2025-11-04 10:58:01.987342: 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`.
2025-11-04 10:58:01.998972: 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 00:00:1762250282.013067 1073598 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250282.017380 1073598 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250282.027806 1073598 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250282.027827 1073598 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250282.027829 1073598 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250282.027831 1073598 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:58:02.031095: 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(
2025-11-04 10:58:08,440	INFO worker.py:1927 -- Started a local Ray instance.
2025-11-04 10:58:09,099	INFO tune.py:253 -- Initializing Ray automatically. For cluster usage or custom Ray initialization, call `ray.init(...)` before `Tuner(...)`.
2025-11-04 10:58:09,170	INFO trial.py:182 -- Creating a new dirname dir_c460f_ad38 because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,172	INFO trial.py:182 -- Creating a new dirname dir_c460f_503a because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,175	INFO trial.py:182 -- Creating a new dirname dir_c460f_43b3 because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,177	INFO trial.py:182 -- Creating a new dirname dir_c460f_2903 because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,179	INFO trial.py:182 -- Creating a new dirname dir_c460f_ca70 because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,181	INFO trial.py:182 -- Creating a new dirname dir_c460f_bfcd because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,183	INFO trial.py:182 -- Creating a new dirname dir_c460f_8d9d because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,185	INFO trial.py:182 -- Creating a new dirname dir_c460f_1ecf because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,187	INFO trial.py:182 -- Creating a new dirname dir_c460f_e3bf because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,190	INFO trial.py:182 -- Creating a new dirname dir_c460f_4d6f because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,192	INFO trial.py:182 -- Creating a new dirname dir_c460f_b142 because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,195	INFO trial.py:182 -- Creating a new dirname dir_c460f_30a7 because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,198	INFO trial.py:182 -- Creating a new dirname dir_c460f_7843 because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,201	INFO trial.py:182 -- Creating a new dirname dir_c460f_2525 because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,204	INFO trial.py:182 -- Creating a new dirname dir_c460f_1463 because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,208	INFO trial.py:182 -- Creating a new dirname dir_c460f_f55f because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,211	INFO trial.py:182 -- Creating a new dirname dir_c460f_29da because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,215	INFO trial.py:182 -- Creating a new dirname dir_c460f_99cc because trial dirname 'dir_c460f' already exists.
2025-11-04 10:58:09,219	INFO trial.py:182 -- Creating a new dirname dir_c460f_2fc7 because trial dirname 'dir_c460f' 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_M/case_M_XGB_acc_gyr_superclasses_CPA_METs/XGBoost_hyperparameters_tuning
To visualize your results with TensorBoard, run: `tensorboard --logdir /tmp/ray/session_2025-11-04_10-58-07_632815_1073598/artifacts/2025-11-04_10-58-09/XGBoost_hyperparameters_tuning/driver_artifacts`

Trial status: 20 PENDING
Current time: 2025-11-04 10:58:09. 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_c460f    PENDING                  726             3        0.00544234      0.636302             0.580642   22.5746                   122      15.9864       110.201               6251 │
│ trial_c460f    PENDING                  414             2        0.0137356       0.596917             0.659758   23.6095                   137       6.21827       71.9343              2631 │
│ trial_c460f    PENDING                  714             2        0.0169717       0.785947             0.558926    8.74867                  115       2.37566      182.962               5326 │
│ trial_c460f    PENDING                  601             2        0.016165        0.598849             0.6889     22.5848                    71      42.0419       275.82                8527 │
│ trial_c460f    PENDING                  489             3        0.0108324       0.588673             0.647797   28.7333                    84      56.8546       192.041               5981 │
│ trial_c460f    PENDING                  331             3        0.0186301       0.545252             0.547475   25.4603                    89     234.952        249.425               3625 │
│ trial_c460f    PENDING                  759             3        0.0120311       0.630485             0.716141   22.7561                   192       6.1371         5.12983             1326 │
│ trial_c460f    PENDING                  587             3        0.00834855      0.514537             0.540897    5.88708                   88     472.582          6.91649             7743 │
│ trial_c460f    PENDING                  706             3        0.00544126      0.83925              0.654572   12.1386                   116       6.71554       25.6606               414 │
│ trial_c460f    PENDING                  506             3        0.00995845      0.642371             0.575906   15.2023                   165     335.902          9.17073             5133 │
│ trial_c460f    PENDING                  578             2        0.0101808       0.528152             0.519611   21.323                    152       8.55117        8.99342             8600 │
│ trial_c460f    PENDING                  556             2        0.012262        0.816118             0.546446   18.9666                   112     850.942          7.78939             6521 │
│ trial_c460f    PENDING                  628             2        0.0191453       0.725575             0.584552   11.0286                   185     126.598         28.5908              7858 │
│ trial_c460f    PENDING                  473             2        0.00732801      0.696769             0.543668    6.57686                  111      12.0231        19.8126              3500 │
│ trial_c460f    PENDING                  547             3        0.017135        0.699772             0.501053   16.8339                   121       2.64176      680.803               8084 │
│ trial_c460f    PENDING                  435             3        0.00555129      0.674893             0.683969   28.6209                    83      65.4602         8.27726              996 │
│ trial_c460f    PENDING                  627             2        0.0167769       0.825116             0.729717   17.4283                   149       2.37567       16.9368              5328 │
│ trial_c460f    PENDING                  715             3        0.0129055       0.684046             0.657446   29.4406                   177     277.049         26.0072              3750 │
│ trial_c460f    PENDING                  699             3        0.00521208      0.557633             0.688334   21.6969                    68       4.95267       47.5975              2102 │
│ trial_c460f    PENDING                  524             3        0.0131243       0.828442             0.508115   28.6208                    81     719.267          5.82707             8869 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.54645 │
│ gamma                        18.9666 │
│ learning_rate                0.01226 │
│ max_depth                          2 │
│ min_child_weight                 112 │
│ num_boost_round                  556 │
│ random_state                    6521 │
│ reg_alpha                    850.942 │
│ reg_lambda                   7.78939 │
│ subsample                    0.81612 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.58064 │
│ gamma                        22.5746 │
│ learning_rate                0.00544 │
│ max_depth                          3 │
│ min_child_weight                 122 │
│ num_boost_round                  726 │
│ random_state                    6251 │
│ reg_alpha                    15.9864 │
│ reg_lambda                   110.201 │
│ subsample                     0.6363 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.71614 │
│ gamma                        22.7561 │
│ learning_rate                0.01203 │
│ max_depth                          3 │
│ min_child_weight                 192 │
│ num_boost_round                  759 │
│ random_state                    1326 │
│ reg_alpha                     6.1371 │
│ reg_lambda                   5.12983 │
│ subsample                    0.63049 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.58455 │
│ gamma                        11.0286 │
│ learning_rate                0.01915 │
│ max_depth                          2 │
│ min_child_weight                 185 │
│ num_boost_round                  628 │
│ random_state                    7858 │
│ reg_alpha                    126.598 │
│ reg_lambda                   28.5908 │
│ subsample                    0.72557 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.68833 │
│ gamma                        21.6969 │
│ learning_rate                0.00521 │
│ max_depth                          3 │
│ min_child_weight                  68 │
│ num_boost_round                  699 │
│ random_state                    2102 │
│ reg_alpha                    4.95267 │
│ reg_lambda                   47.5975 │
│ subsample                    0.55763 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.55893 │
│ gamma                        8.74867 │
│ learning_rate                0.01697 │
│ max_depth                          2 │
│ min_child_weight                 115 │
│ num_boost_round                  714 │
│ random_state                    5326 │
│ reg_alpha                    2.37566 │
│ reg_lambda                   182.962 │
│ subsample                    0.78595 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.51961 │
│ gamma                         21.323 │
│ learning_rate                0.01018 │
│ max_depth                          2 │
│ min_child_weight                 152 │
│ num_boost_round                  578 │
│ random_state                    8600 │
│ reg_alpha                    8.55117 │
│ reg_lambda                   8.99342 │
│ subsample                    0.52815 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.65976 │
│ gamma                        23.6095 │
│ learning_rate                0.01374 │
│ max_depth                          2 │
│ min_child_weight                 137 │
│ num_boost_round                  414 │
│ random_state                    2631 │
│ reg_alpha                    6.21827 │
│ reg_lambda                   71.9343 │
│ subsample                    0.59692 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree              0.5409 │
│ gamma                        5.88708 │
│ learning_rate                0.00835 │
│ max_depth                          3 │
│ min_child_weight                  88 │
│ num_boost_round                  587 │
│ random_state                    7743 │
│ reg_alpha                    472.582 │
│ reg_lambda                   6.91649 │
│ subsample                    0.51454 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.65457 │
│ gamma                        12.1386 │
│ learning_rate                0.00544 │
│ max_depth                          3 │
│ min_child_weight                 116 │
│ num_boost_round                  706 │
│ random_state                     414 │
│ reg_alpha                    6.71554 │
│ reg_lambda                   25.6606 │
│ subsample                    0.83925 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.68397 │
│ gamma                        28.6209 │
│ learning_rate                0.00555 │
│ max_depth                          3 │
│ min_child_weight                  83 │
│ num_boost_round                  435 │
│ random_state                     996 │
│ reg_alpha                    65.4602 │
│ reg_lambda                   8.27726 │
│ subsample                    0.67489 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
[36m(train_xgb_ray_tune pid=1075263)[0m 2025-11-04 10:58:12.381636: 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=1075263)[0m 2025-11-04 10:58:12.403147: 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=1075263)[0m WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
[36m(train_xgb_ray_tune pid=1075263)[0m E0000 00:00:1762250292.432002 1076426 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=1075263)[0m E0000 00:00:1762250292.440401 1076426 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=1075263)[0m W0000 00:00:1762250292.460663 1076426 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=1075263)[0m W0000 00:00:1762250292.460697 1076426 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=1075263)[0m W0000 00:00:1762250292.460700 1076426 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=1075263)[0m W0000 00:00:1762250292.460702 1076426 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=1075263)[0m 2025-11-04 10:58:12.466738: 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=1075263)[0m To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.65745 │
│ gamma                        29.4407 │
│ learning_rate                0.01291 │
│ max_depth                          3 │
│ min_child_weight                 177 │
│ num_boost_round                  715 │
│ random_state                    3750 │
│ reg_alpha                    277.049 │
│ reg_lambda                   26.0072 │
│ subsample                    0.68405 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.50105 │
│ gamma                        16.8339 │
│ learning_rate                0.01713 │
│ max_depth                          3 │
│ min_child_weight                 121 │
│ num_boost_round                  547 │
│ random_state                    8084 │
│ reg_alpha                    2.64176 │
│ reg_lambda                   680.803 │
│ subsample                    0.69977 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.72972 │
│ gamma                        17.4283 │
│ learning_rate                0.01678 │
│ max_depth                          2 │
│ min_child_weight                 149 │
│ num_boost_round                  627 │
│ random_state                    5328 │
│ reg_alpha                    2.37567 │
│ reg_lambda                   16.9368 │
│ subsample                    0.82512 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree              0.6889 │
│ gamma                        22.5848 │
│ learning_rate                0.01616 │
│ max_depth                          2 │
│ min_child_weight                  71 │
│ num_boost_round                  601 │
│ random_state                    8527 │
│ reg_alpha                    42.0419 │
│ reg_lambda                    275.82 │
│ subsample                    0.59885 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree              0.6478 │
│ gamma                        28.7333 │
│ learning_rate                0.01083 │
│ max_depth                          3 │
│ min_child_weight                  84 │
│ num_boost_round                  489 │
│ random_state                    5981 │
│ reg_alpha                    56.8546 │
│ reg_lambda                   192.041 │
│ subsample                    0.58867 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.54748 │
│ gamma                        25.4603 │
│ learning_rate                0.01863 │
│ max_depth                          3 │
│ min_child_weight                  89 │
│ num_boost_round                  331 │
│ random_state                    3625 │
│ reg_alpha                    234.952 │
│ reg_lambda                   249.425 │
│ subsample                    0.54525 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.57591 │
│ gamma                        15.2023 │
│ learning_rate                0.00996 │
│ max_depth                          3 │
│ min_child_weight                 165 │
│ num_boost_round                  506 │
│ random_state                    5133 │
│ reg_alpha                    335.902 │
│ reg_lambda                   9.17073 │
│ subsample                    0.64237 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.50811 │
│ gamma                        28.6208 │
│ learning_rate                0.01312 │
│ max_depth                          3 │
│ min_child_weight                  81 │
│ num_boost_round                  524 │
│ random_state                    8869 │
│ reg_alpha                    719.267 │
│ reg_lambda                   5.82707 │
│ subsample                    0.82844 │
╰──────────────────────────────────────╯
Trial trial_c460f started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_c460f config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.54367 │
│ gamma                        6.57686 │
│ learning_rate                0.00733 │
│ max_depth                          2 │
│ min_child_weight                 111 │
│ num_boost_round                  473 │
│ random_state                    3500 │
│ reg_alpha                    12.0231 │
│ reg_lambda                   19.8126 │
│ subsample                    0.69677 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1075263)[0m [0]	train-mlogloss:1.38442	validation-mlogloss:1.38431
[36m(train_xgb_ray_tune pid=1075263)[0m [1]	train-mlogloss:1.38258	validation-mlogloss:1.38238
[36m(train_xgb_ray_tune pid=1075263)[0m [2]	train-mlogloss:1.38074	validation-mlogloss:1.38048
[36m(train_xgb_ray_tune pid=1075263)[0m [3]	train-mlogloss:1.37892	validation-mlogloss:1.37861
[36m(train_xgb_ray_tune pid=1075263)[0m [4]	train-mlogloss:1.37718	validation-mlogloss:1.37672
[36m(train_xgb_ray_tune pid=1075263)[0m [5]	train-mlogloss:1.37549	validation-mlogloss:1.37499
[36m(train_xgb_ray_tune pid=1075263)[0m [6]	train-mlogloss:1.37372	validation-mlogloss:1.37315
[36m(train_xgb_ray_tune pid=1075263)[0m [7]	train-mlogloss:1.37196	validation-mlogloss:1.37128
[36m(train_xgb_ray_tune pid=1075263)[0m [8]	train-mlogloss:1.37027	validation-mlogloss:1.36956
[36m(train_xgb_ray_tune pid=1075263)[0m [9]	train-mlogloss:1.36845	validation-mlogloss:1.36763
[36m(train_xgb_ray_tune pid=1075263)[0m [10]	train-mlogloss:1.36662	validation-mlogloss:1.36576
[36m(train_xgb_ray_tune pid=1075295)[0m [0]	train-mlogloss:1.38264	validation-mlogloss:1.38259
[36m(train_xgb_ray_tune pid=1075298)[0m [0]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [1]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [2]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [3]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [4]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075299)[0m [0]	train-mlogloss:1.38110	validation-mlogloss:1.38091
[36m(train_xgb_ray_tune pid=1075299)[0m [1]	train-mlogloss:1.37619	validation-mlogloss:1.37591
[36m(train_xgb_ray_tune pid=1075299)[0m [2]	train-mlogloss:1.37091	validation-mlogloss:1.37030
[36m(train_xgb_ray_tune pid=1075299)[0m [3]	train-mlogloss:1.36582	validation-mlogloss:1.36506
[36m(train_xgb_ray_tune pid=1075299)[0m [4]	train-mlogloss:1.36112	validation-mlogloss:1.36020
[36m(train_xgb_ray_tune pid=1075299)[0m [5]	train-mlogloss:1.35613	validation-mlogloss:1.35527
[36m(train_xgb_ray_tune pid=1075263)[0m [11]	train-mlogloss:1.36493	validation-mlogloss:1.36399
[36m(train_xgb_ray_tune pid=1075263)[0m [12]	train-mlogloss:1.36321	validation-mlogloss:1.36222
[36m(train_xgb_ray_tune pid=1075263)[0m [13]	train-mlogloss:1.36145	validation-mlogloss:1.36033
[36m(train_xgb_ray_tune pid=1075263)[0m [14]	train-mlogloss:1.35972	validation-mlogloss:1.35851
[36m(train_xgb_ray_tune pid=1075264)[0m [0]	train-mlogloss:1.38191	validation-mlogloss:1.38150
[36m(train_xgb_ray_tune pid=1075264)[0m [1]	train-mlogloss:1.37737	validation-mlogloss:1.37684
[36m(train_xgb_ray_tune pid=1075289)[0m [0]	train-mlogloss:1.38425	validation-mlogloss:1.38424
[36m(train_xgb_ray_tune pid=1075295)[0m [1]	train-mlogloss:1.37913	validation-mlogloss:1.37900
[36m(train_xgb_ray_tune pid=1075295)[0m [2]	train-mlogloss:1.37569	validation-mlogloss:1.37569
[36m(train_xgb_ray_tune pid=1075295)[0m [3]	train-mlogloss:1.37223	validation-mlogloss:1.37214
[36m(train_xgb_ray_tune pid=1075295)[0m [4]	train-mlogloss:1.36883	validation-mlogloss:1.36869
[36m(train_xgb_ray_tune pid=1075295)[0m [5]	train-mlogloss:1.36554	validation-mlogloss:1.36518
[36m(train_xgb_ray_tune pid=1075295)[0m [6]	train-mlogloss:1.36221	validation-mlogloss:1.36188
[36m(train_xgb_ray_tune pid=1075295)[0m [7]	train-mlogloss:1.35891	validation-mlogloss:1.35845
[36m(train_xgb_ray_tune pid=1075298)[0m [5]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [6]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [7]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [8]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [9]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [10]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [11]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [12]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075299)[0m [6]	train-mlogloss:1.35157	validation-mlogloss:1.35033
[36m(train_xgb_ray_tune pid=1075299)[0m [7]	train-mlogloss:1.34713	validation-mlogloss:1.34573
[36m(train_xgb_ray_tune pid=1075299)[0m [8]	train-mlogloss:1.34288	validation-mlogloss:1.34127
[36m(train_xgb_ray_tune pid=1075299)[0m [9]	train-mlogloss:1.33864	validation-mlogloss:1.33692
[36m(train_xgb_ray_tune pid=1075299)[0m [10]	train-mlogloss:1.33448	validation-mlogloss:1.33261
[36m(train_xgb_ray_tune pid=1075299)[0m [11]	train-mlogloss:1.33045	validation-mlogloss:1.32839
[36m(train_xgb_ray_tune pid=1075263)[0m [15]	train-mlogloss:1.35808	validation-mlogloss:1.35679
[36m(train_xgb_ray_tune pid=1075289)[0m [1]	train-mlogloss:1.38223	validation-mlogloss:1.38217
[36m(train_xgb_ray_tune pid=1075298)[0m [13]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075262)[0m [0]	train-mlogloss:1.38115	validation-mlogloss:1.38090
[36m(train_xgb_ray_tune pid=1075264)[0m [2]	train-mlogloss:1.37300	validation-mlogloss:1.37234
[36m(train_xgb_ray_tune pid=1075262)[0m [1]	train-mlogloss:1.37616	validation-mlogloss:1.37548
[36m(train_xgb_ray_tune pid=1075262)[0m [2]	train-mlogloss:1.37097	validation-mlogloss:1.37026
[36m(train_xgb_ray_tune pid=1075262)[0m [3]	train-mlogloss:1.36616	validation-mlogloss:1.36530
[36m(train_xgb_ray_tune pid=1075262)[0m [4]	train-mlogloss:1.36148	validation-mlogloss:1.36057
[36m(train_xgb_ray_tune pid=1075262)[0m [5]	train-mlogloss:1.35689	validation-mlogloss:1.35573
[36m(train_xgb_ray_tune pid=1075263)[0m [16]	train-mlogloss:1.35632	validation-mlogloss:1.35498
[36m(train_xgb_ray_tune pid=1075263)[0m [17]	train-mlogloss:1.35465	validation-mlogloss:1.35328
[36m(train_xgb_ray_tune pid=1075263)[0m [18]	train-mlogloss:1.35293	validation-mlogloss:1.35149
[36m(train_xgb_ray_tune pid=1075263)[0m [19]	train-mlogloss:1.35122	validation-mlogloss:1.34972
[36m(train_xgb_ray_tune pid=1075264)[0m [3]	train-mlogloss:1.36856	validation-mlogloss:1.36772
[36m(train_xgb_ray_tune pid=1075264)[0m [4]	train-mlogloss:1.36426	validation-mlogloss:1.36348
[36m(train_xgb_ray_tune pid=1075264)[0m [5]	train-mlogloss:1.36019	validation-mlogloss:1.35919
[36m(train_xgb_ray_tune pid=1075264)[0m [6]	train-mlogloss:1.35637	validation-mlogloss:1.35519
[36m(train_xgb_ray_tune pid=1075264)[0m [7]	train-mlogloss:1.35235	validation-mlogloss:1.35098
[36m(train_xgb_ray_tune pid=1075297)[0m [0]	train-mlogloss:1.38432	validation-mlogloss:1.38416
[36m(train_xgb_ray_tune pid=1075297)[0m [1]	train-mlogloss:1.38250	validation-mlogloss:1.38236
[36m(train_xgb_ray_tune pid=1075297)[0m [2]	train-mlogloss:1.38061	validation-mlogloss:1.38043
[36m(train_xgb_ray_tune pid=1075289)[0m [2]	train-mlogloss:1.38023	validation-mlogloss:1.38008
[36m(train_xgb_ray_tune pid=1075289)[0m [3]	train-mlogloss:1.37823	validation-mlogloss:1.37800
[36m(train_xgb_ray_tune pid=1075289)[0m [4]	train-mlogloss:1.37624	validation-mlogloss:1.37593
[36m(train_xgb_ray_tune pid=1075295)[0m [8]	train-mlogloss:1.35538	validation-mlogloss:1.35477
[36m(train_xgb_ray_tune pid=1075295)[0m [9]	train-mlogloss:1.35226	validation-mlogloss:1.35144
[36m(train_xgb_ray_tune pid=1075295)[0m [10]	train-mlogloss:1.34899	validation-mlogloss:1.34824
[36m(train_xgb_ray_tune pid=1075295)[0m [11]	train-mlogloss:1.34580	validation-mlogloss:1.34483
[36m(train_xgb_ray_tune pid=1075295)[0m [12]	train-mlogloss:1.34270	validation-mlogloss:1.34163
[36m(train_xgb_ray_tune pid=1075295)[0m [13]	train-mlogloss:1.33966	validation-mlogloss:1.33855
[36m(train_xgb_ray_tune pid=1075298)[0m [14]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [15]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [16]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[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=1075298)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=1075298)[0m [17]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [18]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [19]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075298)[0m [20]	train-mlogloss:1.38629	validation-mlogloss:1.38629
[36m(train_xgb_ray_tune pid=1075299)[0m [12]	train-mlogloss:1.32640	validation-mlogloss:1.32427
[36m(train_xgb_ray_tune pid=1075299)[0m [13]	train-mlogloss:1.32238	validation-mlogloss:1.32015
[36m(train_xgb_ray_tune pid=1075299)[0m [14]	train-mlogloss:1.31835	validation-mlogloss:1.31595
[36m(train_xgb_ray_tune pid=1075299)[0m [15]	train-mlogloss:1.31450	validation-mlogloss:1.31202
[36m(train_xgb_ray_tune pid=1075299)[0m [16]	train-mlogloss:1.31079	validation-mlogloss:1.30834
[36m(train_xgb_ray_tune pid=1075262)[0m [6]	train-mlogloss:1.35214	validation-mlogloss:1.35094
[36m(train_xgb_ray_tune pid=1075297)[0m [3]	train-mlogloss:1.37866	validation-mlogloss:1.37839
[36m(train_xgb_ray_tune pid=1075289)[0m [5]	train-mlogloss:1.37424	validation-mlogloss:1.37385
[36m(train_xgb_ray_tune pid=1075263)[0m [20]	train-mlogloss:1.34958	validation-mlogloss:1.34792
[36m(train_xgb_ray_tune pid=1075264)[0m [8]	train-mlogloss:1.34833	validation-mlogloss:1.34706
[36m(train_xgb_ray_tune pid=1075295)[0m [14]	train-mlogloss:1.33671	validation-mlogloss:1.33547
[36m(train_xgb_ray_tune pid=1075299)[0m [17]	train-mlogloss:1.30703	validation-mlogloss:1.30450
[36m(train_xgb_ray_tune pid=1075262)[0m [7]	train-mlogloss:1.34776	validation-mlogloss:1.34649

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:16. Total running time: 7s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             4.40469 │
│ time_total_s                 4.40469 │
│ training_iteration                 1 │
│ validation_accuracy          0.26334 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:16. Total running time: 7s
[36m(train_xgb_ray_tune pid=1075262)[0m [8]	train-mlogloss:1.34320	validation-mlogloss:1.34169
[36m(train_xgb_ray_tune pid=1075262)[0m [9]	train-mlogloss:1.33861	validation-mlogloss:1.33706
[36m(train_xgb_ray_tune pid=1075262)[0m [10]	train-mlogloss:1.33423	validation-mlogloss:1.33265
[36m(train_xgb_ray_tune pid=1075262)[0m [11]	train-mlogloss:1.33000	validation-mlogloss:1.32834
[36m(train_xgb_ray_tune pid=1075263)[0m [21]	train-mlogloss:1.34796	validation-mlogloss:1.34616
[36m(train_xgb_ray_tune pid=1075263)[0m [22]	train-mlogloss:1.34636	validation-mlogloss:1.34450
[36m(train_xgb_ray_tune pid=1075263)[0m [23]	train-mlogloss:1.34475	validation-mlogloss:1.34282
[36m(train_xgb_ray_tune pid=1075296)[0m [0]	train-mlogloss:1.38129	validation-mlogloss:1.38144
[36m(train_xgb_ray_tune pid=1075296)[0m [1]	train-mlogloss:1.37629	validation-mlogloss:1.37640
[36m(train_xgb_ray_tune pid=1075264)[0m [9]	train-mlogloss:1.34447	validation-mlogloss:1.34318
[36m(train_xgb_ray_tune pid=1075264)[0m [10]	train-mlogloss:1.34058	validation-mlogloss:1.33929
[36m(train_xgb_ray_tune pid=1075264)[0m [11]	train-mlogloss:1.33682	validation-mlogloss:1.33538
[36m(train_xgb_ray_tune pid=1075297)[0m [4]	train-mlogloss:1.37689	validation-mlogloss:1.37652
[36m(train_xgb_ray_tune pid=1075297)[0m [5]	train-mlogloss:1.37494	validation-mlogloss:1.37447
[36m(train_xgb_ray_tune pid=1075289)[0m [6]	train-mlogloss:1.37233	validation-mlogloss:1.37186
[36m(train_xgb_ray_tune pid=1075289)[0m [7]	train-mlogloss:1.37026	validation-mlogloss:1.36974
[36m(train_xgb_ray_tune pid=1075289)[0m [8]	train-mlogloss:1.36834	validation-mlogloss:1.36776
[36m(train_xgb_ray_tune pid=1075292)[0m [0]	train-mlogloss:1.38378	validation-mlogloss:1.38373
[36m(train_xgb_ray_tune pid=1075292)[0m [1]	train-mlogloss:1.38150	validation-mlogloss:1.38137
[36m(train_xgb_ray_tune pid=1075292)[0m [2]	train-mlogloss:1.37904	validation-mlogloss:1.37890
[36m(train_xgb_ray_tune pid=1075295)[0m [15]	train-mlogloss:1.33379	validation-mlogloss:1.33244
[36m(train_xgb_ray_tune pid=1075295)[0m [16]	train-mlogloss:1.33081	validation-mlogloss:1.32930
[36m(train_xgb_ray_tune pid=1075295)[0m [17]	train-mlogloss:1.32778	validation-mlogloss:1.32590
[36m(train_xgb_ray_tune pid=1075295)[0m [18]	train-mlogloss:1.32489	validation-mlogloss:1.32306
[36m(train_xgb_ray_tune pid=1075270)[0m [0]	train-mlogloss:1.38280	validation-mlogloss:1.38258
[36m(train_xgb_ray_tune pid=1075270)[0m [1]	train-mlogloss:1.37904	validation-mlogloss:1.37865
[36m(train_xgb_ray_tune pid=1075270)[0m [2]	train-mlogloss:1.37530	validation-mlogloss:1.37480
[36m(train_xgb_ray_tune pid=1075270)[0m [3]	train-mlogloss:1.37172	validation-mlogloss:1.37105
[36m(train_xgb_ray_tune pid=1075299)[0m [18]	train-mlogloss:1.30346	validation-mlogloss:1.30057
[36m(train_xgb_ray_tune pid=1075299)[0m [19]	train-mlogloss:1.29996	validation-mlogloss:1.29701
[36m(train_xgb_ray_tune pid=1075299)[0m [20]	train-mlogloss:1.29662	validation-mlogloss:1.29356
[36m(train_xgb_ray_tune pid=1075299)[0m [21]	train-mlogloss:1.29328	validation-mlogloss:1.29003
[36m(train_xgb_ray_tune pid=1075293)[0m [0]	train-mlogloss:1.38404	validation-mlogloss:1.38392
[36m(train_xgb_ray_tune pid=1075293)[0m [1]	train-mlogloss:1.38183	validation-mlogloss:1.38155
[36m(train_xgb_ray_tune pid=1075293)[0m [2]	train-mlogloss:1.37940	validation-mlogloss:1.37893
[36m(train_xgb_ray_tune pid=1075296)[0m [2]	train-mlogloss:1.37141	validation-mlogloss:1.37133
[36m(train_xgb_ray_tune pid=1075264)[0m [12]	train-mlogloss:1.33291	validation-mlogloss:1.33162
[36m(train_xgb_ray_tune pid=1075297)[0m [6]	train-mlogloss:1.37313	validation-mlogloss:1.37261
[36m(train_xgb_ray_tune pid=1075293)[0m [3]	train-mlogloss:1.37720	validation-mlogloss:1.37657
[36m(train_xgb_ray_tune pid=1075262)[0m [12]	train-mlogloss:1.32546	validation-mlogloss:1.32338
[36m(train_xgb_ray_tune pid=1075289)[0m [9]	train-mlogloss:1.36651	validation-mlogloss:1.36593
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[36m(train_xgb_ray_tune pid=1075292)[0m [3]	train-mlogloss:1.37675	validation-mlogloss:1.37660
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[36m(train_xgb_ray_tune pid=1075270)[0m [86]	train-mlogloss:1.17752	validation-mlogloss:1.16683
[36m(train_xgb_ray_tune pid=1075293)[0m [134]	train-mlogloss:1.25322	validation-mlogloss:1.24384
[36m(train_xgb_ray_tune pid=1075262)[0m [125]	train-mlogloss:1.07028	validation-mlogloss:1.06523
[36m(train_xgb_ray_tune pid=1075287)[0m [95]	train-mlogloss:1.21647	validation-mlogloss:1.20484
[36m(train_xgb_ray_tune pid=1075271)[0m [174]	train-mlogloss:1.35999	validation-mlogloss:1.35773
[36m(train_xgb_ray_tune pid=1075297)[0m [74]	train-mlogloss:1.27207	validation-mlogloss:1.26633
[36m(train_xgb_ray_tune pid=1075291)[0m [117]	train-mlogloss:1.29575	validation-mlogloss:1.29063
[36m(train_xgb_ray_tune pid=1075290)[0m [158]	train-mlogloss:1.36285	validation-mlogloss:1.36097
[36m(train_xgb_ray_tune pid=1075295)[0m [127]	train-mlogloss:1.12670	validation-mlogloss:1.11684
[36m(train_xgb_ray_tune pid=1075299)[0m [133]	train-mlogloss:1.10960	validation-mlogloss:1.10060
[36m(train_xgb_ray_tune pid=1075263)[0m [99]	train-mlogloss:1.24362	validation-mlogloss:1.23758
[36m(train_xgb_ray_tune pid=1075288)[0m [137]	train-mlogloss:1.27001	validation-mlogloss:1.26092
[36m(train_xgb_ray_tune pid=1075296)[0m [75]	train-mlogloss:1.14092	validation-mlogloss:1.14098
[36m(train_xgb_ray_tune pid=1075264)[0m [133]	train-mlogloss:1.09075	validation-mlogloss:1.08187
[36m(train_xgb_ray_tune pid=1075294)[0m [111]	train-mlogloss:1.15783	validation-mlogloss:1.14371
[36m(train_xgb_ray_tune pid=1075292)[0m [80]	train-mlogloss:1.23363	validation-mlogloss:1.23359
[36m(train_xgb_ray_tune pid=1075271)[0m [175]	train-mlogloss:1.35999	validation-mlogloss:1.35773
[36m(train_xgb_ray_tune pid=1075300)[0m [108]	train-mlogloss:1.06501	validation-mlogloss:1.05984
[36m(train_xgb_ray_tune pid=1075289)[0m [71]	train-mlogloss:1.26520	validation-mlogloss:1.26138
[36m(train_xgb_ray_tune pid=1075262)[0m [126]	train-mlogloss:1.06915	validation-mlogloss:1.06416
[36m(train_xgb_ray_tune pid=1075291)[0m [118]	train-mlogloss:1.29544	validation-mlogloss:1.29030
[36m(train_xgb_ray_tune pid=1075288)[0m [138]	train-mlogloss:1.26971	validation-mlogloss:1.26059
[36m(train_xgb_ray_tune pid=1075287)[0m [96]	train-mlogloss:1.21534	validation-mlogloss:1.20367
[36m(train_xgb_ray_tune pid=1075264)[0m [134]	train-mlogloss:1.08973	validation-mlogloss:1.08075
[36m(train_xgb_ray_tune pid=1075290)[0m [159]	train-mlogloss:1.36272	validation-mlogloss:1.36082
[36m(train_xgb_ray_tune pid=1075295)[0m [128]	train-mlogloss:1.12555	validation-mlogloss:1.11559
[36m(train_xgb_ray_tune pid=1075270)[0m [87]	train-mlogloss:1.17599	validation-mlogloss:1.16535
[36m(train_xgb_ray_tune pid=1075299)[0m [134]	train-mlogloss:1.10900	validation-mlogloss:1.09995
[36m(train_xgb_ray_tune pid=1075301)[0m [101]	train-mlogloss:1.20140	validation-mlogloss:1.19402
[36m(train_xgb_ray_tune pid=1075262)[0m [127]	train-mlogloss:1.06803	validation-mlogloss:1.06321
[36m(train_xgb_ray_tune pid=1075296)[0m [76]	train-mlogloss:1.13875	validation-mlogloss:1.13881
[36m(train_xgb_ray_tune pid=1075294)[0m [112]	train-mlogloss:1.15691	validation-mlogloss:1.14281
[36m(train_xgb_ray_tune pid=1075300)[0m [109]	train-mlogloss:1.06366	validation-mlogloss:1.05886
[36m(train_xgb_ray_tune pid=1075297)[0m [75]	train-mlogloss:1.27087	validation-mlogloss:1.26510
[36m(train_xgb_ray_tune pid=1075291)[0m [119]	train-mlogloss:1.29513	validation-mlogloss:1.28997
[36m(train_xgb_ray_tune pid=1075290)[0m [160]	train-mlogloss:1.36262	validation-mlogloss:1.36071
[36m(train_xgb_ray_tune pid=1075292)[0m [81]	train-mlogloss:1.23220	validation-mlogloss:1.23222
[36m(train_xgb_ray_tune pid=1075299)[0m [135]	train-mlogloss:1.10840	validation-mlogloss:1.09935
[36m(train_xgb_ray_tune pid=1075263)[0m [100]	train-mlogloss:1.24255	validation-mlogloss:1.23643
[36m(train_xgb_ray_tune pid=1075288)[0m [139]	train-mlogloss:1.26942	validation-mlogloss:1.26027
[36m(train_xgb_ray_tune pid=1075287)[0m [97]	train-mlogloss:1.21424	validation-mlogloss:1.20254
[36m(train_xgb_ray_tune pid=1075264)[0m [135]	train-mlogloss:1.08871	validation-mlogloss:1.07968
[36m(train_xgb_ray_tune pid=1075289)[0m [72]	train-mlogloss:1.26377	validation-mlogloss:1.25989
[36m(train_xgb_ray_tune pid=1075295)[0m [129]	train-mlogloss:1.12452	validation-mlogloss:1.11433
[36m(train_xgb_ray_tune pid=1075270)[0m [88]	train-mlogloss:1.17453	validation-mlogloss:1.16379
[36m(train_xgb_ray_tune pid=1075291)[0m [120]	train-mlogloss:1.29476	validation-mlogloss:1.28956
[36m(train_xgb_ray_tune pid=1075262)[0m [128]	train-mlogloss:1.06692	validation-mlogloss:1.06206
[36m(train_xgb_ray_tune pid=1075294)[0m [113]	train-mlogloss:1.15590	validation-mlogloss:1.14178
[36m(train_xgb_ray_tune pid=1075290)[0m [161]	train-mlogloss:1.36252	validation-mlogloss:1.36060
[36m(train_xgb_ray_tune pid=1075301)[0m [102]	train-mlogloss:1.20016	validation-mlogloss:1.19269
[36m(train_xgb_ray_tune pid=1075288)[0m [140]	train-mlogloss:1.26914	validation-mlogloss:1.25998
[36m(train_xgb_ray_tune pid=1075296)[0m [77]	train-mlogloss:1.13666	validation-mlogloss:1.13683
[36m(train_xgb_ray_tune pid=1075264)[0m [136]	train-mlogloss:1.08774	validation-mlogloss:1.07851
[36m(train_xgb_ray_tune pid=1075300)[0m [110]	train-mlogloss:1.06235	validation-mlogloss:1.05774
[36m(train_xgb_ray_tune pid=1075297)[0m [76]	train-mlogloss:1.26974	validation-mlogloss:1.26391
[36m(train_xgb_ray_tune pid=1075291)[0m [121]	train-mlogloss:1.29426	validation-mlogloss:1.28905
[36m(train_xgb_ray_tune pid=1075295)[0m [130]	train-mlogloss:1.12358	validation-mlogloss:1.11348
[36m(train_xgb_ray_tune pid=1075270)[0m [89]	train-mlogloss:1.17321	validation-mlogloss:1.16232
[36m(train_xgb_ray_tune pid=1075299)[0m [136]	train-mlogloss:1.10771	validation-mlogloss:1.09874
[36m(train_xgb_ray_tune pid=1075293)[0m [135]	train-mlogloss:1.25292	validation-mlogloss:1.24352
[36m(train_xgb_ray_tune pid=1075262)[0m [129]	train-mlogloss:1.06573	validation-mlogloss:1.06088
[36m(train_xgb_ray_tune pid=1075290)[0m [162]	train-mlogloss:1.36240	validation-mlogloss:1.36048
[36m(train_xgb_ray_tune pid=1075292)[0m [82]	train-mlogloss:1.23079	validation-mlogloss:1.23078
[36m(train_xgb_ray_tune pid=1075287)[0m [98]	train-mlogloss:1.21315	validation-mlogloss:1.20134
[36m(train_xgb_ray_tune pid=1075264)[0m [137]	train-mlogloss:1.08673	validation-mlogloss:1.07750
[36m(train_xgb_ray_tune pid=1075294)[0m [114]	train-mlogloss:1.15491	validation-mlogloss:1.14077
[36m(train_xgb_ray_tune pid=1075300)[0m [111]	train-mlogloss:1.06114	validation-mlogloss:1.05662
[36m(train_xgb_ray_tune pid=1075291)[0m [122]	train-mlogloss:1.29401	validation-mlogloss:1.28879
[36m(train_xgb_ray_tune pid=1075263)[0m [101]	train-mlogloss:1.24148	validation-mlogloss:1.23527
[36m(train_xgb_ray_tune pid=1075288)[0m [141]	train-mlogloss:1.26884	validation-mlogloss:1.25965
[36m(train_xgb_ray_tune pid=1075289)[0m [73]	train-mlogloss:1.26243	validation-mlogloss:1.25849
[36m(train_xgb_ray_tune pid=1075290)[0m [163]	train-mlogloss:1.36240	validation-mlogloss:1.36048
[36m(train_xgb_ray_tune pid=1075295)[0m [131]	train-mlogloss:1.12261	validation-mlogloss:1.11261
[36m(train_xgb_ray_tune pid=1075299)[0m [137]	train-mlogloss:1.10708	validation-mlogloss:1.09817
[36m(train_xgb_ray_tune pid=1075301)[0m [103]	train-mlogloss:1.19884	validation-mlogloss:1.19121
[36m(train_xgb_ray_tune pid=1075297)[0m [77]	train-mlogloss:1.26853	validation-mlogloss:1.26259
[36m(train_xgb_ray_tune pid=1075301)[0m 2025-11-04 10:58:12.990657: 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=1075301)[0m 2025-11-04 10:58:13.013291: 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=1075301)[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=1075301)[0m E0000 00:00:1762250293.041555 1076552 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=1075301)[0m E0000 00:00:1762250293.049814 1076552 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=1075301)[0m W0000 00:00:1762250293.069992 1076552 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=1075301)[0m 2025-11-04 10:58:13.076176: 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=1075301)[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=1075291)[0m [123]	train-mlogloss:1.29373	validation-mlogloss:1.28847
[36m(train_xgb_ray_tune pid=1075270)[0m [90]	train-mlogloss:1.17179	validation-mlogloss:1.16085
[36m(train_xgb_ray_tune pid=1075293)[0m [136]	train-mlogloss:1.25262	validation-mlogloss:1.24317
[36m(train_xgb_ray_tune pid=1075288)[0m [142]	train-mlogloss:1.26857	validation-mlogloss:1.25936
[36m(train_xgb_ray_tune pid=1075296)[0m [78]	train-mlogloss:1.13457	validation-mlogloss:1.13466
[36m(train_xgb_ray_tune pid=1075287)[0m [99]	train-mlogloss:1.21211	validation-mlogloss:1.20028
[36m(train_xgb_ray_tune pid=1075264)[0m [138]	train-mlogloss:1.08561	validation-mlogloss:1.07643
[36m(train_xgb_ray_tune pid=1075294)[0m [115]	train-mlogloss:1.15395	validation-mlogloss:1.13976
[36m(train_xgb_ray_tune pid=1075300)[0m [112]	train-mlogloss:1.05990	validation-mlogloss:1.05545
[36m(train_xgb_ray_tune pid=1075290)[0m [164]	train-mlogloss:1.36229	validation-mlogloss:1.36035
[36m(train_xgb_ray_tune pid=1075292)[0m [83]	train-mlogloss:1.22947	validation-mlogloss:1.22940
[36m(train_xgb_ray_tune pid=1075295)[0m [132]	train-mlogloss:1.12157	validation-mlogloss:1.11152
[36m(train_xgb_ray_tune pid=1075299)[0m [138]	train-mlogloss:1.10636	validation-mlogloss:1.09743
[36m(train_xgb_ray_tune pid=1075293)[0m [137]	train-mlogloss:1.25232	validation-mlogloss:1.24285
[36m(train_xgb_ray_tune pid=1075291)[0m [124]	train-mlogloss:1.29344	validation-mlogloss:1.28816

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:20. Total running time: 11s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             7.71378 │
│ time_total_s                 7.71378 │
│ training_iteration                 1 │
│ validation_accuracy          0.41468 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:20. Total running time: 11s
[36m(train_xgb_ray_tune pid=1075262)[0m [130]	train-mlogloss:1.06464	validation-mlogloss:1.05986
[36m(train_xgb_ray_tune pid=1075262)[0m [131]	train-mlogloss:1.06358	validation-mlogloss:1.05901
[36m(train_xgb_ray_tune pid=1075262)[0m [132]	train-mlogloss:1.06250	validation-mlogloss:1.05798
[36m(train_xgb_ray_tune pid=1075262)[0m [133]	train-mlogloss:1.06147	validation-mlogloss:1.05697
[36m(train_xgb_ray_tune pid=1075263)[0m [102]	train-mlogloss:1.24036	validation-mlogloss:1.23410
[36m(train_xgb_ray_tune pid=1075263)[0m [103]	train-mlogloss:1.23929	validation-mlogloss:1.23301
[36m(train_xgb_ray_tune pid=1075263)[0m [104]	train-mlogloss:1.23825	validation-mlogloss:1.23193
[36m(train_xgb_ray_tune pid=1075288)[0m [143]	train-mlogloss:1.26829	validation-mlogloss:1.25906
[36m(train_xgb_ray_tune pid=1075288)[0m [144]	train-mlogloss:1.26801	validation-mlogloss:1.25876
[36m(train_xgb_ray_tune pid=1075288)[0m [145]	train-mlogloss:1.26774	validation-mlogloss:1.25845
[36m(train_xgb_ray_tune pid=1075288)[0m [146]	train-mlogloss:1.26747	validation-mlogloss:1.25816
[36m(train_xgb_ray_tune pid=1075288)[0m [147]	train-mlogloss:1.26722	validation-mlogloss:1.25788
[36m(train_xgb_ray_tune pid=1075288)[0m [148]	train-mlogloss:1.26722	validation-mlogloss:1.25788
[36m(train_xgb_ray_tune pid=1075296)[0m [79]	train-mlogloss:1.13238	validation-mlogloss:1.13241
[36m(train_xgb_ray_tune pid=1075296)[0m [80]	train-mlogloss:1.13038	validation-mlogloss:1.13033
[36m(train_xgb_ray_tune pid=1075296)[0m [81]	train-mlogloss:1.12848	validation-mlogloss:1.12866
[36m(train_xgb_ray_tune pid=1075287)[0m [100]	train-mlogloss:1.21097	validation-mlogloss:1.19909
[36m(train_xgb_ray_tune pid=1075287)[0m [101]	train-mlogloss:1.21000	validation-mlogloss:1.19808
[36m(train_xgb_ray_tune pid=1075287)[0m [102]	train-mlogloss:1.20891	validation-mlogloss:1.19689
[36m(train_xgb_ray_tune pid=1075264)[0m [139]	train-mlogloss:1.08466	validation-mlogloss:1.07550
[36m(train_xgb_ray_tune pid=1075264)[0m [140]	train-mlogloss:1.08372	validation-mlogloss:1.07476
[36m(train_xgb_ray_tune pid=1075264)[0m [141]	train-mlogloss:1.08269	validation-mlogloss:1.07361
[36m(train_xgb_ray_tune pid=1075264)[0m [142]	train-mlogloss:1.08175	validation-mlogloss:1.07282
[36m(train_xgb_ray_tune pid=1075294)[0m [116]	train-mlogloss:1.15303	validation-mlogloss:1.13884
[36m(train_xgb_ray_tune pid=1075294)[0m [117]	train-mlogloss:1.15207	validation-mlogloss:1.13784
[36m(train_xgb_ray_tune pid=1075294)[0m [118]	train-mlogloss:1.15108	validation-mlogloss:1.13669
[36m(train_xgb_ray_tune pid=1075294)[0m [119]	train-mlogloss:1.15008	validation-mlogloss:1.13575
[36m(train_xgb_ray_tune pid=1075300)[0m [113]	train-mlogloss:1.05854	validation-mlogloss:1.05430
[36m(train_xgb_ray_tune pid=1075300)[0m [114]	train-mlogloss:1.05721	validation-mlogloss:1.05317
[36m(train_xgb_ray_tune pid=1075300)[0m [115]	train-mlogloss:1.05601	validation-mlogloss:1.05201
[36m(train_xgb_ray_tune pid=1075300)[0m [116]	train-mlogloss:1.05472	validation-mlogloss:1.05067
[36m(train_xgb_ray_tune pid=1075297)[0m [78]	train-mlogloss:1.26736	validation-mlogloss:1.26131
[36m(train_xgb_ray_tune pid=1075297)[0m [79]	train-mlogloss:1.26604	validation-mlogloss:1.25995
[36m(train_xgb_ray_tune pid=1075297)[0m [80]	train-mlogloss:1.26485	validation-mlogloss:1.25865
[36m(train_xgb_ray_tune pid=1075289)[0m [74]	train-mlogloss:1.26114	validation-mlogloss:1.25713
[36m(train_xgb_ray_tune pid=1075289)[0m [75]	train-mlogloss:1.25984	validation-mlogloss:1.25582
[36m(train_xgb_ray_tune pid=1075289)[0m [76]	train-mlogloss:1.25849	validation-mlogloss:1.25448
[36m(train_xgb_ray_tune pid=1075291)[0m [125]	train-mlogloss:1.29314	validation-mlogloss:1.28784
[36m(train_xgb_ray_tune pid=1075291)[0m [126]	train-mlogloss:1.29287	validation-mlogloss:1.28755
[36m(train_xgb_ray_tune pid=1075291)[0m [127]	train-mlogloss:1.29259	validation-mlogloss:1.28725
[36m(train_xgb_ray_tune pid=1075291)[0m [128]	train-mlogloss:1.29203	validation-mlogloss:1.28667
[36m(train_xgb_ray_tune pid=1075291)[0m [129]	train-mlogloss:1.29174	validation-mlogloss:1.28635
[36m(train_xgb_ray_tune pid=1075290)[0m [165]	train-mlogloss:1.36220	validation-mlogloss:1.36025
[36m(train_xgb_ray_tune pid=1075290)[0m [166]	train-mlogloss:1.36208	validation-mlogloss:1.36012
[36m(train_xgb_ray_tune pid=1075290)[0m [167]	train-mlogloss:1.36208	validation-mlogloss:1.36012
[36m(train_xgb_ray_tune pid=1075290)[0m [168]	train-mlogloss:1.36197	validation-mlogloss:1.36000
[36m(train_xgb_ray_tune pid=1075290)[0m [169]	train-mlogloss:1.36197	validation-mlogloss:1.36000
[36m(train_xgb_ray_tune pid=1075290)[0m [170]	train-mlogloss:1.36185	validation-mlogloss:1.35987
[36m(train_xgb_ray_tune pid=1075290)[0m [171]	train-mlogloss:1.36185	validation-mlogloss:1.35987
[36m(train_xgb_ray_tune pid=1075292)[0m [84]	train-mlogloss:1.22793	validation-mlogloss:1.22789
[36m(train_xgb_ray_tune pid=1075292)[0m [85]	train-mlogloss:1.22653	validation-mlogloss:1.22649
[36m(train_xgb_ray_tune pid=1075292)[0m [86]	train-mlogloss:1.22515	validation-mlogloss:1.22505
[36m(train_xgb_ray_tune pid=1075295)[0m [133]	train-mlogloss:1.12066	validation-mlogloss:1.11060
[36m(train_xgb_ray_tune pid=1075295)[0m [134]	train-mlogloss:1.11965	validation-mlogloss:1.10977
[36m(train_xgb_ray_tune pid=1075295)[0m [135]	train-mlogloss:1.11862	validation-mlogloss:1.10885
[36m(train_xgb_ray_tune pid=1075295)[0m [136]	train-mlogloss:1.11758	validation-mlogloss:1.10810
[36m(train_xgb_ray_tune pid=1075270)[0m [91]	train-mlogloss:1.17023	validation-mlogloss:1.15928
[36m(train_xgb_ray_tune pid=1075270)[0m [92]	train-mlogloss:1.16875	validation-mlogloss:1.15771
[36m(train_xgb_ray_tune pid=1075270)[0m [93]	train-mlogloss:1.16729	validation-mlogloss:1.15607
[36m(train_xgb_ray_tune pid=1075270)[0m [94]	train-mlogloss:1.16585	validation-mlogloss:1.15469
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[36m(train_xgb_ray_tune pid=1075290)[0m [350]	train-mlogloss:1.35353	validation-mlogloss:1.35078
[36m(train_xgb_ray_tune pid=1075299)[0m [295]	train-mlogloss:1.05214	validation-mlogloss:1.04677
[36m(train_xgb_ray_tune pid=1075296)[0m [174]	train-mlogloss:1.01740	validation-mlogloss:1.02287
[36m(train_xgb_ray_tune pid=1075287)[0m [217]	train-mlogloss:1.12937	validation-mlogloss:1.11514
[36m(train_xgb_ray_tune pid=1075264)[0m [266]	train-mlogloss:1.01296	validation-mlogloss:1.00893
[36m(train_xgb_ray_tune pid=1075294)[0m [253]	train-mlogloss:1.07349	validation-mlogloss:1.06127
[36m(train_xgb_ray_tune pid=1075292)[0m [159]	train-mlogloss:1.13876	validation-mlogloss:1.14166
[36m(train_xgb_ray_tune pid=1075288)[0m [316]	train-mlogloss:1.25580	validation-mlogloss:1.24522
[36m(train_xgb_ray_tune pid=1075297)[0m [175]	train-mlogloss:1.18299	validation-mlogloss:1.17101
[36m(train_xgb_ray_tune pid=1075289)[0m [152]	train-mlogloss:1.17501	validation-mlogloss:1.16904
[36m(train_xgb_ray_tune pid=1075291)[0m [295]	train-mlogloss:1.26015	validation-mlogloss:1.25191
[36m(train_xgb_ray_tune pid=1075290)[0m [351]	train-mlogloss:1.35353	validation-mlogloss:1.35078
[36m(train_xgb_ray_tune pid=1075295)[0m [259]	train-mlogloss:1.03441	validation-mlogloss:1.02844
[36m(train_xgb_ray_tune pid=1075270)[0m [189]	train-mlogloss:1.07541	validation-mlogloss:1.06217
[36m(train_xgb_ray_tune pid=1075299)[0m [296]	train-mlogloss:1.05206	validation-mlogloss:1.04675
[36m(train_xgb_ray_tune pid=1075301)[0m [217]	train-mlogloss:1.09202	validation-mlogloss:1.08530
[36m(train_xgb_ray_tune pid=1075263)[0m [188]	train-mlogloss:1.16400	validation-mlogloss:1.15473
[36m(train_xgb_ray_tune pid=1075287)[0m [218]	train-mlogloss:1.12908	validation-mlogloss:1.11485
[36m(train_xgb_ray_tune pid=1075294)[0m [254]	train-mlogloss:1.07318	validation-mlogloss:1.06100
[36m(train_xgb_ray_tune pid=1075300)[0m [230]	train-mlogloss:0.95999	validation-mlogloss:0.97124
[36m(train_xgb_ray_tune pid=1075262)[0m [249]	train-mlogloss:0.97610	validation-mlogloss:0.98103
[36m(train_xgb_ray_tune pid=1075288)[0m [317]	train-mlogloss:1.25580	validation-mlogloss:1.24522
[36m(train_xgb_ray_tune pid=1075296)[0m [175]	train-mlogloss:1.01681	validation-mlogloss:1.02243
[36m(train_xgb_ray_tune pid=1075264)[0m [267]	train-mlogloss:1.01262	validation-mlogloss:1.00857
[36m(train_xgb_ray_tune pid=1075291)[0m [296]	train-mlogloss:1.26002	validation-mlogloss:1.25177
[36m(train_xgb_ray_tune pid=1075290)[0m [352]	train-mlogloss:1.35353	validation-mlogloss:1.35078
[36m(train_xgb_ray_tune pid=1075295)[0m [260]	train-mlogloss:1.03397	validation-mlogloss:1.02816
[36m(train_xgb_ray_tune pid=1075299)[0m [297]	train-mlogloss:1.05206	validation-mlogloss:1.04675
[36m(train_xgb_ray_tune pid=1075297)[0m [176]	train-mlogloss:1.18238	validation-mlogloss:1.17039
[36m(train_xgb_ray_tune pid=1075290)[0m [353]	train-mlogloss:1.35353	validation-mlogloss:1.35078
[36m(train_xgb_ray_tune pid=1075301)[0m [218]	train-mlogloss:1.09134	validation-mlogloss:1.08463
[36m(train_xgb_ray_tune pid=1075287)[0m [219]	train-mlogloss:1.12870	validation-mlogloss:1.11449
[36m(train_xgb_ray_tune pid=1075294)[0m [255]	train-mlogloss:1.07281	validation-mlogloss:1.06066
[36m(train_xgb_ray_tune pid=1075300)[0m [231]	train-mlogloss:0.95944	validation-mlogloss:0.97084
[36m(train_xgb_ray_tune pid=1075289)[0m [153]	train-mlogloss:1.17401	validation-mlogloss:1.16807
[36m(train_xgb_ray_tune pid=1075291)[0m [297]	train-mlogloss:1.25989	validation-mlogloss:1.25162
[36m(train_xgb_ray_tune pid=1075290)[0m [354]	train-mlogloss:1.35353	validation-mlogloss:1.35078
[36m(train_xgb_ray_tune pid=1075295)[0m [261]	train-mlogloss:1.03346	validation-mlogloss:1.02770
[36m(train_xgb_ray_tune pid=1075270)[0m [190]	train-mlogloss:1.07481	validation-mlogloss:1.06160
[36m(train_xgb_ray_tune pid=1075299)[0m [298]	train-mlogloss:1.05199	validation-mlogloss:1.04667
[36m(train_xgb_ray_tune pid=1075262)[0m [250]	train-mlogloss:0.97559	validation-mlogloss:0.98069
[36m(train_xgb_ray_tune pid=1075263)[0m [189]	train-mlogloss:1.16327	validation-mlogloss:1.15396
[36m(train_xgb_ray_tune pid=1075288)[0m [318]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075288)[0m [319]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075296)[0m [176]	train-mlogloss:1.01625	validation-mlogloss:1.02208
[36m(train_xgb_ray_tune pid=1075287)[0m [220]	train-mlogloss:1.12833	validation-mlogloss:1.11408
[36m(train_xgb_ray_tune pid=1075264)[0m [268]	train-mlogloss:1.01222	validation-mlogloss:1.00812
[36m(train_xgb_ray_tune pid=1075297)[0m [177]	train-mlogloss:1.18180	validation-mlogloss:1.16979
[36m(train_xgb_ray_tune pid=1075292)[0m [160]	train-mlogloss:1.13781	validation-mlogloss:1.14078
[36m(train_xgb_ray_tune pid=1075301)[0m [219]	train-mlogloss:1.09069	validation-mlogloss:1.08405
[36m(train_xgb_ray_tune pid=1075294)[0m [256]	train-mlogloss:1.07243	validation-mlogloss:1.06037
[36m(train_xgb_ray_tune pid=1075300)[0m [232]	train-mlogloss:0.95901	validation-mlogloss:0.97061
[36m(train_xgb_ray_tune pid=1075291)[0m [298]	train-mlogloss:1.25976	validation-mlogloss:1.25148
[36m(train_xgb_ray_tune pid=1075299)[0m [299]	train-mlogloss:1.05199	validation-mlogloss:1.04667
[36m(train_xgb_ray_tune pid=1075288)[0m [320]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075264)[0m [269]	train-mlogloss:1.01195	validation-mlogloss:1.00786
[36m(train_xgb_ray_tune pid=1075270)[0m [191]	train-mlogloss:1.07424	validation-mlogloss:1.06102
[36m(train_xgb_ray_tune pid=1075262)[0m [251]	train-mlogloss:0.97501	validation-mlogloss:0.98017
[36m(train_xgb_ray_tune pid=1075262)[0m [252]	train-mlogloss:0.97441	validation-mlogloss:0.97977
[36m(train_xgb_ray_tune pid=1075262)[0m [253]	train-mlogloss:0.97384	validation-mlogloss:0.97934
[36m(train_xgb_ray_tune pid=1075262)[0m [254]	train-mlogloss:0.97337	validation-mlogloss:0.97907
[36m(train_xgb_ray_tune pid=1075262)[0m [255]	train-mlogloss:0.97280	validation-mlogloss:0.97870

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:23. Total running time: 14s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             11.5447 │
│ time_total_s                 11.5447 │
│ training_iteration                 1 │
│ validation_accuracy           0.5474 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1075263)[0m [190]	train-mlogloss:1.16261	validation-mlogloss:1.15320
[36m(train_xgb_ray_tune pid=1075263)[0m [191]	train-mlogloss:1.16182	validation-mlogloss:1.15239
[36m(train_xgb_ray_tune pid=1075263)[0m [192]	train-mlogloss:1.16111	validation-mlogloss:1.15170
[36m(train_xgb_ray_tune pid=1075288)[0m [321]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075288)[0m [322]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075288)[0m [323]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075288)[0m [324]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075288)[0m [325]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075288)[0m [326]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075296)[0m [177]	train-mlogloss:1.01555	validation-mlogloss:1.02147
[36m(train_xgb_ray_tune pid=1075296)[0m [178]	train-mlogloss:1.01496	validation-mlogloss:1.02098
[36m(train_xgb_ray_tune pid=1075296)[0m [179]	train-mlogloss:1.01444	validation-mlogloss:1.02051
[36m(train_xgb_ray_tune pid=1075296)[0m [180]	train-mlogloss:1.01370	validation-mlogloss:1.01962
[36m(train_xgb_ray_tune pid=1075287)[0m [221]	train-mlogloss:1.12796	validation-mlogloss:1.11368
[36m(train_xgb_ray_tune pid=1075287)[0m [222]	train-mlogloss:1.12749	validation-mlogloss:1.11327
[36m(train_xgb_ray_tune pid=1075287)[0m [223]	train-mlogloss:1.12701	validation-mlogloss:1.11276
[36m(train_xgb_ray_tune pid=1075287)[0m [224]	train-mlogloss:1.12647	validation-mlogloss:1.11227
[36m(train_xgb_ray_tune pid=1075287)[0m [225]	train-mlogloss:1.12598	validation-mlogloss:1.11177
[36m(train_xgb_ray_tune pid=1075264)[0m [270]	train-mlogloss:1.01171	validation-mlogloss:1.00770
[36m(train_xgb_ray_tune pid=1075264)[0m [271]	train-mlogloss:1.01139	validation-mlogloss:1.00742
[36m(train_xgb_ray_tune pid=1075264)[0m [272]	train-mlogloss:1.01115	validation-mlogloss:1.00727
[36m(train_xgb_ray_tune pid=1075264)[0m [273]	train-mlogloss:1.01090	validation-mlogloss:1.00708
[36m(train_xgb_ray_tune pid=1075264)[0m [274]	train-mlogloss:1.01049	validation-mlogloss:1.00670
[36m(train_xgb_ray_tune pid=1075294)[0m [257]	train-mlogloss:1.07211	validation-mlogloss:1.06012
[36m(train_xgb_ray_tune pid=1075294)[0m [258]	train-mlogloss:1.07173	validation-mlogloss:1.05981
[36m(train_xgb_ray_tune pid=1075294)[0m [259]	train-mlogloss:1.07141	validation-mlogloss:1.05952
[36m(train_xgb_ray_tune pid=1075294)[0m [260]	train-mlogloss:1.07109	validation-mlogloss:1.05931
[36m(train_xgb_ray_tune pid=1075294)[0m [261]	train-mlogloss:1.07081	validation-mlogloss:1.05910
[36m(train_xgb_ray_tune pid=1075294)[0m [262]	train-mlogloss:1.07052	validation-mlogloss:1.05889
[36m(train_xgb_ray_tune pid=1075300)[0m [233]	train-mlogloss:0.95847	validation-mlogloss:0.97018
[36m(train_xgb_ray_tune pid=1075300)[0m [234]	train-mlogloss:0.95801	validation-mlogloss:0.96973
[36m(train_xgb_ray_tune pid=1075300)[0m [235]	train-mlogloss:0.95759	validation-mlogloss:0.96942
[36m(train_xgb_ray_tune pid=1075300)[0m [236]	train-mlogloss:0.95727	validation-mlogloss:0.96919
[36m(train_xgb_ray_tune pid=1075300)[0m [237]	train-mlogloss:0.95676	validation-mlogloss:0.96871
[36m(train_xgb_ray_tune pid=1075297)[0m [178]	train-mlogloss:1.18116	validation-mlogloss:1.16910
[36m(train_xgb_ray_tune pid=1075297)[0m [179]	train-mlogloss:1.18041	validation-mlogloss:1.16835
[36m(train_xgb_ray_tune pid=1075297)[0m [180]	train-mlogloss:1.17972	validation-mlogloss:1.16764
[36m(train_xgb_ray_tune pid=1075297)[0m [181]	train-mlogloss:1.17895	validation-mlogloss:1.16679
[36m(train_xgb_ray_tune pid=1075289)[0m [154]	train-mlogloss:1.17311	validation-mlogloss:1.16713
[36m(train_xgb_ray_tune pid=1075289)[0m [155]	train-mlogloss:1.17221	validation-mlogloss:1.16625
[36m(train_xgb_ray_tune pid=1075289)[0m [156]	train-mlogloss:1.17126	validation-mlogloss:1.16538
[36m(train_xgb_ray_tune pid=1075291)[0m [299]	train-mlogloss:1.25965	validation-mlogloss:1.25136
[36m(train_xgb_ray_tune pid=1075293)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 2x across cluster][0m
[36m(train_xgb_ray_tune pid=1075293)[0m   _log_deprecation_warning([32m [repeated 2x across cluster][0m
[36m(train_xgb_ray_tune pid=1075291)[0m [300]	train-mlogloss:1.25955	validation-mlogloss:1.25126
[36m(train_xgb_ray_tune pid=1075291)[0m [301]	train-mlogloss:1.25944	validation-mlogloss:1.25115
[36m(train_xgb_ray_tune pid=1075291)[0m [302]	train-mlogloss:1.25944	validation-mlogloss:1.25115
[36m(train_xgb_ray_tune pid=1075291)[0m [303]	train-mlogloss:1.25933	validation-mlogloss:1.25104
[36m(train_xgb_ray_tune pid=1075291)[0m [304]	train-mlogloss:1.25922	validation-mlogloss:1.25092
[36m(train_xgb_ray_tune pid=1075291)[0m [305]	train-mlogloss:1.25912	validation-mlogloss:1.25080
[36m(train_xgb_ray_tune pid=1075292)[0m [161]	train-mlogloss:1.13676	validation-mlogloss:1.13979
[36m(train_xgb_ray_tune pid=1075292)[0m [162]	train-mlogloss:1.13578	validation-mlogloss:1.13879
[36m(train_xgb_ray_tune pid=1075292)[0m [163]	train-mlogloss:1.13484	validation-mlogloss:1.13795

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:23. Total running time: 14s
[36m(train_xgb_ray_tune pid=1075295)[0m [262]	train-mlogloss:1.03306	validation-mlogloss:1.02730
[36m(train_xgb_ray_tune pid=1075295)[0m [263]	train-mlogloss:1.03253	validation-mlogloss:1.02680
[36m(train_xgb_ray_tune pid=1075295)[0m [264]	train-mlogloss:1.03212	validation-mlogloss:1.02639
[36m(train_xgb_ray_tune pid=1075295)[0m [265]	train-mlogloss:1.03166	validation-mlogloss:1.02585
[36m(train_xgb_ray_tune pid=1075295)[0m [266]	train-mlogloss:1.03126	validation-mlogloss:1.02555
[36m(train_xgb_ray_tune pid=1075270)[0m [192]	train-mlogloss:1.07363	validation-mlogloss:1.06030
[36m(train_xgb_ray_tune pid=1075270)[0m [193]	train-mlogloss:1.07299	validation-mlogloss:1.05973
[36m(train_xgb_ray_tune pid=1075270)[0m [194]	train-mlogloss:1.07239	validation-mlogloss:1.05918
[36m(train_xgb_ray_tune pid=1075270)[0m [195]	train-mlogloss:1.07173	validation-mlogloss:1.05861
[36m(train_xgb_ray_tune pid=1075299)[0m [300]	train-mlogloss:1.05199	validation-mlogloss:1.04667
[36m(train_xgb_ray_tune pid=1075299)[0m [301]	train-mlogloss:1.05199	validation-mlogloss:1.04667
[36m(train_xgb_ray_tune pid=1075299)[0m [302]	train-mlogloss:1.05199	validation-mlogloss:1.04667
[36m(train_xgb_ray_tune pid=1075299)[0m [303]	train-mlogloss:1.05191	validation-mlogloss:1.04665
[36m(train_xgb_ray_tune pid=1075299)[0m [304]	train-mlogloss:1.05179	validation-mlogloss:1.04656
[36m(train_xgb_ray_tune pid=1075299)[0m [305]	train-mlogloss:1.05179	validation-mlogloss:1.04656
[36m(train_xgb_ray_tune pid=1075299)[0m [306]	train-mlogloss:1.05179	validation-mlogloss:1.04656
[36m(train_xgb_ray_tune pid=1075299)[0m [307]	train-mlogloss:1.05179	validation-mlogloss:1.04656
[36m(train_xgb_ray_tune pid=1075301)[0m [220]	train-mlogloss:1.09004	validation-mlogloss:1.08342
[36m(train_xgb_ray_tune pid=1075301)[0m [221]	train-mlogloss:1.08938	validation-mlogloss:1.08277
[36m(train_xgb_ray_tune pid=1075301)[0m [222]	train-mlogloss:1.08874	validation-mlogloss:1.08224
[36m(train_xgb_ray_tune pid=1075301)[0m [223]	train-mlogloss:1.08807	validation-mlogloss:1.08158
[36m(train_xgb_ray_tune pid=1075262)[0m [256]	train-mlogloss:0.97234	validation-mlogloss:0.97832
[36m(train_xgb_ray_tune pid=1075263)[0m [193]	train-mlogloss:1.16043	validation-mlogloss:1.15103
[36m(train_xgb_ray_tune pid=1075288)[0m [327]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075288)[0m [328]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075296)[0m [181]	train-mlogloss:1.01304	validation-mlogloss:1.01909
[36m(train_xgb_ray_tune pid=1075264)[0m [275]	train-mlogloss:1.01021	validation-mlogloss:1.00648
[36m(train_xgb_ray_tune pid=1075300)[0m [238]	train-mlogloss:0.95627	validation-mlogloss:0.96836
[36m(train_xgb_ray_tune pid=1075297)[0m [182]	train-mlogloss:1.17820	validation-mlogloss:1.16601
[36m(train_xgb_ray_tune pid=1075295)[0m [267]	train-mlogloss:1.03078	validation-mlogloss:1.02498
[36m(train_xgb_ray_tune pid=1075301)[0m [224]	train-mlogloss:1.08742	validation-mlogloss:1.08101
[36m(train_xgb_ray_tune pid=1075262)[0m [257]	train-mlogloss:0.97183	validation-mlogloss:0.97773
[36m(train_xgb_ray_tune pid=1075287)[0m [226]	train-mlogloss:1.12572	validation-mlogloss:1.11151
[36m(train_xgb_ray_tune pid=1075294)[0m [263]	train-mlogloss:1.07023	validation-mlogloss:1.05863
[36m(train_xgb_ray_tune pid=1075289)[0m [157]	train-mlogloss:1.17036	validation-mlogloss:1.16446
[36m(train_xgb_ray_tune pid=1075291)[0m [306]	train-mlogloss:1.25901	validation-mlogloss:1.25068
[36m(train_xgb_ray_tune pid=1075270)[0m [196]	train-mlogloss:1.07112	validation-mlogloss:1.05799
[36m(train_xgb_ray_tune pid=1075299)[0m [308]	train-mlogloss:1.05179	validation-mlogloss:1.04656
[36m(train_xgb_ray_tune pid=1075288)[0m [329]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075264)[0m [276]	train-mlogloss:1.00989	validation-mlogloss:1.00630
[36m(train_xgb_ray_tune pid=1075291)[0m [307]	train-mlogloss:1.25901	validation-mlogloss:1.25068
[36m(train_xgb_ray_tune pid=1075263)[0m [194]	train-mlogloss:1.15977	validation-mlogloss:1.15033
[36m(train_xgb_ray_tune pid=1075287)[0m [227]	train-mlogloss:1.12536	validation-mlogloss:1.11119
[36m(train_xgb_ray_tune pid=1075294)[0m [264]	train-mlogloss:1.07001	validation-mlogloss:1.05849
[36m(train_xgb_ray_tune pid=1075300)[0m [239]	train-mlogloss:0.95586	validation-mlogloss:0.96816
[36m(train_xgb_ray_tune pid=1075297)[0m [183]	train-mlogloss:1.17750	validation-mlogloss:1.16527
[36m(train_xgb_ray_tune pid=1075295)[0m [268]	train-mlogloss:1.03036	validation-mlogloss:1.02460
[36m(train_xgb_ray_tune pid=1075301)[0m [225]	train-mlogloss:1.08680	validation-mlogloss:1.08038
[36m(train_xgb_ray_tune pid=1075262)[0m [258]	train-mlogloss:0.97134	validation-mlogloss:0.97745
[36m(train_xgb_ray_tune pid=1075288)[0m [330]	train-mlogloss:1.25559	validation-mlogloss:1.24498
[36m(train_xgb_ray_tune pid=1075296)[0m [182]	train-mlogloss:1.01219	validation-mlogloss:1.01829
[36m(train_xgb_ray_tune pid=1075291)[0m [308]	train-mlogloss:1.25889	validation-mlogloss:1.25056
[36m(train_xgb_ray_tune pid=1075270)[0m [197]	train-mlogloss:1.07052	validation-mlogloss:1.05743
[36m(train_xgb_ray_tune pid=1075264)[0m [277]	train-mlogloss:1.00959	validation-mlogloss:1.00604
[36m(train_xgb_ray_tune pid=1075292)[0m [164]	train-mlogloss:1.13389	validation-mlogloss:1.13704
[36m(train_xgb_ray_tune pid=1075299)[0m [309]	train-mlogloss:1.05179	validation-mlogloss:1.04656

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:23. Total running time: 14s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             11.6877 │
│ time_total_s                 11.6877 │
│ training_iteration                 1 │
│ validation_accuracy          0.41081 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1075294)[0m [265]	train-mlogloss:1.06953	validation-mlogloss:1.05810
[36m(train_xgb_ray_tune pid=1075289)[0m [158]	train-mlogloss:1.16946	validation-mlogloss:1.16353
[36m(train_xgb_ray_tune pid=1075295)[0m [269]	train-mlogloss:1.03004	validation-mlogloss:1.02435

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:23. Total running time: 14s
[36m(train_xgb_ray_tune pid=1075287)[0m [228]	train-mlogloss:1.12494	validation-mlogloss:1.11076
[36m(train_xgb_ray_tune pid=1075300)[0m [240]	train-mlogloss:0.95537	validation-mlogloss:0.96793
[36m(train_xgb_ray_tune pid=1075297)[0m [184]	train-mlogloss:1.17682	validation-mlogloss:1.16458
[36m(train_xgb_ray_tune pid=1075291)[0m [309]	train-mlogloss:1.25878	validation-mlogloss:1.25044
[36m(train_xgb_ray_tune pid=1075263)[0m [195]	train-mlogloss:1.15904	validation-mlogloss:1.14954
[36m(train_xgb_ray_tune pid=1075296)[0m [183]	train-mlogloss:1.01148	validation-mlogloss:1.01784
[36m(train_xgb_ray_tune pid=1075264)[0m [278]	train-mlogloss:1.00928	validation-mlogloss:1.00582
[36m(train_xgb_ray_tune pid=1075299)[0m [310]	train-mlogloss:1.05179	validation-mlogloss:1.04656
[36m(train_xgb_ray_tune pid=1075301)[0m [226]	train-mlogloss:1.08609	validation-mlogloss:1.07969
[36m(train_xgb_ray_tune pid=1075294)[0m [266]	train-mlogloss:1.06921	validation-mlogloss:1.05778
[36m(train_xgb_ray_tune pid=1075291)[0m [310]	train-mlogloss:1.25866	validation-mlogloss:1.25029
[36m(train_xgb_ray_tune pid=1075270)[0m [198]	train-mlogloss:1.06990	validation-mlogloss:1.05678
[36m(train_xgb_ray_tune pid=1075262)[0m [259]	train-mlogloss:0.97094	validation-mlogloss:0.97704
[36m(train_xgb_ray_tune pid=1075287)[0m [229]	train-mlogloss:1.12453	validation-mlogloss:1.11031
[36m(train_xgb_ray_tune pid=1075264)[0m [279]	train-mlogloss:1.00887	validation-mlogloss:1.00559
[36m(train_xgb_ray_tune pid=1075300)[0m [241]	train-mlogloss:0.95480	validation-mlogloss:0.96762
[36m(train_xgb_ray_tune pid=1075297)[0m [185]	train-mlogloss:1.17612	validation-mlogloss:1.16398
[36m(train_xgb_ray_tune pid=1075289)[0m [159]	train-mlogloss:1.16853	validation-mlogloss:1.16262
[36m(train_xgb_ray_tune pid=1075291)[0m [311]	train-mlogloss:1.25854	validation-mlogloss:1.25016
[36m(train_xgb_ray_tune pid=1075292)[0m [165]	train-mlogloss:1.13284	validation-mlogloss:1.13599
[36m(train_xgb_ray_tune pid=1075295)[0m [270]	train-mlogloss:1.02971	validation-mlogloss:1.02411
[36m(train_xgb_ray_tune pid=1075299)[0m [311]	train-mlogloss:1.05179	validation-mlogloss:1.04656
[36m(train_xgb_ray_tune pid=1075301)[0m [227]	train-mlogloss:1.08537	validation-mlogloss:1.07901
[36m(train_xgb_ray_tune pid=1075262)[0m [260]	train-mlogloss:0.97046	validation-mlogloss:0.97680
[36m(train_xgb_ray_tune pid=1075263)[0m [196]	train-mlogloss:1.15837	validation-mlogloss:1.14879
[36m(train_xgb_ray_tune pid=1075296)[0m [184]	train-mlogloss:1.01079	validation-mlogloss:1.01714
[36m(train_xgb_ray_tune pid=1075264)[0m [280]	train-mlogloss:1.00854	validation-mlogloss:1.00541
[36m(train_xgb_ray_tune pid=1075294)[0m [267]	train-mlogloss:1.06875	validation-mlogloss:1.05745
[36m(train_xgb_ray_tune pid=1075300)[0m [242]	train-mlogloss:0.95433	validation-mlogloss:0.96724
[36m(train_xgb_ray_tune pid=1075295)[0m [271]	train-mlogloss:1.02940	validation-mlogloss:1.02387
[36m(train_xgb_ray_tune pid=1075270)[0m [199]	train-mlogloss:1.06940	validation-mlogloss:1.05630
[36m(train_xgb_ray_tune pid=1075299)[0m [312]	train-mlogloss:1.05161	validation-mlogloss:1.04642
[36m(train_xgb_ray_tune pid=1075301)[0m [228]	train-mlogloss:1.08479	validation-mlogloss:1.07849
[36m(train_xgb_ray_tune pid=1075294)[0m [268]	train-mlogloss:1.06854	validation-mlogloss:1.05732
[36m(train_xgb_ray_tune pid=1075297)[0m [186]	train-mlogloss:1.17558	validation-mlogloss:1.16343
[36m(train_xgb_ray_tune pid=1075291)[0m [312]	train-mlogloss:1.25843	validation-mlogloss:1.25005
[36m(train_xgb_ray_tune pid=1075292)[0m [166]	train-mlogloss:1.13177	validation-mlogloss:1.13497
[36m(train_xgb_ray_tune pid=1075287)[0m [230]	train-mlogloss:1.12404	validation-mlogloss:1.10987
[36m(train_xgb_ray_tune pid=1075296)[0m [185]	train-mlogloss:1.01016	validation-mlogloss:1.01671
[36m(train_xgb_ray_tune pid=1075294)[0m [269]	train-mlogloss:1.06825	validation-mlogloss:1.05710
[36m(train_xgb_ray_tune pid=1075289)[0m [160]	train-mlogloss:1.16757	validation-mlogloss:1.16163
[36m(train_xgb_ray_tune pid=1075295)[0m [272]	train-mlogloss:1.02903	validation-mlogloss:1.02360
[36m(train_xgb_ray_tune pid=1075270)[0m [200]	train-mlogloss:1.06880	validation-mlogloss:1.05578
[36m(train_xgb_ray_tune pid=1075299)[0m [313]	train-mlogloss:1.05161	validation-mlogloss:1.04642
[36m(train_xgb_ray_tune pid=1075301)[0m [229]	train-mlogloss:1.08420	validation-mlogloss:1.07800
[36m(train_xgb_ray_tune pid=1075262)[0m [261]	train-mlogloss:0.97001	validation-mlogloss:0.97641
[36m(train_xgb_ray_tune pid=1075263)[0m [197]	train-mlogloss:1.15762	validation-mlogloss:1.14803
[36m(train_xgb_ray_tune pid=1075287)[0m [231]	train-mlogloss:1.12355	validation-mlogloss:1.10943
[36m(train_xgb_ray_tune pid=1075264)[0m [281]	train-mlogloss:1.00828	validation-mlogloss:1.00525
[36m(train_xgb_ray_tune pid=1075300)[0m [243]	train-mlogloss:0.95375	validation-mlogloss:0.96694
[36m(train_xgb_ray_tune pid=1075297)[0m [187]	train-mlogloss:1.17493	validation-mlogloss:1.16271
[36m(train_xgb_ray_tune pid=1075291)[0m [313]	train-mlogloss:1.25833	validation-mlogloss:1.24993
[36m(train_xgb_ray_tune pid=1075294)[0m [270]	train-mlogloss:1.06794	validation-mlogloss:1.05690
[36m(train_xgb_ray_tune pid=1075292)[0m [167]	train-mlogloss:1.13083	validation-mlogloss:1.13401
[36m(train_xgb_ray_tune pid=1075299)[0m [314]	train-mlogloss:1.05148	validation-mlogloss:1.04634
[36m(train_xgb_ray_tune pid=1075301)[0m [230]	train-mlogloss:1.08357	validation-mlogloss:1.07745
[36m(train_xgb_ray_tune pid=1075296)[0m [186]	train-mlogloss:1.00968	validation-mlogloss:1.01631
[36m(train_xgb_ray_tune pid=1075291)[0m [314]	train-mlogloss:1.25822	validation-mlogloss:1.24982
[36m(train_xgb_ray_tune pid=1075295)[0m [273]	train-mlogloss:1.02865	validation-mlogloss:1.02336
[36m(train_xgb_ray_tune pid=1075262)[0m [262]	train-mlogloss:0.96947	validation-mlogloss:0.97607
[36m(train_xgb_ray_tune pid=1075287)[0m [232]	train-mlogloss:1.12320	validation-mlogloss:1.10907
[36m(train_xgb_ray_tune pid=1075264)[0m [282]	train-mlogloss:1.00804	validation-mlogloss:1.00505
[36m(train_xgb_ray_tune pid=1075294)[0m [271]	train-mlogloss:1.06756	validation-mlogloss:1.05659
[36m(train_xgb_ray_tune pid=1075300)[0m [244]	train-mlogloss:0.95320	validation-mlogloss:0.96669
[36m(train_xgb_ray_tune pid=1075270)[0m [201]	train-mlogloss:1.06817	validation-mlogloss:1.05524
[36m(train_xgb_ray_tune pid=1075301)[0m [231]	train-mlogloss:1.08292	validation-mlogloss:1.07676
[36m(train_xgb_ray_tune pid=1075297)[0m [188]	train-mlogloss:1.17435	validation-mlogloss:1.16208
[36m(train_xgb_ray_tune pid=1075289)[0m [161]	train-mlogloss:1.16664	validation-mlogloss:1.16067
[36m(train_xgb_ray_tune pid=1075299)[0m [315]	train-mlogloss:1.05148	validation-mlogloss:1.04634
[36m(train_xgb_ray_tune pid=1075263)[0m [198]	train-mlogloss:1.15689	validation-mlogloss:1.14727
[36m(train_xgb_ray_tune pid=1075291)[0m [315]	train-mlogloss:1.25822	validation-mlogloss:1.24982
[36m(train_xgb_ray_tune pid=1075295)[0m [274]	train-mlogloss:1.02828	validation-mlogloss:1.02300
[36m(train_xgb_ray_tune pid=1075296)[0m [187]	train-mlogloss:1.00908	validation-mlogloss:1.01573
[36m(train_xgb_ray_tune pid=1075287)[0m [233]	train-mlogloss:1.12278	validation-mlogloss:1.10868
[36m(train_xgb_ray_tune pid=1075264)[0m [283]	train-mlogloss:1.00778	validation-mlogloss:1.00483
[36m(train_xgb_ray_tune pid=1075294)[0m [272]	train-mlogloss:1.06720	validation-mlogloss:1.05628
[36m(train_xgb_ray_tune pid=1075300)[0m [245]	train-mlogloss:0.95284	validation-mlogloss:0.96645
[36m(train_xgb_ray_tune pid=1075297)[0m [189]	train-mlogloss:1.17368	validation-mlogloss:1.16144
[36m(train_xgb_ray_tune pid=1075292)[0m [168]	train-mlogloss:1.12991	validation-mlogloss:1.13316
[36m(train_xgb_ray_tune pid=1075299)[0m [316]	train-mlogloss:1.05148	validation-mlogloss:1.04634
[36m(train_xgb_ray_tune pid=1075301)[0m [232]	train-mlogloss:1.08221	validation-mlogloss:1.07600
[36m(train_xgb_ray_tune pid=1075262)[0m [263]	train-mlogloss:0.96899	validation-mlogloss:0.97562
[36m(train_xgb_ray_tune pid=1075291)[0m [316]	train-mlogloss:1.25811	validation-mlogloss:1.24970
[36m(train_xgb_ray_tune pid=1075270)[0m [202]	train-mlogloss:1.06752	validation-mlogloss:1.05454
[36m(train_xgb_ray_tune pid=1075294)[0m [273]	train-mlogloss:1.06699	validation-mlogloss:1.05610
[36m(train_xgb_ray_tune pid=1075295)[0m [275]	train-mlogloss:1.02796	validation-mlogloss:1.02269
[36m(train_xgb_ray_tune pid=1075301)[0m [233]	train-mlogloss:1.08153	validation-mlogloss:1.07529
[36m(train_xgb_ray_tune pid=1075263)[0m [199]	train-mlogloss:1.15625	validation-mlogloss:1.14655
[36m(train_xgb_ray_tune pid=1075287)[0m [234]	train-mlogloss:1.12242	validation-mlogloss:1.10831
[36m(train_xgb_ray_tune pid=1075264)[0m [284]	train-mlogloss:1.00745	validation-mlogloss:1.00463
[36m(train_xgb_ray_tune pid=1075297)[0m [190]	train-mlogloss:1.17293	validation-mlogloss:1.16061
[36m(train_xgb_ray_tune pid=1075289)[0m [162]	train-mlogloss:1.16579	validation-mlogloss:1.15981
[36m(train_xgb_ray_tune pid=1075299)[0m [317]	train-mlogloss:1.05148	validation-mlogloss:1.04634
[36m(train_xgb_ray_tune pid=1075262)[0m [264]	train-mlogloss:0.96859	validation-mlogloss:0.97526
[36m(train_xgb_ray_tune pid=1075296)[0m [188]	train-mlogloss:1.00842	validation-mlogloss:1.01516
[36m(train_xgb_ray_tune pid=1075294)[0m [274]	train-mlogloss:1.06670	validation-mlogloss:1.05590
[36m(train_xgb_ray_tune pid=1075300)[0m [246]	train-mlogloss:0.95232	validation-mlogloss:0.96595
[36m(train_xgb_ray_tune pid=1075291)[0m [317]	train-mlogloss:1.25799	validation-mlogloss:1.24957
[36m(train_xgb_ray_tune pid=1075287)[0m [235]	train-mlogloss:1.12202	validation-mlogloss:1.10792
[36m(train_xgb_ray_tune pid=1075299)[0m [318]	train-mlogloss:1.05148	validation-mlogloss:1.04634
[36m(train_xgb_ray_tune pid=1075301)[0m [234]	train-mlogloss:1.08091	validation-mlogloss:1.07481
[36m(train_xgb_ray_tune pid=1075264)[0m [285]	train-mlogloss:1.00714	validation-mlogloss:1.00425
[36m(train_xgb_ray_tune pid=1075294)[0m [275]	train-mlogloss:1.06640	validation-mlogloss:1.05563
[36m(train_xgb_ray_tune pid=1075300)[0m [247]	train-mlogloss:0.95191	validation-mlogloss:0.96555
[36m(train_xgb_ray_tune pid=1075297)[0m [191]	train-mlogloss:1.17242	validation-mlogloss:1.16011
[36m(train_xgb_ray_tune pid=1075291)[0m [318]	train-mlogloss:1.25788	validation-mlogloss:1.24946
[36m(train_xgb_ray_tune pid=1075292)[0m [169]	train-mlogloss:1.12893	validation-mlogloss:1.13217
[36m(train_xgb_ray_tune pid=1075295)[0m [276]	train-mlogloss:1.02754	validation-mlogloss:1.02228
[36m(train_xgb_ray_tune pid=1075270)[0m [203]	train-mlogloss:1.06690	validation-mlogloss:1.05393
[36m(train_xgb_ray_tune pid=1075262)[0m [265]	train-mlogloss:0.96810	validation-mlogloss:0.97473
[36m(train_xgb_ray_tune pid=1075263)[0m [200]	train-mlogloss:1.15553	validation-mlogloss:1.14578

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:24. Total running time: 14s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             11.6466 │
│ time_total_s                 11.6466 │
│ training_iteration                 1 │
│ validation_accuracy          0.53511 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1075296)[0m [189]	train-mlogloss:1.00770	validation-mlogloss:1.01457
[36m(train_xgb_ray_tune pid=1075287)[0m [236]	train-mlogloss:1.12165	validation-mlogloss:1.10753
[36m(train_xgb_ray_tune pid=1075294)[0m [276]	train-mlogloss:1.06612	validation-mlogloss:1.05534
[36m(train_xgb_ray_tune pid=1075297)[0m [192]	train-mlogloss:1.17177	validation-mlogloss:1.15952
[36m(train_xgb_ray_tune pid=1075289)[0m [163]	train-mlogloss:1.16489	validation-mlogloss:1.15893
[36m(train_xgb_ray_tune pid=1075295)[0m [277]	train-mlogloss:1.02692	validation-mlogloss:1.02174
[36m(train_xgb_ray_tune pid=1075299)[0m [319]	train-mlogloss:1.05148	validation-mlogloss:1.04634
[36m(train_xgb_ray_tune pid=1075301)[0m [235]	train-mlogloss:1.08024	validation-mlogloss:1.07427
[36m(train_xgb_ray_tune pid=1075287)[0m [237]	train-mlogloss:1.12129	validation-mlogloss:1.10724
[36m(train_xgb_ray_tune pid=1075264)[0m [286]	train-mlogloss:1.00677	validation-mlogloss:1.00400
[36m(train_xgb_ray_tune pid=1075291)[0m [319]	train-mlogloss:1.25778	validation-mlogloss:1.24935
[36m(train_xgb_ray_tune pid=1075292)[0m [170]	train-mlogloss:1.12804	validation-mlogloss:1.13134
[36m(train_xgb_ray_tune pid=1075270)[0m [204]	train-mlogloss:1.06622	validation-mlogloss:1.05329

