2025-11-03 17:18:18.924175: 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`.
2025-11-03 17:18:18.935852: 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 00:00:1762186698.949660  323661 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186698.953890  323661 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186698.964231  323661 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186698.964259  323661 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186698.964262  323661 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186698.964265  323661 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:18:18.967491: 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(
2025-11-03 17:18:24,700	INFO worker.py:1927 -- Started a local Ray instance.
2025-11-03 17:18:25,372	INFO tune.py:253 -- Initializing Ray automatically. For cluster usage or custom Ray initialization, call `ray.init(...)` before `Tuner(...)`.
2025-11-03 17:18:25,438	INFO trial.py:182 -- Creating a new dirname dir_b9863_f1ad because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,441	INFO trial.py:182 -- Creating a new dirname dir_b9863_9ac7 because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,443	INFO trial.py:182 -- Creating a new dirname dir_b9863_79df because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,446	INFO trial.py:182 -- Creating a new dirname dir_b9863_b58d because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,448	INFO trial.py:182 -- Creating a new dirname dir_b9863_e153 because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,450	INFO trial.py:182 -- Creating a new dirname dir_b9863_5095 because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,452	INFO trial.py:182 -- Creating a new dirname dir_b9863_f0f0 because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,454	INFO trial.py:182 -- Creating a new dirname dir_b9863_50e2 because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,456	INFO trial.py:182 -- Creating a new dirname dir_b9863_c7dc because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,459	INFO trial.py:182 -- Creating a new dirname dir_b9863_9140 because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,462	INFO trial.py:182 -- Creating a new dirname dir_b9863_725e because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,465	INFO trial.py:182 -- Creating a new dirname dir_b9863_97cd because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,468	INFO trial.py:182 -- Creating a new dirname dir_b9863_60d1 because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,471	INFO trial.py:182 -- Creating a new dirname dir_b9863_7b07 because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,475	INFO trial.py:182 -- Creating a new dirname dir_b9863_e94f because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,478	INFO trial.py:182 -- Creating a new dirname dir_b9863_940b because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,483	INFO trial.py:182 -- Creating a new dirname dir_b9863_e726 because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,491	INFO trial.py:182 -- Creating a new dirname dir_b9863_11f2 because trial dirname 'dir_b9863' already exists.
2025-11-03 17:18:25,496	INFO trial.py:182 -- Creating a new dirname dir_b9863_85cf because trial dirname 'dir_b9863' already exists.
1 GPU(s) detected and VRAM set to crossover mode..
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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_PI/case_PI_XGB_acc_gyr_superclasses_CPA_METs/XGBoost_hyperparameters_tuning
To visualize your results with TensorBoard, run: `tensorboard --logdir /tmp/ray/session_2025-11-03_17-18-23_983823_323661/artifacts/2025-11-03_17-18-25/XGBoost_hyperparameters_tuning/driver_artifacts`

Trial status: 20 PENDING
Current time: 2025-11-03 17:18:25. 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_b9863    PENDING                  628             3        0.00744423      0.504952             0.576937   13.9612                   112       2.14385      540.611               6635 │
│ trial_b9863    PENDING                  767             2        0.0127582       0.751678             0.636061   27.2159                   120       7.86891      355.199               9744 │
│ trial_b9863    PENDING                  634             3        0.0185581       0.834024             0.714164   13.2016                   124     198.931        275.297               1017 │
│ trial_b9863    PENDING                  388             3        0.018838        0.637224             0.549674    8.88675                  197      12.7753        61.8836              2876 │
│ trial_b9863    PENDING                  420             2        0.0180166       0.80739              0.712444    6.64513                  185      78.1219       162.178               1023 │
│ trial_b9863    PENDING                  555             3        0.00825242      0.769773             0.632202    5.19447                   52      48.4836       294.162               1804 │
│ trial_b9863    PENDING                  588             2        0.0069269       0.502066             0.683889    6.79868                  178      21.4366       166.915               1677 │
│ trial_b9863    PENDING                  707             3        0.0106103       0.587228             0.70151    10.9406                   101      23.3789       986.965               1328 │
│ trial_b9863    PENDING                  455             3        0.0106544       0.50955              0.59724    15.3759                   127     344.898         60.0014              6583 │
│ trial_b9863    PENDING                  615             3        0.00819303      0.670386             0.717359   25.3107                   112      74.1024       199.986               5959 │
│ trial_b9863    PENDING                  613             2        0.0079888       0.719448             0.771053   16.9002                   183       2.25177      972.425               9160 │
│ trial_b9863    PENDING                  595             2        0.0197272       0.647494             0.830119   23.1508                    92     293.313        321.847               2929 │
│ trial_b9863    PENDING                  338             3        0.00731551      0.50678              0.606173    6.87364                  197       5.78572      209.434               5767 │
│ trial_b9863    PENDING                  580             3        0.0123196       0.789987             0.842133   21.9435                    59     183.313        609.788               2629 │
│ trial_b9863    PENDING                  666             3        0.0154746       0.586134             0.740253   22.1136                   123       9.78015        5.00302              706 │
│ trial_b9863    PENDING                  765             3        0.0195731       0.753195             0.524474    9.79434                  172      98.9698       178.629               3696 │
│ trial_b9863    PENDING                  550             2        0.0152865       0.642751             0.810261   20.5002                   131      69.4834        11.4629              5706 │
│ trial_b9863    PENDING                  379             3        0.0152753       0.74538              0.584298   17.5569                    93     327.299        834.159               3257 │
│ trial_b9863    PENDING                  493             3        0.0157942       0.761821             0.634877   21.5754                   176       1.64461       86.6583              3242 │
│ trial_b9863    PENDING                  522             3        0.013589        0.722285             0.551921    6.16405                  133       7.82715       41.4212               244 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.57694 │
│ gamma                        13.9612 │
│ learning_rate                0.00744 │
│ max_depth                          3 │
│ min_child_weight                 112 │
│ num_boost_round                  628 │
│ random_state                    6635 │
│ reg_alpha                    2.14385 │
│ reg_lambda                   540.611 │
│ subsample                    0.50495 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.54967 │
│ gamma                        8.88675 │
│ learning_rate                0.01884 │
│ max_depth                          3 │
│ min_child_weight                 197 │
│ num_boost_round                  388 │
│ random_state                    2876 │
│ reg_alpha                    12.7753 │
│ reg_lambda                   61.8836 │
│ subsample                    0.63722 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.71416 │
│ gamma                        13.2016 │
│ learning_rate                0.01856 │
│ max_depth                          3 │
│ min_child_weight                 124 │
│ num_boost_round                  634 │
│ random_state                    1017 │
│ reg_alpha                    198.931 │
│ reg_lambda                   275.297 │
│ subsample                    0.83402 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.77105 │
│ gamma                        16.9002 │
│ learning_rate                0.00799 │
│ max_depth                          2 │
│ min_child_weight                 183 │
│ num_boost_round                  613 │
│ random_state                    9160 │
│ reg_alpha                    2.25177 │
│ reg_lambda                   972.425 │
│ subsample                    0.71945 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.63606 │
│ gamma                        27.2159 │
│ learning_rate                0.01276 │
│ max_depth                          2 │
│ min_child_weight                 120 │
│ num_boost_round                  767 │
│ random_state                    9744 │
│ reg_alpha                    7.86891 │
│ reg_lambda                   355.199 │
│ subsample                    0.75168 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.71244 │
│ gamma                        6.64513 │
│ learning_rate                0.01802 │
│ max_depth                          2 │
│ min_child_weight                 185 │
│ num_boost_round                  420 │
│ random_state                    1023 │
│ reg_alpha                    78.1219 │
│ reg_lambda                   162.178 │
│ subsample                    0.80739 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.71736 │
│ gamma                        25.3107 │
│ learning_rate                0.00819 │
│ max_depth                          3 │
│ min_child_weight                 112 │
│ num_boost_round                  615 │
│ random_state                    5959 │
│ reg_alpha                    74.1024 │
│ reg_lambda                   199.986 │
│ subsample                    0.67039 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.59724 │
│ gamma                        15.3759 │
│ learning_rate                0.01065 │
│ max_depth                          3 │
│ min_child_weight                 127 │
│ num_boost_round                  455 │
│ random_state                    6583 │
│ reg_alpha                    344.898 │
│ reg_lambda                   60.0014 │
│ subsample                    0.50955 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.74025 │
│ gamma                        22.1136 │
│ learning_rate                0.01547 │
│ max_depth                          3 │
│ min_child_weight                 123 │
│ num_boost_round                  666 │
│ random_state                     706 │
│ reg_alpha                    9.78015 │
│ reg_lambda                   5.00302 │
│ subsample                    0.58613 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.83012 │
│ gamma                        23.1508 │
│ learning_rate                0.01973 │
│ max_depth                          2 │
│ min_child_weight                  92 │
│ num_boost_round                  595 │
│ random_state                    2929 │
│ reg_alpha                    293.313 │
│ reg_lambda                   321.847 │
│ subsample                    0.64749 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree              0.5843 │
│ gamma                        17.5569 │
│ learning_rate                0.01528 │
│ max_depth                          3 │
│ min_child_weight                  93 │
│ num_boost_round                  379 │
│ random_state                    3257 │
│ reg_alpha                    327.299 │
│ reg_lambda                   834.159 │
│ subsample                    0.74538 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
[36m(train_xgb_ray_tune pid=325294)[0m 2025-11-03 17:18:28.785426: 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=325294)[0m 2025-11-03 17:18:28.806837: 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=325294)[0m WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
[36m(train_xgb_ray_tune pid=325294)[0m E0000 00:00:1762186708.833333  326449 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=325294)[0m E0000 00:00:1762186708.840806  326449 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=325294)[0m W0000 00:00:1762186708.860752  326449 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=325294)[0m W0000 00:00:1762186708.860821  326449 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=325294)[0m W0000 00:00:1762186708.860828  326449 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=325294)[0m W0000 00:00:1762186708.860831  326449 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=325294)[0m 2025-11-03 17:18:28.867026: 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=325294)[0m To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.70151 │
│ gamma                        10.9406 │
│ learning_rate                0.01061 │
│ max_depth                          3 │
│ min_child_weight                 101 │
│ num_boost_round                  707 │
│ random_state                    1328 │
│ reg_alpha                    23.3789 │
│ reg_lambda                   986.965 │
│ subsample                    0.58723 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.68389 │
│ gamma                        6.79868 │
│ learning_rate                0.00693 │
│ max_depth                          2 │
│ min_child_weight                 178 │
│ num_boost_round                  588 │
│ random_state                    1677 │
│ reg_alpha                    21.4366 │
│ reg_lambda                   166.915 │
│ subsample                    0.50207 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.60617 │
│ gamma                        6.87364 │
│ learning_rate                0.00732 │
│ max_depth                          3 │
│ min_child_weight                 197 │
│ num_boost_round                  338 │
│ random_state                    5767 │
│ reg_alpha                    5.78572 │
│ reg_lambda                   209.434 │
│ subsample                    0.50678 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree              0.6322 │
│ gamma                        5.19447 │
│ learning_rate                0.00825 │
│ max_depth                          3 │
│ min_child_weight                  52 │
│ num_boost_round                  555 │
│ random_state                    1804 │
│ reg_alpha                    48.4836 │
│ reg_lambda                   294.162 │
│ subsample                    0.76977 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.63488 │
│ gamma                        21.5754 │
│ learning_rate                0.01579 │
│ max_depth                          3 │
│ min_child_weight                 176 │
│ num_boost_round                  493 │
│ random_state                    3242 │
│ reg_alpha                    1.64461 │
│ reg_lambda                   86.6583 │
│ subsample                    0.76182 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.84213 │
│ gamma                        21.9435 │
│ learning_rate                0.01232 │
│ max_depth                          3 │
│ min_child_weight                  59 │
│ num_boost_round                  580 │
│ random_state                    2629 │
│ reg_alpha                    183.313 │
│ reg_lambda                   609.788 │
│ subsample                    0.78999 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.52447 │
│ gamma                        9.79434 │
│ learning_rate                0.01957 │
│ max_depth                          3 │
│ min_child_weight                 172 │
│ num_boost_round                  765 │
│ random_state                    3696 │
│ reg_alpha                    98.9698 │
│ reg_lambda                   178.629 │
│ subsample                    0.75319 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.55192 │
│ gamma                        6.16405 │
│ learning_rate                0.01359 │
│ max_depth                          3 │
│ min_child_weight                 133 │
│ num_boost_round                  522 │
│ random_state                     244 │
│ reg_alpha                    7.82715 │
│ reg_lambda                   41.4213 │
│ subsample                    0.72229 │
╰──────────────────────────────────────╯
Trial trial_b9863 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b9863 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.81026 │
│ gamma                        20.5002 │
│ learning_rate                0.01529 │
│ max_depth                          2 │
│ min_child_weight                 131 │
│ num_boost_round                  550 │
│ random_state                    5706 │
│ reg_alpha                    69.4834 │
│ reg_lambda                   11.4629 │
│ subsample                    0.64275 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=325294)[0m [0]	train-mlogloss:1.38293	validation-mlogloss:1.38285
[36m(train_xgb_ray_tune pid=325325)[0m [0]	train-mlogloss:1.37626	validation-mlogloss:1.37604
[36m(train_xgb_ray_tune pid=325344)[0m [0]	train-mlogloss:1.37175	validation-mlogloss:1.37142
[36m(train_xgb_ray_tune pid=325344)[0m [1]	train-mlogloss:1.35719	validation-mlogloss:1.35623
[36m(train_xgb_ray_tune pid=325344)[0m [2]	train-mlogloss:1.34291	validation-mlogloss:1.34181
[36m(train_xgb_ray_tune pid=325294)[0m [1]	train-mlogloss:1.37959	validation-mlogloss:1.37944
[36m(train_xgb_ray_tune pid=325294)[0m [2]	train-mlogloss:1.37618	validation-mlogloss:1.37590
[36m(train_xgb_ray_tune pid=325294)[0m [3]	train-mlogloss:1.37293	validation-mlogloss:1.37253
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[36m(train_xgb_ray_tune pid=325294)[0m [6]	train-mlogloss:1.36278	validation-mlogloss:1.36201
[36m(train_xgb_ray_tune pid=325294)[0m [7]	train-mlogloss:1.35958	validation-mlogloss:1.35864
[36m(train_xgb_ray_tune pid=325325)[0m [1]	train-mlogloss:1.36627	validation-mlogloss:1.36559
[36m(train_xgb_ray_tune pid=325325)[0m [2]	train-mlogloss:1.35629	validation-mlogloss:1.35524
[36m(train_xgb_ray_tune pid=325325)[0m [3]	train-mlogloss:1.34670	validation-mlogloss:1.34528
[36m(train_xgb_ray_tune pid=325325)[0m [4]	train-mlogloss:1.33714	validation-mlogloss:1.33529
[36m(train_xgb_ray_tune pid=325325)[0m [5]	train-mlogloss:1.32782	validation-mlogloss:1.32555
[36m(train_xgb_ray_tune pid=325344)[0m [3]	train-mlogloss:1.32894	validation-mlogloss:1.32694
[36m(train_xgb_ray_tune pid=325344)[0m [4]	train-mlogloss:1.31635	validation-mlogloss:1.31402
[36m(train_xgb_ray_tune pid=325344)[0m [5]	train-mlogloss:1.30334	validation-mlogloss:1.30070
[36m(train_xgb_ray_tune pid=325344)[0m [6]	train-mlogloss:1.29048	validation-mlogloss:1.28718
[36m(train_xgb_ray_tune pid=325344)[0m [7]	train-mlogloss:1.27826	validation-mlogloss:1.27469
[36m(train_xgb_ray_tune pid=325344)[0m [8]	train-mlogloss:1.26613	validation-mlogloss:1.26189
[36m(train_xgb_ray_tune pid=325294)[0m [8]	train-mlogloss:1.35633	validation-mlogloss:1.35524
[36m(train_xgb_ray_tune pid=325294)[0m [9]	train-mlogloss:1.35300	validation-mlogloss:1.35174
[36m(train_xgb_ray_tune pid=325294)[0m [10]	train-mlogloss:1.34981	validation-mlogloss:1.34842
[36m(train_xgb_ray_tune pid=325294)[0m [11]	train-mlogloss:1.34674	validation-mlogloss:1.34519
[36m(train_xgb_ray_tune pid=325294)[0m [12]	train-mlogloss:1.34335	validation-mlogloss:1.34165
[36m(train_xgb_ray_tune pid=325294)[0m [13]	train-mlogloss:1.34004	validation-mlogloss:1.33826
[36m(train_xgb_ray_tune pid=325325)[0m [6]	train-mlogloss:1.31863	validation-mlogloss:1.31589
[36m(train_xgb_ray_tune pid=325325)[0m [7]	train-mlogloss:1.30958	validation-mlogloss:1.30635
[36m(train_xgb_ray_tune pid=325325)[0m [8]	train-mlogloss:1.30057	validation-mlogloss:1.29693
[36m(train_xgb_ray_tune pid=325325)[0m [9]	train-mlogloss:1.29176	validation-mlogloss:1.28780
[36m(train_xgb_ray_tune pid=325325)[0m [10]	train-mlogloss:1.28322	validation-mlogloss:1.27880
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[36m(train_xgb_ray_tune pid=325344)[0m [9]	train-mlogloss:1.25394	validation-mlogloss:1.24907
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[36m(train_xgb_ray_tune pid=325344)[0m [11]	train-mlogloss:1.23029	validation-mlogloss:1.22419
[36m(train_xgb_ray_tune pid=325344)[0m [12]	train-mlogloss:1.21930	validation-mlogloss:1.21282
[36m(train_xgb_ray_tune pid=325344)[0m [13]	train-mlogloss:1.20834	validation-mlogloss:1.20149
[36m(train_xgb_ray_tune pid=325344)[0m [14]	train-mlogloss:1.19788	validation-mlogloss:1.19069
[36m(train_xgb_ray_tune pid=325332)[0m [0]	train-mlogloss:1.37394	validation-mlogloss:1.37317
[36m(train_xgb_ray_tune pid=325332)[0m [1]	train-mlogloss:1.36183	validation-mlogloss:1.36030
[36m(train_xgb_ray_tune pid=325332)[0m [2]	train-mlogloss:1.34995	validation-mlogloss:1.34761
[36m(train_xgb_ray_tune pid=325332)[0m [3]	train-mlogloss:1.33913	validation-mlogloss:1.33644
[36m(train_xgb_ray_tune pid=325332)[0m [4]	train-mlogloss:1.32810	validation-mlogloss:1.32492
[36m(train_xgb_ray_tune pid=325332)[0m [5]	train-mlogloss:1.31741	validation-mlogloss:1.31380
[36m(train_xgb_ray_tune pid=325330)[0m [0]	train-mlogloss:1.37263	validation-mlogloss:1.37224
[36m(train_xgb_ray_tune pid=325296)[0m [0]	train-mlogloss:1.37840	validation-mlogloss:1.37804
[36m(train_xgb_ray_tune pid=325294)[0m [14]	train-mlogloss:1.33686	validation-mlogloss:1.33489
[36m(train_xgb_ray_tune pid=325325)[0m [12]	train-mlogloss:1.26686	validation-mlogloss:1.26186
[36m(train_xgb_ray_tune pid=325332)[0m [6]	train-mlogloss:1.30677	validation-mlogloss:1.30255
[36m(train_xgb_ray_tune pid=325330)[0m [1]	train-mlogloss:1.35921	validation-mlogloss:1.35808
[36m(train_xgb_ray_tune pid=325296)[0m [1]	train-mlogloss:1.37067	validation-mlogloss:1.36987
[36m(train_xgb_ray_tune pid=325344)[0m [15]	train-mlogloss:1.18799	validation-mlogloss:1.18068
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[36m(train_xgb_ray_tune pid=325294)[0m [19]	train-mlogloss:1.32120	validation-mlogloss:1.31849
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[36m(train_xgb_ray_tune pid=325325)[0m [13]	train-mlogloss:1.25864	validation-mlogloss:1.25309
[36m(train_xgb_ray_tune pid=325325)[0m [14]	train-mlogloss:1.25103	validation-mlogloss:1.24533
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[36m(train_xgb_ray_tune pid=325325)[0m [16]	train-mlogloss:1.23535	validation-mlogloss:1.22883
[36m(train_xgb_ray_tune pid=325325)[0m [17]	train-mlogloss:1.22791	validation-mlogloss:1.22101
[36m(train_xgb_ray_tune pid=325325)[0m [18]	train-mlogloss:1.22021	validation-mlogloss:1.21313
[36m(train_xgb_ray_tune pid=325327)[0m [0]	train-mlogloss:1.38099	validation-mlogloss:1.38078
[36m(train_xgb_ray_tune pid=325344)[0m [16]	train-mlogloss:1.17782	validation-mlogloss:1.17023
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[36m(train_xgb_ray_tune pid=325344)[0m [18]	train-mlogloss:1.15833	validation-mlogloss:1.14964
[36m(train_xgb_ray_tune pid=325344)[0m [19]	train-mlogloss:1.14880	validation-mlogloss:1.13954
[36m(train_xgb_ray_tune pid=325344)[0m [20]	train-mlogloss:1.13979	validation-mlogloss:1.13015
[36m(train_xgb_ray_tune pid=325332)[0m [7]	train-mlogloss:1.29622	validation-mlogloss:1.29132
[36m(train_xgb_ray_tune pid=325332)[0m [8]	train-mlogloss:1.28622	validation-mlogloss:1.28073
[36m(train_xgb_ray_tune pid=325332)[0m [9]	train-mlogloss:1.27622	validation-mlogloss:1.27013
[36m(train_xgb_ray_tune pid=325332)[0m [10]	train-mlogloss:1.26643	validation-mlogloss:1.25961
[36m(train_xgb_ray_tune pid=325332)[0m [11]	train-mlogloss:1.25730	validation-mlogloss:1.25027
[36m(train_xgb_ray_tune pid=325332)[0m [12]	train-mlogloss:1.24792	validation-mlogloss:1.24040
[36m(train_xgb_ray_tune pid=325341)[0m [0]	train-mlogloss:1.38293	validation-mlogloss:1.38271
[36m(train_xgb_ray_tune pid=325341)[0m [1]	train-mlogloss:1.37914	validation-mlogloss:1.37867
[36m(train_xgb_ray_tune pid=325307)[0m [0]	train-mlogloss:1.38183	validation-mlogloss:1.38160
[36m(train_xgb_ray_tune pid=325330)[0m [2]	train-mlogloss:1.34618	validation-mlogloss:1.34458
[36m(train_xgb_ray_tune pid=325330)[0m [3]	train-mlogloss:1.33342	validation-mlogloss:1.33105
[36m(train_xgb_ray_tune pid=325330)[0m [4]	train-mlogloss:1.32081	validation-mlogloss:1.31790
[36m(train_xgb_ray_tune pid=325330)[0m [5]	train-mlogloss:1.30854	validation-mlogloss:1.30491
[36m(train_xgb_ray_tune pid=325330)[0m [6]	train-mlogloss:1.29657	validation-mlogloss:1.29215
[36m(train_xgb_ray_tune pid=325330)[0m [7]	train-mlogloss:1.28475	validation-mlogloss:1.27935
[36m(train_xgb_ray_tune pid=325296)[0m [8]	train-mlogloss:1.31911	validation-mlogloss:1.31522
[36m(train_xgb_ray_tune pid=325294)[0m [21]	train-mlogloss:1.31506	validation-mlogloss:1.31208
[36m(train_xgb_ray_tune pid=325332)[0m [13]	train-mlogloss:1.23904	validation-mlogloss:1.23101
[36m(train_xgb_ray_tune pid=325344)[0m [21]	train-mlogloss:1.13100	validation-mlogloss:1.12127
[36m(train_xgb_ray_tune pid=325341)[0m [2]	train-mlogloss:1.37567	validation-mlogloss:1.37505
[36m(train_xgb_ray_tune pid=325307)[0m [1]	train-mlogloss:1.37736	validation-mlogloss:1.37675
[36m(train_xgb_ray_tune pid=325296)[0m [9]	train-mlogloss:1.31196	validation-mlogloss:1.30773
[36m(train_xgb_ray_tune pid=325294)[0m [22]	train-mlogloss:1.31208	validation-mlogloss:1.30900
[36m(train_xgb_ray_tune pid=325325)[0m [19]	train-mlogloss:1.21266	validation-mlogloss:1.20517
[36m(train_xgb_ray_tune pid=325327)[0m [1]	train-mlogloss:1.37581	validation-mlogloss:1.37532
[36m(train_xgb_ray_tune pid=325332)[0m [14]	train-mlogloss:1.22995	validation-mlogloss:1.22132
[36m(train_xgb_ray_tune pid=325330)[0m [8]	train-mlogloss:1.27319	validation-mlogloss:1.26712
[36m(train_xgb_ray_tune pid=325344)[0m [22]	train-mlogloss:1.12212	validation-mlogloss:1.11197
[36m(train_xgb_ray_tune pid=325307)[0m [2]	train-mlogloss:1.37298	validation-mlogloss:1.37214
[36m(train_xgb_ray_tune pid=325296)[0m [10]	train-mlogloss:1.30500	validation-mlogloss:1.30045
[36m(train_xgb_ray_tune pid=325296)[0m [11]	train-mlogloss:1.29810	validation-mlogloss:1.29313
[36m(train_xgb_ray_tune pid=325296)[0m [12]	train-mlogloss:1.29145	validation-mlogloss:1.28614
[36m(train_xgb_ray_tune pid=325296)[0m [13]	train-mlogloss:1.28481	validation-mlogloss:1.27906
[36m(train_xgb_ray_tune pid=325296)[0m [14]	train-mlogloss:1.27823	validation-mlogloss:1.27202
[36m(train_xgb_ray_tune pid=325296)[0m [15]	train-mlogloss:1.27166	validation-mlogloss:1.26501
[36m(train_xgb_ray_tune pid=325294)[0m [23]	train-mlogloss:1.30899	validation-mlogloss:1.30579
[36m(train_xgb_ray_tune pid=325294)[0m [24]	train-mlogloss:1.30590	validation-mlogloss:1.30254
[36m(train_xgb_ray_tune pid=325294)[0m [25]	train-mlogloss:1.30298	validation-mlogloss:1.29953
[36m(train_xgb_ray_tune pid=325294)[0m [26]	train-mlogloss:1.30012	validation-mlogloss:1.29654
[36m(train_xgb_ray_tune pid=325294)[0m [27]	train-mlogloss:1.29723	validation-mlogloss:1.29363
[36m(train_xgb_ray_tune pid=325325)[0m [20]	train-mlogloss:1.20507	validation-mlogloss:1.19729
[36m(train_xgb_ray_tune pid=325325)[0m [21]	train-mlogloss:1.19807	validation-mlogloss:1.18993
[36m(train_xgb_ray_tune pid=325325)[0m [22]	train-mlogloss:1.19117	validation-mlogloss:1.18278
[36m(train_xgb_ray_tune pid=325325)[0m [23]	train-mlogloss:1.18401	validation-mlogloss:1.17535
[36m(train_xgb_ray_tune pid=325325)[0m [24]	train-mlogloss:1.17684	validation-mlogloss:1.16805
[36m(train_xgb_ray_tune pid=325327)[0m [2]	train-mlogloss:1.37068	validation-mlogloss:1.36996
[36m(train_xgb_ray_tune pid=325327)[0m [3]	train-mlogloss:1.36562	validation-mlogloss:1.36466
[36m(train_xgb_ray_tune pid=325327)[0m [4]	train-mlogloss:1.36064	validation-mlogloss:1.35942
[36m(train_xgb_ray_tune pid=325344)[0m [23]	train-mlogloss:1.11341	validation-mlogloss:1.10270
[36m(train_xgb_ray_tune pid=325344)[0m [24]	train-mlogloss:1.10499	validation-mlogloss:1.09411
[36m(train_xgb_ray_tune pid=325344)[0m [25]	train-mlogloss:1.09656	validation-mlogloss:1.08551
[36m(train_xgb_ray_tune pid=325344)[0m [26]	train-mlogloss:1.08841	validation-mlogloss:1.07715
[36m(train_xgb_ray_tune pid=325332)[0m [15]	train-mlogloss:1.22110	validation-mlogloss:1.21199
[36m(train_xgb_ray_tune pid=325332)[0m [16]	train-mlogloss:1.21255	validation-mlogloss:1.20309
[36m(train_xgb_ray_tune pid=325332)[0m [17]	train-mlogloss:1.20396	validation-mlogloss:1.19393
[36m(train_xgb_ray_tune pid=325332)[0m [18]	train-mlogloss:1.19555	validation-mlogloss:1.18490
[36m(train_xgb_ray_tune pid=325332)[0m [19]	train-mlogloss:1.18754	validation-mlogloss:1.17643
[36m(train_xgb_ray_tune pid=325332)[0m [20]	train-mlogloss:1.17957	validation-mlogloss:1.16802
[36m(train_xgb_ray_tune pid=325339)[0m [0]	train-mlogloss:1.38234	validation-mlogloss:1.38213
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[36m(train_xgb_ray_tune pid=325341)[0m [3]	train-mlogloss:1.37191	validation-mlogloss:1.37103
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[36m(train_xgb_ray_tune pid=325341)[0m [8]	train-mlogloss:1.35530	validation-mlogloss:1.35353
[36m(train_xgb_ray_tune pid=325307)[0m [3]	train-mlogloss:1.36864	validation-mlogloss:1.36759
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[36m(train_xgb_ray_tune pid=325307)[0m [8]	train-mlogloss:1.34738	validation-mlogloss:1.34528
[36m(train_xgb_ray_tune pid=325340)[0m [0]	train-mlogloss:1.37372	validation-mlogloss:1.37328
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[36m(train_xgb_ray_tune pid=325340)[0m [2]	train-mlogloss:1.34841	validation-mlogloss:1.34668
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[36m(train_xgb_ray_tune pid=325326)[0m [216]	train-mlogloss:0.86672	validation-mlogloss:0.84642
[36m(train_xgb_ray_tune pid=325326)[0m [217]	train-mlogloss:0.86552	validation-mlogloss:0.84513
[36m(train_xgb_ray_tune pid=325326)[0m [218]	train-mlogloss:0.86433	validation-mlogloss:0.84386
[36m(train_xgb_ray_tune pid=325338)[0m [227]	train-mlogloss:0.84113	validation-mlogloss:0.81288
[36m(train_xgb_ray_tune pid=325313)[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=325313)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=325343)[0m 2025-11-03 17:18:29.516045: 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=325343)[0m 2025-11-03 17:18:29.538475: 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=325343)[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=325343)[0m E0000 00:00:1762186709.567995  326579 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=325343)[0m E0000 00:00:1762186709.575867  326579 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=325343)[0m W0000 00:00:1762186709.596830  326579 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=325343)[0m 2025-11-03 17:18:29.603012: 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=325343)[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
[36m(train_xgb_ray_tune pid=325338)[0m [228]	train-mlogloss:0.84037	validation-mlogloss:0.81208
[36m(train_xgb_ray_tune pid=325338)[0m [229]	train-mlogloss:0.83955	validation-mlogloss:0.81117
[36m(train_xgb_ray_tune pid=325338)[0m [230]	train-mlogloss:0.83872	validation-mlogloss:0.81030
[36m(train_xgb_ray_tune pid=325338)[0m [231]	train-mlogloss:0.83790	validation-mlogloss:0.80947
[36m(train_xgb_ray_tune pid=325324)[0m [220]	train-mlogloss:0.67323	validation-mlogloss:0.64426
[36m(train_xgb_ray_tune pid=325324)[0m [221]	train-mlogloss:0.67277	validation-mlogloss:0.64378
[36m(train_xgb_ray_tune pid=325324)[0m [222]	train-mlogloss:0.67234	validation-mlogloss:0.64328
[36m(train_xgb_ray_tune pid=325324)[0m [223]	train-mlogloss:0.67190	validation-mlogloss:0.64282
[36m(train_xgb_ray_tune pid=325324)[0m [224]	train-mlogloss:0.67139	validation-mlogloss:0.64232
[36m(train_xgb_ray_tune pid=325324)[0m [225]	train-mlogloss:0.67089	validation-mlogloss:0.64180
[36m(train_xgb_ray_tune pid=325343)[0m [207]	train-mlogloss:0.61713	validation-mlogloss:0.59326
[36m(train_xgb_ray_tune pid=325343)[0m [208]	train-mlogloss:0.61608	validation-mlogloss:0.59215
[36m(train_xgb_ray_tune pid=325343)[0m [209]	train-mlogloss:0.61517	validation-mlogloss:0.59124
[36m(train_xgb_ray_tune pid=325343)[0m [210]	train-mlogloss:0.61433	validation-mlogloss:0.59042
[36m(train_xgb_ray_tune pid=325343)[0m [211]	train-mlogloss:0.61344	validation-mlogloss:0.58953
[36m(train_xgb_ray_tune pid=325296)[0m [303]	train-mlogloss:0.67187	validation-mlogloss:0.63680
[36m(train_xgb_ray_tune pid=325294)[0m [279]	train-mlogloss:0.86711	validation-mlogloss:0.84406
[36m(train_xgb_ray_tune pid=325325)[0m [278]	train-mlogloss:0.71738	validation-mlogloss:0.69091
[36m(train_xgb_ray_tune pid=325327)[0m [214]	train-mlogloss:0.84979	validation-mlogloss:0.82398
[36m(train_xgb_ray_tune pid=325328)[0m [196]	train-mlogloss:0.82912	validation-mlogloss:0.81461
[36m(train_xgb_ray_tune pid=325330)[0m [263]	train-mlogloss:0.59596	validation-mlogloss:0.56512
[36m(train_xgb_ray_tune pid=325329)[0m [278]	train-mlogloss:0.90987	validation-mlogloss:0.88918
[36m(train_xgb_ray_tune pid=325338)[0m [232]	train-mlogloss:0.83711	validation-mlogloss:0.80864
[36m(train_xgb_ray_tune pid=325296)[0m [304]	train-mlogloss:0.67135	validation-mlogloss:0.63620
[36m(train_xgb_ray_tune pid=325294)[0m [280]	train-mlogloss:0.86628	validation-mlogloss:0.84317
[36m(train_xgb_ray_tune pid=325332)[0m [329]	train-mlogloss:0.62461	validation-mlogloss:0.59012
[36m(train_xgb_ray_tune pid=325339)[0m [215]	train-mlogloss:0.90496	validation-mlogloss:0.88421
[36m(train_xgb_ray_tune pid=325342)[0m [255]	train-mlogloss:0.90609	validation-mlogloss:0.87793
[36m(train_xgb_ray_tune pid=325307)[0m [292]	train-mlogloss:0.80792	validation-mlogloss:0.77835
[36m(train_xgb_ray_tune pid=325329)[0m [279]	train-mlogloss:0.90949	validation-mlogloss:0.88878
[36m(train_xgb_ray_tune pid=325326)[0m [219]	train-mlogloss:0.86324	validation-mlogloss:0.84280
[36m(train_xgb_ray_tune pid=325324)[0m [226]	train-mlogloss:0.67036	validation-mlogloss:0.64120
[36m(train_xgb_ray_tune pid=325343)[0m [212]	train-mlogloss:0.61249	validation-mlogloss:0.58858
[36m(train_xgb_ray_tune pid=325344)[0m [259]	train-mlogloss:0.57859	validation-mlogloss:0.55173
[36m(train_xgb_ray_tune pid=325332)[0m [330]	train-mlogloss:0.62453	validation-mlogloss:0.59005
[36m(train_xgb_ray_tune pid=325341)[0m [295]	train-mlogloss:1.02548	validation-mlogloss:1.00841
[36m(train_xgb_ray_tune pid=325340)[0m [207]	train-mlogloss:0.62377	validation-mlogloss:0.59281
[36m(train_xgb_ray_tune pid=325330)[0m [264]	train-mlogloss:0.59556	validation-mlogloss:0.56463
[36m(train_xgb_ray_tune pid=325338)[0m [233]	train-mlogloss:0.83639	validation-mlogloss:0.80794

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:40. Total running time: 15s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             11.7051 │
│ time_total_s                 11.7051 │
│ training_iteration                 1 │
│ validation_accuracy          0.71531 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=325328)[0m [197]	train-mlogloss:0.82784	validation-mlogloss:0.81327
[36m(train_xgb_ray_tune pid=325342)[0m [256]	train-mlogloss:0.90498	validation-mlogloss:0.87677
[36m(train_xgb_ray_tune pid=325307)[0m [293]	train-mlogloss:0.80710	validation-mlogloss:0.77742
[36m(train_xgb_ray_tune pid=325330)[0m [265]	train-mlogloss:0.59506	validation-mlogloss:0.56404
[36m(train_xgb_ray_tune pid=325331)[0m [219]	train-mlogloss:0.68587	validation-mlogloss:0.65120
[36m(train_xgb_ray_tune pid=325329)[0m [280]	train-mlogloss:0.90912	validation-mlogloss:0.88841
[36m(train_xgb_ray_tune pid=325326)[0m [220]	train-mlogloss:0.86206	validation-mlogloss:0.84156
[36m(train_xgb_ray_tune pid=325324)[0m [227]	train-mlogloss:0.66997	validation-mlogloss:0.64084
[36m(train_xgb_ray_tune pid=325343)[0m [213]	train-mlogloss:0.61154	validation-mlogloss:0.58761

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:40. Total running time: 15s
[36m(train_xgb_ray_tune pid=325296)[0m [305]	train-mlogloss:0.67090	validation-mlogloss:0.63577
[36m(train_xgb_ray_tune pid=325294)[0m [281]	train-mlogloss:0.86538	validation-mlogloss:0.84225
[36m(train_xgb_ray_tune pid=325325)[0m [279]	train-mlogloss:0.71720	validation-mlogloss:0.69068
[36m(train_xgb_ray_tune pid=325325)[0m [280]	train-mlogloss:0.71708	validation-mlogloss:0.69056
[36m(train_xgb_ray_tune pid=325327)[0m [215]	train-mlogloss:0.84876	validation-mlogloss:0.82282
[36m(train_xgb_ray_tune pid=325344)[0m [260]	train-mlogloss:0.57822	validation-mlogloss:0.55139
[36m(train_xgb_ray_tune pid=325332)[0m [331]	train-mlogloss:0.62438	validation-mlogloss:0.58994
[36m(train_xgb_ray_tune pid=325339)[0m [216]	train-mlogloss:0.90380	validation-mlogloss:0.88298
[36m(train_xgb_ray_tune pid=325342)[0m [257]	train-mlogloss:0.90401	validation-mlogloss:0.87579
[36m(train_xgb_ray_tune pid=325307)[0m [294]	train-mlogloss:0.80628	validation-mlogloss:0.77661
[36m(train_xgb_ray_tune pid=325340)[0m [208]	train-mlogloss:0.62309	validation-mlogloss:0.59215
[36m(train_xgb_ray_tune pid=325329)[0m [281]	train-mlogloss:0.90859	validation-mlogloss:0.88791
[36m(train_xgb_ray_tune pid=325338)[0m [234]	train-mlogloss:0.83548	validation-mlogloss:0.80701
[36m(train_xgb_ray_tune pid=325324)[0m [228]	train-mlogloss:0.66948	validation-mlogloss:0.64024
[36m(train_xgb_ray_tune pid=325296)[0m [306]	train-mlogloss:0.67038	validation-mlogloss:0.63520
[36m(train_xgb_ray_tune pid=325294)[0m [282]	train-mlogloss:0.86452	validation-mlogloss:0.84133
[36m(train_xgb_ray_tune pid=325325)[0m [281]	train-mlogloss:0.71688	validation-mlogloss:0.69035
[36m(train_xgb_ray_tune pid=325327)[0m [216]	train-mlogloss:0.84752	validation-mlogloss:0.82155
[36m(train_xgb_ray_tune pid=325344)[0m [261]	train-mlogloss:0.57784	validation-mlogloss:0.55109
[36m(train_xgb_ray_tune pid=325332)[0m [332]	train-mlogloss:0.62417	validation-mlogloss:0.58973
[36m(train_xgb_ray_tune pid=325332)[0m [333]	train-mlogloss:0.62399	validation-mlogloss:0.58958
[36m(train_xgb_ray_tune pid=325328)[0m [198]	train-mlogloss:0.82652	validation-mlogloss:0.81188
[36m(train_xgb_ray_tune pid=325339)[0m [217]	train-mlogloss:0.90271	validation-mlogloss:0.88178
[36m(train_xgb_ray_tune pid=325342)[0m [258]	train-mlogloss:0.90304	validation-mlogloss:0.87478
[36m(train_xgb_ray_tune pid=325341)[0m [296]	train-mlogloss:1.02515	validation-mlogloss:1.00806
[36m(train_xgb_ray_tune pid=325307)[0m [295]	train-mlogloss:0.80553	validation-mlogloss:0.77584
[36m(train_xgb_ray_tune pid=325330)[0m [266]	train-mlogloss:0.59477	validation-mlogloss:0.56373
[36m(train_xgb_ray_tune pid=325330)[0m [267]	train-mlogloss:0.59444	validation-mlogloss:0.56356
[36m(train_xgb_ray_tune pid=325329)[0m [282]	train-mlogloss:0.90798	validation-mlogloss:0.88727
[36m(train_xgb_ray_tune pid=325326)[0m [221]	train-mlogloss:0.86088	validation-mlogloss:0.84029
[36m(train_xgb_ray_tune pid=325326)[0m [222]	train-mlogloss:0.85971	validation-mlogloss:0.83902
[36m(train_xgb_ray_tune pid=325338)[0m [235]	train-mlogloss:0.83482	validation-mlogloss:0.80627
[36m(train_xgb_ray_tune pid=325324)[0m [229]	train-mlogloss:0.66905	validation-mlogloss:0.63977
[36m(train_xgb_ray_tune pid=325343)[0m [214]	train-mlogloss:0.61057	validation-mlogloss:0.58674
[36m(train_xgb_ray_tune pid=325343)[0m [215]	train-mlogloss:0.60968	validation-mlogloss:0.58596
[36m(train_xgb_ray_tune pid=325296)[0m [307]	train-mlogloss:0.66994	validation-mlogloss:0.63473
[36m(train_xgb_ray_tune pid=325296)[0m [308]	train-mlogloss:0.66955	validation-mlogloss:0.63435
[36m(train_xgb_ray_tune pid=325294)[0m [283]	train-mlogloss:0.86363	validation-mlogloss:0.84035
[36m(train_xgb_ray_tune pid=325325)[0m [282]	train-mlogloss:0.71659	validation-mlogloss:0.69008
[36m(train_xgb_ray_tune pid=325325)[0m [283]	train-mlogloss:0.71619	validation-mlogloss:0.68960
[36m(train_xgb_ray_tune pid=325327)[0m [217]	train-mlogloss:0.84653	validation-mlogloss:0.82044
[36m(train_xgb_ray_tune pid=325332)[0m [334]	train-mlogloss:0.62374	validation-mlogloss:0.58928
[36m(train_xgb_ray_tune pid=325328)[0m [199]	train-mlogloss:0.82509	validation-mlogloss:0.81042
[36m(train_xgb_ray_tune pid=325339)[0m [218]	train-mlogloss:0.90160	validation-mlogloss:0.88061
[36m(train_xgb_ray_tune pid=325341)[0m [297]	train-mlogloss:1.02496	validation-mlogloss:1.00787
[36m(train_xgb_ray_tune pid=325307)[0m [296]	train-mlogloss:0.80458	validation-mlogloss:0.77481
[36m(train_xgb_ray_tune pid=325340)[0m [209]	train-mlogloss:0.62238	validation-mlogloss:0.59149
[36m(train_xgb_ray_tune pid=325330)[0m [268]	train-mlogloss:0.59422	validation-mlogloss:0.56339
[36m(train_xgb_ray_tune pid=325331)[0m [220]	train-mlogloss:0.68525	validation-mlogloss:0.65045
[36m(train_xgb_ray_tune pid=325329)[0m [283]	train-mlogloss:0.90754	validation-mlogloss:0.88681
[36m(train_xgb_ray_tune pid=325329)[0m [284]	train-mlogloss:0.90696	validation-mlogloss:0.88623
[36m(train_xgb_ray_tune pid=325326)[0m [223]	train-mlogloss:0.85859	validation-mlogloss:0.83793
[36m(train_xgb_ray_tune pid=325338)[0m [236]	train-mlogloss:0.83396	validation-mlogloss:0.80540
[36m(train_xgb_ray_tune pid=325324)[0m [230]	train-mlogloss:0.66873	validation-mlogloss:0.63947
[36m(train_xgb_ray_tune pid=325296)[0m [309]	train-mlogloss:0.66914	validation-mlogloss:0.63389
[36m(train_xgb_ray_tune pid=325294)[0m [284]	train-mlogloss:0.86280	validation-mlogloss:0.83948
[36m(train_xgb_ray_tune pid=325325)[0m [284]	train-mlogloss:0.71599	validation-mlogloss:0.68940
[36m(train_xgb_ray_tune pid=325327)[0m [218]	train-mlogloss:0.84536	validation-mlogloss:0.81924
[36m(train_xgb_ray_tune pid=325344)[0m [262]	train-mlogloss:0.57752	validation-mlogloss:0.55072
[36m(train_xgb_ray_tune pid=325332)[0m [335]	train-mlogloss:0.62361	validation-mlogloss:0.58912
[36m(train_xgb_ray_tune pid=325328)[0m [200]	train-mlogloss:0.82379	validation-mlogloss:0.80902
[36m(train_xgb_ray_tune pid=325342)[0m [259]	train-mlogloss:0.90208	validation-mlogloss:0.87374
[36m(train_xgb_ray_tune pid=325307)[0m [297]	train-mlogloss:0.80362	validation-mlogloss:0.77385
[36m(train_xgb_ray_tune pid=325340)[0m [210]	train-mlogloss:0.62171	validation-mlogloss:0.59089
[36m(train_xgb_ray_tune pid=325330)[0m [269]	train-mlogloss:0.59388	validation-mlogloss:0.56296
[36m(train_xgb_ray_tune pid=325330)[0m [270]	train-mlogloss:0.59361	validation-mlogloss:0.56267
[36m(train_xgb_ray_tune pid=325331)[0m [221]	train-mlogloss:0.68469	validation-mlogloss:0.64989
[36m(train_xgb_ray_tune pid=325329)[0m [285]	train-mlogloss:0.90644	validation-mlogloss:0.88570
[36m(train_xgb_ray_tune pid=325338)[0m [237]	train-mlogloss:0.83307	validation-mlogloss:0.80450
[36m(train_xgb_ray_tune pid=325324)[0m [231]	train-mlogloss:0.66831	validation-mlogloss:0.63908
[36m(train_xgb_ray_tune pid=325343)[0m [216]	train-mlogloss:0.60879	validation-mlogloss:0.58505
[36m(train_xgb_ray_tune pid=325296)[0m [310]	train-mlogloss:0.66872	validation-mlogloss:0.63347
[36m(train_xgb_ray_tune pid=325294)[0m [285]	train-mlogloss:0.86179	validation-mlogloss:0.83845
[36m(train_xgb_ray_tune pid=325325)[0m [285]	train-mlogloss:0.71581	validation-mlogloss:0.68918
[36m(train_xgb_ray_tune pid=325327)[0m [219]	train-mlogloss:0.84416	validation-mlogloss:0.81795
[36m(train_xgb_ray_tune pid=325344)[0m [263]	train-mlogloss:0.57723	validation-mlogloss:0.55035
[36m(train_xgb_ray_tune pid=325332)[0m [336]	train-mlogloss:0.62342	validation-mlogloss:0.58898
[36m(train_xgb_ray_tune pid=325332)[0m [337]	train-mlogloss:0.62327	validation-mlogloss:0.58884
[36m(train_xgb_ray_tune pid=325328)[0m [201]	train-mlogloss:0.82251	validation-mlogloss:0.80775
[36m(train_xgb_ray_tune pid=325339)[0m [219]	train-mlogloss:0.90048	validation-mlogloss:0.87943
[36m(train_xgb_ray_tune pid=325342)[0m [260]	train-mlogloss:0.90117	validation-mlogloss:0.87275
[36m(train_xgb_ray_tune pid=325341)[0m [298]	train-mlogloss:1.02445	validation-mlogloss:1.00731
[36m(train_xgb_ray_tune pid=325307)[0m [298]	train-mlogloss:0.80286	validation-mlogloss:0.77304
[36m(train_xgb_ray_tune pid=325330)[0m [271]	train-mlogloss:0.59312	validation-mlogloss:0.56206
[36m(train_xgb_ray_tune pid=325329)[0m [286]	train-mlogloss:0.90601	validation-mlogloss:0.88523
[36m(train_xgb_ray_tune pid=325326)[0m [224]	train-mlogloss:0.85744	validation-mlogloss:0.83662
[36m(train_xgb_ray_tune pid=325324)[0m [232]	train-mlogloss:0.66788	validation-mlogloss:0.63870
[36m(train_xgb_ray_tune pid=325343)[0m [217]	train-mlogloss:0.60790	validation-mlogloss:0.58423
[36m(train_xgb_ray_tune pid=325296)[0m [311]	train-mlogloss:0.66829	validation-mlogloss:0.63300
[36m(train_xgb_ray_tune pid=325325)[0m [286]	train-mlogloss:0.71561	validation-mlogloss:0.68894
[36m(train_xgb_ray_tune pid=325339)[0m [220]	train-mlogloss:0.89930	validation-mlogloss:0.87815
[36m(train_xgb_ray_tune pid=325341)[0m [299]	train-mlogloss:1.02415	validation-mlogloss:1.00701
[36m(train_xgb_ray_tune pid=325331)[0m [222]	train-mlogloss:0.68416	validation-mlogloss:0.64932
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[36m(train_xgb_ray_tune pid=325330)[0m [348]	train-mlogloss:0.58022	validation-mlogloss:0.54846
[36m(train_xgb_ray_tune pid=325331)[0m [327]	train-mlogloss:0.65599	validation-mlogloss:0.62097
[36m(train_xgb_ray_tune pid=325326)[0m [304]	train-mlogloss:0.77960	validation-mlogloss:0.75480
[36m(train_xgb_ray_tune pid=325338)[0m [309]	train-mlogloss:0.79155	validation-mlogloss:0.76232
[36m(train_xgb_ray_tune pid=325343)[0m [283]	train-mlogloss:0.56294	validation-mlogloss:0.54234
[36m(train_xgb_ray_tune pid=325296)[0m [417]	train-mlogloss:0.63925	validation-mlogloss:0.60298
[36m(train_xgb_ray_tune pid=325325)[0m [395]	train-mlogloss:0.70912	validation-mlogloss:0.68218
[36m(train_xgb_ray_tune pid=325344)[0m [341]	train-mlogloss:0.56008	validation-mlogloss:0.53360
[36m(train_xgb_ray_tune pid=325342)[0m [335]	train-mlogloss:0.83543	validation-mlogloss:0.80368
[36m(train_xgb_ray_tune pid=325341)[0m [413]	train-mlogloss:1.01076	validation-mlogloss:0.99295
[36m(train_xgb_ray_tune pid=325307)[0m [369]	train-mlogloss:0.75209	validation-mlogloss:0.72039
[36m(train_xgb_ray_tune pid=325340)[0m [276]	train-mlogloss:0.59193	validation-mlogloss:0.56085
[36m(train_xgb_ray_tune pid=325324)[0m [327]	train-mlogloss:0.64359	validation-mlogloss:0.61393
[36m(train_xgb_ray_tune pid=325296)[0m [418]	train-mlogloss:0.63910	validation-mlogloss:0.60285
[36m(train_xgb_ray_tune pid=325294)[0m [352]	train-mlogloss:0.80832	validation-mlogloss:0.78219
[36m(train_xgb_ray_tune pid=325327)[0m [291]	train-mlogloss:0.77985	validation-mlogloss:0.75057
[36m(train_xgb_ray_tune pid=325344)[0m [342]	train-mlogloss:0.55991	validation-mlogloss:0.53340
[36m(train_xgb_ray_tune pid=325328)[0m [258]	train-mlogloss:0.75900	validation-mlogloss:0.74225
[36m(train_xgb_ray_tune pid=325339)[0m [295]	train-mlogloss:0.82549	validation-mlogloss:0.80024
[36m(train_xgb_ray_tune pid=325341)[0m [414]	train-mlogloss:1.01058	validation-mlogloss:0.99276
[36m(train_xgb_ray_tune pid=325331)[0m [328]	train-mlogloss:0.65588	validation-mlogloss:0.62081
[36m(train_xgb_ray_tune pid=325329)[0m [370]	train-mlogloss:0.87606	validation-mlogloss:0.85467
[36m(train_xgb_ray_tune pid=325326)[0m [305]	train-mlogloss:0.77877	validation-mlogloss:0.75391
[36m(train_xgb_ray_tune pid=325338)[0m [310]	train-mlogloss:0.79107	validation-mlogloss:0.76187
[36m(train_xgb_ray_tune pid=325343)[0m [284]	train-mlogloss:0.56235	validation-mlogloss:0.54171
[36m(train_xgb_ray_tune pid=325296)[0m [419]	train-mlogloss:0.63895	validation-mlogloss:0.60270
[36m(train_xgb_ray_tune pid=325294)[0m [353]	train-mlogloss:0.80767	validation-mlogloss:0.78150
[36m(train_xgb_ray_tune pid=325325)[0m [396]	train-mlogloss:0.70912	validation-mlogloss:0.68218
[36m(train_xgb_ray_tune pid=325342)[0m [336]	train-mlogloss:0.83467	validation-mlogloss:0.80288
[36m(train_xgb_ray_tune pid=325341)[0m [415]	train-mlogloss:1.01058	validation-mlogloss:0.99276
[36m(train_xgb_ray_tune pid=325307)[0m [370]	train-mlogloss:0.75147	validation-mlogloss:0.71979
[36m(train_xgb_ray_tune pid=325340)[0m [277]	train-mlogloss:0.59164	validation-mlogloss:0.56062
[36m(train_xgb_ray_tune pid=325330)[0m [349]	train-mlogloss:0.58008	validation-mlogloss:0.54829
[36m(train_xgb_ray_tune pid=325331)[0m [329]	train-mlogloss:0.65577	validation-mlogloss:0.62073
[36m(train_xgb_ray_tune pid=325326)[0m [306]	train-mlogloss:0.77794	validation-mlogloss:0.75306
[36m(train_xgb_ray_tune pid=325338)[0m [311]	train-mlogloss:0.79066	validation-mlogloss:0.76149
[36m(train_xgb_ray_tune pid=325343)[0m [285]	train-mlogloss:0.56188	validation-mlogloss:0.54128
[36m(train_xgb_ray_tune pid=325325)[0m [397]	train-mlogloss:0.70912	validation-mlogloss:0.68218
[36m(train_xgb_ray_tune pid=325344)[0m [343]	train-mlogloss:0.55977	validation-mlogloss:0.53322
[36m(train_xgb_ray_tune pid=325328)[0m [259]	train-mlogloss:0.75802	validation-mlogloss:0.74122
[36m(train_xgb_ray_tune pid=325339)[0m [296]	train-mlogloss:0.82468	validation-mlogloss:0.79941
[36m(train_xgb_ray_tune pid=325342)[0m [337]	train-mlogloss:0.83390	validation-mlogloss:0.80212
[36m(train_xgb_ray_tune pid=325341)[0m [416]	train-mlogloss:1.01058	validation-mlogloss:0.99276
[36m(train_xgb_ray_tune pid=325340)[0m [278]	train-mlogloss:0.59144	validation-mlogloss:0.56046
[36m(train_xgb_ray_tune pid=325330)[0m [350]	train-mlogloss:0.58000	validation-mlogloss:0.54823
[36m(train_xgb_ray_tune pid=325331)[0m [330]	train-mlogloss:0.65568	validation-mlogloss:0.62065
[36m(train_xgb_ray_tune pid=325331)[0m [331]	train-mlogloss:0.65557	validation-mlogloss:0.62057
[36m(train_xgb_ray_tune pid=325329)[0m [371]	train-mlogloss:0.87568	validation-mlogloss:0.85433
[36m(train_xgb_ray_tune pid=325329)[0m [372]	train-mlogloss:0.87552	validation-mlogloss:0.85413
[36m(train_xgb_ray_tune pid=325326)[0m [307]	train-mlogloss:0.77710	validation-mlogloss:0.75217
[36m(train_xgb_ray_tune pid=325324)[0m [328]	train-mlogloss:0.64332	validation-mlogloss:0.61362
[36m(train_xgb_ray_tune pid=325343)[0m [286]	train-mlogloss:0.56139	validation-mlogloss:0.54085
[36m(train_xgb_ray_tune pid=325296)[0m [420]	train-mlogloss:0.63880	validation-mlogloss:0.60256
[36m(train_xgb_ray_tune pid=325294)[0m [354]	train-mlogloss:0.80691	validation-mlogloss:0.78071
[36m(train_xgb_ray_tune pid=325325)[0m [398]	train-mlogloss:0.70912	validation-mlogloss:0.68218
[36m(train_xgb_ray_tune pid=325325)[0m [399]	train-mlogloss:0.70912	validation-mlogloss:0.68218
[36m(train_xgb_ray_tune pid=325327)[0m [292]	train-mlogloss:0.77911	validation-mlogloss:0.74977
[36m(train_xgb_ray_tune pid=325344)[0m [344]	train-mlogloss:0.55964	validation-mlogloss:0.53311
[36m(train_xgb_ray_tune pid=325344)[0m [345]	train-mlogloss:0.55954	validation-mlogloss:0.53300
[36m(train_xgb_ray_tune pid=325328)[0m [260]	train-mlogloss:0.75700	validation-mlogloss:0.74021
[36m(train_xgb_ray_tune pid=325339)[0m [297]	train-mlogloss:0.82385	validation-mlogloss:0.79853
[36m(train_xgb_ray_tune pid=325342)[0m [338]	train-mlogloss:0.83308	validation-mlogloss:0.80126
[36m(train_xgb_ray_tune pid=325341)[0m [417]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325341)[0m [418]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325307)[0m [371]	train-mlogloss:0.75087	validation-mlogloss:0.71914
[36m(train_xgb_ray_tune pid=325340)[0m [279]	train-mlogloss:0.59115	validation-mlogloss:0.56014
[36m(train_xgb_ray_tune pid=325330)[0m [351]	train-mlogloss:0.57986	validation-mlogloss:0.54809
[36m(train_xgb_ray_tune pid=325331)[0m [332]	train-mlogloss:0.65548	validation-mlogloss:0.62049
[36m(train_xgb_ray_tune pid=325331)[0m [333]	train-mlogloss:0.65529	validation-mlogloss:0.62033
[36m(train_xgb_ray_tune pid=325329)[0m [373]	train-mlogloss:0.87529	validation-mlogloss:0.85387
[36m(train_xgb_ray_tune pid=325326)[0m [308]	train-mlogloss:0.77622	validation-mlogloss:0.75129
[36m(train_xgb_ray_tune pid=325338)[0m [312]	train-mlogloss:0.79019	validation-mlogloss:0.76103

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:42. Total running time: 17s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             13.8082 │
│ time_total_s                 13.8082 │
│ training_iteration                 1 │
│ validation_accuracy          0.77112 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=325343)[0m [287]	train-mlogloss:0.56086	validation-mlogloss:0.54026
[36m(train_xgb_ray_tune pid=325296)[0m [421]	train-mlogloss:0.63858	validation-mlogloss:0.60228
[36m(train_xgb_ray_tune pid=325296)[0m [422]	train-mlogloss:0.63843	validation-mlogloss:0.60210
[36m(train_xgb_ray_tune pid=325294)[0m [355]	train-mlogloss:0.80627	validation-mlogloss:0.78005
[36m(train_xgb_ray_tune pid=325325)[0m [400]	train-mlogloss:0.70912	validation-mlogloss:0.68218
[36m(train_xgb_ray_tune pid=325327)[0m [293]	train-mlogloss:0.77833	validation-mlogloss:0.74898
[36m(train_xgb_ray_tune pid=325344)[0m [346]	train-mlogloss:0.55945	validation-mlogloss:0.53289
[36m(train_xgb_ray_tune pid=325339)[0m [298]	train-mlogloss:0.82311	validation-mlogloss:0.79776
[36m(train_xgb_ray_tune pid=325342)[0m [339]	train-mlogloss:0.83227	validation-mlogloss:0.80042
[36m(train_xgb_ray_tune pid=325341)[0m [419]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325307)[0m [372]	train-mlogloss:0.75026	validation-mlogloss:0.71853
[36m(train_xgb_ray_tune pid=325340)[0m [280]	train-mlogloss:0.59085	validation-mlogloss:0.55977
[36m(train_xgb_ray_tune pid=325330)[0m [352]	train-mlogloss:0.57978	validation-mlogloss:0.54803
[36m(train_xgb_ray_tune pid=325331)[0m [334]	train-mlogloss:0.65519	validation-mlogloss:0.62023
[36m(train_xgb_ray_tune pid=325329)[0m [374]	train-mlogloss:0.87505	validation-mlogloss:0.85361
[36m(train_xgb_ray_tune pid=325326)[0m [309]	train-mlogloss:0.77537	validation-mlogloss:0.75046
[36m(train_xgb_ray_tune pid=325338)[0m [313]	train-mlogloss:0.78973	validation-mlogloss:0.76056
[36m(train_xgb_ray_tune pid=325324)[0m [329]	train-mlogloss:0.64306	validation-mlogloss:0.61333

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:42. Total running time: 17s
[36m(train_xgb_ray_tune pid=325294)[0m [356]	train-mlogloss:0.80556	validation-mlogloss:0.77934
[36m(train_xgb_ray_tune pid=325325)[0m [401]	train-mlogloss:0.70912	validation-mlogloss:0.68218
[36m(train_xgb_ray_tune pid=325344)[0m [347]	train-mlogloss:0.55925	validation-mlogloss:0.53264
[36m(train_xgb_ray_tune pid=325328)[0m [261]	train-mlogloss:0.75600	validation-mlogloss:0.73919
[36m(train_xgb_ray_tune pid=325342)[0m [340]	train-mlogloss:0.83163	validation-mlogloss:0.79973
[36m(train_xgb_ray_tune pid=325341)[0m [420]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325340)[0m [281]	train-mlogloss:0.59061	validation-mlogloss:0.55957
[36m(train_xgb_ray_tune pid=325330)[0m [353]	train-mlogloss:0.57970	validation-mlogloss:0.54796
[36m(train_xgb_ray_tune pid=325329)[0m [375]	train-mlogloss:0.87483	validation-mlogloss:0.85336
[36m(train_xgb_ray_tune pid=325296)[0m [423]	train-mlogloss:0.63830	validation-mlogloss:0.60200
[36m(train_xgb_ray_tune pid=325331)[0m [335]	train-mlogloss:0.65509	validation-mlogloss:0.62016
[36m(train_xgb_ray_tune pid=325326)[0m [310]	train-mlogloss:0.77448	validation-mlogloss:0.74950
[36m(train_xgb_ray_tune pid=325325)[0m [402]	train-mlogloss:0.70912	validation-mlogloss:0.68218
[36m(train_xgb_ray_tune pid=325327)[0m [294]	train-mlogloss:0.77766	validation-mlogloss:0.74832
[36m(train_xgb_ray_tune pid=325339)[0m [299]	train-mlogloss:0.82228	validation-mlogloss:0.79692
[36m(train_xgb_ray_tune pid=325341)[0m [421]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325340)[0m [282]	train-mlogloss:0.59030	validation-mlogloss:0.55921
[36m(train_xgb_ray_tune pid=325329)[0m [376]	train-mlogloss:0.87467	validation-mlogloss:0.85317
[36m(train_xgb_ray_tune pid=325343)[0m [288]	train-mlogloss:0.56035	validation-mlogloss:0.53987
[36m(train_xgb_ray_tune pid=325296)[0m [424]	train-mlogloss:0.63815	validation-mlogloss:0.60183
[36m(train_xgb_ray_tune pid=325296)[0m [425]	train-mlogloss:0.63800	validation-mlogloss:0.60169
[36m(train_xgb_ray_tune pid=325296)[0m [426]	train-mlogloss:0.63780	validation-mlogloss:0.60146
[36m(train_xgb_ray_tune pid=325296)[0m [427]	train-mlogloss:0.63766	validation-mlogloss:0.60135
[36m(train_xgb_ray_tune pid=325296)[0m [428]	train-mlogloss:0.63751	validation-mlogloss:0.60119
[36m(train_xgb_ray_tune pid=325296)[0m [429]	train-mlogloss:0.63733	validation-mlogloss:0.60104
[36m(train_xgb_ray_tune pid=325294)[0m [357]	train-mlogloss:0.80482	validation-mlogloss:0.77856
[36m(train_xgb_ray_tune pid=325294)[0m [358]	train-mlogloss:0.80410	validation-mlogloss:0.77782
[36m(train_xgb_ray_tune pid=325325)[0m [403]	train-mlogloss:0.70912	validation-mlogloss:0.68218
[36m(train_xgb_ray_tune pid=325325)[0m [404]	train-mlogloss:0.70912	validation-mlogloss:0.68218
[36m(train_xgb_ray_tune pid=325325)[0m [405]	train-mlogloss:0.70912	validation-mlogloss:0.68218
[36m(train_xgb_ray_tune pid=325325)[0m [406]	train-mlogloss:0.70896	validation-mlogloss:0.68205
[36m(train_xgb_ray_tune pid=325325)[0m [407]	train-mlogloss:0.70896	validation-mlogloss:0.68205
[36m(train_xgb_ray_tune pid=325325)[0m [408]	train-mlogloss:0.70896	validation-mlogloss:0.68205
[36m(train_xgb_ray_tune pid=325325)[0m [409]	train-mlogloss:0.70896	validation-mlogloss:0.68205
[36m(train_xgb_ray_tune pid=325325)[0m [410]	train-mlogloss:0.70896	validation-mlogloss:0.68205
[36m(train_xgb_ray_tune pid=325327)[0m [295]	train-mlogloss:0.77705	validation-mlogloss:0.74765
[36m(train_xgb_ray_tune pid=325327)[0m [296]	train-mlogloss:0.77644	validation-mlogloss:0.74698
[36m(train_xgb_ray_tune pid=325327)[0m [297]	train-mlogloss:0.77574	validation-mlogloss:0.74624
[36m(train_xgb_ray_tune pid=325327)[0m [298]	train-mlogloss:0.77514	validation-mlogloss:0.74557
[36m(train_xgb_ray_tune pid=325327)[0m [299]	train-mlogloss:0.77457	validation-mlogloss:0.74496
[36m(train_xgb_ray_tune pid=325344)[0m [348]	train-mlogloss:0.55901	validation-mlogloss:0.53247
[36m(train_xgb_ray_tune pid=325344)[0m [349]	train-mlogloss:0.55887	validation-mlogloss:0.53235
[36m(train_xgb_ray_tune pid=325344)[0m [350]	train-mlogloss:0.55872	validation-mlogloss:0.53213
[36m(train_xgb_ray_tune pid=325344)[0m [351]	train-mlogloss:0.55858	validation-mlogloss:0.53197
[36m(train_xgb_ray_tune pid=325344)[0m [352]	train-mlogloss:0.55845	validation-mlogloss:0.53186
[36m(train_xgb_ray_tune pid=325344)[0m [353]	train-mlogloss:0.55840	validation-mlogloss:0.53181
[36m(train_xgb_ray_tune pid=325344)[0m [354]	train-mlogloss:0.55831	validation-mlogloss:0.53172
[36m(train_xgb_ray_tune pid=325328)[0m [262]	train-mlogloss:0.75511	validation-mlogloss:0.73824
[36m(train_xgb_ray_tune pid=325328)[0m [263]	train-mlogloss:0.75412	validation-mlogloss:0.73725
[36m(train_xgb_ray_tune pid=325328)[0m [264]	train-mlogloss:0.75316	validation-mlogloss:0.73626
[36m(train_xgb_ray_tune pid=325328)[0m [265]	train-mlogloss:0.75218	validation-mlogloss:0.73522
[36m(train_xgb_ray_tune pid=325339)[0m [300]	train-mlogloss:0.82139	validation-mlogloss:0.79601
[36m(train_xgb_ray_tune pid=325339)[0m [301]	train-mlogloss:0.82069	validation-mlogloss:0.79523
[36m(train_xgb_ray_tune pid=325339)[0m [302]	train-mlogloss:0.81994	validation-mlogloss:0.79446
[36m(train_xgb_ray_tune pid=325339)[0m [303]	train-mlogloss:0.81921	validation-mlogloss:0.79374
[36m(train_xgb_ray_tune pid=325339)[0m [304]	train-mlogloss:0.81846	validation-mlogloss:0.79294
[36m(train_xgb_ray_tune pid=325342)[0m [341]	train-mlogloss:0.83086	validation-mlogloss:0.79892
[36m(train_xgb_ray_tune pid=325342)[0m [342]	train-mlogloss:0.83009	validation-mlogloss:0.79808
[36m(train_xgb_ray_tune pid=325342)[0m [343]	train-mlogloss:0.82940	validation-mlogloss:0.79735
[36m(train_xgb_ray_tune pid=325342)[0m [344]	train-mlogloss:0.82863	validation-mlogloss:0.79653
[36m(train_xgb_ray_tune pid=325342)[0m [345]	train-mlogloss:0.82796	validation-mlogloss:0.79588
[36m(train_xgb_ray_tune pid=325342)[0m [346]	train-mlogloss:0.82725	validation-mlogloss:0.79513
[36m(train_xgb_ray_tune pid=325341)[0m [422]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325341)[0m [423]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325341)[0m [424]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325341)[0m [425]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325341)[0m [426]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325341)[0m [427]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325341)[0m [428]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325341)[0m [429]	train-mlogloss:1.01039	validation-mlogloss:0.99256
[36m(train_xgb_ray_tune pid=325307)[0m [373]	train-mlogloss:0.74972	validation-mlogloss:0.71797
[36m(train_xgb_ray_tune pid=325307)[0m [374]	train-mlogloss:0.74903	validation-mlogloss:0.71728
[36m(train_xgb_ray_tune pid=325307)[0m [375]	train-mlogloss:0.74851	validation-mlogloss:0.71677
[36m(train_xgb_ray_tune pid=325307)[0m [376]	train-mlogloss:0.74793	validation-mlogloss:0.71610
[36m(train_xgb_ray_tune pid=325307)[0m [377]	train-mlogloss:0.74737	validation-mlogloss:0.71553
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[36m(train_xgb_ray_tune pid=325307)[0m [385]	train-mlogloss:0.74262	validation-mlogloss:0.71058
[36m(train_xgb_ray_tune pid=325338)[0m [328]	train-mlogloss:0.78340	validation-mlogloss:0.75432
[36m(train_xgb_ray_tune pid=325296)[0m [438]	train-mlogloss:0.63588	validation-mlogloss:0.59951
[36m(train_xgb_ray_tune pid=325325)[0m [421]	train-mlogloss:0.70896	validation-mlogloss:0.68205
[36m(train_xgb_ray_tune pid=325327)[0m [307]	train-mlogloss:0.76960	validation-mlogloss:0.73976
[36m(train_xgb_ray_tune pid=325339)[0m [311]	train-mlogloss:0.81295	validation-mlogloss:0.78713
[36m(train_xgb_ray_tune pid=325341)[0m [439]	train-mlogloss:1.00928	validation-mlogloss:0.99143
[36m(train_xgb_ray_tune pid=325307)[0m [386]	train-mlogloss:0.74205	validation-mlogloss:0.71000
[36m(train_xgb_ray_tune pid=325340)[0m [297]	train-mlogloss:0.58600	validation-mlogloss:0.55496
[36m(train_xgb_ray_tune pid=325330)[0m [366]	train-mlogloss:0.57851	validation-mlogloss:0.54668
[36m(train_xgb_ray_tune pid=325331)[0m [356]	train-mlogloss:0.65329	validation-mlogloss:0.61823
[36m(train_xgb_ray_tune pid=325331)[0m [357]	train-mlogloss:0.65329	validation-mlogloss:0.61823
[36m(train_xgb_ray_tune pid=325326)[0m [324]	train-mlogloss:0.76369	validation-mlogloss:0.73815
[36m(train_xgb_ray_tune pid=325324)[0m [344]	train-mlogloss:0.64159	validation-mlogloss:0.61183
[36m(train_xgb_ray_tune pid=325343)[0m [299]	train-mlogloss:0.55513	validation-mlogloss:0.53540
[36m(train_xgb_ray_tune pid=325294)[0m [363]	train-mlogloss:0.80080	validation-mlogloss:0.77423
[36m(train_xgb_ray_tune pid=325325)[0m [422]	train-mlogloss:0.70896	validation-mlogloss:0.68205
[36m(train_xgb_ray_tune pid=325344)[0m [364]	train-mlogloss:0.55693	validation-mlogloss:0.53015
[36m(train_xgb_ray_tune pid=325328)[0m [272]	train-mlogloss:0.74594	validation-mlogloss:0.72883
[36m(train_xgb_ray_tune pid=325342)[0m [354]	train-mlogloss:0.82152	validation-mlogloss:0.78904
[36m(train_xgb_ray_tune pid=325341)[0m [440]	train-mlogloss:1.00928	validation-mlogloss:0.99143

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:42. Total running time: 17s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             14.0524 │
│ time_total_s                 14.0524 │
│ training_iteration                 1 │
│ validation_accuracy          0.72474 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:42. Total running time: 17s
[36m(train_xgb_ray_tune pid=325330)[0m [367]	train-mlogloss:0.57844	validation-mlogloss:0.54657
[36m(train_xgb_ray_tune pid=325338)[0m [329]	train-mlogloss:0.78297	validation-mlogloss:0.75389
[36m(train_xgb_ray_tune pid=325324)[0m [345]	train-mlogloss:0.64152	validation-mlogloss:0.61178
[36m(train_xgb_ray_tune pid=325296)[0m [439]	train-mlogloss:0.63569	validation-mlogloss:0.59929
[36m(train_xgb_ray_tune pid=325294)[0m [364]	train-mlogloss:0.80021	validation-mlogloss:0.77363
[36m(train_xgb_ray_tune pid=325325)[0m [423]	train-mlogloss:0.70896	validation-mlogloss:0.68205
[36m(train_xgb_ray_tune pid=325327)[0m [308]	train-mlogloss:0.76895	validation-mlogloss:0.73910
[36m(train_xgb_ray_tune pid=325344)[0m [365]	train-mlogloss:0.55681	validation-mlogloss:0.52996
[36m(train_xgb_ray_tune pid=325339)[0m [312]	train-mlogloss:0.81216	validation-mlogloss:0.78631
[36m(train_xgb_ray_tune pid=325341)[0m [441]	train-mlogloss:1.00928	validation-mlogloss:0.99143
[36m(train_xgb_ray_tune pid=325307)[0m [387]	train-mlogloss:0.74152	validation-mlogloss:0.70951
[36m(train_xgb_ray_tune pid=325340)[0m [298]	train-mlogloss:0.58571	validation-mlogloss:0.55466
[36m(train_xgb_ray_tune pid=325330)[0m [368]	train-mlogloss:0.57836	validation-mlogloss:0.54652
[36m(train_xgb_ray_tune pid=325331)[0m [358]	train-mlogloss:0.65319	validation-mlogloss:0.61816
[36m(train_xgb_ray_tune pid=325331)[0m [359]	train-mlogloss:0.65319	validation-mlogloss:0.61816
[36m(train_xgb_ray_tune pid=325326)[0m [325]	train-mlogloss:0.76291	validation-mlogloss:0.73738
[36m(train_xgb_ray_tune pid=325338)[0m [330]	train-mlogloss:0.78254	validation-mlogloss:0.75345
[36m(train_xgb_ray_tune pid=325324)[0m [346]	train-mlogloss:0.64152	validation-mlogloss:0.61178
[36m(train_xgb_ray_tune pid=325343)[0m [300]	train-mlogloss:0.55468	validation-mlogloss:0.53490
[36m(train_xgb_ray_tune pid=325296)[0m [440]	train-mlogloss:0.63550	validation-mlogloss:0.59910
[36m(train_xgb_ray_tune pid=325296)[0m [441]	train-mlogloss:0.63530	validation-mlogloss:0.59883
[36m(train_xgb_ray_tune pid=325325)[0m [424]	train-mlogloss:0.70896	validation-mlogloss:0.68205
[36m(train_xgb_ray_tune pid=325344)[0m [366]	train-mlogloss:0.55676	validation-mlogloss:0.52993
[36m(train_xgb_ray_tune pid=325328)[0m [273]	train-mlogloss:0.74511	validation-mlogloss:0.72794
[36m(train_xgb_ray_tune pid=325339)[0m [313]	train-mlogloss:0.81143	validation-mlogloss:0.78559
[36m(train_xgb_ray_tune pid=325342)[0m [355]	train-mlogloss:0.82079	validation-mlogloss:0.78828
[36m(train_xgb_ray_tune pid=325341)[0m [442]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325307)[0m [388]	train-mlogloss:0.74102	validation-mlogloss:0.70897
[36m(train_xgb_ray_tune pid=325340)[0m [299]	train-mlogloss:0.58554	validation-mlogloss:0.55452
[36m(train_xgb_ray_tune pid=325331)[0m [360]	train-mlogloss:0.65319	validation-mlogloss:0.61816
[36m(train_xgb_ray_tune pid=325326)[0m [326]	train-mlogloss:0.76222	validation-mlogloss:0.73670
[36m(train_xgb_ray_tune pid=325338)[0m [331]	train-mlogloss:0.78211	validation-mlogloss:0.75303
[36m(train_xgb_ray_tune pid=325324)[0m [347]	train-mlogloss:0.64145	validation-mlogloss:0.61168
[36m(train_xgb_ray_tune pid=325343)[0m [301]	train-mlogloss:0.55415	validation-mlogloss:0.53444
[36m(train_xgb_ray_tune pid=325325)[0m [425]	train-mlogloss:0.70896	validation-mlogloss:0.68205
[36m(train_xgb_ray_tune pid=325327)[0m [309]	train-mlogloss:0.76828	validation-mlogloss:0.73843
[36m(train_xgb_ray_tune pid=325344)[0m [367]	train-mlogloss:0.55665	validation-mlogloss:0.52981
[36m(train_xgb_ray_tune pid=325342)[0m [356]	train-mlogloss:0.82016	validation-mlogloss:0.78758
[36m(train_xgb_ray_tune pid=325341)[0m [443]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325340)[0m [300]	train-mlogloss:0.58523	validation-mlogloss:0.55416
[36m(train_xgb_ray_tune pid=325330)[0m [369]	train-mlogloss:0.57822	validation-mlogloss:0.54634
[36m(train_xgb_ray_tune pid=325331)[0m [361]	train-mlogloss:0.65319	validation-mlogloss:0.61816
[36m(train_xgb_ray_tune pid=325324)[0m [348]	train-mlogloss:0.64137	validation-mlogloss:0.61162
[36m(train_xgb_ray_tune pid=325296)[0m [442]	train-mlogloss:0.63510	validation-mlogloss:0.59862
[36m(train_xgb_ray_tune pid=325294)[0m [365]	train-mlogloss:0.79948	validation-mlogloss:0.77287
[36m(train_xgb_ray_tune pid=325325)[0m [426]	train-mlogloss:0.70896	validation-mlogloss:0.68205
[36m(train_xgb_ray_tune pid=325327)[0m [310]	train-mlogloss:0.76773	validation-mlogloss:0.73780
[36m(train_xgb_ray_tune pid=325341)[0m [444]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325307)[0m [389]	train-mlogloss:0.74042	validation-mlogloss:0.70835
[36m(train_xgb_ray_tune pid=325331)[0m [362]	train-mlogloss:0.65309	validation-mlogloss:0.61808
[36m(train_xgb_ray_tune pid=325326)[0m [327]	train-mlogloss:0.76141	validation-mlogloss:0.73584
[36m(train_xgb_ray_tune pid=325338)[0m [332]	train-mlogloss:0.78170	validation-mlogloss:0.75261
[36m(train_xgb_ray_tune pid=325324)[0m [349]	train-mlogloss:0.64125	validation-mlogloss:0.61147
[36m(train_xgb_ray_tune pid=325343)[0m [302]	train-mlogloss:0.55374	validation-mlogloss:0.53400
[36m(train_xgb_ray_tune pid=325344)[0m [368]	train-mlogloss:0.55651	validation-mlogloss:0.52967
[36m(train_xgb_ray_tune pid=325328)[0m [274]	train-mlogloss:0.74418	validation-mlogloss:0.72699
[36m(train_xgb_ray_tune pid=325339)[0m [314]	train-mlogloss:0.81066	validation-mlogloss:0.78479
[36m(train_xgb_ray_tune pid=325340)[0m [301]	train-mlogloss:0.58498	validation-mlogloss:0.55392
[36m(train_xgb_ray_tune pid=325296)[0m [443]	train-mlogloss:0.63491	validation-mlogloss:0.59840
[36m(train_xgb_ray_tune pid=325294)[0m [366]	train-mlogloss:0.79878	validation-mlogloss:0.77210
[36m(train_xgb_ray_tune pid=325342)[0m [357]	train-mlogloss:0.81943	validation-mlogloss:0.78683
[36m(train_xgb_ray_tune pid=325341)[0m [445]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325307)[0m [390]	train-mlogloss:0.73988	validation-mlogloss:0.70774
[36m(train_xgb_ray_tune pid=325330)[0m [370]	train-mlogloss:0.57814	validation-mlogloss:0.54627
[36m(train_xgb_ray_tune pid=325331)[0m [363]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325326)[0m [328]	train-mlogloss:0.76069	validation-mlogloss:0.73511
[36m(train_xgb_ray_tune pid=325338)[0m [333]	train-mlogloss:0.78128	validation-mlogloss:0.75217
[36m(train_xgb_ray_tune pid=325324)[0m [350]	train-mlogloss:0.64118	validation-mlogloss:0.61140
[36m(train_xgb_ray_tune pid=325296)[0m [444]	train-mlogloss:0.63477	validation-mlogloss:0.59829
[36m(train_xgb_ray_tune pid=325327)[0m [311]	train-mlogloss:0.76719	validation-mlogloss:0.73718
[36m(train_xgb_ray_tune pid=325344)[0m [369]	train-mlogloss:0.55646	validation-mlogloss:0.52964
[36m(train_xgb_ray_tune pid=325339)[0m [315]	train-mlogloss:0.81000	validation-mlogloss:0.78412
[36m(train_xgb_ray_tune pid=325341)[0m [446]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325340)[0m [302]	train-mlogloss:0.58474	validation-mlogloss:0.55367
[36m(train_xgb_ray_tune pid=325330)[0m [371]	train-mlogloss:0.57814	validation-mlogloss:0.54627
[36m(train_xgb_ray_tune pid=325331)[0m [364]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325324)[0m [351]	train-mlogloss:0.64099	validation-mlogloss:0.61125
[36m(train_xgb_ray_tune pid=325343)[0m [303]	train-mlogloss:0.55330	validation-mlogloss:0.53356
[36m(train_xgb_ray_tune pid=325294)[0m [367]	train-mlogloss:0.79808	validation-mlogloss:0.77140
[36m(train_xgb_ray_tune pid=325328)[0m [275]	train-mlogloss:0.74335	validation-mlogloss:0.72619
[36m(train_xgb_ray_tune pid=325307)[0m [391]	train-mlogloss:0.73928	validation-mlogloss:0.70713
[36m(train_xgb_ray_tune pid=325338)[0m [334]	train-mlogloss:0.78095	validation-mlogloss:0.75183
[36m(train_xgb_ray_tune pid=325296)[0m [445]	train-mlogloss:0.63457	validation-mlogloss:0.59802
[36m(train_xgb_ray_tune pid=325344)[0m [370]	train-mlogloss:0.55641	validation-mlogloss:0.52960
[36m(train_xgb_ray_tune pid=325341)[0m [447]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325330)[0m [372]	train-mlogloss:0.57788	validation-mlogloss:0.54597
[36m(train_xgb_ray_tune pid=325331)[0m [365]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325324)[0m [352]	train-mlogloss:0.64092	validation-mlogloss:0.61118
[36m(train_xgb_ray_tune pid=325327)[0m [312]	train-mlogloss:0.76663	validation-mlogloss:0.73656
[36m(train_xgb_ray_tune pid=325339)[0m [316]	train-mlogloss:0.80922	validation-mlogloss:0.78331
[36m(train_xgb_ray_tune pid=325342)[0m [358]	train-mlogloss:0.81880	validation-mlogloss:0.78617
[36m(train_xgb_ray_tune pid=325340)[0m [303]	train-mlogloss:0.58458	validation-mlogloss:0.55346
[36m(train_xgb_ray_tune pid=325326)[0m [329]	train-mlogloss:0.75995	validation-mlogloss:0.73433
[36m(train_xgb_ray_tune pid=325338)[0m [335]	train-mlogloss:0.78060	validation-mlogloss:0.75150
[36m(train_xgb_ray_tune pid=325343)[0m [304]	train-mlogloss:0.55289	validation-mlogloss:0.53316
[36m(train_xgb_ray_tune pid=325296)[0m [446]	train-mlogloss:0.63444	validation-mlogloss:0.59789
[36m(train_xgb_ray_tune pid=325341)[0m [448]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325307)[0m [392]	train-mlogloss:0.73875	validation-mlogloss:0.70656
[36m(train_xgb_ray_tune pid=325330)[0m [373]	train-mlogloss:0.57781	validation-mlogloss:0.54592
[36m(train_xgb_ray_tune pid=325331)[0m [366]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325294)[0m [368]	train-mlogloss:0.79740	validation-mlogloss:0.77071
[36m(train_xgb_ray_tune pid=325328)[0m [276]	train-mlogloss:0.74243	validation-mlogloss:0.72525
[36m(train_xgb_ray_tune pid=325340)[0m [304]	train-mlogloss:0.58429	validation-mlogloss:0.55310
[36m(train_xgb_ray_tune pid=325324)[0m [353]	train-mlogloss:0.64092	validation-mlogloss:0.61118
[36m(train_xgb_ray_tune pid=325327)[0m [313]	train-mlogloss:0.76597	validation-mlogloss:0.73590
[36m(train_xgb_ray_tune pid=325344)[0m [371]	train-mlogloss:0.55628	validation-mlogloss:0.52950
[36m(train_xgb_ray_tune pid=325341)[0m [449]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325307)[0m [393]	train-mlogloss:0.73828	validation-mlogloss:0.70608
[36m(train_xgb_ray_tune pid=325330)[0m [374]	train-mlogloss:0.57781	validation-mlogloss:0.54592
[36m(train_xgb_ray_tune pid=325331)[0m [367]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325326)[0m [330]	train-mlogloss:0.75916	validation-mlogloss:0.73351
[36m(train_xgb_ray_tune pid=325338)[0m [336]	train-mlogloss:0.78019	validation-mlogloss:0.75112
[36m(train_xgb_ray_tune pid=325296)[0m [447]	train-mlogloss:0.63430	validation-mlogloss:0.59778
[36m(train_xgb_ray_tune pid=325294)[0m [369]	train-mlogloss:0.79682	validation-mlogloss:0.77008
[36m(train_xgb_ray_tune pid=325339)[0m [317]	train-mlogloss:0.80844	validation-mlogloss:0.78249
[36m(train_xgb_ray_tune pid=325342)[0m [359]	train-mlogloss:0.81807	validation-mlogloss:0.78544
[36m(train_xgb_ray_tune pid=325331)[0m [368]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325324)[0m [354]	train-mlogloss:0.64080	validation-mlogloss:0.61106
[36m(train_xgb_ray_tune pid=325343)[0m [305]	train-mlogloss:0.55245	validation-mlogloss:0.53277
[36m(train_xgb_ray_tune pid=325344)[0m [372]	train-mlogloss:0.55620	validation-mlogloss:0.52945
[36m(train_xgb_ray_tune pid=325328)[0m [277]	train-mlogloss:0.74163	validation-mlogloss:0.72440
[36m(train_xgb_ray_tune pid=325341)[0m [450]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325340)[0m [305]	train-mlogloss:0.58401	validation-mlogloss:0.55282
[36m(train_xgb_ray_tune pid=325330)[0m [375]	train-mlogloss:0.57781	validation-mlogloss:0.54591
[36m(train_xgb_ray_tune pid=325296)[0m [448]	train-mlogloss:0.63417	validation-mlogloss:0.59767
[36m(train_xgb_ray_tune pid=325296)[0m [449]	train-mlogloss:0.63403	validation-mlogloss:0.59752
[36m(train_xgb_ray_tune pid=325296)[0m [450]	train-mlogloss:0.63390	validation-mlogloss:0.59739
[36m(train_xgb_ray_tune pid=325296)[0m [451]	train-mlogloss:0.63377	validation-mlogloss:0.59726
[36m(train_xgb_ray_tune pid=325296)[0m [452]	train-mlogloss:0.63363	validation-mlogloss:0.59714
[36m(train_xgb_ray_tune pid=325296)[0m [453]	train-mlogloss:0.63345	validation-mlogloss:0.59690
[36m(train_xgb_ray_tune pid=325296)[0m [454]	train-mlogloss:0.63332	validation-mlogloss:0.59675
[36m(train_xgb_ray_tune pid=325296)[0m [455]	train-mlogloss:0.63318	validation-mlogloss:0.59665
[36m(train_xgb_ray_tune pid=325296)[0m [456]	train-mlogloss:0.63299	validation-mlogloss:0.59639
[36m(train_xgb_ray_tune pid=325296)[0m [457]	train-mlogloss:0.63287	validation-mlogloss:0.59627
[36m(train_xgb_ray_tune pid=325294)[0m [370]	train-mlogloss:0.79627	validation-mlogloss:0.76947
[36m(train_xgb_ray_tune pid=325294)[0m [371]	train-mlogloss:0.79560	validation-mlogloss:0.76880
[36m(train_xgb_ray_tune pid=325294)[0m [372]	train-mlogloss:0.79488	validation-mlogloss:0.76807
[36m(train_xgb_ray_tune pid=325294)[0m [373]	train-mlogloss:0.79419	validation-mlogloss:0.76736
[36m(train_xgb_ray_tune pid=325294)[0m [374]	train-mlogloss:0.79355	validation-mlogloss:0.76670
[36m(train_xgb_ray_tune pid=325327)[0m [314]	train-mlogloss:0.76530	validation-mlogloss:0.73522
[36m(train_xgb_ray_tune pid=325327)[0m [315]	train-mlogloss:0.76479	validation-mlogloss:0.73466
[36m(train_xgb_ray_tune pid=325327)[0m [316]	train-mlogloss:0.76426	validation-mlogloss:0.73415
[36m(train_xgb_ray_tune pid=325327)[0m [317]	train-mlogloss:0.76360	validation-mlogloss:0.73348
[36m(train_xgb_ray_tune pid=325327)[0m [318]	train-mlogloss:0.76298	validation-mlogloss:0.73282

