
[36m(train_xgb_ray_tune pid=524080)[0m [613]	train-mlogloss:1.25532	validation-mlogloss:1.34228
[36m(train_xgb_ray_tune pid=524075)[0m [723]	train-mlogloss:1.34591	validation-mlogloss:1.38687
[36m(train_xgb_ray_tune pid=524075)[0m [724]	train-mlogloss:1.34587	validation-mlogloss:1.38688
[36m(train_xgb_ray_tune pid=524075)[0m [725]	train-mlogloss:1.34585	validation-mlogloss:1.38687
[36m(train_xgb_ray_tune pid=524081)[0m [595]	train-mlogloss:1.52000	validation-mlogloss:1.53217
[36m(train_xgb_ray_tune pid=524081)[0m [596]	train-mlogloss:1.51979	validation-mlogloss:1.53196
[36m(train_xgb_ray_tune pid=524081)[0m [597]	train-mlogloss:1.51972	validation-mlogloss:1.53192
[36m(train_xgb_ray_tune pid=524074)[0m [538]	train-mlogloss:1.95640	validation-mlogloss:1.93891
[36m(train_xgb_ray_tune pid=524074)[0m [539]	train-mlogloss:1.95571	validation-mlogloss:1.93817
[36m(train_xgb_ray_tune pid=524077)[0m [493]	train-mlogloss:1.25168	validation-mlogloss:1.34111
[36m(train_xgb_ray_tune pid=524077)[0m [494]	train-mlogloss:1.25157	validation-mlogloss:1.34098
[36m(train_xgb_ray_tune pid=524032)[0m [530]	train-mlogloss:1.43103	validation-mlogloss:1.45906
[36m(train_xgb_ray_tune pid=524032)[0m [531]	train-mlogloss:1.43087	validation-mlogloss:1.45890
[36m(train_xgb_ray_tune pid=524080)[0m [614]	train-mlogloss:1.25517	validation-mlogloss:1.34225
[36m(train_xgb_ray_tune pid=524080)[0m [615]	train-mlogloss:1.25511	validation-mlogloss:1.34222
[36m(train_xgb_ray_tune pid=524075)[0m [726]	train-mlogloss:1.34576	validation-mlogloss:1.38685
[36m(train_xgb_ray_tune pid=524075)[0m [727]	train-mlogloss:1.34574	validation-mlogloss:1.38685
[36m(train_xgb_ray_tune pid=524075)[0m [728]	train-mlogloss:1.34568	validation-mlogloss:1.38681
[36m(train_xgb_ray_tune pid=524081)[0m [598]	train-mlogloss:1.51966	validation-mlogloss:1.53187
[36m(train_xgb_ray_tune pid=524081)[0m [599]	train-mlogloss:1.51959	validation-mlogloss:1.53182
[36m(train_xgb_ray_tune pid=524074)[0m [540]	train-mlogloss:1.95494	validation-mlogloss:1.93738
[36m(train_xgb_ray_tune pid=524074)[0m [541]	train-mlogloss:1.95415	validation-mlogloss:1.93660
[36m(train_xgb_ray_tune pid=524077)[0m [495]	train-mlogloss:1.25146	validation-mlogloss:1.34097
[36m(train_xgb_ray_tune pid=524077)[0m [496]	train-mlogloss:1.25129	validation-mlogloss:1.34083
[36m(train_xgb_ray_tune pid=524077)[0m [497]	train-mlogloss:1.25113	validation-mlogloss:1.34071
[36m(train_xgb_ray_tune pid=524080)[0m [616]	train-mlogloss:1.25509	validation-mlogloss:1.34220
[36m(train_xgb_ray_tune pid=524032)[0m [532]	train-mlogloss:1.43067	validation-mlogloss:1.45869
[36m(train_xgb_ray_tune pid=524032)[0m [533]	train-mlogloss:1.43050	validation-mlogloss:1.45852
[36m(train_xgb_ray_tune pid=524032)[0m [534]	train-mlogloss:1.43036	validation-mlogloss:1.45840
[36m(train_xgb_ray_tune pid=524080)[0m [617]	train-mlogloss:1.25508	validation-mlogloss:1.34221
[36m(train_xgb_ray_tune pid=524080)[0m [618]	train-mlogloss:1.25506	validation-mlogloss:1.34220
[36m(train_xgb_ray_tune pid=524075)[0m [729]	train-mlogloss:1.34564	validation-mlogloss:1.38680
[36m(train_xgb_ray_tune pid=524075)[0m [730]	train-mlogloss:1.34561	validation-mlogloss:1.38676
[36m(train_xgb_ray_tune pid=524081)[0m [600]	train-mlogloss:1.51945	validation-mlogloss:1.53171
[36m(train_xgb_ray_tune pid=524081)[0m [601]	train-mlogloss:1.51934	validation-mlogloss:1.53159
[36m(train_xgb_ray_tune pid=524081)[0m [602]	train-mlogloss:1.51921	validation-mlogloss:1.53150
[36m(train_xgb_ray_tune pid=524074)[0m [542]	train-mlogloss:1.95340	validation-mlogloss:1.93590
[36m(train_xgb_ray_tune pid=524074)[0m [543]	train-mlogloss:1.95268	validation-mlogloss:1.93521
[36m(train_xgb_ray_tune pid=524077)[0m [498]	train-mlogloss:1.25097	validation-mlogloss:1.34064
[36m(train_xgb_ray_tune pid=524077)[0m [499]	train-mlogloss:1.25083	validation-mlogloss:1.34052
[36m(train_xgb_ray_tune pid=524032)[0m [535]	train-mlogloss:1.43024	validation-mlogloss:1.45828
[36m(train_xgb_ray_tune pid=524032)[0m [536]	train-mlogloss:1.43012	validation-mlogloss:1.45814
[36m(train_xgb_ray_tune pid=524080)[0m [619]	train-mlogloss:1.25503	validation-mlogloss:1.34216
[36m(train_xgb_ray_tune pid=524080)[0m [620]	train-mlogloss:1.25500	validation-mlogloss:1.34212
[36m(train_xgb_ray_tune pid=524080)[0m [621]	train-mlogloss:1.25495	validation-mlogloss:1.34211
[36m(train_xgb_ray_tune pid=524075)[0m [731]	train-mlogloss:1.34556	validation-mlogloss:1.38672
[36m(train_xgb_ray_tune pid=524075)[0m [732]	train-mlogloss:1.34556	validation-mlogloss:1.38672
[36m(train_xgb_ray_tune pid=524075)[0m [733]	train-mlogloss:1.34556	validation-mlogloss:1.38672
[36m(train_xgb_ray_tune pid=524081)[0m [603]	train-mlogloss:1.51917	validation-mlogloss:1.53146
[36m(train_xgb_ray_tune pid=524081)[0m [604]	train-mlogloss:1.51910	validation-mlogloss:1.53141
[36m(train_xgb_ray_tune pid=524081)[0m [605]	train-mlogloss:1.51901	validation-mlogloss:1.53130
[36m(train_xgb_ray_tune pid=524074)[0m [544]	train-mlogloss:1.95199	validation-mlogloss:1.93450
[36m(train_xgb_ray_tune pid=524074)[0m [545]	train-mlogloss:1.95128	validation-mlogloss:1.93380
[36m(train_xgb_ray_tune pid=524077)[0m [500]	train-mlogloss:1.25063	validation-mlogloss:1.34041
[36m(train_xgb_ray_tune pid=524077)[0m [501]	train-mlogloss:1.25049	validation-mlogloss:1.34034
[36m(train_xgb_ray_tune pid=524077)[0m [502]	train-mlogloss:1.25039	validation-mlogloss:1.34032
[36m(train_xgb_ray_tune pid=524032)[0m [537]	train-mlogloss:1.42989	validation-mlogloss:1.45795
[36m(train_xgb_ray_tune pid=524032)[0m [538]	train-mlogloss:1.42973	validation-mlogloss:1.45778
[36m(train_xgb_ray_tune pid=524032)[0m [539]	train-mlogloss:1.42959	validation-mlogloss:1.45766
[36m(train_xgb_ray_tune pid=524080)[0m [622]	train-mlogloss:1.25487	validation-mlogloss:1.34201
[36m(train_xgb_ray_tune pid=524080)[0m [623]	train-mlogloss:1.25486	validation-mlogloss:1.34201
[36m(train_xgb_ray_tune pid=524080)[0m [624]	train-mlogloss:1.25480	validation-mlogloss:1.34197
[36m(train_xgb_ray_tune pid=524075)[0m [734]	train-mlogloss:1.34556	validation-mlogloss:1.38672
[36m(train_xgb_ray_tune pid=524075)[0m [735]	train-mlogloss:1.34554	validation-mlogloss:1.38669
[36m(train_xgb_ray_tune pid=524075)[0m [736]	train-mlogloss:1.34554	validation-mlogloss:1.38670
[36m(train_xgb_ray_tune pid=524081)[0m [606]	train-mlogloss:1.51888	validation-mlogloss:1.53120
[36m(train_xgb_ray_tune pid=524081)[0m [607]	train-mlogloss:1.51882	validation-mlogloss:1.53115
[36m(train_xgb_ray_tune pid=524074)[0m [546]	train-mlogloss:1.95056	validation-mlogloss:1.93308
[36m(train_xgb_ray_tune pid=524074)[0m [547]	train-mlogloss:1.94980	validation-mlogloss:1.93234
[36m(train_xgb_ray_tune pid=524077)[0m [503]	train-mlogloss:1.25027	validation-mlogloss:1.34021
[36m(train_xgb_ray_tune pid=524077)[0m [504]	train-mlogloss:1.25014	validation-mlogloss:1.34011
[36m(train_xgb_ray_tune pid=524081)[0m [608]	train-mlogloss:1.51870	validation-mlogloss:1.53105
[36m(train_xgb_ray_tune pid=524032)[0m [540]	train-mlogloss:1.42947	validation-mlogloss:1.45756
[36m(train_xgb_ray_tune pid=524032)[0m [541]	train-mlogloss:1.42933	validation-mlogloss:1.45743
[36m(train_xgb_ray_tune pid=524080)[0m [625]	train-mlogloss:1.25477	validation-mlogloss:1.34197
[36m(train_xgb_ray_tune pid=524080)[0m [626]	train-mlogloss:1.25473	validation-mlogloss:1.34192
[36m(train_xgb_ray_tune pid=524080)[0m [627]	train-mlogloss:1.25466	validation-mlogloss:1.34189
[36m(train_xgb_ray_tune pid=524075)[0m [737]	train-mlogloss:1.34550	validation-mlogloss:1.38662
[36m(train_xgb_ray_tune pid=524075)[0m [738]	train-mlogloss:1.34546	validation-mlogloss:1.38656
[36m(train_xgb_ray_tune pid=524075)[0m [739]	train-mlogloss:1.34541	validation-mlogloss:1.38656
[36m(train_xgb_ray_tune pid=524081)[0m [609]	train-mlogloss:1.51855	validation-mlogloss:1.53091
[36m(train_xgb_ray_tune pid=524081)[0m [610]	train-mlogloss:1.51848	validation-mlogloss:1.53085
[36m(train_xgb_ray_tune pid=524074)[0m [548]	train-mlogloss:1.94906	validation-mlogloss:1.93158
[36m(train_xgb_ray_tune pid=524074)[0m [549]	train-mlogloss:1.94834	validation-mlogloss:1.93086
[36m(train_xgb_ray_tune pid=524077)[0m [505]	train-mlogloss:1.24999	validation-mlogloss:1.34004
[36m(train_xgb_ray_tune pid=524077)[0m [506]	train-mlogloss:1.24995	validation-mlogloss:1.33999
[36m(train_xgb_ray_tune pid=524077)[0m [507]	train-mlogloss:1.24977	validation-mlogloss:1.33995
[36m(train_xgb_ray_tune pid=524032)[0m [542]	train-mlogloss:1.42909	validation-mlogloss:1.45723
[36m(train_xgb_ray_tune pid=524032)[0m [543]	train-mlogloss:1.42893	validation-mlogloss:1.45706
[36m(train_xgb_ray_tune pid=524032)[0m [544]	train-mlogloss:1.42876	validation-mlogloss:1.45694
[36m(train_xgb_ray_tune pid=524080)[0m [628]	train-mlogloss:1.25462	validation-mlogloss:1.34188
[36m(train_xgb_ray_tune pid=524080)[0m [629]	train-mlogloss:1.25462	validation-mlogloss:1.34188
[36m(train_xgb_ray_tune pid=524080)[0m [630]	train-mlogloss:1.25455	validation-mlogloss:1.34177
[36m(train_xgb_ray_tune pid=524075)[0m [740]	train-mlogloss:1.34541	validation-mlogloss:1.38656
[36m(train_xgb_ray_tune pid=524075)[0m [741]	train-mlogloss:1.34537	validation-mlogloss:1.38651
[36m(train_xgb_ray_tune pid=524075)[0m [742]	train-mlogloss:1.34535	validation-mlogloss:1.38648
[36m(train_xgb_ray_tune pid=524081)[0m [611]	train-mlogloss:1.51842	validation-mlogloss:1.53082
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[36m(train_xgb_ray_tune pid=524081)[0m [613]	train-mlogloss:1.51827	validation-mlogloss:1.53065
[36m(train_xgb_ray_tune pid=524074)[0m [550]	train-mlogloss:1.94759	validation-mlogloss:1.93008
[36m(train_xgb_ray_tune pid=524074)[0m [551]	train-mlogloss:1.94685	validation-mlogloss:1.92932
[36m(train_xgb_ray_tune pid=524077)[0m [508]	train-mlogloss:1.24963	validation-mlogloss:1.33986
[36m(train_xgb_ray_tune pid=524077)[0m [509]	train-mlogloss:1.24942	validation-mlogloss:1.33982
[36m(train_xgb_ray_tune pid=524032)[0m [545]	train-mlogloss:1.42859	validation-mlogloss:1.45680
[36m(train_xgb_ray_tune pid=524032)[0m [546]	train-mlogloss:1.42842	validation-mlogloss:1.45666
[36m(train_xgb_ray_tune pid=524080)[0m [631]	train-mlogloss:1.25450	validation-mlogloss:1.34174
[36m(train_xgb_ray_tune pid=524080)[0m [632]	train-mlogloss:1.25448	validation-mlogloss:1.34174
[36m(train_xgb_ray_tune pid=524075)[0m [743]	train-mlogloss:1.34535	validation-mlogloss:1.38649
[36m(train_xgb_ray_tune pid=524075)[0m [744]	train-mlogloss:1.34533	validation-mlogloss:1.38646
[36m(train_xgb_ray_tune pid=524075)[0m [745]	train-mlogloss:1.34528	validation-mlogloss:1.38646
[36m(train_xgb_ray_tune pid=524081)[0m [614]	train-mlogloss:1.51813	validation-mlogloss:1.53054
[36m(train_xgb_ray_tune pid=524081)[0m [615]	train-mlogloss:1.51812	validation-mlogloss:1.53052
[36m(train_xgb_ray_tune pid=524081)[0m [616]	train-mlogloss:1.51797	validation-mlogloss:1.53043
[36m(train_xgb_ray_tune pid=524074)[0m [552]	train-mlogloss:1.94605	validation-mlogloss:1.92853
[36m(train_xgb_ray_tune pid=524074)[0m [553]	train-mlogloss:1.94529	validation-mlogloss:1.92777
[36m(train_xgb_ray_tune pid=524077)[0m [510]	train-mlogloss:1.24926	validation-mlogloss:1.33971
[36m(train_xgb_ray_tune pid=524077)[0m [511]	train-mlogloss:1.24910	validation-mlogloss:1.33966
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[36m(train_xgb_ray_tune pid=524077)[0m [512]	train-mlogloss:1.24897	validation-mlogloss:1.33960
[36m(train_xgb_ray_tune pid=524032)[0m [547]	train-mlogloss:1.42828	validation-mlogloss:1.45653
[36m(train_xgb_ray_tune pid=524032)[0m [548]	train-mlogloss:1.42810	validation-mlogloss:1.45632
[36m(train_xgb_ray_tune pid=524032)[0m [549]	train-mlogloss:1.42799	validation-mlogloss:1.45620
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[36m(train_xgb_ray_tune pid=524032)[0m [551]	train-mlogloss:1.42753	validation-mlogloss:1.45573
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[36m(train_xgb_ray_tune pid=524075)[0m [749]	train-mlogloss:1.34516	validation-mlogloss:1.38632
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[36m(train_xgb_ray_tune pid=524081)[0m [621]	train-mlogloss:1.51756	validation-mlogloss:1.53012
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[36m(train_xgb_ray_tune pid=524075)[0m [751]	train-mlogloss:1.34508	validation-mlogloss:1.38628
[36m(train_xgb_ray_tune pid=524075)[0m [752]	train-mlogloss:1.34508	validation-mlogloss:1.38628
[36m(train_xgb_ray_tune pid=524075)[0m [753]	train-mlogloss:1.34508	validation-mlogloss:1.38628
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[36m(train_xgb_ray_tune pid=524032)[0m [555]	train-mlogloss:1.42686	validation-mlogloss:1.45508
[36m(train_xgb_ray_tune pid=524032)[0m [556]	train-mlogloss:1.42669	validation-mlogloss:1.45492
[36m(train_xgb_ray_tune pid=524080)[0m [643]	train-mlogloss:1.25417	validation-mlogloss:1.34147
[36m(train_xgb_ray_tune pid=524080)[0m [644]	train-mlogloss:1.25414	validation-mlogloss:1.34142
[36m(train_xgb_ray_tune pid=524075)[0m [754]	train-mlogloss:1.34508	validation-mlogloss:1.38628
[36m(train_xgb_ray_tune pid=524075)[0m [755]	train-mlogloss:1.34508	validation-mlogloss:1.38628
[36m(train_xgb_ray_tune pid=524081)[0m [625]	train-mlogloss:1.51725	validation-mlogloss:1.52980
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[36m(train_xgb_ray_tune pid=524081)[0m [627]	train-mlogloss:1.51716	validation-mlogloss:1.52974
[36m(train_xgb_ray_tune pid=524074)[0m [560]	train-mlogloss:1.94038	validation-mlogloss:1.92280
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[36m(train_xgb_ray_tune pid=524077)[0m [520]	train-mlogloss:1.24805	validation-mlogloss:1.33899
[36m(train_xgb_ray_tune pid=524077)[0m [521]	train-mlogloss:1.24794	validation-mlogloss:1.33890
[36m(train_xgb_ray_tune pid=524077)[0m [522]	train-mlogloss:1.24780	validation-mlogloss:1.33881
[36m(train_xgb_ray_tune pid=524032)[0m [557]	train-mlogloss:1.42661	validation-mlogloss:1.45484
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[36m(train_xgb_ray_tune pid=524032)[0m [559]	train-mlogloss:1.42628	validation-mlogloss:1.45449
[36m(train_xgb_ray_tune pid=524080)[0m [646]	train-mlogloss:1.25398	validation-mlogloss:1.34122
[36m(train_xgb_ray_tune pid=524080)[0m [647]	train-mlogloss:1.25395	validation-mlogloss:1.34119
[36m(train_xgb_ray_tune pid=524081)[0m [628]	train-mlogloss:1.51713	validation-mlogloss:1.52970
[36m(train_xgb_ray_tune pid=524081)[0m [629]	train-mlogloss:1.51709	validation-mlogloss:1.52965
[36m(train_xgb_ray_tune pid=524081)[0m [630]	train-mlogloss:1.51703	validation-mlogloss:1.52959
[36m(train_xgb_ray_tune pid=524074)[0m [562]	train-mlogloss:1.93889	validation-mlogloss:1.92133
[36m(train_xgb_ray_tune pid=524074)[0m [563]	train-mlogloss:1.93817	validation-mlogloss:1.92059
[36m(train_xgb_ray_tune pid=524077)[0m [523]	train-mlogloss:1.24771	validation-mlogloss:1.33876
[36m(train_xgb_ray_tune pid=524077)[0m [524]	train-mlogloss:1.24758	validation-mlogloss:1.33868
[36m(train_xgb_ray_tune pid=524032)[0m [560]	train-mlogloss:1.42615	validation-mlogloss:1.45436
[36m(train_xgb_ray_tune pid=524075)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=524075)[0m   _log_deprecation_warning([32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=524032)[0m [561]	train-mlogloss:1.42601	validation-mlogloss:1.45426
[36m(train_xgb_ray_tune pid=524032)[0m [562]	train-mlogloss:1.42587	validation-mlogloss:1.45413
[36m(train_xgb_ray_tune pid=524080)[0m [648]	train-mlogloss:1.25388	validation-mlogloss:1.34112
[36m(train_xgb_ray_tune pid=524080)[0m [649]	train-mlogloss:1.25388	validation-mlogloss:1.34112
[36m(train_xgb_ray_tune pid=524080)[0m [650]	train-mlogloss:1.25383	validation-mlogloss:1.34112
[36m(train_xgb_ray_tune pid=524081)[0m [631]	train-mlogloss:1.51689	validation-mlogloss:1.52947
[36m(train_xgb_ray_tune pid=524081)[0m [632]	train-mlogloss:1.51681	validation-mlogloss:1.52937
[36m(train_xgb_ray_tune pid=524081)[0m [633]	train-mlogloss:1.51669	validation-mlogloss:1.52925
[36m(train_xgb_ray_tune pid=524074)[0m [564]	train-mlogloss:1.93744	validation-mlogloss:1.91989
[36m(train_xgb_ray_tune pid=524074)[0m [565]	train-mlogloss:1.93671	validation-mlogloss:1.91915
[36m(train_xgb_ray_tune pid=524077)[0m [525]	train-mlogloss:1.24742	validation-mlogloss:1.33858
[36m(train_xgb_ray_tune pid=524077)[0m [526]	train-mlogloss:1.24731	validation-mlogloss:1.33847
[36m(train_xgb_ray_tune pid=524077)[0m [527]	train-mlogloss:1.24719	validation-mlogloss:1.33850
[36m(train_xgb_ray_tune pid=524032)[0m [563]	train-mlogloss:1.42573	validation-mlogloss:1.45401
[36m(train_xgb_ray_tune pid=524032)[0m [564]	train-mlogloss:1.42560	validation-mlogloss:1.45389
[36m(train_xgb_ray_tune pid=524080)[0m [651]	train-mlogloss:1.25381	validation-mlogloss:1.34112
[36m(train_xgb_ray_tune pid=524080)[0m [652]	train-mlogloss:1.25370	validation-mlogloss:1.34107
[36m(train_xgb_ray_tune pid=524080)[0m [653]	train-mlogloss:1.25370	validation-mlogloss:1.34107
[36m(train_xgb_ray_tune pid=524081)[0m [634]	train-mlogloss:1.51667	validation-mlogloss:1.52924
[36m(train_xgb_ray_tune pid=524081)[0m [635]	train-mlogloss:1.51662	validation-mlogloss:1.52919
[36m(train_xgb_ray_tune pid=524074)[0m [566]	train-mlogloss:1.93602	validation-mlogloss:1.91845
[36m(train_xgb_ray_tune pid=524074)[0m [567]	train-mlogloss:1.93533	validation-mlogloss:1.91775
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[36m(train_xgb_ray_tune pid=524077)[0m [529]	train-mlogloss:1.24705	validation-mlogloss:1.33840
[36m(train_xgb_ray_tune pid=524081)[0m [636]	train-mlogloss:1.51661	validation-mlogloss:1.52919
[36m(train_xgb_ray_tune pid=524032)[0m [565]	train-mlogloss:1.42549	validation-mlogloss:1.45376
[36m(train_xgb_ray_tune pid=524032)[0m [566]	train-mlogloss:1.42535	validation-mlogloss:1.45364
[36m(train_xgb_ray_tune pid=524032)[0m [567]	train-mlogloss:1.42515	validation-mlogloss:1.45341
[36m(train_xgb_ray_tune pid=524080)[0m [654]	train-mlogloss:1.25362	validation-mlogloss:1.34101
[36m(train_xgb_ray_tune pid=524080)[0m [655]	train-mlogloss:1.25358	validation-mlogloss:1.34098
[36m(train_xgb_ray_tune pid=524080)[0m [656]	train-mlogloss:1.25352	validation-mlogloss:1.34094
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[36m(train_xgb_ray_tune pid=524074)[0m [569]	train-mlogloss:1.93391	validation-mlogloss:1.91632
[36m(train_xgb_ray_tune pid=524077)[0m [530]	train-mlogloss:1.24695	validation-mlogloss:1.33830
[36m(train_xgb_ray_tune pid=524077)[0m [531]	train-mlogloss:1.24668	validation-mlogloss:1.33811
[36m(train_xgb_ray_tune pid=524077)[0m [532]	train-mlogloss:1.24663	validation-mlogloss:1.33806
[36m(train_xgb_ray_tune pid=524032)[0m [568]	train-mlogloss:1.42496	validation-mlogloss:1.45320
[36m(train_xgb_ray_tune pid=524032)[0m [569]	train-mlogloss:1.42487	validation-mlogloss:1.45311
[36m(train_xgb_ray_tune pid=524080)[0m [657]	train-mlogloss:1.25351	validation-mlogloss:1.34094
[36m(train_xgb_ray_tune pid=524080)[0m [658]	train-mlogloss:1.25348	validation-mlogloss:1.34096
[36m(train_xgb_ray_tune pid=524080)[0m [659]	train-mlogloss:1.25344	validation-mlogloss:1.34094
[36m(train_xgb_ray_tune pid=524081)[0m [639]	train-mlogloss:1.51644	validation-mlogloss:1.52905
[36m(train_xgb_ray_tune pid=524081)[0m [640]	train-mlogloss:1.51639	validation-mlogloss:1.52902
[36m(train_xgb_ray_tune pid=524081)[0m [641]	train-mlogloss:1.51635	validation-mlogloss:1.52898
[36m(train_xgb_ray_tune pid=524074)[0m [570]	train-mlogloss:1.93319	validation-mlogloss:1.91560
[36m(train_xgb_ray_tune pid=524074)[0m [571]	train-mlogloss:1.93256	validation-mlogloss:1.91499
[36m(train_xgb_ray_tune pid=524077)[0m [533]	train-mlogloss:1.24647	validation-mlogloss:1.33797
[36m(train_xgb_ray_tune pid=524077)[0m [534]	train-mlogloss:1.24642	validation-mlogloss:1.33793
[36m(train_xgb_ray_tune pid=524032)[0m [570]	train-mlogloss:1.42466	validation-mlogloss:1.45295
[36m(train_xgb_ray_tune pid=524032)[0m [571]	train-mlogloss:1.42456	validation-mlogloss:1.45283
[36m(train_xgb_ray_tune pid=524032)[0m [572]	train-mlogloss:1.42436	validation-mlogloss:1.45267
[36m(train_xgb_ray_tune pid=524080)[0m [660]	train-mlogloss:1.25342	validation-mlogloss:1.34090
[36m(train_xgb_ray_tune pid=524080)[0m [661]	train-mlogloss:1.25337	validation-mlogloss:1.34088
[36m(train_xgb_ray_tune pid=524080)[0m [662]	train-mlogloss:1.25335	validation-mlogloss:1.34087
[36m(train_xgb_ray_tune pid=524081)[0m [642]	train-mlogloss:1.51626	validation-mlogloss:1.52889
[36m(train_xgb_ray_tune pid=524081)[0m [643]	train-mlogloss:1.51623	validation-mlogloss:1.52886
[36m(train_xgb_ray_tune pid=524081)[0m [644]	train-mlogloss:1.51620	validation-mlogloss:1.52882
[36m(train_xgb_ray_tune pid=524074)[0m [572]	train-mlogloss:1.93186	validation-mlogloss:1.91431
[36m(train_xgb_ray_tune pid=524074)[0m [573]	train-mlogloss:1.93115	validation-mlogloss:1.91360
[36m(train_xgb_ray_tune pid=524077)[0m [535]	train-mlogloss:1.24627	validation-mlogloss:1.33778
[36m(train_xgb_ray_tune pid=524077)[0m [536]	train-mlogloss:1.24620	validation-mlogloss:1.33778
[36m(train_xgb_ray_tune pid=524077)[0m [537]	train-mlogloss:1.24606	validation-mlogloss:1.33778

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:42. Total running time: 1min 47s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             104.065 │
│ time_total_s                 104.065 │
│ training_iteration                 1 │
│ validation_accuracy          0.53696 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:42. Total running time: 1min 47s
[36m(train_xgb_ray_tune pid=524032)[0m [573]	train-mlogloss:1.42426	validation-mlogloss:1.45255
[36m(train_xgb_ray_tune pid=524032)[0m [574]	train-mlogloss:1.42415	validation-mlogloss:1.45248
[36m(train_xgb_ray_tune pid=524032)[0m [575]	train-mlogloss:1.42399	validation-mlogloss:1.45238
[36m(train_xgb_ray_tune pid=524080)[0m [663]	train-mlogloss:1.25335	validation-mlogloss:1.34088
[36m(train_xgb_ray_tune pid=524080)[0m [664]	train-mlogloss:1.25328	validation-mlogloss:1.34083
[36m(train_xgb_ray_tune pid=524080)[0m [665]	train-mlogloss:1.25315	validation-mlogloss:1.34082
[36m(train_xgb_ray_tune pid=524081)[0m [645]	train-mlogloss:1.51619	validation-mlogloss:1.52881
[36m(train_xgb_ray_tune pid=524081)[0m [646]	train-mlogloss:1.51610	validation-mlogloss:1.52873
[36m(train_xgb_ray_tune pid=524081)[0m [647]	train-mlogloss:1.51605	validation-mlogloss:1.52868
[36m(train_xgb_ray_tune pid=524074)[0m [574]	train-mlogloss:1.93052	validation-mlogloss:1.91305
[36m(train_xgb_ray_tune pid=524074)[0m [575]	train-mlogloss:1.92981	validation-mlogloss:1.91238
[36m(train_xgb_ray_tune pid=524077)[0m [538]	train-mlogloss:1.24590	validation-mlogloss:1.33774
[36m(train_xgb_ray_tune pid=524077)[0m [539]	train-mlogloss:1.24575	validation-mlogloss:1.33764
[36m(train_xgb_ray_tune pid=524077)[0m [540]	train-mlogloss:1.24570	validation-mlogloss:1.33763
[36m(train_xgb_ray_tune pid=524032)[0m [576]	train-mlogloss:1.42388	validation-mlogloss:1.45227
[36m(train_xgb_ray_tune pid=524032)[0m [577]	train-mlogloss:1.42370	validation-mlogloss:1.45210
[36m(train_xgb_ray_tune pid=524032)[0m [578]	train-mlogloss:1.42362	validation-mlogloss:1.45201
[36m(train_xgb_ray_tune pid=524080)[0m [666]	train-mlogloss:1.25306	validation-mlogloss:1.34075
[36m(train_xgb_ray_tune pid=524080)[0m [667]	train-mlogloss:1.25299	validation-mlogloss:1.34070
[36m(train_xgb_ray_tune pid=524081)[0m [648]	train-mlogloss:1.51602	validation-mlogloss:1.52864
[36m(train_xgb_ray_tune pid=524081)[0m [649]	train-mlogloss:1.51592	validation-mlogloss:1.52856
[36m(train_xgb_ray_tune pid=524081)[0m [650]	train-mlogloss:1.51590	validation-mlogloss:1.52853
[36m(train_xgb_ray_tune pid=524074)[0m [576]	train-mlogloss:1.92908	validation-mlogloss:1.91162
[36m(train_xgb_ray_tune pid=524074)[0m [577]	train-mlogloss:1.92836	validation-mlogloss:1.91088
[36m(train_xgb_ray_tune pid=524077)[0m [541]	train-mlogloss:1.24558	validation-mlogloss:1.33753
[36m(train_xgb_ray_tune pid=524077)[0m [542]	train-mlogloss:1.24553	validation-mlogloss:1.33751
[36m(train_xgb_ray_tune pid=524032)[0m [579]	train-mlogloss:1.42351	validation-mlogloss:1.45190
[36m(train_xgb_ray_tune pid=524032)[0m [580]	train-mlogloss:1.42341	validation-mlogloss:1.45185
[36m(train_xgb_ray_tune pid=524080)[0m [668]	train-mlogloss:1.25293	validation-mlogloss:1.34066
[36m(train_xgb_ray_tune pid=524080)[0m [669]	train-mlogloss:1.25291	validation-mlogloss:1.34062
[36m(train_xgb_ray_tune pid=524080)[0m [670]	train-mlogloss:1.25288	validation-mlogloss:1.34062
[36m(train_xgb_ray_tune pid=524081)[0m [651]	train-mlogloss:1.51583	validation-mlogloss:1.52845
[36m(train_xgb_ray_tune pid=524081)[0m [652]	train-mlogloss:1.51580	validation-mlogloss:1.52843
[36m(train_xgb_ray_tune pid=524081)[0m [653]	train-mlogloss:1.51578	validation-mlogloss:1.52843
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[36m(train_xgb_ray_tune pid=524077)[0m [543]	train-mlogloss:1.24544	validation-mlogloss:1.33749
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[36m(train_xgb_ray_tune pid=524032)[0m [581]	train-mlogloss:1.42323	validation-mlogloss:1.45168
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[36m(train_xgb_ray_tune pid=524032)[0m [583]	train-mlogloss:1.42287	validation-mlogloss:1.45141
[36m(train_xgb_ray_tune pid=524080)[0m [671]	train-mlogloss:1.25285	validation-mlogloss:1.34063
[36m(train_xgb_ray_tune pid=524080)[0m [672]	train-mlogloss:1.25285	validation-mlogloss:1.34063
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[36m(train_xgb_ray_tune pid=524081)[0m [654]	train-mlogloss:1.51573	validation-mlogloss:1.52839
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[36m(train_xgb_ray_tune pid=524074)[0m [580]	train-mlogloss:1.92627	validation-mlogloss:1.90878
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[36m(train_xgb_ray_tune pid=524074)[0m [582]	train-mlogloss:1.92493	validation-mlogloss:1.90744
[36m(train_xgb_ray_tune pid=524077)[0m [546]	train-mlogloss:1.24507	validation-mlogloss:1.33726
[36m(train_xgb_ray_tune pid=524077)[0m [547]	train-mlogloss:1.24491	validation-mlogloss:1.33714
[36m(train_xgb_ray_tune pid=524077)[0m [548]	train-mlogloss:1.24487	validation-mlogloss:1.33709
[36m(train_xgb_ray_tune pid=524032)[0m [584]	train-mlogloss:1.42269	validation-mlogloss:1.45132
[36m(train_xgb_ray_tune pid=524032)[0m [585]	train-mlogloss:1.42251	validation-mlogloss:1.45118
[36m(train_xgb_ray_tune pid=524032)[0m [586]	train-mlogloss:1.42234	validation-mlogloss:1.45104
[36m(train_xgb_ray_tune pid=524080)[0m [674]	train-mlogloss:1.25279	validation-mlogloss:1.34055
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[36m(train_xgb_ray_tune pid=524080)[0m [676]	train-mlogloss:1.25265	validation-mlogloss:1.34045
[36m(train_xgb_ray_tune pid=524081)[0m [657]	train-mlogloss:1.51564	validation-mlogloss:1.52830
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[36m(train_xgb_ray_tune pid=524081)[0m [659]	train-mlogloss:1.51542	validation-mlogloss:1.52808
[36m(train_xgb_ray_tune pid=524074)[0m [583]	train-mlogloss:1.92428	validation-mlogloss:1.90683
[36m(train_xgb_ray_tune pid=524074)[0m [584]	train-mlogloss:1.92359	validation-mlogloss:1.90612
[36m(train_xgb_ray_tune pid=524077)[0m [549]	train-mlogloss:1.24473	validation-mlogloss:1.33691
[36m(train_xgb_ray_tune pid=524077)[0m [550]	train-mlogloss:1.24458	validation-mlogloss:1.33688
[36m(train_xgb_ray_tune pid=524032)[0m [587]	train-mlogloss:1.42222	validation-mlogloss:1.45095
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[36m(train_xgb_ray_tune pid=524032)[0m [589]	train-mlogloss:1.42199	validation-mlogloss:1.45078
[36m(train_xgb_ray_tune pid=524080)[0m [677]	train-mlogloss:1.25262	validation-mlogloss:1.34042
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[36m(train_xgb_ray_tune pid=524080)[0m [679]	train-mlogloss:1.25259	validation-mlogloss:1.34038
[36m(train_xgb_ray_tune pid=524081)[0m [660]	train-mlogloss:1.51533	validation-mlogloss:1.52802
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[36m(train_xgb_ray_tune pid=524081)[0m [662]	train-mlogloss:1.51527	validation-mlogloss:1.52798
[36m(train_xgb_ray_tune pid=524074)[0m [585]	train-mlogloss:1.92290	validation-mlogloss:1.90544
[36m(train_xgb_ray_tune pid=524074)[0m [586]	train-mlogloss:1.92222	validation-mlogloss:1.90481
[36m(train_xgb_ray_tune pid=524077)[0m [551]	train-mlogloss:1.24452	validation-mlogloss:1.33680
[36m(train_xgb_ray_tune pid=524077)[0m [552]	train-mlogloss:1.24446	validation-mlogloss:1.33672
[36m(train_xgb_ray_tune pid=524077)[0m [553]	train-mlogloss:1.24428	validation-mlogloss:1.33665
[36m(train_xgb_ray_tune pid=524032)[0m [590]	train-mlogloss:1.42188	validation-mlogloss:1.45069
[36m(train_xgb_ray_tune pid=524080)[0m [680]	train-mlogloss:1.25259	validation-mlogloss:1.34038
[36m(train_xgb_ray_tune pid=524080)[0m [681]	train-mlogloss:1.25250	validation-mlogloss:1.34031
[36m(train_xgb_ray_tune pid=524080)[0m [682]	train-mlogloss:1.25250	validation-mlogloss:1.34031
[36m(train_xgb_ray_tune pid=524081)[0m [663]	train-mlogloss:1.51527	validation-mlogloss:1.52798
[36m(train_xgb_ray_tune pid=524081)[0m [664]	train-mlogloss:1.51524	validation-mlogloss:1.52796
[36m(train_xgb_ray_tune pid=524081)[0m [665]	train-mlogloss:1.51519	validation-mlogloss:1.52790
[36m(train_xgb_ray_tune pid=524074)[0m [587]	train-mlogloss:1.92160	validation-mlogloss:1.90418
[36m(train_xgb_ray_tune pid=524074)[0m [588]	train-mlogloss:1.92097	validation-mlogloss:1.90358
[36m(train_xgb_ray_tune pid=524077)[0m [554]	train-mlogloss:1.24421	validation-mlogloss:1.33665
[36m(train_xgb_ray_tune pid=524077)[0m [555]	train-mlogloss:1.24404	validation-mlogloss:1.33664
[36m(train_xgb_ray_tune pid=524077)[0m [556]	train-mlogloss:1.24397	validation-mlogloss:1.33657
[36m(train_xgb_ray_tune pid=524080)[0m [683]	train-mlogloss:1.25243	validation-mlogloss:1.34029
[36m(train_xgb_ray_tune pid=524080)[0m [684]	train-mlogloss:1.25241	validation-mlogloss:1.34029
[36m(train_xgb_ray_tune pid=524080)[0m [685]	train-mlogloss:1.25237	validation-mlogloss:1.34025
[36m(train_xgb_ray_tune pid=524081)[0m [666]	train-mlogloss:1.51519	validation-mlogloss:1.52790
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[36m(train_xgb_ray_tune pid=524074)[0m [589]	train-mlogloss:1.92029	validation-mlogloss:1.90295
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[36m(train_xgb_ray_tune pid=524077)[0m [557]	train-mlogloss:1.24389	validation-mlogloss:1.33657
[36m(train_xgb_ray_tune pid=524077)[0m [558]	train-mlogloss:1.24370	validation-mlogloss:1.33651
[36m(train_xgb_ray_tune pid=524080)[0m [686]	train-mlogloss:1.25230	validation-mlogloss:1.34022
[36m(train_xgb_ray_tune pid=524080)[0m [687]	train-mlogloss:1.25229	validation-mlogloss:1.34022
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[36m(train_xgb_ray_tune pid=524074)[0m [591]	train-mlogloss:1.91905	validation-mlogloss:1.90171
[36m(train_xgb_ray_tune pid=524074)[0m [592]	train-mlogloss:1.91835	validation-mlogloss:1.90100
[36m(train_xgb_ray_tune pid=524077)[0m [559]	train-mlogloss:1.24364	validation-mlogloss:1.33639
[36m(train_xgb_ray_tune pid=524077)[0m [560]	train-mlogloss:1.24356	validation-mlogloss:1.33634
[36m(train_xgb_ray_tune pid=524077)[0m [561]	train-mlogloss:1.24351	validation-mlogloss:1.33636
[36m(train_xgb_ray_tune pid=524080)[0m [689]	train-mlogloss:1.25226	validation-mlogloss:1.34021
[36m(train_xgb_ray_tune pid=524080)[0m [690]	train-mlogloss:1.25222	validation-mlogloss:1.34019
[36m(train_xgb_ray_tune pid=524080)[0m [691]	train-mlogloss:1.25217	validation-mlogloss:1.34014
[36m(train_xgb_ray_tune pid=524081)[0m [672]	train-mlogloss:1.51489	validation-mlogloss:1.52765
[36m(train_xgb_ray_tune pid=524081)[0m [673]	train-mlogloss:1.51484	validation-mlogloss:1.52761
[36m(train_xgb_ray_tune pid=524081)[0m [674]	train-mlogloss:1.51482	validation-mlogloss:1.52762
[36m(train_xgb_ray_tune pid=524074)[0m [593]	train-mlogloss:1.91769	validation-mlogloss:1.90036
[36m(train_xgb_ray_tune pid=524074)[0m [594]	train-mlogloss:1.91702	validation-mlogloss:1.89967
[36m(train_xgb_ray_tune pid=524077)[0m [562]	train-mlogloss:1.24326	validation-mlogloss:1.33614
[36m(train_xgb_ray_tune pid=524077)[0m [563]	train-mlogloss:1.24317	validation-mlogloss:1.33610
[36m(train_xgb_ray_tune pid=524077)[0m [564]	train-mlogloss:1.24314	validation-mlogloss:1.33611
[36m(train_xgb_ray_tune pid=524080)[0m [692]	train-mlogloss:1.25213	validation-mlogloss:1.34010
[36m(train_xgb_ray_tune pid=524080)[0m [693]	train-mlogloss:1.25210	validation-mlogloss:1.34011
[36m(train_xgb_ray_tune pid=524080)[0m [694]	train-mlogloss:1.25202	validation-mlogloss:1.34005
[36m(train_xgb_ray_tune pid=524081)[0m [675]	train-mlogloss:1.51482	validation-mlogloss:1.52762
[36m(train_xgb_ray_tune pid=524081)[0m [676]	train-mlogloss:1.51474	validation-mlogloss:1.52753
[36m(train_xgb_ray_tune pid=524081)[0m [677]	train-mlogloss:1.51471	validation-mlogloss:1.52749
[36m(train_xgb_ray_tune pid=524074)[0m [595]	train-mlogloss:1.91637	validation-mlogloss:1.89902
[36m(train_xgb_ray_tune pid=524074)[0m [596]	train-mlogloss:1.91571	validation-mlogloss:1.89836
[36m(train_xgb_ray_tune pid=524077)[0m [565]	train-mlogloss:1.24309	validation-mlogloss:1.33606
[36m(train_xgb_ray_tune pid=524077)[0m [566]	train-mlogloss:1.24288	validation-mlogloss:1.33594
[36m(train_xgb_ray_tune pid=524077)[0m [567]	train-mlogloss:1.24281	validation-mlogloss:1.33594
[36m(train_xgb_ray_tune pid=524074)[0m [597]	train-mlogloss:1.91506	validation-mlogloss:1.89768

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:43. Total running time: 1min 48s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             105.112 │
│ time_total_s                 105.112 │
│ training_iteration                 1 │
│ validation_accuracy          0.51462 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:43. Total running time: 1min 48s
[36m(train_xgb_ray_tune pid=524080)[0m [695]	train-mlogloss:1.25199	validation-mlogloss:1.34001
[36m(train_xgb_ray_tune pid=524080)[0m [696]	train-mlogloss:1.25197	validation-mlogloss:1.33998
[36m(train_xgb_ray_tune pid=524080)[0m [697]	train-mlogloss:1.25196	validation-mlogloss:1.33996
[36m(train_xgb_ray_tune pid=524081)[0m [678]	train-mlogloss:1.51462	validation-mlogloss:1.52744
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[36m(train_xgb_ray_tune pid=524081)[0m [680]	train-mlogloss:1.51450	validation-mlogloss:1.52734
[36m(train_xgb_ray_tune pid=524074)[0m [598]	train-mlogloss:1.91445	validation-mlogloss:1.89703
[36m(train_xgb_ray_tune pid=524074)[0m [599]	train-mlogloss:1.91383	validation-mlogloss:1.89641
[36m(train_xgb_ray_tune pid=524077)[0m [568]	train-mlogloss:1.24267	validation-mlogloss:1.33578
[36m(train_xgb_ray_tune pid=524077)[0m [569]	train-mlogloss:1.24265	validation-mlogloss:1.33575
[36m(train_xgb_ray_tune pid=524080)[0m [698]	train-mlogloss:1.25192	validation-mlogloss:1.33992
[36m(train_xgb_ray_tune pid=524080)[0m [699]	train-mlogloss:1.25191	validation-mlogloss:1.33989
[36m(train_xgb_ray_tune pid=524080)[0m [700]	train-mlogloss:1.25191	validation-mlogloss:1.33989
[36m(train_xgb_ray_tune pid=524081)[0m [681]	train-mlogloss:1.51448	validation-mlogloss:1.52733
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[36m(train_xgb_ray_tune pid=524074)[0m [600]	train-mlogloss:1.91318	validation-mlogloss:1.89577
[36m(train_xgb_ray_tune pid=524074)[0m [601]	train-mlogloss:1.91251	validation-mlogloss:1.89508
[36m(train_xgb_ray_tune pid=524077)[0m [570]	train-mlogloss:1.24260	validation-mlogloss:1.33570
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[36m(train_xgb_ray_tune pid=524081)[0m [684]	train-mlogloss:1.51433	validation-mlogloss:1.52719
[36m(train_xgb_ray_tune pid=524080)[0m [701]	train-mlogloss:1.25189	validation-mlogloss:1.33987
[36m(train_xgb_ray_tune pid=524080)[0m [702]	train-mlogloss:1.25189	validation-mlogloss:1.33987
[36m(train_xgb_ray_tune pid=524080)[0m [703]	train-mlogloss:1.25189	validation-mlogloss:1.33987
[36m(train_xgb_ray_tune pid=524081)[0m [685]	train-mlogloss:1.51423	validation-mlogloss:1.52711
[36m(train_xgb_ray_tune pid=524081)[0m [686]	train-mlogloss:1.51419	validation-mlogloss:1.52708
[36m(train_xgb_ray_tune pid=524081)[0m [687]	train-mlogloss:1.51418	validation-mlogloss:1.52708
[36m(train_xgb_ray_tune pid=524074)[0m [602]	train-mlogloss:1.91185	validation-mlogloss:1.89441
[36m(train_xgb_ray_tune pid=524074)[0m [603]	train-mlogloss:1.91127	validation-mlogloss:1.89382
[36m(train_xgb_ray_tune pid=524077)[0m [573]	train-mlogloss:1.24211	validation-mlogloss:1.33556
[36m(train_xgb_ray_tune pid=524077)[0m [574]	train-mlogloss:1.24207	validation-mlogloss:1.33554
[36m(train_xgb_ray_tune pid=524077)[0m [575]	train-mlogloss:1.24199	validation-mlogloss:1.33552
[36m(train_xgb_ray_tune pid=524080)[0m [704]	train-mlogloss:1.25189	validation-mlogloss:1.33987
[36m(train_xgb_ray_tune pid=524080)[0m [705]	train-mlogloss:1.25187	validation-mlogloss:1.33988
[36m(train_xgb_ray_tune pid=524080)[0m [706]	train-mlogloss:1.25183	validation-mlogloss:1.33984
[36m(train_xgb_ray_tune pid=524080)[0m [707]	train-mlogloss:1.25181	validation-mlogloss:1.33985
[36m(train_xgb_ray_tune pid=524081)[0m [688]	train-mlogloss:1.51416	validation-mlogloss:1.52707
[36m(train_xgb_ray_tune pid=524081)[0m [689]	train-mlogloss:1.51410	validation-mlogloss:1.52705
[36m(train_xgb_ray_tune pid=524081)[0m [690]	train-mlogloss:1.51410	validation-mlogloss:1.52705
[36m(train_xgb_ray_tune pid=524074)[0m [604]	train-mlogloss:1.91068	validation-mlogloss:1.89321
[36m(train_xgb_ray_tune pid=524074)[0m [605]	train-mlogloss:1.91002	validation-mlogloss:1.89251
[36m(train_xgb_ray_tune pid=524077)[0m [576]	train-mlogloss:1.24196	validation-mlogloss:1.33547
[36m(train_xgb_ray_tune pid=524077)[0m [577]	train-mlogloss:1.24186	validation-mlogloss:1.33540
[36m(train_xgb_ray_tune pid=524077)[0m [578]	train-mlogloss:1.24174	validation-mlogloss:1.33533
[36m(train_xgb_ray_tune pid=524080)[0m [708]	train-mlogloss:1.25176	validation-mlogloss:1.33981
[36m(train_xgb_ray_tune pid=524080)[0m [709]	train-mlogloss:1.25173	validation-mlogloss:1.33980
[36m(train_xgb_ray_tune pid=524080)[0m [710]	train-mlogloss:1.25166	validation-mlogloss:1.33974
[36m(train_xgb_ray_tune pid=524081)[0m [691]	train-mlogloss:1.51404	validation-mlogloss:1.52702
[36m(train_xgb_ray_tune pid=524081)[0m [692]	train-mlogloss:1.51400	validation-mlogloss:1.52698
[36m(train_xgb_ray_tune pid=524081)[0m [693]	train-mlogloss:1.51393	validation-mlogloss:1.52689
[36m(train_xgb_ray_tune pid=524074)[0m [606]	train-mlogloss:1.90942	validation-mlogloss:1.89185
[36m(train_xgb_ray_tune pid=524074)[0m [607]	train-mlogloss:1.90879	validation-mlogloss:1.89125
[36m(train_xgb_ray_tune pid=524074)[0m [608]	train-mlogloss:1.90813	validation-mlogloss:1.89061
[36m(train_xgb_ray_tune pid=524077)[0m [579]	train-mlogloss:1.24158	validation-mlogloss:1.33525
[36m(train_xgb_ray_tune pid=524077)[0m [580]	train-mlogloss:1.24147	validation-mlogloss:1.33519
[36m(train_xgb_ray_tune pid=524077)[0m [581]	train-mlogloss:1.24134	validation-mlogloss:1.33515
[36m(train_xgb_ray_tune pid=524080)[0m [711]	train-mlogloss:1.25166	validation-mlogloss:1.33974
[36m(train_xgb_ray_tune pid=524080)[0m [712]	train-mlogloss:1.25166	validation-mlogloss:1.33974
[36m(train_xgb_ray_tune pid=524080)[0m [713]	train-mlogloss:1.25166	validation-mlogloss:1.33975
[36m(train_xgb_ray_tune pid=524081)[0m [694]	train-mlogloss:1.51387	validation-mlogloss:1.52684
[36m(train_xgb_ray_tune pid=524081)[0m [695]	train-mlogloss:1.51380	validation-mlogloss:1.52679
[36m(train_xgb_ray_tune pid=524081)[0m [696]	train-mlogloss:1.51374	validation-mlogloss:1.52672
[36m(train_xgb_ray_tune pid=524074)[0m [609]	train-mlogloss:1.90750	validation-mlogloss:1.89002
[36m(train_xgb_ray_tune pid=524074)[0m [610]	train-mlogloss:1.90683	validation-mlogloss:1.88937
[36m(train_xgb_ray_tune pid=524077)[0m [582]	train-mlogloss:1.24124	validation-mlogloss:1.33504
[36m(train_xgb_ray_tune pid=524077)[0m [583]	train-mlogloss:1.24116	validation-mlogloss:1.33498
[36m(train_xgb_ray_tune pid=524077)[0m [584]	train-mlogloss:1.24107	validation-mlogloss:1.33494
[36m(train_xgb_ray_tune pid=524081)[0m [697]	train-mlogloss:1.51373	validation-mlogloss:1.52671
[36m(train_xgb_ray_tune pid=524081)[0m [698]	train-mlogloss:1.51369	validation-mlogloss:1.52669
[36m(train_xgb_ray_tune pid=524081)[0m [699]	train-mlogloss:1.51368	validation-mlogloss:1.52669
[36m(train_xgb_ray_tune pid=524074)[0m [611]	train-mlogloss:1.90616	validation-mlogloss:1.88868
[36m(train_xgb_ray_tune pid=524074)[0m [612]	train-mlogloss:1.90554	validation-mlogloss:1.88806
[36m(train_xgb_ray_tune pid=524077)[0m [585]	train-mlogloss:1.24091	validation-mlogloss:1.33484
[36m(train_xgb_ray_tune pid=524077)[0m [586]	train-mlogloss:1.24088	validation-mlogloss:1.33483
[36m(train_xgb_ray_tune pid=524077)[0m [587]	train-mlogloss:1.24082	validation-mlogloss:1.33476
[36m(train_xgb_ray_tune pid=524081)[0m [700]	train-mlogloss:1.51362	validation-mlogloss:1.52666
[36m(train_xgb_ray_tune pid=524081)[0m [701]	train-mlogloss:1.51359	validation-mlogloss:1.52663
[36m(train_xgb_ray_tune pid=524081)[0m [702]	train-mlogloss:1.51353	validation-mlogloss:1.52658
[36m(train_xgb_ray_tune pid=524074)[0m [613]	train-mlogloss:1.90487	validation-mlogloss:1.88738
[36m(train_xgb_ray_tune pid=524074)[0m [614]	train-mlogloss:1.90425	validation-mlogloss:1.88677
[36m(train_xgb_ray_tune pid=524077)[0m [588]	train-mlogloss:1.24078	validation-mlogloss:1.33474
[36m(train_xgb_ray_tune pid=524077)[0m [589]	train-mlogloss:1.24069	validation-mlogloss:1.33468
[36m(train_xgb_ray_tune pid=524077)[0m [590]	train-mlogloss:1.24059	validation-mlogloss:1.33463
[36m(train_xgb_ray_tune pid=524081)[0m [703]	train-mlogloss:1.51346	validation-mlogloss:1.52651
[36m(train_xgb_ray_tune pid=524074)[0m [615]	train-mlogloss:1.90368	validation-mlogloss:1.88620
[36m(train_xgb_ray_tune pid=524081)[0m [704]	train-mlogloss:1.51339	validation-mlogloss:1.52641
[36m(train_xgb_ray_tune pid=524081)[0m [705]	train-mlogloss:1.51337	validation-mlogloss:1.52639
[36m(train_xgb_ray_tune pid=524081)[0m [706]	train-mlogloss:1.51332	validation-mlogloss:1.52634
[36m(train_xgb_ray_tune pid=524074)[0m [616]	train-mlogloss:1.90303	validation-mlogloss:1.88553
[36m(train_xgb_ray_tune pid=524074)[0m [617]	train-mlogloss:1.90240	validation-mlogloss:1.88492
[36m(train_xgb_ray_tune pid=524077)[0m [591]	train-mlogloss:1.24056	validation-mlogloss:1.33460
[36m(train_xgb_ray_tune pid=524077)[0m [592]	train-mlogloss:1.24047	validation-mlogloss:1.33449
[36m(train_xgb_ray_tune pid=524077)[0m [593]	train-mlogloss:1.24043	validation-mlogloss:1.33449
[36m(train_xgb_ray_tune pid=524081)[0m [707]	train-mlogloss:1.51327	validation-mlogloss:1.52627
[36m(train_xgb_ray_tune pid=524081)[0m [708]	train-mlogloss:1.51317	validation-mlogloss:1.52617
[36m(train_xgb_ray_tune pid=524081)[0m [709]	train-mlogloss:1.51315	validation-mlogloss:1.52614
[36m(train_xgb_ray_tune pid=524074)[0m [618]	train-mlogloss:1.90180	validation-mlogloss:1.88437
[36m(train_xgb_ray_tune pid=524074)[0m [619]	train-mlogloss:1.90119	validation-mlogloss:1.88379
[36m(train_xgb_ray_tune pid=524077)[0m [594]	train-mlogloss:1.24027	validation-mlogloss:1.33447
[36m(train_xgb_ray_tune pid=524077)[0m [595]	train-mlogloss:1.24016	validation-mlogloss:1.33442
[36m(train_xgb_ray_tune pid=524077)[0m [596]	train-mlogloss:1.24013	validation-mlogloss:1.33439
[36m(train_xgb_ray_tune pid=524081)[0m [710]	train-mlogloss:1.51311	validation-mlogloss:1.52610
[36m(train_xgb_ray_tune pid=524081)[0m [711]	train-mlogloss:1.51308	validation-mlogloss:1.52609
[36m(train_xgb_ray_tune pid=524081)[0m [712]	train-mlogloss:1.51303	validation-mlogloss:1.52604
[36m(train_xgb_ray_tune pid=524074)[0m [620]	train-mlogloss:1.90060	validation-mlogloss:1.88320
[36m(train_xgb_ray_tune pid=524074)[0m [621]	train-mlogloss:1.89997	validation-mlogloss:1.88256
[36m(train_xgb_ray_tune pid=524077)[0m [597]	train-mlogloss:1.24001	validation-mlogloss:1.33435
[36m(train_xgb_ray_tune pid=524081)[0m [713]	train-mlogloss:1.51301	validation-mlogloss:1.52602
[36m(train_xgb_ray_tune pid=524081)[0m [714]	train-mlogloss:1.51298	validation-mlogloss:1.52598
[36m(train_xgb_ray_tune pid=524081)[0m [715]	train-mlogloss:1.51298	validation-mlogloss:1.52598
[36m(train_xgb_ray_tune pid=524081)[0m [716]	train-mlogloss:1.51295	validation-mlogloss:1.52596
[36m(train_xgb_ray_tune pid=524074)[0m [622]	train-mlogloss:1.89935	validation-mlogloss:1.88198
[36m(train_xgb_ray_tune pid=524074)[0m [623]	train-mlogloss:1.89867	validation-mlogloss:1.88133
[36m(train_xgb_ray_tune pid=524074)[0m [624]	train-mlogloss:1.89804	validation-mlogloss:1.88070

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:45. Total running time: 1min 49s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             106.276 │
│ time_total_s                 106.276 │
│ training_iteration                 1 │
│ validation_accuracy             0.55 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:45. Total running time: 1min 49s
[36m(train_xgb_ray_tune pid=524081)[0m [717]	train-mlogloss:1.51293	validation-mlogloss:1.52594
[36m(train_xgb_ray_tune pid=524081)[0m [718]	train-mlogloss:1.51285	validation-mlogloss:1.52587
[36m(train_xgb_ray_tune pid=524081)[0m [719]	train-mlogloss:1.51280	validation-mlogloss:1.52585
[36m(train_xgb_ray_tune pid=524074)[0m [625]	train-mlogloss:1.89740	validation-mlogloss:1.88003
[36m(train_xgb_ray_tune pid=524074)[0m [626]	train-mlogloss:1.89684	validation-mlogloss:1.87950
[36m(train_xgb_ray_tune pid=524081)[0m [720]	train-mlogloss:1.51278	validation-mlogloss:1.52584
[36m(train_xgb_ray_tune pid=524081)[0m [721]	train-mlogloss:1.51275	validation-mlogloss:1.52581
[36m(train_xgb_ray_tune pid=524081)[0m [722]	train-mlogloss:1.51275	validation-mlogloss:1.52581
[36m(train_xgb_ray_tune pid=524074)[0m [627]	train-mlogloss:1.89623	validation-mlogloss:1.87893
[36m(train_xgb_ray_tune pid=524074)[0m [628]	train-mlogloss:1.89560	validation-mlogloss:1.87832
[36m(train_xgb_ray_tune pid=524081)[0m [723]	train-mlogloss:1.51269	validation-mlogloss:1.52577
[36m(train_xgb_ray_tune pid=524081)[0m [724]	train-mlogloss:1.51269	validation-mlogloss:1.52577
[36m(train_xgb_ray_tune pid=524081)[0m [725]	train-mlogloss:1.51266	validation-mlogloss:1.52574
[36m(train_xgb_ray_tune pid=524074)[0m [629]	train-mlogloss:1.89495	validation-mlogloss:1.87765
[36m(train_xgb_ray_tune pid=524074)[0m [630]	train-mlogloss:1.89431	validation-mlogloss:1.87702

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:45. Total running time: 1min 50s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             106.806 │
│ time_total_s                 106.806 │
│ training_iteration                 1 │
│ validation_accuracy          0.54209 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:45. Total running time: 1min 50s
[36m(train_xgb_ray_tune pid=524081)[0m [726]	train-mlogloss:1.51263	validation-mlogloss:1.52572
[36m(train_xgb_ray_tune pid=524081)[0m [727]	train-mlogloss:1.51259	validation-mlogloss:1.52568
[36m(train_xgb_ray_tune pid=524081)[0m [728]	train-mlogloss:1.51256	validation-mlogloss:1.52564
[36m(train_xgb_ray_tune pid=524081)[0m [729]	train-mlogloss:1.51256	validation-mlogloss:1.52564
[36m(train_xgb_ray_tune pid=524074)[0m [631]	train-mlogloss:1.89367	validation-mlogloss:1.87641
[36m(train_xgb_ray_tune pid=524074)[0m [632]	train-mlogloss:1.89301	validation-mlogloss:1.87575
[36m(train_xgb_ray_tune pid=524074)[0m [633]	train-mlogloss:1.89240	validation-mlogloss:1.87516
[36m(train_xgb_ray_tune pid=524081)[0m [730]	train-mlogloss:1.51254	validation-mlogloss:1.52562
[36m(train_xgb_ray_tune pid=524081)[0m [731]	train-mlogloss:1.51254	validation-mlogloss:1.52562
[36m(train_xgb_ray_tune pid=524081)[0m [732]	train-mlogloss:1.51251	validation-mlogloss:1.52562
[36m(train_xgb_ray_tune pid=524074)[0m [634]	train-mlogloss:1.89179	validation-mlogloss:1.87461
[36m(train_xgb_ray_tune pid=524074)[0m [635]	train-mlogloss:1.89116	validation-mlogloss:1.87403
[36m(train_xgb_ray_tune pid=524081)[0m [733]	train-mlogloss:1.51251	validation-mlogloss:1.52562
[36m(train_xgb_ray_tune pid=524081)[0m [734]	train-mlogloss:1.51245	validation-mlogloss:1.52556
[36m(train_xgb_ray_tune pid=524074)[0m [636]	train-mlogloss:1.89059	validation-mlogloss:1.87346
[36m(train_xgb_ray_tune pid=524074)[0m [637]	train-mlogloss:1.88992	validation-mlogloss:1.87286
[36m(train_xgb_ray_tune pid=524074)[0m [638]	train-mlogloss:1.88933	validation-mlogloss:1.87223
[36m(train_xgb_ray_tune pid=524074)[0m [639]	train-mlogloss:1.88869	validation-mlogloss:1.87163
[36m(train_xgb_ray_tune pid=524074)[0m [640]	train-mlogloss:1.88806	validation-mlogloss:1.87104
[36m(train_xgb_ray_tune pid=524074)[0m [641]	train-mlogloss:1.88750	validation-mlogloss:1.87046
[36m(train_xgb_ray_tune pid=524074)[0m [642]	train-mlogloss:1.88691	validation-mlogloss:1.86987
[36m(train_xgb_ray_tune pid=524074)[0m [643]	train-mlogloss:1.88626	validation-mlogloss:1.86927
[36m(train_xgb_ray_tune pid=524074)[0m [644]	train-mlogloss:1.88568	validation-mlogloss:1.86874
[36m(train_xgb_ray_tune pid=524074)[0m [645]	train-mlogloss:1.88506	validation-mlogloss:1.86815
[36m(train_xgb_ray_tune pid=524074)[0m [646]	train-mlogloss:1.88447	validation-mlogloss:1.86755
[36m(train_xgb_ray_tune pid=524074)[0m [647]	train-mlogloss:1.88389	validation-mlogloss:1.86703
[36m(train_xgb_ray_tune pid=524074)[0m [648]	train-mlogloss:1.88329	validation-mlogloss:1.86643
[36m(train_xgb_ray_tune pid=524074)[0m [649]	train-mlogloss:1.88267	validation-mlogloss:1.86581