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:24. Total running time: 14s
[36m(train_xgb_ray_tune pid=1075299)[0m [320]	train-mlogloss:1.05148	validation-mlogloss:1.04634
[36m(train_xgb_ray_tune pid=1075301)[0m [236]	train-mlogloss:1.07959	validation-mlogloss:1.07357
[36m(train_xgb_ray_tune pid=1075262)[0m [266]	train-mlogloss:0.96764	validation-mlogloss:0.97447
[36m(train_xgb_ray_tune pid=1075294)[0m [277]	train-mlogloss:1.06584	validation-mlogloss:1.05506
[36m(train_xgb_ray_tune pid=1075300)[0m [248]	train-mlogloss:0.95153	validation-mlogloss:0.96514
[36m(train_xgb_ray_tune pid=1075296)[0m [190]	train-mlogloss:1.00715	validation-mlogloss:1.01411
[36m(train_xgb_ray_tune pid=1075287)[0m [238]	train-mlogloss:1.12097	validation-mlogloss:1.10694
[36m(train_xgb_ray_tune pid=1075297)[0m [193]	train-mlogloss:1.17122	validation-mlogloss:1.15900
[36m(train_xgb_ray_tune pid=1075291)[0m [320]	train-mlogloss:1.25778	validation-mlogloss:1.24935
[36m(train_xgb_ray_tune pid=1075295)[0m [278]	train-mlogloss:1.02660	validation-mlogloss:1.02145
[36m(train_xgb_ray_tune pid=1075299)[0m [321]	train-mlogloss:1.05148	validation-mlogloss:1.04634
[36m(train_xgb_ray_tune pid=1075263)[0m [201]	train-mlogloss:1.15484	validation-mlogloss:1.14503
[36m(train_xgb_ray_tune pid=1075264)[0m [287]	train-mlogloss:1.00645	validation-mlogloss:1.00372
[36m(train_xgb_ray_tune pid=1075294)[0m [278]	train-mlogloss:1.06556	validation-mlogloss:1.05489
[36m(train_xgb_ray_tune pid=1075300)[0m [249]	train-mlogloss:0.95105	validation-mlogloss:0.96481
[36m(train_xgb_ray_tune pid=1075301)[0m [237]	train-mlogloss:1.07897	validation-mlogloss:1.07295
[36m(train_xgb_ray_tune pid=1075270)[0m [205]	train-mlogloss:1.06568	validation-mlogloss:1.05281
[36m(train_xgb_ray_tune pid=1075262)[0m [267]	train-mlogloss:0.96718	validation-mlogloss:0.97412
[36m(train_xgb_ray_tune pid=1075287)[0m [239]	train-mlogloss:1.12061	validation-mlogloss:1.10658
[36m(train_xgb_ray_tune pid=1075297)[0m [194]	train-mlogloss:1.17050	validation-mlogloss:1.15827
[36m(train_xgb_ray_tune pid=1075289)[0m [164]	train-mlogloss:1.16406	validation-mlogloss:1.15810
[36m(train_xgb_ray_tune pid=1075291)[0m [321]	train-mlogloss:1.25778	validation-mlogloss:1.24935
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[36m(train_xgb_ray_tune pid=1075270)[0m [257]	train-mlogloss:1.03924	validation-mlogloss:1.02898
[36m(train_xgb_ray_tune pid=1075270)[0m [258]	train-mlogloss:1.03886	validation-mlogloss:1.02871
[36m(train_xgb_ray_tune pid=1075270)[0m [259]	train-mlogloss:1.03830	validation-mlogloss:1.02820
[36m(train_xgb_ray_tune pid=1075270)[0m [260]	train-mlogloss:1.03794	validation-mlogloss:1.02803
[36m(train_xgb_ray_tune pid=1075270)[0m [261]	train-mlogloss:1.03754	validation-mlogloss:1.02775
[36m(train_xgb_ray_tune pid=1075301)[0m [308]	train-mlogloss:1.04007	validation-mlogloss:1.03716
[36m(train_xgb_ray_tune pid=1075301)[0m [309]	train-mlogloss:1.03965	validation-mlogloss:1.03672
[36m(train_xgb_ray_tune pid=1075301)[0m [310]	train-mlogloss:1.03920	validation-mlogloss:1.03630
[36m(train_xgb_ray_tune pid=1075301)[0m [311]	train-mlogloss:1.03871	validation-mlogloss:1.03584
[36m(train_xgb_ray_tune pid=1075301)[0m [312]	train-mlogloss:1.03827	validation-mlogloss:1.03536
[36m(train_xgb_ray_tune pid=1075301)[0m [313]	train-mlogloss:1.03782	validation-mlogloss:1.03482
[36m(train_xgb_ray_tune pid=1075301)[0m [314]	train-mlogloss:1.03736	validation-mlogloss:1.03441
[36m(train_xgb_ray_tune pid=1075287)[0m [330]	train-mlogloss:1.09231	validation-mlogloss:1.08073
[36m(train_xgb_ray_tune pid=1075264)[0m [359]	train-mlogloss:0.98817	validation-mlogloss:0.98887
[36m(train_xgb_ray_tune pid=1075294)[0m [376]	train-mlogloss:1.04572	validation-mlogloss:1.03756
[36m(train_xgb_ray_tune pid=1075300)[0m [322]	train-mlogloss:0.92781	validation-mlogloss:0.94992
[36m(train_xgb_ray_tune pid=1075297)[0m [252]	train-mlogloss:1.13817	validation-mlogloss:1.12515
[36m(train_xgb_ray_tune pid=1075292)[0m [220]	train-mlogloss:1.08471	validation-mlogloss:1.08996
[36m(train_xgb_ray_tune pid=1075301)[0m [315]	train-mlogloss:1.03691	validation-mlogloss:1.03403
[36m(train_xgb_ray_tune pid=1075262)[0m [341]	train-mlogloss:0.93820	validation-mlogloss:0.95264
[36m(train_xgb_ray_tune pid=1075263)[0m [252]	train-mlogloss:1.12299	validation-mlogloss:1.11249
[36m(train_xgb_ray_tune pid=1075289)[0m [208]	train-mlogloss:1.12869	validation-mlogloss:1.12224
[36m(train_xgb_ray_tune pid=1075295)[0m [348]	train-mlogloss:1.00678	validation-mlogloss:1.00474
[36m(train_xgb_ray_tune pid=1075270)[0m [262]	train-mlogloss:1.03720	validation-mlogloss:1.02742
[36m(train_xgb_ray_tune pid=1075296)[0m [251]	train-mlogloss:0.98007	validation-mlogloss:0.99259
[36m(train_xgb_ray_tune pid=1075264)[0m [360]	train-mlogloss:0.98799	validation-mlogloss:0.98882
[36m(train_xgb_ray_tune pid=1075294)[0m [377]	train-mlogloss:1.04564	validation-mlogloss:1.03752
[36m(train_xgb_ray_tune pid=1075300)[0m [323]	train-mlogloss:0.92755	validation-mlogloss:0.94978

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:25. Total running time: 16s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             13.5366 │
│ time_total_s                 13.5366 │
│ training_iteration                 1 │
│ validation_accuracy          0.60183 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1075287)[0m [331]	train-mlogloss:1.09214	validation-mlogloss:1.08056
[36m(train_xgb_ray_tune pid=1075301)[0m [316]	train-mlogloss:1.03647	validation-mlogloss:1.03353
[36m(train_xgb_ray_tune pid=1075263)[0m [253]	train-mlogloss:1.12234	validation-mlogloss:1.11179
[36m(train_xgb_ray_tune pid=1075297)[0m [253]	train-mlogloss:1.13773	validation-mlogloss:1.12466
[36m(train_xgb_ray_tune pid=1075295)[0m [349]	train-mlogloss:1.00664	validation-mlogloss:1.00462
[36m(train_xgb_ray_tune pid=1075270)[0m [263]	train-mlogloss:1.03691	validation-mlogloss:1.02712

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:25. Total running time: 16s
[36m(train_xgb_ray_tune pid=1075262)[0m [342]	train-mlogloss:0.93786	validation-mlogloss:0.95244
[36m(train_xgb_ray_tune pid=1075296)[0m [252]	train-mlogloss:0.97972	validation-mlogloss:0.99236

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:25. Total running time: 16s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             13.1527 │
│ time_total_s                 13.1527 │
│ training_iteration                 1 │
│ validation_accuracy          0.54073 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1075287)[0m [332]	train-mlogloss:1.09188	validation-mlogloss:1.08035
[36m(train_xgb_ray_tune pid=1075264)[0m [361]	train-mlogloss:0.98785	validation-mlogloss:0.98874
[36m(train_xgb_ray_tune pid=1075294)[0m [378]	train-mlogloss:1.04557	validation-mlogloss:1.03749
[36m(train_xgb_ray_tune pid=1075300)[0m [324]	train-mlogloss:0.92725	validation-mlogloss:0.94974
[36m(train_xgb_ray_tune pid=1075289)[0m [209]	train-mlogloss:1.12797	validation-mlogloss:1.12148
[36m(train_xgb_ray_tune pid=1075292)[0m [221]	train-mlogloss:1.08391	validation-mlogloss:1.08920
[36m(train_xgb_ray_tune pid=1075301)[0m [317]	train-mlogloss:1.03605	validation-mlogloss:1.03316
[36m(train_xgb_ray_tune pid=1075294)[0m [379]	train-mlogloss:1.04557	validation-mlogloss:1.03749
[36m(train_xgb_ray_tune pid=1075300)[0m [325]	train-mlogloss:0.92707	validation-mlogloss:0.94965
[36m(train_xgb_ray_tune pid=1075295)[0m [350]	train-mlogloss:1.00636	validation-mlogloss:1.00435
[36m(train_xgb_ray_tune pid=1075270)[0m [264]	train-mlogloss:1.03658	validation-mlogloss:1.02681

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:25. Total running time: 16s
[36m(train_xgb_ray_tune pid=1075262)[0m [343]	train-mlogloss:0.93750	validation-mlogloss:0.95228
[36m(train_xgb_ray_tune pid=1075263)[0m [254]	train-mlogloss:1.12189	validation-mlogloss:1.11130
[36m(train_xgb_ray_tune pid=1075296)[0m [253]	train-mlogloss:0.97952	validation-mlogloss:0.99214
[36m(train_xgb_ray_tune pid=1075287)[0m [333]	train-mlogloss:1.09150	validation-mlogloss:1.08005
[36m(train_xgb_ray_tune pid=1075264)[0m [362]	train-mlogloss:0.98769	validation-mlogloss:0.98857
[36m(train_xgb_ray_tune pid=1075294)[0m [380]	train-mlogloss:1.04549	validation-mlogloss:1.03745
[36m(train_xgb_ray_tune pid=1075297)[0m [254]	train-mlogloss:1.13721	validation-mlogloss:1.12407
[36m(train_xgb_ray_tune pid=1075301)[0m [318]	train-mlogloss:1.03561	validation-mlogloss:1.03272
[36m(train_xgb_ray_tune pid=1075262)[0m [344]	train-mlogloss:0.93716	validation-mlogloss:0.95196
[36m(train_xgb_ray_tune pid=1075262)[0m [345]	train-mlogloss:0.93684	validation-mlogloss:0.95186
[36m(train_xgb_ray_tune pid=1075262)[0m [346]	train-mlogloss:0.93642	validation-mlogloss:0.95160
[36m(train_xgb_ray_tune pid=1075262)[0m [347]	train-mlogloss:0.93611	validation-mlogloss:0.95138
[36m(train_xgb_ray_tune pid=1075262)[0m [348]	train-mlogloss:0.93577	validation-mlogloss:0.95125
[36m(train_xgb_ray_tune pid=1075262)[0m [349]	train-mlogloss:0.93543	validation-mlogloss:0.95106
[36m(train_xgb_ray_tune pid=1075262)[0m [350]	train-mlogloss:0.93516	validation-mlogloss:0.95085
[36m(train_xgb_ray_tune pid=1075263)[0m [255]	train-mlogloss:1.12139	validation-mlogloss:1.11077
[36m(train_xgb_ray_tune pid=1075263)[0m [256]	train-mlogloss:1.12087	validation-mlogloss:1.11023
[36m(train_xgb_ray_tune pid=1075263)[0m [257]	train-mlogloss:1.12037	validation-mlogloss:1.10979
[36m(train_xgb_ray_tune pid=1075263)[0m [258]	train-mlogloss:1.11986	validation-mlogloss:1.10930
[36m(train_xgb_ray_tune pid=1075296)[0m [254]	train-mlogloss:0.97913	validation-mlogloss:0.99183
[36m(train_xgb_ray_tune pid=1075296)[0m [255]	train-mlogloss:0.97870	validation-mlogloss:0.99142
[36m(train_xgb_ray_tune pid=1075296)[0m [256]	train-mlogloss:0.97841	validation-mlogloss:0.99118
[36m(train_xgb_ray_tune pid=1075296)[0m [257]	train-mlogloss:0.97820	validation-mlogloss:0.99103
[36m(train_xgb_ray_tune pid=1075296)[0m [258]	train-mlogloss:0.97800	validation-mlogloss:0.99082
[36m(train_xgb_ray_tune pid=1075287)[0m [334]	train-mlogloss:1.09132	validation-mlogloss:1.07993
[36m(train_xgb_ray_tune pid=1075287)[0m [335]	train-mlogloss:1.09109	validation-mlogloss:1.07969
[36m(train_xgb_ray_tune pid=1075287)[0m [336]	train-mlogloss:1.09084	validation-mlogloss:1.07949
[36m(train_xgb_ray_tune pid=1075287)[0m [337]	train-mlogloss:1.09066	validation-mlogloss:1.07930
[36m(train_xgb_ray_tune pid=1075287)[0m [338]	train-mlogloss:1.09049	validation-mlogloss:1.07913
[36m(train_xgb_ray_tune pid=1075264)[0m [363]	train-mlogloss:0.98740	validation-mlogloss:0.98847
[36m(train_xgb_ray_tune pid=1075264)[0m [364]	train-mlogloss:0.98724	validation-mlogloss:0.98825
[36m(train_xgb_ray_tune pid=1075264)[0m [365]	train-mlogloss:0.98705	validation-mlogloss:0.98809
[36m(train_xgb_ray_tune pid=1075264)[0m [366]	train-mlogloss:0.98686	validation-mlogloss:0.98791
[36m(train_xgb_ray_tune pid=1075264)[0m [367]	train-mlogloss:0.98663	validation-mlogloss:0.98778
[36m(train_xgb_ray_tune pid=1075264)[0m [368]	train-mlogloss:0.98644	validation-mlogloss:0.98760
[36m(train_xgb_ray_tune pid=1075294)[0m [381]	train-mlogloss:1.04549	validation-mlogloss:1.03745
[36m(train_xgb_ray_tune pid=1075294)[0m [382]	train-mlogloss:1.04549	validation-mlogloss:1.03745
[36m(train_xgb_ray_tune pid=1075294)[0m [383]	train-mlogloss:1.04549	validation-mlogloss:1.03745
[36m(train_xgb_ray_tune pid=1075294)[0m [384]	train-mlogloss:1.04549	validation-mlogloss:1.03745
[36m(train_xgb_ray_tune pid=1075294)[0m [385]	train-mlogloss:1.04541	validation-mlogloss:1.03743
[36m(train_xgb_ray_tune pid=1075294)[0m [386]	train-mlogloss:1.04533	validation-mlogloss:1.03738
[36m(train_xgb_ray_tune pid=1075294)[0m [387]	train-mlogloss:1.04517	validation-mlogloss:1.03722
[36m(train_xgb_ray_tune pid=1075294)[0m [388]	train-mlogloss:1.04517	validation-mlogloss:1.03722
[36m(train_xgb_ray_tune pid=1075294)[0m [389]	train-mlogloss:1.04509	validation-mlogloss:1.03717
[36m(train_xgb_ray_tune pid=1075294)[0m [390]	train-mlogloss:1.04501	validation-mlogloss:1.03713
[36m(train_xgb_ray_tune pid=1075300)[0m [326]	train-mlogloss:0.92678	validation-mlogloss:0.94947
[36m(train_xgb_ray_tune pid=1075300)[0m [327]	train-mlogloss:0.92652	validation-mlogloss:0.94944
[36m(train_xgb_ray_tune pid=1075300)[0m [328]	train-mlogloss:0.92615	validation-mlogloss:0.94929
[36m(train_xgb_ray_tune pid=1075300)[0m [329]	train-mlogloss:0.92594	validation-mlogloss:0.94919
[36m(train_xgb_ray_tune pid=1075300)[0m [330]	train-mlogloss:0.92566	validation-mlogloss:0.94890
[36m(train_xgb_ray_tune pid=1075300)[0m [331]	train-mlogloss:0.92545	validation-mlogloss:0.94882
[36m(train_xgb_ray_tune pid=1075300)[0m [332]	train-mlogloss:0.92531	validation-mlogloss:0.94862
[36m(train_xgb_ray_tune pid=1075300)[0m [333]	train-mlogloss:0.92503	validation-mlogloss:0.94865
[36m(train_xgb_ray_tune pid=1075300)[0m [334]	train-mlogloss:0.92484	validation-mlogloss:0.94855
[36m(train_xgb_ray_tune pid=1075297)[0m [255]	train-mlogloss:1.13669	validation-mlogloss:1.12353
[36m(train_xgb_ray_tune pid=1075297)[0m [256]	train-mlogloss:1.13625	validation-mlogloss:1.12312
[36m(train_xgb_ray_tune pid=1075297)[0m [257]	train-mlogloss:1.13569	validation-mlogloss:1.12251
[36m(train_xgb_ray_tune pid=1075297)[0m [258]	train-mlogloss:1.13522	validation-mlogloss:1.12206
[36m(train_xgb_ray_tune pid=1075289)[0m [210]	train-mlogloss:1.12718	validation-mlogloss:1.12081
[36m(train_xgb_ray_tune pid=1075289)[0m [211]	train-mlogloss:1.12647	validation-mlogloss:1.12008
[36m(train_xgb_ray_tune pid=1075289)[0m [212]	train-mlogloss:1.12571	validation-mlogloss:1.11939
[36m(train_xgb_ray_tune pid=1075289)[0m [213]	train-mlogloss:1.12502	validation-mlogloss:1.11872
[36m(train_xgb_ray_tune pid=1075289)[0m [214]	train-mlogloss:1.12434	validation-mlogloss:1.11808
[36m(train_xgb_ray_tune pid=1075292)[0m [222]	train-mlogloss:1.08316	validation-mlogloss:1.08844
[36m(train_xgb_ray_tune pid=1075292)[0m [223]	train-mlogloss:1.08246	validation-mlogloss:1.08782
[36m(train_xgb_ray_tune pid=1075292)[0m [224]	train-mlogloss:1.08170	validation-mlogloss:1.08708
[36m(train_xgb_ray_tune pid=1075295)[0m [351]	train-mlogloss:1.00614	validation-mlogloss:1.00419
[36m(train_xgb_ray_tune pid=1075295)[0m [352]	train-mlogloss:1.00581	validation-mlogloss:1.00386
[36m(train_xgb_ray_tune pid=1075295)[0m [353]	train-mlogloss:1.00559	validation-mlogloss:1.00367
[36m(train_xgb_ray_tune pid=1075295)[0m [354]	train-mlogloss:1.00527	validation-mlogloss:1.00352
[36m(train_xgb_ray_tune pid=1075295)[0m [355]	train-mlogloss:1.00508	validation-mlogloss:1.00339
[36m(train_xgb_ray_tune pid=1075295)[0m [356]	train-mlogloss:1.00480	validation-mlogloss:1.00319
[36m(train_xgb_ray_tune pid=1075270)[0m [265]	train-mlogloss:1.03634	validation-mlogloss:1.02662
[36m(train_xgb_ray_tune pid=1075270)[0m [266]	train-mlogloss:1.03609	validation-mlogloss:1.02638
[36m(train_xgb_ray_tune pid=1075270)[0m [267]	train-mlogloss:1.03576	validation-mlogloss:1.02615
[36m(train_xgb_ray_tune pid=1075270)[0m [268]	train-mlogloss:1.03538	validation-mlogloss:1.02579
[36m(train_xgb_ray_tune pid=1075270)[0m [269]	train-mlogloss:1.03511	validation-mlogloss:1.02560
[36m(train_xgb_ray_tune pid=1075270)[0m [270]	train-mlogloss:1.03472	validation-mlogloss:1.02521
[36m(train_xgb_ray_tune pid=1075270)[0m [271]	train-mlogloss:1.03442	validation-mlogloss:1.02496
[36m(train_xgb_ray_tune pid=1075301)[0m [319]	train-mlogloss:1.03511	validation-mlogloss:1.03228
[36m(train_xgb_ray_tune pid=1075301)[0m [320]	train-mlogloss:1.03462	validation-mlogloss:1.03182
[36m(train_xgb_ray_tune pid=1075301)[0m [321]	train-mlogloss:1.03421	validation-mlogloss:1.03147
[36m(train_xgb_ray_tune pid=1075301)[0m [322]	train-mlogloss:1.03374	validation-mlogloss:1.03106
[36m(train_xgb_ray_tune pid=1075301)[0m [323]	train-mlogloss:1.03332	validation-mlogloss:1.03076
[36m(train_xgb_ray_tune pid=1075301)[0m [324]	train-mlogloss:1.03290	validation-mlogloss:1.03043
[36m(train_xgb_ray_tune pid=1075301)[0m [325]	train-mlogloss:1.03243	validation-mlogloss:1.02992
[36m(train_xgb_ray_tune pid=1075262)[0m [351]	train-mlogloss:0.93478	validation-mlogloss:0.95069
[36m(train_xgb_ray_tune pid=1075263)[0m [259]	train-mlogloss:1.11941	validation-mlogloss:1.10885
[36m(train_xgb_ray_tune pid=1075287)[0m [339]	train-mlogloss:1.09031	validation-mlogloss:1.07900
[36m(train_xgb_ray_tune pid=1075264)[0m [369]	train-mlogloss:0.98618	validation-mlogloss:0.98736
[36m(train_xgb_ray_tune pid=1075294)[0m [391]	train-mlogloss:1.04487	validation-mlogloss:1.03699
[36m(train_xgb_ray_tune pid=1075295)[0m [357]	train-mlogloss:1.00450	validation-mlogloss:1.00298
[36m(train_xgb_ray_tune pid=1075300)[0m [335]	train-mlogloss:0.92460	validation-mlogloss:0.94855
[36m(train_xgb_ray_tune pid=1075297)[0m [259]	train-mlogloss:1.13469	validation-mlogloss:1.12149
[36m(train_xgb_ray_tune pid=1075289)[0m [215]	train-mlogloss:1.12366	validation-mlogloss:1.11745
[36m(train_xgb_ray_tune pid=1075292)[0m [225]	train-mlogloss:1.08094	validation-mlogloss:1.08632
[36m(train_xgb_ray_tune pid=1075270)[0m [272]	train-mlogloss:1.03403	validation-mlogloss:1.02468
[36m(train_xgb_ray_tune pid=1075301)[0m [326]	train-mlogloss:1.03201	validation-mlogloss:1.02953
[36m(train_xgb_ray_tune pid=1075262)[0m [352]	train-mlogloss:0.93444	validation-mlogloss:0.95051
[36m(train_xgb_ray_tune pid=1075296)[0m [259]	train-mlogloss:0.97766	validation-mlogloss:0.99047
[36m(train_xgb_ray_tune pid=1075264)[0m [370]	train-mlogloss:0.98611	validation-mlogloss:0.98730
[36m(train_xgb_ray_tune pid=1075294)[0m [392]	train-mlogloss:1.04487	validation-mlogloss:1.03699
[36m(train_xgb_ray_tune pid=1075287)[0m [340]	train-mlogloss:1.09013	validation-mlogloss:1.07884
[36m(train_xgb_ray_tune pid=1075294)[0m [393]	train-mlogloss:1.04471	validation-mlogloss:1.03687
[36m(train_xgb_ray_tune pid=1075295)[0m [358]	train-mlogloss:1.00423	validation-mlogloss:1.00275
[36m(train_xgb_ray_tune pid=1075270)[0m [273]	train-mlogloss:1.03365	validation-mlogloss:1.02441
[36m(train_xgb_ray_tune pid=1075301)[0m [327]	train-mlogloss:1.03160	validation-mlogloss:1.02909
[36m(train_xgb_ray_tune pid=1075262)[0m [353]	train-mlogloss:0.93411	validation-mlogloss:0.95024
[36m(train_xgb_ray_tune pid=1075263)[0m [260]	train-mlogloss:1.11889	validation-mlogloss:1.10835
[36m(train_xgb_ray_tune pid=1075264)[0m [371]	train-mlogloss:0.98598	validation-mlogloss:0.98718
[36m(train_xgb_ray_tune pid=1075300)[0m [336]	train-mlogloss:0.92422	validation-mlogloss:0.94834
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[36m(train_xgb_ray_tune pid=1075300)[0m [392]	train-mlogloss:0.91466	validation-mlogloss:0.94206
[36m(train_xgb_ray_tune pid=1075289)[0m [251]	train-mlogloss:1.09937	validation-mlogloss:1.09314
[36m(train_xgb_ray_tune pid=1075292)[0m [245]	train-mlogloss:1.06604	validation-mlogloss:1.07248
[36m(train_xgb_ray_tune pid=1075270)[0m [323]	train-mlogloss:1.01857	validation-mlogloss:1.01207
[36m(train_xgb_ray_tune pid=1075301)[0m [376]	train-mlogloss:1.01197	validation-mlogloss:1.01282
[36m(train_xgb_ray_tune pid=1075262)[0m [403]	train-mlogloss:0.91972	validation-mlogloss:0.94029
[36m(train_xgb_ray_tune pid=1075297)[0m [287]	train-mlogloss:1.12240	validation-mlogloss:1.10919
[36m(train_xgb_ray_tune pid=1075295)[0m [394]	train-mlogloss:0.99585	validation-mlogloss:0.99608
[36m(train_xgb_ray_tune pid=1075301)[0m [377]	train-mlogloss:1.01161	validation-mlogloss:1.01260
[36m(train_xgb_ray_tune pid=1075262)[0m [404]	train-mlogloss:0.91950	validation-mlogloss:0.94030
[36m(train_xgb_ray_tune pid=1075287)[0m [374]	train-mlogloss:1.08256	validation-mlogloss:1.07276
[36m(train_xgb_ray_tune pid=1075294)[0m [449]	train-mlogloss:1.04173	validation-mlogloss:1.03421
[36m(train_xgb_ray_tune pid=1075300)[0m [393]	train-mlogloss:0.91450	validation-mlogloss:0.94192
[36m(train_xgb_ray_tune pid=1075289)[0m [252]	train-mlogloss:1.09880	validation-mlogloss:1.09247
[36m(train_xgb_ray_tune pid=1075270)[0m [324]	train-mlogloss:1.01832	validation-mlogloss:1.01191
[36m(train_xgb_ray_tune pid=1075263)[0m [285]	train-mlogloss:1.10625	validation-mlogloss:1.09580
[36m(train_xgb_ray_tune pid=1075296)[0m [292]	train-mlogloss:0.96794	validation-mlogloss:0.98286
[36m(train_xgb_ray_tune pid=1075294)[0m [450]	train-mlogloss:1.04173	validation-mlogloss:1.03421
[36m(train_xgb_ray_tune pid=1075300)[0m [394]	train-mlogloss:0.91435	validation-mlogloss:0.94172
[36m(train_xgb_ray_tune pid=1075270)[0m [325]	train-mlogloss:1.01812	validation-mlogloss:1.01171
[36m(train_xgb_ray_tune pid=1075301)[0m [378]	train-mlogloss:1.01128	validation-mlogloss:1.01222
[36m(train_xgb_ray_tune pid=1075262)[0m [405]	train-mlogloss:0.91924	validation-mlogloss:0.94014
[36m(train_xgb_ray_tune pid=1075295)[0m [395]	train-mlogloss:0.99560	validation-mlogloss:0.99584
[36m(train_xgb_ray_tune pid=1075287)[0m [375]	train-mlogloss:1.08240	validation-mlogloss:1.07266
[36m(train_xgb_ray_tune pid=1075294)[0m [451]	train-mlogloss:1.04166	validation-mlogloss:1.03414
[36m(train_xgb_ray_tune pid=1075300)[0m [395]	train-mlogloss:0.91425	validation-mlogloss:0.94169
[36m(train_xgb_ray_tune pid=1075297)[0m [288]	train-mlogloss:1.12193	validation-mlogloss:1.10876
[36m(train_xgb_ray_tune pid=1075292)[0m [246]	train-mlogloss:1.06531	validation-mlogloss:1.07178
[36m(train_xgb_ray_tune pid=1075262)[0m [406]	train-mlogloss:0.91894	validation-mlogloss:0.94000
[36m(train_xgb_ray_tune pid=1075263)[0m [286]	train-mlogloss:1.10582	validation-mlogloss:1.09535
[36m(train_xgb_ray_tune pid=1075296)[0m [293]	train-mlogloss:0.96763	validation-mlogloss:0.98252
[36m(train_xgb_ray_tune pid=1075270)[0m [326]	train-mlogloss:1.01784	validation-mlogloss:1.01153
[36m(train_xgb_ray_tune pid=1075301)[0m [379]	train-mlogloss:1.01089	validation-mlogloss:1.01192
[36m(train_xgb_ray_tune pid=1075294)[0m [452]	train-mlogloss:1.04166	validation-mlogloss:1.03414
[36m(train_xgb_ray_tune pid=1075300)[0m [396]	train-mlogloss:0.91414	validation-mlogloss:0.94163
[36m(train_xgb_ray_tune pid=1075289)[0m [253]	train-mlogloss:1.09816	validation-mlogloss:1.09185
[36m(train_xgb_ray_tune pid=1075295)[0m [396]	train-mlogloss:0.99530	validation-mlogloss:0.99561
[36m(train_xgb_ray_tune pid=1075270)[0m [327]	train-mlogloss:1.01752	validation-mlogloss:1.01137
[36m(train_xgb_ray_tune pid=1075301)[0m [380]	train-mlogloss:1.01057	validation-mlogloss:1.01168
[36m(train_xgb_ray_tune pid=1075262)[0m [407]	train-mlogloss:0.91867	validation-mlogloss:0.93979
[36m(train_xgb_ray_tune pid=1075287)[0m [376]	train-mlogloss:1.08211	validation-mlogloss:1.07238
[36m(train_xgb_ray_tune pid=1075294)[0m [453]	train-mlogloss:1.04158	validation-mlogloss:1.03407
[36m(train_xgb_ray_tune pid=1075300)[0m [397]	train-mlogloss:0.91401	validation-mlogloss:0.94154
[36m(train_xgb_ray_tune pid=1075296)[0m [294]	train-mlogloss:0.96734	validation-mlogloss:0.98233
[36m(train_xgb_ray_tune pid=1075297)[0m [289]	train-mlogloss:1.12159	validation-mlogloss:1.10840
[36m(train_xgb_ray_tune pid=1075295)[0m [397]	train-mlogloss:0.99514	validation-mlogloss:0.99556
[36m(train_xgb_ray_tune pid=1075289)[0m [254]	train-mlogloss:1.09758	validation-mlogloss:1.09126
[36m(train_xgb_ray_tune pid=1075292)[0m [247]	train-mlogloss:1.06456	validation-mlogloss:1.07110
[36m(train_xgb_ray_tune pid=1075270)[0m [328]	train-mlogloss:1.01724	validation-mlogloss:1.01117
[36m(train_xgb_ray_tune pid=1075301)[0m [381]	train-mlogloss:1.01020	validation-mlogloss:1.01142
[36m(train_xgb_ray_tune pid=1075262)[0m [408]	train-mlogloss:0.91839	validation-mlogloss:0.93960
[36m(train_xgb_ray_tune pid=1075263)[0m [287]	train-mlogloss:1.10529	validation-mlogloss:1.09485
[36m(train_xgb_ray_tune pid=1075287)[0m [377]	train-mlogloss:1.08194	validation-mlogloss:1.07228
[36m(train_xgb_ray_tune pid=1075294)[0m [454]	train-mlogloss:1.04151	validation-mlogloss:1.03403
[36m(train_xgb_ray_tune pid=1075300)[0m [398]	train-mlogloss:0.91385	validation-mlogloss:0.94138
[36m(train_xgb_ray_tune pid=1075262)[0m [409]	train-mlogloss:0.91811	validation-mlogloss:0.93937
[36m(train_xgb_ray_tune pid=1075262)[0m [410]	train-mlogloss:0.91787	validation-mlogloss:0.93917
[36m(train_xgb_ray_tune pid=1075262)[0m [411]	train-mlogloss:0.91767	validation-mlogloss:0.93901
[36m(train_xgb_ray_tune pid=1075262)[0m [412]	train-mlogloss:0.91740	validation-mlogloss:0.93877
[36m(train_xgb_ray_tune pid=1075262)[0m [413]	train-mlogloss:0.91717	validation-mlogloss:0.93859
[36m(train_xgb_ray_tune pid=1075262)[0m [414]	train-mlogloss:0.91694	validation-mlogloss:0.93841
[36m(train_xgb_ray_tune pid=1075262)[0m [415]	train-mlogloss:0.91666	validation-mlogloss:0.93822
[36m(train_xgb_ray_tune pid=1075262)[0m [416]	train-mlogloss:0.91647	validation-mlogloss:0.93807
[36m(train_xgb_ray_tune pid=1075262)[0m [417]	train-mlogloss:0.91626	validation-mlogloss:0.93797
[36m(train_xgb_ray_tune pid=1075263)[0m [288]	train-mlogloss:1.10486	validation-mlogloss:1.09441
[36m(train_xgb_ray_tune pid=1075263)[0m [289]	train-mlogloss:1.10442	validation-mlogloss:1.09393
[36m(train_xgb_ray_tune pid=1075263)[0m [290]	train-mlogloss:1.10400	validation-mlogloss:1.09350
[36m(train_xgb_ray_tune pid=1075263)[0m [291]	train-mlogloss:1.10359	validation-mlogloss:1.09303
[36m(train_xgb_ray_tune pid=1075296)[0m [295]	train-mlogloss:0.96712	validation-mlogloss:0.98217
[36m(train_xgb_ray_tune pid=1075296)[0m [296]	train-mlogloss:0.96687	validation-mlogloss:0.98198
[36m(train_xgb_ray_tune pid=1075296)[0m [297]	train-mlogloss:0.96659	validation-mlogloss:0.98169
[36m(train_xgb_ray_tune pid=1075296)[0m [298]	train-mlogloss:0.96628	validation-mlogloss:0.98148
[36m(train_xgb_ray_tune pid=1075296)[0m [299]	train-mlogloss:0.96602	validation-mlogloss:0.98127
[36m(train_xgb_ray_tune pid=1075296)[0m [300]	train-mlogloss:0.96589	validation-mlogloss:0.98115
[36m(train_xgb_ray_tune pid=1075287)[0m [378]	train-mlogloss:1.08179	validation-mlogloss:1.07215
[36m(train_xgb_ray_tune pid=1075287)[0m [379]	train-mlogloss:1.08163	validation-mlogloss:1.07200
[36m(train_xgb_ray_tune pid=1075287)[0m [380]	train-mlogloss:1.08155	validation-mlogloss:1.07191
[36m(train_xgb_ray_tune pid=1075287)[0m [381]	train-mlogloss:1.08124	validation-mlogloss:1.07165
[36m(train_xgb_ray_tune pid=1075287)[0m [382]	train-mlogloss:1.08110	validation-mlogloss:1.07152
[36m(train_xgb_ray_tune pid=1075287)[0m [383]	train-mlogloss:1.08095	validation-mlogloss:1.07141
[36m(train_xgb_ray_tune pid=1075294)[0m [455]	train-mlogloss:1.04151	validation-mlogloss:1.03403
[36m(train_xgb_ray_tune pid=1075294)[0m [456]	train-mlogloss:1.04135	validation-mlogloss:1.03387
[36m(train_xgb_ray_tune pid=1075294)[0m [457]	train-mlogloss:1.04135	validation-mlogloss:1.03387
[36m(train_xgb_ray_tune pid=1075294)[0m [458]	train-mlogloss:1.04135	validation-mlogloss:1.03387
[36m(train_xgb_ray_tune pid=1075294)[0m [459]	train-mlogloss:1.04120	validation-mlogloss:1.03372
[36m(train_xgb_ray_tune pid=1075294)[0m [460]	train-mlogloss:1.04120	validation-mlogloss:1.03372
[36m(train_xgb_ray_tune pid=1075294)[0m [461]	train-mlogloss:1.04120	validation-mlogloss:1.03372
[36m(train_xgb_ray_tune pid=1075300)[0m [399]	train-mlogloss:0.91360	validation-mlogloss:0.94114
[36m(train_xgb_ray_tune pid=1075300)[0m [400]	train-mlogloss:0.91349	validation-mlogloss:0.94112
[36m(train_xgb_ray_tune pid=1075300)[0m [401]	train-mlogloss:0.91336	validation-mlogloss:0.94104
[36m(train_xgb_ray_tune pid=1075300)[0m [402]	train-mlogloss:0.91322	validation-mlogloss:0.94097
[36m(train_xgb_ray_tune pid=1075300)[0m [403]	train-mlogloss:0.91310	validation-mlogloss:0.94093
[36m(train_xgb_ray_tune pid=1075300)[0m [404]	train-mlogloss:0.91292	validation-mlogloss:0.94075
[36m(train_xgb_ray_tune pid=1075300)[0m [405]	train-mlogloss:0.91283	validation-mlogloss:0.94065
[36m(train_xgb_ray_tune pid=1075300)[0m [406]	train-mlogloss:0.91273	validation-mlogloss:0.94063
[36m(train_xgb_ray_tune pid=1075300)[0m [407]	train-mlogloss:0.91255	validation-mlogloss:0.94039
[36m(train_xgb_ray_tune pid=1075300)[0m [408]	train-mlogloss:0.91241	validation-mlogloss:0.94027
[36m(train_xgb_ray_tune pid=1075300)[0m [409]	train-mlogloss:0.91226	validation-mlogloss:0.94017
[36m(train_xgb_ray_tune pid=1075297)[0m [290]	train-mlogloss:1.12123	validation-mlogloss:1.10808
[36m(train_xgb_ray_tune pid=1075297)[0m [291]	train-mlogloss:1.12078	validation-mlogloss:1.10771
[36m(train_xgb_ray_tune pid=1075297)[0m [292]	train-mlogloss:1.12045	validation-mlogloss:1.10735
[36m(train_xgb_ray_tune pid=1075297)[0m [293]	train-mlogloss:1.12000	validation-mlogloss:1.10695
[36m(train_xgb_ray_tune pid=1075297)[0m [294]	train-mlogloss:1.11965	validation-mlogloss:1.10659
[36m(train_xgb_ray_tune pid=1075289)[0m [255]	train-mlogloss:1.09702	validation-mlogloss:1.09070
[36m(train_xgb_ray_tune pid=1075289)[0m [256]	train-mlogloss:1.09645	validation-mlogloss:1.09012
[36m(train_xgb_ray_tune pid=1075289)[0m [257]	train-mlogloss:1.09591	validation-mlogloss:1.08958
[36m(train_xgb_ray_tune pid=1075289)[0m [258]	train-mlogloss:1.09528	validation-mlogloss:1.08889
[36m(train_xgb_ray_tune pid=1075289)[0m [259]	train-mlogloss:1.09470	validation-mlogloss:1.08838
[36m(train_xgb_ray_tune pid=1075289)[0m [260]	train-mlogloss:1.09412	validation-mlogloss:1.08778
[36m(train_xgb_ray_tune pid=1075292)[0m [248]	train-mlogloss:1.06385	validation-mlogloss:1.07045
[36m(train_xgb_ray_tune pid=1075292)[0m [249]	train-mlogloss:1.06312	validation-mlogloss:1.06980
[36m(train_xgb_ray_tune pid=1075292)[0m [250]	train-mlogloss:1.06244	validation-mlogloss:1.06923
[36m(train_xgb_ray_tune pid=1075295)[0m [398]	train-mlogloss:0.99494	validation-mlogloss:0.99542
[36m(train_xgb_ray_tune pid=1075295)[0m [399]	train-mlogloss:0.99475	validation-mlogloss:0.99525
[36m(train_xgb_ray_tune pid=1075295)[0m [400]	train-mlogloss:0.99451	validation-mlogloss:0.99499
[36m(train_xgb_ray_tune pid=1075295)[0m [401]	train-mlogloss:0.99435	validation-mlogloss:0.99495
[36m(train_xgb_ray_tune pid=1075295)[0m [402]	train-mlogloss:0.99410	validation-mlogloss:0.99469
[36m(train_xgb_ray_tune pid=1075295)[0m [403]	train-mlogloss:0.99382	validation-mlogloss:0.99453
[36m(train_xgb_ray_tune pid=1075295)[0m [404]	train-mlogloss:0.99358	validation-mlogloss:0.99438
[36m(train_xgb_ray_tune pid=1075270)[0m [329]	train-mlogloss:1.01696	validation-mlogloss:1.01098
[36m(train_xgb_ray_tune pid=1075270)[0m [330]	train-mlogloss:1.01664	validation-mlogloss:1.01074
[36m(train_xgb_ray_tune pid=1075270)[0m [331]	train-mlogloss:1.01640	validation-mlogloss:1.01059
[36m(train_xgb_ray_tune pid=1075270)[0m [332]	train-mlogloss:1.01615	validation-mlogloss:1.01031
[36m(train_xgb_ray_tune pid=1075270)[0m [333]	train-mlogloss:1.01584	validation-mlogloss:1.01006
[36m(train_xgb_ray_tune pid=1075270)[0m [334]	train-mlogloss:1.01560	validation-mlogloss:1.00991
[36m(train_xgb_ray_tune pid=1075270)[0m [335]	train-mlogloss:1.01536	validation-mlogloss:1.00975
[36m(train_xgb_ray_tune pid=1075270)[0m [336]	train-mlogloss:1.01511	validation-mlogloss:1.00963
[36m(train_xgb_ray_tune pid=1075270)[0m [337]	train-mlogloss:1.01491	validation-mlogloss:1.00947
[36m(train_xgb_ray_tune pid=1075301)[0m [382]	train-mlogloss:1.00979	validation-mlogloss:1.01106
[36m(train_xgb_ray_tune pid=1075301)[0m [383]	train-mlogloss:1.00945	validation-mlogloss:1.01077
[36m(train_xgb_ray_tune pid=1075301)[0m [384]	train-mlogloss:1.00908	validation-mlogloss:1.01039
[36m(train_xgb_ray_tune pid=1075301)[0m [385]	train-mlogloss:1.00868	validation-mlogloss:1.01001
[36m(train_xgb_ray_tune pid=1075301)[0m [386]	train-mlogloss:1.00828	validation-mlogloss:1.00960
[36m(train_xgb_ray_tune pid=1075301)[0m [387]	train-mlogloss:1.00793	validation-mlogloss:1.00936
[36m(train_xgb_ray_tune pid=1075301)[0m [388]	train-mlogloss:1.00755	validation-mlogloss:1.00910
[36m(train_xgb_ray_tune pid=1075301)[0m [389]	train-mlogloss:1.00721	validation-mlogloss:1.00875
[36m(train_xgb_ray_tune pid=1075301)[0m [390]	train-mlogloss:1.00683	validation-mlogloss:1.00844
[36m(train_xgb_ray_tune pid=1075262)[0m [418]	train-mlogloss:0.91604	validation-mlogloss:0.93780
[36m(train_xgb_ray_tune pid=1075263)[0m [292]	train-mlogloss:1.10313	validation-mlogloss:1.09255
[36m(train_xgb_ray_tune pid=1075294)[0m [462]	train-mlogloss:1.04113	validation-mlogloss:1.03368
[36m(train_xgb_ray_tune pid=1075289)[0m [261]	train-mlogloss:1.09360	validation-mlogloss:1.08723
[36m(train_xgb_ray_tune pid=1075270)[0m [338]	train-mlogloss:1.01467	validation-mlogloss:1.00933
[36m(train_xgb_ray_tune pid=1075292)[0m [251]	train-mlogloss:1.06174	validation-mlogloss:1.06859
[36m(train_xgb_ray_tune pid=1075301)[0m [391]	train-mlogloss:1.00647	validation-mlogloss:1.00811

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:26. Total running time: 17s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             14.4723 │
│ time_total_s                 14.4723 │
│ training_iteration                 1 │
│ validation_accuracy          0.62992 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1075296)[0m [301]	train-mlogloss:0.96568	validation-mlogloss:0.98099
[36m(train_xgb_ray_tune pid=1075287)[0m [384]	train-mlogloss:1.08068	validation-mlogloss:1.07117
[36m(train_xgb_ray_tune pid=1075300)[0m [410]	train-mlogloss:0.91204	validation-mlogloss:0.93993
[36m(train_xgb_ray_tune pid=1075297)[0m [295]	train-mlogloss:1.11921	validation-mlogloss:1.10618
[36m(train_xgb_ray_tune pid=1075295)[0m [405]	train-mlogloss:0.99335	validation-mlogloss:0.99416
[36m(train_xgb_ray_tune pid=1075270)[0m [339]	train-mlogloss:1.01439	validation-mlogloss:1.00912
[36m(train_xgb_ray_tune pid=1075262)[0m [419]	train-mlogloss:0.91578	validation-mlogloss:0.93767
[36m(train_xgb_ray_tune pid=1075294)[0m [463]	train-mlogloss:1.04098	validation-mlogloss:1.03356
[36m(train_xgb_ray_tune pid=1075300)[0m [411]	train-mlogloss:0.91194	validation-mlogloss:0.93991
[36m(train_xgb_ray_tune pid=1075289)[0m [262]	train-mlogloss:1.09304	validation-mlogloss:1.08666
[36m(train_xgb_ray_tune pid=1075301)[0m [392]	train-mlogloss:1.00613	validation-mlogloss:1.00780

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:26. Total running time: 17s
[36m(train_xgb_ray_tune pid=1075262)[0m [420]	train-mlogloss:0.91560	validation-mlogloss:0.93757
[36m(train_xgb_ray_tune pid=1075262)[0m [421]	train-mlogloss:0.91528	validation-mlogloss:0.93727
[36m(train_xgb_ray_tune pid=1075262)[0m [422]	train-mlogloss:0.91507	validation-mlogloss:0.93715
[36m(train_xgb_ray_tune pid=1075262)[0m [423]	train-mlogloss:0.91487	validation-mlogloss:0.93702
[36m(train_xgb_ray_tune pid=1075262)[0m [424]	train-mlogloss:0.91470	validation-mlogloss:0.93689
[36m(train_xgb_ray_tune pid=1075262)[0m [425]	train-mlogloss:0.91448	validation-mlogloss:0.93681
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[36m(train_xgb_ray_tune pid=1075289)[0m [316]	train-mlogloss:1.06461	validation-mlogloss:1.05960
[36m(train_xgb_ray_tune pid=1075262)[0m [492]	train-mlogloss:0.90118	validation-mlogloss:0.92796
[36m(train_xgb_ray_tune pid=1075296)[0m [364]	train-mlogloss:0.95222	validation-mlogloss:0.97024
[36m(train_xgb_ray_tune pid=1075297)[0m [367]	train-mlogloss:1.09496	validation-mlogloss:1.08264
[36m(train_xgb_ray_tune pid=1075263)[0m [341]	train-mlogloss:1.08198	validation-mlogloss:1.07175
[36m(train_xgb_ray_tune pid=1075287)[0m [483]	train-mlogloss:1.07327	validation-mlogloss:1.06482
[36m(train_xgb_ray_tune pid=1075294)[0m [546]	train-mlogloss:1.03862	validation-mlogloss:1.03178
[36m(train_xgb_ray_tune pid=1075300)[0m [520]	train-mlogloss:0.90116	validation-mlogloss:0.93197
[36m(train_xgb_ray_tune pid=1075292)[0m [301]	train-mlogloss:1.03048	validation-mlogloss:1.04010
[36m(train_xgb_ray_tune pid=1075295)[0m [472]	train-mlogloss:0.98256	validation-mlogloss:0.98560
[36m(train_xgb_ray_tune pid=1075270)[0m [413]	train-mlogloss:0.99995	validation-mlogloss:0.99864
[36m(train_xgb_ray_tune pid=1075301)[0m [455]	train-mlogloss:0.98593	validation-mlogloss:0.99079
[36m(train_xgb_ray_tune pid=1075296)[0m [365]	train-mlogloss:0.95207	validation-mlogloss:0.97011
[36m(train_xgb_ray_tune pid=1075300)[0m [521]	train-mlogloss:0.90109	validation-mlogloss:0.93193
[36m(train_xgb_ray_tune pid=1075297)[0m [368]	train-mlogloss:1.09471	validation-mlogloss:1.08235
[36m(train_xgb_ray_tune pid=1075287)[0m [484]	train-mlogloss:1.07319	validation-mlogloss:1.06480
[36m(train_xgb_ray_tune pid=1075294)[0m [547]	train-mlogloss:1.03862	validation-mlogloss:1.03178
[36m(train_xgb_ray_tune pid=1075262)[0m [493]	train-mlogloss:0.90093	validation-mlogloss:0.92776
[36m(train_xgb_ray_tune pid=1075262)[0m [494]	train-mlogloss:0.90080	validation-mlogloss:0.92767
[36m(train_xgb_ray_tune pid=1075262)[0m [495]	train-mlogloss:0.90068	validation-mlogloss:0.92761
[36m(train_xgb_ray_tune pid=1075262)[0m [496]	train-mlogloss:0.90050	validation-mlogloss:0.92753
[36m(train_xgb_ray_tune pid=1075262)[0m [497]	train-mlogloss:0.90037	validation-mlogloss:0.92743
[36m(train_xgb_ray_tune pid=1075262)[0m [498]	train-mlogloss:0.90020	validation-mlogloss:0.92733
[36m(train_xgb_ray_tune pid=1075263)[0m [342]	train-mlogloss:1.08166	validation-mlogloss:1.07143
[36m(train_xgb_ray_tune pid=1075263)[0m [343]	train-mlogloss:1.08130	validation-mlogloss:1.07111
[36m(train_xgb_ray_tune pid=1075263)[0m [344]	train-mlogloss:1.08093	validation-mlogloss:1.07071
[36m(train_xgb_ray_tune pid=1075263)[0m [345]	train-mlogloss:1.08050	validation-mlogloss:1.07033
[36m(train_xgb_ray_tune pid=1075263)[0m [346]	train-mlogloss:1.08014	validation-mlogloss:1.07004
[36m(train_xgb_ray_tune pid=1075296)[0m [366]	train-mlogloss:0.95192	validation-mlogloss:0.97010
[36m(train_xgb_ray_tune pid=1075296)[0m [367]	train-mlogloss:0.95172	validation-mlogloss:0.96995
[36m(train_xgb_ray_tune pid=1075296)[0m [368]	train-mlogloss:0.95162	validation-mlogloss:0.96982
[36m(train_xgb_ray_tune pid=1075296)[0m [369]	train-mlogloss:0.95146	validation-mlogloss:0.96962
[36m(train_xgb_ray_tune pid=1075296)[0m [370]	train-mlogloss:0.95123	validation-mlogloss:0.96943
[36m(train_xgb_ray_tune pid=1075296)[0m [371]	train-mlogloss:0.95097	validation-mlogloss:0.96919
[36m(train_xgb_ray_tune pid=1075296)[0m [372]	train-mlogloss:0.95081	validation-mlogloss:0.96902
[36m(train_xgb_ray_tune pid=1075287)[0m [485]	train-mlogloss:1.07319	validation-mlogloss:1.06480
[36m(train_xgb_ray_tune pid=1075287)[0m [486]	train-mlogloss:1.07319	validation-mlogloss:1.06480
[36m(train_xgb_ray_tune pid=1075287)[0m [487]	train-mlogloss:1.07319	validation-mlogloss:1.06480
[36m(train_xgb_ray_tune pid=1075287)[0m [488]	train-mlogloss:1.07312	validation-mlogloss:1.06474
[36m(train_xgb_ray_tune pid=1075294)[0m [548]	train-mlogloss:1.03849	validation-mlogloss:1.03162
[36m(train_xgb_ray_tune pid=1075294)[0m [549]	train-mlogloss:1.03849	validation-mlogloss:1.03162
[36m(train_xgb_ray_tune pid=1075294)[0m [550]	train-mlogloss:1.03848	validation-mlogloss:1.03162
[36m(train_xgb_ray_tune pid=1075294)[0m [551]	train-mlogloss:1.03848	validation-mlogloss:1.03162
[36m(train_xgb_ray_tune pid=1075294)[0m [552]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075294)[0m [553]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075300)[0m [522]	train-mlogloss:0.90109	validation-mlogloss:0.93194
[36m(train_xgb_ray_tune pid=1075300)[0m [523]	train-mlogloss:0.90109	validation-mlogloss:0.93193
[36m(train_xgb_ray_tune pid=1075300)[0m [524]	train-mlogloss:0.90106	validation-mlogloss:0.93191
[36m(train_xgb_ray_tune pid=1075300)[0m [525]	train-mlogloss:0.90098	validation-mlogloss:0.93187
[36m(train_xgb_ray_tune pid=1075300)[0m [526]	train-mlogloss:0.90098	validation-mlogloss:0.93187
[36m(train_xgb_ray_tune pid=1075300)[0m [527]	train-mlogloss:0.90098	validation-mlogloss:0.93187
[36m(train_xgb_ray_tune pid=1075300)[0m [528]	train-mlogloss:0.90092	validation-mlogloss:0.93189
[36m(train_xgb_ray_tune pid=1075300)[0m [529]	train-mlogloss:0.90092	validation-mlogloss:0.93189
[36m(train_xgb_ray_tune pid=1075300)[0m [530]	train-mlogloss:0.90092	validation-mlogloss:0.93188
[36m(train_xgb_ray_tune pid=1075300)[0m [531]	train-mlogloss:0.90084	validation-mlogloss:0.93177
[36m(train_xgb_ray_tune pid=1075300)[0m [532]	train-mlogloss:0.90076	validation-mlogloss:0.93178
[36m(train_xgb_ray_tune pid=1075300)[0m [533]	train-mlogloss:0.90073	validation-mlogloss:0.93175
[36m(train_xgb_ray_tune pid=1075297)[0m [369]	train-mlogloss:1.09439	validation-mlogloss:1.08205
[36m(train_xgb_ray_tune pid=1075297)[0m [370]	train-mlogloss:1.09407	validation-mlogloss:1.08174
[36m(train_xgb_ray_tune pid=1075297)[0m [371]	train-mlogloss:1.09379	validation-mlogloss:1.08144
[36m(train_xgb_ray_tune pid=1075297)[0m [372]	train-mlogloss:1.09352	validation-mlogloss:1.08121
[36m(train_xgb_ray_tune pid=1075297)[0m [373]	train-mlogloss:1.09329	validation-mlogloss:1.08099
[36m(train_xgb_ray_tune pid=1075297)[0m [374]	train-mlogloss:1.09299	validation-mlogloss:1.08074
[36m(train_xgb_ray_tune pid=1075297)[0m [375]	train-mlogloss:1.09265	validation-mlogloss:1.08049
[36m(train_xgb_ray_tune pid=1075297)[0m [376]	train-mlogloss:1.09241	validation-mlogloss:1.08027
[36m(train_xgb_ray_tune pid=1075297)[0m [377]	train-mlogloss:1.09217	validation-mlogloss:1.08000
[36m(train_xgb_ray_tune pid=1075289)[0m [317]	train-mlogloss:1.06413	validation-mlogloss:1.05917
[36m(train_xgb_ray_tune pid=1075289)[0m [318]	train-mlogloss:1.06374	validation-mlogloss:1.05885
[36m(train_xgb_ray_tune pid=1075289)[0m [319]	train-mlogloss:1.06325	validation-mlogloss:1.05832
[36m(train_xgb_ray_tune pid=1075289)[0m [320]	train-mlogloss:1.06283	validation-mlogloss:1.05787
[36m(train_xgb_ray_tune pid=1075289)[0m [321]	train-mlogloss:1.06243	validation-mlogloss:1.05754
[36m(train_xgb_ray_tune pid=1075292)[0m [302]	train-mlogloss:1.02991	validation-mlogloss:1.03963
[36m(train_xgb_ray_tune pid=1075292)[0m [303]	train-mlogloss:1.02932	validation-mlogloss:1.03916
[36m(train_xgb_ray_tune pid=1075292)[0m [304]	train-mlogloss:1.02874	validation-mlogloss:1.03871
[36m(train_xgb_ray_tune pid=1075292)[0m [305]	train-mlogloss:1.02817	validation-mlogloss:1.03815
[36m(train_xgb_ray_tune pid=1075292)[0m [306]	train-mlogloss:1.02766	validation-mlogloss:1.03771
[36m(train_xgb_ray_tune pid=1075292)[0m [307]	train-mlogloss:1.02707	validation-mlogloss:1.03721
[36m(train_xgb_ray_tune pid=1075295)[0m [473]	train-mlogloss:0.98235	validation-mlogloss:0.98549
[36m(train_xgb_ray_tune pid=1075295)[0m [474]	train-mlogloss:0.98223	validation-mlogloss:0.98537
[36m(train_xgb_ray_tune pid=1075295)[0m [475]	train-mlogloss:0.98202	validation-mlogloss:0.98519
[36m(train_xgb_ray_tune pid=1075295)[0m [476]	train-mlogloss:0.98189	validation-mlogloss:0.98505
[36m(train_xgb_ray_tune pid=1075295)[0m [477]	train-mlogloss:0.98184	validation-mlogloss:0.98501
[36m(train_xgb_ray_tune pid=1075295)[0m [478]	train-mlogloss:0.98167	validation-mlogloss:0.98486
[36m(train_xgb_ray_tune pid=1075295)[0m [479]	train-mlogloss:0.98155	validation-mlogloss:0.98480
[36m(train_xgb_ray_tune pid=1075270)[0m [414]	train-mlogloss:0.99980	validation-mlogloss:0.99857
[36m(train_xgb_ray_tune pid=1075270)[0m [415]	train-mlogloss:0.99968	validation-mlogloss:0.99854
[36m(train_xgb_ray_tune pid=1075270)[0m [416]	train-mlogloss:0.99948	validation-mlogloss:0.99833
[36m(train_xgb_ray_tune pid=1075270)[0m [417]	train-mlogloss:0.99929	validation-mlogloss:0.99813
[36m(train_xgb_ray_tune pid=1075270)[0m [418]	train-mlogloss:0.99914	validation-mlogloss:0.99804
[36m(train_xgb_ray_tune pid=1075270)[0m [419]	train-mlogloss:0.99894	validation-mlogloss:0.99785
[36m(train_xgb_ray_tune pid=1075270)[0m [420]	train-mlogloss:0.99880	validation-mlogloss:0.99782
[36m(train_xgb_ray_tune pid=1075301)[0m [456]	train-mlogloss:0.98566	validation-mlogloss:0.99062
[36m(train_xgb_ray_tune pid=1075301)[0m [457]	train-mlogloss:0.98540	validation-mlogloss:0.99035
[36m(train_xgb_ray_tune pid=1075301)[0m [458]	train-mlogloss:0.98511	validation-mlogloss:0.99003
[36m(train_xgb_ray_tune pid=1075301)[0m [459]	train-mlogloss:0.98483	validation-mlogloss:0.98990
[36m(train_xgb_ray_tune pid=1075301)[0m [460]	train-mlogloss:0.98453	validation-mlogloss:0.98961
[36m(train_xgb_ray_tune pid=1075301)[0m [461]	train-mlogloss:0.98421	validation-mlogloss:0.98933
[36m(train_xgb_ray_tune pid=1075262)[0m [499]	train-mlogloss:0.90007	validation-mlogloss:0.92729
[36m(train_xgb_ray_tune pid=1075296)[0m [373]	train-mlogloss:0.95062	validation-mlogloss:0.96882
[36m(train_xgb_ray_tune pid=1075294)[0m [554]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075300)[0m [534]	train-mlogloss:0.90073	validation-mlogloss:0.93175
[36m(train_xgb_ray_tune pid=1075297)[0m [378]	train-mlogloss:1.09190	validation-mlogloss:1.07977
[36m(train_xgb_ray_tune pid=1075292)[0m [308]	train-mlogloss:1.02652	validation-mlogloss:1.03670
[36m(train_xgb_ray_tune pid=1075295)[0m [480]	train-mlogloss:0.98143	validation-mlogloss:0.98473

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:27. Total running time: 18s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             15.6027 │
│ time_total_s                 15.6027 │
│ training_iteration                 1 │
│ validation_accuracy          0.59445 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:27. Total running time: 18s
[36m(train_xgb_ray_tune pid=1075262)[0m [500]	train-mlogloss:0.89995	validation-mlogloss:0.92718
[36m(train_xgb_ray_tune pid=1075262)[0m [501]	train-mlogloss:0.89971	validation-mlogloss:0.92702
[36m(train_xgb_ray_tune pid=1075262)[0m [502]	train-mlogloss:0.89959	validation-mlogloss:0.92691
[36m(train_xgb_ray_tune pid=1075262)[0m [503]	train-mlogloss:0.89945	validation-mlogloss:0.92692
[36m(train_xgb_ray_tune pid=1075262)[0m [504]	train-mlogloss:0.89931	validation-mlogloss:0.92683
[36m(train_xgb_ray_tune pid=1075262)[0m [505]	train-mlogloss:0.89920	validation-mlogloss:0.92675
[36m(train_xgb_ray_tune pid=1075263)[0m [347]	train-mlogloss:1.07979	validation-mlogloss:1.06973
[36m(train_xgb_ray_tune pid=1075263)[0m [348]	train-mlogloss:1.07943	validation-mlogloss:1.06936
[36m(train_xgb_ray_tune pid=1075263)[0m [349]	train-mlogloss:1.07907	validation-mlogloss:1.06908
[36m(train_xgb_ray_tune pid=1075263)[0m [350]	train-mlogloss:1.07872	validation-mlogloss:1.06871
[36m(train_xgb_ray_tune pid=1075263)[0m [351]	train-mlogloss:1.07828	validation-mlogloss:1.06828
[36m(train_xgb_ray_tune pid=1075296)[0m [374]	train-mlogloss:0.95041	validation-mlogloss:0.96868
[36m(train_xgb_ray_tune pid=1075296)[0m [375]	train-mlogloss:0.95031	validation-mlogloss:0.96863
[36m(train_xgb_ray_tune pid=1075296)[0m [376]	train-mlogloss:0.95007	validation-mlogloss:0.96854
[36m(train_xgb_ray_tune pid=1075296)[0m [377]	train-mlogloss:0.94994	validation-mlogloss:0.96838
[36m(train_xgb_ray_tune pid=1075296)[0m [378]	train-mlogloss:0.94966	validation-mlogloss:0.96818
[36m(train_xgb_ray_tune pid=1075296)[0m [379]	train-mlogloss:0.94955	validation-mlogloss:0.96807
[36m(train_xgb_ray_tune pid=1075296)[0m [380]	train-mlogloss:0.94939	validation-mlogloss:0.96799
[36m(train_xgb_ray_tune pid=1075296)[0m [381]	train-mlogloss:0.94924	validation-mlogloss:0.96784
[36m(train_xgb_ray_tune pid=1075294)[0m [555]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075294)[0m [556]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075294)[0m [557]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075294)[0m [558]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075294)[0m [559]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075294)[0m [560]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075294)[0m [561]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075294)[0m [562]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075294)[0m [563]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075294)[0m [564]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075294)[0m [565]	train-mlogloss:1.03841	validation-mlogloss:1.03157
[36m(train_xgb_ray_tune pid=1075300)[0m [535]	train-mlogloss:0.90053	validation-mlogloss:0.93162
[36m(train_xgb_ray_tune pid=1075300)[0m [536]	train-mlogloss:0.90050	validation-mlogloss:0.93155
[36m(train_xgb_ray_tune pid=1075300)[0m [537]	train-mlogloss:0.90050	validation-mlogloss:0.93155
[36m(train_xgb_ray_tune pid=1075300)[0m [538]	train-mlogloss:0.90047	validation-mlogloss:0.93148
[36m(train_xgb_ray_tune pid=1075300)[0m [539]	train-mlogloss:0.90040	validation-mlogloss:0.93148
[36m(train_xgb_ray_tune pid=1075300)[0m [540]	train-mlogloss:0.90040	validation-mlogloss:0.93148
[36m(train_xgb_ray_tune pid=1075300)[0m [541]	train-mlogloss:0.90040	validation-mlogloss:0.93148
[36m(train_xgb_ray_tune pid=1075300)[0m [542]	train-mlogloss:0.90027	validation-mlogloss:0.93146
[36m(train_xgb_ray_tune pid=1075300)[0m [543]	train-mlogloss:0.90020	validation-mlogloss:0.93142
[36m(train_xgb_ray_tune pid=1075300)[0m [544]	train-mlogloss:0.90006	validation-mlogloss:0.93138
[36m(train_xgb_ray_tune pid=1075300)[0m [545]	train-mlogloss:0.89996	validation-mlogloss:0.93126
[36m(train_xgb_ray_tune pid=1075297)[0m [379]	train-mlogloss:1.09165	validation-mlogloss:1.07954
[36m(train_xgb_ray_tune pid=1075297)[0m [380]	train-mlogloss:1.09142	validation-mlogloss:1.07931
[36m(train_xgb_ray_tune pid=1075297)[0m [381]	train-mlogloss:1.09124	validation-mlogloss:1.07914
[36m(train_xgb_ray_tune pid=1075297)[0m [382]	train-mlogloss:1.09092	validation-mlogloss:1.07883
[36m(train_xgb_ray_tune pid=1075297)[0m [383]	train-mlogloss:1.09069	validation-mlogloss:1.07863
[36m(train_xgb_ray_tune pid=1075297)[0m [384]	train-mlogloss:1.09047	validation-mlogloss:1.07842
[36m(train_xgb_ray_tune pid=1075297)[0m [385]	train-mlogloss:1.09024	validation-mlogloss:1.07818
[36m(train_xgb_ray_tune pid=1075297)[0m [386]	train-mlogloss:1.09001	validation-mlogloss:1.07795
[36m(train_xgb_ray_tune pid=1075297)[0m [387]	train-mlogloss:1.08979	validation-mlogloss:1.07775
[36m(train_xgb_ray_tune pid=1075289)[0m [322]	train-mlogloss:1.06195	validation-mlogloss:1.05710
[36m(train_xgb_ray_tune pid=1075289)[0m [323]	train-mlogloss:1.06153	validation-mlogloss:1.05674
[36m(train_xgb_ray_tune pid=1075289)[0m [324]	train-mlogloss:1.06112	validation-mlogloss:1.05638
[36m(train_xgb_ray_tune pid=1075289)[0m [325]	train-mlogloss:1.06074	validation-mlogloss:1.05604
[36m(train_xgb_ray_tune pid=1075289)[0m [326]	train-mlogloss:1.06021	validation-mlogloss:1.05553
[36m(train_xgb_ray_tune pid=1075292)[0m [309]	train-mlogloss:1.02592	validation-mlogloss:1.03619
[36m(train_xgb_ray_tune pid=1075292)[0m [310]	train-mlogloss:1.02537	validation-mlogloss:1.03571
[36m(train_xgb_ray_tune pid=1075292)[0m [311]	train-mlogloss:1.02482	validation-mlogloss:1.03520
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[36m(train_xgb_ray_tune pid=1075296)[0m [396]	train-mlogloss:0.94714	validation-mlogloss:0.96643
[36m(train_xgb_ray_tune pid=1075289)[0m [334]	train-mlogloss:1.05686	validation-mlogloss:1.05231
[36m(train_xgb_ray_tune pid=1075295)[0m [501]	train-mlogloss:0.97869	validation-mlogloss:0.98269
[36m(train_xgb_ray_tune pid=1075262)[0m [518]	train-mlogloss:0.89729	validation-mlogloss:0.92562
[36m(train_xgb_ray_tune pid=1075294)[0m [589]	train-mlogloss:1.03787	validation-mlogloss:1.03106
[36m(train_xgb_ray_tune pid=1075297)[0m [404]	train-mlogloss:1.08568	validation-mlogloss:1.07389
[36m(train_xgb_ray_tune pid=1075300)[0m [568]	train-mlogloss:0.89893	validation-mlogloss:0.93071
[36m(train_xgb_ray_tune pid=1075270)[0m [441]	train-mlogloss:0.99587	validation-mlogloss:0.99583
[36m(train_xgb_ray_tune pid=1075263)[0m [362]	train-mlogloss:1.07445	validation-mlogloss:1.06465
[36m(train_xgb_ray_tune pid=1075296)[0m [397]	train-mlogloss:0.94703	validation-mlogloss:0.96635
[36m(train_xgb_ray_tune pid=1075292)[0m [326]	train-mlogloss:1.01685	validation-mlogloss:1.02832
[36m(train_xgb_ray_tune pid=1075294)[0m [590]	train-mlogloss:1.03787	validation-mlogloss:1.03106
[36m(train_xgb_ray_tune pid=1075300)[0m [569]	train-mlogloss:0.89893	validation-mlogloss:0.93071
[36m(train_xgb_ray_tune pid=1075297)[0m [405]	train-mlogloss:1.08542	validation-mlogloss:1.07368
[36m(train_xgb_ray_tune pid=1075295)[0m [502]	train-mlogloss:0.97853	validation-mlogloss:0.98249
[36m(train_xgb_ray_tune pid=1075262)[0m [519]	train-mlogloss:0.89715	validation-mlogloss:0.92559
[36m(train_xgb_ray_tune pid=1075296)[0m [398]	train-mlogloss:0.94695	validation-mlogloss:0.96631
[36m(train_xgb_ray_tune pid=1075294)[0m [591]	train-mlogloss:1.03787	validation-mlogloss:1.03106
[36m(train_xgb_ray_tune pid=1075300)[0m [570]	train-mlogloss:0.89893	validation-mlogloss:0.93071
[36m(train_xgb_ray_tune pid=1075289)[0m [335]	train-mlogloss:1.05648	validation-mlogloss:1.05195
[36m(train_xgb_ray_tune pid=1075270)[0m [442]	train-mlogloss:0.99570	validation-mlogloss:0.99567
[36m(train_xgb_ray_tune pid=1075292)[0m [327]	train-mlogloss:1.01635	validation-mlogloss:1.02788
[36m(train_xgb_ray_tune pid=1075294)[0m [592]	train-mlogloss:1.03787	validation-mlogloss:1.03106
[36m(train_xgb_ray_tune pid=1075297)[0m [406]	train-mlogloss:1.08515	validation-mlogloss:1.07343
[36m(train_xgb_ray_tune pid=1075263)[0m [363]	train-mlogloss:1.07413	validation-mlogloss:1.06435
[36m(train_xgb_ray_tune pid=1075296)[0m [399]	train-mlogloss:0.94687	validation-mlogloss:0.96626
[36m(train_xgb_ray_tune pid=1075300)[0m [571]	train-mlogloss:0.89893	validation-mlogloss:0.93071
[36m(train_xgb_ray_tune pid=1075295)[0m [503]	train-mlogloss:0.97838	validation-mlogloss:0.98243

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:28. Total running time: 19s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             15.7545 │
│ time_total_s                 15.7545 │
│ training_iteration                 1 │
│ validation_accuracy          0.63413 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:28. Total running time: 19s
[36m(train_xgb_ray_tune pid=1075262)[0m [520]	train-mlogloss:0.89701	validation-mlogloss:0.92548
[36m(train_xgb_ray_tune pid=1075262)[0m [521]	train-mlogloss:0.89688	validation-mlogloss:0.92534
[36m(train_xgb_ray_tune pid=1075262)[0m [522]	train-mlogloss:0.89672	validation-mlogloss:0.92516
[36m(train_xgb_ray_tune pid=1075262)[0m [523]	train-mlogloss:0.89658	validation-mlogloss:0.92509
[36m(train_xgb_ray_tune pid=1075262)[0m [524]	train-mlogloss:0.89639	validation-mlogloss:0.92495
[36m(train_xgb_ray_tune pid=1075262)[0m [525]	train-mlogloss:0.89625	validation-mlogloss:0.92489
[36m(train_xgb_ray_tune pid=1075262)[0m [526]	train-mlogloss:0.89620	validation-mlogloss:0.92486
[36m(train_xgb_ray_tune pid=1075263)[0m [364]	train-mlogloss:1.07371	validation-mlogloss:1.06391
[36m(train_xgb_ray_tune pid=1075263)[0m [365]	train-mlogloss:1.07339	validation-mlogloss:1.06359
[36m(train_xgb_ray_tune pid=1075263)[0m [366]	train-mlogloss:1.07302	validation-mlogloss:1.06320
[36m(train_xgb_ray_tune pid=1075263)[0m [367]	train-mlogloss:1.07266	validation-mlogloss:1.06281
[36m(train_xgb_ray_tune pid=1075296)[0m [400]	train-mlogloss:0.94667	validation-mlogloss:0.96610
[36m(train_xgb_ray_tune pid=1075296)[0m [401]	train-mlogloss:0.94652	validation-mlogloss:0.96590
[36m(train_xgb_ray_tune pid=1075296)[0m [402]	train-mlogloss:0.94639	validation-mlogloss:0.96585
[36m(train_xgb_ray_tune pid=1075296)[0m [403]	train-mlogloss:0.94617	validation-mlogloss:0.96573
[36m(train_xgb_ray_tune pid=1075296)[0m [404]	train-mlogloss:0.94591	validation-mlogloss:0.96551
[36m(train_xgb_ray_tune pid=1075296)[0m [405]	train-mlogloss:0.94577	validation-mlogloss:0.96548
[36m(train_xgb_ray_tune pid=1075296)[0m [406]	train-mlogloss:0.94568	validation-mlogloss:0.96550
[36m(train_xgb_ray_tune pid=1075296)[0m [407]	train-mlogloss:0.94568	validation-mlogloss:0.96550
[36m(train_xgb_ray_tune pid=1075296)[0m [408]	train-mlogloss:0.94568	validation-mlogloss:0.96550
[36m(train_xgb_ray_tune pid=1075296)[0m [409]	train-mlogloss:0.94564	validation-mlogloss:0.96545
[36m(train_xgb_ray_tune pid=1075296)[0m [410]	train-mlogloss:0.94559	validation-mlogloss:0.96541
[36m(train_xgb_ray_tune pid=1075294)[0m [593]	train-mlogloss:1.03787	validation-mlogloss:1.03106
[36m(train_xgb_ray_tune pid=1075294)[0m [594]	train-mlogloss:1.03787	validation-mlogloss:1.03106
[36m(train_xgb_ray_tune pid=1075294)[0m [595]	train-mlogloss:1.03787	validation-mlogloss:1.03106
[36m(train_xgb_ray_tune pid=1075294)[0m [596]	train-mlogloss:1.03787	validation-mlogloss:1.03106
[36m(train_xgb_ray_tune pid=1075294)[0m [597]	train-mlogloss:1.03787	validation-mlogloss:1.03105
[36m(train_xgb_ray_tune pid=1075294)[0m [598]	train-mlogloss:1.03787	validation-mlogloss:1.03105
[36m(train_xgb_ray_tune pid=1075294)[0m [599]	train-mlogloss:1.03787	validation-mlogloss:1.03105
[36m(train_xgb_ray_tune pid=1075294)[0m [600]	train-mlogloss:1.03787	validation-mlogloss:1.03105
[36m(train_xgb_ray_tune pid=1075300)[0m [572]	train-mlogloss:0.89880	validation-mlogloss:0.93058
[36m(train_xgb_ray_tune pid=1075300)[0m [573]	train-mlogloss:0.89873	validation-mlogloss:0.93054
[36m(train_xgb_ray_tune pid=1075300)[0m [574]	train-mlogloss:0.89867	validation-mlogloss:0.93047
[36m(train_xgb_ray_tune pid=1075300)[0m [575]	train-mlogloss:0.89867	validation-mlogloss:0.93047
[36m(train_xgb_ray_tune pid=1075300)[0m [576]	train-mlogloss:0.89867	validation-mlogloss:0.93047
[36m(train_xgb_ray_tune pid=1075300)[0m [577]	train-mlogloss:0.89860	validation-mlogloss:0.93047
[36m(train_xgb_ray_tune pid=1075300)[0m [578]	train-mlogloss:0.89860	validation-mlogloss:0.93047
[36m(train_xgb_ray_tune pid=1075300)[0m [579]	train-mlogloss:0.89860	validation-mlogloss:0.93047
[36m(train_xgb_ray_tune pid=1075300)[0m [580]	train-mlogloss:0.89860	validation-mlogloss:0.93047
[36m(train_xgb_ray_tune pid=1075300)[0m [581]	train-mlogloss:0.89841	validation-mlogloss:0.93037
[36m(train_xgb_ray_tune pid=1075300)[0m [582]	train-mlogloss:0.89841	validation-mlogloss:0.93036
[36m(train_xgb_ray_tune pid=1075300)[0m [583]	train-mlogloss:0.89838	validation-mlogloss:0.93032
[36m(train_xgb_ray_tune pid=1075300)[0m [584]	train-mlogloss:0.89838	validation-mlogloss:0.93031
[36m(train_xgb_ray_tune pid=1075297)[0m [407]	train-mlogloss:1.08494	validation-mlogloss:1.07321
[36m(train_xgb_ray_tune pid=1075297)[0m [408]	train-mlogloss:1.08466	validation-mlogloss:1.07296
[36m(train_xgb_ray_tune pid=1075297)[0m [409]	train-mlogloss:1.08437	validation-mlogloss:1.07266
[36m(train_xgb_ray_tune pid=1075297)[0m [410]	train-mlogloss:1.08414	validation-mlogloss:1.07243
[36m(train_xgb_ray_tune pid=1075297)[0m [411]	train-mlogloss:1.08390	validation-mlogloss:1.07224
[36m(train_xgb_ray_tune pid=1075297)[0m [412]	train-mlogloss:1.08366	validation-mlogloss:1.07196
[36m(train_xgb_ray_tune pid=1075297)[0m [413]	train-mlogloss:1.08342	validation-mlogloss:1.07175
[36m(train_xgb_ray_tune pid=1075297)[0m [414]	train-mlogloss:1.08320	validation-mlogloss:1.07153
[36m(train_xgb_ray_tune pid=1075297)[0m [415]	train-mlogloss:1.08290	validation-mlogloss:1.07125
[36m(train_xgb_ray_tune pid=1075297)[0m [416]	train-mlogloss:1.08267	validation-mlogloss:1.07103
[36m(train_xgb_ray_tune pid=1075289)[0m [336]	train-mlogloss:1.05613	validation-mlogloss:1.05161
[36m(train_xgb_ray_tune pid=1075289)[0m [337]	train-mlogloss:1.05565	validation-mlogloss:1.05115
[36m(train_xgb_ray_tune pid=1075289)[0m [338]	train-mlogloss:1.05534	validation-mlogloss:1.05089
[36m(train_xgb_ray_tune pid=1075289)[0m [339]	train-mlogloss:1.05495	validation-mlogloss:1.05047
[36m(train_xgb_ray_tune pid=1075289)[0m [340]	train-mlogloss:1.05457	validation-mlogloss:1.05010
[36m(train_xgb_ray_tune pid=1075292)[0m [328]	train-mlogloss:1.01580	validation-mlogloss:1.02741
[36m(train_xgb_ray_tune pid=1075292)[0m [329]	train-mlogloss:1.01534	validation-mlogloss:1.02696
[36m(train_xgb_ray_tune pid=1075292)[0m [330]	train-mlogloss:1.01482	validation-mlogloss:1.02647
[36m(train_xgb_ray_tune pid=1075292)[0m [331]	train-mlogloss:1.01429	validation-mlogloss:1.02599
[36m(train_xgb_ray_tune pid=1075292)[0m [332]	train-mlogloss:1.01386	validation-mlogloss:1.02557
[36m(train_xgb_ray_tune pid=1075292)[0m [333]	train-mlogloss:1.01341	validation-mlogloss:1.02516
[36m(train_xgb_ray_tune pid=1075292)[0m [334]	train-mlogloss:1.01294	validation-mlogloss:1.02467
[36m(train_xgb_ray_tune pid=1075295)[0m [504]	train-mlogloss:0.97820	validation-mlogloss:0.98227
[36m(train_xgb_ray_tune pid=1075295)[0m [505]	train-mlogloss:0.97808	validation-mlogloss:0.98214
[36m(train_xgb_ray_tune pid=1075295)[0m [506]	train-mlogloss:0.97799	validation-mlogloss:0.98200
[36m(train_xgb_ray_tune pid=1075295)[0m [507]	train-mlogloss:0.97787	validation-mlogloss:0.98195
[36m(train_xgb_ray_tune pid=1075295)[0m [508]	train-mlogloss:0.97782	validation-mlogloss:0.98190
[36m(train_xgb_ray_tune pid=1075295)[0m [509]	train-mlogloss:0.97777	validation-mlogloss:0.98188
[36m(train_xgb_ray_tune pid=1075295)[0m [510]	train-mlogloss:0.97759	validation-mlogloss:0.98173
[36m(train_xgb_ray_tune pid=1075270)[0m [443]	train-mlogloss:0.99559	validation-mlogloss:0.99566
[36m(train_xgb_ray_tune pid=1075270)[0m [444]	train-mlogloss:0.99545	validation-mlogloss:0.99557
[36m(train_xgb_ray_tune pid=1075270)[0m [445]	train-mlogloss:0.99531	validation-mlogloss:0.99546
[36m(train_xgb_ray_tune pid=1075270)[0m [446]	train-mlogloss:0.99521	validation-mlogloss:0.99541
[36m(train_xgb_ray_tune pid=1075270)[0m [447]	train-mlogloss:0.99512	validation-mlogloss:0.99532
[36m(train_xgb_ray_tune pid=1075270)[0m [448]	train-mlogloss:0.99501	validation-mlogloss:0.99528
[36m(train_xgb_ray_tune pid=1075270)[0m [449]	train-mlogloss:0.99492	validation-mlogloss:0.99523
[36m(train_xgb_ray_tune pid=1075270)[0m [450]	train-mlogloss:0.99482	validation-mlogloss:0.99512
[36m(train_xgb_ray_tune pid=1075270)[0m [451]	train-mlogloss:0.99468	validation-mlogloss:0.99502
[36m(train_xgb_ray_tune pid=1075262)[0m [527]	train-mlogloss:0.89607	validation-mlogloss:0.92477
[36m(train_xgb_ray_tune pid=1075296)[0m [411]	train-mlogloss:0.94547	validation-mlogloss:0.96530
[36m(train_xgb_ray_tune pid=1075300)[0m [585]	train-mlogloss:0.89830	validation-mlogloss:0.93027
[36m(train_xgb_ray_tune pid=1075292)[0m [335]	train-mlogloss:1.01246	validation-mlogloss:1.02423
[36m(train_xgb_ray_tune pid=1075270)[0m [452]	train-mlogloss:0.99462	validation-mlogloss:0.99500
[36m(train_xgb_ray_tune pid=1075263)[0m [368]	train-mlogloss:1.07226	validation-mlogloss:1.06250
[36m(train_xgb_ray_tune pid=1075295)[0m [511]	train-mlogloss:0.97750	validation-mlogloss:0.98168
[36m(train_xgb_ray_tune pid=1075297)[0m [417]	train-mlogloss:1.08246	validation-mlogloss:1.07080
[36m(train_xgb_ray_tune pid=1075300)[0m [586]	train-mlogloss:0.89830	validation-mlogloss:0.93027
[36m(train_xgb_ray_tune pid=1075270)[0m [453]	train-mlogloss:0.99448	validation-mlogloss:0.99491

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:28. Total running time: 19s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             16.1204 │
│ time_total_s                 16.1204 │
│ training_iteration                 1 │
│ validation_accuracy          0.60253 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:28. Total running time: 19s
[36m(train_xgb_ray_tune pid=1075262)[0m [528]	train-mlogloss:0.89592	validation-mlogloss:0.92469
[36m(train_xgb_ray_tune pid=1075262)[0m [529]	train-mlogloss:0.89584	validation-mlogloss:0.92465
[36m(train_xgb_ray_tune pid=1075262)[0m [530]	train-mlogloss:0.89561	validation-mlogloss:0.92440
[36m(train_xgb_ray_tune pid=1075262)[0m [531]	train-mlogloss:0.89551	validation-mlogloss:0.92426
[36m(train_xgb_ray_tune pid=1075262)[0m [532]	train-mlogloss:0.89533	validation-mlogloss:0.92411
[36m(train_xgb_ray_tune pid=1075262)[0m [533]	train-mlogloss:0.89522	validation-mlogloss:0.92403
[36m(train_xgb_ray_tune pid=1075262)[0m [534]	train-mlogloss:0.89505	validation-mlogloss:0.92397
[36m(train_xgb_ray_tune pid=1075263)[0m [369]	train-mlogloss:1.07193	validation-mlogloss:1.06225
[36m(train_xgb_ray_tune pid=1075263)[0m [370]	train-mlogloss:1.07157	validation-mlogloss:1.06191
[36m(train_xgb_ray_tune pid=1075263)[0m [371]	train-mlogloss:1.07121	validation-mlogloss:1.06157
[36m(train_xgb_ray_tune pid=1075263)[0m [372]	train-mlogloss:1.07092	validation-mlogloss:1.06128
[36m(train_xgb_ray_tune pid=1075263)[0m [373]	train-mlogloss:1.07056	validation-mlogloss:1.06092
[36m(train_xgb_ray_tune pid=1075296)[0m [412]	train-mlogloss:0.94528	validation-mlogloss:0.96518
[36m(train_xgb_ray_tune pid=1075296)[0m [413]	train-mlogloss:0.94519	validation-mlogloss:0.96510
[36m(train_xgb_ray_tune pid=1075296)[0m [414]	train-mlogloss:0.94519	validation-mlogloss:0.96509
[36m(train_xgb_ray_tune pid=1075296)[0m [415]	train-mlogloss:0.94519	validation-mlogloss:0.96509
[36m(train_xgb_ray_tune pid=1075296)[0m [416]	train-mlogloss:0.94506	validation-mlogloss:0.96493
[36m(train_xgb_ray_tune pid=1075296)[0m [417]	train-mlogloss:0.94501	validation-mlogloss:0.96488
[36m(train_xgb_ray_tune pid=1075296)[0m [418]	train-mlogloss:0.94501	validation-mlogloss:0.96488
[36m(train_xgb_ray_tune pid=1075296)[0m [419]	train-mlogloss:0.94486	validation-mlogloss:0.96466
[36m(train_xgb_ray_tune pid=1075296)[0m [420]	train-mlogloss:0.94471	validation-mlogloss:0.96451
[36m(train_xgb_ray_tune pid=1075296)[0m [421]	train-mlogloss:0.94467	validation-mlogloss:0.96448
[36m(train_xgb_ray_tune pid=1075296)[0m [422]	train-mlogloss:0.94458	validation-mlogloss:0.96441
[36m(train_xgb_ray_tune pid=1075296)[0m [423]	train-mlogloss:0.94458	validation-mlogloss:0.96440
[36m(train_xgb_ray_tune pid=1075296)[0m [424]	train-mlogloss:0.94444	validation-mlogloss:0.96427
[36m(train_xgb_ray_tune pid=1075300)[0m [587]	train-mlogloss:0.89830	validation-mlogloss:0.93027
[36m(train_xgb_ray_tune pid=1075300)[0m [588]	train-mlogloss:0.89830	validation-mlogloss:0.93027
[36m(train_xgb_ray_tune pid=1075300)[0m [589]	train-mlogloss:0.89830	validation-mlogloss:0.93027
[36m(train_xgb_ray_tune pid=1075300)[0m [590]	train-mlogloss:0.89823	validation-mlogloss:0.93027
[36m(train_xgb_ray_tune pid=1075300)[0m [591]	train-mlogloss:0.89823	validation-mlogloss:0.93026
[36m(train_xgb_ray_tune pid=1075300)[0m [592]	train-mlogloss:0.89809	validation-mlogloss:0.93010
[36m(train_xgb_ray_tune pid=1075300)[0m [593]	train-mlogloss:0.89809	validation-mlogloss:0.93010
[36m(train_xgb_ray_tune pid=1075300)[0m [594]	train-mlogloss:0.89809	validation-mlogloss:0.93010
[36m(train_xgb_ray_tune pid=1075300)[0m [595]	train-mlogloss:0.89809	validation-mlogloss:0.93010
[36m(train_xgb_ray_tune pid=1075300)[0m [596]	train-mlogloss:0.89809	validation-mlogloss:0.93010
[36m(train_xgb_ray_tune pid=1075300)[0m [597]	train-mlogloss:0.89809	validation-mlogloss:0.93010
[36m(train_xgb_ray_tune pid=1075300)[0m [598]	train-mlogloss:0.89809	validation-mlogloss:0.93010
[36m(train_xgb_ray_tune pid=1075300)[0m [599]	train-mlogloss:0.89801	validation-mlogloss:0.93001
[36m(train_xgb_ray_tune pid=1075297)[0m [418]	train-mlogloss:1.08229	validation-mlogloss:1.07065
[36m(train_xgb_ray_tune pid=1075297)[0m [419]	train-mlogloss:1.08206	validation-mlogloss:1.07044
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[36m(train_xgb_ray_tune pid=1075297)[0m [423]	train-mlogloss:1.08118	validation-mlogloss:1.06961
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[36m(train_xgb_ray_tune pid=1075292)[0m [337]	train-mlogloss:1.01142	validation-mlogloss:1.02338
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[36m(train_xgb_ray_tune pid=1075292)[0m [342]	train-mlogloss:1.00895	validation-mlogloss:1.02137
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[36m(train_xgb_ray_tune pid=1075295)[0m [513]	train-mlogloss:0.97741	validation-mlogloss:0.98160
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[36m(train_xgb_ray_tune pid=1075295)[0m [516]	train-mlogloss:0.97710	validation-mlogloss:0.98141
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[36m(train_xgb_ray_tune pid=1075295)[0m [519]	train-mlogloss:0.97683	validation-mlogloss:0.98124
[36m(train_xgb_ray_tune pid=1075270)[0m [454]	train-mlogloss:0.99438	validation-mlogloss:0.99484
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[36m(train_xgb_ray_tune pid=1075270)[0m [460]	train-mlogloss:0.99359	validation-mlogloss:0.99438
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[36m(train_xgb_ray_tune pid=1075270)[0m [464]	train-mlogloss:0.99325	validation-mlogloss:0.99410
[36m(train_xgb_ray_tune pid=1075270)[0m [465]	train-mlogloss:0.99319	validation-mlogloss:0.99406
[36m(train_xgb_ray_tune pid=1075300)[0m [600]	train-mlogloss:0.89801	validation-mlogloss:0.93001
[36m(train_xgb_ray_tune pid=1075262)[0m [535]	train-mlogloss:0.89490	validation-mlogloss:0.92392
[36m(train_xgb_ray_tune pid=1075262)[0m [536]	train-mlogloss:0.89475	validation-mlogloss:0.92382
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[36m(train_xgb_ray_tune pid=1075262)[0m [546]	train-mlogloss:0.89365	validation-mlogloss:0.92292
[36m(train_xgb_ray_tune pid=1075263)[0m [374]	train-mlogloss:1.07021	validation-mlogloss:1.06056
[36m(train_xgb_ray_tune pid=1075263)[0m [375]	train-mlogloss:1.06983	validation-mlogloss:1.06020
[36m(train_xgb_ray_tune pid=1075263)[0m [376]	train-mlogloss:1.06948	validation-mlogloss:1.05984
[36m(train_xgb_ray_tune pid=1075263)[0m [377]	train-mlogloss:1.06912	validation-mlogloss:1.05950
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[36m(train_xgb_ray_tune pid=1075263)[0m [379]	train-mlogloss:1.06853	validation-mlogloss:1.05897
[36m(train_xgb_ray_tune pid=1075296)[0m [425]	train-mlogloss:0.94427	validation-mlogloss:0.96412
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[36m(train_xgb_ray_tune pid=1075296)[0m [429]	train-mlogloss:0.94418	validation-mlogloss:0.96412
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[36m(train_xgb_ray_tune pid=1075296)[0m [436]	train-mlogloss:0.94350	validation-mlogloss:0.96351
[36m(train_xgb_ray_tune pid=1075300)[0m [601]	train-mlogloss:0.89801	validation-mlogloss:0.93001
[36m(train_xgb_ray_tune pid=1075300)[0m [602]	train-mlogloss:0.89801	validation-mlogloss:0.93001
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[36m(train_xgb_ray_tune pid=1075300)[0m [604]	train-mlogloss:0.89793	validation-mlogloss:0.93001
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[36m(train_xgb_ray_tune pid=1075300)[0m [608]	train-mlogloss:0.89793	validation-mlogloss:0.93001
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[36m(train_xgb_ray_tune pid=1075300)[0m [612]	train-mlogloss:0.89771	validation-mlogloss:0.92983
[36m(train_xgb_ray_tune pid=1075300)[0m [613]	train-mlogloss:0.89768	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075300)[0m [614]	train-mlogloss:0.89768	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075297)[0m [428]	train-mlogloss:1.08011	validation-mlogloss:1.06857
[36m(train_xgb_ray_tune pid=1075297)[0m [429]	train-mlogloss:1.07988	validation-mlogloss:1.06837
[36m(train_xgb_ray_tune pid=1075297)[0m [430]	train-mlogloss:1.07960	validation-mlogloss:1.06814
[36m(train_xgb_ray_tune pid=1075297)[0m [431]	train-mlogloss:1.07942	validation-mlogloss:1.06797
[36m(train_xgb_ray_tune pid=1075297)[0m [432]	train-mlogloss:1.07917	validation-mlogloss:1.06776
[36m(train_xgb_ray_tune pid=1075297)[0m [433]	train-mlogloss:1.07899	validation-mlogloss:1.06759
[36m(train_xgb_ray_tune pid=1075297)[0m [434]	train-mlogloss:1.07881	validation-mlogloss:1.06741
[36m(train_xgb_ray_tune pid=1075289)[0m [346]	train-mlogloss:1.05213	validation-mlogloss:1.04785
[36m(train_xgb_ray_tune pid=1075289)[0m [347]	train-mlogloss:1.05180	validation-mlogloss:1.04756
[36m(train_xgb_ray_tune pid=1075289)[0m [348]	train-mlogloss:1.05132	validation-mlogloss:1.04706
[36m(train_xgb_ray_tune pid=1075289)[0m [349]	train-mlogloss:1.05096	validation-mlogloss:1.04675
[36m(train_xgb_ray_tune pid=1075289)[0m [350]	train-mlogloss:1.05055	validation-mlogloss:1.04639
[36m(train_xgb_ray_tune pid=1075289)[0m [351]	train-mlogloss:1.05018	validation-mlogloss:1.04604
[36m(train_xgb_ray_tune pid=1075289)[0m [352]	train-mlogloss:1.04984	validation-mlogloss:1.04564
[36m(train_xgb_ray_tune pid=1075289)[0m [353]	train-mlogloss:1.04945	validation-mlogloss:1.04536
[36m(train_xgb_ray_tune pid=1075289)[0m [354]	train-mlogloss:1.04907	validation-mlogloss:1.04501
[36m(train_xgb_ray_tune pid=1075292)[0m [343]	train-mlogloss:1.00843	validation-mlogloss:1.02099
[36m(train_xgb_ray_tune pid=1075292)[0m [344]	train-mlogloss:1.00797	validation-mlogloss:1.02057
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[36m(train_xgb_ray_tune pid=1075292)[0m [346]	train-mlogloss:1.00698	validation-mlogloss:1.01970
[36m(train_xgb_ray_tune pid=1075292)[0m [347]	train-mlogloss:1.00647	validation-mlogloss:1.01933
[36m(train_xgb_ray_tune pid=1075292)[0m [348]	train-mlogloss:1.00591	validation-mlogloss:1.01879
[36m(train_xgb_ray_tune pid=1075292)[0m [349]	train-mlogloss:1.00549	validation-mlogloss:1.01840
[36m(train_xgb_ray_tune pid=1075295)[0m [520]	train-mlogloss:0.97669	validation-mlogloss:0.98109
[36m(train_xgb_ray_tune pid=1075295)[0m [521]	train-mlogloss:0.97659	validation-mlogloss:0.98101
[36m(train_xgb_ray_tune pid=1075295)[0m [522]	train-mlogloss:0.97648	validation-mlogloss:0.98089
[36m(train_xgb_ray_tune pid=1075295)[0m [523]	train-mlogloss:0.97638	validation-mlogloss:0.98078
[36m(train_xgb_ray_tune pid=1075295)[0m [524]	train-mlogloss:0.97627	validation-mlogloss:0.98073
[36m(train_xgb_ray_tune pid=1075295)[0m [525]	train-mlogloss:0.97617	validation-mlogloss:0.98063
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[36m(train_xgb_ray_tune pid=1075295)[0m [527]	train-mlogloss:0.97595	validation-mlogloss:0.98045
[36m(train_xgb_ray_tune pid=1075270)[0m [466]	train-mlogloss:0.99309	validation-mlogloss:0.99394
[36m(train_xgb_ray_tune pid=1075270)[0m [467]	train-mlogloss:0.99303	validation-mlogloss:0.99390
[36m(train_xgb_ray_tune pid=1075270)[0m [468]	train-mlogloss:0.99286	validation-mlogloss:0.99376
[36m(train_xgb_ray_tune pid=1075270)[0m [469]	train-mlogloss:0.99276	validation-mlogloss:0.99371
[36m(train_xgb_ray_tune pid=1075270)[0m [470]	train-mlogloss:0.99267	validation-mlogloss:0.99365
[36m(train_xgb_ray_tune pid=1075270)[0m [471]	train-mlogloss:0.99251	validation-mlogloss:0.99358
[36m(train_xgb_ray_tune pid=1075270)[0m [472]	train-mlogloss:0.99246	validation-mlogloss:0.99354
[36m(train_xgb_ray_tune pid=1075270)[0m [473]	train-mlogloss:0.99240	validation-mlogloss:0.99349
[36m(train_xgb_ray_tune pid=1075270)[0m [474]	train-mlogloss:0.99226	validation-mlogloss:0.99339
[36m(train_xgb_ray_tune pid=1075270)[0m [475]	train-mlogloss:0.99205	validation-mlogloss:0.99317
[36m(train_xgb_ray_tune pid=1075270)[0m [476]	train-mlogloss:0.99200	validation-mlogloss:0.99313
[36m(train_xgb_ray_tune pid=1075270)[0m [477]	train-mlogloss:0.99191	validation-mlogloss:0.99305
[36m(train_xgb_ray_tune pid=1075270)[0m [478]	train-mlogloss:0.99185	validation-mlogloss:0.99300
[36m(train_xgb_ray_tune pid=1075262)[0m [547]	train-mlogloss:0.89355	validation-mlogloss:0.92281
[36m(train_xgb_ray_tune pid=1075296)[0m [437]	train-mlogloss:0.94346	validation-mlogloss:0.96348
[36m(train_xgb_ray_tune pid=1075300)[0m [615]	train-mlogloss:0.89768	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075292)[0m [350]	train-mlogloss:1.00498	validation-mlogloss:1.01797
[36m(train_xgb_ray_tune pid=1075270)[0m [479]	train-mlogloss:0.99171	validation-mlogloss:0.99284
[36m(train_xgb_ray_tune pid=1075262)[0m [548]	train-mlogloss:0.89342	validation-mlogloss:0.92269
[36m(train_xgb_ray_tune pid=1075296)[0m [438]	train-mlogloss:0.94342	validation-mlogloss:0.96345
[36m(train_xgb_ray_tune pid=1075300)[0m [616]	train-mlogloss:0.89768	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075289)[0m [355]	train-mlogloss:1.04879	validation-mlogloss:1.04476
[36m(train_xgb_ray_tune pid=1075295)[0m [528]	train-mlogloss:0.97584	validation-mlogloss:0.98040
[36m(train_xgb_ray_tune pid=1075270)[0m [480]	train-mlogloss:0.99166	validation-mlogloss:0.99283
[36m(train_xgb_ray_tune pid=1075262)[0m [549]	train-mlogloss:0.89335	validation-mlogloss:0.92266
[36m(train_xgb_ray_tune pid=1075263)[0m [380]	train-mlogloss:1.06817	validation-mlogloss:1.05863
[36m(train_xgb_ray_tune pid=1075296)[0m [439]	train-mlogloss:0.94338	validation-mlogloss:0.96342
[36m(train_xgb_ray_tune pid=1075300)[0m [617]	train-mlogloss:0.89767	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075292)[0m [351]	train-mlogloss:1.00448	validation-mlogloss:1.01755