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:43. Total running time: 17s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             14.5138 │
│ time_total_s                 14.5138 │
│ training_iteration                 1 │
│ validation_accuracy          0.75151 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=325344)[0m [373]	train-mlogloss:0.55612	validation-mlogloss:0.52940
[36m(train_xgb_ray_tune pid=325344)[0m [374]	train-mlogloss:0.55607	validation-mlogloss:0.52932
[36m(train_xgb_ray_tune pid=325344)[0m [375]	train-mlogloss:0.55603	validation-mlogloss:0.52925
[36m(train_xgb_ray_tune pid=325344)[0m [376]	train-mlogloss:0.55595	validation-mlogloss:0.52915
[36m(train_xgb_ray_tune pid=325344)[0m [377]	train-mlogloss:0.55583	validation-mlogloss:0.52900
[36m(train_xgb_ray_tune pid=325344)[0m [378]	train-mlogloss:0.55578	validation-mlogloss:0.52893
[36m(train_xgb_ray_tune pid=325344)[0m [379]	train-mlogloss:0.55566	validation-mlogloss:0.52879
[36m(train_xgb_ray_tune pid=325328)[0m [278]	train-mlogloss:0.74074	validation-mlogloss:0.72347
[36m(train_xgb_ray_tune pid=325328)[0m [279]	train-mlogloss:0.73982	validation-mlogloss:0.72256
[36m(train_xgb_ray_tune pid=325328)[0m [280]	train-mlogloss:0.73900	validation-mlogloss:0.72171
[36m(train_xgb_ray_tune pid=325328)[0m [281]	train-mlogloss:0.73809	validation-mlogloss:0.72080
[36m(train_xgb_ray_tune pid=325339)[0m [318]	train-mlogloss:0.80770	validation-mlogloss:0.78171
[36m(train_xgb_ray_tune pid=325339)[0m [319]	train-mlogloss:0.80688	validation-mlogloss:0.78088
[36m(train_xgb_ray_tune pid=325339)[0m [320]	train-mlogloss:0.80612	validation-mlogloss:0.78009
[36m(train_xgb_ray_tune pid=325339)[0m [321]	train-mlogloss:0.80536	validation-mlogloss:0.77930
[36m(train_xgb_ray_tune pid=325339)[0m [322]	train-mlogloss:0.80461	validation-mlogloss:0.77849
[36m(train_xgb_ray_tune pid=325342)[0m [360]	train-mlogloss:0.81736	validation-mlogloss:0.78467
[36m(train_xgb_ray_tune pid=325342)[0m [361]	train-mlogloss:0.81666	validation-mlogloss:0.78393
[36m(train_xgb_ray_tune pid=325342)[0m [362]	train-mlogloss:0.81609	validation-mlogloss:0.78332
[36m(train_xgb_ray_tune pid=325342)[0m [363]	train-mlogloss:0.81543	validation-mlogloss:0.78266
[36m(train_xgb_ray_tune pid=325342)[0m [364]	train-mlogloss:0.81486	validation-mlogloss:0.78201
[36m(train_xgb_ray_tune pid=325342)[0m [365]	train-mlogloss:0.81421	validation-mlogloss:0.78136
[36m(train_xgb_ray_tune pid=325341)[0m [451]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325341)[0m [452]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325341)[0m [453]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325341)[0m [454]	train-mlogloss:1.00911	validation-mlogloss:0.99125
[36m(train_xgb_ray_tune pid=325307)[0m [394]	train-mlogloss:0.73770	validation-mlogloss:0.70551
[36m(train_xgb_ray_tune pid=325307)[0m [395]	train-mlogloss:0.73718	validation-mlogloss:0.70497
[36m(train_xgb_ray_tune pid=325307)[0m [396]	train-mlogloss:0.73673	validation-mlogloss:0.70452
[36m(train_xgb_ray_tune pid=325307)[0m [397]	train-mlogloss:0.73615	validation-mlogloss:0.70388
[36m(train_xgb_ray_tune pid=325307)[0m [398]	train-mlogloss:0.73564	validation-mlogloss:0.70328
[36m(train_xgb_ray_tune pid=325307)[0m [399]	train-mlogloss:0.73514	validation-mlogloss:0.70276
[36m(train_xgb_ray_tune pid=325307)[0m [400]	train-mlogloss:0.73461	validation-mlogloss:0.70222
[36m(train_xgb_ray_tune pid=325340)[0m [306]	train-mlogloss:0.58378	validation-mlogloss:0.55254
[36m(train_xgb_ray_tune pid=325340)[0m [307]	train-mlogloss:0.58357	validation-mlogloss:0.55243
[36m(train_xgb_ray_tune pid=325340)[0m [308]	train-mlogloss:0.58330	validation-mlogloss:0.55213
[36m(train_xgb_ray_tune pid=325340)[0m [309]	train-mlogloss:0.58314	validation-mlogloss:0.55197
[36m(train_xgb_ray_tune pid=325340)[0m [310]	train-mlogloss:0.58293	validation-mlogloss:0.55176
[36m(train_xgb_ray_tune pid=325340)[0m [311]	train-mlogloss:0.58272	validation-mlogloss:0.55151
[36m(train_xgb_ray_tune pid=325340)[0m [312]	train-mlogloss:0.58240	validation-mlogloss:0.55107
[36m(train_xgb_ray_tune pid=325330)[0m [376]	train-mlogloss:0.57746	validation-mlogloss:0.54549
[36m(train_xgb_ray_tune pid=325330)[0m [377]	train-mlogloss:0.57739	validation-mlogloss:0.54544
[36m(train_xgb_ray_tune pid=325330)[0m [378]	train-mlogloss:0.57739	validation-mlogloss:0.54544
[36m(train_xgb_ray_tune pid=325330)[0m [379]	train-mlogloss:0.57732	validation-mlogloss:0.54532
[36m(train_xgb_ray_tune pid=325330)[0m [380]	train-mlogloss:0.57725	validation-mlogloss:0.54527
[36m(train_xgb_ray_tune pid=325330)[0m [381]	train-mlogloss:0.57718	validation-mlogloss:0.54522
[36m(train_xgb_ray_tune pid=325330)[0m [382]	train-mlogloss:0.57711	validation-mlogloss:0.54517
[36m(train_xgb_ray_tune pid=325330)[0m [383]	train-mlogloss:0.57697	validation-mlogloss:0.54497
[36m(train_xgb_ray_tune pid=325331)[0m [369]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325331)[0m [370]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325331)[0m [371]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325331)[0m [372]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325331)[0m [373]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325331)[0m [374]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325331)[0m [375]	train-mlogloss:0.65299	validation-mlogloss:0.61794
[36m(train_xgb_ray_tune pid=325331)[0m [376]	train-mlogloss:0.65289	validation-mlogloss:0.61779
[36m(train_xgb_ray_tune pid=325331)[0m [377]	train-mlogloss:0.65289	validation-mlogloss:0.61779
[36m(train_xgb_ray_tune pid=325331)[0m [378]	train-mlogloss:0.65289	validation-mlogloss:0.61779
[36m(train_xgb_ray_tune pid=325326)[0m [331]	train-mlogloss:0.75840	validation-mlogloss:0.73271
[36m(train_xgb_ray_tune pid=325326)[0m [332]	train-mlogloss:0.75774	validation-mlogloss:0.73208
[36m(train_xgb_ray_tune pid=325326)[0m [333]	train-mlogloss:0.75706	validation-mlogloss:0.73142
[36m(train_xgb_ray_tune pid=325326)[0m [334]	train-mlogloss:0.75629	validation-mlogloss:0.73063
[36m(train_xgb_ray_tune pid=325326)[0m [335]	train-mlogloss:0.75559	validation-mlogloss:0.72991
[36m(train_xgb_ray_tune pid=325326)[0m [336]	train-mlogloss:0.75495	validation-mlogloss:0.72926
[36m(train_xgb_ray_tune pid=325338)[0m [337]	train-mlogloss:0.77976	validation-mlogloss:0.75071
[36m(train_xgb_ray_tune pid=325338)[0m [338]	train-mlogloss:0.77942	validation-mlogloss:0.75039
[36m(train_xgb_ray_tune pid=325338)[0m [339]	train-mlogloss:0.77901	validation-mlogloss:0.74997
[36m(train_xgb_ray_tune pid=325338)[0m [340]	train-mlogloss:0.77868	validation-mlogloss:0.74961
[36m(train_xgb_ray_tune pid=325338)[0m [341]	train-mlogloss:0.77829	validation-mlogloss:0.74923
[36m(train_xgb_ray_tune pid=325338)[0m [342]	train-mlogloss:0.77787	validation-mlogloss:0.74883
[36m(train_xgb_ray_tune pid=325338)[0m [343]	train-mlogloss:0.77748	validation-mlogloss:0.74844
[36m(train_xgb_ray_tune pid=325324)[0m [355]	train-mlogloss:0.64073	validation-mlogloss:0.61096
[36m(train_xgb_ray_tune pid=325324)[0m [356]	train-mlogloss:0.64073	validation-mlogloss:0.61096
[36m(train_xgb_ray_tune pid=325324)[0m [357]	train-mlogloss:0.64073	validation-mlogloss:0.61096
[36m(train_xgb_ray_tune pid=325324)[0m [358]	train-mlogloss:0.64073	validation-mlogloss:0.61096
[36m(train_xgb_ray_tune pid=325324)[0m [359]	train-mlogloss:0.64073	validation-mlogloss:0.61096
[36m(train_xgb_ray_tune pid=325324)[0m [360]	train-mlogloss:0.64066	validation-mlogloss:0.61086
[36m(train_xgb_ray_tune pid=325324)[0m [361]	train-mlogloss:0.64052	validation-mlogloss:0.61069
[36m(train_xgb_ray_tune pid=325324)[0m [362]	train-mlogloss:0.64052	validation-mlogloss:0.61069
[36m(train_xgb_ray_tune pid=325324)[0m [363]	train-mlogloss:0.64052	validation-mlogloss:0.61069
[36m(train_xgb_ray_tune pid=325324)[0m [364]	train-mlogloss:0.64045	validation-mlogloss:0.61064
[36m(train_xgb_ray_tune pid=325343)[0m [306]	train-mlogloss:0.55203	validation-mlogloss:0.53232
[36m(train_xgb_ray_tune pid=325343)[0m [307]	train-mlogloss:0.55153	validation-mlogloss:0.53182
[36m(train_xgb_ray_tune pid=325343)[0m [308]	train-mlogloss:0.55111	validation-mlogloss:0.53141
[36m(train_xgb_ray_tune pid=325343)[0m [309]	train-mlogloss:0.55070	validation-mlogloss:0.53110
[36m(train_xgb_ray_tune pid=325343)[0m [310]	train-mlogloss:0.55028	validation-mlogloss:0.53078

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:43. Total running time: 17s
[36m(train_xgb_ray_tune pid=325296)[0m [458]	train-mlogloss:0.63273	validation-mlogloss:0.59614
[36m(train_xgb_ray_tune pid=325294)[0m [375]	train-mlogloss:0.79281	validation-mlogloss:0.76594
[36m(train_xgb_ray_tune pid=325327)[0m [319]	train-mlogloss:0.76233	validation-mlogloss:0.73216
[36m(train_xgb_ray_tune pid=325327)[0m [320]	train-mlogloss:0.76169	validation-mlogloss:0.73149
[36m(train_xgb_ray_tune pid=325344)[0m [380]	train-mlogloss:0.55555	validation-mlogloss:0.52867
[36m(train_xgb_ray_tune pid=325344)[0m [381]	train-mlogloss:0.55546	validation-mlogloss:0.52861
[36m(train_xgb_ray_tune pid=325339)[0m [323]	train-mlogloss:0.80383	validation-mlogloss:0.77768
[36m(train_xgb_ray_tune pid=325342)[0m [366]	train-mlogloss:0.81360	validation-mlogloss:0.78072
[36m(train_xgb_ray_tune pid=325307)[0m [401]	train-mlogloss:0.73403	validation-mlogloss:0.70160
[36m(train_xgb_ray_tune pid=325340)[0m [313]	train-mlogloss:0.58215	validation-mlogloss:0.55077
[36m(train_xgb_ray_tune pid=325330)[0m [384]	train-mlogloss:0.57684	validation-mlogloss:0.54485
[36m(train_xgb_ray_tune pid=325330)[0m [385]	train-mlogloss:0.57684	validation-mlogloss:0.54485
[36m(train_xgb_ray_tune pid=325331)[0m [379]	train-mlogloss:0.65289	validation-mlogloss:0.61779
[36m(train_xgb_ray_tune pid=325338)[0m [344]	train-mlogloss:0.77709	validation-mlogloss:0.74805
[36m(train_xgb_ray_tune pid=325324)[0m [365]	train-mlogloss:0.64038	validation-mlogloss:0.61058
[36m(train_xgb_ray_tune pid=325324)[0m [366]	train-mlogloss:0.64038	validation-mlogloss:0.61058
[36m(train_xgb_ray_tune pid=325343)[0m [311]	train-mlogloss:0.54983	validation-mlogloss:0.53041
[36m(train_xgb_ray_tune pid=325296)[0m [459]	train-mlogloss:0.63260	validation-mlogloss:0.59596
[36m(train_xgb_ray_tune pid=325294)[0m [376]	train-mlogloss:0.79219	validation-mlogloss:0.76528
[36m(train_xgb_ray_tune pid=325344)[0m [382]	train-mlogloss:0.55541	validation-mlogloss:0.52858
[36m(train_xgb_ray_tune pid=325328)[0m [282]	train-mlogloss:0.73726	validation-mlogloss:0.71998
[36m(train_xgb_ray_tune pid=325339)[0m [324]	train-mlogloss:0.80320	validation-mlogloss:0.77699
[36m(train_xgb_ray_tune pid=325342)[0m [367]	train-mlogloss:0.81287	validation-mlogloss:0.77997
[36m(train_xgb_ray_tune pid=325307)[0m [402]	train-mlogloss:0.73350	validation-mlogloss:0.70106
[36m(train_xgb_ray_tune pid=325340)[0m [314]	train-mlogloss:0.58181	validation-mlogloss:0.55033
[36m(train_xgb_ray_tune pid=325330)[0m [386]	train-mlogloss:0.57684	validation-mlogloss:0.54485
[36m(train_xgb_ray_tune pid=325331)[0m [380]	train-mlogloss:0.65289	validation-mlogloss:0.61779
[36m(train_xgb_ray_tune pid=325326)[0m [337]	train-mlogloss:0.75425	validation-mlogloss:0.72843
[36m(train_xgb_ray_tune pid=325338)[0m [345]	train-mlogloss:0.77670	validation-mlogloss:0.74764
[36m(train_xgb_ray_tune pid=325324)[0m [367]	train-mlogloss:0.64038	validation-mlogloss:0.61058
[36m(train_xgb_ray_tune pid=325324)[0m [368]	train-mlogloss:0.64031	validation-mlogloss:0.61053
[36m(train_xgb_ray_tune pid=325343)[0m [312]	train-mlogloss:0.54946	validation-mlogloss:0.52999
[36m(train_xgb_ray_tune pid=325296)[0m [460]	train-mlogloss:0.63248	validation-mlogloss:0.59579
[36m(train_xgb_ray_tune pid=325296)[0m [461]	train-mlogloss:0.63240	validation-mlogloss:0.59572
[36m(train_xgb_ray_tune pid=325294)[0m [377]	train-mlogloss:0.79157	validation-mlogloss:0.76463
[36m(train_xgb_ray_tune pid=325327)[0m [321]	train-mlogloss:0.76119	validation-mlogloss:0.73093
[36m(train_xgb_ray_tune pid=325344)[0m [383]	train-mlogloss:0.55536	validation-mlogloss:0.52856
[36m(train_xgb_ray_tune pid=325328)[0m [283]	train-mlogloss:0.73640	validation-mlogloss:0.71911
[36m(train_xgb_ray_tune pid=325339)[0m [325]	train-mlogloss:0.80244	validation-mlogloss:0.77620
[36m(train_xgb_ray_tune pid=325307)[0m [403]	train-mlogloss:0.73301	validation-mlogloss:0.70054
[36m(train_xgb_ray_tune pid=325340)[0m [315]	train-mlogloss:0.58154	validation-mlogloss:0.55001
[36m(train_xgb_ray_tune pid=325330)[0m [387]	train-mlogloss:0.57677	validation-mlogloss:0.54481
[36m(train_xgb_ray_tune pid=325331)[0m [381]	train-mlogloss:0.65279	validation-mlogloss:0.61764
[36m(train_xgb_ray_tune pid=325342)[0m [368]	train-mlogloss:0.81216	validation-mlogloss:0.77925
[36m(train_xgb_ray_tune pid=325338)[0m [346]	train-mlogloss:0.77638	validation-mlogloss:0.74726
[36m(train_xgb_ray_tune pid=325324)[0m [369]	train-mlogloss:0.64025	validation-mlogloss:0.61048
[36m(train_xgb_ray_tune pid=325296)[0m [462]	train-mlogloss:0.63227	validation-mlogloss:0.59561
[36m(train_xgb_ray_tune pid=325344)[0m [384]	train-mlogloss:0.55525	validation-mlogloss:0.52846
[36m(train_xgb_ray_tune pid=325340)[0m [316]	train-mlogloss:0.58122	validation-mlogloss:0.54964
[36m(train_xgb_ray_tune pid=325330)[0m [388]	train-mlogloss:0.57670	validation-mlogloss:0.54476
[36m(train_xgb_ray_tune pid=325331)[0m [382]	train-mlogloss:0.65279	validation-mlogloss:0.61764
[36m(train_xgb_ray_tune pid=325343)[0m [313]	train-mlogloss:0.54896	validation-mlogloss:0.52948
[36m(train_xgb_ray_tune pid=325294)[0m [378]	train-mlogloss:0.79092	validation-mlogloss:0.76395
[36m(train_xgb_ray_tune pid=325327)[0m [322]	train-mlogloss:0.76054	validation-mlogloss:0.73027
[36m(train_xgb_ray_tune pid=325339)[0m [326]	train-mlogloss:0.80177	validation-mlogloss:0.77552
[36m(train_xgb_ray_tune pid=325342)[0m [369]	train-mlogloss:0.81146	validation-mlogloss:0.77850
[36m(train_xgb_ray_tune pid=325307)[0m [404]	train-mlogloss:0.73249	validation-mlogloss:0.70003
[36m(train_xgb_ray_tune pid=325330)[0m [389]	train-mlogloss:0.57670	validation-mlogloss:0.54476
[36m(train_xgb_ray_tune pid=325331)[0m [383]	train-mlogloss:0.65279	validation-mlogloss:0.61764
[36m(train_xgb_ray_tune pid=325338)[0m [347]	train-mlogloss:0.77605	validation-mlogloss:0.74692
[36m(train_xgb_ray_tune pid=325324)[0m [370]	train-mlogloss:0.64018	validation-mlogloss:0.61042
[36m(train_xgb_ray_tune pid=325296)[0m [463]	train-mlogloss:0.63209	validation-mlogloss:0.59541
[36m(train_xgb_ray_tune pid=325344)[0m [385]	train-mlogloss:0.55517	validation-mlogloss:0.52842
[36m(train_xgb_ray_tune pid=325328)[0m [284]	train-mlogloss:0.73550	validation-mlogloss:0.71825
[36m(train_xgb_ray_tune pid=325307)[0m [405]	train-mlogloss:0.73199	validation-mlogloss:0.69947
[36m(train_xgb_ray_tune pid=325340)[0m [317]	train-mlogloss:0.58097	validation-mlogloss:0.54932
[36m(train_xgb_ray_tune pid=325331)[0m [384]	train-mlogloss:0.65279	validation-mlogloss:0.61764
[36m(train_xgb_ray_tune pid=325324)[0m [371]	train-mlogloss:0.63994	validation-mlogloss:0.61017
[36m(train_xgb_ray_tune pid=325343)[0m [314]	train-mlogloss:0.54849	validation-mlogloss:0.52909
[36m(train_xgb_ray_tune pid=325296)[0m [464]	train-mlogloss:0.63190	validation-mlogloss:0.59520
[36m(train_xgb_ray_tune pid=325327)[0m [323]	train-mlogloss:0.75989	validation-mlogloss:0.72962
[36m(train_xgb_ray_tune pid=325344)[0m [386]	train-mlogloss:0.55512	validation-mlogloss:0.52839
[36m(train_xgb_ray_tune pid=325340)[0m [318]	train-mlogloss:0.58075	validation-mlogloss:0.54905
[36m(train_xgb_ray_tune pid=325330)[0m [390]	train-mlogloss:0.57663	validation-mlogloss:0.54472
[36m(train_xgb_ray_tune pid=325339)[0m [327]	train-mlogloss:0.80116	validation-mlogloss:0.77488
[36m(train_xgb_ray_tune pid=325342)[0m [370]	train-mlogloss:0.81080	validation-mlogloss:0.77785
[36m(train_xgb_ray_tune pid=325331)[0m [385]	train-mlogloss:0.65279	validation-mlogloss:0.61764
[36m(train_xgb_ray_tune pid=325338)[0m [348]	train-mlogloss:0.77573	validation-mlogloss:0.74659
[36m(train_xgb_ray_tune pid=325324)[0m [372]	train-mlogloss:0.63987	validation-mlogloss:0.61011
[36m(train_xgb_ray_tune pid=325296)[0m [465]	train-mlogloss:0.63178	validation-mlogloss:0.59509
[36m(train_xgb_ray_tune pid=325294)[0m [379]	train-mlogloss:0.79035	validation-mlogloss:0.76334
[36m(train_xgb_ray_tune pid=325328)[0m [285]	train-mlogloss:0.73465	validation-mlogloss:0.71737
[36m(train_xgb_ray_tune pid=325307)[0m [406]	train-mlogloss:0.73151	validation-mlogloss:0.69902
[36m(train_xgb_ray_tune pid=325340)[0m [319]	train-mlogloss:0.58056	validation-mlogloss:0.54891
[36m(train_xgb_ray_tune pid=325330)[0m [391]	train-mlogloss:0.57656	validation-mlogloss:0.54466
[36m(train_xgb_ray_tune pid=325324)[0m [373]	train-mlogloss:0.63987	validation-mlogloss:0.61011
[36m(train_xgb_ray_tune pid=325343)[0m [315]	train-mlogloss:0.54809	validation-mlogloss:0.52876
[36m(train_xgb_ray_tune pid=325327)[0m [324]	train-mlogloss:0.75926	validation-mlogloss:0.72899
[36m(train_xgb_ray_tune pid=325344)[0m [387]	train-mlogloss:0.55501	validation-mlogloss:0.52825
[36m(train_xgb_ray_tune pid=325339)[0m [328]	train-mlogloss:0.80041	validation-mlogloss:0.77411
[36m(train_xgb_ray_tune pid=325342)[0m [371]	train-mlogloss:0.81014	validation-mlogloss:0.77718
[36m(train_xgb_ray_tune pid=325307)[0m [407]	train-mlogloss:0.73102	validation-mlogloss:0.69846
[36m(train_xgb_ray_tune pid=325340)[0m [320]	train-mlogloss:0.58041	validation-mlogloss:0.54881
[36m(train_xgb_ray_tune pid=325330)[0m [392]	train-mlogloss:0.57656	validation-mlogloss:0.54466
[36m(train_xgb_ray_tune pid=325331)[0m [386]	train-mlogloss:0.65279	validation-mlogloss:0.61764
[36m(train_xgb_ray_tune pid=325331)[0m [387]	train-mlogloss:0.65279	validation-mlogloss:0.61764
[36m(train_xgb_ray_tune pid=325338)[0m [349]	train-mlogloss:0.77540	validation-mlogloss:0.74628
[36m(train_xgb_ray_tune pid=325324)[0m [374]	train-mlogloss:0.63980	validation-mlogloss:0.61006
[36m(train_xgb_ray_tune pid=325296)[0m [466]	train-mlogloss:0.63165	validation-mlogloss:0.59496
[36m(train_xgb_ray_tune pid=325296)[0m [467]	train-mlogloss:0.63153	validation-mlogloss:0.59486

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:43. Total running time: 17s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             14.4964 │
│ time_total_s                 14.4964 │
│ training_iteration                 1 │
│ validation_accuracy          0.68401 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=325294)[0m [380]	train-mlogloss:0.78968	validation-mlogloss:0.76264

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:43. Total running time: 17s
[36m(train_xgb_ray_tune pid=325327)[0m [325]	train-mlogloss:0.75863	validation-mlogloss:0.72834
[36m(train_xgb_ray_tune pid=325328)[0m [286]	train-mlogloss:0.73392	validation-mlogloss:0.71662
[36m(train_xgb_ray_tune pid=325342)[0m [372]	train-mlogloss:0.80944	validation-mlogloss:0.77645
[36m(train_xgb_ray_tune pid=325307)[0m [408]	train-mlogloss:0.73052	validation-mlogloss:0.69796
[36m(train_xgb_ray_tune pid=325340)[0m [321]	train-mlogloss:0.58022	validation-mlogloss:0.54860
[36m(train_xgb_ray_tune pid=325330)[0m [393]	train-mlogloss:0.57649	validation-mlogloss:0.54454
[36m(train_xgb_ray_tune pid=325330)[0m [394]	train-mlogloss:0.57649	validation-mlogloss:0.54454
[36m(train_xgb_ray_tune pid=325331)[0m [388]	train-mlogloss:0.65279	validation-mlogloss:0.61764
[36m(train_xgb_ray_tune pid=325338)[0m [350]	train-mlogloss:0.77501	validation-mlogloss:0.74587
[36m(train_xgb_ray_tune pid=325324)[0m [375]	train-mlogloss:0.63974	validation-mlogloss:0.61000
[36m(train_xgb_ray_tune pid=325324)[0m [376]	train-mlogloss:0.63974	validation-mlogloss:0.61000
[36m(train_xgb_ray_tune pid=325343)[0m [316]	train-mlogloss:0.54775	validation-mlogloss:0.52845
[36m(train_xgb_ray_tune pid=325296)[0m [468]	train-mlogloss:0.63145	validation-mlogloss:0.59475
[36m(train_xgb_ray_tune pid=325294)[0m [381]	train-mlogloss:0.78905	validation-mlogloss:0.76199
[36m(train_xgb_ray_tune pid=325327)[0m [326]	train-mlogloss:0.75812	validation-mlogloss:0.72777
[36m(train_xgb_ray_tune pid=325339)[0m [329]	train-mlogloss:0.79966	validation-mlogloss:0.77332
[36m(train_xgb_ray_tune pid=325307)[0m [409]	train-mlogloss:0.73006	validation-mlogloss:0.69745
[36m(train_xgb_ray_tune pid=325331)[0m [389]	train-mlogloss:0.65258	validation-mlogloss:0.61738
[36m(train_xgb_ray_tune pid=325324)[0m [377]	train-mlogloss:0.63974	validation-mlogloss:0.61000
[36m(train_xgb_ray_tune pid=325296)[0m [469]	train-mlogloss:0.63133	validation-mlogloss:0.59461
[36m(train_xgb_ray_tune pid=325328)[0m [287]	train-mlogloss:0.73306	validation-mlogloss:0.71571
[36m(train_xgb_ray_tune pid=325342)[0m [373]	train-mlogloss:0.80876	validation-mlogloss:0.77575
[36m(train_xgb_ray_tune pid=325340)[0m [322]	train-mlogloss:0.58002	validation-mlogloss:0.54845
[36m(train_xgb_ray_tune pid=325330)[0m [395]	train-mlogloss:0.57643	validation-mlogloss:0.54449
[36m(train_xgb_ray_tune pid=325331)[0m [390]	train-mlogloss:0.65258	validation-mlogloss:0.61738
[36m(train_xgb_ray_tune pid=325324)[0m [378]	train-mlogloss:0.63974	validation-mlogloss:0.61000
[36m(train_xgb_ray_tune pid=325343)[0m [317]	train-mlogloss:0.54733	validation-mlogloss:0.52805
[36m(train_xgb_ray_tune pid=325296)[0m [470]	train-mlogloss:0.63120	validation-mlogloss:0.59451
[36m(train_xgb_ray_tune pid=325327)[0m [327]	train-mlogloss:0.75751	validation-mlogloss:0.72713
[36m(train_xgb_ray_tune pid=325339)[0m [330]	train-mlogloss:0.79895	validation-mlogloss:0.77258
[36m(train_xgb_ray_tune pid=325342)[0m [374]	train-mlogloss:0.80807	validation-mlogloss:0.77503
[36m(train_xgb_ray_tune pid=325307)[0m [410]	train-mlogloss:0.72953	validation-mlogloss:0.69688
[36m(train_xgb_ray_tune pid=325340)[0m [323]	train-mlogloss:0.57983	validation-mlogloss:0.54827
[36m(train_xgb_ray_tune pid=325330)[0m [396]	train-mlogloss:0.57636	validation-mlogloss:0.54438
[36m(train_xgb_ray_tune pid=325331)[0m [391]	train-mlogloss:0.65258	validation-mlogloss:0.61738
[36m(train_xgb_ray_tune pid=325338)[0m [351]	train-mlogloss:0.77461	validation-mlogloss:0.74549
[36m(train_xgb_ray_tune pid=325324)[0m [379]	train-mlogloss:0.63961	validation-mlogloss:0.60984
[36m(train_xgb_ray_tune pid=325296)[0m [471]	train-mlogloss:0.63103	validation-mlogloss:0.59436
[36m(train_xgb_ray_tune pid=325294)[0m [382]	train-mlogloss:0.78838	validation-mlogloss:0.76133
[36m(train_xgb_ray_tune pid=325327)[0m [328]	train-mlogloss:0.75702	validation-mlogloss:0.72653
[36m(train_xgb_ray_tune pid=325328)[0m [288]	train-mlogloss:0.73221	validation-mlogloss:0.71483
[36m(train_xgb_ray_tune pid=325330)[0m [397]	train-mlogloss:0.57636	validation-mlogloss:0.54438
[36m(train_xgb_ray_tune pid=325339)[0m [331]	train-mlogloss:0.79820	validation-mlogloss:0.77182
[36m(train_xgb_ray_tune pid=325307)[0m [411]	train-mlogloss:0.72904	validation-mlogloss:0.69641
[36m(train_xgb_ray_tune pid=325331)[0m [392]	train-mlogloss:0.65258	validation-mlogloss:0.61738
[36m(train_xgb_ray_tune pid=325338)[0m [352]	train-mlogloss:0.77430	validation-mlogloss:0.74516
[36m(train_xgb_ray_tune pid=325324)[0m [380]	train-mlogloss:0.63961	validation-mlogloss:0.60984
[36m(train_xgb_ray_tune pid=325324)[0m [381]	train-mlogloss:0.63961	validation-mlogloss:0.60984

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:43. Total running time: 17s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             14.4169 │
│ time_total_s                 14.4169 │
│ training_iteration                 1 │
│ validation_accuracy          0.74962 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=325343)[0m [318]	train-mlogloss:0.54691	validation-mlogloss:0.52780
[36m(train_xgb_ray_tune pid=325296)[0m [472]	train-mlogloss:0.63091	validation-mlogloss:0.59426
[36m(train_xgb_ray_tune pid=325294)[0m [383]	train-mlogloss:0.78783	validation-mlogloss:0.76069
[36m(train_xgb_ray_tune pid=325327)[0m [329]	train-mlogloss:0.75642	validation-mlogloss:0.72590
[36m(train_xgb_ray_tune pid=325342)[0m [375]	train-mlogloss:0.80737	validation-mlogloss:0.77430
[36m(train_xgb_ray_tune pid=325340)[0m [324]	train-mlogloss:0.57958	validation-mlogloss:0.54802
[36m(train_xgb_ray_tune pid=325330)[0m [398]	train-mlogloss:0.57629	validation-mlogloss:0.54433
[36m(train_xgb_ray_tune pid=325331)[0m [393]	train-mlogloss:0.65258	validation-mlogloss:0.61738
[36m(train_xgb_ray_tune pid=325328)[0m [289]	train-mlogloss:0.73145	validation-mlogloss:0.71403
[36m(train_xgb_ray_tune pid=325339)[0m [332]	train-mlogloss:0.79749	validation-mlogloss:0.77107
[36m(train_xgb_ray_tune pid=325307)[0m [412]	train-mlogloss:0.72851	validation-mlogloss:0.69584
[36m(train_xgb_ray_tune pid=325340)[0m [325]	train-mlogloss:0.57944	validation-mlogloss:0.54789

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:43. Total running time: 17s
[36m(train_xgb_ray_tune pid=325330)[0m [399]	train-mlogloss:0.57629	validation-mlogloss:0.54433
[36m(train_xgb_ray_tune pid=325331)[0m [394]	train-mlogloss:0.65258	validation-mlogloss:0.61738
[36m(train_xgb_ray_tune pid=325338)[0m [353]	train-mlogloss:0.77391	validation-mlogloss:0.74479
[36m(train_xgb_ray_tune pid=325324)[0m [382]	train-mlogloss:0.63950	validation-mlogloss:0.60976
[36m(train_xgb_ray_tune pid=325343)[0m [319]	train-mlogloss:0.54653	validation-mlogloss:0.52742
[36m(train_xgb_ray_tune pid=325294)[0m [384]	train-mlogloss:0.78725	validation-mlogloss:0.76004
[36m(train_xgb_ray_tune pid=325327)[0m [330]	train-mlogloss:0.75581	validation-mlogloss:0.72528
[36m(train_xgb_ray_tune pid=325342)[0m [376]	train-mlogloss:0.80673	validation-mlogloss:0.77364
[36m(train_xgb_ray_tune pid=325330)[0m [400]	train-mlogloss:0.57629	validation-mlogloss:0.54433
[36m(train_xgb_ray_tune pid=325331)[0m [395]	train-mlogloss:0.65258	validation-mlogloss:0.61738
[36m(train_xgb_ray_tune pid=325324)[0m [383]	train-mlogloss:0.63950	validation-mlogloss:0.60976
[36m(train_xgb_ray_tune pid=325296)[0m [473]	train-mlogloss:0.63074	validation-mlogloss:0.59407
[36m(train_xgb_ray_tune pid=325339)[0m [333]	train-mlogloss:0.79689	validation-mlogloss:0.77041
[36m(train_xgb_ray_tune pid=325307)[0m [413]	train-mlogloss:0.72798	validation-mlogloss:0.69529
[36m(train_xgb_ray_tune pid=325340)[0m [326]	train-mlogloss:0.57925	validation-mlogloss:0.54769
[36m(train_xgb_ray_tune pid=325330)[0m [401]	train-mlogloss:0.57622	validation-mlogloss:0.54421
[36m(train_xgb_ray_tune pid=325338)[0m [354]	train-mlogloss:0.77359	validation-mlogloss:0.74450
[36m(train_xgb_ray_tune pid=325324)[0m [384]	train-mlogloss:0.63950	validation-mlogloss:0.60976
[36m(train_xgb_ray_tune pid=325343)[0m [320]	train-mlogloss:0.54621	validation-mlogloss:0.52714
[36m(train_xgb_ray_tune pid=325296)[0m [474]	train-mlogloss:0.63061	validation-mlogloss:0.59396
[36m(train_xgb_ray_tune pid=325294)[0m [385]	train-mlogloss:0.78664	validation-mlogloss:0.75940
[36m(train_xgb_ray_tune pid=325327)[0m [331]	train-mlogloss:0.75523	validation-mlogloss:0.72468
[36m(train_xgb_ray_tune pid=325328)[0m [290]	train-mlogloss:0.73060	validation-mlogloss:0.71317
[36m(train_xgb_ray_tune pid=325340)[0m [327]	train-mlogloss:0.57911	validation-mlogloss:0.54760
[36m(train_xgb_ray_tune pid=325331)[0m [396]	train-mlogloss:0.65248	validation-mlogloss:0.61723
[36m(train_xgb_ray_tune pid=325324)[0m [385]	train-mlogloss:0.63950	validation-mlogloss:0.60976
[36m(train_xgb_ray_tune pid=325342)[0m [377]	train-mlogloss:0.80617	validation-mlogloss:0.77303
[36m(train_xgb_ray_tune pid=325307)[0m [414]	train-mlogloss:0.72748	validation-mlogloss:0.69476
[36m(train_xgb_ray_tune pid=325330)[0m [402]	train-mlogloss:0.57622	validation-mlogloss:0.54421
[36m(train_xgb_ray_tune pid=325331)[0m [397]	train-mlogloss:0.65248	validation-mlogloss:0.61723
[36m(train_xgb_ray_tune pid=325324)[0m [386]	train-mlogloss:0.63950	validation-mlogloss:0.60976
[36m(train_xgb_ray_tune pid=325296)[0m [475]	train-mlogloss:0.63049	validation-mlogloss:0.59382
[36m(train_xgb_ray_tune pid=325294)[0m [386]	train-mlogloss:0.78600	validation-mlogloss:0.75871
[36m(train_xgb_ray_tune pid=325327)[0m [332]	train-mlogloss:0.75471	validation-mlogloss:0.72417
[36m(train_xgb_ray_tune pid=325339)[0m [334]	train-mlogloss:0.79616	validation-mlogloss:0.76965
[36m(train_xgb_ray_tune pid=325340)[0m [328]	train-mlogloss:0.57888	validation-mlogloss:0.54731
[36m(train_xgb_ray_tune pid=325330)[0m [403]	train-mlogloss:0.57622	validation-mlogloss:0.54421
[36m(train_xgb_ray_tune pid=325338)[0m [355]	train-mlogloss:0.77327	validation-mlogloss:0.74420
[36m(train_xgb_ray_tune pid=325324)[0m [387]	train-mlogloss:0.63950	validation-mlogloss:0.60976
[36m(train_xgb_ray_tune pid=325343)[0m [321]	train-mlogloss:0.54576	validation-mlogloss:0.52681
[36m(train_xgb_ray_tune pid=325296)[0m [476]	train-mlogloss:0.63042	validation-mlogloss:0.59375
[36m(train_xgb_ray_tune pid=325328)[0m [291]	train-mlogloss:0.72983	validation-mlogloss:0.71238
[36m(train_xgb_ray_tune pid=325342)[0m [378]	train-mlogloss:0.80559	validation-mlogloss:0.77240
[36m(train_xgb_ray_tune pid=325307)[0m [415]	train-mlogloss:0.72697	validation-mlogloss:0.69423
[36m(train_xgb_ray_tune pid=325330)[0m [404]	train-mlogloss:0.57622	validation-mlogloss:0.54420
[36m(train_xgb_ray_tune pid=325331)[0m [398]	train-mlogloss:0.65238	validation-mlogloss:0.61716
[36m(train_xgb_ray_tune pid=325324)[0m [388]	train-mlogloss:0.63950	validation-mlogloss:0.60976

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:43. Total running time: 17s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             14.9073 │
│ time_total_s                 14.9073 │
│ training_iteration                 1 │
│ validation_accuracy          0.78695 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:43. Total running time: 17s
[36m(train_xgb_ray_tune pid=325296)[0m [477]	train-mlogloss:0.63035	validation-mlogloss:0.59368
[36m(train_xgb_ray_tune pid=325296)[0m [478]	train-mlogloss:0.63027	validation-mlogloss:0.59362
[36m(train_xgb_ray_tune pid=325296)[0m [479]	train-mlogloss:0.63020	validation-mlogloss:0.59356
[36m(train_xgb_ray_tune pid=325296)[0m [480]	train-mlogloss:0.63013	validation-mlogloss:0.59350
[36m(train_xgb_ray_tune pid=325296)[0m [481]	train-mlogloss:0.63006	validation-mlogloss:0.59340
[36m(train_xgb_ray_tune pid=325296)[0m [482]	train-mlogloss:0.62999	validation-mlogloss:0.59334
[36m(train_xgb_ray_tune pid=325296)[0m [483]	train-mlogloss:0.62992	validation-mlogloss:0.59329
[36m(train_xgb_ray_tune pid=325296)[0m [484]	train-mlogloss:0.62985	validation-mlogloss:0.59322
[36m(train_xgb_ray_tune pid=325296)[0m [485]	train-mlogloss:0.62973	validation-mlogloss:0.59305
[36m(train_xgb_ray_tune pid=325296)[0m [486]	train-mlogloss:0.62967	validation-mlogloss:0.59298
[36m(train_xgb_ray_tune pid=325294)[0m [387]	train-mlogloss:0.78546	validation-mlogloss:0.75813
[36m(train_xgb_ray_tune pid=325294)[0m [388]	train-mlogloss:0.78495	validation-mlogloss:0.75756
[36m(train_xgb_ray_tune pid=325294)[0m [389]	train-mlogloss:0.78432	validation-mlogloss:0.75691
[36m(train_xgb_ray_tune pid=325294)[0m [390]	train-mlogloss:0.78369	validation-mlogloss:0.75626
[36m(train_xgb_ray_tune pid=325294)[0m [391]	train-mlogloss:0.78304	validation-mlogloss:0.75561
[36m(train_xgb_ray_tune pid=325294)[0m [392]	train-mlogloss:0.78250	validation-mlogloss:0.75502
[36m(train_xgb_ray_tune pid=325327)[0m [333]	train-mlogloss:0.75410	validation-mlogloss:0.72357
[36m(train_xgb_ray_tune pid=325327)[0m [334]	train-mlogloss:0.75352	validation-mlogloss:0.72297
[36m(train_xgb_ray_tune pid=325327)[0m [335]	train-mlogloss:0.75302	validation-mlogloss:0.72246
[36m(train_xgb_ray_tune pid=325327)[0m [336]	train-mlogloss:0.75243	validation-mlogloss:0.72185
[36m(train_xgb_ray_tune pid=325327)[0m [337]	train-mlogloss:0.75184	validation-mlogloss:0.72122
[36m(train_xgb_ray_tune pid=325327)[0m [338]	train-mlogloss:0.75142	validation-mlogloss:0.72079
[36m(train_xgb_ray_tune pid=325327)[0m [339]	train-mlogloss:0.75084	validation-mlogloss:0.72015
[36m(train_xgb_ray_tune pid=325328)[0m [292]	train-mlogloss:0.72899	validation-mlogloss:0.71153
[36m(train_xgb_ray_tune pid=325328)[0m [293]	train-mlogloss:0.72816	validation-mlogloss:0.71072
[36m(train_xgb_ray_tune pid=325328)[0m [294]	train-mlogloss:0.72737	validation-mlogloss:0.70991
[36m(train_xgb_ray_tune pid=325328)[0m [295]	train-mlogloss:0.72656	validation-mlogloss:0.70909
[36m(train_xgb_ray_tune pid=325328)[0m [296]	train-mlogloss:0.72582	validation-mlogloss:0.70832
[36m(train_xgb_ray_tune pid=325339)[0m [335]	train-mlogloss:0.79547	validation-mlogloss:0.76897
[36m(train_xgb_ray_tune pid=325339)[0m [336]	train-mlogloss:0.79480	validation-mlogloss:0.76823
[36m(train_xgb_ray_tune pid=325339)[0m [337]	train-mlogloss:0.79418	validation-mlogloss:0.76756
[36m(train_xgb_ray_tune pid=325339)[0m [338]	train-mlogloss:0.79348	validation-mlogloss:0.76681
[36m(train_xgb_ray_tune pid=325339)[0m [339]	train-mlogloss:0.79276	validation-mlogloss:0.76607
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[36m(train_xgb_ray_tune pid=325328)[0m [309]	train-mlogloss:0.71581	validation-mlogloss:0.69801
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[36m(train_xgb_ray_tune pid=325338)[0m [390]	train-mlogloss:0.76257	validation-mlogloss:0.73375
[36m(train_xgb_ray_tune pid=325324)[0m [431]	train-mlogloss:0.63897	validation-mlogloss:0.60930
[36m(train_xgb_ray_tune pid=325342)[0m [416]	train-mlogloss:0.78281	validation-mlogloss:0.74881
[36m(train_xgb_ray_tune pid=325307)[0m [442]	train-mlogloss:0.71402	validation-mlogloss:0.68078
[36m(train_xgb_ray_tune pid=325330)[0m [445]	train-mlogloss:0.57502	validation-mlogloss:0.54288
[36m(train_xgb_ray_tune pid=325343)[0m [357]	train-mlogloss:0.53283	validation-mlogloss:0.51599
[36m(train_xgb_ray_tune pid=325327)[0m [361]	train-mlogloss:0.73975	validation-mlogloss:0.70850
[36m(train_xgb_ray_tune pid=325339)[0m [368]	train-mlogloss:0.77453	validation-mlogloss:0.74687
[36m(train_xgb_ray_tune pid=325340)[0m [375]	train-mlogloss:0.57194	validation-mlogloss:0.53977
[36m(train_xgb_ray_tune pid=325324)[0m [432]	train-mlogloss:0.63897	validation-mlogloss:0.60930
[36m(train_xgb_ray_tune pid=325294)[0m [412]	train-mlogloss:0.77100	validation-mlogloss:0.74304
[36m(train_xgb_ray_tune pid=325328)[0m [313]	train-mlogloss:0.71295	validation-mlogloss:0.69505
[36m(train_xgb_ray_tune pid=325330)[0m [446]	train-mlogloss:0.57502	validation-mlogloss:0.54288
[36m(train_xgb_ray_tune pid=325338)[0m [391]	train-mlogloss:0.76239	validation-mlogloss:0.73355
[36m(train_xgb_ray_tune pid=325296)[0m [516]	train-mlogloss:0.62691	validation-mlogloss:0.59005
[36m(train_xgb_ray_tune pid=325342)[0m [417]	train-mlogloss:0.78224	validation-mlogloss:0.74823
[36m(train_xgb_ray_tune pid=325307)[0m [443]	train-mlogloss:0.71355	validation-mlogloss:0.68031
[36m(train_xgb_ray_tune pid=325343)[0m [358]	train-mlogloss:0.53252	validation-mlogloss:0.51580
[36m(train_xgb_ray_tune pid=325327)[0m [362]	train-mlogloss:0.73929	validation-mlogloss:0.70804
[36m(train_xgb_ray_tune pid=325339)[0m [369]	train-mlogloss:0.77403	validation-mlogloss:0.74632
[36m(train_xgb_ray_tune pid=325340)[0m [376]	train-mlogloss:0.57182	validation-mlogloss:0.53964
[36m(train_xgb_ray_tune pid=325330)[0m [447]	train-mlogloss:0.57502	validation-mlogloss:0.54288
[36m(train_xgb_ray_tune pid=325324)[0m [433]	train-mlogloss:0.63897	validation-mlogloss:0.60930

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:43. Total running time: 18s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             14.9274 │
│ time_total_s                 14.9274 │
│ training_iteration                 1 │
│ validation_accuracy          0.75528 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:43. Total running time: 18s
[36m(train_xgb_ray_tune pid=325296)[0m [517]	train-mlogloss:0.62674	validation-mlogloss:0.58987
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[36m(train_xgb_ray_tune pid=325328)[0m [314]	train-mlogloss:0.71225	validation-mlogloss:0.69437
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[36m(train_xgb_ray_tune pid=325328)[0m [318]	train-mlogloss:0.70930	validation-mlogloss:0.69134
[36m(train_xgb_ray_tune pid=325339)[0m [370]	train-mlogloss:0.77353	validation-mlogloss:0.74582
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[36m(train_xgb_ray_tune pid=325342)[0m [418]	train-mlogloss:0.78168	validation-mlogloss:0.74762
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[36m(train_xgb_ray_tune pid=325307)[0m [444]	train-mlogloss:0.71320	validation-mlogloss:0.68000
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[36m(train_xgb_ray_tune pid=325307)[0m [449]	train-mlogloss:0.71101	validation-mlogloss:0.67782
[36m(train_xgb_ray_tune pid=325340)[0m [377]	train-mlogloss:0.57176	validation-mlogloss:0.53959
[36m(train_xgb_ray_tune pid=325340)[0m [378]	train-mlogloss:0.57169	validation-mlogloss:0.53954
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[36m(train_xgb_ray_tune pid=325330)[0m [448]	train-mlogloss:0.57502	validation-mlogloss:0.54288
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[36m(train_xgb_ray_tune pid=325296)[0m [589]	train-mlogloss:0.62233	validation-mlogloss:0.58505
[36m(train_xgb_ray_tune pid=325327)[0m [419]	train-mlogloss:0.71803	validation-mlogloss:0.68631
[36m(train_xgb_ray_tune pid=325342)[0m [475]	train-mlogloss:0.75362	validation-mlogloss:0.71866
[36m(train_xgb_ray_tune pid=325307)[0m [482]	train-mlogloss:0.69747	validation-mlogloss:0.66384
[36m(train_xgb_ray_tune pid=325340)[0m [428]	train-mlogloss:0.56722	validation-mlogloss:0.53458
[36m(train_xgb_ray_tune pid=325330)[0m [517]	train-mlogloss:0.57370	validation-mlogloss:0.54133
[36m(train_xgb_ray_tune pid=325338)[0m [438]	train-mlogloss:0.75384	validation-mlogloss:0.72466
[36m(train_xgb_ray_tune pid=325343)[0m [412]	train-mlogloss:0.51914	validation-mlogloss:0.50486

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:44. Total running time: 19s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             15.6138 │
│ time_total_s                 15.6138 │
│ training_iteration                 1 │
│ validation_accuracy          0.76018 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=325296)[0m [590]	train-mlogloss:0.62228	validation-mlogloss:0.58501
[36m(train_xgb_ray_tune pid=325294)[0m [448]	train-mlogloss:0.75273	validation-mlogloss:0.72384
[36m(train_xgb_ray_tune pid=325328)[0m [344]	train-mlogloss:0.69207	validation-mlogloss:0.67369
[36m(train_xgb_ray_tune pid=325339)[0m [405]	train-mlogloss:0.75478	validation-mlogloss:0.72620
[36m(train_xgb_ray_tune pid=325340)[0m [429]	train-mlogloss:0.56717	validation-mlogloss:0.53454
[36m(train_xgb_ray_tune pid=325330)[0m [518]	train-mlogloss:0.57363	validation-mlogloss:0.54122
[36m(train_xgb_ray_tune pid=325296)[0m [591]	train-mlogloss:0.62228	validation-mlogloss:0.58501
[36m(train_xgb_ray_tune pid=325327)[0m [420]	train-mlogloss:0.71771	validation-mlogloss:0.68600

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:44. Total running time: 19s
[36m(train_xgb_ray_tune pid=325342)[0m [476]	train-mlogloss:0.75318	validation-mlogloss:0.71821
[36m(train_xgb_ray_tune pid=325307)[0m [483]	train-mlogloss:0.69707	validation-mlogloss:0.66345
[36m(train_xgb_ray_tune pid=325330)[0m [519]	train-mlogloss:0.57363	validation-mlogloss:0.54122
[36m(train_xgb_ray_tune pid=325338)[0m [439]	train-mlogloss:0.75373	validation-mlogloss:0.72453
[36m(train_xgb_ray_tune pid=325343)[0m [413]	train-mlogloss:0.51889	validation-mlogloss:0.50469
[36m(train_xgb_ray_tune pid=325296)[0m [592]	train-mlogloss:0.62223	validation-mlogloss:0.58497
[36m(train_xgb_ray_tune pid=325294)[0m [449]	train-mlogloss:0.75236	validation-mlogloss:0.72344
[36m(train_xgb_ray_tune pid=325327)[0m [421]	train-mlogloss:0.71739	validation-mlogloss:0.68570
[36m(train_xgb_ray_tune pid=325328)[0m [345]	train-mlogloss:0.69143	validation-mlogloss:0.67307
[36m(train_xgb_ray_tune pid=325339)[0m [406]	train-mlogloss:0.75427	validation-mlogloss:0.72568
[36m(train_xgb_ray_tune pid=325342)[0m [477]	train-mlogloss:0.75278	validation-mlogloss:0.71778
[36m(train_xgb_ray_tune pid=325307)[0m [484]	train-mlogloss:0.69669	validation-mlogloss:0.66308
[36m(train_xgb_ray_tune pid=325340)[0m [430]	train-mlogloss:0.56712	validation-mlogloss:0.53451
[36m(train_xgb_ray_tune pid=325330)[0m [520]	train-mlogloss:0.57363	validation-mlogloss:0.54122
[36m(train_xgb_ray_tune pid=325338)[0m [440]	train-mlogloss:0.75362	validation-mlogloss:0.72439
[36m(train_xgb_ray_tune pid=325343)[0m [414]	train-mlogloss:0.51859	validation-mlogloss:0.50446
[36m(train_xgb_ray_tune pid=325296)[0m [593]	train-mlogloss:0.62207	validation-mlogloss:0.58480
[36m(train_xgb_ray_tune pid=325294)[0m [450]	train-mlogloss:0.75191	validation-mlogloss:0.72295
[36m(train_xgb_ray_tune pid=325340)[0m [431]	train-mlogloss:0.56707	validation-mlogloss:0.53448
[36m(train_xgb_ray_tune pid=325330)[0m [521]	train-mlogloss:0.57363	validation-mlogloss:0.54122
[36m(train_xgb_ray_tune pid=325339)[0m [407]	train-mlogloss:0.75375	validation-mlogloss:0.72517
[36m(train_xgb_ray_tune pid=325342)[0m [478]	train-mlogloss:0.75235	validation-mlogloss:0.71731
[36m(train_xgb_ray_tune pid=325338)[0m [441]	train-mlogloss:0.75351	validation-mlogloss:0.72425
[36m(train_xgb_ray_tune pid=325296)[0m [594]	train-mlogloss:0.62207	validation-mlogloss:0.58480
[36m(train_xgb_ray_tune pid=325328)[0m [346]	train-mlogloss:0.69086	validation-mlogloss:0.67249
[36m(train_xgb_ray_tune pid=325330)[0m [522]	train-mlogloss:0.57363	validation-mlogloss:0.54122
[36m(train_xgb_ray_tune pid=325327)[0m [422]	train-mlogloss:0.71707	validation-mlogloss:0.68540
[36m(train_xgb_ray_tune pid=325307)[0m [485]	train-mlogloss:0.69628	validation-mlogloss:0.66269
[36m(train_xgb_ray_tune pid=325340)[0m [432]	train-mlogloss:0.56702	validation-mlogloss:0.53445
[36m(train_xgb_ray_tune pid=325343)[0m [415]	train-mlogloss:0.51839	validation-mlogloss:0.50428
[36m(train_xgb_ray_tune pid=325296)[0m [595]	train-mlogloss:0.62207	validation-mlogloss:0.58480
[36m(train_xgb_ray_tune pid=325339)[0m [408]	train-mlogloss:0.75332	validation-mlogloss:0.72467
[36m(train_xgb_ray_tune pid=325330)[0m [523]	train-mlogloss:0.57363	validation-mlogloss:0.54122
[36m(train_xgb_ray_tune pid=325338)[0m [442]	train-mlogloss:0.75341	validation-mlogloss:0.72415
[36m(train_xgb_ray_tune pid=325294)[0m [451]	train-mlogloss:0.75142	validation-mlogloss:0.72239
[36m(train_xgb_ray_tune pid=325328)[0m [347]	train-mlogloss:0.69028	validation-mlogloss:0.67188
[36m(train_xgb_ray_tune pid=325342)[0m [479]	train-mlogloss:0.75193	validation-mlogloss:0.71689
[36m(train_xgb_ray_tune pid=325340)[0m [433]	train-mlogloss:0.56697	validation-mlogloss:0.53442
[36m(train_xgb_ray_tune pid=325343)[0m [416]	train-mlogloss:0.51823	validation-mlogloss:0.50416
[36m(train_xgb_ray_tune pid=325296)[0m [596]	train-mlogloss:0.62202	validation-mlogloss:0.58476
[36m(train_xgb_ray_tune pid=325330)[0m [524]	train-mlogloss:0.57357	validation-mlogloss:0.54118
[36m(train_xgb_ray_tune pid=325327)[0m [423]	train-mlogloss:0.71681	validation-mlogloss:0.68517
[36m(train_xgb_ray_tune pid=325339)[0m [409]	train-mlogloss:0.75288	validation-mlogloss:0.72413
[36m(train_xgb_ray_tune pid=325307)[0m [486]	train-mlogloss:0.69588	validation-mlogloss:0.66232
[36m(train_xgb_ray_tune pid=325338)[0m [443]	train-mlogloss:0.75331	validation-mlogloss:0.72401
[36m(train_xgb_ray_tune pid=325342)[0m [480]	train-mlogloss:0.75146	validation-mlogloss:0.71641
[36m(train_xgb_ray_tune pid=325330)[0m [525]	train-mlogloss:0.57357	validation-mlogloss:0.54118
[36m(train_xgb_ray_tune pid=325343)[0m [417]	train-mlogloss:0.51811	validation-mlogloss:0.50408
[36m(train_xgb_ray_tune pid=325296)[0m [597]	train-mlogloss:0.62202	validation-mlogloss:0.58476
[36m(train_xgb_ray_tune pid=325294)[0m [452]	train-mlogloss:0.75103	validation-mlogloss:0.72197
[36m(train_xgb_ray_tune pid=325340)[0m [434]	train-mlogloss:0.56687	validation-mlogloss:0.53425
[36m(train_xgb_ray_tune pid=325330)[0m [526]	train-mlogloss:0.57357	validation-mlogloss:0.54118
[36m(train_xgb_ray_tune pid=325328)[0m [348]	train-mlogloss:0.68970	validation-mlogloss:0.67132
[36m(train_xgb_ray_tune pid=325339)[0m [410]	train-mlogloss:0.75234	validation-mlogloss:0.72356
[36m(train_xgb_ray_tune pid=325296)[0m [598]	train-mlogloss:0.62197	validation-mlogloss:0.58471
[36m(train_xgb_ray_tune pid=325327)[0m [424]	train-mlogloss:0.71650	validation-mlogloss:0.68484
[36m(train_xgb_ray_tune pid=325307)[0m [487]	train-mlogloss:0.69552	validation-mlogloss:0.66196
[36m(train_xgb_ray_tune pid=325330)[0m [527]	train-mlogloss:0.57357	validation-mlogloss:0.54118
[36m(train_xgb_ray_tune pid=325338)[0m [444]	train-mlogloss:0.75320	validation-mlogloss:0.72391
[36m(train_xgb_ray_tune pid=325342)[0m [481]	train-mlogloss:0.75106	validation-mlogloss:0.71597
[36m(train_xgb_ray_tune pid=325343)[0m [418]	train-mlogloss:0.51792	validation-mlogloss:0.50395
[36m(train_xgb_ray_tune pid=325340)[0m [435]	train-mlogloss:0.56677	validation-mlogloss:0.53413
[36m(train_xgb_ray_tune pid=325296)[0m [599]	train-mlogloss:0.62192	validation-mlogloss:0.58467
[36m(train_xgb_ray_tune pid=325339)[0m [411]	train-mlogloss:0.75191	validation-mlogloss:0.72313
[36m(train_xgb_ray_tune pid=325330)[0m [528]	train-mlogloss:0.57344	validation-mlogloss:0.54100
[36m(train_xgb_ray_tune pid=325294)[0m [453]	train-mlogloss:0.75051	validation-mlogloss:0.72143
[36m(train_xgb_ray_tune pid=325328)[0m [349]	train-mlogloss:0.68920	validation-mlogloss:0.67081
[36m(train_xgb_ray_tune pid=325338)[0m [445]	train-mlogloss:0.75309	validation-mlogloss:0.72377
[36m(train_xgb_ray_tune pid=325327)[0m [425]	train-mlogloss:0.71618	validation-mlogloss:0.68452
[36m(train_xgb_ray_tune pid=325342)[0m [482]	train-mlogloss:0.75060	validation-mlogloss:0.71552
[36m(train_xgb_ray_tune pid=325307)[0m [488]	train-mlogloss:0.69518	validation-mlogloss:0.66160
[36m(train_xgb_ray_tune pid=325340)[0m [436]	train-mlogloss:0.56672	validation-mlogloss:0.53410
[36m(train_xgb_ray_tune pid=325330)[0m [529]	train-mlogloss:0.57338	validation-mlogloss:0.54096
[36m(train_xgb_ray_tune pid=325343)[0m [419]	train-mlogloss:0.51768	validation-mlogloss:0.50368
[36m(train_xgb_ray_tune pid=325296)[0m [600]	train-mlogloss:0.62192	validation-mlogloss:0.58467
[36m(train_xgb_ray_tune pid=325339)[0m [412]	train-mlogloss:0.75149	validation-mlogloss:0.72267
[36m(train_xgb_ray_tune pid=325330)[0m [530]	train-mlogloss:0.57338	validation-mlogloss:0.54096
[36m(train_xgb_ray_tune pid=325338)[0m [446]	train-mlogloss:0.75298	validation-mlogloss:0.72366
[36m(train_xgb_ray_tune pid=325296)[0m [601]	train-mlogloss:0.62187	validation-mlogloss:0.58464
[36m(train_xgb_ray_tune pid=325340)[0m [437]	train-mlogloss:0.56667	validation-mlogloss:0.53406
[36m(train_xgb_ray_tune pid=325343)[0m [420]	train-mlogloss:0.51748	validation-mlogloss:0.50349
[36m(train_xgb_ray_tune pid=325294)[0m [454]	train-mlogloss:0.75011	validation-mlogloss:0.72098
[36m(train_xgb_ray_tune pid=325339)[0m [413]	train-mlogloss:0.75106	validation-mlogloss:0.72221
[36m(train_xgb_ray_tune pid=325342)[0m [483]	train-mlogloss:0.75016	validation-mlogloss:0.71506
[36m(train_xgb_ray_tune pid=325307)[0m [489]	train-mlogloss:0.69478	validation-mlogloss:0.66119
[36m(train_xgb_ray_tune pid=325330)[0m [531]	train-mlogloss:0.57338	validation-mlogloss:0.54097
[36m(train_xgb_ray_tune pid=325327)[0m [426]	train-mlogloss:0.71587	validation-mlogloss:0.68420
[36m(train_xgb_ray_tune pid=325328)[0m [350]	train-mlogloss:0.68855	validation-mlogloss:0.67013
[36m(train_xgb_ray_tune pid=325330)[0m [532]	train-mlogloss:0.57338	validation-mlogloss:0.54096
[36m(train_xgb_ray_tune pid=325338)[0m [447]	train-mlogloss:0.75288	validation-mlogloss:0.72357
[36m(train_xgb_ray_tune pid=325296)[0m [602]	train-mlogloss:0.62182	validation-mlogloss:0.58456
[36m(train_xgb_ray_tune pid=325342)[0m [484]	train-mlogloss:0.74974	validation-mlogloss:0.71460
[36m(train_xgb_ray_tune pid=325340)[0m [438]	train-mlogloss:0.56663	validation-mlogloss:0.53399
[36m(train_xgb_ray_tune pid=325339)[0m [414]	train-mlogloss:0.75061	validation-mlogloss:0.72170
[36m(train_xgb_ray_tune pid=325330)[0m [533]	train-mlogloss:0.57338	validation-mlogloss:0.54096
[36m(train_xgb_ray_tune pid=325296)[0m [603]	train-mlogloss:0.62176	validation-mlogloss:0.58448
[36m(train_xgb_ray_tune pid=325343)[0m [421]	train-mlogloss:0.51727	validation-mlogloss:0.50320
[36m(train_xgb_ray_tune pid=325294)[0m [455]	train-mlogloss:0.74962	validation-mlogloss:0.72049
[36m(train_xgb_ray_tune pid=325327)[0m [427]	train-mlogloss:0.71557	validation-mlogloss:0.68391
[36m(train_xgb_ray_tune pid=325328)[0m [351]	train-mlogloss:0.68800	validation-mlogloss:0.66954
[36m(train_xgb_ray_tune pid=325342)[0m [485]	train-mlogloss:0.74937	validation-mlogloss:0.71421
[36m(train_xgb_ray_tune pid=325307)[0m [490]	train-mlogloss:0.69438	validation-mlogloss:0.66078
[36m(train_xgb_ray_tune pid=325340)[0m [439]	train-mlogloss:0.56658	validation-mlogloss:0.53395
[36m(train_xgb_ray_tune pid=325330)[0m [534]	train-mlogloss:0.57338	validation-mlogloss:0.54097
[36m(train_xgb_ray_tune pid=325338)[0m [448]	train-mlogloss:0.75278	validation-mlogloss:0.72346
[36m(train_xgb_ray_tune pid=325296)[0m [604]	train-mlogloss:0.62176	validation-mlogloss:0.58448
[36m(train_xgb_ray_tune pid=325339)[0m [415]	train-mlogloss:0.75010	validation-mlogloss:0.72121
[36m(train_xgb_ray_tune pid=325330)[0m [535]	train-mlogloss:0.57338	validation-mlogloss:0.54097
[36m(train_xgb_ray_tune pid=325342)[0m [486]	train-mlogloss:0.74894	validation-mlogloss:0.71379
[36m(train_xgb_ray_tune pid=325296)[0m [605]	train-mlogloss:0.62171	validation-mlogloss:0.58443
[36m(train_xgb_ray_tune pid=325328)[0m [352]	train-mlogloss:0.68742	validation-mlogloss:0.66894
[36m(train_xgb_ray_tune pid=325340)[0m [440]	train-mlogloss:0.56653	validation-mlogloss:0.53387
[36m(train_xgb_ray_tune pid=325330)[0m [536]	train-mlogloss:0.57338	validation-mlogloss:0.54097
[36m(train_xgb_ray_tune pid=325338)[0m [449]	train-mlogloss:0.75267	validation-mlogloss:0.72335
[36m(train_xgb_ray_tune pid=325343)[0m [422]	train-mlogloss:0.51709	validation-mlogloss:0.50300
[36m(train_xgb_ray_tune pid=325294)[0m [456]	train-mlogloss:0.74914	validation-mlogloss:0.71997
[36m(train_xgb_ray_tune pid=325327)[0m [428]	train-mlogloss:0.71526	validation-mlogloss:0.68362
[36m(train_xgb_ray_tune pid=325339)[0m [416]	train-mlogloss:0.74958	validation-mlogloss:0.72068
[36m(train_xgb_ray_tune pid=325342)[0m [487]	train-mlogloss:0.74855	validation-mlogloss:0.71340
[36m(train_xgb_ray_tune pid=325307)[0m [491]	train-mlogloss:0.69403	validation-mlogloss:0.66042
[36m(train_xgb_ray_tune pid=325330)[0m [537]	train-mlogloss:0.57338	validation-mlogloss:0.54097
[36m(train_xgb_ray_tune pid=325296)[0m [606]	train-mlogloss:0.62166	validation-mlogloss:0.58441
[36m(train_xgb_ray_tune pid=325342)[0m [488]	train-mlogloss:0.74813	validation-mlogloss:0.71296
[36m(train_xgb_ray_tune pid=325340)[0m [441]	train-mlogloss:0.56644	validation-mlogloss:0.53382
[36m(train_xgb_ray_tune pid=325330)[0m [538]	train-mlogloss:0.57332	validation-mlogloss:0.54093
[36m(train_xgb_ray_tune pid=325338)[0m [450]	train-mlogloss:0.75248	validation-mlogloss:0.72315
[36m(train_xgb_ray_tune pid=325296)[0m [607]	train-mlogloss:0.62166	validation-mlogloss:0.58441
[36m(train_xgb_ray_tune pid=325328)[0m [353]	train-mlogloss:0.68680	validation-mlogloss:0.66832
[36m(train_xgb_ray_tune pid=325339)[0m [417]	train-mlogloss:0.74912	validation-mlogloss:0.72020
[36m(train_xgb_ray_tune pid=325343)[0m [423]	train-mlogloss:0.51686	validation-mlogloss:0.50279
[36m(train_xgb_ray_tune pid=325327)[0m [429]	train-mlogloss:0.71494	validation-mlogloss:0.68329
[36m(train_xgb_ray_tune pid=325307)[0m [492]	train-mlogloss:0.69367	validation-mlogloss:0.66008
[36m(train_xgb_ray_tune pid=325330)[0m [539]	train-mlogloss:0.57332	validation-mlogloss:0.54093
[36m(train_xgb_ray_tune pid=325296)[0m [608]	train-mlogloss:0.62161	validation-mlogloss:0.58437
[36m(train_xgb_ray_tune pid=325294)[0m [457]	train-mlogloss:0.74868	validation-mlogloss:0.71949
[36m(train_xgb_ray_tune pid=325339)[0m [418]	train-mlogloss:0.74873	validation-mlogloss:0.71975
[36m(train_xgb_ray_tune pid=325342)[0m [489]	train-mlogloss:0.74767	validation-mlogloss:0.71250
[36m(train_xgb_ray_tune pid=325340)[0m [442]	train-mlogloss:0.56639	validation-mlogloss:0.53373
[36m(train_xgb_ray_tune pid=325338)[0m [451]	train-mlogloss:0.75238	validation-mlogloss:0.72305
[36m(train_xgb_ray_tune pid=325330)[0m [540]	train-mlogloss:0.57332	validation-mlogloss:0.54093
[36m(train_xgb_ray_tune pid=325296)[0m [609]	train-mlogloss:0.62161	validation-mlogloss:0.58437
[36m(train_xgb_ray_tune pid=325328)[0m [354]	train-mlogloss:0.68623	validation-mlogloss:0.66773
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[36m(train_xgb_ray_tune pid=325307)[0m [493]	train-mlogloss:0.69329	validation-mlogloss:0.65972
[36m(train_xgb_ray_tune pid=325330)[0m [541]	train-mlogloss:0.57332	validation-mlogloss:0.54093
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[36m(train_xgb_ray_tune pid=325294)[0m [493]	train-mlogloss:0.73317	validation-mlogloss:0.70298
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[36m(train_xgb_ray_tune pid=325330)[0m [640]	train-mlogloss:0.57274	validation-mlogloss:0.54021
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[36m(train_xgb_ray_tune pid=325339)[0m [479]	train-mlogloss:0.72387	validation-mlogloss:0.69371
[36m(train_xgb_ray_tune pid=325330)[0m [641]	train-mlogloss:0.57274	validation-mlogloss:0.54021

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:45. Total running time: 20s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             16.6177 │
│ time_total_s                 16.6177 │
│ training_iteration                 1 │
│ validation_accuracy          0.78243 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:45. Total running time: 20s
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[36m(train_xgb_ray_tune pid=325338)[0m [532]	train-mlogloss:0.74552	validation-mlogloss:0.71545
[36m(train_xgb_ray_tune pid=325339)[0m [501]	train-mlogloss:0.71627	validation-mlogloss:0.68564
[36m(train_xgb_ray_tune pid=325342)[0m [582]	train-mlogloss:0.71463	validation-mlogloss:0.67851
[36m(train_xgb_ray_tune pid=325343)[0m [486]	train-mlogloss:0.50790	validation-mlogloss:0.49585
[36m(train_xgb_ray_tune pid=325296)[0m [744]	train-mlogloss:0.62032	validation-mlogloss:0.58301
[36m(train_xgb_ray_tune pid=325327)[0m [499]	train-mlogloss:0.69741	validation-mlogloss:0.66562
[36m(train_xgb_ray_tune pid=325328)[0m [407]	train-mlogloss:0.65886	validation-mlogloss:0.63970
[36m(train_xgb_ray_tune pid=325338)[0m [533]	train-mlogloss:0.74552	validation-mlogloss:0.71545
[36m(train_xgb_ray_tune pid=325294)[0m [507]	train-mlogloss:0.72749	validation-mlogloss:0.69703
[36m(train_xgb_ray_tune pid=325307)[0m [548]	train-mlogloss:0.67478	validation-mlogloss:0.64054
[36m(train_xgb_ray_tune pid=325296)[0m [745]	train-mlogloss:0.62032	validation-mlogloss:0.58302
[36m(train_xgb_ray_tune pid=325342)[0m [583]	train-mlogloss:0.71431	validation-mlogloss:0.67817
[36m(train_xgb_ray_tune pid=325338)[0m [534]	train-mlogloss:0.74552	validation-mlogloss:0.71545
[36m(train_xgb_ray_tune pid=325327)[0m [500]	train-mlogloss:0.69725	validation-mlogloss:0.66544
[36m(train_xgb_ray_tune pid=325339)[0m [502]	train-mlogloss:0.71592	validation-mlogloss:0.68527
[36m(train_xgb_ray_tune pid=325296)[0m [746]	train-mlogloss:0.62032	validation-mlogloss:0.58302
[36m(train_xgb_ray_tune pid=325338)[0m [535]	train-mlogloss:0.74552	validation-mlogloss:0.71545
[36m(train_xgb_ray_tune pid=325343)[0m [487]	train-mlogloss:0.50774	validation-mlogloss:0.49571
[36m(train_xgb_ray_tune pid=325328)[0m [408]	train-mlogloss:0.65837	validation-mlogloss:0.63919
[36m(train_xgb_ray_tune pid=325342)[0m [584]	train-mlogloss:0.71400	validation-mlogloss:0.67787
[36m(train_xgb_ray_tune pid=325296)[0m [747]	train-mlogloss:0.62032	validation-mlogloss:0.58302
[36m(train_xgb_ray_tune pid=325327)[0m [501]	train-mlogloss:0.69699	validation-mlogloss:0.66516
[36m(train_xgb_ray_tune pid=325307)[0m [549]	train-mlogloss:0.67447	validation-mlogloss:0.64026
[36m(train_xgb_ray_tune pid=325338)[0m [536]	train-mlogloss:0.74552	validation-mlogloss:0.71545
[36m(train_xgb_ray_tune pid=325294)[0m [508]	train-mlogloss:0.72705	validation-mlogloss:0.69657
[36m(train_xgb_ray_tune pid=325339)[0m [503]	train-mlogloss:0.71565	validation-mlogloss:0.68495
[36m(train_xgb_ray_tune pid=325342)[0m [585]	train-mlogloss:0.71367	validation-mlogloss:0.67754
[36m(train_xgb_ray_tune pid=325338)[0m [537]	train-mlogloss:0.74552	validation-mlogloss:0.71545
[36m(train_xgb_ray_tune pid=325343)[0m [488]	train-mlogloss:0.50764	validation-mlogloss:0.49555
[36m(train_xgb_ray_tune pid=325296)[0m [748]	train-mlogloss:0.62027	validation-mlogloss:0.58297
[36m(train_xgb_ray_tune pid=325327)[0m [502]	train-mlogloss:0.69684	validation-mlogloss:0.66501
[36m(train_xgb_ray_tune pid=325328)[0m [409]	train-mlogloss:0.65790	validation-mlogloss:0.63871
[36m(train_xgb_ray_tune pid=325296)[0m [749]	train-mlogloss:0.62027	validation-mlogloss:0.58297
[36m(train_xgb_ray_tune pid=325342)[0m [586]	train-mlogloss:0.71333	validation-mlogloss:0.67720
[36m(train_xgb_ray_tune pid=325338)[0m [538]	train-mlogloss:0.74552	validation-mlogloss:0.71545
[36m(train_xgb_ray_tune pid=325327)[0m [503]	train-mlogloss:0.69663	validation-mlogloss:0.66479
[36m(train_xgb_ray_tune pid=325307)[0m [550]	train-mlogloss:0.67417	validation-mlogloss:0.63994
[36m(train_xgb_ray_tune pid=325296)[0m [750]	train-mlogloss:0.62027	validation-mlogloss:0.58297
[36m(train_xgb_ray_tune pid=325294)[0m [509]	train-mlogloss:0.72666	validation-mlogloss:0.69616
[36m(train_xgb_ray_tune pid=325328)[0m [410]	train-mlogloss:0.65743	validation-mlogloss:0.63826
[36m(train_xgb_ray_tune pid=325339)[0m [504]	train-mlogloss:0.71530	validation-mlogloss:0.68456
[36m(train_xgb_ray_tune pid=325338)[0m [539]	train-mlogloss:0.74552	validation-mlogloss:0.71545
[36m(train_xgb_ray_tune pid=325343)[0m [489]	train-mlogloss:0.50753	validation-mlogloss:0.49542
[36m(train_xgb_ray_tune pid=325342)[0m [587]	train-mlogloss:0.71306	validation-mlogloss:0.67692
[36m(train_xgb_ray_tune pid=325327)[0m [504]	train-mlogloss:0.69639	validation-mlogloss:0.66456
[36m(train_xgb_ray_tune pid=325296)[0m [751]	train-mlogloss:0.62027	validation-mlogloss:0.58297
[36m(train_xgb_ray_tune pid=325338)[0m [540]	train-mlogloss:0.74544	validation-mlogloss:0.71538
[36m(train_xgb_ray_tune pid=325339)[0m [505]	train-mlogloss:0.71497	validation-mlogloss:0.68419
[36m(train_xgb_ray_tune pid=325327)[0m [505]	train-mlogloss:0.69613	validation-mlogloss:0.66427

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:45. Total running time: 20s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             17.0261 │
│ time_total_s                 17.0261 │
│ training_iteration                 1 │
│ validation_accuracy          0.77074 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=325328)[0m [411]	train-mlogloss:0.65698	validation-mlogloss:0.63778
[36m(train_xgb_ray_tune pid=325342)[0m [588]	train-mlogloss:0.71276	validation-mlogloss:0.67659
[36m(train_xgb_ray_tune pid=325307)[0m [551]	train-mlogloss:0.67389	validation-mlogloss:0.63966
[36m(train_xgb_ray_tune pid=325338)[0m [541]	train-mlogloss:0.74544	validation-mlogloss:0.71538
[36m(train_xgb_ray_tune pid=325296)[0m [752]	train-mlogloss:0.62027	validation-mlogloss:0.58298
[36m(train_xgb_ray_tune pid=325294)[0m [510]	train-mlogloss:0.72623	validation-mlogloss:0.69573
[36m(train_xgb_ray_tune pid=325343)[0m [490]	train-mlogloss:0.50740	validation-mlogloss:0.49530
[36m(train_xgb_ray_tune pid=325339)[0m [506]	train-mlogloss:0.71462	validation-mlogloss:0.68383
[36m(train_xgb_ray_tune pid=325338)[0m [542]	train-mlogloss:0.74544	validation-mlogloss:0.71538
[36m(train_xgb_ray_tune pid=325296)[0m [753]	train-mlogloss:0.62027	validation-mlogloss:0.58298
[36m(train_xgb_ray_tune pid=325307)[0m [552]	train-mlogloss:0.67361	validation-mlogloss:0.63935
[36m(train_xgb_ray_tune pid=325294)[0m [511]	train-mlogloss:0.72583	validation-mlogloss:0.69527
[36m(train_xgb_ray_tune pid=325328)[0m [412]	train-mlogloss:0.65651	validation-mlogloss:0.63729
[36m(train_xgb_ray_tune pid=325342)[0m [589]	train-mlogloss:0.71246	validation-mlogloss:0.67630
[36m(train_xgb_ray_tune pid=325296)[0m [754]	train-mlogloss:0.62027	validation-mlogloss:0.58298
[36m(train_xgb_ray_tune pid=325327)[0m [506]	train-mlogloss:0.69588	validation-mlogloss:0.66396
[36m(train_xgb_ray_tune pid=325338)[0m [543]	train-mlogloss:0.74544	validation-mlogloss:0.71538
[36m(train_xgb_ray_tune pid=325343)[0m [491]	train-mlogloss:0.50723	validation-mlogloss:0.49510
[36m(train_xgb_ray_tune pid=325339)[0m [507]	train-mlogloss:0.71427	validation-mlogloss:0.68343
[36m(train_xgb_ray_tune pid=325307)[0m [553]	train-mlogloss:0.67334	validation-mlogloss:0.63911