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:46. Total running time: 1min 50s
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             107.522 │
│ time_total_s                 107.522 │
│ training_iteration                 1 │
│ validation_accuracy          0.50949 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:46. Total running time: 1min 50s
[36m(train_xgb_ray_tune pid=524074)[0m [650]	train-mlogloss:1.88206	validation-mlogloss:1.86523
[36m(train_xgb_ray_tune pid=524074)[0m [651]	train-mlogloss:1.88153	validation-mlogloss:1.86469
[36m(train_xgb_ray_tune pid=524074)[0m [652]	train-mlogloss:1.88096	validation-mlogloss:1.86411
[36m(train_xgb_ray_tune pid=524074)[0m [653]	train-mlogloss:1.88035	validation-mlogloss:1.86352
[36m(train_xgb_ray_tune pid=524074)[0m [654]	train-mlogloss:1.87972	validation-mlogloss:1.86289
[36m(train_xgb_ray_tune pid=524074)[0m [655]	train-mlogloss:1.87916	validation-mlogloss:1.86235
[36m(train_xgb_ray_tune pid=524074)[0m [656]	train-mlogloss:1.87858	validation-mlogloss:1.86177
[36m(train_xgb_ray_tune pid=524074)[0m [657]	train-mlogloss:1.87801	validation-mlogloss:1.86119
[36m(train_xgb_ray_tune pid=524074)[0m [658]	train-mlogloss:1.87750	validation-mlogloss:1.86069
[36m(train_xgb_ray_tune pid=524074)[0m [659]	train-mlogloss:1.87691	validation-mlogloss:1.86012
[36m(train_xgb_ray_tune pid=524074)[0m [660]	train-mlogloss:1.87637	validation-mlogloss:1.85959
[36m(train_xgb_ray_tune pid=524074)[0m [661]	train-mlogloss:1.87579	validation-mlogloss:1.85903
[36m(train_xgb_ray_tune pid=524074)[0m [662]	train-mlogloss:1.87524	validation-mlogloss:1.85845
[36m(train_xgb_ray_tune pid=524074)[0m [663]	train-mlogloss:1.87463	validation-mlogloss:1.85791
[36m(train_xgb_ray_tune pid=524074)[0m [664]	train-mlogloss:1.87406	validation-mlogloss:1.85732
[36m(train_xgb_ray_tune pid=524074)[0m [665]	train-mlogloss:1.87352	validation-mlogloss:1.85678
[36m(train_xgb_ray_tune pid=524074)[0m [666]	train-mlogloss:1.87293	validation-mlogloss:1.85620
[36m(train_xgb_ray_tune pid=524074)[0m [667]	train-mlogloss:1.87238	validation-mlogloss:1.85561
[36m(train_xgb_ray_tune pid=524074)[0m [668]	train-mlogloss:1.87187	validation-mlogloss:1.85516
[36m(train_xgb_ray_tune pid=524074)[0m [669]	train-mlogloss:1.87126	validation-mlogloss:1.85454
[36m(train_xgb_ray_tune pid=524074)[0m [670]	train-mlogloss:1.87076	validation-mlogloss:1.85403
[36m(train_xgb_ray_tune pid=524074)[0m [671]	train-mlogloss:1.87015	validation-mlogloss:1.85345
[36m(train_xgb_ray_tune pid=524074)[0m [672]	train-mlogloss:1.86956	validation-mlogloss:1.85289
[36m(train_xgb_ray_tune pid=524074)[0m [673]	train-mlogloss:1.86901	validation-mlogloss:1.85230
[36m(train_xgb_ray_tune pid=524074)[0m [674]	train-mlogloss:1.86847	validation-mlogloss:1.85175
[36m(train_xgb_ray_tune pid=524074)[0m [675]	train-mlogloss:1.86787	validation-mlogloss:1.85116
[36m(train_xgb_ray_tune pid=524074)[0m [676]	train-mlogloss:1.86740	validation-mlogloss:1.85070
[36m(train_xgb_ray_tune pid=524074)[0m [677]	train-mlogloss:1.86688	validation-mlogloss:1.85017
[36m(train_xgb_ray_tune pid=524074)[0m [678]	train-mlogloss:1.86632	validation-mlogloss:1.84964
[36m(train_xgb_ray_tune pid=524074)[0m [679]	train-mlogloss:1.86579	validation-mlogloss:1.84907
[36m(train_xgb_ray_tune pid=524074)[0m [680]	train-mlogloss:1.86527	validation-mlogloss:1.84858
[36m(train_xgb_ray_tune pid=524074)[0m [681]	train-mlogloss:1.86472	validation-mlogloss:1.84805
[36m(train_xgb_ray_tune pid=524074)[0m [682]	train-mlogloss:1.86413	validation-mlogloss:1.84747
[36m(train_xgb_ray_tune pid=524074)[0m [683]	train-mlogloss:1.86359	validation-mlogloss:1.84689
[36m(train_xgb_ray_tune pid=524074)[0m [684]	train-mlogloss:1.86297	validation-mlogloss:1.84629
[36m(train_xgb_ray_tune pid=524074)[0m [685]	train-mlogloss:1.86242	validation-mlogloss:1.84571
[36m(train_xgb_ray_tune pid=524074)[0m [686]	train-mlogloss:1.86184	validation-mlogloss:1.84511
[36m(train_xgb_ray_tune pid=524074)[0m [687]	train-mlogloss:1.86126	validation-mlogloss:1.84452
[36m(train_xgb_ray_tune pid=524074)[0m [688]	train-mlogloss:1.86076	validation-mlogloss:1.84399
[36m(train_xgb_ray_tune pid=524074)[0m [689]	train-mlogloss:1.86019	validation-mlogloss:1.84344
[36m(train_xgb_ray_tune pid=524074)[0m [690]	train-mlogloss:1.85963	validation-mlogloss:1.84292
[36m(train_xgb_ray_tune pid=524074)[0m [691]	train-mlogloss:1.85908	validation-mlogloss:1.84235
[36m(train_xgb_ray_tune pid=524074)[0m [692]	train-mlogloss:1.85851	validation-mlogloss:1.84178
[36m(train_xgb_ray_tune pid=524074)[0m [693]	train-mlogloss:1.85798	validation-mlogloss:1.84124
[36m(train_xgb_ray_tune pid=524074)[0m [694]	train-mlogloss:1.85743	validation-mlogloss:1.84067
[36m(train_xgb_ray_tune pid=524074)[0m [695]	train-mlogloss:1.85691	validation-mlogloss:1.84020
[36m(train_xgb_ray_tune pid=524074)[0m [696]	train-mlogloss:1.85642	validation-mlogloss:1.83966
[36m(train_xgb_ray_tune pid=524074)[0m [697]	train-mlogloss:1.85590	validation-mlogloss:1.83913
[36m(train_xgb_ray_tune pid=524074)[0m [698]	train-mlogloss:1.85542	validation-mlogloss:1.83867
[36m(train_xgb_ray_tune pid=524074)[0m [699]	train-mlogloss:1.85489	validation-mlogloss:1.83817
[36m(train_xgb_ray_tune pid=524074)[0m [700]	train-mlogloss:1.85441	validation-mlogloss:1.83771
[36m(train_xgb_ray_tune pid=524074)[0m [701]	train-mlogloss:1.85387	validation-mlogloss:1.83720
[36m(train_xgb_ray_tune pid=524074)[0m [702]	train-mlogloss:1.85335	validation-mlogloss:1.83671
[36m(train_xgb_ray_tune pid=524074)[0m [703]	train-mlogloss:1.85281	validation-mlogloss:1.83615
[36m(train_xgb_ray_tune pid=524074)[0m [704]	train-mlogloss:1.85234	validation-mlogloss:1.83570
[36m(train_xgb_ray_tune pid=524074)[0m [705]	train-mlogloss:1.85186	validation-mlogloss:1.83519
[36m(train_xgb_ray_tune pid=524074)[0m [706]	train-mlogloss:1.85132	validation-mlogloss:1.83462
[36m(train_xgb_ray_tune pid=524074)[0m [707]	train-mlogloss:1.85079	validation-mlogloss:1.83408
[36m(train_xgb_ray_tune pid=524074)[0m [708]	train-mlogloss:1.85023	validation-mlogloss:1.83353
[36m(train_xgb_ray_tune pid=524074)[0m [709]	train-mlogloss:1.84975	validation-mlogloss:1.83307
[36m(train_xgb_ray_tune pid=524074)[0m [710]	train-mlogloss:1.84920	validation-mlogloss:1.83251
[36m(train_xgb_ray_tune pid=524074)[0m [711]	train-mlogloss:1.84871	validation-mlogloss:1.83202
[36m(train_xgb_ray_tune pid=524074)[0m [712]	train-mlogloss:1.84819	validation-mlogloss:1.83148
[36m(train_xgb_ray_tune pid=524074)[0m [713]	train-mlogloss:1.84766	validation-mlogloss:1.83100
[36m(train_xgb_ray_tune pid=524074)[0m [714]	train-mlogloss:1.84719	validation-mlogloss:1.83054
[36m(train_xgb_ray_tune pid=524074)[0m [715]	train-mlogloss:1.84670	validation-mlogloss:1.83005
[36m(train_xgb_ray_tune pid=524074)[0m [716]	train-mlogloss:1.84616	validation-mlogloss:1.82950
[36m(train_xgb_ray_tune pid=524074)[0m [717]	train-mlogloss:1.84562	validation-mlogloss:1.82896
[36m(train_xgb_ray_tune pid=524074)[0m [718]	train-mlogloss:1.84509	validation-mlogloss:1.82841
[36m(train_xgb_ray_tune pid=524074)[0m [719]	train-mlogloss:1.84457	validation-mlogloss:1.82794
[36m(train_xgb_ray_tune pid=524074)[0m [720]	train-mlogloss:1.84403	validation-mlogloss:1.82741
[36m(train_xgb_ray_tune pid=524074)[0m [721]	train-mlogloss:1.84356	validation-mlogloss:1.82691
[36m(train_xgb_ray_tune pid=524074)[0m [722]	train-mlogloss:1.84310	validation-mlogloss:1.82644
[36m(train_xgb_ray_tune pid=524074)[0m [723]	train-mlogloss:1.84263	validation-mlogloss:1.82596
[36m(train_xgb_ray_tune pid=524074)[0m [724]	train-mlogloss:1.84217	validation-mlogloss:1.82546
[36m(train_xgb_ray_tune pid=524074)[0m [725]	train-mlogloss:1.84166	validation-mlogloss:1.82494
[36m(train_xgb_ray_tune pid=524074)[0m [726]	train-mlogloss:1.84118	validation-mlogloss:1.82444
[36m(train_xgb_ray_tune pid=524074)[0m [727]	train-mlogloss:1.84065	validation-mlogloss:1.82397
[36m(train_xgb_ray_tune pid=524074)[0m [728]	train-mlogloss:1.84017	validation-mlogloss:1.82347
[36m(train_xgb_ray_tune pid=524074)[0m [729]	train-mlogloss:1.83972	validation-mlogloss:1.82302
[36m(train_xgb_ray_tune pid=524074)[0m [730]	train-mlogloss:1.83925	validation-mlogloss:1.82256
[36m(train_xgb_ray_tune pid=524074)[0m [731]	train-mlogloss:1.83874	validation-mlogloss:1.82207
[36m(train_xgb_ray_tune pid=524074)[0m [732]	train-mlogloss:1.83821	validation-mlogloss:1.82157
[36m(train_xgb_ray_tune pid=524074)[0m [733]	train-mlogloss:1.83777	validation-mlogloss:1.82111
[36m(train_xgb_ray_tune pid=524074)[0m [734]	train-mlogloss:1.83726	validation-mlogloss:1.82061
[36m(train_xgb_ray_tune pid=524074)[0m [735]	train-mlogloss:1.83680	validation-mlogloss:1.82012
[36m(train_xgb_ray_tune pid=524074)[0m [736]	train-mlogloss:1.83636	validation-mlogloss:1.81969
[36m(train_xgb_ray_tune pid=524074)[0m [737]	train-mlogloss:1.83588	validation-mlogloss:1.81921
[36m(train_xgb_ray_tune pid=524074)[0m [738]	train-mlogloss:1.83536	validation-mlogloss:1.81869
[36m(train_xgb_ray_tune pid=524074)[0m [739]	train-mlogloss:1.83487	validation-mlogloss:1.81819
[36m(train_xgb_ray_tune pid=524074)[0m [740]	train-mlogloss:1.83443	validation-mlogloss:1.81775
[36m(train_xgb_ray_tune pid=524074)[0m [741]	train-mlogloss:1.83395	validation-mlogloss:1.81728
[36m(train_xgb_ray_tune pid=524074)[0m [742]	train-mlogloss:1.83349	validation-mlogloss:1.81682

Trial trial_815ce finished iteration 1 at 2025-10-27 11:14:50. Total running time: 1min 55s
2025-10-27 11:14:50,924	INFO tune.py:1009 -- Wrote the latest version of all result files and experiment state to '/mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_C/case_C_XGB_acc_gyr_17_classes/XGBoost_hyperparameters_tuning' in 0.0070s.
[36m(train_xgb_ray_tune pid=524074)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 5x across cluster][0m
[36m(train_xgb_ray_tune pid=524074)[0m   _log_deprecation_warning([32m [repeated 5x across cluster][0m
╭──────────────────────────────────────╮
│ Trial trial_815ce result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             112.013 │
│ time_total_s                 112.013 │
│ training_iteration                 1 │
│ validation_accuracy          0.46838 │
╰──────────────────────────────────────╯

Trial trial_815ce completed after 1 iterations at 2025-10-27 11:14:50. Total running time: 1min 55s

Trial status: 20 TERMINATED
Current time: 2025-10-27 11:14:50. Total running time: 1min 55s
Logical resource usage: 1.0/20 CPUs, 0/1 GPUs (0.0/1.0 accelerator_type:G)
╭────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ Trial name     status         num_boost_round     max_depth     learning_rate     subsample     colsample_bytree      gamma     min_child_weight     reg_alpha     reg_lambda     random_state     iter     total time (s)     validation_accuracy │
├────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ trial_815ce    TERMINATED                 591             3        0.0085005       0.528068             0.538545   27.6444                    84       2.77301        5.6084              9789        1           105.112                0.514625  │
│ trial_815ce    TERMINATED                 682             2        0.0146801       0.785254             0.713742   28.1164                   148     230.112          6.03871             4262        1            93.2442               0.414229  │
│ trial_815ce    TERMINATED                 291             2        0.0124667       0.824162             0.57164     5.27421                   62      12.8313       296.871               7779        1            69.7763               0.500593  │
│ trial_815ce    TERMINATED                 373             2        0.00615249      0.817785             0.660271   13.2957                   157      21.6249       164.981               7724        1            82.5157               0.478261  │
│ trial_815ce    TERMINATED                 718             3        0.0132957       0.580279             0.509772   29.263                    112      36.2913        67.778               6110        1           101.691                0.486957  │
│ trial_815ce    TERMINATED                 626             2        0.0197307       0.760867             0.834172   29.7125                    95     297.768         97.9173               518        1            70.9399               0.402767  │
│ trial_815ce    TERMINATED                 647             2        0.0191399       0.637997             0.641773   14.3746                   139      72.7003       158.825               5669        1           100.063                0.47668   │
│ trial_815ce    TERMINATED                 284             2        0.00785538      0.70404              0.765188   29.8994                   171       2.05829       32.3756              7624        1            68.5358               0.488538  │
│ trial_815ce    TERMINATED                 402             3        0.0183588       0.507052             0.829074    6.27376                   78      10.5642       623.61                7375        1            94.0104               0.512846  │
│ trial_815ce    TERMINATED                 756             2        0.0198547       0.539038             0.656365    9.29435                   97      16.981         42.2814              4597        1           104.065                0.536957  │
│ trial_815ce    TERMINATED                 743             3        0.00571989      0.512015             0.664965   21.0431                   119      20.2153       476.006               5012        1           112.013                0.468379  │
│ trial_815ce    TERMINATED                 445             2        0.011522        0.543758             0.820794   11.8266                   144       2.06773      886.585               5060        1            93.4895               0.470949  │
│ trial_815ce    TERMINATED                 714             3        0.0184111       0.611159             0.652786    8.01805                   76      15.9429        41.985                274        1           106.276                0.55      │
│ trial_815ce    TERMINATED                 735             2        0.0129654       0.753519             0.546044    7.53437                  109      77.9489       132.385               2413        1           107.522                0.509486  │
│ trial_815ce    TERMINATED                 789             3        0.0171509       0.536051             0.50909    24.0376                    63     939.294        903.31                3632        1             8.6632               0.0681818 │
│ trial_815ce    TERMINATED                 224             3        0.0188875       0.765795             0.63462    23.754                    147     293.798        248.333               8671        1            47.3779               0.404941  │
│ trial_815ce    TERMINATED                 467             3        0.019242        0.80582              0.523636   10.4785                   156      43.0216        47.2207              9252        1            94.5968               0.538142  │
│ trial_815ce    TERMINATED                 598             3        0.0135708       0.623241             0.761129   14.8588                    71       1.37779       20.6734              6349        1           106.806                0.542095  │
│ trial_815ce    TERMINATED                 567             2        0.00814755      0.728638             0.827736    9.36595                  126      57.4077        13.7875              8719        1            98.9537               0.516206  │
│ trial_815ce    TERMINATED                 217             2        0.0148705       0.565127             0.574846   24.1135                   101     145.722          6.90155             4616        1            47.8721               0.443083  │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Mejores hiperparámetros XGBoost: {'num_boost_round': 714, 'max_depth': 3, 'learning_rate': 0.018411099842392174, 'subsample': 0.6111587968233705, 'colsample_bytree': 0.6527861709892315, 'gamma': 8.018048111494604, 'min_child_weight': 76, 'reg_alpha': 15.942913979737185, 'reg_lambda': 41.985016118283546, 'random_state': 274}
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[38]	train-mlogloss:2.10148	validation-mlogloss:2.11643
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[40]	train-mlogloss:2.08151	validation-mlogloss:2.09707
[41]	train-mlogloss:2.07150	validation-mlogloss:2.08728
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[43]	train-mlogloss:2.05220	validation-mlogloss:2.06846
[44]	train-mlogloss:2.04274	validation-mlogloss:2.05933
[45]	train-mlogloss:2.03342	validation-mlogloss:2.05041
[46]	train-mlogloss:2.02415	validation-mlogloss:2.04147
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[49]	train-mlogloss:1.99765	validation-mlogloss:2.01618
[50]	train-mlogloss:1.98897	validation-mlogloss:2.00802
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[52]	train-mlogloss:1.97234	validation-mlogloss:1.99159
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[55]	train-mlogloss:1.94847	validation-mlogloss:1.96780
[56]	train-mlogloss:1.94060	validation-mlogloss:1.96010
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[58]	train-mlogloss:1.92577	validation-mlogloss:1.94614
[59]	train-mlogloss:1.91819	validation-mlogloss:1.93898
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[110]	train-mlogloss:1.64863	validation-mlogloss:1.67953
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[713]	train-mlogloss:1.25190	validation-mlogloss:1.33965
Saved model to disk.
2025-10-27 11:15:25.320142: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:15:25.332694: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560125.346470  528123 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560125.351089  528123 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560125.362193  528123 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560125.362219  528123 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560125.362222  528123 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560125.362225  528123 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:15:25.365647: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68475	validation-mlogloss:2.68530
[1]	train-mlogloss:2.66139	validation-mlogloss:2.66247
[2]	train-mlogloss:2.63947	validation-mlogloss:2.64016
[3]	train-mlogloss:2.61764	validation-mlogloss:2.61841
[4]	train-mlogloss:2.59652	validation-mlogloss:2.59737
[5]	train-mlogloss:2.57689	validation-mlogloss:2.57844
[6]	train-mlogloss:2.55683	validation-mlogloss:2.55917
[7]	train-mlogloss:2.53681	validation-mlogloss:2.53970
[8]	train-mlogloss:2.51789	validation-mlogloss:2.52081
[9]	train-mlogloss:2.49873	validation-mlogloss:2.50182
[10]	train-mlogloss:2.47997	validation-mlogloss:2.48335
[11]	train-mlogloss:2.46177	validation-mlogloss:2.46579
[12]	train-mlogloss:2.44447	validation-mlogloss:2.44922
[13]	train-mlogloss:2.42739	validation-mlogloss:2.43293
[14]	train-mlogloss:2.41042	validation-mlogloss:2.41657
[15]	train-mlogloss:2.39439	validation-mlogloss:2.40139
[16]	train-mlogloss:2.37902	validation-mlogloss:2.38608
[17]	train-mlogloss:2.36362	validation-mlogloss:2.37111
[18]	train-mlogloss:2.34848	validation-mlogloss:2.35655
[19]	train-mlogloss:2.33369	validation-mlogloss:2.34186
[20]	train-mlogloss:2.31937	validation-mlogloss:2.32839
[21]	train-mlogloss:2.30516	validation-mlogloss:2.31441
[22]	train-mlogloss:2.29115	validation-mlogloss:2.30094
[23]	train-mlogloss:2.27735	validation-mlogloss:2.28773
[24]	train-mlogloss:2.26357	validation-mlogloss:2.27433
[25]	train-mlogloss:2.25093	validation-mlogloss:2.26225
[26]	train-mlogloss:2.23789	validation-mlogloss:2.24918
[27]	train-mlogloss:2.22506	validation-mlogloss:2.23662
[28]	train-mlogloss:2.21233	validation-mlogloss:2.22454
[29]	train-mlogloss:2.20026	validation-mlogloss:2.21256
[30]	train-mlogloss:2.18880	validation-mlogloss:2.20159
[31]	train-mlogloss:2.17676	validation-mlogloss:2.18960
[32]	train-mlogloss:2.16513	validation-mlogloss:2.17800
[33]	train-mlogloss:2.15378	validation-mlogloss:2.16708
[34]	train-mlogloss:2.14289	validation-mlogloss:2.15687
[35]	train-mlogloss:2.13209	validation-mlogloss:2.14601
[36]	train-mlogloss:2.12141	validation-mlogloss:2.13575
[37]	train-mlogloss:2.11055	validation-mlogloss:2.12487
[38]	train-mlogloss:2.10017	validation-mlogloss:2.11517
[39]	train-mlogloss:2.09020	validation-mlogloss:2.10518
[40]	train-mlogloss:2.08020	validation-mlogloss:2.09529
[41]	train-mlogloss:2.07037	validation-mlogloss:2.08598
[42]	train-mlogloss:2.06062	validation-mlogloss:2.07658
[43]	train-mlogloss:2.05117	validation-mlogloss:2.06721
[44]	train-mlogloss:2.04177	validation-mlogloss:2.05823
[45]	train-mlogloss:2.03286	validation-mlogloss:2.04941
[46]	train-mlogloss:2.02376	validation-mlogloss:2.04051
[47]	train-mlogloss:2.01489	validation-mlogloss:2.03204
[48]	train-mlogloss:2.00619	validation-mlogloss:2.02375
[49]	train-mlogloss:1.99793	validation-mlogloss:2.01556
[50]	train-mlogloss:1.98904	validation-mlogloss:2.00697
[51]	train-mlogloss:1.98055	validation-mlogloss:1.99864
[52]	train-mlogloss:1.97255	validation-mlogloss:1.99105
[53]	train-mlogloss:1.96457	validation-mlogloss:1.98346
[54]	train-mlogloss:1.95630	validation-mlogloss:1.97550
[55]	train-mlogloss:1.94853	validation-mlogloss:1.96787
[56]	train-mlogloss:1.94057	validation-mlogloss:1.96022
[57]	train-mlogloss:1.93279	validation-mlogloss:1.95271
[58]	train-mlogloss:1.92514	validation-mlogloss:1.94509
[59]	train-mlogloss:1.91744	validation-mlogloss:1.93773
[60]	train-mlogloss:1.91000	validation-mlogloss:1.93067
[61]	train-mlogloss:1.90284	validation-mlogloss:1.92367
[62]	train-mlogloss:1.89553	validation-mlogloss:1.91648
[63]	train-mlogloss:1.88860	validation-mlogloss:1.91000
[64]	train-mlogloss:1.88155	validation-mlogloss:1.90349
[65]	train-mlogloss:1.87479	validation-mlogloss:1.89683
[66]	train-mlogloss:1.86799	validation-mlogloss:1.89009
[67]	train-mlogloss:1.86136	validation-mlogloss:1.88386
[68]	train-mlogloss:1.85501	validation-mlogloss:1.87771
[69]	train-mlogloss:1.84848	validation-mlogloss:1.87155
[70]	train-mlogloss:1.84209	validation-mlogloss:1.86552
[71]	train-mlogloss:1.83576	validation-mlogloss:1.85933
[72]	train-mlogloss:1.82993	validation-mlogloss:1.85368
[73]	train-mlogloss:1.82389	validation-mlogloss:1.84755
[74]	train-mlogloss:1.81773	validation-mlogloss:1.84200
[75]	train-mlogloss:1.81192	validation-mlogloss:1.83646
[76]	train-mlogloss:1.80608	validation-mlogloss:1.83081
[77]	train-mlogloss:1.80041	validation-mlogloss:1.82543
[78]	train-mlogloss:1.79470	validation-mlogloss:1.81990
[79]	train-mlogloss:1.78934	validation-mlogloss:1.81503
[80]	train-mlogloss:1.78388	validation-mlogloss:1.80987
[81]	train-mlogloss:1.77865	validation-mlogloss:1.80481
[82]	train-mlogloss:1.77339	validation-mlogloss:1.79962
[83]	train-mlogloss:1.76809	validation-mlogloss:1.79431
[84]	train-mlogloss:1.76286	validation-mlogloss:1.78899
[85]	train-mlogloss:1.75762	validation-mlogloss:1.78367
[86]	train-mlogloss:1.75265	validation-mlogloss:1.77898
[87]	train-mlogloss:1.74761	validation-mlogloss:1.77406
[88]	train-mlogloss:1.74262	validation-mlogloss:1.76918
[89]	train-mlogloss:1.73769	validation-mlogloss:1.76417
[90]	train-mlogloss:1.73305	validation-mlogloss:1.75948
[91]	train-mlogloss:1.72835	validation-mlogloss:1.75488
[92]	train-mlogloss:1.72356	validation-mlogloss:1.75015
[93]	train-mlogloss:1.71881	validation-mlogloss:1.74574
[94]	train-mlogloss:1.71411	validation-mlogloss:1.74085
[95]	train-mlogloss:1.70954	validation-mlogloss:1.73656
[96]	train-mlogloss:1.70515	validation-mlogloss:1.73227
[97]	train-mlogloss:1.70064	validation-mlogloss:1.72801
[98]	train-mlogloss:1.69627	validation-mlogloss:1.72382
[99]	train-mlogloss:1.69202	validation-mlogloss:1.71968
[100]	train-mlogloss:1.68787	validation-mlogloss:1.71546
[101]	train-mlogloss:1.68350	validation-mlogloss:1.71163
[102]	train-mlogloss:1.67936	validation-mlogloss:1.70759
[103]	train-mlogloss:1.67518	validation-mlogloss:1.70373
[104]	train-mlogloss:1.67111	validation-mlogloss:1.69979
[105]	train-mlogloss:1.66706	validation-mlogloss:1.69606
[106]	train-mlogloss:1.66312	validation-mlogloss:1.69244
[107]	train-mlogloss:1.65928	validation-mlogloss:1.68897
[108]	train-mlogloss:1.65550	validation-mlogloss:1.68545
[109]	train-mlogloss:1.65171	validation-mlogloss:1.68198
[110]	train-mlogloss:1.64803	validation-mlogloss:1.67849
[111]	train-mlogloss:1.64422	validation-mlogloss:1.67487
[112]	train-mlogloss:1.64048	validation-mlogloss:1.67145
[113]	train-mlogloss:1.63680	validation-mlogloss:1.66809
[114]	train-mlogloss:1.63311	validation-mlogloss:1.66470
[115]	train-mlogloss:1.62951	validation-mlogloss:1.66130
[116]	train-mlogloss:1.62578	validation-mlogloss:1.65787
[117]	train-mlogloss:1.62215	validation-mlogloss:1.65459
[118]	train-mlogloss:1.61864	validation-mlogloss:1.65118
[119]	train-mlogloss:1.61512	validation-mlogloss:1.64812
[120]	train-mlogloss:1.61169	validation-mlogloss:1.64489
[121]	train-mlogloss:1.60833	validation-mlogloss:1.64190
[122]	train-mlogloss:1.60507	validation-mlogloss:1.63883
[123]	train-mlogloss:1.60169	validation-mlogloss:1.63563
[124]	train-mlogloss:1.59830	validation-mlogloss:1.63217
[125]	train-mlogloss:1.59495	validation-mlogloss:1.62943
[126]	train-mlogloss:1.59173	validation-mlogloss:1.62643
[127]	train-mlogloss:1.58856	validation-mlogloss:1.62319
[128]	train-mlogloss:1.58546	validation-mlogloss:1.62014
[129]	train-mlogloss:1.58256	validation-mlogloss:1.61749
[130]	train-mlogloss:1.57963	validation-mlogloss:1.61474
[131]	train-mlogloss:1.57657	validation-mlogloss:1.61186
[132]	train-mlogloss:1.57360	validation-mlogloss:1.60916
[133]	train-mlogloss:1.57066	validation-mlogloss:1.60632
[134]	train-mlogloss:1.56763	validation-mlogloss:1.60346
[135]	train-mlogloss:1.56486	validation-mlogloss:1.60088
[136]	train-mlogloss:1.56198	validation-mlogloss:1.59840
[137]	train-mlogloss:1.55911	validation-mlogloss:1.59583
[138]	train-mlogloss:1.55645	validation-mlogloss:1.59334
[139]	train-mlogloss:1.55361	validation-mlogloss:1.59075
[140]	train-mlogloss:1.55086	validation-mlogloss:1.58826
[141]	train-mlogloss:1.54811	validation-mlogloss:1.58582
[142]	train-mlogloss:1.54540	validation-mlogloss:1.58331
[143]	train-mlogloss:1.54263	validation-mlogloss:1.58084
[144]	train-mlogloss:1.54002	validation-mlogloss:1.57819
[145]	train-mlogloss:1.53744	validation-mlogloss:1.57591
[146]	train-mlogloss:1.53481	validation-mlogloss:1.57349
[147]	train-mlogloss:1.53222	validation-mlogloss:1.57121
[148]	train-mlogloss:1.52966	validation-mlogloss:1.56891
[149]	train-mlogloss:1.52714	validation-mlogloss:1.56677
[150]	train-mlogloss:1.52481	validation-mlogloss:1.56462
[151]	train-mlogloss:1.52229	validation-mlogloss:1.56234
[152]	train-mlogloss:1.51975	validation-mlogloss:1.56007
[153]	train-mlogloss:1.51720	validation-mlogloss:1.55787
[154]	train-mlogloss:1.51483	validation-mlogloss:1.55589
[155]	train-mlogloss:1.51251	validation-mlogloss:1.55384
[156]	train-mlogloss:1.51020	validation-mlogloss:1.55169
[157]	train-mlogloss:1.50772	validation-mlogloss:1.54946
[158]	train-mlogloss:1.50549	validation-mlogloss:1.54744
[159]	train-mlogloss:1.50312	validation-mlogloss:1.54521
[160]	train-mlogloss:1.50078	validation-mlogloss:1.54301
[161]	train-mlogloss:1.49842	validation-mlogloss:1.54080
[162]	train-mlogloss:1.49627	validation-mlogloss:1.53883
[163]	train-mlogloss:1.49401	validation-mlogloss:1.53695
[164]	train-mlogloss:1.49179	validation-mlogloss:1.53509
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[186]	train-mlogloss:1.44912	validation-mlogloss:1.49673
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[188]	train-mlogloss:1.44549	validation-mlogloss:1.49352
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[191]	train-mlogloss:1.44032	validation-mlogloss:1.48882
[192]	train-mlogloss:1.43861	validation-mlogloss:1.48736
[193]	train-mlogloss:1.43689	validation-mlogloss:1.48582
[194]	train-mlogloss:1.43528	validation-mlogloss:1.48460
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[199]	train-mlogloss:1.42722	validation-mlogloss:1.47751
[200]	train-mlogloss:1.42563	validation-mlogloss:1.47609
[201]	train-mlogloss:1.42421	validation-mlogloss:1.47489
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[580]	train-mlogloss:1.25764	validation-mlogloss:1.34439
[581]	train-mlogloss:1.25758	validation-mlogloss:1.34440
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[663]	train-mlogloss:1.25384	validation-mlogloss:1.34201
[664]	train-mlogloss:1.25382	validation-mlogloss:1.34200
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[679]	train-mlogloss:1.25322	validation-mlogloss:1.34167
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[682]	train-mlogloss:1.25295	validation-mlogloss:1.34152
[683]	train-mlogloss:1.25294	validation-mlogloss:1.34151
[684]	train-mlogloss:1.25284	validation-mlogloss:1.34138
[685]	train-mlogloss:1.25281	validation-mlogloss:1.34138
[686]	train-mlogloss:1.25271	validation-mlogloss:1.34133
[687]	train-mlogloss:1.25271	validation-mlogloss:1.34133
[688]	train-mlogloss:1.25268	validation-mlogloss:1.34128
[689]	train-mlogloss:1.25268	validation-mlogloss:1.34128
[690]	train-mlogloss:1.25260	validation-mlogloss:1.34119
[691]	train-mlogloss:1.25255	validation-mlogloss:1.34115
[692]	train-mlogloss:1.25252	validation-mlogloss:1.34111
[693]	train-mlogloss:1.25251	validation-mlogloss:1.34108
[694]	train-mlogloss:1.25239	validation-mlogloss:1.34098
[695]	train-mlogloss:1.25235	validation-mlogloss:1.34095
[696]	train-mlogloss:1.25235	validation-mlogloss:1.34095
[697]	train-mlogloss:1.25229	validation-mlogloss:1.34093
[698]	train-mlogloss:1.25222	validation-mlogloss:1.34085
[699]	train-mlogloss:1.25222	validation-mlogloss:1.34085
[700]	train-mlogloss:1.25216	validation-mlogloss:1.34082
[701]	train-mlogloss:1.25215	validation-mlogloss:1.34081
[702]	train-mlogloss:1.25213	validation-mlogloss:1.34081
[703]	train-mlogloss:1.25209	validation-mlogloss:1.34079
[704]	train-mlogloss:1.25204	validation-mlogloss:1.34075
[705]	train-mlogloss:1.25196	validation-mlogloss:1.34071
[706]	train-mlogloss:1.25195	validation-mlogloss:1.34072
[707]	train-mlogloss:1.25189	validation-mlogloss:1.34069
[708]	train-mlogloss:1.25174	validation-mlogloss:1.34066
[709]	train-mlogloss:1.25170	validation-mlogloss:1.34064
[710]	train-mlogloss:1.25164	validation-mlogloss:1.34061
[711]	train-mlogloss:1.25157	validation-mlogloss:1.34060
[712]	train-mlogloss:1.25154	validation-mlogloss:1.34060
[713]	train-mlogloss:1.25154	validation-mlogloss:1.34060
Saved model to disk.
2025-10-27 11:16:12.343253: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:16:12.355849: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560172.369691  529033 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560172.373846  529033 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560172.385333  529033 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560172.385358  529033 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560172.385362  529033 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560172.385364  529033 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:16:12.388790: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
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[1]	train-mlogloss:2.66019	validation-mlogloss:2.66076
[2]	train-mlogloss:2.63769	validation-mlogloss:2.63866
[3]	train-mlogloss:2.61717	validation-mlogloss:2.61885
[4]	train-mlogloss:2.59576	validation-mlogloss:2.59780
[5]	train-mlogloss:2.57597	validation-mlogloss:2.57817
[6]	train-mlogloss:2.55508	validation-mlogloss:2.55774
[7]	train-mlogloss:2.53534	validation-mlogloss:2.53843
[8]	train-mlogloss:2.51613	validation-mlogloss:2.51904
[9]	train-mlogloss:2.49700	validation-mlogloss:2.50021
[10]	train-mlogloss:2.47899	validation-mlogloss:2.48267
[11]	train-mlogloss:2.46226	validation-mlogloss:2.46596
[12]	train-mlogloss:2.44446	validation-mlogloss:2.44873
[13]	train-mlogloss:2.42771	validation-mlogloss:2.43273
[14]	train-mlogloss:2.41157	validation-mlogloss:2.41716
[15]	train-mlogloss:2.39493	validation-mlogloss:2.40097
[16]	train-mlogloss:2.37925	validation-mlogloss:2.38602
[17]	train-mlogloss:2.36347	validation-mlogloss:2.37083
[18]	train-mlogloss:2.34789	validation-mlogloss:2.35542
[19]	train-mlogloss:2.33289	validation-mlogloss:2.34111
[20]	train-mlogloss:2.31794	validation-mlogloss:2.32625
[21]	train-mlogloss:2.30350	validation-mlogloss:2.31249
[22]	train-mlogloss:2.28973	validation-mlogloss:2.29899
[23]	train-mlogloss:2.27643	validation-mlogloss:2.28637
[24]	train-mlogloss:2.26285	validation-mlogloss:2.27322
[25]	train-mlogloss:2.24959	validation-mlogloss:2.26029
[26]	train-mlogloss:2.23654	validation-mlogloss:2.24769
[27]	train-mlogloss:2.22394	validation-mlogloss:2.23593
[28]	train-mlogloss:2.21150	validation-mlogloss:2.22372
[29]	train-mlogloss:2.19939	validation-mlogloss:2.21190
[30]	train-mlogloss:2.18768	validation-mlogloss:2.20073
[31]	train-mlogloss:2.17593	validation-mlogloss:2.18916
[32]	train-mlogloss:2.16461	validation-mlogloss:2.17824
[33]	train-mlogloss:2.15336	validation-mlogloss:2.16727
[34]	train-mlogloss:2.14227	validation-mlogloss:2.15692
[35]	train-mlogloss:2.13117	validation-mlogloss:2.14609
[36]	train-mlogloss:2.12062	validation-mlogloss:2.13627
[37]	train-mlogloss:2.11017	validation-mlogloss:2.12642
[38]	train-mlogloss:2.09980	validation-mlogloss:2.11587
[39]	train-mlogloss:2.08969	validation-mlogloss:2.10589
[40]	train-mlogloss:2.07951	validation-mlogloss:2.09592
[41]	train-mlogloss:2.06957	validation-mlogloss:2.08639
[42]	train-mlogloss:2.06022	validation-mlogloss:2.07737
[43]	train-mlogloss:2.05084	validation-mlogloss:2.06816
[44]	train-mlogloss:2.04155	validation-mlogloss:2.05927
[45]	train-mlogloss:2.03259	validation-mlogloss:2.05006
[46]	train-mlogloss:2.02350	validation-mlogloss:2.04185
[47]	train-mlogloss:2.01469	validation-mlogloss:2.03369
[48]	train-mlogloss:2.00602	validation-mlogloss:2.02502
[49]	train-mlogloss:1.99708	validation-mlogloss:2.01616
[50]	train-mlogloss:1.98864	validation-mlogloss:2.00781
[51]	train-mlogloss:1.98028	validation-mlogloss:1.99972
[52]	train-mlogloss:1.97203	validation-mlogloss:1.99200
[53]	train-mlogloss:1.96392	validation-mlogloss:1.98407
[54]	train-mlogloss:1.95600	validation-mlogloss:1.97617
[55]	train-mlogloss:1.94808	validation-mlogloss:1.96911
[56]	train-mlogloss:1.94050	validation-mlogloss:1.96169
[57]	train-mlogloss:1.93280	validation-mlogloss:1.95425
[58]	train-mlogloss:1.92502	validation-mlogloss:1.94668
[59]	train-mlogloss:1.91761	validation-mlogloss:1.93918
[60]	train-mlogloss:1.91032	validation-mlogloss:1.93212
[61]	train-mlogloss:1.90330	validation-mlogloss:1.92554
[62]	train-mlogloss:1.89623	validation-mlogloss:1.91884
[63]	train-mlogloss:1.88921	validation-mlogloss:1.91198
[64]	train-mlogloss:1.88224	validation-mlogloss:1.90550
[65]	train-mlogloss:1.87567	validation-mlogloss:1.89927
[66]	train-mlogloss:1.86924	validation-mlogloss:1.89295
[67]	train-mlogloss:1.86256	validation-mlogloss:1.88641
[68]	train-mlogloss:1.85619	validation-mlogloss:1.88025
[69]	train-mlogloss:1.84989	validation-mlogloss:1.87436
[70]	train-mlogloss:1.84351	validation-mlogloss:1.86831
[71]	train-mlogloss:1.83752	validation-mlogloss:1.86265
[72]	train-mlogloss:1.83133	validation-mlogloss:1.85642
[73]	train-mlogloss:1.82514	validation-mlogloss:1.85035
[74]	train-mlogloss:1.81909	validation-mlogloss:1.84435
[75]	train-mlogloss:1.81325	validation-mlogloss:1.83865
[76]	train-mlogloss:1.80746	validation-mlogloss:1.83299
[77]	train-mlogloss:1.80166	validation-mlogloss:1.82728
[78]	train-mlogloss:1.79624	validation-mlogloss:1.82195
[79]	train-mlogloss:1.79063	validation-mlogloss:1.81657
[80]	train-mlogloss:1.78512	validation-mlogloss:1.81112
[81]	train-mlogloss:1.77979	validation-mlogloss:1.80583
[82]	train-mlogloss:1.77445	validation-mlogloss:1.80100
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[84]	train-mlogloss:1.76383	validation-mlogloss:1.79056
[85]	train-mlogloss:1.75867	validation-mlogloss:1.78543
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[88]	train-mlogloss:1.74366	validation-mlogloss:1.77118
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[90]	train-mlogloss:1.73393	validation-mlogloss:1.76224
[91]	train-mlogloss:1.72920	validation-mlogloss:1.75786
[92]	train-mlogloss:1.72463	validation-mlogloss:1.75357
[93]	train-mlogloss:1.72004	validation-mlogloss:1.74894
[94]	train-mlogloss:1.71523	validation-mlogloss:1.74435
[95]	train-mlogloss:1.71068	validation-mlogloss:1.73984
[96]	train-mlogloss:1.70621	validation-mlogloss:1.73579
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[99]	train-mlogloss:1.69285	validation-mlogloss:1.72278
[100]	train-mlogloss:1.68866	validation-mlogloss:1.71865
[101]	train-mlogloss:1.68454	validation-mlogloss:1.71459
[102]	train-mlogloss:1.68040	validation-mlogloss:1.71056
[103]	train-mlogloss:1.67609	validation-mlogloss:1.70655
[104]	train-mlogloss:1.67190	validation-mlogloss:1.70268
[105]	train-mlogloss:1.66804	validation-mlogloss:1.69861
[106]	train-mlogloss:1.66391	validation-mlogloss:1.69471
[107]	train-mlogloss:1.65973	validation-mlogloss:1.69108
[108]	train-mlogloss:1.65582	validation-mlogloss:1.68744
[109]	train-mlogloss:1.65205	validation-mlogloss:1.68397
[110]	train-mlogloss:1.64840	validation-mlogloss:1.68058
[111]	train-mlogloss:1.64457	validation-mlogloss:1.67703
[112]	train-mlogloss:1.64079	validation-mlogloss:1.67328
[113]	train-mlogloss:1.63709	validation-mlogloss:1.66989
[114]	train-mlogloss:1.63351	validation-mlogloss:1.66677
[115]	train-mlogloss:1.62974	validation-mlogloss:1.66325
[116]	train-mlogloss:1.62609	validation-mlogloss:1.65990
[117]	train-mlogloss:1.62256	validation-mlogloss:1.65673
[118]	train-mlogloss:1.61905	validation-mlogloss:1.65339
[119]	train-mlogloss:1.61564	validation-mlogloss:1.65020
[120]	train-mlogloss:1.61232	validation-mlogloss:1.64728
[121]	train-mlogloss:1.60915	validation-mlogloss:1.64416
[122]	train-mlogloss:1.60579	validation-mlogloss:1.64102
[123]	train-mlogloss:1.60250	validation-mlogloss:1.63783
[124]	train-mlogloss:1.59930	validation-mlogloss:1.63501
[125]	train-mlogloss:1.59600	validation-mlogloss:1.63206
[126]	train-mlogloss:1.59286	validation-mlogloss:1.62903
[127]	train-mlogloss:1.58955	validation-mlogloss:1.62599
[128]	train-mlogloss:1.58648	validation-mlogloss:1.62292
[129]	train-mlogloss:1.58348	validation-mlogloss:1.61994
[130]	train-mlogloss:1.58069	validation-mlogloss:1.61731
[131]	train-mlogloss:1.57774	validation-mlogloss:1.61463
[132]	train-mlogloss:1.57480	validation-mlogloss:1.61173
[133]	train-mlogloss:1.57197	validation-mlogloss:1.60904
[134]	train-mlogloss:1.56905	validation-mlogloss:1.60627
[135]	train-mlogloss:1.56608	validation-mlogloss:1.60342
[136]	train-mlogloss:1.56321	validation-mlogloss:1.60064
[137]	train-mlogloss:1.56037	validation-mlogloss:1.59784
[138]	train-mlogloss:1.55741	validation-mlogloss:1.59506
[139]	train-mlogloss:1.55465	validation-mlogloss:1.59241
[140]	train-mlogloss:1.55210	validation-mlogloss:1.59021
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[564]	train-mlogloss:1.25897	validation-mlogloss:1.34477
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[664]	train-mlogloss:1.25456	validation-mlogloss:1.34175
[665]	train-mlogloss:1.25456	validation-mlogloss:1.34175
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[682]	train-mlogloss:1.25396	validation-mlogloss:1.34116
[683]	train-mlogloss:1.25393	validation-mlogloss:1.34112
[684]	train-mlogloss:1.25391	validation-mlogloss:1.34111
[685]	train-mlogloss:1.25391	validation-mlogloss:1.34111
[686]	train-mlogloss:1.25382	validation-mlogloss:1.34108
[687]	train-mlogloss:1.25379	validation-mlogloss:1.34105
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[689]	train-mlogloss:1.25357	validation-mlogloss:1.34089
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[691]	train-mlogloss:1.25353	validation-mlogloss:1.34088
[692]	train-mlogloss:1.25353	validation-mlogloss:1.34088
[693]	train-mlogloss:1.25353	validation-mlogloss:1.34088
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[695]	train-mlogloss:1.25351	validation-mlogloss:1.34089
[696]	train-mlogloss:1.25345	validation-mlogloss:1.34087
[697]	train-mlogloss:1.25340	validation-mlogloss:1.34084
[698]	train-mlogloss:1.25340	validation-mlogloss:1.34084
[699]	train-mlogloss:1.25338	validation-mlogloss:1.34084
[700]	train-mlogloss:1.25325	validation-mlogloss:1.34085
[701]	train-mlogloss:1.25322	validation-mlogloss:1.34083
[702]	train-mlogloss:1.25318	validation-mlogloss:1.34080
[703]	train-mlogloss:1.25316	validation-mlogloss:1.34080
[704]	train-mlogloss:1.25316	validation-mlogloss:1.34080
[705]	train-mlogloss:1.25316	validation-mlogloss:1.34080
[706]	train-mlogloss:1.25315	validation-mlogloss:1.34077
[707]	train-mlogloss:1.25303	validation-mlogloss:1.34069
[708]	train-mlogloss:1.25302	validation-mlogloss:1.34068
[709]	train-mlogloss:1.25297	validation-mlogloss:1.34064
[710]	train-mlogloss:1.25297	validation-mlogloss:1.34065
[711]	train-mlogloss:1.25295	validation-mlogloss:1.34064
[712]	train-mlogloss:1.25288	validation-mlogloss:1.34059
[713]	train-mlogloss:1.25283	validation-mlogloss:1.34054
Saved model to disk.
2025-10-27 11:16:59.357790: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:16:59.370493: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560219.384189  530012 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560219.388367  530012 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560219.399636  530012 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560219.399660  530012 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560219.399662  530012 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560219.399665  530012 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:16:59.403065: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68341	validation-mlogloss:2.68406
[1]	train-mlogloss:2.66043	validation-mlogloss:2.66186
[2]	train-mlogloss:2.63732	validation-mlogloss:2.63891
[3]	train-mlogloss:2.61648	validation-mlogloss:2.61900
[4]	train-mlogloss:2.59627	validation-mlogloss:2.59878
[5]	train-mlogloss:2.57529	validation-mlogloss:2.57856
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[609]	train-mlogloss:1.25561	validation-mlogloss:1.34275
[610]	train-mlogloss:1.25558	validation-mlogloss:1.34275
[611]	train-mlogloss:1.25555	validation-mlogloss:1.34275
[612]	train-mlogloss:1.25551	validation-mlogloss:1.34274
[613]	train-mlogloss:1.25550	validation-mlogloss:1.34271
[614]	train-mlogloss:1.25547	validation-mlogloss:1.34271
[615]	train-mlogloss:1.25534	validation-mlogloss:1.34262
[616]	train-mlogloss:1.25530	validation-mlogloss:1.34260
[617]	train-mlogloss:1.25530	validation-mlogloss:1.34260
[618]	train-mlogloss:1.25529	validation-mlogloss:1.34259
[619]	train-mlogloss:1.25527	validation-mlogloss:1.34257
[620]	train-mlogloss:1.25525	validation-mlogloss:1.34255
[621]	train-mlogloss:1.25514	validation-mlogloss:1.34246
[622]	train-mlogloss:1.25505	validation-mlogloss:1.34243
[623]	train-mlogloss:1.25494	validation-mlogloss:1.34235
[624]	train-mlogloss:1.25493	validation-mlogloss:1.34235
[625]	train-mlogloss:1.25488	validation-mlogloss:1.34234
[626]	train-mlogloss:1.25485	validation-mlogloss:1.34230
[627]	train-mlogloss:1.25482	validation-mlogloss:1.34226
[628]	train-mlogloss:1.25481	validation-mlogloss:1.34226
[629]	train-mlogloss:1.25472	validation-mlogloss:1.34221
[630]	train-mlogloss:1.25466	validation-mlogloss:1.34222
[631]	train-mlogloss:1.25455	validation-mlogloss:1.34216
[632]	train-mlogloss:1.25448	validation-mlogloss:1.34212
[633]	train-mlogloss:1.25443	validation-mlogloss:1.34214
[634]	train-mlogloss:1.25437	validation-mlogloss:1.34210
[635]	train-mlogloss:1.25433	validation-mlogloss:1.34207
[636]	train-mlogloss:1.25431	validation-mlogloss:1.34207
[637]	train-mlogloss:1.25424	validation-mlogloss:1.34201
[638]	train-mlogloss:1.25418	validation-mlogloss:1.34196
[639]	train-mlogloss:1.25410	validation-mlogloss:1.34186
[640]	train-mlogloss:1.25409	validation-mlogloss:1.34185
[641]	train-mlogloss:1.25408	validation-mlogloss:1.34185
[642]	train-mlogloss:1.25402	validation-mlogloss:1.34188
[643]	train-mlogloss:1.25401	validation-mlogloss:1.34185
[644]	train-mlogloss:1.25394	validation-mlogloss:1.34182
[645]	train-mlogloss:1.25394	validation-mlogloss:1.34182
[646]	train-mlogloss:1.25394	validation-mlogloss:1.34182
[647]	train-mlogloss:1.25387	validation-mlogloss:1.34178
[648]	train-mlogloss:1.25385	validation-mlogloss:1.34178
[649]	train-mlogloss:1.25385	validation-mlogloss:1.34178
[650]	train-mlogloss:1.25382	validation-mlogloss:1.34177
[651]	train-mlogloss:1.25370	validation-mlogloss:1.34172
[652]	train-mlogloss:1.25369	validation-mlogloss:1.34171
[653]	train-mlogloss:1.25360	validation-mlogloss:1.34168
[654]	train-mlogloss:1.25352	validation-mlogloss:1.34161
[655]	train-mlogloss:1.25349	validation-mlogloss:1.34155
[656]	train-mlogloss:1.25349	validation-mlogloss:1.34155
[657]	train-mlogloss:1.25346	validation-mlogloss:1.34156
[658]	train-mlogloss:1.25341	validation-mlogloss:1.34152
[659]	train-mlogloss:1.25333	validation-mlogloss:1.34154
[660]	train-mlogloss:1.25333	validation-mlogloss:1.34154
[661]	train-mlogloss:1.25325	validation-mlogloss:1.34155
[662]	train-mlogloss:1.25322	validation-mlogloss:1.34153
[663]	train-mlogloss:1.25319	validation-mlogloss:1.34153
[664]	train-mlogloss:1.25302	validation-mlogloss:1.34147
[665]	train-mlogloss:1.25294	validation-mlogloss:1.34142
[666]	train-mlogloss:1.25288	validation-mlogloss:1.34136
[667]	train-mlogloss:1.25288	validation-mlogloss:1.34136
[668]	train-mlogloss:1.25280	validation-mlogloss:1.34136
[669]	train-mlogloss:1.25274	validation-mlogloss:1.34139
[670]	train-mlogloss:1.25273	validation-mlogloss:1.34138
[671]	train-mlogloss:1.25270	validation-mlogloss:1.34139
[672]	train-mlogloss:1.25268	validation-mlogloss:1.34138
[673]	train-mlogloss:1.25266	validation-mlogloss:1.34138
[674]	train-mlogloss:1.25261	validation-mlogloss:1.34138
[675]	train-mlogloss:1.25259	validation-mlogloss:1.34137
[676]	train-mlogloss:1.25258	validation-mlogloss:1.34136
[677]	train-mlogloss:1.25258	validation-mlogloss:1.34136
[678]	train-mlogloss:1.25250	validation-mlogloss:1.34126
[679]	train-mlogloss:1.25243	validation-mlogloss:1.34120
[680]	train-mlogloss:1.25243	validation-mlogloss:1.34120
[681]	train-mlogloss:1.25232	validation-mlogloss:1.34113
[682]	train-mlogloss:1.25227	validation-mlogloss:1.34107
[683]	train-mlogloss:1.25221	validation-mlogloss:1.34104
[684]	train-mlogloss:1.25221	validation-mlogloss:1.34104
[685]	train-mlogloss:1.25215	validation-mlogloss:1.34099
[686]	train-mlogloss:1.25215	validation-mlogloss:1.34100
[687]	train-mlogloss:1.25213	validation-mlogloss:1.34099
[688]	train-mlogloss:1.25207	validation-mlogloss:1.34093
[689]	train-mlogloss:1.25206	validation-mlogloss:1.34091
[690]	train-mlogloss:1.25206	validation-mlogloss:1.34091
[691]	train-mlogloss:1.25203	validation-mlogloss:1.34091
[692]	train-mlogloss:1.25202	validation-mlogloss:1.34090
[693]	train-mlogloss:1.25202	validation-mlogloss:1.34090
[694]	train-mlogloss:1.25202	validation-mlogloss:1.34090
[695]	train-mlogloss:1.25201	validation-mlogloss:1.34090
[696]	train-mlogloss:1.25198	validation-mlogloss:1.34090
[697]	train-mlogloss:1.25198	validation-mlogloss:1.34089
[698]	train-mlogloss:1.25198	validation-mlogloss:1.34089
[699]	train-mlogloss:1.25195	validation-mlogloss:1.34089
[700]	train-mlogloss:1.25193	validation-mlogloss:1.34090
[701]	train-mlogloss:1.25193	validation-mlogloss:1.34090
[702]	train-mlogloss:1.25188	validation-mlogloss:1.34085
[703]	train-mlogloss:1.25179	validation-mlogloss:1.34083
[704]	train-mlogloss:1.25173	validation-mlogloss:1.34080
[705]	train-mlogloss:1.25170	validation-mlogloss:1.34075
[706]	train-mlogloss:1.25167	validation-mlogloss:1.34071
[707]	train-mlogloss:1.25164	validation-mlogloss:1.34070
[708]	train-mlogloss:1.25164	validation-mlogloss:1.34070
[709]	train-mlogloss:1.25163	validation-mlogloss:1.34067
[710]	train-mlogloss:1.25157	validation-mlogloss:1.34064
[711]	train-mlogloss:1.25157	validation-mlogloss:1.34064
[712]	train-mlogloss:1.25154	validation-mlogloss:1.34060
[713]	train-mlogloss:1.25146	validation-mlogloss:1.34057
Saved model to disk.

=== EJECUCIÓN 1 ===

--- TRAIN (ejecución 1) ---

--- TEST (ejecución 1) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.69 [%]
Global accuracy score (test) = 50.57 [%]
Global F1 score (train) = 62.76 [%]
Global F1 score (test) = 50.79 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.38      0.32       184
 CAMINAR CON MÓVIL O LIBRO       0.46      0.40      0.43       184
       CAMINAR USUAL SPEED       0.29      0.24      0.26       184
            CAMINAR ZIGZAG       0.58      0.54      0.56       184
          DE PIE BARRIENDO       0.55      0.48      0.51       184
   DE PIE DOBLANDO TOALLAS       0.44      0.48      0.46       184
    DE PIE MOVIENDO LIBROS       0.51      0.49      0.50       184
          DE PIE USANDO PC       0.62      0.66      0.64       184
        FASE REPOSO CON K5       0.56      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.87      0.63      0.73       184
           SENTADO LEYENDO       0.33      0.40      0.36       184
         SENTADO USANDO PC       0.41      0.27      0.32       184
      SENTADO VIENDO LA TV       0.43      0.36      0.39       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.67      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.50      2737


Accuracy capturado en la ejecución 1: 50.57 [%]
F1-score capturado en la ejecución 1: 50.79 [%]

=== EJECUCIÓN 2 ===

--- TRAIN (ejecución 2) ---

--- TEST (ejecución 2) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.86 [%]
Global accuracy score (test) = 50.02 [%]
Global F1 score (train) = 62.92 [%]
Global F1 score (test) = 50.12 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.39      0.32       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.40      0.42       184
       CAMINAR USUAL SPEED       0.29      0.21      0.25       184
            CAMINAR ZIGZAG       0.58      0.55      0.56       184
          DE PIE BARRIENDO       0.56      0.48      0.51       184
   DE PIE DOBLANDO TOALLAS       0.43      0.46      0.44       184
    DE PIE MOVIENDO LIBROS       0.48      0.46      0.47       184
          DE PIE USANDO PC       0.60      0.66      0.63       184
        FASE REPOSO CON K5       0.53      0.78      0.63       184
INCREMENTAL CICLOERGOMETRO       0.87      0.63      0.73       184
           SENTADO LEYENDO       0.34      0.41      0.37       184
         SENTADO USANDO PC       0.39      0.24      0.30       184
      SENTADO VIENDO LA TV       0.46      0.40      0.42       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.68      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.51      0.50      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 2: 50.02 [%]
F1-score capturado en la ejecución 2: 50.12 [%]

=== EJECUCIÓN 3 ===

--- TRAIN (ejecución 3) ---

--- TEST (ejecución 3) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 63.02 [%]
Global accuracy score (test) = 50.2 [%]
Global F1 score (train) = 63.1 [%]
Global F1 score (test) = 50.41 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.39      0.32       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.40      0.43       184
       CAMINAR USUAL SPEED       0.29      0.23      0.26       184
            CAMINAR ZIGZAG       0.60      0.56      0.58       184
          DE PIE BARRIENDO       0.56      0.48      0.52       184
   DE PIE DOBLANDO TOALLAS       0.41      0.46      0.43       184
    DE PIE MOVIENDO LIBROS       0.47      0.42      0.44       184
          DE PIE USANDO PC       0.62      0.66      0.64       184
        FASE REPOSO CON K5       0.54      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.86      0.62      0.72       184
           SENTADO LEYENDO       0.34      0.42      0.37       184
         SENTADO USANDO PC       0.39      0.25      0.31       184
      SENTADO VIENDO LA TV       0.47      0.40      0.43       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.67      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.50      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 3: 50.2 [%]
F1-score capturado en la ejecución 3: 50.41 [%]