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:28. Total running time: 19s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s              16.422 │
│ time_total_s                  16.422 │
│ training_iteration                 1 │
│ validation_accuracy          0.61482 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:28. Total running time: 19s
[36m(train_xgb_ray_tune pid=1075262)[0m [550]	train-mlogloss:0.89322	validation-mlogloss:0.92270
[36m(train_xgb_ray_tune pid=1075262)[0m [551]	train-mlogloss:0.89312	validation-mlogloss:0.92261
[36m(train_xgb_ray_tune pid=1075262)[0m [552]	train-mlogloss:0.89298	validation-mlogloss:0.92262
[36m(train_xgb_ray_tune pid=1075262)[0m [553]	train-mlogloss:0.89291	validation-mlogloss:0.92259
[36m(train_xgb_ray_tune pid=1075262)[0m [554]	train-mlogloss:0.89282	validation-mlogloss:0.92257
[36m(train_xgb_ray_tune pid=1075262)[0m [555]	train-mlogloss:0.89271	validation-mlogloss:0.92251
[36m(train_xgb_ray_tune pid=1075262)[0m [556]	train-mlogloss:0.89252	validation-mlogloss:0.92246
[36m(train_xgb_ray_tune pid=1075262)[0m [557]	train-mlogloss:0.89237	validation-mlogloss:0.92231
[36m(train_xgb_ray_tune pid=1075262)[0m [558]	train-mlogloss:0.89226	validation-mlogloss:0.92216
[36m(train_xgb_ray_tune pid=1075262)[0m [559]	train-mlogloss:0.89215	validation-mlogloss:0.92212
[36m(train_xgb_ray_tune pid=1075262)[0m [560]	train-mlogloss:0.89203	validation-mlogloss:0.92202
[36m(train_xgb_ray_tune pid=1075263)[0m [381]	train-mlogloss:1.06792	validation-mlogloss:1.05845
[36m(train_xgb_ray_tune pid=1075263)[0m [382]	train-mlogloss:1.06764	validation-mlogloss:1.05819
[36m(train_xgb_ray_tune pid=1075263)[0m [383]	train-mlogloss:1.06729	validation-mlogloss:1.05787
[36m(train_xgb_ray_tune pid=1075263)[0m [384]	train-mlogloss:1.06700	validation-mlogloss:1.05757
[36m(train_xgb_ray_tune pid=1075263)[0m [385]	train-mlogloss:1.06665	validation-mlogloss:1.05725
[36m(train_xgb_ray_tune pid=1075263)[0m [386]	train-mlogloss:1.06632	validation-mlogloss:1.05689
[36m(train_xgb_ray_tune pid=1075296)[0m [440]	train-mlogloss:0.94338	validation-mlogloss:0.96342
[36m(train_xgb_ray_tune pid=1075296)[0m [441]	train-mlogloss:0.94338	validation-mlogloss:0.96342
[36m(train_xgb_ray_tune pid=1075296)[0m [442]	train-mlogloss:0.94328	validation-mlogloss:0.96333
[36m(train_xgb_ray_tune pid=1075296)[0m [443]	train-mlogloss:0.94319	validation-mlogloss:0.96333
[36m(train_xgb_ray_tune pid=1075296)[0m [444]	train-mlogloss:0.94314	validation-mlogloss:0.96326
[36m(train_xgb_ray_tune pid=1075296)[0m [445]	train-mlogloss:0.94311	validation-mlogloss:0.96326
[36m(train_xgb_ray_tune pid=1075296)[0m [446]	train-mlogloss:0.94311	validation-mlogloss:0.96326
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[36m(train_xgb_ray_tune pid=1075296)[0m [451]	train-mlogloss:0.94271	validation-mlogloss:0.96292
[36m(train_xgb_ray_tune pid=1075296)[0m [452]	train-mlogloss:0.94271	validation-mlogloss:0.96292
[36m(train_xgb_ray_tune pid=1075300)[0m [618]	train-mlogloss:0.89767	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075300)[0m [619]	train-mlogloss:0.89767	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075300)[0m [620]	train-mlogloss:0.89767	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075300)[0m [621]	train-mlogloss:0.89767	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075300)[0m [622]	train-mlogloss:0.89767	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075300)[0m [623]	train-mlogloss:0.89767	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075300)[0m [624]	train-mlogloss:0.89767	validation-mlogloss:0.92981
[36m(train_xgb_ray_tune pid=1075300)[0m [625]	train-mlogloss:0.89761	validation-mlogloss:0.92976
[36m(train_xgb_ray_tune pid=1075300)[0m [626]	train-mlogloss:0.89761	validation-mlogloss:0.92976
[36m(train_xgb_ray_tune pid=1075289)[0m [356]	train-mlogloss:1.04842	validation-mlogloss:1.04450
[36m(train_xgb_ray_tune pid=1075289)[0m [357]	train-mlogloss:1.04797	validation-mlogloss:1.04408
[36m(train_xgb_ray_tune pid=1075289)[0m [358]	train-mlogloss:1.04758	validation-mlogloss:1.04374
[36m(train_xgb_ray_tune pid=1075289)[0m [359]	train-mlogloss:1.04724	validation-mlogloss:1.04343
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[36m(train_xgb_ray_tune pid=1075289)[0m [361]	train-mlogloss:1.04659	validation-mlogloss:1.04287
[36m(train_xgb_ray_tune pid=1075289)[0m [362]	train-mlogloss:1.04612	validation-mlogloss:1.04245
[36m(train_xgb_ray_tune pid=1075289)[0m [363]	train-mlogloss:1.04570	validation-mlogloss:1.04217
[36m(train_xgb_ray_tune pid=1075292)[0m [352]	train-mlogloss:1.00400	validation-mlogloss:1.01721
[36m(train_xgb_ray_tune pid=1075292)[0m [353]	train-mlogloss:1.00350	validation-mlogloss:1.01677
[36m(train_xgb_ray_tune pid=1075292)[0m [354]	train-mlogloss:1.00302	validation-mlogloss:1.01640
[36m(train_xgb_ray_tune pid=1075292)[0m [355]	train-mlogloss:1.00252	validation-mlogloss:1.01601
[36m(train_xgb_ray_tune pid=1075292)[0m [356]	train-mlogloss:1.00202	validation-mlogloss:1.01563
[36m(train_xgb_ray_tune pid=1075292)[0m [357]	train-mlogloss:1.00156	validation-mlogloss:1.01525
[36m(train_xgb_ray_tune pid=1075292)[0m [358]	train-mlogloss:1.00109	validation-mlogloss:1.01483
[36m(train_xgb_ray_tune pid=1075295)[0m [529]	train-mlogloss:0.97574	validation-mlogloss:0.98030
[36m(train_xgb_ray_tune pid=1075295)[0m [530]	train-mlogloss:0.97562	validation-mlogloss:0.98020
[36m(train_xgb_ray_tune pid=1075295)[0m [531]	train-mlogloss:0.97554	validation-mlogloss:0.98016
[36m(train_xgb_ray_tune pid=1075295)[0m [532]	train-mlogloss:0.97543	validation-mlogloss:0.98009
[36m(train_xgb_ray_tune pid=1075295)[0m [533]	train-mlogloss:0.97534	validation-mlogloss:0.98000
[36m(train_xgb_ray_tune pid=1075295)[0m [534]	train-mlogloss:0.97534	validation-mlogloss:0.98000
[36m(train_xgb_ray_tune pid=1075295)[0m [535]	train-mlogloss:0.97520	validation-mlogloss:0.97991
[36m(train_xgb_ray_tune pid=1075295)[0m [536]	train-mlogloss:0.97510	validation-mlogloss:0.97987
[36m(train_xgb_ray_tune pid=1075295)[0m [537]	train-mlogloss:0.97499	validation-mlogloss:0.97982
[36m(train_xgb_ray_tune pid=1075295)[0m [538]	train-mlogloss:0.97488	validation-mlogloss:0.97972
[36m(train_xgb_ray_tune pid=1075270)[0m [481]	train-mlogloss:0.99153	validation-mlogloss:0.99270
[36m(train_xgb_ray_tune pid=1075270)[0m [482]	train-mlogloss:0.99143	validation-mlogloss:0.99262
[36m(train_xgb_ray_tune pid=1075270)[0m [483]	train-mlogloss:0.99130	validation-mlogloss:0.99253
[36m(train_xgb_ray_tune pid=1075270)[0m [484]	train-mlogloss:0.99120	validation-mlogloss:0.99250
[36m(train_xgb_ray_tune pid=1075270)[0m [485]	train-mlogloss:0.99111	validation-mlogloss:0.99244
[36m(train_xgb_ray_tune pid=1075270)[0m [486]	train-mlogloss:0.99106	validation-mlogloss:0.99239
[36m(train_xgb_ray_tune pid=1075270)[0m [487]	train-mlogloss:0.99100	validation-mlogloss:0.99235
[36m(train_xgb_ray_tune pid=1075270)[0m [488]	train-mlogloss:0.99082	validation-mlogloss:0.99214
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[36m(train_xgb_ray_tune pid=1075270)[0m [492]	train-mlogloss:0.99036	validation-mlogloss:0.99190
[36m(train_xgb_ray_tune pid=1075270)[0m [493]	train-mlogloss:0.99023	validation-mlogloss:0.99180
[36m(train_xgb_ray_tune pid=1075262)[0m [561]	train-mlogloss:0.89188	validation-mlogloss:0.92196
[36m(train_xgb_ray_tune pid=1075263)[0m [387]	train-mlogloss:1.06597	validation-mlogloss:1.05657
[36m(train_xgb_ray_tune pid=1075289)[0m [364]	train-mlogloss:1.04537	validation-mlogloss:1.04192
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[36m(train_xgb_ray_tune pid=1075296)[0m [453]	train-mlogloss:0.94257	validation-mlogloss:0.96282
[36m(train_xgb_ray_tune pid=1075270)[0m [494]	train-mlogloss:0.99018	validation-mlogloss:0.99175
[36m(train_xgb_ray_tune pid=1075262)[0m [562]	train-mlogloss:0.89176	validation-mlogloss:0.92192
[36m(train_xgb_ray_tune pid=1075292)[0m [359]	train-mlogloss:1.00065	validation-mlogloss:1.01443
[36m(train_xgb_ray_tune pid=1075295)[0m [540]	train-mlogloss:0.97471	validation-mlogloss:0.97958
[36m(train_xgb_ray_tune pid=1075263)[0m [388]	train-mlogloss:1.06563	validation-mlogloss:1.05623
[36m(train_xgb_ray_tune pid=1075296)[0m [454]	train-mlogloss:0.94257	validation-mlogloss:0.96282
[36m(train_xgb_ray_tune pid=1075289)[0m [365]	train-mlogloss:1.04506	validation-mlogloss:1.04174
[36m(train_xgb_ray_tune pid=1075270)[0m [495]	train-mlogloss:0.99012	validation-mlogloss:0.99174
[36m(train_xgb_ray_tune pid=1075262)[0m [563]	train-mlogloss:0.89165	validation-mlogloss:0.92179
[36m(train_xgb_ray_tune pid=1075295)[0m [541]	train-mlogloss:0.97456	validation-mlogloss:0.97946
[36m(train_xgb_ray_tune pid=1075270)[0m [496]	train-mlogloss:0.99000	validation-mlogloss:0.99166
[36m(train_xgb_ray_tune pid=1075262)[0m [564]	train-mlogloss:0.89153	validation-mlogloss:0.92171
[36m(train_xgb_ray_tune pid=1075300)[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=1075300)[0m   _log_deprecation_warning([32m [repeated 10x across cluster][0m
[36m(train_xgb_ray_tune pid=1075263)[0m [389]	train-mlogloss:1.06527	validation-mlogloss:1.05587
[36m(train_xgb_ray_tune pid=1075296)[0m [455]	train-mlogloss:0.94257	validation-mlogloss:0.96281
[36m(train_xgb_ray_tune pid=1075289)[0m [366]	train-mlogloss:1.04473	validation-mlogloss:1.04141
[36m(train_xgb_ray_tune pid=1075292)[0m [360]	train-mlogloss:1.00016	validation-mlogloss:1.01395
[36m(train_xgb_ray_tune pid=1075295)[0m [542]	train-mlogloss:0.97448	validation-mlogloss:0.97938

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:28. Total running time: 19s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             16.5103 │
│ time_total_s                 16.5103 │
│ training_iteration                 1 │
│ validation_accuracy          0.65063 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:28. Total running time: 19s
[36m(train_xgb_ray_tune pid=1075262)[0m [565]	train-mlogloss:0.89142	validation-mlogloss:0.92170
[36m(train_xgb_ray_tune pid=1075262)[0m [566]	train-mlogloss:0.89134	validation-mlogloss:0.92164
[36m(train_xgb_ray_tune pid=1075262)[0m [567]	train-mlogloss:0.89118	validation-mlogloss:0.92151
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[36m(train_xgb_ray_tune pid=1075262)[0m [570]	train-mlogloss:0.89092	validation-mlogloss:0.92131
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[36m(train_xgb_ray_tune pid=1075262)[0m [572]	train-mlogloss:0.89068	validation-mlogloss:0.92113
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[36m(train_xgb_ray_tune pid=1075262)[0m [574]	train-mlogloss:0.89047	validation-mlogloss:0.92095
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[36m(train_xgb_ray_tune pid=1075263)[0m [390]	train-mlogloss:1.06500	validation-mlogloss:1.05562
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[36m(train_xgb_ray_tune pid=1075263)[0m [393]	train-mlogloss:1.06411	validation-mlogloss:1.05482
[36m(train_xgb_ray_tune pid=1075263)[0m [394]	train-mlogloss:1.06378	validation-mlogloss:1.05448
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[36m(train_xgb_ray_tune pid=1075263)[0m [396]	train-mlogloss:1.06317	validation-mlogloss:1.05393
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[36m(train_xgb_ray_tune pid=1075263)[0m [398]	train-mlogloss:1.06256	validation-mlogloss:1.05335
[36m(train_xgb_ray_tune pid=1075263)[0m [399]	train-mlogloss:1.06224	validation-mlogloss:1.05302
[36m(train_xgb_ray_tune pid=1075296)[0m [456]	train-mlogloss:0.94257	validation-mlogloss:0.96281
[36m(train_xgb_ray_tune pid=1075296)[0m [457]	train-mlogloss:0.94257	validation-mlogloss:0.96281
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[36m(train_xgb_ray_tune pid=1075296)[0m [469]	train-mlogloss:0.94215	validation-mlogloss:0.96254
[36m(train_xgb_ray_tune pid=1075289)[0m [367]	train-mlogloss:1.04430	validation-mlogloss:1.04102
[36m(train_xgb_ray_tune pid=1075289)[0m [368]	train-mlogloss:1.04400	validation-mlogloss:1.04076
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[36m(train_xgb_ray_tune pid=1075292)[0m [361]	train-mlogloss:0.99970	validation-mlogloss:1.01360
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[36m(train_xgb_ray_tune pid=1075292)[0m [363]	train-mlogloss:0.99877	validation-mlogloss:1.01285
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[36m(train_xgb_ray_tune pid=1075295)[0m [543]	train-mlogloss:0.97438	validation-mlogloss:0.97929
[36m(train_xgb_ray_tune pid=1075295)[0m [544]	train-mlogloss:0.97438	validation-mlogloss:0.97929
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[36m(train_xgb_ray_tune pid=1075295)[0m [548]	train-mlogloss:0.97388	validation-mlogloss:0.97881
[36m(train_xgb_ray_tune pid=1075295)[0m [549]	train-mlogloss:0.97384	validation-mlogloss:0.97877
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[36m(train_xgb_ray_tune pid=1075295)[0m [551]	train-mlogloss:0.97371	validation-mlogloss:0.97867
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[36m(train_xgb_ray_tune pid=1075295)[0m [554]	train-mlogloss:0.97335	validation-mlogloss:0.97844
[36m(train_xgb_ray_tune pid=1075295)[0m [555]	train-mlogloss:0.97324	validation-mlogloss:0.97836
[36m(train_xgb_ray_tune pid=1075295)[0m [556]	train-mlogloss:0.97314	validation-mlogloss:0.97827
[36m(train_xgb_ray_tune pid=1075270)[0m [497]	train-mlogloss:0.98988	validation-mlogloss:0.99155
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[36m(train_xgb_ray_tune pid=1075270)[0m [506]	train-mlogloss:0.98881	validation-mlogloss:0.99075
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[36m(train_xgb_ray_tune pid=1075295)[0m [576]	train-mlogloss:0.97162	validation-mlogloss:0.97702
[36m(train_xgb_ray_tune pid=1075295)[0m [577]	train-mlogloss:0.97162	validation-mlogloss:0.97702
[36m(train_xgb_ray_tune pid=1075270)[0m [528]	train-mlogloss:0.98677	validation-mlogloss:0.98890
[36m(train_xgb_ray_tune pid=1075270)[0m [529]	train-mlogloss:0.98664	validation-mlogloss:0.98883
[36m(train_xgb_ray_tune pid=1075270)[0m [530]	train-mlogloss:0.98653	validation-mlogloss:0.98867
[36m(train_xgb_ray_tune pid=1075270)[0m [531]	train-mlogloss:0.98643	validation-mlogloss:0.98858
[36m(train_xgb_ray_tune pid=1075270)[0m [532]	train-mlogloss:0.98639	validation-mlogloss:0.98855
[36m(train_xgb_ray_tune pid=1075270)[0m [533]	train-mlogloss:0.98634	validation-mlogloss:0.98853
[36m(train_xgb_ray_tune pid=1075270)[0m [534]	train-mlogloss:0.98629	validation-mlogloss:0.98850
[36m(train_xgb_ray_tune pid=1075270)[0m [535]	train-mlogloss:0.98624	validation-mlogloss:0.98846
[36m(train_xgb_ray_tune pid=1075270)[0m [536]	train-mlogloss:0.98616	validation-mlogloss:0.98839
[36m(train_xgb_ray_tune pid=1075270)[0m [537]	train-mlogloss:0.98611	validation-mlogloss:0.98839
[36m(train_xgb_ray_tune pid=1075270)[0m [538]	train-mlogloss:0.98597	validation-mlogloss:0.98819
[36m(train_xgb_ray_tune pid=1075270)[0m [539]	train-mlogloss:0.98583	validation-mlogloss:0.98801
[36m(train_xgb_ray_tune pid=1075270)[0m [540]	train-mlogloss:0.98574	validation-mlogloss:0.98787
[36m(train_xgb_ray_tune pid=1075270)[0m [541]	train-mlogloss:0.98569	validation-mlogloss:0.98782
[36m(train_xgb_ray_tune pid=1075270)[0m [542]	train-mlogloss:0.98564	validation-mlogloss:0.98779
[36m(train_xgb_ray_tune pid=1075262)[0m [608]	train-mlogloss:0.88690	validation-mlogloss:0.91886
[36m(train_xgb_ray_tune pid=1075296)[0m [504]	train-mlogloss:0.94068	validation-mlogloss:0.96141
[36m(train_xgb_ray_tune pid=1075289)[0m [397]	train-mlogloss:1.03419	validation-mlogloss:1.03159
[36m(train_xgb_ray_tune pid=1075270)[0m [543]	train-mlogloss:0.98552	validation-mlogloss:0.98764
[36m(train_xgb_ray_tune pid=1075262)[0m [609]	train-mlogloss:0.88684	validation-mlogloss:0.91885
[36m(train_xgb_ray_tune pid=1075263)[0m [424]	train-mlogloss:1.05491	validation-mlogloss:1.04624
[36m(train_xgb_ray_tune pid=1075296)[0m [505]	train-mlogloss:0.94058	validation-mlogloss:0.96132
[36m(train_xgb_ray_tune pid=1075292)[0m [387]	train-mlogloss:0.98829	validation-mlogloss:1.00411
[36m(train_xgb_ray_tune pid=1075270)[0m [544]	train-mlogloss:0.98543	validation-mlogloss:0.98758
[36m(train_xgb_ray_tune pid=1075296)[0m [506]	train-mlogloss:0.94058	validation-mlogloss:0.96132
[36m(train_xgb_ray_tune pid=1075289)[0m [398]	train-mlogloss:1.03388	validation-mlogloss:1.03132
[36m(train_xgb_ray_tune pid=1075262)[0m [610]	train-mlogloss:0.88676	validation-mlogloss:0.91885
[36m(train_xgb_ray_tune pid=1075263)[0m [425]	train-mlogloss:1.05463	validation-mlogloss:1.04598
[36m(train_xgb_ray_tune pid=1075270)[0m [545]	train-mlogloss:0.98533	validation-mlogloss:0.98742

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:29. Total running time: 19s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             17.0079 │
│ time_total_s                 17.0079 │
│ training_iteration                 1 │
│ validation_accuracy          0.62289 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:29. Total running time: 19s
[36m(train_xgb_ray_tune pid=1075262)[0m [611]	train-mlogloss:0.88674	validation-mlogloss:0.91884
[36m(train_xgb_ray_tune pid=1075262)[0m [612]	train-mlogloss:0.88667	validation-mlogloss:0.91874
[36m(train_xgb_ray_tune pid=1075262)[0m [613]	train-mlogloss:0.88658	validation-mlogloss:0.91866
[36m(train_xgb_ray_tune pid=1075262)[0m [614]	train-mlogloss:0.88652	validation-mlogloss:0.91861
[36m(train_xgb_ray_tune pid=1075262)[0m [615]	train-mlogloss:0.88643	validation-mlogloss:0.91857
[36m(train_xgb_ray_tune pid=1075262)[0m [616]	train-mlogloss:0.88633	validation-mlogloss:0.91855
[36m(train_xgb_ray_tune pid=1075262)[0m [617]	train-mlogloss:0.88627	validation-mlogloss:0.91855
[36m(train_xgb_ray_tune pid=1075262)[0m [618]	train-mlogloss:0.88616	validation-mlogloss:0.91844
[36m(train_xgb_ray_tune pid=1075262)[0m [619]	train-mlogloss:0.88608	validation-mlogloss:0.91838
[36m(train_xgb_ray_tune pid=1075262)[0m [620]	train-mlogloss:0.88596	validation-mlogloss:0.91828
[36m(train_xgb_ray_tune pid=1075262)[0m [621]	train-mlogloss:0.88586	validation-mlogloss:0.91822
[36m(train_xgb_ray_tune pid=1075262)[0m [622]	train-mlogloss:0.88577	validation-mlogloss:0.91824
[36m(train_xgb_ray_tune pid=1075262)[0m [623]	train-mlogloss:0.88568	validation-mlogloss:0.91816
[36m(train_xgb_ray_tune pid=1075262)[0m [624]	train-mlogloss:0.88563	validation-mlogloss:0.91810
[36m(train_xgb_ray_tune pid=1075263)[0m [426]	train-mlogloss:1.05430	validation-mlogloss:1.04567
[36m(train_xgb_ray_tune pid=1075263)[0m [427]	train-mlogloss:1.05400	validation-mlogloss:1.04537
[36m(train_xgb_ray_tune pid=1075263)[0m [428]	train-mlogloss:1.05375	validation-mlogloss:1.04514
[36m(train_xgb_ray_tune pid=1075263)[0m [429]	train-mlogloss:1.05350	validation-mlogloss:1.04494
[36m(train_xgb_ray_tune pid=1075263)[0m [430]	train-mlogloss:1.05325	validation-mlogloss:1.04468
[36m(train_xgb_ray_tune pid=1075263)[0m [431]	train-mlogloss:1.05302	validation-mlogloss:1.04444
[36m(train_xgb_ray_tune pid=1075263)[0m [432]	train-mlogloss:1.05276	validation-mlogloss:1.04412
[36m(train_xgb_ray_tune pid=1075263)[0m [433]	train-mlogloss:1.05247	validation-mlogloss:1.04387
[36m(train_xgb_ray_tune pid=1075263)[0m [434]	train-mlogloss:1.05221	validation-mlogloss:1.04363
[36m(train_xgb_ray_tune pid=1075263)[0m [435]	train-mlogloss:1.05200	validation-mlogloss:1.04341
[36m(train_xgb_ray_tune pid=1075296)[0m [507]	train-mlogloss:0.94058	validation-mlogloss:0.96131
[36m(train_xgb_ray_tune pid=1075296)[0m [508]	train-mlogloss:0.94054	validation-mlogloss:0.96128
[36m(train_xgb_ray_tune pid=1075296)[0m [509]	train-mlogloss:0.94051	validation-mlogloss:0.96125
[36m(train_xgb_ray_tune pid=1075296)[0m [510]	train-mlogloss:0.94037	validation-mlogloss:0.96104
[36m(train_xgb_ray_tune pid=1075296)[0m [511]	train-mlogloss:0.94037	validation-mlogloss:0.96105
[36m(train_xgb_ray_tune pid=1075296)[0m [512]	train-mlogloss:0.94022	validation-mlogloss:0.96099
[36m(train_xgb_ray_tune pid=1075296)[0m [513]	train-mlogloss:0.94014	validation-mlogloss:0.96084
[36m(train_xgb_ray_tune pid=1075296)[0m [514]	train-mlogloss:0.94014	validation-mlogloss:0.96084
[36m(train_xgb_ray_tune pid=1075296)[0m [515]	train-mlogloss:0.94014	validation-mlogloss:0.96084
[36m(train_xgb_ray_tune pid=1075296)[0m [516]	train-mlogloss:0.94014	validation-mlogloss:0.96084
[36m(train_xgb_ray_tune pid=1075296)[0m [517]	train-mlogloss:0.94005	validation-mlogloss:0.96069
[36m(train_xgb_ray_tune pid=1075296)[0m [518]	train-mlogloss:0.94005	validation-mlogloss:0.96068
[36m(train_xgb_ray_tune pid=1075296)[0m [519]	train-mlogloss:0.94005	validation-mlogloss:0.96068
[36m(train_xgb_ray_tune pid=1075296)[0m [520]	train-mlogloss:0.94005	validation-mlogloss:0.96068
[36m(train_xgb_ray_tune pid=1075296)[0m [521]	train-mlogloss:0.94005	validation-mlogloss:0.96068
[36m(train_xgb_ray_tune pid=1075289)[0m [399]	train-mlogloss:1.03362	validation-mlogloss:1.03109
[36m(train_xgb_ray_tune pid=1075289)[0m [400]	train-mlogloss:1.03335	validation-mlogloss:1.03083
[36m(train_xgb_ray_tune pid=1075289)[0m [401]	train-mlogloss:1.03307	validation-mlogloss:1.03057
[36m(train_xgb_ray_tune pid=1075289)[0m [402]	train-mlogloss:1.03272	validation-mlogloss:1.03022
[36m(train_xgb_ray_tune pid=1075289)[0m [403]	train-mlogloss:1.03238	validation-mlogloss:1.02993
[36m(train_xgb_ray_tune pid=1075289)[0m [404]	train-mlogloss:1.03219	validation-mlogloss:1.02975
[36m(train_xgb_ray_tune pid=1075289)[0m [405]	train-mlogloss:1.03191	validation-mlogloss:1.02948
[36m(train_xgb_ray_tune pid=1075289)[0m [406]	train-mlogloss:1.03160	validation-mlogloss:1.02923
[36m(train_xgb_ray_tune pid=1075289)[0m [407]	train-mlogloss:1.03130	validation-mlogloss:1.02900
[36m(train_xgb_ray_tune pid=1075289)[0m [408]	train-mlogloss:1.03103	validation-mlogloss:1.02877
[36m(train_xgb_ray_tune pid=1075292)[0m [388]	train-mlogloss:0.98786	validation-mlogloss:1.00378
[36m(train_xgb_ray_tune pid=1075292)[0m [389]	train-mlogloss:0.98744	validation-mlogloss:1.00345
[36m(train_xgb_ray_tune pid=1075292)[0m [390]	train-mlogloss:0.98704	validation-mlogloss:1.00313
[36m(train_xgb_ray_tune pid=1075292)[0m [391]	train-mlogloss:0.98664	validation-mlogloss:1.00284
[36m(train_xgb_ray_tune pid=1075292)[0m [392]	train-mlogloss:0.98618	validation-mlogloss:1.00247
[36m(train_xgb_ray_tune pid=1075292)[0m [393]	train-mlogloss:0.98575	validation-mlogloss:1.00212
[36m(train_xgb_ray_tune pid=1075292)[0m [394]	train-mlogloss:0.98534	validation-mlogloss:1.00173
[36m(train_xgb_ray_tune pid=1075292)[0m [395]	train-mlogloss:0.98490	validation-mlogloss:1.00137
[36m(train_xgb_ray_tune pid=1075270)[0m [546]	train-mlogloss:0.98524	validation-mlogloss:0.98732
[36m(train_xgb_ray_tune pid=1075262)[0m [625]	train-mlogloss:0.88552	validation-mlogloss:0.91802
[36m(train_xgb_ray_tune pid=1075263)[0m [436]	train-mlogloss:1.05180	validation-mlogloss:1.04319
[36m(train_xgb_ray_tune pid=1075296)[0m [522]	train-mlogloss:0.94005	validation-mlogloss:0.96068
[36m(train_xgb_ray_tune pid=1075289)[0m [409]	train-mlogloss:1.03075	validation-mlogloss:1.02852
[36m(train_xgb_ray_tune pid=1075292)[0m [396]	train-mlogloss:0.98445	validation-mlogloss:1.00104

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:29. Total running time: 20s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             16.9954 │
│ time_total_s                 16.9954 │
│ training_iteration                 1 │
│ validation_accuracy          0.63202 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:29. Total running time: 20s
[36m(train_xgb_ray_tune pid=1075262)[0m [626]	train-mlogloss:0.88545	validation-mlogloss:0.91799
[36m(train_xgb_ray_tune pid=1075262)[0m [627]	train-mlogloss:0.88538	validation-mlogloss:0.91792
[36m(train_xgb_ray_tune pid=1075262)[0m [628]	train-mlogloss:0.88526	validation-mlogloss:0.91778
[36m(train_xgb_ray_tune pid=1075262)[0m [629]	train-mlogloss:0.88521	validation-mlogloss:0.91780
[36m(train_xgb_ray_tune pid=1075262)[0m [630]	train-mlogloss:0.88515	validation-mlogloss:0.91772
[36m(train_xgb_ray_tune pid=1075262)[0m [631]	train-mlogloss:0.88503	validation-mlogloss:0.91766
[36m(train_xgb_ray_tune pid=1075262)[0m [632]	train-mlogloss:0.88497	validation-mlogloss:0.91765
[36m(train_xgb_ray_tune pid=1075262)[0m [633]	train-mlogloss:0.88490	validation-mlogloss:0.91760
[36m(train_xgb_ray_tune pid=1075262)[0m [634]	train-mlogloss:0.88483	validation-mlogloss:0.91755
[36m(train_xgb_ray_tune pid=1075262)[0m [635]	train-mlogloss:0.88476	validation-mlogloss:0.91748
[36m(train_xgb_ray_tune pid=1075262)[0m [636]	train-mlogloss:0.88466	validation-mlogloss:0.91745
[36m(train_xgb_ray_tune pid=1075262)[0m [637]	train-mlogloss:0.88454	validation-mlogloss:0.91737
[36m(train_xgb_ray_tune pid=1075262)[0m [638]	train-mlogloss:0.88443	validation-mlogloss:0.91737
[36m(train_xgb_ray_tune pid=1075262)[0m [639]	train-mlogloss:0.88437	validation-mlogloss:0.91737
[36m(train_xgb_ray_tune pid=1075262)[0m [640]	train-mlogloss:0.88430	validation-mlogloss:0.91732
[36m(train_xgb_ray_tune pid=1075263)[0m [437]	train-mlogloss:1.05155	validation-mlogloss:1.04294
[36m(train_xgb_ray_tune pid=1075263)[0m [438]	train-mlogloss:1.05125	validation-mlogloss:1.04262
[36m(train_xgb_ray_tune pid=1075263)[0m [439]	train-mlogloss:1.05098	validation-mlogloss:1.04238
[36m(train_xgb_ray_tune pid=1075263)[0m [440]	train-mlogloss:1.05075	validation-mlogloss:1.04214
[36m(train_xgb_ray_tune pid=1075263)[0m [441]	train-mlogloss:1.05052	validation-mlogloss:1.04195
[36m(train_xgb_ray_tune pid=1075263)[0m [442]	train-mlogloss:1.05020	validation-mlogloss:1.04162
[36m(train_xgb_ray_tune pid=1075263)[0m [443]	train-mlogloss:1.05000	validation-mlogloss:1.04141
[36m(train_xgb_ray_tune pid=1075263)[0m [444]	train-mlogloss:1.04978	validation-mlogloss:1.04122
[36m(train_xgb_ray_tune pid=1075263)[0m [445]	train-mlogloss:1.04950	validation-mlogloss:1.04094
[36m(train_xgb_ray_tune pid=1075263)[0m [446]	train-mlogloss:1.04929	validation-mlogloss:1.04070
[36m(train_xgb_ray_tune pid=1075263)[0m [447]	train-mlogloss:1.04899	validation-mlogloss:1.04045
[36m(train_xgb_ray_tune pid=1075296)[0m [523]	train-mlogloss:0.94005	validation-mlogloss:0.96067
[36m(train_xgb_ray_tune pid=1075296)[0m [524]	train-mlogloss:0.94005	validation-mlogloss:0.96067
[36m(train_xgb_ray_tune pid=1075296)[0m [525]	train-mlogloss:0.94001	validation-mlogloss:0.96064
[36m(train_xgb_ray_tune pid=1075296)[0m [526]	train-mlogloss:0.94001	validation-mlogloss:0.96064
[36m(train_xgb_ray_tune pid=1075296)[0m [527]	train-mlogloss:0.94001	validation-mlogloss:0.96064
[36m(train_xgb_ray_tune pid=1075296)[0m [528]	train-mlogloss:0.94001	validation-mlogloss:0.96064
[36m(train_xgb_ray_tune pid=1075296)[0m [529]	train-mlogloss:0.94001	validation-mlogloss:0.96064
[36m(train_xgb_ray_tune pid=1075296)[0m [530]	train-mlogloss:0.94001	validation-mlogloss:0.96064
[36m(train_xgb_ray_tune pid=1075296)[0m [531]	train-mlogloss:0.94001	validation-mlogloss:0.96064
[36m(train_xgb_ray_tune pid=1075296)[0m [532]	train-mlogloss:0.94001	validation-mlogloss:0.96064
[36m(train_xgb_ray_tune pid=1075296)[0m [533]	train-mlogloss:0.94001	validation-mlogloss:0.96064
[36m(train_xgb_ray_tune pid=1075296)[0m [534]	train-mlogloss:0.94001	validation-mlogloss:0.96064
[36m(train_xgb_ray_tune pid=1075296)[0m [535]	train-mlogloss:0.93993	validation-mlogloss:0.96059
[36m(train_xgb_ray_tune pid=1075296)[0m [536]	train-mlogloss:0.93984	validation-mlogloss:0.96057
[36m(train_xgb_ray_tune pid=1075296)[0m [537]	train-mlogloss:0.93984	validation-mlogloss:0.96057
[36m(train_xgb_ray_tune pid=1075296)[0m [538]	train-mlogloss:0.93984	validation-mlogloss:0.96057
[36m(train_xgb_ray_tune pid=1075289)[0m [410]	train-mlogloss:1.03048	validation-mlogloss:1.02829
[36m(train_xgb_ray_tune pid=1075289)[0m [411]	train-mlogloss:1.03016	validation-mlogloss:1.02795
[36m(train_xgb_ray_tune pid=1075289)[0m [412]	train-mlogloss:1.02984	validation-mlogloss:1.02768
[36m(train_xgb_ray_tune pid=1075289)[0m [413]	train-mlogloss:1.02959	validation-mlogloss:1.02748
[36m(train_xgb_ray_tune pid=1075289)[0m [414]	train-mlogloss:1.02927	validation-mlogloss:1.02717
[36m(train_xgb_ray_tune pid=1075289)[0m [415]	train-mlogloss:1.02903	validation-mlogloss:1.02696
[36m(train_xgb_ray_tune pid=1075289)[0m [416]	train-mlogloss:1.02876	validation-mlogloss:1.02663
[36m(train_xgb_ray_tune pid=1075289)[0m [417]	train-mlogloss:1.02846	validation-mlogloss:1.02632
[36m(train_xgb_ray_tune pid=1075289)[0m [418]	train-mlogloss:1.02804	validation-mlogloss:1.02593
[36m(train_xgb_ray_tune pid=1075289)[0m [419]	train-mlogloss:1.02772	validation-mlogloss:1.02565
[36m(train_xgb_ray_tune pid=1075292)[0m [397]	train-mlogloss:0.98398	validation-mlogloss:1.00066
[36m(train_xgb_ray_tune pid=1075292)[0m [398]	train-mlogloss:0.98353	validation-mlogloss:1.00027
[36m(train_xgb_ray_tune pid=1075292)[0m [399]	train-mlogloss:0.98315	validation-mlogloss:0.99996
[36m(train_xgb_ray_tune pid=1075292)[0m [400]	train-mlogloss:0.98279	validation-mlogloss:0.99972
[36m(train_xgb_ray_tune pid=1075292)[0m [401]	train-mlogloss:0.98241	validation-mlogloss:0.99943
[36m(train_xgb_ray_tune pid=1075292)[0m [402]	train-mlogloss:0.98201	validation-mlogloss:0.99912
[36m(train_xgb_ray_tune pid=1075292)[0m [403]	train-mlogloss:0.98165	validation-mlogloss:0.99880
[36m(train_xgb_ray_tune pid=1075292)[0m [404]	train-mlogloss:0.98118	validation-mlogloss:0.99846
[36m(train_xgb_ray_tune pid=1075292)[0m [405]	train-mlogloss:0.98079	validation-mlogloss:0.99810
[36m(train_xgb_ray_tune pid=1075263)[0m [448]	train-mlogloss:1.04870	validation-mlogloss:1.04022
[36m(train_xgb_ray_tune pid=1075296)[0m [539]	train-mlogloss:0.93984	validation-mlogloss:0.96056
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[36m(train_xgb_ray_tune pid=1075296)[0m [582]	train-mlogloss:0.93903	validation-mlogloss:0.96002
[36m(train_xgb_ray_tune pid=1075296)[0m [583]	train-mlogloss:0.93903	validation-mlogloss:0.96002
[36m(train_xgb_ray_tune pid=1075296)[0m [584]	train-mlogloss:0.93903	validation-mlogloss:0.96002
[36m(train_xgb_ray_tune pid=1075296)[0m [585]	train-mlogloss:0.93899	validation-mlogloss:0.95999
[36m(train_xgb_ray_tune pid=1075296)[0m [586]	train-mlogloss:0.93899	validation-mlogloss:0.95999
[36m(train_xgb_ray_tune pid=1075296)[0m [587]	train-mlogloss:0.93890	validation-mlogloss:0.95997
[36m(train_xgb_ray_tune pid=1075289)[0m [443]	train-mlogloss:1.02098	validation-mlogloss:1.01969
[36m(train_xgb_ray_tune pid=1075289)[0m [444]	train-mlogloss:1.02075	validation-mlogloss:1.01952
[36m(train_xgb_ray_tune pid=1075289)[0m [445]	train-mlogloss:1.02044	validation-mlogloss:1.01924
[36m(train_xgb_ray_tune pid=1075289)[0m [446]	train-mlogloss:1.02015	validation-mlogloss:1.01902
[36m(train_xgb_ray_tune pid=1075289)[0m [447]	train-mlogloss:1.01990	validation-mlogloss:1.01879
[36m(train_xgb_ray_tune pid=1075289)[0m [448]	train-mlogloss:1.01967	validation-mlogloss:1.01866
[36m(train_xgb_ray_tune pid=1075289)[0m [449]	train-mlogloss:1.01942	validation-mlogloss:1.01845
[36m(train_xgb_ray_tune pid=1075289)[0m [450]	train-mlogloss:1.01924	validation-mlogloss:1.01825
[36m(train_xgb_ray_tune pid=1075289)[0m [451]	train-mlogloss:1.01901	validation-mlogloss:1.01802
[36m(train_xgb_ray_tune pid=1075289)[0m [452]	train-mlogloss:1.01875	validation-mlogloss:1.01775
[36m(train_xgb_ray_tune pid=1075289)[0m [453]	train-mlogloss:1.01848	validation-mlogloss:1.01745
[36m(train_xgb_ray_tune pid=1075292)[0m [425]	train-mlogloss:0.97335	validation-mlogloss:0.99209
[36m(train_xgb_ray_tune pid=1075292)[0m [426]	train-mlogloss:0.97303	validation-mlogloss:0.99185
[36m(train_xgb_ray_tune pid=1075292)[0m [427]	train-mlogloss:0.97264	validation-mlogloss:0.99154
[36m(train_xgb_ray_tune pid=1075292)[0m [428]	train-mlogloss:0.97230	validation-mlogloss:0.99126
[36m(train_xgb_ray_tune pid=1075292)[0m [429]	train-mlogloss:0.97199	validation-mlogloss:0.99095
[36m(train_xgb_ray_tune pid=1075292)[0m [430]	train-mlogloss:0.97165	validation-mlogloss:0.99059
[36m(train_xgb_ray_tune pid=1075292)[0m [431]	train-mlogloss:0.97124	validation-mlogloss:0.99016
[36m(train_xgb_ray_tune pid=1075292)[0m [432]	train-mlogloss:0.97088	validation-mlogloss:0.98991
[36m(train_xgb_ray_tune pid=1075292)[0m [433]	train-mlogloss:0.97049	validation-mlogloss:0.98954
[36m(train_xgb_ray_tune pid=1075263)[0m [485]	train-mlogloss:1.03961	validation-mlogloss:1.03204
[36m(train_xgb_ray_tune pid=1075262)[0m [689]	train-mlogloss:0.88060	validation-mlogloss:0.91484

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:29. Total running time: 20s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s              17.736 │
│ time_total_s                  17.736 │
│ training_iteration                 1 │
│ validation_accuracy          0.63904 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:29. Total running time: 20s
[36m(train_xgb_ray_tune pid=1075262)[0m [690]	train-mlogloss:0.88053	validation-mlogloss:0.91483
[36m(train_xgb_ray_tune pid=1075262)[0m [691]	train-mlogloss:0.88046	validation-mlogloss:0.91478
[36m(train_xgb_ray_tune pid=1075262)[0m [692]	train-mlogloss:0.88042	validation-mlogloss:0.91477
[36m(train_xgb_ray_tune pid=1075262)[0m [693]	train-mlogloss:0.88039	validation-mlogloss:0.91477
[36m(train_xgb_ray_tune pid=1075262)[0m [694]	train-mlogloss:0.88032	validation-mlogloss:0.91474
[36m(train_xgb_ray_tune pid=1075262)[0m [695]	train-mlogloss:0.88025	validation-mlogloss:0.91463
[36m(train_xgb_ray_tune pid=1075262)[0m [696]	train-mlogloss:0.88017	validation-mlogloss:0.91458
[36m(train_xgb_ray_tune pid=1075262)[0m [697]	train-mlogloss:0.88008	validation-mlogloss:0.91450
[36m(train_xgb_ray_tune pid=1075262)[0m [698]	train-mlogloss:0.88000	validation-mlogloss:0.91443
[36m(train_xgb_ray_tune pid=1075262)[0m [699]	train-mlogloss:0.87993	validation-mlogloss:0.91442
[36m(train_xgb_ray_tune pid=1075262)[0m [700]	train-mlogloss:0.87988	validation-mlogloss:0.91443
[36m(train_xgb_ray_tune pid=1075262)[0m [701]	train-mlogloss:0.87982	validation-mlogloss:0.91439
[36m(train_xgb_ray_tune pid=1075262)[0m [702]	train-mlogloss:0.87977	validation-mlogloss:0.91437
[36m(train_xgb_ray_tune pid=1075262)[0m [703]	train-mlogloss:0.87973	validation-mlogloss:0.91438
[36m(train_xgb_ray_tune pid=1075262)[0m [704]	train-mlogloss:0.87963	validation-mlogloss:0.91426
[36m(train_xgb_ray_tune pid=1075263)[0m [486]	train-mlogloss:1.03942	validation-mlogloss:1.03187
[36m(train_xgb_ray_tune pid=1075263)[0m [487]	train-mlogloss:1.03920	validation-mlogloss:1.03168
[36m(train_xgb_ray_tune pid=1075263)[0m [488]	train-mlogloss:1.03896	validation-mlogloss:1.03151
[36m(train_xgb_ray_tune pid=1075263)[0m [489]	train-mlogloss:1.03877	validation-mlogloss:1.03132
[36m(train_xgb_ray_tune pid=1075263)[0m [490]	train-mlogloss:1.03852	validation-mlogloss:1.03107
[36m(train_xgb_ray_tune pid=1075263)[0m [491]	train-mlogloss:1.03837	validation-mlogloss:1.03093
[36m(train_xgb_ray_tune pid=1075263)[0m [492]	train-mlogloss:1.03809	validation-mlogloss:1.03072
[36m(train_xgb_ray_tune pid=1075263)[0m [493]	train-mlogloss:1.03789	validation-mlogloss:1.03058
[36m(train_xgb_ray_tune pid=1075263)[0m [494]	train-mlogloss:1.03771	validation-mlogloss:1.03039
[36m(train_xgb_ray_tune pid=1075263)[0m [495]	train-mlogloss:1.03749	validation-mlogloss:1.03021
[36m(train_xgb_ray_tune pid=1075263)[0m [496]	train-mlogloss:1.03727	validation-mlogloss:1.03002
[36m(train_xgb_ray_tune pid=1075263)[0m [497]	train-mlogloss:1.03705	validation-mlogloss:1.02982
[36m(train_xgb_ray_tune pid=1075289)[0m [454]	train-mlogloss:1.01820	validation-mlogloss:1.01721
[36m(train_xgb_ray_tune pid=1075289)[0m [455]	train-mlogloss:1.01796	validation-mlogloss:1.01697
[36m(train_xgb_ray_tune pid=1075289)[0m [456]	train-mlogloss:1.01772	validation-mlogloss:1.01674
[36m(train_xgb_ray_tune pid=1075289)[0m [457]	train-mlogloss:1.01743	validation-mlogloss:1.01648
[36m(train_xgb_ray_tune pid=1075289)[0m [458]	train-mlogloss:1.01718	validation-mlogloss:1.01622
[36m(train_xgb_ray_tune pid=1075289)[0m [459]	train-mlogloss:1.01699	validation-mlogloss:1.01608
[36m(train_xgb_ray_tune pid=1075289)[0m [460]	train-mlogloss:1.01672	validation-mlogloss:1.01586
[36m(train_xgb_ray_tune pid=1075289)[0m [461]	train-mlogloss:1.01646	validation-mlogloss:1.01560
[36m(train_xgb_ray_tune pid=1075289)[0m [462]	train-mlogloss:1.01620	validation-mlogloss:1.01536
[36m(train_xgb_ray_tune pid=1075289)[0m [463]	train-mlogloss:1.01605	validation-mlogloss:1.01523
[36m(train_xgb_ray_tune pid=1075289)[0m [464]	train-mlogloss:1.01582	validation-mlogloss:1.01502
[36m(train_xgb_ray_tune pid=1075292)[0m [434]	train-mlogloss:0.97018	validation-mlogloss:0.98931
[36m(train_xgb_ray_tune pid=1075292)[0m [435]	train-mlogloss:0.96982	validation-mlogloss:0.98903
[36m(train_xgb_ray_tune pid=1075292)[0m [436]	train-mlogloss:0.96947	validation-mlogloss:0.98875
[36m(train_xgb_ray_tune pid=1075292)[0m [437]	train-mlogloss:0.96909	validation-mlogloss:0.98845
[36m(train_xgb_ray_tune pid=1075292)[0m [438]	train-mlogloss:0.96876	validation-mlogloss:0.98816
[36m(train_xgb_ray_tune pid=1075292)[0m [439]	train-mlogloss:0.96840	validation-mlogloss:0.98788
[36m(train_xgb_ray_tune pid=1075292)[0m [440]	train-mlogloss:0.96806	validation-mlogloss:0.98760
[36m(train_xgb_ray_tune pid=1075292)[0m [441]	train-mlogloss:0.96779	validation-mlogloss:0.98736
[36m(train_xgb_ray_tune pid=1075292)[0m [442]	train-mlogloss:0.96746	validation-mlogloss:0.98713
[36m(train_xgb_ray_tune pid=1075263)[0m [498]	train-mlogloss:1.03685	validation-mlogloss:1.02965
[36m(train_xgb_ray_tune pid=1075262)[0m [705]	train-mlogloss:0.87946	validation-mlogloss:0.91411
[36m(train_xgb_ray_tune pid=1075262)[0m [706]	train-mlogloss:0.87937	validation-mlogloss:0.91408
[36m(train_xgb_ray_tune pid=1075262)[0m [707]	train-mlogloss:0.87932	validation-mlogloss:0.91407
[36m(train_xgb_ray_tune pid=1075262)[0m [708]	train-mlogloss:0.87927	validation-mlogloss:0.91401
[36m(train_xgb_ray_tune pid=1075262)[0m [709]	train-mlogloss:0.87919	validation-mlogloss:0.91394
[36m(train_xgb_ray_tune pid=1075262)[0m [710]	train-mlogloss:0.87912	validation-mlogloss:0.91388
[36m(train_xgb_ray_tune pid=1075262)[0m [711]	train-mlogloss:0.87907	validation-mlogloss:0.91382
[36m(train_xgb_ray_tune pid=1075262)[0m [712]	train-mlogloss:0.87903	validation-mlogloss:0.91379
[36m(train_xgb_ray_tune pid=1075262)[0m [713]	train-mlogloss:0.87896	validation-mlogloss:0.91377
[36m(train_xgb_ray_tune pid=1075263)[0m [499]	train-mlogloss:1.03663	validation-mlogloss:1.02947
[36m(train_xgb_ray_tune pid=1075263)[0m [500]	train-mlogloss:1.03642	validation-mlogloss:1.02929
[36m(train_xgb_ray_tune pid=1075263)[0m [501]	train-mlogloss:1.03618	validation-mlogloss:1.02900
[36m(train_xgb_ray_tune pid=1075263)[0m [502]	train-mlogloss:1.03598	validation-mlogloss:1.02888
[36m(train_xgb_ray_tune pid=1075263)[0m [503]	train-mlogloss:1.03577	validation-mlogloss:1.02872
[36m(train_xgb_ray_tune pid=1075263)[0m [504]	train-mlogloss:1.03558	validation-mlogloss:1.02857
[36m(train_xgb_ray_tune pid=1075263)[0m [505]	train-mlogloss:1.03539	validation-mlogloss:1.02839
[36m(train_xgb_ray_tune pid=1075263)[0m [506]	train-mlogloss:1.03517	validation-mlogloss:1.02825
[36m(train_xgb_ray_tune pid=1075263)[0m [507]	train-mlogloss:1.03495	validation-mlogloss:1.02805
[36m(train_xgb_ray_tune pid=1075263)[0m [508]	train-mlogloss:1.03474	validation-mlogloss:1.02784
[36m(train_xgb_ray_tune pid=1075263)[0m [509]	train-mlogloss:1.03461	validation-mlogloss:1.02769
[36m(train_xgb_ray_tune pid=1075263)[0m [510]	train-mlogloss:1.03442	validation-mlogloss:1.02753
[36m(train_xgb_ray_tune pid=1075289)[0m [465]	train-mlogloss:1.01559	validation-mlogloss:1.01478
[36m(train_xgb_ray_tune pid=1075289)[0m [466]	train-mlogloss:1.01533	validation-mlogloss:1.01447
[36m(train_xgb_ray_tune pid=1075289)[0m [467]	train-mlogloss:1.01507	validation-mlogloss:1.01421
[36m(train_xgb_ray_tune pid=1075289)[0m [468]	train-mlogloss:1.01474	validation-mlogloss:1.01391
[36m(train_xgb_ray_tune pid=1075289)[0m [469]	train-mlogloss:1.01449	validation-mlogloss:1.01376
[36m(train_xgb_ray_tune pid=1075289)[0m [470]	train-mlogloss:1.01428	validation-mlogloss:1.01360
[36m(train_xgb_ray_tune pid=1075289)[0m [471]	train-mlogloss:1.01407	validation-mlogloss:1.01341
[36m(train_xgb_ray_tune pid=1075289)[0m [472]	train-mlogloss:1.01379	validation-mlogloss:1.01318
[36m(train_xgb_ray_tune pid=1075289)[0m [473]	train-mlogloss:1.01361	validation-mlogloss:1.01303
[36m(train_xgb_ray_tune pid=1075289)[0m [474]	train-mlogloss:1.01341	validation-mlogloss:1.01287
[36m(train_xgb_ray_tune pid=1075289)[0m [475]	train-mlogloss:1.01321	validation-mlogloss:1.01267
[36m(train_xgb_ray_tune pid=1075292)[0m [443]	train-mlogloss:0.96712	validation-mlogloss:0.98686
[36m(train_xgb_ray_tune pid=1075292)[0m [444]	train-mlogloss:0.96679	validation-mlogloss:0.98657
[36m(train_xgb_ray_tune pid=1075292)[0m [445]	train-mlogloss:0.96646	validation-mlogloss:0.98630
[36m(train_xgb_ray_tune pid=1075292)[0m [446]	train-mlogloss:0.96607	validation-mlogloss:0.98600
[36m(train_xgb_ray_tune pid=1075292)[0m [447]	train-mlogloss:0.96571	validation-mlogloss:0.98571
[36m(train_xgb_ray_tune pid=1075292)[0m [448]	train-mlogloss:0.96539	validation-mlogloss:0.98542
[36m(train_xgb_ray_tune pid=1075292)[0m [449]	train-mlogloss:0.96505	validation-mlogloss:0.98515
[36m(train_xgb_ray_tune pid=1075292)[0m [450]	train-mlogloss:0.96471	validation-mlogloss:0.98488
[36m(train_xgb_ray_tune pid=1075292)[0m [451]	train-mlogloss:0.96443	validation-mlogloss:0.98465
[36m(train_xgb_ray_tune pid=1075263)[0m [511]	train-mlogloss:1.03423	validation-mlogloss:1.02736
[36m(train_xgb_ray_tune pid=1075292)[0m [452]	train-mlogloss:0.96406	validation-mlogloss:0.98429
[36m(train_xgb_ray_tune pid=1075289)[0m [476]	train-mlogloss:1.01294	validation-mlogloss:1.01243
[36m(train_xgb_ray_tune pid=1075263)[0m [512]	train-mlogloss:1.03400	validation-mlogloss:1.02711

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:29. Total running time: 20s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             17.8717 │
│ time_total_s                 17.8717 │
│ training_iteration                 1 │
│ validation_accuracy          0.65098 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:29. Total running time: 20s
[36m(train_xgb_ray_tune pid=1075263)[0m [513]	train-mlogloss:1.03378	validation-mlogloss:1.02692
[36m(train_xgb_ray_tune pid=1075263)[0m [514]	train-mlogloss:1.03361	validation-mlogloss:1.02679
[36m(train_xgb_ray_tune pid=1075263)[0m [515]	train-mlogloss:1.03341	validation-mlogloss:1.02660
[36m(train_xgb_ray_tune pid=1075263)[0m [516]	train-mlogloss:1.03318	validation-mlogloss:1.02636
[36m(train_xgb_ray_tune pid=1075263)[0m [517]	train-mlogloss:1.03296	validation-mlogloss:1.02615
[36m(train_xgb_ray_tune pid=1075263)[0m [518]	train-mlogloss:1.03278	validation-mlogloss:1.02599
[36m(train_xgb_ray_tune pid=1075263)[0m [519]	train-mlogloss:1.03257	validation-mlogloss:1.02583
[36m(train_xgb_ray_tune pid=1075263)[0m [520]	train-mlogloss:1.03240	validation-mlogloss:1.02568
[36m(train_xgb_ray_tune pid=1075263)[0m [521]	train-mlogloss:1.03223	validation-mlogloss:1.02554
[36m(train_xgb_ray_tune pid=1075263)[0m [522]	train-mlogloss:1.03205	validation-mlogloss:1.02539
[36m(train_xgb_ray_tune pid=1075263)[0m [523]	train-mlogloss:1.03184	validation-mlogloss:1.02522
[36m(train_xgb_ray_tune pid=1075263)[0m [524]	train-mlogloss:1.03169	validation-mlogloss:1.02507
[36m(train_xgb_ray_tune pid=1075289)[0m [477]	train-mlogloss:1.01271	validation-mlogloss:1.01224
[36m(train_xgb_ray_tune pid=1075289)[0m [478]	train-mlogloss:1.01242	validation-mlogloss:1.01197
[36m(train_xgb_ray_tune pid=1075289)[0m [479]	train-mlogloss:1.01224	validation-mlogloss:1.01181
[36m(train_xgb_ray_tune pid=1075289)[0m [480]	train-mlogloss:1.01197	validation-mlogloss:1.01156
[36m(train_xgb_ray_tune pid=1075289)[0m [481]	train-mlogloss:1.01174	validation-mlogloss:1.01132
[36m(train_xgb_ray_tune pid=1075289)[0m [482]	train-mlogloss:1.01154	validation-mlogloss:1.01113
[36m(train_xgb_ray_tune pid=1075289)[0m [483]	train-mlogloss:1.01127	validation-mlogloss:1.01091
[36m(train_xgb_ray_tune pid=1075289)[0m [484]	train-mlogloss:1.01110	validation-mlogloss:1.01078
[36m(train_xgb_ray_tune pid=1075289)[0m [485]	train-mlogloss:1.01088	validation-mlogloss:1.01060
[36m(train_xgb_ray_tune pid=1075289)[0m [486]	train-mlogloss:1.01061	validation-mlogloss:1.01040
[36m(train_xgb_ray_tune pid=1075289)[0m [487]	train-mlogloss:1.01028	validation-mlogloss:1.01001
[36m(train_xgb_ray_tune pid=1075292)[0m [453]	train-mlogloss:0.96376	validation-mlogloss:0.98405
[36m(train_xgb_ray_tune pid=1075292)[0m [454]	train-mlogloss:0.96339	validation-mlogloss:0.98365
[36m(train_xgb_ray_tune pid=1075292)[0m [455]	train-mlogloss:0.96304	validation-mlogloss:0.98325
[36m(train_xgb_ray_tune pid=1075292)[0m [456]	train-mlogloss:0.96270	validation-mlogloss:0.98298
[36m(train_xgb_ray_tune pid=1075292)[0m [457]	train-mlogloss:0.96236	validation-mlogloss:0.98265
[36m(train_xgb_ray_tune pid=1075292)[0m [458]	train-mlogloss:0.96202	validation-mlogloss:0.98240
[36m(train_xgb_ray_tune pid=1075292)[0m [459]	train-mlogloss:0.96170	validation-mlogloss:0.98212
[36m(train_xgb_ray_tune pid=1075292)[0m [460]	train-mlogloss:0.96140	validation-mlogloss:0.98182
[36m(train_xgb_ray_tune pid=1075292)[0m [461]	train-mlogloss:0.96105	validation-mlogloss:0.98150
[36m(train_xgb_ray_tune pid=1075263)[0m [525]	train-mlogloss:1.03151	validation-mlogloss:1.02489
[36m(train_xgb_ray_tune pid=1075263)[0m [526]	train-mlogloss:1.03135	validation-mlogloss:1.02475
[36m(train_xgb_ray_tune pid=1075263)[0m [527]	train-mlogloss:1.03118	validation-mlogloss:1.02459
[36m(train_xgb_ray_tune pid=1075263)[0m [528]	train-mlogloss:1.03096	validation-mlogloss:1.02435
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[36m(train_xgb_ray_tune pid=1075289)[0m [669]	train-mlogloss:0.98097	validation-mlogloss:0.98518
[36m(train_xgb_ray_tune pid=1075289)[0m [670]	train-mlogloss:0.98082	validation-mlogloss:0.98504
[36m(train_xgb_ray_tune pid=1075292)[0m [593]	train-mlogloss:0.92441	validation-mlogloss:0.95339
[36m(train_xgb_ray_tune pid=1075292)[0m [594]	train-mlogloss:0.92416	validation-mlogloss:0.95323
[36m(train_xgb_ray_tune pid=1075292)[0m [595]	train-mlogloss:0.92387	validation-mlogloss:0.95307
[36m(train_xgb_ray_tune pid=1075292)[0m [596]	train-mlogloss:0.92364	validation-mlogloss:0.95299
[36m(train_xgb_ray_tune pid=1075292)[0m [597]	train-mlogloss:0.92344	validation-mlogloss:0.95284
[36m(train_xgb_ray_tune pid=1075292)[0m [598]	train-mlogloss:0.92319	validation-mlogloss:0.95264
[36m(train_xgb_ray_tune pid=1075292)[0m [599]	train-mlogloss:0.92294	validation-mlogloss:0.95242
[36m(train_xgb_ray_tune pid=1075292)[0m [600]	train-mlogloss:0.92273	validation-mlogloss:0.95227
[36m(train_xgb_ray_tune pid=1075292)[0m [601]	train-mlogloss:0.92251	validation-mlogloss:0.95213
[36m(train_xgb_ray_tune pid=1075292)[0m [602]	train-mlogloss:0.92229	validation-mlogloss:0.95201
[36m(train_xgb_ray_tune pid=1075263)[0m [720]	train-mlogloss:1.00373	validation-mlogloss:1.00131
[36m(train_xgb_ray_tune pid=1075263)[0m [721]	train-mlogloss:1.00359	validation-mlogloss:1.00116
[36m(train_xgb_ray_tune pid=1075263)[0m [722]	train-mlogloss:1.00348	validation-mlogloss:1.00106
[36m(train_xgb_ray_tune pid=1075263)[0m [723]	train-mlogloss:1.00339	validation-mlogloss:1.00099
[36m(train_xgb_ray_tune pid=1075263)[0m [724]	train-mlogloss:1.00328	validation-mlogloss:1.00089
[36m(train_xgb_ray_tune pid=1075263)[0m [725]	train-mlogloss:1.00317	validation-mlogloss:1.00083
[36m(train_xgb_ray_tune pid=1075289)[0m [671]	train-mlogloss:0.98070	validation-mlogloss:0.98495
[36m(train_xgb_ray_tune pid=1075289)[0m [672]	train-mlogloss:0.98060	validation-mlogloss:0.98488
[36m(train_xgb_ray_tune pid=1075289)[0m [673]	train-mlogloss:0.98049	validation-mlogloss:0.98478
[36m(train_xgb_ray_tune pid=1075289)[0m [674]	train-mlogloss:0.98035	validation-mlogloss:0.98466
[36m(train_xgb_ray_tune pid=1075289)[0m [675]	train-mlogloss:0.98020	validation-mlogloss:0.98456
[36m(train_xgb_ray_tune pid=1075289)[0m [676]	train-mlogloss:0.98009	validation-mlogloss:0.98442
[36m(train_xgb_ray_tune pid=1075289)[0m [677]	train-mlogloss:0.97993	validation-mlogloss:0.98432
[36m(train_xgb_ray_tune pid=1075289)[0m [678]	train-mlogloss:0.97987	validation-mlogloss:0.98426
[36m(train_xgb_ray_tune pid=1075289)[0m [679]	train-mlogloss:0.97977	validation-mlogloss:0.98421
[36m(train_xgb_ray_tune pid=1075289)[0m [680]	train-mlogloss:0.97962	validation-mlogloss:0.98413
[36m(train_xgb_ray_tune pid=1075289)[0m [681]	train-mlogloss:0.97951	validation-mlogloss:0.98407
[36m(train_xgb_ray_tune pid=1075289)[0m [682]	train-mlogloss:0.97941	validation-mlogloss:0.98399
[36m(train_xgb_ray_tune pid=1075292)[0m [603]	train-mlogloss:0.92208	validation-mlogloss:0.95182
[36m(train_xgb_ray_tune pid=1075292)[0m [604]	train-mlogloss:0.92183	validation-mlogloss:0.95167
[36m(train_xgb_ray_tune pid=1075292)[0m [605]	train-mlogloss:0.92158	validation-mlogloss:0.95151
[36m(train_xgb_ray_tune pid=1075292)[0m [606]	train-mlogloss:0.92136	validation-mlogloss:0.95136
[36m(train_xgb_ray_tune pid=1075292)[0m [607]	train-mlogloss:0.92118	validation-mlogloss:0.95131
[36m(train_xgb_ray_tune pid=1075292)[0m [608]	train-mlogloss:0.92093	validation-mlogloss:0.95112
[36m(train_xgb_ray_tune pid=1075292)[0m [609]	train-mlogloss:0.92071	validation-mlogloss:0.95100
[36m(train_xgb_ray_tune pid=1075292)[0m [610]	train-mlogloss:0.92052	validation-mlogloss:0.95086
[36m(train_xgb_ray_tune pid=1075292)[0m [611]	train-mlogloss:0.92030	validation-mlogloss:0.95068
[36m(train_xgb_ray_tune pid=1075292)[0m [612]	train-mlogloss:0.92008	validation-mlogloss:0.95054
[36m(train_xgb_ray_tune pid=1075289)[0m [683]	train-mlogloss:0.97927	validation-mlogloss:0.98385
[36m(train_xgb_ray_tune pid=1075292)[0m [613]	train-mlogloss:0.91983	validation-mlogloss:0.95036

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:31. Total running time: 22s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             19.7262 │
│ time_total_s                 19.7262 │
│ training_iteration                 1 │
│ validation_accuracy          0.63062 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:31. Total running time: 22s
[36m(train_xgb_ray_tune pid=1075289)[0m [684]	train-mlogloss:0.97916	validation-mlogloss:0.98375
[36m(train_xgb_ray_tune pid=1075289)[0m [685]	train-mlogloss:0.97909	validation-mlogloss:0.98369
[36m(train_xgb_ray_tune pid=1075289)[0m [686]	train-mlogloss:0.97901	validation-mlogloss:0.98363
[36m(train_xgb_ray_tune pid=1075289)[0m [687]	train-mlogloss:0.97892	validation-mlogloss:0.98357
[36m(train_xgb_ray_tune pid=1075289)[0m [688]	train-mlogloss:0.97878	validation-mlogloss:0.98350
[36m(train_xgb_ray_tune pid=1075289)[0m [689]	train-mlogloss:0.97867	validation-mlogloss:0.98342
[36m(train_xgb_ray_tune pid=1075289)[0m [690]	train-mlogloss:0.97859	validation-mlogloss:0.98339
[36m(train_xgb_ray_tune pid=1075289)[0m [691]	train-mlogloss:0.97846	validation-mlogloss:0.98329
[36m(train_xgb_ray_tune pid=1075289)[0m [692]	train-mlogloss:0.97831	validation-mlogloss:0.98316
[36m(train_xgb_ray_tune pid=1075289)[0m [693]	train-mlogloss:0.97817	validation-mlogloss:0.98304
[36m(train_xgb_ray_tune pid=1075289)[0m [694]	train-mlogloss:0.97802	validation-mlogloss:0.98291
[36m(train_xgb_ray_tune pid=1075289)[0m [695]	train-mlogloss:0.97796	validation-mlogloss:0.98287
[36m(train_xgb_ray_tune pid=1075289)[0m [696]	train-mlogloss:0.97782	validation-mlogloss:0.98275
[36m(train_xgb_ray_tune pid=1075292)[0m [614]	train-mlogloss:0.91963	validation-mlogloss:0.95014
[36m(train_xgb_ray_tune pid=1075292)[0m [615]	train-mlogloss:0.91946	validation-mlogloss:0.95003
[36m(train_xgb_ray_tune pid=1075292)[0m [616]	train-mlogloss:0.91926	validation-mlogloss:0.94986
[36m(train_xgb_ray_tune pid=1075292)[0m [617]	train-mlogloss:0.91905	validation-mlogloss:0.94964
[36m(train_xgb_ray_tune pid=1075292)[0m [618]	train-mlogloss:0.91885	validation-mlogloss:0.94947
[36m(train_xgb_ray_tune pid=1075292)[0m [619]	train-mlogloss:0.91864	validation-mlogloss:0.94930
[36m(train_xgb_ray_tune pid=1075292)[0m [620]	train-mlogloss:0.91841	validation-mlogloss:0.94918
[36m(train_xgb_ray_tune pid=1075292)[0m [621]	train-mlogloss:0.91823	validation-mlogloss:0.94906
[36m(train_xgb_ray_tune pid=1075292)[0m [622]	train-mlogloss:0.91801	validation-mlogloss:0.94894
[36m(train_xgb_ray_tune pid=1075292)[0m [623]	train-mlogloss:0.91778	validation-mlogloss:0.94873
[36m(train_xgb_ray_tune pid=1075289)[0m [697]	train-mlogloss:0.97771	validation-mlogloss:0.98267
[36m(train_xgb_ray_tune pid=1075292)[0m [624]	train-mlogloss:0.91758	validation-mlogloss:0.94859
[36m(train_xgb_ray_tune pid=1075289)[0m [698]	train-mlogloss:0.97765	validation-mlogloss:0.98262
[36m(train_xgb_ray_tune pid=1075292)[0m [625]	train-mlogloss:0.91738	validation-mlogloss:0.94847
[36m(train_xgb_ray_tune pid=1075292)[0m [626]	train-mlogloss:0.91716	validation-mlogloss:0.94836
[36m(train_xgb_ray_tune pid=1075292)[0m [627]	train-mlogloss:0.91696	validation-mlogloss:0.94822
[36m(train_xgb_ray_tune pid=1075292)[0m [628]	train-mlogloss:0.91676	validation-mlogloss:0.94807
[36m(train_xgb_ray_tune pid=1075292)[0m [629]	train-mlogloss:0.91652	validation-mlogloss:0.94794
[36m(train_xgb_ray_tune pid=1075292)[0m [630]	train-mlogloss:0.91630	validation-mlogloss:0.94777
[36m(train_xgb_ray_tune pid=1075292)[0m [631]	train-mlogloss:0.91610	validation-mlogloss:0.94760
[36m(train_xgb_ray_tune pid=1075292)[0m [632]	train-mlogloss:0.91587	validation-mlogloss:0.94742
[36m(train_xgb_ray_tune pid=1075292)[0m [633]	train-mlogloss:0.91565	validation-mlogloss:0.94724
[36m(train_xgb_ray_tune pid=1075292)[0m [634]	train-mlogloss:0.91548	validation-mlogloss:0.94708

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:31. Total running time: 22s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             19.8046 │
│ time_total_s                 19.8046 │
│ training_iteration                 1 │
│ validation_accuracy          0.63202 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:31. Total running time: 22s
[36m(train_xgb_ray_tune pid=1075292)[0m [635]	train-mlogloss:0.91525	validation-mlogloss:0.94695
[36m(train_xgb_ray_tune pid=1075292)[0m [636]	train-mlogloss:0.91503	validation-mlogloss:0.94680
[36m(train_xgb_ray_tune pid=1075292)[0m [637]	train-mlogloss:0.91484	validation-mlogloss:0.94667
[36m(train_xgb_ray_tune pid=1075292)[0m [638]	train-mlogloss:0.91468	validation-mlogloss:0.94658
[36m(train_xgb_ray_tune pid=1075292)[0m [639]	train-mlogloss:0.91446	validation-mlogloss:0.94643
[36m(train_xgb_ray_tune pid=1075292)[0m [640]	train-mlogloss:0.91426	validation-mlogloss:0.94628
[36m(train_xgb_ray_tune pid=1075292)[0m [641]	train-mlogloss:0.91407	validation-mlogloss:0.94616
[36m(train_xgb_ray_tune pid=1075292)[0m [642]	train-mlogloss:0.91386	validation-mlogloss:0.94598
[36m(train_xgb_ray_tune pid=1075292)[0m [643]	train-mlogloss:0.91362	validation-mlogloss:0.94590
[36m(train_xgb_ray_tune pid=1075292)[0m [644]	train-mlogloss:0.91340	validation-mlogloss:0.94574
[36m(train_xgb_ray_tune pid=1075292)[0m [645]	train-mlogloss:0.91324	validation-mlogloss:0.94565
[36m(train_xgb_ray_tune pid=1075292)[0m [646]	train-mlogloss:0.91308	validation-mlogloss:0.94554
[36m(train_xgb_ray_tune pid=1075292)[0m [647]	train-mlogloss:0.91285	validation-mlogloss:0.94535
[36m(train_xgb_ray_tune pid=1075292)[0m [648]	train-mlogloss:0.91270	validation-mlogloss:0.94523
[36m(train_xgb_ray_tune pid=1075292)[0m [649]	train-mlogloss:0.91250	validation-mlogloss:0.94511
[36m(train_xgb_ray_tune pid=1075292)[0m [650]	train-mlogloss:0.91235	validation-mlogloss:0.94507
[36m(train_xgb_ray_tune pid=1075292)[0m [651]	train-mlogloss:0.91218	validation-mlogloss:0.94496
[36m(train_xgb_ray_tune pid=1075292)[0m [652]	train-mlogloss:0.91200	validation-mlogloss:0.94485
[36m(train_xgb_ray_tune pid=1075292)[0m [653]	train-mlogloss:0.91181	validation-mlogloss:0.94472
[36m(train_xgb_ray_tune pid=1075292)[0m [654]	train-mlogloss:0.91162	validation-mlogloss:0.94464
[36m(train_xgb_ray_tune pid=1075292)[0m [655]	train-mlogloss:0.91141	validation-mlogloss:0.94449
[36m(train_xgb_ray_tune pid=1075292)[0m [656]	train-mlogloss:0.91126	validation-mlogloss:0.94440
[36m(train_xgb_ray_tune pid=1075292)[0m [657]	train-mlogloss:0.91110	validation-mlogloss:0.94432
[36m(train_xgb_ray_tune pid=1075292)[0m [658]	train-mlogloss:0.91090	validation-mlogloss:0.94422
[36m(train_xgb_ray_tune pid=1075292)[0m [659]	train-mlogloss:0.91075	validation-mlogloss:0.94413
2025-11-04 10:58:32,672	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_M/case_M_XGB_acc_gyr_superclasses_CPA_METs/XGBoost_hyperparameters_tuning' in 0.0085s.
[36m(train_xgb_ray_tune pid=1075292)[0m [660]	train-mlogloss:0.91057	validation-mlogloss:0.94405
[36m(train_xgb_ray_tune pid=1075292)[0m [661]	train-mlogloss:0.91040	validation-mlogloss:0.94398
[36m(train_xgb_ray_tune pid=1075292)[0m [662]	train-mlogloss:0.91022	validation-mlogloss:0.94386
[36m(train_xgb_ray_tune pid=1075292)[0m [663]	train-mlogloss:0.91004	validation-mlogloss:0.94372
[36m(train_xgb_ray_tune pid=1075292)[0m [664]	train-mlogloss:0.90988	validation-mlogloss:0.94361
[36m(train_xgb_ray_tune pid=1075292)[0m [665]	train-mlogloss:0.90968	validation-mlogloss:0.94350
[36m(train_xgb_ray_tune pid=1075292)[0m [666]	train-mlogloss:0.90952	validation-mlogloss:0.94336
[36m(train_xgb_ray_tune pid=1075292)[0m [667]	train-mlogloss:0.90933	validation-mlogloss:0.94327
[36m(train_xgb_ray_tune pid=1075292)[0m [668]	train-mlogloss:0.90913	validation-mlogloss:0.94319
[36m(train_xgb_ray_tune pid=1075292)[0m [669]	train-mlogloss:0.90897	validation-mlogloss:0.94308
[36m(train_xgb_ray_tune pid=1075292)[0m [670]	train-mlogloss:0.90876	validation-mlogloss:0.94293
[36m(train_xgb_ray_tune pid=1075292)[0m [671]	train-mlogloss:0.90857	validation-mlogloss:0.94283
[36m(train_xgb_ray_tune pid=1075292)[0m [672]	train-mlogloss:0.90840	validation-mlogloss:0.94275
[36m(train_xgb_ray_tune pid=1075292)[0m [673]	train-mlogloss:0.90825	validation-mlogloss:0.94265
[36m(train_xgb_ray_tune pid=1075292)[0m [674]	train-mlogloss:0.90808	validation-mlogloss:0.94254
[36m(train_xgb_ray_tune pid=1075292)[0m [675]	train-mlogloss:0.90791	validation-mlogloss:0.94239
[36m(train_xgb_ray_tune pid=1075292)[0m [676]	train-mlogloss:0.90772	validation-mlogloss:0.94222
[36m(train_xgb_ray_tune pid=1075292)[0m [677]	train-mlogloss:0.90755	validation-mlogloss:0.94205
[36m(train_xgb_ray_tune pid=1075292)[0m [678]	train-mlogloss:0.90742	validation-mlogloss:0.94195
[36m(train_xgb_ray_tune pid=1075292)[0m [679]	train-mlogloss:0.90723	validation-mlogloss:0.94182
[36m(train_xgb_ray_tune pid=1075292)[0m [680]	train-mlogloss:0.90703	validation-mlogloss:0.94168
[36m(train_xgb_ray_tune pid=1075292)[0m [681]	train-mlogloss:0.90683	validation-mlogloss:0.94151
[36m(train_xgb_ray_tune pid=1075292)[0m [682]	train-mlogloss:0.90663	validation-mlogloss:0.94139
[36m(train_xgb_ray_tune pid=1075292)[0m [683]	train-mlogloss:0.90649	validation-mlogloss:0.94131
[36m(train_xgb_ray_tune pid=1075292)[0m [684]	train-mlogloss:0.90629	validation-mlogloss:0.94117
[36m(train_xgb_ray_tune pid=1075292)[0m [685]	train-mlogloss:0.90613	validation-mlogloss:0.94106
[36m(train_xgb_ray_tune pid=1075292)[0m [686]	train-mlogloss:0.90592	validation-mlogloss:0.94092
[36m(train_xgb_ray_tune pid=1075292)[0m [687]	train-mlogloss:0.90577	validation-mlogloss:0.94077
[36m(train_xgb_ray_tune pid=1075292)[0m [688]	train-mlogloss:0.90561	validation-mlogloss:0.94063
[36m(train_xgb_ray_tune pid=1075292)[0m [689]	train-mlogloss:0.90547	validation-mlogloss:0.94050
[36m(train_xgb_ray_tune pid=1075292)[0m [690]	train-mlogloss:0.90532	validation-mlogloss:0.94036
[36m(train_xgb_ray_tune pid=1075292)[0m [691]	train-mlogloss:0.90513	validation-mlogloss:0.94028
[36m(train_xgb_ray_tune pid=1075292)[0m [692]	train-mlogloss:0.90497	validation-mlogloss:0.94017
[36m(train_xgb_ray_tune pid=1075292)[0m [693]	train-mlogloss:0.90479	validation-mlogloss:0.94007
[36m(train_xgb_ray_tune pid=1075292)[0m [694]	train-mlogloss:0.90465	validation-mlogloss:0.93996
[36m(train_xgb_ray_tune pid=1075292)[0m [695]	train-mlogloss:0.90446	validation-mlogloss:0.93983
[36m(train_xgb_ray_tune pid=1075292)[0m [696]	train-mlogloss:0.90428	validation-mlogloss:0.93968
[36m(train_xgb_ray_tune pid=1075292)[0m [697]	train-mlogloss:0.90411	validation-mlogloss:0.93957
[36m(train_xgb_ray_tune pid=1075292)[0m [698]	train-mlogloss:0.90395	validation-mlogloss:0.93953
[36m(train_xgb_ray_tune pid=1075292)[0m [699]	train-mlogloss:0.90374	validation-mlogloss:0.93941
[36m(train_xgb_ray_tune pid=1075292)[0m [700]	train-mlogloss:0.90355	validation-mlogloss:0.93925
[36m(train_xgb_ray_tune pid=1075292)[0m [701]	train-mlogloss:0.90343	validation-mlogloss:0.93915
[36m(train_xgb_ray_tune pid=1075292)[0m [702]	train-mlogloss:0.90327	validation-mlogloss:0.93902
[36m(train_xgb_ray_tune pid=1075292)[0m [703]	train-mlogloss:0.90308	validation-mlogloss:0.93884
[36m(train_xgb_ray_tune pid=1075292)[0m [704]	train-mlogloss:0.90294	validation-mlogloss:0.93878
[36m(train_xgb_ray_tune pid=1075292)[0m [705]	train-mlogloss:0.90279	validation-mlogloss:0.93874

Trial trial_c460f finished iteration 1 at 2025-11-04 10:58:32. Total running time: 23s
╭──────────────────────────────────────╮
│ Trial trial_c460f result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             20.4913 │
│ time_total_s                 20.4913 │
│ training_iteration                 1 │
│ validation_accuracy          0.64993 │
╰──────────────────────────────────────╯

Trial trial_c460f completed after 1 iterations at 2025-11-04 10:58:32. Total running time: 23s