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:45. Total running time: 20s
[36m(train_xgb_ray_tune pid=325296)[0m [755]	train-mlogloss:0.62027	validation-mlogloss:0.58298
[36m(train_xgb_ray_tune pid=325294)[0m [512]	train-mlogloss:0.72544	validation-mlogloss:0.69487
[36m(train_xgb_ray_tune pid=325342)[0m [590]	train-mlogloss:0.71217	validation-mlogloss:0.67597
[36m(train_xgb_ray_tune pid=325338)[0m [544]	train-mlogloss:0.74544	validation-mlogloss:0.71538
[36m(train_xgb_ray_tune pid=325328)[0m [413]	train-mlogloss:0.65611	validation-mlogloss:0.63684
[36m(train_xgb_ray_tune pid=325343)[0m [492]	train-mlogloss:0.50716	validation-mlogloss:0.49502
[36m(train_xgb_ray_tune pid=325327)[0m [507]	train-mlogloss:0.69567	validation-mlogloss:0.66371
[36m(train_xgb_ray_tune pid=325307)[0m [554]	train-mlogloss:0.67301	validation-mlogloss:0.63877
[36m(train_xgb_ray_tune pid=325338)[0m [545]	train-mlogloss:0.74544	validation-mlogloss:0.71538
[36m(train_xgb_ray_tune pid=325296)[0m [756]	train-mlogloss:0.62022	validation-mlogloss:0.58290
[36m(train_xgb_ray_tune pid=325339)[0m [508]	train-mlogloss:0.71391	validation-mlogloss:0.68304
[36m(train_xgb_ray_tune pid=325342)[0m [591]	train-mlogloss:0.71191	validation-mlogloss:0.67570
[36m(train_xgb_ray_tune pid=325343)[0m [493]	train-mlogloss:0.50705	validation-mlogloss:0.49495
[36m(train_xgb_ray_tune pid=325296)[0m [757]	train-mlogloss:0.62017	validation-mlogloss:0.58286
[36m(train_xgb_ray_tune pid=325294)[0m [513]	train-mlogloss:0.72506	validation-mlogloss:0.69449
[36m(train_xgb_ray_tune pid=325328)[0m [414]	train-mlogloss:0.65565	validation-mlogloss:0.63637
[36m(train_xgb_ray_tune pid=325307)[0m [555]	train-mlogloss:0.67269	validation-mlogloss:0.63840
[36m(train_xgb_ray_tune pid=325338)[0m [546]	train-mlogloss:0.74535	validation-mlogloss:0.71530
[36m(train_xgb_ray_tune pid=325327)[0m [508]	train-mlogloss:0.69545	validation-mlogloss:0.66348
[36m(train_xgb_ray_tune pid=325342)[0m [592]	train-mlogloss:0.71160	validation-mlogloss:0.67539
[36m(train_xgb_ray_tune pid=325338)[0m [547]	train-mlogloss:0.74535	validation-mlogloss:0.71530
[36m(train_xgb_ray_tune pid=325296)[0m [758]	train-mlogloss:0.62017	validation-mlogloss:0.58286
[36m(train_xgb_ray_tune pid=325339)[0m [509]	train-mlogloss:0.71357	validation-mlogloss:0.68267
[36m(train_xgb_ray_tune pid=325307)[0m [556]	train-mlogloss:0.67240	validation-mlogloss:0.63809
[36m(train_xgb_ray_tune pid=325343)[0m [494]	train-mlogloss:0.50698	validation-mlogloss:0.49493
[36m(train_xgb_ray_tune pid=325328)[0m [415]	train-mlogloss:0.65520	validation-mlogloss:0.63591
[36m(train_xgb_ray_tune pid=325338)[0m [548]	train-mlogloss:0.74526	validation-mlogloss:0.71522
[36m(train_xgb_ray_tune pid=325296)[0m [759]	train-mlogloss:0.62012	validation-mlogloss:0.58278
[36m(train_xgb_ray_tune pid=325294)[0m [514]	train-mlogloss:0.72465	validation-mlogloss:0.69409
[36m(train_xgb_ray_tune pid=325327)[0m [509]	train-mlogloss:0.69523	validation-mlogloss:0.66324
[36m(train_xgb_ray_tune pid=325339)[0m [510]	train-mlogloss:0.71328	validation-mlogloss:0.68237
[36m(train_xgb_ray_tune pid=325342)[0m [593]	train-mlogloss:0.71136	validation-mlogloss:0.67516
[36m(train_xgb_ray_tune pid=325307)[0m [557]	train-mlogloss:0.67214	validation-mlogloss:0.63786
[36m(train_xgb_ray_tune pid=325338)[0m [549]	train-mlogloss:0.74518	validation-mlogloss:0.71511
[36m(train_xgb_ray_tune pid=325343)[0m [495]	train-mlogloss:0.50688	validation-mlogloss:0.49483
[36m(train_xgb_ray_tune pid=325296)[0m [760]	train-mlogloss:0.62012	validation-mlogloss:0.58278
[36m(train_xgb_ray_tune pid=325328)[0m [416]	train-mlogloss:0.65475	validation-mlogloss:0.63544
[36m(train_xgb_ray_tune pid=325342)[0m [594]	train-mlogloss:0.71110	validation-mlogloss:0.67491
[36m(train_xgb_ray_tune pid=325338)[0m [550]	train-mlogloss:0.74509	validation-mlogloss:0.71500
[36m(train_xgb_ray_tune pid=325296)[0m [761]	train-mlogloss:0.62012	validation-mlogloss:0.58278
[36m(train_xgb_ray_tune pid=325294)[0m [515]	train-mlogloss:0.72428	validation-mlogloss:0.69367
[36m(train_xgb_ray_tune pid=325327)[0m [510]	train-mlogloss:0.69509	validation-mlogloss:0.66308
[36m(train_xgb_ray_tune pid=325339)[0m [511]	train-mlogloss:0.71293	validation-mlogloss:0.68198
[36m(train_xgb_ray_tune pid=325307)[0m [558]	train-mlogloss:0.67183	validation-mlogloss:0.63756
[36m(train_xgb_ray_tune pid=325343)[0m [496]	train-mlogloss:0.50677	validation-mlogloss:0.49469
[36m(train_xgb_ray_tune pid=325338)[0m [551]	train-mlogloss:0.74509	validation-mlogloss:0.71500
[36m(train_xgb_ray_tune pid=325296)[0m [762]	train-mlogloss:0.62012	validation-mlogloss:0.58278
[36m(train_xgb_ray_tune pid=325307)[0m [559]	train-mlogloss:0.67154	validation-mlogloss:0.63730
[36m(train_xgb_ray_tune pid=325328)[0m [417]	train-mlogloss:0.65431	validation-mlogloss:0.63499
[36m(train_xgb_ray_tune pid=325339)[0m [512]	train-mlogloss:0.71259	validation-mlogloss:0.68164
[36m(train_xgb_ray_tune pid=325342)[0m [595]	train-mlogloss:0.71078	validation-mlogloss:0.67457
[36m(train_xgb_ray_tune pid=325338)[0m [552]	train-mlogloss:0.74509	validation-mlogloss:0.71500
[36m(train_xgb_ray_tune pid=325296)[0m [763]	train-mlogloss:0.62007	validation-mlogloss:0.58271
[36m(train_xgb_ray_tune pid=325294)[0m [516]	train-mlogloss:0.72392	validation-mlogloss:0.69328
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[36m(train_xgb_ray_tune pid=325343)[0m [497]	train-mlogloss:0.50669	validation-mlogloss:0.49468
[36m(train_xgb_ray_tune pid=325307)[0m [560]	train-mlogloss:0.67129	validation-mlogloss:0.63705
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[36m(train_xgb_ray_tune pid=325342)[0m [596]	train-mlogloss:0.71047	validation-mlogloss:0.67424
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[36m(train_xgb_ray_tune pid=325296)[0m [765]	train-mlogloss:0.62007	validation-mlogloss:0.58271
[36m(train_xgb_ray_tune pid=325327)[0m [512]	train-mlogloss:0.69467	validation-mlogloss:0.66261
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[36m(train_xgb_ray_tune pid=325339)[0m [513]	train-mlogloss:0.71224	validation-mlogloss:0.68128
[36m(train_xgb_ray_tune pid=325307)[0m [561]	train-mlogloss:0.67101	validation-mlogloss:0.63676
[36m(train_xgb_ray_tune pid=325342)[0m [597]	train-mlogloss:0.71018	validation-mlogloss:0.67396
[36m(train_xgb_ray_tune pid=325338)[0m [555]	train-mlogloss:0.74509	validation-mlogloss:0.71500
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[36m(train_xgb_ray_tune pid=325294)[0m [518]	train-mlogloss:0.72327	validation-mlogloss:0.69261
[36m(train_xgb_ray_tune pid=325343)[0m [499]	train-mlogloss:0.50650	validation-mlogloss:0.49446
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[36m(train_xgb_ray_tune pid=325339)[0m [514]	train-mlogloss:0.71192	validation-mlogloss:0.68096
[36m(train_xgb_ray_tune pid=325342)[0m [598]	train-mlogloss:0.70988	validation-mlogloss:0.67365
[36m(train_xgb_ray_tune pid=325338)[0m [557]	train-mlogloss:0.74500	validation-mlogloss:0.71488
[36m(train_xgb_ray_tune pid=325343)[0m [500]	train-mlogloss:0.50640	validation-mlogloss:0.49434
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[36m(train_xgb_ray_tune pid=325327)[0m [514]	train-mlogloss:0.69428	validation-mlogloss:0.66230
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[36m(train_xgb_ray_tune pid=325307)[0m [564]	train-mlogloss:0.67018	validation-mlogloss:0.63589
[36m(train_xgb_ray_tune pid=325343)[0m [501]	train-mlogloss:0.50624	validation-mlogloss:0.49416
[36m(train_xgb_ray_tune pid=325294)[0m [520]	train-mlogloss:0.72249	validation-mlogloss:0.69175
[36m(train_xgb_ray_tune pid=325328)[0m [420]	train-mlogloss:0.65302	validation-mlogloss:0.63372
[36m(train_xgb_ray_tune pid=325342)[0m [600]	train-mlogloss:0.70931	validation-mlogloss:0.67303
[36m(train_xgb_ray_tune pid=325338)[0m [559]	train-mlogloss:0.74500	validation-mlogloss:0.71488
[36m(train_xgb_ray_tune pid=325294)[0m [521]	train-mlogloss:0.72210	validation-mlogloss:0.69135
[36m(train_xgb_ray_tune pid=325294)[0m [522]	train-mlogloss:0.72170	validation-mlogloss:0.69093
[36m(train_xgb_ray_tune pid=325294)[0m [523]	train-mlogloss:0.72134	validation-mlogloss:0.69052
[36m(train_xgb_ray_tune pid=325294)[0m [524]	train-mlogloss:0.72095	validation-mlogloss:0.69012
[36m(train_xgb_ray_tune pid=325294)[0m [525]	train-mlogloss:0.72051	validation-mlogloss:0.68965
[36m(train_xgb_ray_tune pid=325294)[0m [526]	train-mlogloss:0.72011	validation-mlogloss:0.68927
[36m(train_xgb_ray_tune pid=325294)[0m [527]	train-mlogloss:0.71978	validation-mlogloss:0.68891
[36m(train_xgb_ray_tune pid=325294)[0m [528]	train-mlogloss:0.71943	validation-mlogloss:0.68850
[36m(train_xgb_ray_tune pid=325294)[0m [529]	train-mlogloss:0.71904	validation-mlogloss:0.68812
[36m(train_xgb_ray_tune pid=325294)[0m [530]	train-mlogloss:0.71865	validation-mlogloss:0.68768
[36m(train_xgb_ray_tune pid=325327)[0m [515]	train-mlogloss:0.69414	validation-mlogloss:0.66213
[36m(train_xgb_ray_tune pid=325327)[0m [516]	train-mlogloss:0.69389	validation-mlogloss:0.66182
[36m(train_xgb_ray_tune pid=325327)[0m [517]	train-mlogloss:0.69374	validation-mlogloss:0.66168
[36m(train_xgb_ray_tune pid=325327)[0m [518]	train-mlogloss:0.69355	validation-mlogloss:0.66150
[36m(train_xgb_ray_tune pid=325327)[0m [519]	train-mlogloss:0.69346	validation-mlogloss:0.66143
[36m(train_xgb_ray_tune pid=325327)[0m [520]	train-mlogloss:0.69331	validation-mlogloss:0.66129
[36m(train_xgb_ray_tune pid=325327)[0m [521]	train-mlogloss:0.69317	validation-mlogloss:0.66115
[36m(train_xgb_ray_tune pid=325327)[0m [522]	train-mlogloss:0.69309	validation-mlogloss:0.66108
[36m(train_xgb_ray_tune pid=325328)[0m [421]	train-mlogloss:0.65256	validation-mlogloss:0.63322
[36m(train_xgb_ray_tune pid=325328)[0m [422]	train-mlogloss:0.65211	validation-mlogloss:0.63279
[36m(train_xgb_ray_tune pid=325328)[0m [423]	train-mlogloss:0.65167	validation-mlogloss:0.63234
[36m(train_xgb_ray_tune pid=325328)[0m [424]	train-mlogloss:0.65124	validation-mlogloss:0.63192
[36m(train_xgb_ray_tune pid=325328)[0m [425]	train-mlogloss:0.65081	validation-mlogloss:0.63148
[36m(train_xgb_ray_tune pid=325328)[0m [426]	train-mlogloss:0.65037	validation-mlogloss:0.63101
[36m(train_xgb_ray_tune pid=325328)[0m [427]	train-mlogloss:0.64995	validation-mlogloss:0.63056
[36m(train_xgb_ray_tune pid=325328)[0m [428]	train-mlogloss:0.64951	validation-mlogloss:0.63006
[36m(train_xgb_ray_tune pid=325339)[0m [516]	train-mlogloss:0.71135	validation-mlogloss:0.68034
[36m(train_xgb_ray_tune pid=325339)[0m [517]	train-mlogloss:0.71103	validation-mlogloss:0.67998
[36m(train_xgb_ray_tune pid=325339)[0m [518]	train-mlogloss:0.71071	validation-mlogloss:0.67968
[36m(train_xgb_ray_tune pid=325339)[0m [519]	train-mlogloss:0.71043	validation-mlogloss:0.67939
[36m(train_xgb_ray_tune pid=325339)[0m [520]	train-mlogloss:0.71011	validation-mlogloss:0.67910
[36m(train_xgb_ray_tune pid=325339)[0m [521]	train-mlogloss:0.70984	validation-mlogloss:0.67881
[36m(train_xgb_ray_tune pid=325339)[0m [522]	train-mlogloss:0.70953	validation-mlogloss:0.67848
[36m(train_xgb_ray_tune pid=325339)[0m [523]	train-mlogloss:0.70924	validation-mlogloss:0.67818
[36m(train_xgb_ray_tune pid=325339)[0m [524]	train-mlogloss:0.70895	validation-mlogloss:0.67788
[36m(train_xgb_ray_tune pid=325339)[0m [525]	train-mlogloss:0.70865	validation-mlogloss:0.67756
[36m(train_xgb_ray_tune pid=325342)[0m [601]	train-mlogloss:0.70896	validation-mlogloss:0.67269
[36m(train_xgb_ray_tune pid=325342)[0m [602]	train-mlogloss:0.70868	validation-mlogloss:0.67240
[36m(train_xgb_ray_tune pid=325342)[0m [603]	train-mlogloss:0.70841	validation-mlogloss:0.67212
[36m(train_xgb_ray_tune pid=325342)[0m [604]	train-mlogloss:0.70810	validation-mlogloss:0.67180
[36m(train_xgb_ray_tune pid=325342)[0m [605]	train-mlogloss:0.70782	validation-mlogloss:0.67151
[36m(train_xgb_ray_tune pid=325342)[0m [606]	train-mlogloss:0.70757	validation-mlogloss:0.67123
[36m(train_xgb_ray_tune pid=325342)[0m [607]	train-mlogloss:0.70727	validation-mlogloss:0.67091
[36m(train_xgb_ray_tune pid=325342)[0m [608]	train-mlogloss:0.70696	validation-mlogloss:0.67055
[36m(train_xgb_ray_tune pid=325342)[0m [609]	train-mlogloss:0.70667	validation-mlogloss:0.67026
[36m(train_xgb_ray_tune pid=325342)[0m [610]	train-mlogloss:0.70639	validation-mlogloss:0.67000
[36m(train_xgb_ray_tune pid=325342)[0m [611]	train-mlogloss:0.70611	validation-mlogloss:0.66972
[36m(train_xgb_ray_tune pid=325307)[0m [565]	train-mlogloss:0.66988	validation-mlogloss:0.63553
[36m(train_xgb_ray_tune pid=325307)[0m [566]	train-mlogloss:0.66958	validation-mlogloss:0.63520
[36m(train_xgb_ray_tune pid=325307)[0m [567]	train-mlogloss:0.66929	validation-mlogloss:0.63490
[36m(train_xgb_ray_tune pid=325307)[0m [568]	train-mlogloss:0.66904	validation-mlogloss:0.63465
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[36m(train_xgb_ray_tune pid=325307)[0m [570]	train-mlogloss:0.66846	validation-mlogloss:0.63407
[36m(train_xgb_ray_tune pid=325307)[0m [571]	train-mlogloss:0.66818	validation-mlogloss:0.63380
[36m(train_xgb_ray_tune pid=325307)[0m [572]	train-mlogloss:0.66788	validation-mlogloss:0.63349
[36m(train_xgb_ray_tune pid=325307)[0m [573]	train-mlogloss:0.66759	validation-mlogloss:0.63318
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[36m(train_xgb_ray_tune pid=325307)[0m [575]	train-mlogloss:0.66703	validation-mlogloss:0.63263
[36m(train_xgb_ray_tune pid=325307)[0m [576]	train-mlogloss:0.66674	validation-mlogloss:0.63236
[36m(train_xgb_ray_tune pid=325338)[0m [560]	train-mlogloss:0.74500	validation-mlogloss:0.71488
[36m(train_xgb_ray_tune pid=325338)[0m [561]	train-mlogloss:0.74500	validation-mlogloss:0.71488
[36m(train_xgb_ray_tune pid=325338)[0m [562]	train-mlogloss:0.74500	validation-mlogloss:0.71488
[36m(train_xgb_ray_tune pid=325338)[0m [563]	train-mlogloss:0.74500	validation-mlogloss:0.71488
[36m(train_xgb_ray_tune pid=325338)[0m [564]	train-mlogloss:0.74500	validation-mlogloss:0.71488
[36m(train_xgb_ray_tune pid=325338)[0m [565]	train-mlogloss:0.74500	validation-mlogloss:0.71488
[36m(train_xgb_ray_tune pid=325338)[0m [566]	train-mlogloss:0.74500	validation-mlogloss:0.71488
[36m(train_xgb_ray_tune pid=325338)[0m [567]	train-mlogloss:0.74500	validation-mlogloss:0.71488
[36m(train_xgb_ray_tune pid=325338)[0m [568]	train-mlogloss:0.74492	validation-mlogloss:0.71480
[36m(train_xgb_ray_tune pid=325338)[0m [569]	train-mlogloss:0.74483	validation-mlogloss:0.71468
[36m(train_xgb_ray_tune pid=325338)[0m [570]	train-mlogloss:0.74483	validation-mlogloss:0.71468
[36m(train_xgb_ray_tune pid=325338)[0m [571]	train-mlogloss:0.74483	validation-mlogloss:0.71468
[36m(train_xgb_ray_tune pid=325338)[0m [572]	train-mlogloss:0.74483	validation-mlogloss:0.71468
[36m(train_xgb_ray_tune pid=325338)[0m [573]	train-mlogloss:0.74483	validation-mlogloss:0.71468
[36m(train_xgb_ray_tune pid=325338)[0m [574]	train-mlogloss:0.74483	validation-mlogloss:0.71468
[36m(train_xgb_ray_tune pid=325338)[0m [575]	train-mlogloss:0.74467	validation-mlogloss:0.71450
[36m(train_xgb_ray_tune pid=325338)[0m [576]	train-mlogloss:0.74467	validation-mlogloss:0.71450
[36m(train_xgb_ray_tune pid=325343)[0m [502]	train-mlogloss:0.50610	validation-mlogloss:0.49403
[36m(train_xgb_ray_tune pid=325343)[0m [503]	train-mlogloss:0.50601	validation-mlogloss:0.49401
[36m(train_xgb_ray_tune pid=325343)[0m [504]	train-mlogloss:0.50591	validation-mlogloss:0.49390
[36m(train_xgb_ray_tune pid=325343)[0m [505]	train-mlogloss:0.50582	validation-mlogloss:0.49379
[36m(train_xgb_ray_tune pid=325343)[0m [506]	train-mlogloss:0.50569	validation-mlogloss:0.49379
[36m(train_xgb_ray_tune pid=325343)[0m [507]	train-mlogloss:0.50560	validation-mlogloss:0.49373
[36m(train_xgb_ray_tune pid=325343)[0m [508]	train-mlogloss:0.50549	validation-mlogloss:0.49363
[36m(train_xgb_ray_tune pid=325343)[0m [509]	train-mlogloss:0.50531	validation-mlogloss:0.49341
[36m(train_xgb_ray_tune pid=325343)[0m [510]	train-mlogloss:0.50522	validation-mlogloss:0.49332
[36m(train_xgb_ray_tune pid=325343)[0m [511]	train-mlogloss:0.50514	validation-mlogloss:0.49322
[36m(train_xgb_ray_tune pid=325343)[0m [512]	train-mlogloss:0.50500	validation-mlogloss:0.49310
[36m(train_xgb_ray_tune pid=325343)[0m [513]	train-mlogloss:0.50489	validation-mlogloss:0.49306
[36m(train_xgb_ray_tune pid=325343)[0m [514]	train-mlogloss:0.50480	validation-mlogloss:0.49299
[36m(train_xgb_ray_tune pid=325294)[0m [531]	train-mlogloss:0.71827	validation-mlogloss:0.68731
[36m(train_xgb_ray_tune pid=325327)[0m [523]	train-mlogloss:0.69294	validation-mlogloss:0.66091
[36m(train_xgb_ray_tune pid=325328)[0m [429]	train-mlogloss:0.64908	validation-mlogloss:0.62962
[36m(train_xgb_ray_tune pid=325339)[0m [526]	train-mlogloss:0.70833	validation-mlogloss:0.67723
[36m(train_xgb_ray_tune pid=325342)[0m [612]	train-mlogloss:0.70580	validation-mlogloss:0.66936
[36m(train_xgb_ray_tune pid=325343)[0m [515]	train-mlogloss:0.50473	validation-mlogloss:0.49294
[36m(train_xgb_ray_tune pid=325338)[0m [577]	train-mlogloss:0.74467	validation-mlogloss:0.71450

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:45. Total running time: 20s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             17.3864 │
│ time_total_s                 17.3864 │
│ training_iteration                 1 │
│ validation_accuracy          0.75528 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:45. Total running time: 20s
[36m(train_xgb_ray_tune pid=325294)[0m [532]	train-mlogloss:0.71795	validation-mlogloss:0.68697
[36m(train_xgb_ray_tune pid=325294)[0m [533]	train-mlogloss:0.71758	validation-mlogloss:0.68659
[36m(train_xgb_ray_tune pid=325294)[0m [534]	train-mlogloss:0.71718	validation-mlogloss:0.68614
[36m(train_xgb_ray_tune pid=325294)[0m [535]	train-mlogloss:0.71683	validation-mlogloss:0.68577
[36m(train_xgb_ray_tune pid=325294)[0m [536]	train-mlogloss:0.71648	validation-mlogloss:0.68539
[36m(train_xgb_ray_tune pid=325294)[0m [537]	train-mlogloss:0.71618	validation-mlogloss:0.68505
[36m(train_xgb_ray_tune pid=325294)[0m [538]	train-mlogloss:0.71585	validation-mlogloss:0.68469
[36m(train_xgb_ray_tune pid=325294)[0m [539]	train-mlogloss:0.71553	validation-mlogloss:0.68437
[36m(train_xgb_ray_tune pid=325294)[0m [540]	train-mlogloss:0.71520	validation-mlogloss:0.68405
[36m(train_xgb_ray_tune pid=325294)[0m [541]	train-mlogloss:0.71485	validation-mlogloss:0.68366
[36m(train_xgb_ray_tune pid=325294)[0m [542]	train-mlogloss:0.71449	validation-mlogloss:0.68326
[36m(train_xgb_ray_tune pid=325327)[0m [524]	train-mlogloss:0.69273	validation-mlogloss:0.66068
[36m(train_xgb_ray_tune pid=325327)[0m [525]	train-mlogloss:0.69248	validation-mlogloss:0.66041
[36m(train_xgb_ray_tune pid=325327)[0m [526]	train-mlogloss:0.69229	validation-mlogloss:0.66020
[36m(train_xgb_ray_tune pid=325327)[0m [527]	train-mlogloss:0.69220	validation-mlogloss:0.66012
[36m(train_xgb_ray_tune pid=325327)[0m [528]	train-mlogloss:0.69201	validation-mlogloss:0.65991
[36m(train_xgb_ray_tune pid=325327)[0m [529]	train-mlogloss:0.69182	validation-mlogloss:0.65970
[36m(train_xgb_ray_tune pid=325327)[0m [530]	train-mlogloss:0.69161	validation-mlogloss:0.65948
[36m(train_xgb_ray_tune pid=325327)[0m [531]	train-mlogloss:0.69147	validation-mlogloss:0.65936
[36m(train_xgb_ray_tune pid=325328)[0m [430]	train-mlogloss:0.64867	validation-mlogloss:0.62918
[36m(train_xgb_ray_tune pid=325328)[0m [431]	train-mlogloss:0.64825	validation-mlogloss:0.62875
[36m(train_xgb_ray_tune pid=325328)[0m [432]	train-mlogloss:0.64782	validation-mlogloss:0.62835
[36m(train_xgb_ray_tune pid=325328)[0m [433]	train-mlogloss:0.64741	validation-mlogloss:0.62794
[36m(train_xgb_ray_tune pid=325328)[0m [434]	train-mlogloss:0.64702	validation-mlogloss:0.62756
[36m(train_xgb_ray_tune pid=325328)[0m [435]	train-mlogloss:0.64662	validation-mlogloss:0.62709
[36m(train_xgb_ray_tune pid=325328)[0m [436]	train-mlogloss:0.64621	validation-mlogloss:0.62663
[36m(train_xgb_ray_tune pid=325328)[0m [437]	train-mlogloss:0.64588	validation-mlogloss:0.62630
[36m(train_xgb_ray_tune pid=325328)[0m [438]	train-mlogloss:0.64551	validation-mlogloss:0.62595
[36m(train_xgb_ray_tune pid=325339)[0m [527]	train-mlogloss:0.70810	validation-mlogloss:0.67702
[36m(train_xgb_ray_tune pid=325339)[0m [528]	train-mlogloss:0.70779	validation-mlogloss:0.67669
[36m(train_xgb_ray_tune pid=325339)[0m [529]	train-mlogloss:0.70747	validation-mlogloss:0.67632
[36m(train_xgb_ray_tune pid=325339)[0m [530]	train-mlogloss:0.70715	validation-mlogloss:0.67598
[36m(train_xgb_ray_tune pid=325339)[0m [531]	train-mlogloss:0.70686	validation-mlogloss:0.67568
[36m(train_xgb_ray_tune pid=325339)[0m [532]	train-mlogloss:0.70659	validation-mlogloss:0.67539
[36m(train_xgb_ray_tune pid=325339)[0m [533]	train-mlogloss:0.70633	validation-mlogloss:0.67512
[36m(train_xgb_ray_tune pid=325339)[0m [534]	train-mlogloss:0.70602	validation-mlogloss:0.67475
[36m(train_xgb_ray_tune pid=325339)[0m [535]	train-mlogloss:0.70574	validation-mlogloss:0.67447
[36m(train_xgb_ray_tune pid=325339)[0m [536]	train-mlogloss:0.70542	validation-mlogloss:0.67415
[36m(train_xgb_ray_tune pid=325307)[0m [577]	train-mlogloss:0.66645	validation-mlogloss:0.63210
[36m(train_xgb_ray_tune pid=325307)[0m [578]	train-mlogloss:0.66617	validation-mlogloss:0.63183
[36m(train_xgb_ray_tune pid=325307)[0m [579]	train-mlogloss:0.66588	validation-mlogloss:0.63154
[36m(train_xgb_ray_tune pid=325307)[0m [580]	train-mlogloss:0.66562	validation-mlogloss:0.63126
[36m(train_xgb_ray_tune pid=325307)[0m [581]	train-mlogloss:0.66532	validation-mlogloss:0.63091
[36m(train_xgb_ray_tune pid=325307)[0m [582]	train-mlogloss:0.66507	validation-mlogloss:0.63067
[36m(train_xgb_ray_tune pid=325307)[0m [583]	train-mlogloss:0.66484	validation-mlogloss:0.63046
[36m(train_xgb_ray_tune pid=325307)[0m [584]	train-mlogloss:0.66459	validation-mlogloss:0.63023
[36m(train_xgb_ray_tune pid=325307)[0m [585]	train-mlogloss:0.66431	validation-mlogloss:0.62992
[36m(train_xgb_ray_tune pid=325307)[0m [586]	train-mlogloss:0.66404	validation-mlogloss:0.62960
[36m(train_xgb_ray_tune pid=325307)[0m [587]	train-mlogloss:0.66376	validation-mlogloss:0.62933
[36m(train_xgb_ray_tune pid=325338)[0m [578]	train-mlogloss:0.74467	validation-mlogloss:0.71450
[36m(train_xgb_ray_tune pid=325338)[0m [579]	train-mlogloss:0.74467	validation-mlogloss:0.71450
[36m(train_xgb_ray_tune pid=325343)[0m [516]	train-mlogloss:0.50466	validation-mlogloss:0.49290
[36m(train_xgb_ray_tune pid=325343)[0m [517]	train-mlogloss:0.50455	validation-mlogloss:0.49272
[36m(train_xgb_ray_tune pid=325343)[0m [518]	train-mlogloss:0.50446	validation-mlogloss:0.49265
[36m(train_xgb_ray_tune pid=325343)[0m [519]	train-mlogloss:0.50430	validation-mlogloss:0.49248
[36m(train_xgb_ray_tune pid=325343)[0m [520]	train-mlogloss:0.50424	validation-mlogloss:0.49242
[36m(train_xgb_ray_tune pid=325343)[0m [521]	train-mlogloss:0.50416	validation-mlogloss:0.49229
[36m(train_xgb_ray_tune pid=325339)[0m [537]	train-mlogloss:0.70513	validation-mlogloss:0.67382

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:46. Total running time: 20s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             17.5748 │
│ time_total_s                 17.5748 │
│ training_iteration                 1 │
│ validation_accuracy          0.74925 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:46. Total running time: 20s

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:46. Total running time: 20s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             17.2057 │
│ time_total_s                 17.2057 │
│ training_iteration                 1 │
│ validation_accuracy           0.7583 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:46. Total running time: 20s

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:46. Total running time: 20s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             17.2117 │
│ time_total_s                 17.2117 │
│ training_iteration                 1 │
│ validation_accuracy          0.79676 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:46. Total running time: 20s
[36m(train_xgb_ray_tune pid=325294)[0m [543]	train-mlogloss:0.71412	validation-mlogloss:0.68288
[36m(train_xgb_ray_tune pid=325294)[0m [544]	train-mlogloss:0.71377	validation-mlogloss:0.68249
[36m(train_xgb_ray_tune pid=325294)[0m [545]	train-mlogloss:0.71343	validation-mlogloss:0.68211
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[36m(train_xgb_ray_tune pid=325294)[0m [547]	train-mlogloss:0.71282	validation-mlogloss:0.68147
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[36m(train_xgb_ray_tune pid=325294)[0m [550]	train-mlogloss:0.71195	validation-mlogloss:0.68051
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[36m(train_xgb_ray_tune pid=325328)[0m [439]	train-mlogloss:0.64510	validation-mlogloss:0.62554
[36m(train_xgb_ray_tune pid=325328)[0m [440]	train-mlogloss:0.64468	validation-mlogloss:0.62512
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[36m(train_xgb_ray_tune pid=325328)[0m [445]	train-mlogloss:0.64274	validation-mlogloss:0.62304
[36m(train_xgb_ray_tune pid=325328)[0m [446]	train-mlogloss:0.64234	validation-mlogloss:0.62263
[36m(train_xgb_ray_tune pid=325328)[0m [447]	train-mlogloss:0.64194	validation-mlogloss:0.62222
[36m(train_xgb_ray_tune pid=325339)[0m [538]	train-mlogloss:0.70484	validation-mlogloss:0.67350
[36m(train_xgb_ray_tune pid=325339)[0m [539]	train-mlogloss:0.70457	validation-mlogloss:0.67323
[36m(train_xgb_ray_tune pid=325339)[0m [540]	train-mlogloss:0.70432	validation-mlogloss:0.67296
[36m(train_xgb_ray_tune pid=325339)[0m [541]	train-mlogloss:0.70403	validation-mlogloss:0.67265
[36m(train_xgb_ray_tune pid=325339)[0m [542]	train-mlogloss:0.70374	validation-mlogloss:0.67235
[36m(train_xgb_ray_tune pid=325339)[0m [543]	train-mlogloss:0.70353	validation-mlogloss:0.67213
[36m(train_xgb_ray_tune pid=325339)[0m [544]	train-mlogloss:0.70323	validation-mlogloss:0.67181
[36m(train_xgb_ray_tune pid=325339)[0m [545]	train-mlogloss:0.70298	validation-mlogloss:0.67154
[36m(train_xgb_ray_tune pid=325339)[0m [546]	train-mlogloss:0.70272	validation-mlogloss:0.67125
[36m(train_xgb_ray_tune pid=325339)[0m [547]	train-mlogloss:0.70243	validation-mlogloss:0.67098

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:46. Total running time: 20s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             17.3936 │
│ time_total_s                 17.3936 │
│ training_iteration                 1 │
│ validation_accuracy          0.75716 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:46. Total running time: 20s
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[36m(train_xgb_ray_tune pid=325328)[0m [470]	train-mlogloss:0.63342	validation-mlogloss:0.61343
[36m(train_xgb_ray_tune pid=325328)[0m [471]	train-mlogloss:0.63307	validation-mlogloss:0.61310
[36m(train_xgb_ray_tune pid=325328)[0m [472]	train-mlogloss:0.63271	validation-mlogloss:0.61276
[36m(train_xgb_ray_tune pid=325328)[0m [473]	train-mlogloss:0.63238	validation-mlogloss:0.61244
[36m(train_xgb_ray_tune pid=325328)[0m [474]	train-mlogloss:0.63202	validation-mlogloss:0.61206
[36m(train_xgb_ray_tune pid=325328)[0m [475]	train-mlogloss:0.63168	validation-mlogloss:0.61166
[36m(train_xgb_ray_tune pid=325328)[0m [476]	train-mlogloss:0.63132	validation-mlogloss:0.61132
[36m(train_xgb_ray_tune pid=325328)[0m [477]	train-mlogloss:0.63096	validation-mlogloss:0.61096
[36m(train_xgb_ray_tune pid=325339)[0m [573]	train-mlogloss:0.69544	validation-mlogloss:0.66336
[36m(train_xgb_ray_tune pid=325339)[0m [574]	train-mlogloss:0.69520	validation-mlogloss:0.66311
[36m(train_xgb_ray_tune pid=325339)[0m [575]	train-mlogloss:0.69493	validation-mlogloss:0.66283
[36m(train_xgb_ray_tune pid=325339)[0m [576]	train-mlogloss:0.69466	validation-mlogloss:0.66253
[36m(train_xgb_ray_tune pid=325339)[0m [577]	train-mlogloss:0.69441	validation-mlogloss:0.66225
[36m(train_xgb_ray_tune pid=325339)[0m [578]	train-mlogloss:0.69415	validation-mlogloss:0.66196
[36m(train_xgb_ray_tune pid=325339)[0m [579]	train-mlogloss:0.69386	validation-mlogloss:0.66166
[36m(train_xgb_ray_tune pid=325339)[0m [580]	train-mlogloss:0.69361	validation-mlogloss:0.66139
[36m(train_xgb_ray_tune pid=325339)[0m [581]	train-mlogloss:0.69338	validation-mlogloss:0.66116
[36m(train_xgb_ray_tune pid=325339)[0m [582]	train-mlogloss:0.69317	validation-mlogloss:0.66094
[36m(train_xgb_ray_tune pid=325339)[0m [583]	train-mlogloss:0.69293	validation-mlogloss:0.66071
[36m(train_xgb_ray_tune pid=325339)[0m [584]	train-mlogloss:0.69267	validation-mlogloss:0.66045
[36m(train_xgb_ray_tune pid=325294)[0m [593]	train-mlogloss:0.69899	validation-mlogloss:0.66661
[36m(train_xgb_ray_tune pid=325327)[0m [591]	train-mlogloss:0.68413	validation-mlogloss:0.65178
[36m(train_xgb_ray_tune pid=325294)[0m [594]	train-mlogloss:0.69868	validation-mlogloss:0.66632
[36m(train_xgb_ray_tune pid=325294)[0m [595]	train-mlogloss:0.69845	validation-mlogloss:0.66607
[36m(train_xgb_ray_tune pid=325294)[0m [596]	train-mlogloss:0.69817	validation-mlogloss:0.66572
[36m(train_xgb_ray_tune pid=325294)[0m [597]	train-mlogloss:0.69792	validation-mlogloss:0.66547
[36m(train_xgb_ray_tune pid=325294)[0m [598]	train-mlogloss:0.69761	validation-mlogloss:0.66514
[36m(train_xgb_ray_tune pid=325294)[0m [599]	train-mlogloss:0.69730	validation-mlogloss:0.66478
[36m(train_xgb_ray_tune pid=325294)[0m [600]	train-mlogloss:0.69704	validation-mlogloss:0.66445
[36m(train_xgb_ray_tune pid=325294)[0m [601]	train-mlogloss:0.69675	validation-mlogloss:0.66414
[36m(train_xgb_ray_tune pid=325294)[0m [602]	train-mlogloss:0.69647	validation-mlogloss:0.66384
[36m(train_xgb_ray_tune pid=325294)[0m [603]	train-mlogloss:0.69621	validation-mlogloss:0.66357
[36m(train_xgb_ray_tune pid=325294)[0m [604]	train-mlogloss:0.69595	validation-mlogloss:0.66326
[36m(train_xgb_ray_tune pid=325294)[0m [605]	train-mlogloss:0.69567	validation-mlogloss:0.66296
[36m(train_xgb_ray_tune pid=325327)[0m [592]	train-mlogloss:0.68406	validation-mlogloss:0.65168
[36m(train_xgb_ray_tune pid=325327)[0m [593]	train-mlogloss:0.68399	validation-mlogloss:0.65161
[36m(train_xgb_ray_tune pid=325327)[0m [594]	train-mlogloss:0.68392	validation-mlogloss:0.65154
[36m(train_xgb_ray_tune pid=325327)[0m [595]	train-mlogloss:0.68385	validation-mlogloss:0.65144
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[36m(train_xgb_ray_tune pid=325327)[0m [597]	train-mlogloss:0.68366	validation-mlogloss:0.65124
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[36m(train_xgb_ray_tune pid=325327)[0m [599]	train-mlogloss:0.68352	validation-mlogloss:0.65109
[36m(train_xgb_ray_tune pid=325327)[0m [600]	train-mlogloss:0.68346	validation-mlogloss:0.65103
[36m(train_xgb_ray_tune pid=325327)[0m [601]	train-mlogloss:0.68327	validation-mlogloss:0.65084
[36m(train_xgb_ray_tune pid=325327)[0m [602]	train-mlogloss:0.68320	validation-mlogloss:0.65077
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[36m(train_xgb_ray_tune pid=325327)[0m [605]	train-mlogloss:0.68294	validation-mlogloss:0.65046
[36m(train_xgb_ray_tune pid=325328)[0m [478]	train-mlogloss:0.63068	validation-mlogloss:0.61068
[36m(train_xgb_ray_tune pid=325328)[0m [479]	train-mlogloss:0.63034	validation-mlogloss:0.61035
[36m(train_xgb_ray_tune pid=325328)[0m [480]	train-mlogloss:0.63002	validation-mlogloss:0.61001
[36m(train_xgb_ray_tune pid=325328)[0m [481]	train-mlogloss:0.62970	validation-mlogloss:0.60965
[36m(train_xgb_ray_tune pid=325328)[0m [482]	train-mlogloss:0.62938	validation-mlogloss:0.60933
[36m(train_xgb_ray_tune pid=325328)[0m [483]	train-mlogloss:0.62903	validation-mlogloss:0.60899
[36m(train_xgb_ray_tune pid=325328)[0m [484]	train-mlogloss:0.62869	validation-mlogloss:0.60863
[36m(train_xgb_ray_tune pid=325328)[0m [485]	train-mlogloss:0.62835	validation-mlogloss:0.60827
[36m(train_xgb_ray_tune pid=325328)[0m [486]	train-mlogloss:0.62800	validation-mlogloss:0.60794
[36m(train_xgb_ray_tune pid=325328)[0m [487]	train-mlogloss:0.62768	validation-mlogloss:0.60764
[36m(train_xgb_ray_tune pid=325339)[0m [585]	train-mlogloss:0.69248	validation-mlogloss:0.66026
[36m(train_xgb_ray_tune pid=325339)[0m [586]	train-mlogloss:0.69222	validation-mlogloss:0.65998
[36m(train_xgb_ray_tune pid=325339)[0m [587]	train-mlogloss:0.69198	validation-mlogloss:0.65966
[36m(train_xgb_ray_tune pid=325339)[0m [588]	train-mlogloss:0.69173	validation-mlogloss:0.65941
[36m(train_xgb_ray_tune pid=325339)[0m [589]	train-mlogloss:0.69147	validation-mlogloss:0.65914
[36m(train_xgb_ray_tune pid=325339)[0m [590]	train-mlogloss:0.69128	validation-mlogloss:0.65896
[36m(train_xgb_ray_tune pid=325339)[0m [591]	train-mlogloss:0.69111	validation-mlogloss:0.65874
[36m(train_xgb_ray_tune pid=325339)[0m [592]	train-mlogloss:0.69088	validation-mlogloss:0.65850
[36m(train_xgb_ray_tune pid=325339)[0m [593]	train-mlogloss:0.69066	validation-mlogloss:0.65827
[36m(train_xgb_ray_tune pid=325339)[0m [594]	train-mlogloss:0.69043	validation-mlogloss:0.65801
[36m(train_xgb_ray_tune pid=325339)[0m [595]	train-mlogloss:0.69022	validation-mlogloss:0.65779
[36m(train_xgb_ray_tune pid=325339)[0m [596]	train-mlogloss:0.68997	validation-mlogloss:0.65752
[36m(train_xgb_ray_tune pid=325339)[0m [597]	train-mlogloss:0.68972	validation-mlogloss:0.65725
[36m(train_xgb_ray_tune pid=325294)[0m [606]	train-mlogloss:0.69542	validation-mlogloss:0.66267
[36m(train_xgb_ray_tune pid=325327)[0m [606]	train-mlogloss:0.68288	validation-mlogloss:0.65041
[36m(train_xgb_ray_tune pid=325339)[0m [598]	train-mlogloss:0.68950	validation-mlogloss:0.65702
[36m(train_xgb_ray_tune pid=325328)[0m [488]	train-mlogloss:0.62739	validation-mlogloss:0.60735
[36m(train_xgb_ray_tune pid=325294)[0m [607]	train-mlogloss:0.69522	validation-mlogloss:0.66247
[36m(train_xgb_ray_tune pid=325327)[0m [607]	train-mlogloss:0.68281	validation-mlogloss:0.65035
[36m(train_xgb_ray_tune pid=325294)[0m [608]	train-mlogloss:0.69492	validation-mlogloss:0.66217
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[36m(train_xgb_ray_tune pid=325294)[0m [613]	train-mlogloss:0.69361	validation-mlogloss:0.66078
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[36m(train_xgb_ray_tune pid=325327)[0m [608]	train-mlogloss:0.68263	validation-mlogloss:0.65013
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[36m(train_xgb_ray_tune pid=325327)[0m [610]	train-mlogloss:0.68250	validation-mlogloss:0.64995
[36m(train_xgb_ray_tune pid=325327)[0m [611]	train-mlogloss:0.68243	validation-mlogloss:0.64988
[36m(train_xgb_ray_tune pid=325327)[0m [612]	train-mlogloss:0.68236	validation-mlogloss:0.64979
[36m(train_xgb_ray_tune pid=325327)[0m [613]	train-mlogloss:0.68229	validation-mlogloss:0.64973
[36m(train_xgb_ray_tune pid=325327)[0m [614]	train-mlogloss:0.68217	validation-mlogloss:0.64958
[36m(train_xgb_ray_tune pid=325328)[0m [489]	train-mlogloss:0.62709	validation-mlogloss:0.60704
[36m(train_xgb_ray_tune pid=325328)[0m [490]	train-mlogloss:0.62674	validation-mlogloss:0.60664
[36m(train_xgb_ray_tune pid=325328)[0m [491]	train-mlogloss:0.62641	validation-mlogloss:0.60632
[36m(train_xgb_ray_tune pid=325328)[0m [492]	train-mlogloss:0.62610	validation-mlogloss:0.60599
[36m(train_xgb_ray_tune pid=325328)[0m [493]	train-mlogloss:0.62580	validation-mlogloss:0.60569
[36m(train_xgb_ray_tune pid=325328)[0m [494]	train-mlogloss:0.62552	validation-mlogloss:0.60542
[36m(train_xgb_ray_tune pid=325328)[0m [495]	train-mlogloss:0.62522	validation-mlogloss:0.60514
[36m(train_xgb_ray_tune pid=325328)[0m [496]	train-mlogloss:0.62489	validation-mlogloss:0.60481
[36m(train_xgb_ray_tune pid=325328)[0m [497]	train-mlogloss:0.62460	validation-mlogloss:0.60449
[36m(train_xgb_ray_tune pid=325328)[0m [498]	train-mlogloss:0.62429	validation-mlogloss:0.60418
[36m(train_xgb_ray_tune pid=325339)[0m [599]	train-mlogloss:0.68931	validation-mlogloss:0.65683
[36m(train_xgb_ray_tune pid=325339)[0m [600]	train-mlogloss:0.68909	validation-mlogloss:0.65660
[36m(train_xgb_ray_tune pid=325339)[0m [601]	train-mlogloss:0.68882	validation-mlogloss:0.65634
[36m(train_xgb_ray_tune pid=325339)[0m [602]	train-mlogloss:0.68857	validation-mlogloss:0.65609
[36m(train_xgb_ray_tune pid=325339)[0m [603]	train-mlogloss:0.68836	validation-mlogloss:0.65585
[36m(train_xgb_ray_tune pid=325339)[0m [604]	train-mlogloss:0.68818	validation-mlogloss:0.65566
[36m(train_xgb_ray_tune pid=325339)[0m [605]	train-mlogloss:0.68794	validation-mlogloss:0.65542
[36m(train_xgb_ray_tune pid=325339)[0m [606]	train-mlogloss:0.68774	validation-mlogloss:0.65521
[36m(train_xgb_ray_tune pid=325339)[0m [607]	train-mlogloss:0.68751	validation-mlogloss:0.65495
[36m(train_xgb_ray_tune pid=325339)[0m [608]	train-mlogloss:0.68725	validation-mlogloss:0.65466
[36m(train_xgb_ray_tune pid=325339)[0m [609]	train-mlogloss:0.68703	validation-mlogloss:0.65445
[36m(train_xgb_ray_tune pid=325339)[0m [610]	train-mlogloss:0.68682	validation-mlogloss:0.65423

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:46. Total running time: 21s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             18.1375 │
│ time_total_s                 18.1375 │
│ training_iteration                 1 │
│ validation_accuracy          0.75452 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:46. Total running time: 21s
[36m(train_xgb_ray_tune pid=325294)[0m [620]	train-mlogloss:0.69184	validation-mlogloss:0.65892
[36m(train_xgb_ray_tune pid=325294)[0m [621]	train-mlogloss:0.69155	validation-mlogloss:0.65861
[36m(train_xgb_ray_tune pid=325294)[0m [622]	train-mlogloss:0.69128	validation-mlogloss:0.65831
[36m(train_xgb_ray_tune pid=325294)[0m [623]	train-mlogloss:0.69104	validation-mlogloss:0.65802
[36m(train_xgb_ray_tune pid=325294)[0m [624]	train-mlogloss:0.69076	validation-mlogloss:0.65772
[36m(train_xgb_ray_tune pid=325294)[0m [625]	train-mlogloss:0.69058	validation-mlogloss:0.65756
[36m(train_xgb_ray_tune pid=325294)[0m [626]	train-mlogloss:0.69031	validation-mlogloss:0.65724
[36m(train_xgb_ray_tune pid=325294)[0m [627]	train-mlogloss:0.69005	validation-mlogloss:0.65697
[36m(train_xgb_ray_tune pid=325328)[0m [499]	train-mlogloss:0.62403	validation-mlogloss:0.60387
[36m(train_xgb_ray_tune pid=325328)[0m [500]	train-mlogloss:0.62372	validation-mlogloss:0.60359
[36m(train_xgb_ray_tune pid=325328)[0m [501]	train-mlogloss:0.62340	validation-mlogloss:0.60324
[36m(train_xgb_ray_tune pid=325328)[0m [502]	train-mlogloss:0.62309	validation-mlogloss:0.60294
[36m(train_xgb_ray_tune pid=325328)[0m [503]	train-mlogloss:0.62276	validation-mlogloss:0.60260
[36m(train_xgb_ray_tune pid=325328)[0m [504]	train-mlogloss:0.62242	validation-mlogloss:0.60226
[36m(train_xgb_ray_tune pid=325328)[0m [505]	train-mlogloss:0.62212	validation-mlogloss:0.60195
[36m(train_xgb_ray_tune pid=325328)[0m [506]	train-mlogloss:0.62181	validation-mlogloss:0.60162
[36m(train_xgb_ray_tune pid=325328)[0m [507]	train-mlogloss:0.62151	validation-mlogloss:0.60133
[36m(train_xgb_ray_tune pid=325339)[0m [611]	train-mlogloss:0.68658	validation-mlogloss:0.65397
[36m(train_xgb_ray_tune pid=325339)[0m [612]	train-mlogloss:0.68634	validation-mlogloss:0.65369
[36m(train_xgb_ray_tune pid=325339)[0m [613]	train-mlogloss:0.68609	validation-mlogloss:0.65341
[36m(train_xgb_ray_tune pid=325339)[0m [614]	train-mlogloss:0.68591	validation-mlogloss:0.65323
[36m(train_xgb_ray_tune pid=325339)[0m [615]	train-mlogloss:0.68567	validation-mlogloss:0.65300
[36m(train_xgb_ray_tune pid=325339)[0m [616]	train-mlogloss:0.68546	validation-mlogloss:0.65274
[36m(train_xgb_ray_tune pid=325339)[0m [617]	train-mlogloss:0.68523	validation-mlogloss:0.65250
[36m(train_xgb_ray_tune pid=325339)[0m [618]	train-mlogloss:0.68498	validation-mlogloss:0.65221
[36m(train_xgb_ray_tune pid=325339)[0m [619]	train-mlogloss:0.68483	validation-mlogloss:0.65205
[36m(train_xgb_ray_tune pid=325339)[0m [620]	train-mlogloss:0.68462	validation-mlogloss:0.65185
[36m(train_xgb_ray_tune pid=325339)[0m [621]	train-mlogloss:0.68440	validation-mlogloss:0.65161
[36m(train_xgb_ray_tune pid=325339)[0m [622]	train-mlogloss:0.68418	validation-mlogloss:0.65139
[36m(train_xgb_ray_tune pid=325328)[0m [508]	train-mlogloss:0.62125	validation-mlogloss:0.60103

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:46. Total running time: 21s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             18.5932 │
│ time_total_s                 18.5932 │
│ training_iteration                 1 │
│ validation_accuracy          0.74811 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:46. Total running time: 21s
[36m(train_xgb_ray_tune pid=325328)[0m [509]	train-mlogloss:0.62094	validation-mlogloss:0.60070
[36m(train_xgb_ray_tune pid=325328)[0m [510]	train-mlogloss:0.62063	validation-mlogloss:0.60040
[36m(train_xgb_ray_tune pid=325328)[0m [511]	train-mlogloss:0.62033	validation-mlogloss:0.60009
[36m(train_xgb_ray_tune pid=325328)[0m [512]	train-mlogloss:0.62004	validation-mlogloss:0.59983
[36m(train_xgb_ray_tune pid=325328)[0m [513]	train-mlogloss:0.61974	validation-mlogloss:0.59955
[36m(train_xgb_ray_tune pid=325328)[0m [514]	train-mlogloss:0.61947	validation-mlogloss:0.59926
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[36m(train_xgb_ray_tune pid=325328)[0m [518]	train-mlogloss:0.61836	validation-mlogloss:0.59815
[36m(train_xgb_ray_tune pid=325339)[0m [623]	train-mlogloss:0.68393	validation-mlogloss:0.65114
[36m(train_xgb_ray_tune pid=325339)[0m [624]	train-mlogloss:0.68373	validation-mlogloss:0.65092
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[36m(train_xgb_ray_tune pid=325339)[0m [626]	train-mlogloss:0.68331	validation-mlogloss:0.65048
[36m(train_xgb_ray_tune pid=325339)[0m [627]	train-mlogloss:0.68308	validation-mlogloss:0.65024
[36m(train_xgb_ray_tune pid=325339)[0m [628]	train-mlogloss:0.68291	validation-mlogloss:0.65008
[36m(train_xgb_ray_tune pid=325339)[0m [629]	train-mlogloss:0.68274	validation-mlogloss:0.64992
[36m(train_xgb_ray_tune pid=325339)[0m [630]	train-mlogloss:0.68255	validation-mlogloss:0.64973
[36m(train_xgb_ray_tune pid=325339)[0m [631]	train-mlogloss:0.68237	validation-mlogloss:0.64956
[36m(train_xgb_ray_tune pid=325339)[0m [632]	train-mlogloss:0.68211	validation-mlogloss:0.64927
[36m(train_xgb_ray_tune pid=325339)[0m [633]	train-mlogloss:0.68194	validation-mlogloss:0.64910
[36m(train_xgb_ray_tune pid=325339)[0m [634]	train-mlogloss:0.68178	validation-mlogloss:0.64894
[36m(train_xgb_ray_tune pid=325339)[0m [635]	train-mlogloss:0.68158	validation-mlogloss:0.64873
[36m(train_xgb_ray_tune pid=325328)[0m [519]	train-mlogloss:0.61807	validation-mlogloss:0.59785
[36m(train_xgb_ray_tune pid=325328)[0m [520]	train-mlogloss:0.61783	validation-mlogloss:0.59762
[36m(train_xgb_ray_tune pid=325328)[0m [521]	train-mlogloss:0.61754	validation-mlogloss:0.59729
[36m(train_xgb_ray_tune pid=325328)[0m [522]	train-mlogloss:0.61729	validation-mlogloss:0.59703
[36m(train_xgb_ray_tune pid=325328)[0m [523]	train-mlogloss:0.61700	validation-mlogloss:0.59672
[36m(train_xgb_ray_tune pid=325328)[0m [524]	train-mlogloss:0.61673	validation-mlogloss:0.59644
[36m(train_xgb_ray_tune pid=325328)[0m [525]	train-mlogloss:0.61647	validation-mlogloss:0.59618
[36m(train_xgb_ray_tune pid=325328)[0m [526]	train-mlogloss:0.61621	validation-mlogloss:0.59594
[36m(train_xgb_ray_tune pid=325328)[0m [527]	train-mlogloss:0.61598	validation-mlogloss:0.59567
[36m(train_xgb_ray_tune pid=325328)[0m [528]	train-mlogloss:0.61571	validation-mlogloss:0.59541
[36m(train_xgb_ray_tune pid=325339)[0m [636]	train-mlogloss:0.68138	validation-mlogloss:0.64853
[36m(train_xgb_ray_tune pid=325339)[0m [637]	train-mlogloss:0.68119	validation-mlogloss:0.64833
[36m(train_xgb_ray_tune pid=325339)[0m [638]	train-mlogloss:0.68096	validation-mlogloss:0.64808
[36m(train_xgb_ray_tune pid=325339)[0m [639]	train-mlogloss:0.68080	validation-mlogloss:0.64792
[36m(train_xgb_ray_tune pid=325339)[0m [640]	train-mlogloss:0.68058	validation-mlogloss:0.64770
[36m(train_xgb_ray_tune pid=325339)[0m [641]	train-mlogloss:0.68042	validation-mlogloss:0.64752
[36m(train_xgb_ray_tune pid=325339)[0m [642]	train-mlogloss:0.68020	validation-mlogloss:0.64730
[36m(train_xgb_ray_tune pid=325339)[0m [643]	train-mlogloss:0.68000	validation-mlogloss:0.64705
[36m(train_xgb_ray_tune pid=325339)[0m [644]	train-mlogloss:0.67978	validation-mlogloss:0.64684
[36m(train_xgb_ray_tune pid=325339)[0m [645]	train-mlogloss:0.67961	validation-mlogloss:0.64668
[36m(train_xgb_ray_tune pid=325339)[0m [646]	train-mlogloss:0.67942	validation-mlogloss:0.64649
[36m(train_xgb_ray_tune pid=325339)[0m [647]	train-mlogloss:0.67924	validation-mlogloss:0.64628
[36m(train_xgb_ray_tune pid=325339)[0m [648]	train-mlogloss:0.67908	validation-mlogloss:0.64611
[36m(train_xgb_ray_tune pid=325328)[0m [529]	train-mlogloss:0.61546	validation-mlogloss:0.59514
[36m(train_xgb_ray_tune pid=325339)[0m [649]	train-mlogloss:0.67892	validation-mlogloss:0.64596
[36m(train_xgb_ray_tune pid=325328)[0m [530]	train-mlogloss:0.61520	validation-mlogloss:0.59485
[36m(train_xgb_ray_tune pid=325328)[0m [531]	train-mlogloss:0.61493	validation-mlogloss:0.59458
[36m(train_xgb_ray_tune pid=325328)[0m [532]	train-mlogloss:0.61466	validation-mlogloss:0.59429
[36m(train_xgb_ray_tune pid=325328)[0m [533]	train-mlogloss:0.61440	validation-mlogloss:0.59404
[36m(train_xgb_ray_tune pid=325328)[0m [534]	train-mlogloss:0.61416	validation-mlogloss:0.59380
[36m(train_xgb_ray_tune pid=325328)[0m [535]	train-mlogloss:0.61389	validation-mlogloss:0.59353
[36m(train_xgb_ray_tune pid=325328)[0m [536]	train-mlogloss:0.61361	validation-mlogloss:0.59322
[36m(train_xgb_ray_tune pid=325328)[0m [537]	train-mlogloss:0.61337	validation-mlogloss:0.59296
[36m(train_xgb_ray_tune pid=325328)[0m [538]	train-mlogloss:0.61312	validation-mlogloss:0.59271
[36m(train_xgb_ray_tune pid=325328)[0m [539]	train-mlogloss:0.61285	validation-mlogloss:0.59242
[36m(train_xgb_ray_tune pid=325339)[0m [650]	train-mlogloss:0.67877	validation-mlogloss:0.64580
[36m(train_xgb_ray_tune pid=325339)[0m [651]	train-mlogloss:0.67863	validation-mlogloss:0.64564
[36m(train_xgb_ray_tune pid=325339)[0m [652]	train-mlogloss:0.67844	validation-mlogloss:0.64546
[36m(train_xgb_ray_tune pid=325339)[0m [653]	train-mlogloss:0.67830	validation-mlogloss:0.64527
[36m(train_xgb_ray_tune pid=325339)[0m [654]	train-mlogloss:0.67816	validation-mlogloss:0.64515
[36m(train_xgb_ray_tune pid=325339)[0m [655]	train-mlogloss:0.67799	validation-mlogloss:0.64497
[36m(train_xgb_ray_tune pid=325339)[0m [656]	train-mlogloss:0.67783	validation-mlogloss:0.64481
[36m(train_xgb_ray_tune pid=325339)[0m [657]	train-mlogloss:0.67765	validation-mlogloss:0.64461
[36m(train_xgb_ray_tune pid=325339)[0m [658]	train-mlogloss:0.67750	validation-mlogloss:0.64445
[36m(train_xgb_ray_tune pid=325339)[0m [659]	train-mlogloss:0.67732	validation-mlogloss:0.64427
[36m(train_xgb_ray_tune pid=325339)[0m [660]	train-mlogloss:0.67719	validation-mlogloss:0.64415
[36m(train_xgb_ray_tune pid=325339)[0m [661]	train-mlogloss:0.67701	validation-mlogloss:0.64399
[36m(train_xgb_ray_tune pid=325339)[0m [662]	train-mlogloss:0.67685	validation-mlogloss:0.64381
[36m(train_xgb_ray_tune pid=325328)[0m [540]	train-mlogloss:0.61262	validation-mlogloss:0.59217
[36m(train_xgb_ray_tune pid=325339)[0m [663]	train-mlogloss:0.67672	validation-mlogloss:0.64370
[36m(train_xgb_ray_tune pid=325328)[0m [541]	train-mlogloss:0.61239	validation-mlogloss:0.59196
[36m(train_xgb_ray_tune pid=325328)[0m [542]	train-mlogloss:0.61214	validation-mlogloss:0.59172
[36m(train_xgb_ray_tune pid=325328)[0m [543]	train-mlogloss:0.61188	validation-mlogloss:0.59148
2025-11-03 17:18:47,614	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_PI/case_PI_XGB_acc_gyr_superclasses_CPA_METs/XGBoost_hyperparameters_tuning' in 0.0098s.
[36m(train_xgb_ray_tune pid=325328)[0m [544]	train-mlogloss:0.61164	validation-mlogloss:0.59121
[36m(train_xgb_ray_tune pid=325328)[0m [545]	train-mlogloss:0.61139	validation-mlogloss:0.59094
[36m(train_xgb_ray_tune pid=325328)[0m [546]	train-mlogloss:0.61116	validation-mlogloss:0.59070
[36m(train_xgb_ray_tune pid=325328)[0m [547]	train-mlogloss:0.61090	validation-mlogloss:0.59043
[36m(train_xgb_ray_tune pid=325328)[0m [548]	train-mlogloss:0.61066	validation-mlogloss:0.59016
[36m(train_xgb_ray_tune pid=325328)[0m [549]	train-mlogloss:0.61040	validation-mlogloss:0.58990
[36m(train_xgb_ray_tune pid=325328)[0m [550]	train-mlogloss:0.61014	validation-mlogloss:0.58965
[36m(train_xgb_ray_tune pid=325339)[0m [664]	train-mlogloss:0.67659	validation-mlogloss:0.64359
[36m(train_xgb_ray_tune pid=325339)[0m [665]	train-mlogloss:0.67642	validation-mlogloss:0.64344
[36m(train_xgb_ray_tune pid=325339)[0m [666]	train-mlogloss:0.67628	validation-mlogloss:0.64328
[36m(train_xgb_ray_tune pid=325339)[0m [667]	train-mlogloss:0.67606	validation-mlogloss:0.64304
[36m(train_xgb_ray_tune pid=325339)[0m [668]	train-mlogloss:0.67593	validation-mlogloss:0.64291
[36m(train_xgb_ray_tune pid=325339)[0m [669]	train-mlogloss:0.67574	validation-mlogloss:0.64270
[36m(train_xgb_ray_tune pid=325339)[0m [670]	train-mlogloss:0.67564	validation-mlogloss:0.64262
[36m(train_xgb_ray_tune pid=325339)[0m [671]	train-mlogloss:0.67551	validation-mlogloss:0.64248
[36m(train_xgb_ray_tune pid=325339)[0m [672]	train-mlogloss:0.67536	validation-mlogloss:0.64232
[36m(train_xgb_ray_tune pid=325339)[0m [673]	train-mlogloss:0.67518	validation-mlogloss:0.64212
[36m(train_xgb_ray_tune pid=325339)[0m [674]	train-mlogloss:0.67501	validation-mlogloss:0.64192
[36m(train_xgb_ray_tune pid=325339)[0m [675]	train-mlogloss:0.67485	validation-mlogloss:0.64177
[36m(train_xgb_ray_tune pid=325339)[0m [676]	train-mlogloss:0.67469	validation-mlogloss:0.64162
[36m(train_xgb_ray_tune pid=325328)[0m [551]	train-mlogloss:0.60990	validation-mlogloss:0.58942
[36m(train_xgb_ray_tune pid=325328)[0m [552]	train-mlogloss:0.60968	validation-mlogloss:0.58919
[36m(train_xgb_ray_tune pid=325328)[0m [553]	train-mlogloss:0.60947	validation-mlogloss:0.58894
[36m(train_xgb_ray_tune pid=325328)[0m [554]	train-mlogloss:0.60924	validation-mlogloss:0.58871
[36m(train_xgb_ray_tune pid=325339)[0m [677]	train-mlogloss:0.67456	validation-mlogloss:0.64149
[36m(train_xgb_ray_tune pid=325339)[0m [678]	train-mlogloss:0.67441	validation-mlogloss:0.64132
[36m(train_xgb_ray_tune pid=325339)[0m [679]	train-mlogloss:0.67425	validation-mlogloss:0.64113
[36m(train_xgb_ray_tune pid=325339)[0m [680]	train-mlogloss:0.67407	validation-mlogloss:0.64094
[36m(train_xgb_ray_tune pid=325339)[0m [681]	train-mlogloss:0.67394	validation-mlogloss:0.64084
[36m(train_xgb_ray_tune pid=325339)[0m [682]	train-mlogloss:0.67381	validation-mlogloss:0.64073
[36m(train_xgb_ray_tune pid=325339)[0m [683]	train-mlogloss:0.67366	validation-mlogloss:0.64060
[36m(train_xgb_ray_tune pid=325339)[0m [684]	train-mlogloss:0.67353	validation-mlogloss:0.64048
[36m(train_xgb_ray_tune pid=325339)[0m [685]	train-mlogloss:0.67340	validation-mlogloss:0.64038
[36m(train_xgb_ray_tune pid=325339)[0m [686]	train-mlogloss:0.67331	validation-mlogloss:0.64028
[36m(train_xgb_ray_tune pid=325339)[0m [687]	train-mlogloss:0.67320	validation-mlogloss:0.64017
[36m(train_xgb_ray_tune pid=325339)[0m [688]	train-mlogloss:0.67311	validation-mlogloss:0.64006
[36m(train_xgb_ray_tune pid=325339)[0m [689]	train-mlogloss:0.67297	validation-mlogloss:0.63987
[36m(train_xgb_ray_tune pid=325339)[0m [690]	train-mlogloss:0.67281	validation-mlogloss:0.63973
[36m(train_xgb_ray_tune pid=325339)[0m [691]	train-mlogloss:0.67269	validation-mlogloss:0.63958

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:47. Total running time: 22s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             18.5869 │
│ time_total_s                 18.5869 │
│ training_iteration                 1 │
│ validation_accuracy           0.7779 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:47. Total running time: 22s
[36m(train_xgb_ray_tune pid=325339)[0m [692]	train-mlogloss:0.67257	validation-mlogloss:0.63946
[36m(train_xgb_ray_tune pid=325339)[0m [693]	train-mlogloss:0.67241	validation-mlogloss:0.63932
[36m(train_xgb_ray_tune pid=325339)[0m [694]	train-mlogloss:0.67232	validation-mlogloss:0.63922
[36m(train_xgb_ray_tune pid=325339)[0m [695]	train-mlogloss:0.67218	validation-mlogloss:0.63908
[36m(train_xgb_ray_tune pid=325339)[0m [696]	train-mlogloss:0.67205	validation-mlogloss:0.63897
[36m(train_xgb_ray_tune pid=325339)[0m [697]	train-mlogloss:0.67193	validation-mlogloss:0.63887
[36m(train_xgb_ray_tune pid=325339)[0m [698]	train-mlogloss:0.67184	validation-mlogloss:0.63879
[36m(train_xgb_ray_tune pid=325339)[0m [699]	train-mlogloss:0.67164	validation-mlogloss:0.63858
[36m(train_xgb_ray_tune pid=325339)[0m [700]	train-mlogloss:0.67152	validation-mlogloss:0.63845
[36m(train_xgb_ray_tune pid=325339)[0m [701]	train-mlogloss:0.67139	validation-mlogloss:0.63834
[36m(train_xgb_ray_tune pid=325339)[0m [702]	train-mlogloss:0.67124	validation-mlogloss:0.63815
[36m(train_xgb_ray_tune pid=325339)[0m [703]	train-mlogloss:0.67111	validation-mlogloss:0.63801
[36m(train_xgb_ray_tune pid=325339)[0m [704]	train-mlogloss:0.67101	validation-mlogloss:0.63793
[36m(train_xgb_ray_tune pid=325339)[0m [705]	train-mlogloss:0.67092	validation-mlogloss:0.63785
[36m(train_xgb_ray_tune pid=325339)[0m [706]	train-mlogloss:0.67076	validation-mlogloss:0.63766

Trial trial_b9863 finished iteration 1 at 2025-11-03 17:18:47. Total running time: 22s
╭──────────────────────────────────────╮
│ Trial trial_b9863 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             18.8665 │
│ time_total_s                 18.8665 │
│ training_iteration                 1 │
│ validation_accuracy          0.75415 │
╰──────────────────────────────────────╯

Trial trial_b9863 completed after 1 iterations at 2025-11-03 17:18:47. Total running time: 22s

Trial status: 20 TERMINATED
Current time: 2025-11-03 17:18:47. Total running time: 22s
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_b9863    TERMINATED                 628             3        0.00744423      0.504952             0.576937   13.9612                   112       2.14385      540.611               6635        1            18.5932                0.748115 │
│ trial_b9863    TERMINATED                 767             2        0.0127582       0.751678             0.636061   27.2159                   120       7.86891      355.199               9744        1            17.3864                0.755279 │
│ trial_b9863    TERMINATED                 634             3        0.0185581       0.834024             0.714164   13.2016                   124     198.931        275.297               1017        1            14.5138                0.751508 │
│ trial_b9863    TERMINATED                 388             3        0.018838        0.637224             0.549674    8.88675                  197      12.7753        61.8836              2876        1            14.9073                0.786953 │
│ trial_b9863    TERMINATED                 420             2        0.0180166       0.80739              0.712444    6.64513                  185      78.1219       162.178               1023        1            13.8082                0.771116 │
│ trial_b9863    TERMINATED                 555             3        0.00825242      0.769773             0.632202    5.19447                   52      48.4836       294.162               1804        1            18.5869                0.777903 │
│ trial_b9863    TERMINATED                 588             2        0.0069269       0.502066             0.683889    6.79868                  178      21.4366       166.915               1677        1            17.3936                0.757164 │
│ trial_b9863    TERMINATED                 707             3        0.0106103       0.587228             0.70151    10.9406                   101      23.3789       986.965               1328        1            18.8665                0.754148 │
│ trial_b9863    TERMINATED                 455             3        0.0106544       0.50955              0.59724    15.3759                   127     344.898         60.0014              6583        1            14.4964                0.684012 │
│ trial_b9863    TERMINATED                 615             3        0.00819303      0.670386             0.717359   25.3107                   112      74.1024       199.986               5959        1            18.1375                0.754525 │
│ trial_b9863    TERMINATED                 613             2        0.0079888       0.719448             0.771053   16.9002                   183       2.25177      972.425               9160        1            17.5748                0.749246 │
│ trial_b9863    TERMINATED                 595             2        0.0197272       0.647494             0.830119   23.1508                    92     293.313        321.847               2929        1            11.7051                0.715309 │
│ trial_b9863    TERMINATED                 338             3        0.00731551      0.50678              0.606173    6.87364                  197       5.78572      209.434               5767        1            14.4169                0.749623 │
│ trial_b9863    TERMINATED                 580             3        0.0123196       0.789987             0.842133   21.9435                    59     183.313        609.788               2629        1            17.2057                0.758296 │
│ trial_b9863    TERMINATED                 666             3        0.0154746       0.586134             0.740253   22.1136                   123       9.78015        5.00302              706        1            17.0261                0.770739 │
│ trial_b9863    TERMINATED                 765             3        0.0195731       0.753195             0.524474    9.79434                  172      98.9698       178.629               3696        1            15.6138                0.760181 │
│ trial_b9863    TERMINATED                 550             2        0.0152865       0.642751             0.810261   20.5002                   131      69.4834        11.4629              5706        1            14.9274                0.755279 │
│ trial_b9863    TERMINATED                 379             3        0.0152753       0.74538              0.584298   17.5569                    93     327.299        834.159               3257        1            14.0524                0.724736 │
│ trial_b9863    TERMINATED                 493             3        0.0157942       0.761821             0.634877   21.5754                   176       1.64461       86.6583              3242        1            16.6177                0.782428 │
│ trial_b9863    TERMINATED                 522             3        0.013589        0.722285             0.551921    6.16405                  133       7.82715       41.4212               244        1            17.2117                0.796757 │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Mejores hiperparámetros XGBoost: {'num_boost_round': 522, 'max_depth': 3, 'learning_rate': 0.013588999226120193, 'subsample': 0.7222854936039842, 'colsample_bytree': 0.5519213439413061, 'gamma': 6.164045885940654, 'min_child_weight': 133, 'reg_alpha': 7.827145884993129, 'reg_lambda': 41.421247762534456, 'random_state': 244}
[0]	train-mlogloss:1.37453	validation-mlogloss:1.37402
[1]	train-mlogloss:1.36315	validation-mlogloss:1.36190
[2]	train-mlogloss:1.35184	validation-mlogloss:1.35015
[3]	train-mlogloss:1.34070	validation-mlogloss:1.33850
[4]	train-mlogloss:1.33009	validation-mlogloss:1.32751
[5]	train-mlogloss:1.31957	validation-mlogloss:1.31665
[6]	train-mlogloss:1.30944	validation-mlogloss:1.30622
[7]	train-mlogloss:1.29917	validation-mlogloss:1.29552
[8]	train-mlogloss:1.28932	validation-mlogloss:1.28521
[9]	train-mlogloss:1.27941	validation-mlogloss:1.27473
[10]	train-mlogloss:1.26977	validation-mlogloss:1.26449
[11]	train-mlogloss:1.26023	validation-mlogloss:1.25444
[12]	train-mlogloss:1.25097	validation-mlogloss:1.24467
[13]	train-mlogloss:1.24219	validation-mlogloss:1.23567
[14]	train-mlogloss:1.23333	validation-mlogloss:1.22632
[15]	train-mlogloss:1.22458	validation-mlogloss:1.21719
[16]	train-mlogloss:1.21605	validation-mlogloss:1.20830
[17]	train-mlogloss:1.20742	validation-mlogloss:1.19923
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[520]	train-mlogloss:0.50457	validation-mlogloss:0.49273
[521]	train-mlogloss:0.50450	validation-mlogloss:0.49264
Saved model to disk.
[36m(train_xgb_ray_tune pid=325339)[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 10x across cluster][0m
[36m(train_xgb_ray_tune pid=325339)[0m   _log_deprecation_warning([32m [repeated 10x across cluster][0m
2025-11-03 17:19:02.883132: 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`.
2025-11-03 17:19:02.894949: 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 00:00:1762186742.908750  327125 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186742.913023  327125 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186742.923177  327125 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186742.923205  327125 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186742.923208  327125 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186742.923211  327125 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:19:02.926557: 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..
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Training a non-convolutional model.
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[456]	train-mlogloss:0.51701	validation-mlogloss:0.49328
[457]	train-mlogloss:0.51684	validation-mlogloss:0.49306
[458]	train-mlogloss:0.51671	validation-mlogloss:0.49297
[459]	train-mlogloss:0.51654	validation-mlogloss:0.49285
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[461]	train-mlogloss:0.51615	validation-mlogloss:0.49249
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[468]	train-mlogloss:0.51522	validation-mlogloss:0.49173
[469]	train-mlogloss:0.51510	validation-mlogloss:0.49156
[470]	train-mlogloss:0.51498	validation-mlogloss:0.49150
[471]	train-mlogloss:0.51481	validation-mlogloss:0.49140
[472]	train-mlogloss:0.51465	validation-mlogloss:0.49117
[473]	train-mlogloss:0.51454	validation-mlogloss:0.49105
[474]	train-mlogloss:0.51439	validation-mlogloss:0.49097
[475]	train-mlogloss:0.51427	validation-mlogloss:0.49080
[476]	train-mlogloss:0.51411	validation-mlogloss:0.49071
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[478]	train-mlogloss:0.51376	validation-mlogloss:0.49040
[479]	train-mlogloss:0.51358	validation-mlogloss:0.49022
[480]	train-mlogloss:0.51347	validation-mlogloss:0.49007
[481]	train-mlogloss:0.51338	validation-mlogloss:0.49000
[482]	train-mlogloss:0.51328	validation-mlogloss:0.48998
[483]	train-mlogloss:0.51317	validation-mlogloss:0.48987
[484]	train-mlogloss:0.51311	validation-mlogloss:0.48984
[485]	train-mlogloss:0.51296	validation-mlogloss:0.48974
[486]	train-mlogloss:0.51286	validation-mlogloss:0.48967
[487]	train-mlogloss:0.51267	validation-mlogloss:0.48955
[488]	train-mlogloss:0.51252	validation-mlogloss:0.48951
[489]	train-mlogloss:0.51243	validation-mlogloss:0.48945
[490]	train-mlogloss:0.51235	validation-mlogloss:0.48942
[491]	train-mlogloss:0.51223	validation-mlogloss:0.48929
[492]	train-mlogloss:0.51215	validation-mlogloss:0.48915
[493]	train-mlogloss:0.51200	validation-mlogloss:0.48897
[494]	train-mlogloss:0.51194	validation-mlogloss:0.48894
[495]	train-mlogloss:0.51189	validation-mlogloss:0.48892
[496]	train-mlogloss:0.51183	validation-mlogloss:0.48889
[497]	train-mlogloss:0.51174	validation-mlogloss:0.48887
[498]	train-mlogloss:0.51164	validation-mlogloss:0.48877
[499]	train-mlogloss:0.51151	validation-mlogloss:0.48864
[500]	train-mlogloss:0.51136	validation-mlogloss:0.48856
[501]	train-mlogloss:0.51130	validation-mlogloss:0.48849
[502]	train-mlogloss:0.51109	validation-mlogloss:0.48828
[503]	train-mlogloss:0.51092	validation-mlogloss:0.48818
[504]	train-mlogloss:0.51077	validation-mlogloss:0.48803
[505]	train-mlogloss:0.51062	validation-mlogloss:0.48785
[506]	train-mlogloss:0.51052	validation-mlogloss:0.48776
[507]	train-mlogloss:0.51046	validation-mlogloss:0.48774
[508]	train-mlogloss:0.51032	validation-mlogloss:0.48763
[509]	train-mlogloss:0.51018	validation-mlogloss:0.48753
[510]	train-mlogloss:0.51009	validation-mlogloss:0.48749
[511]	train-mlogloss:0.51001	validation-mlogloss:0.48737
[512]	train-mlogloss:0.50994	validation-mlogloss:0.48735
[513]	train-mlogloss:0.50987	validation-mlogloss:0.48734
[514]	train-mlogloss:0.50970	validation-mlogloss:0.48724
[515]	train-mlogloss:0.50961	validation-mlogloss:0.48717
[516]	train-mlogloss:0.50950	validation-mlogloss:0.48705
[517]	train-mlogloss:0.50939	validation-mlogloss:0.48693
[518]	train-mlogloss:0.50929	validation-mlogloss:0.48686
[519]	train-mlogloss:0.50920	validation-mlogloss:0.48677
[520]	train-mlogloss:0.50914	validation-mlogloss:0.48674
[521]	train-mlogloss:0.50902	validation-mlogloss:0.48670
Saved model to disk.