=== EJECUCIÓN 4 ===

--- TRAIN (ejecución 4) ---

--- TEST (ejecución 4) ---
2025-10-27 11:17:46.765182: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:17:46.777767: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560266.791333  530976 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560266.795696  530976 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560266.806527  530976 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560266.806549  530976 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560266.806552  530976 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560266.806554  530976 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:17:46.809965: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68405	validation-mlogloss:2.68446
[1]	train-mlogloss:2.65993	validation-mlogloss:2.66117
[2]	train-mlogloss:2.63825	validation-mlogloss:2.63982
[3]	train-mlogloss:2.61644	validation-mlogloss:2.61849
[4]	train-mlogloss:2.59528	validation-mlogloss:2.59768
[5]	train-mlogloss:2.57404	validation-mlogloss:2.57660
[6]	train-mlogloss:2.55327	validation-mlogloss:2.55648
[7]	train-mlogloss:2.53367	validation-mlogloss:2.53788
[8]	train-mlogloss:2.51450	validation-mlogloss:2.51871
[9]	train-mlogloss:2.49636	validation-mlogloss:2.50055
[10]	train-mlogloss:2.47770	validation-mlogloss:2.48250
[11]	train-mlogloss:2.46006	validation-mlogloss:2.46554
[12]	train-mlogloss:2.44250	validation-mlogloss:2.44884
[13]	train-mlogloss:2.42551	validation-mlogloss:2.43237
[14]	train-mlogloss:2.40906	validation-mlogloss:2.41662
[15]	train-mlogloss:2.39365	validation-mlogloss:2.40185
[16]	train-mlogloss:2.37791	validation-mlogloss:2.38689
[17]	train-mlogloss:2.36234	validation-mlogloss:2.37144
[18]	train-mlogloss:2.34714	validation-mlogloss:2.35655
[19]	train-mlogloss:2.33252	validation-mlogloss:2.34266
[20]	train-mlogloss:2.31801	validation-mlogloss:2.32889
[21]	train-mlogloss:2.30355	validation-mlogloss:2.31475
[22]	train-mlogloss:2.28962	validation-mlogloss:2.30105
[23]	train-mlogloss:2.27562	validation-mlogloss:2.28739
[24]	train-mlogloss:2.26224	validation-mlogloss:2.27430
[25]	train-mlogloss:2.24915	validation-mlogloss:2.26172
[26]	train-mlogloss:2.23573	validation-mlogloss:2.24869
[27]	train-mlogloss:2.22340	validation-mlogloss:2.23688
[28]	train-mlogloss:2.21091	validation-mlogloss:2.22484
[29]	train-mlogloss:2.19911	validation-mlogloss:2.21365
[30]	train-mlogloss:2.18713	validation-mlogloss:2.20225
[31]	train-mlogloss:2.17526	validation-mlogloss:2.19053
[32]	train-mlogloss:2.16363	validation-mlogloss:2.17912
[33]	train-mlogloss:2.15284	validation-mlogloss:2.16864
[34]	train-mlogloss:2.14185	validation-mlogloss:2.15806
[35]	train-mlogloss:2.13083	validation-mlogloss:2.14734
[36]	train-mlogloss:2.12019	validation-mlogloss:2.13722
[37]	train-mlogloss:2.10957	validation-mlogloss:2.12672
[38]	train-mlogloss:2.09918	validation-mlogloss:2.11710
[39]	train-mlogloss:2.08901	validation-mlogloss:2.10730
[40]	train-mlogloss:2.07890	validation-mlogloss:2.09690
[41]	train-mlogloss:2.06927	validation-mlogloss:2.08727
[42]	train-mlogloss:2.05953	validation-mlogloss:2.07787
[43]	train-mlogloss:2.04994	validation-mlogloss:2.06813
[44]	train-mlogloss:2.04074	validation-mlogloss:2.05864
[45]	train-mlogloss:2.03169	validation-mlogloss:2.04990
[46]	train-mlogloss:2.02274	validation-mlogloss:2.04096
[47]	train-mlogloss:2.01406	validation-mlogloss:2.03263
[48]	train-mlogloss:2.00531	validation-mlogloss:2.02380
[49]	train-mlogloss:1.99696	validation-mlogloss:2.01546
[50]	train-mlogloss:1.98850	validation-mlogloss:2.00727
[51]	train-mlogloss:1.98030	validation-mlogloss:1.99927
[52]	train-mlogloss:1.97190	validation-mlogloss:1.99147
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[655]	train-mlogloss:1.25408	validation-mlogloss:1.34111
[656]	train-mlogloss:1.25407	validation-mlogloss:1.34111
[657]	train-mlogloss:1.25406	validation-mlogloss:1.34111
[658]	train-mlogloss:1.25397	validation-mlogloss:1.34097
[659]	train-mlogloss:1.25391	validation-mlogloss:1.34095
[660]	train-mlogloss:1.25389	validation-mlogloss:1.34093
[661]	train-mlogloss:1.25389	validation-mlogloss:1.34093
[662]	train-mlogloss:1.25389	validation-mlogloss:1.34094
[663]	train-mlogloss:1.25388	validation-mlogloss:1.34091
[664]	train-mlogloss:1.25381	validation-mlogloss:1.34093
[665]	train-mlogloss:1.25381	validation-mlogloss:1.34092
[666]	train-mlogloss:1.25372	validation-mlogloss:1.34082
[667]	train-mlogloss:1.25369	validation-mlogloss:1.34081
[668]	train-mlogloss:1.25360	validation-mlogloss:1.34069
[669]	train-mlogloss:1.25358	validation-mlogloss:1.34068
[670]	train-mlogloss:1.25350	validation-mlogloss:1.34062
[671]	train-mlogloss:1.25350	validation-mlogloss:1.34062
[672]	train-mlogloss:1.25347	validation-mlogloss:1.34059
[673]	train-mlogloss:1.25341	validation-mlogloss:1.34057
[674]	train-mlogloss:1.25337	validation-mlogloss:1.34057
[675]	train-mlogloss:1.25332	validation-mlogloss:1.34057
[676]	train-mlogloss:1.25331	validation-mlogloss:1.34057
[677]	train-mlogloss:1.25331	validation-mlogloss:1.34057
[678]	train-mlogloss:1.25327	validation-mlogloss:1.34054
[679]	train-mlogloss:1.25321	validation-mlogloss:1.34053
[680]	train-mlogloss:1.25315	validation-mlogloss:1.34055
[681]	train-mlogloss:1.25308	validation-mlogloss:1.34055
[682]	train-mlogloss:1.25304	validation-mlogloss:1.34050
[683]	train-mlogloss:1.25304	validation-mlogloss:1.34051
[684]	train-mlogloss:1.25302	validation-mlogloss:1.34050
[685]	train-mlogloss:1.25298	validation-mlogloss:1.34045
[686]	train-mlogloss:1.25294	validation-mlogloss:1.34044
[687]	train-mlogloss:1.25294	validation-mlogloss:1.34044
[688]	train-mlogloss:1.25288	validation-mlogloss:1.34038
[689]	train-mlogloss:1.25281	validation-mlogloss:1.34037
[690]	train-mlogloss:1.25280	validation-mlogloss:1.34037
[691]	train-mlogloss:1.25278	validation-mlogloss:1.34034
[692]	train-mlogloss:1.25274	validation-mlogloss:1.34028
[693]	train-mlogloss:1.25267	validation-mlogloss:1.34023
[694]	train-mlogloss:1.25262	validation-mlogloss:1.34023
[695]	train-mlogloss:1.25259	validation-mlogloss:1.34023
[696]	train-mlogloss:1.25258	validation-mlogloss:1.34024
[697]	train-mlogloss:1.25251	validation-mlogloss:1.34018
[698]	train-mlogloss:1.25247	validation-mlogloss:1.34015
[699]	train-mlogloss:1.25247	validation-mlogloss:1.34015
[700]	train-mlogloss:1.25242	validation-mlogloss:1.34014
[701]	train-mlogloss:1.25235	validation-mlogloss:1.34008
[702]	train-mlogloss:1.25235	validation-mlogloss:1.34008
[703]	train-mlogloss:1.25235	validation-mlogloss:1.34009
[704]	train-mlogloss:1.25232	validation-mlogloss:1.34007
[705]	train-mlogloss:1.25229	validation-mlogloss:1.34006
[706]	train-mlogloss:1.25224	validation-mlogloss:1.34007
[707]	train-mlogloss:1.25222	validation-mlogloss:1.34006
[708]	train-mlogloss:1.25216	validation-mlogloss:1.34000
[709]	train-mlogloss:1.25213	validation-mlogloss:1.33997
[710]	train-mlogloss:1.25212	validation-mlogloss:1.33996
[711]	train-mlogloss:1.25206	validation-mlogloss:1.33993
[712]	train-mlogloss:1.25206	validation-mlogloss:1.33993
[713]	train-mlogloss:1.25203	validation-mlogloss:1.33993
Saved model to disk.
2025-10-27 11:18:34.298300: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:18:34.311085: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560314.325002  531887 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560314.329470  531887 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560314.340766  531887 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560314.340794  531887 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560314.340805  531887 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560314.340808  531887 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:18:34.344333: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68345	validation-mlogloss:2.68426
[1]	train-mlogloss:2.66068	validation-mlogloss:2.66188
[2]	train-mlogloss:2.63852	validation-mlogloss:2.64036
[3]	train-mlogloss:2.61630	validation-mlogloss:2.61856
[4]	train-mlogloss:2.59604	validation-mlogloss:2.59815
[5]	train-mlogloss:2.57505	validation-mlogloss:2.57745
[6]	train-mlogloss:2.55435	validation-mlogloss:2.55730
[7]	train-mlogloss:2.53560	validation-mlogloss:2.53880
[8]	train-mlogloss:2.51607	validation-mlogloss:2.51915
[9]	train-mlogloss:2.49793	validation-mlogloss:2.50095
[10]	train-mlogloss:2.47996	validation-mlogloss:2.48313
[11]	train-mlogloss:2.46232	validation-mlogloss:2.46554
[12]	train-mlogloss:2.44509	validation-mlogloss:2.44860
[13]	train-mlogloss:2.42844	validation-mlogloss:2.43223
[14]	train-mlogloss:2.41150	validation-mlogloss:2.41597
[15]	train-mlogloss:2.39492	validation-mlogloss:2.40004
[16]	train-mlogloss:2.37877	validation-mlogloss:2.38357
[17]	train-mlogloss:2.36342	validation-mlogloss:2.36911
[18]	train-mlogloss:2.34801	validation-mlogloss:2.35427
[19]	train-mlogloss:2.33335	validation-mlogloss:2.33976
[20]	train-mlogloss:2.31860	validation-mlogloss:2.32552
[21]	train-mlogloss:2.30515	validation-mlogloss:2.31276
[22]	train-mlogloss:2.29151	validation-mlogloss:2.29977
[23]	train-mlogloss:2.27754	validation-mlogloss:2.28613
[24]	train-mlogloss:2.26376	validation-mlogloss:2.27254
[25]	train-mlogloss:2.25070	validation-mlogloss:2.25999
[26]	train-mlogloss:2.23770	validation-mlogloss:2.24728
[27]	train-mlogloss:2.22459	validation-mlogloss:2.23490
[28]	train-mlogloss:2.21231	validation-mlogloss:2.22327
[29]	train-mlogloss:2.20008	validation-mlogloss:2.21163
[30]	train-mlogloss:2.18807	validation-mlogloss:2.20028
[31]	train-mlogloss:2.17640	validation-mlogloss:2.18904
[32]	train-mlogloss:2.16502	validation-mlogloss:2.17825
[33]	train-mlogloss:2.15325	validation-mlogloss:2.16664
[34]	train-mlogloss:2.14209	validation-mlogloss:2.15595
[35]	train-mlogloss:2.13100	validation-mlogloss:2.14483
[36]	train-mlogloss:2.12055	validation-mlogloss:2.13444
[37]	train-mlogloss:2.11009	validation-mlogloss:2.12459
[38]	train-mlogloss:2.09974	validation-mlogloss:2.11488
[39]	train-mlogloss:2.08960	validation-mlogloss:2.10531
[40]	train-mlogloss:2.07968	validation-mlogloss:2.09585
[41]	train-mlogloss:2.06961	validation-mlogloss:2.08586
[42]	train-mlogloss:2.05978	validation-mlogloss:2.07674
[43]	train-mlogloss:2.05009	validation-mlogloss:2.06724
[44]	train-mlogloss:2.04093	validation-mlogloss:2.05806
[45]	train-mlogloss:2.03193	validation-mlogloss:2.04957
[46]	train-mlogloss:2.02289	validation-mlogloss:2.04054
[47]	train-mlogloss:2.01411	validation-mlogloss:2.03226
[48]	train-mlogloss:2.00552	validation-mlogloss:2.02424
[49]	train-mlogloss:1.99687	validation-mlogloss:2.01571
[50]	train-mlogloss:1.98848	validation-mlogloss:2.00763
[51]	train-mlogloss:1.98009	validation-mlogloss:1.99944
[52]	train-mlogloss:1.97171	validation-mlogloss:1.99134
[53]	train-mlogloss:1.96378	validation-mlogloss:1.98381
[54]	train-mlogloss:1.95554	validation-mlogloss:1.97597
[55]	train-mlogloss:1.94781	validation-mlogloss:1.96813
[56]	train-mlogloss:1.94013	validation-mlogloss:1.96076
[57]	train-mlogloss:1.93275	validation-mlogloss:1.95396
[58]	train-mlogloss:1.92553	validation-mlogloss:1.94701
[59]	train-mlogloss:1.91827	validation-mlogloss:1.93973
[60]	train-mlogloss:1.91090	validation-mlogloss:1.93248
[61]	train-mlogloss:1.90365	validation-mlogloss:1.92536
[62]	train-mlogloss:1.89644	validation-mlogloss:1.91831
[63]	train-mlogloss:1.88956	validation-mlogloss:1.91156
[64]	train-mlogloss:1.88266	validation-mlogloss:1.90490
[65]	train-mlogloss:1.87572	validation-mlogloss:1.89846
[66]	train-mlogloss:1.86905	validation-mlogloss:1.89225
[67]	train-mlogloss:1.86232	validation-mlogloss:1.88590
[68]	train-mlogloss:1.85577	validation-mlogloss:1.87966
[69]	train-mlogloss:1.84946	validation-mlogloss:1.87357
[70]	train-mlogloss:1.84313	validation-mlogloss:1.86764
[71]	train-mlogloss:1.83700	validation-mlogloss:1.86172
[72]	train-mlogloss:1.83117	validation-mlogloss:1.85600
[73]	train-mlogloss:1.82539	validation-mlogloss:1.85030
[74]	train-mlogloss:1.81955	validation-mlogloss:1.84453
[75]	train-mlogloss:1.81348	validation-mlogloss:1.83829
[76]	train-mlogloss:1.80752	validation-mlogloss:1.83246
[77]	train-mlogloss:1.80180	validation-mlogloss:1.82699
[78]	train-mlogloss:1.79624	validation-mlogloss:1.82165
[79]	train-mlogloss:1.79069	validation-mlogloss:1.81621
[80]	train-mlogloss:1.78493	validation-mlogloss:1.81058
[81]	train-mlogloss:1.77973	validation-mlogloss:1.80551
[82]	train-mlogloss:1.77434	validation-mlogloss:1.80072
[83]	train-mlogloss:1.76908	validation-mlogloss:1.79587
[84]	train-mlogloss:1.76398	validation-mlogloss:1.79091
[85]	train-mlogloss:1.75882	validation-mlogloss:1.78619
[86]	train-mlogloss:1.75398	validation-mlogloss:1.78140
[87]	train-mlogloss:1.74911	validation-mlogloss:1.77662
[88]	train-mlogloss:1.74413	validation-mlogloss:1.77203
[89]	train-mlogloss:1.73921	validation-mlogloss:1.76726
[90]	train-mlogloss:1.73425	validation-mlogloss:1.76254
[91]	train-mlogloss:1.72953	validation-mlogloss:1.75795
[92]	train-mlogloss:1.72504	validation-mlogloss:1.75344
[93]	train-mlogloss:1.72046	validation-mlogloss:1.74926
[94]	train-mlogloss:1.71582	validation-mlogloss:1.74458
[95]	train-mlogloss:1.71119	validation-mlogloss:1.74023
[96]	train-mlogloss:1.70676	validation-mlogloss:1.73603
[97]	train-mlogloss:1.70218	validation-mlogloss:1.73176
[98]	train-mlogloss:1.69770	validation-mlogloss:1.72765
[99]	train-mlogloss:1.69315	validation-mlogloss:1.72330
[100]	train-mlogloss:1.68871	validation-mlogloss:1.71923
[101]	train-mlogloss:1.68447	validation-mlogloss:1.71524
[102]	train-mlogloss:1.68043	validation-mlogloss:1.71123
[103]	train-mlogloss:1.67636	validation-mlogloss:1.70738
[104]	train-mlogloss:1.67228	validation-mlogloss:1.70346
[105]	train-mlogloss:1.66827	validation-mlogloss:1.69973
[106]	train-mlogloss:1.66430	validation-mlogloss:1.69595
[107]	train-mlogloss:1.66024	validation-mlogloss:1.69199
[108]	train-mlogloss:1.65647	validation-mlogloss:1.68814
[109]	train-mlogloss:1.65267	validation-mlogloss:1.68464
[110]	train-mlogloss:1.64880	validation-mlogloss:1.68081
[111]	train-mlogloss:1.64497	validation-mlogloss:1.67714
[112]	train-mlogloss:1.64119	validation-mlogloss:1.67336
[113]	train-mlogloss:1.63746	validation-mlogloss:1.66982
[114]	train-mlogloss:1.63376	validation-mlogloss:1.66621
[115]	train-mlogloss:1.63029	validation-mlogloss:1.66293
[116]	train-mlogloss:1.62687	validation-mlogloss:1.65964
[117]	train-mlogloss:1.62343	validation-mlogloss:1.65650
[118]	train-mlogloss:1.62006	validation-mlogloss:1.65350
[119]	train-mlogloss:1.61657	validation-mlogloss:1.65009
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[121]	train-mlogloss:1.60974	validation-mlogloss:1.64346
[122]	train-mlogloss:1.60632	validation-mlogloss:1.64035
[123]	train-mlogloss:1.60305	validation-mlogloss:1.63730
[124]	train-mlogloss:1.59974	validation-mlogloss:1.63440
[125]	train-mlogloss:1.59638	validation-mlogloss:1.63123
[126]	train-mlogloss:1.59329	validation-mlogloss:1.62817
[127]	train-mlogloss:1.59030	validation-mlogloss:1.62545
[128]	train-mlogloss:1.58731	validation-mlogloss:1.62290
[129]	train-mlogloss:1.58420	validation-mlogloss:1.61981
[130]	train-mlogloss:1.58112	validation-mlogloss:1.61702
[131]	train-mlogloss:1.57813	validation-mlogloss:1.61417
[132]	train-mlogloss:1.57511	validation-mlogloss:1.61147
[133]	train-mlogloss:1.57211	validation-mlogloss:1.60852
[134]	train-mlogloss:1.56906	validation-mlogloss:1.60559
[135]	train-mlogloss:1.56598	validation-mlogloss:1.60285
[136]	train-mlogloss:1.56310	validation-mlogloss:1.60034
[137]	train-mlogloss:1.56025	validation-mlogloss:1.59775
[138]	train-mlogloss:1.55739	validation-mlogloss:1.59529
[139]	train-mlogloss:1.55445	validation-mlogloss:1.59249
[140]	train-mlogloss:1.55173	validation-mlogloss:1.59002
[141]	train-mlogloss:1.54897	validation-mlogloss:1.58745
[142]	train-mlogloss:1.54624	validation-mlogloss:1.58500
[143]	train-mlogloss:1.54345	validation-mlogloss:1.58232
[144]	train-mlogloss:1.54086	validation-mlogloss:1.57981
[145]	train-mlogloss:1.53830	validation-mlogloss:1.57752
[146]	train-mlogloss:1.53574	validation-mlogloss:1.57516
[147]	train-mlogloss:1.53313	validation-mlogloss:1.57293
[148]	train-mlogloss:1.53056	validation-mlogloss:1.57064
[149]	train-mlogloss:1.52794	validation-mlogloss:1.56827
[150]	train-mlogloss:1.52539	validation-mlogloss:1.56590
[151]	train-mlogloss:1.52310	validation-mlogloss:1.56379
[152]	train-mlogloss:1.52073	validation-mlogloss:1.56153
[153]	train-mlogloss:1.51845	validation-mlogloss:1.55937
[154]	train-mlogloss:1.51602	validation-mlogloss:1.55708
[155]	train-mlogloss:1.51362	validation-mlogloss:1.55487
[156]	train-mlogloss:1.51112	validation-mlogloss:1.55249
[157]	train-mlogloss:1.50900	validation-mlogloss:1.55049
[158]	train-mlogloss:1.50675	validation-mlogloss:1.54849
[159]	train-mlogloss:1.50453	validation-mlogloss:1.54650
[160]	train-mlogloss:1.50223	validation-mlogloss:1.54431
[161]	train-mlogloss:1.49998	validation-mlogloss:1.54202
[162]	train-mlogloss:1.49775	validation-mlogloss:1.54016
[163]	train-mlogloss:1.49538	validation-mlogloss:1.53805
[164]	train-mlogloss:1.49321	validation-mlogloss:1.53603
[165]	train-mlogloss:1.49098	validation-mlogloss:1.53394
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[189]	train-mlogloss:1.44452	validation-mlogloss:1.49272
[190]	train-mlogloss:1.44277	validation-mlogloss:1.49126
[191]	train-mlogloss:1.44097	validation-mlogloss:1.48978
[192]	train-mlogloss:1.43936	validation-mlogloss:1.48821
[193]	train-mlogloss:1.43773	validation-mlogloss:1.48655
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[195]	train-mlogloss:1.43436	validation-mlogloss:1.48369
[196]	train-mlogloss:1.43283	validation-mlogloss:1.48244
[197]	train-mlogloss:1.43115	validation-mlogloss:1.48106
[198]	train-mlogloss:1.42959	validation-mlogloss:1.47977
[199]	train-mlogloss:1.42794	validation-mlogloss:1.47824
[200]	train-mlogloss:1.42638	validation-mlogloss:1.47686
[201]	train-mlogloss:1.42466	validation-mlogloss:1.47531
[202]	train-mlogloss:1.42322	validation-mlogloss:1.47396
[203]	train-mlogloss:1.42171	validation-mlogloss:1.47253
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[205]	train-mlogloss:1.41872	validation-mlogloss:1.46975
[206]	train-mlogloss:1.41720	validation-mlogloss:1.46858
[207]	train-mlogloss:1.41568	validation-mlogloss:1.46722
[208]	train-mlogloss:1.41415	validation-mlogloss:1.46602
[209]	train-mlogloss:1.41272	validation-mlogloss:1.46475
[210]	train-mlogloss:1.41123	validation-mlogloss:1.46347
[211]	train-mlogloss:1.40974	validation-mlogloss:1.46223
[212]	train-mlogloss:1.40829	validation-mlogloss:1.46095
[213]	train-mlogloss:1.40694	validation-mlogloss:1.45976
[214]	train-mlogloss:1.40565	validation-mlogloss:1.45867
[215]	train-mlogloss:1.40408	validation-mlogloss:1.45735
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[525]	train-mlogloss:1.26152	validation-mlogloss:1.34529
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[544]	train-mlogloss:1.26034	validation-mlogloss:1.34463
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[552]	train-mlogloss:1.25974	validation-mlogloss:1.34427
[553]	train-mlogloss:1.25967	validation-mlogloss:1.34422
[554]	train-mlogloss:1.25959	validation-mlogloss:1.34417
[555]	train-mlogloss:1.25950	validation-mlogloss:1.34409
[556]	train-mlogloss:1.25948	validation-mlogloss:1.34405
[557]	train-mlogloss:1.25945	validation-mlogloss:1.34402
[558]	train-mlogloss:1.25943	validation-mlogloss:1.34400
[559]	train-mlogloss:1.25935	validation-mlogloss:1.34394
[560]	train-mlogloss:1.25927	validation-mlogloss:1.34388
[561]	train-mlogloss:1.25921	validation-mlogloss:1.34381
[562]	train-mlogloss:1.25907	validation-mlogloss:1.34380
[563]	train-mlogloss:1.25907	validation-mlogloss:1.34380
[564]	train-mlogloss:1.25906	validation-mlogloss:1.34379
[565]	train-mlogloss:1.25903	validation-mlogloss:1.34376
[566]	train-mlogloss:1.25903	validation-mlogloss:1.34376
[567]	train-mlogloss:1.25901	validation-mlogloss:1.34378
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[569]	train-mlogloss:1.25894	validation-mlogloss:1.34372
[570]	train-mlogloss:1.25894	validation-mlogloss:1.34372
[571]	train-mlogloss:1.25884	validation-mlogloss:1.34363
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[643]	train-mlogloss:1.25557	validation-mlogloss:1.34162
[644]	train-mlogloss:1.25554	validation-mlogloss:1.34160
[645]	train-mlogloss:1.25551	validation-mlogloss:1.34161
[646]	train-mlogloss:1.25548	validation-mlogloss:1.34158
[647]	train-mlogloss:1.25544	validation-mlogloss:1.34159
[648]	train-mlogloss:1.25539	validation-mlogloss:1.34159
[649]	train-mlogloss:1.25534	validation-mlogloss:1.34161
[650]	train-mlogloss:1.25529	validation-mlogloss:1.34158
[651]	train-mlogloss:1.25525	validation-mlogloss:1.34155
[652]	train-mlogloss:1.25521	validation-mlogloss:1.34155
[653]	train-mlogloss:1.25510	validation-mlogloss:1.34149
[654]	train-mlogloss:1.25504	validation-mlogloss:1.34145
[655]	train-mlogloss:1.25501	validation-mlogloss:1.34145
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[657]	train-mlogloss:1.25489	validation-mlogloss:1.34136
[658]	train-mlogloss:1.25489	validation-mlogloss:1.34136
[659]	train-mlogloss:1.25484	validation-mlogloss:1.34135
[660]	train-mlogloss:1.25472	validation-mlogloss:1.34122
[661]	train-mlogloss:1.25470	validation-mlogloss:1.34120
[662]	train-mlogloss:1.25459	validation-mlogloss:1.34116
[663]	train-mlogloss:1.25456	validation-mlogloss:1.34114
[664]	train-mlogloss:1.25451	validation-mlogloss:1.34115
[665]	train-mlogloss:1.25445	validation-mlogloss:1.34109
[666]	train-mlogloss:1.25444	validation-mlogloss:1.34107
[667]	train-mlogloss:1.25444	validation-mlogloss:1.34107
[668]	train-mlogloss:1.25442	validation-mlogloss:1.34107
[669]	train-mlogloss:1.25441	validation-mlogloss:1.34107
[670]	train-mlogloss:1.25439	validation-mlogloss:1.34105
[671]	train-mlogloss:1.25433	validation-mlogloss:1.34102
[672]	train-mlogloss:1.25431	validation-mlogloss:1.34101
[673]	train-mlogloss:1.25425	validation-mlogloss:1.34091
[674]	train-mlogloss:1.25420	validation-mlogloss:1.34090
[675]	train-mlogloss:1.25411	validation-mlogloss:1.34080
[676]	train-mlogloss:1.25409	validation-mlogloss:1.34080
[677]	train-mlogloss:1.25403	validation-mlogloss:1.34079
[678]	train-mlogloss:1.25396	validation-mlogloss:1.34076
[679]	train-mlogloss:1.25390	validation-mlogloss:1.34070
[680]	train-mlogloss:1.25390	validation-mlogloss:1.34070
[681]	train-mlogloss:1.25390	validation-mlogloss:1.34070
[682]	train-mlogloss:1.25390	validation-mlogloss:1.34070
[683]	train-mlogloss:1.25384	validation-mlogloss:1.34068
[684]	train-mlogloss:1.25380	validation-mlogloss:1.34067
[685]	train-mlogloss:1.25379	validation-mlogloss:1.34065
[686]	train-mlogloss:1.25379	validation-mlogloss:1.34064
[687]	train-mlogloss:1.25379	validation-mlogloss:1.34064
[688]	train-mlogloss:1.25374	validation-mlogloss:1.34063
[689]	train-mlogloss:1.25371	validation-mlogloss:1.34063
[690]	train-mlogloss:1.25364	validation-mlogloss:1.34055
[691]	train-mlogloss:1.25363	validation-mlogloss:1.34054
[692]	train-mlogloss:1.25359	validation-mlogloss:1.34053
[693]	train-mlogloss:1.25359	validation-mlogloss:1.34053
[694]	train-mlogloss:1.25355	validation-mlogloss:1.34051
[695]	train-mlogloss:1.25347	validation-mlogloss:1.34045
[696]	train-mlogloss:1.25342	validation-mlogloss:1.34041
[697]	train-mlogloss:1.25340	validation-mlogloss:1.34040
[698]	train-mlogloss:1.25339	validation-mlogloss:1.34041
[699]	train-mlogloss:1.25339	validation-mlogloss:1.34041
[700]	train-mlogloss:1.25338	validation-mlogloss:1.34039
[701]	train-mlogloss:1.25336	validation-mlogloss:1.34037
[702]	train-mlogloss:1.25323	validation-mlogloss:1.34034
[703]	train-mlogloss:1.25322	validation-mlogloss:1.34035
[704]	train-mlogloss:1.25315	validation-mlogloss:1.34032
[705]	train-mlogloss:1.25312	validation-mlogloss:1.34027
[706]	train-mlogloss:1.25312	validation-mlogloss:1.34027
[707]	train-mlogloss:1.25309	validation-mlogloss:1.34024
[708]	train-mlogloss:1.25309	validation-mlogloss:1.34024
[709]	train-mlogloss:1.25305	validation-mlogloss:1.34018
[710]	train-mlogloss:1.25298	validation-mlogloss:1.34008
[711]	train-mlogloss:1.25297	validation-mlogloss:1.34006
[712]	train-mlogloss:1.25297	validation-mlogloss:1.34006
[713]	train-mlogloss:1.25294	validation-mlogloss:1.34001
Saved model to disk.
2025-10-27 11:19:22.424503: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:19:22.437061: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560362.451166  532832 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560362.455587  532832 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560362.466784  532832 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560362.466807  532832 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560362.466811  532832 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560362.466814  532832 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:19:22.470039: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68424	validation-mlogloss:2.68426
[1]	train-mlogloss:2.66198	validation-mlogloss:2.66220
[2]	train-mlogloss:2.64015	validation-mlogloss:2.64083
[3]	train-mlogloss:2.61703	validation-mlogloss:2.61837
[4]	train-mlogloss:2.59631	validation-mlogloss:2.59819
[5]	train-mlogloss:2.57674	validation-mlogloss:2.57889
[6]	train-mlogloss:2.55636	validation-mlogloss:2.55942
[7]	train-mlogloss:2.53671	validation-mlogloss:2.53984
[8]	train-mlogloss:2.51737	validation-mlogloss:2.52069
[9]	train-mlogloss:2.49865	validation-mlogloss:2.50158
[10]	train-mlogloss:2.48008	validation-mlogloss:2.48335
[11]	train-mlogloss:2.46270	validation-mlogloss:2.46614
[12]	train-mlogloss:2.44606	validation-mlogloss:2.45017
[13]	train-mlogloss:2.42938	validation-mlogloss:2.43418
[14]	train-mlogloss:2.41173	validation-mlogloss:2.41726
[15]	train-mlogloss:2.39508	validation-mlogloss:2.40136
[16]	train-mlogloss:2.37953	validation-mlogloss:2.38691
[17]	train-mlogloss:2.36415	validation-mlogloss:2.37218
[18]	train-mlogloss:2.34910	validation-mlogloss:2.35742
[19]	train-mlogloss:2.33410	validation-mlogloss:2.34284
[20]	train-mlogloss:2.31972	validation-mlogloss:2.32851
[21]	train-mlogloss:2.30559	validation-mlogloss:2.31457
[22]	train-mlogloss:2.29165	validation-mlogloss:2.30059
[23]	train-mlogloss:2.27744	validation-mlogloss:2.28750
[24]	train-mlogloss:2.26399	validation-mlogloss:2.27444
[25]	train-mlogloss:2.25086	validation-mlogloss:2.26203
[26]	train-mlogloss:2.23784	validation-mlogloss:2.24938
[27]	train-mlogloss:2.22514	validation-mlogloss:2.23672
[28]	train-mlogloss:2.21339	validation-mlogloss:2.22517
[29]	train-mlogloss:2.20134	validation-mlogloss:2.21341
[30]	train-mlogloss:2.18941	validation-mlogloss:2.20148
[31]	train-mlogloss:2.17752	validation-mlogloss:2.18990
[32]	train-mlogloss:2.16575	validation-mlogloss:2.17885
[33]	train-mlogloss:2.15465	validation-mlogloss:2.16844
[34]	train-mlogloss:2.14362	validation-mlogloss:2.15795
[35]	train-mlogloss:2.13249	validation-mlogloss:2.14742
[36]	train-mlogloss:2.12178	validation-mlogloss:2.13687
[37]	train-mlogloss:2.11120	validation-mlogloss:2.12660
[38]	train-mlogloss:2.10098	validation-mlogloss:2.11676
[39]	train-mlogloss:2.09097	validation-mlogloss:2.10672
[40]	train-mlogloss:2.08086	validation-mlogloss:2.09684
[41]	train-mlogloss:2.07121	validation-mlogloss:2.08813
[42]	train-mlogloss:2.06182	validation-mlogloss:2.07895
[43]	train-mlogloss:2.05231	validation-mlogloss:2.06958
[44]	train-mlogloss:2.04268	validation-mlogloss:2.06001
[45]	train-mlogloss:2.03367	validation-mlogloss:2.05168
[46]	train-mlogloss:2.02452	validation-mlogloss:2.04276
[47]	train-mlogloss:2.01570	validation-mlogloss:2.03461
[48]	train-mlogloss:2.00697	validation-mlogloss:2.02619
[49]	train-mlogloss:1.99826	validation-mlogloss:2.01781
[50]	train-mlogloss:1.98958	validation-mlogloss:2.00923
[51]	train-mlogloss:1.98138	validation-mlogloss:2.00134
[52]	train-mlogloss:1.97297	validation-mlogloss:1.99318
[53]	train-mlogloss:1.96491	validation-mlogloss:1.98533
[54]	train-mlogloss:1.95689	validation-mlogloss:1.97758
[55]	train-mlogloss:1.94894	validation-mlogloss:1.96961
[56]	train-mlogloss:1.94131	validation-mlogloss:1.96232
[57]	train-mlogloss:1.93378	validation-mlogloss:1.95519
[58]	train-mlogloss:1.92641	validation-mlogloss:1.94785
[59]	train-mlogloss:1.91896	validation-mlogloss:1.94105
[60]	train-mlogloss:1.91156	validation-mlogloss:1.93359
[61]	train-mlogloss:1.90421	validation-mlogloss:1.92661
[62]	train-mlogloss:1.89711	validation-mlogloss:1.92011
[63]	train-mlogloss:1.89034	validation-mlogloss:1.91328
[64]	train-mlogloss:1.88347	validation-mlogloss:1.90663
[65]	train-mlogloss:1.87666	validation-mlogloss:1.89995
[66]	train-mlogloss:1.87007	validation-mlogloss:1.89360
[67]	train-mlogloss:1.86340	validation-mlogloss:1.88668
[68]	train-mlogloss:1.85689	validation-mlogloss:1.88051
[69]	train-mlogloss:1.85038	validation-mlogloss:1.87445
[70]	train-mlogloss:1.84404	validation-mlogloss:1.86861
[71]	train-mlogloss:1.83778	validation-mlogloss:1.86293
[72]	train-mlogloss:1.83180	validation-mlogloss:1.85713
[73]	train-mlogloss:1.82587	validation-mlogloss:1.85117
[74]	train-mlogloss:1.81978	validation-mlogloss:1.84516
[75]	train-mlogloss:1.81406	validation-mlogloss:1.83968
[76]	train-mlogloss:1.80831	validation-mlogloss:1.83433
[77]	train-mlogloss:1.80266	validation-mlogloss:1.82905
[78]	train-mlogloss:1.79706	validation-mlogloss:1.82378
[79]	train-mlogloss:1.79143	validation-mlogloss:1.81822
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[683]	train-mlogloss:1.25208	validation-mlogloss:1.34106
[684]	train-mlogloss:1.25207	validation-mlogloss:1.34105
[685]	train-mlogloss:1.25205	validation-mlogloss:1.34104
[686]	train-mlogloss:1.25203	validation-mlogloss:1.34105
[687]	train-mlogloss:1.25203	validation-mlogloss:1.34105
[688]	train-mlogloss:1.25201	validation-mlogloss:1.34106
[689]	train-mlogloss:1.25201	validation-mlogloss:1.34106
[690]	train-mlogloss:1.25195	validation-mlogloss:1.34102
[691]	train-mlogloss:1.25183	validation-mlogloss:1.34099
[692]	train-mlogloss:1.25183	validation-mlogloss:1.34099
[693]	train-mlogloss:1.25180	validation-mlogloss:1.34100
[694]	train-mlogloss:1.25171	validation-mlogloss:1.34099
[695]	train-mlogloss:1.25164	validation-mlogloss:1.34098
[696]	train-mlogloss:1.25163	validation-mlogloss:1.34096
[697]	train-mlogloss:1.25157	validation-mlogloss:1.34091
[698]	train-mlogloss:1.25151	validation-mlogloss:1.34084
[699]	train-mlogloss:1.25148	validation-mlogloss:1.34081
[700]	train-mlogloss:1.25147	validation-mlogloss:1.34080
[701]	train-mlogloss:1.25143	validation-mlogloss:1.34076
[702]	train-mlogloss:1.25141	validation-mlogloss:1.34075
[703]	train-mlogloss:1.25132	validation-mlogloss:1.34065
[704]	train-mlogloss:1.25128	validation-mlogloss:1.34065
[705]	train-mlogloss:1.25120	validation-mlogloss:1.34061
[706]	train-mlogloss:1.25119	validation-mlogloss:1.34061
[707]	train-mlogloss:1.25119	validation-mlogloss:1.34061
[708]	train-mlogloss:1.25118	validation-mlogloss:1.34061
[709]	train-mlogloss:1.25115	validation-mlogloss:1.34061
[710]	train-mlogloss:1.25113	validation-mlogloss:1.34061
[711]	train-mlogloss:1.25113	validation-mlogloss:1.34061
[712]	train-mlogloss:1.25113	validation-mlogloss:1.34061
[713]	train-mlogloss:1.25112	validation-mlogloss:1.34062
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.83 [%]
Global accuracy score (test) = 50.53 [%]
Global F1 score (train) = 62.9 [%]
Global F1 score (test) = 50.69 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.29      0.40      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.40      0.42       184
       CAMINAR USUAL SPEED       0.31      0.24      0.27       184
            CAMINAR ZIGZAG       0.60      0.56      0.58       184
          DE PIE BARRIENDO       0.56      0.51      0.53       184
   DE PIE DOBLANDO TOALLAS       0.42      0.47      0.44       184
    DE PIE MOVIENDO LIBROS       0.47      0.45      0.46       184
          DE PIE USANDO PC       0.62      0.67      0.64       184
        FASE REPOSO CON K5       0.56      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.89      0.62      0.73       184
           SENTADO LEYENDO       0.32      0.40      0.36       184
         SENTADO USANDO PC       0.41      0.24      0.31       184
      SENTADO VIENDO LA TV       0.44      0.38      0.41       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.68      0.60       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.50      2737


Accuracy capturado en la ejecución 4: 50.53 [%]
F1-score capturado en la ejecución 4: 50.69 [%]

=== EJECUCIÓN 5 ===

--- TRAIN (ejecución 5) ---

--- TEST (ejecución 5) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.75 [%]
Global accuracy score (test) = 50.6 [%]
Global F1 score (train) = 62.8 [%]
Global F1 score (test) = 50.81 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.29      0.40      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.40      0.41       184
       CAMINAR USUAL SPEED       0.28      0.22      0.24       184
            CAMINAR ZIGZAG       0.62      0.56      0.59       184
          DE PIE BARRIENDO       0.56      0.49      0.52       184
   DE PIE DOBLANDO TOALLAS       0.44      0.47      0.46       184
    DE PIE MOVIENDO LIBROS       0.48      0.48      0.48       184
          DE PIE USANDO PC       0.63      0.66      0.65       184
        FASE REPOSO CON K5       0.55      0.79      0.64       184
INCREMENTAL CICLOERGOMETRO       0.90      0.63      0.74       184
           SENTADO LEYENDO       0.34      0.43      0.38       184
         SENTADO USANDO PC       0.38      0.24      0.30       184
      SENTADO VIENDO LA TV       0.46      0.38      0.41       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.67      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.51      2737


Accuracy capturado en la ejecución 5: 50.6 [%]
F1-score capturado en la ejecución 5: 50.81 [%]

=== EJECUCIÓN 6 ===

--- TRAIN (ejecución 6) ---

--- TEST (ejecución 6) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.77 [%]
Global accuracy score (test) = 50.2 [%]
Global F1 score (train) = 62.82 [%]
Global F1 score (test) = 50.42 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.26      0.38      0.31       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.40      0.42       184
       CAMINAR USUAL SPEED       0.27      0.20      0.23       184
            CAMINAR ZIGZAG       0.62      0.53      0.57       184
          DE PIE BARRIENDO       0.55      0.49      0.52       184
   DE PIE DOBLANDO TOALLAS       0.42      0.47      0.44       184
    DE PIE MOVIENDO LIBROS       0.48      0.43      0.46       184
          DE PIE USANDO PC       0.63      0.67      0.65       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.88      0.64      0.74       184
           SENTADO LEYENDO       0.35      0.43      0.38       184
         SENTADO USANDO PC       0.39      0.26      0.31       184
      SENTADO VIENDO LA TV       0.46      0.39      0.42       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.68      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.50      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 6: 50.2 [%]
F1-score capturado en la ejecución 6: 50.42 [%]

=== EJECUCIÓN 7 ===

--- TRAIN (ejecución 7) ---

--- TEST (ejecución 7) ---
2025-10-27 11:20:09.590606: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:20:09.603276: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560409.616926  533763 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560409.621277  533763 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560409.632192  533763 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560409.632217  533763 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560409.632220  533763 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560409.632222  533763 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:20:09.635628: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68348	validation-mlogloss:2.68409
[1]	train-mlogloss:2.65985	validation-mlogloss:2.66026
[2]	train-mlogloss:2.63699	validation-mlogloss:2.63768
[3]	train-mlogloss:2.61444	validation-mlogloss:2.61572
[4]	train-mlogloss:2.59296	validation-mlogloss:2.59448
[5]	train-mlogloss:2.57282	validation-mlogloss:2.57523
[6]	train-mlogloss:2.55385	validation-mlogloss:2.55636
[7]	train-mlogloss:2.53503	validation-mlogloss:2.53829
[8]	train-mlogloss:2.51550	validation-mlogloss:2.51917
[9]	train-mlogloss:2.49726	validation-mlogloss:2.50167
[10]	train-mlogloss:2.47895	validation-mlogloss:2.48375
[11]	train-mlogloss:2.46100	validation-mlogloss:2.46618
[12]	train-mlogloss:2.44354	validation-mlogloss:2.44899
[13]	train-mlogloss:2.42677	validation-mlogloss:2.43250
[14]	train-mlogloss:2.41022	validation-mlogloss:2.41661
[15]	train-mlogloss:2.39410	validation-mlogloss:2.40094
[16]	train-mlogloss:2.37861	validation-mlogloss:2.38598
[17]	train-mlogloss:2.36344	validation-mlogloss:2.37073
[18]	train-mlogloss:2.34815	validation-mlogloss:2.35600
[19]	train-mlogloss:2.33317	validation-mlogloss:2.34150
[20]	train-mlogloss:2.31859	validation-mlogloss:2.32696
[21]	train-mlogloss:2.30423	validation-mlogloss:2.31383
[22]	train-mlogloss:2.28998	validation-mlogloss:2.29957
[23]	train-mlogloss:2.27618	validation-mlogloss:2.28575
[24]	train-mlogloss:2.26250	validation-mlogloss:2.27200
[25]	train-mlogloss:2.24901	validation-mlogloss:2.25843
[26]	train-mlogloss:2.23592	validation-mlogloss:2.24574
[27]	train-mlogloss:2.22306	validation-mlogloss:2.23367
[28]	train-mlogloss:2.21070	validation-mlogloss:2.22162
[29]	train-mlogloss:2.19852	validation-mlogloss:2.20985
[30]	train-mlogloss:2.18702	validation-mlogloss:2.19880
[31]	train-mlogloss:2.17509	validation-mlogloss:2.18780
[32]	train-mlogloss:2.16328	validation-mlogloss:2.17633
[33]	train-mlogloss:2.15214	validation-mlogloss:2.16573
[34]	train-mlogloss:2.14134	validation-mlogloss:2.15517
[35]	train-mlogloss:2.13032	validation-mlogloss:2.14488
[36]	train-mlogloss:2.11958	validation-mlogloss:2.13415
[37]	train-mlogloss:2.10892	validation-mlogloss:2.12375
[38]	train-mlogloss:2.09847	validation-mlogloss:2.11362
[39]	train-mlogloss:2.08881	validation-mlogloss:2.10459
[40]	train-mlogloss:2.07917	validation-mlogloss:2.09494
[41]	train-mlogloss:2.06914	validation-mlogloss:2.08541
[42]	train-mlogloss:2.05937	validation-mlogloss:2.07621
[43]	train-mlogloss:2.04973	validation-mlogloss:2.06660
[44]	train-mlogloss:2.04030	validation-mlogloss:2.05696
[45]	train-mlogloss:2.03096	validation-mlogloss:2.04785
[46]	train-mlogloss:2.02188	validation-mlogloss:2.03867
[47]	train-mlogloss:2.01299	validation-mlogloss:2.02988
[48]	train-mlogloss:2.00441	validation-mlogloss:2.02148
[49]	train-mlogloss:1.99597	validation-mlogloss:2.01348
[50]	train-mlogloss:1.98741	validation-mlogloss:2.00533
[51]	train-mlogloss:1.97895	validation-mlogloss:1.99740
[52]	train-mlogloss:1.97076	validation-mlogloss:1.98929
[53]	train-mlogloss:1.96279	validation-mlogloss:1.98132
[54]	train-mlogloss:1.95510	validation-mlogloss:1.97375
[55]	train-mlogloss:1.94729	validation-mlogloss:1.96582
[56]	train-mlogloss:1.93954	validation-mlogloss:1.95816
[57]	train-mlogloss:1.93167	validation-mlogloss:1.95047
[58]	train-mlogloss:1.92434	validation-mlogloss:1.94342
[59]	train-mlogloss:1.91695	validation-mlogloss:1.93610
[60]	train-mlogloss:1.90964	validation-mlogloss:1.92943
[61]	train-mlogloss:1.90251	validation-mlogloss:1.92257
[62]	train-mlogloss:1.89520	validation-mlogloss:1.91548
[63]	train-mlogloss:1.88809	validation-mlogloss:1.90841
[64]	train-mlogloss:1.88114	validation-mlogloss:1.90206
[65]	train-mlogloss:1.87450	validation-mlogloss:1.89572
[66]	train-mlogloss:1.86785	validation-mlogloss:1.88910
[67]	train-mlogloss:1.86135	validation-mlogloss:1.88282
[68]	train-mlogloss:1.85495	validation-mlogloss:1.87648
[69]	train-mlogloss:1.84846	validation-mlogloss:1.87016
[70]	train-mlogloss:1.84228	validation-mlogloss:1.86416
[71]	train-mlogloss:1.83604	validation-mlogloss:1.85812
[72]	train-mlogloss:1.82982	validation-mlogloss:1.85212
[73]	train-mlogloss:1.82386	validation-mlogloss:1.84626
[74]	train-mlogloss:1.81775	validation-mlogloss:1.84042
[75]	train-mlogloss:1.81188	validation-mlogloss:1.83485
[76]	train-mlogloss:1.80604	validation-mlogloss:1.82924
[77]	train-mlogloss:1.80027	validation-mlogloss:1.82370
[78]	train-mlogloss:1.79455	validation-mlogloss:1.81830
[79]	train-mlogloss:1.78901	validation-mlogloss:1.81303
[80]	train-mlogloss:1.78357	validation-mlogloss:1.80741
[81]	train-mlogloss:1.77836	validation-mlogloss:1.80219
[82]	train-mlogloss:1.77280	validation-mlogloss:1.79683
[83]	train-mlogloss:1.76738	validation-mlogloss:1.79161
[84]	train-mlogloss:1.76214	validation-mlogloss:1.78654
[85]	train-mlogloss:1.75699	validation-mlogloss:1.78158
[86]	train-mlogloss:1.75190	validation-mlogloss:1.77660
[87]	train-mlogloss:1.74689	validation-mlogloss:1.77191
[88]	train-mlogloss:1.74202	validation-mlogloss:1.76726
[89]	train-mlogloss:1.73722	validation-mlogloss:1.76257
[90]	train-mlogloss:1.73248	validation-mlogloss:1.75786
[91]	train-mlogloss:1.72796	validation-mlogloss:1.75329
[92]	train-mlogloss:1.72321	validation-mlogloss:1.74866
[93]	train-mlogloss:1.71870	validation-mlogloss:1.74432
[94]	train-mlogloss:1.71409	validation-mlogloss:1.74018
[95]	train-mlogloss:1.70950	validation-mlogloss:1.73581
[96]	train-mlogloss:1.70502	validation-mlogloss:1.73156
[97]	train-mlogloss:1.70053	validation-mlogloss:1.72734
[98]	train-mlogloss:1.69598	validation-mlogloss:1.72315
[99]	train-mlogloss:1.69165	validation-mlogloss:1.71894
[100]	train-mlogloss:1.68723	validation-mlogloss:1.71486
[101]	train-mlogloss:1.68290	validation-mlogloss:1.71080
[102]	train-mlogloss:1.67870	validation-mlogloss:1.70686
[103]	train-mlogloss:1.67448	validation-mlogloss:1.70297
[104]	train-mlogloss:1.67059	validation-mlogloss:1.69892
[105]	train-mlogloss:1.66641	validation-mlogloss:1.69497
[106]	train-mlogloss:1.66238	validation-mlogloss:1.69096
[107]	train-mlogloss:1.65855	validation-mlogloss:1.68719
[108]	train-mlogloss:1.65448	validation-mlogloss:1.68343
[109]	train-mlogloss:1.65066	validation-mlogloss:1.67965
[110]	train-mlogloss:1.64684	validation-mlogloss:1.67596
[111]	train-mlogloss:1.64296	validation-mlogloss:1.67230
[112]	train-mlogloss:1.63915	validation-mlogloss:1.66853
[113]	train-mlogloss:1.63546	validation-mlogloss:1.66495
[114]	train-mlogloss:1.63193	validation-mlogloss:1.66164
[115]	train-mlogloss:1.62837	validation-mlogloss:1.65825
[116]	train-mlogloss:1.62470	validation-mlogloss:1.65502
[117]	train-mlogloss:1.62119	validation-mlogloss:1.65162
[118]	train-mlogloss:1.61784	validation-mlogloss:1.64823
[119]	train-mlogloss:1.61434	validation-mlogloss:1.64496
[120]	train-mlogloss:1.61123	validation-mlogloss:1.64179
[121]	train-mlogloss:1.60783	validation-mlogloss:1.63864
[122]	train-mlogloss:1.60451	validation-mlogloss:1.63545
[123]	train-mlogloss:1.60135	validation-mlogloss:1.63250
[124]	train-mlogloss:1.59809	validation-mlogloss:1.62944
[125]	train-mlogloss:1.59463	validation-mlogloss:1.62659
[126]	train-mlogloss:1.59153	validation-mlogloss:1.62358
[127]	train-mlogloss:1.58827	validation-mlogloss:1.62060
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[705]	train-mlogloss:1.25181	validation-mlogloss:1.33765
[706]	train-mlogloss:1.25175	validation-mlogloss:1.33764
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[709]	train-mlogloss:1.25150	validation-mlogloss:1.33746
[710]	train-mlogloss:1.25150	validation-mlogloss:1.33746
[711]	train-mlogloss:1.25146	validation-mlogloss:1.33743
[712]	train-mlogloss:1.25142	validation-mlogloss:1.33741
[713]	train-mlogloss:1.25139	validation-mlogloss:1.33738
Saved model to disk.
2025-10-27 11:20:56.405989: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:20:56.418461: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560456.432069  534672 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560456.436405  534672 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560456.447380  534672 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560456.447403  534672 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560456.447406  534672 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560456.447408  534672 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:20:56.450812: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68328	validation-mlogloss:2.68402
[1]	train-mlogloss:2.65971	validation-mlogloss:2.66100
[2]	train-mlogloss:2.63704	validation-mlogloss:2.63843
[3]	train-mlogloss:2.61532	validation-mlogloss:2.61754
[4]	train-mlogloss:2.59395	validation-mlogloss:2.59591
[5]	train-mlogloss:2.57342	validation-mlogloss:2.57608
[6]	train-mlogloss:2.55330	validation-mlogloss:2.55617
[7]	train-mlogloss:2.53455	validation-mlogloss:2.53767
[8]	train-mlogloss:2.51521	validation-mlogloss:2.51866
[9]	train-mlogloss:2.49718	validation-mlogloss:2.50045
[10]	train-mlogloss:2.48021	validation-mlogloss:2.48420
[11]	train-mlogloss:2.46345	validation-mlogloss:2.46790
[12]	train-mlogloss:2.44661	validation-mlogloss:2.45184
[13]	train-mlogloss:2.42958	validation-mlogloss:2.43522
[14]	train-mlogloss:2.41293	validation-mlogloss:2.41881
[15]	train-mlogloss:2.39628	validation-mlogloss:2.40247
[16]	train-mlogloss:2.38076	validation-mlogloss:2.38758
[17]	train-mlogloss:2.36590	validation-mlogloss:2.37345
[18]	train-mlogloss:2.35029	validation-mlogloss:2.35850
[19]	train-mlogloss:2.33526	validation-mlogloss:2.34412
[20]	train-mlogloss:2.32078	validation-mlogloss:2.32948
[21]	train-mlogloss:2.30636	validation-mlogloss:2.31520
[22]	train-mlogloss:2.29273	validation-mlogloss:2.30143
[23]	train-mlogloss:2.27906	validation-mlogloss:2.28812
[24]	train-mlogloss:2.26519	validation-mlogloss:2.27502
[25]	train-mlogloss:2.25236	validation-mlogloss:2.26302
[26]	train-mlogloss:2.23939	validation-mlogloss:2.25007
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[29]	train-mlogloss:2.20154	validation-mlogloss:2.21423
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[32]	train-mlogloss:2.16566	validation-mlogloss:2.17942
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[34]	train-mlogloss:2.14352	validation-mlogloss:2.15761
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[49]	train-mlogloss:1.99755	validation-mlogloss:2.01770
[50]	train-mlogloss:1.98925	validation-mlogloss:2.00955
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[53]	train-mlogloss:1.96433	validation-mlogloss:1.98455
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[107]	train-mlogloss:1.65977	validation-mlogloss:1.69150
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[109]	train-mlogloss:1.65201	validation-mlogloss:1.68415
[110]	train-mlogloss:1.64819	validation-mlogloss:1.68050
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[113]	train-mlogloss:1.63683	validation-mlogloss:1.66950
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[595]	train-mlogloss:1.25617	validation-mlogloss:1.34164
[596]	train-mlogloss:1.25617	validation-mlogloss:1.34164
[597]	train-mlogloss:1.25617	validation-mlogloss:1.34164
[598]	train-mlogloss:1.25606	validation-mlogloss:1.34160
[599]	train-mlogloss:1.25602	validation-mlogloss:1.34154
[600]	train-mlogloss:1.25589	validation-mlogloss:1.34143
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[602]	train-mlogloss:1.25581	validation-mlogloss:1.34143
[603]	train-mlogloss:1.25576	validation-mlogloss:1.34140
[604]	train-mlogloss:1.25569	validation-mlogloss:1.34136
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[606]	train-mlogloss:1.25557	validation-mlogloss:1.34129
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[632]	train-mlogloss:1.25453	validation-mlogloss:1.34072
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[643]	train-mlogloss:1.25384	validation-mlogloss:1.34026
[644]	train-mlogloss:1.25384	validation-mlogloss:1.34026
[645]	train-mlogloss:1.25378	validation-mlogloss:1.34020
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[650]	train-mlogloss:1.25368	validation-mlogloss:1.34018
[651]	train-mlogloss:1.25361	validation-mlogloss:1.34009
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[653]	train-mlogloss:1.25359	validation-mlogloss:1.34008
[654]	train-mlogloss:1.25353	validation-mlogloss:1.34003
[655]	train-mlogloss:1.25352	validation-mlogloss:1.34002
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[663]	train-mlogloss:1.25299	validation-mlogloss:1.33961
[664]	train-mlogloss:1.25295	validation-mlogloss:1.33958
[665]	train-mlogloss:1.25291	validation-mlogloss:1.33954
[666]	train-mlogloss:1.25287	validation-mlogloss:1.33953
[667]	train-mlogloss:1.25287	validation-mlogloss:1.33953
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[669]	train-mlogloss:1.25281	validation-mlogloss:1.33951
[670]	train-mlogloss:1.25281	validation-mlogloss:1.33951
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[672]	train-mlogloss:1.25273	validation-mlogloss:1.33947
[673]	train-mlogloss:1.25266	validation-mlogloss:1.33941
[674]	train-mlogloss:1.25263	validation-mlogloss:1.33938
[675]	train-mlogloss:1.25263	validation-mlogloss:1.33938
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[677]	train-mlogloss:1.25254	validation-mlogloss:1.33928
[678]	train-mlogloss:1.25253	validation-mlogloss:1.33927
[679]	train-mlogloss:1.25251	validation-mlogloss:1.33925
[680]	train-mlogloss:1.25251	validation-mlogloss:1.33925
[681]	train-mlogloss:1.25251	validation-mlogloss:1.33924
[682]	train-mlogloss:1.25247	validation-mlogloss:1.33925
[683]	train-mlogloss:1.25238	validation-mlogloss:1.33921
[684]	train-mlogloss:1.25235	validation-mlogloss:1.33918
[685]	train-mlogloss:1.25234	validation-mlogloss:1.33918
[686]	train-mlogloss:1.25222	validation-mlogloss:1.33913
[687]	train-mlogloss:1.25222	validation-mlogloss:1.33913
[688]	train-mlogloss:1.25222	validation-mlogloss:1.33913
[689]	train-mlogloss:1.25219	validation-mlogloss:1.33914
[690]	train-mlogloss:1.25216	validation-mlogloss:1.33912
[691]	train-mlogloss:1.25215	validation-mlogloss:1.33911
[692]	train-mlogloss:1.25215	validation-mlogloss:1.33911
[693]	train-mlogloss:1.25212	validation-mlogloss:1.33910
[694]	train-mlogloss:1.25212	validation-mlogloss:1.33910
[695]	train-mlogloss:1.25207	validation-mlogloss:1.33906
[696]	train-mlogloss:1.25202	validation-mlogloss:1.33905
[697]	train-mlogloss:1.25194	validation-mlogloss:1.33896
[698]	train-mlogloss:1.25193	validation-mlogloss:1.33896
[699]	train-mlogloss:1.25193	validation-mlogloss:1.33896
[700]	train-mlogloss:1.25193	validation-mlogloss:1.33897
[701]	train-mlogloss:1.25189	validation-mlogloss:1.33896
[702]	train-mlogloss:1.25184	validation-mlogloss:1.33891
[703]	train-mlogloss:1.25183	validation-mlogloss:1.33894
[704]	train-mlogloss:1.25183	validation-mlogloss:1.33894
[705]	train-mlogloss:1.25175	validation-mlogloss:1.33889
[706]	train-mlogloss:1.25171	validation-mlogloss:1.33889
[707]	train-mlogloss:1.25171	validation-mlogloss:1.33889
[708]	train-mlogloss:1.25169	validation-mlogloss:1.33888
[709]	train-mlogloss:1.25168	validation-mlogloss:1.33886
[710]	train-mlogloss:1.25162	validation-mlogloss:1.33883
[711]	train-mlogloss:1.25160	validation-mlogloss:1.33883
[712]	train-mlogloss:1.25160	validation-mlogloss:1.33883
[713]	train-mlogloss:1.25159	validation-mlogloss:1.33881
Saved model to disk.
2025-10-27 11:21:44.093399: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:21:44.106211: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560504.120096  535626 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560504.124339  535626 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560504.135599  535626 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560504.135623  535626 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560504.135626  535626 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560504.135629  535626 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:21:44.139019: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68493	validation-mlogloss:2.68524
[1]	train-mlogloss:2.66148	validation-mlogloss:2.66219
[2]	train-mlogloss:2.63974	validation-mlogloss:2.64096
[3]	train-mlogloss:2.61849	validation-mlogloss:2.62053
[4]	train-mlogloss:2.59694	validation-mlogloss:2.59866
[5]	train-mlogloss:2.57760	validation-mlogloss:2.57950
[6]	train-mlogloss:2.55771	validation-mlogloss:2.56011
[7]	train-mlogloss:2.53805	validation-mlogloss:2.54097
[8]	train-mlogloss:2.51849	validation-mlogloss:2.52210
[9]	train-mlogloss:2.49868	validation-mlogloss:2.50297
[10]	train-mlogloss:2.48037	validation-mlogloss:2.48562
[11]	train-mlogloss:2.46295	validation-mlogloss:2.46832
[12]	train-mlogloss:2.44534	validation-mlogloss:2.45080
[13]	train-mlogloss:2.42874	validation-mlogloss:2.43463
[14]	train-mlogloss:2.41163	validation-mlogloss:2.41769
[15]	train-mlogloss:2.39519	validation-mlogloss:2.40177
[16]	train-mlogloss:2.38036	validation-mlogloss:2.38726
[17]	train-mlogloss:2.36472	validation-mlogloss:2.37241
[18]	train-mlogloss:2.34880	validation-mlogloss:2.35703
[19]	train-mlogloss:2.33402	validation-mlogloss:2.34240
[20]	train-mlogloss:2.31942	validation-mlogloss:2.32828
[21]	train-mlogloss:2.30522	validation-mlogloss:2.31466
[22]	train-mlogloss:2.29134	validation-mlogloss:2.30085
[23]	train-mlogloss:2.27750	validation-mlogloss:2.28787
[24]	train-mlogloss:2.26391	validation-mlogloss:2.27509
[25]	train-mlogloss:2.25073	validation-mlogloss:2.26220
[26]	train-mlogloss:2.23754	validation-mlogloss:2.24927
[27]	train-mlogloss:2.22493	validation-mlogloss:2.23693
[28]	train-mlogloss:2.21245	validation-mlogloss:2.22414
[29]	train-mlogloss:2.20029	validation-mlogloss:2.21209
[30]	train-mlogloss:2.18849	validation-mlogloss:2.20100
[31]	train-mlogloss:2.17712	validation-mlogloss:2.18998
[32]	train-mlogloss:2.16584	validation-mlogloss:2.17936
[33]	train-mlogloss:2.15468	validation-mlogloss:2.16897
[34]	train-mlogloss:2.14375	validation-mlogloss:2.15869
[35]	train-mlogloss:2.13258	validation-mlogloss:2.14768
[36]	train-mlogloss:2.12182	validation-mlogloss:2.13699
[37]	train-mlogloss:2.11116	validation-mlogloss:2.12667
[38]	train-mlogloss:2.10093	validation-mlogloss:2.11677
[39]	train-mlogloss:2.09099	validation-mlogloss:2.10698
[40]	train-mlogloss:2.08130	validation-mlogloss:2.09713
[41]	train-mlogloss:2.07131	validation-mlogloss:2.08743
[42]	train-mlogloss:2.06197	validation-mlogloss:2.07774
[43]	train-mlogloss:2.05235	validation-mlogloss:2.06875
[44]	train-mlogloss:2.04302	validation-mlogloss:2.05960
[45]	train-mlogloss:2.03383	validation-mlogloss:2.05059
[46]	train-mlogloss:2.02504	validation-mlogloss:2.04200
[47]	train-mlogloss:2.01603	validation-mlogloss:2.03330
[48]	train-mlogloss:2.00721	validation-mlogloss:2.02476
[49]	train-mlogloss:1.99830	validation-mlogloss:2.01595
[50]	train-mlogloss:1.98972	validation-mlogloss:2.00768
[51]	train-mlogloss:1.98116	validation-mlogloss:1.99951
[52]	train-mlogloss:1.97303	validation-mlogloss:1.99119
[53]	train-mlogloss:1.96483	validation-mlogloss:1.98362
[54]	train-mlogloss:1.95668	validation-mlogloss:1.97595
[55]	train-mlogloss:1.94872	validation-mlogloss:1.96831
[56]	train-mlogloss:1.94117	validation-mlogloss:1.96100
[57]	train-mlogloss:1.93335	validation-mlogloss:1.95345
[58]	train-mlogloss:1.92580	validation-mlogloss:1.94626
[59]	train-mlogloss:1.91845	validation-mlogloss:1.93920
[60]	train-mlogloss:1.91140	validation-mlogloss:1.93213
[61]	train-mlogloss:1.90399	validation-mlogloss:1.92506
[62]	train-mlogloss:1.89690	validation-mlogloss:1.91820
[63]	train-mlogloss:1.88988	validation-mlogloss:1.91166
[64]	train-mlogloss:1.88297	validation-mlogloss:1.90506
[65]	train-mlogloss:1.87626	validation-mlogloss:1.89841
[66]	train-mlogloss:1.86968	validation-mlogloss:1.89185
[67]	train-mlogloss:1.86291	validation-mlogloss:1.88508
[68]	train-mlogloss:1.85663	validation-mlogloss:1.87905
[69]	train-mlogloss:1.85041	validation-mlogloss:1.87311
[70]	train-mlogloss:1.84418	validation-mlogloss:1.86704
[71]	train-mlogloss:1.83784	validation-mlogloss:1.86099
[72]	train-mlogloss:1.83158	validation-mlogloss:1.85501
[73]	train-mlogloss:1.82569	validation-mlogloss:1.84918
[74]	train-mlogloss:1.81988	validation-mlogloss:1.84340
[75]	train-mlogloss:1.81412	validation-mlogloss:1.83784
[76]	train-mlogloss:1.80829	validation-mlogloss:1.83210
[77]	train-mlogloss:1.80253	validation-mlogloss:1.82666
[78]	train-mlogloss:1.79696	validation-mlogloss:1.82155
[79]	train-mlogloss:1.79140	validation-mlogloss:1.81624
[80]	train-mlogloss:1.78593	validation-mlogloss:1.81098
[81]	train-mlogloss:1.78051	validation-mlogloss:1.80574
[82]	train-mlogloss:1.77516	validation-mlogloss:1.80037
[83]	train-mlogloss:1.76977	validation-mlogloss:1.79511
[84]	train-mlogloss:1.76464	validation-mlogloss:1.79000
[85]	train-mlogloss:1.75937	validation-mlogloss:1.78506
[86]	train-mlogloss:1.75453	validation-mlogloss:1.78041
[87]	train-mlogloss:1.74961	validation-mlogloss:1.77523
[88]	train-mlogloss:1.74464	validation-mlogloss:1.77087
[89]	train-mlogloss:1.73975	validation-mlogloss:1.76597
[90]	train-mlogloss:1.73483	validation-mlogloss:1.76129
[91]	train-mlogloss:1.72997	validation-mlogloss:1.75657
[92]	train-mlogloss:1.72519	validation-mlogloss:1.75199
[93]	train-mlogloss:1.72047	validation-mlogloss:1.74756
[94]	train-mlogloss:1.71573	validation-mlogloss:1.74293
[95]	train-mlogloss:1.71117	validation-mlogloss:1.73850
[96]	train-mlogloss:1.70654	validation-mlogloss:1.73413
[97]	train-mlogloss:1.70216	validation-mlogloss:1.72990
[98]	train-mlogloss:1.69782	validation-mlogloss:1.72564
[99]	train-mlogloss:1.69333	validation-mlogloss:1.72134
[100]	train-mlogloss:1.68903	validation-mlogloss:1.71736
[101]	train-mlogloss:1.68467	validation-mlogloss:1.71320
[102]	train-mlogloss:1.68053	validation-mlogloss:1.70942
[103]	train-mlogloss:1.67635	validation-mlogloss:1.70565
[104]	train-mlogloss:1.67230	validation-mlogloss:1.70149
[105]	train-mlogloss:1.66830	validation-mlogloss:1.69786
[106]	train-mlogloss:1.66424	validation-mlogloss:1.69413
[107]	train-mlogloss:1.66030	validation-mlogloss:1.69032
[108]	train-mlogloss:1.65639	validation-mlogloss:1.68653
[109]	train-mlogloss:1.65219	validation-mlogloss:1.68249
[110]	train-mlogloss:1.64836	validation-mlogloss:1.67873
[111]	train-mlogloss:1.64445	validation-mlogloss:1.67519
[112]	train-mlogloss:1.64072	validation-mlogloss:1.67182
[113]	train-mlogloss:1.63706	validation-mlogloss:1.66852
[114]	train-mlogloss:1.63344	validation-mlogloss:1.66485
[115]	train-mlogloss:1.62981	validation-mlogloss:1.66160
[116]	train-mlogloss:1.62620	validation-mlogloss:1.65850
[117]	train-mlogloss:1.62265	validation-mlogloss:1.65544
[118]	train-mlogloss:1.61910	validation-mlogloss:1.65214
[119]	train-mlogloss:1.61552	validation-mlogloss:1.64888
[120]	train-mlogloss:1.61178	validation-mlogloss:1.64538
[121]	train-mlogloss:1.60839	validation-mlogloss:1.64214
[122]	train-mlogloss:1.60492	validation-mlogloss:1.63888
[123]	train-mlogloss:1.60182	validation-mlogloss:1.63605
[124]	train-mlogloss:1.59843	validation-mlogloss:1.63286
[125]	train-mlogloss:1.59529	validation-mlogloss:1.62979
[126]	train-mlogloss:1.59225	validation-mlogloss:1.62668
[127]	train-mlogloss:1.58907	validation-mlogloss:1.62374
[128]	train-mlogloss:1.58599	validation-mlogloss:1.62082
[129]	train-mlogloss:1.58291	validation-mlogloss:1.61786
[130]	train-mlogloss:1.57989	validation-mlogloss:1.61505
[131]	train-mlogloss:1.57684	validation-mlogloss:1.61221
[132]	train-mlogloss:1.57381	validation-mlogloss:1.60952
[133]	train-mlogloss:1.57100	validation-mlogloss:1.60677
[134]	train-mlogloss:1.56822	validation-mlogloss:1.60418
[135]	train-mlogloss:1.56542	validation-mlogloss:1.60135
[136]	train-mlogloss:1.56256	validation-mlogloss:1.59868
[137]	train-mlogloss:1.55964	validation-mlogloss:1.59599
[138]	train-mlogloss:1.55688	validation-mlogloss:1.59357
[139]	train-mlogloss:1.55402	validation-mlogloss:1.59071
[140]	train-mlogloss:1.55115	validation-mlogloss:1.58792
[141]	train-mlogloss:1.54841	validation-mlogloss:1.58557
[142]	train-mlogloss:1.54573	validation-mlogloss:1.58301
[143]	train-mlogloss:1.54319	validation-mlogloss:1.58066
[144]	train-mlogloss:1.54046	validation-mlogloss:1.57816
[145]	train-mlogloss:1.53778	validation-mlogloss:1.57561
[146]	train-mlogloss:1.53499	validation-mlogloss:1.57332
[147]	train-mlogloss:1.53250	validation-mlogloss:1.57095
[148]	train-mlogloss:1.52991	validation-mlogloss:1.56860
[149]	train-mlogloss:1.52741	validation-mlogloss:1.56622
[150]	train-mlogloss:1.52487	validation-mlogloss:1.56386
[151]	train-mlogloss:1.52231	validation-mlogloss:1.56152
[152]	train-mlogloss:1.51994	validation-mlogloss:1.55927
[153]	train-mlogloss:1.51762	validation-mlogloss:1.55710
[154]	train-mlogloss:1.51529	validation-mlogloss:1.55495
[155]	train-mlogloss:1.51284	validation-mlogloss:1.55281
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[466]	train-mlogloss:1.26662	validation-mlogloss:1.35051
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[472]	train-mlogloss:1.26590	validation-mlogloss:1.34993
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[475]	train-mlogloss:1.26561	validation-mlogloss:1.34971
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[554]	train-mlogloss:1.25927	validation-mlogloss:1.34513
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[560]	train-mlogloss:1.25890	validation-mlogloss:1.34499
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[695]	train-mlogloss:1.25305	validation-mlogloss:1.34163
[696]	train-mlogloss:1.25303	validation-mlogloss:1.34160
[697]	train-mlogloss:1.25294	validation-mlogloss:1.34153
[698]	train-mlogloss:1.25291	validation-mlogloss:1.34150
[699]	train-mlogloss:1.25282	validation-mlogloss:1.34151
[700]	train-mlogloss:1.25281	validation-mlogloss:1.34151
[701]	train-mlogloss:1.25279	validation-mlogloss:1.34151
[702]	train-mlogloss:1.25272	validation-mlogloss:1.34142
[703]	train-mlogloss:1.25269	validation-mlogloss:1.34139
[704]	train-mlogloss:1.25262	validation-mlogloss:1.34141
[705]	train-mlogloss:1.25262	validation-mlogloss:1.34141
[706]	train-mlogloss:1.25261	validation-mlogloss:1.34140
[707]	train-mlogloss:1.25255	validation-mlogloss:1.34133
[708]	train-mlogloss:1.25254	validation-mlogloss:1.34132
[709]	train-mlogloss:1.25251	validation-mlogloss:1.34131
[710]	train-mlogloss:1.25249	validation-mlogloss:1.34130
[711]	train-mlogloss:1.25241	validation-mlogloss:1.34131
[712]	train-mlogloss:1.25241	validation-mlogloss:1.34131
[713]	train-mlogloss:1.25234	validation-mlogloss:1.34127
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.82 [%]
Global accuracy score (test) = 50.2 [%]
Global F1 score (train) = 62.89 [%]
Global F1 score (test) = 50.34 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.27      0.40      0.32       184
 CAMINAR CON MÓVIL O LIBRO       0.42      0.40      0.41       184
       CAMINAR USUAL SPEED       0.25      0.17      0.21       184
            CAMINAR ZIGZAG       0.59      0.53      0.56       184
          DE PIE BARRIENDO       0.54      0.48      0.51       184
   DE PIE DOBLANDO TOALLAS       0.43      0.47      0.45       184
    DE PIE MOVIENDO LIBROS       0.48      0.45      0.47       184
          DE PIE USANDO PC       0.60      0.66      0.63       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.88      0.64      0.74       184
           SENTADO LEYENDO       0.36      0.42      0.39       184
         SENTADO USANDO PC       0.43      0.29      0.34       184
      SENTADO VIENDO LA TV       0.46      0.39      0.42       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.67      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.50      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 7: 50.2 [%]
F1-score capturado en la ejecución 7: 50.34 [%]

=== EJECUCIÓN 8 ===

--- TRAIN (ejecución 8) ---

--- TEST (ejecución 8) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.7 [%]
Global accuracy score (test) = 50.31 [%]
Global F1 score (train) = 62.75 [%]
Global F1 score (test) = 50.48 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.27      0.38      0.31       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.39      0.41       184
       CAMINAR USUAL SPEED       0.30      0.23      0.26       184
            CAMINAR ZIGZAG       0.59      0.53      0.56       184
          DE PIE BARRIENDO       0.53      0.50      0.52       184
   DE PIE DOBLANDO TOALLAS       0.46      0.48      0.47       184
    DE PIE MOVIENDO LIBROS       0.48      0.45      0.46       184
          DE PIE USANDO PC       0.63      0.66      0.65       184
        FASE REPOSO CON K5       0.55      0.78      0.64       184
INCREMENTAL CICLOERGOMETRO       0.87      0.64      0.74       184
           SENTADO LEYENDO       0.34      0.43      0.38       184
         SENTADO USANDO PC       0.38      0.23      0.29       184
      SENTADO VIENDO LA TV       0.46      0.39      0.42       184
   SUBIR Y BAJAR ESCALERAS       0.52      0.67      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.51      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 8: 50.31 [%]
F1-score capturado en la ejecución 8: 50.48 [%]

=== EJECUCIÓN 9 ===

--- TRAIN (ejecución 9) ---

--- TEST (ejecución 9) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.84 [%]
Global accuracy score (test) = 50.68 [%]
Global F1 score (train) = 62.91 [%]
Global F1 score (test) = 50.93 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.39      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.47      0.46      0.47       184
       CAMINAR USUAL SPEED       0.31      0.24      0.27       184
            CAMINAR ZIGZAG       0.58      0.54      0.56       184
          DE PIE BARRIENDO       0.56      0.49      0.53       184
   DE PIE DOBLANDO TOALLAS       0.41      0.45      0.43       184
    DE PIE MOVIENDO LIBROS       0.46      0.45      0.45       184
          DE PIE USANDO PC       0.64      0.67      0.65       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.90      0.63      0.74       184
           SENTADO LEYENDO       0.34      0.42      0.38       184
         SENTADO USANDO PC       0.40      0.26      0.32       184
      SENTADO VIENDO LA TV       0.45      0.38      0.41       184
   SUBIR Y BAJAR ESCALERAS       0.54      0.66      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.51      2737


Accuracy capturado en la ejecución 9: 50.68 [%]
F1-score capturado en la ejecución 9: 50.93 [%]