Trial status: 20 TERMINATED
Current time: 2025-11-04 10:58:32. Total running time: 23s
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_c460f    TERMINATED                 726             3        0.00544234      0.636302             0.580642   22.5746                   122      15.9864       110.201               6251        1           19.7261                 0.630618 │
│ trial_c460f    TERMINATED                 414             2        0.0137356       0.596917             0.659758   23.6095                   137       6.21827       71.9343              2631        1           14.4723                 0.629916 │
│ trial_c460f    TERMINATED                 714             2        0.0169717       0.785947             0.558926    8.74867                  115       2.37566      182.962               5326        1           17.8717                 0.650983 │
│ trial_c460f    TERMINATED                 601             2        0.016165        0.598849             0.6889     22.5848                    71      42.0419       275.82                8527        1           16.1204                 0.602528 │
│ trial_c460f    TERMINATED                 489             3        0.0108324       0.588673             0.647797   28.7333                    84      56.8546       192.041               5981        1           15.6027                 0.594452 │
│ trial_c460f    TERMINATED                 331             3        0.0186301       0.545252             0.547475   25.4603                    89     234.952        249.425               3625        1           11.6466                 0.535112 │
│ trial_c460f    TERMINATED                 759             3        0.0120311       0.630485             0.716141   22.7561                   192       6.1371         5.12983             1326        1           17.736                  0.639045 │
│ trial_c460f    TERMINATED                 587             3        0.00834855      0.514537             0.540897    5.88708                   88     472.582          6.91649             7743        1           11.6877                 0.410815 │
│ trial_c460f    TERMINATED                 706             3        0.00544126      0.83925              0.654572   12.1386                   116       6.71554       25.6606               414        1           20.4912                 0.64993  │
│ trial_c460f    TERMINATED                 506             3        0.00995845      0.642371             0.575906   15.2023                   165     335.902          9.17073             5133        1           13.1527                 0.54073  │
│ trial_c460f    TERMINATED                 578             2        0.0101808       0.528152             0.519611   21.323                    152       8.55117        8.99342             8600        1           17.0079                 0.622893 │
│ trial_c460f    TERMINATED                 556             2        0.012262        0.816118             0.546446   18.9666                   112     850.942          7.78939             6521        1            4.40469                0.263343 │
│ trial_c460f    TERMINATED                 628             2        0.0191453       0.725575             0.584552   11.0286                   185     126.598         28.5908              7858        1           13.5366                 0.601826 │
│ trial_c460f    TERMINATED                 473             2        0.00732801      0.696769             0.543668    6.57686                  111      12.0231        19.8126              3500        1           15.7545                 0.634129 │
│ trial_c460f    TERMINATED                 547             3        0.017135        0.699772             0.501053   16.8339                   121       2.64176      680.803               8084        1           16.9954                 0.632022 │
│ trial_c460f    TERMINATED                 435             3        0.00555129      0.674893             0.683969   28.6209                    83      65.4602         8.27726              996        1           16.422                  0.614817 │
│ trial_c460f    TERMINATED                 627             2        0.0167769       0.825116             0.729717   17.4283                   149       2.37567       16.9368              5328        1           16.5103                 0.650632 │
│ trial_c460f    TERMINATED                 715             3        0.0129055       0.684046             0.657446   29.4406                   177     277.049         26.0072              3750        1           11.5447                 0.547402 │
│ trial_c460f    TERMINATED                 699             3        0.00521208      0.557633             0.688334   21.6969                    68       4.95267       47.5975              2102        1           19.8046                 0.632022 │
│ trial_c460f    TERMINATED                 524             3        0.0131243       0.828442             0.508115   28.6208                    81     719.267          5.82707             8869        1            7.71378                0.414677 │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Mejores hiperparámetros XGBoost: {'num_boost_round': 714, 'max_depth': 2, 'learning_rate': 0.016971658241775343, 'subsample': 0.7859470838030091, 'colsample_bytree': 0.5589262717181894, 'gamma': 8.748673937600872, 'min_child_weight': 115, 'reg_alpha': 2.3756551753620863, 'reg_lambda': 182.96207950123733, 'random_state': 5326}
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[712]	train-mlogloss:0.87916	validation-mlogloss:0.91329
[713]	train-mlogloss:0.87911	validation-mlogloss:0.91329
Saved model to disk.
[36m(train_xgb_ray_tune pid=1075292)[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 7x across cluster][0m
[36m(train_xgb_ray_tune pid=1075292)[0m   _log_deprecation_warning([32m [repeated 7x across cluster][0m
2025-11-04 10:58:46.315243: 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`.
2025-11-04 10:58:46.326389: 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 00:00:1762250326.339404 1077152 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250326.343288 1077152 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250326.353197 1077152 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250326.353211 1077152 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250326.353213 1077152 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250326.353215 1077152 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:58:46.356335: 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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[29]	train-mlogloss:1.26115	validation-mlogloss:1.25683
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[32]	train-mlogloss:1.25170	validation-mlogloss:1.24663
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[633]	train-mlogloss:0.88022	validation-mlogloss:0.92063
[634]	train-mlogloss:0.88016	validation-mlogloss:0.92060
[635]	train-mlogloss:0.88005	validation-mlogloss:0.92056
[636]	train-mlogloss:0.88000	validation-mlogloss:0.92050
[637]	train-mlogloss:0.87984	validation-mlogloss:0.92038
[638]	train-mlogloss:0.87975	validation-mlogloss:0.92038
[639]	train-mlogloss:0.87969	validation-mlogloss:0.92030
[640]	train-mlogloss:0.87964	validation-mlogloss:0.92024
[641]	train-mlogloss:0.87957	validation-mlogloss:0.92022
[642]	train-mlogloss:0.87943	validation-mlogloss:0.92021
[643]	train-mlogloss:0.87940	validation-mlogloss:0.92018
[644]	train-mlogloss:0.87924	validation-mlogloss:0.92016
[645]	train-mlogloss:0.87917	validation-mlogloss:0.92007
[646]	train-mlogloss:0.87910	validation-mlogloss:0.92006
[647]	train-mlogloss:0.87907	validation-mlogloss:0.92004
[648]	train-mlogloss:0.87901	validation-mlogloss:0.91998
[649]	train-mlogloss:0.87892	validation-mlogloss:0.91994
[650]	train-mlogloss:0.87880	validation-mlogloss:0.91996
[651]	train-mlogloss:0.87877	validation-mlogloss:0.91994
[652]	train-mlogloss:0.87871	validation-mlogloss:0.91994
[653]	train-mlogloss:0.87866	validation-mlogloss:0.91991
[654]	train-mlogloss:0.87857	validation-mlogloss:0.91992
[655]	train-mlogloss:0.87852	validation-mlogloss:0.91986
[656]	train-mlogloss:0.87846	validation-mlogloss:0.91981
[657]	train-mlogloss:0.87841	validation-mlogloss:0.91981
[658]	train-mlogloss:0.87834	validation-mlogloss:0.91978
[659]	train-mlogloss:0.87828	validation-mlogloss:0.91976
[660]	train-mlogloss:0.87823	validation-mlogloss:0.91970
[661]	train-mlogloss:0.87821	validation-mlogloss:0.91969
[662]	train-mlogloss:0.87812	validation-mlogloss:0.91965
[663]	train-mlogloss:0.87806	validation-mlogloss:0.91956
[664]	train-mlogloss:0.87804	validation-mlogloss:0.91955
[665]	train-mlogloss:0.87797	validation-mlogloss:0.91954
[666]	train-mlogloss:0.87787	validation-mlogloss:0.91945
[667]	train-mlogloss:0.87783	validation-mlogloss:0.91943
[668]	train-mlogloss:0.87778	validation-mlogloss:0.91941
[669]	train-mlogloss:0.87772	validation-mlogloss:0.91944
[670]	train-mlogloss:0.87760	validation-mlogloss:0.91939
[671]	train-mlogloss:0.87754	validation-mlogloss:0.91939
[672]	train-mlogloss:0.87747	validation-mlogloss:0.91936
[673]	train-mlogloss:0.87743	validation-mlogloss:0.91935
[674]	train-mlogloss:0.87734	validation-mlogloss:0.91925
[675]	train-mlogloss:0.87730	validation-mlogloss:0.91923
[676]	train-mlogloss:0.87725	validation-mlogloss:0.91917
[677]	train-mlogloss:0.87718	validation-mlogloss:0.91912
[678]	train-mlogloss:0.87714	validation-mlogloss:0.91910
[679]	train-mlogloss:0.87710	validation-mlogloss:0.91910
[680]	train-mlogloss:0.87698	validation-mlogloss:0.91891
[681]	train-mlogloss:0.87694	validation-mlogloss:0.91889
[682]	train-mlogloss:0.87689	validation-mlogloss:0.91890
[683]	train-mlogloss:0.87683	validation-mlogloss:0.91884
[684]	train-mlogloss:0.87677	validation-mlogloss:0.91882
[685]	train-mlogloss:0.87673	validation-mlogloss:0.91881
[686]	train-mlogloss:0.87662	validation-mlogloss:0.91884
[687]	train-mlogloss:0.87657	validation-mlogloss:0.91876
[688]	train-mlogloss:0.87652	validation-mlogloss:0.91874
[689]	train-mlogloss:0.87648	validation-mlogloss:0.91870
[690]	train-mlogloss:0.87632	validation-mlogloss:0.91862
[691]	train-mlogloss:0.87621	validation-mlogloss:0.91863
[692]	train-mlogloss:0.87617	validation-mlogloss:0.91859
[693]	train-mlogloss:0.87612	validation-mlogloss:0.91856
[694]	train-mlogloss:0.87604	validation-mlogloss:0.91851
[695]	train-mlogloss:0.87595	validation-mlogloss:0.91847
[696]	train-mlogloss:0.87590	validation-mlogloss:0.91847
[697]	train-mlogloss:0.87585	validation-mlogloss:0.91848
[698]	train-mlogloss:0.87581	validation-mlogloss:0.91846
[699]	train-mlogloss:0.87572	validation-mlogloss:0.91846
[700]	train-mlogloss:0.87563	validation-mlogloss:0.91837
[701]	train-mlogloss:0.87545	validation-mlogloss:0.91828
[702]	train-mlogloss:0.87543	validation-mlogloss:0.91828
[703]	train-mlogloss:0.87534	validation-mlogloss:0.91820
[704]	train-mlogloss:0.87532	validation-mlogloss:0.91819
[705]	train-mlogloss:0.87526	validation-mlogloss:0.91816
[706]	train-mlogloss:0.87522	validation-mlogloss:0.91810
[707]	train-mlogloss:0.87516	validation-mlogloss:0.91801
[708]	train-mlogloss:0.87508	validation-mlogloss:0.91801
[709]	train-mlogloss:0.87500	validation-mlogloss:0.91794
[710]	train-mlogloss:0.87487	validation-mlogloss:0.91786
[711]	train-mlogloss:0.87485	validation-mlogloss:0.91785
[712]	train-mlogloss:0.87478	validation-mlogloss:0.91787
[713]	train-mlogloss:0.87474	validation-mlogloss:0.91785
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[1 2 0 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 62.86 [%]
Global accuracy score (test) = 58.96 [%]
Global F1 score (train) = 62.91 [%]
Global F1 score (test) = 59.98 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.42      0.48      0.45       400
MODERATE-INTENSITY       0.57      0.57      0.57       400
         SEDENTARY       0.64      0.69      0.66       400
VIGOROUS-INTENSITY       0.86      0.62      0.72       345

          accuracy                           0.59      1545
         macro avg       0.62      0.59      0.60      1545
      weighted avg       0.61      0.59      0.60      1545


Accuracy capturado en la ejecución 1: 58.96 [%]
F1-score capturado en la ejecución 1: 59.98 [%]

=== EJECUCIÓN 2 ===

--- TRAIN (ejecución 2) ---

--- TEST (ejecución 2) ---
2025-11-04 10:59:03.187189: 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`.
2025-11-04 10:59:03.198613: 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 00:00:1762250343.211996 1077461 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250343.216083 1077461 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250343.225992 1077461 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250343.226009 1077461 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250343.226010 1077461 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250343.226011 1077461 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:59:03.229145: 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:1.38120	validation-mlogloss:1.38101
[1]	train-mlogloss:1.37644	validation-mlogloss:1.37627
[2]	train-mlogloss:1.37145	validation-mlogloss:1.37122
[3]	train-mlogloss:1.36669	validation-mlogloss:1.36674
[4]	train-mlogloss:1.36197	validation-mlogloss:1.36209
[5]	train-mlogloss:1.35718	validation-mlogloss:1.35730
[6]	train-mlogloss:1.35267	validation-mlogloss:1.35284
[7]	train-mlogloss:1.34803	validation-mlogloss:1.34809
[8]	train-mlogloss:1.34352	validation-mlogloss:1.34339
[9]	train-mlogloss:1.33896	validation-mlogloss:1.33876
[10]	train-mlogloss:1.33467	validation-mlogloss:1.33428
[11]	train-mlogloss:1.33039	validation-mlogloss:1.32990
[12]	train-mlogloss:1.32625	validation-mlogloss:1.32559
[13]	train-mlogloss:1.32215	validation-mlogloss:1.32113
[14]	train-mlogloss:1.31794	validation-mlogloss:1.31677
[15]	train-mlogloss:1.31396	validation-mlogloss:1.31259
[16]	train-mlogloss:1.31004	validation-mlogloss:1.30857
[17]	train-mlogloss:1.30615	validation-mlogloss:1.30435
[18]	train-mlogloss:1.30205	validation-mlogloss:1.29986
[19]	train-mlogloss:1.29824	validation-mlogloss:1.29599
[20]	train-mlogloss:1.29422	validation-mlogloss:1.29173
[21]	train-mlogloss:1.29053	validation-mlogloss:1.28782
[22]	train-mlogloss:1.28641	validation-mlogloss:1.28357
[23]	train-mlogloss:1.28281	validation-mlogloss:1.27996
[24]	train-mlogloss:1.27930	validation-mlogloss:1.27634
[25]	train-mlogloss:1.27578	validation-mlogloss:1.27264
[26]	train-mlogloss:1.27234	validation-mlogloss:1.26925
[27]	train-mlogloss:1.26908	validation-mlogloss:1.26577
[28]	train-mlogloss:1.26572	validation-mlogloss:1.26256
[29]	train-mlogloss:1.26245	validation-mlogloss:1.25899
[30]	train-mlogloss:1.25928	validation-mlogloss:1.25554
[31]	train-mlogloss:1.25605	validation-mlogloss:1.25208
[32]	train-mlogloss:1.25292	validation-mlogloss:1.24906
[33]	train-mlogloss:1.24978	validation-mlogloss:1.24593
[34]	train-mlogloss:1.24627	validation-mlogloss:1.24245
[35]	train-mlogloss:1.24329	validation-mlogloss:1.23939
[36]	train-mlogloss:1.24029	validation-mlogloss:1.23653
[37]	train-mlogloss:1.23738	validation-mlogloss:1.23347
[38]	train-mlogloss:1.23449	validation-mlogloss:1.23074
[39]	train-mlogloss:1.23176	validation-mlogloss:1.22806
[40]	train-mlogloss:1.22902	validation-mlogloss:1.22530
[41]	train-mlogloss:1.22572	validation-mlogloss:1.22191
[42]	train-mlogloss:1.22298	validation-mlogloss:1.21912
[43]	train-mlogloss:1.22026	validation-mlogloss:1.21628
[44]	train-mlogloss:1.21742	validation-mlogloss:1.21332
[45]	train-mlogloss:1.21477	validation-mlogloss:1.21070
[46]	train-mlogloss:1.21218	validation-mlogloss:1.20811
[47]	train-mlogloss:1.20944	validation-mlogloss:1.20530
[48]	train-mlogloss:1.20694	validation-mlogloss:1.20280
[49]	train-mlogloss:1.20451	validation-mlogloss:1.20034
[50]	train-mlogloss:1.20214	validation-mlogloss:1.19799
[51]	train-mlogloss:1.19975	validation-mlogloss:1.19560
[52]	train-mlogloss:1.19736	validation-mlogloss:1.19326
[53]	train-mlogloss:1.19499	validation-mlogloss:1.19069
[54]	train-mlogloss:1.19259	validation-mlogloss:1.18847
[55]	train-mlogloss:1.18993	validation-mlogloss:1.18560
[56]	train-mlogloss:1.18767	validation-mlogloss:1.18334
[57]	train-mlogloss:1.18531	validation-mlogloss:1.18102
[58]	train-mlogloss:1.18268	validation-mlogloss:1.17834
[59]	train-mlogloss:1.18019	validation-mlogloss:1.17572
[60]	train-mlogloss:1.17792	validation-mlogloss:1.17351
[61]	train-mlogloss:1.17545	validation-mlogloss:1.17123
[62]	train-mlogloss:1.17319	validation-mlogloss:1.16888
[63]	train-mlogloss:1.17077	validation-mlogloss:1.16659
[64]	train-mlogloss:1.16830	validation-mlogloss:1.16408
[65]	train-mlogloss:1.16592	validation-mlogloss:1.16193
[66]	train-mlogloss:1.16394	validation-mlogloss:1.16011
[67]	train-mlogloss:1.16188	validation-mlogloss:1.15795
[68]	train-mlogloss:1.15985	validation-mlogloss:1.15620
[69]	train-mlogloss:1.15790	validation-mlogloss:1.15420
[70]	train-mlogloss:1.15565	validation-mlogloss:1.15185
[71]	train-mlogloss:1.15380	validation-mlogloss:1.14993
[72]	train-mlogloss:1.15173	validation-mlogloss:1.14791
[73]	train-mlogloss:1.14977	validation-mlogloss:1.14592
[74]	train-mlogloss:1.14787	validation-mlogloss:1.14417
[75]	train-mlogloss:1.14591	validation-mlogloss:1.14219
[76]	train-mlogloss:1.14409	validation-mlogloss:1.14035
[77]	train-mlogloss:1.14212	validation-mlogloss:1.13837
[78]	train-mlogloss:1.14022	validation-mlogloss:1.13654
[79]	train-mlogloss:1.13844	validation-mlogloss:1.13490
[80]	train-mlogloss:1.13652	validation-mlogloss:1.13286
[81]	train-mlogloss:1.13476	validation-mlogloss:1.13100
[82]	train-mlogloss:1.13302	validation-mlogloss:1.12922
[83]	train-mlogloss:1.13133	validation-mlogloss:1.12768
[84]	train-mlogloss:1.12964	validation-mlogloss:1.12589
[85]	train-mlogloss:1.12783	validation-mlogloss:1.12399
[86]	train-mlogloss:1.12617	validation-mlogloss:1.12231
[87]	train-mlogloss:1.12456	validation-mlogloss:1.12067
[88]	train-mlogloss:1.12263	validation-mlogloss:1.11895
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[682]	train-mlogloss:0.88260	validation-mlogloss:0.93590
[683]	train-mlogloss:0.88256	validation-mlogloss:0.93590
[684]	train-mlogloss:0.88245	validation-mlogloss:0.93592
[685]	train-mlogloss:0.88241	validation-mlogloss:0.93589
[686]	train-mlogloss:0.88235	validation-mlogloss:0.93588
[687]	train-mlogloss:0.88225	validation-mlogloss:0.93582
[688]	train-mlogloss:0.88212	validation-mlogloss:0.93572
[689]	train-mlogloss:0.88202	validation-mlogloss:0.93567
[690]	train-mlogloss:0.88194	validation-mlogloss:0.93557
[691]	train-mlogloss:0.88188	validation-mlogloss:0.93554
[692]	train-mlogloss:0.88183	validation-mlogloss:0.93547
[693]	train-mlogloss:0.88178	validation-mlogloss:0.93540
[694]	train-mlogloss:0.88174	validation-mlogloss:0.93539
[695]	train-mlogloss:0.88169	validation-mlogloss:0.93536
[696]	train-mlogloss:0.88155	validation-mlogloss:0.93520
[697]	train-mlogloss:0.88145	validation-mlogloss:0.93520
[698]	train-mlogloss:0.88141	validation-mlogloss:0.93516
[699]	train-mlogloss:0.88133	validation-mlogloss:0.93506
[700]	train-mlogloss:0.88124	validation-mlogloss:0.93495
[701]	train-mlogloss:0.88117	validation-mlogloss:0.93490
[702]	train-mlogloss:0.88110	validation-mlogloss:0.93483
[703]	train-mlogloss:0.88103	validation-mlogloss:0.93480
[704]	train-mlogloss:0.88094	validation-mlogloss:0.93468
[705]	train-mlogloss:0.88081	validation-mlogloss:0.93456
[706]	train-mlogloss:0.88068	validation-mlogloss:0.93449
[707]	train-mlogloss:0.88054	validation-mlogloss:0.93434
[708]	train-mlogloss:0.88048	validation-mlogloss:0.93428
[709]	train-mlogloss:0.88042	validation-mlogloss:0.93420
[710]	train-mlogloss:0.88030	validation-mlogloss:0.93423
[711]	train-mlogloss:0.88014	validation-mlogloss:0.93409
[712]	train-mlogloss:0.88009	validation-mlogloss:0.93403
[713]	train-mlogloss:0.88004	validation-mlogloss:0.93401
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 64.09 [%]
Global accuracy score (test) = 60.58 [%]
Global F1 score (train) = 64.23 [%]
Global F1 score (test) = 61.23 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.43      0.43      0.43       400
MODERATE-INTENSITY       0.56      0.65      0.60       400
         SEDENTARY       0.67      0.74      0.70       400
VIGOROUS-INTENSITY       0.88      0.60      0.72       345

          accuracy                           0.61      1545
         macro avg       0.63      0.61      0.61      1545
      weighted avg       0.63      0.61      0.61      1545


Accuracy capturado en la ejecución 2: 60.58 [%]
F1-score capturado en la ejecución 2: 61.23 [%]

=== EJECUCIÓN 3 ===

--- TRAIN (ejecución 3) ---

--- TEST (ejecución 3) ---
2025-11-04 10:59:20.169949: 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`.
2025-11-04 10:59:20.181502: 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 00:00:1762250360.194866 1077809 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250360.199061 1077809 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250360.209244 1077809 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250360.209263 1077809 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250360.209264 1077809 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250360.209266 1077809 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:59:20.212321: 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:1.38094	validation-mlogloss:1.38074
[1]	train-mlogloss:1.37596	validation-mlogloss:1.37561
[2]	train-mlogloss:1.37091	validation-mlogloss:1.37028
[3]	train-mlogloss:1.36580	validation-mlogloss:1.36502
[4]	train-mlogloss:1.36093	validation-mlogloss:1.36017
[5]	train-mlogloss:1.35626	validation-mlogloss:1.35555
[6]	train-mlogloss:1.35164	validation-mlogloss:1.35098
[7]	train-mlogloss:1.34696	validation-mlogloss:1.34639
[8]	train-mlogloss:1.34237	validation-mlogloss:1.34145
[9]	train-mlogloss:1.33808	validation-mlogloss:1.33716
[10]	train-mlogloss:1.33356	validation-mlogloss:1.33246
[11]	train-mlogloss:1.32880	validation-mlogloss:1.32735
[12]	train-mlogloss:1.32450	validation-mlogloss:1.32302
[13]	train-mlogloss:1.32027	validation-mlogloss:1.31879
[14]	train-mlogloss:1.31624	validation-mlogloss:1.31456
[15]	train-mlogloss:1.31219	validation-mlogloss:1.31064
[16]	train-mlogloss:1.30827	validation-mlogloss:1.30656
[17]	train-mlogloss:1.30434	validation-mlogloss:1.30253
[18]	train-mlogloss:1.30056	validation-mlogloss:1.29872
[19]	train-mlogloss:1.29672	validation-mlogloss:1.29465
[20]	train-mlogloss:1.29301	validation-mlogloss:1.29095
[21]	train-mlogloss:1.28934	validation-mlogloss:1.28691
[22]	train-mlogloss:1.28575	validation-mlogloss:1.28340
[23]	train-mlogloss:1.28206	validation-mlogloss:1.27962
[24]	train-mlogloss:1.27856	validation-mlogloss:1.27614
[25]	train-mlogloss:1.27506	validation-mlogloss:1.27240
[26]	train-mlogloss:1.27167	validation-mlogloss:1.26886
[27]	train-mlogloss:1.26840	validation-mlogloss:1.26563
[28]	train-mlogloss:1.26505	validation-mlogloss:1.26209
[29]	train-mlogloss:1.26168	validation-mlogloss:1.25841
[30]	train-mlogloss:1.25840	validation-mlogloss:1.25502
[31]	train-mlogloss:1.25532	validation-mlogloss:1.25193
[32]	train-mlogloss:1.25216	validation-mlogloss:1.24883
[33]	train-mlogloss:1.24906	validation-mlogloss:1.24557
[34]	train-mlogloss:1.24595	validation-mlogloss:1.24236
[35]	train-mlogloss:1.24282	validation-mlogloss:1.23935
[36]	train-mlogloss:1.23990	validation-mlogloss:1.23611
[37]	train-mlogloss:1.23707	validation-mlogloss:1.23330
[38]	train-mlogloss:1.23412	validation-mlogloss:1.23012
[39]	train-mlogloss:1.23130	validation-mlogloss:1.22727
[40]	train-mlogloss:1.22847	validation-mlogloss:1.22426
[41]	train-mlogloss:1.22569	validation-mlogloss:1.22150
[42]	train-mlogloss:1.22298	validation-mlogloss:1.21873
[43]	train-mlogloss:1.22029	validation-mlogloss:1.21596
[44]	train-mlogloss:1.21762	validation-mlogloss:1.21326
[45]	train-mlogloss:1.21487	validation-mlogloss:1.21028
[46]	train-mlogloss:1.21210	validation-mlogloss:1.20721
[47]	train-mlogloss:1.20953	validation-mlogloss:1.20476
[48]	train-mlogloss:1.20647	validation-mlogloss:1.20143
[49]	train-mlogloss:1.20354	validation-mlogloss:1.19837
[50]	train-mlogloss:1.20107	validation-mlogloss:1.19607
[51]	train-mlogloss:1.19866	validation-mlogloss:1.19352
[52]	train-mlogloss:1.19628	validation-mlogloss:1.19114
[53]	train-mlogloss:1.19374	validation-mlogloss:1.18830
[54]	train-mlogloss:1.19130	validation-mlogloss:1.18579
[55]	train-mlogloss:1.18857	validation-mlogloss:1.18281
[56]	train-mlogloss:1.18619	validation-mlogloss:1.18036
[57]	train-mlogloss:1.18387	validation-mlogloss:1.17794
[58]	train-mlogloss:1.18111	validation-mlogloss:1.17512
[59]	train-mlogloss:1.17904	validation-mlogloss:1.17313
[60]	train-mlogloss:1.17674	validation-mlogloss:1.17074
[61]	train-mlogloss:1.17441	validation-mlogloss:1.16831
[62]	train-mlogloss:1.17230	validation-mlogloss:1.16621
[63]	train-mlogloss:1.17006	validation-mlogloss:1.16399
[64]	train-mlogloss:1.16793	validation-mlogloss:1.16174
[65]	train-mlogloss:1.16548	validation-mlogloss:1.15926
[66]	train-mlogloss:1.16349	validation-mlogloss:1.15731
[67]	train-mlogloss:1.16112	validation-mlogloss:1.15490
[68]	train-mlogloss:1.15900	validation-mlogloss:1.15284
[69]	train-mlogloss:1.15702	validation-mlogloss:1.15082
[70]	train-mlogloss:1.15504	validation-mlogloss:1.14866
[71]	train-mlogloss:1.15306	validation-mlogloss:1.14672
[72]	train-mlogloss:1.15098	validation-mlogloss:1.14444
[73]	train-mlogloss:1.14909	validation-mlogloss:1.14266
[74]	train-mlogloss:1.14682	validation-mlogloss:1.14063
[75]	train-mlogloss:1.14472	validation-mlogloss:1.13848
[76]	train-mlogloss:1.14255	validation-mlogloss:1.13634
[77]	train-mlogloss:1.14068	validation-mlogloss:1.13440
[78]	train-mlogloss:1.13869	validation-mlogloss:1.13231
[79]	train-mlogloss:1.13688	validation-mlogloss:1.13048
[80]	train-mlogloss:1.13498	validation-mlogloss:1.12837
[81]	train-mlogloss:1.13320	validation-mlogloss:1.12647
[82]	train-mlogloss:1.13140	validation-mlogloss:1.12470
[83]	train-mlogloss:1.12965	validation-mlogloss:1.12275
[84]	train-mlogloss:1.12792	validation-mlogloss:1.12087
[85]	train-mlogloss:1.12634	validation-mlogloss:1.11932
[86]	train-mlogloss:1.12455	validation-mlogloss:1.11756
[87]	train-mlogloss:1.12297	validation-mlogloss:1.11591
[88]	train-mlogloss:1.12127	validation-mlogloss:1.11426
[89]	train-mlogloss:1.11960	validation-mlogloss:1.11283
[90]	train-mlogloss:1.11790	validation-mlogloss:1.11139
[91]	train-mlogloss:1.11623	validation-mlogloss:1.10959
[92]	train-mlogloss:1.11459	validation-mlogloss:1.10790
[93]	train-mlogloss:1.11318	validation-mlogloss:1.10640
[94]	train-mlogloss:1.11163	validation-mlogloss:1.10501
[95]	train-mlogloss:1.11007	validation-mlogloss:1.10338
[96]	train-mlogloss:1.10854	validation-mlogloss:1.10188
[97]	train-mlogloss:1.10696	validation-mlogloss:1.10029
[98]	train-mlogloss:1.10527	validation-mlogloss:1.09878
[99]	train-mlogloss:1.10375	validation-mlogloss:1.09735
[100]	train-mlogloss:1.10225	validation-mlogloss:1.09593
[101]	train-mlogloss:1.10084	validation-mlogloss:1.09467
[102]	train-mlogloss:1.09934	validation-mlogloss:1.09296
[103]	train-mlogloss:1.09756	validation-mlogloss:1.09146
[104]	train-mlogloss:1.09623	validation-mlogloss:1.09021
[105]	train-mlogloss:1.09492	validation-mlogloss:1.08900
[106]	train-mlogloss:1.09356	validation-mlogloss:1.08782
[107]	train-mlogloss:1.09218	validation-mlogloss:1.08631
[108]	train-mlogloss:1.09071	validation-mlogloss:1.08503
[109]	train-mlogloss:1.08937	validation-mlogloss:1.08375
[110]	train-mlogloss:1.08806	validation-mlogloss:1.08243
[111]	train-mlogloss:1.08667	validation-mlogloss:1.08085
[112]	train-mlogloss:1.08530	validation-mlogloss:1.07959
[113]	train-mlogloss:1.08395	validation-mlogloss:1.07823
[114]	train-mlogloss:1.08272	validation-mlogloss:1.07713
[115]	train-mlogloss:1.08146	validation-mlogloss:1.07592
[116]	train-mlogloss:1.08022	validation-mlogloss:1.07480
[117]	train-mlogloss:1.07896	validation-mlogloss:1.07363
[118]	train-mlogloss:1.07772	validation-mlogloss:1.07244
[119]	train-mlogloss:1.07650	validation-mlogloss:1.07126
[120]	train-mlogloss:1.07520	validation-mlogloss:1.07007
[121]	train-mlogloss:1.07405	validation-mlogloss:1.06887
[122]	train-mlogloss:1.07280	validation-mlogloss:1.06776
[123]	train-mlogloss:1.07163	validation-mlogloss:1.06688
[124]	train-mlogloss:1.07049	validation-mlogloss:1.06581
[125]	train-mlogloss:1.06934	validation-mlogloss:1.06475
[126]	train-mlogloss:1.06821	validation-mlogloss:1.06377
[127]	train-mlogloss:1.06710	validation-mlogloss:1.06257
[128]	train-mlogloss:1.06589	validation-mlogloss:1.06148
[129]	train-mlogloss:1.06474	validation-mlogloss:1.06032
[130]	train-mlogloss:1.06361	validation-mlogloss:1.05925
[131]	train-mlogloss:1.06256	validation-mlogloss:1.05826
[132]	train-mlogloss:1.06149	validation-mlogloss:1.05743
[133]	train-mlogloss:1.06050	validation-mlogloss:1.05646
[134]	train-mlogloss:1.05939	validation-mlogloss:1.05539
[135]	train-mlogloss:1.05835	validation-mlogloss:1.05447
[136]	train-mlogloss:1.05728	validation-mlogloss:1.05363
[137]	train-mlogloss:1.05619	validation-mlogloss:1.05265
[138]	train-mlogloss:1.05515	validation-mlogloss:1.05150
[139]	train-mlogloss:1.05411	validation-mlogloss:1.05077
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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)
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)
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Training a non-convolutional model.
Loaded model from disk.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 3]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.76 [%]
Global accuracy score (test) = 60.58 [%]
Global F1 score (train) = 63.82 [%]
Global F1 score (test) = 61.47 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.45      0.49      0.47       400
MODERATE-INTENSITY       0.56      0.61      0.58       400
         SEDENTARY       0.68      0.70      0.69       400
VIGOROUS-INTENSITY       0.86      0.62      0.72       345

          accuracy                           0.61      1545
         macro avg       0.63      0.61      0.61      1545
      weighted avg       0.63      0.61      0.61      1545


Accuracy capturado en la ejecución 3: 60.58 [%]
F1-score capturado en la ejecución 3: 61.47 [%]

=== EJECUCIÓN 4 ===

--- TRAIN (ejecución 4) ---

--- TEST (ejecución 4) ---
2025-11-04 10:59:37.142273: 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`.
2025-11-04 10:59:37.154137: 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 00:00:1762250377.168123 1078122 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250377.172296 1078122 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250377.182392 1078122 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250377.182409 1078122 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250377.182410 1078122 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250377.182412 1078122 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:59:37.185581: 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:1.38075	validation-mlogloss:1.38041
[1]	train-mlogloss:1.37549	validation-mlogloss:1.37493
[2]	train-mlogloss:1.37051	validation-mlogloss:1.36973
[3]	train-mlogloss:1.36565	validation-mlogloss:1.36480
[4]	train-mlogloss:1.36068	validation-mlogloss:1.35980
[5]	train-mlogloss:1.35583	validation-mlogloss:1.35472
[6]	train-mlogloss:1.35111	validation-mlogloss:1.34970
[7]	train-mlogloss:1.34661	validation-mlogloss:1.34491
[8]	train-mlogloss:1.34212	validation-mlogloss:1.34037
[9]	train-mlogloss:1.33764	validation-mlogloss:1.33543
[10]	train-mlogloss:1.33308	validation-mlogloss:1.33071
[11]	train-mlogloss:1.32859	validation-mlogloss:1.32611
[12]	train-mlogloss:1.32431	validation-mlogloss:1.32190
[13]	train-mlogloss:1.31999	validation-mlogloss:1.31724
[14]	train-mlogloss:1.31587	validation-mlogloss:1.31300
[15]	train-mlogloss:1.31172	validation-mlogloss:1.30843
[16]	train-mlogloss:1.30758	validation-mlogloss:1.30388
[17]	train-mlogloss:1.30313	validation-mlogloss:1.29897
[18]	train-mlogloss:1.29912	validation-mlogloss:1.29482
[19]	train-mlogloss:1.29493	validation-mlogloss:1.29033
[20]	train-mlogloss:1.29110	validation-mlogloss:1.28633
[21]	train-mlogloss:1.28735	validation-mlogloss:1.28242
[22]	train-mlogloss:1.28364	validation-mlogloss:1.27869
[23]	train-mlogloss:1.27991	validation-mlogloss:1.27497
[24]	train-mlogloss:1.27637	validation-mlogloss:1.27130
[25]	train-mlogloss:1.27275	validation-mlogloss:1.26767
[26]	train-mlogloss:1.26934	validation-mlogloss:1.26422
[27]	train-mlogloss:1.26591	validation-mlogloss:1.26066
[28]	train-mlogloss:1.26251	validation-mlogloss:1.25700
[29]	train-mlogloss:1.25919	validation-mlogloss:1.25361
[30]	train-mlogloss:1.25596	validation-mlogloss:1.25028
[31]	train-mlogloss:1.25278	validation-mlogloss:1.24718
[32]	train-mlogloss:1.24960	validation-mlogloss:1.24377
[33]	train-mlogloss:1.24646	validation-mlogloss:1.24048
[34]	train-mlogloss:1.24332	validation-mlogloss:1.23729
[35]	train-mlogloss:1.24024	validation-mlogloss:1.23399
[36]	train-mlogloss:1.23712	validation-mlogloss:1.23067
[37]	train-mlogloss:1.23422	validation-mlogloss:1.22768
[38]	train-mlogloss:1.23132	validation-mlogloss:1.22476
[39]	train-mlogloss:1.22845	validation-mlogloss:1.22174
[40]	train-mlogloss:1.22559	validation-mlogloss:1.21888
[41]	train-mlogloss:1.22279	validation-mlogloss:1.21619
[42]	train-mlogloss:1.22001	validation-mlogloss:1.21349
[43]	train-mlogloss:1.21685	validation-mlogloss:1.20992
[44]	train-mlogloss:1.21401	validation-mlogloss:1.20679
[45]	train-mlogloss:1.21139	validation-mlogloss:1.20415
[46]	train-mlogloss:1.20876	validation-mlogloss:1.20149
[47]	train-mlogloss:1.20622	validation-mlogloss:1.19861
[48]	train-mlogloss:1.20353	validation-mlogloss:1.19580
[49]	train-mlogloss:1.20093	validation-mlogloss:1.19325
[50]	train-mlogloss:1.19854	validation-mlogloss:1.19077
[51]	train-mlogloss:1.19611	validation-mlogloss:1.18836
[52]	train-mlogloss:1.19383	validation-mlogloss:1.18609
[53]	train-mlogloss:1.19149	validation-mlogloss:1.18372
[54]	train-mlogloss:1.18897	validation-mlogloss:1.18107
[55]	train-mlogloss:1.18664	validation-mlogloss:1.17892
[56]	train-mlogloss:1.18422	validation-mlogloss:1.17627
[57]	train-mlogloss:1.18195	validation-mlogloss:1.17383
[58]	train-mlogloss:1.17934	validation-mlogloss:1.17143
[59]	train-mlogloss:1.17705	validation-mlogloss:1.16901
[60]	train-mlogloss:1.17472	validation-mlogloss:1.16656
[61]	train-mlogloss:1.17247	validation-mlogloss:1.16415
[62]	train-mlogloss:1.17033	validation-mlogloss:1.16184
[63]	train-mlogloss:1.16775	validation-mlogloss:1.15918
[64]	train-mlogloss:1.16529	validation-mlogloss:1.15650
[65]	train-mlogloss:1.16323	validation-mlogloss:1.15444
[66]	train-mlogloss:1.16101	validation-mlogloss:1.15218
[67]	train-mlogloss:1.15891	validation-mlogloss:1.14998
[68]	train-mlogloss:1.15687	validation-mlogloss:1.14795
[69]	train-mlogloss:1.15491	validation-mlogloss:1.14594
[70]	train-mlogloss:1.15303	validation-mlogloss:1.14403
[71]	train-mlogloss:1.15073	validation-mlogloss:1.14172
[72]	train-mlogloss:1.14870	validation-mlogloss:1.13961
[73]	train-mlogloss:1.14646	validation-mlogloss:1.13716
[74]	train-mlogloss:1.14455	validation-mlogloss:1.13518
[75]	train-mlogloss:1.14242	validation-mlogloss:1.13294
[76]	train-mlogloss:1.14046	validation-mlogloss:1.13107
[77]	train-mlogloss:1.13864	validation-mlogloss:1.12914
[78]	train-mlogloss:1.13688	validation-mlogloss:1.12755
[79]	train-mlogloss:1.13478	validation-mlogloss:1.12533
[80]	train-mlogloss:1.13310	validation-mlogloss:1.12362
[81]	train-mlogloss:1.13124	validation-mlogloss:1.12176
[82]	train-mlogloss:1.12963	validation-mlogloss:1.12011
[83]	train-mlogloss:1.12785	validation-mlogloss:1.11820
[84]	train-mlogloss:1.12604	validation-mlogloss:1.11630
[85]	train-mlogloss:1.12429	validation-mlogloss:1.11451
[86]	train-mlogloss:1.12260	validation-mlogloss:1.11296
[87]	train-mlogloss:1.12094	validation-mlogloss:1.11130
[88]	train-mlogloss:1.11922	validation-mlogloss:1.10939
[89]	train-mlogloss:1.11755	validation-mlogloss:1.10758
[90]	train-mlogloss:1.11597	validation-mlogloss:1.10574
[91]	train-mlogloss:1.11444	validation-mlogloss:1.10422
[92]	train-mlogloss:1.11274	validation-mlogloss:1.10239
[93]	train-mlogloss:1.11120	validation-mlogloss:1.10085
[94]	train-mlogloss:1.10964	validation-mlogloss:1.09915
[95]	train-mlogloss:1.10815	validation-mlogloss:1.09779
[96]	train-mlogloss:1.10671	validation-mlogloss:1.09633
[97]	train-mlogloss:1.10532	validation-mlogloss:1.09500
[98]	train-mlogloss:1.10375	validation-mlogloss:1.09338
[99]	train-mlogloss:1.10218	validation-mlogloss:1.09185
[100]	train-mlogloss:1.10037	validation-mlogloss:1.09015
[101]	train-mlogloss:1.09885	validation-mlogloss:1.08864
[102]	train-mlogloss:1.09749	validation-mlogloss:1.08731
[103]	train-mlogloss:1.09612	validation-mlogloss:1.08601
[104]	train-mlogloss:1.09465	validation-mlogloss:1.08445
[105]	train-mlogloss:1.09321	validation-mlogloss:1.08285
[106]	train-mlogloss:1.09152	validation-mlogloss:1.08138
[107]	train-mlogloss:1.08996	validation-mlogloss:1.08006
[108]	train-mlogloss:1.08866	validation-mlogloss:1.07876
[109]	train-mlogloss:1.08729	validation-mlogloss:1.07746
[110]	train-mlogloss:1.08595	validation-mlogloss:1.07611
[111]	train-mlogloss:1.08470	validation-mlogloss:1.07488
[112]	train-mlogloss:1.08337	validation-mlogloss:1.07358
[113]	train-mlogloss:1.08215	validation-mlogloss:1.07243
[114]	train-mlogloss:1.08087	validation-mlogloss:1.07135
[115]	train-mlogloss:1.07960	validation-mlogloss:1.07013
[116]	train-mlogloss:1.07829	validation-mlogloss:1.06890
[117]	train-mlogloss:1.07703	validation-mlogloss:1.06769
[118]	train-mlogloss:1.07579	validation-mlogloss:1.06647
[119]	train-mlogloss:1.07454	validation-mlogloss:1.06529
[120]	train-mlogloss:1.07332	validation-mlogloss:1.06391
[121]	train-mlogloss:1.07195	validation-mlogloss:1.06261
[122]	train-mlogloss:1.07061	validation-mlogloss:1.06155
[123]	train-mlogloss:1.06954	validation-mlogloss:1.06067
[124]	train-mlogloss:1.06849	validation-mlogloss:1.05975
[125]	train-mlogloss:1.06730	validation-mlogloss:1.05865
[126]	train-mlogloss:1.06617	validation-mlogloss:1.05761
[127]	train-mlogloss:1.06497	validation-mlogloss:1.05638
[128]	train-mlogloss:1.06375	validation-mlogloss:1.05526
[129]	train-mlogloss:1.06236	validation-mlogloss:1.05410
[130]	train-mlogloss:1.06131	validation-mlogloss:1.05296
[131]	train-mlogloss:1.06002	validation-mlogloss:1.05165
[132]	train-mlogloss:1.05886	validation-mlogloss:1.05029
[133]	train-mlogloss:1.05781	validation-mlogloss:1.04922
[134]	train-mlogloss:1.05672	validation-mlogloss:1.04826
[135]	train-mlogloss:1.05544	validation-mlogloss:1.04701
[136]	train-mlogloss:1.05439	validation-mlogloss:1.04602
[137]	train-mlogloss:1.05337	validation-mlogloss:1.04510
[138]	train-mlogloss:1.05235	validation-mlogloss:1.04410
[139]	train-mlogloss:1.05137	validation-mlogloss:1.04334
[140]	train-mlogloss:1.05037	validation-mlogloss:1.04238
[141]	train-mlogloss:1.04938	validation-mlogloss:1.04150
[142]	train-mlogloss:1.04833	validation-mlogloss:1.04034
[143]	train-mlogloss:1.04721	validation-mlogloss:1.03928
[144]	train-mlogloss:1.04625	validation-mlogloss:1.03837
[145]	train-mlogloss:1.04531	validation-mlogloss:1.03741
[146]	train-mlogloss:1.04439	validation-mlogloss:1.03665
[147]	train-mlogloss:1.04320	validation-mlogloss:1.03576
[148]	train-mlogloss:1.04226	validation-mlogloss:1.03489
[149]	train-mlogloss:1.04129	validation-mlogloss:1.03393
[150]	train-mlogloss:1.04034	validation-mlogloss:1.03303
[151]	train-mlogloss:1.03936	validation-mlogloss:1.03211
[152]	train-mlogloss:1.03836	validation-mlogloss:1.03125
[153]	train-mlogloss:1.03751	validation-mlogloss:1.03057
[154]	train-mlogloss:1.03659	validation-mlogloss:1.02976
[155]	train-mlogloss:1.03558	validation-mlogloss:1.02868
[156]	train-mlogloss:1.03461	validation-mlogloss:1.02788
[157]	train-mlogloss:1.03365	validation-mlogloss:1.02690
[158]	train-mlogloss:1.03276	validation-mlogloss:1.02612
[159]	train-mlogloss:1.03191	validation-mlogloss:1.02532
[160]	train-mlogloss:1.03103	validation-mlogloss:1.02444
[161]	train-mlogloss:1.03020	validation-mlogloss:1.02367
[162]	train-mlogloss:1.02917	validation-mlogloss:1.02292
[163]	train-mlogloss:1.02832	validation-mlogloss:1.02221
[164]	train-mlogloss:1.02759	validation-mlogloss:1.02146
[165]	train-mlogloss:1.02677	validation-mlogloss:1.02088
[166]	train-mlogloss:1.02600	validation-mlogloss:1.02022
[167]	train-mlogloss:1.02514	validation-mlogloss:1.01940
[168]	train-mlogloss:1.02407	validation-mlogloss:1.01865
[169]	train-mlogloss:1.02324	validation-mlogloss:1.01802
[170]	train-mlogloss:1.02241	validation-mlogloss:1.01743
[171]	train-mlogloss:1.02161	validation-mlogloss:1.01663
[172]	train-mlogloss:1.02064	validation-mlogloss:1.01590
[173]	train-mlogloss:1.01988	validation-mlogloss:1.01518
[174]	train-mlogloss:1.01913	validation-mlogloss:1.01448
[175]	train-mlogloss:1.01836	validation-mlogloss:1.01385
[176]	train-mlogloss:1.01763	validation-mlogloss:1.01310
[177]	train-mlogloss:1.01685	validation-mlogloss:1.01244
[178]	train-mlogloss:1.01615	validation-mlogloss:1.01179
[179]	train-mlogloss:1.01550	validation-mlogloss:1.01126
[180]	train-mlogloss:1.01460	validation-mlogloss:1.01072
[181]	train-mlogloss:1.01391	validation-mlogloss:1.01007
[182]	train-mlogloss:1.01311	validation-mlogloss:1.00923
[183]	train-mlogloss:1.01240	validation-mlogloss:1.00869
[184]	train-mlogloss:1.01162	validation-mlogloss:1.00795
[185]	train-mlogloss:1.01087	validation-mlogloss:1.00730
[186]	train-mlogloss:1.01007	validation-mlogloss:1.00660
[187]	train-mlogloss:1.00939	validation-mlogloss:1.00594
[188]	train-mlogloss:1.00866	validation-mlogloss:1.00529
[189]	train-mlogloss:1.00782	validation-mlogloss:1.00464
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[642]	train-mlogloss:0.88081	validation-mlogloss:0.91470
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[684]	train-mlogloss:0.87786	validation-mlogloss:0.91292
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[689]	train-mlogloss:0.87750	validation-mlogloss:0.91277
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[691]	train-mlogloss:0.87735	validation-mlogloss:0.91258
[692]	train-mlogloss:0.87730	validation-mlogloss:0.91254
[693]	train-mlogloss:0.87721	validation-mlogloss:0.91242
[694]	train-mlogloss:0.87717	validation-mlogloss:0.91239
[695]	train-mlogloss:0.87707	validation-mlogloss:0.91238
[696]	train-mlogloss:0.87701	validation-mlogloss:0.91233
[697]	train-mlogloss:0.87693	validation-mlogloss:0.91228
[698]	train-mlogloss:0.87688	validation-mlogloss:0.91228
[699]	train-mlogloss:0.87684	validation-mlogloss:0.91226
[700]	train-mlogloss:0.87680	validation-mlogloss:0.91226
[701]	train-mlogloss:0.87668	validation-mlogloss:0.91216
[702]	train-mlogloss:0.87658	validation-mlogloss:0.91208
[703]	train-mlogloss:0.87651	validation-mlogloss:0.91205
[704]	train-mlogloss:0.87643	validation-mlogloss:0.91200
[705]	train-mlogloss:0.87639	validation-mlogloss:0.91203
[706]	train-mlogloss:0.87629	validation-mlogloss:0.91198
[707]	train-mlogloss:0.87624	validation-mlogloss:0.91194
[708]	train-mlogloss:0.87615	validation-mlogloss:0.91191
[709]	train-mlogloss:0.87607	validation-mlogloss:0.91194
[710]	train-mlogloss:0.87601	validation-mlogloss:0.91184
[711]	train-mlogloss:0.87593	validation-mlogloss:0.91184
[712]	train-mlogloss:0.87589	validation-mlogloss:0.91179
[713]	train-mlogloss:0.87577	validation-mlogloss:0.91180
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[1 1 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.59 [%]
Global accuracy score (test) = 60.06 [%]
Global F1 score (train) = 63.7 [%]
Global F1 score (test) = 60.86 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.45      0.46      0.46       400
MODERATE-INTENSITY       0.54      0.61      0.57       400
         SEDENTARY       0.65      0.72      0.68       400
VIGOROUS-INTENSITY       0.87      0.62      0.72       345

          accuracy                           0.60      1545
         macro avg       0.63      0.60      0.61      1545
      weighted avg       0.62      0.60      0.60      1545


Accuracy capturado en la ejecución 4: 60.06 [%]
F1-score capturado en la ejecución 4: 60.86 [%]

=== EJECUCIÓN 5 ===

--- TRAIN (ejecución 5) ---

--- TEST (ejecución 5) ---
2025-11-04 10:59:54.169094: 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`.
2025-11-04 10:59:54.180524: 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 00:00:1762250394.193522 1078432 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250394.197407 1078432 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250394.207332 1078432 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250394.207350 1078432 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250394.207351 1078432 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250394.207353 1078432 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:59:54.210478: 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:1.38119	validation-mlogloss:1.38129
[1]	train-mlogloss:1.37615	validation-mlogloss:1.37630
[2]	train-mlogloss:1.37132	validation-mlogloss:1.37122
[3]	train-mlogloss:1.36636	validation-mlogloss:1.36624
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[10]	train-mlogloss:1.33392	validation-mlogloss:1.33330
[11]	train-mlogloss:1.32960	validation-mlogloss:1.32877
[12]	train-mlogloss:1.32535	validation-mlogloss:1.32430
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[16]	train-mlogloss:1.30937	validation-mlogloss:1.30857
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[19]	train-mlogloss:1.29746	validation-mlogloss:1.29644
[20]	train-mlogloss:1.29374	validation-mlogloss:1.29260
[21]	train-mlogloss:1.29010	validation-mlogloss:1.28904
[22]	train-mlogloss:1.28648	validation-mlogloss:1.28512
[23]	train-mlogloss:1.28256	validation-mlogloss:1.28104
[24]	train-mlogloss:1.27902	validation-mlogloss:1.27755
[25]	train-mlogloss:1.27555	validation-mlogloss:1.27398
[26]	train-mlogloss:1.27217	validation-mlogloss:1.27071
[27]	train-mlogloss:1.26875	validation-mlogloss:1.26718
[28]	train-mlogloss:1.26540	validation-mlogloss:1.26375
[29]	train-mlogloss:1.26220	validation-mlogloss:1.26041
[30]	train-mlogloss:1.25855	validation-mlogloss:1.25648
[31]	train-mlogloss:1.25542	validation-mlogloss:1.25326
[32]	train-mlogloss:1.25224	validation-mlogloss:1.24992
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[34]	train-mlogloss:1.24602	validation-mlogloss:1.24368
[35]	train-mlogloss:1.24292	validation-mlogloss:1.24046
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[37]	train-mlogloss:1.23704	validation-mlogloss:1.23455
[38]	train-mlogloss:1.23412	validation-mlogloss:1.23142
[39]	train-mlogloss:1.23118	validation-mlogloss:1.22831
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[43]	train-mlogloss:1.21993	validation-mlogloss:1.21641
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[45]	train-mlogloss:1.21472	validation-mlogloss:1.21103
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[49]	train-mlogloss:1.20418	validation-mlogloss:1.20011
[50]	train-mlogloss:1.20169	validation-mlogloss:1.19745
[51]	train-mlogloss:1.19930	validation-mlogloss:1.19494
[52]	train-mlogloss:1.19686	validation-mlogloss:1.19256
[53]	train-mlogloss:1.19453	validation-mlogloss:1.19009
[54]	train-mlogloss:1.19176	validation-mlogloss:1.18726
[55]	train-mlogloss:1.18946	validation-mlogloss:1.18506
[56]	train-mlogloss:1.18683	validation-mlogloss:1.18235
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[58]	train-mlogloss:1.18248	validation-mlogloss:1.17785
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[72]	train-mlogloss:1.15216	validation-mlogloss:1.14666
[73]	train-mlogloss:1.15032	validation-mlogloss:1.14475
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[76]	train-mlogloss:1.14423	validation-mlogloss:1.13918
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[82]	train-mlogloss:1.13340	validation-mlogloss:1.12844
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[85]	train-mlogloss:1.12793	validation-mlogloss:1.12306
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[89]	train-mlogloss:1.12101	validation-mlogloss:1.11642
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[91]	train-mlogloss:1.11794	validation-mlogloss:1.11353
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[100]	train-mlogloss:1.10461	validation-mlogloss:1.10077
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[103]	train-mlogloss:1.10032	validation-mlogloss:1.09652
[104]	train-mlogloss:1.09885	validation-mlogloss:1.09510
[105]	train-mlogloss:1.09736	validation-mlogloss:1.09364
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[109]	train-mlogloss:1.09184	validation-mlogloss:1.08813
[110]	train-mlogloss:1.09066	validation-mlogloss:1.08684
[111]	train-mlogloss:1.08935	validation-mlogloss:1.08568
[112]	train-mlogloss:1.08803	validation-mlogloss:1.08422
[113]	train-mlogloss:1.08665	validation-mlogloss:1.08277
[114]	train-mlogloss:1.08536	validation-mlogloss:1.08152
[115]	train-mlogloss:1.08408	validation-mlogloss:1.08026
[116]	train-mlogloss:1.08288	validation-mlogloss:1.07910
[117]	train-mlogloss:1.08161	validation-mlogloss:1.07760
[118]	train-mlogloss:1.08052	validation-mlogloss:1.07660
[119]	train-mlogloss:1.07930	validation-mlogloss:1.07565
[120]	train-mlogloss:1.07815	validation-mlogloss:1.07463
[121]	train-mlogloss:1.07677	validation-mlogloss:1.07351
[122]	train-mlogloss:1.07554	validation-mlogloss:1.07230
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[129]	train-mlogloss:1.06767	validation-mlogloss:1.06476
[130]	train-mlogloss:1.06650	validation-mlogloss:1.06364
[131]	train-mlogloss:1.06538	validation-mlogloss:1.06271
[132]	train-mlogloss:1.06430	validation-mlogloss:1.06165
[133]	train-mlogloss:1.06319	validation-mlogloss:1.06055
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[136]	train-mlogloss:1.06001	validation-mlogloss:1.05768
[137]	train-mlogloss:1.05893	validation-mlogloss:1.05657
[138]	train-mlogloss:1.05799	validation-mlogloss:1.05575
[139]	train-mlogloss:1.05702	validation-mlogloss:1.05487
[140]	train-mlogloss:1.05600	validation-mlogloss:1.05374
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[142]	train-mlogloss:1.05405	validation-mlogloss:1.05180
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[146]	train-mlogloss:1.04993	validation-mlogloss:1.04813
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[149]	train-mlogloss:1.04722	validation-mlogloss:1.04560
[150]	train-mlogloss:1.04604	validation-mlogloss:1.04455
[151]	train-mlogloss:1.04515	validation-mlogloss:1.04383
[152]	train-mlogloss:1.04417	validation-mlogloss:1.04301
[153]	train-mlogloss:1.04323	validation-mlogloss:1.04210
[154]	train-mlogloss:1.04234	validation-mlogloss:1.04135
[155]	train-mlogloss:1.04140	validation-mlogloss:1.04032
[156]	train-mlogloss:1.04042	validation-mlogloss:1.03922
[157]	train-mlogloss:1.03955	validation-mlogloss:1.03851
[158]	train-mlogloss:1.03862	validation-mlogloss:1.03773
[159]	train-mlogloss:1.03777	validation-mlogloss:1.03689
[160]	train-mlogloss:1.03690	validation-mlogloss:1.03607
[161]	train-mlogloss:1.03605	validation-mlogloss:1.03542
[162]	train-mlogloss:1.03509	validation-mlogloss:1.03448
[163]	train-mlogloss:1.03422	validation-mlogloss:1.03364
[164]	train-mlogloss:1.03340	validation-mlogloss:1.03303
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[190]	train-mlogloss:1.01340	validation-mlogloss:1.01532
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[197]	train-mlogloss:1.00846	validation-mlogloss:1.01145
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[199]	train-mlogloss:1.00721	validation-mlogloss:1.01041
[200]	train-mlogloss:1.00654	validation-mlogloss:1.00993
[201]	train-mlogloss:1.00592	validation-mlogloss:1.00932
[202]	train-mlogloss:1.00527	validation-mlogloss:1.00895
[203]	train-mlogloss:1.00448	validation-mlogloss:1.00842
[204]	train-mlogloss:1.00390	validation-mlogloss:1.00788
[205]	train-mlogloss:1.00326	validation-mlogloss:1.00725
[206]	train-mlogloss:1.00260	validation-mlogloss:1.00669
[207]	train-mlogloss:1.00204	validation-mlogloss:1.00628
[208]	train-mlogloss:1.00143	validation-mlogloss:1.00582
[209]	train-mlogloss:1.00072	validation-mlogloss:1.00501
[210]	train-mlogloss:1.00016	validation-mlogloss:1.00461
[211]	train-mlogloss:0.99960	validation-mlogloss:1.00419
[212]	train-mlogloss:0.99895	validation-mlogloss:1.00348
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[220]	train-mlogloss:0.99413	validation-mlogloss:1.00026
[221]	train-mlogloss:0.99357	validation-mlogloss:0.99992
[222]	train-mlogloss:0.99295	validation-mlogloss:0.99940
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[636]	train-mlogloss:0.88587	validation-mlogloss:0.92318
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[638]	train-mlogloss:0.88573	validation-mlogloss:0.92318
[639]	train-mlogloss:0.88566	validation-mlogloss:0.92312
[640]	train-mlogloss:0.88555	validation-mlogloss:0.92306
[641]	train-mlogloss:0.88550	validation-mlogloss:0.92299
[642]	train-mlogloss:0.88542	validation-mlogloss:0.92294
[643]	train-mlogloss:0.88529	validation-mlogloss:0.92291
[644]	train-mlogloss:0.88521	validation-mlogloss:0.92285
[645]	train-mlogloss:0.88513	validation-mlogloss:0.92278
[646]	train-mlogloss:0.88500	validation-mlogloss:0.92269
[647]	train-mlogloss:0.88493	validation-mlogloss:0.92266
[648]	train-mlogloss:0.88481	validation-mlogloss:0.92263
[649]	train-mlogloss:0.88475	validation-mlogloss:0.92259
[650]	train-mlogloss:0.88468	validation-mlogloss:0.92255
[651]	train-mlogloss:0.88452	validation-mlogloss:0.92251
[652]	train-mlogloss:0.88440	validation-mlogloss:0.92244
[653]	train-mlogloss:0.88426	validation-mlogloss:0.92236
[654]	train-mlogloss:0.88418	validation-mlogloss:0.92221
[655]	train-mlogloss:0.88412	validation-mlogloss:0.92213
[656]	train-mlogloss:0.88407	validation-mlogloss:0.92211
[657]	train-mlogloss:0.88396	validation-mlogloss:0.92205
[658]	train-mlogloss:0.88385	validation-mlogloss:0.92202
[659]	train-mlogloss:0.88378	validation-mlogloss:0.92196
[660]	train-mlogloss:0.88372	validation-mlogloss:0.92196
[661]	train-mlogloss:0.88367	validation-mlogloss:0.92194
[662]	train-mlogloss:0.88360	validation-mlogloss:0.92192
[663]	train-mlogloss:0.88355	validation-mlogloss:0.92192
[664]	train-mlogloss:0.88345	validation-mlogloss:0.92181
[665]	train-mlogloss:0.88340	validation-mlogloss:0.92178
[666]	train-mlogloss:0.88331	validation-mlogloss:0.92169
[667]	train-mlogloss:0.88327	validation-mlogloss:0.92168
[668]	train-mlogloss:0.88322	validation-mlogloss:0.92169
[669]	train-mlogloss:0.88316	validation-mlogloss:0.92165
[670]	train-mlogloss:0.88307	validation-mlogloss:0.92153
[671]	train-mlogloss:0.88300	validation-mlogloss:0.92148
[672]	train-mlogloss:0.88293	validation-mlogloss:0.92141
[673]	train-mlogloss:0.88291	validation-mlogloss:0.92140
[674]	train-mlogloss:0.88283	validation-mlogloss:0.92141
[675]	train-mlogloss:0.88278	validation-mlogloss:0.92139
[676]	train-mlogloss:0.88271	validation-mlogloss:0.92136
[677]	train-mlogloss:0.88268	validation-mlogloss:0.92134
[678]	train-mlogloss:0.88257	validation-mlogloss:0.92127
[679]	train-mlogloss:0.88250	validation-mlogloss:0.92126
[680]	train-mlogloss:0.88245	validation-mlogloss:0.92126
[681]	train-mlogloss:0.88237	validation-mlogloss:0.92119
[682]	train-mlogloss:0.88231	validation-mlogloss:0.92118
[683]	train-mlogloss:0.88222	validation-mlogloss:0.92109
[684]	train-mlogloss:0.88217	validation-mlogloss:0.92108
[685]	train-mlogloss:0.88210	validation-mlogloss:0.92104
[686]	train-mlogloss:0.88201	validation-mlogloss:0.92095
[687]	train-mlogloss:0.88194	validation-mlogloss:0.92091
[688]	train-mlogloss:0.88188	validation-mlogloss:0.92084
[689]	train-mlogloss:0.88177	validation-mlogloss:0.92078
[690]	train-mlogloss:0.88172	validation-mlogloss:0.92073
[691]	train-mlogloss:0.88167	validation-mlogloss:0.92071
[692]	train-mlogloss:0.88150	validation-mlogloss:0.92065
[693]	train-mlogloss:0.88146	validation-mlogloss:0.92065
[694]	train-mlogloss:0.88139	validation-mlogloss:0.92058
[695]	train-mlogloss:0.88131	validation-mlogloss:0.92055
[696]	train-mlogloss:0.88129	validation-mlogloss:0.92053
[697]	train-mlogloss:0.88120	validation-mlogloss:0.92044
[698]	train-mlogloss:0.88109	validation-mlogloss:0.92043
[699]	train-mlogloss:0.88107	validation-mlogloss:0.92044
[700]	train-mlogloss:0.88100	validation-mlogloss:0.92043
[701]	train-mlogloss:0.88093	validation-mlogloss:0.92038
[702]	train-mlogloss:0.88083	validation-mlogloss:0.92027
[703]	train-mlogloss:0.88078	validation-mlogloss:0.92022
[704]	train-mlogloss:0.88074	validation-mlogloss:0.92023
[705]	train-mlogloss:0.88069	validation-mlogloss:0.92021
[706]	train-mlogloss:0.88065	validation-mlogloss:0.92020
[707]	train-mlogloss:0.88061	validation-mlogloss:0.92020
[708]	train-mlogloss:0.88056	validation-mlogloss:0.92018
[709]	train-mlogloss:0.88045	validation-mlogloss:0.92011
[710]	train-mlogloss:0.88033	validation-mlogloss:0.92005
[711]	train-mlogloss:0.88026	validation-mlogloss:0.91997
[712]	train-mlogloss:0.88021	validation-mlogloss:0.91994
[713]	train-mlogloss:0.88017	validation-mlogloss:0.91990
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 0 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.64 [%]
Global accuracy score (test) = 61.75 [%]
Global F1 score (train) = 63.73 [%]
Global F1 score (test) = 62.31 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.47      0.47      0.47       400
MODERATE-INTENSITY       0.57      0.67      0.62       400
         SEDENTARY       0.67      0.72      0.69       400
VIGOROUS-INTENSITY       0.85      0.62      0.72       345

          accuracy                           0.62      1545
         macro avg       0.64      0.62      0.62      1545
      weighted avg       0.63      0.62      0.62      1545


Accuracy capturado en la ejecución 5: 61.75 [%]
F1-score capturado en la ejecución 5: 62.31 [%]

=== EJECUCIÓN 6 ===

--- TRAIN (ejecución 6) ---

--- TEST (ejecución 6) ---
2025-11-04 11:00:11.220723: 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`.
2025-11-04 11:00:11.232191: 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 00:00:1762250411.245248 1078767 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250411.249328 1078767 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250411.259161 1078767 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250411.259177 1078767 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250411.259185 1078767 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250411.259186 1078767 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:00:11.262345: 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)
Training a non-convolutional model.
[0]	train-mlogloss:1.38105	validation-mlogloss:1.38086
[1]	train-mlogloss:1.37565	validation-mlogloss:1.37541
[2]	train-mlogloss:1.37067	validation-mlogloss:1.37041
[3]	train-mlogloss:1.36573	validation-mlogloss:1.36554
[4]	train-mlogloss:1.36087	validation-mlogloss:1.36058
[5]	train-mlogloss:1.35582	validation-mlogloss:1.35541
[6]	train-mlogloss:1.35092	validation-mlogloss:1.35045
[7]	train-mlogloss:1.34641	validation-mlogloss:1.34575
[8]	train-mlogloss:1.34204	validation-mlogloss:1.34109
[9]	train-mlogloss:1.33718	validation-mlogloss:1.33582
[10]	train-mlogloss:1.33277	validation-mlogloss:1.33153
[11]	train-mlogloss:1.32854	validation-mlogloss:1.32726
[12]	train-mlogloss:1.32455	validation-mlogloss:1.32366
[13]	train-mlogloss:1.32002	validation-mlogloss:1.31866
[14]	train-mlogloss:1.31597	validation-mlogloss:1.31443
[15]	train-mlogloss:1.31197	validation-mlogloss:1.31047
[16]	train-mlogloss:1.30815	validation-mlogloss:1.30648
[17]	train-mlogloss:1.30425	validation-mlogloss:1.30243
[18]	train-mlogloss:1.30036	validation-mlogloss:1.29871
[19]	train-mlogloss:1.29621	validation-mlogloss:1.29423
[20]	train-mlogloss:1.29240	validation-mlogloss:1.29006
[21]	train-mlogloss:1.28865	validation-mlogloss:1.28595
[22]	train-mlogloss:1.28490	validation-mlogloss:1.28221
[23]	train-mlogloss:1.28144	validation-mlogloss:1.27874
[24]	train-mlogloss:1.27783	validation-mlogloss:1.27486
[25]	train-mlogloss:1.27440	validation-mlogloss:1.27155
[26]	train-mlogloss:1.27097	validation-mlogloss:1.26817
[27]	train-mlogloss:1.26762	validation-mlogloss:1.26473
[28]	train-mlogloss:1.26430	validation-mlogloss:1.26120
[29]	train-mlogloss:1.26116	validation-mlogloss:1.25792
[30]	train-mlogloss:1.25751	validation-mlogloss:1.25392
[31]	train-mlogloss:1.25424	validation-mlogloss:1.25039
[32]	train-mlogloss:1.25078	validation-mlogloss:1.24660
[33]	train-mlogloss:1.24769	validation-mlogloss:1.24322
[34]	train-mlogloss:1.24476	validation-mlogloss:1.24008
[35]	train-mlogloss:1.24175	validation-mlogloss:1.23705
[36]	train-mlogloss:1.23882	validation-mlogloss:1.23425
[37]	train-mlogloss:1.23551	validation-mlogloss:1.23080
[38]	train-mlogloss:1.23266	validation-mlogloss:1.22816
[39]	train-mlogloss:1.22987	validation-mlogloss:1.22517
[40]	train-mlogloss:1.22664	validation-mlogloss:1.22200
[41]	train-mlogloss:1.22387	validation-mlogloss:1.21933
[42]	train-mlogloss:1.22117	validation-mlogloss:1.21686
[43]	train-mlogloss:1.21849	validation-mlogloss:1.21426
[44]	train-mlogloss:1.21584	validation-mlogloss:1.21147
[45]	train-mlogloss:1.21315	validation-mlogloss:1.20882
[46]	train-mlogloss:1.21070	validation-mlogloss:1.20630
[47]	train-mlogloss:1.20815	validation-mlogloss:1.20367
[48]	train-mlogloss:1.20558	validation-mlogloss:1.20111
[49]	train-mlogloss:1.20288	validation-mlogloss:1.19845
[50]	train-mlogloss:1.20045	validation-mlogloss:1.19601
[51]	train-mlogloss:1.19797	validation-mlogloss:1.19315
[52]	train-mlogloss:1.19558	validation-mlogloss:1.19070
[53]	train-mlogloss:1.19320	validation-mlogloss:1.18825
[54]	train-mlogloss:1.19081	validation-mlogloss:1.18562
[55]	train-mlogloss:1.18859	validation-mlogloss:1.18343
[56]	train-mlogloss:1.18635	validation-mlogloss:1.18147
[57]	train-mlogloss:1.18411	validation-mlogloss:1.17921
[58]	train-mlogloss:1.18152	validation-mlogloss:1.17640
[59]	train-mlogloss:1.17934	validation-mlogloss:1.17447
[60]	train-mlogloss:1.17707	validation-mlogloss:1.17224
[61]	train-mlogloss:1.17481	validation-mlogloss:1.16983
[62]	train-mlogloss:1.17273	validation-mlogloss:1.16768
[63]	train-mlogloss:1.17052	validation-mlogloss:1.16537
[64]	train-mlogloss:1.16840	validation-mlogloss:1.16321
[65]	train-mlogloss:1.16640	validation-mlogloss:1.16123
[66]	train-mlogloss:1.16421	validation-mlogloss:1.15901
[67]	train-mlogloss:1.16214	validation-mlogloss:1.15698
[68]	train-mlogloss:1.16001	validation-mlogloss:1.15456
[69]	train-mlogloss:1.15793	validation-mlogloss:1.15232
[70]	train-mlogloss:1.15590	validation-mlogloss:1.15045
[71]	train-mlogloss:1.15406	validation-mlogloss:1.14864
[72]	train-mlogloss:1.15222	validation-mlogloss:1.14676
[73]	train-mlogloss:1.15026	validation-mlogloss:1.14464
[74]	train-mlogloss:1.14806	validation-mlogloss:1.14255
[75]	train-mlogloss:1.14621	validation-mlogloss:1.14083
[76]	train-mlogloss:1.14407	validation-mlogloss:1.13878
[77]	train-mlogloss:1.14229	validation-mlogloss:1.13679
[78]	train-mlogloss:1.14026	validation-mlogloss:1.13474
[79]	train-mlogloss:1.13847	validation-mlogloss:1.13291
[80]	train-mlogloss:1.13670	validation-mlogloss:1.13122
[81]	train-mlogloss:1.13477	validation-mlogloss:1.12919
[82]	train-mlogloss:1.13312	validation-mlogloss:1.12785
[83]	train-mlogloss:1.13133	validation-mlogloss:1.12591
[84]	train-mlogloss:1.12957	validation-mlogloss:1.12418
[85]	train-mlogloss:1.12800	validation-mlogloss:1.12265
[86]	train-mlogloss:1.12637	validation-mlogloss:1.12110
[87]	train-mlogloss:1.12462	validation-mlogloss:1.11951
[88]	train-mlogloss:1.12300	validation-mlogloss:1.11798
[89]	train-mlogloss:1.12149	validation-mlogloss:1.11648
[90]	train-mlogloss:1.11988	validation-mlogloss:1.11480
[91]	train-mlogloss:1.11841	validation-mlogloss:1.11325
[92]	train-mlogloss:1.11695	validation-mlogloss:1.11192
[93]	train-mlogloss:1.11516	validation-mlogloss:1.10998
[94]	train-mlogloss:1.11358	validation-mlogloss:1.10837
[95]	train-mlogloss:1.11200	validation-mlogloss:1.10692
[96]	train-mlogloss:1.11040	validation-mlogloss:1.10522
[97]	train-mlogloss:1.10880	validation-mlogloss:1.10375
[98]	train-mlogloss:1.10709	validation-mlogloss:1.10210
[99]	train-mlogloss:1.10562	validation-mlogloss:1.10048
[100]	train-mlogloss:1.10408	validation-mlogloss:1.09891
[101]	train-mlogloss:1.10266	validation-mlogloss:1.09766
[102]	train-mlogloss:1.10134	validation-mlogloss:1.09631
[103]	train-mlogloss:1.09986	validation-mlogloss:1.09492
[104]	train-mlogloss:1.09847	validation-mlogloss:1.09358
[105]	train-mlogloss:1.09718	validation-mlogloss:1.09223
[106]	train-mlogloss:1.09596	validation-mlogloss:1.09101
[107]	train-mlogloss:1.09458	validation-mlogloss:1.08964
[108]	train-mlogloss:1.09326	validation-mlogloss:1.08829
[109]	train-mlogloss:1.09192	validation-mlogloss:1.08684
[110]	train-mlogloss:1.09056	validation-mlogloss:1.08548
[111]	train-mlogloss:1.08924	validation-mlogloss:1.08410
[112]	train-mlogloss:1.08783	validation-mlogloss:1.08280
[113]	train-mlogloss:1.08650	validation-mlogloss:1.08142
[114]	train-mlogloss:1.08510	validation-mlogloss:1.08010
[115]	train-mlogloss:1.08392	validation-mlogloss:1.07907
[116]	train-mlogloss:1.08262	validation-mlogloss:1.07785
[117]	train-mlogloss:1.08138	validation-mlogloss:1.07675
[118]	train-mlogloss:1.08008	validation-mlogloss:1.07563
[119]	train-mlogloss:1.07885	validation-mlogloss:1.07434
[120]	train-mlogloss:1.07737	validation-mlogloss:1.07324
[121]	train-mlogloss:1.07613	validation-mlogloss:1.07210
[122]	train-mlogloss:1.07496	validation-mlogloss:1.07095
[123]	train-mlogloss:1.07371	validation-mlogloss:1.06970
[124]	train-mlogloss:1.07249	validation-mlogloss:1.06859
[125]	train-mlogloss:1.07110	validation-mlogloss:1.06714
[126]	train-mlogloss:1.06989	validation-mlogloss:1.06601
[127]	train-mlogloss:1.06870	validation-mlogloss:1.06490
[128]	train-mlogloss:1.06760	validation-mlogloss:1.06396
[129]	train-mlogloss:1.06653	validation-mlogloss:1.06309
[130]	train-mlogloss:1.06544	validation-mlogloss:1.06198
[131]	train-mlogloss:1.06438	validation-mlogloss:1.06114
[132]	train-mlogloss:1.06317	validation-mlogloss:1.06007
[133]	train-mlogloss:1.06201	validation-mlogloss:1.05874
[134]	train-mlogloss:1.06094	validation-mlogloss:1.05777
[135]	train-mlogloss:1.05986	validation-mlogloss:1.05698
[136]	train-mlogloss:1.05881	validation-mlogloss:1.05592
[137]	train-mlogloss:1.05771	validation-mlogloss:1.05476
[138]	train-mlogloss:1.05670	validation-mlogloss:1.05381
[139]	train-mlogloss:1.05575	validation-mlogloss:1.05293
[140]	train-mlogloss:1.05467	validation-mlogloss:1.05181
[141]	train-mlogloss:1.05363	validation-mlogloss:1.05077
[142]	train-mlogloss:1.05241	validation-mlogloss:1.04990
[143]	train-mlogloss:1.05140	validation-mlogloss:1.04885
[144]	train-mlogloss:1.05032	validation-mlogloss:1.04787
[145]	train-mlogloss:1.04925	validation-mlogloss:1.04689
[146]	train-mlogloss:1.04823	validation-mlogloss:1.04578
[147]	train-mlogloss:1.04726	validation-mlogloss:1.04495
[148]	train-mlogloss:1.04625	validation-mlogloss:1.04391
[149]	train-mlogloss:1.04539	validation-mlogloss:1.04320
[150]	train-mlogloss:1.04438	validation-mlogloss:1.04228
[151]	train-mlogloss:1.04346	validation-mlogloss:1.04132
[152]	train-mlogloss:1.04265	validation-mlogloss:1.04053
[153]	train-mlogloss:1.04177	validation-mlogloss:1.03962
[154]	train-mlogloss:1.04086	validation-mlogloss:1.03885
[155]	train-mlogloss:1.03996	validation-mlogloss:1.03795
[156]	train-mlogloss:1.03901	validation-mlogloss:1.03708
[157]	train-mlogloss:1.03812	validation-mlogloss:1.03607
[158]	train-mlogloss:1.03729	validation-mlogloss:1.03520
[159]	train-mlogloss:1.03649	validation-mlogloss:1.03440
[160]	train-mlogloss:1.03567	validation-mlogloss:1.03360
[161]	train-mlogloss:1.03480	validation-mlogloss:1.03281
[162]	train-mlogloss:1.03398	validation-mlogloss:1.03198
[163]	train-mlogloss:1.03304	validation-mlogloss:1.03111
[164]	train-mlogloss:1.03220	validation-mlogloss:1.03026
[165]	train-mlogloss:1.03141	validation-mlogloss:1.02971
[166]	train-mlogloss:1.03060	validation-mlogloss:1.02892
[167]	train-mlogloss:1.02973	validation-mlogloss:1.02807
[168]	train-mlogloss:1.02889	validation-mlogloss:1.02708
[169]	train-mlogloss:1.02808	validation-mlogloss:1.02635
[170]	train-mlogloss:1.02726	validation-mlogloss:1.02565
[171]	train-mlogloss:1.02652	validation-mlogloss:1.02504
[172]	train-mlogloss:1.02567	validation-mlogloss:1.02439
[173]	train-mlogloss:1.02489	validation-mlogloss:1.02351
[174]	train-mlogloss:1.02415	validation-mlogloss:1.02281
[175]	train-mlogloss:1.02339	validation-mlogloss:1.02227
[176]	train-mlogloss:1.02263	validation-mlogloss:1.02166
[177]	train-mlogloss:1.02186	validation-mlogloss:1.02100
[178]	train-mlogloss:1.02114	validation-mlogloss:1.02043
[179]	train-mlogloss:1.02032	validation-mlogloss:1.01966
[180]	train-mlogloss:1.01957	validation-mlogloss:1.01909
[181]	train-mlogloss:1.01880	validation-mlogloss:1.01842
[182]	train-mlogloss:1.01784	validation-mlogloss:1.01776
[183]	train-mlogloss:1.01713	validation-mlogloss:1.01713
[184]	train-mlogloss:1.01645	validation-mlogloss:1.01643
[185]	train-mlogloss:1.01557	validation-mlogloss:1.01567
[186]	train-mlogloss:1.01486	validation-mlogloss:1.01491
[187]	train-mlogloss:1.01421	validation-mlogloss:1.01432
[188]	train-mlogloss:1.01349	validation-mlogloss:1.01364
[189]	train-mlogloss:1.01276	validation-mlogloss:1.01317
[190]	train-mlogloss:1.01208	validation-mlogloss:1.01249
[191]	train-mlogloss:1.01139	validation-mlogloss:1.01191
[192]	train-mlogloss:1.01069	validation-mlogloss:1.01110
[193]	train-mlogloss:1.01002	validation-mlogloss:1.01042
[194]	train-mlogloss:1.00931	validation-mlogloss:1.00975
[195]	train-mlogloss:1.00863	validation-mlogloss:1.00926
[196]	train-mlogloss:1.00790	validation-mlogloss:1.00872
[197]	train-mlogloss:1.00721	validation-mlogloss:1.00824
[198]	train-mlogloss:1.00644	validation-mlogloss:1.00767
[199]	train-mlogloss:1.00581	validation-mlogloss:1.00717
[200]	train-mlogloss:1.00509	validation-mlogloss:1.00660
[201]	train-mlogloss:1.00440	validation-mlogloss:1.00588
[202]	train-mlogloss:1.00371	validation-mlogloss:1.00526
[203]	train-mlogloss:1.00315	validation-mlogloss:1.00488
[204]	train-mlogloss:1.00247	validation-mlogloss:1.00445
[205]	train-mlogloss:1.00184	validation-mlogloss:1.00402
[206]	train-mlogloss:1.00119	validation-mlogloss:1.00347
[207]	train-mlogloss:1.00064	validation-mlogloss:1.00309
[208]	train-mlogloss:0.99990	validation-mlogloss:1.00264
[209]	train-mlogloss:0.99932	validation-mlogloss:1.00210
[210]	train-mlogloss:0.99870	validation-mlogloss:1.00162
[211]	train-mlogloss:0.99810	validation-mlogloss:1.00107
[212]	train-mlogloss:0.99741	validation-mlogloss:1.00040
[213]	train-mlogloss:0.99681	validation-mlogloss:1.00001
[214]	train-mlogloss:0.99616	validation-mlogloss:0.99948
[215]	train-mlogloss:0.99555	validation-mlogloss:0.99911
[216]	train-mlogloss:0.99496	validation-mlogloss:0.99864
[217]	train-mlogloss:0.99442	validation-mlogloss:0.99814
[218]	train-mlogloss:0.99385	validation-mlogloss:0.99766
[219]	train-mlogloss:0.99322	validation-mlogloss:0.99715
[220]	train-mlogloss:0.99260	validation-mlogloss:0.99658
[221]	train-mlogloss:0.99208	validation-mlogloss:0.99627
[222]	train-mlogloss:0.99146	validation-mlogloss:0.99572
[223]	train-mlogloss:0.99085	validation-mlogloss:0.99518
[224]	train-mlogloss:0.99029	validation-mlogloss:0.99486
[225]	train-mlogloss:0.98970	validation-mlogloss:0.99443
[226]	train-mlogloss:0.98906	validation-mlogloss:0.99404
[227]	train-mlogloss:0.98852	validation-mlogloss:0.99364
[228]	train-mlogloss:0.98796	validation-mlogloss:0.99322
[229]	train-mlogloss:0.98749	validation-mlogloss:0.99280
[230]	train-mlogloss:0.98697	validation-mlogloss:0.99248
[231]	train-mlogloss:0.98642	validation-mlogloss:0.99215
[232]	train-mlogloss:0.98591	validation-mlogloss:0.99181
[233]	train-mlogloss:0.98537	validation-mlogloss:0.99123
[234]	train-mlogloss:0.98487	validation-mlogloss:0.99083
[235]	train-mlogloss:0.98436	validation-mlogloss:0.99043
[236]	train-mlogloss:0.98376	validation-mlogloss:0.98999
[237]	train-mlogloss:0.98321	validation-mlogloss:0.98949
[238]	train-mlogloss:0.98271	validation-mlogloss:0.98904
[239]	train-mlogloss:0.98214	validation-mlogloss:0.98842
[240]	train-mlogloss:0.98166	validation-mlogloss:0.98796
[241]	train-mlogloss:0.98110	validation-mlogloss:0.98757
[242]	train-mlogloss:0.98061	validation-mlogloss:0.98736
[243]	train-mlogloss:0.98006	validation-mlogloss:0.98683
[244]	train-mlogloss:0.97951	validation-mlogloss:0.98654
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[246]	train-mlogloss:0.97854	validation-mlogloss:0.98588
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[248]	train-mlogloss:0.97743	validation-mlogloss:0.98525
[249]	train-mlogloss:0.97699	validation-mlogloss:0.98471
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[251]	train-mlogloss:0.97605	validation-mlogloss:0.98395
[252]	train-mlogloss:0.97560	validation-mlogloss:0.98369
[253]	train-mlogloss:0.97507	validation-mlogloss:0.98304
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[258]	train-mlogloss:0.97262	validation-mlogloss:0.98118
[259]	train-mlogloss:0.97208	validation-mlogloss:0.98080
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[261]	train-mlogloss:0.97120	validation-mlogloss:0.98028
[262]	train-mlogloss:0.97079	validation-mlogloss:0.97990
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[267]	train-mlogloss:0.96842	validation-mlogloss:0.97851
[268]	train-mlogloss:0.96793	validation-mlogloss:0.97831
[269]	train-mlogloss:0.96753	validation-mlogloss:0.97795
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[271]	train-mlogloss:0.96656	validation-mlogloss:0.97757
[272]	train-mlogloss:0.96612	validation-mlogloss:0.97718
[273]	train-mlogloss:0.96566	validation-mlogloss:0.97697
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[275]	train-mlogloss:0.96480	validation-mlogloss:0.97634
[276]	train-mlogloss:0.96440	validation-mlogloss:0.97608
[277]	train-mlogloss:0.96395	validation-mlogloss:0.97588
[278]	train-mlogloss:0.96347	validation-mlogloss:0.97553
[279]	train-mlogloss:0.96295	validation-mlogloss:0.97518
[280]	train-mlogloss:0.96250	validation-mlogloss:0.97493
[281]	train-mlogloss:0.96204	validation-mlogloss:0.97467
[282]	train-mlogloss:0.96158	validation-mlogloss:0.97436
[283]	train-mlogloss:0.96114	validation-mlogloss:0.97409
[284]	train-mlogloss:0.96076	validation-mlogloss:0.97385
[285]	train-mlogloss:0.96030	validation-mlogloss:0.97351
[286]	train-mlogloss:0.95993	validation-mlogloss:0.97337
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[581]	train-mlogloss:0.89102	validation-mlogloss:0.92916
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[583]	train-mlogloss:0.89085	validation-mlogloss:0.92911
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[585]	train-mlogloss:0.89067	validation-mlogloss:0.92906
[586]	train-mlogloss:0.89059	validation-mlogloss:0.92903
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[593]	train-mlogloss:0.88989	validation-mlogloss:0.92855
[594]	train-mlogloss:0.88985	validation-mlogloss:0.92851
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[596]	train-mlogloss:0.88969	validation-mlogloss:0.92837
[597]	train-mlogloss:0.88962	validation-mlogloss:0.92831
[598]	train-mlogloss:0.88949	validation-mlogloss:0.92823
[599]	train-mlogloss:0.88938	validation-mlogloss:0.92819
[600]	train-mlogloss:0.88929	validation-mlogloss:0.92820
[601]	train-mlogloss:0.88915	validation-mlogloss:0.92814
[602]	train-mlogloss:0.88900	validation-mlogloss:0.92803
[603]	train-mlogloss:0.88893	validation-mlogloss:0.92797
[604]	train-mlogloss:0.88879	validation-mlogloss:0.92782
[605]	train-mlogloss:0.88871	validation-mlogloss:0.92776
[606]	train-mlogloss:0.88860	validation-mlogloss:0.92759
[607]	train-mlogloss:0.88853	validation-mlogloss:0.92749
[608]	train-mlogloss:0.88840	validation-mlogloss:0.92733
[609]	train-mlogloss:0.88826	validation-mlogloss:0.92715
[610]	train-mlogloss:0.88816	validation-mlogloss:0.92710
[611]	train-mlogloss:0.88808	validation-mlogloss:0.92701
[612]	train-mlogloss:0.88802	validation-mlogloss:0.92703
[613]	train-mlogloss:0.88791	validation-mlogloss:0.92694
[614]	train-mlogloss:0.88781	validation-mlogloss:0.92688
[615]	train-mlogloss:0.88771	validation-mlogloss:0.92677
[616]	train-mlogloss:0.88759	validation-mlogloss:0.92669
[617]	train-mlogloss:0.88752	validation-mlogloss:0.92664
[618]	train-mlogloss:0.88742	validation-mlogloss:0.92666
[619]	train-mlogloss:0.88736	validation-mlogloss:0.92666
[620]	train-mlogloss:0.88731	validation-mlogloss:0.92659
[621]	train-mlogloss:0.88724	validation-mlogloss:0.92651
[622]	train-mlogloss:0.88718	validation-mlogloss:0.92649
[623]	train-mlogloss:0.88714	validation-mlogloss:0.92645
[624]	train-mlogloss:0.88703	validation-mlogloss:0.92630
[625]	train-mlogloss:0.88698	validation-mlogloss:0.92624
[626]	train-mlogloss:0.88686	validation-mlogloss:0.92621
[627]	train-mlogloss:0.88679	validation-mlogloss:0.92613
[628]	train-mlogloss:0.88673	validation-mlogloss:0.92610
[629]	train-mlogloss:0.88663	validation-mlogloss:0.92595
[630]	train-mlogloss:0.88656	validation-mlogloss:0.92589
[631]	train-mlogloss:0.88651	validation-mlogloss:0.92580
[632]	train-mlogloss:0.88644	validation-mlogloss:0.92575
[633]	train-mlogloss:0.88632	validation-mlogloss:0.92567
[634]	train-mlogloss:0.88620	validation-mlogloss:0.92560
[635]	train-mlogloss:0.88615	validation-mlogloss:0.92556
[636]	train-mlogloss:0.88610	validation-mlogloss:0.92554
[637]	train-mlogloss:0.88598	validation-mlogloss:0.92547
[638]	train-mlogloss:0.88586	validation-mlogloss:0.92539
[639]	train-mlogloss:0.88577	validation-mlogloss:0.92528
[640]	train-mlogloss:0.88564	validation-mlogloss:0.92524
[641]	train-mlogloss:0.88556	validation-mlogloss:0.92514
[642]	train-mlogloss:0.88551	validation-mlogloss:0.92512
[643]	train-mlogloss:0.88540	validation-mlogloss:0.92505
[644]	train-mlogloss:0.88529	validation-mlogloss:0.92496
[645]	train-mlogloss:0.88518	validation-mlogloss:0.92491
[646]	train-mlogloss:0.88511	validation-mlogloss:0.92486
[647]	train-mlogloss:0.88505	validation-mlogloss:0.92486
[648]	train-mlogloss:0.88493	validation-mlogloss:0.92480
[649]	train-mlogloss:0.88481	validation-mlogloss:0.92475
[650]	train-mlogloss:0.88474	validation-mlogloss:0.92470
[651]	train-mlogloss:0.88469	validation-mlogloss:0.92470
[652]	train-mlogloss:0.88456	validation-mlogloss:0.92450
[653]	train-mlogloss:0.88449	validation-mlogloss:0.92442
[654]	train-mlogloss:0.88444	validation-mlogloss:0.92437
[655]	train-mlogloss:0.88435	validation-mlogloss:0.92431
[656]	train-mlogloss:0.88424	validation-mlogloss:0.92428
[657]	train-mlogloss:0.88415	validation-mlogloss:0.92426
[658]	train-mlogloss:0.88400	validation-mlogloss:0.92412
[659]	train-mlogloss:0.88392	validation-mlogloss:0.92404
[660]	train-mlogloss:0.88385	validation-mlogloss:0.92398
[661]	train-mlogloss:0.88380	validation-mlogloss:0.92396
[662]	train-mlogloss:0.88370	validation-mlogloss:0.92388
[663]	train-mlogloss:0.88365	validation-mlogloss:0.92386
[664]	train-mlogloss:0.88356	validation-mlogloss:0.92383
[665]	train-mlogloss:0.88350	validation-mlogloss:0.92380
[666]	train-mlogloss:0.88344	validation-mlogloss:0.92376
[667]	train-mlogloss:0.88339	validation-mlogloss:0.92374
[668]	train-mlogloss:0.88333	validation-mlogloss:0.92377
[669]	train-mlogloss:0.88330	validation-mlogloss:0.92374
[670]	train-mlogloss:0.88323	validation-mlogloss:0.92372
[671]	train-mlogloss:0.88314	validation-mlogloss:0.92369
[672]	train-mlogloss:0.88305	validation-mlogloss:0.92379
[673]	train-mlogloss:0.88293	validation-mlogloss:0.92365
[674]	train-mlogloss:0.88287	validation-mlogloss:0.92357
[675]	train-mlogloss:0.88278	validation-mlogloss:0.92358
[676]	train-mlogloss:0.88274	validation-mlogloss:0.92352
[677]	train-mlogloss:0.88263	validation-mlogloss:0.92342
[678]	train-mlogloss:0.88256	validation-mlogloss:0.92338
[679]	train-mlogloss:0.88244	validation-mlogloss:0.92329
[680]	train-mlogloss:0.88238	validation-mlogloss:0.92324
[681]	train-mlogloss:0.88233	validation-mlogloss:0.92322
[682]	train-mlogloss:0.88231	validation-mlogloss:0.92321
[683]	train-mlogloss:0.88223	validation-mlogloss:0.92314
[684]	train-mlogloss:0.88216	validation-mlogloss:0.92309
[685]	train-mlogloss:0.88208	validation-mlogloss:0.92304
[686]	train-mlogloss:0.88199	validation-mlogloss:0.92303
[687]	train-mlogloss:0.88194	validation-mlogloss:0.92307
[688]	train-mlogloss:0.88186	validation-mlogloss:0.92303
[689]	train-mlogloss:0.88182	validation-mlogloss:0.92301
[690]	train-mlogloss:0.88172	validation-mlogloss:0.92299
[691]	train-mlogloss:0.88167	validation-mlogloss:0.92298
[692]	train-mlogloss:0.88156	validation-mlogloss:0.92289
[693]	train-mlogloss:0.88151	validation-mlogloss:0.92286
[694]	train-mlogloss:0.88146	validation-mlogloss:0.92279
[695]	train-mlogloss:0.88142	validation-mlogloss:0.92279
[696]	train-mlogloss:0.88136	validation-mlogloss:0.92277
[697]	train-mlogloss:0.88132	validation-mlogloss:0.92274
[698]	train-mlogloss:0.88126	validation-mlogloss:0.92269
[699]	train-mlogloss:0.88116	validation-mlogloss:0.92262
[700]	train-mlogloss:0.88103	validation-mlogloss:0.92248
[701]	train-mlogloss:0.88098	validation-mlogloss:0.92246
[702]	train-mlogloss:0.88091	validation-mlogloss:0.92245
[703]	train-mlogloss:0.88087	validation-mlogloss:0.92245
[704]	train-mlogloss:0.88080	validation-mlogloss:0.92242
[705]	train-mlogloss:0.88076	validation-mlogloss:0.92241
[706]	train-mlogloss:0.88074	validation-mlogloss:0.92241
[707]	train-mlogloss:0.88067	validation-mlogloss:0.92236
[708]	train-mlogloss:0.88063	validation-mlogloss:0.92234
[709]	train-mlogloss:0.88059	validation-mlogloss:0.92229
[710]	train-mlogloss:0.88049	validation-mlogloss:0.92221
[711]	train-mlogloss:0.88037	validation-mlogloss:0.92207
[712]	train-mlogloss:0.88031	validation-mlogloss:0.92200
[713]	train-mlogloss:0.88025	validation-mlogloss:0.92195
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 1 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.89 [%]
Global accuracy score (test) = 62.72 [%]
Global F1 score (train) = 64.01 [%]
Global F1 score (test) = 63.13 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.48      0.45      0.46       400
MODERATE-INTENSITY       0.56      0.69      0.62       400
         SEDENTARY       0.70      0.75      0.72       400
VIGOROUS-INTENSITY       0.87      0.61      0.72       345

          accuracy                           0.63      1545
         macro avg       0.65      0.63      0.63      1545
      weighted avg       0.64      0.63      0.63      1545