=== EJECUCIÓN 1 ===

--- TRAIN (ejecución 1) ---

--- TEST (ejecución 1) ---
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 1 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 78.97 [%]
Global accuracy score (test) = 79.88 [%]
Global F1 score (train) = 79.32 [%]
Global F1 score (test) = 80.5 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.69      0.65       350
MODERATE-INTENSITY       0.65      0.65      0.65       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.97      0.92      0.95       322

          accuracy                           0.80      1372
         macro avg       0.81      0.80      0.81      1372
      weighted avg       0.81      0.80      0.80      1372


Accuracy capturado en la ejecución 1: 79.88 [%]
F1-score capturado en la ejecución 1: 80.5 [%]

=== EJECUCIÓN 2 ===

--- TRAIN (ejecución 2) ---

--- TEST (ejecución 2) ---
2025-11-03 17:19:21.567333: 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`.
2025-11-03 17:19:21.579040: 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 00:00:1762186761.593085  327433 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186761.597214  327433 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186761.607917  327433 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186761.607944  327433 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186761.607946  327433 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186761.607948  327433 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:19:21.611369: 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..
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
[0]	train-mlogloss:1.37456	validation-mlogloss:1.37407
[1]	train-mlogloss:1.36310	validation-mlogloss:1.36186
[2]	train-mlogloss:1.35184	validation-mlogloss:1.34986
[3]	train-mlogloss:1.34101	validation-mlogloss:1.33863
[4]	train-mlogloss:1.33028	validation-mlogloss:1.32729
[5]	train-mlogloss:1.31995	validation-mlogloss:1.31654
[6]	train-mlogloss:1.30958	validation-mlogloss:1.30607
[7]	train-mlogloss:1.29972	validation-mlogloss:1.29590
[8]	train-mlogloss:1.28958	validation-mlogloss:1.28524
[9]	train-mlogloss:1.27982	validation-mlogloss:1.27515
[10]	train-mlogloss:1.27052	validation-mlogloss:1.26523
[11]	train-mlogloss:1.26092	validation-mlogloss:1.25506
[12]	train-mlogloss:1.25181	validation-mlogloss:1.24579
[13]	train-mlogloss:1.24262	validation-mlogloss:1.23609
[14]	train-mlogloss:1.23368	validation-mlogloss:1.22699
[15]	train-mlogloss:1.22506	validation-mlogloss:1.21776
[16]	train-mlogloss:1.21624	validation-mlogloss:1.20859
[17]	train-mlogloss:1.20754	validation-mlogloss:1.19936
[18]	train-mlogloss:1.19921	validation-mlogloss:1.19091
[19]	train-mlogloss:1.19102	validation-mlogloss:1.18234
[20]	train-mlogloss:1.18301	validation-mlogloss:1.17398
[21]	train-mlogloss:1.17501	validation-mlogloss:1.16543
[22]	train-mlogloss:1.16737	validation-mlogloss:1.15754
[23]	train-mlogloss:1.15971	validation-mlogloss:1.14946
[24]	train-mlogloss:1.15231	validation-mlogloss:1.14160
[25]	train-mlogloss:1.14499	validation-mlogloss:1.13381
[26]	train-mlogloss:1.13770	validation-mlogloss:1.12590
[27]	train-mlogloss:1.13039	validation-mlogloss:1.11847
[28]	train-mlogloss:1.12340	validation-mlogloss:1.11102
[29]	train-mlogloss:1.11631	validation-mlogloss:1.10360
[30]	train-mlogloss:1.10945	validation-mlogloss:1.09646
[31]	train-mlogloss:1.10272	validation-mlogloss:1.08955
[32]	train-mlogloss:1.09593	validation-mlogloss:1.08228
[33]	train-mlogloss:1.08951	validation-mlogloss:1.07568
[34]	train-mlogloss:1.08327	validation-mlogloss:1.06916
[35]	train-mlogloss:1.07694	validation-mlogloss:1.06254
[36]	train-mlogloss:1.07064	validation-mlogloss:1.05604
[37]	train-mlogloss:1.06454	validation-mlogloss:1.04949
[38]	train-mlogloss:1.05836	validation-mlogloss:1.04304
[39]	train-mlogloss:1.05251	validation-mlogloss:1.03680
[40]	train-mlogloss:1.04651	validation-mlogloss:1.03037
[41]	train-mlogloss:1.04063	validation-mlogloss:1.02441
[42]	train-mlogloss:1.03491	validation-mlogloss:1.01836
[43]	train-mlogloss:1.02938	validation-mlogloss:1.01282
[44]	train-mlogloss:1.02375	validation-mlogloss:1.00715
[45]	train-mlogloss:1.01828	validation-mlogloss:1.00132
[46]	train-mlogloss:1.01295	validation-mlogloss:0.99571
[47]	train-mlogloss:1.00758	validation-mlogloss:0.99009
[48]	train-mlogloss:1.00221	validation-mlogloss:0.98455
[49]	train-mlogloss:0.99676	validation-mlogloss:0.97894
[50]	train-mlogloss:0.99144	validation-mlogloss:0.97345
[51]	train-mlogloss:0.98650	validation-mlogloss:0.96843
[52]	train-mlogloss:0.98158	validation-mlogloss:0.96323
[53]	train-mlogloss:0.97647	validation-mlogloss:0.95816
[54]	train-mlogloss:0.97146	validation-mlogloss:0.95308
[55]	train-mlogloss:0.96668	validation-mlogloss:0.94822
[56]	train-mlogloss:0.96176	validation-mlogloss:0.94324
[57]	train-mlogloss:0.95706	validation-mlogloss:0.93850
[58]	train-mlogloss:0.95254	validation-mlogloss:0.93360
[59]	train-mlogloss:0.94786	validation-mlogloss:0.92859
[60]	train-mlogloss:0.94350	validation-mlogloss:0.92420
[61]	train-mlogloss:0.93917	validation-mlogloss:0.91972
[62]	train-mlogloss:0.93473	validation-mlogloss:0.91519
[63]	train-mlogloss:0.93063	validation-mlogloss:0.91081
[64]	train-mlogloss:0.92638	validation-mlogloss:0.90640
[65]	train-mlogloss:0.92235	validation-mlogloss:0.90214
[66]	train-mlogloss:0.91827	validation-mlogloss:0.89791
[67]	train-mlogloss:0.91417	validation-mlogloss:0.89368
[68]	train-mlogloss:0.90994	validation-mlogloss:0.88921
[69]	train-mlogloss:0.90590	validation-mlogloss:0.88489
[70]	train-mlogloss:0.90178	validation-mlogloss:0.88071
[71]	train-mlogloss:0.89782	validation-mlogloss:0.87659
[72]	train-mlogloss:0.89385	validation-mlogloss:0.87232
[73]	train-mlogloss:0.88995	validation-mlogloss:0.86811
[74]	train-mlogloss:0.88625	validation-mlogloss:0.86430
[75]	train-mlogloss:0.88259	validation-mlogloss:0.86039
[76]	train-mlogloss:0.87895	validation-mlogloss:0.85656
[77]	train-mlogloss:0.87530	validation-mlogloss:0.85266
[78]	train-mlogloss:0.87193	validation-mlogloss:0.84923
[79]	train-mlogloss:0.86848	validation-mlogloss:0.84579
[80]	train-mlogloss:0.86491	validation-mlogloss:0.84210
[81]	train-mlogloss:0.86145	validation-mlogloss:0.83849
[82]	train-mlogloss:0.85810	validation-mlogloss:0.83501
[83]	train-mlogloss:0.85469	validation-mlogloss:0.83152
[84]	train-mlogloss:0.85123	validation-mlogloss:0.82802
[85]	train-mlogloss:0.84783	validation-mlogloss:0.82447
[86]	train-mlogloss:0.84454	validation-mlogloss:0.82097
[87]	train-mlogloss:0.84133	validation-mlogloss:0.81767
[88]	train-mlogloss:0.83818	validation-mlogloss:0.81435
[89]	train-mlogloss:0.83507	validation-mlogloss:0.81116
[90]	train-mlogloss:0.83182	validation-mlogloss:0.80784
[91]	train-mlogloss:0.82857	validation-mlogloss:0.80455
[92]	train-mlogloss:0.82531	validation-mlogloss:0.80123
[93]	train-mlogloss:0.82223	validation-mlogloss:0.79797
[94]	train-mlogloss:0.81946	validation-mlogloss:0.79523
[95]	train-mlogloss:0.81662	validation-mlogloss:0.79239
[96]	train-mlogloss:0.81369	validation-mlogloss:0.78947
[97]	train-mlogloss:0.81057	validation-mlogloss:0.78634
[98]	train-mlogloss:0.80781	validation-mlogloss:0.78337
[99]	train-mlogloss:0.80507	validation-mlogloss:0.78067
[100]	train-mlogloss:0.80244	validation-mlogloss:0.77809
[101]	train-mlogloss:0.79980	validation-mlogloss:0.77534
[102]	train-mlogloss:0.79704	validation-mlogloss:0.77264
[103]	train-mlogloss:0.79453	validation-mlogloss:0.77018
[104]	train-mlogloss:0.79198	validation-mlogloss:0.76756
[105]	train-mlogloss:0.78939	validation-mlogloss:0.76483
[106]	train-mlogloss:0.78678	validation-mlogloss:0.76206
[107]	train-mlogloss:0.78425	validation-mlogloss:0.75942
[108]	train-mlogloss:0.78172	validation-mlogloss:0.75687
[109]	train-mlogloss:0.77921	validation-mlogloss:0.75424
[110]	train-mlogloss:0.77672	validation-mlogloss:0.75169
[111]	train-mlogloss:0.77428	validation-mlogloss:0.74914
[112]	train-mlogloss:0.77179	validation-mlogloss:0.74653
[113]	train-mlogloss:0.76942	validation-mlogloss:0.74394
[114]	train-mlogloss:0.76687	validation-mlogloss:0.74133
[115]	train-mlogloss:0.76441	validation-mlogloss:0.73886
[116]	train-mlogloss:0.76184	validation-mlogloss:0.73628
[117]	train-mlogloss:0.75973	validation-mlogloss:0.73409
[118]	train-mlogloss:0.75736	validation-mlogloss:0.73170
[119]	train-mlogloss:0.75509	validation-mlogloss:0.72922
[120]	train-mlogloss:0.75285	validation-mlogloss:0.72683
[121]	train-mlogloss:0.75063	validation-mlogloss:0.72445
[122]	train-mlogloss:0.74863	validation-mlogloss:0.72233
[123]	train-mlogloss:0.74640	validation-mlogloss:0.72002
[124]	train-mlogloss:0.74443	validation-mlogloss:0.71807
[125]	train-mlogloss:0.74245	validation-mlogloss:0.71593
[126]	train-mlogloss:0.74025	validation-mlogloss:0.71362
[127]	train-mlogloss:0.73805	validation-mlogloss:0.71140
[128]	train-mlogloss:0.73580	validation-mlogloss:0.70921
[129]	train-mlogloss:0.73362	validation-mlogloss:0.70710
[130]	train-mlogloss:0.73170	validation-mlogloss:0.70502
[131]	train-mlogloss:0.72978	validation-mlogloss:0.70307
[132]	train-mlogloss:0.72784	validation-mlogloss:0.70097
[133]	train-mlogloss:0.72588	validation-mlogloss:0.69885
[134]	train-mlogloss:0.72378	validation-mlogloss:0.69673
[135]	train-mlogloss:0.72197	validation-mlogloss:0.69481
[136]	train-mlogloss:0.72004	validation-mlogloss:0.69289
[137]	train-mlogloss:0.71801	validation-mlogloss:0.69083
[138]	train-mlogloss:0.71630	validation-mlogloss:0.68903
[139]	train-mlogloss:0.71456	validation-mlogloss:0.68718
[140]	train-mlogloss:0.71284	validation-mlogloss:0.68539
[141]	train-mlogloss:0.71084	validation-mlogloss:0.68341
[142]	train-mlogloss:0.70896	validation-mlogloss:0.68154
[143]	train-mlogloss:0.70709	validation-mlogloss:0.67965
[144]	train-mlogloss:0.70534	validation-mlogloss:0.67787
[145]	train-mlogloss:0.70348	validation-mlogloss:0.67606
[146]	train-mlogloss:0.70169	validation-mlogloss:0.67422
[147]	train-mlogloss:0.69982	validation-mlogloss:0.67234
[148]	train-mlogloss:0.69804	validation-mlogloss:0.67054
[149]	train-mlogloss:0.69637	validation-mlogloss:0.66893
[150]	train-mlogloss:0.69471	validation-mlogloss:0.66718
[151]	train-mlogloss:0.69297	validation-mlogloss:0.66549
[152]	train-mlogloss:0.69122	validation-mlogloss:0.66379
[153]	train-mlogloss:0.68955	validation-mlogloss:0.66211
[154]	train-mlogloss:0.68784	validation-mlogloss:0.66031
[155]	train-mlogloss:0.68638	validation-mlogloss:0.65894
[156]	train-mlogloss:0.68474	validation-mlogloss:0.65741
[157]	train-mlogloss:0.68314	validation-mlogloss:0.65583
[158]	train-mlogloss:0.68173	validation-mlogloss:0.65438
[159]	train-mlogloss:0.68013	validation-mlogloss:0.65265
[160]	train-mlogloss:0.67850	validation-mlogloss:0.65100
[161]	train-mlogloss:0.67691	validation-mlogloss:0.64938
[162]	train-mlogloss:0.67539	validation-mlogloss:0.64787
[163]	train-mlogloss:0.67387	validation-mlogloss:0.64631
[164]	train-mlogloss:0.67232	validation-mlogloss:0.64464
[165]	train-mlogloss:0.67083	validation-mlogloss:0.64313
[166]	train-mlogloss:0.66954	validation-mlogloss:0.64187
[167]	train-mlogloss:0.66820	validation-mlogloss:0.64040
[168]	train-mlogloss:0.66672	validation-mlogloss:0.63890
[169]	train-mlogloss:0.66542	validation-mlogloss:0.63749
[170]	train-mlogloss:0.66404	validation-mlogloss:0.63603
[171]	train-mlogloss:0.66256	validation-mlogloss:0.63437
[172]	train-mlogloss:0.66122	validation-mlogloss:0.63303
[173]	train-mlogloss:0.65984	validation-mlogloss:0.63160
[174]	train-mlogloss:0.65857	validation-mlogloss:0.63027
[175]	train-mlogloss:0.65728	validation-mlogloss:0.62896
[176]	train-mlogloss:0.65595	validation-mlogloss:0.62764
[177]	train-mlogloss:0.65459	validation-mlogloss:0.62633
[178]	train-mlogloss:0.65331	validation-mlogloss:0.62501
[179]	train-mlogloss:0.65200	validation-mlogloss:0.62362
[180]	train-mlogloss:0.65066	validation-mlogloss:0.62213
[181]	train-mlogloss:0.64935	validation-mlogloss:0.62083
[182]	train-mlogloss:0.64821	validation-mlogloss:0.61975
[183]	train-mlogloss:0.64694	validation-mlogloss:0.61857
[184]	train-mlogloss:0.64576	validation-mlogloss:0.61745
[185]	train-mlogloss:0.64462	validation-mlogloss:0.61622
[186]	train-mlogloss:0.64347	validation-mlogloss:0.61507
[187]	train-mlogloss:0.64228	validation-mlogloss:0.61386
[188]	train-mlogloss:0.64114	validation-mlogloss:0.61278
[189]	train-mlogloss:0.63998	validation-mlogloss:0.61156
[190]	train-mlogloss:0.63888	validation-mlogloss:0.61051
[191]	train-mlogloss:0.63774	validation-mlogloss:0.60939
[192]	train-mlogloss:0.63672	validation-mlogloss:0.60826
[193]	train-mlogloss:0.63575	validation-mlogloss:0.60720
[194]	train-mlogloss:0.63464	validation-mlogloss:0.60606
[195]	train-mlogloss:0.63360	validation-mlogloss:0.60506
[196]	train-mlogloss:0.63256	validation-mlogloss:0.60397
[197]	train-mlogloss:0.63155	validation-mlogloss:0.60301
[198]	train-mlogloss:0.63061	validation-mlogloss:0.60208
[199]	train-mlogloss:0.62952	validation-mlogloss:0.60111
[200]	train-mlogloss:0.62844	validation-mlogloss:0.60001
[201]	train-mlogloss:0.62749	validation-mlogloss:0.59900
[202]	train-mlogloss:0.62648	validation-mlogloss:0.59801
[203]	train-mlogloss:0.62549	validation-mlogloss:0.59699
[204]	train-mlogloss:0.62457	validation-mlogloss:0.59606
[205]	train-mlogloss:0.62353	validation-mlogloss:0.59507
[206]	train-mlogloss:0.62268	validation-mlogloss:0.59426
[207]	train-mlogloss:0.62171	validation-mlogloss:0.59326
[208]	train-mlogloss:0.62074	validation-mlogloss:0.59239
[209]	train-mlogloss:0.61978	validation-mlogloss:0.59146
[210]	train-mlogloss:0.61881	validation-mlogloss:0.59054
[211]	train-mlogloss:0.61788	validation-mlogloss:0.58968
[212]	train-mlogloss:0.61700	validation-mlogloss:0.58876
[213]	train-mlogloss:0.61614	validation-mlogloss:0.58785
[214]	train-mlogloss:0.61522	validation-mlogloss:0.58692
[215]	train-mlogloss:0.61440	validation-mlogloss:0.58616
[216]	train-mlogloss:0.61350	validation-mlogloss:0.58537
[217]	train-mlogloss:0.61265	validation-mlogloss:0.58460
[218]	train-mlogloss:0.61181	validation-mlogloss:0.58383
[219]	train-mlogloss:0.61092	validation-mlogloss:0.58300
[220]	train-mlogloss:0.61003	validation-mlogloss:0.58203
[221]	train-mlogloss:0.60923	validation-mlogloss:0.58113
[222]	train-mlogloss:0.60836	validation-mlogloss:0.58034
[223]	train-mlogloss:0.60763	validation-mlogloss:0.57955
[224]	train-mlogloss:0.60685	validation-mlogloss:0.57875
[225]	train-mlogloss:0.60599	validation-mlogloss:0.57788
[226]	train-mlogloss:0.60523	validation-mlogloss:0.57720
[227]	train-mlogloss:0.60443	validation-mlogloss:0.57651
[228]	train-mlogloss:0.60365	validation-mlogloss:0.57562
[229]	train-mlogloss:0.60295	validation-mlogloss:0.57492
[230]	train-mlogloss:0.60208	validation-mlogloss:0.57404
[231]	train-mlogloss:0.60134	validation-mlogloss:0.57321
[232]	train-mlogloss:0.60061	validation-mlogloss:0.57253
[233]	train-mlogloss:0.59994	validation-mlogloss:0.57185
[234]	train-mlogloss:0.59911	validation-mlogloss:0.57104
[235]	train-mlogloss:0.59835	validation-mlogloss:0.57037
[236]	train-mlogloss:0.59761	validation-mlogloss:0.56968
[237]	train-mlogloss:0.59690	validation-mlogloss:0.56898
[238]	train-mlogloss:0.59621	validation-mlogloss:0.56834
[239]	train-mlogloss:0.59544	validation-mlogloss:0.56766
[240]	train-mlogloss:0.59468	validation-mlogloss:0.56684
[241]	train-mlogloss:0.59396	validation-mlogloss:0.56608
[242]	train-mlogloss:0.59339	validation-mlogloss:0.56563
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[273]	train-mlogloss:0.57419	validation-mlogloss:0.54690
[274]	train-mlogloss:0.57364	validation-mlogloss:0.54643
[275]	train-mlogloss:0.57305	validation-mlogloss:0.54586
[276]	train-mlogloss:0.57253	validation-mlogloss:0.54534
[277]	train-mlogloss:0.57194	validation-mlogloss:0.54466
[278]	train-mlogloss:0.57138	validation-mlogloss:0.54417
[279]	train-mlogloss:0.57087	validation-mlogloss:0.54361
[280]	train-mlogloss:0.57037	validation-mlogloss:0.54316
[281]	train-mlogloss:0.56990	validation-mlogloss:0.54282
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[503]	train-mlogloss:0.51211	validation-mlogloss:0.49241
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[505]	train-mlogloss:0.51189	validation-mlogloss:0.49224
[506]	train-mlogloss:0.51177	validation-mlogloss:0.49210
[507]	train-mlogloss:0.51170	validation-mlogloss:0.49204
[508]	train-mlogloss:0.51163	validation-mlogloss:0.49200
[509]	train-mlogloss:0.51143	validation-mlogloss:0.49189
[510]	train-mlogloss:0.51128	validation-mlogloss:0.49173
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[520]	train-mlogloss:0.51038	validation-mlogloss:0.49081
[521]	train-mlogloss:0.51031	validation-mlogloss:0.49075
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[0 2 0 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 78.95 [%]
Global accuracy score (test) = 80.98 [%]
Global F1 score (train) = 79.25 [%]
Global F1 score (test) = 81.48 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.64      0.72      0.68       350
MODERATE-INTENSITY       0.69      0.64      0.66       350
         SEDENTARY       0.99      0.96      0.98       350
VIGOROUS-INTENSITY       0.97      0.92      0.94       322

          accuracy                           0.81      1372
         macro avg       0.82      0.81      0.81      1372
      weighted avg       0.82      0.81      0.81      1372


Accuracy capturado en la ejecución 2: 80.98 [%]
F1-score capturado en la ejecución 2: 81.48 [%]

=== EJECUCIÓN 3 ===

--- TRAIN (ejecución 3) ---

--- TEST (ejecución 3) ---
2025-11-03 17:19:40.002028: 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`.
2025-11-03 17:19:40.013738: 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 00:00:1762186780.027725  327734 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186780.031905  327734 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186780.042617  327734 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186780.042645  327734 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186780.042648  327734 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186780.042649  327734 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:19:40.045725: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37453	validation-mlogloss:1.37418
[1]	train-mlogloss:1.36294	validation-mlogloss:1.36225
[2]	train-mlogloss:1.35177	validation-mlogloss:1.35098
[3]	train-mlogloss:1.34077	validation-mlogloss:1.33945
[4]	train-mlogloss:1.32969	validation-mlogloss:1.32795
[5]	train-mlogloss:1.31921	validation-mlogloss:1.31753
[6]	train-mlogloss:1.30896	validation-mlogloss:1.30675
[7]	train-mlogloss:1.29874	validation-mlogloss:1.29617
[8]	train-mlogloss:1.28869	validation-mlogloss:1.28558
[9]	train-mlogloss:1.27868	validation-mlogloss:1.27513
[10]	train-mlogloss:1.26897	validation-mlogloss:1.26486
[11]	train-mlogloss:1.25938	validation-mlogloss:1.25485
[12]	train-mlogloss:1.25037	validation-mlogloss:1.24595
[13]	train-mlogloss:1.24156	validation-mlogloss:1.23685
[14]	train-mlogloss:1.23241	validation-mlogloss:1.22729
[15]	train-mlogloss:1.22348	validation-mlogloss:1.21793
[16]	train-mlogloss:1.21487	validation-mlogloss:1.20900
[17]	train-mlogloss:1.20630	validation-mlogloss:1.20014
[18]	train-mlogloss:1.19820	validation-mlogloss:1.19167
[19]	train-mlogloss:1.18990	validation-mlogloss:1.18301
[20]	train-mlogloss:1.18172	validation-mlogloss:1.17456
[21]	train-mlogloss:1.17388	validation-mlogloss:1.16637
[22]	train-mlogloss:1.16618	validation-mlogloss:1.15824
[23]	train-mlogloss:1.15879	validation-mlogloss:1.15075
[24]	train-mlogloss:1.15121	validation-mlogloss:1.14280
[25]	train-mlogloss:1.14366	validation-mlogloss:1.13499
[26]	train-mlogloss:1.13640	validation-mlogloss:1.12745
[27]	train-mlogloss:1.12928	validation-mlogloss:1.12007
[28]	train-mlogloss:1.12226	validation-mlogloss:1.11292
[29]	train-mlogloss:1.11537	validation-mlogloss:1.10586
[30]	train-mlogloss:1.10861	validation-mlogloss:1.09890
[31]	train-mlogloss:1.10193	validation-mlogloss:1.09176
[32]	train-mlogloss:1.09513	validation-mlogloss:1.08459
[33]	train-mlogloss:1.08839	validation-mlogloss:1.07764
[34]	train-mlogloss:1.08189	validation-mlogloss:1.07071
[35]	train-mlogloss:1.07541	validation-mlogloss:1.06383
[36]	train-mlogloss:1.06918	validation-mlogloss:1.05732
[37]	train-mlogloss:1.06285	validation-mlogloss:1.05068
[38]	train-mlogloss:1.05686	validation-mlogloss:1.04428
[39]	train-mlogloss:1.05092	validation-mlogloss:1.03824
[40]	train-mlogloss:1.04487	validation-mlogloss:1.03195
[41]	train-mlogloss:1.03910	validation-mlogloss:1.02598
[42]	train-mlogloss:1.03347	validation-mlogloss:1.02022
[43]	train-mlogloss:1.02776	validation-mlogloss:1.01436
[44]	train-mlogloss:1.02209	validation-mlogloss:1.00841
[45]	train-mlogloss:1.01669	validation-mlogloss:1.00311
[46]	train-mlogloss:1.01107	validation-mlogloss:0.99742
[47]	train-mlogloss:1.00553	validation-mlogloss:0.99172
[48]	train-mlogloss:1.00047	validation-mlogloss:0.98647
[49]	train-mlogloss:0.99497	validation-mlogloss:0.98091
[50]	train-mlogloss:0.98980	validation-mlogloss:0.97561
[51]	train-mlogloss:0.98491	validation-mlogloss:0.97049
[52]	train-mlogloss:0.97972	validation-mlogloss:0.96519
[53]	train-mlogloss:0.97454	validation-mlogloss:0.95989
[54]	train-mlogloss:0.96963	validation-mlogloss:0.95475
[55]	train-mlogloss:0.96486	validation-mlogloss:0.94982
[56]	train-mlogloss:0.95996	validation-mlogloss:0.94488
[57]	train-mlogloss:0.95521	validation-mlogloss:0.93992
[58]	train-mlogloss:0.95051	validation-mlogloss:0.93517
[59]	train-mlogloss:0.94595	validation-mlogloss:0.93068
[60]	train-mlogloss:0.94134	validation-mlogloss:0.92598
[61]	train-mlogloss:0.93695	validation-mlogloss:0.92133
[62]	train-mlogloss:0.93247	validation-mlogloss:0.91667
[63]	train-mlogloss:0.92803	validation-mlogloss:0.91202
[64]	train-mlogloss:0.92370	validation-mlogloss:0.90755
[65]	train-mlogloss:0.91942	validation-mlogloss:0.90318
[66]	train-mlogloss:0.91545	validation-mlogloss:0.89897
[67]	train-mlogloss:0.91151	validation-mlogloss:0.89490
[68]	train-mlogloss:0.90746	validation-mlogloss:0.89078
[69]	train-mlogloss:0.90347	validation-mlogloss:0.88662
[70]	train-mlogloss:0.89944	validation-mlogloss:0.88261
[71]	train-mlogloss:0.89564	validation-mlogloss:0.87867
[72]	train-mlogloss:0.89174	validation-mlogloss:0.87468
[73]	train-mlogloss:0.88803	validation-mlogloss:0.87090
[74]	train-mlogloss:0.88417	validation-mlogloss:0.86678
[75]	train-mlogloss:0.88034	validation-mlogloss:0.86289
[76]	train-mlogloss:0.87677	validation-mlogloss:0.85915
[77]	train-mlogloss:0.87307	validation-mlogloss:0.85538
[78]	train-mlogloss:0.86942	validation-mlogloss:0.85169
[79]	train-mlogloss:0.86583	validation-mlogloss:0.84797
[80]	train-mlogloss:0.86222	validation-mlogloss:0.84433
[81]	train-mlogloss:0.85872	validation-mlogloss:0.84075
[82]	train-mlogloss:0.85526	validation-mlogloss:0.83711
[83]	train-mlogloss:0.85170	validation-mlogloss:0.83351
[84]	train-mlogloss:0.84856	validation-mlogloss:0.83038
[85]	train-mlogloss:0.84528	validation-mlogloss:0.82710
[86]	train-mlogloss:0.84196	validation-mlogloss:0.82366
[87]	train-mlogloss:0.83869	validation-mlogloss:0.82027
[88]	train-mlogloss:0.83554	validation-mlogloss:0.81696
[89]	train-mlogloss:0.83223	validation-mlogloss:0.81372
[90]	train-mlogloss:0.82908	validation-mlogloss:0.81040
[91]	train-mlogloss:0.82589	validation-mlogloss:0.80724
[92]	train-mlogloss:0.82273	validation-mlogloss:0.80395
[93]	train-mlogloss:0.81978	validation-mlogloss:0.80097
[94]	train-mlogloss:0.81684	validation-mlogloss:0.79785
[95]	train-mlogloss:0.81385	validation-mlogloss:0.79469
[96]	train-mlogloss:0.81094	validation-mlogloss:0.79169
[97]	train-mlogloss:0.80817	validation-mlogloss:0.78898
[98]	train-mlogloss:0.80537	validation-mlogloss:0.78619
[99]	train-mlogloss:0.80257	validation-mlogloss:0.78328
[100]	train-mlogloss:0.79998	validation-mlogloss:0.78062
[101]	train-mlogloss:0.79716	validation-mlogloss:0.77768
[102]	train-mlogloss:0.79451	validation-mlogloss:0.77490
[103]	train-mlogloss:0.79197	validation-mlogloss:0.77234
[104]	train-mlogloss:0.78908	validation-mlogloss:0.76950
[105]	train-mlogloss:0.78653	validation-mlogloss:0.76677
[106]	train-mlogloss:0.78414	validation-mlogloss:0.76436
[107]	train-mlogloss:0.78158	validation-mlogloss:0.76173
[108]	train-mlogloss:0.77896	validation-mlogloss:0.75910
[109]	train-mlogloss:0.77651	validation-mlogloss:0.75650
[110]	train-mlogloss:0.77414	validation-mlogloss:0.75416
[111]	train-mlogloss:0.77181	validation-mlogloss:0.75176
[112]	train-mlogloss:0.76954	validation-mlogloss:0.74961
[113]	train-mlogloss:0.76724	validation-mlogloss:0.74724
[114]	train-mlogloss:0.76492	validation-mlogloss:0.74489
[115]	train-mlogloss:0.76270	validation-mlogloss:0.74265
[116]	train-mlogloss:0.76042	validation-mlogloss:0.74036
[117]	train-mlogloss:0.75781	validation-mlogloss:0.73781
[118]	train-mlogloss:0.75553	validation-mlogloss:0.73556
[119]	train-mlogloss:0.75313	validation-mlogloss:0.73321
[120]	train-mlogloss:0.75094	validation-mlogloss:0.73095
[121]	train-mlogloss:0.74869	validation-mlogloss:0.72858
[122]	train-mlogloss:0.74638	validation-mlogloss:0.72628
[123]	train-mlogloss:0.74410	validation-mlogloss:0.72373
[124]	train-mlogloss:0.74180	validation-mlogloss:0.72140
[125]	train-mlogloss:0.73951	validation-mlogloss:0.71916
[126]	train-mlogloss:0.73755	validation-mlogloss:0.71729
[127]	train-mlogloss:0.73556	validation-mlogloss:0.71517
[128]	train-mlogloss:0.73344	validation-mlogloss:0.71291
[129]	train-mlogloss:0.73155	validation-mlogloss:0.71105
[130]	train-mlogloss:0.72961	validation-mlogloss:0.70907
[131]	train-mlogloss:0.72770	validation-mlogloss:0.70710
[132]	train-mlogloss:0.72563	validation-mlogloss:0.70496
[133]	train-mlogloss:0.72361	validation-mlogloss:0.70292
[134]	train-mlogloss:0.72167	validation-mlogloss:0.70091
[135]	train-mlogloss:0.71960	validation-mlogloss:0.69886
[136]	train-mlogloss:0.71770	validation-mlogloss:0.69693
[137]	train-mlogloss:0.71581	validation-mlogloss:0.69501
[138]	train-mlogloss:0.71390	validation-mlogloss:0.69313
[139]	train-mlogloss:0.71200	validation-mlogloss:0.69117
[140]	train-mlogloss:0.71002	validation-mlogloss:0.68919
[141]	train-mlogloss:0.70826	validation-mlogloss:0.68732
[142]	train-mlogloss:0.70636	validation-mlogloss:0.68559
[143]	train-mlogloss:0.70453	validation-mlogloss:0.68372
[144]	train-mlogloss:0.70287	validation-mlogloss:0.68202
[145]	train-mlogloss:0.70097	validation-mlogloss:0.68026
[146]	train-mlogloss:0.69917	validation-mlogloss:0.67853
[147]	train-mlogloss:0.69753	validation-mlogloss:0.67692
[148]	train-mlogloss:0.69576	validation-mlogloss:0.67526
[149]	train-mlogloss:0.69401	validation-mlogloss:0.67353
[150]	train-mlogloss:0.69232	validation-mlogloss:0.67190
[151]	train-mlogloss:0.69064	validation-mlogloss:0.67024
[152]	train-mlogloss:0.68903	validation-mlogloss:0.66857
[153]	train-mlogloss:0.68732	validation-mlogloss:0.66686
[154]	train-mlogloss:0.68579	validation-mlogloss:0.66523
[155]	train-mlogloss:0.68432	validation-mlogloss:0.66358
[156]	train-mlogloss:0.68271	validation-mlogloss:0.66186
[157]	train-mlogloss:0.68106	validation-mlogloss:0.66018
[158]	train-mlogloss:0.67955	validation-mlogloss:0.65878
[159]	train-mlogloss:0.67796	validation-mlogloss:0.65727
[160]	train-mlogloss:0.67640	validation-mlogloss:0.65576
[161]	train-mlogloss:0.67494	validation-mlogloss:0.65439
[162]	train-mlogloss:0.67346	validation-mlogloss:0.65295
[163]	train-mlogloss:0.67203	validation-mlogloss:0.65154
[164]	train-mlogloss:0.67060	validation-mlogloss:0.65002
[165]	train-mlogloss:0.66934	validation-mlogloss:0.64861
[166]	train-mlogloss:0.66788	validation-mlogloss:0.64722
[167]	train-mlogloss:0.66661	validation-mlogloss:0.64602
[168]	train-mlogloss:0.66524	validation-mlogloss:0.64468
[169]	train-mlogloss:0.66398	validation-mlogloss:0.64341
[170]	train-mlogloss:0.66256	validation-mlogloss:0.64195
[171]	train-mlogloss:0.66117	validation-mlogloss:0.64068
[172]	train-mlogloss:0.65981	validation-mlogloss:0.63938
[173]	train-mlogloss:0.65847	validation-mlogloss:0.63807
[174]	train-mlogloss:0.65729	validation-mlogloss:0.63687
[175]	train-mlogloss:0.65603	validation-mlogloss:0.63549
[176]	train-mlogloss:0.65483	validation-mlogloss:0.63425
[177]	train-mlogloss:0.65365	validation-mlogloss:0.63304
[178]	train-mlogloss:0.65250	validation-mlogloss:0.63180
[179]	train-mlogloss:0.65111	validation-mlogloss:0.63044
[180]	train-mlogloss:0.64986	validation-mlogloss:0.62929
[181]	train-mlogloss:0.64861	validation-mlogloss:0.62812
[182]	train-mlogloss:0.64749	validation-mlogloss:0.62698
[183]	train-mlogloss:0.64627	validation-mlogloss:0.62579
[184]	train-mlogloss:0.64510	validation-mlogloss:0.62464
[185]	train-mlogloss:0.64392	validation-mlogloss:0.62350
[186]	train-mlogloss:0.64272	validation-mlogloss:0.62212
[187]	train-mlogloss:0.64153	validation-mlogloss:0.62094
[188]	train-mlogloss:0.64028	validation-mlogloss:0.61963
[189]	train-mlogloss:0.63916	validation-mlogloss:0.61852
[190]	train-mlogloss:0.63799	validation-mlogloss:0.61742
[191]	train-mlogloss:0.63691	validation-mlogloss:0.61642
[192]	train-mlogloss:0.63583	validation-mlogloss:0.61527
[193]	train-mlogloss:0.63468	validation-mlogloss:0.61412
[194]	train-mlogloss:0.63351	validation-mlogloss:0.61303
[195]	train-mlogloss:0.63236	validation-mlogloss:0.61203
[196]	train-mlogloss:0.63130	validation-mlogloss:0.61100
[197]	train-mlogloss:0.63024	validation-mlogloss:0.61003
[198]	train-mlogloss:0.62917	validation-mlogloss:0.60900
[199]	train-mlogloss:0.62807	validation-mlogloss:0.60791
[200]	train-mlogloss:0.62700	validation-mlogloss:0.60688
[201]	train-mlogloss:0.62606	validation-mlogloss:0.60593
[202]	train-mlogloss:0.62507	validation-mlogloss:0.60491
[203]	train-mlogloss:0.62405	validation-mlogloss:0.60402
[204]	train-mlogloss:0.62307	validation-mlogloss:0.60304
[205]	train-mlogloss:0.62207	validation-mlogloss:0.60204
[206]	train-mlogloss:0.62113	validation-mlogloss:0.60118
[207]	train-mlogloss:0.62024	validation-mlogloss:0.60026
[208]	train-mlogloss:0.61923	validation-mlogloss:0.59926
[209]	train-mlogloss:0.61829	validation-mlogloss:0.59843
[210]	train-mlogloss:0.61743	validation-mlogloss:0.59765
[211]	train-mlogloss:0.61660	validation-mlogloss:0.59679
[212]	train-mlogloss:0.61566	validation-mlogloss:0.59592
[213]	train-mlogloss:0.61472	validation-mlogloss:0.59513
[214]	train-mlogloss:0.61383	validation-mlogloss:0.59423
[215]	train-mlogloss:0.61298	validation-mlogloss:0.59336
[216]	train-mlogloss:0.61202	validation-mlogloss:0.59237
[217]	train-mlogloss:0.61115	validation-mlogloss:0.59154
[218]	train-mlogloss:0.61037	validation-mlogloss:0.59067
[219]	train-mlogloss:0.60949	validation-mlogloss:0.58991
[220]	train-mlogloss:0.60858	validation-mlogloss:0.58909
[221]	train-mlogloss:0.60777	validation-mlogloss:0.58830
[222]	train-mlogloss:0.60693	validation-mlogloss:0.58753
[223]	train-mlogloss:0.60611	validation-mlogloss:0.58677
[224]	train-mlogloss:0.60529	validation-mlogloss:0.58601
[225]	train-mlogloss:0.60450	validation-mlogloss:0.58527
[226]	train-mlogloss:0.60367	validation-mlogloss:0.58449
[227]	train-mlogloss:0.60289	validation-mlogloss:0.58376
[228]	train-mlogloss:0.60214	validation-mlogloss:0.58297
[229]	train-mlogloss:0.60139	validation-mlogloss:0.58228
[230]	train-mlogloss:0.60059	validation-mlogloss:0.58168
[231]	train-mlogloss:0.59982	validation-mlogloss:0.58096
[232]	train-mlogloss:0.59907	validation-mlogloss:0.58028
[233]	train-mlogloss:0.59837	validation-mlogloss:0.57960
[234]	train-mlogloss:0.59767	validation-mlogloss:0.57884
[235]	train-mlogloss:0.59698	validation-mlogloss:0.57815
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Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 78.99 [%]
Global accuracy score (test) = 80.47 [%]
Global F1 score (train) = 79.32 [%]
Global F1 score (test) = 81.07 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.71      0.67       350
MODERATE-INTENSITY       0.67      0.64      0.66       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.98      0.92      0.95       322

          accuracy                           0.80      1372
         macro avg       0.82      0.81      0.81      1372
      weighted avg       0.81      0.80      0.81      1372


Accuracy capturado en la ejecución 3: 80.47 [%]
F1-score capturado en la ejecución 3: 81.07 [%]

=== EJECUCIÓN 4 ===

--- TRAIN (ejecución 4) ---

--- TEST (ejecución 4) ---
2025-11-03 17:19:58.417660: 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`.
2025-11-03 17:19:58.429605: 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 00:00:1762186798.443552  328043 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186798.448126  328043 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186798.461027  328043 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186798.461063  328043 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186798.461065  328043 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186798.461067  328043 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:19:58.464205: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37479	validation-mlogloss:1.37443
[1]	train-mlogloss:1.36318	validation-mlogloss:1.36255
[2]	train-mlogloss:1.35241	validation-mlogloss:1.35141
[3]	train-mlogloss:1.34137	validation-mlogloss:1.33958
[4]	train-mlogloss:1.33081	validation-mlogloss:1.32846
[5]	train-mlogloss:1.32068	validation-mlogloss:1.31798
[6]	train-mlogloss:1.31035	validation-mlogloss:1.30725
[7]	train-mlogloss:1.30044	validation-mlogloss:1.29679
[8]	train-mlogloss:1.29051	validation-mlogloss:1.28625
[9]	train-mlogloss:1.28094	validation-mlogloss:1.27640
[10]	train-mlogloss:1.27113	validation-mlogloss:1.26615
[11]	train-mlogloss:1.26150	validation-mlogloss:1.25626
[12]	train-mlogloss:1.25197	validation-mlogloss:1.24643
[13]	train-mlogloss:1.24282	validation-mlogloss:1.23712
[14]	train-mlogloss:1.23407	validation-mlogloss:1.22813
[15]	train-mlogloss:1.22540	validation-mlogloss:1.21905
[16]	train-mlogloss:1.21675	validation-mlogloss:1.20975
[17]	train-mlogloss:1.20823	validation-mlogloss:1.20082
[18]	train-mlogloss:1.19962	validation-mlogloss:1.19175
[19]	train-mlogloss:1.19161	validation-mlogloss:1.18322
[20]	train-mlogloss:1.18365	validation-mlogloss:1.17517
[21]	train-mlogloss:1.17561	validation-mlogloss:1.16667
[22]	train-mlogloss:1.16775	validation-mlogloss:1.15880
[23]	train-mlogloss:1.16001	validation-mlogloss:1.15052
[24]	train-mlogloss:1.15238	validation-mlogloss:1.14255
[25]	train-mlogloss:1.14476	validation-mlogloss:1.13442
[26]	train-mlogloss:1.13726	validation-mlogloss:1.12660
[27]	train-mlogloss:1.13011	validation-mlogloss:1.11894
[28]	train-mlogloss:1.12315	validation-mlogloss:1.11182
[29]	train-mlogloss:1.11613	validation-mlogloss:1.10426
[30]	train-mlogloss:1.10924	validation-mlogloss:1.09693
[31]	train-mlogloss:1.10261	validation-mlogloss:1.09017
[32]	train-mlogloss:1.09615	validation-mlogloss:1.08340
[33]	train-mlogloss:1.08954	validation-mlogloss:1.07647
[34]	train-mlogloss:1.08328	validation-mlogloss:1.07007
[35]	train-mlogloss:1.07680	validation-mlogloss:1.06338
[36]	train-mlogloss:1.07047	validation-mlogloss:1.05676
[37]	train-mlogloss:1.06442	validation-mlogloss:1.05065
[38]	train-mlogloss:1.05816	validation-mlogloss:1.04385
[39]	train-mlogloss:1.05213	validation-mlogloss:1.03781
[40]	train-mlogloss:1.04630	validation-mlogloss:1.03168
[41]	train-mlogloss:1.04023	validation-mlogloss:1.02541
[42]	train-mlogloss:1.03450	validation-mlogloss:1.01963
[43]	train-mlogloss:1.02880	validation-mlogloss:1.01354
[44]	train-mlogloss:1.02337	validation-mlogloss:1.00778
[45]	train-mlogloss:1.01751	validation-mlogloss:1.00177
[46]	train-mlogloss:1.01194	validation-mlogloss:0.99600
[47]	train-mlogloss:1.00637	validation-mlogloss:0.99023
[48]	train-mlogloss:1.00121	validation-mlogloss:0.98487
[49]	train-mlogloss:0.99605	validation-mlogloss:0.97945
[50]	train-mlogloss:0.99097	validation-mlogloss:0.97417
[51]	train-mlogloss:0.98570	validation-mlogloss:0.96892
[52]	train-mlogloss:0.98060	validation-mlogloss:0.96374
[53]	train-mlogloss:0.97544	validation-mlogloss:0.95839
[54]	train-mlogloss:0.97037	validation-mlogloss:0.95308
[55]	train-mlogloss:0.96569	validation-mlogloss:0.94811
[56]	train-mlogloss:0.96079	validation-mlogloss:0.94341
[57]	train-mlogloss:0.95603	validation-mlogloss:0.93850
[58]	train-mlogloss:0.95133	validation-mlogloss:0.93354
[59]	train-mlogloss:0.94686	validation-mlogloss:0.92915
[60]	train-mlogloss:0.94218	validation-mlogloss:0.92444
[61]	train-mlogloss:0.93773	validation-mlogloss:0.92021
[62]	train-mlogloss:0.93330	validation-mlogloss:0.91570
[63]	train-mlogloss:0.92904	validation-mlogloss:0.91125
[64]	train-mlogloss:0.92507	validation-mlogloss:0.90721
[65]	train-mlogloss:0.92076	validation-mlogloss:0.90265
[66]	train-mlogloss:0.91661	validation-mlogloss:0.89828
[67]	train-mlogloss:0.91246	validation-mlogloss:0.89408
[68]	train-mlogloss:0.90833	validation-mlogloss:0.88966
[69]	train-mlogloss:0.90423	validation-mlogloss:0.88544
[70]	train-mlogloss:0.90031	validation-mlogloss:0.88163
[71]	train-mlogloss:0.89648	validation-mlogloss:0.87766
[72]	train-mlogloss:0.89245	validation-mlogloss:0.87347
[73]	train-mlogloss:0.88860	validation-mlogloss:0.86949
[74]	train-mlogloss:0.88474	validation-mlogloss:0.86531
[75]	train-mlogloss:0.88115	validation-mlogloss:0.86168
[76]	train-mlogloss:0.87734	validation-mlogloss:0.85782
[77]	train-mlogloss:0.87380	validation-mlogloss:0.85415
[78]	train-mlogloss:0.87012	validation-mlogloss:0.85014
[79]	train-mlogloss:0.86650	validation-mlogloss:0.84654
[80]	train-mlogloss:0.86286	validation-mlogloss:0.84290
[81]	train-mlogloss:0.85954	validation-mlogloss:0.83942
[82]	train-mlogloss:0.85602	validation-mlogloss:0.83594
[83]	train-mlogloss:0.85247	validation-mlogloss:0.83223
[84]	train-mlogloss:0.84916	validation-mlogloss:0.82882
[85]	train-mlogloss:0.84592	validation-mlogloss:0.82551
[86]	train-mlogloss:0.84265	validation-mlogloss:0.82205
[87]	train-mlogloss:0.83951	validation-mlogloss:0.81861
[88]	train-mlogloss:0.83647	validation-mlogloss:0.81540
[89]	train-mlogloss:0.83329	validation-mlogloss:0.81196
[90]	train-mlogloss:0.83003	validation-mlogloss:0.80857
[91]	train-mlogloss:0.82678	validation-mlogloss:0.80524
[92]	train-mlogloss:0.82379	validation-mlogloss:0.80217
[93]	train-mlogloss:0.82078	validation-mlogloss:0.79900
[94]	train-mlogloss:0.81784	validation-mlogloss:0.79598
[95]	train-mlogloss:0.81491	validation-mlogloss:0.79299
[96]	train-mlogloss:0.81196	validation-mlogloss:0.78991
[97]	train-mlogloss:0.80914	validation-mlogloss:0.78693
[98]	train-mlogloss:0.80629	validation-mlogloss:0.78398
[99]	train-mlogloss:0.80354	validation-mlogloss:0.78111
[100]	train-mlogloss:0.80071	validation-mlogloss:0.77818
[101]	train-mlogloss:0.79799	validation-mlogloss:0.77525
[102]	train-mlogloss:0.79517	validation-mlogloss:0.77234
[103]	train-mlogloss:0.79264	validation-mlogloss:0.76987
[104]	train-mlogloss:0.79000	validation-mlogloss:0.76711
[105]	train-mlogloss:0.78734	validation-mlogloss:0.76438
[106]	train-mlogloss:0.78468	validation-mlogloss:0.76159
[107]	train-mlogloss:0.78223	validation-mlogloss:0.75906
[108]	train-mlogloss:0.77991	validation-mlogloss:0.75666
[109]	train-mlogloss:0.77755	validation-mlogloss:0.75428
[110]	train-mlogloss:0.77503	validation-mlogloss:0.75166
[111]	train-mlogloss:0.77251	validation-mlogloss:0.74918
[112]	train-mlogloss:0.77017	validation-mlogloss:0.74670
[113]	train-mlogloss:0.76758	validation-mlogloss:0.74413
[114]	train-mlogloss:0.76506	validation-mlogloss:0.74154
[115]	train-mlogloss:0.76260	validation-mlogloss:0.73901
[116]	train-mlogloss:0.76032	validation-mlogloss:0.73669
[117]	train-mlogloss:0.75791	validation-mlogloss:0.73436
[118]	train-mlogloss:0.75545	validation-mlogloss:0.73197
[119]	train-mlogloss:0.75321	validation-mlogloss:0.72960
[120]	train-mlogloss:0.75098	validation-mlogloss:0.72740
[121]	train-mlogloss:0.74876	validation-mlogloss:0.72505
[122]	train-mlogloss:0.74648	validation-mlogloss:0.72275
[123]	train-mlogloss:0.74414	validation-mlogloss:0.72033
[124]	train-mlogloss:0.74187	validation-mlogloss:0.71802
[125]	train-mlogloss:0.73967	validation-mlogloss:0.71569
[126]	train-mlogloss:0.73760	validation-mlogloss:0.71349
[127]	train-mlogloss:0.73533	validation-mlogloss:0.71126
[128]	train-mlogloss:0.73318	validation-mlogloss:0.70907
[129]	train-mlogloss:0.73104	validation-mlogloss:0.70699
[130]	train-mlogloss:0.72913	validation-mlogloss:0.70496
[131]	train-mlogloss:0.72707	validation-mlogloss:0.70284
[132]	train-mlogloss:0.72521	validation-mlogloss:0.70097
[133]	train-mlogloss:0.72314	validation-mlogloss:0.69892
[134]	train-mlogloss:0.72111	validation-mlogloss:0.69684
[135]	train-mlogloss:0.71910	validation-mlogloss:0.69485
[136]	train-mlogloss:0.71710	validation-mlogloss:0.69284
[137]	train-mlogloss:0.71541	validation-mlogloss:0.69096
[138]	train-mlogloss:0.71347	validation-mlogloss:0.68894
[139]	train-mlogloss:0.71167	validation-mlogloss:0.68718
[140]	train-mlogloss:0.70997	validation-mlogloss:0.68539
[141]	train-mlogloss:0.70823	validation-mlogloss:0.68357
[142]	train-mlogloss:0.70634	validation-mlogloss:0.68161
[143]	train-mlogloss:0.70466	validation-mlogloss:0.67974
[144]	train-mlogloss:0.70289	validation-mlogloss:0.67792
[145]	train-mlogloss:0.70115	validation-mlogloss:0.67603
[146]	train-mlogloss:0.69939	validation-mlogloss:0.67432
[147]	train-mlogloss:0.69754	validation-mlogloss:0.67247
[148]	train-mlogloss:0.69580	validation-mlogloss:0.67075
[149]	train-mlogloss:0.69412	validation-mlogloss:0.66918
[150]	train-mlogloss:0.69236	validation-mlogloss:0.66756
[151]	train-mlogloss:0.69066	validation-mlogloss:0.66585
[152]	train-mlogloss:0.68925	validation-mlogloss:0.66441
[153]	train-mlogloss:0.68764	validation-mlogloss:0.66269
[154]	train-mlogloss:0.68600	validation-mlogloss:0.66113
[155]	train-mlogloss:0.68445	validation-mlogloss:0.65958
[156]	train-mlogloss:0.68286	validation-mlogloss:0.65799
[157]	train-mlogloss:0.68129	validation-mlogloss:0.65641
[158]	train-mlogloss:0.67979	validation-mlogloss:0.65484
[159]	train-mlogloss:0.67824	validation-mlogloss:0.65336
[160]	train-mlogloss:0.67661	validation-mlogloss:0.65152
[161]	train-mlogloss:0.67512	validation-mlogloss:0.64998
[162]	train-mlogloss:0.67359	validation-mlogloss:0.64834
[163]	train-mlogloss:0.67207	validation-mlogloss:0.64693
[164]	train-mlogloss:0.67052	validation-mlogloss:0.64535
[165]	train-mlogloss:0.66911	validation-mlogloss:0.64390
[166]	train-mlogloss:0.66765	validation-mlogloss:0.64251
[167]	train-mlogloss:0.66636	validation-mlogloss:0.64117
[168]	train-mlogloss:0.66501	validation-mlogloss:0.63981
[169]	train-mlogloss:0.66373	validation-mlogloss:0.63851
[170]	train-mlogloss:0.66241	validation-mlogloss:0.63715
[171]	train-mlogloss:0.66101	validation-mlogloss:0.63581
[172]	train-mlogloss:0.65973	validation-mlogloss:0.63448
[173]	train-mlogloss:0.65841	validation-mlogloss:0.63328
[174]	train-mlogloss:0.65713	validation-mlogloss:0.63198
[175]	train-mlogloss:0.65576	validation-mlogloss:0.63067
[176]	train-mlogloss:0.65458	validation-mlogloss:0.62933
[177]	train-mlogloss:0.65328	validation-mlogloss:0.62816
[178]	train-mlogloss:0.65202	validation-mlogloss:0.62694
[179]	train-mlogloss:0.65077	validation-mlogloss:0.62572
[180]	train-mlogloss:0.64974	validation-mlogloss:0.62462
[181]	train-mlogloss:0.64859	validation-mlogloss:0.62346
[182]	train-mlogloss:0.64733	validation-mlogloss:0.62228
[183]	train-mlogloss:0.64615	validation-mlogloss:0.62113
[184]	train-mlogloss:0.64494	validation-mlogloss:0.61995
[185]	train-mlogloss:0.64372	validation-mlogloss:0.61885
[186]	train-mlogloss:0.64257	validation-mlogloss:0.61761
[187]	train-mlogloss:0.64136	validation-mlogloss:0.61650
[188]	train-mlogloss:0.64030	validation-mlogloss:0.61540
[189]	train-mlogloss:0.63912	validation-mlogloss:0.61428
[190]	train-mlogloss:0.63801	validation-mlogloss:0.61322
[191]	train-mlogloss:0.63693	validation-mlogloss:0.61221
[192]	train-mlogloss:0.63590	validation-mlogloss:0.61107
[193]	train-mlogloss:0.63476	validation-mlogloss:0.60982
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[496]	train-mlogloss:0.51019	validation-mlogloss:0.49797
[497]	train-mlogloss:0.51002	validation-mlogloss:0.49777
[498]	train-mlogloss:0.50986	validation-mlogloss:0.49766
[499]	train-mlogloss:0.50979	validation-mlogloss:0.49756
[500]	train-mlogloss:0.50963	validation-mlogloss:0.49735
[501]	train-mlogloss:0.50954	validation-mlogloss:0.49728
[502]	train-mlogloss:0.50938	validation-mlogloss:0.49717
[503]	train-mlogloss:0.50927	validation-mlogloss:0.49703
[504]	train-mlogloss:0.50919	validation-mlogloss:0.49703
[505]	train-mlogloss:0.50911	validation-mlogloss:0.49696
[506]	train-mlogloss:0.50899	validation-mlogloss:0.49682
[507]	train-mlogloss:0.50889	validation-mlogloss:0.49665
[508]	train-mlogloss:0.50878	validation-mlogloss:0.49651
[509]	train-mlogloss:0.50871	validation-mlogloss:0.49643
[510]	train-mlogloss:0.50863	validation-mlogloss:0.49633
[511]	train-mlogloss:0.50852	validation-mlogloss:0.49625
[512]	train-mlogloss:0.50844	validation-mlogloss:0.49621
[513]	train-mlogloss:0.50836	validation-mlogloss:0.49618
[514]	train-mlogloss:0.50828	validation-mlogloss:0.49609
[515]	train-mlogloss:0.50822	validation-mlogloss:0.49603
[516]	train-mlogloss:0.50812	validation-mlogloss:0.49593
[517]	train-mlogloss:0.50802	validation-mlogloss:0.49593
[518]	train-mlogloss:0.50784	validation-mlogloss:0.49580
[519]	train-mlogloss:0.50774	validation-mlogloss:0.49570
[520]	train-mlogloss:0.50766	validation-mlogloss:0.49565
[521]	train-mlogloss:0.50754	validation-mlogloss:0.49558
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 1 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 78.96 [%]
Global accuracy score (test) = 79.23 [%]
Global F1 score (train) = 79.31 [%]
Global F1 score (test) = 79.73 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.70      0.66       350
MODERATE-INTENSITY       0.65      0.61      0.63       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.95      0.92      0.94       322

          accuracy                           0.79      1372
         macro avg       0.80      0.79      0.80      1372
      weighted avg       0.80      0.79      0.79      1372


Accuracy capturado en la ejecución 4: 79.23 [%]
F1-score capturado en la ejecución 4: 79.73 [%]

=== EJECUCIÓN 5 ===

--- TRAIN (ejecución 5) ---

--- TEST (ejecución 5) ---
2025-11-03 17:20:16.962456: 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`.
2025-11-03 17:20:16.974312: 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 00:00:1762186816.987999  328340 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186816.992377  328340 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186817.002716  328340 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186817.002745  328340 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186817.002748  328340 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186817.002750  328340 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:20:17.006050: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37456	validation-mlogloss:1.37398
[1]	train-mlogloss:1.36324	validation-mlogloss:1.36205
[2]	train-mlogloss:1.35181	validation-mlogloss:1.35017
[3]	train-mlogloss:1.34045	validation-mlogloss:1.33832
[4]	train-mlogloss:1.32972	validation-mlogloss:1.32707
[5]	train-mlogloss:1.31906	validation-mlogloss:1.31608
[6]	train-mlogloss:1.30842	validation-mlogloss:1.30490
[7]	train-mlogloss:1.29843	validation-mlogloss:1.29488
[8]	train-mlogloss:1.28863	validation-mlogloss:1.28469
[9]	train-mlogloss:1.27866	validation-mlogloss:1.27442
[10]	train-mlogloss:1.26900	validation-mlogloss:1.26416
[11]	train-mlogloss:1.25972	validation-mlogloss:1.25483
[12]	train-mlogloss:1.25034	validation-mlogloss:1.24509
[13]	train-mlogloss:1.24098	validation-mlogloss:1.23525
[14]	train-mlogloss:1.23187	validation-mlogloss:1.22560
[15]	train-mlogloss:1.22287	validation-mlogloss:1.21604
[16]	train-mlogloss:1.21413	validation-mlogloss:1.20685
[17]	train-mlogloss:1.20559	validation-mlogloss:1.19801
[18]	train-mlogloss:1.19766	validation-mlogloss:1.18973
[19]	train-mlogloss:1.18942	validation-mlogloss:1.18107
[20]	train-mlogloss:1.18132	validation-mlogloss:1.17251
[21]	train-mlogloss:1.17350	validation-mlogloss:1.16428
[22]	train-mlogloss:1.16571	validation-mlogloss:1.15595
[23]	train-mlogloss:1.15805	validation-mlogloss:1.14793
[24]	train-mlogloss:1.15049	validation-mlogloss:1.14001
[25]	train-mlogloss:1.14328	validation-mlogloss:1.13234
[26]	train-mlogloss:1.13616	validation-mlogloss:1.12518
[27]	train-mlogloss:1.12906	validation-mlogloss:1.11781
[28]	train-mlogloss:1.12180	validation-mlogloss:1.11038
[29]	train-mlogloss:1.11468	validation-mlogloss:1.10302
[30]	train-mlogloss:1.10794	validation-mlogloss:1.09611
[31]	train-mlogloss:1.10115	validation-mlogloss:1.08912
[32]	train-mlogloss:1.09461	validation-mlogloss:1.08235
[33]	train-mlogloss:1.08803	validation-mlogloss:1.07557
[34]	train-mlogloss:1.08146	validation-mlogloss:1.06859
[35]	train-mlogloss:1.07511	validation-mlogloss:1.06182
[36]	train-mlogloss:1.06889	validation-mlogloss:1.05526
[37]	train-mlogloss:1.06276	validation-mlogloss:1.04894
[38]	train-mlogloss:1.05677	validation-mlogloss:1.04265
[39]	train-mlogloss:1.05093	validation-mlogloss:1.03650
[40]	train-mlogloss:1.04509	validation-mlogloss:1.03025
[41]	train-mlogloss:1.03915	validation-mlogloss:1.02420
[42]	train-mlogloss:1.03346	validation-mlogloss:1.01830
[43]	train-mlogloss:1.02763	validation-mlogloss:1.01224
[44]	train-mlogloss:1.02210	validation-mlogloss:1.00671
[45]	train-mlogloss:1.01644	validation-mlogloss:1.00077
[46]	train-mlogloss:1.01083	validation-mlogloss:0.99487
[47]	train-mlogloss:1.00515	validation-mlogloss:0.98925
[48]	train-mlogloss:0.99994	validation-mlogloss:0.98383
[49]	train-mlogloss:0.99448	validation-mlogloss:0.97846
[50]	train-mlogloss:0.98919	validation-mlogloss:0.97299
[51]	train-mlogloss:0.98417	validation-mlogloss:0.96757
[52]	train-mlogloss:0.97945	validation-mlogloss:0.96280
[53]	train-mlogloss:0.97461	validation-mlogloss:0.95796
[54]	train-mlogloss:0.96968	validation-mlogloss:0.95297
[55]	train-mlogloss:0.96494	validation-mlogloss:0.94804
[56]	train-mlogloss:0.96010	validation-mlogloss:0.94298
[57]	train-mlogloss:0.95542	validation-mlogloss:0.93804
[58]	train-mlogloss:0.95039	validation-mlogloss:0.93305
[59]	train-mlogloss:0.94579	validation-mlogloss:0.92827
[60]	train-mlogloss:0.94148	validation-mlogloss:0.92380
[61]	train-mlogloss:0.93713	validation-mlogloss:0.91953
[62]	train-mlogloss:0.93274	validation-mlogloss:0.91503
[63]	train-mlogloss:0.92851	validation-mlogloss:0.91094
[64]	train-mlogloss:0.92416	validation-mlogloss:0.90632
[65]	train-mlogloss:0.91976	validation-mlogloss:0.90187
[66]	train-mlogloss:0.91571	validation-mlogloss:0.89780
[67]	train-mlogloss:0.91138	validation-mlogloss:0.89326
[68]	train-mlogloss:0.90739	validation-mlogloss:0.88918
[69]	train-mlogloss:0.90324	validation-mlogloss:0.88480
[70]	train-mlogloss:0.89943	validation-mlogloss:0.88094
[71]	train-mlogloss:0.89548	validation-mlogloss:0.87693
[72]	train-mlogloss:0.89165	validation-mlogloss:0.87278
[73]	train-mlogloss:0.88770	validation-mlogloss:0.86869
[74]	train-mlogloss:0.88402	validation-mlogloss:0.86502
[75]	train-mlogloss:0.88025	validation-mlogloss:0.86110
[76]	train-mlogloss:0.87676	validation-mlogloss:0.85753
[77]	train-mlogloss:0.87316	validation-mlogloss:0.85394
[78]	train-mlogloss:0.86969	validation-mlogloss:0.85057
[79]	train-mlogloss:0.86613	validation-mlogloss:0.84677
[80]	train-mlogloss:0.86257	validation-mlogloss:0.84305
[81]	train-mlogloss:0.85897	validation-mlogloss:0.83935
[82]	train-mlogloss:0.85544	validation-mlogloss:0.83561
[83]	train-mlogloss:0.85207	validation-mlogloss:0.83214
[84]	train-mlogloss:0.84883	validation-mlogloss:0.82873
[85]	train-mlogloss:0.84549	validation-mlogloss:0.82538
[86]	train-mlogloss:0.84228	validation-mlogloss:0.82213
[87]	train-mlogloss:0.83897	validation-mlogloss:0.81855
[88]	train-mlogloss:0.83578	validation-mlogloss:0.81530
[89]	train-mlogloss:0.83271	validation-mlogloss:0.81217
[90]	train-mlogloss:0.82965	validation-mlogloss:0.80915
[91]	train-mlogloss:0.82641	validation-mlogloss:0.80591
[92]	train-mlogloss:0.82335	validation-mlogloss:0.80276
[93]	train-mlogloss:0.82038	validation-mlogloss:0.79985
[94]	train-mlogloss:0.81739	validation-mlogloss:0.79672
[95]	train-mlogloss:0.81453	validation-mlogloss:0.79379
[96]	train-mlogloss:0.81173	validation-mlogloss:0.79086
[97]	train-mlogloss:0.80883	validation-mlogloss:0.78790
[98]	train-mlogloss:0.80609	validation-mlogloss:0.78496
[99]	train-mlogloss:0.80345	validation-mlogloss:0.78224
[100]	train-mlogloss:0.80066	validation-mlogloss:0.77926
[101]	train-mlogloss:0.79787	validation-mlogloss:0.77639
[102]	train-mlogloss:0.79528	validation-mlogloss:0.77389
[103]	train-mlogloss:0.79271	validation-mlogloss:0.77120
[104]	train-mlogloss:0.78994	validation-mlogloss:0.76829
[105]	train-mlogloss:0.78733	validation-mlogloss:0.76567
[106]	train-mlogloss:0.78471	validation-mlogloss:0.76290
[107]	train-mlogloss:0.78213	validation-mlogloss:0.76022
[108]	train-mlogloss:0.77944	validation-mlogloss:0.75745
[109]	train-mlogloss:0.77718	validation-mlogloss:0.75522
[110]	train-mlogloss:0.77475	validation-mlogloss:0.75271
[111]	train-mlogloss:0.77234	validation-mlogloss:0.75016
[112]	train-mlogloss:0.76986	validation-mlogloss:0.74748
[113]	train-mlogloss:0.76730	validation-mlogloss:0.74494
[114]	train-mlogloss:0.76498	validation-mlogloss:0.74255
[115]	train-mlogloss:0.76249	validation-mlogloss:0.74007
[116]	train-mlogloss:0.76000	validation-mlogloss:0.73755
[117]	train-mlogloss:0.75770	validation-mlogloss:0.73508
[118]	train-mlogloss:0.75521	validation-mlogloss:0.73265
[119]	train-mlogloss:0.75304	validation-mlogloss:0.73034
[120]	train-mlogloss:0.75065	validation-mlogloss:0.72810
[121]	train-mlogloss:0.74846	validation-mlogloss:0.72576
[122]	train-mlogloss:0.74620	validation-mlogloss:0.72348
[123]	train-mlogloss:0.74413	validation-mlogloss:0.72133
[124]	train-mlogloss:0.74187	validation-mlogloss:0.71913
[125]	train-mlogloss:0.73973	validation-mlogloss:0.71689
[126]	train-mlogloss:0.73783	validation-mlogloss:0.71500
[127]	train-mlogloss:0.73562	validation-mlogloss:0.71270
[128]	train-mlogloss:0.73376	validation-mlogloss:0.71080
[129]	train-mlogloss:0.73179	validation-mlogloss:0.70882
[130]	train-mlogloss:0.72968	validation-mlogloss:0.70676
[131]	train-mlogloss:0.72756	validation-mlogloss:0.70466
[132]	train-mlogloss:0.72546	validation-mlogloss:0.70255
[133]	train-mlogloss:0.72351	validation-mlogloss:0.70053
[134]	train-mlogloss:0.72177	validation-mlogloss:0.69875
[135]	train-mlogloss:0.71981	validation-mlogloss:0.69687
[136]	train-mlogloss:0.71801	validation-mlogloss:0.69509
[137]	train-mlogloss:0.71613	validation-mlogloss:0.69319
[138]	train-mlogloss:0.71423	validation-mlogloss:0.69130
[139]	train-mlogloss:0.71253	validation-mlogloss:0.68958
[140]	train-mlogloss:0.71074	validation-mlogloss:0.68775
[141]	train-mlogloss:0.70889	validation-mlogloss:0.68588
[142]	train-mlogloss:0.70703	validation-mlogloss:0.68399
[143]	train-mlogloss:0.70515	validation-mlogloss:0.68221
[144]	train-mlogloss:0.70327	validation-mlogloss:0.68026
[145]	train-mlogloss:0.70147	validation-mlogloss:0.67830
[146]	train-mlogloss:0.69967	validation-mlogloss:0.67643
[147]	train-mlogloss:0.69793	validation-mlogloss:0.67474
[148]	train-mlogloss:0.69635	validation-mlogloss:0.67322
[149]	train-mlogloss:0.69484	validation-mlogloss:0.67167
[150]	train-mlogloss:0.69309	validation-mlogloss:0.66995
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[453]	train-mlogloss:0.51675	validation-mlogloss:0.50347
[454]	train-mlogloss:0.51659	validation-mlogloss:0.50336
[455]	train-mlogloss:0.51648	validation-mlogloss:0.50325
[456]	train-mlogloss:0.51635	validation-mlogloss:0.50309
[457]	train-mlogloss:0.51612	validation-mlogloss:0.50286
[458]	train-mlogloss:0.51599	validation-mlogloss:0.50283
[459]	train-mlogloss:0.51582	validation-mlogloss:0.50272
[460]	train-mlogloss:0.51570	validation-mlogloss:0.50260
[461]	train-mlogloss:0.51560	validation-mlogloss:0.50258
[462]	train-mlogloss:0.51554	validation-mlogloss:0.50254
[463]	train-mlogloss:0.51539	validation-mlogloss:0.50239
[464]	train-mlogloss:0.51526	validation-mlogloss:0.50231
[465]	train-mlogloss:0.51508	validation-mlogloss:0.50212
[466]	train-mlogloss:0.51491	validation-mlogloss:0.50191
[467]	train-mlogloss:0.51475	validation-mlogloss:0.50174
[468]	train-mlogloss:0.51466	validation-mlogloss:0.50174
[469]	train-mlogloss:0.51455	validation-mlogloss:0.50160
[470]	train-mlogloss:0.51439	validation-mlogloss:0.50148
[471]	train-mlogloss:0.51427	validation-mlogloss:0.50135
[472]	train-mlogloss:0.51415	validation-mlogloss:0.50121
[473]	train-mlogloss:0.51400	validation-mlogloss:0.50111
[474]	train-mlogloss:0.51387	validation-mlogloss:0.50102
[475]	train-mlogloss:0.51374	validation-mlogloss:0.50087
[476]	train-mlogloss:0.51362	validation-mlogloss:0.50076
[477]	train-mlogloss:0.51346	validation-mlogloss:0.50062
[478]	train-mlogloss:0.51336	validation-mlogloss:0.50056
[479]	train-mlogloss:0.51325	validation-mlogloss:0.50052
[480]	train-mlogloss:0.51318	validation-mlogloss:0.50048
[481]	train-mlogloss:0.51305	validation-mlogloss:0.50034
[482]	train-mlogloss:0.51292	validation-mlogloss:0.50030
[483]	train-mlogloss:0.51280	validation-mlogloss:0.50015
[484]	train-mlogloss:0.51270	validation-mlogloss:0.50005
[485]	train-mlogloss:0.51258	validation-mlogloss:0.49995
[486]	train-mlogloss:0.51249	validation-mlogloss:0.49994
[487]	train-mlogloss:0.51238	validation-mlogloss:0.49982
[488]	train-mlogloss:0.51230	validation-mlogloss:0.49975
[489]	train-mlogloss:0.51220	validation-mlogloss:0.49969
[490]	train-mlogloss:0.51206	validation-mlogloss:0.49957
[491]	train-mlogloss:0.51203	validation-mlogloss:0.49955
[492]	train-mlogloss:0.51188	validation-mlogloss:0.49946
[493]	train-mlogloss:0.51173	validation-mlogloss:0.49935
[494]	train-mlogloss:0.51153	validation-mlogloss:0.49917
[495]	train-mlogloss:0.51135	validation-mlogloss:0.49900
[496]	train-mlogloss:0.51127	validation-mlogloss:0.49897
[497]	train-mlogloss:0.51115	validation-mlogloss:0.49889
[498]	train-mlogloss:0.51106	validation-mlogloss:0.49882
[499]	train-mlogloss:0.51096	validation-mlogloss:0.49870
[500]	train-mlogloss:0.51089	validation-mlogloss:0.49863
[501]	train-mlogloss:0.51076	validation-mlogloss:0.49853
[502]	train-mlogloss:0.51064	validation-mlogloss:0.49835
[503]	train-mlogloss:0.51052	validation-mlogloss:0.49822
[504]	train-mlogloss:0.51038	validation-mlogloss:0.49819
[505]	train-mlogloss:0.51027	validation-mlogloss:0.49807
[506]	train-mlogloss:0.51015	validation-mlogloss:0.49794
[507]	train-mlogloss:0.51007	validation-mlogloss:0.49786
[508]	train-mlogloss:0.50996	validation-mlogloss:0.49784
[509]	train-mlogloss:0.50987	validation-mlogloss:0.49771
[510]	train-mlogloss:0.50976	validation-mlogloss:0.49766
[511]	train-mlogloss:0.50962	validation-mlogloss:0.49755
[512]	train-mlogloss:0.50949	validation-mlogloss:0.49745
[513]	train-mlogloss:0.50934	validation-mlogloss:0.49730
[514]	train-mlogloss:0.50926	validation-mlogloss:0.49725
[515]	train-mlogloss:0.50915	validation-mlogloss:0.49709
[516]	train-mlogloss:0.50902	validation-mlogloss:0.49698
[517]	train-mlogloss:0.50899	validation-mlogloss:0.49695
[518]	train-mlogloss:0.50891	validation-mlogloss:0.49691
[519]	train-mlogloss:0.50881	validation-mlogloss:0.49679
[520]	train-mlogloss:0.50873	validation-mlogloss:0.49668
[521]	train-mlogloss:0.50862	validation-mlogloss:0.49658
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 0 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.57 [%]
Global accuracy score (test) = 80.69 [%]
Global F1 score (train) = 79.95 [%]
Global F1 score (test) = 81.26 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.64      0.71      0.67       350
MODERATE-INTENSITY       0.67      0.66      0.66       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.97      0.92      0.95       322

          accuracy                           0.81      1372
         macro avg       0.82      0.81      0.81      1372
      weighted avg       0.81      0.81      0.81      1372


Accuracy capturado en la ejecución 5: 80.69 [%]
F1-score capturado en la ejecución 5: 81.26 [%]

=== EJECUCIÓN 6 ===

--- TRAIN (ejecución 6) ---

--- TEST (ejecución 6) ---
2025-11-03 17:20:35.709482: 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`.
2025-11-03 17:20:35.721071: 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 00:00:1762186835.734638  328644 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186835.738906  328644 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186835.749002  328644 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186835.749026  328644 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186835.749029  328644 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186835.749030  328644 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:20:35.752376: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37463	validation-mlogloss:1.37424
[1]	train-mlogloss:1.36302	validation-mlogloss:1.36197
[2]	train-mlogloss:1.35171	validation-mlogloss:1.35021
[3]	train-mlogloss:1.34083	validation-mlogloss:1.33897
[4]	train-mlogloss:1.33000	validation-mlogloss:1.32763
[5]	train-mlogloss:1.31925	validation-mlogloss:1.31646
[6]	train-mlogloss:1.30870	validation-mlogloss:1.30584
[7]	train-mlogloss:1.29834	validation-mlogloss:1.29488
[8]	train-mlogloss:1.28800	validation-mlogloss:1.28406
[9]	train-mlogloss:1.27817	validation-mlogloss:1.27381
[10]	train-mlogloss:1.26883	validation-mlogloss:1.26408
[11]	train-mlogloss:1.25922	validation-mlogloss:1.25428
[12]	train-mlogloss:1.24987	validation-mlogloss:1.24440
[13]	train-mlogloss:1.24063	validation-mlogloss:1.23472
[14]	train-mlogloss:1.23176	validation-mlogloss:1.22550
[15]	train-mlogloss:1.22285	validation-mlogloss:1.21609
[16]	train-mlogloss:1.21437	validation-mlogloss:1.20727
[17]	train-mlogloss:1.20582	validation-mlogloss:1.19836
[18]	train-mlogloss:1.19743	validation-mlogloss:1.18983
[19]	train-mlogloss:1.18936	validation-mlogloss:1.18140
[20]	train-mlogloss:1.18141	validation-mlogloss:1.17322
[21]	train-mlogloss:1.17343	validation-mlogloss:1.16469
[22]	train-mlogloss:1.16561	validation-mlogloss:1.15679
[23]	train-mlogloss:1.15803	validation-mlogloss:1.14886
[24]	train-mlogloss:1.15051	validation-mlogloss:1.14100
[25]	train-mlogloss:1.14334	validation-mlogloss:1.13380
[26]	train-mlogloss:1.13599	validation-mlogloss:1.12620
[27]	train-mlogloss:1.12887	validation-mlogloss:1.11883
[28]	train-mlogloss:1.12179	validation-mlogloss:1.11138
[29]	train-mlogloss:1.11480	validation-mlogloss:1.10399
[30]	train-mlogloss:1.10801	validation-mlogloss:1.09696
[31]	train-mlogloss:1.10129	validation-mlogloss:1.08993
[32]	train-mlogloss:1.09451	validation-mlogloss:1.08280
[33]	train-mlogloss:1.08806	validation-mlogloss:1.07623
[34]	train-mlogloss:1.08158	validation-mlogloss:1.06949
[35]	train-mlogloss:1.07532	validation-mlogloss:1.06306
[36]	train-mlogloss:1.06912	validation-mlogloss:1.05655
[37]	train-mlogloss:1.06285	validation-mlogloss:1.05027
[38]	train-mlogloss:1.05668	validation-mlogloss:1.04411
[39]	train-mlogloss:1.05061	validation-mlogloss:1.03765
[40]	train-mlogloss:1.04449	validation-mlogloss:1.03127
[41]	train-mlogloss:1.03869	validation-mlogloss:1.02552
[42]	train-mlogloss:1.03286	validation-mlogloss:1.01958
[43]	train-mlogloss:1.02724	validation-mlogloss:1.01358
[44]	train-mlogloss:1.02157	validation-mlogloss:1.00778
[45]	train-mlogloss:1.01620	validation-mlogloss:1.00206
[46]	train-mlogloss:1.01080	validation-mlogloss:0.99677
[47]	train-mlogloss:1.00562	validation-mlogloss:0.99133
[48]	train-mlogloss:1.00035	validation-mlogloss:0.98583
[49]	train-mlogloss:0.99521	validation-mlogloss:0.98048
[50]	train-mlogloss:0.98992	validation-mlogloss:0.97520
[51]	train-mlogloss:0.98471	validation-mlogloss:0.96983
[52]	train-mlogloss:0.97963	validation-mlogloss:0.96484
[53]	train-mlogloss:0.97454	validation-mlogloss:0.95975
[54]	train-mlogloss:0.96968	validation-mlogloss:0.95483
[55]	train-mlogloss:0.96476	validation-mlogloss:0.94978
[56]	train-mlogloss:0.96002	validation-mlogloss:0.94480
[57]	train-mlogloss:0.95527	validation-mlogloss:0.94001
[58]	train-mlogloss:0.95049	validation-mlogloss:0.93507
[59]	train-mlogloss:0.94579	validation-mlogloss:0.93035
[60]	train-mlogloss:0.94111	validation-mlogloss:0.92556
[61]	train-mlogloss:0.93682	validation-mlogloss:0.92107
[62]	train-mlogloss:0.93246	validation-mlogloss:0.91670
[63]	train-mlogloss:0.92789	validation-mlogloss:0.91190
[64]	train-mlogloss:0.92359	validation-mlogloss:0.90757
[65]	train-mlogloss:0.91941	validation-mlogloss:0.90329
[66]	train-mlogloss:0.91509	validation-mlogloss:0.89875
[67]	train-mlogloss:0.91093	validation-mlogloss:0.89461
[68]	train-mlogloss:0.90675	validation-mlogloss:0.89046
[69]	train-mlogloss:0.90286	validation-mlogloss:0.88655
[70]	train-mlogloss:0.89906	validation-mlogloss:0.88270
[71]	train-mlogloss:0.89503	validation-mlogloss:0.87863
[72]	train-mlogloss:0.89107	validation-mlogloss:0.87451
[73]	train-mlogloss:0.88723	validation-mlogloss:0.87044
[74]	train-mlogloss:0.88346	validation-mlogloss:0.86667
[75]	train-mlogloss:0.87964	validation-mlogloss:0.86280
[76]	train-mlogloss:0.87592	validation-mlogloss:0.85902
[77]	train-mlogloss:0.87219	validation-mlogloss:0.85508
[78]	train-mlogloss:0.86854	validation-mlogloss:0.85154
[79]	train-mlogloss:0.86503	validation-mlogloss:0.84800
[80]	train-mlogloss:0.86152	validation-mlogloss:0.84461
[81]	train-mlogloss:0.85811	validation-mlogloss:0.84118
[82]	train-mlogloss:0.85463	validation-mlogloss:0.83776
[83]	train-mlogloss:0.85122	validation-mlogloss:0.83419
[84]	train-mlogloss:0.84795	validation-mlogloss:0.83097
[85]	train-mlogloss:0.84469	validation-mlogloss:0.82769
[86]	train-mlogloss:0.84139	validation-mlogloss:0.82422
[87]	train-mlogloss:0.83832	validation-mlogloss:0.82119
[88]	train-mlogloss:0.83521	validation-mlogloss:0.81806
[89]	train-mlogloss:0.83202	validation-mlogloss:0.81463
[90]	train-mlogloss:0.82889	validation-mlogloss:0.81134
[91]	train-mlogloss:0.82557	validation-mlogloss:0.80803
[92]	train-mlogloss:0.82258	validation-mlogloss:0.80496
[93]	train-mlogloss:0.81949	validation-mlogloss:0.80168
[94]	train-mlogloss:0.81642	validation-mlogloss:0.79854
[95]	train-mlogloss:0.81352	validation-mlogloss:0.79557
[96]	train-mlogloss:0.81042	validation-mlogloss:0.79251
[97]	train-mlogloss:0.80761	validation-mlogloss:0.78959
[98]	train-mlogloss:0.80478	validation-mlogloss:0.78682
[99]	train-mlogloss:0.80201	validation-mlogloss:0.78403
[100]	train-mlogloss:0.79932	validation-mlogloss:0.78132
[101]	train-mlogloss:0.79667	validation-mlogloss:0.77872
[102]	train-mlogloss:0.79403	validation-mlogloss:0.77598
[103]	train-mlogloss:0.79121	validation-mlogloss:0.77303
[104]	train-mlogloss:0.78857	validation-mlogloss:0.77024
[105]	train-mlogloss:0.78592	validation-mlogloss:0.76746
[106]	train-mlogloss:0.78304	validation-mlogloss:0.76447
[107]	train-mlogloss:0.78056	validation-mlogloss:0.76177
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[410]	train-mlogloss:0.51877	validation-mlogloss:0.51405
[411]	train-mlogloss:0.51856	validation-mlogloss:0.51386
[412]	train-mlogloss:0.51839	validation-mlogloss:0.51379
[413]	train-mlogloss:0.51818	validation-mlogloss:0.51355
[414]	train-mlogloss:0.51793	validation-mlogloss:0.51329
[415]	train-mlogloss:0.51775	validation-mlogloss:0.51318
[416]	train-mlogloss:0.51745	validation-mlogloss:0.51289
[417]	train-mlogloss:0.51727	validation-mlogloss:0.51279
[418]	train-mlogloss:0.51708	validation-mlogloss:0.51265
[419]	train-mlogloss:0.51688	validation-mlogloss:0.51250
[420]	train-mlogloss:0.51670	validation-mlogloss:0.51236
[421]	train-mlogloss:0.51643	validation-mlogloss:0.51214
[422]	train-mlogloss:0.51624	validation-mlogloss:0.51198
[423]	train-mlogloss:0.51611	validation-mlogloss:0.51188
[424]	train-mlogloss:0.51593	validation-mlogloss:0.51171
[425]	train-mlogloss:0.51568	validation-mlogloss:0.51152
[426]	train-mlogloss:0.51549	validation-mlogloss:0.51140
[427]	train-mlogloss:0.51533	validation-mlogloss:0.51129
[428]	train-mlogloss:0.51511	validation-mlogloss:0.51110
[429]	train-mlogloss:0.51485	validation-mlogloss:0.51100
[430]	train-mlogloss:0.51467	validation-mlogloss:0.51084
[431]	train-mlogloss:0.51450	validation-mlogloss:0.51068
[432]	train-mlogloss:0.51423	validation-mlogloss:0.51064
[433]	train-mlogloss:0.51397	validation-mlogloss:0.51039
[434]	train-mlogloss:0.51384	validation-mlogloss:0.51024
[435]	train-mlogloss:0.51363	validation-mlogloss:0.51009
[436]	train-mlogloss:0.51347	validation-mlogloss:0.50998
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[438]	train-mlogloss:0.51314	validation-mlogloss:0.50967
[439]	train-mlogloss:0.51300	validation-mlogloss:0.50954
[440]	train-mlogloss:0.51283	validation-mlogloss:0.50949
[441]	train-mlogloss:0.51263	validation-mlogloss:0.50931
[442]	train-mlogloss:0.51252	validation-mlogloss:0.50917
[443]	train-mlogloss:0.51242	validation-mlogloss:0.50909
[444]	train-mlogloss:0.51224	validation-mlogloss:0.50900
[445]	train-mlogloss:0.51212	validation-mlogloss:0.50896
[446]	train-mlogloss:0.51198	validation-mlogloss:0.50880
[447]	train-mlogloss:0.51184	validation-mlogloss:0.50878
[448]	train-mlogloss:0.51175	validation-mlogloss:0.50867
[449]	train-mlogloss:0.51162	validation-mlogloss:0.50857
[450]	train-mlogloss:0.51151	validation-mlogloss:0.50844
[451]	train-mlogloss:0.51136	validation-mlogloss:0.50834
[452]	train-mlogloss:0.51121	validation-mlogloss:0.50821
[453]	train-mlogloss:0.51104	validation-mlogloss:0.50811
[454]	train-mlogloss:0.51092	validation-mlogloss:0.50802
[455]	train-mlogloss:0.51082	validation-mlogloss:0.50790
[456]	train-mlogloss:0.51062	validation-mlogloss:0.50774
[457]	train-mlogloss:0.51047	validation-mlogloss:0.50758
[458]	train-mlogloss:0.51029	validation-mlogloss:0.50740
[459]	train-mlogloss:0.51010	validation-mlogloss:0.50726
[460]	train-mlogloss:0.50990	validation-mlogloss:0.50707
[461]	train-mlogloss:0.50979	validation-mlogloss:0.50696
[462]	train-mlogloss:0.50967	validation-mlogloss:0.50683
[463]	train-mlogloss:0.50953	validation-mlogloss:0.50674
[464]	train-mlogloss:0.50936	validation-mlogloss:0.50663
[465]	train-mlogloss:0.50923	validation-mlogloss:0.50648
[466]	train-mlogloss:0.50914	validation-mlogloss:0.50639
[467]	train-mlogloss:0.50901	validation-mlogloss:0.50630
[468]	train-mlogloss:0.50879	validation-mlogloss:0.50618
[469]	train-mlogloss:0.50866	validation-mlogloss:0.50600
[470]	train-mlogloss:0.50854	validation-mlogloss:0.50587
[471]	train-mlogloss:0.50844	validation-mlogloss:0.50579
[472]	train-mlogloss:0.50834	validation-mlogloss:0.50570
[473]	train-mlogloss:0.50820	validation-mlogloss:0.50562
[474]	train-mlogloss:0.50808	validation-mlogloss:0.50548
[475]	train-mlogloss:0.50799	validation-mlogloss:0.50545
[476]	train-mlogloss:0.50788	validation-mlogloss:0.50536
[477]	train-mlogloss:0.50779	validation-mlogloss:0.50525
[478]	train-mlogloss:0.50765	validation-mlogloss:0.50505
[479]	train-mlogloss:0.50753	validation-mlogloss:0.50493
[480]	train-mlogloss:0.50736	validation-mlogloss:0.50474
[481]	train-mlogloss:0.50713	validation-mlogloss:0.50456
[482]	train-mlogloss:0.50705	validation-mlogloss:0.50449
[483]	train-mlogloss:0.50697	validation-mlogloss:0.50441
[484]	train-mlogloss:0.50684	validation-mlogloss:0.50429
[485]	train-mlogloss:0.50674	validation-mlogloss:0.50422
[486]	train-mlogloss:0.50659	validation-mlogloss:0.50401
[487]	train-mlogloss:0.50641	validation-mlogloss:0.50390
[488]	train-mlogloss:0.50629	validation-mlogloss:0.50380
[489]	train-mlogloss:0.50618	validation-mlogloss:0.50370
[490]	train-mlogloss:0.50610	validation-mlogloss:0.50360
[491]	train-mlogloss:0.50601	validation-mlogloss:0.50348
[492]	train-mlogloss:0.50586	validation-mlogloss:0.50336
[493]	train-mlogloss:0.50578	validation-mlogloss:0.50331
[494]	train-mlogloss:0.50567	validation-mlogloss:0.50325
[495]	train-mlogloss:0.50558	validation-mlogloss:0.50317
[496]	train-mlogloss:0.50547	validation-mlogloss:0.50311
[497]	train-mlogloss:0.50534	validation-mlogloss:0.50300
[498]	train-mlogloss:0.50524	validation-mlogloss:0.50288
[499]	train-mlogloss:0.50513	validation-mlogloss:0.50279
[500]	train-mlogloss:0.50501	validation-mlogloss:0.50269
[501]	train-mlogloss:0.50490	validation-mlogloss:0.50258
[502]	train-mlogloss:0.50482	validation-mlogloss:0.50254
[503]	train-mlogloss:0.50470	validation-mlogloss:0.50239
[504]	train-mlogloss:0.50462	validation-mlogloss:0.50239
[505]	train-mlogloss:0.50448	validation-mlogloss:0.50228
[506]	train-mlogloss:0.50438	validation-mlogloss:0.50224
[507]	train-mlogloss:0.50431	validation-mlogloss:0.50216
[508]	train-mlogloss:0.50425	validation-mlogloss:0.50212
[509]	train-mlogloss:0.50414	validation-mlogloss:0.50197
[510]	train-mlogloss:0.50404	validation-mlogloss:0.50187
[511]	train-mlogloss:0.50389	validation-mlogloss:0.50178
[512]	train-mlogloss:0.50375	validation-mlogloss:0.50163
[513]	train-mlogloss:0.50369	validation-mlogloss:0.50160
[514]	train-mlogloss:0.50360	validation-mlogloss:0.50156
[515]	train-mlogloss:0.50353	validation-mlogloss:0.50147
[516]	train-mlogloss:0.50345	validation-mlogloss:0.50138
[517]	train-mlogloss:0.50330	validation-mlogloss:0.50132
[518]	train-mlogloss:0.50323	validation-mlogloss:0.50125
[519]	train-mlogloss:0.50314	validation-mlogloss:0.50119
[520]	train-mlogloss:0.50302	validation-mlogloss:0.50115
[521]	train-mlogloss:0.50294	validation-mlogloss:0.50113
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 0 1 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 78.97 [%]
Global accuracy score (test) = 80.17 [%]
Global F1 score (train) = 79.25 [%]
Global F1 score (test) = 80.78 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.71      0.67       350
MODERATE-INTENSITY       0.67      0.64      0.65       350
         SEDENTARY       0.99      0.94      0.96       350
VIGOROUS-INTENSITY       0.97      0.92      0.95       322

          accuracy                           0.80      1372
         macro avg       0.81      0.80      0.81      1372
      weighted avg       0.81      0.80      0.81      1372


Accuracy capturado en la ejecución 6: 80.17 [%]
F1-score capturado en la ejecución 6: 80.78 [%]

=== EJECUCIÓN 7 ===

--- TRAIN (ejecución 7) ---

--- TEST (ejecución 7) ---
2025-11-03 17:20:54.191201: 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`.
2025-11-03 17:20:54.202992: 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 00:00:1762186854.217172  328962 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186854.221768  328962 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186854.232136  328962 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186854.232166  328962 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186854.232170  328962 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186854.232172  328962 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:20:54.235612: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37461	validation-mlogloss:1.37409
[1]	train-mlogloss:1.36309	validation-mlogloss:1.36226
[2]	train-mlogloss:1.35175	validation-mlogloss:1.35039
[3]	train-mlogloss:1.34113	validation-mlogloss:1.33946
[4]	train-mlogloss:1.33029	validation-mlogloss:1.32843
[5]	train-mlogloss:1.31969	validation-mlogloss:1.31746
[6]	train-mlogloss:1.30932	validation-mlogloss:1.30680
[7]	train-mlogloss:1.29915	validation-mlogloss:1.29629
[8]	train-mlogloss:1.28907	validation-mlogloss:1.28579
[9]	train-mlogloss:1.27898	validation-mlogloss:1.27529
[10]	train-mlogloss:1.26941	validation-mlogloss:1.26529
[11]	train-mlogloss:1.26022	validation-mlogloss:1.25594
[12]	train-mlogloss:1.25116	validation-mlogloss:1.24654
[13]	train-mlogloss:1.24198	validation-mlogloss:1.23684
[14]	train-mlogloss:1.23303	validation-mlogloss:1.22730
[15]	train-mlogloss:1.22406	validation-mlogloss:1.21803
[16]	train-mlogloss:1.21553	validation-mlogloss:1.20925
[17]	train-mlogloss:1.20712	validation-mlogloss:1.20031
[18]	train-mlogloss:1.19844	validation-mlogloss:1.19109
[19]	train-mlogloss:1.18996	validation-mlogloss:1.18234
[20]	train-mlogloss:1.18207	validation-mlogloss:1.17428
[21]	train-mlogloss:1.17429	validation-mlogloss:1.16604
[22]	train-mlogloss:1.16663	validation-mlogloss:1.15799
[23]	train-mlogloss:1.15887	validation-mlogloss:1.14976
[24]	train-mlogloss:1.15129	validation-mlogloss:1.14179
[25]	train-mlogloss:1.14391	validation-mlogloss:1.13417
[26]	train-mlogloss:1.13672	validation-mlogloss:1.12647
[27]	train-mlogloss:1.12960	validation-mlogloss:1.11921
[28]	train-mlogloss:1.12265	validation-mlogloss:1.11207
[29]	train-mlogloss:1.11577	validation-mlogloss:1.10485
[30]	train-mlogloss:1.10891	validation-mlogloss:1.09756
[31]	train-mlogloss:1.10214	validation-mlogloss:1.09050
[32]	train-mlogloss:1.09532	validation-mlogloss:1.08323
[33]	train-mlogloss:1.08876	validation-mlogloss:1.07626
[34]	train-mlogloss:1.08232	validation-mlogloss:1.06952
[35]	train-mlogloss:1.07578	validation-mlogloss:1.06262
[36]	train-mlogloss:1.06965	validation-mlogloss:1.05613
[37]	train-mlogloss:1.06331	validation-mlogloss:1.04947
[38]	train-mlogloss:1.05733	validation-mlogloss:1.04335
[39]	train-mlogloss:1.05142	validation-mlogloss:1.03755
[40]	train-mlogloss:1.04551	validation-mlogloss:1.03139
[41]	train-mlogloss:1.03932	validation-mlogloss:1.02507
[42]	train-mlogloss:1.03345	validation-mlogloss:1.01899
[43]	train-mlogloss:1.02789	validation-mlogloss:1.01326
[44]	train-mlogloss:1.02226	validation-mlogloss:1.00760
[45]	train-mlogloss:1.01660	validation-mlogloss:1.00167
[46]	train-mlogloss:1.01124	validation-mlogloss:0.99620
[47]	train-mlogloss:1.00602	validation-mlogloss:0.99069
[48]	train-mlogloss:1.00059	validation-mlogloss:0.98497
[49]	train-mlogloss:0.99526	validation-mlogloss:0.97940
[50]	train-mlogloss:0.99009	validation-mlogloss:0.97413
[51]	train-mlogloss:0.98506	validation-mlogloss:0.96908
[52]	train-mlogloss:0.98020	validation-mlogloss:0.96385
[53]	train-mlogloss:0.97528	validation-mlogloss:0.95883
[54]	train-mlogloss:0.97024	validation-mlogloss:0.95366
[55]	train-mlogloss:0.96556	validation-mlogloss:0.94872
[56]	train-mlogloss:0.96065	validation-mlogloss:0.94374
[57]	train-mlogloss:0.95584	validation-mlogloss:0.93874
[58]	train-mlogloss:0.95108	validation-mlogloss:0.93386
[59]	train-mlogloss:0.94645	validation-mlogloss:0.92911
[60]	train-mlogloss:0.94195	validation-mlogloss:0.92459
[61]	train-mlogloss:0.93744	validation-mlogloss:0.92002
[62]	train-mlogloss:0.93293	validation-mlogloss:0.91533
[63]	train-mlogloss:0.92863	validation-mlogloss:0.91111
[64]	train-mlogloss:0.92422	validation-mlogloss:0.90652
[65]	train-mlogloss:0.91989	validation-mlogloss:0.90195
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[367]	train-mlogloss:0.52865	validation-mlogloss:0.51406
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[388]	train-mlogloss:0.52250	validation-mlogloss:0.50898
[389]	train-mlogloss:0.52218	validation-mlogloss:0.50870
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[391]	train-mlogloss:0.52160	validation-mlogloss:0.50831
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[400]	train-mlogloss:0.51923	validation-mlogloss:0.50652
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[408]	train-mlogloss:0.51760	validation-mlogloss:0.50499
[409]	train-mlogloss:0.51737	validation-mlogloss:0.50479
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[411]	train-mlogloss:0.51698	validation-mlogloss:0.50438
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[413]	train-mlogloss:0.51658	validation-mlogloss:0.50410
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[415]	train-mlogloss:0.51619	validation-mlogloss:0.50375
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[417]	train-mlogloss:0.51565	validation-mlogloss:0.50336
[418]	train-mlogloss:0.51543	validation-mlogloss:0.50320
[419]	train-mlogloss:0.51523	validation-mlogloss:0.50303
[420]	train-mlogloss:0.51502	validation-mlogloss:0.50290
[421]	train-mlogloss:0.51480	validation-mlogloss:0.50267
[422]	train-mlogloss:0.51464	validation-mlogloss:0.50256
[423]	train-mlogloss:0.51448	validation-mlogloss:0.50245
[424]	train-mlogloss:0.51428	validation-mlogloss:0.50225
[425]	train-mlogloss:0.51404	validation-mlogloss:0.50210
[426]	train-mlogloss:0.51379	validation-mlogloss:0.50197
[427]	train-mlogloss:0.51363	validation-mlogloss:0.50180
[428]	train-mlogloss:0.51344	validation-mlogloss:0.50156
[429]	train-mlogloss:0.51327	validation-mlogloss:0.50142
[430]	train-mlogloss:0.51306	validation-mlogloss:0.50118
[431]	train-mlogloss:0.51290	validation-mlogloss:0.50103
[432]	train-mlogloss:0.51272	validation-mlogloss:0.50086
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[435]	train-mlogloss:0.51229	validation-mlogloss:0.50040
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[440]	train-mlogloss:0.51134	validation-mlogloss:0.49960
[441]	train-mlogloss:0.51115	validation-mlogloss:0.49939
[442]	train-mlogloss:0.51098	validation-mlogloss:0.49927
[443]	train-mlogloss:0.51084	validation-mlogloss:0.49911
[444]	train-mlogloss:0.51075	validation-mlogloss:0.49902
[445]	train-mlogloss:0.51056	validation-mlogloss:0.49883
[446]	train-mlogloss:0.51031	validation-mlogloss:0.49863
[447]	train-mlogloss:0.51004	validation-mlogloss:0.49835
[448]	train-mlogloss:0.50985	validation-mlogloss:0.49823
[449]	train-mlogloss:0.50973	validation-mlogloss:0.49812
[450]	train-mlogloss:0.50958	validation-mlogloss:0.49791
[451]	train-mlogloss:0.50945	validation-mlogloss:0.49778
[452]	train-mlogloss:0.50930	validation-mlogloss:0.49764
[453]	train-mlogloss:0.50914	validation-mlogloss:0.49747
[454]	train-mlogloss:0.50903	validation-mlogloss:0.49737
[455]	train-mlogloss:0.50888	validation-mlogloss:0.49731
[456]	train-mlogloss:0.50876	validation-mlogloss:0.49722
[457]	train-mlogloss:0.50856	validation-mlogloss:0.49702
[458]	train-mlogloss:0.50847	validation-mlogloss:0.49695
[459]	train-mlogloss:0.50835	validation-mlogloss:0.49684
[460]	train-mlogloss:0.50820	validation-mlogloss:0.49678
[461]	train-mlogloss:0.50804	validation-mlogloss:0.49661
[462]	train-mlogloss:0.50794	validation-mlogloss:0.49656
[463]	train-mlogloss:0.50779	validation-mlogloss:0.49641
[464]	train-mlogloss:0.50762	validation-mlogloss:0.49626
[465]	train-mlogloss:0.50753	validation-mlogloss:0.49619
[466]	train-mlogloss:0.50738	validation-mlogloss:0.49601
[467]	train-mlogloss:0.50727	validation-mlogloss:0.49582
[468]	train-mlogloss:0.50711	validation-mlogloss:0.49570
[469]	train-mlogloss:0.50700	validation-mlogloss:0.49563
[470]	train-mlogloss:0.50684	validation-mlogloss:0.49554
[471]	train-mlogloss:0.50663	validation-mlogloss:0.49528
[472]	train-mlogloss:0.50648	validation-mlogloss:0.49517
[473]	train-mlogloss:0.50631	validation-mlogloss:0.49504
[474]	train-mlogloss:0.50620	validation-mlogloss:0.49492
[475]	train-mlogloss:0.50604	validation-mlogloss:0.49472
[476]	train-mlogloss:0.50590	validation-mlogloss:0.49460
[477]	train-mlogloss:0.50574	validation-mlogloss:0.49441
[478]	train-mlogloss:0.50564	validation-mlogloss:0.49435
[479]	train-mlogloss:0.50549	validation-mlogloss:0.49419
[480]	train-mlogloss:0.50537	validation-mlogloss:0.49411
[481]	train-mlogloss:0.50520	validation-mlogloss:0.49401
[482]	train-mlogloss:0.50509	validation-mlogloss:0.49393
[483]	train-mlogloss:0.50488	validation-mlogloss:0.49374
[484]	train-mlogloss:0.50480	validation-mlogloss:0.49372
[485]	train-mlogloss:0.50467	validation-mlogloss:0.49361
[486]	train-mlogloss:0.50454	validation-mlogloss:0.49344
[487]	train-mlogloss:0.50446	validation-mlogloss:0.49333
[488]	train-mlogloss:0.50437	validation-mlogloss:0.49323
[489]	train-mlogloss:0.50430	validation-mlogloss:0.49314
[490]	train-mlogloss:0.50425	validation-mlogloss:0.49310
[491]	train-mlogloss:0.50407	validation-mlogloss:0.49289
[492]	train-mlogloss:0.50395	validation-mlogloss:0.49272
[493]	train-mlogloss:0.50381	validation-mlogloss:0.49257
[494]	train-mlogloss:0.50375	validation-mlogloss:0.49252
[495]	train-mlogloss:0.50361	validation-mlogloss:0.49236
[496]	train-mlogloss:0.50346	validation-mlogloss:0.49220
[497]	train-mlogloss:0.50338	validation-mlogloss:0.49209
[498]	train-mlogloss:0.50331	validation-mlogloss:0.49205
[499]	train-mlogloss:0.50317	validation-mlogloss:0.49186
[500]	train-mlogloss:0.50307	validation-mlogloss:0.49172
[501]	train-mlogloss:0.50295	validation-mlogloss:0.49164
[502]	train-mlogloss:0.50285	validation-mlogloss:0.49149
[503]	train-mlogloss:0.50276	validation-mlogloss:0.49143
[504]	train-mlogloss:0.50263	validation-mlogloss:0.49132
[505]	train-mlogloss:0.50251	validation-mlogloss:0.49117
[506]	train-mlogloss:0.50242	validation-mlogloss:0.49111
[507]	train-mlogloss:0.50235	validation-mlogloss:0.49109
[508]	train-mlogloss:0.50221	validation-mlogloss:0.49095
[509]	train-mlogloss:0.50206	validation-mlogloss:0.49083
[510]	train-mlogloss:0.50193	validation-mlogloss:0.49076
[511]	train-mlogloss:0.50185	validation-mlogloss:0.49069
[512]	train-mlogloss:0.50177	validation-mlogloss:0.49059
[513]	train-mlogloss:0.50170	validation-mlogloss:0.49052
[514]	train-mlogloss:0.50162	validation-mlogloss:0.49040
[515]	train-mlogloss:0.50155	validation-mlogloss:0.49031
[516]	train-mlogloss:0.50137	validation-mlogloss:0.49020
[517]	train-mlogloss:0.50129	validation-mlogloss:0.49018
[518]	train-mlogloss:0.50122	validation-mlogloss:0.49008
[519]	train-mlogloss:0.50114	validation-mlogloss:0.48997
[520]	train-mlogloss:0.50108	validation-mlogloss:0.48995
[521]	train-mlogloss:0.50100	validation-mlogloss:0.48985
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 1 1 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.08 [%]
Global accuracy score (test) = 80.54 [%]
Global F1 score (train) = 79.45 [%]
Global F1 score (test) = 81.07 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.77      0.69       350
MODERATE-INTENSITY       0.69      0.59      0.64       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.98      0.92      0.95       322

          accuracy                           0.81      1372
         macro avg       0.82      0.81      0.81      1372
      weighted avg       0.82      0.81      0.81      1372