=== EJECUCIÓN 10 ===

--- TRAIN (ejecución 10) ---

--- TEST (ejecución 10) ---
2025-10-27 11:22:31.218889: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:22:31.231374: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560551.245186  536564 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560551.249337  536564 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560551.260430  536564 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560551.260454  536564 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560551.260457  536564 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560551.260460  536564 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:22:31.263812: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68311	validation-mlogloss:2.68357
[1]	train-mlogloss:2.66048	validation-mlogloss:2.66125
[2]	train-mlogloss:2.63830	validation-mlogloss:2.63949
[3]	train-mlogloss:2.61580	validation-mlogloss:2.61745
[4]	train-mlogloss:2.59534	validation-mlogloss:2.59756
[5]	train-mlogloss:2.57514	validation-mlogloss:2.57801
[6]	train-mlogloss:2.55535	validation-mlogloss:2.55814
[7]	train-mlogloss:2.53600	validation-mlogloss:2.53932
[8]	train-mlogloss:2.51774	validation-mlogloss:2.52127
[9]	train-mlogloss:2.50006	validation-mlogloss:2.50391
[10]	train-mlogloss:2.48283	validation-mlogloss:2.48770
[11]	train-mlogloss:2.46460	validation-mlogloss:2.46957
[12]	train-mlogloss:2.44747	validation-mlogloss:2.45321
[13]	train-mlogloss:2.43008	validation-mlogloss:2.43709
[14]	train-mlogloss:2.41328	validation-mlogloss:2.42142
[15]	train-mlogloss:2.39678	validation-mlogloss:2.40533
[16]	train-mlogloss:2.38083	validation-mlogloss:2.39016
[17]	train-mlogloss:2.36485	validation-mlogloss:2.37466
[18]	train-mlogloss:2.34933	validation-mlogloss:2.35926
[19]	train-mlogloss:2.33448	validation-mlogloss:2.34491
[20]	train-mlogloss:2.32008	validation-mlogloss:2.33108
[21]	train-mlogloss:2.30583	validation-mlogloss:2.31746
[22]	train-mlogloss:2.29172	validation-mlogloss:2.30351
[23]	train-mlogloss:2.27792	validation-mlogloss:2.28988
[24]	train-mlogloss:2.26436	validation-mlogloss:2.27642
[25]	train-mlogloss:2.25104	validation-mlogloss:2.26351
[26]	train-mlogloss:2.23821	validation-mlogloss:2.25072
[27]	train-mlogloss:2.22550	validation-mlogloss:2.23813
[28]	train-mlogloss:2.21289	validation-mlogloss:2.22569
[29]	train-mlogloss:2.20062	validation-mlogloss:2.21416
[30]	train-mlogloss:2.18914	validation-mlogloss:2.20274
[31]	train-mlogloss:2.17737	validation-mlogloss:2.19152
[32]	train-mlogloss:2.16627	validation-mlogloss:2.18079
[33]	train-mlogloss:2.15475	validation-mlogloss:2.17004
[34]	train-mlogloss:2.14343	validation-mlogloss:2.15922
[35]	train-mlogloss:2.13256	validation-mlogloss:2.14863
[36]	train-mlogloss:2.12197	validation-mlogloss:2.13767
[37]	train-mlogloss:2.11120	validation-mlogloss:2.12730
[38]	train-mlogloss:2.10071	validation-mlogloss:2.11731
[39]	train-mlogloss:2.09035	validation-mlogloss:2.10687
[40]	train-mlogloss:2.08032	validation-mlogloss:2.09700
[41]	train-mlogloss:2.07047	validation-mlogloss:2.08748
[42]	train-mlogloss:2.06114	validation-mlogloss:2.07881
[43]	train-mlogloss:2.05159	validation-mlogloss:2.06936
[44]	train-mlogloss:2.04200	validation-mlogloss:2.06065
[45]	train-mlogloss:2.03275	validation-mlogloss:2.05154
[46]	train-mlogloss:2.02370	validation-mlogloss:2.04292
[47]	train-mlogloss:2.01500	validation-mlogloss:2.03451
[48]	train-mlogloss:2.00643	validation-mlogloss:2.02610
[49]	train-mlogloss:1.99765	validation-mlogloss:2.01727
[50]	train-mlogloss:1.98931	validation-mlogloss:2.00932
[51]	train-mlogloss:1.98113	validation-mlogloss:2.00185
[52]	train-mlogloss:1.97266	validation-mlogloss:1.99367
[53]	train-mlogloss:1.96439	validation-mlogloss:1.98543
[54]	train-mlogloss:1.95661	validation-mlogloss:1.97824
[55]	train-mlogloss:1.94888	validation-mlogloss:1.97028
[56]	train-mlogloss:1.94123	validation-mlogloss:1.96269
[57]	train-mlogloss:1.93392	validation-mlogloss:1.95559
[58]	train-mlogloss:1.92641	validation-mlogloss:1.94828
[59]	train-mlogloss:1.91918	validation-mlogloss:1.94109
[60]	train-mlogloss:1.91203	validation-mlogloss:1.93377
[61]	train-mlogloss:1.90479	validation-mlogloss:1.92674
[62]	train-mlogloss:1.89775	validation-mlogloss:1.92031
[63]	train-mlogloss:1.89067	validation-mlogloss:1.91333
[64]	train-mlogloss:1.88386	validation-mlogloss:1.90678
[65]	train-mlogloss:1.87694	validation-mlogloss:1.90029
[66]	train-mlogloss:1.87041	validation-mlogloss:1.89417
[67]	train-mlogloss:1.86357	validation-mlogloss:1.88753
[68]	train-mlogloss:1.85706	validation-mlogloss:1.88125
[69]	train-mlogloss:1.85048	validation-mlogloss:1.87495
[70]	train-mlogloss:1.84414	validation-mlogloss:1.86891
[71]	train-mlogloss:1.83824	validation-mlogloss:1.86324
[72]	train-mlogloss:1.83204	validation-mlogloss:1.85749
[73]	train-mlogloss:1.82600	validation-mlogloss:1.85179
[74]	train-mlogloss:1.82014	validation-mlogloss:1.84622
[75]	train-mlogloss:1.81444	validation-mlogloss:1.84076
[76]	train-mlogloss:1.80876	validation-mlogloss:1.83520
[77]	train-mlogloss:1.80297	validation-mlogloss:1.82973
[78]	train-mlogloss:1.79741	validation-mlogloss:1.82403
[79]	train-mlogloss:1.79169	validation-mlogloss:1.81806
[80]	train-mlogloss:1.78608	validation-mlogloss:1.81249
[81]	train-mlogloss:1.78062	validation-mlogloss:1.80718
[82]	train-mlogloss:1.77536	validation-mlogloss:1.80209
[83]	train-mlogloss:1.77008	validation-mlogloss:1.79699
[84]	train-mlogloss:1.76488	validation-mlogloss:1.79204
[85]	train-mlogloss:1.75986	validation-mlogloss:1.78752
[86]	train-mlogloss:1.75486	validation-mlogloss:1.78269
[87]	train-mlogloss:1.74975	validation-mlogloss:1.77798
[88]	train-mlogloss:1.74479	validation-mlogloss:1.77302
[89]	train-mlogloss:1.74005	validation-mlogloss:1.76832
[90]	train-mlogloss:1.73528	validation-mlogloss:1.76375
[91]	train-mlogloss:1.73037	validation-mlogloss:1.75899
[92]	train-mlogloss:1.72572	validation-mlogloss:1.75460
[93]	train-mlogloss:1.72098	validation-mlogloss:1.74980
[94]	train-mlogloss:1.71644	validation-mlogloss:1.74548
[95]	train-mlogloss:1.71184	validation-mlogloss:1.74110
[96]	train-mlogloss:1.70713	validation-mlogloss:1.73661
[97]	train-mlogloss:1.70269	validation-mlogloss:1.73221
[98]	train-mlogloss:1.69840	validation-mlogloss:1.72803
[99]	train-mlogloss:1.69403	validation-mlogloss:1.72384
[100]	train-mlogloss:1.68986	validation-mlogloss:1.71984
[101]	train-mlogloss:1.68556	validation-mlogloss:1.71560
[102]	train-mlogloss:1.68128	validation-mlogloss:1.71144
[103]	train-mlogloss:1.67714	validation-mlogloss:1.70746
[104]	train-mlogloss:1.67304	validation-mlogloss:1.70365
[105]	train-mlogloss:1.66898	validation-mlogloss:1.69971
[106]	train-mlogloss:1.66488	validation-mlogloss:1.69578
[107]	train-mlogloss:1.66102	validation-mlogloss:1.69192
[108]	train-mlogloss:1.65716	validation-mlogloss:1.68838
[109]	train-mlogloss:1.65326	validation-mlogloss:1.68487
[110]	train-mlogloss:1.64956	validation-mlogloss:1.68129
[111]	train-mlogloss:1.64570	validation-mlogloss:1.67772
[112]	train-mlogloss:1.64188	validation-mlogloss:1.67413
[113]	train-mlogloss:1.63816	validation-mlogloss:1.67044
[114]	train-mlogloss:1.63453	validation-mlogloss:1.66703
[115]	train-mlogloss:1.63097	validation-mlogloss:1.66353
[116]	train-mlogloss:1.62736	validation-mlogloss:1.66029
[117]	train-mlogloss:1.62391	validation-mlogloss:1.65711
[118]	train-mlogloss:1.62051	validation-mlogloss:1.65367
[119]	train-mlogloss:1.61708	validation-mlogloss:1.65045
[120]	train-mlogloss:1.61370	validation-mlogloss:1.64742
[121]	train-mlogloss:1.61036	validation-mlogloss:1.64404
[122]	train-mlogloss:1.60704	validation-mlogloss:1.64080
[123]	train-mlogloss:1.60386	validation-mlogloss:1.63789
[124]	train-mlogloss:1.60052	validation-mlogloss:1.63486
[125]	train-mlogloss:1.59716	validation-mlogloss:1.63165
[126]	train-mlogloss:1.59396	validation-mlogloss:1.62866
[127]	train-mlogloss:1.59059	validation-mlogloss:1.62551
[128]	train-mlogloss:1.58738	validation-mlogloss:1.62252
[129]	train-mlogloss:1.58426	validation-mlogloss:1.61968
[130]	train-mlogloss:1.58127	validation-mlogloss:1.61708
[131]	train-mlogloss:1.57814	validation-mlogloss:1.61422
[132]	train-mlogloss:1.57501	validation-mlogloss:1.61108
[133]	train-mlogloss:1.57211	validation-mlogloss:1.60842
[134]	train-mlogloss:1.56904	validation-mlogloss:1.60565
[135]	train-mlogloss:1.56633	validation-mlogloss:1.60289
[136]	train-mlogloss:1.56340	validation-mlogloss:1.60018
[137]	train-mlogloss:1.56071	validation-mlogloss:1.59768
[138]	train-mlogloss:1.55793	validation-mlogloss:1.59496
[139]	train-mlogloss:1.55506	validation-mlogloss:1.59215
[140]	train-mlogloss:1.55223	validation-mlogloss:1.58972
[141]	train-mlogloss:1.54943	validation-mlogloss:1.58707
[142]	train-mlogloss:1.54682	validation-mlogloss:1.58473
[143]	train-mlogloss:1.54408	validation-mlogloss:1.58236
[144]	train-mlogloss:1.54144	validation-mlogloss:1.58004
[145]	train-mlogloss:1.53877	validation-mlogloss:1.57741
[146]	train-mlogloss:1.53617	validation-mlogloss:1.57502
[147]	train-mlogloss:1.53359	validation-mlogloss:1.57258
[148]	train-mlogloss:1.53102	validation-mlogloss:1.57023
[149]	train-mlogloss:1.52850	validation-mlogloss:1.56790
[150]	train-mlogloss:1.52606	validation-mlogloss:1.56570
[151]	train-mlogloss:1.52350	validation-mlogloss:1.56338
[152]	train-mlogloss:1.52109	validation-mlogloss:1.56119
[153]	train-mlogloss:1.51863	validation-mlogloss:1.55897
[154]	train-mlogloss:1.51614	validation-mlogloss:1.55681
[155]	train-mlogloss:1.51394	validation-mlogloss:1.55474
[156]	train-mlogloss:1.51158	validation-mlogloss:1.55255
[157]	train-mlogloss:1.50931	validation-mlogloss:1.55030
[158]	train-mlogloss:1.50697	validation-mlogloss:1.54823
[159]	train-mlogloss:1.50468	validation-mlogloss:1.54617
[160]	train-mlogloss:1.50243	validation-mlogloss:1.54408
[161]	train-mlogloss:1.50024	validation-mlogloss:1.54216
[162]	train-mlogloss:1.49795	validation-mlogloss:1.53999
[163]	train-mlogloss:1.49580	validation-mlogloss:1.53796
[164]	train-mlogloss:1.49368	validation-mlogloss:1.53620
[165]	train-mlogloss:1.49164	validation-mlogloss:1.53434
[166]	train-mlogloss:1.48954	validation-mlogloss:1.53248
[167]	train-mlogloss:1.48744	validation-mlogloss:1.53040
[168]	train-mlogloss:1.48515	validation-mlogloss:1.52822
[169]	train-mlogloss:1.48298	validation-mlogloss:1.52633
[170]	train-mlogloss:1.48095	validation-mlogloss:1.52450
[171]	train-mlogloss:1.47889	validation-mlogloss:1.52271
[172]	train-mlogloss:1.47673	validation-mlogloss:1.52086
[173]	train-mlogloss:1.47472	validation-mlogloss:1.51915
[174]	train-mlogloss:1.47276	validation-mlogloss:1.51741
[175]	train-mlogloss:1.47085	validation-mlogloss:1.51565
[176]	train-mlogloss:1.46882	validation-mlogloss:1.51381
[177]	train-mlogloss:1.46688	validation-mlogloss:1.51214
[178]	train-mlogloss:1.46493	validation-mlogloss:1.51042
[179]	train-mlogloss:1.46286	validation-mlogloss:1.50870
[180]	train-mlogloss:1.46094	validation-mlogloss:1.50689
[181]	train-mlogloss:1.45912	validation-mlogloss:1.50543
[182]	train-mlogloss:1.45735	validation-mlogloss:1.50391
[183]	train-mlogloss:1.45554	validation-mlogloss:1.50232
[184]	train-mlogloss:1.45370	validation-mlogloss:1.50060
[185]	train-mlogloss:1.45185	validation-mlogloss:1.49873
[186]	train-mlogloss:1.45001	validation-mlogloss:1.49715
[187]	train-mlogloss:1.44817	validation-mlogloss:1.49548
[188]	train-mlogloss:1.44640	validation-mlogloss:1.49388
[189]	train-mlogloss:1.44462	validation-mlogloss:1.49239
[190]	train-mlogloss:1.44283	validation-mlogloss:1.49097
[191]	train-mlogloss:1.44114	validation-mlogloss:1.48960
[192]	train-mlogloss:1.43944	validation-mlogloss:1.48811
[193]	train-mlogloss:1.43778	validation-mlogloss:1.48670
[194]	train-mlogloss:1.43621	validation-mlogloss:1.48527
[195]	train-mlogloss:1.43448	validation-mlogloss:1.48386
[196]	train-mlogloss:1.43282	validation-mlogloss:1.48250
[197]	train-mlogloss:1.43141	validation-mlogloss:1.48105
[198]	train-mlogloss:1.42973	validation-mlogloss:1.47963
[199]	train-mlogloss:1.42822	validation-mlogloss:1.47832
[200]	train-mlogloss:1.42666	validation-mlogloss:1.47713
[201]	train-mlogloss:1.42503	validation-mlogloss:1.47571
[202]	train-mlogloss:1.42345	validation-mlogloss:1.47439
[203]	train-mlogloss:1.42195	validation-mlogloss:1.47308
[204]	train-mlogloss:1.42037	validation-mlogloss:1.47157
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[537]	train-mlogloss:1.26129	validation-mlogloss:1.34671
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[542]	train-mlogloss:1.26096	validation-mlogloss:1.34663
[543]	train-mlogloss:1.26084	validation-mlogloss:1.34653
[544]	train-mlogloss:1.26078	validation-mlogloss:1.34649
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[562]	train-mlogloss:1.25962	validation-mlogloss:1.34580
[563]	train-mlogloss:1.25962	validation-mlogloss:1.34580
[564]	train-mlogloss:1.25960	validation-mlogloss:1.34577
[565]	train-mlogloss:1.25960	validation-mlogloss:1.34578
[566]	train-mlogloss:1.25950	validation-mlogloss:1.34572
[567]	train-mlogloss:1.25937	validation-mlogloss:1.34575
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[569]	train-mlogloss:1.25933	validation-mlogloss:1.34572
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[571]	train-mlogloss:1.25916	validation-mlogloss:1.34549
[572]	train-mlogloss:1.25911	validation-mlogloss:1.34549
[573]	train-mlogloss:1.25904	validation-mlogloss:1.34544
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[581]	train-mlogloss:1.25861	validation-mlogloss:1.34522
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[640]	train-mlogloss:1.25589	validation-mlogloss:1.34360
[641]	train-mlogloss:1.25584	validation-mlogloss:1.34354
[642]	train-mlogloss:1.25580	validation-mlogloss:1.34351
[643]	train-mlogloss:1.25576	validation-mlogloss:1.34350
[644]	train-mlogloss:1.25566	validation-mlogloss:1.34345
[645]	train-mlogloss:1.25566	validation-mlogloss:1.34346
[646]	train-mlogloss:1.25565	validation-mlogloss:1.34347
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[649]	train-mlogloss:1.25550	validation-mlogloss:1.34337
[650]	train-mlogloss:1.25546	validation-mlogloss:1.34331
[651]	train-mlogloss:1.25546	validation-mlogloss:1.34331
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[653]	train-mlogloss:1.25537	validation-mlogloss:1.34326
[654]	train-mlogloss:1.25529	validation-mlogloss:1.34319
[655]	train-mlogloss:1.25524	validation-mlogloss:1.34313
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[659]	train-mlogloss:1.25519	validation-mlogloss:1.34317
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[661]	train-mlogloss:1.25509	validation-mlogloss:1.34304
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[663]	train-mlogloss:1.25494	validation-mlogloss:1.34293
[664]	train-mlogloss:1.25494	validation-mlogloss:1.34293
[665]	train-mlogloss:1.25488	validation-mlogloss:1.34290
[666]	train-mlogloss:1.25483	validation-mlogloss:1.34290
[667]	train-mlogloss:1.25483	validation-mlogloss:1.34290
[668]	train-mlogloss:1.25480	validation-mlogloss:1.34287
[669]	train-mlogloss:1.25476	validation-mlogloss:1.34281
[670]	train-mlogloss:1.25471	validation-mlogloss:1.34274
[671]	train-mlogloss:1.25466	validation-mlogloss:1.34270
[672]	train-mlogloss:1.25466	validation-mlogloss:1.34270
[673]	train-mlogloss:1.25461	validation-mlogloss:1.34268
[674]	train-mlogloss:1.25461	validation-mlogloss:1.34268
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[676]	train-mlogloss:1.25453	validation-mlogloss:1.34260
[677]	train-mlogloss:1.25452	validation-mlogloss:1.34260
[678]	train-mlogloss:1.25448	validation-mlogloss:1.34257
[679]	train-mlogloss:1.25447	validation-mlogloss:1.34255
[680]	train-mlogloss:1.25443	validation-mlogloss:1.34253
[681]	train-mlogloss:1.25440	validation-mlogloss:1.34251
[682]	train-mlogloss:1.25439	validation-mlogloss:1.34250
[683]	train-mlogloss:1.25436	validation-mlogloss:1.34248
[684]	train-mlogloss:1.25436	validation-mlogloss:1.34249
[685]	train-mlogloss:1.25427	validation-mlogloss:1.34245
[686]	train-mlogloss:1.25422	validation-mlogloss:1.34246
[687]	train-mlogloss:1.25421	validation-mlogloss:1.34243
[688]	train-mlogloss:1.25421	validation-mlogloss:1.34243
[689]	train-mlogloss:1.25416	validation-mlogloss:1.34236
[690]	train-mlogloss:1.25416	validation-mlogloss:1.34236
[691]	train-mlogloss:1.25416	validation-mlogloss:1.34236
[692]	train-mlogloss:1.25413	validation-mlogloss:1.34234
[693]	train-mlogloss:1.25407	validation-mlogloss:1.34236
[694]	train-mlogloss:1.25399	validation-mlogloss:1.34234
[695]	train-mlogloss:1.25395	validation-mlogloss:1.34229
[696]	train-mlogloss:1.25392	validation-mlogloss:1.34226
[697]	train-mlogloss:1.25391	validation-mlogloss:1.34225
[698]	train-mlogloss:1.25383	validation-mlogloss:1.34224
[699]	train-mlogloss:1.25376	validation-mlogloss:1.34220
[700]	train-mlogloss:1.25373	validation-mlogloss:1.34215
[701]	train-mlogloss:1.25370	validation-mlogloss:1.34213
[702]	train-mlogloss:1.25368	validation-mlogloss:1.34211
[703]	train-mlogloss:1.25364	validation-mlogloss:1.34208
[704]	train-mlogloss:1.25363	validation-mlogloss:1.34208
[705]	train-mlogloss:1.25354	validation-mlogloss:1.34203
[706]	train-mlogloss:1.25354	validation-mlogloss:1.34203
[707]	train-mlogloss:1.25354	validation-mlogloss:1.34203
[708]	train-mlogloss:1.25346	validation-mlogloss:1.34207
[709]	train-mlogloss:1.25346	validation-mlogloss:1.34207
[710]	train-mlogloss:1.25346	validation-mlogloss:1.34207
[711]	train-mlogloss:1.25337	validation-mlogloss:1.34203
[712]	train-mlogloss:1.25334	validation-mlogloss:1.34202
[713]	train-mlogloss:1.25331	validation-mlogloss:1.34200
Saved model to disk.
2025-10-27 11:23:19.051537: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:23:19.064324: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560599.078113  537471 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560599.082492  537471 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560599.093400  537471 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560599.093424  537471 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560599.093428  537471 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560599.093430  537471 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:23:19.096849: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68404	validation-mlogloss:2.68394
[1]	train-mlogloss:2.66015	validation-mlogloss:2.66074
[2]	train-mlogloss:2.63882	validation-mlogloss:2.63979
[3]	train-mlogloss:2.61781	validation-mlogloss:2.61888
[4]	train-mlogloss:2.59580	validation-mlogloss:2.59691
[5]	train-mlogloss:2.57410	validation-mlogloss:2.57569
[6]	train-mlogloss:2.55364	validation-mlogloss:2.55557
[7]	train-mlogloss:2.53429	validation-mlogloss:2.53665
[8]	train-mlogloss:2.51457	validation-mlogloss:2.51732
[9]	train-mlogloss:2.49539	validation-mlogloss:2.49854
[10]	train-mlogloss:2.47694	validation-mlogloss:2.48053
[11]	train-mlogloss:2.45931	validation-mlogloss:2.46332
[12]	train-mlogloss:2.44186	validation-mlogloss:2.44733
[13]	train-mlogloss:2.42460	validation-mlogloss:2.43057
[14]	train-mlogloss:2.40843	validation-mlogloss:2.41464
[15]	train-mlogloss:2.39183	validation-mlogloss:2.39877
[16]	train-mlogloss:2.37562	validation-mlogloss:2.38296
[17]	train-mlogloss:2.35967	validation-mlogloss:2.36780
[18]	train-mlogloss:2.34432	validation-mlogloss:2.35285
[19]	train-mlogloss:2.32987	validation-mlogloss:2.33868
[20]	train-mlogloss:2.31543	validation-mlogloss:2.32506
[21]	train-mlogloss:2.30107	validation-mlogloss:2.31081
[22]	train-mlogloss:2.28648	validation-mlogloss:2.29645
[23]	train-mlogloss:2.27324	validation-mlogloss:2.28344
[24]	train-mlogloss:2.26001	validation-mlogloss:2.27058
[25]	train-mlogloss:2.24667	validation-mlogloss:2.25768
[26]	train-mlogloss:2.23368	validation-mlogloss:2.24541
[27]	train-mlogloss:2.22116	validation-mlogloss:2.23358
[28]	train-mlogloss:2.20845	validation-mlogloss:2.22106
[29]	train-mlogloss:2.19657	validation-mlogloss:2.20961
[30]	train-mlogloss:2.18494	validation-mlogloss:2.19862
[31]	train-mlogloss:2.17312	validation-mlogloss:2.18728
[32]	train-mlogloss:2.16158	validation-mlogloss:2.17632
[33]	train-mlogloss:2.15045	validation-mlogloss:2.16563
[34]	train-mlogloss:2.13973	validation-mlogloss:2.15523
[35]	train-mlogloss:2.12873	validation-mlogloss:2.14458
[36]	train-mlogloss:2.11818	validation-mlogloss:2.13427
[37]	train-mlogloss:2.10768	validation-mlogloss:2.12400
[38]	train-mlogloss:2.09737	validation-mlogloss:2.11385
[39]	train-mlogloss:2.08720	validation-mlogloss:2.10394
[40]	train-mlogloss:2.07736	validation-mlogloss:2.09405
[41]	train-mlogloss:2.06764	validation-mlogloss:2.08473
[42]	train-mlogloss:2.05813	validation-mlogloss:2.07599
[43]	train-mlogloss:2.04892	validation-mlogloss:2.06703
[44]	train-mlogloss:2.03962	validation-mlogloss:2.05777
[45]	train-mlogloss:2.03074	validation-mlogloss:2.04914
[46]	train-mlogloss:2.02168	validation-mlogloss:2.04030
[47]	train-mlogloss:2.01245	validation-mlogloss:2.03133
[48]	train-mlogloss:2.00387	validation-mlogloss:2.02281
[49]	train-mlogloss:1.99513	validation-mlogloss:2.01418
[50]	train-mlogloss:1.98663	validation-mlogloss:2.00647
[51]	train-mlogloss:1.97828	validation-mlogloss:1.99833
[52]	train-mlogloss:1.96990	validation-mlogloss:1.99068
[53]	train-mlogloss:1.96177	validation-mlogloss:1.98285
[54]	train-mlogloss:1.95387	validation-mlogloss:1.97489
[55]	train-mlogloss:1.94616	validation-mlogloss:1.96744
[56]	train-mlogloss:1.93855	validation-mlogloss:1.95992
[57]	train-mlogloss:1.93078	validation-mlogloss:1.95230
[58]	train-mlogloss:1.92322	validation-mlogloss:1.94491
[59]	train-mlogloss:1.91586	validation-mlogloss:1.93759
[60]	train-mlogloss:1.90865	validation-mlogloss:1.93032
[61]	train-mlogloss:1.90137	validation-mlogloss:1.92344
[62]	train-mlogloss:1.89437	validation-mlogloss:1.91663
[63]	train-mlogloss:1.88754	validation-mlogloss:1.90965
[64]	train-mlogloss:1.88076	validation-mlogloss:1.90290
[65]	train-mlogloss:1.87395	validation-mlogloss:1.89621
[66]	train-mlogloss:1.86757	validation-mlogloss:1.89009
[67]	train-mlogloss:1.86078	validation-mlogloss:1.88339
[68]	train-mlogloss:1.85430	validation-mlogloss:1.87727
[69]	train-mlogloss:1.84769	validation-mlogloss:1.87094
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[672]	train-mlogloss:1.25385	validation-mlogloss:1.33934
[673]	train-mlogloss:1.25385	validation-mlogloss:1.33934
[674]	train-mlogloss:1.25380	validation-mlogloss:1.33935
[675]	train-mlogloss:1.25372	validation-mlogloss:1.33928
[676]	train-mlogloss:1.25369	validation-mlogloss:1.33925
[677]	train-mlogloss:1.25366	validation-mlogloss:1.33920
[678]	train-mlogloss:1.25356	validation-mlogloss:1.33912
[679]	train-mlogloss:1.25353	validation-mlogloss:1.33907
[680]	train-mlogloss:1.25347	validation-mlogloss:1.33910
[681]	train-mlogloss:1.25344	validation-mlogloss:1.33909
[682]	train-mlogloss:1.25343	validation-mlogloss:1.33907
[683]	train-mlogloss:1.25336	validation-mlogloss:1.33904
[684]	train-mlogloss:1.25332	validation-mlogloss:1.33901
[685]	train-mlogloss:1.25329	validation-mlogloss:1.33901
[686]	train-mlogloss:1.25329	validation-mlogloss:1.33901
[687]	train-mlogloss:1.25329	validation-mlogloss:1.33901
[688]	train-mlogloss:1.25323	validation-mlogloss:1.33898
[689]	train-mlogloss:1.25313	validation-mlogloss:1.33891
[690]	train-mlogloss:1.25307	validation-mlogloss:1.33892
[691]	train-mlogloss:1.25307	validation-mlogloss:1.33892
[692]	train-mlogloss:1.25305	validation-mlogloss:1.33892
[693]	train-mlogloss:1.25305	validation-mlogloss:1.33892
[694]	train-mlogloss:1.25304	validation-mlogloss:1.33890
[695]	train-mlogloss:1.25289	validation-mlogloss:1.33879
[696]	train-mlogloss:1.25283	validation-mlogloss:1.33873
[697]	train-mlogloss:1.25283	validation-mlogloss:1.33873
[698]	train-mlogloss:1.25283	validation-mlogloss:1.33873
[699]	train-mlogloss:1.25281	validation-mlogloss:1.33872
[700]	train-mlogloss:1.25274	validation-mlogloss:1.33869
[701]	train-mlogloss:1.25267	validation-mlogloss:1.33865
[702]	train-mlogloss:1.25264	validation-mlogloss:1.33860
[703]	train-mlogloss:1.25264	validation-mlogloss:1.33860
[704]	train-mlogloss:1.25259	validation-mlogloss:1.33856
[705]	train-mlogloss:1.25257	validation-mlogloss:1.33852
[706]	train-mlogloss:1.25257	validation-mlogloss:1.33852
[707]	train-mlogloss:1.25252	validation-mlogloss:1.33851
[708]	train-mlogloss:1.25250	validation-mlogloss:1.33846
[709]	train-mlogloss:1.25245	validation-mlogloss:1.33841
[710]	train-mlogloss:1.25243	validation-mlogloss:1.33842
[711]	train-mlogloss:1.25243	validation-mlogloss:1.33842
[712]	train-mlogloss:1.25241	validation-mlogloss:1.33838
[713]	train-mlogloss:1.25235	validation-mlogloss:1.33834
Saved model to disk.
2025-10-27 11:24:06.287794: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:24:06.300331: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560646.313964  538426 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560646.318279  538426 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560646.329104  538426 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560646.329127  538426 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560646.329131  538426 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560646.329133  538426 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:24:06.332503: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68426	validation-mlogloss:2.68475
[1]	train-mlogloss:2.66225	validation-mlogloss:2.66353
[2]	train-mlogloss:2.64085	validation-mlogloss:2.64259
[3]	train-mlogloss:2.61875	validation-mlogloss:2.62144
[4]	train-mlogloss:2.59738	validation-mlogloss:2.60031
[5]	train-mlogloss:2.57725	validation-mlogloss:2.58058
[6]	train-mlogloss:2.55682	validation-mlogloss:2.56063
[7]	train-mlogloss:2.53803	validation-mlogloss:2.54214
[8]	train-mlogloss:2.51845	validation-mlogloss:2.52290
[9]	train-mlogloss:2.49954	validation-mlogloss:2.50436
[10]	train-mlogloss:2.48175	validation-mlogloss:2.48662
[11]	train-mlogloss:2.46340	validation-mlogloss:2.46848
[12]	train-mlogloss:2.44590	validation-mlogloss:2.45139
[13]	train-mlogloss:2.42822	validation-mlogloss:2.43496
[14]	train-mlogloss:2.41136	validation-mlogloss:2.41904
[15]	train-mlogloss:2.39515	validation-mlogloss:2.40337
[16]	train-mlogloss:2.37900	validation-mlogloss:2.38751
[17]	train-mlogloss:2.36320	validation-mlogloss:2.37136
[18]	train-mlogloss:2.34740	validation-mlogloss:2.35613
[19]	train-mlogloss:2.33258	validation-mlogloss:2.34174
[20]	train-mlogloss:2.31824	validation-mlogloss:2.32776
[21]	train-mlogloss:2.30374	validation-mlogloss:2.31378
[22]	train-mlogloss:2.28951	validation-mlogloss:2.30003
[23]	train-mlogloss:2.27578	validation-mlogloss:2.28693
[24]	train-mlogloss:2.26236	validation-mlogloss:2.27407
[25]	train-mlogloss:2.24960	validation-mlogloss:2.26148
[26]	train-mlogloss:2.23659	validation-mlogloss:2.24921
[27]	train-mlogloss:2.22424	validation-mlogloss:2.23681
[28]	train-mlogloss:2.21163	validation-mlogloss:2.22426
[29]	train-mlogloss:2.19952	validation-mlogloss:2.21253
[30]	train-mlogloss:2.18780	validation-mlogloss:2.20128
[31]	train-mlogloss:2.17627	validation-mlogloss:2.18996
[32]	train-mlogloss:2.16460	validation-mlogloss:2.17886
[33]	train-mlogloss:2.15331	validation-mlogloss:2.16798
[34]	train-mlogloss:2.14230	validation-mlogloss:2.15716
[35]	train-mlogloss:2.13126	validation-mlogloss:2.14621
[36]	train-mlogloss:2.12071	validation-mlogloss:2.13616
[37]	train-mlogloss:2.11026	validation-mlogloss:2.12590
[38]	train-mlogloss:2.09985	validation-mlogloss:2.11581
[39]	train-mlogloss:2.08984	validation-mlogloss:2.10629
[40]	train-mlogloss:2.07995	validation-mlogloss:2.09646
[41]	train-mlogloss:2.07023	validation-mlogloss:2.08761
[42]	train-mlogloss:2.06043	validation-mlogloss:2.07811
[43]	train-mlogloss:2.05108	validation-mlogloss:2.06913
[44]	train-mlogloss:2.04187	validation-mlogloss:2.05999
[45]	train-mlogloss:2.03262	validation-mlogloss:2.05089
[46]	train-mlogloss:2.02385	validation-mlogloss:2.04223
[47]	train-mlogloss:2.01500	validation-mlogloss:2.03350
[48]	train-mlogloss:2.00641	validation-mlogloss:2.02511
[49]	train-mlogloss:1.99778	validation-mlogloss:2.01695
[50]	train-mlogloss:1.98933	validation-mlogloss:2.00904
[51]	train-mlogloss:1.98097	validation-mlogloss:2.00126
[52]	train-mlogloss:1.97279	validation-mlogloss:1.99341
[53]	train-mlogloss:1.96476	validation-mlogloss:1.98538
[54]	train-mlogloss:1.95656	validation-mlogloss:1.97736
[55]	train-mlogloss:1.94878	validation-mlogloss:1.96992
[56]	train-mlogloss:1.94120	validation-mlogloss:1.96251
[57]	train-mlogloss:1.93379	validation-mlogloss:1.95510
[58]	train-mlogloss:1.92646	validation-mlogloss:1.94782
[59]	train-mlogloss:1.91931	validation-mlogloss:1.94123
[60]	train-mlogloss:1.91193	validation-mlogloss:1.93433
[61]	train-mlogloss:1.90467	validation-mlogloss:1.92743
[62]	train-mlogloss:1.89756	validation-mlogloss:1.92066
[63]	train-mlogloss:1.89068	validation-mlogloss:1.91381
[64]	train-mlogloss:1.88382	validation-mlogloss:1.90706
[65]	train-mlogloss:1.87691	validation-mlogloss:1.90032
[66]	train-mlogloss:1.87006	validation-mlogloss:1.89364
[67]	train-mlogloss:1.86337	validation-mlogloss:1.88707
[68]	train-mlogloss:1.85696	validation-mlogloss:1.88086
[69]	train-mlogloss:1.85053	validation-mlogloss:1.87460
[70]	train-mlogloss:1.84432	validation-mlogloss:1.86837
[71]	train-mlogloss:1.83781	validation-mlogloss:1.86197
[72]	train-mlogloss:1.83145	validation-mlogloss:1.85589
[73]	train-mlogloss:1.82558	validation-mlogloss:1.85002
[74]	train-mlogloss:1.81960	validation-mlogloss:1.84445
[75]	train-mlogloss:1.81393	validation-mlogloss:1.83895
[76]	train-mlogloss:1.80824	validation-mlogloss:1.83334
[77]	train-mlogloss:1.80243	validation-mlogloss:1.82748
[78]	train-mlogloss:1.79695	validation-mlogloss:1.82203
[79]	train-mlogloss:1.79124	validation-mlogloss:1.81663
[80]	train-mlogloss:1.78551	validation-mlogloss:1.81100
[81]	train-mlogloss:1.78015	validation-mlogloss:1.80592
[82]	train-mlogloss:1.77479	validation-mlogloss:1.80073
[83]	train-mlogloss:1.76966	validation-mlogloss:1.79577
[84]	train-mlogloss:1.76426	validation-mlogloss:1.79075
[85]	train-mlogloss:1.75910	validation-mlogloss:1.78572
[86]	train-mlogloss:1.75402	validation-mlogloss:1.78086
[87]	train-mlogloss:1.74899	validation-mlogloss:1.77590
[88]	train-mlogloss:1.74421	validation-mlogloss:1.77120
[89]	train-mlogloss:1.73944	validation-mlogloss:1.76668
[90]	train-mlogloss:1.73463	validation-mlogloss:1.76225
[91]	train-mlogloss:1.72976	validation-mlogloss:1.75753
[92]	train-mlogloss:1.72506	validation-mlogloss:1.75309
[93]	train-mlogloss:1.72039	validation-mlogloss:1.74882
[94]	train-mlogloss:1.71574	validation-mlogloss:1.74434
[95]	train-mlogloss:1.71129	validation-mlogloss:1.74016
[96]	train-mlogloss:1.70679	validation-mlogloss:1.73589
[97]	train-mlogloss:1.70219	validation-mlogloss:1.73143
[98]	train-mlogloss:1.69791	validation-mlogloss:1.72719
[99]	train-mlogloss:1.69355	validation-mlogloss:1.72310
[100]	train-mlogloss:1.68941	validation-mlogloss:1.71892
[101]	train-mlogloss:1.68531	validation-mlogloss:1.71507
[102]	train-mlogloss:1.68131	validation-mlogloss:1.71113
[103]	train-mlogloss:1.67712	validation-mlogloss:1.70724
[104]	train-mlogloss:1.67318	validation-mlogloss:1.70333
[105]	train-mlogloss:1.66894	validation-mlogloss:1.69910
[106]	train-mlogloss:1.66489	validation-mlogloss:1.69525
[107]	train-mlogloss:1.66079	validation-mlogloss:1.69167
[108]	train-mlogloss:1.65685	validation-mlogloss:1.68783
[109]	train-mlogloss:1.65296	validation-mlogloss:1.68400
[110]	train-mlogloss:1.64908	validation-mlogloss:1.68025
[111]	train-mlogloss:1.64524	validation-mlogloss:1.67683
[112]	train-mlogloss:1.64153	validation-mlogloss:1.67308
[113]	train-mlogloss:1.63785	validation-mlogloss:1.66969
[114]	train-mlogloss:1.63427	validation-mlogloss:1.66636
[115]	train-mlogloss:1.63073	validation-mlogloss:1.66288
[116]	train-mlogloss:1.62713	validation-mlogloss:1.65956
[117]	train-mlogloss:1.62372	validation-mlogloss:1.65624
[118]	train-mlogloss:1.62028	validation-mlogloss:1.65276
[119]	train-mlogloss:1.61674	validation-mlogloss:1.64947
[120]	train-mlogloss:1.61338	validation-mlogloss:1.64645
[121]	train-mlogloss:1.60997	validation-mlogloss:1.64319
[122]	train-mlogloss:1.60662	validation-mlogloss:1.64003
[123]	train-mlogloss:1.60336	validation-mlogloss:1.63698
[124]	train-mlogloss:1.60003	validation-mlogloss:1.63394
[125]	train-mlogloss:1.59666	validation-mlogloss:1.63084
[126]	train-mlogloss:1.59352	validation-mlogloss:1.62795
[127]	train-mlogloss:1.59016	validation-mlogloss:1.62476
[128]	train-mlogloss:1.58695	validation-mlogloss:1.62172
[129]	train-mlogloss:1.58373	validation-mlogloss:1.61865
[130]	train-mlogloss:1.58065	validation-mlogloss:1.61587
[131]	train-mlogloss:1.57744	validation-mlogloss:1.61290
[132]	train-mlogloss:1.57442	validation-mlogloss:1.61006
[133]	train-mlogloss:1.57154	validation-mlogloss:1.60753
[134]	train-mlogloss:1.56861	validation-mlogloss:1.60468
[135]	train-mlogloss:1.56565	validation-mlogloss:1.60184
[136]	train-mlogloss:1.56279	validation-mlogloss:1.59922
[137]	train-mlogloss:1.55998	validation-mlogloss:1.59667
[138]	train-mlogloss:1.55728	validation-mlogloss:1.59431
[139]	train-mlogloss:1.55462	validation-mlogloss:1.59181
[140]	train-mlogloss:1.55200	validation-mlogloss:1.58945
[141]	train-mlogloss:1.54911	validation-mlogloss:1.58682
[142]	train-mlogloss:1.54635	validation-mlogloss:1.58430
[143]	train-mlogloss:1.54343	validation-mlogloss:1.58154
[144]	train-mlogloss:1.54090	validation-mlogloss:1.57919
[145]	train-mlogloss:1.53830	validation-mlogloss:1.57693
[146]	train-mlogloss:1.53561	validation-mlogloss:1.57479
[147]	train-mlogloss:1.53310	validation-mlogloss:1.57265
[148]	train-mlogloss:1.53059	validation-mlogloss:1.57019
[149]	train-mlogloss:1.52816	validation-mlogloss:1.56783
[150]	train-mlogloss:1.52578	validation-mlogloss:1.56579
[151]	train-mlogloss:1.52324	validation-mlogloss:1.56341
[152]	train-mlogloss:1.52088	validation-mlogloss:1.56111
[153]	train-mlogloss:1.51846	validation-mlogloss:1.55914
[154]	train-mlogloss:1.51588	validation-mlogloss:1.55687
[155]	train-mlogloss:1.51351	validation-mlogloss:1.55509
[156]	train-mlogloss:1.51113	validation-mlogloss:1.55286
[157]	train-mlogloss:1.50872	validation-mlogloss:1.55071
[158]	train-mlogloss:1.50625	validation-mlogloss:1.54845
[159]	train-mlogloss:1.50398	validation-mlogloss:1.54622
[160]	train-mlogloss:1.50177	validation-mlogloss:1.54431
[161]	train-mlogloss:1.49971	validation-mlogloss:1.54233
[162]	train-mlogloss:1.49761	validation-mlogloss:1.54044
[163]	train-mlogloss:1.49532	validation-mlogloss:1.53837
[164]	train-mlogloss:1.49313	validation-mlogloss:1.53662
[165]	train-mlogloss:1.49105	validation-mlogloss:1.53495
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[167]	train-mlogloss:1.48685	validation-mlogloss:1.53090
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[170]	train-mlogloss:1.48059	validation-mlogloss:1.52527
[171]	train-mlogloss:1.47850	validation-mlogloss:1.52336
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[189]	train-mlogloss:1.44438	validation-mlogloss:1.49300
[190]	train-mlogloss:1.44265	validation-mlogloss:1.49132
[191]	train-mlogloss:1.44111	validation-mlogloss:1.48995
[192]	train-mlogloss:1.43952	validation-mlogloss:1.48844
[193]	train-mlogloss:1.43792	validation-mlogloss:1.48689
[194]	train-mlogloss:1.43630	validation-mlogloss:1.48554
[195]	train-mlogloss:1.43463	validation-mlogloss:1.48383
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[197]	train-mlogloss:1.43138	validation-mlogloss:1.48090
[198]	train-mlogloss:1.42972	validation-mlogloss:1.47941
[199]	train-mlogloss:1.42813	validation-mlogloss:1.47814
[200]	train-mlogloss:1.42664	validation-mlogloss:1.47684
[201]	train-mlogloss:1.42524	validation-mlogloss:1.47570
[202]	train-mlogloss:1.42377	validation-mlogloss:1.47457
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[204]	train-mlogloss:1.42075	validation-mlogloss:1.47195
[205]	train-mlogloss:1.41922	validation-mlogloss:1.47066
[206]	train-mlogloss:1.41766	validation-mlogloss:1.46938
[207]	train-mlogloss:1.41603	validation-mlogloss:1.46806
[208]	train-mlogloss:1.41452	validation-mlogloss:1.46659
[209]	train-mlogloss:1.41294	validation-mlogloss:1.46525
[210]	train-mlogloss:1.41158	validation-mlogloss:1.46408
[211]	train-mlogloss:1.41018	validation-mlogloss:1.46299
[212]	train-mlogloss:1.40882	validation-mlogloss:1.46170
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[214]	train-mlogloss:1.40604	validation-mlogloss:1.45958
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[218]	train-mlogloss:1.40069	validation-mlogloss:1.45486
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[224]	train-mlogloss:1.39321	validation-mlogloss:1.44819
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[228]	train-mlogloss:1.38815	validation-mlogloss:1.44393
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[537]	train-mlogloss:1.26080	validation-mlogloss:1.34649
[538]	train-mlogloss:1.26078	validation-mlogloss:1.34647
[539]	train-mlogloss:1.26075	validation-mlogloss:1.34644
[540]	train-mlogloss:1.26074	validation-mlogloss:1.34645
[541]	train-mlogloss:1.26072	validation-mlogloss:1.34643
[542]	train-mlogloss:1.26062	validation-mlogloss:1.34637
[543]	train-mlogloss:1.26056	validation-mlogloss:1.34637
[544]	train-mlogloss:1.26050	validation-mlogloss:1.34633
[545]	train-mlogloss:1.26045	validation-mlogloss:1.34629
[546]	train-mlogloss:1.26042	validation-mlogloss:1.34629
[547]	train-mlogloss:1.26032	validation-mlogloss:1.34628
[548]	train-mlogloss:1.26031	validation-mlogloss:1.34626
[549]	train-mlogloss:1.26021	validation-mlogloss:1.34615
[550]	train-mlogloss:1.26018	validation-mlogloss:1.34613
[551]	train-mlogloss:1.26007	validation-mlogloss:1.34612
[552]	train-mlogloss:1.25997	validation-mlogloss:1.34605
[553]	train-mlogloss:1.25992	validation-mlogloss:1.34601
[554]	train-mlogloss:1.25982	validation-mlogloss:1.34590
[555]	train-mlogloss:1.25970	validation-mlogloss:1.34580
[556]	train-mlogloss:1.25967	validation-mlogloss:1.34578
[557]	train-mlogloss:1.25961	validation-mlogloss:1.34570
[558]	train-mlogloss:1.25959	validation-mlogloss:1.34568
[559]	train-mlogloss:1.25956	validation-mlogloss:1.34565
[560]	train-mlogloss:1.25951	validation-mlogloss:1.34560
[561]	train-mlogloss:1.25943	validation-mlogloss:1.34551
[562]	train-mlogloss:1.25938	validation-mlogloss:1.34548
[563]	train-mlogloss:1.25931	validation-mlogloss:1.34542
[564]	train-mlogloss:1.25931	validation-mlogloss:1.34542
[565]	train-mlogloss:1.25920	validation-mlogloss:1.34538
[566]	train-mlogloss:1.25902	validation-mlogloss:1.34535
[567]	train-mlogloss:1.25894	validation-mlogloss:1.34532
[568]	train-mlogloss:1.25889	validation-mlogloss:1.34530
[569]	train-mlogloss:1.25887	validation-mlogloss:1.34526
[570]	train-mlogloss:1.25887	validation-mlogloss:1.34526
[571]	train-mlogloss:1.25882	validation-mlogloss:1.34521
[572]	train-mlogloss:1.25878	validation-mlogloss:1.34519
[573]	train-mlogloss:1.25872	validation-mlogloss:1.34520
[574]	train-mlogloss:1.25865	validation-mlogloss:1.34517
[575]	train-mlogloss:1.25859	validation-mlogloss:1.34515
[576]	train-mlogloss:1.25855	validation-mlogloss:1.34510
[577]	train-mlogloss:1.25852	validation-mlogloss:1.34506
[578]	train-mlogloss:1.25846	validation-mlogloss:1.34506
[579]	train-mlogloss:1.25839	validation-mlogloss:1.34501
[580]	train-mlogloss:1.25836	validation-mlogloss:1.34501
[581]	train-mlogloss:1.25825	validation-mlogloss:1.34494
[582]	train-mlogloss:1.25823	validation-mlogloss:1.34495
[583]	train-mlogloss:1.25819	validation-mlogloss:1.34491
[584]	train-mlogloss:1.25819	validation-mlogloss:1.34491
[585]	train-mlogloss:1.25812	validation-mlogloss:1.34482
[586]	train-mlogloss:1.25809	validation-mlogloss:1.34480
[587]	train-mlogloss:1.25803	validation-mlogloss:1.34475
[588]	train-mlogloss:1.25798	validation-mlogloss:1.34470
[589]	train-mlogloss:1.25795	validation-mlogloss:1.34468
[590]	train-mlogloss:1.25795	validation-mlogloss:1.34468
[591]	train-mlogloss:1.25784	validation-mlogloss:1.34463
[592]	train-mlogloss:1.25782	validation-mlogloss:1.34460
[593]	train-mlogloss:1.25775	validation-mlogloss:1.34458
[594]	train-mlogloss:1.25764	validation-mlogloss:1.34459
[595]	train-mlogloss:1.25758	validation-mlogloss:1.34454
[596]	train-mlogloss:1.25756	validation-mlogloss:1.34451
[597]	train-mlogloss:1.25753	validation-mlogloss:1.34450
[598]	train-mlogloss:1.25750	validation-mlogloss:1.34448
[599]	train-mlogloss:1.25737	validation-mlogloss:1.34442
[600]	train-mlogloss:1.25735	validation-mlogloss:1.34441
[601]	train-mlogloss:1.25734	validation-mlogloss:1.34440
[602]	train-mlogloss:1.25734	validation-mlogloss:1.34440
[603]	train-mlogloss:1.25733	validation-mlogloss:1.34438
[604]	train-mlogloss:1.25729	validation-mlogloss:1.34433
[605]	train-mlogloss:1.25728	validation-mlogloss:1.34433
[606]	train-mlogloss:1.25726	validation-mlogloss:1.34434
[607]	train-mlogloss:1.25726	validation-mlogloss:1.34434
[608]	train-mlogloss:1.25719	validation-mlogloss:1.34429
[609]	train-mlogloss:1.25719	validation-mlogloss:1.34430
[610]	train-mlogloss:1.25718	validation-mlogloss:1.34430
[611]	train-mlogloss:1.25712	validation-mlogloss:1.34420
[612]	train-mlogloss:1.25706	validation-mlogloss:1.34420
[613]	train-mlogloss:1.25706	validation-mlogloss:1.34420
[614]	train-mlogloss:1.25696	validation-mlogloss:1.34415
[615]	train-mlogloss:1.25696	validation-mlogloss:1.34415
[616]	train-mlogloss:1.25689	validation-mlogloss:1.34410
[617]	train-mlogloss:1.25687	validation-mlogloss:1.34408
[618]	train-mlogloss:1.25681	validation-mlogloss:1.34402
[619]	train-mlogloss:1.25675	validation-mlogloss:1.34402
[620]	train-mlogloss:1.25674	validation-mlogloss:1.34402
[621]	train-mlogloss:1.25665	validation-mlogloss:1.34402
[622]	train-mlogloss:1.25662	validation-mlogloss:1.34400
[623]	train-mlogloss:1.25662	validation-mlogloss:1.34400
[624]	train-mlogloss:1.25657	validation-mlogloss:1.34397
[625]	train-mlogloss:1.25657	validation-mlogloss:1.34397
[626]	train-mlogloss:1.25653	validation-mlogloss:1.34390
[627]	train-mlogloss:1.25645	validation-mlogloss:1.34390
[628]	train-mlogloss:1.25635	validation-mlogloss:1.34378
[629]	train-mlogloss:1.25632	validation-mlogloss:1.34376
[630]	train-mlogloss:1.25629	validation-mlogloss:1.34375
[631]	train-mlogloss:1.25626	validation-mlogloss:1.34370
[632]	train-mlogloss:1.25616	validation-mlogloss:1.34365
[633]	train-mlogloss:1.25616	validation-mlogloss:1.34365
[634]	train-mlogloss:1.25611	validation-mlogloss:1.34361
[635]	train-mlogloss:1.25609	validation-mlogloss:1.34355
[636]	train-mlogloss:1.25605	validation-mlogloss:1.34352
[637]	train-mlogloss:1.25602	validation-mlogloss:1.34348
[638]	train-mlogloss:1.25594	validation-mlogloss:1.34343
[639]	train-mlogloss:1.25589	validation-mlogloss:1.34342
[640]	train-mlogloss:1.25586	validation-mlogloss:1.34341
[641]	train-mlogloss:1.25584	validation-mlogloss:1.34339
[642]	train-mlogloss:1.25574	validation-mlogloss:1.34331
[643]	train-mlogloss:1.25571	validation-mlogloss:1.34328
[644]	train-mlogloss:1.25569	validation-mlogloss:1.34330
[645]	train-mlogloss:1.25568	validation-mlogloss:1.34328
[646]	train-mlogloss:1.25560	validation-mlogloss:1.34329
[647]	train-mlogloss:1.25558	validation-mlogloss:1.34327
[648]	train-mlogloss:1.25550	validation-mlogloss:1.34323
[649]	train-mlogloss:1.25545	validation-mlogloss:1.34322
[650]	train-mlogloss:1.25542	validation-mlogloss:1.34324
[651]	train-mlogloss:1.25538	validation-mlogloss:1.34319
[652]	train-mlogloss:1.25538	validation-mlogloss:1.34319
[653]	train-mlogloss:1.25533	validation-mlogloss:1.34313
[654]	train-mlogloss:1.25533	validation-mlogloss:1.34313
[655]	train-mlogloss:1.25530	validation-mlogloss:1.34311
[656]	train-mlogloss:1.25530	validation-mlogloss:1.34311
[657]	train-mlogloss:1.25527	validation-mlogloss:1.34309
[658]	train-mlogloss:1.25523	validation-mlogloss:1.34305
[659]	train-mlogloss:1.25523	validation-mlogloss:1.34305
[660]	train-mlogloss:1.25517	validation-mlogloss:1.34298
[661]	train-mlogloss:1.25517	validation-mlogloss:1.34298
[662]	train-mlogloss:1.25517	validation-mlogloss:1.34298
[663]	train-mlogloss:1.25517	validation-mlogloss:1.34298
[664]	train-mlogloss:1.25516	validation-mlogloss:1.34298
[665]	train-mlogloss:1.25514	validation-mlogloss:1.34297
[666]	train-mlogloss:1.25509	validation-mlogloss:1.34296
[667]	train-mlogloss:1.25504	validation-mlogloss:1.34294
[668]	train-mlogloss:1.25502	validation-mlogloss:1.34290
[669]	train-mlogloss:1.25495	validation-mlogloss:1.34287
[670]	train-mlogloss:1.25494	validation-mlogloss:1.34286
[671]	train-mlogloss:1.25490	validation-mlogloss:1.34285
[672]	train-mlogloss:1.25484	validation-mlogloss:1.34281
[673]	train-mlogloss:1.25482	validation-mlogloss:1.34280
[674]	train-mlogloss:1.25482	validation-mlogloss:1.34279
[675]	train-mlogloss:1.25478	validation-mlogloss:1.34275
[676]	train-mlogloss:1.25475	validation-mlogloss:1.34274
[677]	train-mlogloss:1.25475	validation-mlogloss:1.34275
[678]	train-mlogloss:1.25474	validation-mlogloss:1.34275
[679]	train-mlogloss:1.25473	validation-mlogloss:1.34274
[680]	train-mlogloss:1.25464	validation-mlogloss:1.34272
[681]	train-mlogloss:1.25462	validation-mlogloss:1.34272
[682]	train-mlogloss:1.25457	validation-mlogloss:1.34269
[683]	train-mlogloss:1.25455	validation-mlogloss:1.34267
[684]	train-mlogloss:1.25452	validation-mlogloss:1.34264
[685]	train-mlogloss:1.25447	validation-mlogloss:1.34260
[686]	train-mlogloss:1.25446	validation-mlogloss:1.34258
[687]	train-mlogloss:1.25440	validation-mlogloss:1.34255
[688]	train-mlogloss:1.25437	validation-mlogloss:1.34254
[689]	train-mlogloss:1.25427	validation-mlogloss:1.34243
[690]	train-mlogloss:1.25422	validation-mlogloss:1.34240
[691]	train-mlogloss:1.25422	validation-mlogloss:1.34241
[692]	train-mlogloss:1.25413	validation-mlogloss:1.34242
[693]	train-mlogloss:1.25413	validation-mlogloss:1.34242
[694]	train-mlogloss:1.25413	validation-mlogloss:1.34242
[695]	train-mlogloss:1.25407	validation-mlogloss:1.34239
[696]	train-mlogloss:1.25401	validation-mlogloss:1.34236
[697]	train-mlogloss:1.25400	validation-mlogloss:1.34234
[698]	train-mlogloss:1.25400	validation-mlogloss:1.34234
[699]	train-mlogloss:1.25395	validation-mlogloss:1.34230
[700]	train-mlogloss:1.25395	validation-mlogloss:1.34230
[701]	train-mlogloss:1.25395	validation-mlogloss:1.34230
[702]	train-mlogloss:1.25393	validation-mlogloss:1.34229
[703]	train-mlogloss:1.25387	validation-mlogloss:1.34221
[704]	train-mlogloss:1.25386	validation-mlogloss:1.34221
[705]	train-mlogloss:1.25381	validation-mlogloss:1.34219
[706]	train-mlogloss:1.25377	validation-mlogloss:1.34212
[707]	train-mlogloss:1.25377	validation-mlogloss:1.34212
[708]	train-mlogloss:1.25372	validation-mlogloss:1.34206
[709]	train-mlogloss:1.25366	validation-mlogloss:1.34202
[710]	train-mlogloss:1.25363	validation-mlogloss:1.34203
[711]	train-mlogloss:1.25359	validation-mlogloss:1.34200
[712]	train-mlogloss:1.25354	validation-mlogloss:1.34196
[713]	train-mlogloss:1.25352	validation-mlogloss:1.34193
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.9 [%]
Global accuracy score (test) = 50.75 [%]
Global F1 score (train) = 62.99 [%]
Global F1 score (test) = 50.9 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.27      0.38      0.31       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.40      0.42       184
       CAMINAR USUAL SPEED       0.28      0.21      0.24       184
            CAMINAR ZIGZAG       0.60      0.54      0.57       184
          DE PIE BARRIENDO       0.54      0.48      0.51       184
   DE PIE DOBLANDO TOALLAS       0.45      0.47      0.46       184
    DE PIE MOVIENDO LIBROS       0.49      0.48      0.49       184
          DE PIE USANDO PC       0.61      0.67      0.64       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.86      0.64      0.74       184
           SENTADO LEYENDO       0.35      0.41      0.38       184
         SENTADO USANDO PC       0.43      0.28      0.34       184
      SENTADO VIENDO LA TV       0.46      0.40      0.43       184
   SUBIR Y BAJAR ESCALERAS       0.52      0.68      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.51      2737


Accuracy capturado en la ejecución 10: 50.75 [%]
F1-score capturado en la ejecución 10: 50.9 [%]

=== EJECUCIÓN 11 ===

--- TRAIN (ejecución 11) ---

--- TEST (ejecución 11) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.89 [%]
Global accuracy score (test) = 50.38 [%]
Global F1 score (train) = 62.97 [%]
Global F1 score (test) = 50.53 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.38      0.32       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.39      0.41       184
       CAMINAR USUAL SPEED       0.30      0.23      0.26       184
            CAMINAR ZIGZAG       0.59      0.55      0.57       184
          DE PIE BARRIENDO       0.55      0.49      0.52       184
   DE PIE DOBLANDO TOALLAS       0.44      0.48      0.46       184
    DE PIE MOVIENDO LIBROS       0.50      0.46      0.48       184
          DE PIE USANDO PC       0.60      0.67      0.63       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.87      0.64      0.73       184
           SENTADO LEYENDO       0.34      0.41      0.38       184
         SENTADO USANDO PC       0.38      0.24      0.30       184
      SENTADO VIENDO LA TV       0.46      0.39      0.42       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.67      0.60       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 11: 50.38 [%]
F1-score capturado en la ejecución 11: 50.53 [%]

=== EJECUCIÓN 12 ===

--- TRAIN (ejecución 12) ---

--- TEST (ejecución 12) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.88 [%]
Global accuracy score (test) = 51.04 [%]
Global F1 score (train) = 62.96 [%]
Global F1 score (test) = 51.23 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.29      0.40      0.34       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.41      0.42       184
       CAMINAR USUAL SPEED       0.28      0.20      0.23       184
            CAMINAR ZIGZAG       0.61      0.55      0.58       184
          DE PIE BARRIENDO       0.54      0.49      0.51       184
   DE PIE DOBLANDO TOALLAS       0.45      0.48      0.47       184
    DE PIE MOVIENDO LIBROS       0.49      0.48      0.48       184
          DE PIE USANDO PC       0.63      0.67      0.65       184
        FASE REPOSO CON K5       0.55      0.78      0.65       184
INCREMENTAL CICLOERGOMETRO       0.89      0.64      0.75       184
           SENTADO LEYENDO       0.35      0.42      0.38       184
         SENTADO USANDO PC       0.43      0.28      0.34       184
      SENTADO VIENDO LA TV       0.45      0.40      0.43       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.67      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.51      2737


Accuracy capturado en la ejecución 12: 51.04 [%]
F1-score capturado en la ejecución 12: 51.23 [%]