Accuracy capturado en la ejecución 6: 62.72 [%]
F1-score capturado en la ejecución 6: 63.13 [%]

=== EJECUCIÓN 7 ===

--- TRAIN (ejecución 7) ---

--- TEST (ejecución 7) ---
2025-11-04 11:00:28.074101: 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`.
2025-11-04 11:00:28.085405: 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 00:00:1762250428.098838 1079079 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250428.103160 1079079 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250428.113106 1079079 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250428.113124 1079079 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250428.113125 1079079 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250428.113127 1079079 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:00:28.116273: 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:1.38109	validation-mlogloss:1.38116
[1]	train-mlogloss:1.37567	validation-mlogloss:1.37573
[2]	train-mlogloss:1.37072	validation-mlogloss:1.37083
[3]	train-mlogloss:1.36577	validation-mlogloss:1.36584
[4]	train-mlogloss:1.36077	validation-mlogloss:1.36083
[5]	train-mlogloss:1.35597	validation-mlogloss:1.35605
[6]	train-mlogloss:1.35121	validation-mlogloss:1.35103
[7]	train-mlogloss:1.34660	validation-mlogloss:1.34636
[8]	train-mlogloss:1.34208	validation-mlogloss:1.34156
[9]	train-mlogloss:1.33762	validation-mlogloss:1.33708
[10]	train-mlogloss:1.33323	validation-mlogloss:1.33282
[11]	train-mlogloss:1.32881	validation-mlogloss:1.32814
[12]	train-mlogloss:1.32461	validation-mlogloss:1.32377
[13]	train-mlogloss:1.32051	validation-mlogloss:1.31964
[14]	train-mlogloss:1.31618	validation-mlogloss:1.31533
[15]	train-mlogloss:1.31218	validation-mlogloss:1.31111
[16]	train-mlogloss:1.30774	validation-mlogloss:1.30647
[17]	train-mlogloss:1.30379	validation-mlogloss:1.30276
[18]	train-mlogloss:1.29986	validation-mlogloss:1.29878
[19]	train-mlogloss:1.29610	validation-mlogloss:1.29505
[20]	train-mlogloss:1.29237	validation-mlogloss:1.29128
[21]	train-mlogloss:1.28874	validation-mlogloss:1.28752
[22]	train-mlogloss:1.28497	validation-mlogloss:1.28382
[23]	train-mlogloss:1.28129	validation-mlogloss:1.27992
[24]	train-mlogloss:1.27773	validation-mlogloss:1.27633
[25]	train-mlogloss:1.27427	validation-mlogloss:1.27285
[26]	train-mlogloss:1.27088	validation-mlogloss:1.26918
[27]	train-mlogloss:1.26755	validation-mlogloss:1.26588
[28]	train-mlogloss:1.26422	validation-mlogloss:1.26268
[29]	train-mlogloss:1.26111	validation-mlogloss:1.25975
[30]	train-mlogloss:1.25789	validation-mlogloss:1.25652
[31]	train-mlogloss:1.25469	validation-mlogloss:1.25326
[32]	train-mlogloss:1.25149	validation-mlogloss:1.24993
[33]	train-mlogloss:1.24821	validation-mlogloss:1.24649
[34]	train-mlogloss:1.24512	validation-mlogloss:1.24336
[35]	train-mlogloss:1.24215	validation-mlogloss:1.24031
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[630]	train-mlogloss:0.88270	validation-mlogloss:0.93465
[631]	train-mlogloss:0.88265	validation-mlogloss:0.93460
[632]	train-mlogloss:0.88259	validation-mlogloss:0.93457
[633]	train-mlogloss:0.88254	validation-mlogloss:0.93453
[634]	train-mlogloss:0.88241	validation-mlogloss:0.93446
[635]	train-mlogloss:0.88234	validation-mlogloss:0.93440
[636]	train-mlogloss:0.88223	validation-mlogloss:0.93426
[637]	train-mlogloss:0.88217	validation-mlogloss:0.93423
[638]	train-mlogloss:0.88205	validation-mlogloss:0.93419
[639]	train-mlogloss:0.88200	validation-mlogloss:0.93411
[640]	train-mlogloss:0.88184	validation-mlogloss:0.93402
[641]	train-mlogloss:0.88172	validation-mlogloss:0.93396
[642]	train-mlogloss:0.88160	validation-mlogloss:0.93390
[643]	train-mlogloss:0.88149	validation-mlogloss:0.93398
[644]	train-mlogloss:0.88140	validation-mlogloss:0.93392
[645]	train-mlogloss:0.88133	validation-mlogloss:0.93387
[646]	train-mlogloss:0.88129	validation-mlogloss:0.93385
[647]	train-mlogloss:0.88124	validation-mlogloss:0.93380
[648]	train-mlogloss:0.88110	validation-mlogloss:0.93371
[649]	train-mlogloss:0.88100	validation-mlogloss:0.93370
[650]	train-mlogloss:0.88089	validation-mlogloss:0.93360
[651]	train-mlogloss:0.88082	validation-mlogloss:0.93358
[652]	train-mlogloss:0.88074	validation-mlogloss:0.93353
[653]	train-mlogloss:0.88063	validation-mlogloss:0.93346
[654]	train-mlogloss:0.88058	validation-mlogloss:0.93343
[655]	train-mlogloss:0.88047	validation-mlogloss:0.93341
[656]	train-mlogloss:0.88035	validation-mlogloss:0.93338
[657]	train-mlogloss:0.88024	validation-mlogloss:0.93334
[658]	train-mlogloss:0.88014	validation-mlogloss:0.93324
[659]	train-mlogloss:0.88005	validation-mlogloss:0.93314
[660]	train-mlogloss:0.87996	validation-mlogloss:0.93305
[661]	train-mlogloss:0.87983	validation-mlogloss:0.93286
[662]	train-mlogloss:0.87979	validation-mlogloss:0.93279
[663]	train-mlogloss:0.87972	validation-mlogloss:0.93271
[664]	train-mlogloss:0.87968	validation-mlogloss:0.93269
[665]	train-mlogloss:0.87955	validation-mlogloss:0.93272
[666]	train-mlogloss:0.87945	validation-mlogloss:0.93273
[667]	train-mlogloss:0.87938	validation-mlogloss:0.93275
[668]	train-mlogloss:0.87926	validation-mlogloss:0.93266
[669]	train-mlogloss:0.87908	validation-mlogloss:0.93255
[670]	train-mlogloss:0.87900	validation-mlogloss:0.93252
[671]	train-mlogloss:0.87889	validation-mlogloss:0.93239
[672]	train-mlogloss:0.87884	validation-mlogloss:0.93237
[673]	train-mlogloss:0.87876	validation-mlogloss:0.93229
[674]	train-mlogloss:0.87870	validation-mlogloss:0.93224
[675]	train-mlogloss:0.87865	validation-mlogloss:0.93222
[676]	train-mlogloss:0.87858	validation-mlogloss:0.93214
[677]	train-mlogloss:0.87846	validation-mlogloss:0.93212
[678]	train-mlogloss:0.87842	validation-mlogloss:0.93208
[679]	train-mlogloss:0.87836	validation-mlogloss:0.93201
[680]	train-mlogloss:0.87831	validation-mlogloss:0.93197
[681]	train-mlogloss:0.87824	validation-mlogloss:0.93192
[682]	train-mlogloss:0.87818	validation-mlogloss:0.93183
[683]	train-mlogloss:0.87808	validation-mlogloss:0.93177
[684]	train-mlogloss:0.87797	validation-mlogloss:0.93173
[685]	train-mlogloss:0.87795	validation-mlogloss:0.93172
[686]	train-mlogloss:0.87784	validation-mlogloss:0.93165
[687]	train-mlogloss:0.87779	validation-mlogloss:0.93159
[688]	train-mlogloss:0.87773	validation-mlogloss:0.93153
[689]	train-mlogloss:0.87768	validation-mlogloss:0.93152
[690]	train-mlogloss:0.87764	validation-mlogloss:0.93153
[691]	train-mlogloss:0.87752	validation-mlogloss:0.93144
[692]	train-mlogloss:0.87743	validation-mlogloss:0.93135
[693]	train-mlogloss:0.87739	validation-mlogloss:0.93130
[694]	train-mlogloss:0.87735	validation-mlogloss:0.93129
[695]	train-mlogloss:0.87725	validation-mlogloss:0.93126
[696]	train-mlogloss:0.87720	validation-mlogloss:0.93120
[697]	train-mlogloss:0.87714	validation-mlogloss:0.93119
[698]	train-mlogloss:0.87711	validation-mlogloss:0.93114
[699]	train-mlogloss:0.87699	validation-mlogloss:0.93097
[700]	train-mlogloss:0.87692	validation-mlogloss:0.93089
[701]	train-mlogloss:0.87688	validation-mlogloss:0.93087
[702]	train-mlogloss:0.87683	validation-mlogloss:0.93085
[703]	train-mlogloss:0.87678	validation-mlogloss:0.93082
[704]	train-mlogloss:0.87674	validation-mlogloss:0.93082
[705]	train-mlogloss:0.87667	validation-mlogloss:0.93077
[706]	train-mlogloss:0.87660	validation-mlogloss:0.93072
[707]	train-mlogloss:0.87652	validation-mlogloss:0.93077
[708]	train-mlogloss:0.87646	validation-mlogloss:0.93070
[709]	train-mlogloss:0.87640	validation-mlogloss:0.93066
[710]	train-mlogloss:0.87629	validation-mlogloss:0.93059
[711]	train-mlogloss:0.87625	validation-mlogloss:0.93057
[712]	train-mlogloss:0.87620	validation-mlogloss:0.93056
[713]	train-mlogloss:0.87608	validation-mlogloss:0.93045
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[0 2 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.64 [%]
Global accuracy score (test) = 60.26 [%]
Global F1 score (train) = 63.78 [%]
Global F1 score (test) = 61.0 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.44      0.47      0.45       400
MODERATE-INTENSITY       0.54      0.59      0.56       400
         SEDENTARY       0.68      0.74      0.71       400
VIGOROUS-INTENSITY       0.84      0.61      0.71       345

          accuracy                           0.60      1545
         macro avg       0.63      0.60      0.61      1545
      weighted avg       0.62      0.60      0.61      1545


Accuracy capturado en la ejecución 7: 60.26 [%]
F1-score capturado en la ejecución 7: 61.0 [%]

=== EJECUCIÓN 8 ===

--- TRAIN (ejecución 8) ---

--- TEST (ejecución 8) ---
2025-11-04 11:00:45.274387: 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`.
2025-11-04 11:00:45.285975: 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 00:00:1762250445.299235 1079389 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250445.303377 1079389 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250445.313401 1079389 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250445.313420 1079389 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250445.313422 1079389 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250445.313423 1079389 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:00:45.316736: 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:1.38125	validation-mlogloss:1.38107
[1]	train-mlogloss:1.37610	validation-mlogloss:1.37585
[2]	train-mlogloss:1.37122	validation-mlogloss:1.37110
[3]	train-mlogloss:1.36619	validation-mlogloss:1.36587
[4]	train-mlogloss:1.36137	validation-mlogloss:1.36095
[5]	train-mlogloss:1.35651	validation-mlogloss:1.35607
[6]	train-mlogloss:1.35206	validation-mlogloss:1.35122
[7]	train-mlogloss:1.34767	validation-mlogloss:1.34676
[8]	train-mlogloss:1.34298	validation-mlogloss:1.34206
[9]	train-mlogloss:1.33863	validation-mlogloss:1.33763
[10]	train-mlogloss:1.33411	validation-mlogloss:1.33304
[11]	train-mlogloss:1.32934	validation-mlogloss:1.32795
[12]	train-mlogloss:1.32491	validation-mlogloss:1.32350
[13]	train-mlogloss:1.32075	validation-mlogloss:1.31918
[14]	train-mlogloss:1.31661	validation-mlogloss:1.31488
[15]	train-mlogloss:1.31250	validation-mlogloss:1.31083
[16]	train-mlogloss:1.30848	validation-mlogloss:1.30661
[17]	train-mlogloss:1.30460	validation-mlogloss:1.30231
[18]	train-mlogloss:1.30052	validation-mlogloss:1.29819
[19]	train-mlogloss:1.29648	validation-mlogloss:1.29410
[20]	train-mlogloss:1.29276	validation-mlogloss:1.29024
[21]	train-mlogloss:1.28911	validation-mlogloss:1.28644
[22]	train-mlogloss:1.28507	validation-mlogloss:1.28210
[23]	train-mlogloss:1.28145	validation-mlogloss:1.27854
[24]	train-mlogloss:1.27799	validation-mlogloss:1.27483
[25]	train-mlogloss:1.27439	validation-mlogloss:1.27129
[26]	train-mlogloss:1.27104	validation-mlogloss:1.26806
[27]	train-mlogloss:1.26768	validation-mlogloss:1.26477
[28]	train-mlogloss:1.26429	validation-mlogloss:1.26133
[29]	train-mlogloss:1.26104	validation-mlogloss:1.25802
[30]	train-mlogloss:1.25770	validation-mlogloss:1.25463
[31]	train-mlogloss:1.25441	validation-mlogloss:1.25124
[32]	train-mlogloss:1.25125	validation-mlogloss:1.24794
[33]	train-mlogloss:1.24813	validation-mlogloss:1.24477
[34]	train-mlogloss:1.24506	validation-mlogloss:1.24168
[35]	train-mlogloss:1.24210	validation-mlogloss:1.23850
[36]	train-mlogloss:1.23909	validation-mlogloss:1.23525
[37]	train-mlogloss:1.23606	validation-mlogloss:1.23206
[38]	train-mlogloss:1.23315	validation-mlogloss:1.22917
[39]	train-mlogloss:1.23027	validation-mlogloss:1.22629
[40]	train-mlogloss:1.22743	validation-mlogloss:1.22363
[41]	train-mlogloss:1.22469	validation-mlogloss:1.22102
[42]	train-mlogloss:1.22164	validation-mlogloss:1.21789
[43]	train-mlogloss:1.21887	validation-mlogloss:1.21519
[44]	train-mlogloss:1.21625	validation-mlogloss:1.21268
[45]	train-mlogloss:1.21362	validation-mlogloss:1.20980
[46]	train-mlogloss:1.21115	validation-mlogloss:1.20751
[47]	train-mlogloss:1.20864	validation-mlogloss:1.20488
[48]	train-mlogloss:1.20570	validation-mlogloss:1.20181
[49]	train-mlogloss:1.20285	validation-mlogloss:1.19873
[50]	train-mlogloss:1.20047	validation-mlogloss:1.19634
[51]	train-mlogloss:1.19813	validation-mlogloss:1.19382
[52]	train-mlogloss:1.19536	validation-mlogloss:1.19072
[53]	train-mlogloss:1.19301	validation-mlogloss:1.18808
[54]	train-mlogloss:1.19059	validation-mlogloss:1.18550
[55]	train-mlogloss:1.18828	validation-mlogloss:1.18297
[56]	train-mlogloss:1.18562	validation-mlogloss:1.18029
[57]	train-mlogloss:1.18330	validation-mlogloss:1.17804
[58]	train-mlogloss:1.18090	validation-mlogloss:1.17531
[59]	train-mlogloss:1.17857	validation-mlogloss:1.17279
[60]	train-mlogloss:1.17643	validation-mlogloss:1.17052
[61]	train-mlogloss:1.17425	validation-mlogloss:1.16855
[62]	train-mlogloss:1.17214	validation-mlogloss:1.16650
[63]	train-mlogloss:1.16969	validation-mlogloss:1.16380
[64]	train-mlogloss:1.16753	validation-mlogloss:1.16169
[65]	train-mlogloss:1.16549	validation-mlogloss:1.15982
[66]	train-mlogloss:1.16339	validation-mlogloss:1.15778
[67]	train-mlogloss:1.16120	validation-mlogloss:1.15549
[68]	train-mlogloss:1.15888	validation-mlogloss:1.15318
[69]	train-mlogloss:1.15674	validation-mlogloss:1.15094
[70]	train-mlogloss:1.15476	validation-mlogloss:1.14898
[71]	train-mlogloss:1.15285	validation-mlogloss:1.14726
[72]	train-mlogloss:1.15087	validation-mlogloss:1.14527
[73]	train-mlogloss:1.14907	validation-mlogloss:1.14334
[74]	train-mlogloss:1.14687	validation-mlogloss:1.14095
[75]	train-mlogloss:1.14490	validation-mlogloss:1.13908
[76]	train-mlogloss:1.14296	validation-mlogloss:1.13707
[77]	train-mlogloss:1.14122	validation-mlogloss:1.13550
[78]	train-mlogloss:1.13939	validation-mlogloss:1.13355
[79]	train-mlogloss:1.13752	validation-mlogloss:1.13165
[80]	train-mlogloss:1.13572	validation-mlogloss:1.12984
[81]	train-mlogloss:1.13373	validation-mlogloss:1.12800
[82]	train-mlogloss:1.13196	validation-mlogloss:1.12607
[83]	train-mlogloss:1.13023	validation-mlogloss:1.12440
[84]	train-mlogloss:1.12849	validation-mlogloss:1.12246
[85]	train-mlogloss:1.12676	validation-mlogloss:1.12066
[86]	train-mlogloss:1.12518	validation-mlogloss:1.11924
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[678]	train-mlogloss:0.88248	validation-mlogloss:0.92087
[679]	train-mlogloss:0.88234	validation-mlogloss:0.92088
[680]	train-mlogloss:0.88229	validation-mlogloss:0.92078
[681]	train-mlogloss:0.88220	validation-mlogloss:0.92080
[682]	train-mlogloss:0.88214	validation-mlogloss:0.92075
[683]	train-mlogloss:0.88208	validation-mlogloss:0.92070
[684]	train-mlogloss:0.88206	validation-mlogloss:0.92069
[685]	train-mlogloss:0.88199	validation-mlogloss:0.92063
[686]	train-mlogloss:0.88188	validation-mlogloss:0.92058
[687]	train-mlogloss:0.88180	validation-mlogloss:0.92056
[688]	train-mlogloss:0.88173	validation-mlogloss:0.92056
[689]	train-mlogloss:0.88165	validation-mlogloss:0.92057
[690]	train-mlogloss:0.88157	validation-mlogloss:0.92050
[691]	train-mlogloss:0.88152	validation-mlogloss:0.92043
[692]	train-mlogloss:0.88148	validation-mlogloss:0.92042
[693]	train-mlogloss:0.88142	validation-mlogloss:0.92035
[694]	train-mlogloss:0.88136	validation-mlogloss:0.92033
[695]	train-mlogloss:0.88131	validation-mlogloss:0.92031
[696]	train-mlogloss:0.88126	validation-mlogloss:0.92030
[697]	train-mlogloss:0.88116	validation-mlogloss:0.92025
[698]	train-mlogloss:0.88109	validation-mlogloss:0.92024
[699]	train-mlogloss:0.88102	validation-mlogloss:0.92018
[700]	train-mlogloss:0.88096	validation-mlogloss:0.92011
[701]	train-mlogloss:0.88083	validation-mlogloss:0.91999
[702]	train-mlogloss:0.88074	validation-mlogloss:0.91992
[703]	train-mlogloss:0.88068	validation-mlogloss:0.91987
[704]	train-mlogloss:0.88063	validation-mlogloss:0.91983
[705]	train-mlogloss:0.88061	validation-mlogloss:0.91982
[706]	train-mlogloss:0.88051	validation-mlogloss:0.91974
[707]	train-mlogloss:0.88045	validation-mlogloss:0.91970
[708]	train-mlogloss:0.88036	validation-mlogloss:0.91956
[709]	train-mlogloss:0.88033	validation-mlogloss:0.91955
[710]	train-mlogloss:0.88030	validation-mlogloss:0.91954
[711]	train-mlogloss:0.88017	validation-mlogloss:0.91952
[712]	train-mlogloss:0.88009	validation-mlogloss:0.91944
[713]	train-mlogloss:0.88001	validation-mlogloss:0.91938
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 1 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.87 [%]
Global accuracy score (test) = 60.84 [%]
Global F1 score (train) = 64.01 [%]
Global F1 score (test) = 61.48 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.44      0.46      0.45       400
MODERATE-INTENSITY       0.56      0.64      0.60       400
         SEDENTARY       0.68      0.73      0.71       400
VIGOROUS-INTENSITY       0.85      0.60      0.71       345

          accuracy                           0.61      1545
         macro avg       0.63      0.61      0.61      1545
      weighted avg       0.63      0.61      0.61      1545


Accuracy capturado en la ejecución 8: 60.84 [%]
F1-score capturado en la ejecución 8: 61.48 [%]

=== EJECUCIÓN 9 ===

--- TRAIN (ejecución 9) ---

--- TEST (ejecución 9) ---
2025-11-04 11:01:02.315461: 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`.
2025-11-04 11:01:02.326661: 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 00:00:1762250462.340452 1079723 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250462.344716 1079723 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250462.354747 1079723 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250462.354765 1079723 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250462.354766 1079723 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250462.354768 1079723 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:01:02.357887: 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:1.38112	validation-mlogloss:1.38115
[1]	train-mlogloss:1.37589	validation-mlogloss:1.37584
[2]	train-mlogloss:1.37112	validation-mlogloss:1.37095
[3]	train-mlogloss:1.36627	validation-mlogloss:1.36602
[4]	train-mlogloss:1.36136	validation-mlogloss:1.36099
[5]	train-mlogloss:1.35660	validation-mlogloss:1.35594
[6]	train-mlogloss:1.35192	validation-mlogloss:1.35082
[7]	train-mlogloss:1.34723	validation-mlogloss:1.34591
[8]	train-mlogloss:1.34282	validation-mlogloss:1.34142
[9]	train-mlogloss:1.33838	validation-mlogloss:1.33687
[10]	train-mlogloss:1.33389	validation-mlogloss:1.33235
[11]	train-mlogloss:1.32950	validation-mlogloss:1.32767
[12]	train-mlogloss:1.32520	validation-mlogloss:1.32307
[13]	train-mlogloss:1.32097	validation-mlogloss:1.31878
[14]	train-mlogloss:1.31682	validation-mlogloss:1.31431
[15]	train-mlogloss:1.31277	validation-mlogloss:1.31002
[16]	train-mlogloss:1.30884	validation-mlogloss:1.30611
[17]	train-mlogloss:1.30483	validation-mlogloss:1.30194
[18]	train-mlogloss:1.30104	validation-mlogloss:1.29817
[19]	train-mlogloss:1.29722	validation-mlogloss:1.29408
[20]	train-mlogloss:1.29353	validation-mlogloss:1.29046
[21]	train-mlogloss:1.28981	validation-mlogloss:1.28630
[22]	train-mlogloss:1.28613	validation-mlogloss:1.28252
[23]	train-mlogloss:1.28246	validation-mlogloss:1.27872
[24]	train-mlogloss:1.27895	validation-mlogloss:1.27518
[25]	train-mlogloss:1.27527	validation-mlogloss:1.27145
[26]	train-mlogloss:1.27190	validation-mlogloss:1.26802
[27]	train-mlogloss:1.26834	validation-mlogloss:1.26404
[28]	train-mlogloss:1.26491	validation-mlogloss:1.26039
[29]	train-mlogloss:1.26122	validation-mlogloss:1.25626
[30]	train-mlogloss:1.25802	validation-mlogloss:1.25315
[31]	train-mlogloss:1.25475	validation-mlogloss:1.24978
[32]	train-mlogloss:1.25160	validation-mlogloss:1.24641
[33]	train-mlogloss:1.24855	validation-mlogloss:1.24348
[34]	train-mlogloss:1.24542	validation-mlogloss:1.24019
[35]	train-mlogloss:1.24246	validation-mlogloss:1.23704
[36]	train-mlogloss:1.23912	validation-mlogloss:1.23331
[37]	train-mlogloss:1.23622	validation-mlogloss:1.23028
[38]	train-mlogloss:1.23323	validation-mlogloss:1.22693
[39]	train-mlogloss:1.23040	validation-mlogloss:1.22415
[40]	train-mlogloss:1.22746	validation-mlogloss:1.22124
[41]	train-mlogloss:1.22468	validation-mlogloss:1.21824
[42]	train-mlogloss:1.22198	validation-mlogloss:1.21534
[43]	train-mlogloss:1.21900	validation-mlogloss:1.21221
[44]	train-mlogloss:1.21634	validation-mlogloss:1.20947
[45]	train-mlogloss:1.21372	validation-mlogloss:1.20700
[46]	train-mlogloss:1.21117	validation-mlogloss:1.20446
[47]	train-mlogloss:1.20854	validation-mlogloss:1.20184
[48]	train-mlogloss:1.20610	validation-mlogloss:1.19926
[49]	train-mlogloss:1.20348	validation-mlogloss:1.19659
[50]	train-mlogloss:1.20104	validation-mlogloss:1.19422
[51]	train-mlogloss:1.19853	validation-mlogloss:1.19172
[52]	train-mlogloss:1.19615	validation-mlogloss:1.18926
[53]	train-mlogloss:1.19385	validation-mlogloss:1.18704
[54]	train-mlogloss:1.19133	validation-mlogloss:1.18448
[55]	train-mlogloss:1.18898	validation-mlogloss:1.18198
[56]	train-mlogloss:1.18632	validation-mlogloss:1.17927
[57]	train-mlogloss:1.18399	validation-mlogloss:1.17702
[58]	train-mlogloss:1.18178	validation-mlogloss:1.17474
[59]	train-mlogloss:1.17963	validation-mlogloss:1.17250
[60]	train-mlogloss:1.17750	validation-mlogloss:1.17051
[61]	train-mlogloss:1.17531	validation-mlogloss:1.16846
[62]	train-mlogloss:1.17279	validation-mlogloss:1.16614
[63]	train-mlogloss:1.17053	validation-mlogloss:1.16379
[64]	train-mlogloss:1.16832	validation-mlogloss:1.16151
[65]	train-mlogloss:1.16622	validation-mlogloss:1.15959
[66]	train-mlogloss:1.16411	validation-mlogloss:1.15738
[67]	train-mlogloss:1.16214	validation-mlogloss:1.15541
[68]	train-mlogloss:1.16004	validation-mlogloss:1.15345
[69]	train-mlogloss:1.15813	validation-mlogloss:1.15150
[70]	train-mlogloss:1.15584	validation-mlogloss:1.14950
[71]	train-mlogloss:1.15393	validation-mlogloss:1.14767
[72]	train-mlogloss:1.15177	validation-mlogloss:1.14544
[73]	train-mlogloss:1.14976	validation-mlogloss:1.14331
[74]	train-mlogloss:1.14783	validation-mlogloss:1.14113
[75]	train-mlogloss:1.14582	validation-mlogloss:1.13906
[76]	train-mlogloss:1.14399	validation-mlogloss:1.13719
[77]	train-mlogloss:1.14221	validation-mlogloss:1.13535
[78]	train-mlogloss:1.14008	validation-mlogloss:1.13347
[79]	train-mlogloss:1.13832	validation-mlogloss:1.13176
[80]	train-mlogloss:1.13654	validation-mlogloss:1.13001
[81]	train-mlogloss:1.13467	validation-mlogloss:1.12808
[82]	train-mlogloss:1.13286	validation-mlogloss:1.12617
[83]	train-mlogloss:1.13082	validation-mlogloss:1.12399
[84]	train-mlogloss:1.12901	validation-mlogloss:1.12207
[85]	train-mlogloss:1.12722	validation-mlogloss:1.12034
[86]	train-mlogloss:1.12544	validation-mlogloss:1.11825
[87]	train-mlogloss:1.12380	validation-mlogloss:1.11657
[88]	train-mlogloss:1.12220	validation-mlogloss:1.11491
[89]	train-mlogloss:1.12045	validation-mlogloss:1.11335
[90]	train-mlogloss:1.11870	validation-mlogloss:1.11163
[91]	train-mlogloss:1.11707	validation-mlogloss:1.10990
[92]	train-mlogloss:1.11558	validation-mlogloss:1.10858
[93]	train-mlogloss:1.11375	validation-mlogloss:1.10688
[94]	train-mlogloss:1.11227	validation-mlogloss:1.10550
[95]	train-mlogloss:1.11046	validation-mlogloss:1.10389
[96]	train-mlogloss:1.10889	validation-mlogloss:1.10213
[97]	train-mlogloss:1.10731	validation-mlogloss:1.10066
[98]	train-mlogloss:1.10585	validation-mlogloss:1.09934
[99]	train-mlogloss:1.10418	validation-mlogloss:1.09786
[100]	train-mlogloss:1.10266	validation-mlogloss:1.09650
[101]	train-mlogloss:1.10106	validation-mlogloss:1.09485
[102]	train-mlogloss:1.09953	validation-mlogloss:1.09337
[103]	train-mlogloss:1.09812	validation-mlogloss:1.09194
[104]	train-mlogloss:1.09667	validation-mlogloss:1.09054
[105]	train-mlogloss:1.09521	validation-mlogloss:1.08902
[106]	train-mlogloss:1.09359	validation-mlogloss:1.08769
[107]	train-mlogloss:1.09221	validation-mlogloss:1.08644
[108]	train-mlogloss:1.09101	validation-mlogloss:1.08520
[109]	train-mlogloss:1.08942	validation-mlogloss:1.08382
[110]	train-mlogloss:1.08785	validation-mlogloss:1.08234
[111]	train-mlogloss:1.08644	validation-mlogloss:1.08088
[112]	train-mlogloss:1.08492	validation-mlogloss:1.07943
[113]	train-mlogloss:1.08354	validation-mlogloss:1.07803
[114]	train-mlogloss:1.08230	validation-mlogloss:1.07691
[115]	train-mlogloss:1.08096	validation-mlogloss:1.07564
[116]	train-mlogloss:1.07955	validation-mlogloss:1.07445
[117]	train-mlogloss:1.07836	validation-mlogloss:1.07336
[118]	train-mlogloss:1.07703	validation-mlogloss:1.07219
[119]	train-mlogloss:1.07591	validation-mlogloss:1.07115
[120]	train-mlogloss:1.07462	validation-mlogloss:1.06969
[121]	train-mlogloss:1.07336	validation-mlogloss:1.06846
[122]	train-mlogloss:1.07211	validation-mlogloss:1.06718
[123]	train-mlogloss:1.07094	validation-mlogloss:1.06624
[124]	train-mlogloss:1.06973	validation-mlogloss:1.06492
[125]	train-mlogloss:1.06860	validation-mlogloss:1.06389
[126]	train-mlogloss:1.06748	validation-mlogloss:1.06295
[127]	train-mlogloss:1.06636	validation-mlogloss:1.06201
[128]	train-mlogloss:1.06508	validation-mlogloss:1.06062
[129]	train-mlogloss:1.06395	validation-mlogloss:1.05952
[130]	train-mlogloss:1.06286	validation-mlogloss:1.05859
[131]	train-mlogloss:1.06181	validation-mlogloss:1.05764
[132]	train-mlogloss:1.06073	validation-mlogloss:1.05668
[133]	train-mlogloss:1.05938	validation-mlogloss:1.05559
[134]	train-mlogloss:1.05826	validation-mlogloss:1.05450
[135]	train-mlogloss:1.05718	validation-mlogloss:1.05342
[136]	train-mlogloss:1.05612	validation-mlogloss:1.05246
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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)
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.93 [%]
Global accuracy score (test) = 60.13 [%]
Global F1 score (train) = 64.08 [%]
Global F1 score (test) = 60.64 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.44      0.42      0.43       400
MODERATE-INTENSITY       0.54      0.63      0.58       400
         SEDENTARY       0.67      0.74      0.71       400
VIGOROUS-INTENSITY       0.84      0.61      0.71       345

          accuracy                           0.60      1545
         macro avg       0.62      0.60      0.61      1545
      weighted avg       0.62      0.60      0.60      1545


Accuracy capturado en la ejecución 9: 60.13 [%]
F1-score capturado en la ejecución 9: 60.64 [%]

=== EJECUCIÓN 10 ===

--- TRAIN (ejecución 10) ---

--- TEST (ejecución 10) ---
2025-11-04 11:01:19.319860: 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`.
2025-11-04 11:01:19.331215: 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 00:00:1762250479.344314 1080034 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250479.348371 1080034 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250479.358206 1080034 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250479.358222 1080034 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250479.358224 1080034 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250479.358225 1080034 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:01:19.361387: 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:1.38106	validation-mlogloss:1.38081
[1]	train-mlogloss:1.37582	validation-mlogloss:1.37550
[2]	train-mlogloss:1.37079	validation-mlogloss:1.37008
[3]	train-mlogloss:1.36575	validation-mlogloss:1.36458
[4]	train-mlogloss:1.36100	validation-mlogloss:1.35984
[5]	train-mlogloss:1.35590	validation-mlogloss:1.35421
[6]	train-mlogloss:1.35116	validation-mlogloss:1.34924
[7]	train-mlogloss:1.34659	validation-mlogloss:1.34431
[8]	train-mlogloss:1.34211	validation-mlogloss:1.33979
[9]	train-mlogloss:1.33762	validation-mlogloss:1.33517
[10]	train-mlogloss:1.33329	validation-mlogloss:1.33042
[11]	train-mlogloss:1.32915	validation-mlogloss:1.32625
[12]	train-mlogloss:1.32488	validation-mlogloss:1.32190
[13]	train-mlogloss:1.32060	validation-mlogloss:1.31733
[14]	train-mlogloss:1.31653	validation-mlogloss:1.31293
[15]	train-mlogloss:1.31245	validation-mlogloss:1.30866
[16]	train-mlogloss:1.30839	validation-mlogloss:1.30440
[17]	train-mlogloss:1.30444	validation-mlogloss:1.30057
[18]	train-mlogloss:1.30061	validation-mlogloss:1.29663
[19]	train-mlogloss:1.29683	validation-mlogloss:1.29284
[20]	train-mlogloss:1.29312	validation-mlogloss:1.28897
[21]	train-mlogloss:1.28953	validation-mlogloss:1.28525
[22]	train-mlogloss:1.28592	validation-mlogloss:1.28167
[23]	train-mlogloss:1.28237	validation-mlogloss:1.27799
[24]	train-mlogloss:1.27887	validation-mlogloss:1.27432
[25]	train-mlogloss:1.27544	validation-mlogloss:1.27091
[26]	train-mlogloss:1.27204	validation-mlogloss:1.26736
[27]	train-mlogloss:1.26867	validation-mlogloss:1.26396
[28]	train-mlogloss:1.26538	validation-mlogloss:1.26038
[29]	train-mlogloss:1.26210	validation-mlogloss:1.25709
[30]	train-mlogloss:1.25879	validation-mlogloss:1.25367
[31]	train-mlogloss:1.25557	validation-mlogloss:1.25010
[32]	train-mlogloss:1.25243	validation-mlogloss:1.24681
[33]	train-mlogloss:1.24929	validation-mlogloss:1.24369
[34]	train-mlogloss:1.24620	validation-mlogloss:1.24033
[35]	train-mlogloss:1.24318	validation-mlogloss:1.23715
[36]	train-mlogloss:1.24021	validation-mlogloss:1.23404
[37]	train-mlogloss:1.23722	validation-mlogloss:1.23095
[38]	train-mlogloss:1.23394	validation-mlogloss:1.22738
[39]	train-mlogloss:1.23118	validation-mlogloss:1.22479
[40]	train-mlogloss:1.22850	validation-mlogloss:1.22196
[41]	train-mlogloss:1.22580	validation-mlogloss:1.21901
[42]	train-mlogloss:1.22308	validation-mlogloss:1.21628
[43]	train-mlogloss:1.22040	validation-mlogloss:1.21336
[44]	train-mlogloss:1.21734	validation-mlogloss:1.21002
[45]	train-mlogloss:1.21480	validation-mlogloss:1.20750
[46]	train-mlogloss:1.21219	validation-mlogloss:1.20465
[47]	train-mlogloss:1.20961	validation-mlogloss:1.20178
[48]	train-mlogloss:1.20702	validation-mlogloss:1.19898
[49]	train-mlogloss:1.20469	validation-mlogloss:1.19675
[50]	train-mlogloss:1.20189	validation-mlogloss:1.19373
[51]	train-mlogloss:1.19939	validation-mlogloss:1.19116
[52]	train-mlogloss:1.19685	validation-mlogloss:1.18832
[53]	train-mlogloss:1.19452	validation-mlogloss:1.18587
[54]	train-mlogloss:1.19224	validation-mlogloss:1.18353
[55]	train-mlogloss:1.18981	validation-mlogloss:1.18097
[56]	train-mlogloss:1.18748	validation-mlogloss:1.17846
[57]	train-mlogloss:1.18519	validation-mlogloss:1.17605
[58]	train-mlogloss:1.18271	validation-mlogloss:1.17375
[59]	train-mlogloss:1.18058	validation-mlogloss:1.17134
[60]	train-mlogloss:1.17840	validation-mlogloss:1.16934
[61]	train-mlogloss:1.17607	validation-mlogloss:1.16686
[62]	train-mlogloss:1.17405	validation-mlogloss:1.16505
[63]	train-mlogloss:1.17202	validation-mlogloss:1.16315
[64]	train-mlogloss:1.16985	validation-mlogloss:1.16101
[65]	train-mlogloss:1.16779	validation-mlogloss:1.15878
[66]	train-mlogloss:1.16567	validation-mlogloss:1.15665
[67]	train-mlogloss:1.16358	validation-mlogloss:1.15434
[68]	train-mlogloss:1.16149	validation-mlogloss:1.15207
[69]	train-mlogloss:1.15943	validation-mlogloss:1.14991
[70]	train-mlogloss:1.15715	validation-mlogloss:1.14757
[71]	train-mlogloss:1.15529	validation-mlogloss:1.14563
[72]	train-mlogloss:1.15338	validation-mlogloss:1.14382
[73]	train-mlogloss:1.15147	validation-mlogloss:1.14167
[74]	train-mlogloss:1.14963	validation-mlogloss:1.13992
[75]	train-mlogloss:1.14773	validation-mlogloss:1.13797
[76]	train-mlogloss:1.14602	validation-mlogloss:1.13618
[77]	train-mlogloss:1.14416	validation-mlogloss:1.13419
[78]	train-mlogloss:1.14238	validation-mlogloss:1.13243
[79]	train-mlogloss:1.14066	validation-mlogloss:1.13098
[80]	train-mlogloss:1.13882	validation-mlogloss:1.12909
[81]	train-mlogloss:1.13705	validation-mlogloss:1.12718
[82]	train-mlogloss:1.13531	validation-mlogloss:1.12536
[83]	train-mlogloss:1.13353	validation-mlogloss:1.12350
[84]	train-mlogloss:1.13194	validation-mlogloss:1.12209
[85]	train-mlogloss:1.13031	validation-mlogloss:1.12050
[86]	train-mlogloss:1.12833	validation-mlogloss:1.11870
[87]	train-mlogloss:1.12668	validation-mlogloss:1.11683
[88]	train-mlogloss:1.12505	validation-mlogloss:1.11513
[89]	train-mlogloss:1.12346	validation-mlogloss:1.11353
[90]	train-mlogloss:1.12185	validation-mlogloss:1.11194
[91]	train-mlogloss:1.12023	validation-mlogloss:1.11037
[92]	train-mlogloss:1.11861	validation-mlogloss:1.10877
[93]	train-mlogloss:1.11711	validation-mlogloss:1.10738
[94]	train-mlogloss:1.11562	validation-mlogloss:1.10588
[95]	train-mlogloss:1.11414	validation-mlogloss:1.10445
[96]	train-mlogloss:1.11265	validation-mlogloss:1.10309
[97]	train-mlogloss:1.11123	validation-mlogloss:1.10181
[98]	train-mlogloss:1.10979	validation-mlogloss:1.10049
[99]	train-mlogloss:1.10839	validation-mlogloss:1.09904
[100]	train-mlogloss:1.10691	validation-mlogloss:1.09746
[101]	train-mlogloss:1.10537	validation-mlogloss:1.09599
[102]	train-mlogloss:1.10405	validation-mlogloss:1.09491
[103]	train-mlogloss:1.10257	validation-mlogloss:1.09338
[104]	train-mlogloss:1.10113	validation-mlogloss:1.09195
[105]	train-mlogloss:1.09970	validation-mlogloss:1.09043
[106]	train-mlogloss:1.09827	validation-mlogloss:1.08881
[107]	train-mlogloss:1.09696	validation-mlogloss:1.08764
[108]	train-mlogloss:1.09543	validation-mlogloss:1.08638
[109]	train-mlogloss:1.09410	validation-mlogloss:1.08498
[110]	train-mlogloss:1.09285	validation-mlogloss:1.08384
[111]	train-mlogloss:1.09163	validation-mlogloss:1.08269
[112]	train-mlogloss:1.09019	validation-mlogloss:1.08146
[113]	train-mlogloss:1.08897	validation-mlogloss:1.08019
[114]	train-mlogloss:1.08773	validation-mlogloss:1.07893
[115]	train-mlogloss:1.08652	validation-mlogloss:1.07764
[116]	train-mlogloss:1.08523	validation-mlogloss:1.07631
[117]	train-mlogloss:1.08397	validation-mlogloss:1.07510
[118]	train-mlogloss:1.08283	validation-mlogloss:1.07403
[119]	train-mlogloss:1.08170	validation-mlogloss:1.07298
[120]	train-mlogloss:1.08049	validation-mlogloss:1.07184
[121]	train-mlogloss:1.07934	validation-mlogloss:1.07072
[122]	train-mlogloss:1.07810	validation-mlogloss:1.06967
[123]	train-mlogloss:1.07687	validation-mlogloss:1.06842
[124]	train-mlogloss:1.07547	validation-mlogloss:1.06688
[125]	train-mlogloss:1.07431	validation-mlogloss:1.06581
[126]	train-mlogloss:1.07308	validation-mlogloss:1.06450
[127]	train-mlogloss:1.07198	validation-mlogloss:1.06352
[128]	train-mlogloss:1.07097	validation-mlogloss:1.06263
[129]	train-mlogloss:1.06989	validation-mlogloss:1.06161
[130]	train-mlogloss:1.06888	validation-mlogloss:1.06058
[131]	train-mlogloss:1.06783	validation-mlogloss:1.05949
[132]	train-mlogloss:1.06686	validation-mlogloss:1.05859
[133]	train-mlogloss:1.06583	validation-mlogloss:1.05765
[134]	train-mlogloss:1.06475	validation-mlogloss:1.05672
[135]	train-mlogloss:1.06373	validation-mlogloss:1.05585
[136]	train-mlogloss:1.06263	validation-mlogloss:1.05478
[137]	train-mlogloss:1.06160	validation-mlogloss:1.05383
[138]	train-mlogloss:1.06062	validation-mlogloss:1.05294
[139]	train-mlogloss:1.05960	validation-mlogloss:1.05198
[140]	train-mlogloss:1.05863	validation-mlogloss:1.05103
[141]	train-mlogloss:1.05752	validation-mlogloss:1.04987
[142]	train-mlogloss:1.05642	validation-mlogloss:1.04876
[143]	train-mlogloss:1.05538	validation-mlogloss:1.04787
[144]	train-mlogloss:1.05448	validation-mlogloss:1.04704
[145]	train-mlogloss:1.05347	validation-mlogloss:1.04620
[146]	train-mlogloss:1.05242	validation-mlogloss:1.04500
[147]	train-mlogloss:1.05144	validation-mlogloss:1.04406
[148]	train-mlogloss:1.05046	validation-mlogloss:1.04302
[149]	train-mlogloss:1.04948	validation-mlogloss:1.04213
[150]	train-mlogloss:1.04854	validation-mlogloss:1.04116
[151]	train-mlogloss:1.04760	validation-mlogloss:1.04039
[152]	train-mlogloss:1.04669	validation-mlogloss:1.03963
[153]	train-mlogloss:1.04573	validation-mlogloss:1.03876
[154]	train-mlogloss:1.04479	validation-mlogloss:1.03789
[155]	train-mlogloss:1.04402	validation-mlogloss:1.03708
[156]	train-mlogloss:1.04317	validation-mlogloss:1.03625
[157]	train-mlogloss:1.04232	validation-mlogloss:1.03556
[158]	train-mlogloss:1.04150	validation-mlogloss:1.03483
[159]	train-mlogloss:1.04052	validation-mlogloss:1.03398
[160]	train-mlogloss:1.03951	validation-mlogloss:1.03324
[161]	train-mlogloss:1.03867	validation-mlogloss:1.03253
[162]	train-mlogloss:1.03776	validation-mlogloss:1.03160
[163]	train-mlogloss:1.03705	validation-mlogloss:1.03090
[164]	train-mlogloss:1.03622	validation-mlogloss:1.03025
[165]	train-mlogloss:1.03538	validation-mlogloss:1.02932
[166]	train-mlogloss:1.03453	validation-mlogloss:1.02845
[167]	train-mlogloss:1.03373	validation-mlogloss:1.02765
[168]	train-mlogloss:1.03297	validation-mlogloss:1.02712
[169]	train-mlogloss:1.03215	validation-mlogloss:1.02643
[170]	train-mlogloss:1.03130	validation-mlogloss:1.02556
[171]	train-mlogloss:1.03036	validation-mlogloss:1.02469
[172]	train-mlogloss:1.02957	validation-mlogloss:1.02386
[173]	train-mlogloss:1.02874	validation-mlogloss:1.02314
[174]	train-mlogloss:1.02789	validation-mlogloss:1.02239
[175]	train-mlogloss:1.02711	validation-mlogloss:1.02163
[176]	train-mlogloss:1.02646	validation-mlogloss:1.02090
[177]	train-mlogloss:1.02555	validation-mlogloss:1.01997
[178]	train-mlogloss:1.02476	validation-mlogloss:1.01932
[179]	train-mlogloss:1.02400	validation-mlogloss:1.01866
[180]	train-mlogloss:1.02327	validation-mlogloss:1.01797
[181]	train-mlogloss:1.02239	validation-mlogloss:1.01708
[182]	train-mlogloss:1.02168	validation-mlogloss:1.01638
[183]	train-mlogloss:1.02097	validation-mlogloss:1.01570
[184]	train-mlogloss:1.02023	validation-mlogloss:1.01507
[185]	train-mlogloss:1.01950	validation-mlogloss:1.01434
[186]	train-mlogloss:1.01881	validation-mlogloss:1.01376
[187]	train-mlogloss:1.01813	validation-mlogloss:1.01319
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[559]	train-mlogloss:0.89644	validation-mlogloss:0.92641
[560]	train-mlogloss:0.89625	validation-mlogloss:0.92624
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[563]	train-mlogloss:0.89593	validation-mlogloss:0.92604
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[609]	train-mlogloss:0.89104	validation-mlogloss:0.92336
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[622]	train-mlogloss:0.88991	validation-mlogloss:0.92257
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[640]	train-mlogloss:0.88808	validation-mlogloss:0.92127
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[642]	train-mlogloss:0.88793	validation-mlogloss:0.92113
[643]	train-mlogloss:0.88781	validation-mlogloss:0.92101
[644]	train-mlogloss:0.88777	validation-mlogloss:0.92099
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[646]	train-mlogloss:0.88761	validation-mlogloss:0.92090
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[679]	train-mlogloss:0.88521	validation-mlogloss:0.91952
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[683]	train-mlogloss:0.88500	validation-mlogloss:0.91936
[684]	train-mlogloss:0.88492	validation-mlogloss:0.91930
[685]	train-mlogloss:0.88484	validation-mlogloss:0.91927
[686]	train-mlogloss:0.88474	validation-mlogloss:0.91914
[687]	train-mlogloss:0.88466	validation-mlogloss:0.91913
[688]	train-mlogloss:0.88462	validation-mlogloss:0.91915
[689]	train-mlogloss:0.88457	validation-mlogloss:0.91908
[690]	train-mlogloss:0.88450	validation-mlogloss:0.91902
[691]	train-mlogloss:0.88443	validation-mlogloss:0.91900
[692]	train-mlogloss:0.88438	validation-mlogloss:0.91893
[693]	train-mlogloss:0.88434	validation-mlogloss:0.91892
[694]	train-mlogloss:0.88427	validation-mlogloss:0.91888
[695]	train-mlogloss:0.88421	validation-mlogloss:0.91889
[696]	train-mlogloss:0.88404	validation-mlogloss:0.91886
[697]	train-mlogloss:0.88394	validation-mlogloss:0.91891
[698]	train-mlogloss:0.88383	validation-mlogloss:0.91880
[699]	train-mlogloss:0.88379	validation-mlogloss:0.91879
[700]	train-mlogloss:0.88373	validation-mlogloss:0.91866
[701]	train-mlogloss:0.88367	validation-mlogloss:0.91866
[702]	train-mlogloss:0.88359	validation-mlogloss:0.91860
[703]	train-mlogloss:0.88353	validation-mlogloss:0.91858
[704]	train-mlogloss:0.88343	validation-mlogloss:0.91845
[705]	train-mlogloss:0.88336	validation-mlogloss:0.91839
[706]	train-mlogloss:0.88330	validation-mlogloss:0.91833
[707]	train-mlogloss:0.88325	validation-mlogloss:0.91831
[708]	train-mlogloss:0.88321	validation-mlogloss:0.91827
[709]	train-mlogloss:0.88316	validation-mlogloss:0.91820
[710]	train-mlogloss:0.88310	validation-mlogloss:0.91815
[711]	train-mlogloss:0.88298	validation-mlogloss:0.91807
[712]	train-mlogloss:0.88294	validation-mlogloss:0.91804
[713]	train-mlogloss:0.88282	validation-mlogloss:0.91792
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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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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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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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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 0 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.37 [%]
Global accuracy score (test) = 61.23 [%]
Global F1 score (train) = 63.44 [%]
Global F1 score (test) = 61.76 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.47      0.47      0.47       400
MODERATE-INTENSITY       0.55      0.63      0.59       400
         SEDENTARY       0.68      0.74      0.70       400
VIGOROUS-INTENSITY       0.84      0.62      0.71       345

          accuracy                           0.61      1545
         macro avg       0.63      0.61      0.62      1545
      weighted avg       0.63      0.61      0.61      1545


Accuracy capturado en la ejecución 10: 61.23 [%]
F1-score capturado en la ejecución 10: 61.76 [%]

=== EJECUCIÓN 11 ===

--- TRAIN (ejecución 11) ---

--- TEST (ejecución 11) ---
2025-11-04 11:01:36.559184: 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`.
2025-11-04 11:01:36.570446: 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 00:00:1762250496.583863 1080368 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250496.588028 1080368 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250496.598303 1080368 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250496.598320 1080368 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250496.598322 1080368 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250496.598323 1080368 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:01:36.601499: 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:1.38111	validation-mlogloss:1.38094
[1]	train-mlogloss:1.37608	validation-mlogloss:1.37541
[2]	train-mlogloss:1.37096	validation-mlogloss:1.37003
[3]	train-mlogloss:1.36615	validation-mlogloss:1.36521
[4]	train-mlogloss:1.36128	validation-mlogloss:1.36027
[5]	train-mlogloss:1.35657	validation-mlogloss:1.35553
[6]	train-mlogloss:1.35167	validation-mlogloss:1.35034
[7]	train-mlogloss:1.34701	validation-mlogloss:1.34553
[8]	train-mlogloss:1.34253	validation-mlogloss:1.34069
[9]	train-mlogloss:1.33812	validation-mlogloss:1.33596
[10]	train-mlogloss:1.33371	validation-mlogloss:1.33114
[11]	train-mlogloss:1.32949	validation-mlogloss:1.32670
[12]	train-mlogloss:1.32523	validation-mlogloss:1.32225
[13]	train-mlogloss:1.32111	validation-mlogloss:1.31773
[14]	train-mlogloss:1.31702	validation-mlogloss:1.31345
[15]	train-mlogloss:1.31312	validation-mlogloss:1.30922
[16]	train-mlogloss:1.30915	validation-mlogloss:1.30519
[17]	train-mlogloss:1.30525	validation-mlogloss:1.30123
[18]	train-mlogloss:1.30144	validation-mlogloss:1.29718
[19]	train-mlogloss:1.29759	validation-mlogloss:1.29292
[20]	train-mlogloss:1.29343	validation-mlogloss:1.28845
[21]	train-mlogloss:1.28977	validation-mlogloss:1.28460
[22]	train-mlogloss:1.28597	validation-mlogloss:1.28044
[23]	train-mlogloss:1.28243	validation-mlogloss:1.27669
[24]	train-mlogloss:1.27900	validation-mlogloss:1.27303
[25]	train-mlogloss:1.27555	validation-mlogloss:1.26935
[26]	train-mlogloss:1.27215	validation-mlogloss:1.26574
[27]	train-mlogloss:1.26872	validation-mlogloss:1.26239
[28]	train-mlogloss:1.26550	validation-mlogloss:1.25886
[29]	train-mlogloss:1.26218	validation-mlogloss:1.25537
[30]	train-mlogloss:1.25895	validation-mlogloss:1.25179
[31]	train-mlogloss:1.25536	validation-mlogloss:1.24833
[32]	train-mlogloss:1.25222	validation-mlogloss:1.24499
[33]	train-mlogloss:1.24925	validation-mlogloss:1.24183
[34]	train-mlogloss:1.24618	validation-mlogloss:1.23869
[35]	train-mlogloss:1.24326	validation-mlogloss:1.23553
[36]	train-mlogloss:1.24017	validation-mlogloss:1.23211
[37]	train-mlogloss:1.23719	validation-mlogloss:1.22904
[38]	train-mlogloss:1.23433	validation-mlogloss:1.22619
[39]	train-mlogloss:1.23148	validation-mlogloss:1.22323
[40]	train-mlogloss:1.22862	validation-mlogloss:1.22028
[41]	train-mlogloss:1.22588	validation-mlogloss:1.21726
[42]	train-mlogloss:1.22318	validation-mlogloss:1.21465
[43]	train-mlogloss:1.22057	validation-mlogloss:1.21187
[44]	train-mlogloss:1.21793	validation-mlogloss:1.20938
[45]	train-mlogloss:1.21493	validation-mlogloss:1.20642
[46]	train-mlogloss:1.21238	validation-mlogloss:1.20390
[47]	train-mlogloss:1.20983	validation-mlogloss:1.20131
[48]	train-mlogloss:1.20741	validation-mlogloss:1.19916
[49]	train-mlogloss:1.20499	validation-mlogloss:1.19674
[50]	train-mlogloss:1.20255	validation-mlogloss:1.19408
[51]	train-mlogloss:1.20006	validation-mlogloss:1.19149
[52]	train-mlogloss:1.19777	validation-mlogloss:1.18895
[53]	train-mlogloss:1.19541	validation-mlogloss:1.18665
[54]	train-mlogloss:1.19299	validation-mlogloss:1.18415
[55]	train-mlogloss:1.19066	validation-mlogloss:1.18188
[56]	train-mlogloss:1.18836	validation-mlogloss:1.17982
[57]	train-mlogloss:1.18619	validation-mlogloss:1.17773
[58]	train-mlogloss:1.18391	validation-mlogloss:1.17540
[59]	train-mlogloss:1.18182	validation-mlogloss:1.17322
[60]	train-mlogloss:1.17961	validation-mlogloss:1.17091
[61]	train-mlogloss:1.17745	validation-mlogloss:1.16851
[62]	train-mlogloss:1.17497	validation-mlogloss:1.16571
[63]	train-mlogloss:1.17282	validation-mlogloss:1.16360
[64]	train-mlogloss:1.17073	validation-mlogloss:1.16160
[65]	train-mlogloss:1.16857	validation-mlogloss:1.15947
[66]	train-mlogloss:1.16637	validation-mlogloss:1.15708
[67]	train-mlogloss:1.16431	validation-mlogloss:1.15507
[68]	train-mlogloss:1.16218	validation-mlogloss:1.15303
[69]	train-mlogloss:1.15985	validation-mlogloss:1.15090
[70]	train-mlogloss:1.15754	validation-mlogloss:1.14852
[71]	train-mlogloss:1.15526	validation-mlogloss:1.14620
[72]	train-mlogloss:1.15320	validation-mlogloss:1.14414
[73]	train-mlogloss:1.15122	validation-mlogloss:1.14226
[74]	train-mlogloss:1.14926	validation-mlogloss:1.14034
[75]	train-mlogloss:1.14727	validation-mlogloss:1.13825
[76]	train-mlogloss:1.14548	validation-mlogloss:1.13648
[77]	train-mlogloss:1.14334	validation-mlogloss:1.13459
[78]	train-mlogloss:1.14132	validation-mlogloss:1.13256
[79]	train-mlogloss:1.13953	validation-mlogloss:1.13059
[80]	train-mlogloss:1.13738	validation-mlogloss:1.12857
[81]	train-mlogloss:1.13559	validation-mlogloss:1.12669
[82]	train-mlogloss:1.13379	validation-mlogloss:1.12505
[83]	train-mlogloss:1.13205	validation-mlogloss:1.12325
[84]	train-mlogloss:1.13033	validation-mlogloss:1.12126
[85]	train-mlogloss:1.12866	validation-mlogloss:1.11936
[86]	train-mlogloss:1.12689	validation-mlogloss:1.11755
[87]	train-mlogloss:1.12534	validation-mlogloss:1.11620
[88]	train-mlogloss:1.12387	validation-mlogloss:1.11488
[89]	train-mlogloss:1.12225	validation-mlogloss:1.11328
[90]	train-mlogloss:1.12080	validation-mlogloss:1.11185
[91]	train-mlogloss:1.11897	validation-mlogloss:1.11011
[92]	train-mlogloss:1.11750	validation-mlogloss:1.10843
[93]	train-mlogloss:1.11604	validation-mlogloss:1.10720
[94]	train-mlogloss:1.11442	validation-mlogloss:1.10544
[95]	train-mlogloss:1.11270	validation-mlogloss:1.10398
[96]	train-mlogloss:1.11116	validation-mlogloss:1.10262
[97]	train-mlogloss:1.10936	validation-mlogloss:1.10078
[98]	train-mlogloss:1.10786	validation-mlogloss:1.09930
[99]	train-mlogloss:1.10638	validation-mlogloss:1.09759
[100]	train-mlogloss:1.10484	validation-mlogloss:1.09608
[101]	train-mlogloss:1.10341	validation-mlogloss:1.09473
[102]	train-mlogloss:1.10194	validation-mlogloss:1.09305
[103]	train-mlogloss:1.10043	validation-mlogloss:1.09169
[104]	train-mlogloss:1.09883	validation-mlogloss:1.09020
[105]	train-mlogloss:1.09749	validation-mlogloss:1.08890
[106]	train-mlogloss:1.09612	validation-mlogloss:1.08744
[107]	train-mlogloss:1.09477	validation-mlogloss:1.08626
[108]	train-mlogloss:1.09359	validation-mlogloss:1.08526
[109]	train-mlogloss:1.09227	validation-mlogloss:1.08408
[110]	train-mlogloss:1.09075	validation-mlogloss:1.08253
[111]	train-mlogloss:1.08937	validation-mlogloss:1.08121
[112]	train-mlogloss:1.08806	validation-mlogloss:1.07990
[113]	train-mlogloss:1.08678	validation-mlogloss:1.07870
[114]	train-mlogloss:1.08553	validation-mlogloss:1.07772
[115]	train-mlogloss:1.08428	validation-mlogloss:1.07629
[116]	train-mlogloss:1.08303	validation-mlogloss:1.07527
[117]	train-mlogloss:1.08182	validation-mlogloss:1.07404
[118]	train-mlogloss:1.08063	validation-mlogloss:1.07300
[119]	train-mlogloss:1.07945	validation-mlogloss:1.07189
[120]	train-mlogloss:1.07828	validation-mlogloss:1.07088
[121]	train-mlogloss:1.07709	validation-mlogloss:1.06979
[122]	train-mlogloss:1.07593	validation-mlogloss:1.06861
[123]	train-mlogloss:1.07479	validation-mlogloss:1.06741
[124]	train-mlogloss:1.07362	validation-mlogloss:1.06633
[125]	train-mlogloss:1.07258	validation-mlogloss:1.06528
[126]	train-mlogloss:1.07139	validation-mlogloss:1.06416
[127]	train-mlogloss:1.07022	validation-mlogloss:1.06311
[128]	train-mlogloss:1.06905	validation-mlogloss:1.06188
[129]	train-mlogloss:1.06788	validation-mlogloss:1.06074
[130]	train-mlogloss:1.06674	validation-mlogloss:1.05966
[131]	train-mlogloss:1.06568	validation-mlogloss:1.05853
[132]	train-mlogloss:1.06460	validation-mlogloss:1.05767
[133]	train-mlogloss:1.06358	validation-mlogloss:1.05679
[134]	train-mlogloss:1.06258	validation-mlogloss:1.05589
[135]	train-mlogloss:1.06151	validation-mlogloss:1.05494
[136]	train-mlogloss:1.06041	validation-mlogloss:1.05392
[137]	train-mlogloss:1.05938	validation-mlogloss:1.05296
[138]	train-mlogloss:1.05849	validation-mlogloss:1.05226
[139]	train-mlogloss:1.05747	validation-mlogloss:1.05134
[140]	train-mlogloss:1.05641	validation-mlogloss:1.05047
[141]	train-mlogloss:1.05535	validation-mlogloss:1.04938
[142]	train-mlogloss:1.05431	validation-mlogloss:1.04824
[143]	train-mlogloss:1.05319	validation-mlogloss:1.04697
[144]	train-mlogloss:1.05227	validation-mlogloss:1.04606
[145]	train-mlogloss:1.05126	validation-mlogloss:1.04497
[146]	train-mlogloss:1.05031	validation-mlogloss:1.04407
[147]	train-mlogloss:1.04930	validation-mlogloss:1.04307
[148]	train-mlogloss:1.04838	validation-mlogloss:1.04213
[149]	train-mlogloss:1.04733	validation-mlogloss:1.04125
[150]	train-mlogloss:1.04643	validation-mlogloss:1.04052
[151]	train-mlogloss:1.04544	validation-mlogloss:1.03953
[152]	train-mlogloss:1.04454	validation-mlogloss:1.03872
[153]	train-mlogloss:1.04358	validation-mlogloss:1.03781
[154]	train-mlogloss:1.04268	validation-mlogloss:1.03682
[155]	train-mlogloss:1.04174	validation-mlogloss:1.03595
[156]	train-mlogloss:1.04076	validation-mlogloss:1.03484
[157]	train-mlogloss:1.03990	validation-mlogloss:1.03396
[158]	train-mlogloss:1.03902	validation-mlogloss:1.03311
[159]	train-mlogloss:1.03819	validation-mlogloss:1.03228
[160]	train-mlogloss:1.03740	validation-mlogloss:1.03141
[161]	train-mlogloss:1.03652	validation-mlogloss:1.03061
[162]	train-mlogloss:1.03573	validation-mlogloss:1.02997
[163]	train-mlogloss:1.03491	validation-mlogloss:1.02930
[164]	train-mlogloss:1.03402	validation-mlogloss:1.02864
[165]	train-mlogloss:1.03309	validation-mlogloss:1.02772
[166]	train-mlogloss:1.03224	validation-mlogloss:1.02705
[167]	train-mlogloss:1.03140	validation-mlogloss:1.02628
[168]	train-mlogloss:1.03055	validation-mlogloss:1.02559
[169]	train-mlogloss:1.02979	validation-mlogloss:1.02487
[170]	train-mlogloss:1.02896	validation-mlogloss:1.02412
[171]	train-mlogloss:1.02817	validation-mlogloss:1.02339
[172]	train-mlogloss:1.02733	validation-mlogloss:1.02241
[173]	train-mlogloss:1.02652	validation-mlogloss:1.02173
[174]	train-mlogloss:1.02578	validation-mlogloss:1.02117
[175]	train-mlogloss:1.02491	validation-mlogloss:1.02032
[176]	train-mlogloss:1.02410	validation-mlogloss:1.01961
[177]	train-mlogloss:1.02330	validation-mlogloss:1.01901
[178]	train-mlogloss:1.02250	validation-mlogloss:1.01813
[179]	train-mlogloss:1.02171	validation-mlogloss:1.01738
[180]	train-mlogloss:1.02098	validation-mlogloss:1.01689
[181]	train-mlogloss:1.02031	validation-mlogloss:1.01630
[182]	train-mlogloss:1.01956	validation-mlogloss:1.01568
[183]	train-mlogloss:1.01884	validation-mlogloss:1.01510
[184]	train-mlogloss:1.01813	validation-mlogloss:1.01455
[185]	train-mlogloss:1.01747	validation-mlogloss:1.01396
[186]	train-mlogloss:1.01671	validation-mlogloss:1.01326
[187]	train-mlogloss:1.01604	validation-mlogloss:1.01257
[188]	train-mlogloss:1.01532	validation-mlogloss:1.01195
[189]	train-mlogloss:1.01465	validation-mlogloss:1.01142
[190]	train-mlogloss:1.01400	validation-mlogloss:1.01102
[191]	train-mlogloss:1.01329	validation-mlogloss:1.01031
[192]	train-mlogloss:1.01266	validation-mlogloss:1.00987
[193]	train-mlogloss:1.01202	validation-mlogloss:1.00916
[194]	train-mlogloss:1.01130	validation-mlogloss:1.00857
[195]	train-mlogloss:1.01067	validation-mlogloss:1.00800
[196]	train-mlogloss:1.01003	validation-mlogloss:1.00752
[197]	train-mlogloss:1.00929	validation-mlogloss:1.00678
[198]	train-mlogloss:1.00858	validation-mlogloss:1.00619
[199]	train-mlogloss:1.00785	validation-mlogloss:1.00569
[200]	train-mlogloss:1.00717	validation-mlogloss:1.00526
[201]	train-mlogloss:1.00654	validation-mlogloss:1.00485
[202]	train-mlogloss:1.00587	validation-mlogloss:1.00421
[203]	train-mlogloss:1.00530	validation-mlogloss:1.00366
[204]	train-mlogloss:1.00459	validation-mlogloss:1.00309
[205]	train-mlogloss:1.00389	validation-mlogloss:1.00246
[206]	train-mlogloss:1.00325	validation-mlogloss:1.00203
[207]	train-mlogloss:1.00252	validation-mlogloss:1.00135
[208]	train-mlogloss:1.00191	validation-mlogloss:1.00100
[209]	train-mlogloss:1.00126	validation-mlogloss:1.00045
[210]	train-mlogloss:1.00061	validation-mlogloss:1.00001
[211]	train-mlogloss:1.00007	validation-mlogloss:0.99979
[212]	train-mlogloss:0.99949	validation-mlogloss:0.99929
[213]	train-mlogloss:0.99884	validation-mlogloss:0.99870
[214]	train-mlogloss:0.99827	validation-mlogloss:0.99808
[215]	train-mlogloss:0.99769	validation-mlogloss:0.99752
[216]	train-mlogloss:0.99693	validation-mlogloss:0.99693
[217]	train-mlogloss:0.99627	validation-mlogloss:0.99636
[218]	train-mlogloss:0.99568	validation-mlogloss:0.99594
[219]	train-mlogloss:0.99505	validation-mlogloss:0.99547
[220]	train-mlogloss:0.99448	validation-mlogloss:0.99486
[221]	train-mlogloss:0.99394	validation-mlogloss:0.99452
[222]	train-mlogloss:0.99337	validation-mlogloss:0.99385
[223]	train-mlogloss:0.99275	validation-mlogloss:0.99336
[224]	train-mlogloss:0.99219	validation-mlogloss:0.99287
[225]	train-mlogloss:0.99165	validation-mlogloss:0.99240
[226]	train-mlogloss:0.99110	validation-mlogloss:0.99186
[227]	train-mlogloss:0.99060	validation-mlogloss:0.99136
[228]	train-mlogloss:0.99008	validation-mlogloss:0.99091
[229]	train-mlogloss:0.98938	validation-mlogloss:0.99044
[230]	train-mlogloss:0.98883	validation-mlogloss:0.99011
[231]	train-mlogloss:0.98821	validation-mlogloss:0.98973
[232]	train-mlogloss:0.98766	validation-mlogloss:0.98925
[233]	train-mlogloss:0.98706	validation-mlogloss:0.98861
[234]	train-mlogloss:0.98650	validation-mlogloss:0.98820
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[640]	train-mlogloss:0.88612	validation-mlogloss:0.92086
[641]	train-mlogloss:0.88607	validation-mlogloss:0.92081
[642]	train-mlogloss:0.88595	validation-mlogloss:0.92074
[643]	train-mlogloss:0.88584	validation-mlogloss:0.92068
[644]	train-mlogloss:0.88571	validation-mlogloss:0.92056
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[648]	train-mlogloss:0.88552	validation-mlogloss:0.92047
[649]	train-mlogloss:0.88541	validation-mlogloss:0.92032
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[651]	train-mlogloss:0.88526	validation-mlogloss:0.92026
[652]	train-mlogloss:0.88521	validation-mlogloss:0.92024
[653]	train-mlogloss:0.88516	validation-mlogloss:0.92021
[654]	train-mlogloss:0.88503	validation-mlogloss:0.92014
[655]	train-mlogloss:0.88488	validation-mlogloss:0.92006
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[658]	train-mlogloss:0.88466	validation-mlogloss:0.91991
[659]	train-mlogloss:0.88455	validation-mlogloss:0.91985
[660]	train-mlogloss:0.88447	validation-mlogloss:0.91981
[661]	train-mlogloss:0.88442	validation-mlogloss:0.91982
[662]	train-mlogloss:0.88431	validation-mlogloss:0.91971
[663]	train-mlogloss:0.88424	validation-mlogloss:0.91969
[664]	train-mlogloss:0.88418	validation-mlogloss:0.91965
[665]	train-mlogloss:0.88409	validation-mlogloss:0.91955
[666]	train-mlogloss:0.88402	validation-mlogloss:0.91948
[667]	train-mlogloss:0.88389	validation-mlogloss:0.91943
[668]	train-mlogloss:0.88379	validation-mlogloss:0.91938
[669]	train-mlogloss:0.88372	validation-mlogloss:0.91932
[670]	train-mlogloss:0.88365	validation-mlogloss:0.91928
[671]	train-mlogloss:0.88359	validation-mlogloss:0.91925
[672]	train-mlogloss:0.88353	validation-mlogloss:0.91924
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[675]	train-mlogloss:0.88336	validation-mlogloss:0.91917
[676]	train-mlogloss:0.88326	validation-mlogloss:0.91902
[677]	train-mlogloss:0.88315	validation-mlogloss:0.91893
[678]	train-mlogloss:0.88307	validation-mlogloss:0.91890
[679]	train-mlogloss:0.88296	validation-mlogloss:0.91882
[680]	train-mlogloss:0.88283	validation-mlogloss:0.91873
[681]	train-mlogloss:0.88277	validation-mlogloss:0.91871
[682]	train-mlogloss:0.88274	validation-mlogloss:0.91868
[683]	train-mlogloss:0.88270	validation-mlogloss:0.91864
[684]	train-mlogloss:0.88265	validation-mlogloss:0.91857
[685]	train-mlogloss:0.88260	validation-mlogloss:0.91857
[686]	train-mlogloss:0.88253	validation-mlogloss:0.91857
[687]	train-mlogloss:0.88242	validation-mlogloss:0.91852
[688]	train-mlogloss:0.88237	validation-mlogloss:0.91852
[689]	train-mlogloss:0.88230	validation-mlogloss:0.91840
[690]	train-mlogloss:0.88225	validation-mlogloss:0.91839
[691]	train-mlogloss:0.88218	validation-mlogloss:0.91832
[692]	train-mlogloss:0.88204	validation-mlogloss:0.91812
[693]	train-mlogloss:0.88197	validation-mlogloss:0.91811
[694]	train-mlogloss:0.88189	validation-mlogloss:0.91808
[695]	train-mlogloss:0.88183	validation-mlogloss:0.91807
[696]	train-mlogloss:0.88175	validation-mlogloss:0.91799
[697]	train-mlogloss:0.88168	validation-mlogloss:0.91787
[698]	train-mlogloss:0.88166	validation-mlogloss:0.91786
[699]	train-mlogloss:0.88160	validation-mlogloss:0.91786
[700]	train-mlogloss:0.88154	validation-mlogloss:0.91786
[701]	train-mlogloss:0.88150	validation-mlogloss:0.91786
[702]	train-mlogloss:0.88140	validation-mlogloss:0.91787
[703]	train-mlogloss:0.88135	validation-mlogloss:0.91788
[704]	train-mlogloss:0.88129	validation-mlogloss:0.91781
[705]	train-mlogloss:0.88115	validation-mlogloss:0.91768
[706]	train-mlogloss:0.88102	validation-mlogloss:0.91749
[707]	train-mlogloss:0.88095	validation-mlogloss:0.91743
[708]	train-mlogloss:0.88084	validation-mlogloss:0.91736
[709]	train-mlogloss:0.88076	validation-mlogloss:0.91735
[710]	train-mlogloss:0.88068	validation-mlogloss:0.91734
[711]	train-mlogloss:0.88061	validation-mlogloss:0.91730
[712]	train-mlogloss:0.88053	validation-mlogloss:0.91720
[713]	train-mlogloss:0.88042	validation-mlogloss:0.91707
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 3]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.53 [%]
Global accuracy score (test) = 59.81 [%]
Global F1 score (train) = 63.56 [%]
Global F1 score (test) = 60.68 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.43      0.46      0.45       400
MODERATE-INTENSITY       0.55      0.60      0.57       400
         SEDENTARY       0.65      0.72      0.69       400
VIGOROUS-INTENSITY       0.88      0.62      0.72       345

          accuracy                           0.60      1545
         macro avg       0.63      0.60      0.61      1545
      weighted avg       0.62      0.60      0.60      1545


Accuracy capturado en la ejecución 11: 59.81 [%]
F1-score capturado en la ejecución 11: 60.68 [%]

=== EJECUCIÓN 12 ===

--- TRAIN (ejecución 12) ---

--- TEST (ejecución 12) ---
2025-11-04 11:01:53.524057: 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`.
2025-11-04 11:01:53.535310: 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 00:00:1762250513.548343 1080682 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250513.552490 1080682 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250513.562138 1080682 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250513.562153 1080682 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250513.562154 1080682 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250513.562155 1080682 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:01:53.565248: 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)
Training a non-convolutional model.
[0]	train-mlogloss:1.38115	validation-mlogloss:1.38098
[1]	train-mlogloss:1.37614	validation-mlogloss:1.37591
[2]	train-mlogloss:1.37115	validation-mlogloss:1.37092
[3]	train-mlogloss:1.36623	validation-mlogloss:1.36561
[4]	train-mlogloss:1.36144	validation-mlogloss:1.36096
[5]	train-mlogloss:1.35671	validation-mlogloss:1.35623
[6]	train-mlogloss:1.35200	validation-mlogloss:1.35133
[7]	train-mlogloss:1.34731	validation-mlogloss:1.34640
[8]	train-mlogloss:1.34270	validation-mlogloss:1.34178
[9]	train-mlogloss:1.33813	validation-mlogloss:1.33715
[10]	train-mlogloss:1.33363	validation-mlogloss:1.33242
[11]	train-mlogloss:1.32930	validation-mlogloss:1.32817
[12]	train-mlogloss:1.32504	validation-mlogloss:1.32393
[13]	train-mlogloss:1.32098	validation-mlogloss:1.31974
[14]	train-mlogloss:1.31650	validation-mlogloss:1.31516
[15]	train-mlogloss:1.31258	validation-mlogloss:1.31121
[16]	train-mlogloss:1.30846	validation-mlogloss:1.30715
[17]	train-mlogloss:1.30446	validation-mlogloss:1.30324
[18]	train-mlogloss:1.30064	validation-mlogloss:1.29950
[19]	train-mlogloss:1.29682	validation-mlogloss:1.29567
[20]	train-mlogloss:1.29281	validation-mlogloss:1.29160
[21]	train-mlogloss:1.28917	validation-mlogloss:1.28796
[22]	train-mlogloss:1.28561	validation-mlogloss:1.28439
[23]	train-mlogloss:1.28205	validation-mlogloss:1.28078
[24]	train-mlogloss:1.27816	validation-mlogloss:1.27665
[25]	train-mlogloss:1.27462	validation-mlogloss:1.27310
[26]	train-mlogloss:1.27118	validation-mlogloss:1.26952
[27]	train-mlogloss:1.26765	validation-mlogloss:1.26599
[28]	train-mlogloss:1.26440	validation-mlogloss:1.26251
[29]	train-mlogloss:1.26097	validation-mlogloss:1.25901
[30]	train-mlogloss:1.25772	validation-mlogloss:1.25573
[31]	train-mlogloss:1.25457	validation-mlogloss:1.25266
[32]	train-mlogloss:1.25136	validation-mlogloss:1.24930
[33]	train-mlogloss:1.24819	validation-mlogloss:1.24595
[34]	train-mlogloss:1.24514	validation-mlogloss:1.24303
[35]	train-mlogloss:1.24222	validation-mlogloss:1.24031
[36]	train-mlogloss:1.23924	validation-mlogloss:1.23724
[37]	train-mlogloss:1.23634	validation-mlogloss:1.23457
[38]	train-mlogloss:1.23331	validation-mlogloss:1.23140
[39]	train-mlogloss:1.23049	validation-mlogloss:1.22842
[40]	train-mlogloss:1.22773	validation-mlogloss:1.22590
[41]	train-mlogloss:1.22484	validation-mlogloss:1.22287
[42]	train-mlogloss:1.22178	validation-mlogloss:1.21972
[43]	train-mlogloss:1.21901	validation-mlogloss:1.21702
[44]	train-mlogloss:1.21625	validation-mlogloss:1.21450
[45]	train-mlogloss:1.21365	validation-mlogloss:1.21174
[46]	train-mlogloss:1.21086	validation-mlogloss:1.20879
[47]	train-mlogloss:1.20828	validation-mlogloss:1.20600
[48]	train-mlogloss:1.20569	validation-mlogloss:1.20341
[49]	train-mlogloss:1.20309	validation-mlogloss:1.20079
[50]	train-mlogloss:1.20013	validation-mlogloss:1.19782
[51]	train-mlogloss:1.19786	validation-mlogloss:1.19571
[52]	train-mlogloss:1.19509	validation-mlogloss:1.19286
[53]	train-mlogloss:1.19248	validation-mlogloss:1.19024
[54]	train-mlogloss:1.18965	validation-mlogloss:1.18728
[55]	train-mlogloss:1.18736	validation-mlogloss:1.18506
[56]	train-mlogloss:1.18512	validation-mlogloss:1.18293
[57]	train-mlogloss:1.18275	validation-mlogloss:1.18055
[58]	train-mlogloss:1.18053	validation-mlogloss:1.17832
[59]	train-mlogloss:1.17820	validation-mlogloss:1.17600
[60]	train-mlogloss:1.17594	validation-mlogloss:1.17379
[61]	train-mlogloss:1.17335	validation-mlogloss:1.17138
[62]	train-mlogloss:1.17123	validation-mlogloss:1.16957
[63]	train-mlogloss:1.16903	validation-mlogloss:1.16731
[64]	train-mlogloss:1.16688	validation-mlogloss:1.16514
[65]	train-mlogloss:1.16485	validation-mlogloss:1.16319
[66]	train-mlogloss:1.16281	validation-mlogloss:1.16133
[67]	train-mlogloss:1.16079	validation-mlogloss:1.15932
[68]	train-mlogloss:1.15868	validation-mlogloss:1.15731
[69]	train-mlogloss:1.15653	validation-mlogloss:1.15504
[70]	train-mlogloss:1.15447	validation-mlogloss:1.15295
[71]	train-mlogloss:1.15245	validation-mlogloss:1.15098
[72]	train-mlogloss:1.15049	validation-mlogloss:1.14894
[73]	train-mlogloss:1.14865	validation-mlogloss:1.14718
[74]	train-mlogloss:1.14638	validation-mlogloss:1.14498
[75]	train-mlogloss:1.14448	validation-mlogloss:1.14316
[76]	train-mlogloss:1.14241	validation-mlogloss:1.14147
[77]	train-mlogloss:1.14069	validation-mlogloss:1.13969
[78]	train-mlogloss:1.13862	validation-mlogloss:1.13787
[79]	train-mlogloss:1.13652	validation-mlogloss:1.13597
[80]	train-mlogloss:1.13460	validation-mlogloss:1.13425
[81]	train-mlogloss:1.13288	validation-mlogloss:1.13274
[82]	train-mlogloss:1.13109	validation-mlogloss:1.13091
[83]	train-mlogloss:1.12911	validation-mlogloss:1.12918
[84]	train-mlogloss:1.12732	validation-mlogloss:1.12740
[85]	train-mlogloss:1.12558	validation-mlogloss:1.12578
[86]	train-mlogloss:1.12398	validation-mlogloss:1.12423
[87]	train-mlogloss:1.12237	validation-mlogloss:1.12274
[88]	train-mlogloss:1.12080	validation-mlogloss:1.12132
[89]	train-mlogloss:1.11914	validation-mlogloss:1.11989
[90]	train-mlogloss:1.11726	validation-mlogloss:1.11826
[91]	train-mlogloss:1.11562	validation-mlogloss:1.11667
[92]	train-mlogloss:1.11394	validation-mlogloss:1.11502
[93]	train-mlogloss:1.11238	validation-mlogloss:1.11367
[94]	train-mlogloss:1.11088	validation-mlogloss:1.11231
[95]	train-mlogloss:1.10931	validation-mlogloss:1.11090
[96]	train-mlogloss:1.10782	validation-mlogloss:1.10953
[97]	train-mlogloss:1.10610	validation-mlogloss:1.10792
[98]	train-mlogloss:1.10432	validation-mlogloss:1.10632
[99]	train-mlogloss:1.10277	validation-mlogloss:1.10478
[100]	train-mlogloss:1.10137	validation-mlogloss:1.10349
[101]	train-mlogloss:1.09987	validation-mlogloss:1.10196
[102]	train-mlogloss:1.09840	validation-mlogloss:1.10061
[103]	train-mlogloss:1.09697	validation-mlogloss:1.09928
[104]	train-mlogloss:1.09552	validation-mlogloss:1.09801
[105]	train-mlogloss:1.09412	validation-mlogloss:1.09656
[106]	train-mlogloss:1.09258	validation-mlogloss:1.09534
[107]	train-mlogloss:1.09121	validation-mlogloss:1.09384
[108]	train-mlogloss:1.08983	validation-mlogloss:1.09271
[109]	train-mlogloss:1.08829	validation-mlogloss:1.09146
[110]	train-mlogloss:1.08699	validation-mlogloss:1.09028
[111]	train-mlogloss:1.08569	validation-mlogloss:1.08907
[112]	train-mlogloss:1.08441	validation-mlogloss:1.08786
[113]	train-mlogloss:1.08315	validation-mlogloss:1.08675
[114]	train-mlogloss:1.08187	validation-mlogloss:1.08566
[115]	train-mlogloss:1.08050	validation-mlogloss:1.08447
[116]	train-mlogloss:1.07922	validation-mlogloss:1.08319
[117]	train-mlogloss:1.07788	validation-mlogloss:1.08202
[118]	train-mlogloss:1.07664	validation-mlogloss:1.08092
[119]	train-mlogloss:1.07517	validation-mlogloss:1.07977
[120]	train-mlogloss:1.07405	validation-mlogloss:1.07895
[121]	train-mlogloss:1.07284	validation-mlogloss:1.07788
[122]	train-mlogloss:1.07172	validation-mlogloss:1.07681
[123]	train-mlogloss:1.07051	validation-mlogloss:1.07552
[124]	train-mlogloss:1.06939	validation-mlogloss:1.07460
[125]	train-mlogloss:1.06798	validation-mlogloss:1.07336
[126]	train-mlogloss:1.06694	validation-mlogloss:1.07249
[127]	train-mlogloss:1.06576	validation-mlogloss:1.07145
[128]	train-mlogloss:1.06467	validation-mlogloss:1.07039
[129]	train-mlogloss:1.06344	validation-mlogloss:1.06919
[130]	train-mlogloss:1.06243	validation-mlogloss:1.06836
[131]	train-mlogloss:1.06120	validation-mlogloss:1.06718
[132]	train-mlogloss:1.06007	validation-mlogloss:1.06607
[133]	train-mlogloss:1.05897	validation-mlogloss:1.06492
[134]	train-mlogloss:1.05765	validation-mlogloss:1.06389
[135]	train-mlogloss:1.05660	validation-mlogloss:1.06293
[136]	train-mlogloss:1.05550	validation-mlogloss:1.06192
[137]	train-mlogloss:1.05444	validation-mlogloss:1.06111
[138]	train-mlogloss:1.05337	validation-mlogloss:1.06001
[139]	train-mlogloss:1.05229	validation-mlogloss:1.05904
[140]	train-mlogloss:1.05121	validation-mlogloss:1.05804
[141]	train-mlogloss:1.05007	validation-mlogloss:1.05696
[142]	train-mlogloss:1.04901	validation-mlogloss:1.05587
[143]	train-mlogloss:1.04809	validation-mlogloss:1.05491
[144]	train-mlogloss:1.04709	validation-mlogloss:1.05389
[145]	train-mlogloss:1.04623	validation-mlogloss:1.05306
[146]	train-mlogloss:1.04534	validation-mlogloss:1.05244
[147]	train-mlogloss:1.04424	validation-mlogloss:1.05164
[148]	train-mlogloss:1.04328	validation-mlogloss:1.05094
[149]	train-mlogloss:1.04231	validation-mlogloss:1.05009
[150]	train-mlogloss:1.04137	validation-mlogloss:1.04923
[151]	train-mlogloss:1.04040	validation-mlogloss:1.04819
[152]	train-mlogloss:1.03958	validation-mlogloss:1.04754
[153]	train-mlogloss:1.03865	validation-mlogloss:1.04669
[154]	train-mlogloss:1.03771	validation-mlogloss:1.04579
[155]	train-mlogloss:1.03673	validation-mlogloss:1.04498
[156]	train-mlogloss:1.03586	validation-mlogloss:1.04423
[157]	train-mlogloss:1.03495	validation-mlogloss:1.04339
[158]	train-mlogloss:1.03405	validation-mlogloss:1.04269
[159]	train-mlogloss:1.03318	validation-mlogloss:1.04203
[160]	train-mlogloss:1.03225	validation-mlogloss:1.04122
[161]	train-mlogloss:1.03129	validation-mlogloss:1.04024
[162]	train-mlogloss:1.03034	validation-mlogloss:1.03927
[163]	train-mlogloss:1.02945	validation-mlogloss:1.03842
[164]	train-mlogloss:1.02861	validation-mlogloss:1.03760
[165]	train-mlogloss:1.02785	validation-mlogloss:1.03693
[166]	train-mlogloss:1.02703	validation-mlogloss:1.03630
[167]	train-mlogloss:1.02620	validation-mlogloss:1.03558
[168]	train-mlogloss:1.02535	validation-mlogloss:1.03476
[169]	train-mlogloss:1.02451	validation-mlogloss:1.03384
[170]	train-mlogloss:1.02370	validation-mlogloss:1.03298
[171]	train-mlogloss:1.02293	validation-mlogloss:1.03251
[172]	train-mlogloss:1.02209	validation-mlogloss:1.03168
[173]	train-mlogloss:1.02138	validation-mlogloss:1.03111
[174]	train-mlogloss:1.02057	validation-mlogloss:1.03039
[175]	train-mlogloss:1.01988	validation-mlogloss:1.02977
[176]	train-mlogloss:1.01902	validation-mlogloss:1.02898
[177]	train-mlogloss:1.01823	validation-mlogloss:1.02845
[178]	train-mlogloss:1.01742	validation-mlogloss:1.02788
[179]	train-mlogloss:1.01663	validation-mlogloss:1.02724
[180]	train-mlogloss:1.01585	validation-mlogloss:1.02640
[181]	train-mlogloss:1.01510	validation-mlogloss:1.02573
[182]	train-mlogloss:1.01441	validation-mlogloss:1.02511
[183]	train-mlogloss:1.01368	validation-mlogloss:1.02437
[184]	train-mlogloss:1.01297	validation-mlogloss:1.02378
[185]	train-mlogloss:1.01226	validation-mlogloss:1.02318
[186]	train-mlogloss:1.01154	validation-mlogloss:1.02266
[187]	train-mlogloss:1.01082	validation-mlogloss:1.02202
[188]	train-mlogloss:1.01010	validation-mlogloss:1.02152
[189]	train-mlogloss:1.00931	validation-mlogloss:1.02066
[190]	train-mlogloss:1.00863	validation-mlogloss:1.02002
[191]	train-mlogloss:1.00798	validation-mlogloss:1.01956
[192]	train-mlogloss:1.00726	validation-mlogloss:1.01899
[193]	train-mlogloss:1.00654	validation-mlogloss:1.01839
[194]	train-mlogloss:1.00594	validation-mlogloss:1.01776
[195]	train-mlogloss:1.00522	validation-mlogloss:1.01732
[196]	train-mlogloss:1.00460	validation-mlogloss:1.01701
[197]	train-mlogloss:1.00390	validation-mlogloss:1.01640
[198]	train-mlogloss:1.00311	validation-mlogloss:1.01578
[199]	train-mlogloss:1.00246	validation-mlogloss:1.01544
[200]	train-mlogloss:1.00187	validation-mlogloss:1.01498
[201]	train-mlogloss:1.00125	validation-mlogloss:1.01449
[202]	train-mlogloss:1.00067	validation-mlogloss:1.01393
[203]	train-mlogloss:1.00004	validation-mlogloss:1.01331
[204]	train-mlogloss:0.99945	validation-mlogloss:1.01289
[205]	train-mlogloss:0.99884	validation-mlogloss:1.01245
[206]	train-mlogloss:0.99822	validation-mlogloss:1.01176
[207]	train-mlogloss:0.99741	validation-mlogloss:1.01128
[208]	train-mlogloss:0.99680	validation-mlogloss:1.01087
[209]	train-mlogloss:0.99611	validation-mlogloss:1.01033
[210]	train-mlogloss:0.99553	validation-mlogloss:1.01004
[211]	train-mlogloss:0.99480	validation-mlogloss:1.00956
[212]	train-mlogloss:0.99423	validation-mlogloss:1.00925
[213]	train-mlogloss:0.99369	validation-mlogloss:1.00870
[214]	train-mlogloss:0.99309	validation-mlogloss:1.00810
[215]	train-mlogloss:0.99243	validation-mlogloss:1.00759
[216]	train-mlogloss:0.99179	validation-mlogloss:1.00702
[217]	train-mlogloss:0.99122	validation-mlogloss:1.00674
[218]	train-mlogloss:0.99066	validation-mlogloss:1.00633
[219]	train-mlogloss:0.99007	validation-mlogloss:1.00593
[220]	train-mlogloss:0.98938	validation-mlogloss:1.00539
[221]	train-mlogloss:0.98872	validation-mlogloss:1.00504
[222]	train-mlogloss:0.98805	validation-mlogloss:1.00461
[223]	train-mlogloss:0.98750	validation-mlogloss:1.00437
[224]	train-mlogloss:0.98692	validation-mlogloss:1.00372
[225]	train-mlogloss:0.98637	validation-mlogloss:1.00334
[226]	train-mlogloss:0.98581	validation-mlogloss:1.00291
[227]	train-mlogloss:0.98520	validation-mlogloss:1.00249
[228]	train-mlogloss:0.98457	validation-mlogloss:1.00206
[229]	train-mlogloss:0.98396	validation-mlogloss:1.00167
[230]	train-mlogloss:0.98338	validation-mlogloss:1.00118
[231]	train-mlogloss:0.98278	validation-mlogloss:1.00088
[232]	train-mlogloss:0.98223	validation-mlogloss:1.00051
[233]	train-mlogloss:0.98176	validation-mlogloss:1.00014
[234]	train-mlogloss:0.98120	validation-mlogloss:0.99982
[235]	train-mlogloss:0.98066	validation-mlogloss:0.99942
[236]	train-mlogloss:0.98012	validation-mlogloss:0.99913
[237]	train-mlogloss:0.97954	validation-mlogloss:0.99861
[238]	train-mlogloss:0.97901	validation-mlogloss:0.99820
[239]	train-mlogloss:0.97841	validation-mlogloss:0.99783
[240]	train-mlogloss:0.97793	validation-mlogloss:0.99745
[241]	train-mlogloss:0.97740	validation-mlogloss:0.99703
[242]	train-mlogloss:0.97677	validation-mlogloss:0.99664
[243]	train-mlogloss:0.97632	validation-mlogloss:0.99631
[244]	train-mlogloss:0.97582	validation-mlogloss:0.99603
[245]	train-mlogloss:0.97526	validation-mlogloss:0.99537
[246]	train-mlogloss:0.97478	validation-mlogloss:0.99507
[247]	train-mlogloss:0.97425	validation-mlogloss:0.99489
[248]	train-mlogloss:0.97374	validation-mlogloss:0.99465
[249]	train-mlogloss:0.97321	validation-mlogloss:0.99431
[250]	train-mlogloss:0.97272	validation-mlogloss:0.99392
[251]	train-mlogloss:0.97212	validation-mlogloss:0.99331
[252]	train-mlogloss:0.97159	validation-mlogloss:0.99281
[253]	train-mlogloss:0.97101	validation-mlogloss:0.99241
[254]	train-mlogloss:0.97047	validation-mlogloss:0.99202
[255]	train-mlogloss:0.96996	validation-mlogloss:0.99149
[256]	train-mlogloss:0.96951	validation-mlogloss:0.99121
[257]	train-mlogloss:0.96913	validation-mlogloss:0.99086
[258]	train-mlogloss:0.96862	validation-mlogloss:0.99060
[259]	train-mlogloss:0.96813	validation-mlogloss:0.99024
[260]	train-mlogloss:0.96766	validation-mlogloss:0.98975
[261]	train-mlogloss:0.96728	validation-mlogloss:0.98950
[262]	train-mlogloss:0.96679	validation-mlogloss:0.98891
[263]	train-mlogloss:0.96631	validation-mlogloss:0.98869
[264]	train-mlogloss:0.96588	validation-mlogloss:0.98835
[265]	train-mlogloss:0.96541	validation-mlogloss:0.98804
[266]	train-mlogloss:0.96494	validation-mlogloss:0.98764
[267]	train-mlogloss:0.96450	validation-mlogloss:0.98713
[268]	train-mlogloss:0.96397	validation-mlogloss:0.98680
[269]	train-mlogloss:0.96357	validation-mlogloss:0.98647
[270]	train-mlogloss:0.96315	validation-mlogloss:0.98619
[271]	train-mlogloss:0.96265	validation-mlogloss:0.98590
[272]	train-mlogloss:0.96220	validation-mlogloss:0.98560
[273]	train-mlogloss:0.96170	validation-mlogloss:0.98517
[274]	train-mlogloss:0.96127	validation-mlogloss:0.98491
[275]	train-mlogloss:0.96081	validation-mlogloss:0.98478
[276]	train-mlogloss:0.96033	validation-mlogloss:0.98455
[277]	train-mlogloss:0.95990	validation-mlogloss:0.98432
[278]	train-mlogloss:0.95949	validation-mlogloss:0.98397
[279]	train-mlogloss:0.95908	validation-mlogloss:0.98363
[280]	train-mlogloss:0.95857	validation-mlogloss:0.98323
[281]	train-mlogloss:0.95815	validation-mlogloss:0.98270
[282]	train-mlogloss:0.95768	validation-mlogloss:0.98237
[283]	train-mlogloss:0.95727	validation-mlogloss:0.98196
[284]	train-mlogloss:0.95675	validation-mlogloss:0.98163
[285]	train-mlogloss:0.95632	validation-mlogloss:0.98140
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[582]	train-mlogloss:0.88627	validation-mlogloss:0.93982
[583]	train-mlogloss:0.88620	validation-mlogloss:0.93973
[584]	train-mlogloss:0.88611	validation-mlogloss:0.93963
[585]	train-mlogloss:0.88590	validation-mlogloss:0.93947
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[598]	train-mlogloss:0.88458	validation-mlogloss:0.93864
[599]	train-mlogloss:0.88451	validation-mlogloss:0.93860
[600]	train-mlogloss:0.88446	validation-mlogloss:0.93859
[601]	train-mlogloss:0.88440	validation-mlogloss:0.93855
[602]	train-mlogloss:0.88433	validation-mlogloss:0.93850
[603]	train-mlogloss:0.88419	validation-mlogloss:0.93844
[604]	train-mlogloss:0.88408	validation-mlogloss:0.93843
[605]	train-mlogloss:0.88398	validation-mlogloss:0.93834
[606]	train-mlogloss:0.88392	validation-mlogloss:0.93831
[607]	train-mlogloss:0.88382	validation-mlogloss:0.93828
[608]	train-mlogloss:0.88376	validation-mlogloss:0.93826
[609]	train-mlogloss:0.88370	validation-mlogloss:0.93823
[610]	train-mlogloss:0.88355	validation-mlogloss:0.93814
[611]	train-mlogloss:0.88349	validation-mlogloss:0.93807
[612]	train-mlogloss:0.88333	validation-mlogloss:0.93795
[613]	train-mlogloss:0.88325	validation-mlogloss:0.93791
[614]	train-mlogloss:0.88317	validation-mlogloss:0.93786
[615]	train-mlogloss:0.88311	validation-mlogloss:0.93786
[616]	train-mlogloss:0.88303	validation-mlogloss:0.93779
[617]	train-mlogloss:0.88297	validation-mlogloss:0.93773
[618]	train-mlogloss:0.88290	validation-mlogloss:0.93768
[619]	train-mlogloss:0.88285	validation-mlogloss:0.93766
[620]	train-mlogloss:0.88274	validation-mlogloss:0.93768
[621]	train-mlogloss:0.88266	validation-mlogloss:0.93761
[622]	train-mlogloss:0.88257	validation-mlogloss:0.93769
[623]	train-mlogloss:0.88253	validation-mlogloss:0.93769
[624]	train-mlogloss:0.88249	validation-mlogloss:0.93769
[625]	train-mlogloss:0.88241	validation-mlogloss:0.93766
[626]	train-mlogloss:0.88232	validation-mlogloss:0.93757
[627]	train-mlogloss:0.88223	validation-mlogloss:0.93750
[628]	train-mlogloss:0.88215	validation-mlogloss:0.93743
[629]	train-mlogloss:0.88202	validation-mlogloss:0.93736
[630]	train-mlogloss:0.88197	validation-mlogloss:0.93738
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[632]	train-mlogloss:0.88185	validation-mlogloss:0.93735
[633]	train-mlogloss:0.88183	validation-mlogloss:0.93733
[634]	train-mlogloss:0.88174	validation-mlogloss:0.93727
[635]	train-mlogloss:0.88166	validation-mlogloss:0.93723
[636]	train-mlogloss:0.88157	validation-mlogloss:0.93714
[637]	train-mlogloss:0.88149	validation-mlogloss:0.93707
[638]	train-mlogloss:0.88144	validation-mlogloss:0.93704
[639]	train-mlogloss:0.88136	validation-mlogloss:0.93704
[640]	train-mlogloss:0.88120	validation-mlogloss:0.93693
[641]	train-mlogloss:0.88111	validation-mlogloss:0.93681
[642]	train-mlogloss:0.88105	validation-mlogloss:0.93676
[643]	train-mlogloss:0.88093	validation-mlogloss:0.93668
[644]	train-mlogloss:0.88084	validation-mlogloss:0.93662
[645]	train-mlogloss:0.88075	validation-mlogloss:0.93662
[646]	train-mlogloss:0.88068	validation-mlogloss:0.93655
[647]	train-mlogloss:0.88054	validation-mlogloss:0.93652
[648]	train-mlogloss:0.88049	validation-mlogloss:0.93645
[649]	train-mlogloss:0.88042	validation-mlogloss:0.93642
[650]	train-mlogloss:0.88035	validation-mlogloss:0.93640
[651]	train-mlogloss:0.88029	validation-mlogloss:0.93635
[652]	train-mlogloss:0.88015	validation-mlogloss:0.93628
[653]	train-mlogloss:0.88008	validation-mlogloss:0.93622
[654]	train-mlogloss:0.87999	validation-mlogloss:0.93618
[655]	train-mlogloss:0.87993	validation-mlogloss:0.93612
[656]	train-mlogloss:0.87988	validation-mlogloss:0.93608
[657]	train-mlogloss:0.87979	validation-mlogloss:0.93598
[658]	train-mlogloss:0.87973	validation-mlogloss:0.93592
[659]	train-mlogloss:0.87959	validation-mlogloss:0.93587
[660]	train-mlogloss:0.87955	validation-mlogloss:0.93584
[661]	train-mlogloss:0.87949	validation-mlogloss:0.93576
[662]	train-mlogloss:0.87941	validation-mlogloss:0.93569
[663]	train-mlogloss:0.87934	validation-mlogloss:0.93566
[664]	train-mlogloss:0.87928	validation-mlogloss:0.93561
[665]	train-mlogloss:0.87918	validation-mlogloss:0.93552
[666]	train-mlogloss:0.87911	validation-mlogloss:0.93550
[667]	train-mlogloss:0.87904	validation-mlogloss:0.93550
[668]	train-mlogloss:0.87902	validation-mlogloss:0.93548
[669]	train-mlogloss:0.87897	validation-mlogloss:0.93549
[670]	train-mlogloss:0.87887	validation-mlogloss:0.93541
[671]	train-mlogloss:0.87880	validation-mlogloss:0.93537
[672]	train-mlogloss:0.87878	validation-mlogloss:0.93536
[673]	train-mlogloss:0.87871	validation-mlogloss:0.93525
[674]	train-mlogloss:0.87863	validation-mlogloss:0.93521
[675]	train-mlogloss:0.87858	validation-mlogloss:0.93518
[676]	train-mlogloss:0.87853	validation-mlogloss:0.93519
[677]	train-mlogloss:0.87847	validation-mlogloss:0.93515
[678]	train-mlogloss:0.87843	validation-mlogloss:0.93510
[679]	train-mlogloss:0.87837	validation-mlogloss:0.93508
[680]	train-mlogloss:0.87832	validation-mlogloss:0.93505
[681]	train-mlogloss:0.87819	validation-mlogloss:0.93500
[682]	train-mlogloss:0.87814	validation-mlogloss:0.93499
[683]	train-mlogloss:0.87805	validation-mlogloss:0.93488
[684]	train-mlogloss:0.87799	validation-mlogloss:0.93485
[685]	train-mlogloss:0.87788	validation-mlogloss:0.93478
[686]	train-mlogloss:0.87783	validation-mlogloss:0.93478
[687]	train-mlogloss:0.87774	validation-mlogloss:0.93476
[688]	train-mlogloss:0.87761	validation-mlogloss:0.93467
[689]	train-mlogloss:0.87751	validation-mlogloss:0.93456
[690]	train-mlogloss:0.87739	validation-mlogloss:0.93448
[691]	train-mlogloss:0.87730	validation-mlogloss:0.93446
[692]	train-mlogloss:0.87725	validation-mlogloss:0.93445
[693]	train-mlogloss:0.87720	validation-mlogloss:0.93445
[694]	train-mlogloss:0.87714	validation-mlogloss:0.93437
[695]	train-mlogloss:0.87709	validation-mlogloss:0.93430
[696]	train-mlogloss:0.87702	validation-mlogloss:0.93422
[697]	train-mlogloss:0.87698	validation-mlogloss:0.93423
[698]	train-mlogloss:0.87688	validation-mlogloss:0.93424
[699]	train-mlogloss:0.87682	validation-mlogloss:0.93421
[700]	train-mlogloss:0.87672	validation-mlogloss:0.93417
[701]	train-mlogloss:0.87668	validation-mlogloss:0.93416
[702]	train-mlogloss:0.87661	validation-mlogloss:0.93411
[703]	train-mlogloss:0.87654	validation-mlogloss:0.93410
[704]	train-mlogloss:0.87648	validation-mlogloss:0.93408
[705]	train-mlogloss:0.87641	validation-mlogloss:0.93406
[706]	train-mlogloss:0.87635	validation-mlogloss:0.93402
[707]	train-mlogloss:0.87628	validation-mlogloss:0.93397
[708]	train-mlogloss:0.87626	validation-mlogloss:0.93396
[709]	train-mlogloss:0.87614	validation-mlogloss:0.93391
[710]	train-mlogloss:0.87605	validation-mlogloss:0.93384
[711]	train-mlogloss:0.87596	validation-mlogloss:0.93380
[712]	train-mlogloss:0.87590	validation-mlogloss:0.93376
[713]	train-mlogloss:0.87582	validation-mlogloss:0.93368
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[1 2 1 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 64.01 [%]
Global accuracy score (test) = 60.06 [%]
Global F1 score (train) = 64.1 [%]
Global F1 score (test) = 60.82 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.46      0.45      0.45       400
MODERATE-INTENSITY       0.53      0.65      0.58       400
         SEDENTARY       0.66      0.69      0.68       400
VIGOROUS-INTENSITY       0.86      0.62      0.72       345