Accuracy capturado en la ejecución 7: 80.54 [%]
F1-score capturado en la ejecución 7: 81.07 [%]

=== EJECUCIÓN 8 ===

--- TRAIN (ejecución 8) ---

--- TEST (ejecución 8) ---
2025-11-03 17:21:12.823068: 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`.
2025-11-03 17:21:12.834838: 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 00:00:1762186872.849004  329250 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186872.853241  329250 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186872.863878  329250 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186872.863910  329250 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186872.863913  329250 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186872.863915  329250 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:21:12.867162: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37501	validation-mlogloss:1.37445
[1]	train-mlogloss:1.36367	validation-mlogloss:1.36263
[2]	train-mlogloss:1.35207	validation-mlogloss:1.35073
[3]	train-mlogloss:1.34122	validation-mlogloss:1.33913
[4]	train-mlogloss:1.33019	validation-mlogloss:1.32749
[5]	train-mlogloss:1.31950	validation-mlogloss:1.31618
[6]	train-mlogloss:1.30941	validation-mlogloss:1.30582
[7]	train-mlogloss:1.29916	validation-mlogloss:1.29488
[8]	train-mlogloss:1.28914	validation-mlogloss:1.28451
[9]	train-mlogloss:1.27952	validation-mlogloss:1.27459
[10]	train-mlogloss:1.26968	validation-mlogloss:1.26421
[11]	train-mlogloss:1.26026	validation-mlogloss:1.25450
[12]	train-mlogloss:1.25111	validation-mlogloss:1.24483
[13]	train-mlogloss:1.24178	validation-mlogloss:1.23526
[14]	train-mlogloss:1.23296	validation-mlogloss:1.22621
[15]	train-mlogloss:1.22404	validation-mlogloss:1.21672
[16]	train-mlogloss:1.21544	validation-mlogloss:1.20782
[17]	train-mlogloss:1.20700	validation-mlogloss:1.19896
[18]	train-mlogloss:1.19863	validation-mlogloss:1.19009
[19]	train-mlogloss:1.19046	validation-mlogloss:1.18172
[20]	train-mlogloss:1.18243	validation-mlogloss:1.17319
[21]	train-mlogloss:1.17420	validation-mlogloss:1.16478
[22]	train-mlogloss:1.16645	validation-mlogloss:1.15663
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[445]	train-mlogloss:0.51521	validation-mlogloss:0.50672
[446]	train-mlogloss:0.51509	validation-mlogloss:0.50661
[447]	train-mlogloss:0.51481	validation-mlogloss:0.50647
[448]	train-mlogloss:0.51473	validation-mlogloss:0.50640
[449]	train-mlogloss:0.51456	validation-mlogloss:0.50626
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[452]	train-mlogloss:0.51401	validation-mlogloss:0.50573
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[458]	train-mlogloss:0.51293	validation-mlogloss:0.50492
[459]	train-mlogloss:0.51274	validation-mlogloss:0.50475
[460]	train-mlogloss:0.51257	validation-mlogloss:0.50452
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[470]	train-mlogloss:0.51113	validation-mlogloss:0.50329
[471]	train-mlogloss:0.51099	validation-mlogloss:0.50319
[472]	train-mlogloss:0.51088	validation-mlogloss:0.50302
[473]	train-mlogloss:0.51080	validation-mlogloss:0.50291
[474]	train-mlogloss:0.51061	validation-mlogloss:0.50282
[475]	train-mlogloss:0.51045	validation-mlogloss:0.50268
[476]	train-mlogloss:0.51036	validation-mlogloss:0.50264
[477]	train-mlogloss:0.51021	validation-mlogloss:0.50249
[478]	train-mlogloss:0.51005	validation-mlogloss:0.50240
[479]	train-mlogloss:0.50993	validation-mlogloss:0.50227
[480]	train-mlogloss:0.50981	validation-mlogloss:0.50216
[481]	train-mlogloss:0.50965	validation-mlogloss:0.50207
[482]	train-mlogloss:0.50958	validation-mlogloss:0.50205
[483]	train-mlogloss:0.50935	validation-mlogloss:0.50186
[484]	train-mlogloss:0.50915	validation-mlogloss:0.50171
[485]	train-mlogloss:0.50903	validation-mlogloss:0.50157
[486]	train-mlogloss:0.50888	validation-mlogloss:0.50143
[487]	train-mlogloss:0.50871	validation-mlogloss:0.50126
[488]	train-mlogloss:0.50860	validation-mlogloss:0.50111
[489]	train-mlogloss:0.50844	validation-mlogloss:0.50096
[490]	train-mlogloss:0.50830	validation-mlogloss:0.50088
[491]	train-mlogloss:0.50823	validation-mlogloss:0.50088
[492]	train-mlogloss:0.50812	validation-mlogloss:0.50080
[493]	train-mlogloss:0.50802	validation-mlogloss:0.50071
[494]	train-mlogloss:0.50782	validation-mlogloss:0.50058
[495]	train-mlogloss:0.50771	validation-mlogloss:0.50054
[496]	train-mlogloss:0.50760	validation-mlogloss:0.50045
[497]	train-mlogloss:0.50753	validation-mlogloss:0.50035
[498]	train-mlogloss:0.50740	validation-mlogloss:0.50029
[499]	train-mlogloss:0.50733	validation-mlogloss:0.50024
[500]	train-mlogloss:0.50724	validation-mlogloss:0.50019
[501]	train-mlogloss:0.50718	validation-mlogloss:0.50012
[502]	train-mlogloss:0.50707	validation-mlogloss:0.50005
[503]	train-mlogloss:0.50699	validation-mlogloss:0.49996
[504]	train-mlogloss:0.50683	validation-mlogloss:0.49984
[505]	train-mlogloss:0.50676	validation-mlogloss:0.49974
[506]	train-mlogloss:0.50666	validation-mlogloss:0.49962
[507]	train-mlogloss:0.50655	validation-mlogloss:0.49948
[508]	train-mlogloss:0.50647	validation-mlogloss:0.49935
[509]	train-mlogloss:0.50632	validation-mlogloss:0.49924
[510]	train-mlogloss:0.50625	validation-mlogloss:0.49921
[511]	train-mlogloss:0.50604	validation-mlogloss:0.49901
[512]	train-mlogloss:0.50592	validation-mlogloss:0.49889
[513]	train-mlogloss:0.50581	validation-mlogloss:0.49882
[514]	train-mlogloss:0.50563	validation-mlogloss:0.49863
[515]	train-mlogloss:0.50547	validation-mlogloss:0.49847
[516]	train-mlogloss:0.50541	validation-mlogloss:0.49843
[517]	train-mlogloss:0.50522	validation-mlogloss:0.49828
[518]	train-mlogloss:0.50514	validation-mlogloss:0.49821
[519]	train-mlogloss:0.50498	validation-mlogloss:0.49810
[520]	train-mlogloss:0.50487	validation-mlogloss:0.49802
[521]	train-mlogloss:0.50475	validation-mlogloss:0.49792
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.36 [%]
Global accuracy score (test) = 80.32 [%]
Global F1 score (train) = 79.71 [%]
Global F1 score (test) = 80.87 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.71      0.67       350
MODERATE-INTENSITY       0.67      0.63      0.65       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.97      0.92      0.94       322

          accuracy                           0.80      1372
         macro avg       0.81      0.81      0.81      1372
      weighted avg       0.81      0.80      0.81      1372


Accuracy capturado en la ejecución 8: 80.32 [%]
F1-score capturado en la ejecución 8: 80.87 [%]

=== EJECUCIÓN 9 ===

--- TRAIN (ejecución 9) ---

--- TEST (ejecución 9) ---
2025-11-03 17:21:31.794896: 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`.
2025-11-03 17:21:31.806459: 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 00:00:1762186891.820111  329563 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186891.824541  329563 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186891.834741  329563 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186891.834769  329563 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186891.834772  329563 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186891.834775  329563 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:21:31.837954: 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..
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
[0]	train-mlogloss:1.37485	validation-mlogloss:1.37433
[1]	train-mlogloss:1.36316	validation-mlogloss:1.36241
[2]	train-mlogloss:1.35199	validation-mlogloss:1.35065
[3]	train-mlogloss:1.34103	validation-mlogloss:1.33934
[4]	train-mlogloss:1.33007	validation-mlogloss:1.32789
[5]	train-mlogloss:1.31956	validation-mlogloss:1.31690
[6]	train-mlogloss:1.30954	validation-mlogloss:1.30684
[7]	train-mlogloss:1.29977	validation-mlogloss:1.29682
[8]	train-mlogloss:1.29004	validation-mlogloss:1.28668
[9]	train-mlogloss:1.28045	validation-mlogloss:1.27689
[10]	train-mlogloss:1.27069	validation-mlogloss:1.26656
[11]	train-mlogloss:1.26143	validation-mlogloss:1.25672
[12]	train-mlogloss:1.25207	validation-mlogloss:1.24679
[13]	train-mlogloss:1.24305	validation-mlogloss:1.23729
[14]	train-mlogloss:1.23415	validation-mlogloss:1.22809
[15]	train-mlogloss:1.22561	validation-mlogloss:1.21928
[16]	train-mlogloss:1.21711	validation-mlogloss:1.21060
[17]	train-mlogloss:1.20863	validation-mlogloss:1.20180
[18]	train-mlogloss:1.20046	validation-mlogloss:1.19334
[19]	train-mlogloss:1.19224	validation-mlogloss:1.18495
[20]	train-mlogloss:1.18422	validation-mlogloss:1.17649
[21]	train-mlogloss:1.17651	validation-mlogloss:1.16836
[22]	train-mlogloss:1.16873	validation-mlogloss:1.16015
[23]	train-mlogloss:1.16109	validation-mlogloss:1.15227
[24]	train-mlogloss:1.15365	validation-mlogloss:1.14454
[25]	train-mlogloss:1.14613	validation-mlogloss:1.13666
[26]	train-mlogloss:1.13891	validation-mlogloss:1.12919
[27]	train-mlogloss:1.13189	validation-mlogloss:1.12191
[28]	train-mlogloss:1.12476	validation-mlogloss:1.11441
[29]	train-mlogloss:1.11768	validation-mlogloss:1.10749
[30]	train-mlogloss:1.11071	validation-mlogloss:1.10028
[31]	train-mlogloss:1.10383	validation-mlogloss:1.09302
[32]	train-mlogloss:1.09714	validation-mlogloss:1.08605
[33]	train-mlogloss:1.09057	validation-mlogloss:1.07918
[34]	train-mlogloss:1.08407	validation-mlogloss:1.07231
[35]	train-mlogloss:1.07787	validation-mlogloss:1.06594
[36]	train-mlogloss:1.07168	validation-mlogloss:1.05935
[37]	train-mlogloss:1.06543	validation-mlogloss:1.05309
[38]	train-mlogloss:1.05946	validation-mlogloss:1.04706
[39]	train-mlogloss:1.05329	validation-mlogloss:1.04077
[40]	train-mlogloss:1.04748	validation-mlogloss:1.03465
[41]	train-mlogloss:1.04157	validation-mlogloss:1.02883
[42]	train-mlogloss:1.03586	validation-mlogloss:1.02271
[43]	train-mlogloss:1.03007	validation-mlogloss:1.01706
[44]	train-mlogloss:1.02462	validation-mlogloss:1.01138
[45]	train-mlogloss:1.01896	validation-mlogloss:1.00544
[46]	train-mlogloss:1.01345	validation-mlogloss:0.99998
[47]	train-mlogloss:1.00787	validation-mlogloss:0.99435
[48]	train-mlogloss:1.00268	validation-mlogloss:0.98911
[49]	train-mlogloss:0.99722	validation-mlogloss:0.98342
[50]	train-mlogloss:0.99194	validation-mlogloss:0.97798
[51]	train-mlogloss:0.98680	validation-mlogloss:0.97283
[52]	train-mlogloss:0.98168	validation-mlogloss:0.96735
[53]	train-mlogloss:0.97653	validation-mlogloss:0.96201
[54]	train-mlogloss:0.97176	validation-mlogloss:0.95720
[55]	train-mlogloss:0.96681	validation-mlogloss:0.95220
[56]	train-mlogloss:0.96199	validation-mlogloss:0.94719
[57]	train-mlogloss:0.95738	validation-mlogloss:0.94252
[58]	train-mlogloss:0.95272	validation-mlogloss:0.93779
[59]	train-mlogloss:0.94813	validation-mlogloss:0.93316
[60]	train-mlogloss:0.94344	validation-mlogloss:0.92829
[61]	train-mlogloss:0.93889	validation-mlogloss:0.92367
[62]	train-mlogloss:0.93439	validation-mlogloss:0.91893
[63]	train-mlogloss:0.93018	validation-mlogloss:0.91476
[64]	train-mlogloss:0.92578	validation-mlogloss:0.91023
[65]	train-mlogloss:0.92141	validation-mlogloss:0.90561
[66]	train-mlogloss:0.91727	validation-mlogloss:0.90123
[67]	train-mlogloss:0.91301	validation-mlogloss:0.89683
[68]	train-mlogloss:0.90893	validation-mlogloss:0.89266
[69]	train-mlogloss:0.90478	validation-mlogloss:0.88843
[70]	train-mlogloss:0.90061	validation-mlogloss:0.88414
[71]	train-mlogloss:0.89660	validation-mlogloss:0.88011
[72]	train-mlogloss:0.89276	validation-mlogloss:0.87616
[73]	train-mlogloss:0.88893	validation-mlogloss:0.87222
[74]	train-mlogloss:0.88510	validation-mlogloss:0.86822
[75]	train-mlogloss:0.88142	validation-mlogloss:0.86446
[76]	train-mlogloss:0.87795	validation-mlogloss:0.86091
[77]	train-mlogloss:0.87450	validation-mlogloss:0.85748
[78]	train-mlogloss:0.87090	validation-mlogloss:0.85375
[79]	train-mlogloss:0.86757	validation-mlogloss:0.85036
[80]	train-mlogloss:0.86403	validation-mlogloss:0.84663
[81]	train-mlogloss:0.86055	validation-mlogloss:0.84302
[82]	train-mlogloss:0.85709	validation-mlogloss:0.83948
[83]	train-mlogloss:0.85353	validation-mlogloss:0.83572
[84]	train-mlogloss:0.85017	validation-mlogloss:0.83214
[85]	train-mlogloss:0.84692	validation-mlogloss:0.82878
[86]	train-mlogloss:0.84364	validation-mlogloss:0.82542
[87]	train-mlogloss:0.84035	validation-mlogloss:0.82201
[88]	train-mlogloss:0.83716	validation-mlogloss:0.81874
[89]	train-mlogloss:0.83398	validation-mlogloss:0.81542
[90]	train-mlogloss:0.83108	validation-mlogloss:0.81241
[91]	train-mlogloss:0.82786	validation-mlogloss:0.80914
[92]	train-mlogloss:0.82478	validation-mlogloss:0.80593
[93]	train-mlogloss:0.82180	validation-mlogloss:0.80282
[94]	train-mlogloss:0.81883	validation-mlogloss:0.79974
[95]	train-mlogloss:0.81590	validation-mlogloss:0.79675
[96]	train-mlogloss:0.81288	validation-mlogloss:0.79354
[97]	train-mlogloss:0.81009	validation-mlogloss:0.79068
[98]	train-mlogloss:0.80736	validation-mlogloss:0.78786
[99]	train-mlogloss:0.80461	validation-mlogloss:0.78496
[100]	train-mlogloss:0.80177	validation-mlogloss:0.78204
[101]	train-mlogloss:0.79895	validation-mlogloss:0.77912
[102]	train-mlogloss:0.79624	validation-mlogloss:0.77631
[103]	train-mlogloss:0.79355	validation-mlogloss:0.77336
[104]	train-mlogloss:0.79080	validation-mlogloss:0.77058
[105]	train-mlogloss:0.78807	validation-mlogloss:0.76771
[106]	train-mlogloss:0.78532	validation-mlogloss:0.76483
[107]	train-mlogloss:0.78278	validation-mlogloss:0.76236
[108]	train-mlogloss:0.78008	validation-mlogloss:0.75961
[109]	train-mlogloss:0.77776	validation-mlogloss:0.75723
[110]	train-mlogloss:0.77529	validation-mlogloss:0.75447
[111]	train-mlogloss:0.77292	validation-mlogloss:0.75195
[112]	train-mlogloss:0.77040	validation-mlogloss:0.74929
[113]	train-mlogloss:0.76800	validation-mlogloss:0.74672
[114]	train-mlogloss:0.76558	validation-mlogloss:0.74413
[115]	train-mlogloss:0.76316	validation-mlogloss:0.74176
[116]	train-mlogloss:0.76064	validation-mlogloss:0.73930
[117]	train-mlogloss:0.75847	validation-mlogloss:0.73705
[118]	train-mlogloss:0.75598	validation-mlogloss:0.73452
[119]	train-mlogloss:0.75377	validation-mlogloss:0.73217
[120]	train-mlogloss:0.75158	validation-mlogloss:0.73001
[121]	train-mlogloss:0.74924	validation-mlogloss:0.72755
[122]	train-mlogloss:0.74689	validation-mlogloss:0.72508
[123]	train-mlogloss:0.74478	validation-mlogloss:0.72278
[124]	train-mlogloss:0.74255	validation-mlogloss:0.72045
[125]	train-mlogloss:0.74026	validation-mlogloss:0.71820
[126]	train-mlogloss:0.73815	validation-mlogloss:0.71600
[127]	train-mlogloss:0.73610	validation-mlogloss:0.71386
[128]	train-mlogloss:0.73390	validation-mlogloss:0.71163
[129]	train-mlogloss:0.73169	validation-mlogloss:0.70949
[130]	train-mlogloss:0.72961	validation-mlogloss:0.70738
[131]	train-mlogloss:0.72768	validation-mlogloss:0.70536
[132]	train-mlogloss:0.72567	validation-mlogloss:0.70339
[133]	train-mlogloss:0.72359	validation-mlogloss:0.70128
[134]	train-mlogloss:0.72181	validation-mlogloss:0.69949
[135]	train-mlogloss:0.71990	validation-mlogloss:0.69751
[136]	train-mlogloss:0.71813	validation-mlogloss:0.69568
[137]	train-mlogloss:0.71639	validation-mlogloss:0.69393
[138]	train-mlogloss:0.71441	validation-mlogloss:0.69195
[139]	train-mlogloss:0.71252	validation-mlogloss:0.69007
[140]	train-mlogloss:0.71062	validation-mlogloss:0.68820
[141]	train-mlogloss:0.70865	validation-mlogloss:0.68628
[142]	train-mlogloss:0.70683	validation-mlogloss:0.68443
[143]	train-mlogloss:0.70509	validation-mlogloss:0.68263
[144]	train-mlogloss:0.70322	validation-mlogloss:0.68078
[145]	train-mlogloss:0.70155	validation-mlogloss:0.67908
[146]	train-mlogloss:0.69974	validation-mlogloss:0.67731
[147]	train-mlogloss:0.69795	validation-mlogloss:0.67548
[148]	train-mlogloss:0.69627	validation-mlogloss:0.67372
[149]	train-mlogloss:0.69465	validation-mlogloss:0.67204
[150]	train-mlogloss:0.69306	validation-mlogloss:0.67045
[151]	train-mlogloss:0.69141	validation-mlogloss:0.66885
[152]	train-mlogloss:0.68994	validation-mlogloss:0.66718
[153]	train-mlogloss:0.68829	validation-mlogloss:0.66556
[154]	train-mlogloss:0.68675	validation-mlogloss:0.66396
[155]	train-mlogloss:0.68512	validation-mlogloss:0.66238
[156]	train-mlogloss:0.68354	validation-mlogloss:0.66083
[157]	train-mlogloss:0.68198	validation-mlogloss:0.65931
[158]	train-mlogloss:0.68053	validation-mlogloss:0.65779
[159]	train-mlogloss:0.67895	validation-mlogloss:0.65625
[160]	train-mlogloss:0.67756	validation-mlogloss:0.65482
[161]	train-mlogloss:0.67619	validation-mlogloss:0.65340
[162]	train-mlogloss:0.67466	validation-mlogloss:0.65191
[163]	train-mlogloss:0.67318	validation-mlogloss:0.65040
[164]	train-mlogloss:0.67177	validation-mlogloss:0.64905
[165]	train-mlogloss:0.67035	validation-mlogloss:0.64770
[166]	train-mlogloss:0.66910	validation-mlogloss:0.64659
[167]	train-mlogloss:0.66779	validation-mlogloss:0.64521
[168]	train-mlogloss:0.66636	validation-mlogloss:0.64384
[169]	train-mlogloss:0.66499	validation-mlogloss:0.64253
[170]	train-mlogloss:0.66372	validation-mlogloss:0.64115
[171]	train-mlogloss:0.66247	validation-mlogloss:0.63991
[172]	train-mlogloss:0.66118	validation-mlogloss:0.63859
[173]	train-mlogloss:0.65973	validation-mlogloss:0.63710
[174]	train-mlogloss:0.65837	validation-mlogloss:0.63582
[175]	train-mlogloss:0.65711	validation-mlogloss:0.63462
[176]	train-mlogloss:0.65586	validation-mlogloss:0.63334
[177]	train-mlogloss:0.65460	validation-mlogloss:0.63213
[178]	train-mlogloss:0.65334	validation-mlogloss:0.63094
[179]	train-mlogloss:0.65198	validation-mlogloss:0.62965
[180]	train-mlogloss:0.65073	validation-mlogloss:0.62836
[181]	train-mlogloss:0.64959	validation-mlogloss:0.62716
[182]	train-mlogloss:0.64834	validation-mlogloss:0.62600
[183]	train-mlogloss:0.64713	validation-mlogloss:0.62476
[184]	train-mlogloss:0.64592	validation-mlogloss:0.62364
[185]	train-mlogloss:0.64472	validation-mlogloss:0.62246
[186]	train-mlogloss:0.64358	validation-mlogloss:0.62137
[187]	train-mlogloss:0.64238	validation-mlogloss:0.62011
[188]	train-mlogloss:0.64132	validation-mlogloss:0.61900
[189]	train-mlogloss:0.64015	validation-mlogloss:0.61788
[190]	train-mlogloss:0.63910	validation-mlogloss:0.61692
[191]	train-mlogloss:0.63797	validation-mlogloss:0.61580
[192]	train-mlogloss:0.63689	validation-mlogloss:0.61479
[193]	train-mlogloss:0.63574	validation-mlogloss:0.61364
[194]	train-mlogloss:0.63464	validation-mlogloss:0.61258
[195]	train-mlogloss:0.63359	validation-mlogloss:0.61157
[196]	train-mlogloss:0.63249	validation-mlogloss:0.61061
[197]	train-mlogloss:0.63151	validation-mlogloss:0.60958
[198]	train-mlogloss:0.63046	validation-mlogloss:0.60845
[199]	train-mlogloss:0.62954	validation-mlogloss:0.60749
[200]	train-mlogloss:0.62853	validation-mlogloss:0.60650
[201]	train-mlogloss:0.62761	validation-mlogloss:0.60558
[202]	train-mlogloss:0.62665	validation-mlogloss:0.60463
[203]	train-mlogloss:0.62572	validation-mlogloss:0.60364
[204]	train-mlogloss:0.62478	validation-mlogloss:0.60267
[205]	train-mlogloss:0.62372	validation-mlogloss:0.60166
[206]	train-mlogloss:0.62272	validation-mlogloss:0.60071
[207]	train-mlogloss:0.62163	validation-mlogloss:0.59965
[208]	train-mlogloss:0.62057	validation-mlogloss:0.59872
[209]	train-mlogloss:0.61965	validation-mlogloss:0.59785
[210]	train-mlogloss:0.61886	validation-mlogloss:0.59702
[211]	train-mlogloss:0.61795	validation-mlogloss:0.59602
[212]	train-mlogloss:0.61701	validation-mlogloss:0.59509
[213]	train-mlogloss:0.61608	validation-mlogloss:0.59428
[214]	train-mlogloss:0.61517	validation-mlogloss:0.59341
[215]	train-mlogloss:0.61418	validation-mlogloss:0.59250
[216]	train-mlogloss:0.61331	validation-mlogloss:0.59165
[217]	train-mlogloss:0.61241	validation-mlogloss:0.59078
[218]	train-mlogloss:0.61151	validation-mlogloss:0.58994
[219]	train-mlogloss:0.61065	validation-mlogloss:0.58897
[220]	train-mlogloss:0.60980	validation-mlogloss:0.58818
[221]	train-mlogloss:0.60892	validation-mlogloss:0.58738
[222]	train-mlogloss:0.60811	validation-mlogloss:0.58654
[223]	train-mlogloss:0.60740	validation-mlogloss:0.58574
[224]	train-mlogloss:0.60648	validation-mlogloss:0.58493
[225]	train-mlogloss:0.60569	validation-mlogloss:0.58427
[226]	train-mlogloss:0.60488	validation-mlogloss:0.58360
[227]	train-mlogloss:0.60402	validation-mlogloss:0.58266
[228]	train-mlogloss:0.60325	validation-mlogloss:0.58198
[229]	train-mlogloss:0.60238	validation-mlogloss:0.58121
[230]	train-mlogloss:0.60165	validation-mlogloss:0.58052
[231]	train-mlogloss:0.60089	validation-mlogloss:0.57982
[232]	train-mlogloss:0.60017	validation-mlogloss:0.57916
[233]	train-mlogloss:0.59944	validation-mlogloss:0.57845
[234]	train-mlogloss:0.59868	validation-mlogloss:0.57768
[235]	train-mlogloss:0.59795	validation-mlogloss:0.57706
[236]	train-mlogloss:0.59715	validation-mlogloss:0.57633
[237]	train-mlogloss:0.59650	validation-mlogloss:0.57570
[238]	train-mlogloss:0.59582	validation-mlogloss:0.57511
[239]	train-mlogloss:0.59503	validation-mlogloss:0.57451
[240]	train-mlogloss:0.59428	validation-mlogloss:0.57389
[241]	train-mlogloss:0.59358	validation-mlogloss:0.57326
[242]	train-mlogloss:0.59290	validation-mlogloss:0.57267
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[265]	train-mlogloss:0.57779	validation-mlogloss:0.55845
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[274]	train-mlogloss:0.57261	validation-mlogloss:0.55372
[275]	train-mlogloss:0.57205	validation-mlogloss:0.55315
[276]	train-mlogloss:0.57152	validation-mlogloss:0.55262
[277]	train-mlogloss:0.57091	validation-mlogloss:0.55206
[278]	train-mlogloss:0.57042	validation-mlogloss:0.55161
[279]	train-mlogloss:0.56985	validation-mlogloss:0.55109
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[389]	train-mlogloss:0.52820	validation-mlogloss:0.51480
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[412]	train-mlogloss:0.52311	validation-mlogloss:0.51039
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[444]	train-mlogloss:0.51795	validation-mlogloss:0.50592
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[488]	train-mlogloss:0.51209	validation-mlogloss:0.50080
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[500]	train-mlogloss:0.51073	validation-mlogloss:0.49970
[501]	train-mlogloss:0.51060	validation-mlogloss:0.49960
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[504]	train-mlogloss:0.51028	validation-mlogloss:0.49930
[505]	train-mlogloss:0.51018	validation-mlogloss:0.49927
[506]	train-mlogloss:0.51000	validation-mlogloss:0.49913
[507]	train-mlogloss:0.50989	validation-mlogloss:0.49904
[508]	train-mlogloss:0.50970	validation-mlogloss:0.49895
[509]	train-mlogloss:0.50964	validation-mlogloss:0.49889
[510]	train-mlogloss:0.50958	validation-mlogloss:0.49889
[511]	train-mlogloss:0.50953	validation-mlogloss:0.49888
[512]	train-mlogloss:0.50935	validation-mlogloss:0.49877
[513]	train-mlogloss:0.50923	validation-mlogloss:0.49863
[514]	train-mlogloss:0.50915	validation-mlogloss:0.49858
[515]	train-mlogloss:0.50903	validation-mlogloss:0.49846
[516]	train-mlogloss:0.50898	validation-mlogloss:0.49841
[517]	train-mlogloss:0.50886	validation-mlogloss:0.49836
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[520]	train-mlogloss:0.50866	validation-mlogloss:0.49817
[521]	train-mlogloss:0.50854	validation-mlogloss:0.49799
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.38 [%]
Global accuracy score (test) = 78.86 [%]
Global F1 score (train) = 79.71 [%]
Global F1 score (test) = 79.43 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.61      0.69      0.65       350
MODERATE-INTENSITY       0.64      0.61      0.62       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.95      0.92      0.94       322

          accuracy                           0.79      1372
         macro avg       0.80      0.79      0.79      1372
      weighted avg       0.80      0.79      0.79      1372


Accuracy capturado en la ejecución 9: 78.86 [%]
F1-score capturado en la ejecución 9: 79.43 [%]

=== EJECUCIÓN 10 ===

--- TRAIN (ejecución 10) ---

--- TEST (ejecución 10) ---
2025-11-03 17:21:50.501835: 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`.
2025-11-03 17:21:50.513492: 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 00:00:1762186910.527621  329866 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186910.531941  329866 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186910.542445  329866 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186910.542477  329866 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186910.542479  329866 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186910.542481  329866 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:21:50.545777: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37436	validation-mlogloss:1.37378
[1]	train-mlogloss:1.36260	validation-mlogloss:1.36126
[2]	train-mlogloss:1.35145	validation-mlogloss:1.34973
[3]	train-mlogloss:1.34029	validation-mlogloss:1.33787
[4]	train-mlogloss:1.32920	validation-mlogloss:1.32680
[5]	train-mlogloss:1.31838	validation-mlogloss:1.31531
[6]	train-mlogloss:1.30818	validation-mlogloss:1.30485
[7]	train-mlogloss:1.29789	validation-mlogloss:1.29407
[8]	train-mlogloss:1.28791	validation-mlogloss:1.28361
[9]	train-mlogloss:1.27794	validation-mlogloss:1.27284
[10]	train-mlogloss:1.26837	validation-mlogloss:1.26278
[11]	train-mlogloss:1.25881	validation-mlogloss:1.25260
[12]	train-mlogloss:1.24933	validation-mlogloss:1.24285
[13]	train-mlogloss:1.24022	validation-mlogloss:1.23325
[14]	train-mlogloss:1.23125	validation-mlogloss:1.22382
[15]	train-mlogloss:1.22244	validation-mlogloss:1.21464
[16]	train-mlogloss:1.21398	validation-mlogloss:1.20593
[17]	train-mlogloss:1.20563	validation-mlogloss:1.19733
[18]	train-mlogloss:1.19743	validation-mlogloss:1.18872
[19]	train-mlogloss:1.18934	validation-mlogloss:1.18020
[20]	train-mlogloss:1.18168	validation-mlogloss:1.17234
[21]	train-mlogloss:1.17373	validation-mlogloss:1.16400
[22]	train-mlogloss:1.16599	validation-mlogloss:1.15600
[23]	train-mlogloss:1.15832	validation-mlogloss:1.14787
[24]	train-mlogloss:1.15076	validation-mlogloss:1.13985
[25]	train-mlogloss:1.14342	validation-mlogloss:1.13209
[26]	train-mlogloss:1.13613	validation-mlogloss:1.12434
[27]	train-mlogloss:1.12846	validation-mlogloss:1.11637
[28]	train-mlogloss:1.12149	validation-mlogloss:1.10907
[29]	train-mlogloss:1.11459	validation-mlogloss:1.10173
[30]	train-mlogloss:1.10775	validation-mlogloss:1.09446
[31]	train-mlogloss:1.10100	validation-mlogloss:1.08713
[32]	train-mlogloss:1.09435	validation-mlogloss:1.08019
[33]	train-mlogloss:1.08768	validation-mlogloss:1.07320
[34]	train-mlogloss:1.08113	validation-mlogloss:1.06629
[35]	train-mlogloss:1.07455	validation-mlogloss:1.05962
[36]	train-mlogloss:1.06819	validation-mlogloss:1.05296
[37]	train-mlogloss:1.06201	validation-mlogloss:1.04660
[38]	train-mlogloss:1.05583	validation-mlogloss:1.04031
[39]	train-mlogloss:1.04964	validation-mlogloss:1.03399
[40]	train-mlogloss:1.04377	validation-mlogloss:1.02798
[41]	train-mlogloss:1.03789	validation-mlogloss:1.02192
[42]	train-mlogloss:1.03218	validation-mlogloss:1.01619
[43]	train-mlogloss:1.02651	validation-mlogloss:1.01046
[44]	train-mlogloss:1.02094	validation-mlogloss:1.00464
[45]	train-mlogloss:1.01558	validation-mlogloss:0.99902
[46]	train-mlogloss:1.01009	validation-mlogloss:0.99323
[47]	train-mlogloss:1.00495	validation-mlogloss:0.98774
[48]	train-mlogloss:0.99977	validation-mlogloss:0.98224
[49]	train-mlogloss:0.99455	validation-mlogloss:0.97680
[50]	train-mlogloss:0.98924	validation-mlogloss:0.97135
[51]	train-mlogloss:0.98418	validation-mlogloss:0.96616
[52]	train-mlogloss:0.97896	validation-mlogloss:0.96085
[53]	train-mlogloss:0.97407	validation-mlogloss:0.95589
[54]	train-mlogloss:0.96898	validation-mlogloss:0.95062
[55]	train-mlogloss:0.96423	validation-mlogloss:0.94559
[56]	train-mlogloss:0.95963	validation-mlogloss:0.94082
[57]	train-mlogloss:0.95488	validation-mlogloss:0.93594
[58]	train-mlogloss:0.95030	validation-mlogloss:0.93142
[59]	train-mlogloss:0.94559	validation-mlogloss:0.92676
[60]	train-mlogloss:0.94095	validation-mlogloss:0.92192
[61]	train-mlogloss:0.93625	validation-mlogloss:0.91701
[62]	train-mlogloss:0.93191	validation-mlogloss:0.91252
[63]	train-mlogloss:0.92761	validation-mlogloss:0.90821
[64]	train-mlogloss:0.92333	validation-mlogloss:0.90391
[65]	train-mlogloss:0.91917	validation-mlogloss:0.89985
[66]	train-mlogloss:0.91506	validation-mlogloss:0.89569
[67]	train-mlogloss:0.91095	validation-mlogloss:0.89135
[68]	train-mlogloss:0.90676	validation-mlogloss:0.88686
[69]	train-mlogloss:0.90280	validation-mlogloss:0.88276
[70]	train-mlogloss:0.89883	validation-mlogloss:0.87861
[71]	train-mlogloss:0.89498	validation-mlogloss:0.87457
[72]	train-mlogloss:0.89116	validation-mlogloss:0.87075
[73]	train-mlogloss:0.88717	validation-mlogloss:0.86664
[74]	train-mlogloss:0.88335	validation-mlogloss:0.86280
[75]	train-mlogloss:0.87969	validation-mlogloss:0.85902
[76]	train-mlogloss:0.87586	validation-mlogloss:0.85505
[77]	train-mlogloss:0.87227	validation-mlogloss:0.85134
[78]	train-mlogloss:0.86882	validation-mlogloss:0.84758
[79]	train-mlogloss:0.86516	validation-mlogloss:0.84379
[80]	train-mlogloss:0.86153	validation-mlogloss:0.84012
[81]	train-mlogloss:0.85801	validation-mlogloss:0.83647
[82]	train-mlogloss:0.85447	validation-mlogloss:0.83294
[83]	train-mlogloss:0.85113	validation-mlogloss:0.82950
[84]	train-mlogloss:0.84784	validation-mlogloss:0.82608
[85]	train-mlogloss:0.84474	validation-mlogloss:0.82305
[86]	train-mlogloss:0.84144	validation-mlogloss:0.81972
[87]	train-mlogloss:0.83823	validation-mlogloss:0.81644
[88]	train-mlogloss:0.83501	validation-mlogloss:0.81311
[89]	train-mlogloss:0.83177	validation-mlogloss:0.80988
[90]	train-mlogloss:0.82859	validation-mlogloss:0.80650
[91]	train-mlogloss:0.82555	validation-mlogloss:0.80325
[92]	train-mlogloss:0.82246	validation-mlogloss:0.80008
[93]	train-mlogloss:0.81948	validation-mlogloss:0.79714
[94]	train-mlogloss:0.81649	validation-mlogloss:0.79410
[95]	train-mlogloss:0.81347	validation-mlogloss:0.79093
[96]	train-mlogloss:0.81049	validation-mlogloss:0.78797
[97]	train-mlogloss:0.80763	validation-mlogloss:0.78495
[98]	train-mlogloss:0.80436	validation-mlogloss:0.78166
[99]	train-mlogloss:0.80149	validation-mlogloss:0.77872
[100]	train-mlogloss:0.79849	validation-mlogloss:0.77569
[101]	train-mlogloss:0.79573	validation-mlogloss:0.77269
[102]	train-mlogloss:0.79296	validation-mlogloss:0.76989
[103]	train-mlogloss:0.79024	validation-mlogloss:0.76712
[104]	train-mlogloss:0.78766	validation-mlogloss:0.76465
[105]	train-mlogloss:0.78504	validation-mlogloss:0.76175
[106]	train-mlogloss:0.78227	validation-mlogloss:0.75898
[107]	train-mlogloss:0.77962	validation-mlogloss:0.75616
[108]	train-mlogloss:0.77710	validation-mlogloss:0.75345
[109]	train-mlogloss:0.77472	validation-mlogloss:0.75104
[110]	train-mlogloss:0.77210	validation-mlogloss:0.74834
[111]	train-mlogloss:0.76968	validation-mlogloss:0.74582
[112]	train-mlogloss:0.76731	validation-mlogloss:0.74345
[113]	train-mlogloss:0.76499	validation-mlogloss:0.74114
[114]	train-mlogloss:0.76248	validation-mlogloss:0.73858
[115]	train-mlogloss:0.76006	validation-mlogloss:0.73620
[116]	train-mlogloss:0.75758	validation-mlogloss:0.73370
[117]	train-mlogloss:0.75520	validation-mlogloss:0.73126
[118]	train-mlogloss:0.75291	validation-mlogloss:0.72891
[119]	train-mlogloss:0.75055	validation-mlogloss:0.72658
[120]	train-mlogloss:0.74826	validation-mlogloss:0.72416
[121]	train-mlogloss:0.74584	validation-mlogloss:0.72181
[122]	train-mlogloss:0.74358	validation-mlogloss:0.71939
[123]	train-mlogloss:0.74128	validation-mlogloss:0.71713
[124]	train-mlogloss:0.73922	validation-mlogloss:0.71500
[125]	train-mlogloss:0.73696	validation-mlogloss:0.71279
[126]	train-mlogloss:0.73471	validation-mlogloss:0.71056
[127]	train-mlogloss:0.73276	validation-mlogloss:0.70859
[128]	train-mlogloss:0.73060	validation-mlogloss:0.70639
[129]	train-mlogloss:0.72845	validation-mlogloss:0.70413
[130]	train-mlogloss:0.72633	validation-mlogloss:0.70203
[131]	train-mlogloss:0.72426	validation-mlogloss:0.69994
[132]	train-mlogloss:0.72231	validation-mlogloss:0.69802
[133]	train-mlogloss:0.72023	validation-mlogloss:0.69595
[134]	train-mlogloss:0.71830	validation-mlogloss:0.69395
[135]	train-mlogloss:0.71629	validation-mlogloss:0.69189
[136]	train-mlogloss:0.71436	validation-mlogloss:0.68999
[137]	train-mlogloss:0.71259	validation-mlogloss:0.68812
[138]	train-mlogloss:0.71067	validation-mlogloss:0.68627
[139]	train-mlogloss:0.70889	validation-mlogloss:0.68440
[140]	train-mlogloss:0.70718	validation-mlogloss:0.68263
[141]	train-mlogloss:0.70525	validation-mlogloss:0.68069
[142]	train-mlogloss:0.70356	validation-mlogloss:0.67907
[143]	train-mlogloss:0.70171	validation-mlogloss:0.67740
[144]	train-mlogloss:0.70003	validation-mlogloss:0.67579
[145]	train-mlogloss:0.69841	validation-mlogloss:0.67415
[146]	train-mlogloss:0.69663	validation-mlogloss:0.67236
[147]	train-mlogloss:0.69489	validation-mlogloss:0.67059
[148]	train-mlogloss:0.69321	validation-mlogloss:0.66888
[149]	train-mlogloss:0.69155	validation-mlogloss:0.66713
[150]	train-mlogloss:0.69001	validation-mlogloss:0.66552
[151]	train-mlogloss:0.68823	validation-mlogloss:0.66389
[152]	train-mlogloss:0.68654	validation-mlogloss:0.66232
[153]	train-mlogloss:0.68490	validation-mlogloss:0.66071
[154]	train-mlogloss:0.68325	validation-mlogloss:0.65903
[155]	train-mlogloss:0.68150	validation-mlogloss:0.65736
[156]	train-mlogloss:0.67994	validation-mlogloss:0.65569
[157]	train-mlogloss:0.67839	validation-mlogloss:0.65417
[158]	train-mlogloss:0.67680	validation-mlogloss:0.65267
[159]	train-mlogloss:0.67523	validation-mlogloss:0.65102
[160]	train-mlogloss:0.67381	validation-mlogloss:0.64950
[161]	train-mlogloss:0.67239	validation-mlogloss:0.64809
[162]	train-mlogloss:0.67088	validation-mlogloss:0.64660
[163]	train-mlogloss:0.66939	validation-mlogloss:0.64514
[164]	train-mlogloss:0.66779	validation-mlogloss:0.64370
[165]	train-mlogloss:0.66630	validation-mlogloss:0.64240
[166]	train-mlogloss:0.66490	validation-mlogloss:0.64105
[167]	train-mlogloss:0.66355	validation-mlogloss:0.63981
[168]	train-mlogloss:0.66220	validation-mlogloss:0.63850
[169]	train-mlogloss:0.66084	validation-mlogloss:0.63705
[170]	train-mlogloss:0.65965	validation-mlogloss:0.63569
[171]	train-mlogloss:0.65835	validation-mlogloss:0.63424
[172]	train-mlogloss:0.65701	validation-mlogloss:0.63284
[173]	train-mlogloss:0.65567	validation-mlogloss:0.63158
[174]	train-mlogloss:0.65449	validation-mlogloss:0.63034
[175]	train-mlogloss:0.65321	validation-mlogloss:0.62910
[176]	train-mlogloss:0.65196	validation-mlogloss:0.62791
[177]	train-mlogloss:0.65073	validation-mlogloss:0.62665
[178]	train-mlogloss:0.64943	validation-mlogloss:0.62549
[179]	train-mlogloss:0.64822	validation-mlogloss:0.62420
[180]	train-mlogloss:0.64708	validation-mlogloss:0.62300
[181]	train-mlogloss:0.64580	validation-mlogloss:0.62178
[182]	train-mlogloss:0.64451	validation-mlogloss:0.62060
[183]	train-mlogloss:0.64326	validation-mlogloss:0.61941
[184]	train-mlogloss:0.64198	validation-mlogloss:0.61821
[185]	train-mlogloss:0.64082	validation-mlogloss:0.61713
[186]	train-mlogloss:0.63959	validation-mlogloss:0.61582
[187]	train-mlogloss:0.63843	validation-mlogloss:0.61467
[188]	train-mlogloss:0.63730	validation-mlogloss:0.61364
[189]	train-mlogloss:0.63620	validation-mlogloss:0.61246
[190]	train-mlogloss:0.63509	validation-mlogloss:0.61127
[191]	train-mlogloss:0.63394	validation-mlogloss:0.61021
[192]	train-mlogloss:0.63284	validation-mlogloss:0.60908
[193]	train-mlogloss:0.63182	validation-mlogloss:0.60809
[194]	train-mlogloss:0.63073	validation-mlogloss:0.60696
[195]	train-mlogloss:0.62965	validation-mlogloss:0.60584
[196]	train-mlogloss:0.62867	validation-mlogloss:0.60484
[197]	train-mlogloss:0.62758	validation-mlogloss:0.60383
[198]	train-mlogloss:0.62658	validation-mlogloss:0.60281
[199]	train-mlogloss:0.62555	validation-mlogloss:0.60180
[200]	train-mlogloss:0.62450	validation-mlogloss:0.60078
[201]	train-mlogloss:0.62347	validation-mlogloss:0.59980
[202]	train-mlogloss:0.62249	validation-mlogloss:0.59893
[203]	train-mlogloss:0.62142	validation-mlogloss:0.59789
[204]	train-mlogloss:0.62032	validation-mlogloss:0.59689
[205]	train-mlogloss:0.61928	validation-mlogloss:0.59602
[206]	train-mlogloss:0.61824	validation-mlogloss:0.59492
[207]	train-mlogloss:0.61726	validation-mlogloss:0.59395
[208]	train-mlogloss:0.61639	validation-mlogloss:0.59305
[209]	train-mlogloss:0.61556	validation-mlogloss:0.59223
[210]	train-mlogloss:0.61459	validation-mlogloss:0.59135
[211]	train-mlogloss:0.61374	validation-mlogloss:0.59047
[212]	train-mlogloss:0.61286	validation-mlogloss:0.58962
[213]	train-mlogloss:0.61192	validation-mlogloss:0.58876
[214]	train-mlogloss:0.61098	validation-mlogloss:0.58783
[215]	train-mlogloss:0.61017	validation-mlogloss:0.58706
[216]	train-mlogloss:0.60925	validation-mlogloss:0.58618
[217]	train-mlogloss:0.60843	validation-mlogloss:0.58533
[218]	train-mlogloss:0.60754	validation-mlogloss:0.58443
[219]	train-mlogloss:0.60665	validation-mlogloss:0.58357
[220]	train-mlogloss:0.60579	validation-mlogloss:0.58276
[221]	train-mlogloss:0.60494	validation-mlogloss:0.58204
[222]	train-mlogloss:0.60406	validation-mlogloss:0.58120
[223]	train-mlogloss:0.60322	validation-mlogloss:0.58045
[224]	train-mlogloss:0.60238	validation-mlogloss:0.57962
[225]	train-mlogloss:0.60150	validation-mlogloss:0.57880
[226]	train-mlogloss:0.60074	validation-mlogloss:0.57807
[227]	train-mlogloss:0.59987	validation-mlogloss:0.57707
[228]	train-mlogloss:0.59909	validation-mlogloss:0.57624
[229]	train-mlogloss:0.59830	validation-mlogloss:0.57552
[230]	train-mlogloss:0.59758	validation-mlogloss:0.57477
[231]	train-mlogloss:0.59679	validation-mlogloss:0.57407
[232]	train-mlogloss:0.59597	validation-mlogloss:0.57338
[233]	train-mlogloss:0.59511	validation-mlogloss:0.57254
[234]	train-mlogloss:0.59423	validation-mlogloss:0.57159
[235]	train-mlogloss:0.59354	validation-mlogloss:0.57093
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Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[1 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.21 [%]
Global accuracy score (test) = 81.27 [%]
Global F1 score (train) = 79.56 [%]
Global F1 score (test) = 81.82 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.65      0.72      0.68       350
MODERATE-INTENSITY       0.69      0.67      0.68       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.97      0.92      0.95       322

          accuracy                           0.81      1372
         macro avg       0.82      0.81      0.82      1372
      weighted avg       0.82      0.81      0.82      1372


Accuracy capturado en la ejecución 10: 81.27 [%]
F1-score capturado en la ejecución 10: 81.82 [%]

=== EJECUCIÓN 11 ===

--- TRAIN (ejecución 11) ---

--- TEST (ejecución 11) ---
2025-11-03 17:22:09.241179: 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`.
2025-11-03 17:22:09.252838: 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 00:00:1762186929.266534  330157 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186929.270965  330157 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186929.281306  330157 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186929.281335  330157 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186929.281338  330157 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186929.281340  330157 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:22:09.284733: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37484	validation-mlogloss:1.37458
[1]	train-mlogloss:1.36339	validation-mlogloss:1.36247
[2]	train-mlogloss:1.35267	validation-mlogloss:1.35156
[3]	train-mlogloss:1.34162	validation-mlogloss:1.34003
[4]	train-mlogloss:1.33058	validation-mlogloss:1.32859
[5]	train-mlogloss:1.32017	validation-mlogloss:1.31759
[6]	train-mlogloss:1.30973	validation-mlogloss:1.30650
[7]	train-mlogloss:1.29966	validation-mlogloss:1.29616
[8]	train-mlogloss:1.28959	validation-mlogloss:1.28550
[9]	train-mlogloss:1.27967	validation-mlogloss:1.27528
[10]	train-mlogloss:1.27016	validation-mlogloss:1.26538
[11]	train-mlogloss:1.26076	validation-mlogloss:1.25533
[12]	train-mlogloss:1.25172	validation-mlogloss:1.24575
[13]	train-mlogloss:1.24260	validation-mlogloss:1.23610
[14]	train-mlogloss:1.23350	validation-mlogloss:1.22657
[15]	train-mlogloss:1.22468	validation-mlogloss:1.21712
[16]	train-mlogloss:1.21623	validation-mlogloss:1.20842
[17]	train-mlogloss:1.20798	validation-mlogloss:1.19991
[18]	train-mlogloss:1.19974	validation-mlogloss:1.19154
[19]	train-mlogloss:1.19138	validation-mlogloss:1.18287
[20]	train-mlogloss:1.18307	validation-mlogloss:1.17408
[21]	train-mlogloss:1.17519	validation-mlogloss:1.16587
[22]	train-mlogloss:1.16766	validation-mlogloss:1.15821
[23]	train-mlogloss:1.16013	validation-mlogloss:1.15033
[24]	train-mlogloss:1.15258	validation-mlogloss:1.14241
[25]	train-mlogloss:1.14520	validation-mlogloss:1.13490
[26]	train-mlogloss:1.13803	validation-mlogloss:1.12749
[27]	train-mlogloss:1.13088	validation-mlogloss:1.12010
[28]	train-mlogloss:1.12397	validation-mlogloss:1.11308
[29]	train-mlogloss:1.11684	validation-mlogloss:1.10542
[30]	train-mlogloss:1.10986	validation-mlogloss:1.09810
[31]	train-mlogloss:1.10320	validation-mlogloss:1.09120
[32]	train-mlogloss:1.09620	validation-mlogloss:1.08400
[33]	train-mlogloss:1.08997	validation-mlogloss:1.07773
[34]	train-mlogloss:1.08359	validation-mlogloss:1.07102
[35]	train-mlogloss:1.07729	validation-mlogloss:1.06436
[36]	train-mlogloss:1.07101	validation-mlogloss:1.05774
[37]	train-mlogloss:1.06485	validation-mlogloss:1.05155
[38]	train-mlogloss:1.05857	validation-mlogloss:1.04508
[39]	train-mlogloss:1.05249	validation-mlogloss:1.03880
[40]	train-mlogloss:1.04683	validation-mlogloss:1.03289
[41]	train-mlogloss:1.04090	validation-mlogloss:1.02680
[42]	train-mlogloss:1.03526	validation-mlogloss:1.02087
[43]	train-mlogloss:1.02968	validation-mlogloss:1.01509
[44]	train-mlogloss:1.02391	validation-mlogloss:1.00916
[45]	train-mlogloss:1.01850	validation-mlogloss:1.00331
[46]	train-mlogloss:1.01304	validation-mlogloss:0.99768
[47]	train-mlogloss:1.00744	validation-mlogloss:0.99190
[48]	train-mlogloss:1.00212	validation-mlogloss:0.98666
[49]	train-mlogloss:0.99672	validation-mlogloss:0.98117
[50]	train-mlogloss:0.99158	validation-mlogloss:0.97577
[51]	train-mlogloss:0.98620	validation-mlogloss:0.97017
[52]	train-mlogloss:0.98106	validation-mlogloss:0.96504
[53]	train-mlogloss:0.97603	validation-mlogloss:0.95995
[54]	train-mlogloss:0.97116	validation-mlogloss:0.95495
[55]	train-mlogloss:0.96621	validation-mlogloss:0.94972
[56]	train-mlogloss:0.96137	validation-mlogloss:0.94485
[57]	train-mlogloss:0.95666	validation-mlogloss:0.93990
[58]	train-mlogloss:0.95209	validation-mlogloss:0.93526
[59]	train-mlogloss:0.94755	validation-mlogloss:0.93065
[60]	train-mlogloss:0.94308	validation-mlogloss:0.92600
[61]	train-mlogloss:0.93852	validation-mlogloss:0.92132
[62]	train-mlogloss:0.93410	validation-mlogloss:0.91704
[63]	train-mlogloss:0.92986	validation-mlogloss:0.91289
[64]	train-mlogloss:0.92550	validation-mlogloss:0.90830
[65]	train-mlogloss:0.92114	validation-mlogloss:0.90381
[66]	train-mlogloss:0.91708	validation-mlogloss:0.89965
[67]	train-mlogloss:0.91288	validation-mlogloss:0.89551
[68]	train-mlogloss:0.90887	validation-mlogloss:0.89164
[69]	train-mlogloss:0.90479	validation-mlogloss:0.88753
[70]	train-mlogloss:0.90089	validation-mlogloss:0.88352
[71]	train-mlogloss:0.89694	validation-mlogloss:0.87942
[72]	train-mlogloss:0.89299	validation-mlogloss:0.87548
[73]	train-mlogloss:0.88919	validation-mlogloss:0.87153
[74]	train-mlogloss:0.88555	validation-mlogloss:0.86778
[75]	train-mlogloss:0.88183	validation-mlogloss:0.86402
[76]	train-mlogloss:0.87821	validation-mlogloss:0.86034
[77]	train-mlogloss:0.87468	validation-mlogloss:0.85678
[78]	train-mlogloss:0.87123	validation-mlogloss:0.85344
[79]	train-mlogloss:0.86766	validation-mlogloss:0.84982
[80]	train-mlogloss:0.86411	validation-mlogloss:0.84613
[81]	train-mlogloss:0.86051	validation-mlogloss:0.84238
[82]	train-mlogloss:0.85711	validation-mlogloss:0.83893
[83]	train-mlogloss:0.85374	validation-mlogloss:0.83568
[84]	train-mlogloss:0.85040	validation-mlogloss:0.83238
[85]	train-mlogloss:0.84710	validation-mlogloss:0.82881
[86]	train-mlogloss:0.84384	validation-mlogloss:0.82537
[87]	train-mlogloss:0.84056	validation-mlogloss:0.82188
[88]	train-mlogloss:0.83738	validation-mlogloss:0.81860
[89]	train-mlogloss:0.83420	validation-mlogloss:0.81547
[90]	train-mlogloss:0.83104	validation-mlogloss:0.81222
[91]	train-mlogloss:0.82806	validation-mlogloss:0.80905
[92]	train-mlogloss:0.82506	validation-mlogloss:0.80597
[93]	train-mlogloss:0.82222	validation-mlogloss:0.80304
[94]	train-mlogloss:0.81930	validation-mlogloss:0.80012
[95]	train-mlogloss:0.81629	validation-mlogloss:0.79698
[96]	train-mlogloss:0.81333	validation-mlogloss:0.79393
[97]	train-mlogloss:0.81054	validation-mlogloss:0.79110
[98]	train-mlogloss:0.80779	validation-mlogloss:0.78823
[99]	train-mlogloss:0.80505	validation-mlogloss:0.78542
[100]	train-mlogloss:0.80219	validation-mlogloss:0.78255
[101]	train-mlogloss:0.79959	validation-mlogloss:0.77983
[102]	train-mlogloss:0.79691	validation-mlogloss:0.77705
[103]	train-mlogloss:0.79420	validation-mlogloss:0.77429
[104]	train-mlogloss:0.79153	validation-mlogloss:0.77149
[105]	train-mlogloss:0.78898	validation-mlogloss:0.76885
[106]	train-mlogloss:0.78642	validation-mlogloss:0.76626
[107]	train-mlogloss:0.78397	validation-mlogloss:0.76386
[108]	train-mlogloss:0.78124	validation-mlogloss:0.76117
[109]	train-mlogloss:0.77848	validation-mlogloss:0.75846
[110]	train-mlogloss:0.77586	validation-mlogloss:0.75570
[111]	train-mlogloss:0.77340	validation-mlogloss:0.75319
[112]	train-mlogloss:0.77083	validation-mlogloss:0.75059
[113]	train-mlogloss:0.76829	validation-mlogloss:0.74806
[114]	train-mlogloss:0.76606	validation-mlogloss:0.74575
[115]	train-mlogloss:0.76371	validation-mlogloss:0.74333
[116]	train-mlogloss:0.76131	validation-mlogloss:0.74092
[117]	train-mlogloss:0.75881	validation-mlogloss:0.73836
[118]	train-mlogloss:0.75638	validation-mlogloss:0.73591
[119]	train-mlogloss:0.75420	validation-mlogloss:0.73358
[120]	train-mlogloss:0.75203	validation-mlogloss:0.73126
[121]	train-mlogloss:0.74992	validation-mlogloss:0.72914
[122]	train-mlogloss:0.74753	validation-mlogloss:0.72681
[123]	train-mlogloss:0.74533	validation-mlogloss:0.72451
[124]	train-mlogloss:0.74305	validation-mlogloss:0.72221
[125]	train-mlogloss:0.74092	validation-mlogloss:0.72000
[126]	train-mlogloss:0.73868	validation-mlogloss:0.71779
[127]	train-mlogloss:0.73651	validation-mlogloss:0.71562
[128]	train-mlogloss:0.73454	validation-mlogloss:0.71350
[129]	train-mlogloss:0.73242	validation-mlogloss:0.71142
[130]	train-mlogloss:0.73034	validation-mlogloss:0.70942
[131]	train-mlogloss:0.72832	validation-mlogloss:0.70740
[132]	train-mlogloss:0.72632	validation-mlogloss:0.70527
[133]	train-mlogloss:0.72443	validation-mlogloss:0.70342
[134]	train-mlogloss:0.72250	validation-mlogloss:0.70138
[135]	train-mlogloss:0.72068	validation-mlogloss:0.69947
[136]	train-mlogloss:0.71862	validation-mlogloss:0.69753
[137]	train-mlogloss:0.71682	validation-mlogloss:0.69565
[138]	train-mlogloss:0.71494	validation-mlogloss:0.69380
[139]	train-mlogloss:0.71299	validation-mlogloss:0.69183
[140]	train-mlogloss:0.71123	validation-mlogloss:0.69012
[141]	train-mlogloss:0.70935	validation-mlogloss:0.68825
[142]	train-mlogloss:0.70766	validation-mlogloss:0.68652
[143]	train-mlogloss:0.70600	validation-mlogloss:0.68473
[144]	train-mlogloss:0.70448	validation-mlogloss:0.68317
[145]	train-mlogloss:0.70269	validation-mlogloss:0.68128
[146]	train-mlogloss:0.70082	validation-mlogloss:0.67934
[147]	train-mlogloss:0.69907	validation-mlogloss:0.67755
[148]	train-mlogloss:0.69737	validation-mlogloss:0.67577
[149]	train-mlogloss:0.69563	validation-mlogloss:0.67406
[150]	train-mlogloss:0.69383	validation-mlogloss:0.67228
[151]	train-mlogloss:0.69218	validation-mlogloss:0.67062
[152]	train-mlogloss:0.69064	validation-mlogloss:0.66906
[153]	train-mlogloss:0.68904	validation-mlogloss:0.66748
[154]	train-mlogloss:0.68751	validation-mlogloss:0.66593
[155]	train-mlogloss:0.68585	validation-mlogloss:0.66430
[156]	train-mlogloss:0.68419	validation-mlogloss:0.66270
[157]	train-mlogloss:0.68256	validation-mlogloss:0.66116
[158]	train-mlogloss:0.68092	validation-mlogloss:0.65947
[159]	train-mlogloss:0.67952	validation-mlogloss:0.65796
[160]	train-mlogloss:0.67804	validation-mlogloss:0.65650
[161]	train-mlogloss:0.67657	validation-mlogloss:0.65504
[162]	train-mlogloss:0.67514	validation-mlogloss:0.65363
[163]	train-mlogloss:0.67365	validation-mlogloss:0.65216
[164]	train-mlogloss:0.67209	validation-mlogloss:0.65068
[165]	train-mlogloss:0.67052	validation-mlogloss:0.64900
[166]	train-mlogloss:0.66904	validation-mlogloss:0.64750
[167]	train-mlogloss:0.66778	validation-mlogloss:0.64623
[168]	train-mlogloss:0.66640	validation-mlogloss:0.64475
[169]	train-mlogloss:0.66492	validation-mlogloss:0.64329
[170]	train-mlogloss:0.66345	validation-mlogloss:0.64196
[171]	train-mlogloss:0.66208	validation-mlogloss:0.64059
[172]	train-mlogloss:0.66067	validation-mlogloss:0.63921
[173]	train-mlogloss:0.65931	validation-mlogloss:0.63790
[174]	train-mlogloss:0.65798	validation-mlogloss:0.63664
[175]	train-mlogloss:0.65665	validation-mlogloss:0.63528
[176]	train-mlogloss:0.65526	validation-mlogloss:0.63397
[177]	train-mlogloss:0.65396	validation-mlogloss:0.63269
[178]	train-mlogloss:0.65279	validation-mlogloss:0.63154
[179]	train-mlogloss:0.65163	validation-mlogloss:0.63044
[180]	train-mlogloss:0.65029	validation-mlogloss:0.62910
[181]	train-mlogloss:0.64908	validation-mlogloss:0.62793
[182]	train-mlogloss:0.64781	validation-mlogloss:0.62674
[183]	train-mlogloss:0.64672	validation-mlogloss:0.62569
[184]	train-mlogloss:0.64546	validation-mlogloss:0.62457
[185]	train-mlogloss:0.64427	validation-mlogloss:0.62344
[186]	train-mlogloss:0.64313	validation-mlogloss:0.62240
[187]	train-mlogloss:0.64189	validation-mlogloss:0.62115
[188]	train-mlogloss:0.64060	validation-mlogloss:0.61983
[189]	train-mlogloss:0.63953	validation-mlogloss:0.61873
[190]	train-mlogloss:0.63848	validation-mlogloss:0.61769
[191]	train-mlogloss:0.63737	validation-mlogloss:0.61664
[192]	train-mlogloss:0.63626	validation-mlogloss:0.61562
[193]	train-mlogloss:0.63524	validation-mlogloss:0.61459
[194]	train-mlogloss:0.63423	validation-mlogloss:0.61362
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[497]	train-mlogloss:0.51024	validation-mlogloss:0.50421
[498]	train-mlogloss:0.51016	validation-mlogloss:0.50414
[499]	train-mlogloss:0.51014	validation-mlogloss:0.50411
[500]	train-mlogloss:0.51004	validation-mlogloss:0.50404
[501]	train-mlogloss:0.50996	validation-mlogloss:0.50403
[502]	train-mlogloss:0.50984	validation-mlogloss:0.50394
[503]	train-mlogloss:0.50976	validation-mlogloss:0.50382
[504]	train-mlogloss:0.50965	validation-mlogloss:0.50375
[505]	train-mlogloss:0.50954	validation-mlogloss:0.50363
[506]	train-mlogloss:0.50945	validation-mlogloss:0.50350
[507]	train-mlogloss:0.50931	validation-mlogloss:0.50334
[508]	train-mlogloss:0.50922	validation-mlogloss:0.50321
[509]	train-mlogloss:0.50912	validation-mlogloss:0.50309
[510]	train-mlogloss:0.50900	validation-mlogloss:0.50297
[511]	train-mlogloss:0.50887	validation-mlogloss:0.50284
[512]	train-mlogloss:0.50876	validation-mlogloss:0.50276
[513]	train-mlogloss:0.50869	validation-mlogloss:0.50274
[514]	train-mlogloss:0.50861	validation-mlogloss:0.50267
[515]	train-mlogloss:0.50851	validation-mlogloss:0.50257
[516]	train-mlogloss:0.50841	validation-mlogloss:0.50248
[517]	train-mlogloss:0.50824	validation-mlogloss:0.50231
[518]	train-mlogloss:0.50812	validation-mlogloss:0.50216
[519]	train-mlogloss:0.50801	validation-mlogloss:0.50205
[520]	train-mlogloss:0.50794	validation-mlogloss:0.50200
[521]	train-mlogloss:0.50784	validation-mlogloss:0.50185
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 1 2 ... 0 3 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.1 [%]
Global accuracy score (test) = 80.54 [%]
Global F1 score (train) = 79.48 [%]
Global F1 score (test) = 81.06 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.71      0.67       350
MODERATE-INTENSITY       0.67      0.63      0.65       350
         SEDENTARY       0.99      0.96      0.97       350
VIGOROUS-INTENSITY       0.97      0.92      0.94       322

          accuracy                           0.81      1372
         macro avg       0.82      0.81      0.81      1372
      weighted avg       0.81      0.81      0.81      1372


Accuracy capturado en la ejecución 11: 80.54 [%]
F1-score capturado en la ejecución 11: 81.06 [%]

=== EJECUCIÓN 12 ===

--- TRAIN (ejecución 12) ---

--- TEST (ejecución 12) ---
2025-11-03 17:22:27.928551: 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`.
2025-11-03 17:22:27.940343: 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 00:00:1762186947.954252  330475 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186947.958667  330475 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186947.968760  330475 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186947.968789  330475 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186947.968792  330475 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186947.968795  330475 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:22:27.972114: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37474	validation-mlogloss:1.37418
[1]	train-mlogloss:1.36327	validation-mlogloss:1.36246
[2]	train-mlogloss:1.35195	validation-mlogloss:1.35063
[3]	train-mlogloss:1.34104	validation-mlogloss:1.33941
[4]	train-mlogloss:1.33010	validation-mlogloss:1.32782
[5]	train-mlogloss:1.31970	validation-mlogloss:1.31689
[6]	train-mlogloss:1.30936	validation-mlogloss:1.30597
[7]	train-mlogloss:1.29908	validation-mlogloss:1.29524
[8]	train-mlogloss:1.28936	validation-mlogloss:1.28513
[9]	train-mlogloss:1.27955	validation-mlogloss:1.27484
[10]	train-mlogloss:1.26976	validation-mlogloss:1.26456
[11]	train-mlogloss:1.26048	validation-mlogloss:1.25493
[12]	train-mlogloss:1.25130	validation-mlogloss:1.24525
[13]	train-mlogloss:1.24201	validation-mlogloss:1.23549
[14]	train-mlogloss:1.23329	validation-mlogloss:1.22624
[15]	train-mlogloss:1.22459	validation-mlogloss:1.21742
[16]	train-mlogloss:1.21596	validation-mlogloss:1.20837
[17]	train-mlogloss:1.20721	validation-mlogloss:1.19924
[18]	train-mlogloss:1.19869	validation-mlogloss:1.19049
[19]	train-mlogloss:1.19053	validation-mlogloss:1.18197
[20]	train-mlogloss:1.18234	validation-mlogloss:1.17332
[21]	train-mlogloss:1.17435	validation-mlogloss:1.16492
[22]	train-mlogloss:1.16631	validation-mlogloss:1.15667
[23]	train-mlogloss:1.15858	validation-mlogloss:1.14847
[24]	train-mlogloss:1.15113	validation-mlogloss:1.14084
[25]	train-mlogloss:1.14371	validation-mlogloss:1.13318
[26]	train-mlogloss:1.13620	validation-mlogloss:1.12553
[27]	train-mlogloss:1.12883	validation-mlogloss:1.11810
[28]	train-mlogloss:1.12186	validation-mlogloss:1.11090
[29]	train-mlogloss:1.11503	validation-mlogloss:1.10368
[30]	train-mlogloss:1.10789	validation-mlogloss:1.09625
[31]	train-mlogloss:1.10115	validation-mlogloss:1.08926
[32]	train-mlogloss:1.09419	validation-mlogloss:1.08208
[33]	train-mlogloss:1.08774	validation-mlogloss:1.07527
[34]	train-mlogloss:1.08147	validation-mlogloss:1.06878
[35]	train-mlogloss:1.07535	validation-mlogloss:1.06226
[36]	train-mlogloss:1.06910	validation-mlogloss:1.05566
[37]	train-mlogloss:1.06291	validation-mlogloss:1.04916
[38]	train-mlogloss:1.05675	validation-mlogloss:1.04282
[39]	train-mlogloss:1.05084	validation-mlogloss:1.03655
[40]	train-mlogloss:1.04513	validation-mlogloss:1.03065
[41]	train-mlogloss:1.03945	validation-mlogloss:1.02503
[42]	train-mlogloss:1.03374	validation-mlogloss:1.01903
[43]	train-mlogloss:1.02820	validation-mlogloss:1.01321
[44]	train-mlogloss:1.02249	validation-mlogloss:1.00727
[45]	train-mlogloss:1.01682	validation-mlogloss:1.00154
[46]	train-mlogloss:1.01138	validation-mlogloss:0.99598
[47]	train-mlogloss:1.00598	validation-mlogloss:0.99050
[48]	train-mlogloss:1.00066	validation-mlogloss:0.98496
[49]	train-mlogloss:0.99535	validation-mlogloss:0.97958
[50]	train-mlogloss:0.99018	validation-mlogloss:0.97415
[51]	train-mlogloss:0.98486	validation-mlogloss:0.96875
[52]	train-mlogloss:0.97975	validation-mlogloss:0.96339
[53]	train-mlogloss:0.97477	validation-mlogloss:0.95829
[54]	train-mlogloss:0.96988	validation-mlogloss:0.95329
[55]	train-mlogloss:0.96492	validation-mlogloss:0.94819
[56]	train-mlogloss:0.96028	validation-mlogloss:0.94355
[57]	train-mlogloss:0.95562	validation-mlogloss:0.93870
[58]	train-mlogloss:0.95098	validation-mlogloss:0.93390
[59]	train-mlogloss:0.94653	validation-mlogloss:0.92935
[60]	train-mlogloss:0.94200	validation-mlogloss:0.92475
[61]	train-mlogloss:0.93753	validation-mlogloss:0.92026
[62]	train-mlogloss:0.93315	validation-mlogloss:0.91565
[63]	train-mlogloss:0.92880	validation-mlogloss:0.91127
[64]	train-mlogloss:0.92450	validation-mlogloss:0.90685
[65]	train-mlogloss:0.92030	validation-mlogloss:0.90254
[66]	train-mlogloss:0.91613	validation-mlogloss:0.89821
[67]	train-mlogloss:0.91202	validation-mlogloss:0.89390
[68]	train-mlogloss:0.90792	validation-mlogloss:0.88961
[69]	train-mlogloss:0.90389	validation-mlogloss:0.88542
[70]	train-mlogloss:0.89997	validation-mlogloss:0.88141
[71]	train-mlogloss:0.89612	validation-mlogloss:0.87771
[72]	train-mlogloss:0.89226	validation-mlogloss:0.87386
[73]	train-mlogloss:0.88848	validation-mlogloss:0.87002
[74]	train-mlogloss:0.88467	validation-mlogloss:0.86617
[75]	train-mlogloss:0.88082	validation-mlogloss:0.86234
[76]	train-mlogloss:0.87686	validation-mlogloss:0.85834
[77]	train-mlogloss:0.87324	validation-mlogloss:0.85449
[78]	train-mlogloss:0.86969	validation-mlogloss:0.85075
[79]	train-mlogloss:0.86600	validation-mlogloss:0.84697
[80]	train-mlogloss:0.86253	validation-mlogloss:0.84339
[81]	train-mlogloss:0.85904	validation-mlogloss:0.83978
[82]	train-mlogloss:0.85554	validation-mlogloss:0.83609
[83]	train-mlogloss:0.85202	validation-mlogloss:0.83234
[84]	train-mlogloss:0.84842	validation-mlogloss:0.82867
[85]	train-mlogloss:0.84516	validation-mlogloss:0.82530
[86]	train-mlogloss:0.84185	validation-mlogloss:0.82189
[87]	train-mlogloss:0.83854	validation-mlogloss:0.81863
[88]	train-mlogloss:0.83542	validation-mlogloss:0.81533
[89]	train-mlogloss:0.83215	validation-mlogloss:0.81197
[90]	train-mlogloss:0.82898	validation-mlogloss:0.80865
[91]	train-mlogloss:0.82601	validation-mlogloss:0.80556
[92]	train-mlogloss:0.82299	validation-mlogloss:0.80245
[93]	train-mlogloss:0.81994	validation-mlogloss:0.79919
[94]	train-mlogloss:0.81699	validation-mlogloss:0.79612
[95]	train-mlogloss:0.81410	validation-mlogloss:0.79312
[96]	train-mlogloss:0.81131	validation-mlogloss:0.79020
[97]	train-mlogloss:0.80854	validation-mlogloss:0.78761
[98]	train-mlogloss:0.80558	validation-mlogloss:0.78464
[99]	train-mlogloss:0.80278	validation-mlogloss:0.78170
[100]	train-mlogloss:0.80006	validation-mlogloss:0.77885
[101]	train-mlogloss:0.79737	validation-mlogloss:0.77604
[102]	train-mlogloss:0.79464	validation-mlogloss:0.77314
[103]	train-mlogloss:0.79210	validation-mlogloss:0.77057
[104]	train-mlogloss:0.78944	validation-mlogloss:0.76782
[105]	train-mlogloss:0.78669	validation-mlogloss:0.76495
[106]	train-mlogloss:0.78407	validation-mlogloss:0.76233
[107]	train-mlogloss:0.78128	validation-mlogloss:0.75944
[108]	train-mlogloss:0.77868	validation-mlogloss:0.75674
[109]	train-mlogloss:0.77609	validation-mlogloss:0.75414
[110]	train-mlogloss:0.77340	validation-mlogloss:0.75144
[111]	train-mlogloss:0.77098	validation-mlogloss:0.74894
[112]	train-mlogloss:0.76858	validation-mlogloss:0.74652
[113]	train-mlogloss:0.76635	validation-mlogloss:0.74435
[114]	train-mlogloss:0.76400	validation-mlogloss:0.74189
[115]	train-mlogloss:0.76162	validation-mlogloss:0.73943
[116]	train-mlogloss:0.75931	validation-mlogloss:0.73709
[117]	train-mlogloss:0.75716	validation-mlogloss:0.73484
[118]	train-mlogloss:0.75473	validation-mlogloss:0.73241
[119]	train-mlogloss:0.75263	validation-mlogloss:0.73026
[120]	train-mlogloss:0.75018	validation-mlogloss:0.72785
[121]	train-mlogloss:0.74782	validation-mlogloss:0.72555
[122]	train-mlogloss:0.74574	validation-mlogloss:0.72337
[123]	train-mlogloss:0.74376	validation-mlogloss:0.72139
[124]	train-mlogloss:0.74146	validation-mlogloss:0.71908
[125]	train-mlogloss:0.73921	validation-mlogloss:0.71687
[126]	train-mlogloss:0.73711	validation-mlogloss:0.71474
[127]	train-mlogloss:0.73505	validation-mlogloss:0.71251
[128]	train-mlogloss:0.73279	validation-mlogloss:0.71032
[129]	train-mlogloss:0.73068	validation-mlogloss:0.70816
[130]	train-mlogloss:0.72877	validation-mlogloss:0.70619
[131]	train-mlogloss:0.72688	validation-mlogloss:0.70426
[132]	train-mlogloss:0.72479	validation-mlogloss:0.70213
[133]	train-mlogloss:0.72266	validation-mlogloss:0.69998
[134]	train-mlogloss:0.72059	validation-mlogloss:0.69787
[135]	train-mlogloss:0.71865	validation-mlogloss:0.69584
[136]	train-mlogloss:0.71681	validation-mlogloss:0.69389
[137]	train-mlogloss:0.71484	validation-mlogloss:0.69179
[138]	train-mlogloss:0.71296	validation-mlogloss:0.68999
[139]	train-mlogloss:0.71110	validation-mlogloss:0.68819
[140]	train-mlogloss:0.70911	validation-mlogloss:0.68620
[141]	train-mlogloss:0.70727	validation-mlogloss:0.68438
[142]	train-mlogloss:0.70543	validation-mlogloss:0.68244
[143]	train-mlogloss:0.70375	validation-mlogloss:0.68067
[144]	train-mlogloss:0.70192	validation-mlogloss:0.67883
[145]	train-mlogloss:0.70008	validation-mlogloss:0.67703
[146]	train-mlogloss:0.69840	validation-mlogloss:0.67532
[147]	train-mlogloss:0.69680	validation-mlogloss:0.67364
[148]	train-mlogloss:0.69515	validation-mlogloss:0.67199
[149]	train-mlogloss:0.69355	validation-mlogloss:0.67040
[150]	train-mlogloss:0.69177	validation-mlogloss:0.66867
[151]	train-mlogloss:0.69001	validation-mlogloss:0.66689
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[454]	train-mlogloss:0.51215	validation-mlogloss:0.50328
[455]	train-mlogloss:0.51201	validation-mlogloss:0.50312
[456]	train-mlogloss:0.51181	validation-mlogloss:0.50292
[457]	train-mlogloss:0.51167	validation-mlogloss:0.50283
[458]	train-mlogloss:0.51142	validation-mlogloss:0.50267
[459]	train-mlogloss:0.51124	validation-mlogloss:0.50254
[460]	train-mlogloss:0.51108	validation-mlogloss:0.50242
[461]	train-mlogloss:0.51095	validation-mlogloss:0.50230
[462]	train-mlogloss:0.51079	validation-mlogloss:0.50213
[463]	train-mlogloss:0.51063	validation-mlogloss:0.50195
[464]	train-mlogloss:0.51042	validation-mlogloss:0.50177
[465]	train-mlogloss:0.51034	validation-mlogloss:0.50172
[466]	train-mlogloss:0.51025	validation-mlogloss:0.50165
[467]	train-mlogloss:0.51016	validation-mlogloss:0.50157
[468]	train-mlogloss:0.50998	validation-mlogloss:0.50140
[469]	train-mlogloss:0.50984	validation-mlogloss:0.50127
[470]	train-mlogloss:0.50964	validation-mlogloss:0.50114
[471]	train-mlogloss:0.50949	validation-mlogloss:0.50105
[472]	train-mlogloss:0.50938	validation-mlogloss:0.50090
[473]	train-mlogloss:0.50928	validation-mlogloss:0.50086
[474]	train-mlogloss:0.50913	validation-mlogloss:0.50071
[475]	train-mlogloss:0.50905	validation-mlogloss:0.50060
[476]	train-mlogloss:0.50893	validation-mlogloss:0.50060
[477]	train-mlogloss:0.50874	validation-mlogloss:0.50045
[478]	train-mlogloss:0.50867	validation-mlogloss:0.50043
[479]	train-mlogloss:0.50860	validation-mlogloss:0.50036
[480]	train-mlogloss:0.50845	validation-mlogloss:0.50032
[481]	train-mlogloss:0.50830	validation-mlogloss:0.50021
[482]	train-mlogloss:0.50817	validation-mlogloss:0.50016
[483]	train-mlogloss:0.50804	validation-mlogloss:0.50004
[484]	train-mlogloss:0.50796	validation-mlogloss:0.49997
[485]	train-mlogloss:0.50780	validation-mlogloss:0.49995
[486]	train-mlogloss:0.50770	validation-mlogloss:0.49994
[487]	train-mlogloss:0.50760	validation-mlogloss:0.49984
[488]	train-mlogloss:0.50747	validation-mlogloss:0.49965
[489]	train-mlogloss:0.50732	validation-mlogloss:0.49950
[490]	train-mlogloss:0.50724	validation-mlogloss:0.49947
[491]	train-mlogloss:0.50715	validation-mlogloss:0.49945
[492]	train-mlogloss:0.50706	validation-mlogloss:0.49933
[493]	train-mlogloss:0.50685	validation-mlogloss:0.49917
[494]	train-mlogloss:0.50675	validation-mlogloss:0.49912
[495]	train-mlogloss:0.50666	validation-mlogloss:0.49911
[496]	train-mlogloss:0.50649	validation-mlogloss:0.49897
[497]	train-mlogloss:0.50638	validation-mlogloss:0.49885
[498]	train-mlogloss:0.50626	validation-mlogloss:0.49873
[499]	train-mlogloss:0.50617	validation-mlogloss:0.49873
[500]	train-mlogloss:0.50606	validation-mlogloss:0.49862
[501]	train-mlogloss:0.50591	validation-mlogloss:0.49855
[502]	train-mlogloss:0.50582	validation-mlogloss:0.49844
[503]	train-mlogloss:0.50576	validation-mlogloss:0.49840
[504]	train-mlogloss:0.50563	validation-mlogloss:0.49827
[505]	train-mlogloss:0.50557	validation-mlogloss:0.49821
[506]	train-mlogloss:0.50546	validation-mlogloss:0.49807
[507]	train-mlogloss:0.50536	validation-mlogloss:0.49795
[508]	train-mlogloss:0.50518	validation-mlogloss:0.49777
[509]	train-mlogloss:0.50512	validation-mlogloss:0.49770
[510]	train-mlogloss:0.50504	validation-mlogloss:0.49763
[511]	train-mlogloss:0.50494	validation-mlogloss:0.49761
[512]	train-mlogloss:0.50487	validation-mlogloss:0.49752
[513]	train-mlogloss:0.50476	validation-mlogloss:0.49744
[514]	train-mlogloss:0.50468	validation-mlogloss:0.49738
[515]	train-mlogloss:0.50454	validation-mlogloss:0.49720
[516]	train-mlogloss:0.50437	validation-mlogloss:0.49701
[517]	train-mlogloss:0.50428	validation-mlogloss:0.49687
[518]	train-mlogloss:0.50410	validation-mlogloss:0.49676
[519]	train-mlogloss:0.50402	validation-mlogloss:0.49671
[520]	train-mlogloss:0.50388	validation-mlogloss:0.49660
[521]	train-mlogloss:0.50373	validation-mlogloss:0.49647
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[0 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 78.93 [%]
Global accuracy score (test) = 79.52 [%]
Global F1 score (train) = 79.27 [%]
Global F1 score (test) = 80.06 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.71      0.66       350
MODERATE-INTENSITY       0.65      0.62      0.64       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.95      0.92      0.94       322

          accuracy                           0.80      1372
         macro avg       0.81      0.80      0.80      1372
      weighted avg       0.80      0.80      0.80      1372