=== EJECUCIÓN 13 ===

--- TRAIN (ejecución 13) ---

--- TEST (ejecución 13) ---
2025-10-27 11:24:53.840464: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:24:53.853312: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560693.867102  539347 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560693.871233  539347 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560693.882574  539347 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560693.882606  539347 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560693.882609  539347 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560693.882611  539347 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:24:53.886027: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68468	validation-mlogloss:2.68479
[1]	train-mlogloss:2.66199	validation-mlogloss:2.66223
[2]	train-mlogloss:2.64132	validation-mlogloss:2.64169
[3]	train-mlogloss:2.61853	validation-mlogloss:2.61937
[4]	train-mlogloss:2.59675	validation-mlogloss:2.59867
[5]	train-mlogloss:2.57616	validation-mlogloss:2.57871
[6]	train-mlogloss:2.55743	validation-mlogloss:2.56055
[7]	train-mlogloss:2.53717	validation-mlogloss:2.54022
[8]	train-mlogloss:2.51699	validation-mlogloss:2.52043
[9]	train-mlogloss:2.49846	validation-mlogloss:2.50170
[10]	train-mlogloss:2.47992	validation-mlogloss:2.48351
[11]	train-mlogloss:2.46200	validation-mlogloss:2.46546
[12]	train-mlogloss:2.44450	validation-mlogloss:2.44809
[13]	train-mlogloss:2.42686	validation-mlogloss:2.43067
[14]	train-mlogloss:2.41028	validation-mlogloss:2.41446
[15]	train-mlogloss:2.39416	validation-mlogloss:2.39940
[16]	train-mlogloss:2.37799	validation-mlogloss:2.38403
[17]	train-mlogloss:2.36211	validation-mlogloss:2.36899
[18]	train-mlogloss:2.34684	validation-mlogloss:2.35386
[19]	train-mlogloss:2.33231	validation-mlogloss:2.33974
[20]	train-mlogloss:2.31769	validation-mlogloss:2.32592
[21]	train-mlogloss:2.30395	validation-mlogloss:2.31250
[22]	train-mlogloss:2.28968	validation-mlogloss:2.29952
[23]	train-mlogloss:2.27618	validation-mlogloss:2.28577
[24]	train-mlogloss:2.26274	validation-mlogloss:2.27278
[25]	train-mlogloss:2.24966	validation-mlogloss:2.26041
[26]	train-mlogloss:2.23635	validation-mlogloss:2.24769
[27]	train-mlogloss:2.22369	validation-mlogloss:2.23560
[28]	train-mlogloss:2.21124	validation-mlogloss:2.22336
[29]	train-mlogloss:2.19899	validation-mlogloss:2.21106
[30]	train-mlogloss:2.18707	validation-mlogloss:2.19938
[31]	train-mlogloss:2.17527	validation-mlogloss:2.18804
[32]	train-mlogloss:2.16382	validation-mlogloss:2.17714
[33]	train-mlogloss:2.15282	validation-mlogloss:2.16628
[34]	train-mlogloss:2.14162	validation-mlogloss:2.15521
[35]	train-mlogloss:2.13073	validation-mlogloss:2.14431
[36]	train-mlogloss:2.11993	validation-mlogloss:2.13408
[37]	train-mlogloss:2.10945	validation-mlogloss:2.12421
[38]	train-mlogloss:2.09901	validation-mlogloss:2.11388
[39]	train-mlogloss:2.08902	validation-mlogloss:2.10449
[40]	train-mlogloss:2.07940	validation-mlogloss:2.09534
[41]	train-mlogloss:2.06964	validation-mlogloss:2.08620
[42]	train-mlogloss:2.05998	validation-mlogloss:2.07677
[43]	train-mlogloss:2.05079	validation-mlogloss:2.06797
[44]	train-mlogloss:2.04182	validation-mlogloss:2.05967
[45]	train-mlogloss:2.03265	validation-mlogloss:2.05060
[46]	train-mlogloss:2.02356	validation-mlogloss:2.04143
[47]	train-mlogloss:2.01454	validation-mlogloss:2.03270
[48]	train-mlogloss:2.00564	validation-mlogloss:2.02405
[49]	train-mlogloss:1.99709	validation-mlogloss:2.01566
[50]	train-mlogloss:1.98876	validation-mlogloss:2.00753
[51]	train-mlogloss:1.98026	validation-mlogloss:1.99939
[52]	train-mlogloss:1.97178	validation-mlogloss:1.99079
[53]	train-mlogloss:1.96381	validation-mlogloss:1.98318
[54]	train-mlogloss:1.95595	validation-mlogloss:1.97564
[55]	train-mlogloss:1.94802	validation-mlogloss:1.96817
[56]	train-mlogloss:1.94014	validation-mlogloss:1.96059
[57]	train-mlogloss:1.93274	validation-mlogloss:1.95327
[58]	train-mlogloss:1.92553	validation-mlogloss:1.94586
[59]	train-mlogloss:1.91806	validation-mlogloss:1.93844
[60]	train-mlogloss:1.91076	validation-mlogloss:1.93134
[61]	train-mlogloss:1.90349	validation-mlogloss:1.92445
[62]	train-mlogloss:1.89628	validation-mlogloss:1.91746
[63]	train-mlogloss:1.88933	validation-mlogloss:1.91100
[64]	train-mlogloss:1.88249	validation-mlogloss:1.90419
[65]	train-mlogloss:1.87589	validation-mlogloss:1.89774
[66]	train-mlogloss:1.86914	validation-mlogloss:1.89113
[67]	train-mlogloss:1.86252	validation-mlogloss:1.88457
[68]	train-mlogloss:1.85591	validation-mlogloss:1.87811
[69]	train-mlogloss:1.84935	validation-mlogloss:1.87179
[70]	train-mlogloss:1.84300	validation-mlogloss:1.86556
[71]	train-mlogloss:1.83692	validation-mlogloss:1.85970
[72]	train-mlogloss:1.83096	validation-mlogloss:1.85372
[73]	train-mlogloss:1.82500	validation-mlogloss:1.84787
[74]	train-mlogloss:1.81905	validation-mlogloss:1.84241
[75]	train-mlogloss:1.81330	validation-mlogloss:1.83660
[76]	train-mlogloss:1.80742	validation-mlogloss:1.83069
[77]	train-mlogloss:1.80163	validation-mlogloss:1.82495
[78]	train-mlogloss:1.79594	validation-mlogloss:1.81937
[79]	train-mlogloss:1.79033	validation-mlogloss:1.81381
[80]	train-mlogloss:1.78476	validation-mlogloss:1.80854
[81]	train-mlogloss:1.77938	validation-mlogloss:1.80326
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[83]	train-mlogloss:1.76860	validation-mlogloss:1.79278
[84]	train-mlogloss:1.76330	validation-mlogloss:1.78769
[85]	train-mlogloss:1.75818	validation-mlogloss:1.78263
[86]	train-mlogloss:1.75320	validation-mlogloss:1.77784
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[88]	train-mlogloss:1.74320	validation-mlogloss:1.76810
[89]	train-mlogloss:1.73833	validation-mlogloss:1.76350
[90]	train-mlogloss:1.73339	validation-mlogloss:1.75860
[91]	train-mlogloss:1.72864	validation-mlogloss:1.75402
[92]	train-mlogloss:1.72379	validation-mlogloss:1.74950
[93]	train-mlogloss:1.71911	validation-mlogloss:1.74501
[94]	train-mlogloss:1.71445	validation-mlogloss:1.74060
[95]	train-mlogloss:1.71006	validation-mlogloss:1.73629
[96]	train-mlogloss:1.70562	validation-mlogloss:1.73213
[97]	train-mlogloss:1.70127	validation-mlogloss:1.72789
[98]	train-mlogloss:1.69706	validation-mlogloss:1.72402
[99]	train-mlogloss:1.69271	validation-mlogloss:1.72009
[100]	train-mlogloss:1.68853	validation-mlogloss:1.71608
[101]	train-mlogloss:1.68437	validation-mlogloss:1.71228
[102]	train-mlogloss:1.68012	validation-mlogloss:1.70831
[103]	train-mlogloss:1.67599	validation-mlogloss:1.70454
[104]	train-mlogloss:1.67166	validation-mlogloss:1.70052
[105]	train-mlogloss:1.66761	validation-mlogloss:1.69677
[106]	train-mlogloss:1.66360	validation-mlogloss:1.69295
[107]	train-mlogloss:1.65974	validation-mlogloss:1.68908
[108]	train-mlogloss:1.65577	validation-mlogloss:1.68532
[109]	train-mlogloss:1.65197	validation-mlogloss:1.68164
[110]	train-mlogloss:1.64805	validation-mlogloss:1.67775
[111]	train-mlogloss:1.64432	validation-mlogloss:1.67427
[112]	train-mlogloss:1.64050	validation-mlogloss:1.67050
[113]	train-mlogloss:1.63677	validation-mlogloss:1.66703
[114]	train-mlogloss:1.63316	validation-mlogloss:1.66353
[115]	train-mlogloss:1.62948	validation-mlogloss:1.66027
[116]	train-mlogloss:1.62599	validation-mlogloss:1.65690
[117]	train-mlogloss:1.62256	validation-mlogloss:1.65360
[118]	train-mlogloss:1.61912	validation-mlogloss:1.65034
[119]	train-mlogloss:1.61566	validation-mlogloss:1.64713
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[121]	train-mlogloss:1.60884	validation-mlogloss:1.64063
[122]	train-mlogloss:1.60553	validation-mlogloss:1.63755
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[124]	train-mlogloss:1.59905	validation-mlogloss:1.63139
[125]	train-mlogloss:1.59569	validation-mlogloss:1.62821
[126]	train-mlogloss:1.59251	validation-mlogloss:1.62540
[127]	train-mlogloss:1.58924	validation-mlogloss:1.62238
[128]	train-mlogloss:1.58612	validation-mlogloss:1.61947
[129]	train-mlogloss:1.58306	validation-mlogloss:1.61658
[130]	train-mlogloss:1.58001	validation-mlogloss:1.61380
[131]	train-mlogloss:1.57698	validation-mlogloss:1.61118
[132]	train-mlogloss:1.57413	validation-mlogloss:1.60831
[133]	train-mlogloss:1.57112	validation-mlogloss:1.60557
[134]	train-mlogloss:1.56813	validation-mlogloss:1.60291
[135]	train-mlogloss:1.56514	validation-mlogloss:1.60025
[136]	train-mlogloss:1.56223	validation-mlogloss:1.59751
[137]	train-mlogloss:1.55923	validation-mlogloss:1.59479
[138]	train-mlogloss:1.55647	validation-mlogloss:1.59209
[139]	train-mlogloss:1.55368	validation-mlogloss:1.58948
[140]	train-mlogloss:1.55080	validation-mlogloss:1.58682
[141]	train-mlogloss:1.54805	validation-mlogloss:1.58425
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[143]	train-mlogloss:1.54247	validation-mlogloss:1.57898
[144]	train-mlogloss:1.53965	validation-mlogloss:1.57635
[145]	train-mlogloss:1.53703	validation-mlogloss:1.57392
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[148]	train-mlogloss:1.52923	validation-mlogloss:1.56689
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[150]	train-mlogloss:1.52430	validation-mlogloss:1.56215
[151]	train-mlogloss:1.52186	validation-mlogloss:1.56009
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[154]	train-mlogloss:1.51449	validation-mlogloss:1.55330
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[664]	train-mlogloss:1.25340	validation-mlogloss:1.33953
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[681]	train-mlogloss:1.25273	validation-mlogloss:1.33907
[682]	train-mlogloss:1.25273	validation-mlogloss:1.33907
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[684]	train-mlogloss:1.25260	validation-mlogloss:1.33900
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[686]	train-mlogloss:1.25245	validation-mlogloss:1.33888
[687]	train-mlogloss:1.25239	validation-mlogloss:1.33884
[688]	train-mlogloss:1.25237	validation-mlogloss:1.33882
[689]	train-mlogloss:1.25233	validation-mlogloss:1.33877
[690]	train-mlogloss:1.25231	validation-mlogloss:1.33875
[691]	train-mlogloss:1.25228	validation-mlogloss:1.33874
[692]	train-mlogloss:1.25220	validation-mlogloss:1.33868
[693]	train-mlogloss:1.25215	validation-mlogloss:1.33863
[694]	train-mlogloss:1.25212	validation-mlogloss:1.33863
[695]	train-mlogloss:1.25210	validation-mlogloss:1.33860
[696]	train-mlogloss:1.25209	validation-mlogloss:1.33860
[697]	train-mlogloss:1.25207	validation-mlogloss:1.33858
[698]	train-mlogloss:1.25207	validation-mlogloss:1.33858
[699]	train-mlogloss:1.25206	validation-mlogloss:1.33860
[700]	train-mlogloss:1.25206	validation-mlogloss:1.33860
[701]	train-mlogloss:1.25203	validation-mlogloss:1.33857
[702]	train-mlogloss:1.25203	validation-mlogloss:1.33858
[703]	train-mlogloss:1.25192	validation-mlogloss:1.33845
[704]	train-mlogloss:1.25191	validation-mlogloss:1.33842
[705]	train-mlogloss:1.25191	validation-mlogloss:1.33842
[706]	train-mlogloss:1.25183	validation-mlogloss:1.33836
[707]	train-mlogloss:1.25176	validation-mlogloss:1.33830
[708]	train-mlogloss:1.25172	validation-mlogloss:1.33829
[709]	train-mlogloss:1.25167	validation-mlogloss:1.33831
[710]	train-mlogloss:1.25167	validation-mlogloss:1.33831
[711]	train-mlogloss:1.25165	validation-mlogloss:1.33829
[712]	train-mlogloss:1.25157	validation-mlogloss:1.33825
[713]	train-mlogloss:1.25154	validation-mlogloss:1.33822
Saved model to disk.
2025-10-27 11:25:41.420319: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:25:41.432963: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560741.446634  540285 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560741.450804  540285 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560741.461979  540285 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560741.462001  540285 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560741.462004  540285 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560741.462007  540285 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:25:41.465453: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
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[1]	train-mlogloss:2.66126	validation-mlogloss:2.66233
[2]	train-mlogloss:2.63945	validation-mlogloss:2.64190
[3]	train-mlogloss:2.61707	validation-mlogloss:2.62000
[4]	train-mlogloss:2.59535	validation-mlogloss:2.59830
[5]	train-mlogloss:2.57485	validation-mlogloss:2.57853
[6]	train-mlogloss:2.55562	validation-mlogloss:2.55944
[7]	train-mlogloss:2.53575	validation-mlogloss:2.53968
[8]	train-mlogloss:2.51762	validation-mlogloss:2.52145
[9]	train-mlogloss:2.49899	validation-mlogloss:2.50243
[10]	train-mlogloss:2.48027	validation-mlogloss:2.48425
[11]	train-mlogloss:2.46214	validation-mlogloss:2.46614
[12]	train-mlogloss:2.44500	validation-mlogloss:2.44956
[13]	train-mlogloss:2.42855	validation-mlogloss:2.43357
[14]	train-mlogloss:2.41240	validation-mlogloss:2.41742
[15]	train-mlogloss:2.39637	validation-mlogloss:2.40155
[16]	train-mlogloss:2.38079	validation-mlogloss:2.38620
[17]	train-mlogloss:2.36458	validation-mlogloss:2.37055
[18]	train-mlogloss:2.34924	validation-mlogloss:2.35544
[19]	train-mlogloss:2.33413	validation-mlogloss:2.34044
[20]	train-mlogloss:2.31943	validation-mlogloss:2.32640
[21]	train-mlogloss:2.30502	validation-mlogloss:2.31202
[22]	train-mlogloss:2.29023	validation-mlogloss:2.29800
[23]	train-mlogloss:2.27660	validation-mlogloss:2.28488
[24]	train-mlogloss:2.26269	validation-mlogloss:2.27174
[25]	train-mlogloss:2.24936	validation-mlogloss:2.25830
[26]	train-mlogloss:2.23690	validation-mlogloss:2.24544
[27]	train-mlogloss:2.22427	validation-mlogloss:2.23325
[28]	train-mlogloss:2.21173	validation-mlogloss:2.22090
[29]	train-mlogloss:2.19968	validation-mlogloss:2.20966
[30]	train-mlogloss:2.18760	validation-mlogloss:2.19832
[31]	train-mlogloss:2.17613	validation-mlogloss:2.18741
[32]	train-mlogloss:2.16470	validation-mlogloss:2.17676
[33]	train-mlogloss:2.15335	validation-mlogloss:2.16592
[34]	train-mlogloss:2.14230	validation-mlogloss:2.15557
[35]	train-mlogloss:2.13141	validation-mlogloss:2.14506
[36]	train-mlogloss:2.12052	validation-mlogloss:2.13438
[37]	train-mlogloss:2.11004	validation-mlogloss:2.12367
[38]	train-mlogloss:2.09952	validation-mlogloss:2.11336
[39]	train-mlogloss:2.08923	validation-mlogloss:2.10365
[40]	train-mlogloss:2.07897	validation-mlogloss:2.09372
[41]	train-mlogloss:2.06905	validation-mlogloss:2.08378
[42]	train-mlogloss:2.05955	validation-mlogloss:2.07483
[43]	train-mlogloss:2.04984	validation-mlogloss:2.06580
[44]	train-mlogloss:2.04040	validation-mlogloss:2.05656
[45]	train-mlogloss:2.03133	validation-mlogloss:2.04774
[46]	train-mlogloss:2.02230	validation-mlogloss:2.03857
[47]	train-mlogloss:2.01327	validation-mlogloss:2.02979
[48]	train-mlogloss:2.00454	validation-mlogloss:2.02130
[49]	train-mlogloss:1.99565	validation-mlogloss:2.01289
[50]	train-mlogloss:1.98729	validation-mlogloss:2.00494
[51]	train-mlogloss:1.97881	validation-mlogloss:1.99669
[52]	train-mlogloss:1.97074	validation-mlogloss:1.98908
[53]	train-mlogloss:1.96247	validation-mlogloss:1.98099
[54]	train-mlogloss:1.95483	validation-mlogloss:1.97373
[55]	train-mlogloss:1.94697	validation-mlogloss:1.96575
[56]	train-mlogloss:1.93932	validation-mlogloss:1.95817
[57]	train-mlogloss:1.93180	validation-mlogloss:1.95123
[58]	train-mlogloss:1.92430	validation-mlogloss:1.94400
[59]	train-mlogloss:1.91705	validation-mlogloss:1.93717
[60]	train-mlogloss:1.90980	validation-mlogloss:1.93030
[61]	train-mlogloss:1.90269	validation-mlogloss:1.92334
[62]	train-mlogloss:1.89562	validation-mlogloss:1.91622
[63]	train-mlogloss:1.88880	validation-mlogloss:1.90997
[64]	train-mlogloss:1.88209	validation-mlogloss:1.90373
[65]	train-mlogloss:1.87540	validation-mlogloss:1.89722
[66]	train-mlogloss:1.86869	validation-mlogloss:1.89082
[67]	train-mlogloss:1.86217	validation-mlogloss:1.88460
[68]	train-mlogloss:1.85578	validation-mlogloss:1.87812
[69]	train-mlogloss:1.84947	validation-mlogloss:1.87193
[70]	train-mlogloss:1.84307	validation-mlogloss:1.86579
[71]	train-mlogloss:1.83708	validation-mlogloss:1.86025
[72]	train-mlogloss:1.83113	validation-mlogloss:1.85436
[73]	train-mlogloss:1.82543	validation-mlogloss:1.84888
[74]	train-mlogloss:1.81935	validation-mlogloss:1.84308
[75]	train-mlogloss:1.81327	validation-mlogloss:1.83731
[76]	train-mlogloss:1.80750	validation-mlogloss:1.83166
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[79]	train-mlogloss:1.79069	validation-mlogloss:1.81548
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[81]	train-mlogloss:1.77981	validation-mlogloss:1.80515
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[84]	train-mlogloss:1.76386	validation-mlogloss:1.78958
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[94]	train-mlogloss:1.71532	validation-mlogloss:1.74256
[95]	train-mlogloss:1.71079	validation-mlogloss:1.73808
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[100]	train-mlogloss:1.68864	validation-mlogloss:1.71779
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[103]	train-mlogloss:1.67625	validation-mlogloss:1.70589
[104]	train-mlogloss:1.67213	validation-mlogloss:1.70197
[105]	train-mlogloss:1.66828	validation-mlogloss:1.69828
[106]	train-mlogloss:1.66417	validation-mlogloss:1.69450
[107]	train-mlogloss:1.66046	validation-mlogloss:1.69094
[108]	train-mlogloss:1.65658	validation-mlogloss:1.68736
[109]	train-mlogloss:1.65262	validation-mlogloss:1.68370
[110]	train-mlogloss:1.64866	validation-mlogloss:1.68005
[111]	train-mlogloss:1.64481	validation-mlogloss:1.67640
[112]	train-mlogloss:1.64094	validation-mlogloss:1.67286
[113]	train-mlogloss:1.63739	validation-mlogloss:1.66954
[114]	train-mlogloss:1.63374	validation-mlogloss:1.66614
[115]	train-mlogloss:1.63016	validation-mlogloss:1.66264
[116]	train-mlogloss:1.62656	validation-mlogloss:1.65918
[117]	train-mlogloss:1.62308	validation-mlogloss:1.65582
[118]	train-mlogloss:1.61958	validation-mlogloss:1.65252
[119]	train-mlogloss:1.61616	validation-mlogloss:1.64942
[120]	train-mlogloss:1.61292	validation-mlogloss:1.64641
[121]	train-mlogloss:1.60953	validation-mlogloss:1.64337
[122]	train-mlogloss:1.60606	validation-mlogloss:1.63996
[123]	train-mlogloss:1.60273	validation-mlogloss:1.63698
[124]	train-mlogloss:1.59945	validation-mlogloss:1.63365
[125]	train-mlogloss:1.59620	validation-mlogloss:1.63061
[126]	train-mlogloss:1.59293	validation-mlogloss:1.62746
[127]	train-mlogloss:1.58971	validation-mlogloss:1.62438
[128]	train-mlogloss:1.58666	validation-mlogloss:1.62132
[129]	train-mlogloss:1.58348	validation-mlogloss:1.61825
[130]	train-mlogloss:1.58050	validation-mlogloss:1.61545
[131]	train-mlogloss:1.57752	validation-mlogloss:1.61267
[132]	train-mlogloss:1.57464	validation-mlogloss:1.60987
[133]	train-mlogloss:1.57176	validation-mlogloss:1.60733
[134]	train-mlogloss:1.56873	validation-mlogloss:1.60455
[135]	train-mlogloss:1.56581	validation-mlogloss:1.60192
[136]	train-mlogloss:1.56297	validation-mlogloss:1.59942
[137]	train-mlogloss:1.56003	validation-mlogloss:1.59660
[138]	train-mlogloss:1.55727	validation-mlogloss:1.59393
[139]	train-mlogloss:1.55437	validation-mlogloss:1.59142
[140]	train-mlogloss:1.55158	validation-mlogloss:1.58884
[141]	train-mlogloss:1.54901	validation-mlogloss:1.58649
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[563]	train-mlogloss:1.25974	validation-mlogloss:1.34429
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[566]	train-mlogloss:1.25957	validation-mlogloss:1.34421
[567]	train-mlogloss:1.25941	validation-mlogloss:1.34418
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[573]	train-mlogloss:1.25918	validation-mlogloss:1.34404
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[575]	train-mlogloss:1.25907	validation-mlogloss:1.34397
[576]	train-mlogloss:1.25907	validation-mlogloss:1.34397
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[660]	train-mlogloss:1.25466	validation-mlogloss:1.34123
[661]	train-mlogloss:1.25460	validation-mlogloss:1.34118
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[663]	train-mlogloss:1.25453	validation-mlogloss:1.34113
[664]	train-mlogloss:1.25448	validation-mlogloss:1.34110
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[666]	train-mlogloss:1.25436	validation-mlogloss:1.34103
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[672]	train-mlogloss:1.25412	validation-mlogloss:1.34091
[673]	train-mlogloss:1.25405	validation-mlogloss:1.34087
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[677]	train-mlogloss:1.25396	validation-mlogloss:1.34077
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[679]	train-mlogloss:1.25390	validation-mlogloss:1.34073
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[681]	train-mlogloss:1.25388	validation-mlogloss:1.34073
[682]	train-mlogloss:1.25388	validation-mlogloss:1.34073
[683]	train-mlogloss:1.25381	validation-mlogloss:1.34071
[684]	train-mlogloss:1.25379	validation-mlogloss:1.34072
[685]	train-mlogloss:1.25376	validation-mlogloss:1.34066
[686]	train-mlogloss:1.25371	validation-mlogloss:1.34060
[687]	train-mlogloss:1.25368	validation-mlogloss:1.34058
[688]	train-mlogloss:1.25361	validation-mlogloss:1.34058
[689]	train-mlogloss:1.25358	validation-mlogloss:1.34053
[690]	train-mlogloss:1.25355	validation-mlogloss:1.34053
[691]	train-mlogloss:1.25350	validation-mlogloss:1.34055
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[693]	train-mlogloss:1.25336	validation-mlogloss:1.34053
[694]	train-mlogloss:1.25336	validation-mlogloss:1.34053
[695]	train-mlogloss:1.25335	validation-mlogloss:1.34051
[696]	train-mlogloss:1.25332	validation-mlogloss:1.34047
[697]	train-mlogloss:1.25330	validation-mlogloss:1.34045
[698]	train-mlogloss:1.25330	validation-mlogloss:1.34045
[699]	train-mlogloss:1.25330	validation-mlogloss:1.34045
[700]	train-mlogloss:1.25325	validation-mlogloss:1.34046
[701]	train-mlogloss:1.25321	validation-mlogloss:1.34044
[702]	train-mlogloss:1.25321	validation-mlogloss:1.34044
[703]	train-mlogloss:1.25320	validation-mlogloss:1.34042
[704]	train-mlogloss:1.25315	validation-mlogloss:1.34039
[705]	train-mlogloss:1.25312	validation-mlogloss:1.34034
[706]	train-mlogloss:1.25309	validation-mlogloss:1.34032
[707]	train-mlogloss:1.25302	validation-mlogloss:1.34031
[708]	train-mlogloss:1.25295	validation-mlogloss:1.34027
[709]	train-mlogloss:1.25286	validation-mlogloss:1.34018
[710]	train-mlogloss:1.25283	validation-mlogloss:1.34015
[711]	train-mlogloss:1.25279	validation-mlogloss:1.34010
[712]	train-mlogloss:1.25274	validation-mlogloss:1.34006
[713]	train-mlogloss:1.25274	validation-mlogloss:1.34006
Saved model to disk.
2025-10-27 11:26:28.903250: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:26:28.915933: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560788.929793  541242 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560788.934169  541242 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560788.945061  541242 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560788.945085  541242 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560788.945088  541242 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560788.945091  541242 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:26:28.948496: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68325	validation-mlogloss:2.68399
[1]	train-mlogloss:2.66158	validation-mlogloss:2.66335
[2]	train-mlogloss:2.63948	validation-mlogloss:2.64157
[3]	train-mlogloss:2.61778	validation-mlogloss:2.62063
[4]	train-mlogloss:2.59751	validation-mlogloss:2.60111
[5]	train-mlogloss:2.57719	validation-mlogloss:2.58177
[6]	train-mlogloss:2.55741	validation-mlogloss:2.56216
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[610]	train-mlogloss:1.25501	validation-mlogloss:1.34155
[611]	train-mlogloss:1.25495	validation-mlogloss:1.34155
[612]	train-mlogloss:1.25495	validation-mlogloss:1.34155
[613]	train-mlogloss:1.25493	validation-mlogloss:1.34155
[614]	train-mlogloss:1.25487	validation-mlogloss:1.34150
[615]	train-mlogloss:1.25479	validation-mlogloss:1.34143
[616]	train-mlogloss:1.25476	validation-mlogloss:1.34141
[617]	train-mlogloss:1.25471	validation-mlogloss:1.34140
[618]	train-mlogloss:1.25463	validation-mlogloss:1.34133
[619]	train-mlogloss:1.25459	validation-mlogloss:1.34132
[620]	train-mlogloss:1.25455	validation-mlogloss:1.34132
[621]	train-mlogloss:1.25455	validation-mlogloss:1.34132
[622]	train-mlogloss:1.25445	validation-mlogloss:1.34125
[623]	train-mlogloss:1.25441	validation-mlogloss:1.34121
[624]	train-mlogloss:1.25439	validation-mlogloss:1.34121
[625]	train-mlogloss:1.25433	validation-mlogloss:1.34115
[626]	train-mlogloss:1.25432	validation-mlogloss:1.34114
[627]	train-mlogloss:1.25431	validation-mlogloss:1.34114
[628]	train-mlogloss:1.25428	validation-mlogloss:1.34109
[629]	train-mlogloss:1.25428	validation-mlogloss:1.34109
[630]	train-mlogloss:1.25426	validation-mlogloss:1.34108
[631]	train-mlogloss:1.25425	validation-mlogloss:1.34109
[632]	train-mlogloss:1.25418	validation-mlogloss:1.34107
[633]	train-mlogloss:1.25412	validation-mlogloss:1.34098
[634]	train-mlogloss:1.25404	validation-mlogloss:1.34094
[635]	train-mlogloss:1.25391	validation-mlogloss:1.34088
[636]	train-mlogloss:1.25386	validation-mlogloss:1.34084
[637]	train-mlogloss:1.25386	validation-mlogloss:1.34084
[638]	train-mlogloss:1.25383	validation-mlogloss:1.34083
[639]	train-mlogloss:1.25383	validation-mlogloss:1.34083
[640]	train-mlogloss:1.25371	validation-mlogloss:1.34082
[641]	train-mlogloss:1.25367	validation-mlogloss:1.34079
[642]	train-mlogloss:1.25357	validation-mlogloss:1.34068
[643]	train-mlogloss:1.25354	validation-mlogloss:1.34066
[644]	train-mlogloss:1.25354	validation-mlogloss:1.34066
[645]	train-mlogloss:1.25342	validation-mlogloss:1.34057
[646]	train-mlogloss:1.25342	validation-mlogloss:1.34057
[647]	train-mlogloss:1.25342	validation-mlogloss:1.34057
[648]	train-mlogloss:1.25341	validation-mlogloss:1.34056
[649]	train-mlogloss:1.25334	validation-mlogloss:1.34054
[650]	train-mlogloss:1.25328	validation-mlogloss:1.34054
[651]	train-mlogloss:1.25325	validation-mlogloss:1.34054
[652]	train-mlogloss:1.25319	validation-mlogloss:1.34051
[653]	train-mlogloss:1.25315	validation-mlogloss:1.34048
[654]	train-mlogloss:1.25312	validation-mlogloss:1.34043
[655]	train-mlogloss:1.25305	validation-mlogloss:1.34039
[656]	train-mlogloss:1.25296	validation-mlogloss:1.34033
[657]	train-mlogloss:1.25296	validation-mlogloss:1.34033
[658]	train-mlogloss:1.25292	validation-mlogloss:1.34028
[659]	train-mlogloss:1.25292	validation-mlogloss:1.34028
[660]	train-mlogloss:1.25292	validation-mlogloss:1.34029
[661]	train-mlogloss:1.25291	validation-mlogloss:1.34029
[662]	train-mlogloss:1.25283	validation-mlogloss:1.34026
[663]	train-mlogloss:1.25274	validation-mlogloss:1.34023
[664]	train-mlogloss:1.25273	validation-mlogloss:1.34025
[665]	train-mlogloss:1.25271	validation-mlogloss:1.34024
[666]	train-mlogloss:1.25257	validation-mlogloss:1.34012
[667]	train-mlogloss:1.25255	validation-mlogloss:1.34010
[668]	train-mlogloss:1.25248	validation-mlogloss:1.33999
[669]	train-mlogloss:1.25247	validation-mlogloss:1.33998
[670]	train-mlogloss:1.25239	validation-mlogloss:1.33993
[671]	train-mlogloss:1.25234	validation-mlogloss:1.33989
[672]	train-mlogloss:1.25234	validation-mlogloss:1.33989
[673]	train-mlogloss:1.25234	validation-mlogloss:1.33989
[674]	train-mlogloss:1.25233	validation-mlogloss:1.33988
[675]	train-mlogloss:1.25224	validation-mlogloss:1.33981
[676]	train-mlogloss:1.25223	validation-mlogloss:1.33982
[677]	train-mlogloss:1.25218	validation-mlogloss:1.33984
[678]	train-mlogloss:1.25216	validation-mlogloss:1.33983
[679]	train-mlogloss:1.25213	validation-mlogloss:1.33981
[680]	train-mlogloss:1.25211	validation-mlogloss:1.33979
[681]	train-mlogloss:1.25210	validation-mlogloss:1.33979
[682]	train-mlogloss:1.25210	validation-mlogloss:1.33980
[683]	train-mlogloss:1.25208	validation-mlogloss:1.33977
[684]	train-mlogloss:1.25208	validation-mlogloss:1.33977
[685]	train-mlogloss:1.25207	validation-mlogloss:1.33978
[686]	train-mlogloss:1.25207	validation-mlogloss:1.33978
[687]	train-mlogloss:1.25202	validation-mlogloss:1.33975
[688]	train-mlogloss:1.25195	validation-mlogloss:1.33973
[689]	train-mlogloss:1.25192	validation-mlogloss:1.33975
[690]	train-mlogloss:1.25188	validation-mlogloss:1.33976
[691]	train-mlogloss:1.25187	validation-mlogloss:1.33975
[692]	train-mlogloss:1.25180	validation-mlogloss:1.33974
[693]	train-mlogloss:1.25177	validation-mlogloss:1.33971
[694]	train-mlogloss:1.25175	validation-mlogloss:1.33971
[695]	train-mlogloss:1.25174	validation-mlogloss:1.33970
[696]	train-mlogloss:1.25171	validation-mlogloss:1.33968
[697]	train-mlogloss:1.25166	validation-mlogloss:1.33966
[698]	train-mlogloss:1.25161	validation-mlogloss:1.33962
[699]	train-mlogloss:1.25161	validation-mlogloss:1.33962
[700]	train-mlogloss:1.25160	validation-mlogloss:1.33962
[701]	train-mlogloss:1.25158	validation-mlogloss:1.33962
[702]	train-mlogloss:1.25153	validation-mlogloss:1.33957
[703]	train-mlogloss:1.25147	validation-mlogloss:1.33954
[704]	train-mlogloss:1.25141	validation-mlogloss:1.33952
[705]	train-mlogloss:1.25140	validation-mlogloss:1.33950
[706]	train-mlogloss:1.25138	validation-mlogloss:1.33951
[707]	train-mlogloss:1.25132	validation-mlogloss:1.33948
[708]	train-mlogloss:1.25132	validation-mlogloss:1.33948
[709]	train-mlogloss:1.25127	validation-mlogloss:1.33945
[710]	train-mlogloss:1.25121	validation-mlogloss:1.33942
[711]	train-mlogloss:1.25118	validation-mlogloss:1.33940
[712]	train-mlogloss:1.25113	validation-mlogloss:1.33935
[713]	train-mlogloss:1.25111	validation-mlogloss:1.33935
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.61 [%]
Global accuracy score (test) = 50.24 [%]
Global F1 score (train) = 62.68 [%]
Global F1 score (test) = 50.48 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.26      0.38      0.31       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.39      0.42       184
       CAMINAR USUAL SPEED       0.27      0.21      0.24       184
            CAMINAR ZIGZAG       0.59      0.55      0.57       184
          DE PIE BARRIENDO       0.57      0.50      0.53       184
   DE PIE DOBLANDO TOALLAS       0.41      0.46      0.43       184
    DE PIE MOVIENDO LIBROS       0.47      0.43      0.45       184
          DE PIE USANDO PC       0.61      0.66      0.64       184
        FASE REPOSO CON K5       0.54      0.79      0.64       184
INCREMENTAL CICLOERGOMETRO       0.88      0.64      0.74       184
           SENTADO LEYENDO       0.36      0.42      0.39       184
         SENTADO USANDO PC       0.40      0.27      0.32       184
      SENTADO VIENDO LA TV       0.48      0.40      0.44       184
   SUBIR Y BAJAR ESCALERAS       0.54      0.66      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.50      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 13: 50.24 [%]
F1-score capturado en la ejecución 13: 50.48 [%]

=== EJECUCIÓN 14 ===

--- TRAIN (ejecución 14) ---

--- TEST (ejecución 14) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.83 [%]
Global accuracy score (test) = 50.64 [%]
Global F1 score (train) = 62.87 [%]
Global F1 score (test) = 50.91 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.27      0.36      0.31       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.43      0.44       184
       CAMINAR USUAL SPEED       0.30      0.24      0.26       184
            CAMINAR ZIGZAG       0.60      0.54      0.57       184
          DE PIE BARRIENDO       0.55      0.50      0.52       184
   DE PIE DOBLANDO TOALLAS       0.43      0.47      0.45       184
    DE PIE MOVIENDO LIBROS       0.48      0.46      0.47       184
          DE PIE USANDO PC       0.62      0.66      0.64       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.90      0.62      0.74       184
           SENTADO LEYENDO       0.36      0.43      0.39       184
         SENTADO USANDO PC       0.39      0.27      0.32       184
      SENTADO VIENDO LA TV       0.46      0.37      0.41       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.66      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.51      2737


Accuracy capturado en la ejecución 14: 50.64 [%]
F1-score capturado en la ejecución 14: 50.91 [%]

=== EJECUCIÓN 15 ===

--- TRAIN (ejecución 15) ---

--- TEST (ejecución 15) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.72 [%]
Global accuracy score (test) = 50.35 [%]
Global F1 score (train) = 62.76 [%]
Global F1 score (test) = 50.47 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.39      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.40      0.41       184
       CAMINAR USUAL SPEED       0.26      0.21      0.23       184
            CAMINAR ZIGZAG       0.60      0.54      0.57       184
          DE PIE BARRIENDO       0.54      0.49      0.51       184
   DE PIE DOBLANDO TOALLAS       0.43      0.45      0.44       184
    DE PIE MOVIENDO LIBROS       0.49      0.47      0.48       184
          DE PIE USANDO PC       0.61      0.67      0.64       184
        FASE REPOSO CON K5       0.55      0.80      0.65       184
INCREMENTAL CICLOERGOMETRO       0.87      0.64      0.73       184
           SENTADO LEYENDO       0.35      0.41      0.38       184
         SENTADO USANDO PC       0.39      0.25      0.30       184
      SENTADO VIENDO LA TV       0.47      0.40      0.43       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.67      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.51      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 15: 50.35 [%]
F1-score capturado en la ejecución 15: 50.47 [%]

=== EJECUCIÓN 16 ===

--- TRAIN (ejecución 16) ---

--- TEST (ejecución 16) ---
2025-10-27 11:27:16.284620: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:27:16.297420: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560836.311187  542165 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560836.315566  542165 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560836.326416  542165 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560836.326439  542165 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560836.326442  542165 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560836.326444  542165 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:27:16.329842: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68506	validation-mlogloss:2.68588
[1]	train-mlogloss:2.66131	validation-mlogloss:2.66336
[2]	train-mlogloss:2.63824	validation-mlogloss:2.64120
[3]	train-mlogloss:2.61769	validation-mlogloss:2.62150
[4]	train-mlogloss:2.59750	validation-mlogloss:2.60141
[5]	train-mlogloss:2.57673	validation-mlogloss:2.58020
[6]	train-mlogloss:2.55738	validation-mlogloss:2.56102
[7]	train-mlogloss:2.53851	validation-mlogloss:2.54200
[8]	train-mlogloss:2.51890	validation-mlogloss:2.52267
[9]	train-mlogloss:2.49989	validation-mlogloss:2.50386
[10]	train-mlogloss:2.48273	validation-mlogloss:2.48723
[11]	train-mlogloss:2.46507	validation-mlogloss:2.47047
[12]	train-mlogloss:2.44697	validation-mlogloss:2.45298
[13]	train-mlogloss:2.43000	validation-mlogloss:2.43653
[14]	train-mlogloss:2.41298	validation-mlogloss:2.42015
[15]	train-mlogloss:2.39650	validation-mlogloss:2.40415
[16]	train-mlogloss:2.38024	validation-mlogloss:2.38862
[17]	train-mlogloss:2.36503	validation-mlogloss:2.37350
[18]	train-mlogloss:2.34980	validation-mlogloss:2.35869
[19]	train-mlogloss:2.33473	validation-mlogloss:2.34437
[20]	train-mlogloss:2.32023	validation-mlogloss:2.33055
[21]	train-mlogloss:2.30561	validation-mlogloss:2.31620
[22]	train-mlogloss:2.29130	validation-mlogloss:2.30234
[23]	train-mlogloss:2.27739	validation-mlogloss:2.28859
[24]	train-mlogloss:2.26416	validation-mlogloss:2.27571
[25]	train-mlogloss:2.25134	validation-mlogloss:2.26395
[26]	train-mlogloss:2.23820	validation-mlogloss:2.25116
[27]	train-mlogloss:2.22540	validation-mlogloss:2.23834
[28]	train-mlogloss:2.21308	validation-mlogloss:2.22638
[29]	train-mlogloss:2.20063	validation-mlogloss:2.21426
[30]	train-mlogloss:2.18906	validation-mlogloss:2.20302
[31]	train-mlogloss:2.17701	validation-mlogloss:2.19099
[32]	train-mlogloss:2.16526	validation-mlogloss:2.17955
[33]	train-mlogloss:2.15400	validation-mlogloss:2.16819
[34]	train-mlogloss:2.14281	validation-mlogloss:2.15734
[35]	train-mlogloss:2.13186	validation-mlogloss:2.14645
[36]	train-mlogloss:2.12117	validation-mlogloss:2.13616
[37]	train-mlogloss:2.11066	validation-mlogloss:2.12538
[38]	train-mlogloss:2.10041	validation-mlogloss:2.11594
[39]	train-mlogloss:2.09016	validation-mlogloss:2.10589
[40]	train-mlogloss:2.07992	validation-mlogloss:2.09628
[41]	train-mlogloss:2.07020	validation-mlogloss:2.08708
[42]	train-mlogloss:2.06037	validation-mlogloss:2.07781
[43]	train-mlogloss:2.05077	validation-mlogloss:2.06838
[44]	train-mlogloss:2.04155	validation-mlogloss:2.05919
[45]	train-mlogloss:2.03223	validation-mlogloss:2.05020
[46]	train-mlogloss:2.02328	validation-mlogloss:2.04184
[47]	train-mlogloss:2.01414	validation-mlogloss:2.03302
[48]	train-mlogloss:2.00575	validation-mlogloss:2.02507
[49]	train-mlogloss:1.99721	validation-mlogloss:2.01688
[50]	train-mlogloss:1.98873	validation-mlogloss:2.00875
[51]	train-mlogloss:1.98073	validation-mlogloss:2.00064
[52]	train-mlogloss:1.97238	validation-mlogloss:1.99251
[53]	train-mlogloss:1.96424	validation-mlogloss:1.98457
[54]	train-mlogloss:1.95617	validation-mlogloss:1.97669
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[657]	train-mlogloss:1.25396	validation-mlogloss:1.34254
[658]	train-mlogloss:1.25396	validation-mlogloss:1.34254
[659]	train-mlogloss:1.25396	validation-mlogloss:1.34254
[660]	train-mlogloss:1.25385	validation-mlogloss:1.34252
[661]	train-mlogloss:1.25378	validation-mlogloss:1.34247
[662]	train-mlogloss:1.25374	validation-mlogloss:1.34249
[663]	train-mlogloss:1.25364	validation-mlogloss:1.34248
[664]	train-mlogloss:1.25364	validation-mlogloss:1.34248
[665]	train-mlogloss:1.25359	validation-mlogloss:1.34244
[666]	train-mlogloss:1.25355	validation-mlogloss:1.34246
[667]	train-mlogloss:1.25346	validation-mlogloss:1.34242
[668]	train-mlogloss:1.25345	validation-mlogloss:1.34239
[669]	train-mlogloss:1.25341	validation-mlogloss:1.34238
[670]	train-mlogloss:1.25341	validation-mlogloss:1.34238
[671]	train-mlogloss:1.25329	validation-mlogloss:1.34222
[672]	train-mlogloss:1.25325	validation-mlogloss:1.34222
[673]	train-mlogloss:1.25323	validation-mlogloss:1.34219
[674]	train-mlogloss:1.25322	validation-mlogloss:1.34219
[675]	train-mlogloss:1.25319	validation-mlogloss:1.34216
[676]	train-mlogloss:1.25313	validation-mlogloss:1.34208
[677]	train-mlogloss:1.25307	validation-mlogloss:1.34201
[678]	train-mlogloss:1.25303	validation-mlogloss:1.34197
[679]	train-mlogloss:1.25301	validation-mlogloss:1.34195
[680]	train-mlogloss:1.25300	validation-mlogloss:1.34193
[681]	train-mlogloss:1.25296	validation-mlogloss:1.34190
[682]	train-mlogloss:1.25287	validation-mlogloss:1.34185
[683]	train-mlogloss:1.25282	validation-mlogloss:1.34183
[684]	train-mlogloss:1.25279	validation-mlogloss:1.34178
[685]	train-mlogloss:1.25273	validation-mlogloss:1.34171
[686]	train-mlogloss:1.25270	validation-mlogloss:1.34170
[687]	train-mlogloss:1.25270	validation-mlogloss:1.34170
[688]	train-mlogloss:1.25265	validation-mlogloss:1.34167
[689]	train-mlogloss:1.25256	validation-mlogloss:1.34159
[690]	train-mlogloss:1.25255	validation-mlogloss:1.34158
[691]	train-mlogloss:1.25253	validation-mlogloss:1.34156
[692]	train-mlogloss:1.25253	validation-mlogloss:1.34156
[693]	train-mlogloss:1.25253	validation-mlogloss:1.34156
[694]	train-mlogloss:1.25250	validation-mlogloss:1.34157
[695]	train-mlogloss:1.25246	validation-mlogloss:1.34153
[696]	train-mlogloss:1.25243	validation-mlogloss:1.34148
[697]	train-mlogloss:1.25243	validation-mlogloss:1.34148
[698]	train-mlogloss:1.25232	validation-mlogloss:1.34136
[699]	train-mlogloss:1.25230	validation-mlogloss:1.34135
[700]	train-mlogloss:1.25229	validation-mlogloss:1.34135
[701]	train-mlogloss:1.25228	validation-mlogloss:1.34135
[702]	train-mlogloss:1.25228	validation-mlogloss:1.34135
[703]	train-mlogloss:1.25218	validation-mlogloss:1.34131
[704]	train-mlogloss:1.25215	validation-mlogloss:1.34130
[705]	train-mlogloss:1.25207	validation-mlogloss:1.34121
[706]	train-mlogloss:1.25204	validation-mlogloss:1.34119
[707]	train-mlogloss:1.25196	validation-mlogloss:1.34114
[708]	train-mlogloss:1.25193	validation-mlogloss:1.34112
[709]	train-mlogloss:1.25190	validation-mlogloss:1.34109
[710]	train-mlogloss:1.25190	validation-mlogloss:1.34109
[711]	train-mlogloss:1.25187	validation-mlogloss:1.34105
[712]	train-mlogloss:1.25182	validation-mlogloss:1.34101
[713]	train-mlogloss:1.25176	validation-mlogloss:1.34096
Saved model to disk.
2025-10-27 11:28:03.363728: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:28:03.376553: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560883.390477  543082 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560883.394874  543082 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560883.406191  543082 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560883.406222  543082 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560883.406226  543082 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560883.406228  543082 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:28:03.409690: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68543	validation-mlogloss:2.68567
[1]	train-mlogloss:2.66177	validation-mlogloss:2.66237
[2]	train-mlogloss:2.63944	validation-mlogloss:2.64066
[3]	train-mlogloss:2.61635	validation-mlogloss:2.61851
[4]	train-mlogloss:2.59580	validation-mlogloss:2.59793
[5]	train-mlogloss:2.57603	validation-mlogloss:2.57880
[6]	train-mlogloss:2.55677	validation-mlogloss:2.55951
[7]	train-mlogloss:2.53674	validation-mlogloss:2.53965
[8]	train-mlogloss:2.51760	validation-mlogloss:2.52105
[9]	train-mlogloss:2.49880	validation-mlogloss:2.50260
[10]	train-mlogloss:2.48041	validation-mlogloss:2.48434
[11]	train-mlogloss:2.46207	validation-mlogloss:2.46629
[12]	train-mlogloss:2.44534	validation-mlogloss:2.45041
[13]	train-mlogloss:2.42814	validation-mlogloss:2.43341
[14]	train-mlogloss:2.41138	validation-mlogloss:2.41670
[15]	train-mlogloss:2.39509	validation-mlogloss:2.40054
[16]	train-mlogloss:2.37899	validation-mlogloss:2.38461
[17]	train-mlogloss:2.36308	validation-mlogloss:2.36963
[18]	train-mlogloss:2.34753	validation-mlogloss:2.35482
[19]	train-mlogloss:2.33247	validation-mlogloss:2.34019
[20]	train-mlogloss:2.31847	validation-mlogloss:2.32657
[21]	train-mlogloss:2.30423	validation-mlogloss:2.31250
[22]	train-mlogloss:2.28998	validation-mlogloss:2.29858
[23]	train-mlogloss:2.27631	validation-mlogloss:2.28529
[24]	train-mlogloss:2.26278	validation-mlogloss:2.27223
[25]	train-mlogloss:2.24929	validation-mlogloss:2.25970
[26]	train-mlogloss:2.23599	validation-mlogloss:2.24691
[27]	train-mlogloss:2.22329	validation-mlogloss:2.23455
[28]	train-mlogloss:2.21075	validation-mlogloss:2.22211
[29]	train-mlogloss:2.19888	validation-mlogloss:2.21065
[30]	train-mlogloss:2.18689	validation-mlogloss:2.19865
[31]	train-mlogloss:2.17492	validation-mlogloss:2.18743
[32]	train-mlogloss:2.16341	validation-mlogloss:2.17680
[33]	train-mlogloss:2.15198	validation-mlogloss:2.16616
[34]	train-mlogloss:2.14091	validation-mlogloss:2.15525
[35]	train-mlogloss:2.12977	validation-mlogloss:2.14464
[36]	train-mlogloss:2.11920	validation-mlogloss:2.13417
[37]	train-mlogloss:2.10876	validation-mlogloss:2.12380
[38]	train-mlogloss:2.09830	validation-mlogloss:2.11360
[39]	train-mlogloss:2.08832	validation-mlogloss:2.10356
[40]	train-mlogloss:2.07833	validation-mlogloss:2.09373
[41]	train-mlogloss:2.06854	validation-mlogloss:2.08398
[42]	train-mlogloss:2.05924	validation-mlogloss:2.07513
[43]	train-mlogloss:2.05002	validation-mlogloss:2.06622
[44]	train-mlogloss:2.04038	validation-mlogloss:2.05729
[45]	train-mlogloss:2.03092	validation-mlogloss:2.04796
[46]	train-mlogloss:2.02211	validation-mlogloss:2.03949
[47]	train-mlogloss:2.01353	validation-mlogloss:2.03116
[48]	train-mlogloss:2.00488	validation-mlogloss:2.02282
[49]	train-mlogloss:1.99636	validation-mlogloss:2.01409
[50]	train-mlogloss:1.98782	validation-mlogloss:2.00560
[51]	train-mlogloss:1.97914	validation-mlogloss:1.99702
[52]	train-mlogloss:1.97076	validation-mlogloss:1.98883
[53]	train-mlogloss:1.96264	validation-mlogloss:1.98094
[54]	train-mlogloss:1.95483	validation-mlogloss:1.97358
[55]	train-mlogloss:1.94686	validation-mlogloss:1.96574
[56]	train-mlogloss:1.93941	validation-mlogloss:1.95817
[57]	train-mlogloss:1.93175	validation-mlogloss:1.95082
[58]	train-mlogloss:1.92421	validation-mlogloss:1.94371
[59]	train-mlogloss:1.91679	validation-mlogloss:1.93653
[60]	train-mlogloss:1.90947	validation-mlogloss:1.92953
[61]	train-mlogloss:1.90246	validation-mlogloss:1.92279
[62]	train-mlogloss:1.89577	validation-mlogloss:1.91647
[63]	train-mlogloss:1.88888	validation-mlogloss:1.90987
[64]	train-mlogloss:1.88201	validation-mlogloss:1.90310
[65]	train-mlogloss:1.87545	validation-mlogloss:1.89689
[66]	train-mlogloss:1.86866	validation-mlogloss:1.89065
[67]	train-mlogloss:1.86240	validation-mlogloss:1.88479
[68]	train-mlogloss:1.85596	validation-mlogloss:1.87865
[69]	train-mlogloss:1.84963	validation-mlogloss:1.87261
[70]	train-mlogloss:1.84337	validation-mlogloss:1.86645
[71]	train-mlogloss:1.83735	validation-mlogloss:1.86064
[72]	train-mlogloss:1.83139	validation-mlogloss:1.85478
[73]	train-mlogloss:1.82534	validation-mlogloss:1.84894
[74]	train-mlogloss:1.81968	validation-mlogloss:1.84340
[75]	train-mlogloss:1.81365	validation-mlogloss:1.83755
[76]	train-mlogloss:1.80768	validation-mlogloss:1.83172
[77]	train-mlogloss:1.80212	validation-mlogloss:1.82632
[78]	train-mlogloss:1.79668	validation-mlogloss:1.82086
[79]	train-mlogloss:1.79100	validation-mlogloss:1.81557
[80]	train-mlogloss:1.78542	validation-mlogloss:1.81021
[81]	train-mlogloss:1.77990	validation-mlogloss:1.80489
[82]	train-mlogloss:1.77446	validation-mlogloss:1.79988
[83]	train-mlogloss:1.76908	validation-mlogloss:1.79481
[84]	train-mlogloss:1.76390	validation-mlogloss:1.79005
[85]	train-mlogloss:1.75865	validation-mlogloss:1.78495
[86]	train-mlogloss:1.75341	validation-mlogloss:1.78015
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[88]	train-mlogloss:1.74364	validation-mlogloss:1.77091
[89]	train-mlogloss:1.73867	validation-mlogloss:1.76608
[90]	train-mlogloss:1.73382	validation-mlogloss:1.76126
[91]	train-mlogloss:1.72901	validation-mlogloss:1.75662
[92]	train-mlogloss:1.72452	validation-mlogloss:1.75235
[93]	train-mlogloss:1.71989	validation-mlogloss:1.74793
[94]	train-mlogloss:1.71526	validation-mlogloss:1.74337
[95]	train-mlogloss:1.71067	validation-mlogloss:1.73905
[96]	train-mlogloss:1.70597	validation-mlogloss:1.73482
[97]	train-mlogloss:1.70167	validation-mlogloss:1.73097
[98]	train-mlogloss:1.69719	validation-mlogloss:1.72669
[99]	train-mlogloss:1.69273	validation-mlogloss:1.72272
[100]	train-mlogloss:1.68839	validation-mlogloss:1.71882
[101]	train-mlogloss:1.68417	validation-mlogloss:1.71461
[102]	train-mlogloss:1.68023	validation-mlogloss:1.71099
[103]	train-mlogloss:1.67599	validation-mlogloss:1.70712
[104]	train-mlogloss:1.67198	validation-mlogloss:1.70297
[105]	train-mlogloss:1.66803	validation-mlogloss:1.69920
[106]	train-mlogloss:1.66416	validation-mlogloss:1.69564
[107]	train-mlogloss:1.66032	validation-mlogloss:1.69198
[108]	train-mlogloss:1.65626	validation-mlogloss:1.68798
[109]	train-mlogloss:1.65240	validation-mlogloss:1.68437
[110]	train-mlogloss:1.64846	validation-mlogloss:1.68068
[111]	train-mlogloss:1.64459	validation-mlogloss:1.67714
[112]	train-mlogloss:1.64082	validation-mlogloss:1.67354
[113]	train-mlogloss:1.63715	validation-mlogloss:1.66999
[114]	train-mlogloss:1.63347	validation-mlogloss:1.66652
[115]	train-mlogloss:1.62979	validation-mlogloss:1.66319
[116]	train-mlogloss:1.62616	validation-mlogloss:1.65969
[117]	train-mlogloss:1.62255	validation-mlogloss:1.65630
[118]	train-mlogloss:1.61900	validation-mlogloss:1.65284
[119]	train-mlogloss:1.61565	validation-mlogloss:1.64976
[120]	train-mlogloss:1.61222	validation-mlogloss:1.64653
[121]	train-mlogloss:1.60890	validation-mlogloss:1.64337
[122]	train-mlogloss:1.60539	validation-mlogloss:1.64025
[123]	train-mlogloss:1.60206	validation-mlogloss:1.63715
[124]	train-mlogloss:1.59880	validation-mlogloss:1.63407
[125]	train-mlogloss:1.59576	validation-mlogloss:1.63113
[126]	train-mlogloss:1.59244	validation-mlogloss:1.62828
[127]	train-mlogloss:1.58931	validation-mlogloss:1.62536
[128]	train-mlogloss:1.58606	validation-mlogloss:1.62221
[129]	train-mlogloss:1.58269	validation-mlogloss:1.61915
[130]	train-mlogloss:1.57969	validation-mlogloss:1.61619
[131]	train-mlogloss:1.57653	validation-mlogloss:1.61326
[132]	train-mlogloss:1.57360	validation-mlogloss:1.61045
[133]	train-mlogloss:1.57066	validation-mlogloss:1.60755
[134]	train-mlogloss:1.56761	validation-mlogloss:1.60463
[135]	train-mlogloss:1.56468	validation-mlogloss:1.60187
[136]	train-mlogloss:1.56177	validation-mlogloss:1.59914
[137]	train-mlogloss:1.55890	validation-mlogloss:1.59659
[138]	train-mlogloss:1.55602	validation-mlogloss:1.59409
[139]	train-mlogloss:1.55327	validation-mlogloss:1.59181
[140]	train-mlogloss:1.55066	validation-mlogloss:1.58936
[141]	train-mlogloss:1.54780	validation-mlogloss:1.58709
[142]	train-mlogloss:1.54494	validation-mlogloss:1.58453
[143]	train-mlogloss:1.54213	validation-mlogloss:1.58184
[144]	train-mlogloss:1.53955	validation-mlogloss:1.57938
[145]	train-mlogloss:1.53689	validation-mlogloss:1.57669
[146]	train-mlogloss:1.53437	validation-mlogloss:1.57419
[147]	train-mlogloss:1.53183	validation-mlogloss:1.57182
[148]	train-mlogloss:1.52937	validation-mlogloss:1.56951
[149]	train-mlogloss:1.52689	validation-mlogloss:1.56723
[150]	train-mlogloss:1.52439	validation-mlogloss:1.56480
[151]	train-mlogloss:1.52194	validation-mlogloss:1.56245
[152]	train-mlogloss:1.51949	validation-mlogloss:1.56030
[153]	train-mlogloss:1.51691	validation-mlogloss:1.55797
[154]	train-mlogloss:1.51448	validation-mlogloss:1.55599
[155]	train-mlogloss:1.51203	validation-mlogloss:1.55365
[156]	train-mlogloss:1.50948	validation-mlogloss:1.55113
[157]	train-mlogloss:1.50710	validation-mlogloss:1.54912
[158]	train-mlogloss:1.50493	validation-mlogloss:1.54713
[159]	train-mlogloss:1.50267	validation-mlogloss:1.54524
[160]	train-mlogloss:1.50039	validation-mlogloss:1.54310
[161]	train-mlogloss:1.49803	validation-mlogloss:1.54103
[162]	train-mlogloss:1.49562	validation-mlogloss:1.53890
[163]	train-mlogloss:1.49345	validation-mlogloss:1.53703
[164]	train-mlogloss:1.49124	validation-mlogloss:1.53507
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[189]	train-mlogloss:1.44244	validation-mlogloss:1.49194
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[191]	train-mlogloss:1.43886	validation-mlogloss:1.48879
[192]	train-mlogloss:1.43716	validation-mlogloss:1.48726
[193]	train-mlogloss:1.43550	validation-mlogloss:1.48579
[194]	train-mlogloss:1.43385	validation-mlogloss:1.48441
[195]	train-mlogloss:1.43214	validation-mlogloss:1.48294
[196]	train-mlogloss:1.43065	validation-mlogloss:1.48179
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[198]	train-mlogloss:1.42742	validation-mlogloss:1.47912
[199]	train-mlogloss:1.42571	validation-mlogloss:1.47760
[200]	train-mlogloss:1.42420	validation-mlogloss:1.47633
[201]	train-mlogloss:1.42262	validation-mlogloss:1.47511
[202]	train-mlogloss:1.42097	validation-mlogloss:1.47354
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[205]	train-mlogloss:1.41666	validation-mlogloss:1.46981
[206]	train-mlogloss:1.41513	validation-mlogloss:1.46862
[207]	train-mlogloss:1.41368	validation-mlogloss:1.46739
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[209]	train-mlogloss:1.41092	validation-mlogloss:1.46502
[210]	train-mlogloss:1.40942	validation-mlogloss:1.46389
[211]	train-mlogloss:1.40794	validation-mlogloss:1.46280
[212]	train-mlogloss:1.40655	validation-mlogloss:1.46155
[213]	train-mlogloss:1.40514	validation-mlogloss:1.46022
[214]	train-mlogloss:1.40359	validation-mlogloss:1.45903
[215]	train-mlogloss:1.40226	validation-mlogloss:1.45789
[216]	train-mlogloss:1.40095	validation-mlogloss:1.45685
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[523]	train-mlogloss:1.26132	validation-mlogloss:1.34642
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[525]	train-mlogloss:1.26119	validation-mlogloss:1.34629
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[530]	train-mlogloss:1.26081	validation-mlogloss:1.34621
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[534]	train-mlogloss:1.26056	validation-mlogloss:1.34612
[535]	train-mlogloss:1.26053	validation-mlogloss:1.34608
[536]	train-mlogloss:1.26053	validation-mlogloss:1.34608
[537]	train-mlogloss:1.26053	validation-mlogloss:1.34608
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[539]	train-mlogloss:1.26035	validation-mlogloss:1.34597
[540]	train-mlogloss:1.26030	validation-mlogloss:1.34594
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[542]	train-mlogloss:1.26022	validation-mlogloss:1.34592
[543]	train-mlogloss:1.26019	validation-mlogloss:1.34589
[544]	train-mlogloss:1.26019	validation-mlogloss:1.34589
[545]	train-mlogloss:1.26017	validation-mlogloss:1.34588
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[549]	train-mlogloss:1.26001	validation-mlogloss:1.34577
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[552]	train-mlogloss:1.25986	validation-mlogloss:1.34568
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[554]	train-mlogloss:1.25975	validation-mlogloss:1.34558
[555]	train-mlogloss:1.25969	validation-mlogloss:1.34556
[556]	train-mlogloss:1.25962	validation-mlogloss:1.34551
[557]	train-mlogloss:1.25948	validation-mlogloss:1.34539
[558]	train-mlogloss:1.25939	validation-mlogloss:1.34531
[559]	train-mlogloss:1.25931	validation-mlogloss:1.34523
[560]	train-mlogloss:1.25921	validation-mlogloss:1.34517
[561]	train-mlogloss:1.25918	validation-mlogloss:1.34516
[562]	train-mlogloss:1.25918	validation-mlogloss:1.34516
[563]	train-mlogloss:1.25910	validation-mlogloss:1.34514
[564]	train-mlogloss:1.25902	validation-mlogloss:1.34504
[565]	train-mlogloss:1.25895	validation-mlogloss:1.34505
[566]	train-mlogloss:1.25886	validation-mlogloss:1.34496
[567]	train-mlogloss:1.25886	validation-mlogloss:1.34496
[568]	train-mlogloss:1.25880	validation-mlogloss:1.34494
[569]	train-mlogloss:1.25873	validation-mlogloss:1.34488
[570]	train-mlogloss:1.25870	validation-mlogloss:1.34484
[571]	train-mlogloss:1.25858	validation-mlogloss:1.34473
[572]	train-mlogloss:1.25858	validation-mlogloss:1.34473
[573]	train-mlogloss:1.25851	validation-mlogloss:1.34473
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[575]	train-mlogloss:1.25824	validation-mlogloss:1.34464
[576]	train-mlogloss:1.25811	validation-mlogloss:1.34456
[577]	train-mlogloss:1.25811	validation-mlogloss:1.34456
[578]	train-mlogloss:1.25802	validation-mlogloss:1.34452
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[580]	train-mlogloss:1.25794	validation-mlogloss:1.34443
[581]	train-mlogloss:1.25790	validation-mlogloss:1.34439
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[624]	train-mlogloss:1.25621	validation-mlogloss:1.34320
[625]	train-mlogloss:1.25615	validation-mlogloss:1.34320
[626]	train-mlogloss:1.25612	validation-mlogloss:1.34319
[627]	train-mlogloss:1.25608	validation-mlogloss:1.34316
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[640]	train-mlogloss:1.25559	validation-mlogloss:1.34299
[641]	train-mlogloss:1.25550	validation-mlogloss:1.34300
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[643]	train-mlogloss:1.25549	validation-mlogloss:1.34298
[644]	train-mlogloss:1.25539	validation-mlogloss:1.34297
[645]	train-mlogloss:1.25535	validation-mlogloss:1.34295
[646]	train-mlogloss:1.25535	validation-mlogloss:1.34296
[647]	train-mlogloss:1.25521	validation-mlogloss:1.34283
[648]	train-mlogloss:1.25520	validation-mlogloss:1.34281
[649]	train-mlogloss:1.25507	validation-mlogloss:1.34275
[650]	train-mlogloss:1.25504	validation-mlogloss:1.34270
[651]	train-mlogloss:1.25499	validation-mlogloss:1.34264
[652]	train-mlogloss:1.25499	validation-mlogloss:1.34264
[653]	train-mlogloss:1.25496	validation-mlogloss:1.34260
[654]	train-mlogloss:1.25489	validation-mlogloss:1.34260
[655]	train-mlogloss:1.25484	validation-mlogloss:1.34254
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[659]	train-mlogloss:1.25454	validation-mlogloss:1.34249
[660]	train-mlogloss:1.25454	validation-mlogloss:1.34249
[661]	train-mlogloss:1.25451	validation-mlogloss:1.34249
[662]	train-mlogloss:1.25444	validation-mlogloss:1.34250
[663]	train-mlogloss:1.25439	validation-mlogloss:1.34238
[664]	train-mlogloss:1.25433	validation-mlogloss:1.34237
[665]	train-mlogloss:1.25431	validation-mlogloss:1.34233
[666]	train-mlogloss:1.25429	validation-mlogloss:1.34234
[667]	train-mlogloss:1.25426	validation-mlogloss:1.34233
[668]	train-mlogloss:1.25424	validation-mlogloss:1.34232
[669]	train-mlogloss:1.25424	validation-mlogloss:1.34232
[670]	train-mlogloss:1.25424	validation-mlogloss:1.34232
[671]	train-mlogloss:1.25418	validation-mlogloss:1.34224
[672]	train-mlogloss:1.25407	validation-mlogloss:1.34220
[673]	train-mlogloss:1.25404	validation-mlogloss:1.34218
[674]	train-mlogloss:1.25397	validation-mlogloss:1.34214
[675]	train-mlogloss:1.25394	validation-mlogloss:1.34210
[676]	train-mlogloss:1.25391	validation-mlogloss:1.34209
[677]	train-mlogloss:1.25389	validation-mlogloss:1.34208
[678]	train-mlogloss:1.25383	validation-mlogloss:1.34203
[679]	train-mlogloss:1.25380	validation-mlogloss:1.34202
[680]	train-mlogloss:1.25376	validation-mlogloss:1.34201
[681]	train-mlogloss:1.25374	validation-mlogloss:1.34199
[682]	train-mlogloss:1.25367	validation-mlogloss:1.34192
[683]	train-mlogloss:1.25363	validation-mlogloss:1.34186
[684]	train-mlogloss:1.25363	validation-mlogloss:1.34186
[685]	train-mlogloss:1.25363	validation-mlogloss:1.34186
[686]	train-mlogloss:1.25359	validation-mlogloss:1.34181
[687]	train-mlogloss:1.25355	validation-mlogloss:1.34179
[688]	train-mlogloss:1.25349	validation-mlogloss:1.34173
[689]	train-mlogloss:1.25342	validation-mlogloss:1.34168
[690]	train-mlogloss:1.25339	validation-mlogloss:1.34165
[691]	train-mlogloss:1.25339	validation-mlogloss:1.34165
[692]	train-mlogloss:1.25336	validation-mlogloss:1.34164
[693]	train-mlogloss:1.25336	validation-mlogloss:1.34164
[694]	train-mlogloss:1.25328	validation-mlogloss:1.34156
[695]	train-mlogloss:1.25328	validation-mlogloss:1.34156
[696]	train-mlogloss:1.25327	validation-mlogloss:1.34154
[697]	train-mlogloss:1.25327	validation-mlogloss:1.34154
[698]	train-mlogloss:1.25322	validation-mlogloss:1.34152
[699]	train-mlogloss:1.25319	validation-mlogloss:1.34149
[700]	train-mlogloss:1.25313	validation-mlogloss:1.34149
[701]	train-mlogloss:1.25312	validation-mlogloss:1.34147
[702]	train-mlogloss:1.25310	validation-mlogloss:1.34145
[703]	train-mlogloss:1.25303	validation-mlogloss:1.34141
[704]	train-mlogloss:1.25301	validation-mlogloss:1.34141
[705]	train-mlogloss:1.25298	validation-mlogloss:1.34138
[706]	train-mlogloss:1.25293	validation-mlogloss:1.34136
[707]	train-mlogloss:1.25293	validation-mlogloss:1.34136
[708]	train-mlogloss:1.25286	validation-mlogloss:1.34129
[709]	train-mlogloss:1.25286	validation-mlogloss:1.34129
[710]	train-mlogloss:1.25281	validation-mlogloss:1.34126
[711]	train-mlogloss:1.25276	validation-mlogloss:1.34122
[712]	train-mlogloss:1.25271	validation-mlogloss:1.34117
[713]	train-mlogloss:1.25267	validation-mlogloss:1.34116
Saved model to disk.
2025-10-27 11:28:50.451004: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:28:50.463750: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560930.477602  544039 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560930.482053  544039 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560930.493537  544039 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560930.493573  544039 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560930.493577  544039 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560930.493580  544039 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:28:50.497089: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68481	validation-mlogloss:2.68455
[1]	train-mlogloss:2.66211	validation-mlogloss:2.66246
[2]	train-mlogloss:2.63943	validation-mlogloss:2.64056
[3]	train-mlogloss:2.61698	validation-mlogloss:2.61872
[4]	train-mlogloss:2.59447	validation-mlogloss:2.59632
[5]	train-mlogloss:2.57325	validation-mlogloss:2.57551
[6]	train-mlogloss:2.55361	validation-mlogloss:2.55611
[7]	train-mlogloss:2.53413	validation-mlogloss:2.53664
[8]	train-mlogloss:2.51493	validation-mlogloss:2.51784
[9]	train-mlogloss:2.49637	validation-mlogloss:2.49993
[10]	train-mlogloss:2.47836	validation-mlogloss:2.48237
[11]	train-mlogloss:2.46082	validation-mlogloss:2.46517
[12]	train-mlogloss:2.44316	validation-mlogloss:2.44792
[13]	train-mlogloss:2.42609	validation-mlogloss:2.43091
[14]	train-mlogloss:2.40956	validation-mlogloss:2.41535
[15]	train-mlogloss:2.39303	validation-mlogloss:2.40001
[16]	train-mlogloss:2.37787	validation-mlogloss:2.38528
[17]	train-mlogloss:2.36230	validation-mlogloss:2.36999
[18]	train-mlogloss:2.34687	validation-mlogloss:2.35511
[19]	train-mlogloss:2.33227	validation-mlogloss:2.34147
[20]	train-mlogloss:2.31838	validation-mlogloss:2.32801
[21]	train-mlogloss:2.30412	validation-mlogloss:2.31407
[22]	train-mlogloss:2.29046	validation-mlogloss:2.30056
[23]	train-mlogloss:2.27671	validation-mlogloss:2.28735
[24]	train-mlogloss:2.26347	validation-mlogloss:2.27417
[25]	train-mlogloss:2.25058	validation-mlogloss:2.26139
[26]	train-mlogloss:2.23784	validation-mlogloss:2.24861
[27]	train-mlogloss:2.22533	validation-mlogloss:2.23638
[28]	train-mlogloss:2.21231	validation-mlogloss:2.22345
[29]	train-mlogloss:2.20012	validation-mlogloss:2.21108
[30]	train-mlogloss:2.18802	validation-mlogloss:2.19958
[31]	train-mlogloss:2.17640	validation-mlogloss:2.18772
[32]	train-mlogloss:2.16512	validation-mlogloss:2.17670
[33]	train-mlogloss:2.15357	validation-mlogloss:2.16537
[34]	train-mlogloss:2.14229	validation-mlogloss:2.15427
[35]	train-mlogloss:2.13110	validation-mlogloss:2.14402
[36]	train-mlogloss:2.12078	validation-mlogloss:2.13377
[37]	train-mlogloss:2.11029	validation-mlogloss:2.12369
[38]	train-mlogloss:2.09999	validation-mlogloss:2.11381
[39]	train-mlogloss:2.08997	validation-mlogloss:2.10387
[40]	train-mlogloss:2.07990	validation-mlogloss:2.09442
[41]	train-mlogloss:2.06999	validation-mlogloss:2.08527
[42]	train-mlogloss:2.06001	validation-mlogloss:2.07591
[43]	train-mlogloss:2.05073	validation-mlogloss:2.06730
[44]	train-mlogloss:2.04128	validation-mlogloss:2.05809
[45]	train-mlogloss:2.03191	validation-mlogloss:2.04889
[46]	train-mlogloss:2.02299	validation-mlogloss:2.04040
[47]	train-mlogloss:2.01428	validation-mlogloss:2.03207
[48]	train-mlogloss:2.00524	validation-mlogloss:2.02336
[49]	train-mlogloss:1.99636	validation-mlogloss:2.01471
[50]	train-mlogloss:1.98777	validation-mlogloss:2.00649
[51]	train-mlogloss:1.97917	validation-mlogloss:1.99812
[52]	train-mlogloss:1.97082	validation-mlogloss:1.98981
[53]	train-mlogloss:1.96265	validation-mlogloss:1.98218
[54]	train-mlogloss:1.95474	validation-mlogloss:1.97451
[55]	train-mlogloss:1.94698	validation-mlogloss:1.96723
[56]	train-mlogloss:1.93914	validation-mlogloss:1.95955
[57]	train-mlogloss:1.93155	validation-mlogloss:1.95232
[58]	train-mlogloss:1.92421	validation-mlogloss:1.94515
[59]	train-mlogloss:1.91682	validation-mlogloss:1.93790
[60]	train-mlogloss:1.90959	validation-mlogloss:1.93084
[61]	train-mlogloss:1.90245	validation-mlogloss:1.92412
[62]	train-mlogloss:1.89524	validation-mlogloss:1.91729
[63]	train-mlogloss:1.88846	validation-mlogloss:1.91092
[64]	train-mlogloss:1.88185	validation-mlogloss:1.90454
[65]	train-mlogloss:1.87502	validation-mlogloss:1.89789
[66]	train-mlogloss:1.86842	validation-mlogloss:1.89137
[67]	train-mlogloss:1.86192	validation-mlogloss:1.88522
[68]	train-mlogloss:1.85553	validation-mlogloss:1.87895
[69]	train-mlogloss:1.84917	validation-mlogloss:1.87279
[70]	train-mlogloss:1.84276	validation-mlogloss:1.86658
[71]	train-mlogloss:1.83661	validation-mlogloss:1.86073
[72]	train-mlogloss:1.83032	validation-mlogloss:1.85453
[73]	train-mlogloss:1.82426	validation-mlogloss:1.84869
[74]	train-mlogloss:1.81831	validation-mlogloss:1.84306
[75]	train-mlogloss:1.81249	validation-mlogloss:1.83719
[76]	train-mlogloss:1.80677	validation-mlogloss:1.83176
[77]	train-mlogloss:1.80100	validation-mlogloss:1.82612
[78]	train-mlogloss:1.79527	validation-mlogloss:1.82066
[79]	train-mlogloss:1.78974	validation-mlogloss:1.81548
[80]	train-mlogloss:1.78439	validation-mlogloss:1.81007
[81]	train-mlogloss:1.77896	validation-mlogloss:1.80474
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[684]	train-mlogloss:1.25308	validation-mlogloss:1.34038
[685]	train-mlogloss:1.25301	validation-mlogloss:1.34030
[686]	train-mlogloss:1.25301	validation-mlogloss:1.34030
[687]	train-mlogloss:1.25301	validation-mlogloss:1.34030
[688]	train-mlogloss:1.25299	validation-mlogloss:1.34029
[689]	train-mlogloss:1.25295	validation-mlogloss:1.34023
[690]	train-mlogloss:1.25293	validation-mlogloss:1.34021
[691]	train-mlogloss:1.25290	validation-mlogloss:1.34017
[692]	train-mlogloss:1.25283	validation-mlogloss:1.34014
[693]	train-mlogloss:1.25275	validation-mlogloss:1.34005
[694]	train-mlogloss:1.25273	validation-mlogloss:1.34004
[695]	train-mlogloss:1.25272	validation-mlogloss:1.34002
[696]	train-mlogloss:1.25266	validation-mlogloss:1.33998
[697]	train-mlogloss:1.25266	validation-mlogloss:1.33998
[698]	train-mlogloss:1.25265	validation-mlogloss:1.33997
[699]	train-mlogloss:1.25265	validation-mlogloss:1.33997
[700]	train-mlogloss:1.25264	validation-mlogloss:1.33998
[701]	train-mlogloss:1.25263	validation-mlogloss:1.33998
[702]	train-mlogloss:1.25263	validation-mlogloss:1.33999
[703]	train-mlogloss:1.25263	validation-mlogloss:1.33999
[704]	train-mlogloss:1.25260	validation-mlogloss:1.33998
[705]	train-mlogloss:1.25255	validation-mlogloss:1.33991
[706]	train-mlogloss:1.25252	validation-mlogloss:1.33989
[707]	train-mlogloss:1.25250	validation-mlogloss:1.33986
[708]	train-mlogloss:1.25249	validation-mlogloss:1.33985
[709]	train-mlogloss:1.25242	validation-mlogloss:1.33983
[710]	train-mlogloss:1.25242	validation-mlogloss:1.33983
[711]	train-mlogloss:1.25242	validation-mlogloss:1.33983
[712]	train-mlogloss:1.25240	validation-mlogloss:1.33982
[713]	train-mlogloss:1.25240	validation-mlogloss:1.33982
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.95 [%]
Global accuracy score (test) = 50.6 [%]
Global F1 score (train) = 63.03 [%]
Global F1 score (test) = 50.73 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.40      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.46      0.42      0.44       184
       CAMINAR USUAL SPEED       0.28      0.20      0.24       184
            CAMINAR ZIGZAG       0.58      0.54      0.56       184
          DE PIE BARRIENDO       0.55      0.50      0.52       184
   DE PIE DOBLANDO TOALLAS       0.43      0.46      0.45       184
    DE PIE MOVIENDO LIBROS       0.47      0.44      0.46       184
          DE PIE USANDO PC       0.63      0.67      0.65       184
        FASE REPOSO CON K5       0.54      0.79      0.64       184
INCREMENTAL CICLOERGOMETRO       0.88      0.62      0.73       184
           SENTADO LEYENDO       0.35      0.43      0.39       184
         SENTADO USANDO PC       0.41      0.27      0.32       184
      SENTADO VIENDO LA TV       0.46      0.38      0.42       184
   SUBIR Y BAJAR ESCALERAS       0.54      0.69      0.61       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.50      2737