          accuracy                           0.60      1545
         macro avg       0.63      0.60      0.61      1545
      weighted avg       0.62      0.60      0.60      1545


Accuracy capturado en la ejecución 12: 60.06 [%]
F1-score capturado en la ejecución 12: 60.82 [%]

=== EJECUCIÓN 13 ===

--- TRAIN (ejecución 13) ---

--- TEST (ejecución 13) ---
2025-11-04 11:02:10.397061: 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`.
2025-11-04 11:02:10.408565: 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 00:00:1762250530.422022 1080993 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250530.426223 1080993 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250530.436092 1080993 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250530.436110 1080993 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250530.436111 1080993 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250530.436113 1080993 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:02:10.439215: 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:1.38111	validation-mlogloss:1.38090
[1]	train-mlogloss:1.37600	validation-mlogloss:1.37576
[2]	train-mlogloss:1.37091	validation-mlogloss:1.37051
[3]	train-mlogloss:1.36593	validation-mlogloss:1.36534
[4]	train-mlogloss:1.36063	validation-mlogloss:1.35961
[5]	train-mlogloss:1.35585	validation-mlogloss:1.35468
[6]	train-mlogloss:1.35121	validation-mlogloss:1.34994
[7]	train-mlogloss:1.34655	validation-mlogloss:1.34511
[8]	train-mlogloss:1.34222	validation-mlogloss:1.34042
[9]	train-mlogloss:1.33784	validation-mlogloss:1.33588
[10]	train-mlogloss:1.33349	validation-mlogloss:1.33129
[11]	train-mlogloss:1.32918	validation-mlogloss:1.32672
[12]	train-mlogloss:1.32482	validation-mlogloss:1.32209
[13]	train-mlogloss:1.32070	validation-mlogloss:1.31779
[14]	train-mlogloss:1.31657	validation-mlogloss:1.31357
[15]	train-mlogloss:1.31207	validation-mlogloss:1.30903
[16]	train-mlogloss:1.30811	validation-mlogloss:1.30500
[17]	train-mlogloss:1.30428	validation-mlogloss:1.30117
[18]	train-mlogloss:1.30041	validation-mlogloss:1.29740
[19]	train-mlogloss:1.29673	validation-mlogloss:1.29323
[20]	train-mlogloss:1.29297	validation-mlogloss:1.28948
[21]	train-mlogloss:1.28930	validation-mlogloss:1.28565
[22]	train-mlogloss:1.28560	validation-mlogloss:1.28171
[23]	train-mlogloss:1.28199	validation-mlogloss:1.27794
[24]	train-mlogloss:1.27847	validation-mlogloss:1.27421
[25]	train-mlogloss:1.27504	validation-mlogloss:1.27074
[26]	train-mlogloss:1.27166	validation-mlogloss:1.26713
[27]	train-mlogloss:1.26831	validation-mlogloss:1.26376
[28]	train-mlogloss:1.26495	validation-mlogloss:1.26046
[29]	train-mlogloss:1.26183	validation-mlogloss:1.25734
[30]	train-mlogloss:1.25809	validation-mlogloss:1.25327
[31]	train-mlogloss:1.25496	validation-mlogloss:1.24990
[32]	train-mlogloss:1.25168	validation-mlogloss:1.24629
[33]	train-mlogloss:1.24864	validation-mlogloss:1.24311
[34]	train-mlogloss:1.24553	validation-mlogloss:1.23978
[35]	train-mlogloss:1.24255	validation-mlogloss:1.23668
[36]	train-mlogloss:1.23952	validation-mlogloss:1.23350
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[630]	train-mlogloss:0.88424	validation-mlogloss:0.92651
[631]	train-mlogloss:0.88415	validation-mlogloss:0.92641
[632]	train-mlogloss:0.88408	validation-mlogloss:0.92633
[633]	train-mlogloss:0.88403	validation-mlogloss:0.92625
[634]	train-mlogloss:0.88395	validation-mlogloss:0.92622
[635]	train-mlogloss:0.88387	validation-mlogloss:0.92617
[636]	train-mlogloss:0.88373	validation-mlogloss:0.92616
[637]	train-mlogloss:0.88367	validation-mlogloss:0.92613
[638]	train-mlogloss:0.88359	validation-mlogloss:0.92611
[639]	train-mlogloss:0.88351	validation-mlogloss:0.92608
[640]	train-mlogloss:0.88339	validation-mlogloss:0.92611
[641]	train-mlogloss:0.88331	validation-mlogloss:0.92608
[642]	train-mlogloss:0.88326	validation-mlogloss:0.92610
[643]	train-mlogloss:0.88321	validation-mlogloss:0.92608
[644]	train-mlogloss:0.88312	validation-mlogloss:0.92612
[645]	train-mlogloss:0.88306	validation-mlogloss:0.92608
[646]	train-mlogloss:0.88291	validation-mlogloss:0.92603
[647]	train-mlogloss:0.88283	validation-mlogloss:0.92601
[648]	train-mlogloss:0.88275	validation-mlogloss:0.92594
[649]	train-mlogloss:0.88270	validation-mlogloss:0.92588
[650]	train-mlogloss:0.88264	validation-mlogloss:0.92581
[651]	train-mlogloss:0.88258	validation-mlogloss:0.92578
[652]	train-mlogloss:0.88248	validation-mlogloss:0.92577
[653]	train-mlogloss:0.88236	validation-mlogloss:0.92567
[654]	train-mlogloss:0.88231	validation-mlogloss:0.92567
[655]	train-mlogloss:0.88223	validation-mlogloss:0.92562
[656]	train-mlogloss:0.88218	validation-mlogloss:0.92563
[657]	train-mlogloss:0.88206	validation-mlogloss:0.92551
[658]	train-mlogloss:0.88197	validation-mlogloss:0.92545
[659]	train-mlogloss:0.88189	validation-mlogloss:0.92538
[660]	train-mlogloss:0.88179	validation-mlogloss:0.92544
[661]	train-mlogloss:0.88170	validation-mlogloss:0.92546
[662]	train-mlogloss:0.88163	validation-mlogloss:0.92541
[663]	train-mlogloss:0.88148	validation-mlogloss:0.92533
[664]	train-mlogloss:0.88131	validation-mlogloss:0.92522
[665]	train-mlogloss:0.88126	validation-mlogloss:0.92515
[666]	train-mlogloss:0.88112	validation-mlogloss:0.92510
[667]	train-mlogloss:0.88106	validation-mlogloss:0.92502
[668]	train-mlogloss:0.88102	validation-mlogloss:0.92499
[669]	train-mlogloss:0.88094	validation-mlogloss:0.92498
[670]	train-mlogloss:0.88087	validation-mlogloss:0.92490
[671]	train-mlogloss:0.88079	validation-mlogloss:0.92484
[672]	train-mlogloss:0.88074	validation-mlogloss:0.92483
[673]	train-mlogloss:0.88068	validation-mlogloss:0.92477
[674]	train-mlogloss:0.88060	validation-mlogloss:0.92473
[675]	train-mlogloss:0.88048	validation-mlogloss:0.92463
[676]	train-mlogloss:0.88041	validation-mlogloss:0.92461
[677]	train-mlogloss:0.88033	validation-mlogloss:0.92458
[678]	train-mlogloss:0.88028	validation-mlogloss:0.92460
[679]	train-mlogloss:0.88023	validation-mlogloss:0.92453
[680]	train-mlogloss:0.88018	validation-mlogloss:0.92453
[681]	train-mlogloss:0.88014	validation-mlogloss:0.92453
[682]	train-mlogloss:0.88007	validation-mlogloss:0.92454
[683]	train-mlogloss:0.88002	validation-mlogloss:0.92447
[684]	train-mlogloss:0.87994	validation-mlogloss:0.92440
[685]	train-mlogloss:0.87983	validation-mlogloss:0.92431
[686]	train-mlogloss:0.87970	validation-mlogloss:0.92417
[687]	train-mlogloss:0.87968	validation-mlogloss:0.92416
[688]	train-mlogloss:0.87961	validation-mlogloss:0.92414
[689]	train-mlogloss:0.87946	validation-mlogloss:0.92414
[690]	train-mlogloss:0.87939	validation-mlogloss:0.92407
[691]	train-mlogloss:0.87935	validation-mlogloss:0.92407
[692]	train-mlogloss:0.87927	validation-mlogloss:0.92402
[693]	train-mlogloss:0.87922	validation-mlogloss:0.92402
[694]	train-mlogloss:0.87913	validation-mlogloss:0.92396
[695]	train-mlogloss:0.87904	validation-mlogloss:0.92389
[696]	train-mlogloss:0.87890	validation-mlogloss:0.92381
[697]	train-mlogloss:0.87884	validation-mlogloss:0.92377
[698]	train-mlogloss:0.87880	validation-mlogloss:0.92377
[699]	train-mlogloss:0.87873	validation-mlogloss:0.92375
[700]	train-mlogloss:0.87865	validation-mlogloss:0.92370
[701]	train-mlogloss:0.87858	validation-mlogloss:0.92369
[702]	train-mlogloss:0.87851	validation-mlogloss:0.92369
[703]	train-mlogloss:0.87838	validation-mlogloss:0.92369
[704]	train-mlogloss:0.87821	validation-mlogloss:0.92360
[705]	train-mlogloss:0.87816	validation-mlogloss:0.92354
[706]	train-mlogloss:0.87810	validation-mlogloss:0.92351
[707]	train-mlogloss:0.87805	validation-mlogloss:0.92352
[708]	train-mlogloss:0.87800	validation-mlogloss:0.92345
[709]	train-mlogloss:0.87798	validation-mlogloss:0.92345
[710]	train-mlogloss:0.87793	validation-mlogloss:0.92344
[711]	train-mlogloss:0.87789	validation-mlogloss:0.92340
[712]	train-mlogloss:0.87779	validation-mlogloss:0.92331
[713]	train-mlogloss:0.87775	validation-mlogloss:0.92329
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.58 [%]
Global accuracy score (test) = 61.1 [%]
Global F1 score (train) = 63.73 [%]
Global F1 score (test) = 61.9 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.47      0.49      0.48       400
MODERATE-INTENSITY       0.54      0.62      0.58       400
         SEDENTARY       0.68      0.72      0.70       400
VIGOROUS-INTENSITY       0.87      0.62      0.72       345

          accuracy                           0.61      1545
         macro avg       0.64      0.61      0.62      1545
      weighted avg       0.63      0.61      0.62      1545


Accuracy capturado en la ejecución 13: 61.1 [%]
F1-score capturado en la ejecución 13: 61.9 [%]

=== EJECUCIÓN 14 ===

--- TRAIN (ejecución 14) ---

--- TEST (ejecución 14) ---
2025-11-04 11:02:27.367074: 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`.
2025-11-04 11:02:27.378441: 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 00:00:1762250547.391562 1081330 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250547.395570 1081330 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250547.405649 1081330 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250547.405670 1081330 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250547.405671 1081330 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250547.405673 1081330 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:02:27.408832: 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:1.38121	validation-mlogloss:1.38107
[1]	train-mlogloss:1.37615	validation-mlogloss:1.37574
[2]	train-mlogloss:1.37122	validation-mlogloss:1.37072
[3]	train-mlogloss:1.36628	validation-mlogloss:1.36554
[4]	train-mlogloss:1.36145	validation-mlogloss:1.36057
[5]	train-mlogloss:1.35670	validation-mlogloss:1.35572
[6]	train-mlogloss:1.35207	validation-mlogloss:1.35053
[7]	train-mlogloss:1.34755	validation-mlogloss:1.34589
[8]	train-mlogloss:1.34316	validation-mlogloss:1.34147
[9]	train-mlogloss:1.33836	validation-mlogloss:1.33635
[10]	train-mlogloss:1.33385	validation-mlogloss:1.33155
[11]	train-mlogloss:1.32961	validation-mlogloss:1.32712
[12]	train-mlogloss:1.32529	validation-mlogloss:1.32248
[13]	train-mlogloss:1.32119	validation-mlogloss:1.31801
[14]	train-mlogloss:1.31701	validation-mlogloss:1.31364
[15]	train-mlogloss:1.31301	validation-mlogloss:1.30928
[16]	train-mlogloss:1.30912	validation-mlogloss:1.30477
[17]	train-mlogloss:1.30539	validation-mlogloss:1.30097
[18]	train-mlogloss:1.30154	validation-mlogloss:1.29710
[19]	train-mlogloss:1.29781	validation-mlogloss:1.29310
[20]	train-mlogloss:1.29370	validation-mlogloss:1.28864
[21]	train-mlogloss:1.29008	validation-mlogloss:1.28500
[22]	train-mlogloss:1.28643	validation-mlogloss:1.28109
[23]	train-mlogloss:1.28292	validation-mlogloss:1.27746
[24]	train-mlogloss:1.27943	validation-mlogloss:1.27386
[25]	train-mlogloss:1.27597	validation-mlogloss:1.27014
[26]	train-mlogloss:1.27249	validation-mlogloss:1.26636
[27]	train-mlogloss:1.26922	validation-mlogloss:1.26322
[28]	train-mlogloss:1.26578	validation-mlogloss:1.25942
[29]	train-mlogloss:1.26251	validation-mlogloss:1.25609
[30]	train-mlogloss:1.25882	validation-mlogloss:1.25208
[31]	train-mlogloss:1.25556	validation-mlogloss:1.24849
[32]	train-mlogloss:1.25245	validation-mlogloss:1.24521
[33]	train-mlogloss:1.24884	validation-mlogloss:1.24145
[34]	train-mlogloss:1.24575	validation-mlogloss:1.23808
[35]	train-mlogloss:1.24272	validation-mlogloss:1.23522
[36]	train-mlogloss:1.23974	validation-mlogloss:1.23192
[37]	train-mlogloss:1.23675	validation-mlogloss:1.22866
[38]	train-mlogloss:1.23351	validation-mlogloss:1.22504
[39]	train-mlogloss:1.23061	validation-mlogloss:1.22197
[40]	train-mlogloss:1.22740	validation-mlogloss:1.21890
[41]	train-mlogloss:1.22466	validation-mlogloss:1.21586
[42]	train-mlogloss:1.22191	validation-mlogloss:1.21313
[43]	train-mlogloss:1.21886	validation-mlogloss:1.20996
[44]	train-mlogloss:1.21628	validation-mlogloss:1.20716
[45]	train-mlogloss:1.21365	validation-mlogloss:1.20470
[46]	train-mlogloss:1.21107	validation-mlogloss:1.20226
[47]	train-mlogloss:1.20846	validation-mlogloss:1.19936
[48]	train-mlogloss:1.20600	validation-mlogloss:1.19688
[49]	train-mlogloss:1.20371	validation-mlogloss:1.19476
[50]	train-mlogloss:1.20131	validation-mlogloss:1.19222
[51]	train-mlogloss:1.19902	validation-mlogloss:1.19013
[52]	train-mlogloss:1.19668	validation-mlogloss:1.18758
[53]	train-mlogloss:1.19434	validation-mlogloss:1.18518
[54]	train-mlogloss:1.19191	validation-mlogloss:1.18247
[55]	train-mlogloss:1.18965	validation-mlogloss:1.18013
[56]	train-mlogloss:1.18742	validation-mlogloss:1.17780
[57]	train-mlogloss:1.18515	validation-mlogloss:1.17547
[58]	train-mlogloss:1.18295	validation-mlogloss:1.17320
[59]	train-mlogloss:1.18066	validation-mlogloss:1.17084
[60]	train-mlogloss:1.17853	validation-mlogloss:1.16866
[61]	train-mlogloss:1.17627	validation-mlogloss:1.16643
[62]	train-mlogloss:1.17419	validation-mlogloss:1.16431
[63]	train-mlogloss:1.17190	validation-mlogloss:1.16195
[64]	train-mlogloss:1.16988	validation-mlogloss:1.15979
[65]	train-mlogloss:1.16775	validation-mlogloss:1.15777
[66]	train-mlogloss:1.16541	validation-mlogloss:1.15534
[67]	train-mlogloss:1.16346	validation-mlogloss:1.15326
[68]	train-mlogloss:1.16108	validation-mlogloss:1.15085
[69]	train-mlogloss:1.15916	validation-mlogloss:1.14894
[70]	train-mlogloss:1.15716	validation-mlogloss:1.14714
[71]	train-mlogloss:1.15497	validation-mlogloss:1.14519
[72]	train-mlogloss:1.15300	validation-mlogloss:1.14327
[73]	train-mlogloss:1.15079	validation-mlogloss:1.14084
[74]	train-mlogloss:1.14889	validation-mlogloss:1.13905
[75]	train-mlogloss:1.14711	validation-mlogloss:1.13713
[76]	train-mlogloss:1.14516	validation-mlogloss:1.13496
[77]	train-mlogloss:1.14325	validation-mlogloss:1.13310
[78]	train-mlogloss:1.14131	validation-mlogloss:1.13102
[79]	train-mlogloss:1.13948	validation-mlogloss:1.12918
[80]	train-mlogloss:1.13773	validation-mlogloss:1.12737
[81]	train-mlogloss:1.13569	validation-mlogloss:1.12560
[82]	train-mlogloss:1.13391	validation-mlogloss:1.12376
[83]	train-mlogloss:1.13215	validation-mlogloss:1.12181
[84]	train-mlogloss:1.13054	validation-mlogloss:1.12026
[85]	train-mlogloss:1.12879	validation-mlogloss:1.11855
[86]	train-mlogloss:1.12693	validation-mlogloss:1.11657
[87]	train-mlogloss:1.12531	validation-mlogloss:1.11506
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[678]	train-mlogloss:0.88350	validation-mlogloss:0.91818
[679]	train-mlogloss:0.88338	validation-mlogloss:0.91815
[680]	train-mlogloss:0.88336	validation-mlogloss:0.91815
[681]	train-mlogloss:0.88329	validation-mlogloss:0.91810
[682]	train-mlogloss:0.88314	validation-mlogloss:0.91803
[683]	train-mlogloss:0.88306	validation-mlogloss:0.91791
[684]	train-mlogloss:0.88299	validation-mlogloss:0.91792
[685]	train-mlogloss:0.88292	validation-mlogloss:0.91787
[686]	train-mlogloss:0.88287	validation-mlogloss:0.91787
[687]	train-mlogloss:0.88276	validation-mlogloss:0.91780
[688]	train-mlogloss:0.88269	validation-mlogloss:0.91774
[689]	train-mlogloss:0.88264	validation-mlogloss:0.91767
[690]	train-mlogloss:0.88257	validation-mlogloss:0.91761
[691]	train-mlogloss:0.88255	validation-mlogloss:0.91760
[692]	train-mlogloss:0.88242	validation-mlogloss:0.91753
[693]	train-mlogloss:0.88238	validation-mlogloss:0.91751
[694]	train-mlogloss:0.88234	validation-mlogloss:0.91744
[695]	train-mlogloss:0.88228	validation-mlogloss:0.91740
[696]	train-mlogloss:0.88221	validation-mlogloss:0.91737
[697]	train-mlogloss:0.88219	validation-mlogloss:0.91736
[698]	train-mlogloss:0.88209	validation-mlogloss:0.91731
[699]	train-mlogloss:0.88199	validation-mlogloss:0.91726
[700]	train-mlogloss:0.88195	validation-mlogloss:0.91722
[701]	train-mlogloss:0.88183	validation-mlogloss:0.91715
[702]	train-mlogloss:0.88181	validation-mlogloss:0.91714
[703]	train-mlogloss:0.88174	validation-mlogloss:0.91709
[704]	train-mlogloss:0.88169	validation-mlogloss:0.91704
[705]	train-mlogloss:0.88167	validation-mlogloss:0.91702
[706]	train-mlogloss:0.88165	validation-mlogloss:0.91701
[707]	train-mlogloss:0.88160	validation-mlogloss:0.91701
[708]	train-mlogloss:0.88160	validation-mlogloss:0.91701
[709]	train-mlogloss:0.88156	validation-mlogloss:0.91697
[710]	train-mlogloss:0.88151	validation-mlogloss:0.91697
[711]	train-mlogloss:0.88144	validation-mlogloss:0.91698
[712]	train-mlogloss:0.88131	validation-mlogloss:0.91686
[713]	train-mlogloss:0.88120	validation-mlogloss:0.91671
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 1 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.32 [%]
Global accuracy score (test) = 61.49 [%]
Global F1 score (train) = 63.55 [%]
Global F1 score (test) = 62.27 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.46      0.51      0.49       400
MODERATE-INTENSITY       0.58      0.60      0.59       400
         SEDENTARY       0.66      0.73      0.70       400
VIGOROUS-INTENSITY       0.87      0.62      0.72       345

          accuracy                           0.61      1545
         macro avg       0.64      0.61      0.62      1545
      weighted avg       0.63      0.61      0.62      1545


Accuracy capturado en la ejecución 14: 61.49 [%]
F1-score capturado en la ejecución 14: 62.27 [%]

=== EJECUCIÓN 15 ===

--- TRAIN (ejecución 15) ---

--- TEST (ejecución 15) ---
2025-11-04 11:02:44.392269: 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`.
2025-11-04 11:02:44.403520: 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 00:00:1762250564.416534 1081639 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250564.420642 1081639 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250564.430450 1081639 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250564.430467 1081639 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250564.430468 1081639 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250564.430470 1081639 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:02:44.433615: 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:1.38096	validation-mlogloss:1.38101
[1]	train-mlogloss:1.37591	validation-mlogloss:1.37588
[2]	train-mlogloss:1.37080	validation-mlogloss:1.37073
[3]	train-mlogloss:1.36591	validation-mlogloss:1.36578
[4]	train-mlogloss:1.36105	validation-mlogloss:1.36071
[5]	train-mlogloss:1.35617	validation-mlogloss:1.35565
[6]	train-mlogloss:1.35141	validation-mlogloss:1.35071
[7]	train-mlogloss:1.34682	validation-mlogloss:1.34601
[8]	train-mlogloss:1.34219	validation-mlogloss:1.34133
[9]	train-mlogloss:1.33768	validation-mlogloss:1.33678
[10]	train-mlogloss:1.33324	validation-mlogloss:1.33219
[11]	train-mlogloss:1.32871	validation-mlogloss:1.32746
[12]	train-mlogloss:1.32444	validation-mlogloss:1.32329
[13]	train-mlogloss:1.32026	validation-mlogloss:1.31907
[14]	train-mlogloss:1.31618	validation-mlogloss:1.31507
[15]	train-mlogloss:1.31207	validation-mlogloss:1.31090
[16]	train-mlogloss:1.30807	validation-mlogloss:1.30705
[17]	train-mlogloss:1.30394	validation-mlogloss:1.30278
[18]	train-mlogloss:1.30007	validation-mlogloss:1.29862
[19]	train-mlogloss:1.29623	validation-mlogloss:1.29472
[20]	train-mlogloss:1.29247	validation-mlogloss:1.29093
[21]	train-mlogloss:1.28857	validation-mlogloss:1.28693
[22]	train-mlogloss:1.28451	validation-mlogloss:1.28244
[23]	train-mlogloss:1.28086	validation-mlogloss:1.27899
[24]	train-mlogloss:1.27727	validation-mlogloss:1.27539
[25]	train-mlogloss:1.27367	validation-mlogloss:1.27162
[26]	train-mlogloss:1.27019	validation-mlogloss:1.26823
[27]	train-mlogloss:1.26705	validation-mlogloss:1.26517
[28]	train-mlogloss:1.26371	validation-mlogloss:1.26170
[29]	train-mlogloss:1.26039	validation-mlogloss:1.25839
[30]	train-mlogloss:1.25673	validation-mlogloss:1.25458
[31]	train-mlogloss:1.25309	validation-mlogloss:1.25066
[32]	train-mlogloss:1.24990	validation-mlogloss:1.24738
[33]	train-mlogloss:1.24677	validation-mlogloss:1.24434
[34]	train-mlogloss:1.24370	validation-mlogloss:1.24110
[35]	train-mlogloss:1.24060	validation-mlogloss:1.23808
[36]	train-mlogloss:1.23756	validation-mlogloss:1.23494
[37]	train-mlogloss:1.23456	validation-mlogloss:1.23194
[38]	train-mlogloss:1.23173	validation-mlogloss:1.22909
[39]	train-mlogloss:1.22879	validation-mlogloss:1.22615
[40]	train-mlogloss:1.22611	validation-mlogloss:1.22345
[41]	train-mlogloss:1.22318	validation-mlogloss:1.22031
[42]	train-mlogloss:1.22044	validation-mlogloss:1.21761
[43]	train-mlogloss:1.21774	validation-mlogloss:1.21518
[44]	train-mlogloss:1.21503	validation-mlogloss:1.21248
[45]	train-mlogloss:1.21190	validation-mlogloss:1.20916
[46]	train-mlogloss:1.20883	validation-mlogloss:1.20607
[47]	train-mlogloss:1.20582	validation-mlogloss:1.20280
[48]	train-mlogloss:1.20331	validation-mlogloss:1.20053
[49]	train-mlogloss:1.20089	validation-mlogloss:1.19819
[50]	train-mlogloss:1.19827	validation-mlogloss:1.19542
[51]	train-mlogloss:1.19574	validation-mlogloss:1.19266
[52]	train-mlogloss:1.19331	validation-mlogloss:1.19039
[53]	train-mlogloss:1.19085	validation-mlogloss:1.18778
[54]	train-mlogloss:1.18821	validation-mlogloss:1.18539
[55]	train-mlogloss:1.18587	validation-mlogloss:1.18307
[56]	train-mlogloss:1.18352	validation-mlogloss:1.18083
[57]	train-mlogloss:1.18127	validation-mlogloss:1.17860
[58]	train-mlogloss:1.17860	validation-mlogloss:1.17588
[59]	train-mlogloss:1.17628	validation-mlogloss:1.17351
[60]	train-mlogloss:1.17406	validation-mlogloss:1.17161
[61]	train-mlogloss:1.17183	validation-mlogloss:1.16919
[62]	train-mlogloss:1.16938	validation-mlogloss:1.16691
[63]	train-mlogloss:1.16700	validation-mlogloss:1.16467
[64]	train-mlogloss:1.16501	validation-mlogloss:1.16261
[65]	train-mlogloss:1.16289	validation-mlogloss:1.16028
[66]	train-mlogloss:1.16076	validation-mlogloss:1.15796
[67]	train-mlogloss:1.15858	validation-mlogloss:1.15586
[68]	train-mlogloss:1.15648	validation-mlogloss:1.15378
[69]	train-mlogloss:1.15415	validation-mlogloss:1.15143
[70]	train-mlogloss:1.15187	validation-mlogloss:1.14907
[71]	train-mlogloss:1.14991	validation-mlogloss:1.14693
[72]	train-mlogloss:1.14781	validation-mlogloss:1.14477
[73]	train-mlogloss:1.14596	validation-mlogloss:1.14299
[74]	train-mlogloss:1.14396	validation-mlogloss:1.14108
[75]	train-mlogloss:1.14207	validation-mlogloss:1.13921
[76]	train-mlogloss:1.14000	validation-mlogloss:1.13738
[77]	train-mlogloss:1.13816	validation-mlogloss:1.13548
[78]	train-mlogloss:1.13633	validation-mlogloss:1.13368
[79]	train-mlogloss:1.13452	validation-mlogloss:1.13189
[80]	train-mlogloss:1.13285	validation-mlogloss:1.13033
[81]	train-mlogloss:1.13079	validation-mlogloss:1.12859
[82]	train-mlogloss:1.12903	validation-mlogloss:1.12669
[83]	train-mlogloss:1.12736	validation-mlogloss:1.12486
[84]	train-mlogloss:1.12561	validation-mlogloss:1.12331
[85]	train-mlogloss:1.12393	validation-mlogloss:1.12159
[86]	train-mlogloss:1.12217	validation-mlogloss:1.11975
[87]	train-mlogloss:1.12041	validation-mlogloss:1.11808
[88]	train-mlogloss:1.11878	validation-mlogloss:1.11635
[89]	train-mlogloss:1.11718	validation-mlogloss:1.11476
[90]	train-mlogloss:1.11559	validation-mlogloss:1.11314
[91]	train-mlogloss:1.11395	validation-mlogloss:1.11152
[92]	train-mlogloss:1.11235	validation-mlogloss:1.10985
[93]	train-mlogloss:1.11083	validation-mlogloss:1.10830
[94]	train-mlogloss:1.10934	validation-mlogloss:1.10676
[95]	train-mlogloss:1.10780	validation-mlogloss:1.10532
[96]	train-mlogloss:1.10621	validation-mlogloss:1.10390
[97]	train-mlogloss:1.10471	validation-mlogloss:1.10255
[98]	train-mlogloss:1.10326	validation-mlogloss:1.10123
[99]	train-mlogloss:1.10178	validation-mlogloss:1.09993
[100]	train-mlogloss:1.10037	validation-mlogloss:1.09853
[101]	train-mlogloss:1.09898	validation-mlogloss:1.09743
[102]	train-mlogloss:1.09756	validation-mlogloss:1.09620
[103]	train-mlogloss:1.09613	validation-mlogloss:1.09486
[104]	train-mlogloss:1.09476	validation-mlogloss:1.09352
[105]	train-mlogloss:1.09355	validation-mlogloss:1.09238
[106]	train-mlogloss:1.09227	validation-mlogloss:1.09118
[107]	train-mlogloss:1.09087	validation-mlogloss:1.09003
[108]	train-mlogloss:1.08946	validation-mlogloss:1.08871
[109]	train-mlogloss:1.08809	validation-mlogloss:1.08769
[110]	train-mlogloss:1.08684	validation-mlogloss:1.08676
[111]	train-mlogloss:1.08546	validation-mlogloss:1.08553
[112]	train-mlogloss:1.08394	validation-mlogloss:1.08443
[113]	train-mlogloss:1.08275	validation-mlogloss:1.08331
[114]	train-mlogloss:1.08139	validation-mlogloss:1.08182
[115]	train-mlogloss:1.08009	validation-mlogloss:1.08065
[116]	train-mlogloss:1.07881	validation-mlogloss:1.07937
[117]	train-mlogloss:1.07771	validation-mlogloss:1.07828
[118]	train-mlogloss:1.07643	validation-mlogloss:1.07711
[119]	train-mlogloss:1.07533	validation-mlogloss:1.07603
[120]	train-mlogloss:1.07423	validation-mlogloss:1.07511
[121]	train-mlogloss:1.07311	validation-mlogloss:1.07417
[122]	train-mlogloss:1.07191	validation-mlogloss:1.07314
[123]	train-mlogloss:1.07064	validation-mlogloss:1.07181
[124]	train-mlogloss:1.06927	validation-mlogloss:1.07074
[125]	train-mlogloss:1.06814	validation-mlogloss:1.06957
[126]	train-mlogloss:1.06695	validation-mlogloss:1.06840
[127]	train-mlogloss:1.06590	validation-mlogloss:1.06729
[128]	train-mlogloss:1.06488	validation-mlogloss:1.06625
[129]	train-mlogloss:1.06373	validation-mlogloss:1.06509
[130]	train-mlogloss:1.06265	validation-mlogloss:1.06404
[131]	train-mlogloss:1.06155	validation-mlogloss:1.06301
[132]	train-mlogloss:1.06051	validation-mlogloss:1.06201
[133]	train-mlogloss:1.05940	validation-mlogloss:1.06090
[134]	train-mlogloss:1.05835	validation-mlogloss:1.05996
[135]	train-mlogloss:1.05732	validation-mlogloss:1.05914
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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)
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 1 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.8 [%]
Global accuracy score (test) = 58.96 [%]
Global F1 score (train) = 63.92 [%]
Global F1 score (test) = 59.6 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.42      0.41      0.41       400
MODERATE-INTENSITY       0.54      0.62      0.58       400
         SEDENTARY       0.64      0.72      0.68       400
VIGOROUS-INTENSITY       0.86      0.62      0.72       345

          accuracy                           0.59      1545
         macro avg       0.61      0.59      0.60      1545
      weighted avg       0.60      0.59      0.59      1545


Accuracy capturado en la ejecución 15: 58.96 [%]
F1-score capturado en la ejecución 15: 59.6 [%]

=== EJECUCIÓN 16 ===

--- TRAIN (ejecución 16) ---

--- TEST (ejecución 16) ---
2025-11-04 11:03:01.521237: 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`.
2025-11-04 11:03:01.533168: 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 00:00:1762250581.547266 1081950 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250581.551657 1081950 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250581.562134 1081950 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250581.562152 1081950 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250581.562153 1081950 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250581.562155 1081950 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:03:01.565491: 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:1.38085	validation-mlogloss:1.38060
[1]	train-mlogloss:1.37577	validation-mlogloss:1.37537
[2]	train-mlogloss:1.37095	validation-mlogloss:1.37053
[3]	train-mlogloss:1.36602	validation-mlogloss:1.36539
[4]	train-mlogloss:1.36109	validation-mlogloss:1.36038
[5]	train-mlogloss:1.35628	validation-mlogloss:1.35555
[6]	train-mlogloss:1.35175	validation-mlogloss:1.35057
[7]	train-mlogloss:1.34718	validation-mlogloss:1.34557
[8]	train-mlogloss:1.34272	validation-mlogloss:1.34098
[9]	train-mlogloss:1.33833	validation-mlogloss:1.33650
[10]	train-mlogloss:1.33399	validation-mlogloss:1.33210
[11]	train-mlogloss:1.32965	validation-mlogloss:1.32750
[12]	train-mlogloss:1.32538	validation-mlogloss:1.32311
[13]	train-mlogloss:1.32120	validation-mlogloss:1.31844
[14]	train-mlogloss:1.31701	validation-mlogloss:1.31384
[15]	train-mlogloss:1.31297	validation-mlogloss:1.30974
[16]	train-mlogloss:1.30902	validation-mlogloss:1.30547
[17]	train-mlogloss:1.30507	validation-mlogloss:1.30140
[18]	train-mlogloss:1.30125	validation-mlogloss:1.29757
[19]	train-mlogloss:1.29752	validation-mlogloss:1.29368
[20]	train-mlogloss:1.29374	validation-mlogloss:1.28996
[21]	train-mlogloss:1.29003	validation-mlogloss:1.28612
[22]	train-mlogloss:1.28648	validation-mlogloss:1.28243
[23]	train-mlogloss:1.28289	validation-mlogloss:1.27849
[24]	train-mlogloss:1.27941	validation-mlogloss:1.27473
[25]	train-mlogloss:1.27593	validation-mlogloss:1.27114
[26]	train-mlogloss:1.27245	validation-mlogloss:1.26760
[27]	train-mlogloss:1.26905	validation-mlogloss:1.26405
[28]	train-mlogloss:1.26566	validation-mlogloss:1.26072
[29]	train-mlogloss:1.26244	validation-mlogloss:1.25753
[30]	train-mlogloss:1.25921	validation-mlogloss:1.25398
[31]	train-mlogloss:1.25581	validation-mlogloss:1.25010
[32]	train-mlogloss:1.25258	validation-mlogloss:1.24691
[33]	train-mlogloss:1.24953	validation-mlogloss:1.24383
[34]	train-mlogloss:1.24653	validation-mlogloss:1.24075
[35]	train-mlogloss:1.24349	validation-mlogloss:1.23747
[36]	train-mlogloss:1.24045	validation-mlogloss:1.23423
[37]	train-mlogloss:1.23751	validation-mlogloss:1.23112
[38]	train-mlogloss:1.23467	validation-mlogloss:1.22780
[39]	train-mlogloss:1.23187	validation-mlogloss:1.22501
[40]	train-mlogloss:1.22892	validation-mlogloss:1.22171
[41]	train-mlogloss:1.22572	validation-mlogloss:1.21859
[42]	train-mlogloss:1.22305	validation-mlogloss:1.21565
[43]	train-mlogloss:1.22029	validation-mlogloss:1.21282
[44]	train-mlogloss:1.21763	validation-mlogloss:1.20995
[45]	train-mlogloss:1.21491	validation-mlogloss:1.20704
[46]	train-mlogloss:1.21232	validation-mlogloss:1.20451
[47]	train-mlogloss:1.20981	validation-mlogloss:1.20185
[48]	train-mlogloss:1.20707	validation-mlogloss:1.19884
[49]	train-mlogloss:1.20455	validation-mlogloss:1.19647
[50]	train-mlogloss:1.20209	validation-mlogloss:1.19390
[51]	train-mlogloss:1.19929	validation-mlogloss:1.19099
[52]	train-mlogloss:1.19686	validation-mlogloss:1.18831
[53]	train-mlogloss:1.19448	validation-mlogloss:1.18598
[54]	train-mlogloss:1.19171	validation-mlogloss:1.18300
[55]	train-mlogloss:1.18899	validation-mlogloss:1.18002
[56]	train-mlogloss:1.18670	validation-mlogloss:1.17764
[57]	train-mlogloss:1.18440	validation-mlogloss:1.17539
[58]	train-mlogloss:1.18217	validation-mlogloss:1.17297
[59]	train-mlogloss:1.17988	validation-mlogloss:1.17055
[60]	train-mlogloss:1.17768	validation-mlogloss:1.16820
[61]	train-mlogloss:1.17543	validation-mlogloss:1.16563
[62]	train-mlogloss:1.17314	validation-mlogloss:1.16317
[63]	train-mlogloss:1.17095	validation-mlogloss:1.16097
[64]	train-mlogloss:1.16847	validation-mlogloss:1.15852
[65]	train-mlogloss:1.16631	validation-mlogloss:1.15619
[66]	train-mlogloss:1.16435	validation-mlogloss:1.15414
[67]	train-mlogloss:1.16228	validation-mlogloss:1.15182
[68]	train-mlogloss:1.16020	validation-mlogloss:1.14965
[69]	train-mlogloss:1.15818	validation-mlogloss:1.14740
[70]	train-mlogloss:1.15585	validation-mlogloss:1.14523
[71]	train-mlogloss:1.15390	validation-mlogloss:1.14334
[72]	train-mlogloss:1.15189	validation-mlogloss:1.14120
[73]	train-mlogloss:1.14987	validation-mlogloss:1.13917
[74]	train-mlogloss:1.14803	validation-mlogloss:1.13725
[75]	train-mlogloss:1.14610	validation-mlogloss:1.13532
[76]	train-mlogloss:1.14424	validation-mlogloss:1.13341
[77]	train-mlogloss:1.14244	validation-mlogloss:1.13138
[78]	train-mlogloss:1.14056	validation-mlogloss:1.12939
[79]	train-mlogloss:1.13876	validation-mlogloss:1.12754
[80]	train-mlogloss:1.13669	validation-mlogloss:1.12572
[81]	train-mlogloss:1.13491	validation-mlogloss:1.12377
[82]	train-mlogloss:1.13321	validation-mlogloss:1.12220
[83]	train-mlogloss:1.13145	validation-mlogloss:1.12047
[84]	train-mlogloss:1.12976	validation-mlogloss:1.11885
[85]	train-mlogloss:1.12806	validation-mlogloss:1.11700
[86]	train-mlogloss:1.12618	validation-mlogloss:1.11493
[87]	train-mlogloss:1.12443	validation-mlogloss:1.11312
[88]	train-mlogloss:1.12272	validation-mlogloss:1.11119
[89]	train-mlogloss:1.12116	validation-mlogloss:1.10957
[90]	train-mlogloss:1.11957	validation-mlogloss:1.10785
[91]	train-mlogloss:1.11788	validation-mlogloss:1.10615
[92]	train-mlogloss:1.11644	validation-mlogloss:1.10484
[93]	train-mlogloss:1.11488	validation-mlogloss:1.10326
[94]	train-mlogloss:1.11335	validation-mlogloss:1.10165
[95]	train-mlogloss:1.11182	validation-mlogloss:1.10002
[96]	train-mlogloss:1.11028	validation-mlogloss:1.09863
[97]	train-mlogloss:1.10886	validation-mlogloss:1.09733
[98]	train-mlogloss:1.10733	validation-mlogloss:1.09573
[99]	train-mlogloss:1.10582	validation-mlogloss:1.09425
[100]	train-mlogloss:1.10435	validation-mlogloss:1.09268
[101]	train-mlogloss:1.10291	validation-mlogloss:1.09125
[102]	train-mlogloss:1.10143	validation-mlogloss:1.08974
[103]	train-mlogloss:1.10004	validation-mlogloss:1.08852
[104]	train-mlogloss:1.09855	validation-mlogloss:1.08697
[105]	train-mlogloss:1.09711	validation-mlogloss:1.08558
[106]	train-mlogloss:1.09575	validation-mlogloss:1.08424
[107]	train-mlogloss:1.09437	validation-mlogloss:1.08288
[108]	train-mlogloss:1.09302	validation-mlogloss:1.08144
[109]	train-mlogloss:1.09174	validation-mlogloss:1.08024
[110]	train-mlogloss:1.09054	validation-mlogloss:1.07910
[111]	train-mlogloss:1.08921	validation-mlogloss:1.07768
[112]	train-mlogloss:1.08788	validation-mlogloss:1.07654
[113]	train-mlogloss:1.08656	validation-mlogloss:1.07537
[114]	train-mlogloss:1.08528	validation-mlogloss:1.07417
[115]	train-mlogloss:1.08383	validation-mlogloss:1.07277
[116]	train-mlogloss:1.08257	validation-mlogloss:1.07172
[117]	train-mlogloss:1.08126	validation-mlogloss:1.07042
[118]	train-mlogloss:1.08005	validation-mlogloss:1.06921
[119]	train-mlogloss:1.07884	validation-mlogloss:1.06810
[120]	train-mlogloss:1.07760	validation-mlogloss:1.06695
[121]	train-mlogloss:1.07649	validation-mlogloss:1.06614
[122]	train-mlogloss:1.07525	validation-mlogloss:1.06486
[123]	train-mlogloss:1.07418	validation-mlogloss:1.06371
[124]	train-mlogloss:1.07297	validation-mlogloss:1.06269
[125]	train-mlogloss:1.07176	validation-mlogloss:1.06166
[126]	train-mlogloss:1.07069	validation-mlogloss:1.06076
[127]	train-mlogloss:1.06947	validation-mlogloss:1.05971
[128]	train-mlogloss:1.06830	validation-mlogloss:1.05868
[129]	train-mlogloss:1.06711	validation-mlogloss:1.05756
[130]	train-mlogloss:1.06599	validation-mlogloss:1.05643
[131]	train-mlogloss:1.06485	validation-mlogloss:1.05548
[132]	train-mlogloss:1.06368	validation-mlogloss:1.05437
[133]	train-mlogloss:1.06258	validation-mlogloss:1.05340
[134]	train-mlogloss:1.06151	validation-mlogloss:1.05232
[135]	train-mlogloss:1.06042	validation-mlogloss:1.05135
[136]	train-mlogloss:1.05931	validation-mlogloss:1.05011
[137]	train-mlogloss:1.05824	validation-mlogloss:1.04914
[138]	train-mlogloss:1.05721	validation-mlogloss:1.04812
[139]	train-mlogloss:1.05620	validation-mlogloss:1.04734
[140]	train-mlogloss:1.05531	validation-mlogloss:1.04669
[141]	train-mlogloss:1.05423	validation-mlogloss:1.04550
[142]	train-mlogloss:1.05319	validation-mlogloss:1.04465
[143]	train-mlogloss:1.05221	validation-mlogloss:1.04365
[144]	train-mlogloss:1.05128	validation-mlogloss:1.04273
[145]	train-mlogloss:1.05018	validation-mlogloss:1.04154
[146]	train-mlogloss:1.04922	validation-mlogloss:1.04055
[147]	train-mlogloss:1.04831	validation-mlogloss:1.03976
[148]	train-mlogloss:1.04743	validation-mlogloss:1.03907
[149]	train-mlogloss:1.04647	validation-mlogloss:1.03825
[150]	train-mlogloss:1.04553	validation-mlogloss:1.03721
[151]	train-mlogloss:1.04464	validation-mlogloss:1.03642
[152]	train-mlogloss:1.04361	validation-mlogloss:1.03544
[153]	train-mlogloss:1.04271	validation-mlogloss:1.03453
[154]	train-mlogloss:1.04180	validation-mlogloss:1.03383
[155]	train-mlogloss:1.04095	validation-mlogloss:1.03308
[156]	train-mlogloss:1.04006	validation-mlogloss:1.03219
[157]	train-mlogloss:1.03910	validation-mlogloss:1.03129
[158]	train-mlogloss:1.03813	validation-mlogloss:1.03047
[159]	train-mlogloss:1.03731	validation-mlogloss:1.02981
[160]	train-mlogloss:1.03635	validation-mlogloss:1.02888
[161]	train-mlogloss:1.03548	validation-mlogloss:1.02792
[162]	train-mlogloss:1.03458	validation-mlogloss:1.02714
[163]	train-mlogloss:1.03369	validation-mlogloss:1.02628
[164]	train-mlogloss:1.03283	validation-mlogloss:1.02552
[165]	train-mlogloss:1.03198	validation-mlogloss:1.02484
[166]	train-mlogloss:1.03122	validation-mlogloss:1.02426
[167]	train-mlogloss:1.03035	validation-mlogloss:1.02328
[168]	train-mlogloss:1.02959	validation-mlogloss:1.02265
[169]	train-mlogloss:1.02876	validation-mlogloss:1.02176
[170]	train-mlogloss:1.02793	validation-mlogloss:1.02102
[171]	train-mlogloss:1.02708	validation-mlogloss:1.02017
[172]	train-mlogloss:1.02628	validation-mlogloss:1.01951
[173]	train-mlogloss:1.02548	validation-mlogloss:1.01882
[174]	train-mlogloss:1.02464	validation-mlogloss:1.01794
[175]	train-mlogloss:1.02380	validation-mlogloss:1.01724
[176]	train-mlogloss:1.02305	validation-mlogloss:1.01650
[177]	train-mlogloss:1.02229	validation-mlogloss:1.01558
[178]	train-mlogloss:1.02156	validation-mlogloss:1.01503
[179]	train-mlogloss:1.02073	validation-mlogloss:1.01436
[180]	train-mlogloss:1.01993	validation-mlogloss:1.01366
[181]	train-mlogloss:1.01921	validation-mlogloss:1.01295
[182]	train-mlogloss:1.01846	validation-mlogloss:1.01228
[183]	train-mlogloss:1.01767	validation-mlogloss:1.01177
[184]	train-mlogloss:1.01683	validation-mlogloss:1.01121
[185]	train-mlogloss:1.01617	validation-mlogloss:1.01076
[186]	train-mlogloss:1.01545	validation-mlogloss:1.01022
[187]	train-mlogloss:1.01467	validation-mlogloss:1.00958
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[641]	train-mlogloss:0.88762	validation-mlogloss:0.91847
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[679]	train-mlogloss:0.88484	validation-mlogloss:0.91706
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[681]	train-mlogloss:0.88475	validation-mlogloss:0.91702
[682]	train-mlogloss:0.88463	validation-mlogloss:0.91695
[683]	train-mlogloss:0.88459	validation-mlogloss:0.91695
[684]	train-mlogloss:0.88452	validation-mlogloss:0.91690
[685]	train-mlogloss:0.88447	validation-mlogloss:0.91683
[686]	train-mlogloss:0.88438	validation-mlogloss:0.91683
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[688]	train-mlogloss:0.88427	validation-mlogloss:0.91672
[689]	train-mlogloss:0.88418	validation-mlogloss:0.91663
[690]	train-mlogloss:0.88411	validation-mlogloss:0.91659
[691]	train-mlogloss:0.88403	validation-mlogloss:0.91659
[692]	train-mlogloss:0.88394	validation-mlogloss:0.91657
[693]	train-mlogloss:0.88386	validation-mlogloss:0.91655
[694]	train-mlogloss:0.88382	validation-mlogloss:0.91652
[695]	train-mlogloss:0.88374	validation-mlogloss:0.91641
[696]	train-mlogloss:0.88367	validation-mlogloss:0.91635
[697]	train-mlogloss:0.88359	validation-mlogloss:0.91627
[698]	train-mlogloss:0.88354	validation-mlogloss:0.91623
[699]	train-mlogloss:0.88348	validation-mlogloss:0.91621
[700]	train-mlogloss:0.88341	validation-mlogloss:0.91620
[701]	train-mlogloss:0.88334	validation-mlogloss:0.91617
[702]	train-mlogloss:0.88329	validation-mlogloss:0.91614
[703]	train-mlogloss:0.88324	validation-mlogloss:0.91606
[704]	train-mlogloss:0.88316	validation-mlogloss:0.91604
[705]	train-mlogloss:0.88310	validation-mlogloss:0.91595
[706]	train-mlogloss:0.88300	validation-mlogloss:0.91586
[707]	train-mlogloss:0.88294	validation-mlogloss:0.91579
[708]	train-mlogloss:0.88289	validation-mlogloss:0.91578
[709]	train-mlogloss:0.88282	validation-mlogloss:0.91576
[710]	train-mlogloss:0.88275	validation-mlogloss:0.91568
[711]	train-mlogloss:0.88268	validation-mlogloss:0.91568
[712]	train-mlogloss:0.88262	validation-mlogloss:0.91564
[713]	train-mlogloss:0.88253	validation-mlogloss:0.91559
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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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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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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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)
Training a non-convolutional model.
Loaded model from disk.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 1 2 ... 3 0 3]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.43 [%]
Global accuracy score (test) = 59.29 [%]
Global F1 score (train) = 63.6 [%]
Global F1 score (test) = 59.98 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.44      0.46      0.45       400
MODERATE-INTENSITY       0.53      0.58      0.56       400
         SEDENTARY       0.65      0.71      0.68       400
VIGOROUS-INTENSITY       0.83      0.62      0.71       345

          accuracy                           0.59      1545
         macro avg       0.61      0.59      0.60      1545
      weighted avg       0.61      0.59      0.60      1545


Accuracy capturado en la ejecución 16: 59.29 [%]
F1-score capturado en la ejecución 16: 59.98 [%]

=== EJECUCIÓN 17 ===

--- TRAIN (ejecución 17) ---

--- TEST (ejecución 17) ---
2025-11-04 11:03:18.695361: 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`.
2025-11-04 11:03:18.707328: 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 00:00:1762250598.721543 1082285 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250598.725992 1082285 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250598.736544 1082285 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250598.736571 1082285 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250598.736573 1082285 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250598.736574 1082285 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:03:18.740035: 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:1.38096	validation-mlogloss:1.38071
[1]	train-mlogloss:1.37572	validation-mlogloss:1.37557
[2]	train-mlogloss:1.37070	validation-mlogloss:1.37051
[3]	train-mlogloss:1.36584	validation-mlogloss:1.36545
[4]	train-mlogloss:1.36092	validation-mlogloss:1.36011
[5]	train-mlogloss:1.35620	validation-mlogloss:1.35505
[6]	train-mlogloss:1.35148	validation-mlogloss:1.35027
[7]	train-mlogloss:1.34713	validation-mlogloss:1.34601
[8]	train-mlogloss:1.34266	validation-mlogloss:1.34169
[9]	train-mlogloss:1.33833	validation-mlogloss:1.33752
[10]	train-mlogloss:1.33349	validation-mlogloss:1.33243
[11]	train-mlogloss:1.32913	validation-mlogloss:1.32774
[12]	train-mlogloss:1.32491	validation-mlogloss:1.32357
[13]	train-mlogloss:1.32073	validation-mlogloss:1.31941
[14]	train-mlogloss:1.31658	validation-mlogloss:1.31520
[15]	train-mlogloss:1.31249	validation-mlogloss:1.31086
[16]	train-mlogloss:1.30845	validation-mlogloss:1.30675
[17]	train-mlogloss:1.30440	validation-mlogloss:1.30278
[18]	train-mlogloss:1.30048	validation-mlogloss:1.29873
[19]	train-mlogloss:1.29662	validation-mlogloss:1.29473
[20]	train-mlogloss:1.29286	validation-mlogloss:1.29114
[21]	train-mlogloss:1.28910	validation-mlogloss:1.28725
[22]	train-mlogloss:1.28548	validation-mlogloss:1.28362
[23]	train-mlogloss:1.28173	validation-mlogloss:1.27961
[24]	train-mlogloss:1.27811	validation-mlogloss:1.27577
[25]	train-mlogloss:1.27460	validation-mlogloss:1.27237
[26]	train-mlogloss:1.27115	validation-mlogloss:1.26879
[27]	train-mlogloss:1.26774	validation-mlogloss:1.26515
[28]	train-mlogloss:1.26443	validation-mlogloss:1.26176
[29]	train-mlogloss:1.26115	validation-mlogloss:1.25862
[30]	train-mlogloss:1.25798	validation-mlogloss:1.25542
[31]	train-mlogloss:1.25485	validation-mlogloss:1.25239
[32]	train-mlogloss:1.25125	validation-mlogloss:1.24872
[33]	train-mlogloss:1.24794	validation-mlogloss:1.24507
[34]	train-mlogloss:1.24484	validation-mlogloss:1.24184
[35]	train-mlogloss:1.24182	validation-mlogloss:1.23869
[36]	train-mlogloss:1.23887	validation-mlogloss:1.23560
[37]	train-mlogloss:1.23592	validation-mlogloss:1.23272
[38]	train-mlogloss:1.23302	validation-mlogloss:1.22979
[39]	train-mlogloss:1.23015	validation-mlogloss:1.22685
[40]	train-mlogloss:1.22732	validation-mlogloss:1.22409
[41]	train-mlogloss:1.22454	validation-mlogloss:1.22132
[42]	train-mlogloss:1.22186	validation-mlogloss:1.21841
[43]	train-mlogloss:1.21917	validation-mlogloss:1.21575
[44]	train-mlogloss:1.21609	validation-mlogloss:1.21251
[45]	train-mlogloss:1.21331	validation-mlogloss:1.20964
[46]	train-mlogloss:1.21078	validation-mlogloss:1.20711
[47]	train-mlogloss:1.20822	validation-mlogloss:1.20451
[48]	train-mlogloss:1.20525	validation-mlogloss:1.20147
[49]	train-mlogloss:1.20280	validation-mlogloss:1.19917
[50]	train-mlogloss:1.20034	validation-mlogloss:1.19659
[51]	train-mlogloss:1.19790	validation-mlogloss:1.19414
[52]	train-mlogloss:1.19546	validation-mlogloss:1.19167
[53]	train-mlogloss:1.19312	validation-mlogloss:1.18926
[54]	train-mlogloss:1.19070	validation-mlogloss:1.18657
[55]	train-mlogloss:1.18825	validation-mlogloss:1.18400
[56]	train-mlogloss:1.18585	validation-mlogloss:1.18159
[57]	train-mlogloss:1.18356	validation-mlogloss:1.17920
[58]	train-mlogloss:1.18130	validation-mlogloss:1.17697
[59]	train-mlogloss:1.17898	validation-mlogloss:1.17456
[60]	train-mlogloss:1.17689	validation-mlogloss:1.17244
[61]	train-mlogloss:1.17435	validation-mlogloss:1.16968
[62]	train-mlogloss:1.17213	validation-mlogloss:1.16727
[63]	train-mlogloss:1.16973	validation-mlogloss:1.16510
[64]	train-mlogloss:1.16726	validation-mlogloss:1.16285
[65]	train-mlogloss:1.16514	validation-mlogloss:1.16080
[66]	train-mlogloss:1.16271	validation-mlogloss:1.15845
[67]	train-mlogloss:1.16066	validation-mlogloss:1.15636
[68]	train-mlogloss:1.15856	validation-mlogloss:1.15416
[69]	train-mlogloss:1.15667	validation-mlogloss:1.15229
[70]	train-mlogloss:1.15478	validation-mlogloss:1.15054
[71]	train-mlogloss:1.15280	validation-mlogloss:1.14841
[72]	train-mlogloss:1.15094	validation-mlogloss:1.14664
[73]	train-mlogloss:1.14875	validation-mlogloss:1.14451
[74]	train-mlogloss:1.14692	validation-mlogloss:1.14270
[75]	train-mlogloss:1.14499	validation-mlogloss:1.14084
[76]	train-mlogloss:1.14294	validation-mlogloss:1.13871
[77]	train-mlogloss:1.14115	validation-mlogloss:1.13695
[78]	train-mlogloss:1.13943	validation-mlogloss:1.13541
[79]	train-mlogloss:1.13757	validation-mlogloss:1.13338
[80]	train-mlogloss:1.13575	validation-mlogloss:1.13164
[81]	train-mlogloss:1.13402	validation-mlogloss:1.13005
[82]	train-mlogloss:1.13226	validation-mlogloss:1.12831
[83]	train-mlogloss:1.13065	validation-mlogloss:1.12655
[84]	train-mlogloss:1.12888	validation-mlogloss:1.12472
[85]	train-mlogloss:1.12728	validation-mlogloss:1.12321
[86]	train-mlogloss:1.12553	validation-mlogloss:1.12128
[87]	train-mlogloss:1.12386	validation-mlogloss:1.11949
[88]	train-mlogloss:1.12210	validation-mlogloss:1.11753
[89]	train-mlogloss:1.12023	validation-mlogloss:1.11562
[90]	train-mlogloss:1.11869	validation-mlogloss:1.11395
[91]	train-mlogloss:1.11715	validation-mlogloss:1.11234
[92]	train-mlogloss:1.11555	validation-mlogloss:1.11088
[93]	train-mlogloss:1.11375	validation-mlogloss:1.10926
[94]	train-mlogloss:1.11228	validation-mlogloss:1.10789
[95]	train-mlogloss:1.11080	validation-mlogloss:1.10650
[96]	train-mlogloss:1.10920	validation-mlogloss:1.10485
[97]	train-mlogloss:1.10785	validation-mlogloss:1.10377
[98]	train-mlogloss:1.10618	validation-mlogloss:1.10220
[99]	train-mlogloss:1.10462	validation-mlogloss:1.10063
[100]	train-mlogloss:1.10312	validation-mlogloss:1.09917
[101]	train-mlogloss:1.10146	validation-mlogloss:1.09766
[102]	train-mlogloss:1.09993	validation-mlogloss:1.09613
[103]	train-mlogloss:1.09848	validation-mlogloss:1.09467
[104]	train-mlogloss:1.09706	validation-mlogloss:1.09330
[105]	train-mlogloss:1.09566	validation-mlogloss:1.09188
[106]	train-mlogloss:1.09421	validation-mlogloss:1.09058
[107]	train-mlogloss:1.09286	validation-mlogloss:1.08914
[108]	train-mlogloss:1.09149	validation-mlogloss:1.08795
[109]	train-mlogloss:1.09022	validation-mlogloss:1.08679
[110]	train-mlogloss:1.08886	validation-mlogloss:1.08552
[111]	train-mlogloss:1.08746	validation-mlogloss:1.08415
[112]	train-mlogloss:1.08616	validation-mlogloss:1.08293
[113]	train-mlogloss:1.08487	validation-mlogloss:1.08158
[114]	train-mlogloss:1.08361	validation-mlogloss:1.08042
[115]	train-mlogloss:1.08233	validation-mlogloss:1.07940
[116]	train-mlogloss:1.08113	validation-mlogloss:1.07810
[117]	train-mlogloss:1.07986	validation-mlogloss:1.07684
[118]	train-mlogloss:1.07871	validation-mlogloss:1.07579
[119]	train-mlogloss:1.07751	validation-mlogloss:1.07481
[120]	train-mlogloss:1.07629	validation-mlogloss:1.07378
[121]	train-mlogloss:1.07515	validation-mlogloss:1.07274
[122]	train-mlogloss:1.07388	validation-mlogloss:1.07145
[123]	train-mlogloss:1.07268	validation-mlogloss:1.07035
[124]	train-mlogloss:1.07161	validation-mlogloss:1.06937
[125]	train-mlogloss:1.07043	validation-mlogloss:1.06835
[126]	train-mlogloss:1.06925	validation-mlogloss:1.06737
[127]	train-mlogloss:1.06809	validation-mlogloss:1.06628
[128]	train-mlogloss:1.06689	validation-mlogloss:1.06523
[129]	train-mlogloss:1.06572	validation-mlogloss:1.06398
[130]	train-mlogloss:1.06463	validation-mlogloss:1.06281
[131]	train-mlogloss:1.06331	validation-mlogloss:1.06171
[132]	train-mlogloss:1.06218	validation-mlogloss:1.06069
[133]	train-mlogloss:1.06120	validation-mlogloss:1.05974
[134]	train-mlogloss:1.06017	validation-mlogloss:1.05866
[135]	train-mlogloss:1.05906	validation-mlogloss:1.05754
[136]	train-mlogloss:1.05799	validation-mlogloss:1.05641
[137]	train-mlogloss:1.05700	validation-mlogloss:1.05554
[138]	train-mlogloss:1.05600	validation-mlogloss:1.05453
[139]	train-mlogloss:1.05500	validation-mlogloss:1.05350
[140]	train-mlogloss:1.05400	validation-mlogloss:1.05256
[141]	train-mlogloss:1.05296	validation-mlogloss:1.05143
[142]	train-mlogloss:1.05201	validation-mlogloss:1.05057
[143]	train-mlogloss:1.05105	validation-mlogloss:1.04977
[144]	train-mlogloss:1.05011	validation-mlogloss:1.04879
[145]	train-mlogloss:1.04921	validation-mlogloss:1.04805
[146]	train-mlogloss:1.04820	validation-mlogloss:1.04710
[147]	train-mlogloss:1.04736	validation-mlogloss:1.04649
[148]	train-mlogloss:1.04638	validation-mlogloss:1.04566
[149]	train-mlogloss:1.04544	validation-mlogloss:1.04479
[150]	train-mlogloss:1.04450	validation-mlogloss:1.04380
[151]	train-mlogloss:1.04367	validation-mlogloss:1.04309
[152]	train-mlogloss:1.04268	validation-mlogloss:1.04198
[153]	train-mlogloss:1.04175	validation-mlogloss:1.04110
[154]	train-mlogloss:1.04078	validation-mlogloss:1.04006
[155]	train-mlogloss:1.03995	validation-mlogloss:1.03921
[156]	train-mlogloss:1.03899	validation-mlogloss:1.03840
[157]	train-mlogloss:1.03817	validation-mlogloss:1.03768
[158]	train-mlogloss:1.03736	validation-mlogloss:1.03683
[159]	train-mlogloss:1.03653	validation-mlogloss:1.03603
[160]	train-mlogloss:1.03566	validation-mlogloss:1.03530
[161]	train-mlogloss:1.03485	validation-mlogloss:1.03453
[162]	train-mlogloss:1.03397	validation-mlogloss:1.03374
[163]	train-mlogloss:1.03309	validation-mlogloss:1.03312
[164]	train-mlogloss:1.03227	validation-mlogloss:1.03242
[165]	train-mlogloss:1.03141	validation-mlogloss:1.03160
[166]	train-mlogloss:1.03055	validation-mlogloss:1.03085
[167]	train-mlogloss:1.02973	validation-mlogloss:1.03021
[168]	train-mlogloss:1.02893	validation-mlogloss:1.02939
[169]	train-mlogloss:1.02808	validation-mlogloss:1.02862
[170]	train-mlogloss:1.02723	validation-mlogloss:1.02773
[171]	train-mlogloss:1.02631	validation-mlogloss:1.02709
[172]	train-mlogloss:1.02552	validation-mlogloss:1.02633
[173]	train-mlogloss:1.02470	validation-mlogloss:1.02564
[174]	train-mlogloss:1.02387	validation-mlogloss:1.02484
[175]	train-mlogloss:1.02309	validation-mlogloss:1.02409
[176]	train-mlogloss:1.02233	validation-mlogloss:1.02354
[177]	train-mlogloss:1.02156	validation-mlogloss:1.02288
[178]	train-mlogloss:1.02084	validation-mlogloss:1.02231
[179]	train-mlogloss:1.02006	validation-mlogloss:1.02152
[180]	train-mlogloss:1.01931	validation-mlogloss:1.02088
[181]	train-mlogloss:1.01850	validation-mlogloss:1.02011
[182]	train-mlogloss:1.01777	validation-mlogloss:1.01958
[183]	train-mlogloss:1.01707	validation-mlogloss:1.01908
[184]	train-mlogloss:1.01636	validation-mlogloss:1.01841
[185]	train-mlogloss:1.01561	validation-mlogloss:1.01770
[186]	train-mlogloss:1.01485	validation-mlogloss:1.01687
[187]	train-mlogloss:1.01407	validation-mlogloss:1.01614
[188]	train-mlogloss:1.01339	validation-mlogloss:1.01569
[189]	train-mlogloss:1.01277	validation-mlogloss:1.01513
[190]	train-mlogloss:1.01207	validation-mlogloss:1.01448
[191]	train-mlogloss:1.01133	validation-mlogloss:1.01395
[192]	train-mlogloss:1.01063	validation-mlogloss:1.01334
[193]	train-mlogloss:1.01001	validation-mlogloss:1.01297
[194]	train-mlogloss:1.00937	validation-mlogloss:1.01252
[195]	train-mlogloss:1.00868	validation-mlogloss:1.01218
[196]	train-mlogloss:1.00802	validation-mlogloss:1.01160
[197]	train-mlogloss:1.00734	validation-mlogloss:1.01100
[198]	train-mlogloss:1.00666	validation-mlogloss:1.01051
[199]	train-mlogloss:1.00597	validation-mlogloss:1.01000
[200]	train-mlogloss:1.00529	validation-mlogloss:1.00939
[201]	train-mlogloss:1.00449	validation-mlogloss:1.00881
[202]	train-mlogloss:1.00384	validation-mlogloss:1.00817
[203]	train-mlogloss:1.00310	validation-mlogloss:1.00756
[204]	train-mlogloss:1.00253	validation-mlogloss:1.00719
[205]	train-mlogloss:1.00196	validation-mlogloss:1.00663
[206]	train-mlogloss:1.00135	validation-mlogloss:1.00604
[207]	train-mlogloss:1.00077	validation-mlogloss:1.00558
[208]	train-mlogloss:1.00015	validation-mlogloss:1.00523
[209]	train-mlogloss:0.99950	validation-mlogloss:1.00462
[210]	train-mlogloss:0.99888	validation-mlogloss:1.00395
[211]	train-mlogloss:0.99827	validation-mlogloss:1.00345
[212]	train-mlogloss:0.99768	validation-mlogloss:1.00289
[213]	train-mlogloss:0.99704	validation-mlogloss:1.00235
[214]	train-mlogloss:0.99649	validation-mlogloss:1.00193
[215]	train-mlogloss:0.99595	validation-mlogloss:1.00160
[216]	train-mlogloss:0.99538	validation-mlogloss:1.00101
[217]	train-mlogloss:0.99480	validation-mlogloss:1.00052
[218]	train-mlogloss:0.99424	validation-mlogloss:1.00008
[219]	train-mlogloss:0.99362	validation-mlogloss:0.99955
[220]	train-mlogloss:0.99304	validation-mlogloss:0.99905
[221]	train-mlogloss:0.99249	validation-mlogloss:0.99849
[222]	train-mlogloss:0.99201	validation-mlogloss:0.99814
[223]	train-mlogloss:0.99140	validation-mlogloss:0.99763
[224]	train-mlogloss:0.99082	validation-mlogloss:0.99731
[225]	train-mlogloss:0.99024	validation-mlogloss:0.99685
[226]	train-mlogloss:0.98963	validation-mlogloss:0.99651
[227]	train-mlogloss:0.98910	validation-mlogloss:0.99612
[228]	train-mlogloss:0.98852	validation-mlogloss:0.99577
[229]	train-mlogloss:0.98800	validation-mlogloss:0.99542
[230]	train-mlogloss:0.98748	validation-mlogloss:0.99504
[231]	train-mlogloss:0.98696	validation-mlogloss:0.99450
[232]	train-mlogloss:0.98637	validation-mlogloss:0.99423
[233]	train-mlogloss:0.98585	validation-mlogloss:0.99375
[234]	train-mlogloss:0.98523	validation-mlogloss:0.99330
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[639]	train-mlogloss:0.89020	validation-mlogloss:0.92940
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[641]	train-mlogloss:0.89002	validation-mlogloss:0.92915
[642]	train-mlogloss:0.88995	validation-mlogloss:0.92913
[643]	train-mlogloss:0.88985	validation-mlogloss:0.92903
[644]	train-mlogloss:0.88978	validation-mlogloss:0.92900
[645]	train-mlogloss:0.88970	validation-mlogloss:0.92892
[646]	train-mlogloss:0.88963	validation-mlogloss:0.92887
[647]	train-mlogloss:0.88958	validation-mlogloss:0.92882
[648]	train-mlogloss:0.88953	validation-mlogloss:0.92879
[649]	train-mlogloss:0.88946	validation-mlogloss:0.92879
[650]	train-mlogloss:0.88934	validation-mlogloss:0.92871
[651]	train-mlogloss:0.88929	validation-mlogloss:0.92867
[652]	train-mlogloss:0.88919	validation-mlogloss:0.92859
[653]	train-mlogloss:0.88913	validation-mlogloss:0.92852
[654]	train-mlogloss:0.88910	validation-mlogloss:0.92847
[655]	train-mlogloss:0.88898	validation-mlogloss:0.92837
[656]	train-mlogloss:0.88894	validation-mlogloss:0.92834
[657]	train-mlogloss:0.88884	validation-mlogloss:0.92827
[658]	train-mlogloss:0.88882	validation-mlogloss:0.92826
[659]	train-mlogloss:0.88870	validation-mlogloss:0.92819
[660]	train-mlogloss:0.88862	validation-mlogloss:0.92824
[661]	train-mlogloss:0.88857	validation-mlogloss:0.92819
[662]	train-mlogloss:0.88851	validation-mlogloss:0.92817
[663]	train-mlogloss:0.88843	validation-mlogloss:0.92813
[664]	train-mlogloss:0.88838	validation-mlogloss:0.92805
[665]	train-mlogloss:0.88833	validation-mlogloss:0.92798
[666]	train-mlogloss:0.88825	validation-mlogloss:0.92791
[667]	train-mlogloss:0.88821	validation-mlogloss:0.92789
[668]	train-mlogloss:0.88814	validation-mlogloss:0.92792
[669]	train-mlogloss:0.88806	validation-mlogloss:0.92781
[670]	train-mlogloss:0.88801	validation-mlogloss:0.92777
[671]	train-mlogloss:0.88788	validation-mlogloss:0.92774
[672]	train-mlogloss:0.88780	validation-mlogloss:0.92768
[673]	train-mlogloss:0.88776	validation-mlogloss:0.92765
[674]	train-mlogloss:0.88770	validation-mlogloss:0.92760
[675]	train-mlogloss:0.88764	validation-mlogloss:0.92754
[676]	train-mlogloss:0.88758	validation-mlogloss:0.92751
[677]	train-mlogloss:0.88749	validation-mlogloss:0.92748
[678]	train-mlogloss:0.88737	validation-mlogloss:0.92734
[679]	train-mlogloss:0.88735	validation-mlogloss:0.92733
[680]	train-mlogloss:0.88730	validation-mlogloss:0.92730
[681]	train-mlogloss:0.88723	validation-mlogloss:0.92726
[682]	train-mlogloss:0.88712	validation-mlogloss:0.92719
[683]	train-mlogloss:0.88703	validation-mlogloss:0.92718
[684]	train-mlogloss:0.88699	validation-mlogloss:0.92715
[685]	train-mlogloss:0.88690	validation-mlogloss:0.92713
[686]	train-mlogloss:0.88679	validation-mlogloss:0.92705
[687]	train-mlogloss:0.88674	validation-mlogloss:0.92705
[688]	train-mlogloss:0.88670	validation-mlogloss:0.92699
[689]	train-mlogloss:0.88665	validation-mlogloss:0.92692
[690]	train-mlogloss:0.88658	validation-mlogloss:0.92688
[691]	train-mlogloss:0.88650	validation-mlogloss:0.92684
[692]	train-mlogloss:0.88642	validation-mlogloss:0.92669
[693]	train-mlogloss:0.88629	validation-mlogloss:0.92655
[694]	train-mlogloss:0.88626	validation-mlogloss:0.92654
[695]	train-mlogloss:0.88622	validation-mlogloss:0.92647
[696]	train-mlogloss:0.88617	validation-mlogloss:0.92646
[697]	train-mlogloss:0.88609	validation-mlogloss:0.92642
[698]	train-mlogloss:0.88604	validation-mlogloss:0.92636
[699]	train-mlogloss:0.88595	validation-mlogloss:0.92629
[700]	train-mlogloss:0.88588	validation-mlogloss:0.92629
[701]	train-mlogloss:0.88583	validation-mlogloss:0.92631
[702]	train-mlogloss:0.88578	validation-mlogloss:0.92628
[703]	train-mlogloss:0.88571	validation-mlogloss:0.92622
[704]	train-mlogloss:0.88561	validation-mlogloss:0.92613
[705]	train-mlogloss:0.88553	validation-mlogloss:0.92610
[706]	train-mlogloss:0.88541	validation-mlogloss:0.92603
[707]	train-mlogloss:0.88532	validation-mlogloss:0.92589
[708]	train-mlogloss:0.88525	validation-mlogloss:0.92583
[709]	train-mlogloss:0.88517	validation-mlogloss:0.92579
[710]	train-mlogloss:0.88509	validation-mlogloss:0.92570
[711]	train-mlogloss:0.88503	validation-mlogloss:0.92563
[712]	train-mlogloss:0.88496	validation-mlogloss:0.92560
[713]	train-mlogloss:0.88489	validation-mlogloss:0.92554
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[1 2 1 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.65 [%]
Global accuracy score (test) = 58.38 [%]
Global F1 score (train) = 63.69 [%]
Global F1 score (test) = 59.15 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.41      0.41      0.41       400
MODERATE-INTENSITY       0.52      0.62      0.57       400
         SEDENTARY       0.67      0.69      0.68       400
VIGOROUS-INTENSITY       0.83      0.61      0.70       345

          accuracy                           0.58      1545
         macro avg       0.61      0.58      0.59      1545
      weighted avg       0.60      0.58      0.59      1545


Accuracy capturado en la ejecución 17: 58.38 [%]
F1-score capturado en la ejecución 17: 59.15 [%]