Accuracy capturado en la ejecución 12: 79.52 [%]
F1-score capturado en la ejecución 12: 80.06 [%]

=== EJECUCIÓN 13 ===

--- TRAIN (ejecución 13) ---

--- TEST (ejecución 13) ---
2025-11-03 17:22:46.798662: 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`.
2025-11-03 17:22:46.810419: 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 00:00:1762186966.824084  330788 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186966.828203  330788 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186966.838805  330788 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186966.838837  330788 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186966.838840  330788 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186966.838841  330788 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:22:46.842113: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37452	validation-mlogloss:1.37387
[1]	train-mlogloss:1.36318	validation-mlogloss:1.36230
[2]	train-mlogloss:1.35196	validation-mlogloss:1.35052
[3]	train-mlogloss:1.34090	validation-mlogloss:1.33892
[4]	train-mlogloss:1.33008	validation-mlogloss:1.32759
[5]	train-mlogloss:1.31956	validation-mlogloss:1.31661
[6]	train-mlogloss:1.30935	validation-mlogloss:1.30587
[7]	train-mlogloss:1.29914	validation-mlogloss:1.29509
[8]	train-mlogloss:1.28958	validation-mlogloss:1.28505
[9]	train-mlogloss:1.27951	validation-mlogloss:1.27475
[10]	train-mlogloss:1.26982	validation-mlogloss:1.26448
[11]	train-mlogloss:1.26043	validation-mlogloss:1.25466
[12]	train-mlogloss:1.25122	validation-mlogloss:1.24501
[13]	train-mlogloss:1.24191	validation-mlogloss:1.23522
[14]	train-mlogloss:1.23323	validation-mlogloss:1.22623
[15]	train-mlogloss:1.22446	validation-mlogloss:1.21728
[16]	train-mlogloss:1.21597	validation-mlogloss:1.20848
[17]	train-mlogloss:1.20746	validation-mlogloss:1.19977
[18]	train-mlogloss:1.19879	validation-mlogloss:1.19040
[19]	train-mlogloss:1.19079	validation-mlogloss:1.18212
[20]	train-mlogloss:1.18290	validation-mlogloss:1.17399
[21]	train-mlogloss:1.17488	validation-mlogloss:1.16556
[22]	train-mlogloss:1.16736	validation-mlogloss:1.15763
[23]	train-mlogloss:1.15982	validation-mlogloss:1.14973
[24]	train-mlogloss:1.15220	validation-mlogloss:1.14179
[25]	train-mlogloss:1.14470	validation-mlogloss:1.13390
[26]	train-mlogloss:1.13749	validation-mlogloss:1.12627
[27]	train-mlogloss:1.13051	validation-mlogloss:1.11924
[28]	train-mlogloss:1.12358	validation-mlogloss:1.11206
[29]	train-mlogloss:1.11658	validation-mlogloss:1.10466
[30]	train-mlogloss:1.10992	validation-mlogloss:1.09769
[31]	train-mlogloss:1.10319	validation-mlogloss:1.09073
[32]	train-mlogloss:1.09641	validation-mlogloss:1.08364
[33]	train-mlogloss:1.08985	validation-mlogloss:1.07668
[34]	train-mlogloss:1.08315	validation-mlogloss:1.06964
[35]	train-mlogloss:1.07670	validation-mlogloss:1.06286
[36]	train-mlogloss:1.07057	validation-mlogloss:1.05638
[37]	train-mlogloss:1.06451	validation-mlogloss:1.05008
[38]	train-mlogloss:1.05851	validation-mlogloss:1.04374
[39]	train-mlogloss:1.05273	validation-mlogloss:1.03762
[40]	train-mlogloss:1.04701	validation-mlogloss:1.03174
[41]	train-mlogloss:1.04116	validation-mlogloss:1.02567
[42]	train-mlogloss:1.03557	validation-mlogloss:1.02011
[43]	train-mlogloss:1.02997	validation-mlogloss:1.01421
[44]	train-mlogloss:1.02466	validation-mlogloss:1.00876
[45]	train-mlogloss:1.01909	validation-mlogloss:1.00292
[46]	train-mlogloss:1.01359	validation-mlogloss:0.99735
[47]	train-mlogloss:1.00835	validation-mlogloss:0.99218
[48]	train-mlogloss:1.00328	validation-mlogloss:0.98695
[49]	train-mlogloss:0.99790	validation-mlogloss:0.98164
[50]	train-mlogloss:0.99278	validation-mlogloss:0.97624
[51]	train-mlogloss:0.98780	validation-mlogloss:0.97124
[52]	train-mlogloss:0.98274	validation-mlogloss:0.96626
[53]	train-mlogloss:0.97778	validation-mlogloss:0.96142
[54]	train-mlogloss:0.97276	validation-mlogloss:0.95610
[55]	train-mlogloss:0.96825	validation-mlogloss:0.95132
[56]	train-mlogloss:0.96348	validation-mlogloss:0.94631
[57]	train-mlogloss:0.95893	validation-mlogloss:0.94154
[58]	train-mlogloss:0.95429	validation-mlogloss:0.93675
[59]	train-mlogloss:0.94974	validation-mlogloss:0.93196
[60]	train-mlogloss:0.94528	validation-mlogloss:0.92762
[61]	train-mlogloss:0.94080	validation-mlogloss:0.92288
[62]	train-mlogloss:0.93629	validation-mlogloss:0.91831
[63]	train-mlogloss:0.93185	validation-mlogloss:0.91384
[64]	train-mlogloss:0.92749	validation-mlogloss:0.90942
[65]	train-mlogloss:0.92341	validation-mlogloss:0.90550
[66]	train-mlogloss:0.91932	validation-mlogloss:0.90133
[67]	train-mlogloss:0.91499	validation-mlogloss:0.89705
[68]	train-mlogloss:0.91102	validation-mlogloss:0.89305
[69]	train-mlogloss:0.90702	validation-mlogloss:0.88891
[70]	train-mlogloss:0.90305	validation-mlogloss:0.88482
[71]	train-mlogloss:0.89908	validation-mlogloss:0.88084
[72]	train-mlogloss:0.89536	validation-mlogloss:0.87714
[73]	train-mlogloss:0.89146	validation-mlogloss:0.87312
[74]	train-mlogloss:0.88759	validation-mlogloss:0.86917
[75]	train-mlogloss:0.88383	validation-mlogloss:0.86530
[76]	train-mlogloss:0.88014	validation-mlogloss:0.86155
[77]	train-mlogloss:0.87665	validation-mlogloss:0.85825
[78]	train-mlogloss:0.87322	validation-mlogloss:0.85480
[79]	train-mlogloss:0.86978	validation-mlogloss:0.85134
[80]	train-mlogloss:0.86610	validation-mlogloss:0.84766
[81]	train-mlogloss:0.86263	validation-mlogloss:0.84394
[82]	train-mlogloss:0.85915	validation-mlogloss:0.84030
[83]	train-mlogloss:0.85570	validation-mlogloss:0.83683
[84]	train-mlogloss:0.85244	validation-mlogloss:0.83355
[85]	train-mlogloss:0.84932	validation-mlogloss:0.83036
[86]	train-mlogloss:0.84605	validation-mlogloss:0.82695
[87]	train-mlogloss:0.84277	validation-mlogloss:0.82334
[88]	train-mlogloss:0.83952	validation-mlogloss:0.82003
[89]	train-mlogloss:0.83657	validation-mlogloss:0.81701
[90]	train-mlogloss:0.83343	validation-mlogloss:0.81377
[91]	train-mlogloss:0.83031	validation-mlogloss:0.81049
[92]	train-mlogloss:0.82741	validation-mlogloss:0.80745
[93]	train-mlogloss:0.82442	validation-mlogloss:0.80441
[94]	train-mlogloss:0.82143	validation-mlogloss:0.80127
[95]	train-mlogloss:0.81845	validation-mlogloss:0.79815
[96]	train-mlogloss:0.81550	validation-mlogloss:0.79526
[97]	train-mlogloss:0.81259	validation-mlogloss:0.79239
[98]	train-mlogloss:0.80977	validation-mlogloss:0.78946
[99]	train-mlogloss:0.80684	validation-mlogloss:0.78655
[100]	train-mlogloss:0.80407	validation-mlogloss:0.78378
[101]	train-mlogloss:0.80102	validation-mlogloss:0.78075
[102]	train-mlogloss:0.79826	validation-mlogloss:0.77780
[103]	train-mlogloss:0.79563	validation-mlogloss:0.77497
[104]	train-mlogloss:0.79294	validation-mlogloss:0.77197
[105]	train-mlogloss:0.79024	validation-mlogloss:0.76930
[106]	train-mlogloss:0.78767	validation-mlogloss:0.76654
[107]	train-mlogloss:0.78510	validation-mlogloss:0.76378
[108]	train-mlogloss:0.78260	validation-mlogloss:0.76120
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[411]	train-mlogloss:0.52350	validation-mlogloss:0.51189
[412]	train-mlogloss:0.52337	validation-mlogloss:0.51181
[413]	train-mlogloss:0.52312	validation-mlogloss:0.51163
[414]	train-mlogloss:0.52288	validation-mlogloss:0.51150
[415]	train-mlogloss:0.52265	validation-mlogloss:0.51129
[416]	train-mlogloss:0.52238	validation-mlogloss:0.51103
[417]	train-mlogloss:0.52218	validation-mlogloss:0.51091
[418]	train-mlogloss:0.52203	validation-mlogloss:0.51084
[419]	train-mlogloss:0.52183	validation-mlogloss:0.51061
[420]	train-mlogloss:0.52163	validation-mlogloss:0.51047
[421]	train-mlogloss:0.52138	validation-mlogloss:0.51030
[422]	train-mlogloss:0.52115	validation-mlogloss:0.51015
[423]	train-mlogloss:0.52092	validation-mlogloss:0.50985
[424]	train-mlogloss:0.52077	validation-mlogloss:0.50969
[425]	train-mlogloss:0.52060	validation-mlogloss:0.50955
[426]	train-mlogloss:0.52040	validation-mlogloss:0.50941
[427]	train-mlogloss:0.52023	validation-mlogloss:0.50931
[428]	train-mlogloss:0.52008	validation-mlogloss:0.50918
[429]	train-mlogloss:0.51984	validation-mlogloss:0.50895
[430]	train-mlogloss:0.51964	validation-mlogloss:0.50884
[431]	train-mlogloss:0.51954	validation-mlogloss:0.50871
[432]	train-mlogloss:0.51931	validation-mlogloss:0.50854
[433]	train-mlogloss:0.51919	validation-mlogloss:0.50850
[434]	train-mlogloss:0.51901	validation-mlogloss:0.50835
[435]	train-mlogloss:0.51882	validation-mlogloss:0.50831
[436]	train-mlogloss:0.51865	validation-mlogloss:0.50809
[437]	train-mlogloss:0.51844	validation-mlogloss:0.50791
[438]	train-mlogloss:0.51828	validation-mlogloss:0.50778
[439]	train-mlogloss:0.51813	validation-mlogloss:0.50768
[440]	train-mlogloss:0.51800	validation-mlogloss:0.50755
[441]	train-mlogloss:0.51780	validation-mlogloss:0.50741
[442]	train-mlogloss:0.51764	validation-mlogloss:0.50727
[443]	train-mlogloss:0.51752	validation-mlogloss:0.50718
[444]	train-mlogloss:0.51739	validation-mlogloss:0.50703
[445]	train-mlogloss:0.51726	validation-mlogloss:0.50691
[446]	train-mlogloss:0.51714	validation-mlogloss:0.50674
[447]	train-mlogloss:0.51703	validation-mlogloss:0.50671
[448]	train-mlogloss:0.51686	validation-mlogloss:0.50656
[449]	train-mlogloss:0.51674	validation-mlogloss:0.50653
[450]	train-mlogloss:0.51659	validation-mlogloss:0.50638
[451]	train-mlogloss:0.51646	validation-mlogloss:0.50631
[452]	train-mlogloss:0.51628	validation-mlogloss:0.50609
[453]	train-mlogloss:0.51616	validation-mlogloss:0.50601
[454]	train-mlogloss:0.51600	validation-mlogloss:0.50586
[455]	train-mlogloss:0.51589	validation-mlogloss:0.50576
[456]	train-mlogloss:0.51566	validation-mlogloss:0.50547
[457]	train-mlogloss:0.51553	validation-mlogloss:0.50529
[458]	train-mlogloss:0.51534	validation-mlogloss:0.50520
[459]	train-mlogloss:0.51525	validation-mlogloss:0.50516
[460]	train-mlogloss:0.51514	validation-mlogloss:0.50504
[461]	train-mlogloss:0.51496	validation-mlogloss:0.50478
[462]	train-mlogloss:0.51486	validation-mlogloss:0.50471
[463]	train-mlogloss:0.51474	validation-mlogloss:0.50462
[464]	train-mlogloss:0.51461	validation-mlogloss:0.50453
[465]	train-mlogloss:0.51442	validation-mlogloss:0.50441
[466]	train-mlogloss:0.51421	validation-mlogloss:0.50424
[467]	train-mlogloss:0.51412	validation-mlogloss:0.50413
[468]	train-mlogloss:0.51401	validation-mlogloss:0.50399
[469]	train-mlogloss:0.51385	validation-mlogloss:0.50387
[470]	train-mlogloss:0.51377	validation-mlogloss:0.50375
[471]	train-mlogloss:0.51361	validation-mlogloss:0.50370
[472]	train-mlogloss:0.51345	validation-mlogloss:0.50353
[473]	train-mlogloss:0.51333	validation-mlogloss:0.50342
[474]	train-mlogloss:0.51323	validation-mlogloss:0.50328
[475]	train-mlogloss:0.51300	validation-mlogloss:0.50302
[476]	train-mlogloss:0.51286	validation-mlogloss:0.50299
[477]	train-mlogloss:0.51278	validation-mlogloss:0.50290
[478]	train-mlogloss:0.51273	validation-mlogloss:0.50287
[479]	train-mlogloss:0.51262	validation-mlogloss:0.50271
[480]	train-mlogloss:0.51243	validation-mlogloss:0.50258
[481]	train-mlogloss:0.51227	validation-mlogloss:0.50239
[482]	train-mlogloss:0.51216	validation-mlogloss:0.50237
[483]	train-mlogloss:0.51201	validation-mlogloss:0.50225
[484]	train-mlogloss:0.51190	validation-mlogloss:0.50215
[485]	train-mlogloss:0.51176	validation-mlogloss:0.50204
[486]	train-mlogloss:0.51166	validation-mlogloss:0.50193
[487]	train-mlogloss:0.51146	validation-mlogloss:0.50175
[488]	train-mlogloss:0.51136	validation-mlogloss:0.50167
[489]	train-mlogloss:0.51119	validation-mlogloss:0.50156
[490]	train-mlogloss:0.51098	validation-mlogloss:0.50143
[491]	train-mlogloss:0.51087	validation-mlogloss:0.50127
[492]	train-mlogloss:0.51071	validation-mlogloss:0.50116
[493]	train-mlogloss:0.51062	validation-mlogloss:0.50111
[494]	train-mlogloss:0.51053	validation-mlogloss:0.50102
[495]	train-mlogloss:0.51044	validation-mlogloss:0.50088
[496]	train-mlogloss:0.51028	validation-mlogloss:0.50072
[497]	train-mlogloss:0.51019	validation-mlogloss:0.50064
[498]	train-mlogloss:0.51005	validation-mlogloss:0.50058
[499]	train-mlogloss:0.50991	validation-mlogloss:0.50052
[500]	train-mlogloss:0.50980	validation-mlogloss:0.50049
[501]	train-mlogloss:0.50964	validation-mlogloss:0.50035
[502]	train-mlogloss:0.50955	validation-mlogloss:0.50024
[503]	train-mlogloss:0.50948	validation-mlogloss:0.50017
[504]	train-mlogloss:0.50936	validation-mlogloss:0.50008
[505]	train-mlogloss:0.50929	validation-mlogloss:0.50006
[506]	train-mlogloss:0.50919	validation-mlogloss:0.50005
[507]	train-mlogloss:0.50910	validation-mlogloss:0.49994
[508]	train-mlogloss:0.50903	validation-mlogloss:0.49986
[509]	train-mlogloss:0.50894	validation-mlogloss:0.49976
[510]	train-mlogloss:0.50886	validation-mlogloss:0.49972
[511]	train-mlogloss:0.50877	validation-mlogloss:0.49964
[512]	train-mlogloss:0.50869	validation-mlogloss:0.49956
[513]	train-mlogloss:0.50858	validation-mlogloss:0.49941
[514]	train-mlogloss:0.50846	validation-mlogloss:0.49925
[515]	train-mlogloss:0.50829	validation-mlogloss:0.49910
[516]	train-mlogloss:0.50825	validation-mlogloss:0.49908
[517]	train-mlogloss:0.50812	validation-mlogloss:0.49896
[518]	train-mlogloss:0.50804	validation-mlogloss:0.49887
[519]	train-mlogloss:0.50792	validation-mlogloss:0.49874
[520]	train-mlogloss:0.50779	validation-mlogloss:0.49863
[521]	train-mlogloss:0.50775	validation-mlogloss:0.49858
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 1 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.02 [%]
Global accuracy score (test) = 80.83 [%]
Global F1 score (train) = 79.35 [%]
Global F1 score (test) = 81.24 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.65      0.71      0.68       350
MODERATE-INTENSITY       0.67      0.65      0.66       350
         SEDENTARY       0.99      0.96      0.98       350
VIGOROUS-INTENSITY       0.95      0.92      0.93       322

          accuracy                           0.81      1372
         macro avg       0.82      0.81      0.81      1372
      weighted avg       0.81      0.81      0.81      1372


Accuracy capturado en la ejecución 13: 80.83 [%]
F1-score capturado en la ejecución 13: 81.24 [%]

=== EJECUCIÓN 14 ===

--- TRAIN (ejecución 14) ---

--- TEST (ejecución 14) ---
2025-11-03 17:23:05.455680: 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`.
2025-11-03 17:23:05.467197: 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 00:00:1762186985.481123  331101 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762186985.485588  331101 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762186985.495950  331101 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186985.495981  331101 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186985.495984  331101 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762186985.495986  331101 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:23:05.499323: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37451	validation-mlogloss:1.37385
[1]	train-mlogloss:1.36336	validation-mlogloss:1.36243
[2]	train-mlogloss:1.35231	validation-mlogloss:1.35084
[3]	train-mlogloss:1.34150	validation-mlogloss:1.33946
[4]	train-mlogloss:1.33053	validation-mlogloss:1.32806
[5]	train-mlogloss:1.32025	validation-mlogloss:1.31721
[6]	train-mlogloss:1.30995	validation-mlogloss:1.30628
[7]	train-mlogloss:1.30005	validation-mlogloss:1.29589
[8]	train-mlogloss:1.29033	validation-mlogloss:1.28585
[9]	train-mlogloss:1.28060	validation-mlogloss:1.27568
[10]	train-mlogloss:1.27102	validation-mlogloss:1.26548
[11]	train-mlogloss:1.26161	validation-mlogloss:1.25561
[12]	train-mlogloss:1.25249	validation-mlogloss:1.24606
[13]	train-mlogloss:1.24356	validation-mlogloss:1.23664
[14]	train-mlogloss:1.23483	validation-mlogloss:1.22762
[15]	train-mlogloss:1.22587	validation-mlogloss:1.21821
[16]	train-mlogloss:1.21730	validation-mlogloss:1.20929
[17]	train-mlogloss:1.20883	validation-mlogloss:1.20028
[18]	train-mlogloss:1.20051	validation-mlogloss:1.19145
[19]	train-mlogloss:1.19230	validation-mlogloss:1.18274
[20]	train-mlogloss:1.18399	validation-mlogloss:1.17401
[21]	train-mlogloss:1.17610	validation-mlogloss:1.16575
[22]	train-mlogloss:1.16827	validation-mlogloss:1.15740
[23]	train-mlogloss:1.16057	validation-mlogloss:1.14905
[24]	train-mlogloss:1.15321	validation-mlogloss:1.14122
[25]	train-mlogloss:1.14597	validation-mlogloss:1.13352
[26]	train-mlogloss:1.13896	validation-mlogloss:1.12630
[27]	train-mlogloss:1.13174	validation-mlogloss:1.11897
[28]	train-mlogloss:1.12493	validation-mlogloss:1.11188
[29]	train-mlogloss:1.11800	validation-mlogloss:1.10458
[30]	train-mlogloss:1.11113	validation-mlogloss:1.09755
[31]	train-mlogloss:1.10455	validation-mlogloss:1.09069
[32]	train-mlogloss:1.09791	validation-mlogloss:1.08373
[33]	train-mlogloss:1.09111	validation-mlogloss:1.07656
[34]	train-mlogloss:1.08460	validation-mlogloss:1.06967
[35]	train-mlogloss:1.07825	validation-mlogloss:1.06292
[36]	train-mlogloss:1.07211	validation-mlogloss:1.05643
[37]	train-mlogloss:1.06577	validation-mlogloss:1.04966
[38]	train-mlogloss:1.05962	validation-mlogloss:1.04342
[39]	train-mlogloss:1.05364	validation-mlogloss:1.03696
[40]	train-mlogloss:1.04770	validation-mlogloss:1.03084
[41]	train-mlogloss:1.04204	validation-mlogloss:1.02491
[42]	train-mlogloss:1.03620	validation-mlogloss:1.01876
[43]	train-mlogloss:1.03062	validation-mlogloss:1.01277
[44]	train-mlogloss:1.02518	validation-mlogloss:1.00717
[45]	train-mlogloss:1.01965	validation-mlogloss:1.00138
[46]	train-mlogloss:1.01427	validation-mlogloss:0.99601
[47]	train-mlogloss:1.00910	validation-mlogloss:0.99069
[48]	train-mlogloss:1.00402	validation-mlogloss:0.98550
[49]	train-mlogloss:0.99878	validation-mlogloss:0.97994
[50]	train-mlogloss:0.99364	validation-mlogloss:0.97442
[51]	train-mlogloss:0.98854	validation-mlogloss:0.96904
[52]	train-mlogloss:0.98334	validation-mlogloss:0.96360
[53]	train-mlogloss:0.97834	validation-mlogloss:0.95857
[54]	train-mlogloss:0.97351	validation-mlogloss:0.95381
[55]	train-mlogloss:0.96876	validation-mlogloss:0.94894
[56]	train-mlogloss:0.96396	validation-mlogloss:0.94406
[57]	train-mlogloss:0.95915	validation-mlogloss:0.93902
[58]	train-mlogloss:0.95453	validation-mlogloss:0.93428
[59]	train-mlogloss:0.95006	validation-mlogloss:0.92980
[60]	train-mlogloss:0.94542	validation-mlogloss:0.92487
[61]	train-mlogloss:0.94097	validation-mlogloss:0.92027
[62]	train-mlogloss:0.93649	validation-mlogloss:0.91553
[63]	train-mlogloss:0.93203	validation-mlogloss:0.91080
[64]	train-mlogloss:0.92797	validation-mlogloss:0.90671
[65]	train-mlogloss:0.92383	validation-mlogloss:0.90241
[66]	train-mlogloss:0.91967	validation-mlogloss:0.89808
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[368]	train-mlogloss:0.53488	validation-mlogloss:0.51747
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[418]	train-mlogloss:0.52249	validation-mlogloss:0.50722
[419]	train-mlogloss:0.52224	validation-mlogloss:0.50701
[420]	train-mlogloss:0.52209	validation-mlogloss:0.50694
[421]	train-mlogloss:0.52196	validation-mlogloss:0.50683
[422]	train-mlogloss:0.52179	validation-mlogloss:0.50666
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[424]	train-mlogloss:0.52143	validation-mlogloss:0.50628
[425]	train-mlogloss:0.52121	validation-mlogloss:0.50613
[426]	train-mlogloss:0.52103	validation-mlogloss:0.50601
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[441]	train-mlogloss:0.51848	validation-mlogloss:0.50410
[442]	train-mlogloss:0.51838	validation-mlogloss:0.50405
[443]	train-mlogloss:0.51815	validation-mlogloss:0.50398
[444]	train-mlogloss:0.51797	validation-mlogloss:0.50380
[445]	train-mlogloss:0.51776	validation-mlogloss:0.50360
[446]	train-mlogloss:0.51757	validation-mlogloss:0.50348
[447]	train-mlogloss:0.51739	validation-mlogloss:0.50336
[448]	train-mlogloss:0.51724	validation-mlogloss:0.50329
[449]	train-mlogloss:0.51707	validation-mlogloss:0.50316
[450]	train-mlogloss:0.51699	validation-mlogloss:0.50310
[451]	train-mlogloss:0.51687	validation-mlogloss:0.50305
[452]	train-mlogloss:0.51670	validation-mlogloss:0.50291
[453]	train-mlogloss:0.51646	validation-mlogloss:0.50268
[454]	train-mlogloss:0.51630	validation-mlogloss:0.50248
[455]	train-mlogloss:0.51616	validation-mlogloss:0.50231
[456]	train-mlogloss:0.51609	validation-mlogloss:0.50225
[457]	train-mlogloss:0.51598	validation-mlogloss:0.50215
[458]	train-mlogloss:0.51582	validation-mlogloss:0.50204
[459]	train-mlogloss:0.51570	validation-mlogloss:0.50188
[460]	train-mlogloss:0.51551	validation-mlogloss:0.50166
[461]	train-mlogloss:0.51530	validation-mlogloss:0.50155
[462]	train-mlogloss:0.51514	validation-mlogloss:0.50143
[463]	train-mlogloss:0.51503	validation-mlogloss:0.50132
[464]	train-mlogloss:0.51487	validation-mlogloss:0.50119
[465]	train-mlogloss:0.51471	validation-mlogloss:0.50108
[466]	train-mlogloss:0.51465	validation-mlogloss:0.50102
[467]	train-mlogloss:0.51456	validation-mlogloss:0.50098
[468]	train-mlogloss:0.51445	validation-mlogloss:0.50086
[469]	train-mlogloss:0.51424	validation-mlogloss:0.50066
[470]	train-mlogloss:0.51409	validation-mlogloss:0.50052
[471]	train-mlogloss:0.51402	validation-mlogloss:0.50045
[472]	train-mlogloss:0.51389	validation-mlogloss:0.50038
[473]	train-mlogloss:0.51371	validation-mlogloss:0.50020
[474]	train-mlogloss:0.51347	validation-mlogloss:0.50001
[475]	train-mlogloss:0.51340	validation-mlogloss:0.50000
[476]	train-mlogloss:0.51321	validation-mlogloss:0.49978
[477]	train-mlogloss:0.51309	validation-mlogloss:0.49969
[478]	train-mlogloss:0.51288	validation-mlogloss:0.49954
[479]	train-mlogloss:0.51277	validation-mlogloss:0.49945
[480]	train-mlogloss:0.51261	validation-mlogloss:0.49933
[481]	train-mlogloss:0.51253	validation-mlogloss:0.49923
[482]	train-mlogloss:0.51241	validation-mlogloss:0.49909
[483]	train-mlogloss:0.51228	validation-mlogloss:0.49895
[484]	train-mlogloss:0.51211	validation-mlogloss:0.49880
[485]	train-mlogloss:0.51201	validation-mlogloss:0.49868
[486]	train-mlogloss:0.51191	validation-mlogloss:0.49860
[487]	train-mlogloss:0.51183	validation-mlogloss:0.49854
[488]	train-mlogloss:0.51170	validation-mlogloss:0.49845
[489]	train-mlogloss:0.51149	validation-mlogloss:0.49828
[490]	train-mlogloss:0.51132	validation-mlogloss:0.49817
[491]	train-mlogloss:0.51123	validation-mlogloss:0.49809
[492]	train-mlogloss:0.51113	validation-mlogloss:0.49805
[493]	train-mlogloss:0.51101	validation-mlogloss:0.49794
[494]	train-mlogloss:0.51093	validation-mlogloss:0.49789
[495]	train-mlogloss:0.51074	validation-mlogloss:0.49769
[496]	train-mlogloss:0.51063	validation-mlogloss:0.49764
[497]	train-mlogloss:0.51055	validation-mlogloss:0.49759
[498]	train-mlogloss:0.51046	validation-mlogloss:0.49752
[499]	train-mlogloss:0.51034	validation-mlogloss:0.49742
[500]	train-mlogloss:0.51012	validation-mlogloss:0.49722
[501]	train-mlogloss:0.51003	validation-mlogloss:0.49718
[502]	train-mlogloss:0.50993	validation-mlogloss:0.49717
[503]	train-mlogloss:0.50981	validation-mlogloss:0.49711
[504]	train-mlogloss:0.50971	validation-mlogloss:0.49696
[505]	train-mlogloss:0.50952	validation-mlogloss:0.49688
[506]	train-mlogloss:0.50943	validation-mlogloss:0.49684
[507]	train-mlogloss:0.50932	validation-mlogloss:0.49675
[508]	train-mlogloss:0.50917	validation-mlogloss:0.49669
[509]	train-mlogloss:0.50904	validation-mlogloss:0.49664
[510]	train-mlogloss:0.50890	validation-mlogloss:0.49661
[511]	train-mlogloss:0.50883	validation-mlogloss:0.49656
[512]	train-mlogloss:0.50875	validation-mlogloss:0.49650
[513]	train-mlogloss:0.50855	validation-mlogloss:0.49625
[514]	train-mlogloss:0.50847	validation-mlogloss:0.49620
[515]	train-mlogloss:0.50841	validation-mlogloss:0.49612
[516]	train-mlogloss:0.50826	validation-mlogloss:0.49605
[517]	train-mlogloss:0.50812	validation-mlogloss:0.49594
[518]	train-mlogloss:0.50801	validation-mlogloss:0.49585
[519]	train-mlogloss:0.50797	validation-mlogloss:0.49581
[520]	train-mlogloss:0.50791	validation-mlogloss:0.49577
[521]	train-mlogloss:0.50776	validation-mlogloss:0.49575
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 0 0 1]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.33 [%]
Global accuracy score (test) = 79.81 [%]
Global F1 score (train) = 79.65 [%]
Global F1 score (test) = 80.37 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.70      0.66       350
MODERATE-INTENSITY       0.66      0.63      0.64       350
         SEDENTARY       0.99      0.96      0.97       350
VIGOROUS-INTENSITY       0.97      0.92      0.94       322

          accuracy                           0.80      1372
         macro avg       0.81      0.80      0.80      1372
      weighted avg       0.81      0.80      0.80      1372


Accuracy capturado en la ejecución 14: 79.81 [%]
F1-score capturado en la ejecución 14: 80.37 [%]

=== EJECUCIÓN 15 ===

--- TRAIN (ejecución 15) ---

--- TEST (ejecución 15) ---
2025-11-03 17:23:24.244141: 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`.
2025-11-03 17:23:24.255976: 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 00:00:1762187004.269734  331397 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187004.274121  331397 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187004.284411  331397 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187004.284441  331397 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187004.284444  331397 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187004.284446  331397 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:23:24.287877: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37515	validation-mlogloss:1.37503
[1]	train-mlogloss:1.36337	validation-mlogloss:1.36281
[2]	train-mlogloss:1.35207	validation-mlogloss:1.35086
[3]	train-mlogloss:1.34129	validation-mlogloss:1.33999
[4]	train-mlogloss:1.33031	validation-mlogloss:1.32834
[5]	train-mlogloss:1.31989	validation-mlogloss:1.31744
[6]	train-mlogloss:1.30966	validation-mlogloss:1.30665
[7]	train-mlogloss:1.29961	validation-mlogloss:1.29607
[8]	train-mlogloss:1.28976	validation-mlogloss:1.28559
[9]	train-mlogloss:1.27998	validation-mlogloss:1.27598
[10]	train-mlogloss:1.27012	validation-mlogloss:1.26553
[11]	train-mlogloss:1.26055	validation-mlogloss:1.25544
[12]	train-mlogloss:1.25096	validation-mlogloss:1.24554
[13]	train-mlogloss:1.24182	validation-mlogloss:1.23601
[14]	train-mlogloss:1.23277	validation-mlogloss:1.22654
[15]	train-mlogloss:1.22384	validation-mlogloss:1.21732
[16]	train-mlogloss:1.21497	validation-mlogloss:1.20841
[17]	train-mlogloss:1.20640	validation-mlogloss:1.19940
[18]	train-mlogloss:1.19804	validation-mlogloss:1.19037
[19]	train-mlogloss:1.18981	validation-mlogloss:1.18185
[20]	train-mlogloss:1.18169	validation-mlogloss:1.17344
[21]	train-mlogloss:1.17385	validation-mlogloss:1.16536
[22]	train-mlogloss:1.16618	validation-mlogloss:1.15719
[23]	train-mlogloss:1.15868	validation-mlogloss:1.14923
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[444]	train-mlogloss:0.51671	validation-mlogloss:0.50678
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[446]	train-mlogloss:0.51647	validation-mlogloss:0.50657
[447]	train-mlogloss:0.51628	validation-mlogloss:0.50643
[448]	train-mlogloss:0.51610	validation-mlogloss:0.50631
[449]	train-mlogloss:0.51595	validation-mlogloss:0.50617
[450]	train-mlogloss:0.51588	validation-mlogloss:0.50610
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[468]	train-mlogloss:0.51317	validation-mlogloss:0.50371
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[470]	train-mlogloss:0.51295	validation-mlogloss:0.50350
[471]	train-mlogloss:0.51280	validation-mlogloss:0.50334
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[473]	train-mlogloss:0.51253	validation-mlogloss:0.50307
[474]	train-mlogloss:0.51240	validation-mlogloss:0.50298
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[476]	train-mlogloss:0.51214	validation-mlogloss:0.50276
[477]	train-mlogloss:0.51204	validation-mlogloss:0.50263
[478]	train-mlogloss:0.51190	validation-mlogloss:0.50250
[479]	train-mlogloss:0.51181	validation-mlogloss:0.50248
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[481]	train-mlogloss:0.51152	validation-mlogloss:0.50223
[482]	train-mlogloss:0.51143	validation-mlogloss:0.50218
[483]	train-mlogloss:0.51120	validation-mlogloss:0.50196
[484]	train-mlogloss:0.51111	validation-mlogloss:0.50191
[485]	train-mlogloss:0.51103	validation-mlogloss:0.50180
[486]	train-mlogloss:0.51092	validation-mlogloss:0.50165
[487]	train-mlogloss:0.51071	validation-mlogloss:0.50143
[488]	train-mlogloss:0.51059	validation-mlogloss:0.50132
[489]	train-mlogloss:0.51046	validation-mlogloss:0.50122
[490]	train-mlogloss:0.51033	validation-mlogloss:0.50114
[491]	train-mlogloss:0.51023	validation-mlogloss:0.50112
[492]	train-mlogloss:0.51014	validation-mlogloss:0.50102
[493]	train-mlogloss:0.50999	validation-mlogloss:0.50089
[494]	train-mlogloss:0.50992	validation-mlogloss:0.50080
[495]	train-mlogloss:0.50982	validation-mlogloss:0.50064
[496]	train-mlogloss:0.50976	validation-mlogloss:0.50063
[497]	train-mlogloss:0.50967	validation-mlogloss:0.50058
[498]	train-mlogloss:0.50950	validation-mlogloss:0.50046
[499]	train-mlogloss:0.50938	validation-mlogloss:0.50032
[500]	train-mlogloss:0.50932	validation-mlogloss:0.50028
[501]	train-mlogloss:0.50921	validation-mlogloss:0.50023
[502]	train-mlogloss:0.50913	validation-mlogloss:0.50023
[503]	train-mlogloss:0.50902	validation-mlogloss:0.50011
[504]	train-mlogloss:0.50886	validation-mlogloss:0.50005
[505]	train-mlogloss:0.50870	validation-mlogloss:0.49986
[506]	train-mlogloss:0.50859	validation-mlogloss:0.49975
[507]	train-mlogloss:0.50842	validation-mlogloss:0.49963
[508]	train-mlogloss:0.50828	validation-mlogloss:0.49960
[509]	train-mlogloss:0.50818	validation-mlogloss:0.49946
[510]	train-mlogloss:0.50809	validation-mlogloss:0.49937
[511]	train-mlogloss:0.50796	validation-mlogloss:0.49930
[512]	train-mlogloss:0.50786	validation-mlogloss:0.49919
[513]	train-mlogloss:0.50778	validation-mlogloss:0.49912
[514]	train-mlogloss:0.50768	validation-mlogloss:0.49906
[515]	train-mlogloss:0.50752	validation-mlogloss:0.49898
[516]	train-mlogloss:0.50743	validation-mlogloss:0.49892
[517]	train-mlogloss:0.50730	validation-mlogloss:0.49884
[518]	train-mlogloss:0.50722	validation-mlogloss:0.49885
[519]	train-mlogloss:0.50716	validation-mlogloss:0.49878
[520]	train-mlogloss:0.50709	validation-mlogloss:0.49870
[521]	train-mlogloss:0.50701	validation-mlogloss:0.49859
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 1 0 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.31 [%]
Global accuracy score (test) = 80.32 [%]
Global F1 score (train) = 79.7 [%]
Global F1 score (test) = 80.97 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.64      0.68      0.66       350
MODERATE-INTENSITY       0.65      0.67      0.66       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.98      0.92      0.95       322

          accuracy                           0.80      1372
         macro avg       0.81      0.81      0.81      1372
      weighted avg       0.81      0.80      0.81      1372


Accuracy capturado en la ejecución 15: 80.32 [%]
F1-score capturado en la ejecución 15: 80.97 [%]

=== EJECUCIÓN 16 ===

--- TRAIN (ejecución 16) ---

--- TEST (ejecución 16) ---
2025-11-03 17:23:42.963249: 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`.
2025-11-03 17:23:42.975042: 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 00:00:1762187022.988631  331715 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187022.992771  331715 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187023.003199  331715 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187023.003237  331715 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187023.003239  331715 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187023.003241  331715 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:23:43.006596: 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..
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
[0]	train-mlogloss:1.37487	validation-mlogloss:1.37437
[1]	train-mlogloss:1.36321	validation-mlogloss:1.36219
[2]	train-mlogloss:1.35182	validation-mlogloss:1.35032
[3]	train-mlogloss:1.34120	validation-mlogloss:1.33942
[4]	train-mlogloss:1.33068	validation-mlogloss:1.32879
[5]	train-mlogloss:1.31968	validation-mlogloss:1.31726
[6]	train-mlogloss:1.30916	validation-mlogloss:1.30625
[7]	train-mlogloss:1.29868	validation-mlogloss:1.29519
[8]	train-mlogloss:1.28844	validation-mlogloss:1.28470
[9]	train-mlogloss:1.27856	validation-mlogloss:1.27460
[10]	train-mlogloss:1.26884	validation-mlogloss:1.26433
[11]	train-mlogloss:1.25966	validation-mlogloss:1.25515
[12]	train-mlogloss:1.25025	validation-mlogloss:1.24562
[13]	train-mlogloss:1.24112	validation-mlogloss:1.23585
[14]	train-mlogloss:1.23190	validation-mlogloss:1.22628
[15]	train-mlogloss:1.22302	validation-mlogloss:1.21722
[16]	train-mlogloss:1.21404	validation-mlogloss:1.20817
[17]	train-mlogloss:1.20570	validation-mlogloss:1.19964
[18]	train-mlogloss:1.19744	validation-mlogloss:1.19118
[19]	train-mlogloss:1.18922	validation-mlogloss:1.18248
[20]	train-mlogloss:1.18110	validation-mlogloss:1.17384
[21]	train-mlogloss:1.17315	validation-mlogloss:1.16539
[22]	train-mlogloss:1.16532	validation-mlogloss:1.15715
[23]	train-mlogloss:1.15748	validation-mlogloss:1.14908
[24]	train-mlogloss:1.14998	validation-mlogloss:1.14119
[25]	train-mlogloss:1.14270	validation-mlogloss:1.13366
[26]	train-mlogloss:1.13545	validation-mlogloss:1.12623
[27]	train-mlogloss:1.12828	validation-mlogloss:1.11897
[28]	train-mlogloss:1.12131	validation-mlogloss:1.11174
[29]	train-mlogloss:1.11414	validation-mlogloss:1.10420
[30]	train-mlogloss:1.10739	validation-mlogloss:1.09720
[31]	train-mlogloss:1.10065	validation-mlogloss:1.09023
[32]	train-mlogloss:1.09381	validation-mlogloss:1.08314
[33]	train-mlogloss:1.08741	validation-mlogloss:1.07666
[34]	train-mlogloss:1.08107	validation-mlogloss:1.06997
[35]	train-mlogloss:1.07473	validation-mlogloss:1.06331
[36]	train-mlogloss:1.06847	validation-mlogloss:1.05689
[37]	train-mlogloss:1.06223	validation-mlogloss:1.05050
[38]	train-mlogloss:1.05611	validation-mlogloss:1.04410
[39]	train-mlogloss:1.04985	validation-mlogloss:1.03770
[40]	train-mlogloss:1.04385	validation-mlogloss:1.03140
[41]	train-mlogloss:1.03796	validation-mlogloss:1.02538
[42]	train-mlogloss:1.03225	validation-mlogloss:1.01934
[43]	train-mlogloss:1.02642	validation-mlogloss:1.01316
[44]	train-mlogloss:1.02081	validation-mlogloss:1.00750
[45]	train-mlogloss:1.01543	validation-mlogloss:1.00205
[46]	train-mlogloss:1.01011	validation-mlogloss:0.99645
[47]	train-mlogloss:1.00502	validation-mlogloss:0.99125
[48]	train-mlogloss:0.99966	validation-mlogloss:0.98582
[49]	train-mlogloss:0.99391	validation-mlogloss:0.98002
[50]	train-mlogloss:0.98879	validation-mlogloss:0.97470
[51]	train-mlogloss:0.98365	validation-mlogloss:0.96924
[52]	train-mlogloss:0.97855	validation-mlogloss:0.96411
[53]	train-mlogloss:0.97381	validation-mlogloss:0.95920
[54]	train-mlogloss:0.96888	validation-mlogloss:0.95441
[55]	train-mlogloss:0.96390	validation-mlogloss:0.94943
[56]	train-mlogloss:0.95927	validation-mlogloss:0.94475
[57]	train-mlogloss:0.95462	validation-mlogloss:0.93997
[58]	train-mlogloss:0.94983	validation-mlogloss:0.93494
[59]	train-mlogloss:0.94510	validation-mlogloss:0.93009
[60]	train-mlogloss:0.94033	validation-mlogloss:0.92526
[61]	train-mlogloss:0.93590	validation-mlogloss:0.92066
[62]	train-mlogloss:0.93177	validation-mlogloss:0.91633
[63]	train-mlogloss:0.92740	validation-mlogloss:0.91183
[64]	train-mlogloss:0.92297	validation-mlogloss:0.90734
[65]	train-mlogloss:0.91859	validation-mlogloss:0.90276
[66]	train-mlogloss:0.91449	validation-mlogloss:0.89863
[67]	train-mlogloss:0.91024	validation-mlogloss:0.89423
[68]	train-mlogloss:0.90611	validation-mlogloss:0.89005
[69]	train-mlogloss:0.90204	validation-mlogloss:0.88587
[70]	train-mlogloss:0.89803	validation-mlogloss:0.88171
[71]	train-mlogloss:0.89404	validation-mlogloss:0.87766
[72]	train-mlogloss:0.89013	validation-mlogloss:0.87369
[73]	train-mlogloss:0.88633	validation-mlogloss:0.86968
[74]	train-mlogloss:0.88261	validation-mlogloss:0.86588
[75]	train-mlogloss:0.87900	validation-mlogloss:0.86223
[76]	train-mlogloss:0.87520	validation-mlogloss:0.85839
[77]	train-mlogloss:0.87162	validation-mlogloss:0.85468
[78]	train-mlogloss:0.86800	validation-mlogloss:0.85069
[79]	train-mlogloss:0.86436	validation-mlogloss:0.84694
[80]	train-mlogloss:0.86082	validation-mlogloss:0.84328
[81]	train-mlogloss:0.85749	validation-mlogloss:0.83996
[82]	train-mlogloss:0.85416	validation-mlogloss:0.83664
[83]	train-mlogloss:0.85074	validation-mlogloss:0.83324
[84]	train-mlogloss:0.84749	validation-mlogloss:0.82989
[85]	train-mlogloss:0.84422	validation-mlogloss:0.82665
[86]	train-mlogloss:0.84084	validation-mlogloss:0.82317
[87]	train-mlogloss:0.83774	validation-mlogloss:0.82002
[88]	train-mlogloss:0.83448	validation-mlogloss:0.81667
[89]	train-mlogloss:0.83141	validation-mlogloss:0.81362
[90]	train-mlogloss:0.82833	validation-mlogloss:0.81048
[91]	train-mlogloss:0.82515	validation-mlogloss:0.80716
[92]	train-mlogloss:0.82206	validation-mlogloss:0.80403
[93]	train-mlogloss:0.81902	validation-mlogloss:0.80094
[94]	train-mlogloss:0.81586	validation-mlogloss:0.79762
[95]	train-mlogloss:0.81302	validation-mlogloss:0.79484
[96]	train-mlogloss:0.81023	validation-mlogloss:0.79192
[97]	train-mlogloss:0.80737	validation-mlogloss:0.78905
[98]	train-mlogloss:0.80456	validation-mlogloss:0.78612
[99]	train-mlogloss:0.80178	validation-mlogloss:0.78319
[100]	train-mlogloss:0.79884	validation-mlogloss:0.78022
[101]	train-mlogloss:0.79603	validation-mlogloss:0.77724
[102]	train-mlogloss:0.79310	validation-mlogloss:0.77417
[103]	train-mlogloss:0.79048	validation-mlogloss:0.77136
[104]	train-mlogloss:0.78779	validation-mlogloss:0.76864
[105]	train-mlogloss:0.78517	validation-mlogloss:0.76593
[106]	train-mlogloss:0.78254	validation-mlogloss:0.76314
[107]	train-mlogloss:0.77985	validation-mlogloss:0.76027
[108]	train-mlogloss:0.77713	validation-mlogloss:0.75754
[109]	train-mlogloss:0.77458	validation-mlogloss:0.75482
[110]	train-mlogloss:0.77222	validation-mlogloss:0.75250
[111]	train-mlogloss:0.76979	validation-mlogloss:0.75000
[112]	train-mlogloss:0.76739	validation-mlogloss:0.74730
[113]	train-mlogloss:0.76505	validation-mlogloss:0.74478
[114]	train-mlogloss:0.76267	validation-mlogloss:0.74232
[115]	train-mlogloss:0.76012	validation-mlogloss:0.73968
[116]	train-mlogloss:0.75775	validation-mlogloss:0.73717
[117]	train-mlogloss:0.75535	validation-mlogloss:0.73473
[118]	train-mlogloss:0.75288	validation-mlogloss:0.73220
[119]	train-mlogloss:0.75040	validation-mlogloss:0.72967
[120]	train-mlogloss:0.74810	validation-mlogloss:0.72735
[121]	train-mlogloss:0.74576	validation-mlogloss:0.72504
[122]	train-mlogloss:0.74342	validation-mlogloss:0.72271
[123]	train-mlogloss:0.74138	validation-mlogloss:0.72059
[124]	train-mlogloss:0.73905	validation-mlogloss:0.71819
[125]	train-mlogloss:0.73704	validation-mlogloss:0.71608
[126]	train-mlogloss:0.73478	validation-mlogloss:0.71376
[127]	train-mlogloss:0.73276	validation-mlogloss:0.71164
[128]	train-mlogloss:0.73062	validation-mlogloss:0.70943
[129]	train-mlogloss:0.72847	validation-mlogloss:0.70720
[130]	train-mlogloss:0.72626	validation-mlogloss:0.70494
[131]	train-mlogloss:0.72424	validation-mlogloss:0.70294
[132]	train-mlogloss:0.72219	validation-mlogloss:0.70087
[133]	train-mlogloss:0.72028	validation-mlogloss:0.69884
[134]	train-mlogloss:0.71818	validation-mlogloss:0.69678
[135]	train-mlogloss:0.71640	validation-mlogloss:0.69503
[136]	train-mlogloss:0.71453	validation-mlogloss:0.69309
[137]	train-mlogloss:0.71253	validation-mlogloss:0.69098
[138]	train-mlogloss:0.71069	validation-mlogloss:0.68904
[139]	train-mlogloss:0.70873	validation-mlogloss:0.68697
[140]	train-mlogloss:0.70694	validation-mlogloss:0.68514
[141]	train-mlogloss:0.70516	validation-mlogloss:0.68318
[142]	train-mlogloss:0.70348	validation-mlogloss:0.68136
[143]	train-mlogloss:0.70182	validation-mlogloss:0.67956
[144]	train-mlogloss:0.70001	validation-mlogloss:0.67781
[145]	train-mlogloss:0.69839	validation-mlogloss:0.67605
[146]	train-mlogloss:0.69645	validation-mlogloss:0.67421
[147]	train-mlogloss:0.69464	validation-mlogloss:0.67233
[148]	train-mlogloss:0.69290	validation-mlogloss:0.67055
[149]	train-mlogloss:0.69140	validation-mlogloss:0.66894
[150]	train-mlogloss:0.68967	validation-mlogloss:0.66724
[151]	train-mlogloss:0.68789	validation-mlogloss:0.66543
[152]	train-mlogloss:0.68636	validation-mlogloss:0.66392
[153]	train-mlogloss:0.68472	validation-mlogloss:0.66232
[154]	train-mlogloss:0.68313	validation-mlogloss:0.66059
[155]	train-mlogloss:0.68147	validation-mlogloss:0.65898
[156]	train-mlogloss:0.67988	validation-mlogloss:0.65738
[157]	train-mlogloss:0.67819	validation-mlogloss:0.65578
[158]	train-mlogloss:0.67666	validation-mlogloss:0.65410
[159]	train-mlogloss:0.67513	validation-mlogloss:0.65264
[160]	train-mlogloss:0.67355	validation-mlogloss:0.65113
[161]	train-mlogloss:0.67197	validation-mlogloss:0.64964
[162]	train-mlogloss:0.67048	validation-mlogloss:0.64819
[163]	train-mlogloss:0.66912	validation-mlogloss:0.64686
[164]	train-mlogloss:0.66767	validation-mlogloss:0.64529
[165]	train-mlogloss:0.66624	validation-mlogloss:0.64380
[166]	train-mlogloss:0.66478	validation-mlogloss:0.64238
[167]	train-mlogloss:0.66330	validation-mlogloss:0.64084
[168]	train-mlogloss:0.66185	validation-mlogloss:0.63946
[169]	train-mlogloss:0.66043	validation-mlogloss:0.63805
[170]	train-mlogloss:0.65908	validation-mlogloss:0.63670
[171]	train-mlogloss:0.65773	validation-mlogloss:0.63531
[172]	train-mlogloss:0.65638	validation-mlogloss:0.63392
[173]	train-mlogloss:0.65507	validation-mlogloss:0.63251
[174]	train-mlogloss:0.65388	validation-mlogloss:0.63111
[175]	train-mlogloss:0.65252	validation-mlogloss:0.62977
[176]	train-mlogloss:0.65124	validation-mlogloss:0.62847
[177]	train-mlogloss:0.64989	validation-mlogloss:0.62724
[178]	train-mlogloss:0.64862	validation-mlogloss:0.62599
[179]	train-mlogloss:0.64733	validation-mlogloss:0.62477
[180]	train-mlogloss:0.64615	validation-mlogloss:0.62355
[181]	train-mlogloss:0.64491	validation-mlogloss:0.62231
[182]	train-mlogloss:0.64363	validation-mlogloss:0.62102
[183]	train-mlogloss:0.64228	validation-mlogloss:0.61975
[184]	train-mlogloss:0.64107	validation-mlogloss:0.61860
[185]	train-mlogloss:0.63971	validation-mlogloss:0.61709
[186]	train-mlogloss:0.63851	validation-mlogloss:0.61595
[187]	train-mlogloss:0.63739	validation-mlogloss:0.61484
[188]	train-mlogloss:0.63621	validation-mlogloss:0.61370
[189]	train-mlogloss:0.63501	validation-mlogloss:0.61245
[190]	train-mlogloss:0.63399	validation-mlogloss:0.61141
[191]	train-mlogloss:0.63291	validation-mlogloss:0.61037
[192]	train-mlogloss:0.63175	validation-mlogloss:0.60921
[193]	train-mlogloss:0.63065	validation-mlogloss:0.60808
[194]	train-mlogloss:0.62949	validation-mlogloss:0.60706
[195]	train-mlogloss:0.62847	validation-mlogloss:0.60607
[196]	train-mlogloss:0.62736	validation-mlogloss:0.60498
[197]	train-mlogloss:0.62636	validation-mlogloss:0.60398
[198]	train-mlogloss:0.62533	validation-mlogloss:0.60299
[199]	train-mlogloss:0.62429	validation-mlogloss:0.60202
[200]	train-mlogloss:0.62324	validation-mlogloss:0.60086
[201]	train-mlogloss:0.62225	validation-mlogloss:0.59982
[202]	train-mlogloss:0.62119	validation-mlogloss:0.59883
[203]	train-mlogloss:0.62020	validation-mlogloss:0.59779
[204]	train-mlogloss:0.61927	validation-mlogloss:0.59684
[205]	train-mlogloss:0.61830	validation-mlogloss:0.59578
[206]	train-mlogloss:0.61729	validation-mlogloss:0.59485
[207]	train-mlogloss:0.61634	validation-mlogloss:0.59395
[208]	train-mlogloss:0.61538	validation-mlogloss:0.59309
[209]	train-mlogloss:0.61444	validation-mlogloss:0.59214
[210]	train-mlogloss:0.61353	validation-mlogloss:0.59121
[211]	train-mlogloss:0.61265	validation-mlogloss:0.59046
[212]	train-mlogloss:0.61170	validation-mlogloss:0.58944
[213]	train-mlogloss:0.61073	validation-mlogloss:0.58852
[214]	train-mlogloss:0.60983	validation-mlogloss:0.58765
[215]	train-mlogloss:0.60896	validation-mlogloss:0.58682
[216]	train-mlogloss:0.60807	validation-mlogloss:0.58589
[217]	train-mlogloss:0.60711	validation-mlogloss:0.58495
[218]	train-mlogloss:0.60625	validation-mlogloss:0.58419
[219]	train-mlogloss:0.60545	validation-mlogloss:0.58337
[220]	train-mlogloss:0.60464	validation-mlogloss:0.58263
[221]	train-mlogloss:0.60379	validation-mlogloss:0.58186
[222]	train-mlogloss:0.60302	validation-mlogloss:0.58099
[223]	train-mlogloss:0.60216	validation-mlogloss:0.58021
[224]	train-mlogloss:0.60126	validation-mlogloss:0.57937
[225]	train-mlogloss:0.60038	validation-mlogloss:0.57858
[226]	train-mlogloss:0.59946	validation-mlogloss:0.57758
[227]	train-mlogloss:0.59868	validation-mlogloss:0.57684
[228]	train-mlogloss:0.59784	validation-mlogloss:0.57609
[229]	train-mlogloss:0.59708	validation-mlogloss:0.57539
[230]	train-mlogloss:0.59632	validation-mlogloss:0.57469
[231]	train-mlogloss:0.59558	validation-mlogloss:0.57397
[232]	train-mlogloss:0.59479	validation-mlogloss:0.57330
[233]	train-mlogloss:0.59403	validation-mlogloss:0.57262
[234]	train-mlogloss:0.59337	validation-mlogloss:0.57195
[235]	train-mlogloss:0.59262	validation-mlogloss:0.57120
[236]	train-mlogloss:0.59202	validation-mlogloss:0.57052
[237]	train-mlogloss:0.59129	validation-mlogloss:0.56978
[238]	train-mlogloss:0.59053	validation-mlogloss:0.56919
[239]	train-mlogloss:0.58972	validation-mlogloss:0.56846
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[241]	train-mlogloss:0.58823	validation-mlogloss:0.56716
[242]	train-mlogloss:0.58750	validation-mlogloss:0.56652
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[274]	train-mlogloss:0.56778	validation-mlogloss:0.54734
[275]	train-mlogloss:0.56725	validation-mlogloss:0.54686
[276]	train-mlogloss:0.56674	validation-mlogloss:0.54645
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[278]	train-mlogloss:0.56573	validation-mlogloss:0.54556
[279]	train-mlogloss:0.56518	validation-mlogloss:0.54505
[280]	train-mlogloss:0.56467	validation-mlogloss:0.54460
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[503]	train-mlogloss:0.50361	validation-mlogloss:0.49225
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[505]	train-mlogloss:0.50346	validation-mlogloss:0.49215
[506]	train-mlogloss:0.50337	validation-mlogloss:0.49204
[507]	train-mlogloss:0.50319	validation-mlogloss:0.49187
[508]	train-mlogloss:0.50309	validation-mlogloss:0.49180
[509]	train-mlogloss:0.50292	validation-mlogloss:0.49161
[510]	train-mlogloss:0.50277	validation-mlogloss:0.49150
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[512]	train-mlogloss:0.50253	validation-mlogloss:0.49127
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[520]	train-mlogloss:0.50158	validation-mlogloss:0.49053
[521]	train-mlogloss:0.50149	validation-mlogloss:0.49044
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[1 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.4 [%]
Global accuracy score (test) = 80.76 [%]
Global F1 score (train) = 79.74 [%]
Global F1 score (test) = 81.23 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.64      0.70      0.67       350
MODERATE-INTENSITY       0.68      0.65      0.67       350
         SEDENTARY       0.99      0.96      0.97       350
VIGOROUS-INTENSITY       0.95      0.92      0.94       322

          accuracy                           0.81      1372
         macro avg       0.82      0.81      0.81      1372
      weighted avg       0.81      0.81      0.81      1372


Accuracy capturado en la ejecución 16: 80.76 [%]
F1-score capturado en la ejecución 16: 81.23 [%]

=== EJECUCIÓN 17 ===

--- TRAIN (ejecución 17) ---

--- TEST (ejecución 17) ---
2025-11-03 17:24:01.768001: 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`.
2025-11-03 17:24:01.779828: 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 00:00:1762187041.793982  332030 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187041.798073  332030 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187041.808761  332030 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187041.808791  332030 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187041.808794  332030 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187041.808795  332030 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:24:01.812087: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37451	validation-mlogloss:1.37375
[1]	train-mlogloss:1.36281	validation-mlogloss:1.36188
[2]	train-mlogloss:1.35144	validation-mlogloss:1.35026
[3]	train-mlogloss:1.34057	validation-mlogloss:1.33905
[4]	train-mlogloss:1.32964	validation-mlogloss:1.32746
[5]	train-mlogloss:1.31944	validation-mlogloss:1.31699
[6]	train-mlogloss:1.30895	validation-mlogloss:1.30595
[7]	train-mlogloss:1.29862	validation-mlogloss:1.29543
[8]	train-mlogloss:1.28866	validation-mlogloss:1.28495
[9]	train-mlogloss:1.27874	validation-mlogloss:1.27469
[10]	train-mlogloss:1.26902	validation-mlogloss:1.26433
[11]	train-mlogloss:1.25976	validation-mlogloss:1.25446
[12]	train-mlogloss:1.25032	validation-mlogloss:1.24448
[13]	train-mlogloss:1.24137	validation-mlogloss:1.23511
[14]	train-mlogloss:1.23211	validation-mlogloss:1.22546
[15]	train-mlogloss:1.22327	validation-mlogloss:1.21623
[16]	train-mlogloss:1.21471	validation-mlogloss:1.20747
[17]	train-mlogloss:1.20628	validation-mlogloss:1.19866
[18]	train-mlogloss:1.19796	validation-mlogloss:1.18991
[19]	train-mlogloss:1.18969	validation-mlogloss:1.18133
[20]	train-mlogloss:1.18145	validation-mlogloss:1.17261
[21]	train-mlogloss:1.17355	validation-mlogloss:1.16435
[22]	train-mlogloss:1.16572	validation-mlogloss:1.15629
[23]	train-mlogloss:1.15810	validation-mlogloss:1.14832
[24]	train-mlogloss:1.15053	validation-mlogloss:1.14038
[25]	train-mlogloss:1.14307	validation-mlogloss:1.13251
[26]	train-mlogloss:1.13556	validation-mlogloss:1.12446
[27]	train-mlogloss:1.12861	validation-mlogloss:1.11747
[28]	train-mlogloss:1.12131	validation-mlogloss:1.10980
[29]	train-mlogloss:1.11437	validation-mlogloss:1.10263
[30]	train-mlogloss:1.10751	validation-mlogloss:1.09534
[31]	train-mlogloss:1.10055	validation-mlogloss:1.08800
[32]	train-mlogloss:1.09381	validation-mlogloss:1.08111
[33]	train-mlogloss:1.08715	validation-mlogloss:1.07402
[34]	train-mlogloss:1.08096	validation-mlogloss:1.06769
[35]	train-mlogloss:1.07455	validation-mlogloss:1.06100
[36]	train-mlogloss:1.06830	validation-mlogloss:1.05441
[37]	train-mlogloss:1.06200	validation-mlogloss:1.04798
[38]	train-mlogloss:1.05580	validation-mlogloss:1.04157
[39]	train-mlogloss:1.04968	validation-mlogloss:1.03522
[40]	train-mlogloss:1.04360	validation-mlogloss:1.02897
[41]	train-mlogloss:1.03784	validation-mlogloss:1.02314
[42]	train-mlogloss:1.03217	validation-mlogloss:1.01725
[43]	train-mlogloss:1.02649	validation-mlogloss:1.01137
[44]	train-mlogloss:1.02099	validation-mlogloss:1.00571
[45]	train-mlogloss:1.01568	validation-mlogloss:1.00025
[46]	train-mlogloss:1.00999	validation-mlogloss:0.99431
[47]	train-mlogloss:1.00471	validation-mlogloss:0.98915
[48]	train-mlogloss:0.99940	validation-mlogloss:0.98351
[49]	train-mlogloss:0.99411	validation-mlogloss:0.97798
[50]	train-mlogloss:0.98888	validation-mlogloss:0.97271
[51]	train-mlogloss:0.98384	validation-mlogloss:0.96765
[52]	train-mlogloss:0.97894	validation-mlogloss:0.96240
[53]	train-mlogloss:0.97410	validation-mlogloss:0.95753
[54]	train-mlogloss:0.96925	validation-mlogloss:0.95252
[55]	train-mlogloss:0.96432	validation-mlogloss:0.94749
[56]	train-mlogloss:0.95935	validation-mlogloss:0.94241
[57]	train-mlogloss:0.95462	validation-mlogloss:0.93758
[58]	train-mlogloss:0.95002	validation-mlogloss:0.93298
[59]	train-mlogloss:0.94562	validation-mlogloss:0.92857
[60]	train-mlogloss:0.94114	validation-mlogloss:0.92422
[61]	train-mlogloss:0.93684	validation-mlogloss:0.91970
[62]	train-mlogloss:0.93235	validation-mlogloss:0.91500
[63]	train-mlogloss:0.92782	validation-mlogloss:0.91052
[64]	train-mlogloss:0.92336	validation-mlogloss:0.90582
[65]	train-mlogloss:0.91917	validation-mlogloss:0.90140
[66]	train-mlogloss:0.91499	validation-mlogloss:0.89710
[67]	train-mlogloss:0.91087	validation-mlogloss:0.89270
[68]	train-mlogloss:0.90665	validation-mlogloss:0.88830
[69]	train-mlogloss:0.90247	validation-mlogloss:0.88396
[70]	train-mlogloss:0.89856	validation-mlogloss:0.88004
[71]	train-mlogloss:0.89476	validation-mlogloss:0.87616
[72]	train-mlogloss:0.89103	validation-mlogloss:0.87231
[73]	train-mlogloss:0.88730	validation-mlogloss:0.86853
[74]	train-mlogloss:0.88360	validation-mlogloss:0.86472
[75]	train-mlogloss:0.88003	validation-mlogloss:0.86104
[76]	train-mlogloss:0.87644	validation-mlogloss:0.85734
[77]	train-mlogloss:0.87298	validation-mlogloss:0.85393
[78]	train-mlogloss:0.86931	validation-mlogloss:0.85012
[79]	train-mlogloss:0.86570	validation-mlogloss:0.84633
[80]	train-mlogloss:0.86215	validation-mlogloss:0.84270
[81]	train-mlogloss:0.85879	validation-mlogloss:0.83913
[82]	train-mlogloss:0.85528	validation-mlogloss:0.83556
[83]	train-mlogloss:0.85199	validation-mlogloss:0.83232
[84]	train-mlogloss:0.84849	validation-mlogloss:0.82898
[85]	train-mlogloss:0.84531	validation-mlogloss:0.82578
[86]	train-mlogloss:0.84223	validation-mlogloss:0.82263
[87]	train-mlogloss:0.83921	validation-mlogloss:0.81963
[88]	train-mlogloss:0.83608	validation-mlogloss:0.81660
[89]	train-mlogloss:0.83302	validation-mlogloss:0.81347
[90]	train-mlogloss:0.82985	validation-mlogloss:0.81038
[91]	train-mlogloss:0.82666	validation-mlogloss:0.80721
[92]	train-mlogloss:0.82362	validation-mlogloss:0.80412
[93]	train-mlogloss:0.82059	validation-mlogloss:0.80096
[94]	train-mlogloss:0.81780	validation-mlogloss:0.79793
[95]	train-mlogloss:0.81487	validation-mlogloss:0.79488
[96]	train-mlogloss:0.81194	validation-mlogloss:0.79181
[97]	train-mlogloss:0.80908	validation-mlogloss:0.78886
[98]	train-mlogloss:0.80617	validation-mlogloss:0.78580
[99]	train-mlogloss:0.80339	validation-mlogloss:0.78289
[100]	train-mlogloss:0.80074	validation-mlogloss:0.78014
[101]	train-mlogloss:0.79811	validation-mlogloss:0.77738
[102]	train-mlogloss:0.79532	validation-mlogloss:0.77438
[103]	train-mlogloss:0.79269	validation-mlogloss:0.77154
[104]	train-mlogloss:0.79022	validation-mlogloss:0.76893
[105]	train-mlogloss:0.78758	validation-mlogloss:0.76619
[106]	train-mlogloss:0.78505	validation-mlogloss:0.76356
[107]	train-mlogloss:0.78250	validation-mlogloss:0.76080
[108]	train-mlogloss:0.77969	validation-mlogloss:0.75793
[109]	train-mlogloss:0.77716	validation-mlogloss:0.75531
[110]	train-mlogloss:0.77462	validation-mlogloss:0.75265
[111]	train-mlogloss:0.77190	validation-mlogloss:0.74993
[112]	train-mlogloss:0.76922	validation-mlogloss:0.74716
[113]	train-mlogloss:0.76687	validation-mlogloss:0.74466
[114]	train-mlogloss:0.76445	validation-mlogloss:0.74217
[115]	train-mlogloss:0.76217	validation-mlogloss:0.73992
[116]	train-mlogloss:0.75963	validation-mlogloss:0.73727
[117]	train-mlogloss:0.75719	validation-mlogloss:0.73476
[118]	train-mlogloss:0.75487	validation-mlogloss:0.73238
[119]	train-mlogloss:0.75278	validation-mlogloss:0.73029
[120]	train-mlogloss:0.75031	validation-mlogloss:0.72771
[121]	train-mlogloss:0.74828	validation-mlogloss:0.72558
[122]	train-mlogloss:0.74619	validation-mlogloss:0.72341
[123]	train-mlogloss:0.74412	validation-mlogloss:0.72134
[124]	train-mlogloss:0.74183	validation-mlogloss:0.71903
[125]	train-mlogloss:0.73987	validation-mlogloss:0.71698
[126]	train-mlogloss:0.73761	validation-mlogloss:0.71469
[127]	train-mlogloss:0.73538	validation-mlogloss:0.71240
[128]	train-mlogloss:0.73314	validation-mlogloss:0.71011
[129]	train-mlogloss:0.73097	validation-mlogloss:0.70787
[130]	train-mlogloss:0.72908	validation-mlogloss:0.70585
[131]	train-mlogloss:0.72693	validation-mlogloss:0.70366
[132]	train-mlogloss:0.72501	validation-mlogloss:0.70173
[133]	train-mlogloss:0.72291	validation-mlogloss:0.69967
[134]	train-mlogloss:0.72104	validation-mlogloss:0.69785
[135]	train-mlogloss:0.71918	validation-mlogloss:0.69582
[136]	train-mlogloss:0.71733	validation-mlogloss:0.69380
[137]	train-mlogloss:0.71553	validation-mlogloss:0.69197
[138]	train-mlogloss:0.71349	validation-mlogloss:0.68984
[139]	train-mlogloss:0.71157	validation-mlogloss:0.68791
[140]	train-mlogloss:0.70980	validation-mlogloss:0.68607
[141]	train-mlogloss:0.70792	validation-mlogloss:0.68422
[142]	train-mlogloss:0.70609	validation-mlogloss:0.68231
[143]	train-mlogloss:0.70442	validation-mlogloss:0.68047
[144]	train-mlogloss:0.70266	validation-mlogloss:0.67856
[145]	train-mlogloss:0.70080	validation-mlogloss:0.67668
[146]	train-mlogloss:0.69896	validation-mlogloss:0.67486
[147]	train-mlogloss:0.69727	validation-mlogloss:0.67304
[148]	train-mlogloss:0.69559	validation-mlogloss:0.67136
[149]	train-mlogloss:0.69377	validation-mlogloss:0.66956
[150]	train-mlogloss:0.69201	validation-mlogloss:0.66783
[151]	train-mlogloss:0.69036	validation-mlogloss:0.66616
[152]	train-mlogloss:0.68867	validation-mlogloss:0.66452
[153]	train-mlogloss:0.68702	validation-mlogloss:0.66283
[154]	train-mlogloss:0.68542	validation-mlogloss:0.66122
[155]	train-mlogloss:0.68398	validation-mlogloss:0.65974
[156]	train-mlogloss:0.68234	validation-mlogloss:0.65798
[157]	train-mlogloss:0.68073	validation-mlogloss:0.65640
[158]	train-mlogloss:0.67919	validation-mlogloss:0.65475
[159]	train-mlogloss:0.67764	validation-mlogloss:0.65313
[160]	train-mlogloss:0.67621	validation-mlogloss:0.65156
[161]	train-mlogloss:0.67479	validation-mlogloss:0.65005
[162]	train-mlogloss:0.67325	validation-mlogloss:0.64845
[163]	train-mlogloss:0.67181	validation-mlogloss:0.64705
[164]	train-mlogloss:0.67034	validation-mlogloss:0.64567
[165]	train-mlogloss:0.66885	validation-mlogloss:0.64413
[166]	train-mlogloss:0.66756	validation-mlogloss:0.64276
[167]	train-mlogloss:0.66611	validation-mlogloss:0.64130
[168]	train-mlogloss:0.66481	validation-mlogloss:0.63995
[169]	train-mlogloss:0.66344	validation-mlogloss:0.63852
[170]	train-mlogloss:0.66207	validation-mlogloss:0.63708
[171]	train-mlogloss:0.66069	validation-mlogloss:0.63573
[172]	train-mlogloss:0.65930	validation-mlogloss:0.63417
[173]	train-mlogloss:0.65795	validation-mlogloss:0.63270
[174]	train-mlogloss:0.65673	validation-mlogloss:0.63144
[175]	train-mlogloss:0.65550	validation-mlogloss:0.63022
[176]	train-mlogloss:0.65414	validation-mlogloss:0.62892
[177]	train-mlogloss:0.65275	validation-mlogloss:0.62763
[178]	train-mlogloss:0.65156	validation-mlogloss:0.62644
[179]	train-mlogloss:0.65038	validation-mlogloss:0.62520
[180]	train-mlogloss:0.64910	validation-mlogloss:0.62397
[181]	train-mlogloss:0.64780	validation-mlogloss:0.62276
[182]	train-mlogloss:0.64652	validation-mlogloss:0.62143
[183]	train-mlogloss:0.64526	validation-mlogloss:0.62017
[184]	train-mlogloss:0.64400	validation-mlogloss:0.61896
[185]	train-mlogloss:0.64282	validation-mlogloss:0.61776
[186]	train-mlogloss:0.64179	validation-mlogloss:0.61666
[187]	train-mlogloss:0.64066	validation-mlogloss:0.61560
[188]	train-mlogloss:0.63956	validation-mlogloss:0.61456
[189]	train-mlogloss:0.63839	validation-mlogloss:0.61336
[190]	train-mlogloss:0.63738	validation-mlogloss:0.61227
[191]	train-mlogloss:0.63629	validation-mlogloss:0.61128
[192]	train-mlogloss:0.63506	validation-mlogloss:0.60993
[193]	train-mlogloss:0.63394	validation-mlogloss:0.60878
[194]	train-mlogloss:0.63286	validation-mlogloss:0.60755
[195]	train-mlogloss:0.63173	validation-mlogloss:0.60625
[196]	train-mlogloss:0.63059	validation-mlogloss:0.60509
[197]	train-mlogloss:0.62945	validation-mlogloss:0.60387
[198]	train-mlogloss:0.62841	validation-mlogloss:0.60280
[199]	train-mlogloss:0.62740	validation-mlogloss:0.60168
[200]	train-mlogloss:0.62636	validation-mlogloss:0.60062
[201]	train-mlogloss:0.62533	validation-mlogloss:0.59965
[202]	train-mlogloss:0.62432	validation-mlogloss:0.59865
[203]	train-mlogloss:0.62335	validation-mlogloss:0.59764
[204]	train-mlogloss:0.62243	validation-mlogloss:0.59669
[205]	train-mlogloss:0.62142	validation-mlogloss:0.59558
[206]	train-mlogloss:0.62043	validation-mlogloss:0.59466
[207]	train-mlogloss:0.61940	validation-mlogloss:0.59359
[208]	train-mlogloss:0.61843	validation-mlogloss:0.59269
[209]	train-mlogloss:0.61746	validation-mlogloss:0.59170
[210]	train-mlogloss:0.61648	validation-mlogloss:0.59080
[211]	train-mlogloss:0.61560	validation-mlogloss:0.58978
[212]	train-mlogloss:0.61474	validation-mlogloss:0.58895
[213]	train-mlogloss:0.61386	validation-mlogloss:0.58811
[214]	train-mlogloss:0.61288	validation-mlogloss:0.58704
[215]	train-mlogloss:0.61200	validation-mlogloss:0.58616
[216]	train-mlogloss:0.61118	validation-mlogloss:0.58536
[217]	train-mlogloss:0.61028	validation-mlogloss:0.58452
[218]	train-mlogloss:0.60942	validation-mlogloss:0.58362
[219]	train-mlogloss:0.60839	validation-mlogloss:0.58256
[220]	train-mlogloss:0.60759	validation-mlogloss:0.58175
[221]	train-mlogloss:0.60680	validation-mlogloss:0.58093
[222]	train-mlogloss:0.60597	validation-mlogloss:0.57998
[223]	train-mlogloss:0.60507	validation-mlogloss:0.57911
[224]	train-mlogloss:0.60430	validation-mlogloss:0.57831
[225]	train-mlogloss:0.60345	validation-mlogloss:0.57747
[226]	train-mlogloss:0.60257	validation-mlogloss:0.57651
[227]	train-mlogloss:0.60177	validation-mlogloss:0.57572
[228]	train-mlogloss:0.60096	validation-mlogloss:0.57484
[229]	train-mlogloss:0.60016	validation-mlogloss:0.57412
[230]	train-mlogloss:0.59946	validation-mlogloss:0.57332
[231]	train-mlogloss:0.59866	validation-mlogloss:0.57252
[232]	train-mlogloss:0.59787	validation-mlogloss:0.57178
[233]	train-mlogloss:0.59709	validation-mlogloss:0.57101
[234]	train-mlogloss:0.59624	validation-mlogloss:0.57024
[235]	train-mlogloss:0.59544	validation-mlogloss:0.56943
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Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 1 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.65 [%]
Global accuracy score (test) = 79.81 [%]
Global F1 score (train) = 80.0 [%]
Global F1 score (test) = 80.39 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.70      0.66       350
MODERATE-INTENSITY       0.65      0.63      0.64       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.97      0.92      0.94       322

          accuracy                           0.80      1372
         macro avg       0.81      0.80      0.80      1372
      weighted avg       0.81      0.80      0.80      1372


Accuracy capturado en la ejecución 17: 79.81 [%]
F1-score capturado en la ejecución 17: 80.39 [%]

=== EJECUCIÓN 18 ===

--- TRAIN (ejecución 18) ---

--- TEST (ejecución 18) ---
2025-11-03 17:24:20.509317: 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`.
2025-11-03 17:24:20.521162: 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 00:00:1762187060.534770  332334 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187060.539184  332334 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187060.549321  332334 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187060.549347  332334 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187060.549350  332334 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187060.549352  332334 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:24:20.552774: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37460	validation-mlogloss:1.37397
[1]	train-mlogloss:1.36312	validation-mlogloss:1.36198
[2]	train-mlogloss:1.35202	validation-mlogloss:1.35033
[3]	train-mlogloss:1.34114	validation-mlogloss:1.33897
[4]	train-mlogloss:1.33038	validation-mlogloss:1.32767
[5]	train-mlogloss:1.32015	validation-mlogloss:1.31713
[6]	train-mlogloss:1.31002	validation-mlogloss:1.30650
[7]	train-mlogloss:1.29976	validation-mlogloss:1.29556
[8]	train-mlogloss:1.28985	validation-mlogloss:1.28500
[9]	train-mlogloss:1.28033	validation-mlogloss:1.27539
[10]	train-mlogloss:1.27078	validation-mlogloss:1.26564
[11]	train-mlogloss:1.26159	validation-mlogloss:1.25603
[12]	train-mlogloss:1.25237	validation-mlogloss:1.24636
[13]	train-mlogloss:1.24344	validation-mlogloss:1.23698
[14]	train-mlogloss:1.23444	validation-mlogloss:1.22747
[15]	train-mlogloss:1.22565	validation-mlogloss:1.21812
[16]	train-mlogloss:1.21694	validation-mlogloss:1.20891
[17]	train-mlogloss:1.20852	validation-mlogloss:1.19984
[18]	train-mlogloss:1.20010	validation-mlogloss:1.19105
[19]	train-mlogloss:1.19174	validation-mlogloss:1.18229
[20]	train-mlogloss:1.18374	validation-mlogloss:1.17386
[21]	train-mlogloss:1.17545	validation-mlogloss:1.16520
[22]	train-mlogloss:1.16741	validation-mlogloss:1.15667
[23]	train-mlogloss:1.15994	validation-mlogloss:1.14885
[24]	train-mlogloss:1.15242	validation-mlogloss:1.14094
[25]	train-mlogloss:1.14502	validation-mlogloss:1.13303
[26]	train-mlogloss:1.13779	validation-mlogloss:1.12543
[27]	train-mlogloss:1.13087	validation-mlogloss:1.11818
[28]	train-mlogloss:1.12383	validation-mlogloss:1.11078
[29]	train-mlogloss:1.11699	validation-mlogloss:1.10364
[30]	train-mlogloss:1.10998	validation-mlogloss:1.09638
[31]	train-mlogloss:1.10336	validation-mlogloss:1.08916
[32]	train-mlogloss:1.09663	validation-mlogloss:1.08199
[33]	train-mlogloss:1.09025	validation-mlogloss:1.07518
[34]	train-mlogloss:1.08395	validation-mlogloss:1.06857
[35]	train-mlogloss:1.07768	validation-mlogloss:1.06191
[36]	train-mlogloss:1.07130	validation-mlogloss:1.05495
[37]	train-mlogloss:1.06524	validation-mlogloss:1.04883
[38]	train-mlogloss:1.05935	validation-mlogloss:1.04262
[39]	train-mlogloss:1.05334	validation-mlogloss:1.03645
[40]	train-mlogloss:1.04744	validation-mlogloss:1.03046
[41]	train-mlogloss:1.04152	validation-mlogloss:1.02450
[42]	train-mlogloss:1.03568	validation-mlogloss:1.01858
[43]	train-mlogloss:1.02983	validation-mlogloss:1.01253
[44]	train-mlogloss:1.02415	validation-mlogloss:1.00676
[45]	train-mlogloss:1.01865	validation-mlogloss:1.00098
[46]	train-mlogloss:1.01291	validation-mlogloss:0.99490
[47]	train-mlogloss:1.00748	validation-mlogloss:0.98919
[48]	train-mlogloss:1.00215	validation-mlogloss:0.98378
[49]	train-mlogloss:0.99674	validation-mlogloss:0.97815
[50]	train-mlogloss:0.99163	validation-mlogloss:0.97300
[51]	train-mlogloss:0.98668	validation-mlogloss:0.96794
[52]	train-mlogloss:0.98156	validation-mlogloss:0.96262
[53]	train-mlogloss:0.97660	validation-mlogloss:0.95737
[54]	train-mlogloss:0.97186	validation-mlogloss:0.95222
[55]	train-mlogloss:0.96707	validation-mlogloss:0.94713
[56]	train-mlogloss:0.96248	validation-mlogloss:0.94243
[57]	train-mlogloss:0.95791	validation-mlogloss:0.93773
[58]	train-mlogloss:0.95334	validation-mlogloss:0.93282
[59]	train-mlogloss:0.94870	validation-mlogloss:0.92799
[60]	train-mlogloss:0.94417	validation-mlogloss:0.92333
[61]	train-mlogloss:0.93973	validation-mlogloss:0.91891
[62]	train-mlogloss:0.93531	validation-mlogloss:0.91427
[63]	train-mlogloss:0.93108	validation-mlogloss:0.90982
[64]	train-mlogloss:0.92689	validation-mlogloss:0.90548
[65]	train-mlogloss:0.92273	validation-mlogloss:0.90112
[66]	train-mlogloss:0.91860	validation-mlogloss:0.89702
[67]	train-mlogloss:0.91432	validation-mlogloss:0.89252
[68]	train-mlogloss:0.91045	validation-mlogloss:0.88843
[69]	train-mlogloss:0.90648	validation-mlogloss:0.88437
[70]	train-mlogloss:0.90252	validation-mlogloss:0.88020
[71]	train-mlogloss:0.89853	validation-mlogloss:0.87601
[72]	train-mlogloss:0.89462	validation-mlogloss:0.87192
[73]	train-mlogloss:0.89084	validation-mlogloss:0.86793
[74]	train-mlogloss:0.88711	validation-mlogloss:0.86414
[75]	train-mlogloss:0.88342	validation-mlogloss:0.86033
[76]	train-mlogloss:0.87970	validation-mlogloss:0.85644
[77]	train-mlogloss:0.87622	validation-mlogloss:0.85284
[78]	train-mlogloss:0.87260	validation-mlogloss:0.84917
[79]	train-mlogloss:0.86909	validation-mlogloss:0.84558
[80]	train-mlogloss:0.86563	validation-mlogloss:0.84209
[81]	train-mlogloss:0.86220	validation-mlogloss:0.83855
[82]	train-mlogloss:0.85874	validation-mlogloss:0.83493
[83]	train-mlogloss:0.85544	validation-mlogloss:0.83133
[84]	train-mlogloss:0.85222	validation-mlogloss:0.82797
[85]	train-mlogloss:0.84896	validation-mlogloss:0.82456
[86]	train-mlogloss:0.84564	validation-mlogloss:0.82100
[87]	train-mlogloss:0.84251	validation-mlogloss:0.81773
[88]	train-mlogloss:0.83945	validation-mlogloss:0.81459
[89]	train-mlogloss:0.83643	validation-mlogloss:0.81145
[90]	train-mlogloss:0.83335	validation-mlogloss:0.80840
[91]	train-mlogloss:0.83040	validation-mlogloss:0.80521
[92]	train-mlogloss:0.82730	validation-mlogloss:0.80195
[93]	train-mlogloss:0.82440	validation-mlogloss:0.79887
[94]	train-mlogloss:0.82141	validation-mlogloss:0.79568
[95]	train-mlogloss:0.81840	validation-mlogloss:0.79266
[96]	train-mlogloss:0.81564	validation-mlogloss:0.78984
[97]	train-mlogloss:0.81278	validation-mlogloss:0.78689
[98]	train-mlogloss:0.80978	validation-mlogloss:0.78369
[99]	train-mlogloss:0.80703	validation-mlogloss:0.78077
[100]	train-mlogloss:0.80433	validation-mlogloss:0.77807
[101]	train-mlogloss:0.80160	validation-mlogloss:0.77526
[102]	train-mlogloss:0.79898	validation-mlogloss:0.77263
[103]	train-mlogloss:0.79635	validation-mlogloss:0.76980
[104]	train-mlogloss:0.79378	validation-mlogloss:0.76708
[105]	train-mlogloss:0.79098	validation-mlogloss:0.76416
[106]	train-mlogloss:0.78853	validation-mlogloss:0.76165
[107]	train-mlogloss:0.78600	validation-mlogloss:0.75892
[108]	train-mlogloss:0.78356	validation-mlogloss:0.75635
[109]	train-mlogloss:0.78113	validation-mlogloss:0.75378
[110]	train-mlogloss:0.77869	validation-mlogloss:0.75117
[111]	train-mlogloss:0.77633	validation-mlogloss:0.74873
[112]	train-mlogloss:0.77392	validation-mlogloss:0.74622
[113]	train-mlogloss:0.77144	validation-mlogloss:0.74356
[114]	train-mlogloss:0.76909	validation-mlogloss:0.74107
[115]	train-mlogloss:0.76679	validation-mlogloss:0.73866
[116]	train-mlogloss:0.76434	validation-mlogloss:0.73615
[117]	train-mlogloss:0.76182	validation-mlogloss:0.73366
[118]	train-mlogloss:0.75955	validation-mlogloss:0.73131
[119]	train-mlogloss:0.75727	validation-mlogloss:0.72902
[120]	train-mlogloss:0.75517	validation-mlogloss:0.72689
[121]	train-mlogloss:0.75287	validation-mlogloss:0.72456
[122]	train-mlogloss:0.75053	validation-mlogloss:0.72223
[123]	train-mlogloss:0.74824	validation-mlogloss:0.71987
[124]	train-mlogloss:0.74615	validation-mlogloss:0.71770
[125]	train-mlogloss:0.74394	validation-mlogloss:0.71546
[126]	train-mlogloss:0.74193	validation-mlogloss:0.71332
[127]	train-mlogloss:0.73974	validation-mlogloss:0.71102
[128]	train-mlogloss:0.73759	validation-mlogloss:0.70891
[129]	train-mlogloss:0.73560	validation-mlogloss:0.70691
[130]	train-mlogloss:0.73353	validation-mlogloss:0.70484
[131]	train-mlogloss:0.73141	validation-mlogloss:0.70277
[132]	train-mlogloss:0.72957	validation-mlogloss:0.70075
[133]	train-mlogloss:0.72754	validation-mlogloss:0.69868
[134]	train-mlogloss:0.72555	validation-mlogloss:0.69662
[135]	train-mlogloss:0.72376	validation-mlogloss:0.69472
[136]	train-mlogloss:0.72194	validation-mlogloss:0.69283
[137]	train-mlogloss:0.72000	validation-mlogloss:0.69077
[138]	train-mlogloss:0.71802	validation-mlogloss:0.68874
[139]	train-mlogloss:0.71612	validation-mlogloss:0.68670
[140]	train-mlogloss:0.71433	validation-mlogloss:0.68483
[141]	train-mlogloss:0.71262	validation-mlogloss:0.68307
[142]	train-mlogloss:0.71072	validation-mlogloss:0.68120
[143]	train-mlogloss:0.70888	validation-mlogloss:0.67936
[144]	train-mlogloss:0.70707	validation-mlogloss:0.67751
[145]	train-mlogloss:0.70548	validation-mlogloss:0.67587
[146]	train-mlogloss:0.70380	validation-mlogloss:0.67412
[147]	train-mlogloss:0.70214	validation-mlogloss:0.67242
[148]	train-mlogloss:0.70043	validation-mlogloss:0.67051
[149]	train-mlogloss:0.69875	validation-mlogloss:0.66868
[150]	train-mlogloss:0.69712	validation-mlogloss:0.66708
[151]	train-mlogloss:0.69547	validation-mlogloss:0.66534
[152]	train-mlogloss:0.69379	validation-mlogloss:0.66364
[153]	train-mlogloss:0.69217	validation-mlogloss:0.66207
[154]	train-mlogloss:0.69058	validation-mlogloss:0.66056
[155]	train-mlogloss:0.68891	validation-mlogloss:0.65884
[156]	train-mlogloss:0.68733	validation-mlogloss:0.65735
[157]	train-mlogloss:0.68597	validation-mlogloss:0.65593
[158]	train-mlogloss:0.68436	validation-mlogloss:0.65428
[159]	train-mlogloss:0.68272	validation-mlogloss:0.65249
[160]	train-mlogloss:0.68122	validation-mlogloss:0.65101
[161]	train-mlogloss:0.67966	validation-mlogloss:0.64951
[162]	train-mlogloss:0.67819	validation-mlogloss:0.64797
[163]	train-mlogloss:0.67678	validation-mlogloss:0.64650
[164]	train-mlogloss:0.67532	validation-mlogloss:0.64485
[165]	train-mlogloss:0.67389	validation-mlogloss:0.64339
[166]	train-mlogloss:0.67253	validation-mlogloss:0.64194
[167]	train-mlogloss:0.67121	validation-mlogloss:0.64057
[168]	train-mlogloss:0.66982	validation-mlogloss:0.63922
[169]	train-mlogloss:0.66856	validation-mlogloss:0.63802
[170]	train-mlogloss:0.66715	validation-mlogloss:0.63658
[171]	train-mlogloss:0.66577	validation-mlogloss:0.63513
[172]	train-mlogloss:0.66444	validation-mlogloss:0.63382
[173]	train-mlogloss:0.66323	validation-mlogloss:0.63257
[174]	train-mlogloss:0.66179	validation-mlogloss:0.63108
[175]	train-mlogloss:0.66046	validation-mlogloss:0.62975
[176]	train-mlogloss:0.65923	validation-mlogloss:0.62838
[177]	train-mlogloss:0.65789	validation-mlogloss:0.62705
[178]	train-mlogloss:0.65674	validation-mlogloss:0.62591
[179]	train-mlogloss:0.65564	validation-mlogloss:0.62478
[180]	train-mlogloss:0.65434	validation-mlogloss:0.62357
[181]	train-mlogloss:0.65315	validation-mlogloss:0.62231
[182]	train-mlogloss:0.65196	validation-mlogloss:0.62106
[183]	train-mlogloss:0.65065	validation-mlogloss:0.61976
[184]	train-mlogloss:0.64945	validation-mlogloss:0.61857
[185]	train-mlogloss:0.64835	validation-mlogloss:0.61739
[186]	train-mlogloss:0.64726	validation-mlogloss:0.61626
[187]	train-mlogloss:0.64604	validation-mlogloss:0.61513
[188]	train-mlogloss:0.64498	validation-mlogloss:0.61407
[189]	train-mlogloss:0.64384	validation-mlogloss:0.61290
[190]	train-mlogloss:0.64276	validation-mlogloss:0.61189
[191]	train-mlogloss:0.64170	validation-mlogloss:0.61083
[192]	train-mlogloss:0.64050	validation-mlogloss:0.60959
[193]	train-mlogloss:0.63940	validation-mlogloss:0.60848
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[496]	train-mlogloss:0.51452	validation-mlogloss:0.49458
[497]	train-mlogloss:0.51441	validation-mlogloss:0.49451
[498]	train-mlogloss:0.51430	validation-mlogloss:0.49441
[499]	train-mlogloss:0.51419	validation-mlogloss:0.49435
[500]	train-mlogloss:0.51411	validation-mlogloss:0.49433
[501]	train-mlogloss:0.51400	validation-mlogloss:0.49423
[502]	train-mlogloss:0.51392	validation-mlogloss:0.49418
[503]	train-mlogloss:0.51385	validation-mlogloss:0.49413
[504]	train-mlogloss:0.51380	validation-mlogloss:0.49410
[505]	train-mlogloss:0.51367	validation-mlogloss:0.49406
[506]	train-mlogloss:0.51359	validation-mlogloss:0.49402
[507]	train-mlogloss:0.51349	validation-mlogloss:0.49390
[508]	train-mlogloss:0.51340	validation-mlogloss:0.49385
[509]	train-mlogloss:0.51334	validation-mlogloss:0.49383
[510]	train-mlogloss:0.51327	validation-mlogloss:0.49379
[511]	train-mlogloss:0.51316	validation-mlogloss:0.49364
[512]	train-mlogloss:0.51306	validation-mlogloss:0.49353
[513]	train-mlogloss:0.51288	validation-mlogloss:0.49342
[514]	train-mlogloss:0.51279	validation-mlogloss:0.49328
[515]	train-mlogloss:0.51271	validation-mlogloss:0.49321
[516]	train-mlogloss:0.51263	validation-mlogloss:0.49312
[517]	train-mlogloss:0.51259	validation-mlogloss:0.49308
[518]	train-mlogloss:0.51250	validation-mlogloss:0.49301
[519]	train-mlogloss:0.51242	validation-mlogloss:0.49292
[520]	train-mlogloss:0.51232	validation-mlogloss:0.49279
[521]	train-mlogloss:0.51223	validation-mlogloss:0.49269
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[1 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.02 [%]
Global accuracy score (test) = 79.74 [%]
Global F1 score (train) = 79.27 [%]
Global F1 score (test) = 80.3 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.70      0.66       350
MODERATE-INTENSITY       0.65      0.63      0.64       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.96      0.92      0.94       322

          accuracy                           0.80      1372
         macro avg       0.81      0.80      0.80      1372
      weighted avg       0.80      0.80      0.80      1372