Accuracy capturado en la ejecución 16: 50.6 [%]
F1-score capturado en la ejecución 16: 50.73 [%]

=== EJECUCIÓN 17 ===

--- TRAIN (ejecución 17) ---

--- TEST (ejecución 17) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.78 [%]
Global accuracy score (test) = 50.86 [%]
Global F1 score (train) = 62.84 [%]
Global F1 score (test) = 50.99 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.27      0.39      0.32       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.40      0.42       184
       CAMINAR USUAL SPEED       0.24      0.16      0.19       184
            CAMINAR ZIGZAG       0.60      0.56      0.58       184
          DE PIE BARRIENDO       0.56      0.51      0.53       184
   DE PIE DOBLANDO TOALLAS       0.46      0.50      0.48       184
    DE PIE MOVIENDO LIBROS       0.49      0.46      0.48       184
          DE PIE USANDO PC       0.63      0.67      0.65       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.87      0.63      0.73       184
           SENTADO LEYENDO       0.37      0.45      0.40       184
         SENTADO USANDO PC       0.44      0.29      0.35       184
      SENTADO VIENDO LA TV       0.47      0.39      0.43       184
   SUBIR Y BAJAR ESCALERAS       0.52      0.66      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.51      2737


Accuracy capturado en la ejecución 17: 50.86 [%]
F1-score capturado en la ejecución 17: 50.99 [%]

=== EJECUCIÓN 18 ===

--- TRAIN (ejecución 18) ---

--- TEST (ejecución 18) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[ 2  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.66 [%]
Global accuracy score (test) = 50.35 [%]
Global F1 score (train) = 62.71 [%]
Global F1 score (test) = 50.46 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.40      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.39      0.41       184
       CAMINAR USUAL SPEED       0.33      0.22      0.26       184
            CAMINAR ZIGZAG       0.57      0.55      0.56       184
          DE PIE BARRIENDO       0.54      0.49      0.52       184
   DE PIE DOBLANDO TOALLAS       0.43      0.46      0.44       184
    DE PIE MOVIENDO LIBROS       0.46      0.43      0.45       184
          DE PIE USANDO PC       0.61      0.67      0.64       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.90      0.61      0.73       184
           SENTADO LEYENDO       0.35      0.42      0.38       184
         SENTADO USANDO PC       0.42      0.26      0.32       184
      SENTADO VIENDO LA TV       0.46      0.39      0.42       184
   SUBIR Y BAJAR ESCALERAS       0.52      0.68      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.51      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 18: 50.35 [%]
F1-score capturado en la ejecución 18: 50.46 [%]

=== EJECUCIÓN 19 ===

--- TRAIN (ejecución 19) ---

--- TEST (ejecución 19) ---
2025-10-27 11:29:37.926715: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:29:37.939578: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761560977.953650  544955 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761560977.957944  544955 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761560977.969120  544955 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560977.969143  544955 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560977.969147  544955 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761560977.969149  544955 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:29:37.972562: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68604	validation-mlogloss:2.68603
[1]	train-mlogloss:2.66277	validation-mlogloss:2.66270
[2]	train-mlogloss:2.63924	validation-mlogloss:2.63985
[3]	train-mlogloss:2.61675	validation-mlogloss:2.61786
[4]	train-mlogloss:2.59494	validation-mlogloss:2.59634
[5]	train-mlogloss:2.57444	validation-mlogloss:2.57629
[6]	train-mlogloss:2.55433	validation-mlogloss:2.55667
[7]	train-mlogloss:2.53474	validation-mlogloss:2.53749
[8]	train-mlogloss:2.51667	validation-mlogloss:2.51962
[9]	train-mlogloss:2.49863	validation-mlogloss:2.50198
[10]	train-mlogloss:2.48080	validation-mlogloss:2.48439
[11]	train-mlogloss:2.46292	validation-mlogloss:2.46648
[12]	train-mlogloss:2.44545	validation-mlogloss:2.44898
[13]	train-mlogloss:2.42857	validation-mlogloss:2.43198
[14]	train-mlogloss:2.41203	validation-mlogloss:2.41607
[15]	train-mlogloss:2.39567	validation-mlogloss:2.40028
[16]	train-mlogloss:2.37934	validation-mlogloss:2.38442
[17]	train-mlogloss:2.36425	validation-mlogloss:2.36965
[18]	train-mlogloss:2.34928	validation-mlogloss:2.35531
[19]	train-mlogloss:2.33399	validation-mlogloss:2.34031
[20]	train-mlogloss:2.31898	validation-mlogloss:2.32594
[21]	train-mlogloss:2.30446	validation-mlogloss:2.31216
[22]	train-mlogloss:2.29009	validation-mlogloss:2.29789
[23]	train-mlogloss:2.27633	validation-mlogloss:2.28452
[24]	train-mlogloss:2.26289	validation-mlogloss:2.27181
[25]	train-mlogloss:2.24982	validation-mlogloss:2.25940
[26]	train-mlogloss:2.23717	validation-mlogloss:2.24726
[27]	train-mlogloss:2.22459	validation-mlogloss:2.23504
[28]	train-mlogloss:2.21205	validation-mlogloss:2.22292
[29]	train-mlogloss:2.19979	validation-mlogloss:2.21132
[30]	train-mlogloss:2.18800	validation-mlogloss:2.19917
[31]	train-mlogloss:2.17623	validation-mlogloss:2.18824
[32]	train-mlogloss:2.16463	validation-mlogloss:2.17706
[33]	train-mlogloss:2.15344	validation-mlogloss:2.16601
[34]	train-mlogloss:2.14215	validation-mlogloss:2.15495
[35]	train-mlogloss:2.13135	validation-mlogloss:2.14480
[36]	train-mlogloss:2.12064	validation-mlogloss:2.13457
[37]	train-mlogloss:2.11017	validation-mlogloss:2.12468
[38]	train-mlogloss:2.09973	validation-mlogloss:2.11443
[39]	train-mlogloss:2.08958	validation-mlogloss:2.10520
[40]	train-mlogloss:2.07949	validation-mlogloss:2.09512
[41]	train-mlogloss:2.06960	validation-mlogloss:2.08543
[42]	train-mlogloss:2.05977	validation-mlogloss:2.07586
[43]	train-mlogloss:2.05026	validation-mlogloss:2.06650
[44]	train-mlogloss:2.04114	validation-mlogloss:2.05763
[45]	train-mlogloss:2.03200	validation-mlogloss:2.04877
[46]	train-mlogloss:2.02279	validation-mlogloss:2.04001
[47]	train-mlogloss:2.01390	validation-mlogloss:2.03166
[48]	train-mlogloss:2.00534	validation-mlogloss:2.02300
[49]	train-mlogloss:1.99680	validation-mlogloss:2.01454
[50]	train-mlogloss:1.98825	validation-mlogloss:2.00676
[51]	train-mlogloss:1.97969	validation-mlogloss:1.99851
[52]	train-mlogloss:1.97129	validation-mlogloss:1.99036
[53]	train-mlogloss:1.96324	validation-mlogloss:1.98284
[54]	train-mlogloss:1.95531	validation-mlogloss:1.97491
[55]	train-mlogloss:1.94754	validation-mlogloss:1.96780
[56]	train-mlogloss:1.93984	validation-mlogloss:1.95994
[57]	train-mlogloss:1.93209	validation-mlogloss:1.95231
[58]	train-mlogloss:1.92446	validation-mlogloss:1.94479
[59]	train-mlogloss:1.91716	validation-mlogloss:1.93766
[60]	train-mlogloss:1.91001	validation-mlogloss:1.93054
[61]	train-mlogloss:1.90296	validation-mlogloss:1.92371
[62]	train-mlogloss:1.89576	validation-mlogloss:1.91701
[63]	train-mlogloss:1.88873	validation-mlogloss:1.91051
[64]	train-mlogloss:1.88181	validation-mlogloss:1.90371
[65]	train-mlogloss:1.87516	validation-mlogloss:1.89734
[66]	train-mlogloss:1.86859	validation-mlogloss:1.89107
[67]	train-mlogloss:1.86188	validation-mlogloss:1.88447
[68]	train-mlogloss:1.85541	validation-mlogloss:1.87838
[69]	train-mlogloss:1.84905	validation-mlogloss:1.87187
[70]	train-mlogloss:1.84269	validation-mlogloss:1.86565
[71]	train-mlogloss:1.83632	validation-mlogloss:1.85939
[72]	train-mlogloss:1.83024	validation-mlogloss:1.85368
[73]	train-mlogloss:1.82417	validation-mlogloss:1.84776
[74]	train-mlogloss:1.81802	validation-mlogloss:1.84175
[75]	train-mlogloss:1.81217	validation-mlogloss:1.83606
[76]	train-mlogloss:1.80627	validation-mlogloss:1.83058
[77]	train-mlogloss:1.80065	validation-mlogloss:1.82514
[78]	train-mlogloss:1.79499	validation-mlogloss:1.81968
[79]	train-mlogloss:1.78967	validation-mlogloss:1.81451
[80]	train-mlogloss:1.78448	validation-mlogloss:1.80948
[81]	train-mlogloss:1.77918	validation-mlogloss:1.80451
[82]	train-mlogloss:1.77401	validation-mlogloss:1.79942
[83]	train-mlogloss:1.76888	validation-mlogloss:1.79446
[84]	train-mlogloss:1.76369	validation-mlogloss:1.78947
[85]	train-mlogloss:1.75840	validation-mlogloss:1.78448
[86]	train-mlogloss:1.75342	validation-mlogloss:1.77978
[87]	train-mlogloss:1.74829	validation-mlogloss:1.77482
[88]	train-mlogloss:1.74319	validation-mlogloss:1.76968
[89]	train-mlogloss:1.73844	validation-mlogloss:1.76511
[90]	train-mlogloss:1.73354	validation-mlogloss:1.76017
[91]	train-mlogloss:1.72898	validation-mlogloss:1.75570
[92]	train-mlogloss:1.72414	validation-mlogloss:1.75120
[93]	train-mlogloss:1.71942	validation-mlogloss:1.74676
[94]	train-mlogloss:1.71459	validation-mlogloss:1.74218
[95]	train-mlogloss:1.70990	validation-mlogloss:1.73743
[96]	train-mlogloss:1.70546	validation-mlogloss:1.73312
[97]	train-mlogloss:1.70107	validation-mlogloss:1.72924
[98]	train-mlogloss:1.69664	validation-mlogloss:1.72507
[99]	train-mlogloss:1.69239	validation-mlogloss:1.72093
[100]	train-mlogloss:1.68820	validation-mlogloss:1.71663
[101]	train-mlogloss:1.68381	validation-mlogloss:1.71273
[102]	train-mlogloss:1.67969	validation-mlogloss:1.70864
[103]	train-mlogloss:1.67551	validation-mlogloss:1.70435
[104]	train-mlogloss:1.67128	validation-mlogloss:1.70049
[105]	train-mlogloss:1.66707	validation-mlogloss:1.69665
[106]	train-mlogloss:1.66323	validation-mlogloss:1.69316
[107]	train-mlogloss:1.65923	validation-mlogloss:1.68916
[108]	train-mlogloss:1.65505	validation-mlogloss:1.68557
[109]	train-mlogloss:1.65126	validation-mlogloss:1.68220
[110]	train-mlogloss:1.64735	validation-mlogloss:1.67855
[111]	train-mlogloss:1.64363	validation-mlogloss:1.67507
[112]	train-mlogloss:1.63984	validation-mlogloss:1.67153
[113]	train-mlogloss:1.63632	validation-mlogloss:1.66823
[114]	train-mlogloss:1.63279	validation-mlogloss:1.66481
[115]	train-mlogloss:1.62921	validation-mlogloss:1.66130
[116]	train-mlogloss:1.62578	validation-mlogloss:1.65802
[117]	train-mlogloss:1.62226	validation-mlogloss:1.65480
[118]	train-mlogloss:1.61884	validation-mlogloss:1.65153
[119]	train-mlogloss:1.61546	validation-mlogloss:1.64851
[120]	train-mlogloss:1.61210	validation-mlogloss:1.64546
[121]	train-mlogloss:1.60882	validation-mlogloss:1.64223
[122]	train-mlogloss:1.60547	validation-mlogloss:1.63918
[123]	train-mlogloss:1.60204	validation-mlogloss:1.63594
[124]	train-mlogloss:1.59875	validation-mlogloss:1.63283
[125]	train-mlogloss:1.59550	validation-mlogloss:1.62985
[126]	train-mlogloss:1.59230	validation-mlogloss:1.62672
[127]	train-mlogloss:1.58905	validation-mlogloss:1.62372
[128]	train-mlogloss:1.58593	validation-mlogloss:1.62085
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[708]	train-mlogloss:1.25161	validation-mlogloss:1.33980
[709]	train-mlogloss:1.25157	validation-mlogloss:1.33977
[710]	train-mlogloss:1.25154	validation-mlogloss:1.33978
[711]	train-mlogloss:1.25150	validation-mlogloss:1.33973
[712]	train-mlogloss:1.25146	validation-mlogloss:1.33972
[713]	train-mlogloss:1.25142	validation-mlogloss:1.33970
Saved model to disk.
2025-10-27 11:30:25.974133: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:30:25.986726: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761561026.000648  545944 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761561026.005101  545944 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761561026.016270  545944 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561026.016295  545944 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561026.016298  545944 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561026.016302  545944 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:30:26.019781: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68366	validation-mlogloss:2.68408
[1]	train-mlogloss:2.66125	validation-mlogloss:2.66179
[2]	train-mlogloss:2.63887	validation-mlogloss:2.64002
[3]	train-mlogloss:2.61635	validation-mlogloss:2.61786
[4]	train-mlogloss:2.59456	validation-mlogloss:2.59682
[5]	train-mlogloss:2.57423	validation-mlogloss:2.57683
[6]	train-mlogloss:2.55367	validation-mlogloss:2.55698
[7]	train-mlogloss:2.53434	validation-mlogloss:2.53812
[8]	train-mlogloss:2.51496	validation-mlogloss:2.51919
[9]	train-mlogloss:2.49609	validation-mlogloss:2.50047
[10]	train-mlogloss:2.47880	validation-mlogloss:2.48330
[11]	train-mlogloss:2.46106	validation-mlogloss:2.46594
[12]	train-mlogloss:2.44397	validation-mlogloss:2.44905
[13]	train-mlogloss:2.42712	validation-mlogloss:2.43275
[14]	train-mlogloss:2.41007	validation-mlogloss:2.41612
[15]	train-mlogloss:2.39352	validation-mlogloss:2.40013
[16]	train-mlogloss:2.37784	validation-mlogloss:2.38489
[17]	train-mlogloss:2.36253	validation-mlogloss:2.37031
[18]	train-mlogloss:2.34724	validation-mlogloss:2.35506
[19]	train-mlogloss:2.33239	validation-mlogloss:2.34069
[20]	train-mlogloss:2.31774	validation-mlogloss:2.32668
[21]	train-mlogloss:2.30350	validation-mlogloss:2.31256
[22]	train-mlogloss:2.28973	validation-mlogloss:2.29935
[23]	train-mlogloss:2.27625	validation-mlogloss:2.28610
[24]	train-mlogloss:2.26275	validation-mlogloss:2.27333
[25]	train-mlogloss:2.24956	validation-mlogloss:2.26031
[26]	train-mlogloss:2.23681	validation-mlogloss:2.24805
[27]	train-mlogloss:2.22451	validation-mlogloss:2.23668
[28]	train-mlogloss:2.21212	validation-mlogloss:2.22488
[29]	train-mlogloss:2.20030	validation-mlogloss:2.21367
[30]	train-mlogloss:2.18833	validation-mlogloss:2.20158
[31]	train-mlogloss:2.17615	validation-mlogloss:2.18968
[32]	train-mlogloss:2.16447	validation-mlogloss:2.17864
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[34]	train-mlogloss:2.14223	validation-mlogloss:2.15751
[35]	train-mlogloss:2.13130	validation-mlogloss:2.14719
[36]	train-mlogloss:2.12022	validation-mlogloss:2.13624
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[49]	train-mlogloss:1.99679	validation-mlogloss:2.01655
[50]	train-mlogloss:1.98823	validation-mlogloss:2.00795
[51]	train-mlogloss:1.98019	validation-mlogloss:1.99989
[52]	train-mlogloss:1.97204	validation-mlogloss:1.99269
[53]	train-mlogloss:1.96381	validation-mlogloss:1.98485
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[55]	train-mlogloss:1.94819	validation-mlogloss:1.96941
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[105]	train-mlogloss:1.66847	validation-mlogloss:1.69862
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[109]	train-mlogloss:1.65287	validation-mlogloss:1.68375
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[111]	train-mlogloss:1.64540	validation-mlogloss:1.67644
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[114]	train-mlogloss:1.63460	validation-mlogloss:1.66615
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[130]	train-mlogloss:1.58079	validation-mlogloss:1.61629
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[594]	train-mlogloss:1.25683	validation-mlogloss:1.34483
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[680]	train-mlogloss:1.25288	validation-mlogloss:1.34205
[681]	train-mlogloss:1.25287	validation-mlogloss:1.34203
[682]	train-mlogloss:1.25287	validation-mlogloss:1.34204
[683]	train-mlogloss:1.25285	validation-mlogloss:1.34204
[684]	train-mlogloss:1.25283	validation-mlogloss:1.34202
[685]	train-mlogloss:1.25281	validation-mlogloss:1.34199
[686]	train-mlogloss:1.25276	validation-mlogloss:1.34195
[687]	train-mlogloss:1.25276	validation-mlogloss:1.34195
[688]	train-mlogloss:1.25276	validation-mlogloss:1.34195
[689]	train-mlogloss:1.25274	validation-mlogloss:1.34195
[690]	train-mlogloss:1.25270	validation-mlogloss:1.34191
[691]	train-mlogloss:1.25269	validation-mlogloss:1.34192
[692]	train-mlogloss:1.25267	validation-mlogloss:1.34193
[693]	train-mlogloss:1.25264	validation-mlogloss:1.34192
[694]	train-mlogloss:1.25264	validation-mlogloss:1.34191
[695]	train-mlogloss:1.25256	validation-mlogloss:1.34184
[696]	train-mlogloss:1.25245	validation-mlogloss:1.34174
[697]	train-mlogloss:1.25245	validation-mlogloss:1.34174
[698]	train-mlogloss:1.25245	validation-mlogloss:1.34173
[699]	train-mlogloss:1.25245	validation-mlogloss:1.34174
[700]	train-mlogloss:1.25242	validation-mlogloss:1.34173
[701]	train-mlogloss:1.25233	validation-mlogloss:1.34173
[702]	train-mlogloss:1.25233	validation-mlogloss:1.34173
[703]	train-mlogloss:1.25233	validation-mlogloss:1.34173
[704]	train-mlogloss:1.25227	validation-mlogloss:1.34170
[705]	train-mlogloss:1.25224	validation-mlogloss:1.34169
[706]	train-mlogloss:1.25216	validation-mlogloss:1.34171
[707]	train-mlogloss:1.25212	validation-mlogloss:1.34167
[708]	train-mlogloss:1.25212	validation-mlogloss:1.34167
[709]	train-mlogloss:1.25211	validation-mlogloss:1.34166
[710]	train-mlogloss:1.25204	validation-mlogloss:1.34164
[711]	train-mlogloss:1.25196	validation-mlogloss:1.34161
[712]	train-mlogloss:1.25192	validation-mlogloss:1.34161
[713]	train-mlogloss:1.25190	validation-mlogloss:1.34161
Saved model to disk.
2025-10-27 11:31:13.359810: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:31:13.372529: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761561073.386226  546871 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761561073.390581  546871 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761561073.401627  546871 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561073.401652  546871 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561073.401655  546871 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561073.401657  546871 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:31:13.405064: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
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[1]	train-mlogloss:2.66147	validation-mlogloss:2.66185
[2]	train-mlogloss:2.63965	validation-mlogloss:2.64088
[3]	train-mlogloss:2.61756	validation-mlogloss:2.61932
[4]	train-mlogloss:2.59687	validation-mlogloss:2.59923
[5]	train-mlogloss:2.57624	validation-mlogloss:2.57924
[6]	train-mlogloss:2.55525	validation-mlogloss:2.55889
[7]	train-mlogloss:2.53609	validation-mlogloss:2.54019
[8]	train-mlogloss:2.51697	validation-mlogloss:2.52081
[9]	train-mlogloss:2.49810	validation-mlogloss:2.50199
[10]	train-mlogloss:2.48057	validation-mlogloss:2.48481
[11]	train-mlogloss:2.46191	validation-mlogloss:2.46697
[12]	train-mlogloss:2.44415	validation-mlogloss:2.44959
[13]	train-mlogloss:2.42775	validation-mlogloss:2.43381
[14]	train-mlogloss:2.41098	validation-mlogloss:2.41749
[15]	train-mlogloss:2.39441	validation-mlogloss:2.40172
[16]	train-mlogloss:2.37912	validation-mlogloss:2.38736
[17]	train-mlogloss:2.36449	validation-mlogloss:2.37358
[18]	train-mlogloss:2.34912	validation-mlogloss:2.35791
[19]	train-mlogloss:2.33393	validation-mlogloss:2.34309
[20]	train-mlogloss:2.31955	validation-mlogloss:2.32920
[21]	train-mlogloss:2.30484	validation-mlogloss:2.31495
[22]	train-mlogloss:2.29049	validation-mlogloss:2.30202
[23]	train-mlogloss:2.27681	validation-mlogloss:2.28824
[24]	train-mlogloss:2.26309	validation-mlogloss:2.27524
[25]	train-mlogloss:2.24984	validation-mlogloss:2.26199
[26]	train-mlogloss:2.23654	validation-mlogloss:2.24885
[27]	train-mlogloss:2.22385	validation-mlogloss:2.23661
[28]	train-mlogloss:2.21138	validation-mlogloss:2.22427
[29]	train-mlogloss:2.19950	validation-mlogloss:2.21230
[30]	train-mlogloss:2.18749	validation-mlogloss:2.20132
[31]	train-mlogloss:2.17559	validation-mlogloss:2.18955
[32]	train-mlogloss:2.16393	validation-mlogloss:2.17817
[33]	train-mlogloss:2.15260	validation-mlogloss:2.16699
[34]	train-mlogloss:2.14140	validation-mlogloss:2.15614
[35]	train-mlogloss:2.13076	validation-mlogloss:2.14589
[36]	train-mlogloss:2.11993	validation-mlogloss:2.13566
[37]	train-mlogloss:2.10969	validation-mlogloss:2.12627
[38]	train-mlogloss:2.09962	validation-mlogloss:2.11635
[39]	train-mlogloss:2.08926	validation-mlogloss:2.10619
[40]	train-mlogloss:2.07914	validation-mlogloss:2.09633
[41]	train-mlogloss:2.06944	validation-mlogloss:2.08640
[42]	train-mlogloss:2.05948	validation-mlogloss:2.07679
[43]	train-mlogloss:2.04976	validation-mlogloss:2.06714
[44]	train-mlogloss:2.04056	validation-mlogloss:2.05799
[45]	train-mlogloss:2.03141	validation-mlogloss:2.04926
[46]	train-mlogloss:2.02241	validation-mlogloss:2.04090
[47]	train-mlogloss:2.01342	validation-mlogloss:2.03248
[48]	train-mlogloss:2.00458	validation-mlogloss:2.02408
[49]	train-mlogloss:1.99598	validation-mlogloss:2.01598
[50]	train-mlogloss:1.98752	validation-mlogloss:2.00793
[51]	train-mlogloss:1.97911	validation-mlogloss:1.99952
[52]	train-mlogloss:1.97082	validation-mlogloss:1.99145
[53]	train-mlogloss:1.96290	validation-mlogloss:1.98394
[54]	train-mlogloss:1.95523	validation-mlogloss:1.97725
[55]	train-mlogloss:1.94729	validation-mlogloss:1.96963
[56]	train-mlogloss:1.93964	validation-mlogloss:1.96230
[57]	train-mlogloss:1.93188	validation-mlogloss:1.95460
[58]	train-mlogloss:1.92451	validation-mlogloss:1.94729
[59]	train-mlogloss:1.91713	validation-mlogloss:1.94000
[60]	train-mlogloss:1.90990	validation-mlogloss:1.93275
[61]	train-mlogloss:1.90278	validation-mlogloss:1.92585
[62]	train-mlogloss:1.89588	validation-mlogloss:1.91943
[63]	train-mlogloss:1.88912	validation-mlogloss:1.91248
[64]	train-mlogloss:1.88201	validation-mlogloss:1.90548
[65]	train-mlogloss:1.87514	validation-mlogloss:1.89908
[66]	train-mlogloss:1.86856	validation-mlogloss:1.89297
[67]	train-mlogloss:1.86182	validation-mlogloss:1.88651
[68]	train-mlogloss:1.85506	validation-mlogloss:1.88006
[69]	train-mlogloss:1.84860	validation-mlogloss:1.87372
[70]	train-mlogloss:1.84234	validation-mlogloss:1.86760
[71]	train-mlogloss:1.83624	validation-mlogloss:1.86159
[72]	train-mlogloss:1.83013	validation-mlogloss:1.85577
[73]	train-mlogloss:1.82424	validation-mlogloss:1.85015
[74]	train-mlogloss:1.81833	validation-mlogloss:1.84423
[75]	train-mlogloss:1.81232	validation-mlogloss:1.83838
[76]	train-mlogloss:1.80645	validation-mlogloss:1.83268
[77]	train-mlogloss:1.80061	validation-mlogloss:1.82711
[78]	train-mlogloss:1.79488	validation-mlogloss:1.82171
[79]	train-mlogloss:1.78945	validation-mlogloss:1.81640
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[81]	train-mlogloss:1.77840	validation-mlogloss:1.80564
[82]	train-mlogloss:1.77316	validation-mlogloss:1.80060
[83]	train-mlogloss:1.76799	validation-mlogloss:1.79564
[84]	train-mlogloss:1.76271	validation-mlogloss:1.79023
[85]	train-mlogloss:1.75769	validation-mlogloss:1.78533
[86]	train-mlogloss:1.75270	validation-mlogloss:1.78086
[87]	train-mlogloss:1.74764	validation-mlogloss:1.77613
[88]	train-mlogloss:1.74278	validation-mlogloss:1.77133
[89]	train-mlogloss:1.73790	validation-mlogloss:1.76676
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[91]	train-mlogloss:1.72825	validation-mlogloss:1.75717
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[94]	train-mlogloss:1.71410	validation-mlogloss:1.74353
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[96]	train-mlogloss:1.70519	validation-mlogloss:1.73488
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[99]	train-mlogloss:1.69228	validation-mlogloss:1.72205
[100]	train-mlogloss:1.68807	validation-mlogloss:1.71802
[101]	train-mlogloss:1.68387	validation-mlogloss:1.71398
[102]	train-mlogloss:1.67968	validation-mlogloss:1.71008
[103]	train-mlogloss:1.67537	validation-mlogloss:1.70593
[104]	train-mlogloss:1.67130	validation-mlogloss:1.70231
[105]	train-mlogloss:1.66718	validation-mlogloss:1.69846
[106]	train-mlogloss:1.66305	validation-mlogloss:1.69443
[107]	train-mlogloss:1.65903	validation-mlogloss:1.69061
[108]	train-mlogloss:1.65519	validation-mlogloss:1.68666
[109]	train-mlogloss:1.65139	validation-mlogloss:1.68307
[110]	train-mlogloss:1.64743	validation-mlogloss:1.67939
[111]	train-mlogloss:1.64372	validation-mlogloss:1.67591
[112]	train-mlogloss:1.63993	validation-mlogloss:1.67246
[113]	train-mlogloss:1.63634	validation-mlogloss:1.66898
[114]	train-mlogloss:1.63256	validation-mlogloss:1.66541
[115]	train-mlogloss:1.62905	validation-mlogloss:1.66199
[116]	train-mlogloss:1.62559	validation-mlogloss:1.65895
[117]	train-mlogloss:1.62209	validation-mlogloss:1.65540
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[121]	train-mlogloss:1.60838	validation-mlogloss:1.64231
[122]	train-mlogloss:1.60513	validation-mlogloss:1.63950
[123]	train-mlogloss:1.60177	validation-mlogloss:1.63625
[124]	train-mlogloss:1.59857	validation-mlogloss:1.63312
[125]	train-mlogloss:1.59534	validation-mlogloss:1.62981
[126]	train-mlogloss:1.59207	validation-mlogloss:1.62694
[127]	train-mlogloss:1.58890	validation-mlogloss:1.62393
[128]	train-mlogloss:1.58565	validation-mlogloss:1.62080
[129]	train-mlogloss:1.58246	validation-mlogloss:1.61771
[130]	train-mlogloss:1.57938	validation-mlogloss:1.61500
[131]	train-mlogloss:1.57632	validation-mlogloss:1.61205
[132]	train-mlogloss:1.57330	validation-mlogloss:1.60932
[133]	train-mlogloss:1.57044	validation-mlogloss:1.60679
[134]	train-mlogloss:1.56754	validation-mlogloss:1.60419
[135]	train-mlogloss:1.56453	validation-mlogloss:1.60146
[136]	train-mlogloss:1.56156	validation-mlogloss:1.59872
[137]	train-mlogloss:1.55866	validation-mlogloss:1.59576
[138]	train-mlogloss:1.55578	validation-mlogloss:1.59310
[139]	train-mlogloss:1.55312	validation-mlogloss:1.59062
[140]	train-mlogloss:1.55023	validation-mlogloss:1.58807
[141]	train-mlogloss:1.54749	validation-mlogloss:1.58555
[142]	train-mlogloss:1.54477	validation-mlogloss:1.58307
[143]	train-mlogloss:1.54226	validation-mlogloss:1.58061
[144]	train-mlogloss:1.53956	validation-mlogloss:1.57816
[145]	train-mlogloss:1.53694	validation-mlogloss:1.57596
[146]	train-mlogloss:1.53436	validation-mlogloss:1.57336
[147]	train-mlogloss:1.53172	validation-mlogloss:1.57104
[148]	train-mlogloss:1.52912	validation-mlogloss:1.56864
[149]	train-mlogloss:1.52663	validation-mlogloss:1.56642
[150]	train-mlogloss:1.52404	validation-mlogloss:1.56428
[151]	train-mlogloss:1.52147	validation-mlogloss:1.56213
[152]	train-mlogloss:1.51900	validation-mlogloss:1.55981
[153]	train-mlogloss:1.51662	validation-mlogloss:1.55765
[154]	train-mlogloss:1.51434	validation-mlogloss:1.55543
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[458]	train-mlogloss:1.26825	validation-mlogloss:1.34998
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[472]	train-mlogloss:1.26684	validation-mlogloss:1.34911
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[474]	train-mlogloss:1.26669	validation-mlogloss:1.34892
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[477]	train-mlogloss:1.26640	validation-mlogloss:1.34871
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[536]	train-mlogloss:1.26124	validation-mlogloss:1.34528
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[553]	train-mlogloss:1.26017	validation-mlogloss:1.34450
[554]	train-mlogloss:1.26007	validation-mlogloss:1.34446
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[556]	train-mlogloss:1.25994	validation-mlogloss:1.34441
[557]	train-mlogloss:1.25994	validation-mlogloss:1.34441
[558]	train-mlogloss:1.25994	validation-mlogloss:1.34441
[559]	train-mlogloss:1.25991	validation-mlogloss:1.34439
[560]	train-mlogloss:1.25983	validation-mlogloss:1.34436
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[562]	train-mlogloss:1.25975	validation-mlogloss:1.34434
[563]	train-mlogloss:1.25968	validation-mlogloss:1.34432
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[565]	train-mlogloss:1.25959	validation-mlogloss:1.34427
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[659]	train-mlogloss:1.25472	validation-mlogloss:1.34115
[660]	train-mlogloss:1.25472	validation-mlogloss:1.34116
[661]	train-mlogloss:1.25464	validation-mlogloss:1.34111
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[663]	train-mlogloss:1.25461	validation-mlogloss:1.34109
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[676]	train-mlogloss:1.25400	validation-mlogloss:1.34060
[677]	train-mlogloss:1.25385	validation-mlogloss:1.34053
[678]	train-mlogloss:1.25379	validation-mlogloss:1.34047
[679]	train-mlogloss:1.25376	validation-mlogloss:1.34044
[680]	train-mlogloss:1.25365	validation-mlogloss:1.34043
[681]	train-mlogloss:1.25360	validation-mlogloss:1.34041
[682]	train-mlogloss:1.25359	validation-mlogloss:1.34039
[683]	train-mlogloss:1.25356	validation-mlogloss:1.34037
[684]	train-mlogloss:1.25352	validation-mlogloss:1.34032
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[689]	train-mlogloss:1.25336	validation-mlogloss:1.34021
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[691]	train-mlogloss:1.25322	validation-mlogloss:1.34008
[692]	train-mlogloss:1.25316	validation-mlogloss:1.34007
[693]	train-mlogloss:1.25310	validation-mlogloss:1.33999
[694]	train-mlogloss:1.25308	validation-mlogloss:1.33999
[695]	train-mlogloss:1.25302	validation-mlogloss:1.33998
[696]	train-mlogloss:1.25302	validation-mlogloss:1.33998
[697]	train-mlogloss:1.25301	validation-mlogloss:1.33997
[698]	train-mlogloss:1.25292	validation-mlogloss:1.33991
[699]	train-mlogloss:1.25280	validation-mlogloss:1.33985
[700]	train-mlogloss:1.25277	validation-mlogloss:1.33987
[701]	train-mlogloss:1.25275	validation-mlogloss:1.33984
[702]	train-mlogloss:1.25270	validation-mlogloss:1.33981
[703]	train-mlogloss:1.25266	validation-mlogloss:1.33982
[704]	train-mlogloss:1.25265	validation-mlogloss:1.33981
[705]	train-mlogloss:1.25260	validation-mlogloss:1.33979
[706]	train-mlogloss:1.25255	validation-mlogloss:1.33979
[707]	train-mlogloss:1.25252	validation-mlogloss:1.33974
[708]	train-mlogloss:1.25243	validation-mlogloss:1.33968
[709]	train-mlogloss:1.25242	validation-mlogloss:1.33967
[710]	train-mlogloss:1.25239	validation-mlogloss:1.33962
[711]	train-mlogloss:1.25239	validation-mlogloss:1.33962
[712]	train-mlogloss:1.25232	validation-mlogloss:1.33957
[713]	train-mlogloss:1.25230	validation-mlogloss:1.33956
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.83 [%]
Global accuracy score (test) = 50.31 [%]
Global F1 score (train) = 62.89 [%]
Global F1 score (test) = 50.47 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.39      0.32       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.40      0.42       184
       CAMINAR USUAL SPEED       0.27      0.20      0.23       184
            CAMINAR ZIGZAG       0.61      0.56      0.58       184
          DE PIE BARRIENDO       0.54      0.50      0.52       184
   DE PIE DOBLANDO TOALLAS       0.43      0.47      0.45       184
    DE PIE MOVIENDO LIBROS       0.49      0.46      0.47       184
          DE PIE USANDO PC       0.62      0.66      0.64       184
        FASE REPOSO CON K5       0.55      0.79      0.64       184
INCREMENTAL CICLOERGOMETRO       0.88      0.62      0.73       184
           SENTADO LEYENDO       0.34      0.42      0.38       184
         SENTADO USANDO PC       0.40      0.26      0.32       184
      SENTADO VIENDO LA TV       0.45      0.37      0.40       184
   SUBIR Y BAJAR ESCALERAS       0.52      0.67      0.58       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.51      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 19: 50.31 [%]
F1-score capturado en la ejecución 19: 50.47 [%]

=== EJECUCIÓN 20 ===

--- TRAIN (ejecución 20) ---

--- TEST (ejecución 20) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.89 [%]
Global accuracy score (test) = 50.42 [%]
Global F1 score (train) = 62.95 [%]
Global F1 score (test) = 50.58 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.27      0.38      0.32       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.39      0.41       184
       CAMINAR USUAL SPEED       0.25      0.18      0.21       184
            CAMINAR ZIGZAG       0.57      0.53      0.55       184
          DE PIE BARRIENDO       0.54      0.49      0.51       184
   DE PIE DOBLANDO TOALLAS       0.45      0.47      0.46       184
    DE PIE MOVIENDO LIBROS       0.48      0.48      0.48       184
          DE PIE USANDO PC       0.60      0.66      0.63       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.90      0.61      0.73       184
           SENTADO LEYENDO       0.36      0.42      0.39       184
         SENTADO USANDO PC       0.42      0.27      0.33       184
      SENTADO VIENDO LA TV       0.47      0.42      0.44       184
   SUBIR Y BAJAR ESCALERAS       0.54      0.68      0.60       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 20: 50.42 [%]
F1-score capturado en la ejecución 20: 50.58 [%]

=== EJECUCIÓN 21 ===

--- TRAIN (ejecución 21) ---

--- TEST (ejecución 21) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.91 [%]
Global accuracy score (test) = 50.16 [%]
Global F1 score (train) = 62.96 [%]
Global F1 score (test) = 50.36 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.29      0.39      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.42      0.39      0.40       184
       CAMINAR USUAL SPEED       0.28      0.22      0.25       184
            CAMINAR ZIGZAG       0.60      0.56      0.58       184
          DE PIE BARRIENDO       0.56      0.49      0.52       184
   DE PIE DOBLANDO TOALLAS       0.43      0.47      0.45       184
    DE PIE MOVIENDO LIBROS       0.47      0.42      0.45       184
          DE PIE USANDO PC       0.64      0.66      0.65       184
        FASE REPOSO CON K5       0.54      0.79      0.64       184
INCREMENTAL CICLOERGOMETRO       0.88      0.62      0.73       184
           SENTADO LEYENDO       0.34      0.41      0.37       184
         SENTADO USANDO PC       0.40      0.27      0.32       184
      SENTADO VIENDO LA TV       0.45      0.38      0.41       184
   SUBIR Y BAJAR ESCALERAS       0.52      0.68      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.50      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 21: 50.16 [%]
F1-score capturado en la ejecución 21: 50.36 [%]