=== EJECUCIÓN 18 ===

--- TRAIN (ejecución 18) ---

--- TEST (ejecución 18) ---
2025-11-04 11:03:35.922664: 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`.
2025-11-04 11:03:35.934369: 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 00:00:1762250615.947809 1082597 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250615.952174 1082597 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250615.962262 1082597 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250615.962283 1082597 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250615.962284 1082597 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250615.962285 1082597 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:03:35.965480: 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)
Training a non-convolutional model.
[0]	train-mlogloss:1.38095	validation-mlogloss:1.38084
[1]	train-mlogloss:1.37580	validation-mlogloss:1.37563
[2]	train-mlogloss:1.37081	validation-mlogloss:1.37063
[3]	train-mlogloss:1.36585	validation-mlogloss:1.36569
[4]	train-mlogloss:1.36096	validation-mlogloss:1.36071
[5]	train-mlogloss:1.35606	validation-mlogloss:1.35589
[6]	train-mlogloss:1.35126	validation-mlogloss:1.35117
[7]	train-mlogloss:1.34674	validation-mlogloss:1.34671
[8]	train-mlogloss:1.34227	validation-mlogloss:1.34198
[9]	train-mlogloss:1.33774	validation-mlogloss:1.33731
[10]	train-mlogloss:1.33329	validation-mlogloss:1.33281
[11]	train-mlogloss:1.32894	validation-mlogloss:1.32835
[12]	train-mlogloss:1.32471	validation-mlogloss:1.32421
[13]	train-mlogloss:1.32043	validation-mlogloss:1.31981
[14]	train-mlogloss:1.31620	validation-mlogloss:1.31526
[15]	train-mlogloss:1.31202	validation-mlogloss:1.31102
[16]	train-mlogloss:1.30798	validation-mlogloss:1.30686
[17]	train-mlogloss:1.30399	validation-mlogloss:1.30301
[18]	train-mlogloss:1.30002	validation-mlogloss:1.29902
[19]	train-mlogloss:1.29592	validation-mlogloss:1.29476
[20]	train-mlogloss:1.29205	validation-mlogloss:1.29071
[21]	train-mlogloss:1.28832	validation-mlogloss:1.28671
[22]	train-mlogloss:1.28468	validation-mlogloss:1.28322
[23]	train-mlogloss:1.28115	validation-mlogloss:1.27969
[24]	train-mlogloss:1.27744	validation-mlogloss:1.27579
[25]	train-mlogloss:1.27383	validation-mlogloss:1.27195
[26]	train-mlogloss:1.27001	validation-mlogloss:1.26798
[27]	train-mlogloss:1.26667	validation-mlogloss:1.26471
[28]	train-mlogloss:1.26326	validation-mlogloss:1.26116
[29]	train-mlogloss:1.25998	validation-mlogloss:1.25786
[30]	train-mlogloss:1.25672	validation-mlogloss:1.25456
[31]	train-mlogloss:1.25345	validation-mlogloss:1.25125
[32]	train-mlogloss:1.25017	validation-mlogloss:1.24778
[33]	train-mlogloss:1.24706	validation-mlogloss:1.24479
[34]	train-mlogloss:1.24396	validation-mlogloss:1.24167
[35]	train-mlogloss:1.24091	validation-mlogloss:1.23846
[36]	train-mlogloss:1.23792	validation-mlogloss:1.23523
[37]	train-mlogloss:1.23498	validation-mlogloss:1.23231
[38]	train-mlogloss:1.23207	validation-mlogloss:1.22944
[39]	train-mlogloss:1.22912	validation-mlogloss:1.22675
[40]	train-mlogloss:1.22617	validation-mlogloss:1.22354
[41]	train-mlogloss:1.22339	validation-mlogloss:1.22080
[42]	train-mlogloss:1.22065	validation-mlogloss:1.21795
[43]	train-mlogloss:1.21759	validation-mlogloss:1.21468
[44]	train-mlogloss:1.21492	validation-mlogloss:1.21202
[45]	train-mlogloss:1.21223	validation-mlogloss:1.20945
[46]	train-mlogloss:1.20963	validation-mlogloss:1.20698
[47]	train-mlogloss:1.20716	validation-mlogloss:1.20451
[48]	train-mlogloss:1.20448	validation-mlogloss:1.20165
[49]	train-mlogloss:1.20199	validation-mlogloss:1.19927
[50]	train-mlogloss:1.19945	validation-mlogloss:1.19667
[51]	train-mlogloss:1.19706	validation-mlogloss:1.19433
[52]	train-mlogloss:1.19467	validation-mlogloss:1.19184
[53]	train-mlogloss:1.19224	validation-mlogloss:1.18926
[54]	train-mlogloss:1.18985	validation-mlogloss:1.18683
[55]	train-mlogloss:1.18753	validation-mlogloss:1.18451
[56]	train-mlogloss:1.18517	validation-mlogloss:1.18212
[57]	train-mlogloss:1.18244	validation-mlogloss:1.17920
[58]	train-mlogloss:1.17983	validation-mlogloss:1.17680
[59]	train-mlogloss:1.17758	validation-mlogloss:1.17452
[60]	train-mlogloss:1.17499	validation-mlogloss:1.17168
[61]	train-mlogloss:1.17271	validation-mlogloss:1.16938
[62]	train-mlogloss:1.17062	validation-mlogloss:1.16714
[63]	train-mlogloss:1.16853	validation-mlogloss:1.16499
[64]	train-mlogloss:1.16629	validation-mlogloss:1.16256
[65]	train-mlogloss:1.16425	validation-mlogloss:1.16069
[66]	train-mlogloss:1.16223	validation-mlogloss:1.15872
[67]	train-mlogloss:1.16017	validation-mlogloss:1.15679
[68]	train-mlogloss:1.15815	validation-mlogloss:1.15474
[69]	train-mlogloss:1.15615	validation-mlogloss:1.15283
[70]	train-mlogloss:1.15409	validation-mlogloss:1.15063
[71]	train-mlogloss:1.15206	validation-mlogloss:1.14865
[72]	train-mlogloss:1.15002	validation-mlogloss:1.14674
[73]	train-mlogloss:1.14806	validation-mlogloss:1.14479
[74]	train-mlogloss:1.14581	validation-mlogloss:1.14252
[75]	train-mlogloss:1.14389	validation-mlogloss:1.14069
[76]	train-mlogloss:1.14197	validation-mlogloss:1.13890
[77]	train-mlogloss:1.13980	validation-mlogloss:1.13670
[78]	train-mlogloss:1.13785	validation-mlogloss:1.13475
[79]	train-mlogloss:1.13610	validation-mlogloss:1.13299
[80]	train-mlogloss:1.13446	validation-mlogloss:1.13150
[81]	train-mlogloss:1.13272	validation-mlogloss:1.12969
[82]	train-mlogloss:1.13073	validation-mlogloss:1.12808
[83]	train-mlogloss:1.12890	validation-mlogloss:1.12613
[84]	train-mlogloss:1.12708	validation-mlogloss:1.12446
[85]	train-mlogloss:1.12498	validation-mlogloss:1.12245
[86]	train-mlogloss:1.12327	validation-mlogloss:1.12090
[87]	train-mlogloss:1.12155	validation-mlogloss:1.11905
[88]	train-mlogloss:1.11966	validation-mlogloss:1.11731
[89]	train-mlogloss:1.11805	validation-mlogloss:1.11575
[90]	train-mlogloss:1.11637	validation-mlogloss:1.11402
[91]	train-mlogloss:1.11476	validation-mlogloss:1.11268
[92]	train-mlogloss:1.11290	validation-mlogloss:1.11099
[93]	train-mlogloss:1.11135	validation-mlogloss:1.10973
[94]	train-mlogloss:1.10974	validation-mlogloss:1.10818
[95]	train-mlogloss:1.10823	validation-mlogloss:1.10675
[96]	train-mlogloss:1.10663	validation-mlogloss:1.10506
[97]	train-mlogloss:1.10518	validation-mlogloss:1.10345
[98]	train-mlogloss:1.10373	validation-mlogloss:1.10180
[99]	train-mlogloss:1.10219	validation-mlogloss:1.10019
[100]	train-mlogloss:1.10078	validation-mlogloss:1.09877
[101]	train-mlogloss:1.09943	validation-mlogloss:1.09764
[102]	train-mlogloss:1.09796	validation-mlogloss:1.09632
[103]	train-mlogloss:1.09659	validation-mlogloss:1.09516
[104]	train-mlogloss:1.09518	validation-mlogloss:1.09384
[105]	train-mlogloss:1.09382	validation-mlogloss:1.09240
[106]	train-mlogloss:1.09249	validation-mlogloss:1.09108
[107]	train-mlogloss:1.09108	validation-mlogloss:1.08969
[108]	train-mlogloss:1.08972	validation-mlogloss:1.08834
[109]	train-mlogloss:1.08844	validation-mlogloss:1.08713
[110]	train-mlogloss:1.08706	validation-mlogloss:1.08566
[111]	train-mlogloss:1.08579	validation-mlogloss:1.08465
[112]	train-mlogloss:1.08442	validation-mlogloss:1.08324
[113]	train-mlogloss:1.08316	validation-mlogloss:1.08211
[114]	train-mlogloss:1.08186	validation-mlogloss:1.08089
[115]	train-mlogloss:1.08061	validation-mlogloss:1.07963
[116]	train-mlogloss:1.07933	validation-mlogloss:1.07845
[117]	train-mlogloss:1.07802	validation-mlogloss:1.07724
[118]	train-mlogloss:1.07681	validation-mlogloss:1.07593
[119]	train-mlogloss:1.07551	validation-mlogloss:1.07463
[120]	train-mlogloss:1.07422	validation-mlogloss:1.07336
[121]	train-mlogloss:1.07295	validation-mlogloss:1.07225
[122]	train-mlogloss:1.07176	validation-mlogloss:1.07103
[123]	train-mlogloss:1.07051	validation-mlogloss:1.06975
[124]	train-mlogloss:1.06927	validation-mlogloss:1.06862
[125]	train-mlogloss:1.06811	validation-mlogloss:1.06735
[126]	train-mlogloss:1.06699	validation-mlogloss:1.06639
[127]	train-mlogloss:1.06591	validation-mlogloss:1.06533
[128]	train-mlogloss:1.06470	validation-mlogloss:1.06437
[129]	train-mlogloss:1.06359	validation-mlogloss:1.06331
[130]	train-mlogloss:1.06247	validation-mlogloss:1.06211
[131]	train-mlogloss:1.06137	validation-mlogloss:1.06109
[132]	train-mlogloss:1.06025	validation-mlogloss:1.06005
[133]	train-mlogloss:1.05912	validation-mlogloss:1.05895
[134]	train-mlogloss:1.05806	validation-mlogloss:1.05797
[135]	train-mlogloss:1.05697	validation-mlogloss:1.05687
[136]	train-mlogloss:1.05577	validation-mlogloss:1.05562
[137]	train-mlogloss:1.05470	validation-mlogloss:1.05457
[138]	train-mlogloss:1.05375	validation-mlogloss:1.05372
[139]	train-mlogloss:1.05273	validation-mlogloss:1.05267
[140]	train-mlogloss:1.05169	validation-mlogloss:1.05166
[141]	train-mlogloss:1.05070	validation-mlogloss:1.05061
[142]	train-mlogloss:1.04965	validation-mlogloss:1.04955
[143]	train-mlogloss:1.04864	validation-mlogloss:1.04842
[144]	train-mlogloss:1.04767	validation-mlogloss:1.04734
[145]	train-mlogloss:1.04674	validation-mlogloss:1.04657
[146]	train-mlogloss:1.04584	validation-mlogloss:1.04573
[147]	train-mlogloss:1.04482	validation-mlogloss:1.04464
[148]	train-mlogloss:1.04395	validation-mlogloss:1.04377
[149]	train-mlogloss:1.04293	validation-mlogloss:1.04257
[150]	train-mlogloss:1.04189	validation-mlogloss:1.04169
[151]	train-mlogloss:1.04100	validation-mlogloss:1.04080
[152]	train-mlogloss:1.04004	validation-mlogloss:1.03991
[153]	train-mlogloss:1.03911	validation-mlogloss:1.03920
[154]	train-mlogloss:1.03830	validation-mlogloss:1.03858
[155]	train-mlogloss:1.03753	validation-mlogloss:1.03812
[156]	train-mlogloss:1.03661	validation-mlogloss:1.03739
[157]	train-mlogloss:1.03583	validation-mlogloss:1.03650
[158]	train-mlogloss:1.03494	validation-mlogloss:1.03572
[159]	train-mlogloss:1.03399	validation-mlogloss:1.03504
[160]	train-mlogloss:1.03318	validation-mlogloss:1.03439
[161]	train-mlogloss:1.03229	validation-mlogloss:1.03376
[162]	train-mlogloss:1.03151	validation-mlogloss:1.03299
[163]	train-mlogloss:1.03064	validation-mlogloss:1.03234
[164]	train-mlogloss:1.02979	validation-mlogloss:1.03166
[165]	train-mlogloss:1.02893	validation-mlogloss:1.03075
[166]	train-mlogloss:1.02806	validation-mlogloss:1.03015
[167]	train-mlogloss:1.02718	validation-mlogloss:1.02919
[168]	train-mlogloss:1.02614	validation-mlogloss:1.02841
[169]	train-mlogloss:1.02537	validation-mlogloss:1.02781
[170]	train-mlogloss:1.02445	validation-mlogloss:1.02721
[171]	train-mlogloss:1.02339	validation-mlogloss:1.02647
[172]	train-mlogloss:1.02270	validation-mlogloss:1.02590
[173]	train-mlogloss:1.02195	validation-mlogloss:1.02526
[174]	train-mlogloss:1.02118	validation-mlogloss:1.02471
[175]	train-mlogloss:1.02045	validation-mlogloss:1.02411
[176]	train-mlogloss:1.01976	validation-mlogloss:1.02352
[177]	train-mlogloss:1.01895	validation-mlogloss:1.02263
[178]	train-mlogloss:1.01821	validation-mlogloss:1.02205
[179]	train-mlogloss:1.01746	validation-mlogloss:1.02138
[180]	train-mlogloss:1.01685	validation-mlogloss:1.02113
[181]	train-mlogloss:1.01608	validation-mlogloss:1.02046
[182]	train-mlogloss:1.01531	validation-mlogloss:1.01969
[183]	train-mlogloss:1.01459	validation-mlogloss:1.01920
[184]	train-mlogloss:1.01380	validation-mlogloss:1.01877
[185]	train-mlogloss:1.01301	validation-mlogloss:1.01803
[186]	train-mlogloss:1.01215	validation-mlogloss:1.01759
[187]	train-mlogloss:1.01150	validation-mlogloss:1.01683
[188]	train-mlogloss:1.01070	validation-mlogloss:1.01634
[189]	train-mlogloss:1.01004	validation-mlogloss:1.01576
[190]	train-mlogloss:1.00936	validation-mlogloss:1.01507
[191]	train-mlogloss:1.00866	validation-mlogloss:1.01450
[192]	train-mlogloss:1.00792	validation-mlogloss:1.01400
[193]	train-mlogloss:1.00716	validation-mlogloss:1.01315
[194]	train-mlogloss:1.00646	validation-mlogloss:1.01263
[195]	train-mlogloss:1.00571	validation-mlogloss:1.01212
[196]	train-mlogloss:1.00505	validation-mlogloss:1.01145
[197]	train-mlogloss:1.00440	validation-mlogloss:1.01071
[198]	train-mlogloss:1.00376	validation-mlogloss:1.01007
[199]	train-mlogloss:1.00311	validation-mlogloss:1.00961
[200]	train-mlogloss:1.00243	validation-mlogloss:1.00880
[201]	train-mlogloss:1.00175	validation-mlogloss:1.00828
[202]	train-mlogloss:1.00116	validation-mlogloss:1.00777
[203]	train-mlogloss:1.00049	validation-mlogloss:1.00728
[204]	train-mlogloss:0.99983	validation-mlogloss:1.00671
[205]	train-mlogloss:0.99924	validation-mlogloss:1.00637
[206]	train-mlogloss:0.99858	validation-mlogloss:1.00574
[207]	train-mlogloss:0.99787	validation-mlogloss:1.00520
[208]	train-mlogloss:0.99731	validation-mlogloss:1.00497
[209]	train-mlogloss:0.99674	validation-mlogloss:1.00449
[210]	train-mlogloss:0.99614	validation-mlogloss:1.00402
[211]	train-mlogloss:0.99554	validation-mlogloss:1.00358
[212]	train-mlogloss:0.99490	validation-mlogloss:1.00310
[213]	train-mlogloss:0.99427	validation-mlogloss:1.00274
[214]	train-mlogloss:0.99365	validation-mlogloss:1.00227
[215]	train-mlogloss:0.99307	validation-mlogloss:1.00184
[216]	train-mlogloss:0.99245	validation-mlogloss:1.00136
[217]	train-mlogloss:0.99185	validation-mlogloss:1.00083
[218]	train-mlogloss:0.99125	validation-mlogloss:1.00039
[219]	train-mlogloss:0.99065	validation-mlogloss:0.99985
[220]	train-mlogloss:0.99009	validation-mlogloss:0.99947
[221]	train-mlogloss:0.98948	validation-mlogloss:0.99906
[222]	train-mlogloss:0.98893	validation-mlogloss:0.99872
[223]	train-mlogloss:0.98828	validation-mlogloss:0.99819
[224]	train-mlogloss:0.98769	validation-mlogloss:0.99758
[225]	train-mlogloss:0.98720	validation-mlogloss:0.99744
[226]	train-mlogloss:0.98665	validation-mlogloss:0.99694
[227]	train-mlogloss:0.98610	validation-mlogloss:0.99632
[228]	train-mlogloss:0.98551	validation-mlogloss:0.99615
[229]	train-mlogloss:0.98500	validation-mlogloss:0.99575
[230]	train-mlogloss:0.98446	validation-mlogloss:0.99534
[231]	train-mlogloss:0.98390	validation-mlogloss:0.99506
[232]	train-mlogloss:0.98336	validation-mlogloss:0.99463
[233]	train-mlogloss:0.98279	validation-mlogloss:0.99427
[234]	train-mlogloss:0.98225	validation-mlogloss:0.99366
[235]	train-mlogloss:0.98167	validation-mlogloss:0.99317
[236]	train-mlogloss:0.98112	validation-mlogloss:0.99274
[237]	train-mlogloss:0.98059	validation-mlogloss:0.99249
[238]	train-mlogloss:0.98002	validation-mlogloss:0.99198
[239]	train-mlogloss:0.97955	validation-mlogloss:0.99157
[240]	train-mlogloss:0.97901	validation-mlogloss:0.99122
[241]	train-mlogloss:0.97846	validation-mlogloss:0.99088
[242]	train-mlogloss:0.97792	validation-mlogloss:0.99037
[243]	train-mlogloss:0.97745	validation-mlogloss:0.99011
[244]	train-mlogloss:0.97689	validation-mlogloss:0.98966
[245]	train-mlogloss:0.97636	validation-mlogloss:0.98923
[246]	train-mlogloss:0.97583	validation-mlogloss:0.98892
[247]	train-mlogloss:0.97518	validation-mlogloss:0.98844
[248]	train-mlogloss:0.97470	validation-mlogloss:0.98799
[249]	train-mlogloss:0.97412	validation-mlogloss:0.98752
[250]	train-mlogloss:0.97367	validation-mlogloss:0.98717
[251]	train-mlogloss:0.97314	validation-mlogloss:0.98688
[252]	train-mlogloss:0.97263	validation-mlogloss:0.98638
[253]	train-mlogloss:0.97206	validation-mlogloss:0.98598
[254]	train-mlogloss:0.97163	validation-mlogloss:0.98555
[255]	train-mlogloss:0.97111	validation-mlogloss:0.98503
[256]	train-mlogloss:0.97052	validation-mlogloss:0.98466
[257]	train-mlogloss:0.97009	validation-mlogloss:0.98427
[258]	train-mlogloss:0.96965	validation-mlogloss:0.98393
[259]	train-mlogloss:0.96915	validation-mlogloss:0.98364
[260]	train-mlogloss:0.96867	validation-mlogloss:0.98320
[261]	train-mlogloss:0.96821	validation-mlogloss:0.98284
[262]	train-mlogloss:0.96768	validation-mlogloss:0.98256
[263]	train-mlogloss:0.96721	validation-mlogloss:0.98223
[264]	train-mlogloss:0.96681	validation-mlogloss:0.98181
[265]	train-mlogloss:0.96639	validation-mlogloss:0.98149
[266]	train-mlogloss:0.96591	validation-mlogloss:0.98109
[267]	train-mlogloss:0.96545	validation-mlogloss:0.98069
[268]	train-mlogloss:0.96498	validation-mlogloss:0.98032
[269]	train-mlogloss:0.96453	validation-mlogloss:0.98010
[270]	train-mlogloss:0.96410	validation-mlogloss:0.97984
[271]	train-mlogloss:0.96365	validation-mlogloss:0.97959
[272]	train-mlogloss:0.96317	validation-mlogloss:0.97931
[273]	train-mlogloss:0.96281	validation-mlogloss:0.97896
[274]	train-mlogloss:0.96242	validation-mlogloss:0.97875
[275]	train-mlogloss:0.96196	validation-mlogloss:0.97840
[276]	train-mlogloss:0.96151	validation-mlogloss:0.97810
[277]	train-mlogloss:0.96110	validation-mlogloss:0.97787
[278]	train-mlogloss:0.96071	validation-mlogloss:0.97755
[279]	train-mlogloss:0.96027	validation-mlogloss:0.97737
[280]	train-mlogloss:0.95976	validation-mlogloss:0.97694
[281]	train-mlogloss:0.95930	validation-mlogloss:0.97666
[282]	train-mlogloss:0.95888	validation-mlogloss:0.97622
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[585]	train-mlogloss:0.89006	validation-mlogloss:0.92895
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[595]	train-mlogloss:0.88920	validation-mlogloss:0.92821
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[597]	train-mlogloss:0.88902	validation-mlogloss:0.92807
[598]	train-mlogloss:0.88890	validation-mlogloss:0.92806
[599]	train-mlogloss:0.88885	validation-mlogloss:0.92804
[600]	train-mlogloss:0.88874	validation-mlogloss:0.92796
[601]	train-mlogloss:0.88868	validation-mlogloss:0.92790
[602]	train-mlogloss:0.88860	validation-mlogloss:0.92782
[603]	train-mlogloss:0.88851	validation-mlogloss:0.92777
[604]	train-mlogloss:0.88846	validation-mlogloss:0.92775
[605]	train-mlogloss:0.88841	validation-mlogloss:0.92775
[606]	train-mlogloss:0.88832	validation-mlogloss:0.92764
[607]	train-mlogloss:0.88826	validation-mlogloss:0.92761
[608]	train-mlogloss:0.88817	validation-mlogloss:0.92753
[609]	train-mlogloss:0.88807	validation-mlogloss:0.92755
[610]	train-mlogloss:0.88796	validation-mlogloss:0.92742
[611]	train-mlogloss:0.88786	validation-mlogloss:0.92733
[612]	train-mlogloss:0.88776	validation-mlogloss:0.92722
[613]	train-mlogloss:0.88768	validation-mlogloss:0.92715
[614]	train-mlogloss:0.88756	validation-mlogloss:0.92703
[615]	train-mlogloss:0.88740	validation-mlogloss:0.92698
[616]	train-mlogloss:0.88733	validation-mlogloss:0.92697
[617]	train-mlogloss:0.88721	validation-mlogloss:0.92684
[618]	train-mlogloss:0.88715	validation-mlogloss:0.92681
[619]	train-mlogloss:0.88706	validation-mlogloss:0.92673
[620]	train-mlogloss:0.88698	validation-mlogloss:0.92664
[621]	train-mlogloss:0.88691	validation-mlogloss:0.92664
[622]	train-mlogloss:0.88678	validation-mlogloss:0.92653
[623]	train-mlogloss:0.88673	validation-mlogloss:0.92647
[624]	train-mlogloss:0.88666	validation-mlogloss:0.92646
[625]	train-mlogloss:0.88655	validation-mlogloss:0.92634
[626]	train-mlogloss:0.88648	validation-mlogloss:0.92630
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[629]	train-mlogloss:0.88617	validation-mlogloss:0.92610
[630]	train-mlogloss:0.88613	validation-mlogloss:0.92609
[631]	train-mlogloss:0.88604	validation-mlogloss:0.92595
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[633]	train-mlogloss:0.88581	validation-mlogloss:0.92591
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[635]	train-mlogloss:0.88567	validation-mlogloss:0.92582
[636]	train-mlogloss:0.88561	validation-mlogloss:0.92575
[637]	train-mlogloss:0.88556	validation-mlogloss:0.92573
[638]	train-mlogloss:0.88549	validation-mlogloss:0.92573
[639]	train-mlogloss:0.88538	validation-mlogloss:0.92572
[640]	train-mlogloss:0.88531	validation-mlogloss:0.92559
[641]	train-mlogloss:0.88525	validation-mlogloss:0.92556
[642]	train-mlogloss:0.88519	validation-mlogloss:0.92553
[643]	train-mlogloss:0.88514	validation-mlogloss:0.92549
[644]	train-mlogloss:0.88508	validation-mlogloss:0.92541
[645]	train-mlogloss:0.88506	validation-mlogloss:0.92540
[646]	train-mlogloss:0.88501	validation-mlogloss:0.92535
[647]	train-mlogloss:0.88489	validation-mlogloss:0.92527
[648]	train-mlogloss:0.88485	validation-mlogloss:0.92528
[649]	train-mlogloss:0.88483	validation-mlogloss:0.92525
[650]	train-mlogloss:0.88474	validation-mlogloss:0.92519
[651]	train-mlogloss:0.88467	validation-mlogloss:0.92513
[652]	train-mlogloss:0.88463	validation-mlogloss:0.92513
[653]	train-mlogloss:0.88452	validation-mlogloss:0.92506
[654]	train-mlogloss:0.88446	validation-mlogloss:0.92502
[655]	train-mlogloss:0.88439	validation-mlogloss:0.92498
[656]	train-mlogloss:0.88420	validation-mlogloss:0.92484
[657]	train-mlogloss:0.88415	validation-mlogloss:0.92479
[658]	train-mlogloss:0.88412	validation-mlogloss:0.92477
[659]	train-mlogloss:0.88408	validation-mlogloss:0.92471
[660]	train-mlogloss:0.88402	validation-mlogloss:0.92468
[661]	train-mlogloss:0.88394	validation-mlogloss:0.92461
[662]	train-mlogloss:0.88383	validation-mlogloss:0.92456
[663]	train-mlogloss:0.88378	validation-mlogloss:0.92449
[664]	train-mlogloss:0.88371	validation-mlogloss:0.92441
[665]	train-mlogloss:0.88366	validation-mlogloss:0.92437
[666]	train-mlogloss:0.88359	validation-mlogloss:0.92428
[667]	train-mlogloss:0.88354	validation-mlogloss:0.92426
[668]	train-mlogloss:0.88347	validation-mlogloss:0.92422
[669]	train-mlogloss:0.88341	validation-mlogloss:0.92420
[670]	train-mlogloss:0.88337	validation-mlogloss:0.92419
[671]	train-mlogloss:0.88332	validation-mlogloss:0.92414
[672]	train-mlogloss:0.88327	validation-mlogloss:0.92410
[673]	train-mlogloss:0.88319	validation-mlogloss:0.92409
[674]	train-mlogloss:0.88312	validation-mlogloss:0.92403
[675]	train-mlogloss:0.88307	validation-mlogloss:0.92400
[676]	train-mlogloss:0.88297	validation-mlogloss:0.92396
[677]	train-mlogloss:0.88291	validation-mlogloss:0.92389
[678]	train-mlogloss:0.88285	validation-mlogloss:0.92389
[679]	train-mlogloss:0.88281	validation-mlogloss:0.92388
[680]	train-mlogloss:0.88277	validation-mlogloss:0.92384
[681]	train-mlogloss:0.88271	validation-mlogloss:0.92379
[682]	train-mlogloss:0.88258	validation-mlogloss:0.92369
[683]	train-mlogloss:0.88253	validation-mlogloss:0.92369
[684]	train-mlogloss:0.88248	validation-mlogloss:0.92367
[685]	train-mlogloss:0.88242	validation-mlogloss:0.92365
[686]	train-mlogloss:0.88237	validation-mlogloss:0.92360
[687]	train-mlogloss:0.88230	validation-mlogloss:0.92358
[688]	train-mlogloss:0.88218	validation-mlogloss:0.92364
[689]	train-mlogloss:0.88209	validation-mlogloss:0.92362
[690]	train-mlogloss:0.88201	validation-mlogloss:0.92358
[691]	train-mlogloss:0.88194	validation-mlogloss:0.92353
[692]	train-mlogloss:0.88189	validation-mlogloss:0.92353
[693]	train-mlogloss:0.88183	validation-mlogloss:0.92351
[694]	train-mlogloss:0.88176	validation-mlogloss:0.92347
[695]	train-mlogloss:0.88170	validation-mlogloss:0.92341
[696]	train-mlogloss:0.88166	validation-mlogloss:0.92341
[697]	train-mlogloss:0.88156	validation-mlogloss:0.92329
[698]	train-mlogloss:0.88147	validation-mlogloss:0.92318
[699]	train-mlogloss:0.88138	validation-mlogloss:0.92314
[700]	train-mlogloss:0.88133	validation-mlogloss:0.92308
[701]	train-mlogloss:0.88132	validation-mlogloss:0.92306
[702]	train-mlogloss:0.88117	validation-mlogloss:0.92289
[703]	train-mlogloss:0.88109	validation-mlogloss:0.92287
[704]	train-mlogloss:0.88102	validation-mlogloss:0.92286
[705]	train-mlogloss:0.88100	validation-mlogloss:0.92285
[706]	train-mlogloss:0.88092	validation-mlogloss:0.92282
[707]	train-mlogloss:0.88082	validation-mlogloss:0.92279
[708]	train-mlogloss:0.88072	validation-mlogloss:0.92272
[709]	train-mlogloss:0.88064	validation-mlogloss:0.92271
[710]	train-mlogloss:0.88053	validation-mlogloss:0.92264
[711]	train-mlogloss:0.88044	validation-mlogloss:0.92252
[712]	train-mlogloss:0.88036	validation-mlogloss:0.92253
[713]	train-mlogloss:0.88034	validation-mlogloss:0.92251
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[0 2 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.5 [%]
Global accuracy score (test) = 58.64 [%]
Global F1 score (train) = 63.55 [%]
Global F1 score (test) = 59.49 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.42      0.43      0.42       400
MODERATE-INTENSITY       0.53      0.60      0.56       400
         SEDENTARY       0.65      0.71      0.68       400
VIGOROUS-INTENSITY       0.87      0.61      0.72       345

          accuracy                           0.59      1545
         macro avg       0.62      0.59      0.59      1545
      weighted avg       0.61      0.59      0.59      1545


Accuracy capturado en la ejecución 18: 58.64 [%]
F1-score capturado en la ejecución 18: 59.49 [%]

=== EJECUCIÓN 19 ===

--- TRAIN (ejecución 19) ---

--- TEST (ejecución 19) ---
2025-11-04 11:03:52.986578: 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`.
2025-11-04 11:03:52.997893: 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 00:00:1762250633.011463 1082909 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250633.015742 1082909 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250633.025655 1082909 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250633.025670 1082909 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250633.025672 1082909 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250633.025673 1082909 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:03:53.028793: 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:1.38104	validation-mlogloss:1.38078
[1]	train-mlogloss:1.37567	validation-mlogloss:1.37525
[2]	train-mlogloss:1.37060	validation-mlogloss:1.36998
[3]	train-mlogloss:1.36569	validation-mlogloss:1.36500
[4]	train-mlogloss:1.36094	validation-mlogloss:1.36008
[5]	train-mlogloss:1.35597	validation-mlogloss:1.35498
[6]	train-mlogloss:1.35123	validation-mlogloss:1.35021
[7]	train-mlogloss:1.34656	validation-mlogloss:1.34550
[8]	train-mlogloss:1.34175	validation-mlogloss:1.34034
[9]	train-mlogloss:1.33718	validation-mlogloss:1.33564
[10]	train-mlogloss:1.33269	validation-mlogloss:1.33115
[11]	train-mlogloss:1.32833	validation-mlogloss:1.32669
[12]	train-mlogloss:1.32396	validation-mlogloss:1.32232
[13]	train-mlogloss:1.31976	validation-mlogloss:1.31807
[14]	train-mlogloss:1.31569	validation-mlogloss:1.31399
[15]	train-mlogloss:1.31168	validation-mlogloss:1.30983
[16]	train-mlogloss:1.30770	validation-mlogloss:1.30591
[17]	train-mlogloss:1.30380	validation-mlogloss:1.30196
[18]	train-mlogloss:1.29989	validation-mlogloss:1.29793
[19]	train-mlogloss:1.29617	validation-mlogloss:1.29407
[20]	train-mlogloss:1.29262	validation-mlogloss:1.29023
[21]	train-mlogloss:1.28880	validation-mlogloss:1.28616
[22]	train-mlogloss:1.28495	validation-mlogloss:1.28221
[23]	train-mlogloss:1.28095	validation-mlogloss:1.27807
[24]	train-mlogloss:1.27745	validation-mlogloss:1.27470
[25]	train-mlogloss:1.27387	validation-mlogloss:1.27072
[26]	train-mlogloss:1.27052	validation-mlogloss:1.26711
[27]	train-mlogloss:1.26697	validation-mlogloss:1.26351
[28]	train-mlogloss:1.26361	validation-mlogloss:1.26002
[29]	train-mlogloss:1.26029	validation-mlogloss:1.25651
[30]	train-mlogloss:1.25712	validation-mlogloss:1.25322
[31]	train-mlogloss:1.25387	validation-mlogloss:1.24973
[32]	train-mlogloss:1.25059	validation-mlogloss:1.24632
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[626]	train-mlogloss:0.88709	validation-mlogloss:0.93054
[627]	train-mlogloss:0.88704	validation-mlogloss:0.93047
[628]	train-mlogloss:0.88697	validation-mlogloss:0.93041
[629]	train-mlogloss:0.88691	validation-mlogloss:0.93040
[630]	train-mlogloss:0.88683	validation-mlogloss:0.93032
[631]	train-mlogloss:0.88671	validation-mlogloss:0.93029
[632]	train-mlogloss:0.88663	validation-mlogloss:0.93023
[633]	train-mlogloss:0.88651	validation-mlogloss:0.93016
[634]	train-mlogloss:0.88645	validation-mlogloss:0.93012
[635]	train-mlogloss:0.88640	validation-mlogloss:0.93013
[636]	train-mlogloss:0.88629	validation-mlogloss:0.93002
[637]	train-mlogloss:0.88623	validation-mlogloss:0.93001
[638]	train-mlogloss:0.88610	validation-mlogloss:0.92992
[639]	train-mlogloss:0.88599	validation-mlogloss:0.92982
[640]	train-mlogloss:0.88592	validation-mlogloss:0.92979
[641]	train-mlogloss:0.88588	validation-mlogloss:0.92976
[642]	train-mlogloss:0.88580	validation-mlogloss:0.92965
[643]	train-mlogloss:0.88574	validation-mlogloss:0.92960
[644]	train-mlogloss:0.88570	validation-mlogloss:0.92958
[645]	train-mlogloss:0.88563	validation-mlogloss:0.92954
[646]	train-mlogloss:0.88557	validation-mlogloss:0.92951
[647]	train-mlogloss:0.88545	validation-mlogloss:0.92937
[648]	train-mlogloss:0.88538	validation-mlogloss:0.92935
[649]	train-mlogloss:0.88527	validation-mlogloss:0.92925
[650]	train-mlogloss:0.88521	validation-mlogloss:0.92922
[651]	train-mlogloss:0.88511	validation-mlogloss:0.92918
[652]	train-mlogloss:0.88501	validation-mlogloss:0.92913
[653]	train-mlogloss:0.88491	validation-mlogloss:0.92907
[654]	train-mlogloss:0.88482	validation-mlogloss:0.92895
[655]	train-mlogloss:0.88477	validation-mlogloss:0.92887
[656]	train-mlogloss:0.88472	validation-mlogloss:0.92888
[657]	train-mlogloss:0.88468	validation-mlogloss:0.92882
[658]	train-mlogloss:0.88458	validation-mlogloss:0.92869
[659]	train-mlogloss:0.88447	validation-mlogloss:0.92854
[660]	train-mlogloss:0.88439	validation-mlogloss:0.92849
[661]	train-mlogloss:0.88434	validation-mlogloss:0.92842
[662]	train-mlogloss:0.88427	validation-mlogloss:0.92835
[663]	train-mlogloss:0.88421	validation-mlogloss:0.92833
[664]	train-mlogloss:0.88412	validation-mlogloss:0.92834
[665]	train-mlogloss:0.88404	validation-mlogloss:0.92831
[666]	train-mlogloss:0.88396	validation-mlogloss:0.92822
[667]	train-mlogloss:0.88382	validation-mlogloss:0.92818
[668]	train-mlogloss:0.88375	validation-mlogloss:0.92810
[669]	train-mlogloss:0.88368	validation-mlogloss:0.92805
[670]	train-mlogloss:0.88364	validation-mlogloss:0.92801
[671]	train-mlogloss:0.88358	validation-mlogloss:0.92795
[672]	train-mlogloss:0.88349	validation-mlogloss:0.92791
[673]	train-mlogloss:0.88338	validation-mlogloss:0.92788
[674]	train-mlogloss:0.88327	validation-mlogloss:0.92788
[675]	train-mlogloss:0.88323	validation-mlogloss:0.92784
[676]	train-mlogloss:0.88315	validation-mlogloss:0.92777
[677]	train-mlogloss:0.88305	validation-mlogloss:0.92766
[678]	train-mlogloss:0.88299	validation-mlogloss:0.92763
[679]	train-mlogloss:0.88295	validation-mlogloss:0.92760
[680]	train-mlogloss:0.88288	validation-mlogloss:0.92756
[681]	train-mlogloss:0.88278	validation-mlogloss:0.92751
[682]	train-mlogloss:0.88272	validation-mlogloss:0.92744
[683]	train-mlogloss:0.88269	validation-mlogloss:0.92740
[684]	train-mlogloss:0.88266	validation-mlogloss:0.92740
[685]	train-mlogloss:0.88260	validation-mlogloss:0.92734
[686]	train-mlogloss:0.88249	validation-mlogloss:0.92740
[687]	train-mlogloss:0.88247	validation-mlogloss:0.92739
[688]	train-mlogloss:0.88243	validation-mlogloss:0.92741
[689]	train-mlogloss:0.88233	validation-mlogloss:0.92731
[690]	train-mlogloss:0.88226	validation-mlogloss:0.92722
[691]	train-mlogloss:0.88219	validation-mlogloss:0.92716
[692]	train-mlogloss:0.88209	validation-mlogloss:0.92717
[693]	train-mlogloss:0.88204	validation-mlogloss:0.92712
[694]	train-mlogloss:0.88192	validation-mlogloss:0.92702
[695]	train-mlogloss:0.88178	validation-mlogloss:0.92692
[696]	train-mlogloss:0.88165	validation-mlogloss:0.92680
[697]	train-mlogloss:0.88159	validation-mlogloss:0.92675
[698]	train-mlogloss:0.88159	validation-mlogloss:0.92675
[699]	train-mlogloss:0.88153	validation-mlogloss:0.92669
[700]	train-mlogloss:0.88148	validation-mlogloss:0.92666
[701]	train-mlogloss:0.88142	validation-mlogloss:0.92664
[702]	train-mlogloss:0.88131	validation-mlogloss:0.92654
[703]	train-mlogloss:0.88125	validation-mlogloss:0.92653
[704]	train-mlogloss:0.88117	validation-mlogloss:0.92653
[705]	train-mlogloss:0.88112	validation-mlogloss:0.92648
[706]	train-mlogloss:0.88095	validation-mlogloss:0.92642
[707]	train-mlogloss:0.88089	validation-mlogloss:0.92633
[708]	train-mlogloss:0.88084	validation-mlogloss:0.92629
[709]	train-mlogloss:0.88076	validation-mlogloss:0.92628
[710]	train-mlogloss:0.88072	validation-mlogloss:0.92627
[711]	train-mlogloss:0.88068	validation-mlogloss:0.92623
[712]	train-mlogloss:0.88062	validation-mlogloss:0.92619
[713]	train-mlogloss:0.88053	validation-mlogloss:0.92614
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 3]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.66 [%]
Global accuracy score (test) = 61.88 [%]
Global F1 score (train) = 63.79 [%]
Global F1 score (test) = 62.46 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.47      0.46      0.47       400
MODERATE-INTENSITY       0.56      0.65      0.60       400
         SEDENTARY       0.68      0.74      0.71       400
VIGOROUS-INTENSITY       0.87      0.62      0.72       345

          accuracy                           0.62      1545
         macro avg       0.64      0.62      0.62      1545
      weighted avg       0.64      0.62      0.62      1545


Accuracy capturado en la ejecución 19: 61.88 [%]
F1-score capturado en la ejecución 19: 62.46 [%]

=== EJECUCIÓN 20 ===

--- TRAIN (ejecución 20) ---

--- TEST (ejecución 20) ---
2025-11-04 11:04:09.941290: 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`.
2025-11-04 11:04:09.952720: 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 00:00:1762250649.966415 1083238 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250649.970453 1083238 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250649.980684 1083238 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250649.980701 1083238 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250649.980702 1083238 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250649.980703 1083238 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:04:09.983758: 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:1.38084	validation-mlogloss:1.38071
[1]	train-mlogloss:1.37574	validation-mlogloss:1.37565
[2]	train-mlogloss:1.37083	validation-mlogloss:1.37050
[3]	train-mlogloss:1.36579	validation-mlogloss:1.36550
[4]	train-mlogloss:1.36104	validation-mlogloss:1.36076
[5]	train-mlogloss:1.35639	validation-mlogloss:1.35610
[6]	train-mlogloss:1.35192	validation-mlogloss:1.35132
[7]	train-mlogloss:1.34727	validation-mlogloss:1.34673
[8]	train-mlogloss:1.34239	validation-mlogloss:1.34146
[9]	train-mlogloss:1.33798	validation-mlogloss:1.33696
[10]	train-mlogloss:1.33353	validation-mlogloss:1.33211
[11]	train-mlogloss:1.32905	validation-mlogloss:1.32775
[12]	train-mlogloss:1.32485	validation-mlogloss:1.32363
[13]	train-mlogloss:1.32058	validation-mlogloss:1.31929
[14]	train-mlogloss:1.31639	validation-mlogloss:1.31504
[15]	train-mlogloss:1.31190	validation-mlogloss:1.31032
[16]	train-mlogloss:1.30794	validation-mlogloss:1.30617
[17]	train-mlogloss:1.30415	validation-mlogloss:1.30235
[18]	train-mlogloss:1.30025	validation-mlogloss:1.29821
[19]	train-mlogloss:1.29660	validation-mlogloss:1.29428
[20]	train-mlogloss:1.29301	validation-mlogloss:1.29083
[21]	train-mlogloss:1.28942	validation-mlogloss:1.28718
[22]	train-mlogloss:1.28584	validation-mlogloss:1.28343
[23]	train-mlogloss:1.28225	validation-mlogloss:1.27979
[24]	train-mlogloss:1.27861	validation-mlogloss:1.27627
[25]	train-mlogloss:1.27515	validation-mlogloss:1.27263
[26]	train-mlogloss:1.27160	validation-mlogloss:1.26923
[27]	train-mlogloss:1.26819	validation-mlogloss:1.26593
[28]	train-mlogloss:1.26478	validation-mlogloss:1.26243
[29]	train-mlogloss:1.26155	validation-mlogloss:1.25921
[30]	train-mlogloss:1.25832	validation-mlogloss:1.25608
[31]	train-mlogloss:1.25508	validation-mlogloss:1.25246
[32]	train-mlogloss:1.25191	validation-mlogloss:1.24914
[33]	train-mlogloss:1.24848	validation-mlogloss:1.24558
[34]	train-mlogloss:1.24542	validation-mlogloss:1.24231
[35]	train-mlogloss:1.24236	validation-mlogloss:1.23916
[36]	train-mlogloss:1.23936	validation-mlogloss:1.23619
[37]	train-mlogloss:1.23638	validation-mlogloss:1.23320
[38]	train-mlogloss:1.23345	validation-mlogloss:1.23010
[39]	train-mlogloss:1.23063	validation-mlogloss:1.22726
[40]	train-mlogloss:1.22733	validation-mlogloss:1.22358
[41]	train-mlogloss:1.22463	validation-mlogloss:1.22096
[42]	train-mlogloss:1.22199	validation-mlogloss:1.21843
[43]	train-mlogloss:1.21887	validation-mlogloss:1.21490
[44]	train-mlogloss:1.21620	validation-mlogloss:1.21215
[45]	train-mlogloss:1.21351	validation-mlogloss:1.20950
[46]	train-mlogloss:1.21048	validation-mlogloss:1.20633
[47]	train-mlogloss:1.20796	validation-mlogloss:1.20390
[48]	train-mlogloss:1.20533	validation-mlogloss:1.20132
[49]	train-mlogloss:1.20285	validation-mlogloss:1.19884
[50]	train-mlogloss:1.20039	validation-mlogloss:1.19624
[51]	train-mlogloss:1.19786	validation-mlogloss:1.19371
[52]	train-mlogloss:1.19546	validation-mlogloss:1.19154
[53]	train-mlogloss:1.19312	validation-mlogloss:1.18939
[54]	train-mlogloss:1.19077	validation-mlogloss:1.18699
[55]	train-mlogloss:1.18838	validation-mlogloss:1.18474
[56]	train-mlogloss:1.18611	validation-mlogloss:1.18249
[57]	train-mlogloss:1.18390	validation-mlogloss:1.18023
[58]	train-mlogloss:1.18169	validation-mlogloss:1.17812
[59]	train-mlogloss:1.17962	validation-mlogloss:1.17601
[60]	train-mlogloss:1.17703	validation-mlogloss:1.17346
[61]	train-mlogloss:1.17459	validation-mlogloss:1.17114
[62]	train-mlogloss:1.17231	validation-mlogloss:1.16879
[63]	train-mlogloss:1.17012	validation-mlogloss:1.16663
[64]	train-mlogloss:1.16798	validation-mlogloss:1.16437
[65]	train-mlogloss:1.16571	validation-mlogloss:1.16194
[66]	train-mlogloss:1.16331	validation-mlogloss:1.15958
[67]	train-mlogloss:1.16134	validation-mlogloss:1.15780
[68]	train-mlogloss:1.15928	validation-mlogloss:1.15554
[69]	train-mlogloss:1.15726	validation-mlogloss:1.15357
[70]	train-mlogloss:1.15500	validation-mlogloss:1.15154
[71]	train-mlogloss:1.15302	validation-mlogloss:1.14936
[72]	train-mlogloss:1.15116	validation-mlogloss:1.14752
[73]	train-mlogloss:1.14925	validation-mlogloss:1.14547
[74]	train-mlogloss:1.14736	validation-mlogloss:1.14386
[75]	train-mlogloss:1.14548	validation-mlogloss:1.14193
[76]	train-mlogloss:1.14360	validation-mlogloss:1.13988
[77]	train-mlogloss:1.14164	validation-mlogloss:1.13794
[78]	train-mlogloss:1.13974	validation-mlogloss:1.13609
[79]	train-mlogloss:1.13800	validation-mlogloss:1.13432
[80]	train-mlogloss:1.13611	validation-mlogloss:1.13228
[81]	train-mlogloss:1.13431	validation-mlogloss:1.13042
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[673]	train-mlogloss:0.88514	validation-mlogloss:0.92222
[674]	train-mlogloss:0.88510	validation-mlogloss:0.92221
[675]	train-mlogloss:0.88504	validation-mlogloss:0.92215
[676]	train-mlogloss:0.88497	validation-mlogloss:0.92213
[677]	train-mlogloss:0.88486	validation-mlogloss:0.92214
[678]	train-mlogloss:0.88477	validation-mlogloss:0.92209
[679]	train-mlogloss:0.88468	validation-mlogloss:0.92198
[680]	train-mlogloss:0.88459	validation-mlogloss:0.92188
[681]	train-mlogloss:0.88453	validation-mlogloss:0.92186
[682]	train-mlogloss:0.88446	validation-mlogloss:0.92177
[683]	train-mlogloss:0.88434	validation-mlogloss:0.92170
[684]	train-mlogloss:0.88426	validation-mlogloss:0.92162
[685]	train-mlogloss:0.88421	validation-mlogloss:0.92158
[686]	train-mlogloss:0.88417	validation-mlogloss:0.92150
[687]	train-mlogloss:0.88409	validation-mlogloss:0.92142
[688]	train-mlogloss:0.88402	validation-mlogloss:0.92134
[689]	train-mlogloss:0.88392	validation-mlogloss:0.92125
[690]	train-mlogloss:0.88387	validation-mlogloss:0.92125
[691]	train-mlogloss:0.88381	validation-mlogloss:0.92121
[692]	train-mlogloss:0.88371	validation-mlogloss:0.92116
[693]	train-mlogloss:0.88365	validation-mlogloss:0.92113
[694]	train-mlogloss:0.88360	validation-mlogloss:0.92118
[695]	train-mlogloss:0.88355	validation-mlogloss:0.92112
[696]	train-mlogloss:0.88344	validation-mlogloss:0.92106
[697]	train-mlogloss:0.88340	validation-mlogloss:0.92101
[698]	train-mlogloss:0.88327	validation-mlogloss:0.92096
[699]	train-mlogloss:0.88318	validation-mlogloss:0.92092
[700]	train-mlogloss:0.88313	validation-mlogloss:0.92086
[701]	train-mlogloss:0.88311	validation-mlogloss:0.92085
[702]	train-mlogloss:0.88305	validation-mlogloss:0.92081
[703]	train-mlogloss:0.88299	validation-mlogloss:0.92074
[704]	train-mlogloss:0.88295	validation-mlogloss:0.92071
[705]	train-mlogloss:0.88290	validation-mlogloss:0.92067
[706]	train-mlogloss:0.88282	validation-mlogloss:0.92057
[707]	train-mlogloss:0.88274	validation-mlogloss:0.92048
[708]	train-mlogloss:0.88268	validation-mlogloss:0.92044
[709]	train-mlogloss:0.88262	validation-mlogloss:0.92042
[710]	train-mlogloss:0.88257	validation-mlogloss:0.92040
[711]	train-mlogloss:0.88251	validation-mlogloss:0.92037
[712]	train-mlogloss:0.88244	validation-mlogloss:0.92033
[713]	train-mlogloss:0.88238	validation-mlogloss:0.92028
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[1 2 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.11 [%]
Global accuracy score (test) = 59.94 [%]
Global F1 score (train) = 63.17 [%]
Global F1 score (test) = 60.71 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.45      0.46      0.46       400
MODERATE-INTENSITY       0.54      0.61      0.57       400
         SEDENTARY       0.65      0.71      0.68       400
VIGOROUS-INTENSITY       0.86      0.62      0.72       345

          accuracy                           0.60      1545
         macro avg       0.63      0.60      0.61      1545
      weighted avg       0.62      0.60      0.60      1545


Accuracy capturado en la ejecución 20: 59.94 [%]
F1-score capturado en la ejecución 20: 60.71 [%]

=== EJECUCIÓN 21 ===

--- TRAIN (ejecución 21) ---

--- TEST (ejecución 21) ---
2025-11-04 11:04:26.952813: 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`.
2025-11-04 11:04:26.963904: 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 00:00:1762250666.977037 1083565 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250666.981168 1083565 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250666.990953 1083565 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250666.990970 1083565 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250666.990972 1083565 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250666.990973 1083565 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:04:26.994140: 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:1.38098	validation-mlogloss:1.38062
[1]	train-mlogloss:1.37590	validation-mlogloss:1.37531
[2]	train-mlogloss:1.37077	validation-mlogloss:1.36963
[3]	train-mlogloss:1.36601	validation-mlogloss:1.36474
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[5]	train-mlogloss:1.35684	validation-mlogloss:1.35533
[6]	train-mlogloss:1.35212	validation-mlogloss:1.35055
[7]	train-mlogloss:1.34745	validation-mlogloss:1.34567
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[9]	train-mlogloss:1.33837	validation-mlogloss:1.33629
[10]	train-mlogloss:1.33394	validation-mlogloss:1.33166
[11]	train-mlogloss:1.32967	validation-mlogloss:1.32734
[12]	train-mlogloss:1.32544	validation-mlogloss:1.32299
[13]	train-mlogloss:1.32135	validation-mlogloss:1.31888
[14]	train-mlogloss:1.31714	validation-mlogloss:1.31442
[15]	train-mlogloss:1.31322	validation-mlogloss:1.31032
[16]	train-mlogloss:1.30910	validation-mlogloss:1.30590
[17]	train-mlogloss:1.30532	validation-mlogloss:1.30178
[18]	train-mlogloss:1.30141	validation-mlogloss:1.29767
[19]	train-mlogloss:1.29777	validation-mlogloss:1.29389
[20]	train-mlogloss:1.29412	validation-mlogloss:1.28999
[21]	train-mlogloss:1.29052	validation-mlogloss:1.28643
[22]	train-mlogloss:1.28687	validation-mlogloss:1.28262
[23]	train-mlogloss:1.28323	validation-mlogloss:1.27860
[24]	train-mlogloss:1.27979	validation-mlogloss:1.27501
[25]	train-mlogloss:1.27622	validation-mlogloss:1.27146
[26]	train-mlogloss:1.27287	validation-mlogloss:1.26780
[27]	train-mlogloss:1.26908	validation-mlogloss:1.26375
[28]	train-mlogloss:1.26583	validation-mlogloss:1.26038
[29]	train-mlogloss:1.26215	validation-mlogloss:1.25636
[30]	train-mlogloss:1.25895	validation-mlogloss:1.25294
[31]	train-mlogloss:1.25579	validation-mlogloss:1.24966
[32]	train-mlogloss:1.25267	validation-mlogloss:1.24639
[33]	train-mlogloss:1.24950	validation-mlogloss:1.24287
[34]	train-mlogloss:1.24640	validation-mlogloss:1.23956
[35]	train-mlogloss:1.24303	validation-mlogloss:1.23582
[36]	train-mlogloss:1.24018	validation-mlogloss:1.23287
[37]	train-mlogloss:1.23737	validation-mlogloss:1.23006
[38]	train-mlogloss:1.23406	validation-mlogloss:1.22685
[39]	train-mlogloss:1.23121	validation-mlogloss:1.22390
[40]	train-mlogloss:1.22838	validation-mlogloss:1.22085
[41]	train-mlogloss:1.22562	validation-mlogloss:1.21806
[42]	train-mlogloss:1.22292	validation-mlogloss:1.21525
[43]	train-mlogloss:1.22021	validation-mlogloss:1.21257
[44]	train-mlogloss:1.21748	validation-mlogloss:1.20960
[45]	train-mlogloss:1.21491	validation-mlogloss:1.20687
[46]	train-mlogloss:1.21230	validation-mlogloss:1.20429
[47]	train-mlogloss:1.20977	validation-mlogloss:1.20159
[48]	train-mlogloss:1.20710	validation-mlogloss:1.19882
[49]	train-mlogloss:1.20457	validation-mlogloss:1.19608
[50]	train-mlogloss:1.20216	validation-mlogloss:1.19359
[51]	train-mlogloss:1.19965	validation-mlogloss:1.19091
[52]	train-mlogloss:1.19716	validation-mlogloss:1.18813
[53]	train-mlogloss:1.19491	validation-mlogloss:1.18579
[54]	train-mlogloss:1.19247	validation-mlogloss:1.18334
[55]	train-mlogloss:1.19016	validation-mlogloss:1.18089
[56]	train-mlogloss:1.18781	validation-mlogloss:1.17852
[57]	train-mlogloss:1.18545	validation-mlogloss:1.17599
[58]	train-mlogloss:1.18312	validation-mlogloss:1.17336
[59]	train-mlogloss:1.18055	validation-mlogloss:1.17054
[60]	train-mlogloss:1.17834	validation-mlogloss:1.16813
[61]	train-mlogloss:1.17608	validation-mlogloss:1.16585
[62]	train-mlogloss:1.17400	validation-mlogloss:1.16373
[63]	train-mlogloss:1.17183	validation-mlogloss:1.16160
[64]	train-mlogloss:1.16975	validation-mlogloss:1.15958
[65]	train-mlogloss:1.16736	validation-mlogloss:1.15731
[66]	train-mlogloss:1.16524	validation-mlogloss:1.15494
[67]	train-mlogloss:1.16328	validation-mlogloss:1.15304
[68]	train-mlogloss:1.16095	validation-mlogloss:1.15056
[69]	train-mlogloss:1.15864	validation-mlogloss:1.14829
[70]	train-mlogloss:1.15654	validation-mlogloss:1.14590
[71]	train-mlogloss:1.15446	validation-mlogloss:1.14358
[72]	train-mlogloss:1.15262	validation-mlogloss:1.14181
[73]	train-mlogloss:1.15063	validation-mlogloss:1.13990
[74]	train-mlogloss:1.14882	validation-mlogloss:1.13814
[75]	train-mlogloss:1.14678	validation-mlogloss:1.13609
[76]	train-mlogloss:1.14486	validation-mlogloss:1.13414
[77]	train-mlogloss:1.14296	validation-mlogloss:1.13209
[78]	train-mlogloss:1.14107	validation-mlogloss:1.13003
[79]	train-mlogloss:1.13942	validation-mlogloss:1.12838
[80]	train-mlogloss:1.13769	validation-mlogloss:1.12694
[81]	train-mlogloss:1.13602	validation-mlogloss:1.12509
[82]	train-mlogloss:1.13416	validation-mlogloss:1.12324
[83]	train-mlogloss:1.13248	validation-mlogloss:1.12168
[84]	train-mlogloss:1.13052	validation-mlogloss:1.11974
[85]	train-mlogloss:1.12890	validation-mlogloss:1.11802
[86]	train-mlogloss:1.12703	validation-mlogloss:1.11622
[87]	train-mlogloss:1.12508	validation-mlogloss:1.11447
[88]	train-mlogloss:1.12337	validation-mlogloss:1.11271
[89]	train-mlogloss:1.12171	validation-mlogloss:1.11111
[90]	train-mlogloss:1.11984	validation-mlogloss:1.10935
[91]	train-mlogloss:1.11826	validation-mlogloss:1.10778
[92]	train-mlogloss:1.11653	validation-mlogloss:1.10597
[93]	train-mlogloss:1.11496	validation-mlogloss:1.10435
[94]	train-mlogloss:1.11336	validation-mlogloss:1.10289
[95]	train-mlogloss:1.11179	validation-mlogloss:1.10129
[96]	train-mlogloss:1.11019	validation-mlogloss:1.09967
[97]	train-mlogloss:1.10869	validation-mlogloss:1.09810
[98]	train-mlogloss:1.10717	validation-mlogloss:1.09666
[99]	train-mlogloss:1.10571	validation-mlogloss:1.09504
[100]	train-mlogloss:1.10429	validation-mlogloss:1.09357
[101]	train-mlogloss:1.10268	validation-mlogloss:1.09217
[102]	train-mlogloss:1.10113	validation-mlogloss:1.09075
[103]	train-mlogloss:1.09973	validation-mlogloss:1.08926
[104]	train-mlogloss:1.09837	validation-mlogloss:1.08782
[105]	train-mlogloss:1.09711	validation-mlogloss:1.08661
[106]	train-mlogloss:1.09577	validation-mlogloss:1.08516
[107]	train-mlogloss:1.09452	validation-mlogloss:1.08398
[108]	train-mlogloss:1.09306	validation-mlogloss:1.08267
[109]	train-mlogloss:1.09173	validation-mlogloss:1.08133
[110]	train-mlogloss:1.09041	validation-mlogloss:1.07994
[111]	train-mlogloss:1.08923	validation-mlogloss:1.07879
[112]	train-mlogloss:1.08787	validation-mlogloss:1.07756
[113]	train-mlogloss:1.08665	validation-mlogloss:1.07624
[114]	train-mlogloss:1.08529	validation-mlogloss:1.07476
[115]	train-mlogloss:1.08412	validation-mlogloss:1.07371
[116]	train-mlogloss:1.08278	validation-mlogloss:1.07228
[117]	train-mlogloss:1.08149	validation-mlogloss:1.07117
[118]	train-mlogloss:1.08026	validation-mlogloss:1.06983
[119]	train-mlogloss:1.07904	validation-mlogloss:1.06853
[120]	train-mlogloss:1.07784	validation-mlogloss:1.06739
[121]	train-mlogloss:1.07665	validation-mlogloss:1.06622
[122]	train-mlogloss:1.07537	validation-mlogloss:1.06487
[123]	train-mlogloss:1.07420	validation-mlogloss:1.06379
[124]	train-mlogloss:1.07312	validation-mlogloss:1.06290
[125]	train-mlogloss:1.07205	validation-mlogloss:1.06201
[126]	train-mlogloss:1.07088	validation-mlogloss:1.06085
[127]	train-mlogloss:1.06982	validation-mlogloss:1.05985
[128]	train-mlogloss:1.06869	validation-mlogloss:1.05875
[129]	train-mlogloss:1.06752	validation-mlogloss:1.05763
[130]	train-mlogloss:1.06637	validation-mlogloss:1.05637
[131]	train-mlogloss:1.06533	validation-mlogloss:1.05547
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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)
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[1 2 1 ... 3 0 3]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.59 [%]
Global accuracy score (test) = 60.0 [%]
Global F1 score (train) = 63.63 [%]
Global F1 score (test) = 60.74 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.45      0.45      0.45       400
MODERATE-INTENSITY       0.54      0.61      0.57       400
         SEDENTARY       0.65      0.73      0.69       400
VIGOROUS-INTENSITY       0.87      0.62      0.72       345

          accuracy                           0.60      1545
         macro avg       0.63      0.60      0.61      1545
      weighted avg       0.62      0.60      0.60      1545


Accuracy capturado en la ejecución 21: 60.0 [%]
F1-score capturado en la ejecución 21: 60.74 [%]

=== EJECUCIÓN 22 ===

--- TRAIN (ejecución 22) ---

--- TEST (ejecución 22) ---
2025-11-04 11:04:44.115788: 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`.
2025-11-04 11:04:44.127450: 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 00:00:1762250684.140544 1083899 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250684.144633 1083899 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250684.154401 1083899 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250684.154420 1083899 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250684.154421 1083899 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250684.154423 1083899 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:04:44.157587: 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:1.38121	validation-mlogloss:1.38108
[1]	train-mlogloss:1.37623	validation-mlogloss:1.37607
[2]	train-mlogloss:1.37121	validation-mlogloss:1.37082
[3]	train-mlogloss:1.36643	validation-mlogloss:1.36609
[4]	train-mlogloss:1.36165	validation-mlogloss:1.36133
[5]	train-mlogloss:1.35686	validation-mlogloss:1.35632
[6]	train-mlogloss:1.35218	validation-mlogloss:1.35150
[7]	train-mlogloss:1.34755	validation-mlogloss:1.34684
[8]	train-mlogloss:1.34317	validation-mlogloss:1.34221
[9]	train-mlogloss:1.33886	validation-mlogloss:1.33791
[10]	train-mlogloss:1.33452	validation-mlogloss:1.33350
[11]	train-mlogloss:1.33022	validation-mlogloss:1.32909
[12]	train-mlogloss:1.32597	validation-mlogloss:1.32478
[13]	train-mlogloss:1.32189	validation-mlogloss:1.32061
[14]	train-mlogloss:1.31783	validation-mlogloss:1.31646
[15]	train-mlogloss:1.31341	validation-mlogloss:1.31147
[16]	train-mlogloss:1.30943	validation-mlogloss:1.30760
[17]	train-mlogloss:1.30539	validation-mlogloss:1.30339
[18]	train-mlogloss:1.30153	validation-mlogloss:1.29932
[19]	train-mlogloss:1.29773	validation-mlogloss:1.29542
[20]	train-mlogloss:1.29401	validation-mlogloss:1.29142
[21]	train-mlogloss:1.29036	validation-mlogloss:1.28767
[22]	train-mlogloss:1.28676	validation-mlogloss:1.28418
[23]	train-mlogloss:1.28298	validation-mlogloss:1.28040
[24]	train-mlogloss:1.27942	validation-mlogloss:1.27665
[25]	train-mlogloss:1.27600	validation-mlogloss:1.27293
[26]	train-mlogloss:1.27265	validation-mlogloss:1.26945
[27]	train-mlogloss:1.26929	validation-mlogloss:1.26605
[28]	train-mlogloss:1.26587	validation-mlogloss:1.26245
[29]	train-mlogloss:1.26261	validation-mlogloss:1.25900
[30]	train-mlogloss:1.25932	validation-mlogloss:1.25561
[31]	train-mlogloss:1.25627	validation-mlogloss:1.25244
[32]	train-mlogloss:1.25316	validation-mlogloss:1.24947
[33]	train-mlogloss:1.25004	validation-mlogloss:1.24646
[34]	train-mlogloss:1.24705	validation-mlogloss:1.24360
[35]	train-mlogloss:1.24392	validation-mlogloss:1.24054
[36]	train-mlogloss:1.24048	validation-mlogloss:1.23691
[37]	train-mlogloss:1.23750	validation-mlogloss:1.23377
[38]	train-mlogloss:1.23464	validation-mlogloss:1.23111
[39]	train-mlogloss:1.23181	validation-mlogloss:1.22828
[40]	train-mlogloss:1.22889	validation-mlogloss:1.22523
[41]	train-mlogloss:1.22597	validation-mlogloss:1.22231
[42]	train-mlogloss:1.22278	validation-mlogloss:1.21928
[43]	train-mlogloss:1.21999	validation-mlogloss:1.21629
[44]	train-mlogloss:1.21731	validation-mlogloss:1.21364
[45]	train-mlogloss:1.21436	validation-mlogloss:1.21054
[46]	train-mlogloss:1.21172	validation-mlogloss:1.20771
[47]	train-mlogloss:1.20913	validation-mlogloss:1.20481
[48]	train-mlogloss:1.20659	validation-mlogloss:1.20210
[49]	train-mlogloss:1.20408	validation-mlogloss:1.19932
[50]	train-mlogloss:1.20150	validation-mlogloss:1.19652
[51]	train-mlogloss:1.19910	validation-mlogloss:1.19398
[52]	train-mlogloss:1.19671	validation-mlogloss:1.19166
[53]	train-mlogloss:1.19398	validation-mlogloss:1.18884
[54]	train-mlogloss:1.19163	validation-mlogloss:1.18639
[55]	train-mlogloss:1.18927	validation-mlogloss:1.18407
[56]	train-mlogloss:1.18690	validation-mlogloss:1.18172
[57]	train-mlogloss:1.18464	validation-mlogloss:1.17951
[58]	train-mlogloss:1.18240	validation-mlogloss:1.17725
[59]	train-mlogloss:1.18024	validation-mlogloss:1.17497
[60]	train-mlogloss:1.17807	validation-mlogloss:1.17276
[61]	train-mlogloss:1.17579	validation-mlogloss:1.17023
[62]	train-mlogloss:1.17360	validation-mlogloss:1.16783
[63]	train-mlogloss:1.17132	validation-mlogloss:1.16561
[64]	train-mlogloss:1.16916	validation-mlogloss:1.16334
[65]	train-mlogloss:1.16703	validation-mlogloss:1.16119
[66]	train-mlogloss:1.16486	validation-mlogloss:1.15886
[67]	train-mlogloss:1.16280	validation-mlogloss:1.15678
[68]	train-mlogloss:1.16064	validation-mlogloss:1.15459
[69]	train-mlogloss:1.15858	validation-mlogloss:1.15236
[70]	train-mlogloss:1.15657	validation-mlogloss:1.15016
[71]	train-mlogloss:1.15457	validation-mlogloss:1.14810
[72]	train-mlogloss:1.15257	validation-mlogloss:1.14607
[73]	train-mlogloss:1.15074	validation-mlogloss:1.14412
[74]	train-mlogloss:1.14879	validation-mlogloss:1.14225
[75]	train-mlogloss:1.14689	validation-mlogloss:1.14041
[76]	train-mlogloss:1.14495	validation-mlogloss:1.13827
[77]	train-mlogloss:1.14310	validation-mlogloss:1.13634
[78]	train-mlogloss:1.14124	validation-mlogloss:1.13445
[79]	train-mlogloss:1.13936	validation-mlogloss:1.13271
[80]	train-mlogloss:1.13752	validation-mlogloss:1.13078
[81]	train-mlogloss:1.13551	validation-mlogloss:1.12900
[82]	train-mlogloss:1.13376	validation-mlogloss:1.12722
[83]	train-mlogloss:1.13202	validation-mlogloss:1.12550
[84]	train-mlogloss:1.13006	validation-mlogloss:1.12375
[85]	train-mlogloss:1.12832	validation-mlogloss:1.12203
[86]	train-mlogloss:1.12670	validation-mlogloss:1.12034
[87]	train-mlogloss:1.12511	validation-mlogloss:1.11868
[88]	train-mlogloss:1.12350	validation-mlogloss:1.11697
[89]	train-mlogloss:1.12188	validation-mlogloss:1.11535
[90]	train-mlogloss:1.12037	validation-mlogloss:1.11415
[91]	train-mlogloss:1.11879	validation-mlogloss:1.11272
[92]	train-mlogloss:1.11718	validation-mlogloss:1.11096
[93]	train-mlogloss:1.11559	validation-mlogloss:1.10940
[94]	train-mlogloss:1.11400	validation-mlogloss:1.10777
[95]	train-mlogloss:1.11245	validation-mlogloss:1.10630
[96]	train-mlogloss:1.11101	validation-mlogloss:1.10493
[97]	train-mlogloss:1.10944	validation-mlogloss:1.10345
[98]	train-mlogloss:1.10797	validation-mlogloss:1.10192
[99]	train-mlogloss:1.10653	validation-mlogloss:1.10056
[100]	train-mlogloss:1.10505	validation-mlogloss:1.09898
[101]	train-mlogloss:1.10350	validation-mlogloss:1.09724
[102]	train-mlogloss:1.10200	validation-mlogloss:1.09570
[103]	train-mlogloss:1.10061	validation-mlogloss:1.09427
[104]	train-mlogloss:1.09910	validation-mlogloss:1.09285
[105]	train-mlogloss:1.09744	validation-mlogloss:1.09154
[106]	train-mlogloss:1.09602	validation-mlogloss:1.09017
[107]	train-mlogloss:1.09473	validation-mlogloss:1.08879
[108]	train-mlogloss:1.09339	validation-mlogloss:1.08751
[109]	train-mlogloss:1.09208	validation-mlogloss:1.08614
[110]	train-mlogloss:1.09080	validation-mlogloss:1.08505
[111]	train-mlogloss:1.08947	validation-mlogloss:1.08379
[112]	train-mlogloss:1.08809	validation-mlogloss:1.08230
[113]	train-mlogloss:1.08682	validation-mlogloss:1.08091
[114]	train-mlogloss:1.08548	validation-mlogloss:1.07980
[115]	train-mlogloss:1.08425	validation-mlogloss:1.07864
[116]	train-mlogloss:1.08303	validation-mlogloss:1.07762
[117]	train-mlogloss:1.08163	validation-mlogloss:1.07645
[118]	train-mlogloss:1.08038	validation-mlogloss:1.07517
[119]	train-mlogloss:1.07914	validation-mlogloss:1.07404
[120]	train-mlogloss:1.07803	validation-mlogloss:1.07313
[121]	train-mlogloss:1.07680	validation-mlogloss:1.07177
[122]	train-mlogloss:1.07563	validation-mlogloss:1.07071
[123]	train-mlogloss:1.07448	validation-mlogloss:1.06952
[124]	train-mlogloss:1.07332	validation-mlogloss:1.06843
[125]	train-mlogloss:1.07227	validation-mlogloss:1.06737
[126]	train-mlogloss:1.07113	validation-mlogloss:1.06636
[127]	train-mlogloss:1.06995	validation-mlogloss:1.06520
[128]	train-mlogloss:1.06875	validation-mlogloss:1.06395
[129]	train-mlogloss:1.06769	validation-mlogloss:1.06300
[130]	train-mlogloss:1.06665	validation-mlogloss:1.06188
[131]	train-mlogloss:1.06552	validation-mlogloss:1.06092
[132]	train-mlogloss:1.06444	validation-mlogloss:1.05984
[133]	train-mlogloss:1.06327	validation-mlogloss:1.05876
[134]	train-mlogloss:1.06227	validation-mlogloss:1.05788
[135]	train-mlogloss:1.06119	validation-mlogloss:1.05693
[136]	train-mlogloss:1.06013	validation-mlogloss:1.05589
[137]	train-mlogloss:1.05907	validation-mlogloss:1.05492
[138]	train-mlogloss:1.05785	validation-mlogloss:1.05386
[139]	train-mlogloss:1.05672	validation-mlogloss:1.05256
[140]	train-mlogloss:1.05572	validation-mlogloss:1.05164
[141]	train-mlogloss:1.05464	validation-mlogloss:1.05043
[142]	train-mlogloss:1.05352	validation-mlogloss:1.04929
[143]	train-mlogloss:1.05250	validation-mlogloss:1.04840
[144]	train-mlogloss:1.05156	validation-mlogloss:1.04744
[145]	train-mlogloss:1.05067	validation-mlogloss:1.04650
[146]	train-mlogloss:1.04974	validation-mlogloss:1.04564
[147]	train-mlogloss:1.04878	validation-mlogloss:1.04482
[148]	train-mlogloss:1.04790	validation-mlogloss:1.04406
[149]	train-mlogloss:1.04693	validation-mlogloss:1.04322
[150]	train-mlogloss:1.04584	validation-mlogloss:1.04233
[151]	train-mlogloss:1.04494	validation-mlogloss:1.04145
[152]	train-mlogloss:1.04406	validation-mlogloss:1.04058
[153]	train-mlogloss:1.04304	validation-mlogloss:1.03943
[154]	train-mlogloss:1.04215	validation-mlogloss:1.03866
[155]	train-mlogloss:1.04129	validation-mlogloss:1.03793
[156]	train-mlogloss:1.04042	validation-mlogloss:1.03699
[157]	train-mlogloss:1.03938	validation-mlogloss:1.03610
[158]	train-mlogloss:1.03854	validation-mlogloss:1.03541
[159]	train-mlogloss:1.03761	validation-mlogloss:1.03455
[160]	train-mlogloss:1.03666	validation-mlogloss:1.03347
[161]	train-mlogloss:1.03579	validation-mlogloss:1.03270
[162]	train-mlogloss:1.03491	validation-mlogloss:1.03201
[163]	train-mlogloss:1.03410	validation-mlogloss:1.03124
[164]	train-mlogloss:1.03320	validation-mlogloss:1.03036
[165]	train-mlogloss:1.03236	validation-mlogloss:1.02947
[166]	train-mlogloss:1.03147	validation-mlogloss:1.02863
[167]	train-mlogloss:1.03066	validation-mlogloss:1.02782
[168]	train-mlogloss:1.02967	validation-mlogloss:1.02694
[169]	train-mlogloss:1.02887	validation-mlogloss:1.02630
[170]	train-mlogloss:1.02802	validation-mlogloss:1.02552
[171]	train-mlogloss:1.02720	validation-mlogloss:1.02483
[172]	train-mlogloss:1.02636	validation-mlogloss:1.02418
[173]	train-mlogloss:1.02554	validation-mlogloss:1.02336
[174]	train-mlogloss:1.02477	validation-mlogloss:1.02260
[175]	train-mlogloss:1.02395	validation-mlogloss:1.02196
[176]	train-mlogloss:1.02317	validation-mlogloss:1.02127
[177]	train-mlogloss:1.02235	validation-mlogloss:1.02055
[178]	train-mlogloss:1.02141	validation-mlogloss:1.01981
[179]	train-mlogloss:1.02058	validation-mlogloss:1.01897
[180]	train-mlogloss:1.01968	validation-mlogloss:1.01826
[181]	train-mlogloss:1.01899	validation-mlogloss:1.01763
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[679]	train-mlogloss:0.88429	validation-mlogloss:0.92404
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[681]	train-mlogloss:0.88418	validation-mlogloss:0.92391
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[684]	train-mlogloss:0.88400	validation-mlogloss:0.92377
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[687]	train-mlogloss:0.88382	validation-mlogloss:0.92355
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[689]	train-mlogloss:0.88372	validation-mlogloss:0.92353
[690]	train-mlogloss:0.88367	validation-mlogloss:0.92349
[691]	train-mlogloss:0.88359	validation-mlogloss:0.92344
[692]	train-mlogloss:0.88353	validation-mlogloss:0.92342
[693]	train-mlogloss:0.88347	validation-mlogloss:0.92338
[694]	train-mlogloss:0.88339	validation-mlogloss:0.92336
[695]	train-mlogloss:0.88328	validation-mlogloss:0.92324
[696]	train-mlogloss:0.88323	validation-mlogloss:0.92316
[697]	train-mlogloss:0.88317	validation-mlogloss:0.92310
[698]	train-mlogloss:0.88313	validation-mlogloss:0.92308
[699]	train-mlogloss:0.88308	validation-mlogloss:0.92305
[700]	train-mlogloss:0.88303	validation-mlogloss:0.92300
[701]	train-mlogloss:0.88298	validation-mlogloss:0.92299
[702]	train-mlogloss:0.88290	validation-mlogloss:0.92295
[703]	train-mlogloss:0.88285	validation-mlogloss:0.92290
[704]	train-mlogloss:0.88278	validation-mlogloss:0.92285
[705]	train-mlogloss:0.88268	validation-mlogloss:0.92278
[706]	train-mlogloss:0.88263	validation-mlogloss:0.92277
[707]	train-mlogloss:0.88259	validation-mlogloss:0.92276
[708]	train-mlogloss:0.88252	validation-mlogloss:0.92275
[709]	train-mlogloss:0.88241	validation-mlogloss:0.92271
[710]	train-mlogloss:0.88232	validation-mlogloss:0.92263
[711]	train-mlogloss:0.88225	validation-mlogloss:0.92259
[712]	train-mlogloss:0.88219	validation-mlogloss:0.92260
[713]	train-mlogloss:0.88214	validation-mlogloss:0.92261
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)
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 0 ... 3 0 3]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.23 [%]
Global accuracy score (test) = 60.39 [%]
Global F1 score (train) = 63.31 [%]
Global F1 score (test) = 61.14 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.44      0.46      0.45       400
MODERATE-INTENSITY       0.56      0.64      0.60       400
         SEDENTARY       0.67      0.69      0.68       400
VIGOROUS-INTENSITY       0.85      0.62      0.72       345

          accuracy                           0.60      1545
         macro avg       0.63      0.60      0.61      1545
      weighted avg       0.62      0.60      0.61      1545


Accuracy capturado en la ejecución 22: 60.39 [%]
F1-score capturado en la ejecución 22: 61.14 [%]

=== EJECUCIÓN 23 ===

--- TRAIN (ejecución 23) ---

--- TEST (ejecución 23) ---
2025-11-04 11:05:01.122040: 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`.
2025-11-04 11:05:01.133193: 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 00:00:1762250701.146838 1084210 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250701.151117 1084210 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250701.161162 1084210 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250701.161179 1084210 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250701.161181 1084210 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250701.161189 1084210 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:05:01.164133: 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:1.38100	validation-mlogloss:1.38088
[1]	train-mlogloss:1.37591	validation-mlogloss:1.37570
[2]	train-mlogloss:1.37095	validation-mlogloss:1.37064
[3]	train-mlogloss:1.36590	validation-mlogloss:1.36575
[4]	train-mlogloss:1.36091	validation-mlogloss:1.36030
[5]	train-mlogloss:1.35627	validation-mlogloss:1.35572
[6]	train-mlogloss:1.35153	validation-mlogloss:1.35098
[7]	train-mlogloss:1.34661	validation-mlogloss:1.34597
[8]	train-mlogloss:1.34201	validation-mlogloss:1.34134
[9]	train-mlogloss:1.33748	validation-mlogloss:1.33667
[10]	train-mlogloss:1.33300	validation-mlogloss:1.33216
[11]	train-mlogloss:1.32855	validation-mlogloss:1.32757
[12]	train-mlogloss:1.32435	validation-mlogloss:1.32337
[13]	train-mlogloss:1.31983	validation-mlogloss:1.31856
[14]	train-mlogloss:1.31569	validation-mlogloss:1.31454
[15]	train-mlogloss:1.31158	validation-mlogloss:1.31008
[16]	train-mlogloss:1.30768	validation-mlogloss:1.30592
[17]	train-mlogloss:1.30370	validation-mlogloss:1.30206
[18]	train-mlogloss:1.29976	validation-mlogloss:1.29805
[19]	train-mlogloss:1.29601	validation-mlogloss:1.29409
[20]	train-mlogloss:1.29233	validation-mlogloss:1.29015
[21]	train-mlogloss:1.28857	validation-mlogloss:1.28625
[22]	train-mlogloss:1.28494	validation-mlogloss:1.28271
[23]	train-mlogloss:1.28102	validation-mlogloss:1.27857
[24]	train-mlogloss:1.27748	validation-mlogloss:1.27507
[25]	train-mlogloss:1.27400	validation-mlogloss:1.27133
[26]	train-mlogloss:1.27027	validation-mlogloss:1.26768
[27]	train-mlogloss:1.26659	validation-mlogloss:1.26398
[28]	train-mlogloss:1.26284	validation-mlogloss:1.25989
[29]	train-mlogloss:1.25944	validation-mlogloss:1.25646
[30]	train-mlogloss:1.25606	validation-mlogloss:1.25302
[31]	train-mlogloss:1.25271	validation-mlogloss:1.24968
[32]	train-mlogloss:1.24963	validation-mlogloss:1.24659
[33]	train-mlogloss:1.24655	validation-mlogloss:1.24349
[34]	train-mlogloss:1.24335	validation-mlogloss:1.24019
[35]	train-mlogloss:1.24029	validation-mlogloss:1.23709
[36]	train-mlogloss:1.23722	validation-mlogloss:1.23386
[37]	train-mlogloss:1.23429	validation-mlogloss:1.23100
[38]	train-mlogloss:1.23137	validation-mlogloss:1.22815
[39]	train-mlogloss:1.22805	validation-mlogloss:1.22472
[40]	train-mlogloss:1.22524	validation-mlogloss:1.22210
[41]	train-mlogloss:1.22241	validation-mlogloss:1.21945
[42]	train-mlogloss:1.21960	validation-mlogloss:1.21675
[43]	train-mlogloss:1.21694	validation-mlogloss:1.21429
[44]	train-mlogloss:1.21430	validation-mlogloss:1.21155
[45]	train-mlogloss:1.21166	validation-mlogloss:1.20887
[46]	train-mlogloss:1.20859	validation-mlogloss:1.20561
[47]	train-mlogloss:1.20592	validation-mlogloss:1.20304
[48]	train-mlogloss:1.20323	validation-mlogloss:1.20035
[49]	train-mlogloss:1.20073	validation-mlogloss:1.19770
[50]	train-mlogloss:1.19808	validation-mlogloss:1.19486
[51]	train-mlogloss:1.19553	validation-mlogloss:1.19226
[52]	train-mlogloss:1.19303	validation-mlogloss:1.18983
[53]	train-mlogloss:1.19066	validation-mlogloss:1.18739
[54]	train-mlogloss:1.18790	validation-mlogloss:1.18457
[55]	train-mlogloss:1.18523	validation-mlogloss:1.18171
[56]	train-mlogloss:1.18292	validation-mlogloss:1.17935
[57]	train-mlogloss:1.18058	validation-mlogloss:1.17702
[58]	train-mlogloss:1.17828	validation-mlogloss:1.17464
[59]	train-mlogloss:1.17609	validation-mlogloss:1.17221
[60]	train-mlogloss:1.17365	validation-mlogloss:1.17005
[61]	train-mlogloss:1.17142	validation-mlogloss:1.16796
[62]	train-mlogloss:1.16931	validation-mlogloss:1.16573
[63]	train-mlogloss:1.16708	validation-mlogloss:1.16374
[64]	train-mlogloss:1.16493	validation-mlogloss:1.16164
[65]	train-mlogloss:1.16265	validation-mlogloss:1.15925
[66]	train-mlogloss:1.16049	validation-mlogloss:1.15687
[67]	train-mlogloss:1.15831	validation-mlogloss:1.15475
[68]	train-mlogloss:1.15604	validation-mlogloss:1.15223
[69]	train-mlogloss:1.15395	validation-mlogloss:1.15012
[70]	train-mlogloss:1.15201	validation-mlogloss:1.14837
[71]	train-mlogloss:1.14972	validation-mlogloss:1.14577
[72]	train-mlogloss:1.14778	validation-mlogloss:1.14375
[73]	train-mlogloss:1.14585	validation-mlogloss:1.14188
[74]	train-mlogloss:1.14368	validation-mlogloss:1.13981
[75]	train-mlogloss:1.14183	validation-mlogloss:1.13815
[76]	train-mlogloss:1.13987	validation-mlogloss:1.13610
[77]	train-mlogloss:1.13771	validation-mlogloss:1.13407
[78]	train-mlogloss:1.13558	validation-mlogloss:1.13210
[79]	train-mlogloss:1.13385	validation-mlogloss:1.13065
[80]	train-mlogloss:1.13201	validation-mlogloss:1.12875
[81]	train-mlogloss:1.13018	validation-mlogloss:1.12707
[82]	train-mlogloss:1.12857	validation-mlogloss:1.12560
[83]	train-mlogloss:1.12680	validation-mlogloss:1.12383
[84]	train-mlogloss:1.12498	validation-mlogloss:1.12197
[85]	train-mlogloss:1.12333	validation-mlogloss:1.12028
[86]	train-mlogloss:1.12158	validation-mlogloss:1.11850
[87]	train-mlogloss:1.11964	validation-mlogloss:1.11660
[88]	train-mlogloss:1.11800	validation-mlogloss:1.11497
[89]	train-mlogloss:1.11641	validation-mlogloss:1.11352
[90]	train-mlogloss:1.11473	validation-mlogloss:1.11199
[91]	train-mlogloss:1.11321	validation-mlogloss:1.11032
[92]	train-mlogloss:1.11155	validation-mlogloss:1.10865
[93]	train-mlogloss:1.10991	validation-mlogloss:1.10690
[94]	train-mlogloss:1.10850	validation-mlogloss:1.10579
[95]	train-mlogloss:1.10702	validation-mlogloss:1.10428
[96]	train-mlogloss:1.10557	validation-mlogloss:1.10311
[97]	train-mlogloss:1.10402	validation-mlogloss:1.10164
[98]	train-mlogloss:1.10250	validation-mlogloss:1.10007
[99]	train-mlogloss:1.10097	validation-mlogloss:1.09845
[100]	train-mlogloss:1.09957	validation-mlogloss:1.09715
[101]	train-mlogloss:1.09803	validation-mlogloss:1.09583
[102]	train-mlogloss:1.09647	validation-mlogloss:1.09441
[103]	train-mlogloss:1.09500	validation-mlogloss:1.09295
[104]	train-mlogloss:1.09351	validation-mlogloss:1.09145
[105]	train-mlogloss:1.09185	validation-mlogloss:1.08975
[106]	train-mlogloss:1.09038	validation-mlogloss:1.08822
[107]	train-mlogloss:1.08894	validation-mlogloss:1.08679
[108]	train-mlogloss:1.08753	validation-mlogloss:1.08530
[109]	train-mlogloss:1.08620	validation-mlogloss:1.08391
[110]	train-mlogloss:1.08481	validation-mlogloss:1.08252
[111]	train-mlogloss:1.08347	validation-mlogloss:1.08131
[112]	train-mlogloss:1.08212	validation-mlogloss:1.07996
[113]	train-mlogloss:1.08079	validation-mlogloss:1.07855
[114]	train-mlogloss:1.07959	validation-mlogloss:1.07744
[115]	train-mlogloss:1.07824	validation-mlogloss:1.07608
[116]	train-mlogloss:1.07699	validation-mlogloss:1.07502
[117]	train-mlogloss:1.07579	validation-mlogloss:1.07394
[118]	train-mlogloss:1.07453	validation-mlogloss:1.07264
[119]	train-mlogloss:1.07337	validation-mlogloss:1.07156
[120]	train-mlogloss:1.07225	validation-mlogloss:1.07045
[121]	train-mlogloss:1.07117	validation-mlogloss:1.06950
[122]	train-mlogloss:1.06995	validation-mlogloss:1.06825
[123]	train-mlogloss:1.06872	validation-mlogloss:1.06708
[124]	train-mlogloss:1.06764	validation-mlogloss:1.06596
[125]	train-mlogloss:1.06642	validation-mlogloss:1.06481
[126]	train-mlogloss:1.06535	validation-mlogloss:1.06396
[127]	train-mlogloss:1.06421	validation-mlogloss:1.06306
[128]	train-mlogloss:1.06307	validation-mlogloss:1.06199
[129]	train-mlogloss:1.06196	validation-mlogloss:1.06104
[130]	train-mlogloss:1.06084	validation-mlogloss:1.05979
[131]	train-mlogloss:1.05968	validation-mlogloss:1.05871
[132]	train-mlogloss:1.05856	validation-mlogloss:1.05762
[133]	train-mlogloss:1.05750	validation-mlogloss:1.05680
[134]	train-mlogloss:1.05621	validation-mlogloss:1.05582
[135]	train-mlogloss:1.05514	validation-mlogloss:1.05479
[136]	train-mlogloss:1.05408	validation-mlogloss:1.05382
[137]	train-mlogloss:1.05306	validation-mlogloss:1.05275
[138]	train-mlogloss:1.05211	validation-mlogloss:1.05202
[139]	train-mlogloss:1.05109	validation-mlogloss:1.05100
[140]	train-mlogloss:1.05002	validation-mlogloss:1.04988
[141]	train-mlogloss:1.04896	validation-mlogloss:1.04873
[142]	train-mlogloss:1.04799	validation-mlogloss:1.04790
[143]	train-mlogloss:1.04693	validation-mlogloss:1.04692
[144]	train-mlogloss:1.04598	validation-mlogloss:1.04605
[145]	train-mlogloss:1.04510	validation-mlogloss:1.04527
[146]	train-mlogloss:1.04413	validation-mlogloss:1.04441
[147]	train-mlogloss:1.04312	validation-mlogloss:1.04349
[148]	train-mlogloss:1.04219	validation-mlogloss:1.04268
[149]	train-mlogloss:1.04129	validation-mlogloss:1.04188
[150]	train-mlogloss:1.04033	validation-mlogloss:1.04091
[151]	train-mlogloss:1.03927	validation-mlogloss:1.04018
[152]	train-mlogloss:1.03838	validation-mlogloss:1.03937
[153]	train-mlogloss:1.03748	validation-mlogloss:1.03864
[154]	train-mlogloss:1.03652	validation-mlogloss:1.03778
[155]	train-mlogloss:1.03564	validation-mlogloss:1.03682
[156]	train-mlogloss:1.03473	validation-mlogloss:1.03588
[157]	train-mlogloss:1.03384	validation-mlogloss:1.03505
[158]	train-mlogloss:1.03291	validation-mlogloss:1.03421
[159]	train-mlogloss:1.03214	validation-mlogloss:1.03359
[160]	train-mlogloss:1.03128	validation-mlogloss:1.03288
[161]	train-mlogloss:1.03050	validation-mlogloss:1.03216
[162]	train-mlogloss:1.02964	validation-mlogloss:1.03157
[163]	train-mlogloss:1.02880	validation-mlogloss:1.03087
[164]	train-mlogloss:1.02774	validation-mlogloss:1.03008
[165]	train-mlogloss:1.02693	validation-mlogloss:1.02943
[166]	train-mlogloss:1.02613	validation-mlogloss:1.02875
[167]	train-mlogloss:1.02530	validation-mlogloss:1.02813
[168]	train-mlogloss:1.02452	validation-mlogloss:1.02751
[169]	train-mlogloss:1.02371	validation-mlogloss:1.02686
[170]	train-mlogloss:1.02289	validation-mlogloss:1.02614
[171]	train-mlogloss:1.02209	validation-mlogloss:1.02544
[172]	train-mlogloss:1.02142	validation-mlogloss:1.02510
[173]	train-mlogloss:1.02067	validation-mlogloss:1.02445
[174]	train-mlogloss:1.01987	validation-mlogloss:1.02358
[175]	train-mlogloss:1.01910	validation-mlogloss:1.02303
[176]	train-mlogloss:1.01833	validation-mlogloss:1.02222
[177]	train-mlogloss:1.01761	validation-mlogloss:1.02148
[178]	train-mlogloss:1.01681	validation-mlogloss:1.02064
[179]	train-mlogloss:1.01606	validation-mlogloss:1.02002
[180]	train-mlogloss:1.01536	validation-mlogloss:1.01941
[181]	train-mlogloss:1.01469	validation-mlogloss:1.01882
[182]	train-mlogloss:1.01385	validation-mlogloss:1.01809
[183]	train-mlogloss:1.01308	validation-mlogloss:1.01741
[184]	train-mlogloss:1.01238	validation-mlogloss:1.01680
[185]	train-mlogloss:1.01170	validation-mlogloss:1.01647
[186]	train-mlogloss:1.01083	validation-mlogloss:1.01573
[187]	train-mlogloss:1.01025	validation-mlogloss:1.01514
[188]	train-mlogloss:1.00946	validation-mlogloss:1.01429
[189]	train-mlogloss:1.00865	validation-mlogloss:1.01365
[190]	train-mlogloss:1.00802	validation-mlogloss:1.01309
[191]	train-mlogloss:1.00723	validation-mlogloss:1.01242
[192]	train-mlogloss:1.00653	validation-mlogloss:1.01176
[193]	train-mlogloss:1.00592	validation-mlogloss:1.01112
[194]	train-mlogloss:1.00527	validation-mlogloss:1.01051
[195]	train-mlogloss:1.00451	validation-mlogloss:1.00980
[196]	train-mlogloss:1.00386	validation-mlogloss:1.00916
[197]	train-mlogloss:1.00314	validation-mlogloss:1.00863
[198]	train-mlogloss:1.00245	validation-mlogloss:1.00799
[199]	train-mlogloss:1.00175	validation-mlogloss:1.00741
[200]	train-mlogloss:1.00107	validation-mlogloss:1.00682
[201]	train-mlogloss:1.00040	validation-mlogloss:1.00612
[202]	train-mlogloss:0.99980	validation-mlogloss:1.00566
[203]	train-mlogloss:0.99916	validation-mlogloss:1.00498
[204]	train-mlogloss:0.99854	validation-mlogloss:1.00437
[205]	train-mlogloss:0.99793	validation-mlogloss:1.00411
[206]	train-mlogloss:0.99728	validation-mlogloss:1.00364
[207]	train-mlogloss:0.99660	validation-mlogloss:1.00329
[208]	train-mlogloss:0.99605	validation-mlogloss:1.00291
[209]	train-mlogloss:0.99532	validation-mlogloss:1.00244
[210]	train-mlogloss:0.99473	validation-mlogloss:1.00202
[211]	train-mlogloss:0.99411	validation-mlogloss:1.00160
[212]	train-mlogloss:0.99352	validation-mlogloss:1.00107
[213]	train-mlogloss:0.99300	validation-mlogloss:1.00072
[214]	train-mlogloss:0.99236	validation-mlogloss:1.00015
[215]	train-mlogloss:0.99176	validation-mlogloss:0.99968
[216]	train-mlogloss:0.99112	validation-mlogloss:0.99912
[217]	train-mlogloss:0.99055	validation-mlogloss:0.99867
[218]	train-mlogloss:0.98990	validation-mlogloss:0.99807
[219]	train-mlogloss:0.98931	validation-mlogloss:0.99765
[220]	train-mlogloss:0.98869	validation-mlogloss:0.99699
[221]	train-mlogloss:0.98792	validation-mlogloss:0.99648
[222]	train-mlogloss:0.98742	validation-mlogloss:0.99619
[223]	train-mlogloss:0.98688	validation-mlogloss:0.99588
[224]	train-mlogloss:0.98629	validation-mlogloss:0.99548
[225]	train-mlogloss:0.98571	validation-mlogloss:0.99509
[226]	train-mlogloss:0.98520	validation-mlogloss:0.99469
[227]	train-mlogloss:0.98466	validation-mlogloss:0.99427
[228]	train-mlogloss:0.98414	validation-mlogloss:0.99398
[229]	train-mlogloss:0.98349	validation-mlogloss:0.99348
[230]	train-mlogloss:0.98280	validation-mlogloss:0.99299
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[641]	train-mlogloss:0.88129	validation-mlogloss:0.92733
[642]	train-mlogloss:0.88123	validation-mlogloss:0.92732
[643]	train-mlogloss:0.88116	validation-mlogloss:0.92726
[644]	train-mlogloss:0.88107	validation-mlogloss:0.92724
[645]	train-mlogloss:0.88096	validation-mlogloss:0.92715
[646]	train-mlogloss:0.88092	validation-mlogloss:0.92714
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[648]	train-mlogloss:0.88072	validation-mlogloss:0.92702
[649]	train-mlogloss:0.88066	validation-mlogloss:0.92695
[650]	train-mlogloss:0.88061	validation-mlogloss:0.92693
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[652]	train-mlogloss:0.88049	validation-mlogloss:0.92684
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[656]	train-mlogloss:0.88028	validation-mlogloss:0.92670
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[661]	train-mlogloss:0.87992	validation-mlogloss:0.92653
[662]	train-mlogloss:0.87989	validation-mlogloss:0.92651
[663]	train-mlogloss:0.87980	validation-mlogloss:0.92642
[664]	train-mlogloss:0.87978	validation-mlogloss:0.92641
[665]	train-mlogloss:0.87969	validation-mlogloss:0.92631
[666]	train-mlogloss:0.87953	validation-mlogloss:0.92623
[667]	train-mlogloss:0.87944	validation-mlogloss:0.92618
[668]	train-mlogloss:0.87936	validation-mlogloss:0.92610
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[670]	train-mlogloss:0.87921	validation-mlogloss:0.92595
[671]	train-mlogloss:0.87913	validation-mlogloss:0.92592
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[675]	train-mlogloss:0.87884	validation-mlogloss:0.92581
[676]	train-mlogloss:0.87875	validation-mlogloss:0.92575
[677]	train-mlogloss:0.87869	validation-mlogloss:0.92567
[678]	train-mlogloss:0.87860	validation-mlogloss:0.92566
[679]	train-mlogloss:0.87849	validation-mlogloss:0.92552
[680]	train-mlogloss:0.87843	validation-mlogloss:0.92551
[681]	train-mlogloss:0.87837	validation-mlogloss:0.92543
[682]	train-mlogloss:0.87832	validation-mlogloss:0.92544
[683]	train-mlogloss:0.87825	validation-mlogloss:0.92539
[684]	train-mlogloss:0.87821	validation-mlogloss:0.92532
[685]	train-mlogloss:0.87815	validation-mlogloss:0.92531
[686]	train-mlogloss:0.87811	validation-mlogloss:0.92527
[687]	train-mlogloss:0.87806	validation-mlogloss:0.92528
[688]	train-mlogloss:0.87800	validation-mlogloss:0.92526
[689]	train-mlogloss:0.87796	validation-mlogloss:0.92526
[690]	train-mlogloss:0.87788	validation-mlogloss:0.92517
[691]	train-mlogloss:0.87779	validation-mlogloss:0.92508
[692]	train-mlogloss:0.87774	validation-mlogloss:0.92509
[693]	train-mlogloss:0.87765	validation-mlogloss:0.92514
[694]	train-mlogloss:0.87749	validation-mlogloss:0.92503
[695]	train-mlogloss:0.87744	validation-mlogloss:0.92503
[696]	train-mlogloss:0.87739	validation-mlogloss:0.92504
[697]	train-mlogloss:0.87732	validation-mlogloss:0.92502
[698]	train-mlogloss:0.87726	validation-mlogloss:0.92495
[699]	train-mlogloss:0.87721	validation-mlogloss:0.92499
[700]	train-mlogloss:0.87715	validation-mlogloss:0.92494
[701]	train-mlogloss:0.87701	validation-mlogloss:0.92481
[702]	train-mlogloss:0.87691	validation-mlogloss:0.92477
[703]	train-mlogloss:0.87684	validation-mlogloss:0.92472
[704]	train-mlogloss:0.87668	validation-mlogloss:0.92464
[705]	train-mlogloss:0.87662	validation-mlogloss:0.92457
[706]	train-mlogloss:0.87658	validation-mlogloss:0.92459
[707]	train-mlogloss:0.87654	validation-mlogloss:0.92458
[708]	train-mlogloss:0.87649	validation-mlogloss:0.92452
[709]	train-mlogloss:0.87642	validation-mlogloss:0.92452
[710]	train-mlogloss:0.87638	validation-mlogloss:0.92446
[711]	train-mlogloss:0.87631	validation-mlogloss:0.92448
[712]	train-mlogloss:0.87625	validation-mlogloss:0.92444
[713]	train-mlogloss:0.87617	validation-mlogloss:0.92440
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 3]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.61 [%]
Global accuracy score (test) = 60.52 [%]
Global F1 score (train) = 63.73 [%]
Global F1 score (test) = 61.23 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.44      0.47      0.45       400
MODERATE-INTENSITY       0.56      0.61      0.58       400
         SEDENTARY       0.68      0.73      0.70       400
VIGOROUS-INTENSITY       0.83      0.62      0.71       345

          accuracy                           0.61      1545
         macro avg       0.63      0.61      0.61      1545
      weighted avg       0.62      0.61      0.61      1545