Accuracy capturado en la ejecución 18: 79.74 [%]
F1-score capturado en la ejecución 18: 80.3 [%]

=== EJECUCIÓN 19 ===

--- TRAIN (ejecución 19) ---

--- TEST (ejecución 19) ---
2025-11-03 17:24:39.471539: 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`.
2025-11-03 17:24:39.483056: 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 00:00:1762187079.497175  332655 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187079.501566  332655 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187079.512031  332655 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187079.512063  332655 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187079.512066  332655 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187079.512067  332655 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:24:39.515289: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37428	validation-mlogloss:1.37353
[1]	train-mlogloss:1.36295	validation-mlogloss:1.36179
[2]	train-mlogloss:1.35201	validation-mlogloss:1.35050
[3]	train-mlogloss:1.34083	validation-mlogloss:1.33863
[4]	train-mlogloss:1.33003	validation-mlogloss:1.32732
[5]	train-mlogloss:1.31946	validation-mlogloss:1.31608
[6]	train-mlogloss:1.30897	validation-mlogloss:1.30505
[7]	train-mlogloss:1.29899	validation-mlogloss:1.29458
[8]	train-mlogloss:1.28913	validation-mlogloss:1.28444
[9]	train-mlogloss:1.27895	validation-mlogloss:1.27408
[10]	train-mlogloss:1.26957	validation-mlogloss:1.26440
[11]	train-mlogloss:1.26009	validation-mlogloss:1.25436
[12]	train-mlogloss:1.25091	validation-mlogloss:1.24472
[13]	train-mlogloss:1.24196	validation-mlogloss:1.23540
[14]	train-mlogloss:1.23306	validation-mlogloss:1.22600
[15]	train-mlogloss:1.22444	validation-mlogloss:1.21683
[16]	train-mlogloss:1.21583	validation-mlogloss:1.20779
[17]	train-mlogloss:1.20728	validation-mlogloss:1.19881
[18]	train-mlogloss:1.19850	validation-mlogloss:1.18966
[19]	train-mlogloss:1.19019	validation-mlogloss:1.18089
[20]	train-mlogloss:1.18212	validation-mlogloss:1.17247
[21]	train-mlogloss:1.17442	validation-mlogloss:1.16444
[22]	train-mlogloss:1.16655	validation-mlogloss:1.15613
[23]	train-mlogloss:1.15868	validation-mlogloss:1.14783
[24]	train-mlogloss:1.15109	validation-mlogloss:1.13963
[25]	train-mlogloss:1.14356	validation-mlogloss:1.13177
[26]	train-mlogloss:1.13628	validation-mlogloss:1.12398
[27]	train-mlogloss:1.12915	validation-mlogloss:1.11629
[28]	train-mlogloss:1.12206	validation-mlogloss:1.10885
[29]	train-mlogloss:1.11495	validation-mlogloss:1.10143
[30]	train-mlogloss:1.10814	validation-mlogloss:1.09414
[31]	train-mlogloss:1.10137	validation-mlogloss:1.08693
[32]	train-mlogloss:1.09455	validation-mlogloss:1.08006
[33]	train-mlogloss:1.08786	validation-mlogloss:1.07305
[34]	train-mlogloss:1.08133	validation-mlogloss:1.06626
[35]	train-mlogloss:1.07500	validation-mlogloss:1.05949
[36]	train-mlogloss:1.06879	validation-mlogloss:1.05281
[37]	train-mlogloss:1.06261	validation-mlogloss:1.04621
[38]	train-mlogloss:1.05670	validation-mlogloss:1.03997
[39]	train-mlogloss:1.05056	validation-mlogloss:1.03337
[40]	train-mlogloss:1.04473	validation-mlogloss:1.02718
[41]	train-mlogloss:1.03910	validation-mlogloss:1.02128
[42]	train-mlogloss:1.03330	validation-mlogloss:1.01502
[43]	train-mlogloss:1.02731	validation-mlogloss:1.00867
[44]	train-mlogloss:1.02167	validation-mlogloss:1.00300
[45]	train-mlogloss:1.01580	validation-mlogloss:0.99691
[46]	train-mlogloss:1.01031	validation-mlogloss:0.99132
[47]	train-mlogloss:1.00485	validation-mlogloss:0.98548
[48]	train-mlogloss:0.99946	validation-mlogloss:0.97992
[49]	train-mlogloss:0.99437	validation-mlogloss:0.97465
[50]	train-mlogloss:0.98900	validation-mlogloss:0.96917
[51]	train-mlogloss:0.98399	validation-mlogloss:0.96392
[52]	train-mlogloss:0.97886	validation-mlogloss:0.95852
[53]	train-mlogloss:0.97396	validation-mlogloss:0.95330
[54]	train-mlogloss:0.96921	validation-mlogloss:0.94841
[55]	train-mlogloss:0.96457	validation-mlogloss:0.94339
[56]	train-mlogloss:0.95978	validation-mlogloss:0.93859
[57]	train-mlogloss:0.95517	validation-mlogloss:0.93394
[58]	train-mlogloss:0.95050	validation-mlogloss:0.92913
[59]	train-mlogloss:0.94580	validation-mlogloss:0.92433
[60]	train-mlogloss:0.94125	validation-mlogloss:0.91980
[61]	train-mlogloss:0.93668	validation-mlogloss:0.91514
[62]	train-mlogloss:0.93217	validation-mlogloss:0.91049
[63]	train-mlogloss:0.92795	validation-mlogloss:0.90621
[64]	train-mlogloss:0.92378	validation-mlogloss:0.90177
[65]	train-mlogloss:0.91954	validation-mlogloss:0.89737
[66]	train-mlogloss:0.91527	validation-mlogloss:0.89298
[67]	train-mlogloss:0.91122	validation-mlogloss:0.88900
[68]	train-mlogloss:0.90699	validation-mlogloss:0.88452
[69]	train-mlogloss:0.90318	validation-mlogloss:0.88066
[70]	train-mlogloss:0.89939	validation-mlogloss:0.87685
[71]	train-mlogloss:0.89556	validation-mlogloss:0.87291
[72]	train-mlogloss:0.89161	validation-mlogloss:0.86873
[73]	train-mlogloss:0.88770	validation-mlogloss:0.86474
[74]	train-mlogloss:0.88364	validation-mlogloss:0.86066
[75]	train-mlogloss:0.87967	validation-mlogloss:0.85666
[76]	train-mlogloss:0.87607	validation-mlogloss:0.85313
[77]	train-mlogloss:0.87255	validation-mlogloss:0.84947
[78]	train-mlogloss:0.86892	validation-mlogloss:0.84574
[79]	train-mlogloss:0.86527	validation-mlogloss:0.84189
[80]	train-mlogloss:0.86169	validation-mlogloss:0.83822
[81]	train-mlogloss:0.85794	validation-mlogloss:0.83444
[82]	train-mlogloss:0.85461	validation-mlogloss:0.83104
[83]	train-mlogloss:0.85128	validation-mlogloss:0.82755
[84]	train-mlogloss:0.84808	validation-mlogloss:0.82427
[85]	train-mlogloss:0.84490	validation-mlogloss:0.82095
[86]	train-mlogloss:0.84154	validation-mlogloss:0.81743
[87]	train-mlogloss:0.83824	validation-mlogloss:0.81397
[88]	train-mlogloss:0.83508	validation-mlogloss:0.81067
[89]	train-mlogloss:0.83208	validation-mlogloss:0.80764
[90]	train-mlogloss:0.82885	validation-mlogloss:0.80432
[91]	train-mlogloss:0.82583	validation-mlogloss:0.80126
[92]	train-mlogloss:0.82275	validation-mlogloss:0.79807
[93]	train-mlogloss:0.81970	validation-mlogloss:0.79504
[94]	train-mlogloss:0.81671	validation-mlogloss:0.79198
[95]	train-mlogloss:0.81386	validation-mlogloss:0.78890
[96]	train-mlogloss:0.81098	validation-mlogloss:0.78603
[97]	train-mlogloss:0.80823	validation-mlogloss:0.78330
[98]	train-mlogloss:0.80543	validation-mlogloss:0.78038
[99]	train-mlogloss:0.80266	validation-mlogloss:0.77765
[100]	train-mlogloss:0.79986	validation-mlogloss:0.77477
[101]	train-mlogloss:0.79711	validation-mlogloss:0.77193
[102]	train-mlogloss:0.79429	validation-mlogloss:0.76905
[103]	train-mlogloss:0.79139	validation-mlogloss:0.76604
[104]	train-mlogloss:0.78872	validation-mlogloss:0.76311
[105]	train-mlogloss:0.78608	validation-mlogloss:0.76024
[106]	train-mlogloss:0.78358	validation-mlogloss:0.75765
[107]	train-mlogloss:0.78103	validation-mlogloss:0.75493
[108]	train-mlogloss:0.77861	validation-mlogloss:0.75236
[109]	train-mlogloss:0.77627	validation-mlogloss:0.74990
[110]	train-mlogloss:0.77386	validation-mlogloss:0.74739
[111]	train-mlogloss:0.77153	validation-mlogloss:0.74497
[112]	train-mlogloss:0.76924	validation-mlogloss:0.74270
[113]	train-mlogloss:0.76665	validation-mlogloss:0.74001
[114]	train-mlogloss:0.76425	validation-mlogloss:0.73740
[115]	train-mlogloss:0.76171	validation-mlogloss:0.73473
[116]	train-mlogloss:0.75936	validation-mlogloss:0.73243
[117]	train-mlogloss:0.75697	validation-mlogloss:0.73001
[118]	train-mlogloss:0.75478	validation-mlogloss:0.72772
[119]	train-mlogloss:0.75259	validation-mlogloss:0.72546
[120]	train-mlogloss:0.75045	validation-mlogloss:0.72325
[121]	train-mlogloss:0.74821	validation-mlogloss:0.72093
[122]	train-mlogloss:0.74609	validation-mlogloss:0.71875
[123]	train-mlogloss:0.74393	validation-mlogloss:0.71655
[124]	train-mlogloss:0.74181	validation-mlogloss:0.71426
[125]	train-mlogloss:0.73965	validation-mlogloss:0.71203
[126]	train-mlogloss:0.73749	validation-mlogloss:0.70983
[127]	train-mlogloss:0.73534	validation-mlogloss:0.70759
[128]	train-mlogloss:0.73325	validation-mlogloss:0.70544
[129]	train-mlogloss:0.73115	validation-mlogloss:0.70325
[130]	train-mlogloss:0.72906	validation-mlogloss:0.70109
[131]	train-mlogloss:0.72682	validation-mlogloss:0.69886
[132]	train-mlogloss:0.72490	validation-mlogloss:0.69694
[133]	train-mlogloss:0.72280	validation-mlogloss:0.69489
[134]	train-mlogloss:0.72096	validation-mlogloss:0.69291
[135]	train-mlogloss:0.71894	validation-mlogloss:0.69084
[136]	train-mlogloss:0.71697	validation-mlogloss:0.68886
[137]	train-mlogloss:0.71508	validation-mlogloss:0.68689
[138]	train-mlogloss:0.71326	validation-mlogloss:0.68481
[139]	train-mlogloss:0.71133	validation-mlogloss:0.68284
[140]	train-mlogloss:0.70946	validation-mlogloss:0.68086
[141]	train-mlogloss:0.70759	validation-mlogloss:0.67905
[142]	train-mlogloss:0.70589	validation-mlogloss:0.67732
[143]	train-mlogloss:0.70403	validation-mlogloss:0.67548
[144]	train-mlogloss:0.70241	validation-mlogloss:0.67376
[145]	train-mlogloss:0.70060	validation-mlogloss:0.67197
[146]	train-mlogloss:0.69890	validation-mlogloss:0.67021
[147]	train-mlogloss:0.69714	validation-mlogloss:0.66842
[148]	train-mlogloss:0.69552	validation-mlogloss:0.66663
[149]	train-mlogloss:0.69387	validation-mlogloss:0.66488
[150]	train-mlogloss:0.69226	validation-mlogloss:0.66324
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[453]	train-mlogloss:0.51256	validation-mlogloss:0.49109
[454]	train-mlogloss:0.51247	validation-mlogloss:0.49104
[455]	train-mlogloss:0.51237	validation-mlogloss:0.49100
[456]	train-mlogloss:0.51228	validation-mlogloss:0.49092
[457]	train-mlogloss:0.51216	validation-mlogloss:0.49086
[458]	train-mlogloss:0.51206	validation-mlogloss:0.49082
[459]	train-mlogloss:0.51195	validation-mlogloss:0.49067
[460]	train-mlogloss:0.51173	validation-mlogloss:0.49040
[461]	train-mlogloss:0.51164	validation-mlogloss:0.49032
[462]	train-mlogloss:0.51151	validation-mlogloss:0.49023
[463]	train-mlogloss:0.51141	validation-mlogloss:0.49009
[464]	train-mlogloss:0.51123	validation-mlogloss:0.48990
[465]	train-mlogloss:0.51101	validation-mlogloss:0.48976
[466]	train-mlogloss:0.51089	validation-mlogloss:0.48960
[467]	train-mlogloss:0.51082	validation-mlogloss:0.48953
[468]	train-mlogloss:0.51060	validation-mlogloss:0.48926
[469]	train-mlogloss:0.51050	validation-mlogloss:0.48922
[470]	train-mlogloss:0.51033	validation-mlogloss:0.48901
[471]	train-mlogloss:0.51023	validation-mlogloss:0.48890
[472]	train-mlogloss:0.51013	validation-mlogloss:0.48889
[473]	train-mlogloss:0.51004	validation-mlogloss:0.48887
[474]	train-mlogloss:0.50995	validation-mlogloss:0.48881
[475]	train-mlogloss:0.50983	validation-mlogloss:0.48866
[476]	train-mlogloss:0.50974	validation-mlogloss:0.48861
[477]	train-mlogloss:0.50959	validation-mlogloss:0.48845
[478]	train-mlogloss:0.50944	validation-mlogloss:0.48825
[479]	train-mlogloss:0.50933	validation-mlogloss:0.48817
[480]	train-mlogloss:0.50920	validation-mlogloss:0.48804
[481]	train-mlogloss:0.50897	validation-mlogloss:0.48782
[482]	train-mlogloss:0.50881	validation-mlogloss:0.48761
[483]	train-mlogloss:0.50871	validation-mlogloss:0.48749
[484]	train-mlogloss:0.50849	validation-mlogloss:0.48734
[485]	train-mlogloss:0.50841	validation-mlogloss:0.48729
[486]	train-mlogloss:0.50831	validation-mlogloss:0.48724
[487]	train-mlogloss:0.50816	validation-mlogloss:0.48701
[488]	train-mlogloss:0.50787	validation-mlogloss:0.48672
[489]	train-mlogloss:0.50772	validation-mlogloss:0.48661
[490]	train-mlogloss:0.50758	validation-mlogloss:0.48644
[491]	train-mlogloss:0.50745	validation-mlogloss:0.48629
[492]	train-mlogloss:0.50736	validation-mlogloss:0.48622
[493]	train-mlogloss:0.50733	validation-mlogloss:0.48620
[494]	train-mlogloss:0.50725	validation-mlogloss:0.48614
[495]	train-mlogloss:0.50718	validation-mlogloss:0.48607
[496]	train-mlogloss:0.50705	validation-mlogloss:0.48594
[497]	train-mlogloss:0.50696	validation-mlogloss:0.48587
[498]	train-mlogloss:0.50685	validation-mlogloss:0.48574
[499]	train-mlogloss:0.50677	validation-mlogloss:0.48570
[500]	train-mlogloss:0.50663	validation-mlogloss:0.48558
[501]	train-mlogloss:0.50655	validation-mlogloss:0.48556
[502]	train-mlogloss:0.50645	validation-mlogloss:0.48550
[503]	train-mlogloss:0.50629	validation-mlogloss:0.48538
[504]	train-mlogloss:0.50611	validation-mlogloss:0.48524
[505]	train-mlogloss:0.50601	validation-mlogloss:0.48516
[506]	train-mlogloss:0.50594	validation-mlogloss:0.48511
[507]	train-mlogloss:0.50587	validation-mlogloss:0.48502
[508]	train-mlogloss:0.50573	validation-mlogloss:0.48488
[509]	train-mlogloss:0.50559	validation-mlogloss:0.48471
[510]	train-mlogloss:0.50548	validation-mlogloss:0.48456
[511]	train-mlogloss:0.50526	validation-mlogloss:0.48443
[512]	train-mlogloss:0.50518	validation-mlogloss:0.48433
[513]	train-mlogloss:0.50509	validation-mlogloss:0.48427
[514]	train-mlogloss:0.50495	validation-mlogloss:0.48416
[515]	train-mlogloss:0.50485	validation-mlogloss:0.48412
[516]	train-mlogloss:0.50470	validation-mlogloss:0.48403
[517]	train-mlogloss:0.50461	validation-mlogloss:0.48397
[518]	train-mlogloss:0.50454	validation-mlogloss:0.48390
[519]	train-mlogloss:0.50441	validation-mlogloss:0.48385
[520]	train-mlogloss:0.50431	validation-mlogloss:0.48378
[521]	train-mlogloss:0.50425	validation-mlogloss:0.48375
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[0 2 2 ... 0 3 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.06 [%]
Global accuracy score (test) = 78.86 [%]
Global F1 score (train) = 79.37 [%]
Global F1 score (test) = 79.5 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.60      0.67      0.63       350
MODERATE-INTENSITY       0.64      0.62      0.63       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.97      0.92      0.95       322

          accuracy                           0.79      1372
         macro avg       0.80      0.79      0.80      1372
      weighted avg       0.80      0.79      0.79      1372


Accuracy capturado en la ejecución 19: 78.86 [%]
F1-score capturado en la ejecución 19: 79.5 [%]

=== EJECUCIÓN 20 ===

--- TRAIN (ejecución 20) ---

--- TEST (ejecución 20) ---
2025-11-03 17:24:58.356714: 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`.
2025-11-03 17:24:58.368284: 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 00:00:1762187098.381783  332962 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187098.386214  332962 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187098.396436  332962 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187098.396466  332962 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187098.396469  332962 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187098.396471  332962 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:24:58.399688: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37429	validation-mlogloss:1.37388
[1]	train-mlogloss:1.36273	validation-mlogloss:1.36186
[2]	train-mlogloss:1.35136	validation-mlogloss:1.35002
[3]	train-mlogloss:1.34028	validation-mlogloss:1.33848
[4]	train-mlogloss:1.32932	validation-mlogloss:1.32723
[5]	train-mlogloss:1.31875	validation-mlogloss:1.31649
[6]	train-mlogloss:1.30857	validation-mlogloss:1.30590
[7]	train-mlogloss:1.29863	validation-mlogloss:1.29549
[8]	train-mlogloss:1.28836	validation-mlogloss:1.28490
[9]	train-mlogloss:1.27868	validation-mlogloss:1.27490
[10]	train-mlogloss:1.26886	validation-mlogloss:1.26470
[11]	train-mlogloss:1.25958	validation-mlogloss:1.25505
[12]	train-mlogloss:1.25031	validation-mlogloss:1.24551
[13]	train-mlogloss:1.24126	validation-mlogloss:1.23600
[14]	train-mlogloss:1.23223	validation-mlogloss:1.22658
[15]	train-mlogloss:1.22349	validation-mlogloss:1.21743
[16]	train-mlogloss:1.21468	validation-mlogloss:1.20841
[17]	train-mlogloss:1.20614	validation-mlogloss:1.19948
[18]	train-mlogloss:1.19791	validation-mlogloss:1.19097
[19]	train-mlogloss:1.18986	validation-mlogloss:1.18265
[20]	train-mlogloss:1.18198	validation-mlogloss:1.17436
[21]	train-mlogloss:1.17413	validation-mlogloss:1.16623
[22]	train-mlogloss:1.16633	validation-mlogloss:1.15810
[23]	train-mlogloss:1.15861	validation-mlogloss:1.14986
[24]	train-mlogloss:1.15081	validation-mlogloss:1.14174
[25]	train-mlogloss:1.14351	validation-mlogloss:1.13409
[26]	train-mlogloss:1.13606	validation-mlogloss:1.12627
[27]	train-mlogloss:1.12900	validation-mlogloss:1.11905
[28]	train-mlogloss:1.12203	validation-mlogloss:1.11169
[29]	train-mlogloss:1.11507	validation-mlogloss:1.10421
[30]	train-mlogloss:1.10836	validation-mlogloss:1.09720
[31]	train-mlogloss:1.10170	validation-mlogloss:1.09055
[32]	train-mlogloss:1.09509	validation-mlogloss:1.08349
[33]	train-mlogloss:1.08858	validation-mlogloss:1.07695
[34]	train-mlogloss:1.08195	validation-mlogloss:1.07012
[35]	train-mlogloss:1.07556	validation-mlogloss:1.06344
[36]	train-mlogloss:1.06932	validation-mlogloss:1.05708
[37]	train-mlogloss:1.06330	validation-mlogloss:1.05108
[38]	train-mlogloss:1.05705	validation-mlogloss:1.04465
[39]	train-mlogloss:1.05118	validation-mlogloss:1.03866
[40]	train-mlogloss:1.04540	validation-mlogloss:1.03275
[41]	train-mlogloss:1.03983	validation-mlogloss:1.02701
[42]	train-mlogloss:1.03395	validation-mlogloss:1.02084
[43]	train-mlogloss:1.02834	validation-mlogloss:1.01509
[44]	train-mlogloss:1.02258	validation-mlogloss:1.00912
[45]	train-mlogloss:1.01681	validation-mlogloss:1.00310
[46]	train-mlogloss:1.01133	validation-mlogloss:0.99744
[47]	train-mlogloss:1.00609	validation-mlogloss:0.99201
[48]	train-mlogloss:1.00092	validation-mlogloss:0.98670
[49]	train-mlogloss:0.99548	validation-mlogloss:0.98111
[50]	train-mlogloss:0.99031	validation-mlogloss:0.97577
[51]	train-mlogloss:0.98517	validation-mlogloss:0.97037
[52]	train-mlogloss:0.98016	validation-mlogloss:0.96526
[53]	train-mlogloss:0.97508	validation-mlogloss:0.96015
[54]	train-mlogloss:0.97006	validation-mlogloss:0.95511
[55]	train-mlogloss:0.96507	validation-mlogloss:0.94998
[56]	train-mlogloss:0.96013	validation-mlogloss:0.94496
[57]	train-mlogloss:0.95524	validation-mlogloss:0.93995
[58]	train-mlogloss:0.95047	validation-mlogloss:0.93515
[59]	train-mlogloss:0.94587	validation-mlogloss:0.93043
[60]	train-mlogloss:0.94151	validation-mlogloss:0.92600
[61]	train-mlogloss:0.93696	validation-mlogloss:0.92132
[62]	train-mlogloss:0.93240	validation-mlogloss:0.91661
[63]	train-mlogloss:0.92808	validation-mlogloss:0.91220
[64]	train-mlogloss:0.92364	validation-mlogloss:0.90780
[65]	train-mlogloss:0.91941	validation-mlogloss:0.90361
[66]	train-mlogloss:0.91527	validation-mlogloss:0.89972
[67]	train-mlogloss:0.91098	validation-mlogloss:0.89531
[68]	train-mlogloss:0.90692	validation-mlogloss:0.89117
[69]	train-mlogloss:0.90300	validation-mlogloss:0.88708
[70]	train-mlogloss:0.89910	validation-mlogloss:0.88307
[71]	train-mlogloss:0.89505	validation-mlogloss:0.87886
[72]	train-mlogloss:0.89124	validation-mlogloss:0.87466
[73]	train-mlogloss:0.88733	validation-mlogloss:0.87091
[74]	train-mlogloss:0.88368	validation-mlogloss:0.86723
[75]	train-mlogloss:0.87997	validation-mlogloss:0.86355
[76]	train-mlogloss:0.87612	validation-mlogloss:0.85954
[77]	train-mlogloss:0.87241	validation-mlogloss:0.85579
[78]	train-mlogloss:0.86883	validation-mlogloss:0.85210
[79]	train-mlogloss:0.86526	validation-mlogloss:0.84841
[80]	train-mlogloss:0.86186	validation-mlogloss:0.84525
[81]	train-mlogloss:0.85854	validation-mlogloss:0.84175
[82]	train-mlogloss:0.85506	validation-mlogloss:0.83837
[83]	train-mlogloss:0.85162	validation-mlogloss:0.83482
[84]	train-mlogloss:0.84822	validation-mlogloss:0.83138
[85]	train-mlogloss:0.84488	validation-mlogloss:0.82788
[86]	train-mlogloss:0.84148	validation-mlogloss:0.82426
[87]	train-mlogloss:0.83833	validation-mlogloss:0.82115
[88]	train-mlogloss:0.83504	validation-mlogloss:0.81768
[89]	train-mlogloss:0.83179	validation-mlogloss:0.81425
[90]	train-mlogloss:0.82858	validation-mlogloss:0.81085
[91]	train-mlogloss:0.82545	validation-mlogloss:0.80761
[92]	train-mlogloss:0.82234	validation-mlogloss:0.80436
[93]	train-mlogloss:0.81930	validation-mlogloss:0.80130
[94]	train-mlogloss:0.81630	validation-mlogloss:0.79825
[95]	train-mlogloss:0.81301	validation-mlogloss:0.79493
[96]	train-mlogloss:0.81016	validation-mlogloss:0.79191
[97]	train-mlogloss:0.80718	validation-mlogloss:0.78896
[98]	train-mlogloss:0.80448	validation-mlogloss:0.78618
[99]	train-mlogloss:0.80175	validation-mlogloss:0.78351
[100]	train-mlogloss:0.79882	validation-mlogloss:0.78053
[101]	train-mlogloss:0.79616	validation-mlogloss:0.77790
[102]	train-mlogloss:0.79364	validation-mlogloss:0.77538
[103]	train-mlogloss:0.79103	validation-mlogloss:0.77272
[104]	train-mlogloss:0.78838	validation-mlogloss:0.77002
[105]	train-mlogloss:0.78579	validation-mlogloss:0.76755
[106]	train-mlogloss:0.78325	validation-mlogloss:0.76494
[107]	train-mlogloss:0.78076	validation-mlogloss:0.76243
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[410]	train-mlogloss:0.51895	validation-mlogloss:0.50835
[411]	train-mlogloss:0.51879	validation-mlogloss:0.50831
[412]	train-mlogloss:0.51863	validation-mlogloss:0.50817
[413]	train-mlogloss:0.51845	validation-mlogloss:0.50797
[414]	train-mlogloss:0.51832	validation-mlogloss:0.50785
[415]	train-mlogloss:0.51811	validation-mlogloss:0.50759
[416]	train-mlogloss:0.51787	validation-mlogloss:0.50735
[417]	train-mlogloss:0.51775	validation-mlogloss:0.50725
[418]	train-mlogloss:0.51753	validation-mlogloss:0.50705
[419]	train-mlogloss:0.51735	validation-mlogloss:0.50685
[420]	train-mlogloss:0.51710	validation-mlogloss:0.50668
[421]	train-mlogloss:0.51687	validation-mlogloss:0.50654
[422]	train-mlogloss:0.51667	validation-mlogloss:0.50634
[423]	train-mlogloss:0.51648	validation-mlogloss:0.50621
[424]	train-mlogloss:0.51637	validation-mlogloss:0.50611
[425]	train-mlogloss:0.51622	validation-mlogloss:0.50597
[426]	train-mlogloss:0.51601	validation-mlogloss:0.50580
[427]	train-mlogloss:0.51580	validation-mlogloss:0.50555
[428]	train-mlogloss:0.51563	validation-mlogloss:0.50545
[429]	train-mlogloss:0.51541	validation-mlogloss:0.50524
[430]	train-mlogloss:0.51528	validation-mlogloss:0.50508
[431]	train-mlogloss:0.51511	validation-mlogloss:0.50497
[432]	train-mlogloss:0.51493	validation-mlogloss:0.50480
[433]	train-mlogloss:0.51462	validation-mlogloss:0.50454
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[435]	train-mlogloss:0.51423	validation-mlogloss:0.50420
[436]	train-mlogloss:0.51408	validation-mlogloss:0.50410
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[438]	train-mlogloss:0.51383	validation-mlogloss:0.50383
[439]	train-mlogloss:0.51369	validation-mlogloss:0.50377
[440]	train-mlogloss:0.51354	validation-mlogloss:0.50361
[441]	train-mlogloss:0.51337	validation-mlogloss:0.50349
[442]	train-mlogloss:0.51314	validation-mlogloss:0.50339
[443]	train-mlogloss:0.51300	validation-mlogloss:0.50318
[444]	train-mlogloss:0.51291	validation-mlogloss:0.50310
[445]	train-mlogloss:0.51278	validation-mlogloss:0.50296
[446]	train-mlogloss:0.51257	validation-mlogloss:0.50283
[447]	train-mlogloss:0.51236	validation-mlogloss:0.50262
[448]	train-mlogloss:0.51216	validation-mlogloss:0.50247
[449]	train-mlogloss:0.51193	validation-mlogloss:0.50223
[450]	train-mlogloss:0.51167	validation-mlogloss:0.50197
[451]	train-mlogloss:0.51150	validation-mlogloss:0.50185
[452]	train-mlogloss:0.51135	validation-mlogloss:0.50172
[453]	train-mlogloss:0.51122	validation-mlogloss:0.50164
[454]	train-mlogloss:0.51107	validation-mlogloss:0.50156
[455]	train-mlogloss:0.51088	validation-mlogloss:0.50140
[456]	train-mlogloss:0.51078	validation-mlogloss:0.50135
[457]	train-mlogloss:0.51059	validation-mlogloss:0.50121
[458]	train-mlogloss:0.51044	validation-mlogloss:0.50111
[459]	train-mlogloss:0.51032	validation-mlogloss:0.50097
[460]	train-mlogloss:0.51020	validation-mlogloss:0.50090
[461]	train-mlogloss:0.50999	validation-mlogloss:0.50065
[462]	train-mlogloss:0.50983	validation-mlogloss:0.50051
[463]	train-mlogloss:0.50963	validation-mlogloss:0.50033
[464]	train-mlogloss:0.50951	validation-mlogloss:0.50023
[465]	train-mlogloss:0.50937	validation-mlogloss:0.50016
[466]	train-mlogloss:0.50921	validation-mlogloss:0.49996
[467]	train-mlogloss:0.50906	validation-mlogloss:0.49984
[468]	train-mlogloss:0.50895	validation-mlogloss:0.49976
[469]	train-mlogloss:0.50889	validation-mlogloss:0.49971
[470]	train-mlogloss:0.50880	validation-mlogloss:0.49964
[471]	train-mlogloss:0.50866	validation-mlogloss:0.49946
[472]	train-mlogloss:0.50852	validation-mlogloss:0.49934
[473]	train-mlogloss:0.50832	validation-mlogloss:0.49918
[474]	train-mlogloss:0.50822	validation-mlogloss:0.49909
[475]	train-mlogloss:0.50816	validation-mlogloss:0.49904
[476]	train-mlogloss:0.50802	validation-mlogloss:0.49900
[477]	train-mlogloss:0.50791	validation-mlogloss:0.49890
[478]	train-mlogloss:0.50772	validation-mlogloss:0.49880
[479]	train-mlogloss:0.50756	validation-mlogloss:0.49865
[480]	train-mlogloss:0.50747	validation-mlogloss:0.49853
[481]	train-mlogloss:0.50737	validation-mlogloss:0.49842
[482]	train-mlogloss:0.50726	validation-mlogloss:0.49828
[483]	train-mlogloss:0.50718	validation-mlogloss:0.49822
[484]	train-mlogloss:0.50709	validation-mlogloss:0.49816
[485]	train-mlogloss:0.50702	validation-mlogloss:0.49809
[486]	train-mlogloss:0.50683	validation-mlogloss:0.49784
[487]	train-mlogloss:0.50670	validation-mlogloss:0.49777
[488]	train-mlogloss:0.50659	validation-mlogloss:0.49762
[489]	train-mlogloss:0.50645	validation-mlogloss:0.49749
[490]	train-mlogloss:0.50623	validation-mlogloss:0.49740
[491]	train-mlogloss:0.50611	validation-mlogloss:0.49730
[492]	train-mlogloss:0.50602	validation-mlogloss:0.49723
[493]	train-mlogloss:0.50587	validation-mlogloss:0.49699
[494]	train-mlogloss:0.50577	validation-mlogloss:0.49691
[495]	train-mlogloss:0.50565	validation-mlogloss:0.49684
[496]	train-mlogloss:0.50543	validation-mlogloss:0.49660
[497]	train-mlogloss:0.50536	validation-mlogloss:0.49657
[498]	train-mlogloss:0.50526	validation-mlogloss:0.49646
[499]	train-mlogloss:0.50521	validation-mlogloss:0.49640
[500]	train-mlogloss:0.50510	validation-mlogloss:0.49637
[501]	train-mlogloss:0.50499	validation-mlogloss:0.49621
[502]	train-mlogloss:0.50492	validation-mlogloss:0.49612
[503]	train-mlogloss:0.50482	validation-mlogloss:0.49609
[504]	train-mlogloss:0.50476	validation-mlogloss:0.49606
[505]	train-mlogloss:0.50470	validation-mlogloss:0.49604
[506]	train-mlogloss:0.50452	validation-mlogloss:0.49585
[507]	train-mlogloss:0.50443	validation-mlogloss:0.49573
[508]	train-mlogloss:0.50434	validation-mlogloss:0.49563
[509]	train-mlogloss:0.50424	validation-mlogloss:0.49551
[510]	train-mlogloss:0.50413	validation-mlogloss:0.49544
[511]	train-mlogloss:0.50406	validation-mlogloss:0.49536
[512]	train-mlogloss:0.50397	validation-mlogloss:0.49537
[513]	train-mlogloss:0.50388	validation-mlogloss:0.49529
[514]	train-mlogloss:0.50376	validation-mlogloss:0.49515
[515]	train-mlogloss:0.50372	validation-mlogloss:0.49515
[516]	train-mlogloss:0.50364	validation-mlogloss:0.49512
[517]	train-mlogloss:0.50352	validation-mlogloss:0.49501
[518]	train-mlogloss:0.50342	validation-mlogloss:0.49489
[519]	train-mlogloss:0.50334	validation-mlogloss:0.49480
[520]	train-mlogloss:0.50320	validation-mlogloss:0.49467
[521]	train-mlogloss:0.50305	validation-mlogloss:0.49457
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 78.96 [%]
Global accuracy score (test) = 79.96 [%]
Global F1 score (train) = 79.33 [%]
Global F1 score (test) = 80.65 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.69      0.65       350
MODERATE-INTENSITY       0.65      0.65      0.65       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.99      0.92      0.95       322

          accuracy                           0.80      1372
         macro avg       0.81      0.80      0.81      1372
      weighted avg       0.81      0.80      0.80      1372


Accuracy capturado en la ejecución 20: 79.96 [%]
F1-score capturado en la ejecución 20: 80.65 [%]

=== EJECUCIÓN 21 ===

--- TRAIN (ejecución 21) ---

--- TEST (ejecución 21) ---
2025-11-03 17:25:17.412560: 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`.
2025-11-03 17:25:17.424369: 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 00:00:1762187117.440575  333271 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187117.445421  333271 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187117.457020  333271 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187117.457053  333271 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187117.457055  333271 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187117.457057  333271 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:25:17.460237: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37489	validation-mlogloss:1.37391
[1]	train-mlogloss:1.36340	validation-mlogloss:1.36173
[2]	train-mlogloss:1.35250	validation-mlogloss:1.35014
[3]	train-mlogloss:1.34152	validation-mlogloss:1.33827
[4]	train-mlogloss:1.33081	validation-mlogloss:1.32687
[5]	train-mlogloss:1.32037	validation-mlogloss:1.31605
[6]	train-mlogloss:1.31019	validation-mlogloss:1.30525
[7]	train-mlogloss:1.30003	validation-mlogloss:1.29436
[8]	train-mlogloss:1.29009	validation-mlogloss:1.28378
[9]	train-mlogloss:1.28023	validation-mlogloss:1.27309
[10]	train-mlogloss:1.27088	validation-mlogloss:1.26312
[11]	train-mlogloss:1.26140	validation-mlogloss:1.25314
[12]	train-mlogloss:1.25222	validation-mlogloss:1.24319
[13]	train-mlogloss:1.24302	validation-mlogloss:1.23359
[14]	train-mlogloss:1.23423	validation-mlogloss:1.22443
[15]	train-mlogloss:1.22583	validation-mlogloss:1.21544
[16]	train-mlogloss:1.21721	validation-mlogloss:1.20648
[17]	train-mlogloss:1.20869	validation-mlogloss:1.19759
[18]	train-mlogloss:1.20026	validation-mlogloss:1.18879
[19]	train-mlogloss:1.19181	validation-mlogloss:1.17996
[20]	train-mlogloss:1.18353	validation-mlogloss:1.17107
[21]	train-mlogloss:1.17552	validation-mlogloss:1.16250
[22]	train-mlogloss:1.16767	validation-mlogloss:1.15409
[23]	train-mlogloss:1.15980	validation-mlogloss:1.14567
[24]	train-mlogloss:1.15227	validation-mlogloss:1.13769
[25]	train-mlogloss:1.14480	validation-mlogloss:1.12973
[26]	train-mlogloss:1.13765	validation-mlogloss:1.12225
[27]	train-mlogloss:1.13046	validation-mlogloss:1.11441
[28]	train-mlogloss:1.12351	validation-mlogloss:1.10691
[29]	train-mlogloss:1.11658	validation-mlogloss:1.09939
[30]	train-mlogloss:1.10976	validation-mlogloss:1.09219
[31]	train-mlogloss:1.10300	validation-mlogloss:1.08490
[32]	train-mlogloss:1.09603	validation-mlogloss:1.07754
[33]	train-mlogloss:1.08932	validation-mlogloss:1.07037
[34]	train-mlogloss:1.08289	validation-mlogloss:1.06344
[35]	train-mlogloss:1.07665	validation-mlogloss:1.05678
[36]	train-mlogloss:1.07026	validation-mlogloss:1.05001
[37]	train-mlogloss:1.06425	validation-mlogloss:1.04365
[38]	train-mlogloss:1.05821	validation-mlogloss:1.03718
[39]	train-mlogloss:1.05227	validation-mlogloss:1.03091
[40]	train-mlogloss:1.04662	validation-mlogloss:1.02515
[41]	train-mlogloss:1.04052	validation-mlogloss:1.01856
[42]	train-mlogloss:1.03497	validation-mlogloss:1.01279
[43]	train-mlogloss:1.02918	validation-mlogloss:1.00665
[44]	train-mlogloss:1.02326	validation-mlogloss:1.00053
[45]	train-mlogloss:1.01786	validation-mlogloss:0.99478
[46]	train-mlogloss:1.01244	validation-mlogloss:0.98922
[47]	train-mlogloss:1.00707	validation-mlogloss:0.98366
[48]	train-mlogloss:1.00162	validation-mlogloss:0.97797
[49]	train-mlogloss:0.99643	validation-mlogloss:0.97248
[50]	train-mlogloss:0.99134	validation-mlogloss:0.96706
[51]	train-mlogloss:0.98646	validation-mlogloss:0.96198
[52]	train-mlogloss:0.98141	validation-mlogloss:0.95660
[53]	train-mlogloss:0.97657	validation-mlogloss:0.95134
[54]	train-mlogloss:0.97172	validation-mlogloss:0.94616
[55]	train-mlogloss:0.96698	validation-mlogloss:0.94106
[56]	train-mlogloss:0.96208	validation-mlogloss:0.93581
[57]	train-mlogloss:0.95719	validation-mlogloss:0.93051
[58]	train-mlogloss:0.95249	validation-mlogloss:0.92540
[59]	train-mlogloss:0.94788	validation-mlogloss:0.92036
[60]	train-mlogloss:0.94338	validation-mlogloss:0.91576
[61]	train-mlogloss:0.93910	validation-mlogloss:0.91115
[62]	train-mlogloss:0.93484	validation-mlogloss:0.90659
[63]	train-mlogloss:0.93048	validation-mlogloss:0.90220
[64]	train-mlogloss:0.92616	validation-mlogloss:0.89788
[65]	train-mlogloss:0.92197	validation-mlogloss:0.89375
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[420]	train-mlogloss:0.52075	validation-mlogloss:0.48226
[421]	train-mlogloss:0.52060	validation-mlogloss:0.48216
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[424]	train-mlogloss:0.51998	validation-mlogloss:0.48165
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[441]	train-mlogloss:0.51698	validation-mlogloss:0.47865
[442]	train-mlogloss:0.51678	validation-mlogloss:0.47842
[443]	train-mlogloss:0.51666	validation-mlogloss:0.47828
[444]	train-mlogloss:0.51652	validation-mlogloss:0.47814
[445]	train-mlogloss:0.51644	validation-mlogloss:0.47809
[446]	train-mlogloss:0.51631	validation-mlogloss:0.47794
[447]	train-mlogloss:0.51615	validation-mlogloss:0.47767
[448]	train-mlogloss:0.51599	validation-mlogloss:0.47753
[449]	train-mlogloss:0.51589	validation-mlogloss:0.47744
[450]	train-mlogloss:0.51569	validation-mlogloss:0.47731
[451]	train-mlogloss:0.51549	validation-mlogloss:0.47712
[452]	train-mlogloss:0.51537	validation-mlogloss:0.47702
[453]	train-mlogloss:0.51519	validation-mlogloss:0.47684
[454]	train-mlogloss:0.51507	validation-mlogloss:0.47673
[455]	train-mlogloss:0.51490	validation-mlogloss:0.47657
[456]	train-mlogloss:0.51480	validation-mlogloss:0.47648
[457]	train-mlogloss:0.51465	validation-mlogloss:0.47637
[458]	train-mlogloss:0.51454	validation-mlogloss:0.47623
[459]	train-mlogloss:0.51441	validation-mlogloss:0.47613
[460]	train-mlogloss:0.51427	validation-mlogloss:0.47599
[461]	train-mlogloss:0.51410	validation-mlogloss:0.47592
[462]	train-mlogloss:0.51398	validation-mlogloss:0.47587
[463]	train-mlogloss:0.51385	validation-mlogloss:0.47574
[464]	train-mlogloss:0.51373	validation-mlogloss:0.47567
[465]	train-mlogloss:0.51357	validation-mlogloss:0.47557
[466]	train-mlogloss:0.51348	validation-mlogloss:0.47548
[467]	train-mlogloss:0.51330	validation-mlogloss:0.47525
[468]	train-mlogloss:0.51317	validation-mlogloss:0.47511
[469]	train-mlogloss:0.51302	validation-mlogloss:0.47499
[470]	train-mlogloss:0.51284	validation-mlogloss:0.47485
[471]	train-mlogloss:0.51269	validation-mlogloss:0.47481
[472]	train-mlogloss:0.51262	validation-mlogloss:0.47478
[473]	train-mlogloss:0.51249	validation-mlogloss:0.47472
[474]	train-mlogloss:0.51232	validation-mlogloss:0.47449
[475]	train-mlogloss:0.51214	validation-mlogloss:0.47437
[476]	train-mlogloss:0.51204	validation-mlogloss:0.47434
[477]	train-mlogloss:0.51189	validation-mlogloss:0.47422
[478]	train-mlogloss:0.51172	validation-mlogloss:0.47402
[479]	train-mlogloss:0.51155	validation-mlogloss:0.47383
[480]	train-mlogloss:0.51142	validation-mlogloss:0.47368
[481]	train-mlogloss:0.51124	validation-mlogloss:0.47353
[482]	train-mlogloss:0.51111	validation-mlogloss:0.47342
[483]	train-mlogloss:0.51099	validation-mlogloss:0.47328
[484]	train-mlogloss:0.51080	validation-mlogloss:0.47311
[485]	train-mlogloss:0.51070	validation-mlogloss:0.47306
[486]	train-mlogloss:0.51060	validation-mlogloss:0.47297
[487]	train-mlogloss:0.51045	validation-mlogloss:0.47285
[488]	train-mlogloss:0.51035	validation-mlogloss:0.47275
[489]	train-mlogloss:0.51017	validation-mlogloss:0.47257
[490]	train-mlogloss:0.51007	validation-mlogloss:0.47248
[491]	train-mlogloss:0.50997	validation-mlogloss:0.47234
[492]	train-mlogloss:0.50983	validation-mlogloss:0.47227
[493]	train-mlogloss:0.50968	validation-mlogloss:0.47208
[494]	train-mlogloss:0.50961	validation-mlogloss:0.47198
[495]	train-mlogloss:0.50953	validation-mlogloss:0.47191
[496]	train-mlogloss:0.50943	validation-mlogloss:0.47181
[497]	train-mlogloss:0.50920	validation-mlogloss:0.47165
[498]	train-mlogloss:0.50911	validation-mlogloss:0.47157
[499]	train-mlogloss:0.50903	validation-mlogloss:0.47152
[500]	train-mlogloss:0.50893	validation-mlogloss:0.47150
[501]	train-mlogloss:0.50888	validation-mlogloss:0.47147
[502]	train-mlogloss:0.50878	validation-mlogloss:0.47144
[503]	train-mlogloss:0.50869	validation-mlogloss:0.47136
[504]	train-mlogloss:0.50860	validation-mlogloss:0.47126
[505]	train-mlogloss:0.50842	validation-mlogloss:0.47118
[506]	train-mlogloss:0.50827	validation-mlogloss:0.47111
[507]	train-mlogloss:0.50814	validation-mlogloss:0.47106
[508]	train-mlogloss:0.50801	validation-mlogloss:0.47093
[509]	train-mlogloss:0.50790	validation-mlogloss:0.47089
[510]	train-mlogloss:0.50783	validation-mlogloss:0.47081
[511]	train-mlogloss:0.50772	validation-mlogloss:0.47066
[512]	train-mlogloss:0.50762	validation-mlogloss:0.47057
[513]	train-mlogloss:0.50752	validation-mlogloss:0.47043
[514]	train-mlogloss:0.50736	validation-mlogloss:0.47028
[515]	train-mlogloss:0.50728	validation-mlogloss:0.47019
[516]	train-mlogloss:0.50721	validation-mlogloss:0.47013
[517]	train-mlogloss:0.50709	validation-mlogloss:0.47002
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[520]	train-mlogloss:0.50684	validation-mlogloss:0.46988
[521]	train-mlogloss:0.50674	validation-mlogloss:0.46974
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 0 1 1]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.34 [%]
Global accuracy score (test) = 78.86 [%]
Global F1 score (train) = 79.66 [%]
Global F1 score (test) = 79.52 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.60      0.70      0.65       350
MODERATE-INTENSITY       0.64      0.60      0.62       350
         SEDENTARY       0.99      0.94      0.96       350
VIGOROUS-INTENSITY       0.97      0.92      0.95       322

          accuracy                           0.79      1372
         macro avg       0.80      0.79      0.80      1372
      weighted avg       0.80      0.79      0.79      1372


Accuracy capturado en la ejecución 21: 78.86 [%]
F1-score capturado en la ejecución 21: 79.52 [%]

=== EJECUCIÓN 22 ===

--- TRAIN (ejecución 22) ---

--- TEST (ejecución 22) ---
2025-11-03 17:25:36.145555: 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`.
2025-11-03 17:25:36.157368: 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 00:00:1762187136.171464  333570 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187136.175688  333570 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187136.186292  333570 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187136.186317  333570 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187136.186319  333570 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187136.186321  333570 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:25:36.189655: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37462	validation-mlogloss:1.37428
[1]	train-mlogloss:1.36319	validation-mlogloss:1.36244
[2]	train-mlogloss:1.35198	validation-mlogloss:1.35068
[3]	train-mlogloss:1.34104	validation-mlogloss:1.33909
[4]	train-mlogloss:1.33014	validation-mlogloss:1.32762
[5]	train-mlogloss:1.31951	validation-mlogloss:1.31619
[6]	train-mlogloss:1.30915	validation-mlogloss:1.30518
[7]	train-mlogloss:1.29908	validation-mlogloss:1.29442
[8]	train-mlogloss:1.28922	validation-mlogloss:1.28418
[9]	train-mlogloss:1.27960	validation-mlogloss:1.27422
[10]	train-mlogloss:1.26999	validation-mlogloss:1.26406
[11]	train-mlogloss:1.26083	validation-mlogloss:1.25462
[12]	train-mlogloss:1.25136	validation-mlogloss:1.24479
[13]	train-mlogloss:1.24234	validation-mlogloss:1.23531
[14]	train-mlogloss:1.23358	validation-mlogloss:1.22625
[15]	train-mlogloss:1.22477	validation-mlogloss:1.21700
[16]	train-mlogloss:1.21617	validation-mlogloss:1.20809
[17]	train-mlogloss:1.20751	validation-mlogloss:1.19890
[18]	train-mlogloss:1.19920	validation-mlogloss:1.19021
[19]	train-mlogloss:1.19105	validation-mlogloss:1.18188
[20]	train-mlogloss:1.18316	validation-mlogloss:1.17388
[21]	train-mlogloss:1.17525	validation-mlogloss:1.16553
[22]	train-mlogloss:1.16771	validation-mlogloss:1.15793
[23]	train-mlogloss:1.16023	validation-mlogloss:1.15027
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[447]	train-mlogloss:0.51784	validation-mlogloss:0.50314
[448]	train-mlogloss:0.51772	validation-mlogloss:0.50305
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[483]	train-mlogloss:0.51289	validation-mlogloss:0.49904
[484]	train-mlogloss:0.51270	validation-mlogloss:0.49893
[485]	train-mlogloss:0.51262	validation-mlogloss:0.49885
[486]	train-mlogloss:0.51250	validation-mlogloss:0.49877
[487]	train-mlogloss:0.51233	validation-mlogloss:0.49859
[488]	train-mlogloss:0.51223	validation-mlogloss:0.49850
[489]	train-mlogloss:0.51214	validation-mlogloss:0.49841
[490]	train-mlogloss:0.51202	validation-mlogloss:0.49825
[491]	train-mlogloss:0.51187	validation-mlogloss:0.49817
[492]	train-mlogloss:0.51176	validation-mlogloss:0.49810
[493]	train-mlogloss:0.51165	validation-mlogloss:0.49802
[494]	train-mlogloss:0.51156	validation-mlogloss:0.49792
[495]	train-mlogloss:0.51137	validation-mlogloss:0.49777
[496]	train-mlogloss:0.51123	validation-mlogloss:0.49768
[497]	train-mlogloss:0.51112	validation-mlogloss:0.49753
[498]	train-mlogloss:0.51098	validation-mlogloss:0.49739
[499]	train-mlogloss:0.51092	validation-mlogloss:0.49733
[500]	train-mlogloss:0.51075	validation-mlogloss:0.49720
[501]	train-mlogloss:0.51068	validation-mlogloss:0.49711
[502]	train-mlogloss:0.51059	validation-mlogloss:0.49697
[503]	train-mlogloss:0.51052	validation-mlogloss:0.49694
[504]	train-mlogloss:0.51045	validation-mlogloss:0.49687
[505]	train-mlogloss:0.51041	validation-mlogloss:0.49681
[506]	train-mlogloss:0.51032	validation-mlogloss:0.49668
[507]	train-mlogloss:0.51020	validation-mlogloss:0.49661
[508]	train-mlogloss:0.51004	validation-mlogloss:0.49642
[509]	train-mlogloss:0.51001	validation-mlogloss:0.49641
[510]	train-mlogloss:0.50995	validation-mlogloss:0.49633
[511]	train-mlogloss:0.50987	validation-mlogloss:0.49624
[512]	train-mlogloss:0.50978	validation-mlogloss:0.49614
[513]	train-mlogloss:0.50971	validation-mlogloss:0.49607
[514]	train-mlogloss:0.50961	validation-mlogloss:0.49599
[515]	train-mlogloss:0.50952	validation-mlogloss:0.49587
[516]	train-mlogloss:0.50944	validation-mlogloss:0.49580
[517]	train-mlogloss:0.50937	validation-mlogloss:0.49570
[518]	train-mlogloss:0.50930	validation-mlogloss:0.49566
[519]	train-mlogloss:0.50922	validation-mlogloss:0.49564
[520]	train-mlogloss:0.50913	validation-mlogloss:0.49556
[521]	train-mlogloss:0.50906	validation-mlogloss:0.49548
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.21 [%]
Global accuracy score (test) = 81.12 [%]
Global F1 score (train) = 79.59 [%]
Global F1 score (test) = 81.69 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.64      0.72      0.68       350
MODERATE-INTENSITY       0.69      0.66      0.67       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.97      0.92      0.95       322

          accuracy                           0.81      1372
         macro avg       0.82      0.81      0.82      1372
      weighted avg       0.82      0.81      0.81      1372


Accuracy capturado en la ejecución 22: 81.12 [%]
F1-score capturado en la ejecución 22: 81.69 [%]

=== EJECUCIÓN 23 ===

--- TRAIN (ejecución 23) ---

--- TEST (ejecución 23) ---
2025-11-03 17:25:51.828296: 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`.
2025-11-03 17:25:51.839655: 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 00:00:1762187151.852889  333845 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187151.857085  333845 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187151.867310  333845 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187151.867330  333845 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187151.867333  333845 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187151.867334  333845 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:25:51.870401: 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..
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
[0]	train-mlogloss:1.37487	validation-mlogloss:1.37450
[1]	train-mlogloss:1.36346	validation-mlogloss:1.36251
[2]	train-mlogloss:1.35233	validation-mlogloss:1.35068
[3]	train-mlogloss:1.34122	validation-mlogloss:1.33912
[4]	train-mlogloss:1.33043	validation-mlogloss:1.32775
[5]	train-mlogloss:1.31988	validation-mlogloss:1.31675
[6]	train-mlogloss:1.30933	validation-mlogloss:1.30585
[7]	train-mlogloss:1.29919	validation-mlogloss:1.29546
[8]	train-mlogloss:1.28937	validation-mlogloss:1.28519
[9]	train-mlogloss:1.27978	validation-mlogloss:1.27537
[10]	train-mlogloss:1.27010	validation-mlogloss:1.26508
[11]	train-mlogloss:1.26071	validation-mlogloss:1.25561
[12]	train-mlogloss:1.25138	validation-mlogloss:1.24585
[13]	train-mlogloss:1.24219	validation-mlogloss:1.23610
[14]	train-mlogloss:1.23326	validation-mlogloss:1.22663
[15]	train-mlogloss:1.22419	validation-mlogloss:1.21694
[16]	train-mlogloss:1.21561	validation-mlogloss:1.20804
[17]	train-mlogloss:1.20712	validation-mlogloss:1.19912
[18]	train-mlogloss:1.19881	validation-mlogloss:1.19028
[19]	train-mlogloss:1.19084	validation-mlogloss:1.18195
[20]	train-mlogloss:1.18281	validation-mlogloss:1.17346
[21]	train-mlogloss:1.17470	validation-mlogloss:1.16507
[22]	train-mlogloss:1.16698	validation-mlogloss:1.15682
[23]	train-mlogloss:1.15950	validation-mlogloss:1.14899
[24]	train-mlogloss:1.15210	validation-mlogloss:1.14128
[25]	train-mlogloss:1.14462	validation-mlogloss:1.13329
[26]	train-mlogloss:1.13732	validation-mlogloss:1.12588
[27]	train-mlogloss:1.13006	validation-mlogloss:1.11831
[28]	train-mlogloss:1.12309	validation-mlogloss:1.11109
[29]	train-mlogloss:1.11619	validation-mlogloss:1.10378
[30]	train-mlogloss:1.10940	validation-mlogloss:1.09676
[31]	train-mlogloss:1.10273	validation-mlogloss:1.08962
[32]	train-mlogloss:1.09605	validation-mlogloss:1.08270
[33]	train-mlogloss:1.08968	validation-mlogloss:1.07606
[34]	train-mlogloss:1.08308	validation-mlogloss:1.06888
[35]	train-mlogloss:1.07683	validation-mlogloss:1.06240
[36]	train-mlogloss:1.07050	validation-mlogloss:1.05586
[37]	train-mlogloss:1.06414	validation-mlogloss:1.04928
[38]	train-mlogloss:1.05792	validation-mlogloss:1.04292
[39]	train-mlogloss:1.05155	validation-mlogloss:1.03632
[40]	train-mlogloss:1.04542	validation-mlogloss:1.02993
[41]	train-mlogloss:1.03963	validation-mlogloss:1.02387
[42]	train-mlogloss:1.03397	validation-mlogloss:1.01806
[43]	train-mlogloss:1.02822	validation-mlogloss:1.01203
[44]	train-mlogloss:1.02232	validation-mlogloss:1.00591
[45]	train-mlogloss:1.01657	validation-mlogloss:1.00008
[46]	train-mlogloss:1.01077	validation-mlogloss:0.99425
[47]	train-mlogloss:1.00526	validation-mlogloss:0.98837
[48]	train-mlogloss:0.99976	validation-mlogloss:0.98287
[49]	train-mlogloss:0.99446	validation-mlogloss:0.97751
[50]	train-mlogloss:0.98926	validation-mlogloss:0.97211
[51]	train-mlogloss:0.98405	validation-mlogloss:0.96676
[52]	train-mlogloss:0.97922	validation-mlogloss:0.96190
[53]	train-mlogloss:0.97431	validation-mlogloss:0.95683
[54]	train-mlogloss:0.96927	validation-mlogloss:0.95182
[55]	train-mlogloss:0.96461	validation-mlogloss:0.94681
[56]	train-mlogloss:0.95994	validation-mlogloss:0.94196
[57]	train-mlogloss:0.95518	validation-mlogloss:0.93720
[58]	train-mlogloss:0.95040	validation-mlogloss:0.93221
[59]	train-mlogloss:0.94570	validation-mlogloss:0.92759
[60]	train-mlogloss:0.94105	validation-mlogloss:0.92297
[61]	train-mlogloss:0.93642	validation-mlogloss:0.91855
[62]	train-mlogloss:0.93216	validation-mlogloss:0.91400
[63]	train-mlogloss:0.92776	validation-mlogloss:0.90947
[64]	train-mlogloss:0.92326	validation-mlogloss:0.90495
[65]	train-mlogloss:0.91903	validation-mlogloss:0.90047
[66]	train-mlogloss:0.91473	validation-mlogloss:0.89617
[67]	train-mlogloss:0.91051	validation-mlogloss:0.89181
[68]	train-mlogloss:0.90647	validation-mlogloss:0.88778
[69]	train-mlogloss:0.90247	validation-mlogloss:0.88365
[70]	train-mlogloss:0.89863	validation-mlogloss:0.87953
[71]	train-mlogloss:0.89474	validation-mlogloss:0.87531
[72]	train-mlogloss:0.89094	validation-mlogloss:0.87145
[73]	train-mlogloss:0.88718	validation-mlogloss:0.86784
[74]	train-mlogloss:0.88309	validation-mlogloss:0.86369
[75]	train-mlogloss:0.87931	validation-mlogloss:0.85974
[76]	train-mlogloss:0.87579	validation-mlogloss:0.85593
[77]	train-mlogloss:0.87196	validation-mlogloss:0.85198
[78]	train-mlogloss:0.86838	validation-mlogloss:0.84814
[79]	train-mlogloss:0.86478	validation-mlogloss:0.84449
[80]	train-mlogloss:0.86128	validation-mlogloss:0.84104
[81]	train-mlogloss:0.85801	validation-mlogloss:0.83764
[82]	train-mlogloss:0.85460	validation-mlogloss:0.83436
[83]	train-mlogloss:0.85117	validation-mlogloss:0.83071
[84]	train-mlogloss:0.84775	validation-mlogloss:0.82719
[85]	train-mlogloss:0.84452	validation-mlogloss:0.82387
[86]	train-mlogloss:0.84123	validation-mlogloss:0.82047
[87]	train-mlogloss:0.83818	validation-mlogloss:0.81729
[88]	train-mlogloss:0.83509	validation-mlogloss:0.81418
[89]	train-mlogloss:0.83191	validation-mlogloss:0.81083
[90]	train-mlogloss:0.82868	validation-mlogloss:0.80752
[91]	train-mlogloss:0.82563	validation-mlogloss:0.80444
[92]	train-mlogloss:0.82261	validation-mlogloss:0.80128
[93]	train-mlogloss:0.81974	validation-mlogloss:0.79834
[94]	train-mlogloss:0.81671	validation-mlogloss:0.79513
[95]	train-mlogloss:0.81384	validation-mlogloss:0.79220
[96]	train-mlogloss:0.81092	validation-mlogloss:0.78927
[97]	train-mlogloss:0.80793	validation-mlogloss:0.78622
[98]	train-mlogloss:0.80517	validation-mlogloss:0.78327
[99]	train-mlogloss:0.80213	validation-mlogloss:0.78028
[100]	train-mlogloss:0.79934	validation-mlogloss:0.77727
[101]	train-mlogloss:0.79672	validation-mlogloss:0.77453
[102]	train-mlogloss:0.79393	validation-mlogloss:0.77173
[103]	train-mlogloss:0.79113	validation-mlogloss:0.76887
[104]	train-mlogloss:0.78853	validation-mlogloss:0.76617
[105]	train-mlogloss:0.78593	validation-mlogloss:0.76332
[106]	train-mlogloss:0.78346	validation-mlogloss:0.76067
[107]	train-mlogloss:0.78105	validation-mlogloss:0.75814
[108]	train-mlogloss:0.77846	validation-mlogloss:0.75554
[109]	train-mlogloss:0.77600	validation-mlogloss:0.75296
[110]	train-mlogloss:0.77350	validation-mlogloss:0.75048
[111]	train-mlogloss:0.77106	validation-mlogloss:0.74793
[112]	train-mlogloss:0.76859	validation-mlogloss:0.74529
[113]	train-mlogloss:0.76623	validation-mlogloss:0.74286
[114]	train-mlogloss:0.76386	validation-mlogloss:0.74054
[115]	train-mlogloss:0.76152	validation-mlogloss:0.73815
[116]	train-mlogloss:0.75925	validation-mlogloss:0.73576
[117]	train-mlogloss:0.75680	validation-mlogloss:0.73327
[118]	train-mlogloss:0.75464	validation-mlogloss:0.73107
[119]	train-mlogloss:0.75237	validation-mlogloss:0.72865
[120]	train-mlogloss:0.75018	validation-mlogloss:0.72642
[121]	train-mlogloss:0.74791	validation-mlogloss:0.72419
[122]	train-mlogloss:0.74555	validation-mlogloss:0.72189
[123]	train-mlogloss:0.74325	validation-mlogloss:0.71947
[124]	train-mlogloss:0.74094	validation-mlogloss:0.71715
[125]	train-mlogloss:0.73890	validation-mlogloss:0.71500
[126]	train-mlogloss:0.73684	validation-mlogloss:0.71285
[127]	train-mlogloss:0.73487	validation-mlogloss:0.71070
[128]	train-mlogloss:0.73269	validation-mlogloss:0.70845
[129]	train-mlogloss:0.73077	validation-mlogloss:0.70642
[130]	train-mlogloss:0.72867	validation-mlogloss:0.70423
[131]	train-mlogloss:0.72656	validation-mlogloss:0.70205
[132]	train-mlogloss:0.72446	validation-mlogloss:0.69999
[133]	train-mlogloss:0.72268	validation-mlogloss:0.69806
[134]	train-mlogloss:0.72061	validation-mlogloss:0.69596
[135]	train-mlogloss:0.71867	validation-mlogloss:0.69388
[136]	train-mlogloss:0.71669	validation-mlogloss:0.69180
[137]	train-mlogloss:0.71488	validation-mlogloss:0.68989
[138]	train-mlogloss:0.71308	validation-mlogloss:0.68800
[139]	train-mlogloss:0.71111	validation-mlogloss:0.68607
[140]	train-mlogloss:0.70925	validation-mlogloss:0.68424
[141]	train-mlogloss:0.70738	validation-mlogloss:0.68240
[142]	train-mlogloss:0.70563	validation-mlogloss:0.68039
[143]	train-mlogloss:0.70377	validation-mlogloss:0.67857
[144]	train-mlogloss:0.70201	validation-mlogloss:0.67685
[145]	train-mlogloss:0.70039	validation-mlogloss:0.67515
[146]	train-mlogloss:0.69868	validation-mlogloss:0.67342
[147]	train-mlogloss:0.69685	validation-mlogloss:0.67151
[148]	train-mlogloss:0.69520	validation-mlogloss:0.66975
[149]	train-mlogloss:0.69334	validation-mlogloss:0.66773
[150]	train-mlogloss:0.69161	validation-mlogloss:0.66607
[151]	train-mlogloss:0.68994	validation-mlogloss:0.66441
[152]	train-mlogloss:0.68851	validation-mlogloss:0.66284
[153]	train-mlogloss:0.68693	validation-mlogloss:0.66115
[154]	train-mlogloss:0.68545	validation-mlogloss:0.65953
[155]	train-mlogloss:0.68401	validation-mlogloss:0.65806
[156]	train-mlogloss:0.68240	validation-mlogloss:0.65644
[157]	train-mlogloss:0.68079	validation-mlogloss:0.65486
[158]	train-mlogloss:0.67924	validation-mlogloss:0.65335
[159]	train-mlogloss:0.67767	validation-mlogloss:0.65165
[160]	train-mlogloss:0.67624	validation-mlogloss:0.65008
[161]	train-mlogloss:0.67480	validation-mlogloss:0.64867
[162]	train-mlogloss:0.67328	validation-mlogloss:0.64705
[163]	train-mlogloss:0.67189	validation-mlogloss:0.64548
[164]	train-mlogloss:0.67044	validation-mlogloss:0.64408
[165]	train-mlogloss:0.66894	validation-mlogloss:0.64260
[166]	train-mlogloss:0.66759	validation-mlogloss:0.64109
[167]	train-mlogloss:0.66616	validation-mlogloss:0.63955
[168]	train-mlogloss:0.66478	validation-mlogloss:0.63810
[169]	train-mlogloss:0.66339	validation-mlogloss:0.63668
[170]	train-mlogloss:0.66197	validation-mlogloss:0.63525
[171]	train-mlogloss:0.66060	validation-mlogloss:0.63388
[172]	train-mlogloss:0.65921	validation-mlogloss:0.63251
[173]	train-mlogloss:0.65789	validation-mlogloss:0.63124
[174]	train-mlogloss:0.65661	validation-mlogloss:0.62988
[175]	train-mlogloss:0.65534	validation-mlogloss:0.62850
[176]	train-mlogloss:0.65403	validation-mlogloss:0.62731
[177]	train-mlogloss:0.65284	validation-mlogloss:0.62605
[178]	train-mlogloss:0.65165	validation-mlogloss:0.62489
[179]	train-mlogloss:0.65037	validation-mlogloss:0.62358
[180]	train-mlogloss:0.64916	validation-mlogloss:0.62242
[181]	train-mlogloss:0.64790	validation-mlogloss:0.62113
[182]	train-mlogloss:0.64676	validation-mlogloss:0.62007
[183]	train-mlogloss:0.64551	validation-mlogloss:0.61890
[184]	train-mlogloss:0.64431	validation-mlogloss:0.61759
[185]	train-mlogloss:0.64312	validation-mlogloss:0.61642
[186]	train-mlogloss:0.64188	validation-mlogloss:0.61510
[187]	train-mlogloss:0.64066	validation-mlogloss:0.61395
[188]	train-mlogloss:0.63952	validation-mlogloss:0.61277
[189]	train-mlogloss:0.63837	validation-mlogloss:0.61162
[190]	train-mlogloss:0.63725	validation-mlogloss:0.61064
[191]	train-mlogloss:0.63607	validation-mlogloss:0.60954
[192]	train-mlogloss:0.63495	validation-mlogloss:0.60843
[193]	train-mlogloss:0.63382	validation-mlogloss:0.60736
[194]	train-mlogloss:0.63280	validation-mlogloss:0.60635
[195]	train-mlogloss:0.63173	validation-mlogloss:0.60524
[196]	train-mlogloss:0.63061	validation-mlogloss:0.60411
[197]	train-mlogloss:0.62961	validation-mlogloss:0.60305
[198]	train-mlogloss:0.62872	validation-mlogloss:0.60210
[199]	train-mlogloss:0.62766	validation-mlogloss:0.60103
[200]	train-mlogloss:0.62660	validation-mlogloss:0.59999
[201]	train-mlogloss:0.62557	validation-mlogloss:0.59905
[202]	train-mlogloss:0.62457	validation-mlogloss:0.59811
[203]	train-mlogloss:0.62366	validation-mlogloss:0.59710
[204]	train-mlogloss:0.62271	validation-mlogloss:0.59615
[205]	train-mlogloss:0.62165	validation-mlogloss:0.59500
[206]	train-mlogloss:0.62062	validation-mlogloss:0.59380
[207]	train-mlogloss:0.61961	validation-mlogloss:0.59274
[208]	train-mlogloss:0.61868	validation-mlogloss:0.59169
[209]	train-mlogloss:0.61782	validation-mlogloss:0.59082
[210]	train-mlogloss:0.61685	validation-mlogloss:0.58990
[211]	train-mlogloss:0.61597	validation-mlogloss:0.58901
[212]	train-mlogloss:0.61506	validation-mlogloss:0.58807
[213]	train-mlogloss:0.61409	validation-mlogloss:0.58711
[214]	train-mlogloss:0.61322	validation-mlogloss:0.58619
[215]	train-mlogloss:0.61234	validation-mlogloss:0.58540
[216]	train-mlogloss:0.61144	validation-mlogloss:0.58452
[217]	train-mlogloss:0.61058	validation-mlogloss:0.58369
[218]	train-mlogloss:0.60973	validation-mlogloss:0.58288
[219]	train-mlogloss:0.60881	validation-mlogloss:0.58193
[220]	train-mlogloss:0.60790	validation-mlogloss:0.58099
[221]	train-mlogloss:0.60709	validation-mlogloss:0.58019
[222]	train-mlogloss:0.60626	validation-mlogloss:0.57945
[223]	train-mlogloss:0.60536	validation-mlogloss:0.57863
[224]	train-mlogloss:0.60457	validation-mlogloss:0.57783
[225]	train-mlogloss:0.60375	validation-mlogloss:0.57696
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[227]	train-mlogloss:0.60212	validation-mlogloss:0.57535
[228]	train-mlogloss:0.60137	validation-mlogloss:0.57467
[229]	train-mlogloss:0.60040	validation-mlogloss:0.57358
[230]	train-mlogloss:0.59969	validation-mlogloss:0.57286
[231]	train-mlogloss:0.59889	validation-mlogloss:0.57198
[232]	train-mlogloss:0.59810	validation-mlogloss:0.57121
[233]	train-mlogloss:0.59740	validation-mlogloss:0.57060
[234]	train-mlogloss:0.59663	validation-mlogloss:0.56992
[235]	train-mlogloss:0.59589	validation-mlogloss:0.56916
[236]	train-mlogloss:0.59519	validation-mlogloss:0.56853
[237]	train-mlogloss:0.59448	validation-mlogloss:0.56785
[238]	train-mlogloss:0.59375	validation-mlogloss:0.56716
[239]	train-mlogloss:0.59309	validation-mlogloss:0.56654
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[241]	train-mlogloss:0.59167	validation-mlogloss:0.56504
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[273]	train-mlogloss:0.57194	validation-mlogloss:0.54645
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[278]	train-mlogloss:0.56914	validation-mlogloss:0.54381
[279]	train-mlogloss:0.56866	validation-mlogloss:0.54333
[280]	train-mlogloss:0.56816	validation-mlogloss:0.54287
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[500]	train-mlogloss:0.50901	validation-mlogloss:0.49083
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[503]	train-mlogloss:0.50867	validation-mlogloss:0.49047
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[505]	train-mlogloss:0.50844	validation-mlogloss:0.49020
[506]	train-mlogloss:0.50833	validation-mlogloss:0.49009
[507]	train-mlogloss:0.50815	validation-mlogloss:0.48994
[508]	train-mlogloss:0.50798	validation-mlogloss:0.48970
[509]	train-mlogloss:0.50788	validation-mlogloss:0.48966
[510]	train-mlogloss:0.50778	validation-mlogloss:0.48959
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[520]	train-mlogloss:0.50689	validation-mlogloss:0.48895
[521]	train-mlogloss:0.50682	validation-mlogloss:0.48884
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[1 1 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.12 [%]
Global accuracy score (test) = 79.08 [%]
Global F1 score (train) = 79.46 [%]
Global F1 score (test) = 79.68 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.60      0.71      0.65       350
MODERATE-INTENSITY       0.66      0.60      0.63       350
         SEDENTARY       0.99      0.94      0.96       350
VIGOROUS-INTENSITY       0.96      0.92      0.94       322

          accuracy                           0.79      1372
         macro avg       0.80      0.79      0.80      1372
      weighted avg       0.80      0.79      0.79      1372


Accuracy capturado en la ejecución 23: 79.08 [%]
F1-score capturado en la ejecución 23: 79.68 [%]