=== EJECUCIÓN 22 ===

--- TRAIN (ejecución 22) ---

--- TEST (ejecución 22) ---
2025-10-27 11:32:00.913990: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:32:00.927193: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761561120.941652  547804 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761561120.946019  547804 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761561120.957594  547804 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561120.957618  547804 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561120.957621  547804 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561120.957623  547804 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:32:00.960831: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68374	validation-mlogloss:2.68409
[1]	train-mlogloss:2.65989	validation-mlogloss:2.66032
[2]	train-mlogloss:2.63785	validation-mlogloss:2.63894
[3]	train-mlogloss:2.61473	validation-mlogloss:2.61636
[4]	train-mlogloss:2.59377	validation-mlogloss:2.59535
[5]	train-mlogloss:2.57291	validation-mlogloss:2.57473
[6]	train-mlogloss:2.55281	validation-mlogloss:2.55507
[7]	train-mlogloss:2.53408	validation-mlogloss:2.53699
[8]	train-mlogloss:2.51470	validation-mlogloss:2.51811
[9]	train-mlogloss:2.49585	validation-mlogloss:2.49978
[10]	train-mlogloss:2.47774	validation-mlogloss:2.48195
[11]	train-mlogloss:2.46033	validation-mlogloss:2.46500
[12]	train-mlogloss:2.44310	validation-mlogloss:2.44832
[13]	train-mlogloss:2.42585	validation-mlogloss:2.43191
[14]	train-mlogloss:2.40964	validation-mlogloss:2.41577
[15]	train-mlogloss:2.39330	validation-mlogloss:2.40050
[16]	train-mlogloss:2.37728	validation-mlogloss:2.38477
[17]	train-mlogloss:2.36250	validation-mlogloss:2.37045
[18]	train-mlogloss:2.34799	validation-mlogloss:2.35727
[19]	train-mlogloss:2.33322	validation-mlogloss:2.34256
[20]	train-mlogloss:2.31875	validation-mlogloss:2.32855
[21]	train-mlogloss:2.30451	validation-mlogloss:2.31487
[22]	train-mlogloss:2.29047	validation-mlogloss:2.30141
[23]	train-mlogloss:2.27659	validation-mlogloss:2.28809
[24]	train-mlogloss:2.26291	validation-mlogloss:2.27443
[25]	train-mlogloss:2.24964	validation-mlogloss:2.26178
[26]	train-mlogloss:2.23679	validation-mlogloss:2.24915
[27]	train-mlogloss:2.22411	validation-mlogloss:2.23677
[28]	train-mlogloss:2.21156	validation-mlogloss:2.22480
[29]	train-mlogloss:2.19911	validation-mlogloss:2.21269
[30]	train-mlogloss:2.18714	validation-mlogloss:2.20124
[31]	train-mlogloss:2.17541	validation-mlogloss:2.18960
[32]	train-mlogloss:2.16417	validation-mlogloss:2.17847
[33]	train-mlogloss:2.15268	validation-mlogloss:2.16740
[34]	train-mlogloss:2.14145	validation-mlogloss:2.15706
[35]	train-mlogloss:2.13056	validation-mlogloss:2.14654
[36]	train-mlogloss:2.11969	validation-mlogloss:2.13597
[37]	train-mlogloss:2.10937	validation-mlogloss:2.12556
[38]	train-mlogloss:2.09914	validation-mlogloss:2.11539
[39]	train-mlogloss:2.08887	validation-mlogloss:2.10538
[40]	train-mlogloss:2.07918	validation-mlogloss:2.09582
[41]	train-mlogloss:2.06932	validation-mlogloss:2.08635
[42]	train-mlogloss:2.05989	validation-mlogloss:2.07710
[43]	train-mlogloss:2.05013	validation-mlogloss:2.06794
[44]	train-mlogloss:2.04090	validation-mlogloss:2.05918
[45]	train-mlogloss:2.03156	validation-mlogloss:2.05008
[46]	train-mlogloss:2.02238	validation-mlogloss:2.04125
[47]	train-mlogloss:2.01380	validation-mlogloss:2.03249
[48]	train-mlogloss:2.00518	validation-mlogloss:2.02384
[49]	train-mlogloss:1.99651	validation-mlogloss:2.01520
[50]	train-mlogloss:1.98823	validation-mlogloss:2.00717
[51]	train-mlogloss:1.97998	validation-mlogloss:1.99927
[52]	train-mlogloss:1.97162	validation-mlogloss:1.99141
[53]	train-mlogloss:1.96356	validation-mlogloss:1.98352
[54]	train-mlogloss:1.95592	validation-mlogloss:1.97611
[55]	train-mlogloss:1.94792	validation-mlogloss:1.96829
[56]	train-mlogloss:1.94024	validation-mlogloss:1.96121
[57]	train-mlogloss:1.93270	validation-mlogloss:1.95386
[58]	train-mlogloss:1.92517	validation-mlogloss:1.94661
[59]	train-mlogloss:1.91802	validation-mlogloss:1.93970
[60]	train-mlogloss:1.91076	validation-mlogloss:1.93265
[61]	train-mlogloss:1.90354	validation-mlogloss:1.92599
[62]	train-mlogloss:1.89629	validation-mlogloss:1.91901
[63]	train-mlogloss:1.88918	validation-mlogloss:1.91212
[64]	train-mlogloss:1.88256	validation-mlogloss:1.90568
[65]	train-mlogloss:1.87586	validation-mlogloss:1.89957
[66]	train-mlogloss:1.86917	validation-mlogloss:1.89309
[67]	train-mlogloss:1.86246	validation-mlogloss:1.88640
[68]	train-mlogloss:1.85578	validation-mlogloss:1.87978
[69]	train-mlogloss:1.84960	validation-mlogloss:1.87408
[70]	train-mlogloss:1.84328	validation-mlogloss:1.86799
[71]	train-mlogloss:1.83706	validation-mlogloss:1.86202
[72]	train-mlogloss:1.83089	validation-mlogloss:1.85610
[73]	train-mlogloss:1.82472	validation-mlogloss:1.84991
[74]	train-mlogloss:1.81901	validation-mlogloss:1.84472
[75]	train-mlogloss:1.81304	validation-mlogloss:1.83880
[76]	train-mlogloss:1.80715	validation-mlogloss:1.83315
[77]	train-mlogloss:1.80168	validation-mlogloss:1.82764
[78]	train-mlogloss:1.79607	validation-mlogloss:1.82242
[79]	train-mlogloss:1.79036	validation-mlogloss:1.81695
[80]	train-mlogloss:1.78496	validation-mlogloss:1.81161
[81]	train-mlogloss:1.77939	validation-mlogloss:1.80652
[82]	train-mlogloss:1.77398	validation-mlogloss:1.80127
[83]	train-mlogloss:1.76858	validation-mlogloss:1.79617
[84]	train-mlogloss:1.76351	validation-mlogloss:1.79129
[85]	train-mlogloss:1.75851	validation-mlogloss:1.78650
[86]	train-mlogloss:1.75354	validation-mlogloss:1.78182
[87]	train-mlogloss:1.74869	validation-mlogloss:1.77697
[88]	train-mlogloss:1.74372	validation-mlogloss:1.77213
[89]	train-mlogloss:1.73897	validation-mlogloss:1.76730
[90]	train-mlogloss:1.73424	validation-mlogloss:1.76301
[91]	train-mlogloss:1.72923	validation-mlogloss:1.75823
[92]	train-mlogloss:1.72461	validation-mlogloss:1.75353
[93]	train-mlogloss:1.71981	validation-mlogloss:1.74904
[94]	train-mlogloss:1.71510	validation-mlogloss:1.74438
[95]	train-mlogloss:1.71045	validation-mlogloss:1.73992
[96]	train-mlogloss:1.70593	validation-mlogloss:1.73559
[97]	train-mlogloss:1.70149	validation-mlogloss:1.73114
[98]	train-mlogloss:1.69698	validation-mlogloss:1.72695
[99]	train-mlogloss:1.69270	validation-mlogloss:1.72289
[100]	train-mlogloss:1.68835	validation-mlogloss:1.71882
[101]	train-mlogloss:1.68406	validation-mlogloss:1.71486
[102]	train-mlogloss:1.67985	validation-mlogloss:1.71101
[103]	train-mlogloss:1.67573	validation-mlogloss:1.70704
[104]	train-mlogloss:1.67164	validation-mlogloss:1.70332
[105]	train-mlogloss:1.66769	validation-mlogloss:1.69959
[106]	train-mlogloss:1.66371	validation-mlogloss:1.69599
[107]	train-mlogloss:1.65960	validation-mlogloss:1.69219
[108]	train-mlogloss:1.65562	validation-mlogloss:1.68833
[109]	train-mlogloss:1.65175	validation-mlogloss:1.68457
[110]	train-mlogloss:1.64781	validation-mlogloss:1.68092
[111]	train-mlogloss:1.64402	validation-mlogloss:1.67731
[112]	train-mlogloss:1.64031	validation-mlogloss:1.67381
[113]	train-mlogloss:1.63651	validation-mlogloss:1.67038
[114]	train-mlogloss:1.63281	validation-mlogloss:1.66691
[115]	train-mlogloss:1.62934	validation-mlogloss:1.66377
[116]	train-mlogloss:1.62592	validation-mlogloss:1.66040
[117]	train-mlogloss:1.62250	validation-mlogloss:1.65723
[118]	train-mlogloss:1.61914	validation-mlogloss:1.65374
[119]	train-mlogloss:1.61573	validation-mlogloss:1.65058
[120]	train-mlogloss:1.61236	validation-mlogloss:1.64730
[121]	train-mlogloss:1.60883	validation-mlogloss:1.64379
[122]	train-mlogloss:1.60552	validation-mlogloss:1.64077
[123]	train-mlogloss:1.60216	validation-mlogloss:1.63785
[124]	train-mlogloss:1.59890	validation-mlogloss:1.63468
[125]	train-mlogloss:1.59557	validation-mlogloss:1.63161
[126]	train-mlogloss:1.59224	validation-mlogloss:1.62826
[127]	train-mlogloss:1.58886	validation-mlogloss:1.62523
[128]	train-mlogloss:1.58559	validation-mlogloss:1.62211
[129]	train-mlogloss:1.58249	validation-mlogloss:1.61929
[130]	train-mlogloss:1.57947	validation-mlogloss:1.61634
[131]	train-mlogloss:1.57652	validation-mlogloss:1.61370
[132]	train-mlogloss:1.57341	validation-mlogloss:1.61079
[133]	train-mlogloss:1.57044	validation-mlogloss:1.60800
[134]	train-mlogloss:1.56752	validation-mlogloss:1.60503
[135]	train-mlogloss:1.56455	validation-mlogloss:1.60236
[136]	train-mlogloss:1.56170	validation-mlogloss:1.59979
[137]	train-mlogloss:1.55882	validation-mlogloss:1.59692
[138]	train-mlogloss:1.55594	validation-mlogloss:1.59433
[139]	train-mlogloss:1.55318	validation-mlogloss:1.59172
[140]	train-mlogloss:1.55054	validation-mlogloss:1.58920
[141]	train-mlogloss:1.54773	validation-mlogloss:1.58652
[142]	train-mlogloss:1.54521	validation-mlogloss:1.58436
[143]	train-mlogloss:1.54253	validation-mlogloss:1.58186
[144]	train-mlogloss:1.53988	validation-mlogloss:1.57945
[145]	train-mlogloss:1.53736	validation-mlogloss:1.57704
[146]	train-mlogloss:1.53472	validation-mlogloss:1.57446
[147]	train-mlogloss:1.53211	validation-mlogloss:1.57206
[148]	train-mlogloss:1.52954	validation-mlogloss:1.56964
[149]	train-mlogloss:1.52712	validation-mlogloss:1.56731
[150]	train-mlogloss:1.52456	validation-mlogloss:1.56508
[151]	train-mlogloss:1.52216	validation-mlogloss:1.56273
[152]	train-mlogloss:1.51967	validation-mlogloss:1.56059
[153]	train-mlogloss:1.51739	validation-mlogloss:1.55842
[154]	train-mlogloss:1.51500	validation-mlogloss:1.55641
[155]	train-mlogloss:1.51267	validation-mlogloss:1.55412
[156]	train-mlogloss:1.51031	validation-mlogloss:1.55211
[157]	train-mlogloss:1.50786	validation-mlogloss:1.54993
[158]	train-mlogloss:1.50547	validation-mlogloss:1.54776
[159]	train-mlogloss:1.50314	validation-mlogloss:1.54548
[160]	train-mlogloss:1.50084	validation-mlogloss:1.54335
[161]	train-mlogloss:1.49856	validation-mlogloss:1.54137
[162]	train-mlogloss:1.49622	validation-mlogloss:1.53923
[163]	train-mlogloss:1.49396	validation-mlogloss:1.53710
[164]	train-mlogloss:1.49181	validation-mlogloss:1.53509
[165]	train-mlogloss:1.48969	validation-mlogloss:1.53346
[166]	train-mlogloss:1.48750	validation-mlogloss:1.53153
[167]	train-mlogloss:1.48532	validation-mlogloss:1.52959
[168]	train-mlogloss:1.48321	validation-mlogloss:1.52771
[169]	train-mlogloss:1.48115	validation-mlogloss:1.52599
[170]	train-mlogloss:1.47909	validation-mlogloss:1.52423
[171]	train-mlogloss:1.47713	validation-mlogloss:1.52257
[172]	train-mlogloss:1.47511	validation-mlogloss:1.52075
[173]	train-mlogloss:1.47312	validation-mlogloss:1.51908
[174]	train-mlogloss:1.47104	validation-mlogloss:1.51743
[175]	train-mlogloss:1.46931	validation-mlogloss:1.51587
[176]	train-mlogloss:1.46731	validation-mlogloss:1.51411
[177]	train-mlogloss:1.46534	validation-mlogloss:1.51233
[178]	train-mlogloss:1.46341	validation-mlogloss:1.51071
[179]	train-mlogloss:1.46158	validation-mlogloss:1.50891
[180]	train-mlogloss:1.45971	validation-mlogloss:1.50711
[181]	train-mlogloss:1.45788	validation-mlogloss:1.50555
[182]	train-mlogloss:1.45598	validation-mlogloss:1.50378
[183]	train-mlogloss:1.45417	validation-mlogloss:1.50225
[184]	train-mlogloss:1.45234	validation-mlogloss:1.50065
[185]	train-mlogloss:1.45051	validation-mlogloss:1.49889
[186]	train-mlogloss:1.44886	validation-mlogloss:1.49737
[187]	train-mlogloss:1.44708	validation-mlogloss:1.49583
[188]	train-mlogloss:1.44528	validation-mlogloss:1.49433
[189]	train-mlogloss:1.44361	validation-mlogloss:1.49302
[190]	train-mlogloss:1.44190	validation-mlogloss:1.49134
[191]	train-mlogloss:1.44029	validation-mlogloss:1.48979
[192]	train-mlogloss:1.43851	validation-mlogloss:1.48835
[193]	train-mlogloss:1.43684	validation-mlogloss:1.48679
[194]	train-mlogloss:1.43523	validation-mlogloss:1.48510
[195]	train-mlogloss:1.43364	validation-mlogloss:1.48377
[196]	train-mlogloss:1.43208	validation-mlogloss:1.48248
[197]	train-mlogloss:1.43041	validation-mlogloss:1.48099
[198]	train-mlogloss:1.42884	validation-mlogloss:1.47956
[199]	train-mlogloss:1.42726	validation-mlogloss:1.47831
[200]	train-mlogloss:1.42576	validation-mlogloss:1.47696
[201]	train-mlogloss:1.42418	validation-mlogloss:1.47556
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[505]	train-mlogloss:1.26177	validation-mlogloss:1.34499
[506]	train-mlogloss:1.26176	validation-mlogloss:1.34497
[507]	train-mlogloss:1.26174	validation-mlogloss:1.34497
[508]	train-mlogloss:1.26155	validation-mlogloss:1.34492
[509]	train-mlogloss:1.26145	validation-mlogloss:1.34482
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[514]	train-mlogloss:1.26107	validation-mlogloss:1.34464
[515]	train-mlogloss:1.26107	validation-mlogloss:1.34464
[516]	train-mlogloss:1.26103	validation-mlogloss:1.34464
[517]	train-mlogloss:1.26095	validation-mlogloss:1.34457
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[524]	train-mlogloss:1.26046	validation-mlogloss:1.34431
[525]	train-mlogloss:1.26033	validation-mlogloss:1.34419
[526]	train-mlogloss:1.26031	validation-mlogloss:1.34417
[527]	train-mlogloss:1.26031	validation-mlogloss:1.34418
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[530]	train-mlogloss:1.26008	validation-mlogloss:1.34387
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[534]	train-mlogloss:1.25979	validation-mlogloss:1.34366
[535]	train-mlogloss:1.25966	validation-mlogloss:1.34358
[536]	train-mlogloss:1.25957	validation-mlogloss:1.34354
[537]	train-mlogloss:1.25941	validation-mlogloss:1.34350
[538]	train-mlogloss:1.25930	validation-mlogloss:1.34341
[539]	train-mlogloss:1.25924	validation-mlogloss:1.34335
[540]	train-mlogloss:1.25912	validation-mlogloss:1.34335
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[542]	train-mlogloss:1.25904	validation-mlogloss:1.34325
[543]	train-mlogloss:1.25901	validation-mlogloss:1.34320
[544]	train-mlogloss:1.25898	validation-mlogloss:1.34321
[545]	train-mlogloss:1.25891	validation-mlogloss:1.34311
[546]	train-mlogloss:1.25879	validation-mlogloss:1.34304
[547]	train-mlogloss:1.25878	validation-mlogloss:1.34301
[548]	train-mlogloss:1.25873	validation-mlogloss:1.34294
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[550]	train-mlogloss:1.25859	validation-mlogloss:1.34274
[551]	train-mlogloss:1.25857	validation-mlogloss:1.34272
[552]	train-mlogloss:1.25854	validation-mlogloss:1.34271
[553]	train-mlogloss:1.25854	validation-mlogloss:1.34271
[554]	train-mlogloss:1.25844	validation-mlogloss:1.34261
[555]	train-mlogloss:1.25839	validation-mlogloss:1.34259
[556]	train-mlogloss:1.25824	validation-mlogloss:1.34262
[557]	train-mlogloss:1.25821	validation-mlogloss:1.34262
[558]	train-mlogloss:1.25815	validation-mlogloss:1.34255
[559]	train-mlogloss:1.25813	validation-mlogloss:1.34255
[560]	train-mlogloss:1.25809	validation-mlogloss:1.34249
[561]	train-mlogloss:1.25799	validation-mlogloss:1.34240
[562]	train-mlogloss:1.25799	validation-mlogloss:1.34240
[563]	train-mlogloss:1.25794	validation-mlogloss:1.34241
[564]	train-mlogloss:1.25794	validation-mlogloss:1.34241
[565]	train-mlogloss:1.25790	validation-mlogloss:1.34238
[566]	train-mlogloss:1.25785	validation-mlogloss:1.34240
[567]	train-mlogloss:1.25778	validation-mlogloss:1.34234
[568]	train-mlogloss:1.25775	validation-mlogloss:1.34233
[569]	train-mlogloss:1.25771	validation-mlogloss:1.34229
[570]	train-mlogloss:1.25760	validation-mlogloss:1.34223
[571]	train-mlogloss:1.25752	validation-mlogloss:1.34216
[572]	train-mlogloss:1.25742	validation-mlogloss:1.34208
[573]	train-mlogloss:1.25737	validation-mlogloss:1.34208
[574]	train-mlogloss:1.25735	validation-mlogloss:1.34206
[575]	train-mlogloss:1.25733	validation-mlogloss:1.34204
[576]	train-mlogloss:1.25733	validation-mlogloss:1.34204
[577]	train-mlogloss:1.25720	validation-mlogloss:1.34203
[578]	train-mlogloss:1.25720	validation-mlogloss:1.34203
[579]	train-mlogloss:1.25713	validation-mlogloss:1.34202
[580]	train-mlogloss:1.25706	validation-mlogloss:1.34195
[581]	train-mlogloss:1.25703	validation-mlogloss:1.34193
[582]	train-mlogloss:1.25696	validation-mlogloss:1.34190
[583]	train-mlogloss:1.25689	validation-mlogloss:1.34188
[584]	train-mlogloss:1.25683	validation-mlogloss:1.34183
[585]	train-mlogloss:1.25680	validation-mlogloss:1.34178
[586]	train-mlogloss:1.25673	validation-mlogloss:1.34179
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[590]	train-mlogloss:1.25654	validation-mlogloss:1.34168
[591]	train-mlogloss:1.25644	validation-mlogloss:1.34161
[592]	train-mlogloss:1.25642	validation-mlogloss:1.34161
[593]	train-mlogloss:1.25635	validation-mlogloss:1.34157
[594]	train-mlogloss:1.25630	validation-mlogloss:1.34156
[595]	train-mlogloss:1.25624	validation-mlogloss:1.34157
[596]	train-mlogloss:1.25623	validation-mlogloss:1.34157
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[603]	train-mlogloss:1.25590	validation-mlogloss:1.34156
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[610]	train-mlogloss:1.25552	validation-mlogloss:1.34127
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[618]	train-mlogloss:1.25513	validation-mlogloss:1.34101
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[620]	train-mlogloss:1.25502	validation-mlogloss:1.34095
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[622]	train-mlogloss:1.25493	validation-mlogloss:1.34084
[623]	train-mlogloss:1.25493	validation-mlogloss:1.34085
[624]	train-mlogloss:1.25486	validation-mlogloss:1.34081
[625]	train-mlogloss:1.25486	validation-mlogloss:1.34081
[626]	train-mlogloss:1.25485	validation-mlogloss:1.34081
[627]	train-mlogloss:1.25484	validation-mlogloss:1.34079
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[629]	train-mlogloss:1.25475	validation-mlogloss:1.34069
[630]	train-mlogloss:1.25468	validation-mlogloss:1.34065
[631]	train-mlogloss:1.25458	validation-mlogloss:1.34054
[632]	train-mlogloss:1.25458	validation-mlogloss:1.34054
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[634]	train-mlogloss:1.25451	validation-mlogloss:1.34052
[635]	train-mlogloss:1.25446	validation-mlogloss:1.34051
[636]	train-mlogloss:1.25438	validation-mlogloss:1.34043
[637]	train-mlogloss:1.25422	validation-mlogloss:1.34040
[638]	train-mlogloss:1.25415	validation-mlogloss:1.34042
[639]	train-mlogloss:1.25408	validation-mlogloss:1.34044
[640]	train-mlogloss:1.25402	validation-mlogloss:1.34039
[641]	train-mlogloss:1.25399	validation-mlogloss:1.34039
[642]	train-mlogloss:1.25393	validation-mlogloss:1.34038
[643]	train-mlogloss:1.25382	validation-mlogloss:1.34029
[644]	train-mlogloss:1.25376	validation-mlogloss:1.34023
[645]	train-mlogloss:1.25371	validation-mlogloss:1.34019
[646]	train-mlogloss:1.25366	validation-mlogloss:1.34017
[647]	train-mlogloss:1.25365	validation-mlogloss:1.34016
[648]	train-mlogloss:1.25354	validation-mlogloss:1.34006
[649]	train-mlogloss:1.25354	validation-mlogloss:1.34006
[650]	train-mlogloss:1.25353	validation-mlogloss:1.34004
[651]	train-mlogloss:1.25350	validation-mlogloss:1.34005
[652]	train-mlogloss:1.25346	validation-mlogloss:1.34000
[653]	train-mlogloss:1.25339	validation-mlogloss:1.33996
[654]	train-mlogloss:1.25337	validation-mlogloss:1.33992
[655]	train-mlogloss:1.25337	validation-mlogloss:1.33992
[656]	train-mlogloss:1.25329	validation-mlogloss:1.33987
[657]	train-mlogloss:1.25329	validation-mlogloss:1.33987
[658]	train-mlogloss:1.25323	validation-mlogloss:1.33984
[659]	train-mlogloss:1.25321	validation-mlogloss:1.33982
[660]	train-mlogloss:1.25317	validation-mlogloss:1.33975
[661]	train-mlogloss:1.25314	validation-mlogloss:1.33975
[662]	train-mlogloss:1.25306	validation-mlogloss:1.33967
[663]	train-mlogloss:1.25306	validation-mlogloss:1.33967
[664]	train-mlogloss:1.25298	validation-mlogloss:1.33962
[665]	train-mlogloss:1.25295	validation-mlogloss:1.33961
[666]	train-mlogloss:1.25295	validation-mlogloss:1.33961
[667]	train-mlogloss:1.25292	validation-mlogloss:1.33960
[668]	train-mlogloss:1.25287	validation-mlogloss:1.33959
[669]	train-mlogloss:1.25286	validation-mlogloss:1.33958
[670]	train-mlogloss:1.25283	validation-mlogloss:1.33955
[671]	train-mlogloss:1.25280	validation-mlogloss:1.33952
[672]	train-mlogloss:1.25278	validation-mlogloss:1.33951
[673]	train-mlogloss:1.25278	validation-mlogloss:1.33951
[674]	train-mlogloss:1.25274	validation-mlogloss:1.33944
[675]	train-mlogloss:1.25264	validation-mlogloss:1.33938
[676]	train-mlogloss:1.25261	validation-mlogloss:1.33937
[677]	train-mlogloss:1.25257	validation-mlogloss:1.33935
[678]	train-mlogloss:1.25255	validation-mlogloss:1.33938
[679]	train-mlogloss:1.25253	validation-mlogloss:1.33936
[680]	train-mlogloss:1.25248	validation-mlogloss:1.33929
[681]	train-mlogloss:1.25246	validation-mlogloss:1.33928
[682]	train-mlogloss:1.25246	validation-mlogloss:1.33928
[683]	train-mlogloss:1.25245	validation-mlogloss:1.33928
[684]	train-mlogloss:1.25243	validation-mlogloss:1.33927
[685]	train-mlogloss:1.25241	validation-mlogloss:1.33927
[686]	train-mlogloss:1.25241	validation-mlogloss:1.33927
[687]	train-mlogloss:1.25235	validation-mlogloss:1.33924
[688]	train-mlogloss:1.25231	validation-mlogloss:1.33920
[689]	train-mlogloss:1.25223	validation-mlogloss:1.33914
[690]	train-mlogloss:1.25218	validation-mlogloss:1.33907
[691]	train-mlogloss:1.25218	validation-mlogloss:1.33907
[692]	train-mlogloss:1.25218	validation-mlogloss:1.33907
[693]	train-mlogloss:1.25213	validation-mlogloss:1.33903
[694]	train-mlogloss:1.25213	validation-mlogloss:1.33904
[695]	train-mlogloss:1.25208	validation-mlogloss:1.33903
[696]	train-mlogloss:1.25208	validation-mlogloss:1.33903
[697]	train-mlogloss:1.25207	validation-mlogloss:1.33902
[698]	train-mlogloss:1.25206	validation-mlogloss:1.33903
[699]	train-mlogloss:1.25193	validation-mlogloss:1.33901
[700]	train-mlogloss:1.25185	validation-mlogloss:1.33900
[701]	train-mlogloss:1.25185	validation-mlogloss:1.33900
[702]	train-mlogloss:1.25180	validation-mlogloss:1.33894
[703]	train-mlogloss:1.25179	validation-mlogloss:1.33895
[704]	train-mlogloss:1.25178	validation-mlogloss:1.33897
[705]	train-mlogloss:1.25176	validation-mlogloss:1.33894
[706]	train-mlogloss:1.25173	validation-mlogloss:1.33892
[707]	train-mlogloss:1.25168	validation-mlogloss:1.33887
[708]	train-mlogloss:1.25165	validation-mlogloss:1.33886
[709]	train-mlogloss:1.25162	validation-mlogloss:1.33885
[710]	train-mlogloss:1.25160	validation-mlogloss:1.33883
[711]	train-mlogloss:1.25159	validation-mlogloss:1.33882
[712]	train-mlogloss:1.25159	validation-mlogloss:1.33882
[713]	train-mlogloss:1.25154	validation-mlogloss:1.33877
Saved model to disk.
2025-10-27 11:32:48.018286: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:32:48.030742: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761561168.044431  548770 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761561168.048842  548770 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761561168.060045  548770 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561168.060070  548770 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561168.060075  548770 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561168.060106  548770 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:32:48.063498: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68540	validation-mlogloss:2.68633
[1]	train-mlogloss:2.66320	validation-mlogloss:2.66417
[2]	train-mlogloss:2.64134	validation-mlogloss:2.64310
[3]	train-mlogloss:2.61986	validation-mlogloss:2.62212
[4]	train-mlogloss:2.59917	validation-mlogloss:2.60202
[5]	train-mlogloss:2.57793	validation-mlogloss:2.58104
[6]	train-mlogloss:2.55837	validation-mlogloss:2.56177
[7]	train-mlogloss:2.53795	validation-mlogloss:2.54203
[8]	train-mlogloss:2.51849	validation-mlogloss:2.52289
[9]	train-mlogloss:2.50037	validation-mlogloss:2.50532
[10]	train-mlogloss:2.48186	validation-mlogloss:2.48738
[11]	train-mlogloss:2.46454	validation-mlogloss:2.47060
[12]	train-mlogloss:2.44706	validation-mlogloss:2.45359
[13]	train-mlogloss:2.43026	validation-mlogloss:2.43738
[14]	train-mlogloss:2.41308	validation-mlogloss:2.42084
[15]	train-mlogloss:2.39675	validation-mlogloss:2.40486
[16]	train-mlogloss:2.38090	validation-mlogloss:2.38899
[17]	train-mlogloss:2.36520	validation-mlogloss:2.37401
[18]	train-mlogloss:2.34987	validation-mlogloss:2.35894
[19]	train-mlogloss:2.33527	validation-mlogloss:2.34417
[20]	train-mlogloss:2.32040	validation-mlogloss:2.32983
[21]	train-mlogloss:2.30619	validation-mlogloss:2.31688
[22]	train-mlogloss:2.29207	validation-mlogloss:2.30336
[23]	train-mlogloss:2.27808	validation-mlogloss:2.28976
[24]	train-mlogloss:2.26427	validation-mlogloss:2.27678
[25]	train-mlogloss:2.25103	validation-mlogloss:2.26352
[26]	train-mlogloss:2.23815	validation-mlogloss:2.25067
[27]	train-mlogloss:2.22576	validation-mlogloss:2.23877
[28]	train-mlogloss:2.21327	validation-mlogloss:2.22634
[29]	train-mlogloss:2.20099	validation-mlogloss:2.21440
[30]	train-mlogloss:2.18858	validation-mlogloss:2.20266
[31]	train-mlogloss:2.17655	validation-mlogloss:2.19115
[32]	train-mlogloss:2.16502	validation-mlogloss:2.17985
[33]	train-mlogloss:2.15341	validation-mlogloss:2.16873
[34]	train-mlogloss:2.14228	validation-mlogloss:2.15793
[35]	train-mlogloss:2.13164	validation-mlogloss:2.14687
[36]	train-mlogloss:2.12090	validation-mlogloss:2.13686
[37]	train-mlogloss:2.11110	validation-mlogloss:2.12757
[38]	train-mlogloss:2.10096	validation-mlogloss:2.11792
[39]	train-mlogloss:2.09073	validation-mlogloss:2.10734
[40]	train-mlogloss:2.08069	validation-mlogloss:2.09788
[41]	train-mlogloss:2.07055	validation-mlogloss:2.08827
[42]	train-mlogloss:2.06098	validation-mlogloss:2.07948
[43]	train-mlogloss:2.05141	validation-mlogloss:2.07039
[44]	train-mlogloss:2.04241	validation-mlogloss:2.06185
[45]	train-mlogloss:2.03354	validation-mlogloss:2.05283
[46]	train-mlogloss:2.02474	validation-mlogloss:2.04429
[47]	train-mlogloss:2.01550	validation-mlogloss:2.03507
[48]	train-mlogloss:2.00638	validation-mlogloss:2.02601
[49]	train-mlogloss:1.99806	validation-mlogloss:2.01808
[50]	train-mlogloss:1.98970	validation-mlogloss:2.00997
[51]	train-mlogloss:1.98116	validation-mlogloss:2.00121
[52]	train-mlogloss:1.97292	validation-mlogloss:1.99321
[53]	train-mlogloss:1.96461	validation-mlogloss:1.98559
[54]	train-mlogloss:1.95657	validation-mlogloss:1.97755
[55]	train-mlogloss:1.94883	validation-mlogloss:1.96984
[56]	train-mlogloss:1.94068	validation-mlogloss:1.96202
[57]	train-mlogloss:1.93316	validation-mlogloss:1.95478
[58]	train-mlogloss:1.92559	validation-mlogloss:1.94738
[59]	train-mlogloss:1.91826	validation-mlogloss:1.94028
[60]	train-mlogloss:1.91082	validation-mlogloss:1.93312
[61]	train-mlogloss:1.90366	validation-mlogloss:1.92613
[62]	train-mlogloss:1.89661	validation-mlogloss:1.91945
[63]	train-mlogloss:1.88952	validation-mlogloss:1.91249
[64]	train-mlogloss:1.88249	validation-mlogloss:1.90599
[65]	train-mlogloss:1.87569	validation-mlogloss:1.89965
[66]	train-mlogloss:1.86901	validation-mlogloss:1.89285
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[669]	train-mlogloss:1.25465	validation-mlogloss:1.34177
[670]	train-mlogloss:1.25460	validation-mlogloss:1.34169
[671]	train-mlogloss:1.25460	validation-mlogloss:1.34170
[672]	train-mlogloss:1.25460	validation-mlogloss:1.34170
[673]	train-mlogloss:1.25460	validation-mlogloss:1.34170
[674]	train-mlogloss:1.25455	validation-mlogloss:1.34167
[675]	train-mlogloss:1.25447	validation-mlogloss:1.34166
[676]	train-mlogloss:1.25446	validation-mlogloss:1.34163
[677]	train-mlogloss:1.25441	validation-mlogloss:1.34158
[678]	train-mlogloss:1.25441	validation-mlogloss:1.34158
[679]	train-mlogloss:1.25441	validation-mlogloss:1.34158
[680]	train-mlogloss:1.25429	validation-mlogloss:1.34150
[681]	train-mlogloss:1.25426	validation-mlogloss:1.34150
[682]	train-mlogloss:1.25426	validation-mlogloss:1.34150
[683]	train-mlogloss:1.25422	validation-mlogloss:1.34148
[684]	train-mlogloss:1.25422	validation-mlogloss:1.34148
[685]	train-mlogloss:1.25414	validation-mlogloss:1.34145
[686]	train-mlogloss:1.25411	validation-mlogloss:1.34141
[687]	train-mlogloss:1.25398	validation-mlogloss:1.34133
[688]	train-mlogloss:1.25394	validation-mlogloss:1.34129
[689]	train-mlogloss:1.25392	validation-mlogloss:1.34128
[690]	train-mlogloss:1.25390	validation-mlogloss:1.34128
[691]	train-mlogloss:1.25381	validation-mlogloss:1.34124
[692]	train-mlogloss:1.25381	validation-mlogloss:1.34124
[693]	train-mlogloss:1.25381	validation-mlogloss:1.34124
[694]	train-mlogloss:1.25381	validation-mlogloss:1.34124
[695]	train-mlogloss:1.25381	validation-mlogloss:1.34124
[696]	train-mlogloss:1.25377	validation-mlogloss:1.34121
[697]	train-mlogloss:1.25371	validation-mlogloss:1.34117
[698]	train-mlogloss:1.25370	validation-mlogloss:1.34116
[699]	train-mlogloss:1.25370	validation-mlogloss:1.34116
[700]	train-mlogloss:1.25365	validation-mlogloss:1.34111
[701]	train-mlogloss:1.25358	validation-mlogloss:1.34103
[702]	train-mlogloss:1.25358	validation-mlogloss:1.34103
[703]	train-mlogloss:1.25357	validation-mlogloss:1.34102
[704]	train-mlogloss:1.25357	validation-mlogloss:1.34102
[705]	train-mlogloss:1.25350	validation-mlogloss:1.34101
[706]	train-mlogloss:1.25348	validation-mlogloss:1.34101
[707]	train-mlogloss:1.25345	validation-mlogloss:1.34099
[708]	train-mlogloss:1.25345	validation-mlogloss:1.34099
[709]	train-mlogloss:1.25343	validation-mlogloss:1.34095
[710]	train-mlogloss:1.25335	validation-mlogloss:1.34093
[711]	train-mlogloss:1.25331	validation-mlogloss:1.34088
[712]	train-mlogloss:1.25326	validation-mlogloss:1.34087
[713]	train-mlogloss:1.25324	validation-mlogloss:1.34087
Saved model to disk.
2025-10-27 11:33:35.518820: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:33:35.531689: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761561215.545612  549706 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761561215.549988  549706 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761561215.560794  549706 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561215.560818  549706 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561215.560822  549706 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561215.560824  549706 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:33:35.564211: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68401	validation-mlogloss:2.68417
[1]	train-mlogloss:2.66224	validation-mlogloss:2.66256
[2]	train-mlogloss:2.63962	validation-mlogloss:2.64035
[3]	train-mlogloss:2.61773	validation-mlogloss:2.61821
[4]	train-mlogloss:2.59567	validation-mlogloss:2.59629
[5]	train-mlogloss:2.57554	validation-mlogloss:2.57683
[6]	train-mlogloss:2.55562	validation-mlogloss:2.55727
[7]	train-mlogloss:2.53562	validation-mlogloss:2.53800
[8]	train-mlogloss:2.51637	validation-mlogloss:2.51923
[9]	train-mlogloss:2.49870	validation-mlogloss:2.50126
[10]	train-mlogloss:2.48108	validation-mlogloss:2.48367
[11]	train-mlogloss:2.46333	validation-mlogloss:2.46675
[12]	train-mlogloss:2.44623	validation-mlogloss:2.45021
[13]	train-mlogloss:2.42913	validation-mlogloss:2.43348
[14]	train-mlogloss:2.41234	validation-mlogloss:2.41691
[15]	train-mlogloss:2.39632	validation-mlogloss:2.40187
[16]	train-mlogloss:2.38039	validation-mlogloss:2.38616
[17]	train-mlogloss:2.36532	validation-mlogloss:2.37188
[18]	train-mlogloss:2.34980	validation-mlogloss:2.35680
[19]	train-mlogloss:2.33493	validation-mlogloss:2.34289
[20]	train-mlogloss:2.32005	validation-mlogloss:2.32845
[21]	train-mlogloss:2.30506	validation-mlogloss:2.31405
[22]	train-mlogloss:2.29101	validation-mlogloss:2.30018
[23]	train-mlogloss:2.27740	validation-mlogloss:2.28625
[24]	train-mlogloss:2.26409	validation-mlogloss:2.27342
[25]	train-mlogloss:2.25071	validation-mlogloss:2.26050
[26]	train-mlogloss:2.23734	validation-mlogloss:2.24704
[27]	train-mlogloss:2.22476	validation-mlogloss:2.23461
[28]	train-mlogloss:2.21250	validation-mlogloss:2.22308
[29]	train-mlogloss:2.20038	validation-mlogloss:2.21127
[30]	train-mlogloss:2.18832	validation-mlogloss:2.19951
[31]	train-mlogloss:2.17658	validation-mlogloss:2.18821
[32]	train-mlogloss:2.16523	validation-mlogloss:2.17763
[33]	train-mlogloss:2.15380	validation-mlogloss:2.16663
[34]	train-mlogloss:2.14284	validation-mlogloss:2.15588
[35]	train-mlogloss:2.13171	validation-mlogloss:2.14493
[36]	train-mlogloss:2.12088	validation-mlogloss:2.13459
[37]	train-mlogloss:2.11017	validation-mlogloss:2.12461
[38]	train-mlogloss:2.09983	validation-mlogloss:2.11450
[39]	train-mlogloss:2.08969	validation-mlogloss:2.10513
[40]	train-mlogloss:2.07949	validation-mlogloss:2.09553
[41]	train-mlogloss:2.06970	validation-mlogloss:2.08617
[42]	train-mlogloss:2.05976	validation-mlogloss:2.07693
[43]	train-mlogloss:2.05036	validation-mlogloss:2.06820
[44]	train-mlogloss:2.04114	validation-mlogloss:2.05929
[45]	train-mlogloss:2.03233	validation-mlogloss:2.05062
[46]	train-mlogloss:2.02333	validation-mlogloss:2.04175
[47]	train-mlogloss:2.01422	validation-mlogloss:2.03322
[48]	train-mlogloss:2.00524	validation-mlogloss:2.02478
[49]	train-mlogloss:1.99650	validation-mlogloss:2.01647
[50]	train-mlogloss:1.98789	validation-mlogloss:2.00795
[51]	train-mlogloss:1.97940	validation-mlogloss:1.99985
[52]	train-mlogloss:1.97102	validation-mlogloss:1.99190
[53]	train-mlogloss:1.96298	validation-mlogloss:1.98391
[54]	train-mlogloss:1.95493	validation-mlogloss:1.97615
[55]	train-mlogloss:1.94683	validation-mlogloss:1.96850
[56]	train-mlogloss:1.93885	validation-mlogloss:1.96056
[57]	train-mlogloss:1.93153	validation-mlogloss:1.95368
[58]	train-mlogloss:1.92412	validation-mlogloss:1.94653
[59]	train-mlogloss:1.91676	validation-mlogloss:1.93904
[60]	train-mlogloss:1.90960	validation-mlogloss:1.93222
[61]	train-mlogloss:1.90244	validation-mlogloss:1.92481
[62]	train-mlogloss:1.89546	validation-mlogloss:1.91790
[63]	train-mlogloss:1.88841	validation-mlogloss:1.91101
[64]	train-mlogloss:1.88115	validation-mlogloss:1.90397
[65]	train-mlogloss:1.87434	validation-mlogloss:1.89725
[66]	train-mlogloss:1.86770	validation-mlogloss:1.89074
[67]	train-mlogloss:1.86097	validation-mlogloss:1.88412
[68]	train-mlogloss:1.85419	validation-mlogloss:1.87769
[69]	train-mlogloss:1.84801	validation-mlogloss:1.87184
[70]	train-mlogloss:1.84160	validation-mlogloss:1.86569
[71]	train-mlogloss:1.83546	validation-mlogloss:1.85995
[72]	train-mlogloss:1.82947	validation-mlogloss:1.85426
[73]	train-mlogloss:1.82333	validation-mlogloss:1.84832
[74]	train-mlogloss:1.81742	validation-mlogloss:1.84269
[75]	train-mlogloss:1.81152	validation-mlogloss:1.83682
[76]	train-mlogloss:1.80562	validation-mlogloss:1.83123
[77]	train-mlogloss:1.79978	validation-mlogloss:1.82543
[78]	train-mlogloss:1.79408	validation-mlogloss:1.82001
[79]	train-mlogloss:1.78854	validation-mlogloss:1.81443
[80]	train-mlogloss:1.78307	validation-mlogloss:1.80905
[81]	train-mlogloss:1.77767	validation-mlogloss:1.80380
[82]	train-mlogloss:1.77225	validation-mlogloss:1.79838
[83]	train-mlogloss:1.76707	validation-mlogloss:1.79345
[84]	train-mlogloss:1.76199	validation-mlogloss:1.78854
[85]	train-mlogloss:1.75695	validation-mlogloss:1.78360
[86]	train-mlogloss:1.75185	validation-mlogloss:1.77849
[87]	train-mlogloss:1.74692	validation-mlogloss:1.77397
[88]	train-mlogloss:1.74211	validation-mlogloss:1.76930
[89]	train-mlogloss:1.73709	validation-mlogloss:1.76462
[90]	train-mlogloss:1.73227	validation-mlogloss:1.76011
[91]	train-mlogloss:1.72723	validation-mlogloss:1.75552
[92]	train-mlogloss:1.72261	validation-mlogloss:1.75101
[93]	train-mlogloss:1.71811	validation-mlogloss:1.74675
[94]	train-mlogloss:1.71360	validation-mlogloss:1.74218
[95]	train-mlogloss:1.70886	validation-mlogloss:1.73765
[96]	train-mlogloss:1.70445	validation-mlogloss:1.73330
[97]	train-mlogloss:1.69998	validation-mlogloss:1.72921
[98]	train-mlogloss:1.69558	validation-mlogloss:1.72502
[99]	train-mlogloss:1.69112	validation-mlogloss:1.72059
[100]	train-mlogloss:1.68685	validation-mlogloss:1.71660
[101]	train-mlogloss:1.68247	validation-mlogloss:1.71233
[102]	train-mlogloss:1.67842	validation-mlogloss:1.70800
[103]	train-mlogloss:1.67441	validation-mlogloss:1.70416
[104]	train-mlogloss:1.67026	validation-mlogloss:1.70034
[105]	train-mlogloss:1.66628	validation-mlogloss:1.69671
[106]	train-mlogloss:1.66243	validation-mlogloss:1.69300
[107]	train-mlogloss:1.65852	validation-mlogloss:1.68896
[108]	train-mlogloss:1.65469	validation-mlogloss:1.68534
[109]	train-mlogloss:1.65090	validation-mlogloss:1.68181
[110]	train-mlogloss:1.64705	validation-mlogloss:1.67804
[111]	train-mlogloss:1.64325	validation-mlogloss:1.67449
[112]	train-mlogloss:1.63946	validation-mlogloss:1.67079
[113]	train-mlogloss:1.63580	validation-mlogloss:1.66720
[114]	train-mlogloss:1.63217	validation-mlogloss:1.66384
[115]	train-mlogloss:1.62866	validation-mlogloss:1.66078
[116]	train-mlogloss:1.62509	validation-mlogloss:1.65740
[117]	train-mlogloss:1.62161	validation-mlogloss:1.65407
[118]	train-mlogloss:1.61815	validation-mlogloss:1.65085
[119]	train-mlogloss:1.61484	validation-mlogloss:1.64771
[120]	train-mlogloss:1.61155	validation-mlogloss:1.64440
[121]	train-mlogloss:1.60801	validation-mlogloss:1.64108
[122]	train-mlogloss:1.60469	validation-mlogloss:1.63801
[123]	train-mlogloss:1.60137	validation-mlogloss:1.63487
[124]	train-mlogloss:1.59804	validation-mlogloss:1.63170
[125]	train-mlogloss:1.59489	validation-mlogloss:1.62881
[126]	train-mlogloss:1.59154	validation-mlogloss:1.62562
[127]	train-mlogloss:1.58840	validation-mlogloss:1.62278
[128]	train-mlogloss:1.58522	validation-mlogloss:1.61984
[129]	train-mlogloss:1.58206	validation-mlogloss:1.61699
[130]	train-mlogloss:1.57905	validation-mlogloss:1.61418
[131]	train-mlogloss:1.57604	validation-mlogloss:1.61131
[132]	train-mlogloss:1.57292	validation-mlogloss:1.60834
[133]	train-mlogloss:1.56998	validation-mlogloss:1.60567
[134]	train-mlogloss:1.56699	validation-mlogloss:1.60267
[135]	train-mlogloss:1.56396	validation-mlogloss:1.59992
[136]	train-mlogloss:1.56103	validation-mlogloss:1.59709
[137]	train-mlogloss:1.55816	validation-mlogloss:1.59446
[138]	train-mlogloss:1.55528	validation-mlogloss:1.59166
[139]	train-mlogloss:1.55258	validation-mlogloss:1.58902
[140]	train-mlogloss:1.54969	validation-mlogloss:1.58638
[141]	train-mlogloss:1.54688	validation-mlogloss:1.58382
[142]	train-mlogloss:1.54412	validation-mlogloss:1.58127
[143]	train-mlogloss:1.54152	validation-mlogloss:1.57894
[144]	train-mlogloss:1.53890	validation-mlogloss:1.57667
[145]	train-mlogloss:1.53623	validation-mlogloss:1.57421
[146]	train-mlogloss:1.53352	validation-mlogloss:1.57163
[147]	train-mlogloss:1.53085	validation-mlogloss:1.56919
[148]	train-mlogloss:1.52823	validation-mlogloss:1.56685
[149]	train-mlogloss:1.52564	validation-mlogloss:1.56446
[150]	train-mlogloss:1.52310	validation-mlogloss:1.56216
[151]	train-mlogloss:1.52071	validation-mlogloss:1.55988
[152]	train-mlogloss:1.51834	validation-mlogloss:1.55766
[153]	train-mlogloss:1.51603	validation-mlogloss:1.55562
[154]	train-mlogloss:1.51367	validation-mlogloss:1.55322
[155]	train-mlogloss:1.51140	validation-mlogloss:1.55104
[156]	train-mlogloss:1.50907	validation-mlogloss:1.54907
[157]	train-mlogloss:1.50685	validation-mlogloss:1.54700
[158]	train-mlogloss:1.50447	validation-mlogloss:1.54497
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[160]	train-mlogloss:1.49990	validation-mlogloss:1.54080
[161]	train-mlogloss:1.49767	validation-mlogloss:1.53886
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[163]	train-mlogloss:1.49326	validation-mlogloss:1.53484
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[190]	train-mlogloss:1.44105	validation-mlogloss:1.48956
[191]	train-mlogloss:1.43933	validation-mlogloss:1.48809
[192]	train-mlogloss:1.43769	validation-mlogloss:1.48674
[193]	train-mlogloss:1.43596	validation-mlogloss:1.48518
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[201]	train-mlogloss:1.42335	validation-mlogloss:1.47409
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[209]	train-mlogloss:1.41152	validation-mlogloss:1.46368
[210]	train-mlogloss:1.40990	validation-mlogloss:1.46227
[211]	train-mlogloss:1.40849	validation-mlogloss:1.46116
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[221]	train-mlogloss:1.39486	validation-mlogloss:1.44954
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[533]	train-mlogloss:1.25929	validation-mlogloss:1.34461
[534]	train-mlogloss:1.25925	validation-mlogloss:1.34455
[535]	train-mlogloss:1.25923	validation-mlogloss:1.34453
[536]	train-mlogloss:1.25916	validation-mlogloss:1.34446
[537]	train-mlogloss:1.25916	validation-mlogloss:1.34446
[538]	train-mlogloss:1.25915	validation-mlogloss:1.34445
[539]	train-mlogloss:1.25908	validation-mlogloss:1.34439
[540]	train-mlogloss:1.25901	validation-mlogloss:1.34432
[541]	train-mlogloss:1.25887	validation-mlogloss:1.34428
[542]	train-mlogloss:1.25884	validation-mlogloss:1.34424
[543]	train-mlogloss:1.25875	validation-mlogloss:1.34418
[544]	train-mlogloss:1.25875	validation-mlogloss:1.34418
[545]	train-mlogloss:1.25871	validation-mlogloss:1.34416
[546]	train-mlogloss:1.25863	validation-mlogloss:1.34414
[547]	train-mlogloss:1.25849	validation-mlogloss:1.34417
[548]	train-mlogloss:1.25846	validation-mlogloss:1.34414
[549]	train-mlogloss:1.25840	validation-mlogloss:1.34405
[550]	train-mlogloss:1.25840	validation-mlogloss:1.34405
[551]	train-mlogloss:1.25838	validation-mlogloss:1.34402
[552]	train-mlogloss:1.25833	validation-mlogloss:1.34398
[553]	train-mlogloss:1.25827	validation-mlogloss:1.34393
[554]	train-mlogloss:1.25827	validation-mlogloss:1.34393
[555]	train-mlogloss:1.25811	validation-mlogloss:1.34394
[556]	train-mlogloss:1.25809	validation-mlogloss:1.34392
[557]	train-mlogloss:1.25806	validation-mlogloss:1.34393
[558]	train-mlogloss:1.25790	validation-mlogloss:1.34383
[559]	train-mlogloss:1.25789	validation-mlogloss:1.34381
[560]	train-mlogloss:1.25779	validation-mlogloss:1.34379
[561]	train-mlogloss:1.25778	validation-mlogloss:1.34377
[562]	train-mlogloss:1.25770	validation-mlogloss:1.34370
[563]	train-mlogloss:1.25768	validation-mlogloss:1.34366
[564]	train-mlogloss:1.25761	validation-mlogloss:1.34363
[565]	train-mlogloss:1.25760	validation-mlogloss:1.34362
[566]	train-mlogloss:1.25752	validation-mlogloss:1.34355
[567]	train-mlogloss:1.25738	validation-mlogloss:1.34344
[568]	train-mlogloss:1.25725	validation-mlogloss:1.34336
[569]	train-mlogloss:1.25723	validation-mlogloss:1.34337
[570]	train-mlogloss:1.25721	validation-mlogloss:1.34332
[571]	train-mlogloss:1.25711	validation-mlogloss:1.34329
[572]	train-mlogloss:1.25703	validation-mlogloss:1.34322
[573]	train-mlogloss:1.25701	validation-mlogloss:1.34320
[574]	train-mlogloss:1.25695	validation-mlogloss:1.34317
[575]	train-mlogloss:1.25688	validation-mlogloss:1.34312
[576]	train-mlogloss:1.25686	validation-mlogloss:1.34313
[577]	train-mlogloss:1.25674	validation-mlogloss:1.34305
[578]	train-mlogloss:1.25666	validation-mlogloss:1.34300
[579]	train-mlogloss:1.25662	validation-mlogloss:1.34294
[580]	train-mlogloss:1.25657	validation-mlogloss:1.34291
[581]	train-mlogloss:1.25656	validation-mlogloss:1.34290
[582]	train-mlogloss:1.25654	validation-mlogloss:1.34289
[583]	train-mlogloss:1.25651	validation-mlogloss:1.34289
[584]	train-mlogloss:1.25641	validation-mlogloss:1.34282
[585]	train-mlogloss:1.25641	validation-mlogloss:1.34282
[586]	train-mlogloss:1.25630	validation-mlogloss:1.34278
[587]	train-mlogloss:1.25626	validation-mlogloss:1.34275
[588]	train-mlogloss:1.25625	validation-mlogloss:1.34273
[589]	train-mlogloss:1.25621	validation-mlogloss:1.34270
[590]	train-mlogloss:1.25619	validation-mlogloss:1.34267
[591]	train-mlogloss:1.25606	validation-mlogloss:1.34262
[592]	train-mlogloss:1.25605	validation-mlogloss:1.34261
[593]	train-mlogloss:1.25603	validation-mlogloss:1.34260
[594]	train-mlogloss:1.25596	validation-mlogloss:1.34259
[595]	train-mlogloss:1.25590	validation-mlogloss:1.34255
[596]	train-mlogloss:1.25583	validation-mlogloss:1.34252
[597]	train-mlogloss:1.25578	validation-mlogloss:1.34247
[598]	train-mlogloss:1.25575	validation-mlogloss:1.34244
[599]	train-mlogloss:1.25575	validation-mlogloss:1.34244
[600]	train-mlogloss:1.25564	validation-mlogloss:1.34234
[601]	train-mlogloss:1.25555	validation-mlogloss:1.34237
[602]	train-mlogloss:1.25541	validation-mlogloss:1.34221
[603]	train-mlogloss:1.25541	validation-mlogloss:1.34221
[604]	train-mlogloss:1.25533	validation-mlogloss:1.34217
[605]	train-mlogloss:1.25532	validation-mlogloss:1.34217
[606]	train-mlogloss:1.25525	validation-mlogloss:1.34216
[607]	train-mlogloss:1.25525	validation-mlogloss:1.34216
[608]	train-mlogloss:1.25525	validation-mlogloss:1.34216
[609]	train-mlogloss:1.25518	validation-mlogloss:1.34215
[610]	train-mlogloss:1.25513	validation-mlogloss:1.34212
[611]	train-mlogloss:1.25505	validation-mlogloss:1.34203
[612]	train-mlogloss:1.25491	validation-mlogloss:1.34200
[613]	train-mlogloss:1.25484	validation-mlogloss:1.34197
[614]	train-mlogloss:1.25473	validation-mlogloss:1.34192
[615]	train-mlogloss:1.25470	validation-mlogloss:1.34190
[616]	train-mlogloss:1.25470	validation-mlogloss:1.34190
[617]	train-mlogloss:1.25465	validation-mlogloss:1.34190
[618]	train-mlogloss:1.25463	validation-mlogloss:1.34188
[619]	train-mlogloss:1.25457	validation-mlogloss:1.34181
[620]	train-mlogloss:1.25437	validation-mlogloss:1.34168
[621]	train-mlogloss:1.25437	validation-mlogloss:1.34168
[622]	train-mlogloss:1.25431	validation-mlogloss:1.34163
[623]	train-mlogloss:1.25423	validation-mlogloss:1.34158
[624]	train-mlogloss:1.25417	validation-mlogloss:1.34155
[625]	train-mlogloss:1.25409	validation-mlogloss:1.34146
[626]	train-mlogloss:1.25402	validation-mlogloss:1.34139
[627]	train-mlogloss:1.25398	validation-mlogloss:1.34139
[628]	train-mlogloss:1.25397	validation-mlogloss:1.34138
[629]	train-mlogloss:1.25391	validation-mlogloss:1.34136
[630]	train-mlogloss:1.25390	validation-mlogloss:1.34136
[631]	train-mlogloss:1.25380	validation-mlogloss:1.34134
[632]	train-mlogloss:1.25380	validation-mlogloss:1.34134
[633]	train-mlogloss:1.25372	validation-mlogloss:1.34133
[634]	train-mlogloss:1.25369	validation-mlogloss:1.34130
[635]	train-mlogloss:1.25368	validation-mlogloss:1.34130
[636]	train-mlogloss:1.25368	validation-mlogloss:1.34129
[637]	train-mlogloss:1.25364	validation-mlogloss:1.34128
[638]	train-mlogloss:1.25359	validation-mlogloss:1.34126
[639]	train-mlogloss:1.25359	validation-mlogloss:1.34126
[640]	train-mlogloss:1.25353	validation-mlogloss:1.34123
[641]	train-mlogloss:1.25351	validation-mlogloss:1.34122
[642]	train-mlogloss:1.25345	validation-mlogloss:1.34119
[643]	train-mlogloss:1.25344	validation-mlogloss:1.34117
[644]	train-mlogloss:1.25330	validation-mlogloss:1.34106
[645]	train-mlogloss:1.25323	validation-mlogloss:1.34104
[646]	train-mlogloss:1.25318	validation-mlogloss:1.34100
[647]	train-mlogloss:1.25316	validation-mlogloss:1.34101
[648]	train-mlogloss:1.25311	validation-mlogloss:1.34095
[649]	train-mlogloss:1.25302	validation-mlogloss:1.34089
[650]	train-mlogloss:1.25299	validation-mlogloss:1.34088
[651]	train-mlogloss:1.25299	validation-mlogloss:1.34088
[652]	train-mlogloss:1.25297	validation-mlogloss:1.34088
[653]	train-mlogloss:1.25295	validation-mlogloss:1.34085
[654]	train-mlogloss:1.25295	validation-mlogloss:1.34085
[655]	train-mlogloss:1.25294	validation-mlogloss:1.34085
[656]	train-mlogloss:1.25294	validation-mlogloss:1.34085
[657]	train-mlogloss:1.25284	validation-mlogloss:1.34081
[658]	train-mlogloss:1.25277	validation-mlogloss:1.34071
[659]	train-mlogloss:1.25273	validation-mlogloss:1.34070
[660]	train-mlogloss:1.25266	validation-mlogloss:1.34069
[661]	train-mlogloss:1.25266	validation-mlogloss:1.34069
[662]	train-mlogloss:1.25256	validation-mlogloss:1.34060
[663]	train-mlogloss:1.25255	validation-mlogloss:1.34060
[664]	train-mlogloss:1.25250	validation-mlogloss:1.34056
[665]	train-mlogloss:1.25243	validation-mlogloss:1.34054
[666]	train-mlogloss:1.25239	validation-mlogloss:1.34051
[667]	train-mlogloss:1.25230	validation-mlogloss:1.34044
[668]	train-mlogloss:1.25229	validation-mlogloss:1.34044
[669]	train-mlogloss:1.25221	validation-mlogloss:1.34045
[670]	train-mlogloss:1.25220	validation-mlogloss:1.34045
[671]	train-mlogloss:1.25214	validation-mlogloss:1.34040
[672]	train-mlogloss:1.25210	validation-mlogloss:1.34038
[673]	train-mlogloss:1.25209	validation-mlogloss:1.34037
[674]	train-mlogloss:1.25204	validation-mlogloss:1.34032
[675]	train-mlogloss:1.25202	validation-mlogloss:1.34034
[676]	train-mlogloss:1.25197	validation-mlogloss:1.34032
[677]	train-mlogloss:1.25190	validation-mlogloss:1.34024
[678]	train-mlogloss:1.25186	validation-mlogloss:1.34023
[679]	train-mlogloss:1.25184	validation-mlogloss:1.34023
[680]	train-mlogloss:1.25182	validation-mlogloss:1.34021
[681]	train-mlogloss:1.25178	validation-mlogloss:1.34016
[682]	train-mlogloss:1.25178	validation-mlogloss:1.34016
[683]	train-mlogloss:1.25176	validation-mlogloss:1.34017
[684]	train-mlogloss:1.25172	validation-mlogloss:1.34013
[685]	train-mlogloss:1.25170	validation-mlogloss:1.34012
[686]	train-mlogloss:1.25170	validation-mlogloss:1.34013
[687]	train-mlogloss:1.25170	validation-mlogloss:1.34013
[688]	train-mlogloss:1.25163	validation-mlogloss:1.34012
[689]	train-mlogloss:1.25158	validation-mlogloss:1.34012
[690]	train-mlogloss:1.25152	validation-mlogloss:1.34009
[691]	train-mlogloss:1.25149	validation-mlogloss:1.34009
[692]	train-mlogloss:1.25141	validation-mlogloss:1.34007
[693]	train-mlogloss:1.25140	validation-mlogloss:1.34006
[694]	train-mlogloss:1.25140	validation-mlogloss:1.34006
[695]	train-mlogloss:1.25140	validation-mlogloss:1.34006
[696]	train-mlogloss:1.25140	validation-mlogloss:1.34006
[697]	train-mlogloss:1.25135	validation-mlogloss:1.34003
[698]	train-mlogloss:1.25130	validation-mlogloss:1.33998
[699]	train-mlogloss:1.25127	validation-mlogloss:1.33996
[700]	train-mlogloss:1.25118	validation-mlogloss:1.33986
[701]	train-mlogloss:1.25113	validation-mlogloss:1.33985
[702]	train-mlogloss:1.25109	validation-mlogloss:1.33980
[703]	train-mlogloss:1.25102	validation-mlogloss:1.33973
[704]	train-mlogloss:1.25100	validation-mlogloss:1.33969
[705]	train-mlogloss:1.25100	validation-mlogloss:1.33969
[706]	train-mlogloss:1.25100	validation-mlogloss:1.33969
[707]	train-mlogloss:1.25094	validation-mlogloss:1.33965
[708]	train-mlogloss:1.25088	validation-mlogloss:1.33962
[709]	train-mlogloss:1.25076	validation-mlogloss:1.33956
[710]	train-mlogloss:1.25068	validation-mlogloss:1.33959
[711]	train-mlogloss:1.25063	validation-mlogloss:1.33955
[712]	train-mlogloss:1.25063	validation-mlogloss:1.33955
[713]	train-mlogloss:1.25057	validation-mlogloss:1.33947
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.9 [%]
Global accuracy score (test) = 51.08 [%]
Global F1 score (train) = 62.97 [%]
Global F1 score (test) = 51.26 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.29      0.39      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.43      0.44       184
       CAMINAR USUAL SPEED       0.28      0.22      0.25       184
            CAMINAR ZIGZAG       0.59      0.53      0.56       184
          DE PIE BARRIENDO       0.54      0.51      0.52       184
   DE PIE DOBLANDO TOALLAS       0.44      0.47      0.46       184
    DE PIE MOVIENDO LIBROS       0.50      0.48      0.49       184
          DE PIE USANDO PC       0.61      0.66      0.64       184
        FASE REPOSO CON K5       0.56      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.88      0.63      0.73       184
           SENTADO LEYENDO       0.36      0.43      0.40       184
         SENTADO USANDO PC       0.40      0.26      0.32       184
      SENTADO VIENDO LA TV       0.47      0.40      0.43       184
   SUBIR Y BAJAR ESCALERAS       0.54      0.67      0.60       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.51      2737


Accuracy capturado en la ejecución 22: 51.08 [%]
F1-score capturado en la ejecución 22: 51.26 [%]

=== EJECUCIÓN 23 ===

--- TRAIN (ejecución 23) ---

--- TEST (ejecución 23) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.69 [%]
Global accuracy score (test) = 50.68 [%]
Global F1 score (train) = 62.76 [%]
Global F1 score (test) = 50.86 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.29      0.38      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.42      0.38      0.40       184
       CAMINAR USUAL SPEED       0.27      0.21      0.24       184
            CAMINAR ZIGZAG       0.59      0.55      0.57       184
          DE PIE BARRIENDO       0.56      0.49      0.52       184
   DE PIE DOBLANDO TOALLAS       0.45      0.48      0.46       184
    DE PIE MOVIENDO LIBROS       0.49      0.47      0.48       184
          DE PIE USANDO PC       0.64      0.66      0.65       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.90      0.63      0.74       184
           SENTADO LEYENDO       0.35      0.42      0.38       184
         SENTADO USANDO PC       0.42      0.29      0.34       184
      SENTADO VIENDO LA TV       0.45      0.38      0.41       184
   SUBIR Y BAJAR ESCALERAS       0.52      0.68      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.51      2737


Accuracy capturado en la ejecución 23: 50.68 [%]
F1-score capturado en la ejecución 23: 50.86 [%]

=== EJECUCIÓN 24 ===

--- TRAIN (ejecución 24) ---

--- TEST (ejecución 24) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.77 [%]
Global accuracy score (test) = 50.68 [%]
Global F1 score (train) = 62.83 [%]
Global F1 score (test) = 50.85 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.39      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.39      0.42       184
       CAMINAR USUAL SPEED       0.29      0.23      0.25       184
            CAMINAR ZIGZAG       0.58      0.54      0.56       184
          DE PIE BARRIENDO       0.55      0.49      0.52       184
   DE PIE DOBLANDO TOALLAS       0.44      0.47      0.46       184
    DE PIE MOVIENDO LIBROS       0.49      0.47      0.48       184
          DE PIE USANDO PC       0.60      0.67      0.63       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.87      0.64      0.74       184
           SENTADO LEYENDO       0.36      0.43      0.39       184
         SENTADO USANDO PC       0.43      0.26      0.32       184
      SENTADO VIENDO LA TV       0.47      0.39      0.43       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.66      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.51      2737


Accuracy capturado en la ejecución 24: 50.68 [%]
F1-score capturado en la ejecución 24: 50.85 [%]

=== EJECUCIÓN 25 ===

--- TRAIN (ejecución 25) ---

--- TEST (ejecución 25) ---
2025-10-27 11:34:23.121512: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:34:23.134152: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761561263.147846  550636 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761561263.152059  550636 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761561263.163168  550636 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561263.163190  550636 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561263.163193  550636 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561263.163196  550636 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:34:23.166555: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68489	validation-mlogloss:2.68531
[1]	train-mlogloss:2.66144	validation-mlogloss:2.66267
[2]	train-mlogloss:2.63983	validation-mlogloss:2.64304
[3]	train-mlogloss:2.61861	validation-mlogloss:2.62243
[4]	train-mlogloss:2.59788	validation-mlogloss:2.60226
[5]	train-mlogloss:2.57693	validation-mlogloss:2.58125
[6]	train-mlogloss:2.55610	validation-mlogloss:2.56050
[7]	train-mlogloss:2.53604	validation-mlogloss:2.54093
[8]	train-mlogloss:2.51648	validation-mlogloss:2.52189
[9]	train-mlogloss:2.49749	validation-mlogloss:2.50330
[10]	train-mlogloss:2.47943	validation-mlogloss:2.48480
[11]	train-mlogloss:2.46186	validation-mlogloss:2.46717
[12]	train-mlogloss:2.44425	validation-mlogloss:2.44974
[13]	train-mlogloss:2.42772	validation-mlogloss:2.43383
[14]	train-mlogloss:2.41095	validation-mlogloss:2.41785
[15]	train-mlogloss:2.39428	validation-mlogloss:2.40185
[16]	train-mlogloss:2.37862	validation-mlogloss:2.38681
[17]	train-mlogloss:2.36267	validation-mlogloss:2.37156
[18]	train-mlogloss:2.34713	validation-mlogloss:2.35625
[19]	train-mlogloss:2.33274	validation-mlogloss:2.34238
[20]	train-mlogloss:2.31792	validation-mlogloss:2.32822
[21]	train-mlogloss:2.30345	validation-mlogloss:2.31392
[22]	train-mlogloss:2.28958	validation-mlogloss:2.30036
[23]	train-mlogloss:2.27572	validation-mlogloss:2.28705
[24]	train-mlogloss:2.26231	validation-mlogloss:2.27411
[25]	train-mlogloss:2.24925	validation-mlogloss:2.26134
[26]	train-mlogloss:2.23640	validation-mlogloss:2.24907
[27]	train-mlogloss:2.22411	validation-mlogloss:2.23723
[28]	train-mlogloss:2.21153	validation-mlogloss:2.22549
[29]	train-mlogloss:2.19918	validation-mlogloss:2.21309
[30]	train-mlogloss:2.18733	validation-mlogloss:2.20149
[31]	train-mlogloss:2.17565	validation-mlogloss:2.19008
[32]	train-mlogloss:2.16437	validation-mlogloss:2.17914
[33]	train-mlogloss:2.15332	validation-mlogloss:2.16809
[34]	train-mlogloss:2.14182	validation-mlogloss:2.15683
[35]	train-mlogloss:2.13101	validation-mlogloss:2.14655
[36]	train-mlogloss:2.12048	validation-mlogloss:2.13628
[37]	train-mlogloss:2.10992	validation-mlogloss:2.12611
[38]	train-mlogloss:2.09959	validation-mlogloss:2.11696
[39]	train-mlogloss:2.08921	validation-mlogloss:2.10663
[40]	train-mlogloss:2.07931	validation-mlogloss:2.09687
[41]	train-mlogloss:2.06937	validation-mlogloss:2.08741
[42]	train-mlogloss:2.06026	validation-mlogloss:2.07852
[43]	train-mlogloss:2.05084	validation-mlogloss:2.06970
[44]	train-mlogloss:2.04115	validation-mlogloss:2.06037
[45]	train-mlogloss:2.03198	validation-mlogloss:2.05155
[46]	train-mlogloss:2.02291	validation-mlogloss:2.04267
[47]	train-mlogloss:2.01391	validation-mlogloss:2.03415
[48]	train-mlogloss:2.00538	validation-mlogloss:2.02608
[49]	train-mlogloss:1.99688	validation-mlogloss:2.01793
[50]	train-mlogloss:1.98843	validation-mlogloss:2.00967
[51]	train-mlogloss:1.98006	validation-mlogloss:2.00158
[52]	train-mlogloss:1.97182	validation-mlogloss:1.99363
[53]	train-mlogloss:1.96344	validation-mlogloss:1.98566
[54]	train-mlogloss:1.95553	validation-mlogloss:1.97799
[55]	train-mlogloss:1.94757	validation-mlogloss:1.97042
[56]	train-mlogloss:1.93996	validation-mlogloss:1.96313
[57]	train-mlogloss:1.93223	validation-mlogloss:1.95565
[58]	train-mlogloss:1.92470	validation-mlogloss:1.94810
[59]	train-mlogloss:1.91719	validation-mlogloss:1.94101
[60]	train-mlogloss:1.91006	validation-mlogloss:1.93404
[61]	train-mlogloss:1.90278	validation-mlogloss:1.92699
[62]	train-mlogloss:1.89583	validation-mlogloss:1.92020
[63]	train-mlogloss:1.88891	validation-mlogloss:1.91346
[64]	train-mlogloss:1.88185	validation-mlogloss:1.90663
[65]	train-mlogloss:1.87501	validation-mlogloss:1.89993
[66]	train-mlogloss:1.86833	validation-mlogloss:1.89335
[67]	train-mlogloss:1.86183	validation-mlogloss:1.88707
[68]	train-mlogloss:1.85558	validation-mlogloss:1.88109
[69]	train-mlogloss:1.84928	validation-mlogloss:1.87459
[70]	train-mlogloss:1.84318	validation-mlogloss:1.86862
[71]	train-mlogloss:1.83698	validation-mlogloss:1.86262
[72]	train-mlogloss:1.83069	validation-mlogloss:1.85681
[73]	train-mlogloss:1.82461	validation-mlogloss:1.85057
[74]	train-mlogloss:1.81869	validation-mlogloss:1.84469
[75]	train-mlogloss:1.81286	validation-mlogloss:1.83921
[76]	train-mlogloss:1.80722	validation-mlogloss:1.83369
[77]	train-mlogloss:1.80166	validation-mlogloss:1.82832
[78]	train-mlogloss:1.79585	validation-mlogloss:1.82269
[79]	train-mlogloss:1.79015	validation-mlogloss:1.81720
[80]	train-mlogloss:1.78468	validation-mlogloss:1.81204
[81]	train-mlogloss:1.77939	validation-mlogloss:1.80694
[82]	train-mlogloss:1.77402	validation-mlogloss:1.80177
[83]	train-mlogloss:1.76871	validation-mlogloss:1.79672
[84]	train-mlogloss:1.76350	validation-mlogloss:1.79176
[85]	train-mlogloss:1.75825	validation-mlogloss:1.78670
[86]	train-mlogloss:1.75318	validation-mlogloss:1.78195
[87]	train-mlogloss:1.74829	validation-mlogloss:1.77727
[88]	train-mlogloss:1.74332	validation-mlogloss:1.77241
[89]	train-mlogloss:1.73858	validation-mlogloss:1.76765
[90]	train-mlogloss:1.73396	validation-mlogloss:1.76303
[91]	train-mlogloss:1.72946	validation-mlogloss:1.75856
[92]	train-mlogloss:1.72455	validation-mlogloss:1.75410
[93]	train-mlogloss:1.71991	validation-mlogloss:1.74938
[94]	train-mlogloss:1.71534	validation-mlogloss:1.74541
[95]	train-mlogloss:1.71074	validation-mlogloss:1.74114
[96]	train-mlogloss:1.70620	validation-mlogloss:1.73659
[97]	train-mlogloss:1.70159	validation-mlogloss:1.73202
[98]	train-mlogloss:1.69706	validation-mlogloss:1.72778
[99]	train-mlogloss:1.69291	validation-mlogloss:1.72359
[100]	train-mlogloss:1.68860	validation-mlogloss:1.71952
[101]	train-mlogloss:1.68430	validation-mlogloss:1.71537
[102]	train-mlogloss:1.68000	validation-mlogloss:1.71134
[103]	train-mlogloss:1.67585	validation-mlogloss:1.70741
[104]	train-mlogloss:1.67179	validation-mlogloss:1.70361
[105]	train-mlogloss:1.66783	validation-mlogloss:1.70014
[106]	train-mlogloss:1.66383	validation-mlogloss:1.69654
[107]	train-mlogloss:1.65985	validation-mlogloss:1.69273
[108]	train-mlogloss:1.65595	validation-mlogloss:1.68913
[109]	train-mlogloss:1.65198	validation-mlogloss:1.68546
[110]	train-mlogloss:1.64828	validation-mlogloss:1.68186
[111]	train-mlogloss:1.64452	validation-mlogloss:1.67844
[112]	train-mlogloss:1.64078	validation-mlogloss:1.67474
[113]	train-mlogloss:1.63724	validation-mlogloss:1.67127
[114]	train-mlogloss:1.63354	validation-mlogloss:1.66780
[115]	train-mlogloss:1.62991	validation-mlogloss:1.66441
[116]	train-mlogloss:1.62645	validation-mlogloss:1.66129
[117]	train-mlogloss:1.62282	validation-mlogloss:1.65782
[118]	train-mlogloss:1.61926	validation-mlogloss:1.65462
[119]	train-mlogloss:1.61584	validation-mlogloss:1.65148
[120]	train-mlogloss:1.61231	validation-mlogloss:1.64801
[121]	train-mlogloss:1.60893	validation-mlogloss:1.64487
[122]	train-mlogloss:1.60559	validation-mlogloss:1.64157
[123]	train-mlogloss:1.60220	validation-mlogloss:1.63826
[124]	train-mlogloss:1.59897	validation-mlogloss:1.63499
[125]	train-mlogloss:1.59584	validation-mlogloss:1.63180
[126]	train-mlogloss:1.59276	validation-mlogloss:1.62892
[127]	train-mlogloss:1.58960	validation-mlogloss:1.62571
[128]	train-mlogloss:1.58632	validation-mlogloss:1.62260
[129]	train-mlogloss:1.58331	validation-mlogloss:1.61981
[130]	train-mlogloss:1.58034	validation-mlogloss:1.61703
[131]	train-mlogloss:1.57744	validation-mlogloss:1.61406
[132]	train-mlogloss:1.57450	validation-mlogloss:1.61130
[133]	train-mlogloss:1.57150	validation-mlogloss:1.60838
[134]	train-mlogloss:1.56858	validation-mlogloss:1.60572
[135]	train-mlogloss:1.56577	validation-mlogloss:1.60323
[136]	train-mlogloss:1.56277	validation-mlogloss:1.60048
[137]	train-mlogloss:1.55993	validation-mlogloss:1.59782
[138]	train-mlogloss:1.55721	validation-mlogloss:1.59531
[139]	train-mlogloss:1.55436	validation-mlogloss:1.59284
[140]	train-mlogloss:1.55163	validation-mlogloss:1.59025
[141]	train-mlogloss:1.54899	validation-mlogloss:1.58786
[142]	train-mlogloss:1.54622	validation-mlogloss:1.58514
[143]	train-mlogloss:1.54340	validation-mlogloss:1.58252
[144]	train-mlogloss:1.54075	validation-mlogloss:1.58035
[145]	train-mlogloss:1.53827	validation-mlogloss:1.57818
[146]	train-mlogloss:1.53551	validation-mlogloss:1.57583
[147]	train-mlogloss:1.53293	validation-mlogloss:1.57352
[148]	train-mlogloss:1.53046	validation-mlogloss:1.57117
[149]	train-mlogloss:1.52810	validation-mlogloss:1.56892
[150]	train-mlogloss:1.52553	validation-mlogloss:1.56642
[151]	train-mlogloss:1.52297	validation-mlogloss:1.56401
[152]	train-mlogloss:1.52047	validation-mlogloss:1.56167
[153]	train-mlogloss:1.51798	validation-mlogloss:1.55949
[154]	train-mlogloss:1.51566	validation-mlogloss:1.55724
[155]	train-mlogloss:1.51337	validation-mlogloss:1.55503
[156]	train-mlogloss:1.51094	validation-mlogloss:1.55277
[157]	train-mlogloss:1.50873	validation-mlogloss:1.55065
[158]	train-mlogloss:1.50621	validation-mlogloss:1.54851
[159]	train-mlogloss:1.50399	validation-mlogloss:1.54643
[160]	train-mlogloss:1.50183	validation-mlogloss:1.54452
[161]	train-mlogloss:1.49952	validation-mlogloss:1.54241
[162]	train-mlogloss:1.49713	validation-mlogloss:1.54023
[163]	train-mlogloss:1.49498	validation-mlogloss:1.53795
[164]	train-mlogloss:1.49271	validation-mlogloss:1.53588
[165]	train-mlogloss:1.49041	validation-mlogloss:1.53373
[166]	train-mlogloss:1.48822	validation-mlogloss:1.53179
[167]	train-mlogloss:1.48611	validation-mlogloss:1.52987
[168]	train-mlogloss:1.48405	validation-mlogloss:1.52789
[169]	train-mlogloss:1.48193	validation-mlogloss:1.52585
[170]	train-mlogloss:1.47989	validation-mlogloss:1.52406
[171]	train-mlogloss:1.47796	validation-mlogloss:1.52237
[172]	train-mlogloss:1.47587	validation-mlogloss:1.52059
[173]	train-mlogloss:1.47389	validation-mlogloss:1.51881
[174]	train-mlogloss:1.47183	validation-mlogloss:1.51679
[175]	train-mlogloss:1.46986	validation-mlogloss:1.51498
[176]	train-mlogloss:1.46790	validation-mlogloss:1.51305
[177]	train-mlogloss:1.46595	validation-mlogloss:1.51121
[178]	train-mlogloss:1.46431	validation-mlogloss:1.50965
[179]	train-mlogloss:1.46245	validation-mlogloss:1.50792
[180]	train-mlogloss:1.46047	validation-mlogloss:1.50605
[181]	train-mlogloss:1.45860	validation-mlogloss:1.50451
[182]	train-mlogloss:1.45666	validation-mlogloss:1.50282
[183]	train-mlogloss:1.45488	validation-mlogloss:1.50131
[184]	train-mlogloss:1.45311	validation-mlogloss:1.49951
[185]	train-mlogloss:1.45109	validation-mlogloss:1.49782
[186]	train-mlogloss:1.44946	validation-mlogloss:1.49649
[187]	train-mlogloss:1.44760	validation-mlogloss:1.49472
[188]	train-mlogloss:1.44586	validation-mlogloss:1.49308
[189]	train-mlogloss:1.44414	validation-mlogloss:1.49142
[190]	train-mlogloss:1.44243	validation-mlogloss:1.48980
[191]	train-mlogloss:1.44070	validation-mlogloss:1.48838
[192]	train-mlogloss:1.43896	validation-mlogloss:1.48684
[193]	train-mlogloss:1.43724	validation-mlogloss:1.48530
[194]	train-mlogloss:1.43554	validation-mlogloss:1.48398
[195]	train-mlogloss:1.43385	validation-mlogloss:1.48242
[196]	train-mlogloss:1.43239	validation-mlogloss:1.48108
[197]	train-mlogloss:1.43058	validation-mlogloss:1.47959
[198]	train-mlogloss:1.42899	validation-mlogloss:1.47818
[199]	train-mlogloss:1.42737	validation-mlogloss:1.47679
[200]	train-mlogloss:1.42574	validation-mlogloss:1.47536
[201]	train-mlogloss:1.42415	validation-mlogloss:1.47400
[202]	train-mlogloss:1.42259	validation-mlogloss:1.47272
[203]	train-mlogloss:1.42098	validation-mlogloss:1.47145
[204]	train-mlogloss:1.41950	validation-mlogloss:1.47010
[205]	train-mlogloss:1.41787	validation-mlogloss:1.46870
[206]	train-mlogloss:1.41641	validation-mlogloss:1.46751
[207]	train-mlogloss:1.41500	validation-mlogloss:1.46636
[208]	train-mlogloss:1.41364	validation-mlogloss:1.46498
[209]	train-mlogloss:1.41212	validation-mlogloss:1.46368
[210]	train-mlogloss:1.41070	validation-mlogloss:1.46251
[211]	train-mlogloss:1.40931	validation-mlogloss:1.46139
[212]	train-mlogloss:1.40786	validation-mlogloss:1.46024
[213]	train-mlogloss:1.40653	validation-mlogloss:1.45901
[214]	train-mlogloss:1.40513	validation-mlogloss:1.45789
[215]	train-mlogloss:1.40366	validation-mlogloss:1.45678
[216]	train-mlogloss:1.40236	validation-mlogloss:1.45570
[217]	train-mlogloss:1.40091	validation-mlogloss:1.45437
[218]	train-mlogloss:1.39972	validation-mlogloss:1.45324
[219]	train-mlogloss:1.39851	validation-mlogloss:1.45219
[220]	train-mlogloss:1.39730	validation-mlogloss:1.45117
[221]	train-mlogloss:1.39602	validation-mlogloss:1.45027
[222]	train-mlogloss:1.39477	validation-mlogloss:1.44925
[223]	train-mlogloss:1.39350	validation-mlogloss:1.44813
[224]	train-mlogloss:1.39231	validation-mlogloss:1.44709
[225]	train-mlogloss:1.39118	validation-mlogloss:1.44601
[226]	train-mlogloss:1.38983	validation-mlogloss:1.44484
[227]	train-mlogloss:1.38871	validation-mlogloss:1.44394
[228]	train-mlogloss:1.38745	validation-mlogloss:1.44290
[229]	train-mlogloss:1.38614	validation-mlogloss:1.44184
[230]	train-mlogloss:1.38486	validation-mlogloss:1.44080
[231]	train-mlogloss:1.38365	validation-mlogloss:1.43974
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[580]	train-mlogloss:1.25896	validation-mlogloss:1.34353
[581]	train-mlogloss:1.25894	validation-mlogloss:1.34350
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[584]	train-mlogloss:1.25879	validation-mlogloss:1.34336
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[663]	train-mlogloss:1.25519	validation-mlogloss:1.34110
[664]	train-mlogloss:1.25515	validation-mlogloss:1.34104
[665]	train-mlogloss:1.25512	validation-mlogloss:1.34098
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[673]	train-mlogloss:1.25482	validation-mlogloss:1.34084
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[682]	train-mlogloss:1.25442	validation-mlogloss:1.34066
[683]	train-mlogloss:1.25440	validation-mlogloss:1.34065
[684]	train-mlogloss:1.25435	validation-mlogloss:1.34065
[685]	train-mlogloss:1.25432	validation-mlogloss:1.34065
[686]	train-mlogloss:1.25428	validation-mlogloss:1.34061
[687]	train-mlogloss:1.25426	validation-mlogloss:1.34061
[688]	train-mlogloss:1.25425	validation-mlogloss:1.34060
[689]	train-mlogloss:1.25419	validation-mlogloss:1.34057
[690]	train-mlogloss:1.25419	validation-mlogloss:1.34058
[691]	train-mlogloss:1.25416	validation-mlogloss:1.34053
[692]	train-mlogloss:1.25414	validation-mlogloss:1.34049
[693]	train-mlogloss:1.25410	validation-mlogloss:1.34049
[694]	train-mlogloss:1.25402	validation-mlogloss:1.34044
[695]	train-mlogloss:1.25395	validation-mlogloss:1.34043
[696]	train-mlogloss:1.25394	validation-mlogloss:1.34044
[697]	train-mlogloss:1.25393	validation-mlogloss:1.34042
[698]	train-mlogloss:1.25389	validation-mlogloss:1.34039
[699]	train-mlogloss:1.25384	validation-mlogloss:1.34031
[700]	train-mlogloss:1.25381	validation-mlogloss:1.34029
[701]	train-mlogloss:1.25370	validation-mlogloss:1.34015
[702]	train-mlogloss:1.25365	validation-mlogloss:1.34009
[703]	train-mlogloss:1.25363	validation-mlogloss:1.34009
[704]	train-mlogloss:1.25362	validation-mlogloss:1.34009
[705]	train-mlogloss:1.25357	validation-mlogloss:1.34005
[706]	train-mlogloss:1.25347	validation-mlogloss:1.34001
[707]	train-mlogloss:1.25347	validation-mlogloss:1.34002
[708]	train-mlogloss:1.25345	validation-mlogloss:1.33999
[709]	train-mlogloss:1.25338	validation-mlogloss:1.33997
[710]	train-mlogloss:1.25333	validation-mlogloss:1.33994
[711]	train-mlogloss:1.25330	validation-mlogloss:1.33994
[712]	train-mlogloss:1.25328	validation-mlogloss:1.33992
[713]	train-mlogloss:1.25327	validation-mlogloss:1.33991
Saved model to disk.
2025-10-27 11:35:10.395648: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:35:10.408342: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761561310.422273  551604 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761561310.426803  551604 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761561310.438061  551604 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561310.438084  551604 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561310.438087  551604 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561310.438089  551604 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:35:10.441458: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68547	validation-mlogloss:2.68506
[1]	train-mlogloss:2.66278	validation-mlogloss:2.66268
[2]	train-mlogloss:2.64086	validation-mlogloss:2.64082
[3]	train-mlogloss:2.61828	validation-mlogloss:2.61899
[4]	train-mlogloss:2.59647	validation-mlogloss:2.59747
[5]	train-mlogloss:2.57612	validation-mlogloss:2.57771
[6]	train-mlogloss:2.55685	validation-mlogloss:2.55884
[7]	train-mlogloss:2.53719	validation-mlogloss:2.53939
[8]	train-mlogloss:2.51873	validation-mlogloss:2.52117
[9]	train-mlogloss:2.50043	validation-mlogloss:2.50329
[10]	train-mlogloss:2.48128	validation-mlogloss:2.48437
[11]	train-mlogloss:2.46321	validation-mlogloss:2.46658
[12]	train-mlogloss:2.44569	validation-mlogloss:2.44930
[13]	train-mlogloss:2.42847	validation-mlogloss:2.43197
[14]	train-mlogloss:2.41143	validation-mlogloss:2.41536
[15]	train-mlogloss:2.39465	validation-mlogloss:2.39901
[16]	train-mlogloss:2.37830	validation-mlogloss:2.38388
[17]	train-mlogloss:2.36277	validation-mlogloss:2.36904
[18]	train-mlogloss:2.34733	validation-mlogloss:2.35451
[19]	train-mlogloss:2.33306	validation-mlogloss:2.34058
[20]	train-mlogloss:2.31876	validation-mlogloss:2.32638
[21]	train-mlogloss:2.30506	validation-mlogloss:2.31291
[22]	train-mlogloss:2.29072	validation-mlogloss:2.29929
[23]	train-mlogloss:2.27736	validation-mlogloss:2.28659
[24]	train-mlogloss:2.26395	validation-mlogloss:2.27381
[25]	train-mlogloss:2.25072	validation-mlogloss:2.26116
[26]	train-mlogloss:2.23770	validation-mlogloss:2.24915
[27]	train-mlogloss:2.22494	validation-mlogloss:2.23657
[28]	train-mlogloss:2.21221	validation-mlogloss:2.22434
[29]	train-mlogloss:2.19954	validation-mlogloss:2.21199
[30]	train-mlogloss:2.18728	validation-mlogloss:2.20051
[31]	train-mlogloss:2.17545	validation-mlogloss:2.18887
[32]	train-mlogloss:2.16381	validation-mlogloss:2.17739
[33]	train-mlogloss:2.15244	validation-mlogloss:2.16642
[34]	train-mlogloss:2.14137	validation-mlogloss:2.15607
[35]	train-mlogloss:2.13044	validation-mlogloss:2.14526
[36]	train-mlogloss:2.11958	validation-mlogloss:2.13446
[37]	train-mlogloss:2.10930	validation-mlogloss:2.12475
[38]	train-mlogloss:2.09904	validation-mlogloss:2.11482
[39]	train-mlogloss:2.08897	validation-mlogloss:2.10523
[40]	train-mlogloss:2.07861	validation-mlogloss:2.09495
[41]	train-mlogloss:2.06840	validation-mlogloss:2.08516
[42]	train-mlogloss:2.05895	validation-mlogloss:2.07636
[43]	train-mlogloss:2.04953	validation-mlogloss:2.06717
[44]	train-mlogloss:2.03988	validation-mlogloss:2.05793
[45]	train-mlogloss:2.03092	validation-mlogloss:2.04940
[46]	train-mlogloss:2.02175	validation-mlogloss:2.04031
[47]	train-mlogloss:2.01304	validation-mlogloss:2.03179
[48]	train-mlogloss:2.00423	validation-mlogloss:2.02324
[49]	train-mlogloss:1.99552	validation-mlogloss:2.01496
[50]	train-mlogloss:1.98687	validation-mlogloss:2.00665
[51]	train-mlogloss:1.97850	validation-mlogloss:1.99856
[52]	train-mlogloss:1.97023	validation-mlogloss:1.99074
[53]	train-mlogloss:1.96209	validation-mlogloss:1.98280
[54]	train-mlogloss:1.95409	validation-mlogloss:1.97512
[55]	train-mlogloss:1.94623	validation-mlogloss:1.96767
[56]	train-mlogloss:1.93880	validation-mlogloss:1.96039
[57]	train-mlogloss:1.93101	validation-mlogloss:1.95279
[58]	train-mlogloss:1.92333	validation-mlogloss:1.94561
[59]	train-mlogloss:1.91590	validation-mlogloss:1.93832
[60]	train-mlogloss:1.90867	validation-mlogloss:1.93123
[61]	train-mlogloss:1.90169	validation-mlogloss:1.92430
[62]	train-mlogloss:1.89479	validation-mlogloss:1.91776
[63]	train-mlogloss:1.88787	validation-mlogloss:1.91085
[64]	train-mlogloss:1.88114	validation-mlogloss:1.90413
[65]	train-mlogloss:1.87435	validation-mlogloss:1.89753
[66]	train-mlogloss:1.86785	validation-mlogloss:1.89124
[67]	train-mlogloss:1.86132	validation-mlogloss:1.88496
[68]	train-mlogloss:1.85505	validation-mlogloss:1.87885
[69]	train-mlogloss:1.84891	validation-mlogloss:1.87275
[70]	train-mlogloss:1.84241	validation-mlogloss:1.86639
[71]	train-mlogloss:1.83631	validation-mlogloss:1.86062
[72]	train-mlogloss:1.83010	validation-mlogloss:1.85444
[73]	train-mlogloss:1.82411	validation-mlogloss:1.84878
[74]	train-mlogloss:1.81830	validation-mlogloss:1.84331
[75]	train-mlogloss:1.81236	validation-mlogloss:1.83732
[76]	train-mlogloss:1.80668	validation-mlogloss:1.83163
[77]	train-mlogloss:1.80099	validation-mlogloss:1.82602
[78]	train-mlogloss:1.79535	validation-mlogloss:1.82043
[79]	train-mlogloss:1.78960	validation-mlogloss:1.81502
[80]	train-mlogloss:1.78407	validation-mlogloss:1.81000
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[82]	train-mlogloss:1.77294	validation-mlogloss:1.79893
[83]	train-mlogloss:1.76771	validation-mlogloss:1.79379
[84]	train-mlogloss:1.76271	validation-mlogloss:1.78874
[85]	train-mlogloss:1.75737	validation-mlogloss:1.78371
[86]	train-mlogloss:1.75221	validation-mlogloss:1.77881
[87]	train-mlogloss:1.74723	validation-mlogloss:1.77405
[88]	train-mlogloss:1.74244	validation-mlogloss:1.76942
[89]	train-mlogloss:1.73749	validation-mlogloss:1.76443
[90]	train-mlogloss:1.73274	validation-mlogloss:1.75985
[91]	train-mlogloss:1.72780	validation-mlogloss:1.75496
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[93]	train-mlogloss:1.71839	validation-mlogloss:1.74592
[94]	train-mlogloss:1.71375	validation-mlogloss:1.74162
[95]	train-mlogloss:1.70925	validation-mlogloss:1.73738
[96]	train-mlogloss:1.70489	validation-mlogloss:1.73303
[97]	train-mlogloss:1.70038	validation-mlogloss:1.72867
[98]	train-mlogloss:1.69601	validation-mlogloss:1.72438
[99]	train-mlogloss:1.69178	validation-mlogloss:1.72049
[100]	train-mlogloss:1.68731	validation-mlogloss:1.71609
[101]	train-mlogloss:1.68299	validation-mlogloss:1.71193
[102]	train-mlogloss:1.67885	validation-mlogloss:1.70820
[103]	train-mlogloss:1.67470	validation-mlogloss:1.70409
[104]	train-mlogloss:1.67067	validation-mlogloss:1.70032
[105]	train-mlogloss:1.66647	validation-mlogloss:1.69644
[106]	train-mlogloss:1.66260	validation-mlogloss:1.69274
[107]	train-mlogloss:1.65845	validation-mlogloss:1.68890
[108]	train-mlogloss:1.65453	validation-mlogloss:1.68520
[109]	train-mlogloss:1.65054	validation-mlogloss:1.68133
[110]	train-mlogloss:1.64682	validation-mlogloss:1.67772
[111]	train-mlogloss:1.64310	validation-mlogloss:1.67448
[112]	train-mlogloss:1.63917	validation-mlogloss:1.67082
[113]	train-mlogloss:1.63549	validation-mlogloss:1.66735
[114]	train-mlogloss:1.63165	validation-mlogloss:1.66377
[115]	train-mlogloss:1.62803	validation-mlogloss:1.66014
[116]	train-mlogloss:1.62453	validation-mlogloss:1.65684
[117]	train-mlogloss:1.62096	validation-mlogloss:1.65350
[118]	train-mlogloss:1.61757	validation-mlogloss:1.65042
[119]	train-mlogloss:1.61407	validation-mlogloss:1.64724
[120]	train-mlogloss:1.61070	validation-mlogloss:1.64405
[121]	train-mlogloss:1.60747	validation-mlogloss:1.64103
[122]	train-mlogloss:1.60413	validation-mlogloss:1.63768
[123]	train-mlogloss:1.60088	validation-mlogloss:1.63470
[124]	train-mlogloss:1.59752	validation-mlogloss:1.63155
[125]	train-mlogloss:1.59433	validation-mlogloss:1.62858
[126]	train-mlogloss:1.59107	validation-mlogloss:1.62551
[127]	train-mlogloss:1.58802	validation-mlogloss:1.62278
[128]	train-mlogloss:1.58492	validation-mlogloss:1.61957
[129]	train-mlogloss:1.58180	validation-mlogloss:1.61673
[130]	train-mlogloss:1.57887	validation-mlogloss:1.61389
[131]	train-mlogloss:1.57581	validation-mlogloss:1.61110
[132]	train-mlogloss:1.57270	validation-mlogloss:1.60844
[133]	train-mlogloss:1.56976	validation-mlogloss:1.60561
[134]	train-mlogloss:1.56678	validation-mlogloss:1.60295
[135]	train-mlogloss:1.56400	validation-mlogloss:1.60013
[136]	train-mlogloss:1.56115	validation-mlogloss:1.59744
[137]	train-mlogloss:1.55829	validation-mlogloss:1.59490
[138]	train-mlogloss:1.55539	validation-mlogloss:1.59230
[139]	train-mlogloss:1.55260	validation-mlogloss:1.58971
[140]	train-mlogloss:1.54970	validation-mlogloss:1.58705
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[563]	train-mlogloss:1.25762	validation-mlogloss:1.34412
[564]	train-mlogloss:1.25747	validation-mlogloss:1.34402
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[566]	train-mlogloss:1.25736	validation-mlogloss:1.34392
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[569]	train-mlogloss:1.25714	validation-mlogloss:1.34382
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[571]	train-mlogloss:1.25709	validation-mlogloss:1.34378
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[575]	train-mlogloss:1.25683	validation-mlogloss:1.34364
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[578]	train-mlogloss:1.25668	validation-mlogloss:1.34349
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[660]	train-mlogloss:1.25358	validation-mlogloss:1.34184
[661]	train-mlogloss:1.25355	validation-mlogloss:1.34180
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[663]	train-mlogloss:1.25338	validation-mlogloss:1.34171
[664]	train-mlogloss:1.25337	validation-mlogloss:1.34169
[665]	train-mlogloss:1.25334	validation-mlogloss:1.34165
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[678]	train-mlogloss:1.25302	validation-mlogloss:1.34155
[679]	train-mlogloss:1.25301	validation-mlogloss:1.34156
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[681]	train-mlogloss:1.25295	validation-mlogloss:1.34149
[682]	train-mlogloss:1.25290	validation-mlogloss:1.34150
[683]	train-mlogloss:1.25283	validation-mlogloss:1.34139
[684]	train-mlogloss:1.25283	validation-mlogloss:1.34139
[685]	train-mlogloss:1.25277	validation-mlogloss:1.34141
[686]	train-mlogloss:1.25274	validation-mlogloss:1.34137
[687]	train-mlogloss:1.25257	validation-mlogloss:1.34129
[688]	train-mlogloss:1.25247	validation-mlogloss:1.34119
[689]	train-mlogloss:1.25244	validation-mlogloss:1.34119
[690]	train-mlogloss:1.25243	validation-mlogloss:1.34118
[691]	train-mlogloss:1.25242	validation-mlogloss:1.34118
[692]	train-mlogloss:1.25239	validation-mlogloss:1.34117
[693]	train-mlogloss:1.25237	validation-mlogloss:1.34117
[694]	train-mlogloss:1.25229	validation-mlogloss:1.34107
[695]	train-mlogloss:1.25221	validation-mlogloss:1.34101
[696]	train-mlogloss:1.25220	validation-mlogloss:1.34098
[697]	train-mlogloss:1.25217	validation-mlogloss:1.34097
[698]	train-mlogloss:1.25212	validation-mlogloss:1.34091
[699]	train-mlogloss:1.25209	validation-mlogloss:1.34086
[700]	train-mlogloss:1.25200	validation-mlogloss:1.34077
[701]	train-mlogloss:1.25200	validation-mlogloss:1.34077
[702]	train-mlogloss:1.25200	validation-mlogloss:1.34077
[703]	train-mlogloss:1.25195	validation-mlogloss:1.34071
[704]	train-mlogloss:1.25190	validation-mlogloss:1.34067
[705]	train-mlogloss:1.25189	validation-mlogloss:1.34064
[706]	train-mlogloss:1.25185	validation-mlogloss:1.34061
[707]	train-mlogloss:1.25178	validation-mlogloss:1.34054
[708]	train-mlogloss:1.25173	validation-mlogloss:1.34049
[709]	train-mlogloss:1.25173	validation-mlogloss:1.34049
[710]	train-mlogloss:1.25169	validation-mlogloss:1.34047
[711]	train-mlogloss:1.25169	validation-mlogloss:1.34046
[712]	train-mlogloss:1.25168	validation-mlogloss:1.34047
[713]	train-mlogloss:1.25168	validation-mlogloss:1.34047
Saved model to disk.
2025-10-27 11:35:57.588598: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:35:57.601550: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761561357.615938  552524 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761561357.620408  552524 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761561357.631363  552524 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561357.631390  552524 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561357.631394  552524 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561357.631396  552524 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:35:57.634811: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68333	validation-mlogloss:2.68390
[1]	train-mlogloss:2.65903	validation-mlogloss:2.66007
[2]	train-mlogloss:2.63616	validation-mlogloss:2.63816
[3]	train-mlogloss:2.61559	validation-mlogloss:2.61822
[4]	train-mlogloss:2.59490	validation-mlogloss:2.59858
[5]	train-mlogloss:2.57445	validation-mlogloss:2.57804
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[609]	train-mlogloss:1.25691	validation-mlogloss:1.34399
[610]	train-mlogloss:1.25683	validation-mlogloss:1.34392
[611]	train-mlogloss:1.25683	validation-mlogloss:1.34392
[612]	train-mlogloss:1.25674	validation-mlogloss:1.34389
[613]	train-mlogloss:1.25669	validation-mlogloss:1.34385
[614]	train-mlogloss:1.25667	validation-mlogloss:1.34385
[615]	train-mlogloss:1.25664	validation-mlogloss:1.34381
[616]	train-mlogloss:1.25655	validation-mlogloss:1.34374
[617]	train-mlogloss:1.25654	validation-mlogloss:1.34373
[618]	train-mlogloss:1.25646	validation-mlogloss:1.34369
[619]	train-mlogloss:1.25640	validation-mlogloss:1.34364
[620]	train-mlogloss:1.25636	validation-mlogloss:1.34363
[621]	train-mlogloss:1.25628	validation-mlogloss:1.34356
[622]	train-mlogloss:1.25624	validation-mlogloss:1.34352
[623]	train-mlogloss:1.25620	validation-mlogloss:1.34347
[624]	train-mlogloss:1.25618	validation-mlogloss:1.34347
[625]	train-mlogloss:1.25612	validation-mlogloss:1.34342
[626]	train-mlogloss:1.25612	validation-mlogloss:1.34342
[627]	train-mlogloss:1.25612	validation-mlogloss:1.34342
[628]	train-mlogloss:1.25607	validation-mlogloss:1.34341
[629]	train-mlogloss:1.25607	validation-mlogloss:1.34341
[630]	train-mlogloss:1.25601	validation-mlogloss:1.34336
[631]	train-mlogloss:1.25594	validation-mlogloss:1.34332
[632]	train-mlogloss:1.25577	validation-mlogloss:1.34330
[633]	train-mlogloss:1.25570	validation-mlogloss:1.34331
[634]	train-mlogloss:1.25569	validation-mlogloss:1.34331
[635]	train-mlogloss:1.25561	validation-mlogloss:1.34334
[636]	train-mlogloss:1.25558	validation-mlogloss:1.34332
[637]	train-mlogloss:1.25548	validation-mlogloss:1.34327
[638]	train-mlogloss:1.25545	validation-mlogloss:1.34326
[639]	train-mlogloss:1.25545	validation-mlogloss:1.34326
[640]	train-mlogloss:1.25543	validation-mlogloss:1.34324
[641]	train-mlogloss:1.25542	validation-mlogloss:1.34325
[642]	train-mlogloss:1.25541	validation-mlogloss:1.34324
[643]	train-mlogloss:1.25540	validation-mlogloss:1.34324
[644]	train-mlogloss:1.25537	validation-mlogloss:1.34322
[645]	train-mlogloss:1.25531	validation-mlogloss:1.34319
[646]	train-mlogloss:1.25517	validation-mlogloss:1.34308
[647]	train-mlogloss:1.25516	validation-mlogloss:1.34307
[648]	train-mlogloss:1.25510	validation-mlogloss:1.34306
[649]	train-mlogloss:1.25506	validation-mlogloss:1.34302
[650]	train-mlogloss:1.25499	validation-mlogloss:1.34295
[651]	train-mlogloss:1.25497	validation-mlogloss:1.34296
[652]	train-mlogloss:1.25492	validation-mlogloss:1.34293
[653]	train-mlogloss:1.25492	validation-mlogloss:1.34293
[654]	train-mlogloss:1.25486	validation-mlogloss:1.34292
[655]	train-mlogloss:1.25479	validation-mlogloss:1.34285
[656]	train-mlogloss:1.25479	validation-mlogloss:1.34285
[657]	train-mlogloss:1.25472	validation-mlogloss:1.34280
[658]	train-mlogloss:1.25471	validation-mlogloss:1.34278
[659]	train-mlogloss:1.25471	validation-mlogloss:1.34278
[660]	train-mlogloss:1.25469	validation-mlogloss:1.34276
[661]	train-mlogloss:1.25464	validation-mlogloss:1.34271
[662]	train-mlogloss:1.25461	validation-mlogloss:1.34270
[663]	train-mlogloss:1.25455	validation-mlogloss:1.34269
[664]	train-mlogloss:1.25448	validation-mlogloss:1.34265
[665]	train-mlogloss:1.25441	validation-mlogloss:1.34259
[666]	train-mlogloss:1.25431	validation-mlogloss:1.34253
[667]	train-mlogloss:1.25426	validation-mlogloss:1.34253
[668]	train-mlogloss:1.25426	validation-mlogloss:1.34253
[669]	train-mlogloss:1.25419	validation-mlogloss:1.34249
[670]	train-mlogloss:1.25411	validation-mlogloss:1.34242
[671]	train-mlogloss:1.25404	validation-mlogloss:1.34238
[672]	train-mlogloss:1.25401	validation-mlogloss:1.34235
[673]	train-mlogloss:1.25401	validation-mlogloss:1.34235
[674]	train-mlogloss:1.25396	validation-mlogloss:1.34234
[675]	train-mlogloss:1.25396	validation-mlogloss:1.34234
[676]	train-mlogloss:1.25396	validation-mlogloss:1.34234
[677]	train-mlogloss:1.25387	validation-mlogloss:1.34225
[678]	train-mlogloss:1.25383	validation-mlogloss:1.34224
[679]	train-mlogloss:1.25375	validation-mlogloss:1.34221
[680]	train-mlogloss:1.25373	validation-mlogloss:1.34220
[681]	train-mlogloss:1.25366	validation-mlogloss:1.34211
[682]	train-mlogloss:1.25358	validation-mlogloss:1.34209
[683]	train-mlogloss:1.25356	validation-mlogloss:1.34206
[684]	train-mlogloss:1.25353	validation-mlogloss:1.34205
[685]	train-mlogloss:1.25353	validation-mlogloss:1.34205
[686]	train-mlogloss:1.25346	validation-mlogloss:1.34201
[687]	train-mlogloss:1.25337	validation-mlogloss:1.34191
[688]	train-mlogloss:1.25336	validation-mlogloss:1.34189
[689]	train-mlogloss:1.25324	validation-mlogloss:1.34177
[690]	train-mlogloss:1.25324	validation-mlogloss:1.34177
[691]	train-mlogloss:1.25320	validation-mlogloss:1.34173
[692]	train-mlogloss:1.25320	validation-mlogloss:1.34173
[693]	train-mlogloss:1.25318	validation-mlogloss:1.34173
[694]	train-mlogloss:1.25310	validation-mlogloss:1.34171
[695]	train-mlogloss:1.25304	validation-mlogloss:1.34163
[696]	train-mlogloss:1.25303	validation-mlogloss:1.34164
[697]	train-mlogloss:1.25303	validation-mlogloss:1.34164
[698]	train-mlogloss:1.25296	validation-mlogloss:1.34161
[699]	train-mlogloss:1.25292	validation-mlogloss:1.34157
[700]	train-mlogloss:1.25284	validation-mlogloss:1.34152
[701]	train-mlogloss:1.25278	validation-mlogloss:1.34147
[702]	train-mlogloss:1.25278	validation-mlogloss:1.34147
[703]	train-mlogloss:1.25276	validation-mlogloss:1.34147
[704]	train-mlogloss:1.25275	validation-mlogloss:1.34148
[705]	train-mlogloss:1.25267	validation-mlogloss:1.34143
[706]	train-mlogloss:1.25261	validation-mlogloss:1.34136
[707]	train-mlogloss:1.25256	validation-mlogloss:1.34131
[708]	train-mlogloss:1.25254	validation-mlogloss:1.34130
[709]	train-mlogloss:1.25248	validation-mlogloss:1.34129
[710]	train-mlogloss:1.25245	validation-mlogloss:1.34128
[711]	train-mlogloss:1.25245	validation-mlogloss:1.34128
[712]	train-mlogloss:1.25242	validation-mlogloss:1.34121
[713]	train-mlogloss:1.25242	validation-mlogloss:1.34121
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.81 [%]
Global accuracy score (test) = 50.64 [%]
Global F1 score (train) = 62.84 [%]
Global F1 score (test) = 50.84 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.39      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.47      0.42      0.44       184
       CAMINAR USUAL SPEED       0.28      0.22      0.25       184
            CAMINAR ZIGZAG       0.58      0.55      0.57       184
          DE PIE BARRIENDO       0.52      0.48      0.50       184
   DE PIE DOBLANDO TOALLAS       0.45      0.47      0.46       184
    DE PIE MOVIENDO LIBROS       0.49      0.46      0.47       184
          DE PIE USANDO PC       0.62      0.67      0.64       184
        FASE REPOSO CON K5       0.54      0.79      0.64       184
INCREMENTAL CICLOERGOMETRO       0.88      0.61      0.72       184
           SENTADO LEYENDO       0.35      0.41      0.38       184
         SENTADO USANDO PC       0.41      0.26      0.32       184
      SENTADO VIENDO LA TV       0.46      0.41      0.43       184
   SUBIR Y BAJAR ESCALERAS       0.55      0.68      0.61       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.51      2737