=== EJECUCIÓN 24 ===

--- TRAIN (ejecución 24) ---

--- TEST (ejecución 24) ---
2025-11-03 17:26:07.713144: 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`.
2025-11-03 17:26:07.724980: 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 00:00:1762187167.738499  334154 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187167.742933  334154 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187167.753051  334154 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187167.753074  334154 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187167.753076  334154 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187167.753078  334154 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:26:07.756373: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37449	validation-mlogloss:1.37410
[1]	train-mlogloss:1.36295	validation-mlogloss:1.36195
[2]	train-mlogloss:1.35182	validation-mlogloss:1.35005
[3]	train-mlogloss:1.34068	validation-mlogloss:1.33871
[4]	train-mlogloss:1.33010	validation-mlogloss:1.32799
[5]	train-mlogloss:1.31952	validation-mlogloss:1.31709
[6]	train-mlogloss:1.30907	validation-mlogloss:1.30611
[7]	train-mlogloss:1.29902	validation-mlogloss:1.29525
[8]	train-mlogloss:1.28916	validation-mlogloss:1.28489
[9]	train-mlogloss:1.27916	validation-mlogloss:1.27433
[10]	train-mlogloss:1.26976	validation-mlogloss:1.26459
[11]	train-mlogloss:1.26004	validation-mlogloss:1.25434
[12]	train-mlogloss:1.25078	validation-mlogloss:1.24468
[13]	train-mlogloss:1.24182	validation-mlogloss:1.23541
[14]	train-mlogloss:1.23298	validation-mlogloss:1.22625
[15]	train-mlogloss:1.22424	validation-mlogloss:1.21723
[16]	train-mlogloss:1.21559	validation-mlogloss:1.20801
[17]	train-mlogloss:1.20705	validation-mlogloss:1.19907
[18]	train-mlogloss:1.19884	validation-mlogloss:1.19052
[19]	train-mlogloss:1.19090	validation-mlogloss:1.18234
[20]	train-mlogloss:1.18257	validation-mlogloss:1.17371
[21]	train-mlogloss:1.17451	validation-mlogloss:1.16526
[22]	train-mlogloss:1.16637	validation-mlogloss:1.15715
[23]	train-mlogloss:1.15866	validation-mlogloss:1.14918
[24]	train-mlogloss:1.15113	validation-mlogloss:1.14139
[25]	train-mlogloss:1.14367	validation-mlogloss:1.13348
[26]	train-mlogloss:1.13639	validation-mlogloss:1.12566
[27]	train-mlogloss:1.12932	validation-mlogloss:1.11829
[28]	train-mlogloss:1.12231	validation-mlogloss:1.11093
[29]	train-mlogloss:1.11539	validation-mlogloss:1.10397
[30]	train-mlogloss:1.10845	validation-mlogloss:1.09680
[31]	train-mlogloss:1.10169	validation-mlogloss:1.08966
[32]	train-mlogloss:1.09514	validation-mlogloss:1.08298
[33]	train-mlogloss:1.08849	validation-mlogloss:1.07624
[34]	train-mlogloss:1.08189	validation-mlogloss:1.06954
[35]	train-mlogloss:1.07563	validation-mlogloss:1.06303
[36]	train-mlogloss:1.06908	validation-mlogloss:1.05633
[37]	train-mlogloss:1.06302	validation-mlogloss:1.04991
[38]	train-mlogloss:1.05693	validation-mlogloss:1.04352
[39]	train-mlogloss:1.05070	validation-mlogloss:1.03711
[40]	train-mlogloss:1.04443	validation-mlogloss:1.03071
[41]	train-mlogloss:1.03846	validation-mlogloss:1.02459
[42]	train-mlogloss:1.03237	validation-mlogloss:1.01844
[43]	train-mlogloss:1.02667	validation-mlogloss:1.01261
[44]	train-mlogloss:1.02110	validation-mlogloss:1.00672
[45]	train-mlogloss:1.01552	validation-mlogloss:1.00126
[46]	train-mlogloss:1.01005	validation-mlogloss:0.99561
[47]	train-mlogloss:1.00472	validation-mlogloss:0.99015
[48]	train-mlogloss:0.99939	validation-mlogloss:0.98486
[49]	train-mlogloss:0.99427	validation-mlogloss:0.97982
[50]	train-mlogloss:0.98934	validation-mlogloss:0.97473
[51]	train-mlogloss:0.98422	validation-mlogloss:0.96951
[52]	train-mlogloss:0.97901	validation-mlogloss:0.96410
[53]	train-mlogloss:0.97396	validation-mlogloss:0.95888
[54]	train-mlogloss:0.96905	validation-mlogloss:0.95375
[55]	train-mlogloss:0.96451	validation-mlogloss:0.94908
[56]	train-mlogloss:0.95987	validation-mlogloss:0.94441
[57]	train-mlogloss:0.95515	validation-mlogloss:0.93948
[58]	train-mlogloss:0.95061	validation-mlogloss:0.93475
[59]	train-mlogloss:0.94589	validation-mlogloss:0.92989
[60]	train-mlogloss:0.94134	validation-mlogloss:0.92534
[61]	train-mlogloss:0.93680	validation-mlogloss:0.92081
[62]	train-mlogloss:0.93229	validation-mlogloss:0.91616
[63]	train-mlogloss:0.92804	validation-mlogloss:0.91179
[64]	train-mlogloss:0.92375	validation-mlogloss:0.90727
[65]	train-mlogloss:0.91941	validation-mlogloss:0.90283
[66]	train-mlogloss:0.91506	validation-mlogloss:0.89838
[67]	train-mlogloss:0.91089	validation-mlogloss:0.89420
[68]	train-mlogloss:0.90682	validation-mlogloss:0.89021
[69]	train-mlogloss:0.90288	validation-mlogloss:0.88609
[70]	train-mlogloss:0.89884	validation-mlogloss:0.88204
[71]	train-mlogloss:0.89504	validation-mlogloss:0.87836
[72]	train-mlogloss:0.89126	validation-mlogloss:0.87444
[73]	train-mlogloss:0.88753	validation-mlogloss:0.87064
[74]	train-mlogloss:0.88386	validation-mlogloss:0.86703
[75]	train-mlogloss:0.88022	validation-mlogloss:0.86328
[76]	train-mlogloss:0.87638	validation-mlogloss:0.85926
[77]	train-mlogloss:0.87275	validation-mlogloss:0.85556
[78]	train-mlogloss:0.86909	validation-mlogloss:0.85154
[79]	train-mlogloss:0.86561	validation-mlogloss:0.84805
[80]	train-mlogloss:0.86199	validation-mlogloss:0.84427
[81]	train-mlogloss:0.85859	validation-mlogloss:0.84081
[82]	train-mlogloss:0.85515	validation-mlogloss:0.83746
[83]	train-mlogloss:0.85175	validation-mlogloss:0.83398
[84]	train-mlogloss:0.84843	validation-mlogloss:0.83058
[85]	train-mlogloss:0.84495	validation-mlogloss:0.82714
[86]	train-mlogloss:0.84168	validation-mlogloss:0.82384
[87]	train-mlogloss:0.83847	validation-mlogloss:0.82053
[88]	train-mlogloss:0.83524	validation-mlogloss:0.81720
[89]	train-mlogloss:0.83223	validation-mlogloss:0.81427
[90]	train-mlogloss:0.82919	validation-mlogloss:0.81110
[91]	train-mlogloss:0.82613	validation-mlogloss:0.80799
[92]	train-mlogloss:0.82313	validation-mlogloss:0.80504
[93]	train-mlogloss:0.82009	validation-mlogloss:0.80196
[94]	train-mlogloss:0.81693	validation-mlogloss:0.79880
[95]	train-mlogloss:0.81401	validation-mlogloss:0.79589
[96]	train-mlogloss:0.81102	validation-mlogloss:0.79279
[97]	train-mlogloss:0.80812	validation-mlogloss:0.78982
[98]	train-mlogloss:0.80525	validation-mlogloss:0.78670
[99]	train-mlogloss:0.80240	validation-mlogloss:0.78371
[100]	train-mlogloss:0.79935	validation-mlogloss:0.78061
[101]	train-mlogloss:0.79664	validation-mlogloss:0.77786
[102]	train-mlogloss:0.79407	validation-mlogloss:0.77525
[103]	train-mlogloss:0.79121	validation-mlogloss:0.77241
[104]	train-mlogloss:0.78872	validation-mlogloss:0.76975
[105]	train-mlogloss:0.78603	validation-mlogloss:0.76703
[106]	train-mlogloss:0.78342	validation-mlogloss:0.76431
[107]	train-mlogloss:0.78097	validation-mlogloss:0.76181
[108]	train-mlogloss:0.77847	validation-mlogloss:0.75928
[109]	train-mlogloss:0.77597	validation-mlogloss:0.75672
[110]	train-mlogloss:0.77349	validation-mlogloss:0.75412
[111]	train-mlogloss:0.77092	validation-mlogloss:0.75148
[112]	train-mlogloss:0.76845	validation-mlogloss:0.74892
[113]	train-mlogloss:0.76608	validation-mlogloss:0.74651
[114]	train-mlogloss:0.76381	validation-mlogloss:0.74410
[115]	train-mlogloss:0.76148	validation-mlogloss:0.74176
[116]	train-mlogloss:0.75917	validation-mlogloss:0.73907
[117]	train-mlogloss:0.75694	validation-mlogloss:0.73673
[118]	train-mlogloss:0.75467	validation-mlogloss:0.73427
[119]	train-mlogloss:0.75240	validation-mlogloss:0.73196
[120]	train-mlogloss:0.74997	validation-mlogloss:0.72950
[121]	train-mlogloss:0.74766	validation-mlogloss:0.72714
[122]	train-mlogloss:0.74528	validation-mlogloss:0.72469
[123]	train-mlogloss:0.74316	validation-mlogloss:0.72256
[124]	train-mlogloss:0.74097	validation-mlogloss:0.72033
[125]	train-mlogloss:0.73873	validation-mlogloss:0.71802
[126]	train-mlogloss:0.73665	validation-mlogloss:0.71600
[127]	train-mlogloss:0.73440	validation-mlogloss:0.71376
[128]	train-mlogloss:0.73220	validation-mlogloss:0.71154
[129]	train-mlogloss:0.73001	validation-mlogloss:0.70931
[130]	train-mlogloss:0.72796	validation-mlogloss:0.70715
[131]	train-mlogloss:0.72594	validation-mlogloss:0.70507
[132]	train-mlogloss:0.72388	validation-mlogloss:0.70295
[133]	train-mlogloss:0.72198	validation-mlogloss:0.70099
[134]	train-mlogloss:0.71995	validation-mlogloss:0.69896
[135]	train-mlogloss:0.71790	validation-mlogloss:0.69688
[136]	train-mlogloss:0.71608	validation-mlogloss:0.69493
[137]	train-mlogloss:0.71406	validation-mlogloss:0.69284
[138]	train-mlogloss:0.71212	validation-mlogloss:0.69089
[139]	train-mlogloss:0.71022	validation-mlogloss:0.68910
[140]	train-mlogloss:0.70827	validation-mlogloss:0.68720
[141]	train-mlogloss:0.70655	validation-mlogloss:0.68539
[142]	train-mlogloss:0.70478	validation-mlogloss:0.68352
[143]	train-mlogloss:0.70292	validation-mlogloss:0.68162
[144]	train-mlogloss:0.70123	validation-mlogloss:0.67988
[145]	train-mlogloss:0.69953	validation-mlogloss:0.67820
[146]	train-mlogloss:0.69775	validation-mlogloss:0.67646
[147]	train-mlogloss:0.69587	validation-mlogloss:0.67480
[148]	train-mlogloss:0.69420	validation-mlogloss:0.67313
[149]	train-mlogloss:0.69258	validation-mlogloss:0.67151
[150]	train-mlogloss:0.69087	validation-mlogloss:0.66979
[151]	train-mlogloss:0.68914	validation-mlogloss:0.66801
[152]	train-mlogloss:0.68746	validation-mlogloss:0.66641
[153]	train-mlogloss:0.68591	validation-mlogloss:0.66489
[154]	train-mlogloss:0.68440	validation-mlogloss:0.66329
[155]	train-mlogloss:0.68296	validation-mlogloss:0.66187
[156]	train-mlogloss:0.68140	validation-mlogloss:0.66023
[157]	train-mlogloss:0.67991	validation-mlogloss:0.65866
[158]	train-mlogloss:0.67852	validation-mlogloss:0.65722
[159]	train-mlogloss:0.67694	validation-mlogloss:0.65562
[160]	train-mlogloss:0.67536	validation-mlogloss:0.65409
[161]	train-mlogloss:0.67375	validation-mlogloss:0.65233
[162]	train-mlogloss:0.67239	validation-mlogloss:0.65087
[163]	train-mlogloss:0.67096	validation-mlogloss:0.64944
[164]	train-mlogloss:0.66949	validation-mlogloss:0.64797
[165]	train-mlogloss:0.66827	validation-mlogloss:0.64666
[166]	train-mlogloss:0.66686	validation-mlogloss:0.64528
[167]	train-mlogloss:0.66542	validation-mlogloss:0.64385
[168]	train-mlogloss:0.66415	validation-mlogloss:0.64251
[169]	train-mlogloss:0.66275	validation-mlogloss:0.64115
[170]	train-mlogloss:0.66148	validation-mlogloss:0.63985
[171]	train-mlogloss:0.66003	validation-mlogloss:0.63836
[172]	train-mlogloss:0.65856	validation-mlogloss:0.63694
[173]	train-mlogloss:0.65716	validation-mlogloss:0.63556
[174]	train-mlogloss:0.65579	validation-mlogloss:0.63415
[175]	train-mlogloss:0.65447	validation-mlogloss:0.63295
[176]	train-mlogloss:0.65321	validation-mlogloss:0.63159
[177]	train-mlogloss:0.65182	validation-mlogloss:0.63029
[178]	train-mlogloss:0.65053	validation-mlogloss:0.62905
[179]	train-mlogloss:0.64919	validation-mlogloss:0.62780
[180]	train-mlogloss:0.64813	validation-mlogloss:0.62666
[181]	train-mlogloss:0.64687	validation-mlogloss:0.62555
[182]	train-mlogloss:0.64559	validation-mlogloss:0.62431
[183]	train-mlogloss:0.64432	validation-mlogloss:0.62315
[184]	train-mlogloss:0.64302	validation-mlogloss:0.62176
[185]	train-mlogloss:0.64194	validation-mlogloss:0.62065
[186]	train-mlogloss:0.64071	validation-mlogloss:0.61943
[187]	train-mlogloss:0.63953	validation-mlogloss:0.61838
[188]	train-mlogloss:0.63829	validation-mlogloss:0.61708
[189]	train-mlogloss:0.63720	validation-mlogloss:0.61617
[190]	train-mlogloss:0.63610	validation-mlogloss:0.61525
[191]	train-mlogloss:0.63489	validation-mlogloss:0.61403
[192]	train-mlogloss:0.63379	validation-mlogloss:0.61303
[193]	train-mlogloss:0.63261	validation-mlogloss:0.61197
[194]	train-mlogloss:0.63155	validation-mlogloss:0.61098
[195]	train-mlogloss:0.63043	validation-mlogloss:0.60991
[196]	train-mlogloss:0.62932	validation-mlogloss:0.60882
[197]	train-mlogloss:0.62819	validation-mlogloss:0.60756
[198]	train-mlogloss:0.62716	validation-mlogloss:0.60653
[199]	train-mlogloss:0.62601	validation-mlogloss:0.60540
[200]	train-mlogloss:0.62505	validation-mlogloss:0.60450
[201]	train-mlogloss:0.62400	validation-mlogloss:0.60350
[202]	train-mlogloss:0.62302	validation-mlogloss:0.60251
[203]	train-mlogloss:0.62194	validation-mlogloss:0.60153
[204]	train-mlogloss:0.62093	validation-mlogloss:0.60061
[205]	train-mlogloss:0.61984	validation-mlogloss:0.59948
[206]	train-mlogloss:0.61886	validation-mlogloss:0.59862
[207]	train-mlogloss:0.61787	validation-mlogloss:0.59758
[208]	train-mlogloss:0.61698	validation-mlogloss:0.59670
[209]	train-mlogloss:0.61608	validation-mlogloss:0.59575
[210]	train-mlogloss:0.61511	validation-mlogloss:0.59472
[211]	train-mlogloss:0.61419	validation-mlogloss:0.59380
[212]	train-mlogloss:0.61324	validation-mlogloss:0.59287
[213]	train-mlogloss:0.61233	validation-mlogloss:0.59204
[214]	train-mlogloss:0.61142	validation-mlogloss:0.59122
[215]	train-mlogloss:0.61059	validation-mlogloss:0.59038
[216]	train-mlogloss:0.60956	validation-mlogloss:0.58923
[217]	train-mlogloss:0.60876	validation-mlogloss:0.58845
[218]	train-mlogloss:0.60790	validation-mlogloss:0.58765
[219]	train-mlogloss:0.60698	validation-mlogloss:0.58680
[220]	train-mlogloss:0.60603	validation-mlogloss:0.58594
[221]	train-mlogloss:0.60511	validation-mlogloss:0.58523
[222]	train-mlogloss:0.60419	validation-mlogloss:0.58444
[223]	train-mlogloss:0.60333	validation-mlogloss:0.58367
[224]	train-mlogloss:0.60253	validation-mlogloss:0.58292
[225]	train-mlogloss:0.60169	validation-mlogloss:0.58213
[226]	train-mlogloss:0.60088	validation-mlogloss:0.58134
[227]	train-mlogloss:0.60004	validation-mlogloss:0.58057
[228]	train-mlogloss:0.59916	validation-mlogloss:0.57982
[229]	train-mlogloss:0.59840	validation-mlogloss:0.57911
[230]	train-mlogloss:0.59759	validation-mlogloss:0.57845
[231]	train-mlogloss:0.59676	validation-mlogloss:0.57770
[232]	train-mlogloss:0.59595	validation-mlogloss:0.57700
[233]	train-mlogloss:0.59518	validation-mlogloss:0.57639
[234]	train-mlogloss:0.59434	validation-mlogloss:0.57569
[235]	train-mlogloss:0.59351	validation-mlogloss:0.57502
[236]	train-mlogloss:0.59276	validation-mlogloss:0.57433
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Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[0 0 0 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 78.85 [%]
Global accuracy score (test) = 79.52 [%]
Global F1 score (train) = 79.16 [%]
Global F1 score (test) = 80.05 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.69      0.66       350
MODERATE-INTENSITY       0.66      0.63      0.64       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.95      0.92      0.94       322

          accuracy                           0.80      1372
         macro avg       0.80      0.80      0.80      1372
      weighted avg       0.80      0.80      0.80      1372


Accuracy capturado en la ejecución 24: 79.52 [%]
F1-score capturado en la ejecución 24: 80.05 [%]

=== EJECUCIÓN 25 ===

--- TRAIN (ejecución 25) ---

--- TEST (ejecución 25) ---
2025-11-03 17:26:23.857218: 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`.
2025-11-03 17:26:23.869255: 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 00:00:1762187183.883667  334436 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187183.887824  334436 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187183.898099  334436 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187183.898121  334436 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187183.898124  334436 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187183.898126  334436 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:26:23.901238: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37454	validation-mlogloss:1.37421
[1]	train-mlogloss:1.36294	validation-mlogloss:1.36212
[2]	train-mlogloss:1.35163	validation-mlogloss:1.35024
[3]	train-mlogloss:1.34067	validation-mlogloss:1.33872
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[5]	train-mlogloss:1.31930	validation-mlogloss:1.31682
[6]	train-mlogloss:1.30906	validation-mlogloss:1.30620
[7]	train-mlogloss:1.29874	validation-mlogloss:1.29515
[8]	train-mlogloss:1.28885	validation-mlogloss:1.28501
[9]	train-mlogloss:1.27895	validation-mlogloss:1.27491
[10]	train-mlogloss:1.26916	validation-mlogloss:1.26471
[11]	train-mlogloss:1.25944	validation-mlogloss:1.25468
[12]	train-mlogloss:1.25025	validation-mlogloss:1.24497
[13]	train-mlogloss:1.24118	validation-mlogloss:1.23574
[14]	train-mlogloss:1.23212	validation-mlogloss:1.22658
[15]	train-mlogloss:1.22322	validation-mlogloss:1.21740
[16]	train-mlogloss:1.21441	validation-mlogloss:1.20805
[17]	train-mlogloss:1.20589	validation-mlogloss:1.19919
[18]	train-mlogloss:1.19750	validation-mlogloss:1.19041
[19]	train-mlogloss:1.18914	validation-mlogloss:1.18159
[20]	train-mlogloss:1.18098	validation-mlogloss:1.17311
[21]	train-mlogloss:1.17305	validation-mlogloss:1.16471
[22]	train-mlogloss:1.16533	validation-mlogloss:1.15665
[23]	train-mlogloss:1.15768	validation-mlogloss:1.14878
[24]	train-mlogloss:1.14998	validation-mlogloss:1.14077
[25]	train-mlogloss:1.14236	validation-mlogloss:1.13302
[26]	train-mlogloss:1.13539	validation-mlogloss:1.12588
[27]	train-mlogloss:1.12811	validation-mlogloss:1.11808
[28]	train-mlogloss:1.12106	validation-mlogloss:1.11058
[29]	train-mlogloss:1.11424	validation-mlogloss:1.10372
[30]	train-mlogloss:1.10752	validation-mlogloss:1.09669
[31]	train-mlogloss:1.10095	validation-mlogloss:1.08979
[32]	train-mlogloss:1.09443	validation-mlogloss:1.08308
[33]	train-mlogloss:1.08789	validation-mlogloss:1.07610
[34]	train-mlogloss:1.08128	validation-mlogloss:1.06930
[35]	train-mlogloss:1.07505	validation-mlogloss:1.06303
[36]	train-mlogloss:1.06891	validation-mlogloss:1.05655
[37]	train-mlogloss:1.06279	validation-mlogloss:1.05016
[38]	train-mlogloss:1.05662	validation-mlogloss:1.04365
[39]	train-mlogloss:1.05077	validation-mlogloss:1.03777
[40]	train-mlogloss:1.04505	validation-mlogloss:1.03176
[41]	train-mlogloss:1.03929	validation-mlogloss:1.02564
[42]	train-mlogloss:1.03359	validation-mlogloss:1.01971
[43]	train-mlogloss:1.02805	validation-mlogloss:1.01396
[44]	train-mlogloss:1.02219	validation-mlogloss:1.00797
[45]	train-mlogloss:1.01668	validation-mlogloss:1.00207
[46]	train-mlogloss:1.01125	validation-mlogloss:0.99626
[47]	train-mlogloss:1.00603	validation-mlogloss:0.99076
[48]	train-mlogloss:1.00060	validation-mlogloss:0.98495
[49]	train-mlogloss:0.99545	validation-mlogloss:0.97977
[50]	train-mlogloss:0.99025	validation-mlogloss:0.97446
[51]	train-mlogloss:0.98500	validation-mlogloss:0.96910
[52]	train-mlogloss:0.97986	validation-mlogloss:0.96385
[53]	train-mlogloss:0.97491	validation-mlogloss:0.95869
[54]	train-mlogloss:0.97007	validation-mlogloss:0.95361
[55]	train-mlogloss:0.96525	validation-mlogloss:0.94867
[56]	train-mlogloss:0.96029	validation-mlogloss:0.94353
[57]	train-mlogloss:0.95564	validation-mlogloss:0.93864
[58]	train-mlogloss:0.95095	validation-mlogloss:0.93376
[59]	train-mlogloss:0.94620	validation-mlogloss:0.92878
[60]	train-mlogloss:0.94179	validation-mlogloss:0.92435
[61]	train-mlogloss:0.93726	validation-mlogloss:0.91970
[62]	train-mlogloss:0.93283	validation-mlogloss:0.91522
[63]	train-mlogloss:0.92839	validation-mlogloss:0.91071
[64]	train-mlogloss:0.92389	validation-mlogloss:0.90612
[65]	train-mlogloss:0.91970	validation-mlogloss:0.90163
[66]	train-mlogloss:0.91555	validation-mlogloss:0.89716
[67]	train-mlogloss:0.91141	validation-mlogloss:0.89289
[68]	train-mlogloss:0.90737	validation-mlogloss:0.88874
[69]	train-mlogloss:0.90324	validation-mlogloss:0.88438
[70]	train-mlogloss:0.89939	validation-mlogloss:0.88051
[71]	train-mlogloss:0.89545	validation-mlogloss:0.87628
[72]	train-mlogloss:0.89150	validation-mlogloss:0.87224
[73]	train-mlogloss:0.88774	validation-mlogloss:0.86838
[74]	train-mlogloss:0.88397	validation-mlogloss:0.86442
[75]	train-mlogloss:0.88034	validation-mlogloss:0.86059
[76]	train-mlogloss:0.87663	validation-mlogloss:0.85660
[77]	train-mlogloss:0.87270	validation-mlogloss:0.85270
[78]	train-mlogloss:0.86913	validation-mlogloss:0.84898
[79]	train-mlogloss:0.86567	validation-mlogloss:0.84555
[80]	train-mlogloss:0.86209	validation-mlogloss:0.84184
[81]	train-mlogloss:0.85852	validation-mlogloss:0.83827
[82]	train-mlogloss:0.85493	validation-mlogloss:0.83457
[83]	train-mlogloss:0.85166	validation-mlogloss:0.83132
[84]	train-mlogloss:0.84830	validation-mlogloss:0.82783
[85]	train-mlogloss:0.84508	validation-mlogloss:0.82438
[86]	train-mlogloss:0.84175	validation-mlogloss:0.82098
[87]	train-mlogloss:0.83853	validation-mlogloss:0.81787
[88]	train-mlogloss:0.83533	validation-mlogloss:0.81476
[89]	train-mlogloss:0.83215	validation-mlogloss:0.81138
[90]	train-mlogloss:0.82896	validation-mlogloss:0.80825
[91]	train-mlogloss:0.82603	validation-mlogloss:0.80536
[92]	train-mlogloss:0.82295	validation-mlogloss:0.80211
[93]	train-mlogloss:0.81999	validation-mlogloss:0.79903
[94]	train-mlogloss:0.81681	validation-mlogloss:0.79577
[95]	train-mlogloss:0.81395	validation-mlogloss:0.79282
[96]	train-mlogloss:0.81110	validation-mlogloss:0.78988
[97]	train-mlogloss:0.80828	validation-mlogloss:0.78691
[98]	train-mlogloss:0.80547	validation-mlogloss:0.78413
[99]	train-mlogloss:0.80269	validation-mlogloss:0.78127
[100]	train-mlogloss:0.79974	validation-mlogloss:0.77820
[101]	train-mlogloss:0.79698	validation-mlogloss:0.77527
[102]	train-mlogloss:0.79435	validation-mlogloss:0.77251
[103]	train-mlogloss:0.79173	validation-mlogloss:0.76980
[104]	train-mlogloss:0.78921	validation-mlogloss:0.76724
[105]	train-mlogloss:0.78667	validation-mlogloss:0.76461
[106]	train-mlogloss:0.78419	validation-mlogloss:0.76196
[107]	train-mlogloss:0.78168	validation-mlogloss:0.75934
[108]	train-mlogloss:0.77917	validation-mlogloss:0.75671
[109]	train-mlogloss:0.77661	validation-mlogloss:0.75426
[110]	train-mlogloss:0.77416	validation-mlogloss:0.75173
[111]	train-mlogloss:0.77169	validation-mlogloss:0.74903
[112]	train-mlogloss:0.76931	validation-mlogloss:0.74660
[113]	train-mlogloss:0.76690	validation-mlogloss:0.74408
[114]	train-mlogloss:0.76467	validation-mlogloss:0.74179
[115]	train-mlogloss:0.76237	validation-mlogloss:0.73928
[116]	train-mlogloss:0.76002	validation-mlogloss:0.73685
[117]	train-mlogloss:0.75789	validation-mlogloss:0.73459
[118]	train-mlogloss:0.75572	validation-mlogloss:0.73235
[119]	train-mlogloss:0.75336	validation-mlogloss:0.72994
[120]	train-mlogloss:0.75099	validation-mlogloss:0.72759
[121]	train-mlogloss:0.74862	validation-mlogloss:0.72517
[122]	train-mlogloss:0.74649	validation-mlogloss:0.72292
[123]	train-mlogloss:0.74424	validation-mlogloss:0.72036
[124]	train-mlogloss:0.74197	validation-mlogloss:0.71808
[125]	train-mlogloss:0.73973	validation-mlogloss:0.71581
[126]	train-mlogloss:0.73777	validation-mlogloss:0.71372
[127]	train-mlogloss:0.73576	validation-mlogloss:0.71160
[128]	train-mlogloss:0.73355	validation-mlogloss:0.70946
[129]	train-mlogloss:0.73156	validation-mlogloss:0.70742
[130]	train-mlogloss:0.72941	validation-mlogloss:0.70524
[131]	train-mlogloss:0.72750	validation-mlogloss:0.70335
[132]	train-mlogloss:0.72544	validation-mlogloss:0.70120
[133]	train-mlogloss:0.72346	validation-mlogloss:0.69924
[134]	train-mlogloss:0.72170	validation-mlogloss:0.69742
[135]	train-mlogloss:0.71972	validation-mlogloss:0.69547
[136]	train-mlogloss:0.71763	validation-mlogloss:0.69347
[137]	train-mlogloss:0.71586	validation-mlogloss:0.69174
[138]	train-mlogloss:0.71394	validation-mlogloss:0.68988
[139]	train-mlogloss:0.71198	validation-mlogloss:0.68796
[140]	train-mlogloss:0.71027	validation-mlogloss:0.68628
[141]	train-mlogloss:0.70837	validation-mlogloss:0.68446
[142]	train-mlogloss:0.70665	validation-mlogloss:0.68266
[143]	train-mlogloss:0.70494	validation-mlogloss:0.68094
[144]	train-mlogloss:0.70315	validation-mlogloss:0.67914
[145]	train-mlogloss:0.70129	validation-mlogloss:0.67736
[146]	train-mlogloss:0.69952	validation-mlogloss:0.67559
[147]	train-mlogloss:0.69773	validation-mlogloss:0.67383
[148]	train-mlogloss:0.69613	validation-mlogloss:0.67221
[149]	train-mlogloss:0.69457	validation-mlogloss:0.67058
[150]	train-mlogloss:0.69297	validation-mlogloss:0.66900
[151]	train-mlogloss:0.69129	validation-mlogloss:0.66728
[152]	train-mlogloss:0.68975	validation-mlogloss:0.66577
[153]	train-mlogloss:0.68811	validation-mlogloss:0.66414
[154]	train-mlogloss:0.68644	validation-mlogloss:0.66250
[155]	train-mlogloss:0.68501	validation-mlogloss:0.66097
[156]	train-mlogloss:0.68356	validation-mlogloss:0.65951
[157]	train-mlogloss:0.68201	validation-mlogloss:0.65793
[158]	train-mlogloss:0.68034	validation-mlogloss:0.65632
[159]	train-mlogloss:0.67873	validation-mlogloss:0.65479
[160]	train-mlogloss:0.67721	validation-mlogloss:0.65327
[161]	train-mlogloss:0.67566	validation-mlogloss:0.65182
[162]	train-mlogloss:0.67425	validation-mlogloss:0.65050
[163]	train-mlogloss:0.67285	validation-mlogloss:0.64915
[164]	train-mlogloss:0.67137	validation-mlogloss:0.64775
[165]	train-mlogloss:0.66989	validation-mlogloss:0.64631
[166]	train-mlogloss:0.66843	validation-mlogloss:0.64479
[167]	train-mlogloss:0.66710	validation-mlogloss:0.64350
[168]	train-mlogloss:0.66574	validation-mlogloss:0.64212
[169]	train-mlogloss:0.66429	validation-mlogloss:0.64058
[170]	train-mlogloss:0.66283	validation-mlogloss:0.63932
[171]	train-mlogloss:0.66146	validation-mlogloss:0.63803
[172]	train-mlogloss:0.66014	validation-mlogloss:0.63670
[173]	train-mlogloss:0.65881	validation-mlogloss:0.63540
[174]	train-mlogloss:0.65740	validation-mlogloss:0.63415
[175]	train-mlogloss:0.65597	validation-mlogloss:0.63283
[176]	train-mlogloss:0.65467	validation-mlogloss:0.63163
[177]	train-mlogloss:0.65343	validation-mlogloss:0.63038
[178]	train-mlogloss:0.65214	validation-mlogloss:0.62917
[179]	train-mlogloss:0.65087	validation-mlogloss:0.62799
[180]	train-mlogloss:0.64964	validation-mlogloss:0.62675
[181]	train-mlogloss:0.64842	validation-mlogloss:0.62552
[182]	train-mlogloss:0.64716	validation-mlogloss:0.62428
[183]	train-mlogloss:0.64591	validation-mlogloss:0.62305
[184]	train-mlogloss:0.64476	validation-mlogloss:0.62198
[185]	train-mlogloss:0.64364	validation-mlogloss:0.62090
[186]	train-mlogloss:0.64244	validation-mlogloss:0.61976
[187]	train-mlogloss:0.64137	validation-mlogloss:0.61856
[188]	train-mlogloss:0.64019	validation-mlogloss:0.61729
[189]	train-mlogloss:0.63915	validation-mlogloss:0.61618
[190]	train-mlogloss:0.63791	validation-mlogloss:0.61496
[191]	train-mlogloss:0.63678	validation-mlogloss:0.61379
[192]	train-mlogloss:0.63567	validation-mlogloss:0.61262
[193]	train-mlogloss:0.63446	validation-mlogloss:0.61153
[194]	train-mlogloss:0.63332	validation-mlogloss:0.61028
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[497]	train-mlogloss:0.50822	validation-mlogloss:0.49992
[498]	train-mlogloss:0.50815	validation-mlogloss:0.49988
[499]	train-mlogloss:0.50805	validation-mlogloss:0.49981
[500]	train-mlogloss:0.50791	validation-mlogloss:0.49965
[501]	train-mlogloss:0.50781	validation-mlogloss:0.49960
[502]	train-mlogloss:0.50769	validation-mlogloss:0.49957
[503]	train-mlogloss:0.50761	validation-mlogloss:0.49957
[504]	train-mlogloss:0.50754	validation-mlogloss:0.49947
[505]	train-mlogloss:0.50740	validation-mlogloss:0.49934
[506]	train-mlogloss:0.50730	validation-mlogloss:0.49929
[507]	train-mlogloss:0.50721	validation-mlogloss:0.49923
[508]	train-mlogloss:0.50714	validation-mlogloss:0.49922
[509]	train-mlogloss:0.50705	validation-mlogloss:0.49920
[510]	train-mlogloss:0.50698	validation-mlogloss:0.49915
[511]	train-mlogloss:0.50690	validation-mlogloss:0.49905
[512]	train-mlogloss:0.50675	validation-mlogloss:0.49898
[513]	train-mlogloss:0.50668	validation-mlogloss:0.49893
[514]	train-mlogloss:0.50657	validation-mlogloss:0.49882
[515]	train-mlogloss:0.50644	validation-mlogloss:0.49869
[516]	train-mlogloss:0.50636	validation-mlogloss:0.49858
[517]	train-mlogloss:0.50630	validation-mlogloss:0.49852
[518]	train-mlogloss:0.50626	validation-mlogloss:0.49847
[519]	train-mlogloss:0.50620	validation-mlogloss:0.49839
[520]	train-mlogloss:0.50614	validation-mlogloss:0.49838
[521]	train-mlogloss:0.50602	validation-mlogloss:0.49839
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.4 [%]
Global accuracy score (test) = 80.47 [%]
Global F1 score (train) = 79.8 [%]
Global F1 score (test) = 81.07 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.71      0.66       350
MODERATE-INTENSITY       0.67      0.64      0.66       350
         SEDENTARY       0.99      0.96      0.97       350
VIGOROUS-INTENSITY       0.98      0.92      0.95       322

          accuracy                           0.80      1372
         macro avg       0.82      0.81      0.81      1372
      weighted avg       0.81      0.80      0.81      1372


Accuracy capturado en la ejecución 25: 80.47 [%]
F1-score capturado en la ejecución 25: 81.07 [%]

=== EJECUCIÓN 26 ===

--- TRAIN (ejecución 26) ---

--- TEST (ejecución 26) ---
2025-11-03 17:26:39.651764: 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`.
2025-11-03 17:26:39.663125: 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 00:00:1762187199.676547  334711 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187199.680779  334711 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187199.690685  334711 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187199.690705  334711 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187199.690708  334711 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187199.690710  334711 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:26:39.693920: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37478	validation-mlogloss:1.37394
[1]	train-mlogloss:1.36320	validation-mlogloss:1.36180
[2]	train-mlogloss:1.35191	validation-mlogloss:1.34977
[3]	train-mlogloss:1.34077	validation-mlogloss:1.33786
[4]	train-mlogloss:1.32988	validation-mlogloss:1.32636
[5]	train-mlogloss:1.31923	validation-mlogloss:1.31490
[6]	train-mlogloss:1.30895	validation-mlogloss:1.30378
[7]	train-mlogloss:1.29843	validation-mlogloss:1.29264
[8]	train-mlogloss:1.28823	validation-mlogloss:1.28165
[9]	train-mlogloss:1.27805	validation-mlogloss:1.27127
[10]	train-mlogloss:1.26834	validation-mlogloss:1.26092
[11]	train-mlogloss:1.25879	validation-mlogloss:1.25073
[12]	train-mlogloss:1.24936	validation-mlogloss:1.24065
[13]	train-mlogloss:1.24040	validation-mlogloss:1.23106
[14]	train-mlogloss:1.23148	validation-mlogloss:1.22157
[15]	train-mlogloss:1.22289	validation-mlogloss:1.21254
[16]	train-mlogloss:1.21423	validation-mlogloss:1.20352
[17]	train-mlogloss:1.20572	validation-mlogloss:1.19452
[18]	train-mlogloss:1.19748	validation-mlogloss:1.18582
[19]	train-mlogloss:1.18943	validation-mlogloss:1.17773
[20]	train-mlogloss:1.18147	validation-mlogloss:1.16959
[21]	train-mlogloss:1.17355	validation-mlogloss:1.16128
[22]	train-mlogloss:1.16569	validation-mlogloss:1.15295
[23]	train-mlogloss:1.15815	validation-mlogloss:1.14525
[24]	train-mlogloss:1.15060	validation-mlogloss:1.13716
[25]	train-mlogloss:1.14326	validation-mlogloss:1.12926
[26]	train-mlogloss:1.13605	validation-mlogloss:1.12171
[27]	train-mlogloss:1.12864	validation-mlogloss:1.11413
[28]	train-mlogloss:1.12172	validation-mlogloss:1.10703
[29]	train-mlogloss:1.11501	validation-mlogloss:1.10015
[30]	train-mlogloss:1.10815	validation-mlogloss:1.09298
[31]	train-mlogloss:1.10138	validation-mlogloss:1.08588
[32]	train-mlogloss:1.09481	validation-mlogloss:1.07887
[33]	train-mlogloss:1.08832	validation-mlogloss:1.07203
[34]	train-mlogloss:1.08191	validation-mlogloss:1.06537
[35]	train-mlogloss:1.07541	validation-mlogloss:1.05850
[36]	train-mlogloss:1.06914	validation-mlogloss:1.05193
[37]	train-mlogloss:1.06309	validation-mlogloss:1.04557
[38]	train-mlogloss:1.05703	validation-mlogloss:1.03925
[39]	train-mlogloss:1.05093	validation-mlogloss:1.03289
[40]	train-mlogloss:1.04493	validation-mlogloss:1.02661
[41]	train-mlogloss:1.03911	validation-mlogloss:1.02051
[42]	train-mlogloss:1.03330	validation-mlogloss:1.01436
[43]	train-mlogloss:1.02753	validation-mlogloss:1.00856
[44]	train-mlogloss:1.02215	validation-mlogloss:1.00304
[45]	train-mlogloss:1.01671	validation-mlogloss:0.99734
[46]	train-mlogloss:1.01138	validation-mlogloss:0.99158
[47]	train-mlogloss:1.00583	validation-mlogloss:0.98592
[48]	train-mlogloss:1.00044	validation-mlogloss:0.98066
[49]	train-mlogloss:0.99519	validation-mlogloss:0.97519
[50]	train-mlogloss:0.98984	validation-mlogloss:0.96964
[51]	train-mlogloss:0.98461	validation-mlogloss:0.96432
[52]	train-mlogloss:0.97954	validation-mlogloss:0.95899
[53]	train-mlogloss:0.97453	validation-mlogloss:0.95399
[54]	train-mlogloss:0.96964	validation-mlogloss:0.94895
[55]	train-mlogloss:0.96478	validation-mlogloss:0.94392
[56]	train-mlogloss:0.96021	validation-mlogloss:0.93915
[57]	train-mlogloss:0.95553	validation-mlogloss:0.93427
[58]	train-mlogloss:0.95090	validation-mlogloss:0.92970
[59]	train-mlogloss:0.94632	validation-mlogloss:0.92500
[60]	train-mlogloss:0.94184	validation-mlogloss:0.92030
[61]	train-mlogloss:0.93737	validation-mlogloss:0.91561
[62]	train-mlogloss:0.93282	validation-mlogloss:0.91090
[63]	train-mlogloss:0.92854	validation-mlogloss:0.90643
[64]	train-mlogloss:0.92432	validation-mlogloss:0.90213
[65]	train-mlogloss:0.91999	validation-mlogloss:0.89772
[66]	train-mlogloss:0.91564	validation-mlogloss:0.89334
[67]	train-mlogloss:0.91140	validation-mlogloss:0.88898
[68]	train-mlogloss:0.90740	validation-mlogloss:0.88486
[69]	train-mlogloss:0.90348	validation-mlogloss:0.88078
[70]	train-mlogloss:0.89939	validation-mlogloss:0.87669
[71]	train-mlogloss:0.89546	validation-mlogloss:0.87251
[72]	train-mlogloss:0.89159	validation-mlogloss:0.86847
[73]	train-mlogloss:0.88784	validation-mlogloss:0.86440
[74]	train-mlogloss:0.88413	validation-mlogloss:0.86069
[75]	train-mlogloss:0.88037	validation-mlogloss:0.85689
[76]	train-mlogloss:0.87676	validation-mlogloss:0.85320
[77]	train-mlogloss:0.87295	validation-mlogloss:0.84920
[78]	train-mlogloss:0.86945	validation-mlogloss:0.84555
[79]	train-mlogloss:0.86586	validation-mlogloss:0.84196
[80]	train-mlogloss:0.86236	validation-mlogloss:0.83828
[81]	train-mlogloss:0.85906	validation-mlogloss:0.83494
[82]	train-mlogloss:0.85561	validation-mlogloss:0.83136
[83]	train-mlogloss:0.85220	validation-mlogloss:0.82797
[84]	train-mlogloss:0.84887	validation-mlogloss:0.82450
[85]	train-mlogloss:0.84559	validation-mlogloss:0.82105
[86]	train-mlogloss:0.84252	validation-mlogloss:0.81800
[87]	train-mlogloss:0.83934	validation-mlogloss:0.81463
[88]	train-mlogloss:0.83615	validation-mlogloss:0.81122
[89]	train-mlogloss:0.83313	validation-mlogloss:0.80805
[90]	train-mlogloss:0.83001	validation-mlogloss:0.80479
[91]	train-mlogloss:0.82702	validation-mlogloss:0.80170
[92]	train-mlogloss:0.82401	validation-mlogloss:0.79839
[93]	train-mlogloss:0.82094	validation-mlogloss:0.79515
[94]	train-mlogloss:0.81787	validation-mlogloss:0.79209
[95]	train-mlogloss:0.81500	validation-mlogloss:0.78909
[96]	train-mlogloss:0.81222	validation-mlogloss:0.78607
[97]	train-mlogloss:0.80932	validation-mlogloss:0.78289
[98]	train-mlogloss:0.80660	validation-mlogloss:0.78014
[99]	train-mlogloss:0.80381	validation-mlogloss:0.77726
[100]	train-mlogloss:0.80105	validation-mlogloss:0.77435
[101]	train-mlogloss:0.79828	validation-mlogloss:0.77139
[102]	train-mlogloss:0.79550	validation-mlogloss:0.76854
[103]	train-mlogloss:0.79292	validation-mlogloss:0.76583
[104]	train-mlogloss:0.79042	validation-mlogloss:0.76325
[105]	train-mlogloss:0.78786	validation-mlogloss:0.76051
[106]	train-mlogloss:0.78516	validation-mlogloss:0.75783
[107]	train-mlogloss:0.78255	validation-mlogloss:0.75503
[108]	train-mlogloss:0.77989	validation-mlogloss:0.75220
[109]	train-mlogloss:0.77735	validation-mlogloss:0.74959
[110]	train-mlogloss:0.77495	validation-mlogloss:0.74708
[111]	train-mlogloss:0.77261	validation-mlogloss:0.74467
[112]	train-mlogloss:0.77012	validation-mlogloss:0.74221
[113]	train-mlogloss:0.76763	validation-mlogloss:0.73964
[114]	train-mlogloss:0.76533	validation-mlogloss:0.73715
[115]	train-mlogloss:0.76285	validation-mlogloss:0.73462
[116]	train-mlogloss:0.76025	validation-mlogloss:0.73197
[117]	train-mlogloss:0.75771	validation-mlogloss:0.72943
[118]	train-mlogloss:0.75524	validation-mlogloss:0.72690
[119]	train-mlogloss:0.75280	validation-mlogloss:0.72445
[120]	train-mlogloss:0.75059	validation-mlogloss:0.72205
[121]	train-mlogloss:0.74859	validation-mlogloss:0.71999
[122]	train-mlogloss:0.74634	validation-mlogloss:0.71768
[123]	train-mlogloss:0.74405	validation-mlogloss:0.71527
[124]	train-mlogloss:0.74172	validation-mlogloss:0.71297
[125]	train-mlogloss:0.73938	validation-mlogloss:0.71068
[126]	train-mlogloss:0.73731	validation-mlogloss:0.70849
[127]	train-mlogloss:0.73532	validation-mlogloss:0.70645
[128]	train-mlogloss:0.73347	validation-mlogloss:0.70446
[129]	train-mlogloss:0.73132	validation-mlogloss:0.70225
[130]	train-mlogloss:0.72924	validation-mlogloss:0.70015
[131]	train-mlogloss:0.72715	validation-mlogloss:0.69799
[132]	train-mlogloss:0.72507	validation-mlogloss:0.69597
[133]	train-mlogloss:0.72297	validation-mlogloss:0.69385
[134]	train-mlogloss:0.72089	validation-mlogloss:0.69169
[135]	train-mlogloss:0.71894	validation-mlogloss:0.68972
[136]	train-mlogloss:0.71706	validation-mlogloss:0.68778
[137]	train-mlogloss:0.71537	validation-mlogloss:0.68603
[138]	train-mlogloss:0.71365	validation-mlogloss:0.68424
[139]	train-mlogloss:0.71173	validation-mlogloss:0.68233
[140]	train-mlogloss:0.70985	validation-mlogloss:0.68036
[141]	train-mlogloss:0.70808	validation-mlogloss:0.67843
[142]	train-mlogloss:0.70640	validation-mlogloss:0.67667
[143]	train-mlogloss:0.70468	validation-mlogloss:0.67488
[144]	train-mlogloss:0.70281	validation-mlogloss:0.67302
[145]	train-mlogloss:0.70109	validation-mlogloss:0.67126
[146]	train-mlogloss:0.69925	validation-mlogloss:0.66942
[147]	train-mlogloss:0.69743	validation-mlogloss:0.66766
[148]	train-mlogloss:0.69566	validation-mlogloss:0.66595
[149]	train-mlogloss:0.69392	validation-mlogloss:0.66404
[150]	train-mlogloss:0.69217	validation-mlogloss:0.66220
[151]	train-mlogloss:0.69045	validation-mlogloss:0.66047
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[454]	train-mlogloss:0.51506	validation-mlogloss:0.49263
[455]	train-mlogloss:0.51490	validation-mlogloss:0.49249
[456]	train-mlogloss:0.51479	validation-mlogloss:0.49238
[457]	train-mlogloss:0.51464	validation-mlogloss:0.49226
[458]	train-mlogloss:0.51445	validation-mlogloss:0.49207
[459]	train-mlogloss:0.51429	validation-mlogloss:0.49194
[460]	train-mlogloss:0.51412	validation-mlogloss:0.49177
[461]	train-mlogloss:0.51399	validation-mlogloss:0.49166
[462]	train-mlogloss:0.51386	validation-mlogloss:0.49150
[463]	train-mlogloss:0.51370	validation-mlogloss:0.49135
[464]	train-mlogloss:0.51358	validation-mlogloss:0.49123
[465]	train-mlogloss:0.51341	validation-mlogloss:0.49107
[466]	train-mlogloss:0.51324	validation-mlogloss:0.49086
[467]	train-mlogloss:0.51307	validation-mlogloss:0.49075
[468]	train-mlogloss:0.51289	validation-mlogloss:0.49062
[469]	train-mlogloss:0.51273	validation-mlogloss:0.49048
[470]	train-mlogloss:0.51260	validation-mlogloss:0.49034
[471]	train-mlogloss:0.51248	validation-mlogloss:0.49028
[472]	train-mlogloss:0.51238	validation-mlogloss:0.49015
[473]	train-mlogloss:0.51224	validation-mlogloss:0.49007
[474]	train-mlogloss:0.51212	validation-mlogloss:0.48994
[475]	train-mlogloss:0.51195	validation-mlogloss:0.48979
[476]	train-mlogloss:0.51172	validation-mlogloss:0.48962
[477]	train-mlogloss:0.51161	validation-mlogloss:0.48949
[478]	train-mlogloss:0.51150	validation-mlogloss:0.48938
[479]	train-mlogloss:0.51139	validation-mlogloss:0.48927
[480]	train-mlogloss:0.51124	validation-mlogloss:0.48917
[481]	train-mlogloss:0.51113	validation-mlogloss:0.48911
[482]	train-mlogloss:0.51101	validation-mlogloss:0.48898
[483]	train-mlogloss:0.51083	validation-mlogloss:0.48882
[484]	train-mlogloss:0.51064	validation-mlogloss:0.48861
[485]	train-mlogloss:0.51054	validation-mlogloss:0.48850
[486]	train-mlogloss:0.51038	validation-mlogloss:0.48837
[487]	train-mlogloss:0.51029	validation-mlogloss:0.48828
[488]	train-mlogloss:0.51015	validation-mlogloss:0.48817
[489]	train-mlogloss:0.51002	validation-mlogloss:0.48802
[490]	train-mlogloss:0.50984	validation-mlogloss:0.48781
[491]	train-mlogloss:0.50970	validation-mlogloss:0.48771
[492]	train-mlogloss:0.50958	validation-mlogloss:0.48760
[493]	train-mlogloss:0.50938	validation-mlogloss:0.48745
[494]	train-mlogloss:0.50930	validation-mlogloss:0.48739
[495]	train-mlogloss:0.50922	validation-mlogloss:0.48735
[496]	train-mlogloss:0.50906	validation-mlogloss:0.48718
[497]	train-mlogloss:0.50899	validation-mlogloss:0.48711
[498]	train-mlogloss:0.50889	validation-mlogloss:0.48700
[499]	train-mlogloss:0.50878	validation-mlogloss:0.48693
[500]	train-mlogloss:0.50862	validation-mlogloss:0.48674
[501]	train-mlogloss:0.50853	validation-mlogloss:0.48664
[502]	train-mlogloss:0.50844	validation-mlogloss:0.48666
[503]	train-mlogloss:0.50836	validation-mlogloss:0.48659
[504]	train-mlogloss:0.50822	validation-mlogloss:0.48649
[505]	train-mlogloss:0.50811	validation-mlogloss:0.48640
[506]	train-mlogloss:0.50804	validation-mlogloss:0.48633
[507]	train-mlogloss:0.50800	validation-mlogloss:0.48629
[508]	train-mlogloss:0.50790	validation-mlogloss:0.48627
[509]	train-mlogloss:0.50782	validation-mlogloss:0.48623
[510]	train-mlogloss:0.50765	validation-mlogloss:0.48605
[511]	train-mlogloss:0.50757	validation-mlogloss:0.48602
[512]	train-mlogloss:0.50747	validation-mlogloss:0.48590
[513]	train-mlogloss:0.50738	validation-mlogloss:0.48587
[514]	train-mlogloss:0.50730	validation-mlogloss:0.48578
[515]	train-mlogloss:0.50720	validation-mlogloss:0.48568
[516]	train-mlogloss:0.50703	validation-mlogloss:0.48553
[517]	train-mlogloss:0.50692	validation-mlogloss:0.48542
[518]	train-mlogloss:0.50681	validation-mlogloss:0.48528
[519]	train-mlogloss:0.50672	validation-mlogloss:0.48522
[520]	train-mlogloss:0.50660	validation-mlogloss:0.48513
[521]	train-mlogloss:0.50650	validation-mlogloss:0.48503
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[1 1 0 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.64 [%]
Global accuracy score (test) = 81.41 [%]
Global F1 score (train) = 79.93 [%]
Global F1 score (test) = 81.92 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.65      0.72      0.68       350
MODERATE-INTENSITY       0.69      0.67      0.68       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.96      0.92      0.94       322

          accuracy                           0.81      1372
         macro avg       0.82      0.82      0.82      1372
      weighted avg       0.82      0.81      0.82      1372


Accuracy capturado en la ejecución 26: 81.41 [%]
F1-score capturado en la ejecución 26: 81.92 [%]

=== EJECUCIÓN 27 ===

--- TRAIN (ejecución 27) ---

--- TEST (ejecución 27) ---
2025-11-03 17:26:55.871309: 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`.
2025-11-03 17:26:55.882810: 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 00:00:1762187215.896139  334989 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187215.900471  334989 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187215.910525  334989 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187215.910546  334989 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187215.910549  334989 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187215.910550  334989 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:26:55.913821: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37425	validation-mlogloss:1.37350
[1]	train-mlogloss:1.36288	validation-mlogloss:1.36169
[2]	train-mlogloss:1.35161	validation-mlogloss:1.35020
[3]	train-mlogloss:1.34036	validation-mlogloss:1.33861
[4]	train-mlogloss:1.32917	validation-mlogloss:1.32730
[5]	train-mlogloss:1.31845	validation-mlogloss:1.31616
[6]	train-mlogloss:1.30795	validation-mlogloss:1.30539
[7]	train-mlogloss:1.29766	validation-mlogloss:1.29480
[8]	train-mlogloss:1.28729	validation-mlogloss:1.28405
[9]	train-mlogloss:1.27732	validation-mlogloss:1.27381
[10]	train-mlogloss:1.26778	validation-mlogloss:1.26422
[11]	train-mlogloss:1.25826	validation-mlogloss:1.25457
[12]	train-mlogloss:1.24884	validation-mlogloss:1.24475
[13]	train-mlogloss:1.23966	validation-mlogloss:1.23529
[14]	train-mlogloss:1.23049	validation-mlogloss:1.22586
[15]	train-mlogloss:1.22157	validation-mlogloss:1.21653
[16]	train-mlogloss:1.21269	validation-mlogloss:1.20731
[17]	train-mlogloss:1.20414	validation-mlogloss:1.19844
[18]	train-mlogloss:1.19569	validation-mlogloss:1.18965
[19]	train-mlogloss:1.18740	validation-mlogloss:1.18099
[20]	train-mlogloss:1.17922	validation-mlogloss:1.17236
[21]	train-mlogloss:1.17119	validation-mlogloss:1.16422
[22]	train-mlogloss:1.16327	validation-mlogloss:1.15620
[23]	train-mlogloss:1.15536	validation-mlogloss:1.14811
[24]	train-mlogloss:1.14786	validation-mlogloss:1.14070
[25]	train-mlogloss:1.14036	validation-mlogloss:1.13278
[26]	train-mlogloss:1.13303	validation-mlogloss:1.12515
[27]	train-mlogloss:1.12559	validation-mlogloss:1.11734
[28]	train-mlogloss:1.11858	validation-mlogloss:1.11012
[29]	train-mlogloss:1.11169	validation-mlogloss:1.10329
[30]	train-mlogloss:1.10464	validation-mlogloss:1.09613
[31]	train-mlogloss:1.09791	validation-mlogloss:1.08901
[32]	train-mlogloss:1.09104	validation-mlogloss:1.08199
[33]	train-mlogloss:1.08438	validation-mlogloss:1.07539
[34]	train-mlogloss:1.07780	validation-mlogloss:1.06855
[35]	train-mlogloss:1.07108	validation-mlogloss:1.06173
[36]	train-mlogloss:1.06490	validation-mlogloss:1.05549
[37]	train-mlogloss:1.05872	validation-mlogloss:1.04949
[38]	train-mlogloss:1.05252	validation-mlogloss:1.04314
[39]	train-mlogloss:1.04632	validation-mlogloss:1.03688
[40]	train-mlogloss:1.04035	validation-mlogloss:1.03058
[41]	train-mlogloss:1.03434	validation-mlogloss:1.02443
[42]	train-mlogloss:1.02858	validation-mlogloss:1.01853
[43]	train-mlogloss:1.02268	validation-mlogloss:1.01269
[44]	train-mlogloss:1.01709	validation-mlogloss:1.00712
[45]	train-mlogloss:1.01157	validation-mlogloss:1.00137
[46]	train-mlogloss:1.00577	validation-mlogloss:0.99567
[47]	train-mlogloss:1.00031	validation-mlogloss:0.99005
[48]	train-mlogloss:0.99516	validation-mlogloss:0.98467
[49]	train-mlogloss:0.98980	validation-mlogloss:0.97920
[50]	train-mlogloss:0.98441	validation-mlogloss:0.97387
[51]	train-mlogloss:0.97923	validation-mlogloss:0.96867
[52]	train-mlogloss:0.97427	validation-mlogloss:0.96342
[53]	train-mlogloss:0.96932	validation-mlogloss:0.95853
[54]	train-mlogloss:0.96430	validation-mlogloss:0.95352
[55]	train-mlogloss:0.95944	validation-mlogloss:0.94865
[56]	train-mlogloss:0.95452	validation-mlogloss:0.94382
[57]	train-mlogloss:0.94971	validation-mlogloss:0.93885
[58]	train-mlogloss:0.94515	validation-mlogloss:0.93442
[59]	train-mlogloss:0.94039	validation-mlogloss:0.92960
[60]	train-mlogloss:0.93583	validation-mlogloss:0.92500
[61]	train-mlogloss:0.93146	validation-mlogloss:0.92050
[62]	train-mlogloss:0.92711	validation-mlogloss:0.91613
[63]	train-mlogloss:0.92277	validation-mlogloss:0.91181
[64]	train-mlogloss:0.91843	validation-mlogloss:0.90751
[65]	train-mlogloss:0.91406	validation-mlogloss:0.90308
[66]	train-mlogloss:0.90983	validation-mlogloss:0.89892
[67]	train-mlogloss:0.90569	validation-mlogloss:0.89471
[68]	train-mlogloss:0.90164	validation-mlogloss:0.89065
[69]	train-mlogloss:0.89767	validation-mlogloss:0.88663
[70]	train-mlogloss:0.89373	validation-mlogloss:0.88258
[71]	train-mlogloss:0.88975	validation-mlogloss:0.87862
[72]	train-mlogloss:0.88584	validation-mlogloss:0.87471
[73]	train-mlogloss:0.88206	validation-mlogloss:0.87097
[74]	train-mlogloss:0.87816	validation-mlogloss:0.86702
[75]	train-mlogloss:0.87451	validation-mlogloss:0.86326
[76]	train-mlogloss:0.87081	validation-mlogloss:0.85952
[77]	train-mlogloss:0.86727	validation-mlogloss:0.85612
[78]	train-mlogloss:0.86368	validation-mlogloss:0.85245
[79]	train-mlogloss:0.85991	validation-mlogloss:0.84883
[80]	train-mlogloss:0.85649	validation-mlogloss:0.84531
[81]	train-mlogloss:0.85311	validation-mlogloss:0.84181
[82]	train-mlogloss:0.84978	validation-mlogloss:0.83834
[83]	train-mlogloss:0.84643	validation-mlogloss:0.83500
[84]	train-mlogloss:0.84307	validation-mlogloss:0.83159
[85]	train-mlogloss:0.83981	validation-mlogloss:0.82822
[86]	train-mlogloss:0.83653	validation-mlogloss:0.82492
[87]	train-mlogloss:0.83317	validation-mlogloss:0.82160
[88]	train-mlogloss:0.82997	validation-mlogloss:0.81851
[89]	train-mlogloss:0.82674	validation-mlogloss:0.81528
[90]	train-mlogloss:0.82369	validation-mlogloss:0.81211
[91]	train-mlogloss:0.82059	validation-mlogloss:0.80910
[92]	train-mlogloss:0.81757	validation-mlogloss:0.80599
[93]	train-mlogloss:0.81450	validation-mlogloss:0.80295
[94]	train-mlogloss:0.81156	validation-mlogloss:0.80006
[95]	train-mlogloss:0.80874	validation-mlogloss:0.79724
[96]	train-mlogloss:0.80582	validation-mlogloss:0.79427
[97]	train-mlogloss:0.80296	validation-mlogloss:0.79146
[98]	train-mlogloss:0.80008	validation-mlogloss:0.78853
[99]	train-mlogloss:0.79727	validation-mlogloss:0.78580
[100]	train-mlogloss:0.79425	validation-mlogloss:0.78280
[101]	train-mlogloss:0.79146	validation-mlogloss:0.78009
[102]	train-mlogloss:0.78876	validation-mlogloss:0.77742
[103]	train-mlogloss:0.78612	validation-mlogloss:0.77465
[104]	train-mlogloss:0.78338	validation-mlogloss:0.77197
[105]	train-mlogloss:0.78071	validation-mlogloss:0.76915
[106]	train-mlogloss:0.77810	validation-mlogloss:0.76646
[107]	train-mlogloss:0.77561	validation-mlogloss:0.76387
[108]	train-mlogloss:0.77302	validation-mlogloss:0.76113
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[411]	train-mlogloss:0.51733	validation-mlogloss:0.51878
[412]	train-mlogloss:0.51718	validation-mlogloss:0.51868
[413]	train-mlogloss:0.51695	validation-mlogloss:0.51851
[414]	train-mlogloss:0.51680	validation-mlogloss:0.51842
[415]	train-mlogloss:0.51670	validation-mlogloss:0.51837
[416]	train-mlogloss:0.51647	validation-mlogloss:0.51810
[417]	train-mlogloss:0.51632	validation-mlogloss:0.51802
[418]	train-mlogloss:0.51611	validation-mlogloss:0.51782
[419]	train-mlogloss:0.51594	validation-mlogloss:0.51765
[420]	train-mlogloss:0.51572	validation-mlogloss:0.51736
[421]	train-mlogloss:0.51556	validation-mlogloss:0.51723
[422]	train-mlogloss:0.51535	validation-mlogloss:0.51702
[423]	train-mlogloss:0.51514	validation-mlogloss:0.51685
[424]	train-mlogloss:0.51484	validation-mlogloss:0.51657
[425]	train-mlogloss:0.51468	validation-mlogloss:0.51647
[426]	train-mlogloss:0.51445	validation-mlogloss:0.51629
[427]	train-mlogloss:0.51424	validation-mlogloss:0.51605
[428]	train-mlogloss:0.51402	validation-mlogloss:0.51577
[429]	train-mlogloss:0.51385	validation-mlogloss:0.51568
[430]	train-mlogloss:0.51367	validation-mlogloss:0.51555
[431]	train-mlogloss:0.51349	validation-mlogloss:0.51533
[432]	train-mlogloss:0.51333	validation-mlogloss:0.51521
[433]	train-mlogloss:0.51313	validation-mlogloss:0.51511
[434]	train-mlogloss:0.51299	validation-mlogloss:0.51504
[435]	train-mlogloss:0.51288	validation-mlogloss:0.51497
[436]	train-mlogloss:0.51270	validation-mlogloss:0.51488
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[438]	train-mlogloss:0.51231	validation-mlogloss:0.51460
[439]	train-mlogloss:0.51220	validation-mlogloss:0.51448
[440]	train-mlogloss:0.51198	validation-mlogloss:0.51425
[441]	train-mlogloss:0.51179	validation-mlogloss:0.51399
[442]	train-mlogloss:0.51166	validation-mlogloss:0.51393
[443]	train-mlogloss:0.51155	validation-mlogloss:0.51384
[444]	train-mlogloss:0.51134	validation-mlogloss:0.51363
[445]	train-mlogloss:0.51124	validation-mlogloss:0.51349
[446]	train-mlogloss:0.51112	validation-mlogloss:0.51344
[447]	train-mlogloss:0.51099	validation-mlogloss:0.51329
[448]	train-mlogloss:0.51076	validation-mlogloss:0.51311
[449]	train-mlogloss:0.51066	validation-mlogloss:0.51304
[450]	train-mlogloss:0.51056	validation-mlogloss:0.51294
[451]	train-mlogloss:0.51046	validation-mlogloss:0.51291
[452]	train-mlogloss:0.51029	validation-mlogloss:0.51269
[453]	train-mlogloss:0.51015	validation-mlogloss:0.51263
[454]	train-mlogloss:0.51003	validation-mlogloss:0.51249
[455]	train-mlogloss:0.50996	validation-mlogloss:0.51242
[456]	train-mlogloss:0.50985	validation-mlogloss:0.51230
[457]	train-mlogloss:0.50971	validation-mlogloss:0.51223
[458]	train-mlogloss:0.50963	validation-mlogloss:0.51217
[459]	train-mlogloss:0.50952	validation-mlogloss:0.51208
[460]	train-mlogloss:0.50937	validation-mlogloss:0.51197
[461]	train-mlogloss:0.50926	validation-mlogloss:0.51187
[462]	train-mlogloss:0.50914	validation-mlogloss:0.51174
[463]	train-mlogloss:0.50895	validation-mlogloss:0.51168
[464]	train-mlogloss:0.50885	validation-mlogloss:0.51165
[465]	train-mlogloss:0.50874	validation-mlogloss:0.51151
[466]	train-mlogloss:0.50854	validation-mlogloss:0.51131
[467]	train-mlogloss:0.50847	validation-mlogloss:0.51123
[468]	train-mlogloss:0.50835	validation-mlogloss:0.51114
[469]	train-mlogloss:0.50826	validation-mlogloss:0.51111
[470]	train-mlogloss:0.50815	validation-mlogloss:0.51097
[471]	train-mlogloss:0.50807	validation-mlogloss:0.51094
[472]	train-mlogloss:0.50802	validation-mlogloss:0.51089
[473]	train-mlogloss:0.50792	validation-mlogloss:0.51086
[474]	train-mlogloss:0.50773	validation-mlogloss:0.51077
[475]	train-mlogloss:0.50761	validation-mlogloss:0.51074
[476]	train-mlogloss:0.50750	validation-mlogloss:0.51067
[477]	train-mlogloss:0.50740	validation-mlogloss:0.51054
[478]	train-mlogloss:0.50731	validation-mlogloss:0.51040
[479]	train-mlogloss:0.50720	validation-mlogloss:0.51027
[480]	train-mlogloss:0.50705	validation-mlogloss:0.51015
[481]	train-mlogloss:0.50689	validation-mlogloss:0.50999
[482]	train-mlogloss:0.50675	validation-mlogloss:0.50984
[483]	train-mlogloss:0.50661	validation-mlogloss:0.50972
[484]	train-mlogloss:0.50646	validation-mlogloss:0.50955
[485]	train-mlogloss:0.50639	validation-mlogloss:0.50952
[486]	train-mlogloss:0.50627	validation-mlogloss:0.50938
[487]	train-mlogloss:0.50614	validation-mlogloss:0.50922
[488]	train-mlogloss:0.50606	validation-mlogloss:0.50920
[489]	train-mlogloss:0.50584	validation-mlogloss:0.50908
[490]	train-mlogloss:0.50568	validation-mlogloss:0.50889
[491]	train-mlogloss:0.50561	validation-mlogloss:0.50887
[492]	train-mlogloss:0.50547	validation-mlogloss:0.50875
[493]	train-mlogloss:0.50538	validation-mlogloss:0.50863
[494]	train-mlogloss:0.50530	validation-mlogloss:0.50859
[495]	train-mlogloss:0.50518	validation-mlogloss:0.50854
[496]	train-mlogloss:0.50509	validation-mlogloss:0.50843
[497]	train-mlogloss:0.50498	validation-mlogloss:0.50835
[498]	train-mlogloss:0.50483	validation-mlogloss:0.50829
[499]	train-mlogloss:0.50474	validation-mlogloss:0.50817
[500]	train-mlogloss:0.50470	validation-mlogloss:0.50814
[501]	train-mlogloss:0.50458	validation-mlogloss:0.50809
[502]	train-mlogloss:0.50451	validation-mlogloss:0.50801
[503]	train-mlogloss:0.50442	validation-mlogloss:0.50788
[504]	train-mlogloss:0.50433	validation-mlogloss:0.50782
[505]	train-mlogloss:0.50427	validation-mlogloss:0.50773
[506]	train-mlogloss:0.50416	validation-mlogloss:0.50767
[507]	train-mlogloss:0.50407	validation-mlogloss:0.50766
[508]	train-mlogloss:0.50393	validation-mlogloss:0.50752
[509]	train-mlogloss:0.50383	validation-mlogloss:0.50745
[510]	train-mlogloss:0.50365	validation-mlogloss:0.50722
[511]	train-mlogloss:0.50351	validation-mlogloss:0.50711
[512]	train-mlogloss:0.50332	validation-mlogloss:0.50698
[513]	train-mlogloss:0.50321	validation-mlogloss:0.50689
[514]	train-mlogloss:0.50313	validation-mlogloss:0.50683
[515]	train-mlogloss:0.50303	validation-mlogloss:0.50677
[516]	train-mlogloss:0.50295	validation-mlogloss:0.50674
[517]	train-mlogloss:0.50285	validation-mlogloss:0.50665
[518]	train-mlogloss:0.50270	validation-mlogloss:0.50649
[519]	train-mlogloss:0.50262	validation-mlogloss:0.50637
[520]	train-mlogloss:0.50252	validation-mlogloss:0.50629
[521]	train-mlogloss:0.50243	validation-mlogloss:0.50620
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 1 ... 1 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.02 [%]
Global accuracy score (test) = 80.98 [%]
Global F1 score (train) = 79.31 [%]
Global F1 score (test) = 81.55 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.64      0.69      0.67       350
MODERATE-INTENSITY       0.67      0.68      0.68       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.97      0.92      0.95       322

          accuracy                           0.81      1372
         macro avg       0.82      0.81      0.82      1372
      weighted avg       0.82      0.81      0.81      1372


Accuracy capturado en la ejecución 27: 80.98 [%]
F1-score capturado en la ejecución 27: 81.55 [%]

=== EJECUCIÓN 28 ===

--- TRAIN (ejecución 28) ---

--- TEST (ejecución 28) ---
2025-11-03 17:27:12.018852: 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`.
2025-11-03 17:27:12.030063: 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 00:00:1762187232.043365  335263 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187232.047673  335263 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187232.058085  335263 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187232.058106  335263 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187232.058108  335263 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187232.058110  335263 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:27:12.061127: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37460	validation-mlogloss:1.37435
[1]	train-mlogloss:1.36315	validation-mlogloss:1.36224
[2]	train-mlogloss:1.35206	validation-mlogloss:1.35066
[3]	train-mlogloss:1.34104	validation-mlogloss:1.33921
[4]	train-mlogloss:1.33036	validation-mlogloss:1.32813
[5]	train-mlogloss:1.31983	validation-mlogloss:1.31684
[6]	train-mlogloss:1.30944	validation-mlogloss:1.30594
[7]	train-mlogloss:1.29938	validation-mlogloss:1.29548
[8]	train-mlogloss:1.28945	validation-mlogloss:1.28491
[9]	train-mlogloss:1.27970	validation-mlogloss:1.27459
[10]	train-mlogloss:1.27026	validation-mlogloss:1.26491
[11]	train-mlogloss:1.26064	validation-mlogloss:1.25486
[12]	train-mlogloss:1.25154	validation-mlogloss:1.24511
[13]	train-mlogloss:1.24242	validation-mlogloss:1.23577
[14]	train-mlogloss:1.23366	validation-mlogloss:1.22678
[15]	train-mlogloss:1.22444	validation-mlogloss:1.21707
[16]	train-mlogloss:1.21592	validation-mlogloss:1.20825
[17]	train-mlogloss:1.20738	validation-mlogloss:1.19931
[18]	train-mlogloss:1.19917	validation-mlogloss:1.19061
[19]	train-mlogloss:1.19101	validation-mlogloss:1.18188
[20]	train-mlogloss:1.18313	validation-mlogloss:1.17358
[21]	train-mlogloss:1.17498	validation-mlogloss:1.16491
[22]	train-mlogloss:1.16708	validation-mlogloss:1.15650
[23]	train-mlogloss:1.15910	validation-mlogloss:1.14821
[24]	train-mlogloss:1.15162	validation-mlogloss:1.14043
[25]	train-mlogloss:1.14435	validation-mlogloss:1.13291
[26]	train-mlogloss:1.13711	validation-mlogloss:1.12552
[27]	train-mlogloss:1.12977	validation-mlogloss:1.11775
[28]	train-mlogloss:1.12263	validation-mlogloss:1.11022
[29]	train-mlogloss:1.11566	validation-mlogloss:1.10292
[30]	train-mlogloss:1.10889	validation-mlogloss:1.09586
[31]	train-mlogloss:1.10215	validation-mlogloss:1.08861
[32]	train-mlogloss:1.09560	validation-mlogloss:1.08185
[33]	train-mlogloss:1.08903	validation-mlogloss:1.07490
[34]	train-mlogloss:1.08253	validation-mlogloss:1.06806
[35]	train-mlogloss:1.07602	validation-mlogloss:1.06136
[36]	train-mlogloss:1.06999	validation-mlogloss:1.05519
[37]	train-mlogloss:1.06385	validation-mlogloss:1.04876
[38]	train-mlogloss:1.05762	validation-mlogloss:1.04223
[39]	train-mlogloss:1.05159	validation-mlogloss:1.03605
[40]	train-mlogloss:1.04567	validation-mlogloss:1.03018
[41]	train-mlogloss:1.03968	validation-mlogloss:1.02381
[42]	train-mlogloss:1.03417	validation-mlogloss:1.01822
[43]	train-mlogloss:1.02843	validation-mlogloss:1.01235
[44]	train-mlogloss:1.02297	validation-mlogloss:1.00663
[45]	train-mlogloss:1.01744	validation-mlogloss:1.00094
[46]	train-mlogloss:1.01214	validation-mlogloss:0.99566
[47]	train-mlogloss:1.00698	validation-mlogloss:0.99006
[48]	train-mlogloss:1.00154	validation-mlogloss:0.98431
[49]	train-mlogloss:0.99626	validation-mlogloss:0.97892
[50]	train-mlogloss:0.99102	validation-mlogloss:0.97327
[51]	train-mlogloss:0.98592	validation-mlogloss:0.96808
[52]	train-mlogloss:0.98081	validation-mlogloss:0.96300
[53]	train-mlogloss:0.97573	validation-mlogloss:0.95764
[54]	train-mlogloss:0.97093	validation-mlogloss:0.95253
[55]	train-mlogloss:0.96597	validation-mlogloss:0.94758
[56]	train-mlogloss:0.96126	validation-mlogloss:0.94261
[57]	train-mlogloss:0.95656	validation-mlogloss:0.93771
[58]	train-mlogloss:0.95185	validation-mlogloss:0.93292
[59]	train-mlogloss:0.94721	validation-mlogloss:0.92789
[60]	train-mlogloss:0.94259	validation-mlogloss:0.92302
[61]	train-mlogloss:0.93824	validation-mlogloss:0.91849
[62]	train-mlogloss:0.93387	validation-mlogloss:0.91391
[63]	train-mlogloss:0.92939	validation-mlogloss:0.90925
[64]	train-mlogloss:0.92520	validation-mlogloss:0.90514
[65]	train-mlogloss:0.92088	validation-mlogloss:0.90050
[66]	train-mlogloss:0.91672	validation-mlogloss:0.89611
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[400]	train-mlogloss:0.52720	validation-mlogloss:0.50165
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[408]	train-mlogloss:0.52543	validation-mlogloss:0.49999
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[420]	train-mlogloss:0.52295	validation-mlogloss:0.49787
[421]	train-mlogloss:0.52277	validation-mlogloss:0.49767
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[424]	train-mlogloss:0.52218	validation-mlogloss:0.49730
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[441]	train-mlogloss:0.51922	validation-mlogloss:0.49494
[442]	train-mlogloss:0.51905	validation-mlogloss:0.49481
[443]	train-mlogloss:0.51886	validation-mlogloss:0.49471
[444]	train-mlogloss:0.51871	validation-mlogloss:0.49459
[445]	train-mlogloss:0.51854	validation-mlogloss:0.49442
[446]	train-mlogloss:0.51845	validation-mlogloss:0.49432
[447]	train-mlogloss:0.51831	validation-mlogloss:0.49412
[448]	train-mlogloss:0.51819	validation-mlogloss:0.49402
[449]	train-mlogloss:0.51800	validation-mlogloss:0.49385
[450]	train-mlogloss:0.51784	validation-mlogloss:0.49369
[451]	train-mlogloss:0.51772	validation-mlogloss:0.49354
[452]	train-mlogloss:0.51765	validation-mlogloss:0.49350
[453]	train-mlogloss:0.51748	validation-mlogloss:0.49332
[454]	train-mlogloss:0.51730	validation-mlogloss:0.49312
[455]	train-mlogloss:0.51716	validation-mlogloss:0.49299
[456]	train-mlogloss:0.51705	validation-mlogloss:0.49294
[457]	train-mlogloss:0.51690	validation-mlogloss:0.49277
[458]	train-mlogloss:0.51668	validation-mlogloss:0.49250
[459]	train-mlogloss:0.51654	validation-mlogloss:0.49243
[460]	train-mlogloss:0.51639	validation-mlogloss:0.49230
[461]	train-mlogloss:0.51629	validation-mlogloss:0.49220
[462]	train-mlogloss:0.51618	validation-mlogloss:0.49201
[463]	train-mlogloss:0.51609	validation-mlogloss:0.49192
[464]	train-mlogloss:0.51591	validation-mlogloss:0.49181
[465]	train-mlogloss:0.51573	validation-mlogloss:0.49169
[466]	train-mlogloss:0.51560	validation-mlogloss:0.49157
[467]	train-mlogloss:0.51554	validation-mlogloss:0.49153
[468]	train-mlogloss:0.51539	validation-mlogloss:0.49139
[469]	train-mlogloss:0.51523	validation-mlogloss:0.49127
[470]	train-mlogloss:0.51505	validation-mlogloss:0.49113
[471]	train-mlogloss:0.51495	validation-mlogloss:0.49109
[472]	train-mlogloss:0.51475	validation-mlogloss:0.49090
[473]	train-mlogloss:0.51463	validation-mlogloss:0.49079
[474]	train-mlogloss:0.51455	validation-mlogloss:0.49077
[475]	train-mlogloss:0.51441	validation-mlogloss:0.49068
[476]	train-mlogloss:0.51430	validation-mlogloss:0.49051
[477]	train-mlogloss:0.51417	validation-mlogloss:0.49039
[478]	train-mlogloss:0.51397	validation-mlogloss:0.49021
[479]	train-mlogloss:0.51384	validation-mlogloss:0.49013
[480]	train-mlogloss:0.51371	validation-mlogloss:0.49004
[481]	train-mlogloss:0.51357	validation-mlogloss:0.48989
[482]	train-mlogloss:0.51347	validation-mlogloss:0.48980
[483]	train-mlogloss:0.51336	validation-mlogloss:0.48965
[484]	train-mlogloss:0.51320	validation-mlogloss:0.48945
[485]	train-mlogloss:0.51311	validation-mlogloss:0.48937
[486]	train-mlogloss:0.51300	validation-mlogloss:0.48931
[487]	train-mlogloss:0.51285	validation-mlogloss:0.48924
[488]	train-mlogloss:0.51275	validation-mlogloss:0.48915
[489]	train-mlogloss:0.51267	validation-mlogloss:0.48903
[490]	train-mlogloss:0.51254	validation-mlogloss:0.48889
[491]	train-mlogloss:0.51236	validation-mlogloss:0.48869
[492]	train-mlogloss:0.51228	validation-mlogloss:0.48863
[493]	train-mlogloss:0.51215	validation-mlogloss:0.48847
[494]	train-mlogloss:0.51205	validation-mlogloss:0.48836
[495]	train-mlogloss:0.51190	validation-mlogloss:0.48820
[496]	train-mlogloss:0.51183	validation-mlogloss:0.48811
[497]	train-mlogloss:0.51170	validation-mlogloss:0.48792
[498]	train-mlogloss:0.51161	validation-mlogloss:0.48781
[499]	train-mlogloss:0.51149	validation-mlogloss:0.48766
[500]	train-mlogloss:0.51136	validation-mlogloss:0.48751
[501]	train-mlogloss:0.51127	validation-mlogloss:0.48743
[502]	train-mlogloss:0.51118	validation-mlogloss:0.48738
[503]	train-mlogloss:0.51108	validation-mlogloss:0.48726
[504]	train-mlogloss:0.51102	validation-mlogloss:0.48721
[505]	train-mlogloss:0.51088	validation-mlogloss:0.48713
[506]	train-mlogloss:0.51079	validation-mlogloss:0.48710
[507]	train-mlogloss:0.51073	validation-mlogloss:0.48705
[508]	train-mlogloss:0.51066	validation-mlogloss:0.48697
[509]	train-mlogloss:0.51051	validation-mlogloss:0.48686
[510]	train-mlogloss:0.51045	validation-mlogloss:0.48685
[511]	train-mlogloss:0.51035	validation-mlogloss:0.48678
[512]	train-mlogloss:0.51027	validation-mlogloss:0.48676
[513]	train-mlogloss:0.51016	validation-mlogloss:0.48673
[514]	train-mlogloss:0.51008	validation-mlogloss:0.48666
[515]	train-mlogloss:0.50999	validation-mlogloss:0.48658
[516]	train-mlogloss:0.50990	validation-mlogloss:0.48652
[517]	train-mlogloss:0.50980	validation-mlogloss:0.48639
[518]	train-mlogloss:0.50973	validation-mlogloss:0.48635
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[520]	train-mlogloss:0.50957	validation-mlogloss:0.48616
[521]	train-mlogloss:0.50947	validation-mlogloss:0.48609
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 1 0 1]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 78.46 [%]
Global accuracy score (test) = 80.25 [%]
Global F1 score (train) = 78.78 [%]
Global F1 score (test) = 80.82 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.69      0.66       350
MODERATE-INTENSITY       0.66      0.64      0.65       350
         SEDENTARY       0.99      0.97      0.98       350
VIGOROUS-INTENSITY       0.98      0.92      0.95       322

          accuracy                           0.80      1372
         macro avg       0.81      0.80      0.81      1372
      weighted avg       0.81      0.80      0.81      1372


Accuracy capturado en la ejecución 28: 80.25 [%]
F1-score capturado en la ejecución 28: 80.82 [%]

=== EJECUCIÓN 29 ===

--- TRAIN (ejecución 29) ---

--- TEST (ejecución 29) ---
2025-11-03 17:27:28.329244: 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`.
2025-11-03 17:27:28.340745: 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 00:00:1762187248.354455  335540 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762187248.358733  335540 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762187248.369067  335540 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187248.369093  335540 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187248.369095  335540 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762187248.369097  335540 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-03 17:27:28.372571: 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..
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Training a non-convolutional model.
[0]	train-mlogloss:1.37453	validation-mlogloss:1.37384
[1]	train-mlogloss:1.36271	validation-mlogloss:1.36139
[2]	train-mlogloss:1.35164	validation-mlogloss:1.34991
[3]	train-mlogloss:1.34055	validation-mlogloss:1.33827
[4]	train-mlogloss:1.32971	validation-mlogloss:1.32679
[5]	train-mlogloss:1.31914	validation-mlogloss:1.31569
[6]	train-mlogloss:1.30916	validation-mlogloss:1.30546
[7]	train-mlogloss:1.29914	validation-mlogloss:1.29494
[8]	train-mlogloss:1.28935	validation-mlogloss:1.28482
[9]	train-mlogloss:1.27943	validation-mlogloss:1.27416
[10]	train-mlogloss:1.26980	validation-mlogloss:1.26398
[11]	train-mlogloss:1.26018	validation-mlogloss:1.25379
[12]	train-mlogloss:1.25099	validation-mlogloss:1.24416
[13]	train-mlogloss:1.24166	validation-mlogloss:1.23464
[14]	train-mlogloss:1.23272	validation-mlogloss:1.22526
[15]	train-mlogloss:1.22390	validation-mlogloss:1.21626
[16]	train-mlogloss:1.21550	validation-mlogloss:1.20768
[17]	train-mlogloss:1.20685	validation-mlogloss:1.19880
[18]	train-mlogloss:1.19850	validation-mlogloss:1.19005
[19]	train-mlogloss:1.19060	validation-mlogloss:1.18178
[20]	train-mlogloss:1.18263	validation-mlogloss:1.17359
[21]	train-mlogloss:1.17466	validation-mlogloss:1.16542
[22]	train-mlogloss:1.16687	validation-mlogloss:1.15735
[23]	train-mlogloss:1.15940	validation-mlogloss:1.14994
[24]	train-mlogloss:1.15175	validation-mlogloss:1.14182
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[412]	train-mlogloss:0.52120	validation-mlogloss:0.50506
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[415]	train-mlogloss:0.52081	validation-mlogloss:0.50473
[416]	train-mlogloss:0.52055	validation-mlogloss:0.50452
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[418]	train-mlogloss:0.52012	validation-mlogloss:0.50420
[419]	train-mlogloss:0.51994	validation-mlogloss:0.50403
[420]	train-mlogloss:0.51984	validation-mlogloss:0.50397
[421]	train-mlogloss:0.51965	validation-mlogloss:0.50385
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[423]	train-mlogloss:0.51920	validation-mlogloss:0.50356
[424]	train-mlogloss:0.51907	validation-mlogloss:0.50341
[425]	train-mlogloss:0.51896	validation-mlogloss:0.50332
[426]	train-mlogloss:0.51880	validation-mlogloss:0.50318
[427]	train-mlogloss:0.51858	validation-mlogloss:0.50295
[428]	train-mlogloss:0.51832	validation-mlogloss:0.50274
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[431]	train-mlogloss:0.51773	validation-mlogloss:0.50218
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[441]	train-mlogloss:0.51606	validation-mlogloss:0.50080
[442]	train-mlogloss:0.51584	validation-mlogloss:0.50066
[443]	train-mlogloss:0.51569	validation-mlogloss:0.50050
[444]	train-mlogloss:0.51549	validation-mlogloss:0.50040
[445]	train-mlogloss:0.51534	validation-mlogloss:0.50029
[446]	train-mlogloss:0.51521	validation-mlogloss:0.50014
[447]	train-mlogloss:0.51508	validation-mlogloss:0.50001
[448]	train-mlogloss:0.51491	validation-mlogloss:0.49988
[449]	train-mlogloss:0.51480	validation-mlogloss:0.49975
[450]	train-mlogloss:0.51454	validation-mlogloss:0.49953
[451]	train-mlogloss:0.51445	validation-mlogloss:0.49946
[452]	train-mlogloss:0.51432	validation-mlogloss:0.49931
[453]	train-mlogloss:0.51420	validation-mlogloss:0.49921
[454]	train-mlogloss:0.51405	validation-mlogloss:0.49914
[455]	train-mlogloss:0.51394	validation-mlogloss:0.49906
[456]	train-mlogloss:0.51371	validation-mlogloss:0.49883
[457]	train-mlogloss:0.51358	validation-mlogloss:0.49866
[458]	train-mlogloss:0.51346	validation-mlogloss:0.49858
[459]	train-mlogloss:0.51331	validation-mlogloss:0.49846
[460]	train-mlogloss:0.51318	validation-mlogloss:0.49832
[461]	train-mlogloss:0.51309	validation-mlogloss:0.49822
[462]	train-mlogloss:0.51291	validation-mlogloss:0.49801
[463]	train-mlogloss:0.51281	validation-mlogloss:0.49798
[464]	train-mlogloss:0.51265	validation-mlogloss:0.49781
[465]	train-mlogloss:0.51256	validation-mlogloss:0.49777
[466]	train-mlogloss:0.51239	validation-mlogloss:0.49763
[467]	train-mlogloss:0.51230	validation-mlogloss:0.49749
[468]	train-mlogloss:0.51210	validation-mlogloss:0.49739
[469]	train-mlogloss:0.51201	validation-mlogloss:0.49739
[470]	train-mlogloss:0.51182	validation-mlogloss:0.49724
[471]	train-mlogloss:0.51175	validation-mlogloss:0.49720
[472]	train-mlogloss:0.51163	validation-mlogloss:0.49705
[473]	train-mlogloss:0.51153	validation-mlogloss:0.49695
[474]	train-mlogloss:0.51143	validation-mlogloss:0.49684
[475]	train-mlogloss:0.51131	validation-mlogloss:0.49671
[476]	train-mlogloss:0.51124	validation-mlogloss:0.49664
[477]	train-mlogloss:0.51112	validation-mlogloss:0.49653
[478]	train-mlogloss:0.51097	validation-mlogloss:0.49647
[479]	train-mlogloss:0.51088	validation-mlogloss:0.49634
[480]	train-mlogloss:0.51075	validation-mlogloss:0.49619
[481]	train-mlogloss:0.51065	validation-mlogloss:0.49617
[482]	train-mlogloss:0.51055	validation-mlogloss:0.49604
[483]	train-mlogloss:0.51038	validation-mlogloss:0.49589
[484]	train-mlogloss:0.51023	validation-mlogloss:0.49575
[485]	train-mlogloss:0.51005	validation-mlogloss:0.49562
[486]	train-mlogloss:0.50996	validation-mlogloss:0.49556
[487]	train-mlogloss:0.50982	validation-mlogloss:0.49549
[488]	train-mlogloss:0.50966	validation-mlogloss:0.49538
[489]	train-mlogloss:0.50956	validation-mlogloss:0.49521
[490]	train-mlogloss:0.50940	validation-mlogloss:0.49510
[491]	train-mlogloss:0.50928	validation-mlogloss:0.49500
[492]	train-mlogloss:0.50912	validation-mlogloss:0.49491
[493]	train-mlogloss:0.50906	validation-mlogloss:0.49483
[494]	train-mlogloss:0.50891	validation-mlogloss:0.49472
[495]	train-mlogloss:0.50883	validation-mlogloss:0.49462
[496]	train-mlogloss:0.50876	validation-mlogloss:0.49460
[497]	train-mlogloss:0.50862	validation-mlogloss:0.49443
[498]	train-mlogloss:0.50854	validation-mlogloss:0.49435
[499]	train-mlogloss:0.50841	validation-mlogloss:0.49429
[500]	train-mlogloss:0.50833	validation-mlogloss:0.49417
[501]	train-mlogloss:0.50827	validation-mlogloss:0.49413
[502]	train-mlogloss:0.50816	validation-mlogloss:0.49398
[503]	train-mlogloss:0.50808	validation-mlogloss:0.49393
[504]	train-mlogloss:0.50785	validation-mlogloss:0.49371
[505]	train-mlogloss:0.50776	validation-mlogloss:0.49359
[506]	train-mlogloss:0.50765	validation-mlogloss:0.49352
[507]	train-mlogloss:0.50757	validation-mlogloss:0.49338
[508]	train-mlogloss:0.50747	validation-mlogloss:0.49334
[509]	train-mlogloss:0.50742	validation-mlogloss:0.49330
[510]	train-mlogloss:0.50733	validation-mlogloss:0.49327
[511]	train-mlogloss:0.50717	validation-mlogloss:0.49310
[512]	train-mlogloss:0.50705	validation-mlogloss:0.49301
[513]	train-mlogloss:0.50701	validation-mlogloss:0.49303
[514]	train-mlogloss:0.50693	validation-mlogloss:0.49298
[515]	train-mlogloss:0.50682	validation-mlogloss:0.49287
[516]	train-mlogloss:0.50662	validation-mlogloss:0.49271
[517]	train-mlogloss:0.50652	validation-mlogloss:0.49269
[518]	train-mlogloss:0.50646	validation-mlogloss:0.49262
[519]	train-mlogloss:0.50639	validation-mlogloss:0.49255
[520]	train-mlogloss:0.50630	validation-mlogloss:0.49245
[521]	train-mlogloss:0.50615	validation-mlogloss:0.49232
Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[2 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.16 [%]
Global accuracy score (test) = 81.34 [%]
Global F1 score (train) = 79.55 [%]
Global F1 score (test) = 81.88 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.65      0.73      0.68       350
MODERATE-INTENSITY       0.69      0.66      0.68       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.97      0.92      0.95       322

          accuracy                           0.81      1372
         macro avg       0.82      0.82      0.82      1372
      weighted avg       0.82      0.81      0.82      1372


Accuracy capturado en la ejecución 29: 81.34 [%]
F1-score capturado en la ejecución 29: 81.88 [%]

=== EJECUCIÓN 30 ===

--- TRAIN (ejecución 30) ---

--- TEST (ejecución 30) ---
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk.
(1372, 91)
(9708, 91)
[[2.]
 [2.]
 [2.]
 ...
 [0.]
 [0.]
 [0.]]
(1372, 1)
[1 2 2 ... 0 0 0]
(1372,)
-------------------------------------------------

Global accuracy score (train) = 79.36 [%]
Global accuracy score (test) = 79.81 [%]
Global F1 score (train) = 79.74 [%]
Global F1 score (test) = 80.44 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.60      0.74      0.66       350
MODERATE-INTENSITY       0.68      0.59      0.63       350
         SEDENTARY       0.99      0.95      0.97       350
VIGOROUS-INTENSITY       0.99      0.92      0.95       322

          accuracy                           0.80      1372
         macro avg       0.81      0.80      0.80      1372
      weighted avg       0.81      0.80      0.80      1372


Accuracy capturado en la ejecución 30: 79.81 [%]
F1-score capturado en la ejecución 30: 80.44 [%]

=== RESUMEN FINAL ===
Accuracies: [79.88, 80.98, 80.47, 79.23, 80.69, 80.17, 80.54, 80.32, 78.86, 81.27, 80.54, 79.52, 80.83, 79.81, 80.32, 80.76, 79.81, 79.74, 78.86, 79.96, 78.86, 81.12, 79.08, 79.52, 80.47, 81.41, 80.98, 80.25, 81.34, 79.81]
F1-scores: [80.5, 81.48, 81.07, 79.73, 81.26, 80.78, 81.07, 80.87, 79.43, 81.82, 81.06, 80.06, 81.24, 80.37, 80.97, 81.23, 80.39, 80.3, 79.5, 80.65, 79.52, 81.69, 79.68, 80.05, 81.07, 81.92, 81.55, 80.82, 81.88, 80.44]
Accuracy mean: 80.1800 | std: 0.7451
F1 mean: 80.7467 | std: 0.7226

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