Accuracy capturado en la ejecución 25: 50.64 [%]
F1-score capturado en la ejecución 25: 50.84 [%]

=== EJECUCIÓN 26 ===

--- TRAIN (ejecución 26) ---

--- TEST (ejecución 26) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.74 [%]
Global accuracy score (test) = 50.16 [%]
Global F1 score (train) = 62.83 [%]
Global F1 score (test) = 50.3 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.29      0.40      0.34       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.40      0.42       184
       CAMINAR USUAL SPEED       0.24      0.18      0.21       184
            CAMINAR ZIGZAG       0.60      0.56      0.58       184
          DE PIE BARRIENDO       0.54      0.49      0.52       184
   DE PIE DOBLANDO TOALLAS       0.43      0.45      0.44       184
    DE PIE MOVIENDO LIBROS       0.49      0.47      0.48       184
          DE PIE USANDO PC       0.62      0.66      0.64       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.88      0.63      0.73       184
           SENTADO LEYENDO       0.32      0.39      0.35       184
         SENTADO USANDO PC       0.38      0.26      0.31       184
      SENTADO VIENDO LA TV       0.46      0.39      0.42       184
   SUBIR Y BAJAR ESCALERAS       0.52      0.68      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.51      0.50      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 26: 50.16 [%]
F1-score capturado en la ejecución 26: 50.3 [%]

=== EJECUCIÓN 27 ===

--- TRAIN (ejecución 27) ---

--- TEST (ejecución 27) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.81 [%]
Global accuracy score (test) = 50.75 [%]
Global F1 score (train) = 62.87 [%]
Global F1 score (test) = 50.92 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.38      0.32       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.40      0.42       184
       CAMINAR USUAL SPEED       0.30      0.23      0.26       184
            CAMINAR ZIGZAG       0.59      0.53      0.56       184
          DE PIE BARRIENDO       0.55      0.51      0.53       184
   DE PIE DOBLANDO TOALLAS       0.43      0.45      0.44       184
    DE PIE MOVIENDO LIBROS       0.49      0.47      0.48       184
          DE PIE USANDO PC       0.60      0.66      0.63       184
        FASE REPOSO CON K5       0.55      0.78      0.65       184
INCREMENTAL CICLOERGOMETRO       0.89      0.64      0.74       184
           SENTADO LEYENDO       0.37      0.46      0.41       184
         SENTADO USANDO PC       0.41      0.27      0.32       184
      SENTADO VIENDO LA TV       0.47      0.39      0.42       184
   SUBIR Y BAJAR ESCALERAS       0.52      0.68      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.51      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.51      0.51      2737


Accuracy capturado en la ejecución 27: 50.75 [%]
F1-score capturado en la ejecución 27: 50.92 [%]

=== EJECUCIÓN 28 ===

--- TRAIN (ejecución 28) ---

--- TEST (ejecución 28) ---
2025-10-27 11:36:44.934433: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:36:44.947048: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761561404.960732  553442 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761561404.965097  553442 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761561404.976144  553442 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561404.976169  553442 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561404.976172  553442 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561404.976174  553442 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:36:44.979625: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68395	validation-mlogloss:2.68467
[1]	train-mlogloss:2.66133	validation-mlogloss:2.66229
[2]	train-mlogloss:2.63911	validation-mlogloss:2.64085
[3]	train-mlogloss:2.61631	validation-mlogloss:2.61872
[4]	train-mlogloss:2.59636	validation-mlogloss:2.59907
[5]	train-mlogloss:2.57560	validation-mlogloss:2.57877
[6]	train-mlogloss:2.55592	validation-mlogloss:2.55919
[7]	train-mlogloss:2.53581	validation-mlogloss:2.53895
[8]	train-mlogloss:2.51678	validation-mlogloss:2.51982
[9]	train-mlogloss:2.49745	validation-mlogloss:2.50086
[10]	train-mlogloss:2.47891	validation-mlogloss:2.48243
[11]	train-mlogloss:2.46136	validation-mlogloss:2.46460
[12]	train-mlogloss:2.44549	validation-mlogloss:2.44916
[13]	train-mlogloss:2.42906	validation-mlogloss:2.43305
[14]	train-mlogloss:2.41299	validation-mlogloss:2.41705
[15]	train-mlogloss:2.39640	validation-mlogloss:2.40127
[16]	train-mlogloss:2.38062	validation-mlogloss:2.38544
[17]	train-mlogloss:2.36476	validation-mlogloss:2.36960
[18]	train-mlogloss:2.34939	validation-mlogloss:2.35514
[19]	train-mlogloss:2.33437	validation-mlogloss:2.34069
[20]	train-mlogloss:2.31987	validation-mlogloss:2.32660
[21]	train-mlogloss:2.30514	validation-mlogloss:2.31245
[22]	train-mlogloss:2.29087	validation-mlogloss:2.29838
[23]	train-mlogloss:2.27717	validation-mlogloss:2.28541
[24]	train-mlogloss:2.26360	validation-mlogloss:2.27227
[25]	train-mlogloss:2.25076	validation-mlogloss:2.25954
[26]	train-mlogloss:2.23785	validation-mlogloss:2.24731
[27]	train-mlogloss:2.22566	validation-mlogloss:2.23498
[28]	train-mlogloss:2.21294	validation-mlogloss:2.22231
[29]	train-mlogloss:2.20082	validation-mlogloss:2.21068
[30]	train-mlogloss:2.18883	validation-mlogloss:2.19916
[31]	train-mlogloss:2.17718	validation-mlogloss:2.18848
[32]	train-mlogloss:2.16541	validation-mlogloss:2.17715
[33]	train-mlogloss:2.15395	validation-mlogloss:2.16620
[34]	train-mlogloss:2.14301	validation-mlogloss:2.15550
[35]	train-mlogloss:2.13212	validation-mlogloss:2.14463
[36]	train-mlogloss:2.12136	validation-mlogloss:2.13473
[37]	train-mlogloss:2.11081	validation-mlogloss:2.12476
[38]	train-mlogloss:2.10026	validation-mlogloss:2.11478
[39]	train-mlogloss:2.09003	validation-mlogloss:2.10471
[40]	train-mlogloss:2.08005	validation-mlogloss:2.09499
[41]	train-mlogloss:2.07019	validation-mlogloss:2.08537
[42]	train-mlogloss:2.06042	validation-mlogloss:2.07593
[43]	train-mlogloss:2.05105	validation-mlogloss:2.06667
[44]	train-mlogloss:2.04156	validation-mlogloss:2.05739
[45]	train-mlogloss:2.03237	validation-mlogloss:2.04822
[46]	train-mlogloss:2.02345	validation-mlogloss:2.03933
[47]	train-mlogloss:2.01449	validation-mlogloss:2.03039
[48]	train-mlogloss:2.00556	validation-mlogloss:2.02200
[49]	train-mlogloss:1.99713	validation-mlogloss:2.01394
[50]	train-mlogloss:1.98885	validation-mlogloss:2.00565
[51]	train-mlogloss:1.98048	validation-mlogloss:1.99755
[52]	train-mlogloss:1.97235	validation-mlogloss:1.98975
[53]	train-mlogloss:1.96424	validation-mlogloss:1.98191
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[656]	train-mlogloss:1.25490	validation-mlogloss:1.33884
[657]	train-mlogloss:1.25487	validation-mlogloss:1.33882
[658]	train-mlogloss:1.25486	validation-mlogloss:1.33881
[659]	train-mlogloss:1.25483	validation-mlogloss:1.33877
[660]	train-mlogloss:1.25477	validation-mlogloss:1.33880
[661]	train-mlogloss:1.25473	validation-mlogloss:1.33877
[662]	train-mlogloss:1.25471	validation-mlogloss:1.33877
[663]	train-mlogloss:1.25463	validation-mlogloss:1.33875
[664]	train-mlogloss:1.25458	validation-mlogloss:1.33870
[665]	train-mlogloss:1.25457	validation-mlogloss:1.33869
[666]	train-mlogloss:1.25454	validation-mlogloss:1.33866
[667]	train-mlogloss:1.25454	validation-mlogloss:1.33867
[668]	train-mlogloss:1.25445	validation-mlogloss:1.33864
[669]	train-mlogloss:1.25434	validation-mlogloss:1.33851
[670]	train-mlogloss:1.25431	validation-mlogloss:1.33850
[671]	train-mlogloss:1.25418	validation-mlogloss:1.33842
[672]	train-mlogloss:1.25416	validation-mlogloss:1.33842
[673]	train-mlogloss:1.25413	validation-mlogloss:1.33840
[674]	train-mlogloss:1.25412	validation-mlogloss:1.33838
[675]	train-mlogloss:1.25410	validation-mlogloss:1.33837
[676]	train-mlogloss:1.25407	validation-mlogloss:1.33839
[677]	train-mlogloss:1.25406	validation-mlogloss:1.33836
[678]	train-mlogloss:1.25402	validation-mlogloss:1.33835
[679]	train-mlogloss:1.25400	validation-mlogloss:1.33836
[680]	train-mlogloss:1.25395	validation-mlogloss:1.33831
[681]	train-mlogloss:1.25389	validation-mlogloss:1.33831
[682]	train-mlogloss:1.25386	validation-mlogloss:1.33828
[683]	train-mlogloss:1.25377	validation-mlogloss:1.33824
[684]	train-mlogloss:1.25373	validation-mlogloss:1.33820
[685]	train-mlogloss:1.25371	validation-mlogloss:1.33821
[686]	train-mlogloss:1.25369	validation-mlogloss:1.33818
[687]	train-mlogloss:1.25364	validation-mlogloss:1.33813
[688]	train-mlogloss:1.25364	validation-mlogloss:1.33813
[689]	train-mlogloss:1.25356	validation-mlogloss:1.33805
[690]	train-mlogloss:1.25356	validation-mlogloss:1.33805
[691]	train-mlogloss:1.25353	validation-mlogloss:1.33804
[692]	train-mlogloss:1.25352	validation-mlogloss:1.33803
[693]	train-mlogloss:1.25348	validation-mlogloss:1.33802
[694]	train-mlogloss:1.25347	validation-mlogloss:1.33801
[695]	train-mlogloss:1.25345	validation-mlogloss:1.33799
[696]	train-mlogloss:1.25341	validation-mlogloss:1.33796
[697]	train-mlogloss:1.25341	validation-mlogloss:1.33796
[698]	train-mlogloss:1.25336	validation-mlogloss:1.33789
[699]	train-mlogloss:1.25336	validation-mlogloss:1.33789
[700]	train-mlogloss:1.25318	validation-mlogloss:1.33783
[701]	train-mlogloss:1.25317	validation-mlogloss:1.33780
[702]	train-mlogloss:1.25317	validation-mlogloss:1.33780
[703]	train-mlogloss:1.25312	validation-mlogloss:1.33774
[704]	train-mlogloss:1.25309	validation-mlogloss:1.33773
[705]	train-mlogloss:1.25307	validation-mlogloss:1.33770
[706]	train-mlogloss:1.25306	validation-mlogloss:1.33771
[707]	train-mlogloss:1.25306	validation-mlogloss:1.33771
[708]	train-mlogloss:1.25302	validation-mlogloss:1.33768
[709]	train-mlogloss:1.25298	validation-mlogloss:1.33763
[710]	train-mlogloss:1.25295	validation-mlogloss:1.33761
[711]	train-mlogloss:1.25292	validation-mlogloss:1.33758
[712]	train-mlogloss:1.25287	validation-mlogloss:1.33756
[713]	train-mlogloss:1.25286	validation-mlogloss:1.33755
Saved model to disk.
2025-10-27 11:37:32.620834: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-10-27 11:37:32.633381: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1761561452.647015  554405 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761561452.651358  554405 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761561452.662384  554405 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561452.662406  554405 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561452.662409  554405 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761561452.662412  554405 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 11:37:32.665780: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.68379	validation-mlogloss:2.68412
[1]	train-mlogloss:2.66101	validation-mlogloss:2.66216
[2]	train-mlogloss:2.63803	validation-mlogloss:2.63961
[3]	train-mlogloss:2.61636	validation-mlogloss:2.61815
[4]	train-mlogloss:2.59555	validation-mlogloss:2.59804
[5]	train-mlogloss:2.57490	validation-mlogloss:2.57778
[6]	train-mlogloss:2.55524	validation-mlogloss:2.55908
[7]	train-mlogloss:2.53530	validation-mlogloss:2.53967
[8]	train-mlogloss:2.51553	validation-mlogloss:2.52003
[9]	train-mlogloss:2.49740	validation-mlogloss:2.50218
[10]	train-mlogloss:2.47915	validation-mlogloss:2.48436
[11]	train-mlogloss:2.46180	validation-mlogloss:2.46690
[12]	train-mlogloss:2.44573	validation-mlogloss:2.45088
[13]	train-mlogloss:2.42831	validation-mlogloss:2.43484
[14]	train-mlogloss:2.41152	validation-mlogloss:2.41832
[15]	train-mlogloss:2.39490	validation-mlogloss:2.40190
[16]	train-mlogloss:2.37889	validation-mlogloss:2.38636
[17]	train-mlogloss:2.36334	validation-mlogloss:2.37100
[18]	train-mlogloss:2.34781	validation-mlogloss:2.35597
[19]	train-mlogloss:2.33323	validation-mlogloss:2.34164
[20]	train-mlogloss:2.31896	validation-mlogloss:2.32752
[21]	train-mlogloss:2.30473	validation-mlogloss:2.31368
[22]	train-mlogloss:2.29052	validation-mlogloss:2.30006
[23]	train-mlogloss:2.27675	validation-mlogloss:2.28673
[24]	train-mlogloss:2.26337	validation-mlogloss:2.27371
[25]	train-mlogloss:2.25009	validation-mlogloss:2.26072
[26]	train-mlogloss:2.23676	validation-mlogloss:2.24799
[27]	train-mlogloss:2.22408	validation-mlogloss:2.23557
[28]	train-mlogloss:2.21160	validation-mlogloss:2.22382
[29]	train-mlogloss:2.19945	validation-mlogloss:2.21175
[30]	train-mlogloss:2.18740	validation-mlogloss:2.20016
[31]	train-mlogloss:2.17564	validation-mlogloss:2.18893
[32]	train-mlogloss:2.16425	validation-mlogloss:2.17779
[33]	train-mlogloss:2.15334	validation-mlogloss:2.16752
[34]	train-mlogloss:2.14195	validation-mlogloss:2.15617
[35]	train-mlogloss:2.13156	validation-mlogloss:2.14642
[36]	train-mlogloss:2.12091	validation-mlogloss:2.13660
[37]	train-mlogloss:2.10995	validation-mlogloss:2.12584
[38]	train-mlogloss:2.09966	validation-mlogloss:2.11558
[39]	train-mlogloss:2.08941	validation-mlogloss:2.10540
[40]	train-mlogloss:2.07927	validation-mlogloss:2.09574
[41]	train-mlogloss:2.06951	validation-mlogloss:2.08658
[42]	train-mlogloss:2.05987	validation-mlogloss:2.07724
[43]	train-mlogloss:2.05045	validation-mlogloss:2.06770
[44]	train-mlogloss:2.04137	validation-mlogloss:2.05879
[45]	train-mlogloss:2.03207	validation-mlogloss:2.04967
[46]	train-mlogloss:2.02320	validation-mlogloss:2.04106
[47]	train-mlogloss:2.01435	validation-mlogloss:2.03220
[48]	train-mlogloss:2.00524	validation-mlogloss:2.02317
[49]	train-mlogloss:1.99665	validation-mlogloss:2.01460
[50]	train-mlogloss:1.98816	validation-mlogloss:2.00669
[51]	train-mlogloss:1.97972	validation-mlogloss:1.99854
[52]	train-mlogloss:1.97163	validation-mlogloss:1.99037
[53]	train-mlogloss:1.96363	validation-mlogloss:1.98291
[54]	train-mlogloss:1.95564	validation-mlogloss:1.97528
[55]	train-mlogloss:1.94767	validation-mlogloss:1.96748
[56]	train-mlogloss:1.93991	validation-mlogloss:1.96009
[57]	train-mlogloss:1.93227	validation-mlogloss:1.95296
[58]	train-mlogloss:1.92497	validation-mlogloss:1.94556
[59]	train-mlogloss:1.91763	validation-mlogloss:1.93828
[60]	train-mlogloss:1.91047	validation-mlogloss:1.93144
[61]	train-mlogloss:1.90310	validation-mlogloss:1.92423
[62]	train-mlogloss:1.89587	validation-mlogloss:1.91691
[63]	train-mlogloss:1.88909	validation-mlogloss:1.91044
[64]	train-mlogloss:1.88228	validation-mlogloss:1.90386
[65]	train-mlogloss:1.87540	validation-mlogloss:1.89721
[66]	train-mlogloss:1.86878	validation-mlogloss:1.89066
[67]	train-mlogloss:1.86211	validation-mlogloss:1.88417
[68]	train-mlogloss:1.85566	validation-mlogloss:1.87804
[69]	train-mlogloss:1.84937	validation-mlogloss:1.87227
[70]	train-mlogloss:1.84317	validation-mlogloss:1.86620
[71]	train-mlogloss:1.83700	validation-mlogloss:1.86024
[72]	train-mlogloss:1.83066	validation-mlogloss:1.85417
[73]	train-mlogloss:1.82465	validation-mlogloss:1.84833
[74]	train-mlogloss:1.81892	validation-mlogloss:1.84268
[75]	train-mlogloss:1.81329	validation-mlogloss:1.83720
[76]	train-mlogloss:1.80756	validation-mlogloss:1.83169
[77]	train-mlogloss:1.80174	validation-mlogloss:1.82572
[78]	train-mlogloss:1.79605	validation-mlogloss:1.82006
[79]	train-mlogloss:1.79042	validation-mlogloss:1.81445
[80]	train-mlogloss:1.78503	validation-mlogloss:1.80921
[81]	train-mlogloss:1.77967	validation-mlogloss:1.80396
[82]	train-mlogloss:1.77422	validation-mlogloss:1.79875
[83]	train-mlogloss:1.76904	validation-mlogloss:1.79396
[84]	train-mlogloss:1.76384	validation-mlogloss:1.78873
[85]	train-mlogloss:1.75884	validation-mlogloss:1.78380
[86]	train-mlogloss:1.75397	validation-mlogloss:1.77904
[87]	train-mlogloss:1.74911	validation-mlogloss:1.77431
[88]	train-mlogloss:1.74411	validation-mlogloss:1.76962
[89]	train-mlogloss:1.73911	validation-mlogloss:1.76524
[90]	train-mlogloss:1.73404	validation-mlogloss:1.76083
[91]	train-mlogloss:1.72922	validation-mlogloss:1.75631
[92]	train-mlogloss:1.72428	validation-mlogloss:1.75154
[93]	train-mlogloss:1.71953	validation-mlogloss:1.74668
[94]	train-mlogloss:1.71481	validation-mlogloss:1.74233
[95]	train-mlogloss:1.71018	validation-mlogloss:1.73787
[96]	train-mlogloss:1.70594	validation-mlogloss:1.73381
[97]	train-mlogloss:1.70150	validation-mlogloss:1.72948
[98]	train-mlogloss:1.69704	validation-mlogloss:1.72523
[99]	train-mlogloss:1.69262	validation-mlogloss:1.72096
[100]	train-mlogloss:1.68827	validation-mlogloss:1.71699
[101]	train-mlogloss:1.68403	validation-mlogloss:1.71305
[102]	train-mlogloss:1.67983	validation-mlogloss:1.70900
[103]	train-mlogloss:1.67589	validation-mlogloss:1.70511
[104]	train-mlogloss:1.67188	validation-mlogloss:1.70099
[105]	train-mlogloss:1.66784	validation-mlogloss:1.69696
[106]	train-mlogloss:1.66381	validation-mlogloss:1.69312
[107]	train-mlogloss:1.65994	validation-mlogloss:1.68944
[108]	train-mlogloss:1.65599	validation-mlogloss:1.68566
[109]	train-mlogloss:1.65217	validation-mlogloss:1.68205
[110]	train-mlogloss:1.64834	validation-mlogloss:1.67862
[111]	train-mlogloss:1.64449	validation-mlogloss:1.67497
[112]	train-mlogloss:1.64085	validation-mlogloss:1.67150
[113]	train-mlogloss:1.63703	validation-mlogloss:1.66805
[114]	train-mlogloss:1.63360	validation-mlogloss:1.66460
[115]	train-mlogloss:1.63002	validation-mlogloss:1.66120
[116]	train-mlogloss:1.62655	validation-mlogloss:1.65812
[117]	train-mlogloss:1.62315	validation-mlogloss:1.65487
[118]	train-mlogloss:1.61971	validation-mlogloss:1.65168
[119]	train-mlogloss:1.61626	validation-mlogloss:1.64833
[120]	train-mlogloss:1.61276	validation-mlogloss:1.64513
[121]	train-mlogloss:1.60940	validation-mlogloss:1.64220
[122]	train-mlogloss:1.60595	validation-mlogloss:1.63891
[123]	train-mlogloss:1.60259	validation-mlogloss:1.63579
[124]	train-mlogloss:1.59928	validation-mlogloss:1.63283
[125]	train-mlogloss:1.59613	validation-mlogloss:1.62983
[126]	train-mlogloss:1.59291	validation-mlogloss:1.62668
[127]	train-mlogloss:1.58977	validation-mlogloss:1.62391
[128]	train-mlogloss:1.58659	validation-mlogloss:1.62090
[129]	train-mlogloss:1.58349	validation-mlogloss:1.61800
[130]	train-mlogloss:1.58048	validation-mlogloss:1.61527
[131]	train-mlogloss:1.57745	validation-mlogloss:1.61224
[132]	train-mlogloss:1.57442	validation-mlogloss:1.60938
[133]	train-mlogloss:1.57142	validation-mlogloss:1.60670
[134]	train-mlogloss:1.56842	validation-mlogloss:1.60368
[135]	train-mlogloss:1.56561	validation-mlogloss:1.60093
[136]	train-mlogloss:1.56269	validation-mlogloss:1.59840
[137]	train-mlogloss:1.55997	validation-mlogloss:1.59590
[138]	train-mlogloss:1.55732	validation-mlogloss:1.59368
[139]	train-mlogloss:1.55451	validation-mlogloss:1.59107
[140]	train-mlogloss:1.55171	validation-mlogloss:1.58844
[141]	train-mlogloss:1.54892	validation-mlogloss:1.58575
[142]	train-mlogloss:1.54634	validation-mlogloss:1.58323
[143]	train-mlogloss:1.54368	validation-mlogloss:1.58089
[144]	train-mlogloss:1.54115	validation-mlogloss:1.57859
[145]	train-mlogloss:1.53850	validation-mlogloss:1.57613
[146]	train-mlogloss:1.53608	validation-mlogloss:1.57388
[147]	train-mlogloss:1.53349	validation-mlogloss:1.57165
[148]	train-mlogloss:1.53095	validation-mlogloss:1.56928
[149]	train-mlogloss:1.52863	validation-mlogloss:1.56716
[150]	train-mlogloss:1.52616	validation-mlogloss:1.56504
[151]	train-mlogloss:1.52361	validation-mlogloss:1.56265
[152]	train-mlogloss:1.52109	validation-mlogloss:1.56027
[153]	train-mlogloss:1.51876	validation-mlogloss:1.55813
[154]	train-mlogloss:1.51644	validation-mlogloss:1.55599
[155]	train-mlogloss:1.51422	validation-mlogloss:1.55389
[156]	train-mlogloss:1.51162	validation-mlogloss:1.55164
[157]	train-mlogloss:1.50919	validation-mlogloss:1.54928
[158]	train-mlogloss:1.50689	validation-mlogloss:1.54720
[159]	train-mlogloss:1.50456	validation-mlogloss:1.54517
[160]	train-mlogloss:1.50235	validation-mlogloss:1.54302
[161]	train-mlogloss:1.50005	validation-mlogloss:1.54088
[162]	train-mlogloss:1.49769	validation-mlogloss:1.53880
[163]	train-mlogloss:1.49567	validation-mlogloss:1.53690
[164]	train-mlogloss:1.49348	validation-mlogloss:1.53496
[165]	train-mlogloss:1.49129	validation-mlogloss:1.53299
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[168]	train-mlogloss:1.48491	validation-mlogloss:1.52719
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[170]	train-mlogloss:1.48090	validation-mlogloss:1.52367
[171]	train-mlogloss:1.47887	validation-mlogloss:1.52210
[172]	train-mlogloss:1.47681	validation-mlogloss:1.52036
[173]	train-mlogloss:1.47483	validation-mlogloss:1.51851
[174]	train-mlogloss:1.47285	validation-mlogloss:1.51665
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[188]	train-mlogloss:1.44624	validation-mlogloss:1.49293
[189]	train-mlogloss:1.44450	validation-mlogloss:1.49135
[190]	train-mlogloss:1.44275	validation-mlogloss:1.48980
[191]	train-mlogloss:1.44113	validation-mlogloss:1.48848
[192]	train-mlogloss:1.43949	validation-mlogloss:1.48700
[193]	train-mlogloss:1.43775	validation-mlogloss:1.48556
[194]	train-mlogloss:1.43604	validation-mlogloss:1.48396
[195]	train-mlogloss:1.43447	validation-mlogloss:1.48264
[196]	train-mlogloss:1.43281	validation-mlogloss:1.48132
[197]	train-mlogloss:1.43131	validation-mlogloss:1.48006
[198]	train-mlogloss:1.42965	validation-mlogloss:1.47870
[199]	train-mlogloss:1.42821	validation-mlogloss:1.47741
[200]	train-mlogloss:1.42671	validation-mlogloss:1.47598
[201]	train-mlogloss:1.42506	validation-mlogloss:1.47465
[202]	train-mlogloss:1.42351	validation-mlogloss:1.47354
[203]	train-mlogloss:1.42194	validation-mlogloss:1.47209
[204]	train-mlogloss:1.42046	validation-mlogloss:1.47077
[205]	train-mlogloss:1.41911	validation-mlogloss:1.46941
[206]	train-mlogloss:1.41762	validation-mlogloss:1.46797
[207]	train-mlogloss:1.41618	validation-mlogloss:1.46680
[208]	train-mlogloss:1.41468	validation-mlogloss:1.46546
[209]	train-mlogloss:1.41331	validation-mlogloss:1.46449
[210]	train-mlogloss:1.41172	validation-mlogloss:1.46314
[211]	train-mlogloss:1.41034	validation-mlogloss:1.46213
[212]	train-mlogloss:1.40895	validation-mlogloss:1.46070
[213]	train-mlogloss:1.40760	validation-mlogloss:1.45949
[214]	train-mlogloss:1.40623	validation-mlogloss:1.45833
[215]	train-mlogloss:1.40475	validation-mlogloss:1.45703
[216]	train-mlogloss:1.40348	validation-mlogloss:1.45574
[217]	train-mlogloss:1.40210	validation-mlogloss:1.45454
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[521]	train-mlogloss:1.26180	validation-mlogloss:1.34512
[522]	train-mlogloss:1.26166	validation-mlogloss:1.34498
[523]	train-mlogloss:1.26158	validation-mlogloss:1.34494
[524]	train-mlogloss:1.26151	validation-mlogloss:1.34490
[525]	train-mlogloss:1.26144	validation-mlogloss:1.34487
[526]	train-mlogloss:1.26141	validation-mlogloss:1.34486
[527]	train-mlogloss:1.26136	validation-mlogloss:1.34481
[528]	train-mlogloss:1.26134	validation-mlogloss:1.34477
[529]	train-mlogloss:1.26132	validation-mlogloss:1.34476
[530]	train-mlogloss:1.26119	validation-mlogloss:1.34461
[531]	train-mlogloss:1.26113	validation-mlogloss:1.34461
[532]	train-mlogloss:1.26100	validation-mlogloss:1.34450
[533]	train-mlogloss:1.26088	validation-mlogloss:1.34444
[534]	train-mlogloss:1.26087	validation-mlogloss:1.34443
[535]	train-mlogloss:1.26073	validation-mlogloss:1.34434
[536]	train-mlogloss:1.26061	validation-mlogloss:1.34430
[537]	train-mlogloss:1.26049	validation-mlogloss:1.34422
[538]	train-mlogloss:1.26044	validation-mlogloss:1.34423
[539]	train-mlogloss:1.26040	validation-mlogloss:1.34423
[540]	train-mlogloss:1.26029	validation-mlogloss:1.34414
[541]	train-mlogloss:1.26023	validation-mlogloss:1.34409
[542]	train-mlogloss:1.26015	validation-mlogloss:1.34400
[543]	train-mlogloss:1.26013	validation-mlogloss:1.34399
[544]	train-mlogloss:1.26008	validation-mlogloss:1.34397
[545]	train-mlogloss:1.26003	validation-mlogloss:1.34395
[546]	train-mlogloss:1.25991	validation-mlogloss:1.34393
[547]	train-mlogloss:1.25990	validation-mlogloss:1.34393
[548]	train-mlogloss:1.25984	validation-mlogloss:1.34390
[549]	train-mlogloss:1.25976	validation-mlogloss:1.34384
[550]	train-mlogloss:1.25971	validation-mlogloss:1.34378
[551]	train-mlogloss:1.25966	validation-mlogloss:1.34373
[552]	train-mlogloss:1.25960	validation-mlogloss:1.34373
[553]	train-mlogloss:1.25954	validation-mlogloss:1.34369
[554]	train-mlogloss:1.25945	validation-mlogloss:1.34363
[555]	train-mlogloss:1.25942	validation-mlogloss:1.34360
[556]	train-mlogloss:1.25940	validation-mlogloss:1.34358
[557]	train-mlogloss:1.25928	validation-mlogloss:1.34347
[558]	train-mlogloss:1.25925	validation-mlogloss:1.34346
[559]	train-mlogloss:1.25921	validation-mlogloss:1.34341
[560]	train-mlogloss:1.25921	validation-mlogloss:1.34341
[561]	train-mlogloss:1.25919	validation-mlogloss:1.34339
[562]	train-mlogloss:1.25916	validation-mlogloss:1.34335
[563]	train-mlogloss:1.25912	validation-mlogloss:1.34334
[564]	train-mlogloss:1.25907	validation-mlogloss:1.34331
[565]	train-mlogloss:1.25904	validation-mlogloss:1.34331
[566]	train-mlogloss:1.25903	validation-mlogloss:1.34333
[567]	train-mlogloss:1.25888	validation-mlogloss:1.34324
[568]	train-mlogloss:1.25881	validation-mlogloss:1.34326
[569]	train-mlogloss:1.25875	validation-mlogloss:1.34321
[570]	train-mlogloss:1.25875	validation-mlogloss:1.34321
[571]	train-mlogloss:1.25873	validation-mlogloss:1.34318
[572]	train-mlogloss:1.25872	validation-mlogloss:1.34318
[573]	train-mlogloss:1.25865	validation-mlogloss:1.34319
[574]	train-mlogloss:1.25861	validation-mlogloss:1.34316
[575]	train-mlogloss:1.25858	validation-mlogloss:1.34312
[576]	train-mlogloss:1.25857	validation-mlogloss:1.34310
[577]	train-mlogloss:1.25852	validation-mlogloss:1.34307
[578]	train-mlogloss:1.25852	validation-mlogloss:1.34307
[579]	train-mlogloss:1.25847	validation-mlogloss:1.34300
[580]	train-mlogloss:1.25842	validation-mlogloss:1.34297
[581]	train-mlogloss:1.25832	validation-mlogloss:1.34293
[582]	train-mlogloss:1.25828	validation-mlogloss:1.34288
[583]	train-mlogloss:1.25825	validation-mlogloss:1.34287
[584]	train-mlogloss:1.25816	validation-mlogloss:1.34281
[585]	train-mlogloss:1.25813	validation-mlogloss:1.34280
[586]	train-mlogloss:1.25813	validation-mlogloss:1.34280
[587]	train-mlogloss:1.25810	validation-mlogloss:1.34280
[588]	train-mlogloss:1.25808	validation-mlogloss:1.34280
[589]	train-mlogloss:1.25807	validation-mlogloss:1.34280
[590]	train-mlogloss:1.25804	validation-mlogloss:1.34278
[591]	train-mlogloss:1.25801	validation-mlogloss:1.34275
[592]	train-mlogloss:1.25787	validation-mlogloss:1.34267
[593]	train-mlogloss:1.25781	validation-mlogloss:1.34262
[594]	train-mlogloss:1.25776	validation-mlogloss:1.34262
[595]	train-mlogloss:1.25771	validation-mlogloss:1.34257
[596]	train-mlogloss:1.25771	validation-mlogloss:1.34257
[597]	train-mlogloss:1.25761	validation-mlogloss:1.34247
[598]	train-mlogloss:1.25761	validation-mlogloss:1.34247
[599]	train-mlogloss:1.25759	validation-mlogloss:1.34245
[600]	train-mlogloss:1.25751	validation-mlogloss:1.34240
[601]	train-mlogloss:1.25750	validation-mlogloss:1.34239
[602]	train-mlogloss:1.25745	validation-mlogloss:1.34233
[603]	train-mlogloss:1.25742	validation-mlogloss:1.34233
[604]	train-mlogloss:1.25734	validation-mlogloss:1.34222
[605]	train-mlogloss:1.25722	validation-mlogloss:1.34214
[606]	train-mlogloss:1.25706	validation-mlogloss:1.34200
[607]	train-mlogloss:1.25705	validation-mlogloss:1.34197
[608]	train-mlogloss:1.25702	validation-mlogloss:1.34196
[609]	train-mlogloss:1.25697	validation-mlogloss:1.34195
[610]	train-mlogloss:1.25690	validation-mlogloss:1.34188
[611]	train-mlogloss:1.25690	validation-mlogloss:1.34188
[612]	train-mlogloss:1.25686	validation-mlogloss:1.34187
[613]	train-mlogloss:1.25683	validation-mlogloss:1.34183
[614]	train-mlogloss:1.25675	validation-mlogloss:1.34174
[615]	train-mlogloss:1.25656	validation-mlogloss:1.34157
[616]	train-mlogloss:1.25655	validation-mlogloss:1.34159
[617]	train-mlogloss:1.25653	validation-mlogloss:1.34160
[618]	train-mlogloss:1.25652	validation-mlogloss:1.34156
[619]	train-mlogloss:1.25647	validation-mlogloss:1.34156
[620]	train-mlogloss:1.25637	validation-mlogloss:1.34148
[621]	train-mlogloss:1.25626	validation-mlogloss:1.34139
[622]	train-mlogloss:1.25621	validation-mlogloss:1.34138
[623]	train-mlogloss:1.25615	validation-mlogloss:1.34131
[624]	train-mlogloss:1.25615	validation-mlogloss:1.34131
[625]	train-mlogloss:1.25606	validation-mlogloss:1.34138
[626]	train-mlogloss:1.25600	validation-mlogloss:1.34134
[627]	train-mlogloss:1.25599	validation-mlogloss:1.34131
[628]	train-mlogloss:1.25596	validation-mlogloss:1.34130
[629]	train-mlogloss:1.25596	validation-mlogloss:1.34130
[630]	train-mlogloss:1.25589	validation-mlogloss:1.34128
[631]	train-mlogloss:1.25588	validation-mlogloss:1.34125
[632]	train-mlogloss:1.25588	validation-mlogloss:1.34125
[633]	train-mlogloss:1.25579	validation-mlogloss:1.34119
[634]	train-mlogloss:1.25570	validation-mlogloss:1.34114
[635]	train-mlogloss:1.25563	validation-mlogloss:1.34103
[636]	train-mlogloss:1.25558	validation-mlogloss:1.34103
[637]	train-mlogloss:1.25554	validation-mlogloss:1.34102
[638]	train-mlogloss:1.25544	validation-mlogloss:1.34100
[639]	train-mlogloss:1.25531	validation-mlogloss:1.34097
[640]	train-mlogloss:1.25528	validation-mlogloss:1.34096
[641]	train-mlogloss:1.25528	validation-mlogloss:1.34096
[642]	train-mlogloss:1.25528	validation-mlogloss:1.34096
[643]	train-mlogloss:1.25522	validation-mlogloss:1.34094
[644]	train-mlogloss:1.25521	validation-mlogloss:1.34090
[645]	train-mlogloss:1.25516	validation-mlogloss:1.34089
[646]	train-mlogloss:1.25509	validation-mlogloss:1.34085
[647]	train-mlogloss:1.25507	validation-mlogloss:1.34085
[648]	train-mlogloss:1.25506	validation-mlogloss:1.34084
[649]	train-mlogloss:1.25500	validation-mlogloss:1.34083
[650]	train-mlogloss:1.25499	validation-mlogloss:1.34082
[651]	train-mlogloss:1.25494	validation-mlogloss:1.34079
[652]	train-mlogloss:1.25490	validation-mlogloss:1.34075
[653]	train-mlogloss:1.25488	validation-mlogloss:1.34075
[654]	train-mlogloss:1.25474	validation-mlogloss:1.34069
[655]	train-mlogloss:1.25470	validation-mlogloss:1.34065
[656]	train-mlogloss:1.25465	validation-mlogloss:1.34057
[657]	train-mlogloss:1.25463	validation-mlogloss:1.34055
[658]	train-mlogloss:1.25459	validation-mlogloss:1.34053
[659]	train-mlogloss:1.25453	validation-mlogloss:1.34045
[660]	train-mlogloss:1.25449	validation-mlogloss:1.34046
[661]	train-mlogloss:1.25448	validation-mlogloss:1.34045
[662]	train-mlogloss:1.25442	validation-mlogloss:1.34043
[663]	train-mlogloss:1.25434	validation-mlogloss:1.34038
[664]	train-mlogloss:1.25434	validation-mlogloss:1.34038
[665]	train-mlogloss:1.25431	validation-mlogloss:1.34038
[666]	train-mlogloss:1.25421	validation-mlogloss:1.34033
[667]	train-mlogloss:1.25421	validation-mlogloss:1.34033
[668]	train-mlogloss:1.25418	validation-mlogloss:1.34028
[669]	train-mlogloss:1.25415	validation-mlogloss:1.34027
[670]	train-mlogloss:1.25411	validation-mlogloss:1.34026
[671]	train-mlogloss:1.25403	validation-mlogloss:1.34022
[672]	train-mlogloss:1.25401	validation-mlogloss:1.34022
[673]	train-mlogloss:1.25401	validation-mlogloss:1.34022
[674]	train-mlogloss:1.25398	validation-mlogloss:1.34022
[675]	train-mlogloss:1.25395	validation-mlogloss:1.34021
[676]	train-mlogloss:1.25389	validation-mlogloss:1.34017
[677]	train-mlogloss:1.25386	validation-mlogloss:1.34017
[678]	train-mlogloss:1.25386	validation-mlogloss:1.34017
[679]	train-mlogloss:1.25379	validation-mlogloss:1.34011
[680]	train-mlogloss:1.25374	validation-mlogloss:1.34006
[681]	train-mlogloss:1.25373	validation-mlogloss:1.34006
[682]	train-mlogloss:1.25370	validation-mlogloss:1.34006
[683]	train-mlogloss:1.25368	validation-mlogloss:1.34004
[684]	train-mlogloss:1.25362	validation-mlogloss:1.34005
[685]	train-mlogloss:1.25362	validation-mlogloss:1.34005
[686]	train-mlogloss:1.25362	validation-mlogloss:1.34005
[687]	train-mlogloss:1.25360	validation-mlogloss:1.34004
[688]	train-mlogloss:1.25357	validation-mlogloss:1.34002
[689]	train-mlogloss:1.25350	validation-mlogloss:1.34002
[690]	train-mlogloss:1.25339	validation-mlogloss:1.33999
[691]	train-mlogloss:1.25338	validation-mlogloss:1.33998
[692]	train-mlogloss:1.25333	validation-mlogloss:1.33997
[693]	train-mlogloss:1.25333	validation-mlogloss:1.33997
[694]	train-mlogloss:1.25333	validation-mlogloss:1.33997
[695]	train-mlogloss:1.25328	validation-mlogloss:1.33994
[696]	train-mlogloss:1.25323	validation-mlogloss:1.33990
[697]	train-mlogloss:1.25322	validation-mlogloss:1.33991
[698]	train-mlogloss:1.25316	validation-mlogloss:1.33986
[699]	train-mlogloss:1.25315	validation-mlogloss:1.33987
[700]	train-mlogloss:1.25310	validation-mlogloss:1.33982
[701]	train-mlogloss:1.25309	validation-mlogloss:1.33979
[702]	train-mlogloss:1.25309	validation-mlogloss:1.33979
[703]	train-mlogloss:1.25309	validation-mlogloss:1.33979
[704]	train-mlogloss:1.25306	validation-mlogloss:1.33977
[705]	train-mlogloss:1.25301	validation-mlogloss:1.33977
[706]	train-mlogloss:1.25298	validation-mlogloss:1.33977
[707]	train-mlogloss:1.25295	validation-mlogloss:1.33972
[708]	train-mlogloss:1.25292	validation-mlogloss:1.33970
[709]	train-mlogloss:1.25291	validation-mlogloss:1.33970
[710]	train-mlogloss:1.25289	validation-mlogloss:1.33969
[711]	train-mlogloss:1.25276	validation-mlogloss:1.33971
[712]	train-mlogloss:1.25273	validation-mlogloss:1.33969
[713]	train-mlogloss:1.25270	validation-mlogloss:1.33963
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13  2 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.75 [%]
Global accuracy score (test) = 50.42 [%]
Global F1 score (train) = 62.81 [%]
Global F1 score (test) = 50.64 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.39      0.32       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.39      0.41       184
       CAMINAR USUAL SPEED       0.29      0.23      0.26       184
            CAMINAR ZIGZAG       0.58      0.53      0.56       184
          DE PIE BARRIENDO       0.55      0.48      0.51       184
   DE PIE DOBLANDO TOALLAS       0.43      0.48      0.45       184
    DE PIE MOVIENDO LIBROS       0.48      0.45      0.46       184
          DE PIE USANDO PC       0.63      0.67      0.65       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.86      0.61      0.72       184
           SENTADO LEYENDO       0.36      0.43      0.39       184
         SENTADO USANDO PC       0.41      0.26      0.32       184
      SENTADO VIENDO LA TV       0.47      0.40      0.43       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.67      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.52      0.50      0.50      2737


Accuracy capturado en la ejecución 28: 50.42 [%]
F1-score capturado en la ejecución 28: 50.64 [%]

=== EJECUCIÓN 29 ===

--- TRAIN (ejecución 29) ---

--- TEST (ejecución 29) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.61 [%]
Global accuracy score (test) = 50.49 [%]
Global F1 score (train) = 62.65 [%]
Global F1 score (test) = 50.6 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.40      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.42      0.44       184
       CAMINAR USUAL SPEED       0.29      0.20      0.24       184
            CAMINAR ZIGZAG       0.59      0.53      0.56       184
          DE PIE BARRIENDO       0.55      0.51      0.53       184
   DE PIE DOBLANDO TOALLAS       0.42      0.45      0.43       184
    DE PIE MOVIENDO LIBROS       0.46      0.43      0.44       184
          DE PIE USANDO PC       0.61      0.67      0.64       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.88      0.64      0.74       184
           SENTADO LEYENDO       0.36      0.42      0.39       184
         SENTADO USANDO PC       0.42      0.26      0.32       184
      SENTADO VIENDO LA TV       0.45      0.40      0.42       184
   SUBIR Y BAJAR ESCALERAS       0.53      0.68      0.60       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.51      0.51      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 29: 50.49 [%]
F1-score capturado en la ejecución 29: 50.6 [%]

=== EJECUCIÓN 30 ===

--- TRAIN (ejecución 30) ---

--- TEST (ejecución 30) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 91)
(18331, 91)
[[ 2.]
 [ 2.]
 [ 2.]
 ...
 [13.]
 [13.]
 [13.]]
(2737, 1)
[13 13 13 ... 13 13  1]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 62.76 [%]
Global accuracy score (test) = 50.13 [%]
Global F1 score (train) = 62.81 [%]
Global F1 score (test) = 50.28 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.28      0.40      0.33       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.39      0.41       184
       CAMINAR USUAL SPEED       0.27      0.19      0.22       184
            CAMINAR ZIGZAG       0.60      0.54      0.57       184
          DE PIE BARRIENDO       0.56      0.51      0.53       184
   DE PIE DOBLANDO TOALLAS       0.41      0.45      0.43       184
    DE PIE MOVIENDO LIBROS       0.47      0.45      0.46       184
          DE PIE USANDO PC       0.63      0.67      0.65       184
        FASE REPOSO CON K5       0.55      0.79      0.65       184
INCREMENTAL CICLOERGOMETRO       0.88      0.62      0.73       184
           SENTADO LEYENDO       0.33      0.41      0.37       184
         SENTADO USANDO PC       0.43      0.28      0.34       184
      SENTADO VIENDO LA TV       0.43      0.36      0.39       184
   SUBIR Y BAJAR ESCALERAS       0.51      0.68      0.59       184
                    TROTAR       0.93      0.81      0.87       161

                  accuracy                           0.50      2737
                 macro avg       0.52      0.50      0.50      2737
              weighted avg       0.51      0.50      0.50      2737


Accuracy capturado en la ejecución 30: 50.13 [%]
F1-score capturado en la ejecución 30: 50.28 [%]

=== RESUMEN FINAL ===
Accuracies: [50.57, 50.02, 50.2, 50.53, 50.6, 50.2, 50.2, 50.31, 50.68, 50.75, 50.38, 51.04, 50.24, 50.64, 50.35, 50.6, 50.86, 50.35, 50.31, 50.42, 50.16, 51.08, 50.68, 50.68, 50.64, 50.16, 50.75, 50.42, 50.49, 50.13]
F1-scores: [50.79, 50.12, 50.41, 50.69, 50.81, 50.42, 50.34, 50.48, 50.93, 50.9, 50.53, 51.23, 50.48, 50.91, 50.47, 50.73, 50.99, 50.46, 50.47, 50.58, 50.36, 51.26, 50.86, 50.85, 50.84, 50.3, 50.92, 50.64, 50.6, 50.28]
Accuracy mean: 50.4813 | std: 0.2655
F1 mean: 50.6550 | std: 0.2763

Resultados guardados en /mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_C/case_C_XGB_acc_gyr_17_classes/metrics_test.npz