Accuracy capturado en la ejecución 23: 60.52 [%]
F1-score capturado en la ejecución 23: 61.23 [%]

=== EJECUCIÓN 24 ===

--- TRAIN (ejecución 24) ---

--- TEST (ejecución 24) ---
2025-11-04 11:05:18.139137: 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`.
2025-11-04 11:05:18.150249: 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 00:00:1762250718.163501 1084525 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250718.167688 1084525 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250718.177870 1084525 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250718.177888 1084525 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250718.177889 1084525 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250718.177890 1084525 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:05:18.180841: 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)
Training a non-convolutional model.
[0]	train-mlogloss:1.38103	validation-mlogloss:1.38072
[1]	train-mlogloss:1.37606	validation-mlogloss:1.37552
[2]	train-mlogloss:1.37093	validation-mlogloss:1.37040
[3]	train-mlogloss:1.36600	validation-mlogloss:1.36558
[4]	train-mlogloss:1.36119	validation-mlogloss:1.36085
[5]	train-mlogloss:1.35650	validation-mlogloss:1.35593
[6]	train-mlogloss:1.35174	validation-mlogloss:1.35059
[7]	train-mlogloss:1.34711	validation-mlogloss:1.34570
[8]	train-mlogloss:1.34251	validation-mlogloss:1.34104
[9]	train-mlogloss:1.33808	validation-mlogloss:1.33656
[10]	train-mlogloss:1.33358	validation-mlogloss:1.33182
[11]	train-mlogloss:1.32918	validation-mlogloss:1.32733
[12]	train-mlogloss:1.32478	validation-mlogloss:1.32271
[13]	train-mlogloss:1.32060	validation-mlogloss:1.31841
[14]	train-mlogloss:1.31649	validation-mlogloss:1.31412
[15]	train-mlogloss:1.31250	validation-mlogloss:1.31010
[16]	train-mlogloss:1.30824	validation-mlogloss:1.30559
[17]	train-mlogloss:1.30391	validation-mlogloss:1.30110
[18]	train-mlogloss:1.29983	validation-mlogloss:1.29678
[19]	train-mlogloss:1.29596	validation-mlogloss:1.29292
[20]	train-mlogloss:1.29213	validation-mlogloss:1.28877
[21]	train-mlogloss:1.28830	validation-mlogloss:1.28489
[22]	train-mlogloss:1.28452	validation-mlogloss:1.28083
[23]	train-mlogloss:1.28098	validation-mlogloss:1.27716
[24]	train-mlogloss:1.27743	validation-mlogloss:1.27357
[25]	train-mlogloss:1.27388	validation-mlogloss:1.26996
[26]	train-mlogloss:1.27034	validation-mlogloss:1.26630
[27]	train-mlogloss:1.26682	validation-mlogloss:1.26254
[28]	train-mlogloss:1.26357	validation-mlogloss:1.25897
[29]	train-mlogloss:1.25988	validation-mlogloss:1.25515
[30]	train-mlogloss:1.25665	validation-mlogloss:1.25163
[31]	train-mlogloss:1.25345	validation-mlogloss:1.24830
[32]	train-mlogloss:1.25026	validation-mlogloss:1.24498
[33]	train-mlogloss:1.24715	validation-mlogloss:1.24204
[34]	train-mlogloss:1.24408	validation-mlogloss:1.23910
[35]	train-mlogloss:1.24102	validation-mlogloss:1.23591
[36]	train-mlogloss:1.23802	validation-mlogloss:1.23269
[37]	train-mlogloss:1.23507	validation-mlogloss:1.22980
[38]	train-mlogloss:1.23227	validation-mlogloss:1.22694
[39]	train-mlogloss:1.22936	validation-mlogloss:1.22395
[40]	train-mlogloss:1.22643	validation-mlogloss:1.22118
[41]	train-mlogloss:1.22366	validation-mlogloss:1.21827
[42]	train-mlogloss:1.22042	validation-mlogloss:1.21490
[43]	train-mlogloss:1.21771	validation-mlogloss:1.21210
[44]	train-mlogloss:1.21505	validation-mlogloss:1.20932
[45]	train-mlogloss:1.21242	validation-mlogloss:1.20685
[46]	train-mlogloss:1.20976	validation-mlogloss:1.20406
[47]	train-mlogloss:1.20676	validation-mlogloss:1.20075
[48]	train-mlogloss:1.20422	validation-mlogloss:1.19835
[49]	train-mlogloss:1.20150	validation-mlogloss:1.19551
[50]	train-mlogloss:1.19860	validation-mlogloss:1.19261
[51]	train-mlogloss:1.19611	validation-mlogloss:1.19007
[52]	train-mlogloss:1.19369	validation-mlogloss:1.18754
[53]	train-mlogloss:1.19127	validation-mlogloss:1.18525
[54]	train-mlogloss:1.18889	validation-mlogloss:1.18295
[55]	train-mlogloss:1.18646	validation-mlogloss:1.18063
[56]	train-mlogloss:1.18417	validation-mlogloss:1.17817
[57]	train-mlogloss:1.18188	validation-mlogloss:1.17581
[58]	train-mlogloss:1.17922	validation-mlogloss:1.17306
[59]	train-mlogloss:1.17661	validation-mlogloss:1.17048
[60]	train-mlogloss:1.17410	validation-mlogloss:1.16794
[61]	train-mlogloss:1.17155	validation-mlogloss:1.16535
[62]	train-mlogloss:1.16936	validation-mlogloss:1.16288
[63]	train-mlogloss:1.16723	validation-mlogloss:1.16080
[64]	train-mlogloss:1.16503	validation-mlogloss:1.15835
[65]	train-mlogloss:1.16286	validation-mlogloss:1.15609
[66]	train-mlogloss:1.16082	validation-mlogloss:1.15410
[67]	train-mlogloss:1.15866	validation-mlogloss:1.15196
[68]	train-mlogloss:1.15656	validation-mlogloss:1.14979
[69]	train-mlogloss:1.15420	validation-mlogloss:1.14747
[70]	train-mlogloss:1.15222	validation-mlogloss:1.14532
[71]	train-mlogloss:1.15022	validation-mlogloss:1.14327
[72]	train-mlogloss:1.14822	validation-mlogloss:1.14123
[73]	train-mlogloss:1.14618	validation-mlogloss:1.13894
[74]	train-mlogloss:1.14428	validation-mlogloss:1.13701
[75]	train-mlogloss:1.14227	validation-mlogloss:1.13496
[76]	train-mlogloss:1.14018	validation-mlogloss:1.13299
[77]	train-mlogloss:1.13838	validation-mlogloss:1.13129
[78]	train-mlogloss:1.13651	validation-mlogloss:1.12926
[79]	train-mlogloss:1.13466	validation-mlogloss:1.12735
[80]	train-mlogloss:1.13282	validation-mlogloss:1.12556
[81]	train-mlogloss:1.13109	validation-mlogloss:1.12376
[82]	train-mlogloss:1.12928	validation-mlogloss:1.12180
[83]	train-mlogloss:1.12746	validation-mlogloss:1.12005
[84]	train-mlogloss:1.12581	validation-mlogloss:1.11829
[85]	train-mlogloss:1.12415	validation-mlogloss:1.11649
[86]	train-mlogloss:1.12252	validation-mlogloss:1.11483
[87]	train-mlogloss:1.12079	validation-mlogloss:1.11288
[88]	train-mlogloss:1.11888	validation-mlogloss:1.11081
[89]	train-mlogloss:1.11723	validation-mlogloss:1.10902
[90]	train-mlogloss:1.11562	validation-mlogloss:1.10735
[91]	train-mlogloss:1.11402	validation-mlogloss:1.10589
[92]	train-mlogloss:1.11237	validation-mlogloss:1.10439
[93]	train-mlogloss:1.11081	validation-mlogloss:1.10268
[94]	train-mlogloss:1.10921	validation-mlogloss:1.10104
[95]	train-mlogloss:1.10776	validation-mlogloss:1.09968
[96]	train-mlogloss:1.10619	validation-mlogloss:1.09816
[97]	train-mlogloss:1.10472	validation-mlogloss:1.09684
[98]	train-mlogloss:1.10319	validation-mlogloss:1.09516
[99]	train-mlogloss:1.10172	validation-mlogloss:1.09377
[100]	train-mlogloss:1.10038	validation-mlogloss:1.09231
[101]	train-mlogloss:1.09888	validation-mlogloss:1.09086
[102]	train-mlogloss:1.09744	validation-mlogloss:1.08942
[103]	train-mlogloss:1.09598	validation-mlogloss:1.08800
[104]	train-mlogloss:1.09469	validation-mlogloss:1.08668
[105]	train-mlogloss:1.09337	validation-mlogloss:1.08532
[106]	train-mlogloss:1.09203	validation-mlogloss:1.08411
[107]	train-mlogloss:1.09064	validation-mlogloss:1.08278
[108]	train-mlogloss:1.08919	validation-mlogloss:1.08151
[109]	train-mlogloss:1.08783	validation-mlogloss:1.08033
[110]	train-mlogloss:1.08644	validation-mlogloss:1.07906
[111]	train-mlogloss:1.08517	validation-mlogloss:1.07794
[112]	train-mlogloss:1.08391	validation-mlogloss:1.07686
[113]	train-mlogloss:1.08264	validation-mlogloss:1.07556
[114]	train-mlogloss:1.08138	validation-mlogloss:1.07452
[115]	train-mlogloss:1.08007	validation-mlogloss:1.07304
[116]	train-mlogloss:1.07880	validation-mlogloss:1.07182
[117]	train-mlogloss:1.07745	validation-mlogloss:1.07042
[118]	train-mlogloss:1.07599	validation-mlogloss:1.06906
[119]	train-mlogloss:1.07482	validation-mlogloss:1.06783
[120]	train-mlogloss:1.07355	validation-mlogloss:1.06650
[121]	train-mlogloss:1.07228	validation-mlogloss:1.06523
[122]	train-mlogloss:1.07113	validation-mlogloss:1.06408
[123]	train-mlogloss:1.06997	validation-mlogloss:1.06296
[124]	train-mlogloss:1.06882	validation-mlogloss:1.06203
[125]	train-mlogloss:1.06771	validation-mlogloss:1.06105
[126]	train-mlogloss:1.06661	validation-mlogloss:1.06008
[127]	train-mlogloss:1.06548	validation-mlogloss:1.05901
[128]	train-mlogloss:1.06445	validation-mlogloss:1.05819
[129]	train-mlogloss:1.06331	validation-mlogloss:1.05724
[130]	train-mlogloss:1.06221	validation-mlogloss:1.05635
[131]	train-mlogloss:1.06111	validation-mlogloss:1.05524
[132]	train-mlogloss:1.06003	validation-mlogloss:1.05425
[133]	train-mlogloss:1.05904	validation-mlogloss:1.05349
[134]	train-mlogloss:1.05796	validation-mlogloss:1.05250
[135]	train-mlogloss:1.05694	validation-mlogloss:1.05154
[136]	train-mlogloss:1.05583	validation-mlogloss:1.05053
[137]	train-mlogloss:1.05471	validation-mlogloss:1.04940
[138]	train-mlogloss:1.05358	validation-mlogloss:1.04834
[139]	train-mlogloss:1.05256	validation-mlogloss:1.04750
[140]	train-mlogloss:1.05150	validation-mlogloss:1.04666
[141]	train-mlogloss:1.05040	validation-mlogloss:1.04562
[142]	train-mlogloss:1.04937	validation-mlogloss:1.04463
[143]	train-mlogloss:1.04839	validation-mlogloss:1.04372
[144]	train-mlogloss:1.04737	validation-mlogloss:1.04276
[145]	train-mlogloss:1.04640	validation-mlogloss:1.04174
[146]	train-mlogloss:1.04540	validation-mlogloss:1.04072
[147]	train-mlogloss:1.04448	validation-mlogloss:1.04002
[148]	train-mlogloss:1.04350	validation-mlogloss:1.03891
[149]	train-mlogloss:1.04254	validation-mlogloss:1.03796
[150]	train-mlogloss:1.04170	validation-mlogloss:1.03715
[151]	train-mlogloss:1.04070	validation-mlogloss:1.03615
[152]	train-mlogloss:1.03973	validation-mlogloss:1.03527
[153]	train-mlogloss:1.03886	validation-mlogloss:1.03449
[154]	train-mlogloss:1.03784	validation-mlogloss:1.03343
[155]	train-mlogloss:1.03701	validation-mlogloss:1.03274
[156]	train-mlogloss:1.03615	validation-mlogloss:1.03207
[157]	train-mlogloss:1.03528	validation-mlogloss:1.03128
[158]	train-mlogloss:1.03437	validation-mlogloss:1.03032
[159]	train-mlogloss:1.03348	validation-mlogloss:1.02946
[160]	train-mlogloss:1.03267	validation-mlogloss:1.02862
[161]	train-mlogloss:1.03182	validation-mlogloss:1.02775
[162]	train-mlogloss:1.03101	validation-mlogloss:1.02708
[163]	train-mlogloss:1.03011	validation-mlogloss:1.02642
[164]	train-mlogloss:1.02932	validation-mlogloss:1.02568
[165]	train-mlogloss:1.02855	validation-mlogloss:1.02500
[166]	train-mlogloss:1.02768	validation-mlogloss:1.02434
[167]	train-mlogloss:1.02676	validation-mlogloss:1.02357
[168]	train-mlogloss:1.02595	validation-mlogloss:1.02290
[169]	train-mlogloss:1.02501	validation-mlogloss:1.02216
[170]	train-mlogloss:1.02416	validation-mlogloss:1.02153
[171]	train-mlogloss:1.02331	validation-mlogloss:1.02085
[172]	train-mlogloss:1.02255	validation-mlogloss:1.02024
[173]	train-mlogloss:1.02182	validation-mlogloss:1.01944
[174]	train-mlogloss:1.02101	validation-mlogloss:1.01887
[175]	train-mlogloss:1.02016	validation-mlogloss:1.01822
[176]	train-mlogloss:1.01935	validation-mlogloss:1.01760
[177]	train-mlogloss:1.01854	validation-mlogloss:1.01696
[178]	train-mlogloss:1.01779	validation-mlogloss:1.01634
[179]	train-mlogloss:1.01701	validation-mlogloss:1.01565
[180]	train-mlogloss:1.01618	validation-mlogloss:1.01488
[181]	train-mlogloss:1.01531	validation-mlogloss:1.01411
[182]	train-mlogloss:1.01463	validation-mlogloss:1.01351
[183]	train-mlogloss:1.01393	validation-mlogloss:1.01296
[184]	train-mlogloss:1.01326	validation-mlogloss:1.01230
[185]	train-mlogloss:1.01248	validation-mlogloss:1.01163
[186]	train-mlogloss:1.01179	validation-mlogloss:1.01111
[187]	train-mlogloss:1.01101	validation-mlogloss:1.01041
[188]	train-mlogloss:1.01022	validation-mlogloss:1.00980
[189]	train-mlogloss:1.00955	validation-mlogloss:1.00936
[190]	train-mlogloss:1.00883	validation-mlogloss:1.00860
[191]	train-mlogloss:1.00805	validation-mlogloss:1.00806
[192]	train-mlogloss:1.00730	validation-mlogloss:1.00747
[193]	train-mlogloss:1.00651	validation-mlogloss:1.00675
[194]	train-mlogloss:1.00582	validation-mlogloss:1.00617
[195]	train-mlogloss:1.00519	validation-mlogloss:1.00571
[196]	train-mlogloss:1.00445	validation-mlogloss:1.00484
[197]	train-mlogloss:1.00373	validation-mlogloss:1.00432
[198]	train-mlogloss:1.00308	validation-mlogloss:1.00377
[199]	train-mlogloss:1.00231	validation-mlogloss:1.00310
[200]	train-mlogloss:1.00160	validation-mlogloss:1.00269
[201]	train-mlogloss:1.00090	validation-mlogloss:1.00222
[202]	train-mlogloss:1.00026	validation-mlogloss:1.00178
[203]	train-mlogloss:0.99962	validation-mlogloss:1.00123
[204]	train-mlogloss:0.99895	validation-mlogloss:1.00076
[205]	train-mlogloss:0.99829	validation-mlogloss:1.00027
[206]	train-mlogloss:0.99768	validation-mlogloss:0.99970
[207]	train-mlogloss:0.99707	validation-mlogloss:0.99911
[208]	train-mlogloss:0.99643	validation-mlogloss:0.99846
[209]	train-mlogloss:0.99587	validation-mlogloss:0.99815
[210]	train-mlogloss:0.99521	validation-mlogloss:0.99763
[211]	train-mlogloss:0.99461	validation-mlogloss:0.99693
[212]	train-mlogloss:0.99404	validation-mlogloss:0.99638
[213]	train-mlogloss:0.99348	validation-mlogloss:0.99598
[214]	train-mlogloss:0.99286	validation-mlogloss:0.99541
[215]	train-mlogloss:0.99231	validation-mlogloss:0.99503
[216]	train-mlogloss:0.99171	validation-mlogloss:0.99454
[217]	train-mlogloss:0.99113	validation-mlogloss:0.99406
[218]	train-mlogloss:0.99050	validation-mlogloss:0.99363
[219]	train-mlogloss:0.98987	validation-mlogloss:0.99331
[220]	train-mlogloss:0.98923	validation-mlogloss:0.99277
[221]	train-mlogloss:0.98870	validation-mlogloss:0.99228
[222]	train-mlogloss:0.98804	validation-mlogloss:0.99171
[223]	train-mlogloss:0.98736	validation-mlogloss:0.99127
[224]	train-mlogloss:0.98678	validation-mlogloss:0.99095
[225]	train-mlogloss:0.98624	validation-mlogloss:0.99072
[226]	train-mlogloss:0.98569	validation-mlogloss:0.99037
[227]	train-mlogloss:0.98516	validation-mlogloss:0.99004
[228]	train-mlogloss:0.98455	validation-mlogloss:0.98969
[229]	train-mlogloss:0.98393	validation-mlogloss:0.98907
[230]	train-mlogloss:0.98335	validation-mlogloss:0.98867
[231]	train-mlogloss:0.98285	validation-mlogloss:0.98817
[232]	train-mlogloss:0.98230	validation-mlogloss:0.98791
[233]	train-mlogloss:0.98170	validation-mlogloss:0.98740
[234]	train-mlogloss:0.98111	validation-mlogloss:0.98692
[235]	train-mlogloss:0.98058	validation-mlogloss:0.98652
[236]	train-mlogloss:0.98001	validation-mlogloss:0.98614
[237]	train-mlogloss:0.97945	validation-mlogloss:0.98578
[238]	train-mlogloss:0.97885	validation-mlogloss:0.98536
[239]	train-mlogloss:0.97839	validation-mlogloss:0.98506
[240]	train-mlogloss:0.97784	validation-mlogloss:0.98469
[241]	train-mlogloss:0.97729	validation-mlogloss:0.98427
[242]	train-mlogloss:0.97672	validation-mlogloss:0.98366
[243]	train-mlogloss:0.97624	validation-mlogloss:0.98327
[244]	train-mlogloss:0.97561	validation-mlogloss:0.98288
[245]	train-mlogloss:0.97510	validation-mlogloss:0.98249
[246]	train-mlogloss:0.97462	validation-mlogloss:0.98201
[247]	train-mlogloss:0.97414	validation-mlogloss:0.98174
[248]	train-mlogloss:0.97366	validation-mlogloss:0.98135
[249]	train-mlogloss:0.97317	validation-mlogloss:0.98095
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[251]	train-mlogloss:0.97222	validation-mlogloss:0.98036
[252]	train-mlogloss:0.97171	validation-mlogloss:0.98001
[253]	train-mlogloss:0.97123	validation-mlogloss:0.97973
[254]	train-mlogloss:0.97077	validation-mlogloss:0.97939
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[257]	train-mlogloss:0.96933	validation-mlogloss:0.97817
[258]	train-mlogloss:0.96885	validation-mlogloss:0.97793
[259]	train-mlogloss:0.96835	validation-mlogloss:0.97759
[260]	train-mlogloss:0.96778	validation-mlogloss:0.97724
[261]	train-mlogloss:0.96729	validation-mlogloss:0.97692
[262]	train-mlogloss:0.96680	validation-mlogloss:0.97657
[263]	train-mlogloss:0.96634	validation-mlogloss:0.97628
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[265]	train-mlogloss:0.96549	validation-mlogloss:0.97571
[266]	train-mlogloss:0.96494	validation-mlogloss:0.97528
[267]	train-mlogloss:0.96446	validation-mlogloss:0.97492
[268]	train-mlogloss:0.96403	validation-mlogloss:0.97465
[269]	train-mlogloss:0.96352	validation-mlogloss:0.97441
[270]	train-mlogloss:0.96296	validation-mlogloss:0.97410
[271]	train-mlogloss:0.96245	validation-mlogloss:0.97376
[272]	train-mlogloss:0.96193	validation-mlogloss:0.97340
[273]	train-mlogloss:0.96146	validation-mlogloss:0.97310
[274]	train-mlogloss:0.96100	validation-mlogloss:0.97282
[275]	train-mlogloss:0.96054	validation-mlogloss:0.97259
[276]	train-mlogloss:0.96004	validation-mlogloss:0.97209
[277]	train-mlogloss:0.95965	validation-mlogloss:0.97193
[278]	train-mlogloss:0.95919	validation-mlogloss:0.97156
[279]	train-mlogloss:0.95867	validation-mlogloss:0.97127
[280]	train-mlogloss:0.95825	validation-mlogloss:0.97084
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[575]	train-mlogloss:0.88734	validation-mlogloss:0.92713
[576]	train-mlogloss:0.88727	validation-mlogloss:0.92709
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[578]	train-mlogloss:0.88709	validation-mlogloss:0.92716
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[585]	train-mlogloss:0.88630	validation-mlogloss:0.92654
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[595]	train-mlogloss:0.88527	validation-mlogloss:0.92597
[596]	train-mlogloss:0.88515	validation-mlogloss:0.92596
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[598]	train-mlogloss:0.88503	validation-mlogloss:0.92585
[599]	train-mlogloss:0.88496	validation-mlogloss:0.92583
[600]	train-mlogloss:0.88489	validation-mlogloss:0.92575
[601]	train-mlogloss:0.88481	validation-mlogloss:0.92566
[602]	train-mlogloss:0.88479	validation-mlogloss:0.92565
[603]	train-mlogloss:0.88472	validation-mlogloss:0.92555
[604]	train-mlogloss:0.88463	validation-mlogloss:0.92547
[605]	train-mlogloss:0.88458	validation-mlogloss:0.92545
[606]	train-mlogloss:0.88445	validation-mlogloss:0.92551
[607]	train-mlogloss:0.88429	validation-mlogloss:0.92544
[608]	train-mlogloss:0.88410	validation-mlogloss:0.92540
[609]	train-mlogloss:0.88405	validation-mlogloss:0.92540
[610]	train-mlogloss:0.88390	validation-mlogloss:0.92531
[611]	train-mlogloss:0.88381	validation-mlogloss:0.92529
[612]	train-mlogloss:0.88374	validation-mlogloss:0.92524
[613]	train-mlogloss:0.88362	validation-mlogloss:0.92519
[614]	train-mlogloss:0.88355	validation-mlogloss:0.92511
[615]	train-mlogloss:0.88349	validation-mlogloss:0.92509
[616]	train-mlogloss:0.88341	validation-mlogloss:0.92503
[617]	train-mlogloss:0.88328	validation-mlogloss:0.92486
[618]	train-mlogloss:0.88321	validation-mlogloss:0.92482
[619]	train-mlogloss:0.88306	validation-mlogloss:0.92475
[620]	train-mlogloss:0.88301	validation-mlogloss:0.92473
[621]	train-mlogloss:0.88295	validation-mlogloss:0.92473
[622]	train-mlogloss:0.88283	validation-mlogloss:0.92465
[623]	train-mlogloss:0.88275	validation-mlogloss:0.92463
[624]	train-mlogloss:0.88265	validation-mlogloss:0.92458
[625]	train-mlogloss:0.88258	validation-mlogloss:0.92452
[626]	train-mlogloss:0.88252	validation-mlogloss:0.92453
[627]	train-mlogloss:0.88240	validation-mlogloss:0.92464
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[629]	train-mlogloss:0.88222	validation-mlogloss:0.92452
[630]	train-mlogloss:0.88216	validation-mlogloss:0.92443
[631]	train-mlogloss:0.88208	validation-mlogloss:0.92430
[632]	train-mlogloss:0.88202	validation-mlogloss:0.92427
[633]	train-mlogloss:0.88193	validation-mlogloss:0.92412
[634]	train-mlogloss:0.88187	validation-mlogloss:0.92409
[635]	train-mlogloss:0.88175	validation-mlogloss:0.92399
[636]	train-mlogloss:0.88164	validation-mlogloss:0.92394
[637]	train-mlogloss:0.88157	validation-mlogloss:0.92389
[638]	train-mlogloss:0.88152	validation-mlogloss:0.92386
[639]	train-mlogloss:0.88140	validation-mlogloss:0.92378
[640]	train-mlogloss:0.88129	validation-mlogloss:0.92366
[641]	train-mlogloss:0.88119	validation-mlogloss:0.92355
[642]	train-mlogloss:0.88111	validation-mlogloss:0.92353
[643]	train-mlogloss:0.88106	validation-mlogloss:0.92349
[644]	train-mlogloss:0.88095	validation-mlogloss:0.92336
[645]	train-mlogloss:0.88081	validation-mlogloss:0.92336
[646]	train-mlogloss:0.88076	validation-mlogloss:0.92334
[647]	train-mlogloss:0.88069	validation-mlogloss:0.92330
[648]	train-mlogloss:0.88061	validation-mlogloss:0.92332
[649]	train-mlogloss:0.88054	validation-mlogloss:0.92327
[650]	train-mlogloss:0.88049	validation-mlogloss:0.92323
[651]	train-mlogloss:0.88044	validation-mlogloss:0.92319
[652]	train-mlogloss:0.88033	validation-mlogloss:0.92312
[653]	train-mlogloss:0.88028	validation-mlogloss:0.92308
[654]	train-mlogloss:0.88018	validation-mlogloss:0.92303
[655]	train-mlogloss:0.88013	validation-mlogloss:0.92297
[656]	train-mlogloss:0.87999	validation-mlogloss:0.92299
[657]	train-mlogloss:0.87987	validation-mlogloss:0.92293
[658]	train-mlogloss:0.87977	validation-mlogloss:0.92285
[659]	train-mlogloss:0.87972	validation-mlogloss:0.92280
[660]	train-mlogloss:0.87966	validation-mlogloss:0.92278
[661]	train-mlogloss:0.87958	validation-mlogloss:0.92275
[662]	train-mlogloss:0.87948	validation-mlogloss:0.92274
[663]	train-mlogloss:0.87941	validation-mlogloss:0.92271
[664]	train-mlogloss:0.87926	validation-mlogloss:0.92271
[665]	train-mlogloss:0.87910	validation-mlogloss:0.92267
[666]	train-mlogloss:0.87905	validation-mlogloss:0.92260
[667]	train-mlogloss:0.87897	validation-mlogloss:0.92259
[668]	train-mlogloss:0.87883	validation-mlogloss:0.92252
[669]	train-mlogloss:0.87878	validation-mlogloss:0.92248
[670]	train-mlogloss:0.87865	validation-mlogloss:0.92243
[671]	train-mlogloss:0.87851	validation-mlogloss:0.92233
[672]	train-mlogloss:0.87843	validation-mlogloss:0.92227
[673]	train-mlogloss:0.87840	validation-mlogloss:0.92223
[674]	train-mlogloss:0.87826	validation-mlogloss:0.92222
[675]	train-mlogloss:0.87823	validation-mlogloss:0.92221
[676]	train-mlogloss:0.87819	validation-mlogloss:0.92220
[677]	train-mlogloss:0.87815	validation-mlogloss:0.92220
[678]	train-mlogloss:0.87806	validation-mlogloss:0.92221
[679]	train-mlogloss:0.87797	validation-mlogloss:0.92211
[680]	train-mlogloss:0.87792	validation-mlogloss:0.92206
[681]	train-mlogloss:0.87778	validation-mlogloss:0.92192
[682]	train-mlogloss:0.87768	validation-mlogloss:0.92189
[683]	train-mlogloss:0.87763	validation-mlogloss:0.92188
[684]	train-mlogloss:0.87758	validation-mlogloss:0.92188
[685]	train-mlogloss:0.87755	validation-mlogloss:0.92187
[686]	train-mlogloss:0.87746	validation-mlogloss:0.92176
[687]	train-mlogloss:0.87744	validation-mlogloss:0.92175
[688]	train-mlogloss:0.87733	validation-mlogloss:0.92166
[689]	train-mlogloss:0.87725	validation-mlogloss:0.92158
[690]	train-mlogloss:0.87723	validation-mlogloss:0.92156
[691]	train-mlogloss:0.87718	validation-mlogloss:0.92154
[692]	train-mlogloss:0.87710	validation-mlogloss:0.92152
[693]	train-mlogloss:0.87701	validation-mlogloss:0.92144
[694]	train-mlogloss:0.87690	validation-mlogloss:0.92137
[695]	train-mlogloss:0.87684	validation-mlogloss:0.92132
[696]	train-mlogloss:0.87674	validation-mlogloss:0.92117
[697]	train-mlogloss:0.87669	validation-mlogloss:0.92110
[698]	train-mlogloss:0.87665	validation-mlogloss:0.92107
[699]	train-mlogloss:0.87658	validation-mlogloss:0.92103
[700]	train-mlogloss:0.87651	validation-mlogloss:0.92100
[701]	train-mlogloss:0.87646	validation-mlogloss:0.92098
[702]	train-mlogloss:0.87641	validation-mlogloss:0.92093
[703]	train-mlogloss:0.87636	validation-mlogloss:0.92088
[704]	train-mlogloss:0.87620	validation-mlogloss:0.92080
[705]	train-mlogloss:0.87613	validation-mlogloss:0.92079
[706]	train-mlogloss:0.87611	validation-mlogloss:0.92079
[707]	train-mlogloss:0.87607	validation-mlogloss:0.92075
[708]	train-mlogloss:0.87600	validation-mlogloss:0.92074
[709]	train-mlogloss:0.87596	validation-mlogloss:0.92072
[710]	train-mlogloss:0.87590	validation-mlogloss:0.92069
[711]	train-mlogloss:0.87583	validation-mlogloss:0.92075
[712]	train-mlogloss:0.87579	validation-mlogloss:0.92074
[713]	train-mlogloss:0.87575	validation-mlogloss:0.92073
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 3]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.29 [%]
Global accuracy score (test) = 61.1 [%]
Global F1 score (train) = 63.25 [%]
Global F1 score (test) = 61.53 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.46      0.43      0.45       400
MODERATE-INTENSITY       0.55      0.66      0.60       400
         SEDENTARY       0.67      0.74      0.71       400
VIGOROUS-INTENSITY       0.84      0.62      0.71       345

          accuracy                           0.61      1545
         macro avg       0.63      0.61      0.62      1545
      weighted avg       0.62      0.61      0.61      1545


Accuracy capturado en la ejecución 24: 61.1 [%]
F1-score capturado en la ejecución 24: 61.53 [%]

=== EJECUCIÓN 25 ===

--- TRAIN (ejecución 25) ---

--- TEST (ejecución 25) ---
2025-11-04 11:05:35.273703: 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`.
2025-11-04 11:05:35.285175: 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 00:00:1762250735.298591 1084858 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250735.302764 1084858 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250735.312692 1084858 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250735.312709 1084858 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250735.312711 1084858 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250735.312712 1084858 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:05:35.315817: 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:1.38105	validation-mlogloss:1.38082
[1]	train-mlogloss:1.37589	validation-mlogloss:1.37545
[2]	train-mlogloss:1.37094	validation-mlogloss:1.37044
[3]	train-mlogloss:1.36590	validation-mlogloss:1.36534
[4]	train-mlogloss:1.36113	validation-mlogloss:1.36032
[5]	train-mlogloss:1.35626	validation-mlogloss:1.35525
[6]	train-mlogloss:1.35155	validation-mlogloss:1.35022
[7]	train-mlogloss:1.34672	validation-mlogloss:1.34511
[8]	train-mlogloss:1.34208	validation-mlogloss:1.34005
[9]	train-mlogloss:1.33763	validation-mlogloss:1.33528
[10]	train-mlogloss:1.33311	validation-mlogloss:1.33066
[11]	train-mlogloss:1.32875	validation-mlogloss:1.32619
[12]	train-mlogloss:1.32444	validation-mlogloss:1.32177
[13]	train-mlogloss:1.32025	validation-mlogloss:1.31754
[14]	train-mlogloss:1.31615	validation-mlogloss:1.31344
[15]	train-mlogloss:1.31193	validation-mlogloss:1.30898
[16]	train-mlogloss:1.30790	validation-mlogloss:1.30476
[17]	train-mlogloss:1.30398	validation-mlogloss:1.30047
[18]	train-mlogloss:1.29988	validation-mlogloss:1.29634
[19]	train-mlogloss:1.29600	validation-mlogloss:1.29267
[20]	train-mlogloss:1.29177	validation-mlogloss:1.28809
[21]	train-mlogloss:1.28804	validation-mlogloss:1.28396
[22]	train-mlogloss:1.28435	validation-mlogloss:1.28016
[23]	train-mlogloss:1.28036	validation-mlogloss:1.27578
[24]	train-mlogloss:1.27665	validation-mlogloss:1.27169
[25]	train-mlogloss:1.27307	validation-mlogloss:1.26803
[26]	train-mlogloss:1.26963	validation-mlogloss:1.26454
[27]	train-mlogloss:1.26604	validation-mlogloss:1.26093
[28]	train-mlogloss:1.26268	validation-mlogloss:1.25758
[29]	train-mlogloss:1.25940	validation-mlogloss:1.25433
[30]	train-mlogloss:1.25615	validation-mlogloss:1.25096
[31]	train-mlogloss:1.25289	validation-mlogloss:1.24761
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[624]	train-mlogloss:0.88621	validation-mlogloss:0.92335
[625]	train-mlogloss:0.88609	validation-mlogloss:0.92329
[626]	train-mlogloss:0.88601	validation-mlogloss:0.92320
[627]	train-mlogloss:0.88594	validation-mlogloss:0.92315
[628]	train-mlogloss:0.88587	validation-mlogloss:0.92307
[629]	train-mlogloss:0.88581	validation-mlogloss:0.92306
[630]	train-mlogloss:0.88573	validation-mlogloss:0.92303
[631]	train-mlogloss:0.88565	validation-mlogloss:0.92296
[632]	train-mlogloss:0.88553	validation-mlogloss:0.92289
[633]	train-mlogloss:0.88548	validation-mlogloss:0.92287
[634]	train-mlogloss:0.88539	validation-mlogloss:0.92281
[635]	train-mlogloss:0.88531	validation-mlogloss:0.92277
[636]	train-mlogloss:0.88518	validation-mlogloss:0.92276
[637]	train-mlogloss:0.88508	validation-mlogloss:0.92271
[638]	train-mlogloss:0.88497	validation-mlogloss:0.92265
[639]	train-mlogloss:0.88486	validation-mlogloss:0.92265
[640]	train-mlogloss:0.88478	validation-mlogloss:0.92266
[641]	train-mlogloss:0.88472	validation-mlogloss:0.92259
[642]	train-mlogloss:0.88463	validation-mlogloss:0.92255
[643]	train-mlogloss:0.88449	validation-mlogloss:0.92245
[644]	train-mlogloss:0.88443	validation-mlogloss:0.92239
[645]	train-mlogloss:0.88434	validation-mlogloss:0.92224
[646]	train-mlogloss:0.88427	validation-mlogloss:0.92222
[647]	train-mlogloss:0.88419	validation-mlogloss:0.92215
[648]	train-mlogloss:0.88412	validation-mlogloss:0.92210
[649]	train-mlogloss:0.88402	validation-mlogloss:0.92207
[650]	train-mlogloss:0.88393	validation-mlogloss:0.92205
[651]	train-mlogloss:0.88384	validation-mlogloss:0.92198
[652]	train-mlogloss:0.88379	validation-mlogloss:0.92196
[653]	train-mlogloss:0.88373	validation-mlogloss:0.92191
[654]	train-mlogloss:0.88365	validation-mlogloss:0.92197
[655]	train-mlogloss:0.88354	validation-mlogloss:0.92194
[656]	train-mlogloss:0.88344	validation-mlogloss:0.92185
[657]	train-mlogloss:0.88338	validation-mlogloss:0.92181
[658]	train-mlogloss:0.88332	validation-mlogloss:0.92177
[659]	train-mlogloss:0.88328	validation-mlogloss:0.92175
[660]	train-mlogloss:0.88324	validation-mlogloss:0.92174
[661]	train-mlogloss:0.88309	validation-mlogloss:0.92167
[662]	train-mlogloss:0.88302	validation-mlogloss:0.92162
[663]	train-mlogloss:0.88295	validation-mlogloss:0.92154
[664]	train-mlogloss:0.88287	validation-mlogloss:0.92149
[665]	train-mlogloss:0.88279	validation-mlogloss:0.92145
[666]	train-mlogloss:0.88273	validation-mlogloss:0.92143
[667]	train-mlogloss:0.88269	validation-mlogloss:0.92141
[668]	train-mlogloss:0.88257	validation-mlogloss:0.92123
[669]	train-mlogloss:0.88251	validation-mlogloss:0.92127
[670]	train-mlogloss:0.88247	validation-mlogloss:0.92122
[671]	train-mlogloss:0.88242	validation-mlogloss:0.92122
[672]	train-mlogloss:0.88237	validation-mlogloss:0.92119
[673]	train-mlogloss:0.88230	validation-mlogloss:0.92113
[674]	train-mlogloss:0.88222	validation-mlogloss:0.92109
[675]	train-mlogloss:0.88217	validation-mlogloss:0.92107
[676]	train-mlogloss:0.88208	validation-mlogloss:0.92104
[677]	train-mlogloss:0.88201	validation-mlogloss:0.92101
[678]	train-mlogloss:0.88191	validation-mlogloss:0.92091
[679]	train-mlogloss:0.88179	validation-mlogloss:0.92087
[680]	train-mlogloss:0.88172	validation-mlogloss:0.92081
[681]	train-mlogloss:0.88162	validation-mlogloss:0.92074
[682]	train-mlogloss:0.88153	validation-mlogloss:0.92069
[683]	train-mlogloss:0.88145	validation-mlogloss:0.92059
[684]	train-mlogloss:0.88140	validation-mlogloss:0.92054
[685]	train-mlogloss:0.88134	validation-mlogloss:0.92048
[686]	train-mlogloss:0.88129	validation-mlogloss:0.92044
[687]	train-mlogloss:0.88120	validation-mlogloss:0.92030
[688]	train-mlogloss:0.88111	validation-mlogloss:0.92024
[689]	train-mlogloss:0.88106	validation-mlogloss:0.92017
[690]	train-mlogloss:0.88102	validation-mlogloss:0.92016
[691]	train-mlogloss:0.88097	validation-mlogloss:0.92014
[692]	train-mlogloss:0.88093	validation-mlogloss:0.92012
[693]	train-mlogloss:0.88083	validation-mlogloss:0.92004
[694]	train-mlogloss:0.88075	validation-mlogloss:0.92001
[695]	train-mlogloss:0.88071	validation-mlogloss:0.91999
[696]	train-mlogloss:0.88064	validation-mlogloss:0.91998
[697]	train-mlogloss:0.88058	validation-mlogloss:0.91991
[698]	train-mlogloss:0.88047	validation-mlogloss:0.91976
[699]	train-mlogloss:0.88043	validation-mlogloss:0.91971
[700]	train-mlogloss:0.88036	validation-mlogloss:0.91971
[701]	train-mlogloss:0.88030	validation-mlogloss:0.91965
[702]	train-mlogloss:0.88023	validation-mlogloss:0.91961
[703]	train-mlogloss:0.88010	validation-mlogloss:0.91953
[704]	train-mlogloss:0.88002	validation-mlogloss:0.91943
[705]	train-mlogloss:0.87987	validation-mlogloss:0.91923
[706]	train-mlogloss:0.87981	validation-mlogloss:0.91921
[707]	train-mlogloss:0.87976	validation-mlogloss:0.91919
[708]	train-mlogloss:0.87971	validation-mlogloss:0.91924
[709]	train-mlogloss:0.87961	validation-mlogloss:0.91912
[710]	train-mlogloss:0.87956	validation-mlogloss:0.91910
[711]	train-mlogloss:0.87954	validation-mlogloss:0.91910
[712]	train-mlogloss:0.87944	validation-mlogloss:0.91900
[713]	train-mlogloss:0.87940	validation-mlogloss:0.91899
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 3]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.61 [%]
Global accuracy score (test) = 60.45 [%]
Global F1 score (train) = 63.61 [%]
Global F1 score (test) = 61.29 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.43      0.45      0.44       400
MODERATE-INTENSITY       0.56      0.63      0.59       400
         SEDENTARY       0.67      0.71      0.69       400
VIGOROUS-INTENSITY       0.87      0.62      0.73       345

          accuracy                           0.60      1545
         macro avg       0.63      0.61      0.61      1545
      weighted avg       0.62      0.60      0.61      1545


Accuracy capturado en la ejecución 25: 60.45 [%]
F1-score capturado en la ejecución 25: 61.29 [%]

=== EJECUCIÓN 26 ===

--- TRAIN (ejecución 26) ---

--- TEST (ejecución 26) ---
2025-11-04 11:05:52.266749: 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`.
2025-11-04 11:05:52.277889: 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 00:00:1762250752.290810 1085170 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250752.294811 1085170 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250752.304731 1085170 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250752.304747 1085170 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250752.304748 1085170 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250752.304749 1085170 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:05:52.307654: 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:1.38103	validation-mlogloss:1.38059
[1]	train-mlogloss:1.37565	validation-mlogloss:1.37492
[2]	train-mlogloss:1.37073	validation-mlogloss:1.36987
[3]	train-mlogloss:1.36590	validation-mlogloss:1.36446
[4]	train-mlogloss:1.36079	validation-mlogloss:1.35912
[5]	train-mlogloss:1.35607	validation-mlogloss:1.35412
[6]	train-mlogloss:1.35154	validation-mlogloss:1.34937
[7]	train-mlogloss:1.34687	validation-mlogloss:1.34467
[8]	train-mlogloss:1.34195	validation-mlogloss:1.33937
[9]	train-mlogloss:1.33737	validation-mlogloss:1.33452
[10]	train-mlogloss:1.33278	validation-mlogloss:1.32981
[11]	train-mlogloss:1.32842	validation-mlogloss:1.32541
[12]	train-mlogloss:1.32422	validation-mlogloss:1.32118
[13]	train-mlogloss:1.32024	validation-mlogloss:1.31723
[14]	train-mlogloss:1.31585	validation-mlogloss:1.31237
[15]	train-mlogloss:1.31175	validation-mlogloss:1.30811
[16]	train-mlogloss:1.30781	validation-mlogloss:1.30401
[17]	train-mlogloss:1.30381	validation-mlogloss:1.29986
[18]	train-mlogloss:1.29996	validation-mlogloss:1.29568
[19]	train-mlogloss:1.29612	validation-mlogloss:1.29210
[20]	train-mlogloss:1.29242	validation-mlogloss:1.28825
[21]	train-mlogloss:1.28865	validation-mlogloss:1.28424
[22]	train-mlogloss:1.28491	validation-mlogloss:1.28011
[23]	train-mlogloss:1.28148	validation-mlogloss:1.27655
[24]	train-mlogloss:1.27792	validation-mlogloss:1.27284
[25]	train-mlogloss:1.27444	validation-mlogloss:1.26939
[26]	train-mlogloss:1.27104	validation-mlogloss:1.26600
[27]	train-mlogloss:1.26762	validation-mlogloss:1.26235
[28]	train-mlogloss:1.26442	validation-mlogloss:1.25900
[29]	train-mlogloss:1.26119	validation-mlogloss:1.25556
[30]	train-mlogloss:1.25747	validation-mlogloss:1.25152
[31]	train-mlogloss:1.25434	validation-mlogloss:1.24810
[32]	train-mlogloss:1.25109	validation-mlogloss:1.24499
[33]	train-mlogloss:1.24791	validation-mlogloss:1.24184
[34]	train-mlogloss:1.24493	validation-mlogloss:1.23870
[35]	train-mlogloss:1.24201	validation-mlogloss:1.23547
[36]	train-mlogloss:1.23894	validation-mlogloss:1.23212
[37]	train-mlogloss:1.23597	validation-mlogloss:1.22891
[38]	train-mlogloss:1.23322	validation-mlogloss:1.22597
[39]	train-mlogloss:1.23035	validation-mlogloss:1.22298
[40]	train-mlogloss:1.22756	validation-mlogloss:1.21986
[41]	train-mlogloss:1.22481	validation-mlogloss:1.21680
[42]	train-mlogloss:1.22209	validation-mlogloss:1.21399
[43]	train-mlogloss:1.21935	validation-mlogloss:1.21136
[44]	train-mlogloss:1.21672	validation-mlogloss:1.20863
[45]	train-mlogloss:1.21427	validation-mlogloss:1.20613
[46]	train-mlogloss:1.21174	validation-mlogloss:1.20322
[47]	train-mlogloss:1.20913	validation-mlogloss:1.20053
[48]	train-mlogloss:1.20624	validation-mlogloss:1.19731
[49]	train-mlogloss:1.20369	validation-mlogloss:1.19459
[50]	train-mlogloss:1.20126	validation-mlogloss:1.19213
[51]	train-mlogloss:1.19887	validation-mlogloss:1.18962
[52]	train-mlogloss:1.19647	validation-mlogloss:1.18721
[53]	train-mlogloss:1.19408	validation-mlogloss:1.18501
[54]	train-mlogloss:1.19177	validation-mlogloss:1.18288
[55]	train-mlogloss:1.18944	validation-mlogloss:1.18066
[56]	train-mlogloss:1.18701	validation-mlogloss:1.17815
[57]	train-mlogloss:1.18438	validation-mlogloss:1.17549
[58]	train-mlogloss:1.18211	validation-mlogloss:1.17301
[59]	train-mlogloss:1.17986	validation-mlogloss:1.17089
[60]	train-mlogloss:1.17724	validation-mlogloss:1.16843
[61]	train-mlogloss:1.17501	validation-mlogloss:1.16601
[62]	train-mlogloss:1.17288	validation-mlogloss:1.16371
[63]	train-mlogloss:1.17040	validation-mlogloss:1.16105
[64]	train-mlogloss:1.16813	validation-mlogloss:1.15856
[65]	train-mlogloss:1.16603	validation-mlogloss:1.15648
[66]	train-mlogloss:1.16361	validation-mlogloss:1.15423
[67]	train-mlogloss:1.16129	validation-mlogloss:1.15216
[68]	train-mlogloss:1.15902	validation-mlogloss:1.14963
[69]	train-mlogloss:1.15706	validation-mlogloss:1.14783
[70]	train-mlogloss:1.15484	validation-mlogloss:1.14533
[71]	train-mlogloss:1.15302	validation-mlogloss:1.14369
[72]	train-mlogloss:1.15082	validation-mlogloss:1.14142
[73]	train-mlogloss:1.14884	validation-mlogloss:1.13933
[74]	train-mlogloss:1.14693	validation-mlogloss:1.13729
[75]	train-mlogloss:1.14501	validation-mlogloss:1.13523
[76]	train-mlogloss:1.14327	validation-mlogloss:1.13347
[77]	train-mlogloss:1.14157	validation-mlogloss:1.13177
[78]	train-mlogloss:1.13974	validation-mlogloss:1.12984
[79]	train-mlogloss:1.13771	validation-mlogloss:1.12775
[80]	train-mlogloss:1.13584	validation-mlogloss:1.12576
[81]	train-mlogloss:1.13393	validation-mlogloss:1.12382
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[674]	train-mlogloss:0.88315	validation-mlogloss:0.92009
[675]	train-mlogloss:0.88309	validation-mlogloss:0.92009
[676]	train-mlogloss:0.88299	validation-mlogloss:0.91999
[677]	train-mlogloss:0.88291	validation-mlogloss:0.91997
[678]	train-mlogloss:0.88286	validation-mlogloss:0.91998
[679]	train-mlogloss:0.88281	validation-mlogloss:0.91995
[680]	train-mlogloss:0.88276	validation-mlogloss:0.91988
[681]	train-mlogloss:0.88272	validation-mlogloss:0.91983
[682]	train-mlogloss:0.88259	validation-mlogloss:0.91972
[683]	train-mlogloss:0.88254	validation-mlogloss:0.91974
[684]	train-mlogloss:0.88244	validation-mlogloss:0.91975
[685]	train-mlogloss:0.88239	validation-mlogloss:0.91969
[686]	train-mlogloss:0.88228	validation-mlogloss:0.91965
[687]	train-mlogloss:0.88217	validation-mlogloss:0.91961
[688]	train-mlogloss:0.88204	validation-mlogloss:0.91954
[689]	train-mlogloss:0.88199	validation-mlogloss:0.91953
[690]	train-mlogloss:0.88193	validation-mlogloss:0.91948
[691]	train-mlogloss:0.88186	validation-mlogloss:0.91947
[692]	train-mlogloss:0.88176	validation-mlogloss:0.91945
[693]	train-mlogloss:0.88170	validation-mlogloss:0.91945
[694]	train-mlogloss:0.88166	validation-mlogloss:0.91944
[695]	train-mlogloss:0.88153	validation-mlogloss:0.91937
[696]	train-mlogloss:0.88145	validation-mlogloss:0.91929
[697]	train-mlogloss:0.88141	validation-mlogloss:0.91927
[698]	train-mlogloss:0.88135	validation-mlogloss:0.91921
[699]	train-mlogloss:0.88130	validation-mlogloss:0.91918
[700]	train-mlogloss:0.88126	validation-mlogloss:0.91915
[701]	train-mlogloss:0.88119	validation-mlogloss:0.91912
[702]	train-mlogloss:0.88111	validation-mlogloss:0.91909
[703]	train-mlogloss:0.88107	validation-mlogloss:0.91906
[704]	train-mlogloss:0.88096	validation-mlogloss:0.91900
[705]	train-mlogloss:0.88094	validation-mlogloss:0.91899
[706]	train-mlogloss:0.88081	validation-mlogloss:0.91892
[707]	train-mlogloss:0.88075	validation-mlogloss:0.91885
[708]	train-mlogloss:0.88071	validation-mlogloss:0.91882
[709]	train-mlogloss:0.88063	validation-mlogloss:0.91884
[710]	train-mlogloss:0.88053	validation-mlogloss:0.91872
[711]	train-mlogloss:0.88047	validation-mlogloss:0.91870
[712]	train-mlogloss:0.88036	validation-mlogloss:0.91870
[713]	train-mlogloss:0.88030	validation-mlogloss:0.91858
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 1 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.46 [%]
Global accuracy score (test) = 58.83 [%]
Global F1 score (train) = 63.51 [%]
Global F1 score (test) = 59.77 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.44      0.48      0.46       400
MODERATE-INTENSITY       0.52      0.59      0.56       400
         SEDENTARY       0.66      0.67      0.67       400
VIGOROUS-INTENSITY       0.84      0.61      0.71       345

          accuracy                           0.59      1545
         macro avg       0.62      0.59      0.60      1545
      weighted avg       0.61      0.59      0.59      1545


Accuracy capturado en la ejecución 26: 58.83 [%]
F1-score capturado en la ejecución 26: 59.77 [%]

=== EJECUCIÓN 27 ===

--- TRAIN (ejecución 27) ---

--- TEST (ejecución 27) ---
2025-11-04 11:06:09.268155: 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`.
2025-11-04 11:06:09.279554: 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 00:00:1762250769.292884 1085481 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250769.297141 1085481 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250769.306991 1085481 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250769.307007 1085481 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250769.307008 1085481 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250769.307010 1085481 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:06:09.310111: 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:1.38122	validation-mlogloss:1.38094
[1]	train-mlogloss:1.37617	validation-mlogloss:1.37572
[2]	train-mlogloss:1.37146	validation-mlogloss:1.37072
[3]	train-mlogloss:1.36654	validation-mlogloss:1.36562
[4]	train-mlogloss:1.36186	validation-mlogloss:1.36080
[5]	train-mlogloss:1.35717	validation-mlogloss:1.35589
[6]	train-mlogloss:1.35254	validation-mlogloss:1.35091
[7]	train-mlogloss:1.34764	validation-mlogloss:1.34574
[8]	train-mlogloss:1.34319	validation-mlogloss:1.34095
[9]	train-mlogloss:1.33878	validation-mlogloss:1.33610
[10]	train-mlogloss:1.33450	validation-mlogloss:1.33159
[11]	train-mlogloss:1.33035	validation-mlogloss:1.32699
[12]	train-mlogloss:1.32615	validation-mlogloss:1.32245
[13]	train-mlogloss:1.32191	validation-mlogloss:1.31770
[14]	train-mlogloss:1.31779	validation-mlogloss:1.31347
[15]	train-mlogloss:1.31378	validation-mlogloss:1.30930
[16]	train-mlogloss:1.30989	validation-mlogloss:1.30503
[17]	train-mlogloss:1.30546	validation-mlogloss:1.30057
[18]	train-mlogloss:1.30161	validation-mlogloss:1.29659
[19]	train-mlogloss:1.29789	validation-mlogloss:1.29282
[20]	train-mlogloss:1.29415	validation-mlogloss:1.28882
[21]	train-mlogloss:1.29043	validation-mlogloss:1.28469
[22]	train-mlogloss:1.28684	validation-mlogloss:1.28069
[23]	train-mlogloss:1.28329	validation-mlogloss:1.27694
[24]	train-mlogloss:1.27984	validation-mlogloss:1.27333
[25]	train-mlogloss:1.27639	validation-mlogloss:1.26979
[26]	train-mlogloss:1.27295	validation-mlogloss:1.26597
[27]	train-mlogloss:1.26960	validation-mlogloss:1.26256
[28]	train-mlogloss:1.26630	validation-mlogloss:1.25931
[29]	train-mlogloss:1.26304	validation-mlogloss:1.25581
[30]	train-mlogloss:1.25983	validation-mlogloss:1.25236
[31]	train-mlogloss:1.25675	validation-mlogloss:1.24908
[32]	train-mlogloss:1.25368	validation-mlogloss:1.24574
[33]	train-mlogloss:1.25067	validation-mlogloss:1.24253
[34]	train-mlogloss:1.24767	validation-mlogloss:1.23947
[35]	train-mlogloss:1.24469	validation-mlogloss:1.23622
[36]	train-mlogloss:1.24184	validation-mlogloss:1.23329
[37]	train-mlogloss:1.23897	validation-mlogloss:1.23043
[38]	train-mlogloss:1.23608	validation-mlogloss:1.22745
[39]	train-mlogloss:1.23309	validation-mlogloss:1.22418
[40]	train-mlogloss:1.23025	validation-mlogloss:1.22121
[41]	train-mlogloss:1.22741	validation-mlogloss:1.21823
[42]	train-mlogloss:1.22471	validation-mlogloss:1.21531
[43]	train-mlogloss:1.22200	validation-mlogloss:1.21240
[44]	train-mlogloss:1.21939	validation-mlogloss:1.20995
[45]	train-mlogloss:1.21677	validation-mlogloss:1.20716
[46]	train-mlogloss:1.21420	validation-mlogloss:1.20461
[47]	train-mlogloss:1.21132	validation-mlogloss:1.20160
[48]	train-mlogloss:1.20886	validation-mlogloss:1.19910
[49]	train-mlogloss:1.20628	validation-mlogloss:1.19638
[50]	train-mlogloss:1.20375	validation-mlogloss:1.19362
[51]	train-mlogloss:1.20139	validation-mlogloss:1.19136
[52]	train-mlogloss:1.19902	validation-mlogloss:1.18899
[53]	train-mlogloss:1.19624	validation-mlogloss:1.18576
[54]	train-mlogloss:1.19360	validation-mlogloss:1.18277
[55]	train-mlogloss:1.19125	validation-mlogloss:1.18025
[56]	train-mlogloss:1.18858	validation-mlogloss:1.17761
[57]	train-mlogloss:1.18620	validation-mlogloss:1.17524
[58]	train-mlogloss:1.18359	validation-mlogloss:1.17230
[59]	train-mlogloss:1.18137	validation-mlogloss:1.16992
[60]	train-mlogloss:1.17906	validation-mlogloss:1.16749
[61]	train-mlogloss:1.17661	validation-mlogloss:1.16475
[62]	train-mlogloss:1.17451	validation-mlogloss:1.16248
[63]	train-mlogloss:1.17214	validation-mlogloss:1.15984
[64]	train-mlogloss:1.17004	validation-mlogloss:1.15778
[65]	train-mlogloss:1.16791	validation-mlogloss:1.15545
[66]	train-mlogloss:1.16597	validation-mlogloss:1.15338
[67]	train-mlogloss:1.16395	validation-mlogloss:1.15138
[68]	train-mlogloss:1.16181	validation-mlogloss:1.14887
[69]	train-mlogloss:1.15958	validation-mlogloss:1.14645
[70]	train-mlogloss:1.15753	validation-mlogloss:1.14437
[71]	train-mlogloss:1.15527	validation-mlogloss:1.14199
[72]	train-mlogloss:1.15330	validation-mlogloss:1.13994
[73]	train-mlogloss:1.15116	validation-mlogloss:1.13755
[74]	train-mlogloss:1.14933	validation-mlogloss:1.13575
[75]	train-mlogloss:1.14753	validation-mlogloss:1.13396
[76]	train-mlogloss:1.14557	validation-mlogloss:1.13181
[77]	train-mlogloss:1.14371	validation-mlogloss:1.12980
[78]	train-mlogloss:1.14191	validation-mlogloss:1.12801
[79]	train-mlogloss:1.14023	validation-mlogloss:1.12643
[80]	train-mlogloss:1.13836	validation-mlogloss:1.12459
[81]	train-mlogloss:1.13669	validation-mlogloss:1.12298
[82]	train-mlogloss:1.13493	validation-mlogloss:1.12118
[83]	train-mlogloss:1.13312	validation-mlogloss:1.11937
[84]	train-mlogloss:1.13142	validation-mlogloss:1.11749
[85]	train-mlogloss:1.12980	validation-mlogloss:1.11584
[86]	train-mlogloss:1.12807	validation-mlogloss:1.11398
[87]	train-mlogloss:1.12635	validation-mlogloss:1.11206
[88]	train-mlogloss:1.12471	validation-mlogloss:1.11034
[89]	train-mlogloss:1.12304	validation-mlogloss:1.10869
[90]	train-mlogloss:1.12146	validation-mlogloss:1.10715
[91]	train-mlogloss:1.11987	validation-mlogloss:1.10564
[92]	train-mlogloss:1.11826	validation-mlogloss:1.10404
[93]	train-mlogloss:1.11672	validation-mlogloss:1.10259
[94]	train-mlogloss:1.11500	validation-mlogloss:1.10078
[95]	train-mlogloss:1.11343	validation-mlogloss:1.09906
[96]	train-mlogloss:1.11197	validation-mlogloss:1.09751
[97]	train-mlogloss:1.11041	validation-mlogloss:1.09570
[98]	train-mlogloss:1.10893	validation-mlogloss:1.09418
[99]	train-mlogloss:1.10754	validation-mlogloss:1.09271
[100]	train-mlogloss:1.10598	validation-mlogloss:1.09106
[101]	train-mlogloss:1.10454	validation-mlogloss:1.08980
[102]	train-mlogloss:1.10297	validation-mlogloss:1.08841
[103]	train-mlogloss:1.10130	validation-mlogloss:1.08659
[104]	train-mlogloss:1.09989	validation-mlogloss:1.08530
[105]	train-mlogloss:1.09824	validation-mlogloss:1.08391
[106]	train-mlogloss:1.09686	validation-mlogloss:1.08256
[107]	train-mlogloss:1.09531	validation-mlogloss:1.08119
[108]	train-mlogloss:1.09396	validation-mlogloss:1.07991
[109]	train-mlogloss:1.09246	validation-mlogloss:1.07851
[110]	train-mlogloss:1.09116	validation-mlogloss:1.07709
[111]	train-mlogloss:1.08982	validation-mlogloss:1.07576
[112]	train-mlogloss:1.08861	validation-mlogloss:1.07458
[113]	train-mlogloss:1.08733	validation-mlogloss:1.07342
[114]	train-mlogloss:1.08596	validation-mlogloss:1.07212
[115]	train-mlogloss:1.08465	validation-mlogloss:1.07077
[116]	train-mlogloss:1.08336	validation-mlogloss:1.06929
[117]	train-mlogloss:1.08205	validation-mlogloss:1.06806
[118]	train-mlogloss:1.08071	validation-mlogloss:1.06657
[119]	train-mlogloss:1.07946	validation-mlogloss:1.06525
[120]	train-mlogloss:1.07817	validation-mlogloss:1.06383
[121]	train-mlogloss:1.07708	validation-mlogloss:1.06266
[122]	train-mlogloss:1.07590	validation-mlogloss:1.06156
[123]	train-mlogloss:1.07479	validation-mlogloss:1.06036
[124]	train-mlogloss:1.07348	validation-mlogloss:1.05918
[125]	train-mlogloss:1.07233	validation-mlogloss:1.05801
[126]	train-mlogloss:1.07118	validation-mlogloss:1.05676
[127]	train-mlogloss:1.07005	validation-mlogloss:1.05566
[128]	train-mlogloss:1.06892	validation-mlogloss:1.05442
[129]	train-mlogloss:1.06777	validation-mlogloss:1.05327
[130]	train-mlogloss:1.06663	validation-mlogloss:1.05210
[131]	train-mlogloss:1.06556	validation-mlogloss:1.05106
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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)
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 0 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.89 [%]
Global accuracy score (test) = 61.04 [%]
Global F1 score (train) = 64.09 [%]
Global F1 score (test) = 61.82 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.46      0.51      0.48       400
MODERATE-INTENSITY       0.57      0.59      0.58       400
         SEDENTARY       0.66      0.73      0.69       400
VIGOROUS-INTENSITY       0.86      0.62      0.72       345

          accuracy                           0.61      1545
         macro avg       0.64      0.61      0.62      1545
      weighted avg       0.63      0.61      0.61      1545


Accuracy capturado en la ejecución 27: 61.04 [%]
F1-score capturado en la ejecución 27: 61.82 [%]

=== EJECUCIÓN 28 ===

--- TRAIN (ejecución 28) ---

--- TEST (ejecución 28) ---
2025-11-04 11:06:26.172858: 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`.
2025-11-04 11:06:26.184266: 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 00:00:1762250786.197492 1085814 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250786.201411 1085814 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250786.211419 1085814 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250786.211440 1085814 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250786.211441 1085814 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250786.211443 1085814 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:06:26.214527: 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:1.38139	validation-mlogloss:1.38154
[1]	train-mlogloss:1.37661	validation-mlogloss:1.37694
[2]	train-mlogloss:1.37175	validation-mlogloss:1.37205
[3]	train-mlogloss:1.36693	validation-mlogloss:1.36716
[4]	train-mlogloss:1.36227	validation-mlogloss:1.36226
[5]	train-mlogloss:1.35736	validation-mlogloss:1.35710
[6]	train-mlogloss:1.35283	validation-mlogloss:1.35246
[7]	train-mlogloss:1.34808	validation-mlogloss:1.34757
[8]	train-mlogloss:1.34361	validation-mlogloss:1.34304
[9]	train-mlogloss:1.33934	validation-mlogloss:1.33851
[10]	train-mlogloss:1.33498	validation-mlogloss:1.33411
[11]	train-mlogloss:1.33081	validation-mlogloss:1.33012
[12]	train-mlogloss:1.32658	validation-mlogloss:1.32586
[13]	train-mlogloss:1.32253	validation-mlogloss:1.32162
[14]	train-mlogloss:1.31867	validation-mlogloss:1.31766
[15]	train-mlogloss:1.31432	validation-mlogloss:1.31299
[16]	train-mlogloss:1.31050	validation-mlogloss:1.30926
[17]	train-mlogloss:1.30640	validation-mlogloss:1.30505
[18]	train-mlogloss:1.30273	validation-mlogloss:1.30121
[19]	train-mlogloss:1.29899	validation-mlogloss:1.29714
[20]	train-mlogloss:1.29518	validation-mlogloss:1.29353
[21]	train-mlogloss:1.29131	validation-mlogloss:1.28944
[22]	train-mlogloss:1.28749	validation-mlogloss:1.28543
[23]	train-mlogloss:1.28358	validation-mlogloss:1.28133
[24]	train-mlogloss:1.28014	validation-mlogloss:1.27796
[25]	train-mlogloss:1.27676	validation-mlogloss:1.27474
[26]	train-mlogloss:1.27328	validation-mlogloss:1.27099
[27]	train-mlogloss:1.26991	validation-mlogloss:1.26756
[28]	train-mlogloss:1.26673	validation-mlogloss:1.26417
[29]	train-mlogloss:1.26351	validation-mlogloss:1.26088
[30]	train-mlogloss:1.26028	validation-mlogloss:1.25778
[31]	train-mlogloss:1.25722	validation-mlogloss:1.25468
[32]	train-mlogloss:1.25419	validation-mlogloss:1.25185
[33]	train-mlogloss:1.25118	validation-mlogloss:1.24901
[34]	train-mlogloss:1.24816	validation-mlogloss:1.24587
[35]	train-mlogloss:1.24519	validation-mlogloss:1.24278
[36]	train-mlogloss:1.24225	validation-mlogloss:1.23985
[37]	train-mlogloss:1.23886	validation-mlogloss:1.23615
[38]	train-mlogloss:1.23602	validation-mlogloss:1.23311
[39]	train-mlogloss:1.23327	validation-mlogloss:1.23014
[40]	train-mlogloss:1.23045	validation-mlogloss:1.22752
[41]	train-mlogloss:1.22734	validation-mlogloss:1.22407
[42]	train-mlogloss:1.22466	validation-mlogloss:1.22151
[43]	train-mlogloss:1.22192	validation-mlogloss:1.21892
[44]	train-mlogloss:1.21932	validation-mlogloss:1.21621
[45]	train-mlogloss:1.21674	validation-mlogloss:1.21351
[46]	train-mlogloss:1.21419	validation-mlogloss:1.21071
[47]	train-mlogloss:1.21144	validation-mlogloss:1.20776
[48]	train-mlogloss:1.20896	validation-mlogloss:1.20514
[49]	train-mlogloss:1.20629	validation-mlogloss:1.20238
[50]	train-mlogloss:1.20388	validation-mlogloss:1.20014
[51]	train-mlogloss:1.20144	validation-mlogloss:1.19746
[52]	train-mlogloss:1.19908	validation-mlogloss:1.19537
[53]	train-mlogloss:1.19669	validation-mlogloss:1.19306
[54]	train-mlogloss:1.19424	validation-mlogloss:1.19066
[55]	train-mlogloss:1.19179	validation-mlogloss:1.18806
[56]	train-mlogloss:1.18944	validation-mlogloss:1.18579
[57]	train-mlogloss:1.18689	validation-mlogloss:1.18342
[58]	train-mlogloss:1.18463	validation-mlogloss:1.18123
[59]	train-mlogloss:1.18248	validation-mlogloss:1.17900
[60]	train-mlogloss:1.18028	validation-mlogloss:1.17673
[61]	train-mlogloss:1.17807	validation-mlogloss:1.17481
[62]	train-mlogloss:1.17611	validation-mlogloss:1.17290
[63]	train-mlogloss:1.17402	validation-mlogloss:1.17085
[64]	train-mlogloss:1.17207	validation-mlogloss:1.16895
[65]	train-mlogloss:1.16959	validation-mlogloss:1.16646
[66]	train-mlogloss:1.16760	validation-mlogloss:1.16464
[67]	train-mlogloss:1.16548	validation-mlogloss:1.16262
[68]	train-mlogloss:1.16335	validation-mlogloss:1.16053
[69]	train-mlogloss:1.16143	validation-mlogloss:1.15866
[70]	train-mlogloss:1.15941	validation-mlogloss:1.15661
[71]	train-mlogloss:1.15765	validation-mlogloss:1.15485
[72]	train-mlogloss:1.15568	validation-mlogloss:1.15287
[73]	train-mlogloss:1.15369	validation-mlogloss:1.15110
[74]	train-mlogloss:1.15177	validation-mlogloss:1.14906
[75]	train-mlogloss:1.14977	validation-mlogloss:1.14709
[76]	train-mlogloss:1.14799	validation-mlogloss:1.14522
[77]	train-mlogloss:1.14626	validation-mlogloss:1.14339
[78]	train-mlogloss:1.14437	validation-mlogloss:1.14132
[79]	train-mlogloss:1.14259	validation-mlogloss:1.13960
[80]	train-mlogloss:1.14087	validation-mlogloss:1.13788
[81]	train-mlogloss:1.13914	validation-mlogloss:1.13611
[82]	train-mlogloss:1.13709	validation-mlogloss:1.13428
[83]	train-mlogloss:1.13540	validation-mlogloss:1.13253
[84]	train-mlogloss:1.13374	validation-mlogloss:1.13104
[85]	train-mlogloss:1.13180	validation-mlogloss:1.12919
[86]	train-mlogloss:1.13021	validation-mlogloss:1.12771
[87]	train-mlogloss:1.12860	validation-mlogloss:1.12595
[88]	train-mlogloss:1.12700	validation-mlogloss:1.12451
[89]	train-mlogloss:1.12541	validation-mlogloss:1.12315
[90]	train-mlogloss:1.12393	validation-mlogloss:1.12157
[91]	train-mlogloss:1.12231	validation-mlogloss:1.11993
[92]	train-mlogloss:1.12075	validation-mlogloss:1.11834
[93]	train-mlogloss:1.11927	validation-mlogloss:1.11703
[94]	train-mlogloss:1.11766	validation-mlogloss:1.11537
[95]	train-mlogloss:1.11597	validation-mlogloss:1.11377
[96]	train-mlogloss:1.11447	validation-mlogloss:1.11228
[97]	train-mlogloss:1.11297	validation-mlogloss:1.11084
[98]	train-mlogloss:1.11125	validation-mlogloss:1.10923
[99]	train-mlogloss:1.10981	validation-mlogloss:1.10777
[100]	train-mlogloss:1.10841	validation-mlogloss:1.10648
[101]	train-mlogloss:1.10691	validation-mlogloss:1.10507
[102]	train-mlogloss:1.10557	validation-mlogloss:1.10385
[103]	train-mlogloss:1.10427	validation-mlogloss:1.10277
[104]	train-mlogloss:1.10282	validation-mlogloss:1.10135
[105]	train-mlogloss:1.10155	validation-mlogloss:1.10034
[106]	train-mlogloss:1.10015	validation-mlogloss:1.09917
[107]	train-mlogloss:1.09874	validation-mlogloss:1.09804
[108]	train-mlogloss:1.09713	validation-mlogloss:1.09648
[109]	train-mlogloss:1.09580	validation-mlogloss:1.09517
[110]	train-mlogloss:1.09449	validation-mlogloss:1.09387
[111]	train-mlogloss:1.09317	validation-mlogloss:1.09263
[112]	train-mlogloss:1.09190	validation-mlogloss:1.09128
[113]	train-mlogloss:1.09051	validation-mlogloss:1.08996
[114]	train-mlogloss:1.08914	validation-mlogloss:1.08876
[115]	train-mlogloss:1.08785	validation-mlogloss:1.08750
[116]	train-mlogloss:1.08660	validation-mlogloss:1.08636
[117]	train-mlogloss:1.08532	validation-mlogloss:1.08512
[118]	train-mlogloss:1.08400	validation-mlogloss:1.08361
[119]	train-mlogloss:1.08251	validation-mlogloss:1.08217
[120]	train-mlogloss:1.08111	validation-mlogloss:1.08087
[121]	train-mlogloss:1.07985	validation-mlogloss:1.07958
[122]	train-mlogloss:1.07864	validation-mlogloss:1.07847
[123]	train-mlogloss:1.07749	validation-mlogloss:1.07736
[124]	train-mlogloss:1.07635	validation-mlogloss:1.07623
[125]	train-mlogloss:1.07525	validation-mlogloss:1.07531
[126]	train-mlogloss:1.07410	validation-mlogloss:1.07416
[127]	train-mlogloss:1.07289	validation-mlogloss:1.07294
[128]	train-mlogloss:1.07178	validation-mlogloss:1.07204
[129]	train-mlogloss:1.07042	validation-mlogloss:1.07100
[130]	train-mlogloss:1.06928	validation-mlogloss:1.06997
[131]	train-mlogloss:1.06814	validation-mlogloss:1.06903
[132]	train-mlogloss:1.06709	validation-mlogloss:1.06798
[133]	train-mlogloss:1.06596	validation-mlogloss:1.06698
[134]	train-mlogloss:1.06489	validation-mlogloss:1.06607
[135]	train-mlogloss:1.06381	validation-mlogloss:1.06515
[136]	train-mlogloss:1.06283	validation-mlogloss:1.06442
[137]	train-mlogloss:1.06182	validation-mlogloss:1.06342
[138]	train-mlogloss:1.06073	validation-mlogloss:1.06221
[139]	train-mlogloss:1.05969	validation-mlogloss:1.06107
[140]	train-mlogloss:1.05866	validation-mlogloss:1.06018
[141]	train-mlogloss:1.05760	validation-mlogloss:1.05926
[142]	train-mlogloss:1.05660	validation-mlogloss:1.05842
[143]	train-mlogloss:1.05559	validation-mlogloss:1.05735
[144]	train-mlogloss:1.05465	validation-mlogloss:1.05647
[145]	train-mlogloss:1.05369	validation-mlogloss:1.05550
[146]	train-mlogloss:1.05272	validation-mlogloss:1.05468
[147]	train-mlogloss:1.05189	validation-mlogloss:1.05383
[148]	train-mlogloss:1.05088	validation-mlogloss:1.05278
[149]	train-mlogloss:1.04990	validation-mlogloss:1.05181
[150]	train-mlogloss:1.04894	validation-mlogloss:1.05072
[151]	train-mlogloss:1.04798	validation-mlogloss:1.04983
[152]	train-mlogloss:1.04698	validation-mlogloss:1.04901
[153]	train-mlogloss:1.04603	validation-mlogloss:1.04802
[154]	train-mlogloss:1.04518	validation-mlogloss:1.04730
[155]	train-mlogloss:1.04429	validation-mlogloss:1.04643
[156]	train-mlogloss:1.04336	validation-mlogloss:1.04553
[157]	train-mlogloss:1.04242	validation-mlogloss:1.04491
[158]	train-mlogloss:1.04158	validation-mlogloss:1.04432
[159]	train-mlogloss:1.04075	validation-mlogloss:1.04352
[160]	train-mlogloss:1.03992	validation-mlogloss:1.04271
[161]	train-mlogloss:1.03903	validation-mlogloss:1.04180
[162]	train-mlogloss:1.03805	validation-mlogloss:1.04104
[163]	train-mlogloss:1.03723	validation-mlogloss:1.04020
[164]	train-mlogloss:1.03637	validation-mlogloss:1.03947
[165]	train-mlogloss:1.03556	validation-mlogloss:1.03885
[166]	train-mlogloss:1.03464	validation-mlogloss:1.03800
[167]	train-mlogloss:1.03385	validation-mlogloss:1.03747
[168]	train-mlogloss:1.03307	validation-mlogloss:1.03683
[169]	train-mlogloss:1.03210	validation-mlogloss:1.03584
[170]	train-mlogloss:1.03128	validation-mlogloss:1.03492
[171]	train-mlogloss:1.03054	validation-mlogloss:1.03432
[172]	train-mlogloss:1.02970	validation-mlogloss:1.03361
[173]	train-mlogloss:1.02899	validation-mlogloss:1.03301
[174]	train-mlogloss:1.02822	validation-mlogloss:1.03218
[175]	train-mlogloss:1.02747	validation-mlogloss:1.03160
[176]	train-mlogloss:1.02668	validation-mlogloss:1.03096
[177]	train-mlogloss:1.02592	validation-mlogloss:1.03030
[178]	train-mlogloss:1.02521	validation-mlogloss:1.02978
[179]	train-mlogloss:1.02430	validation-mlogloss:1.02921
[180]	train-mlogloss:1.02344	validation-mlogloss:1.02855
[181]	train-mlogloss:1.02275	validation-mlogloss:1.02777
[182]	train-mlogloss:1.02197	validation-mlogloss:1.02706
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[642]	train-mlogloss:0.88731	validation-mlogloss:0.93883
[643]	train-mlogloss:0.88723	validation-mlogloss:0.93874
[644]	train-mlogloss:0.88717	validation-mlogloss:0.93876
[645]	train-mlogloss:0.88701	validation-mlogloss:0.93877
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[679]	train-mlogloss:0.88446	validation-mlogloss:0.93708
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[684]	train-mlogloss:0.88408	validation-mlogloss:0.93677
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[689]	train-mlogloss:0.88370	validation-mlogloss:0.93644
[690]	train-mlogloss:0.88360	validation-mlogloss:0.93641
[691]	train-mlogloss:0.88353	validation-mlogloss:0.93635
[692]	train-mlogloss:0.88340	validation-mlogloss:0.93622
[693]	train-mlogloss:0.88338	validation-mlogloss:0.93621
[694]	train-mlogloss:0.88332	validation-mlogloss:0.93617
[695]	train-mlogloss:0.88327	validation-mlogloss:0.93620
[696]	train-mlogloss:0.88323	validation-mlogloss:0.93618
[697]	train-mlogloss:0.88319	validation-mlogloss:0.93613
[698]	train-mlogloss:0.88314	validation-mlogloss:0.93609
[699]	train-mlogloss:0.88302	validation-mlogloss:0.93599
[700]	train-mlogloss:0.88293	validation-mlogloss:0.93591
[701]	train-mlogloss:0.88291	validation-mlogloss:0.93590
[702]	train-mlogloss:0.88284	validation-mlogloss:0.93584
[703]	train-mlogloss:0.88278	validation-mlogloss:0.93584
[704]	train-mlogloss:0.88267	validation-mlogloss:0.93582
[705]	train-mlogloss:0.88252	validation-mlogloss:0.93581
[706]	train-mlogloss:0.88244	validation-mlogloss:0.93574
[707]	train-mlogloss:0.88238	validation-mlogloss:0.93571
[708]	train-mlogloss:0.88230	validation-mlogloss:0.93558
[709]	train-mlogloss:0.88223	validation-mlogloss:0.93550
[710]	train-mlogloss:0.88214	validation-mlogloss:0.93542
[711]	train-mlogloss:0.88205	validation-mlogloss:0.93531
[712]	train-mlogloss:0.88198	validation-mlogloss:0.93528
[713]	train-mlogloss:0.88190	validation-mlogloss:0.93523
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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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)
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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)
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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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 3]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.65 [%]
Global accuracy score (test) = 60.65 [%]
Global F1 score (train) = 63.65 [%]
Global F1 score (test) = 61.5 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.45      0.51      0.48       400
MODERATE-INTENSITY       0.56      0.57      0.56       400
         SEDENTARY       0.68      0.73      0.70       400
VIGOROUS-INTENSITY       0.86      0.62      0.72       345

          accuracy                           0.61      1545
         macro avg       0.63      0.61      0.61      1545
      weighted avg       0.63      0.61      0.61      1545


Accuracy capturado en la ejecución 28: 60.65 [%]
F1-score capturado en la ejecución 28: 61.5 [%]

=== EJECUCIÓN 29 ===

--- TRAIN (ejecución 29) ---

--- TEST (ejecución 29) ---
2025-11-04 11:06:43.054904: 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`.
2025-11-04 11:06:43.065851: 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 00:00:1762250803.079052 1086124 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762250803.082961 1086124 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762250803.093012 1086124 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250803.093028 1086124 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250803.093029 1086124 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762250803.093030 1086124 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 11:06:43.095997: 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:1.38111	validation-mlogloss:1.38082
[1]	train-mlogloss:1.37600	validation-mlogloss:1.37553
[2]	train-mlogloss:1.37114	validation-mlogloss:1.37056
[3]	train-mlogloss:1.36607	validation-mlogloss:1.36520
[4]	train-mlogloss:1.36127	validation-mlogloss:1.36030
[5]	train-mlogloss:1.35605	validation-mlogloss:1.35471
[6]	train-mlogloss:1.35131	validation-mlogloss:1.34976
[7]	train-mlogloss:1.34679	validation-mlogloss:1.34501
[8]	train-mlogloss:1.34196	validation-mlogloss:1.33998
[9]	train-mlogloss:1.33749	validation-mlogloss:1.33545
[10]	train-mlogloss:1.33305	validation-mlogloss:1.33103
[11]	train-mlogloss:1.32853	validation-mlogloss:1.32631
[12]	train-mlogloss:1.32423	validation-mlogloss:1.32205
[13]	train-mlogloss:1.32012	validation-mlogloss:1.31791
[14]	train-mlogloss:1.31606	validation-mlogloss:1.31360
[15]	train-mlogloss:1.31213	validation-mlogloss:1.30972
[16]	train-mlogloss:1.30799	validation-mlogloss:1.30536
[17]	train-mlogloss:1.30404	validation-mlogloss:1.30135
[18]	train-mlogloss:1.30008	validation-mlogloss:1.29708
[19]	train-mlogloss:1.29636	validation-mlogloss:1.29337
[20]	train-mlogloss:1.29255	validation-mlogloss:1.28964
[21]	train-mlogloss:1.28890	validation-mlogloss:1.28600
[22]	train-mlogloss:1.28527	validation-mlogloss:1.28234
[23]	train-mlogloss:1.28165	validation-mlogloss:1.27863
[24]	train-mlogloss:1.27804	validation-mlogloss:1.27467
[25]	train-mlogloss:1.27452	validation-mlogloss:1.27102
[26]	train-mlogloss:1.27111	validation-mlogloss:1.26747
[27]	train-mlogloss:1.26776	validation-mlogloss:1.26407
[28]	train-mlogloss:1.26441	validation-mlogloss:1.26060
[29]	train-mlogloss:1.26113	validation-mlogloss:1.25741
[30]	train-mlogloss:1.25780	validation-mlogloss:1.25404
[31]	train-mlogloss:1.25447	validation-mlogloss:1.25045
[32]	train-mlogloss:1.25129	validation-mlogloss:1.24744
[33]	train-mlogloss:1.24823	validation-mlogloss:1.24463
[34]	train-mlogloss:1.24469	validation-mlogloss:1.24098
[35]	train-mlogloss:1.24163	validation-mlogloss:1.23772
[36]	train-mlogloss:1.23856	validation-mlogloss:1.23473
[37]	train-mlogloss:1.23536	validation-mlogloss:1.23146
[38]	train-mlogloss:1.23248	validation-mlogloss:1.22843
[39]	train-mlogloss:1.22967	validation-mlogloss:1.22553
[40]	train-mlogloss:1.22691	validation-mlogloss:1.22241
[41]	train-mlogloss:1.22412	validation-mlogloss:1.21960
[42]	train-mlogloss:1.22138	validation-mlogloss:1.21688
[43]	train-mlogloss:1.21874	validation-mlogloss:1.21386
[44]	train-mlogloss:1.21601	validation-mlogloss:1.21112
[45]	train-mlogloss:1.21298	validation-mlogloss:1.20788
[46]	train-mlogloss:1.21031	validation-mlogloss:1.20506
[47]	train-mlogloss:1.20779	validation-mlogloss:1.20273
[48]	train-mlogloss:1.20526	validation-mlogloss:1.20028
[49]	train-mlogloss:1.20281	validation-mlogloss:1.19782
[50]	train-mlogloss:1.20033	validation-mlogloss:1.19515
[51]	train-mlogloss:1.19782	validation-mlogloss:1.19256
[52]	train-mlogloss:1.19529	validation-mlogloss:1.19006
[53]	train-mlogloss:1.19253	validation-mlogloss:1.18711
[54]	train-mlogloss:1.18978	validation-mlogloss:1.18406
[55]	train-mlogloss:1.18735	validation-mlogloss:1.18168
[56]	train-mlogloss:1.18503	validation-mlogloss:1.17953
[57]	train-mlogloss:1.18267	validation-mlogloss:1.17712
[58]	train-mlogloss:1.18037	validation-mlogloss:1.17478
[59]	train-mlogloss:1.17818	validation-mlogloss:1.17252
[60]	train-mlogloss:1.17602	validation-mlogloss:1.17037
[61]	train-mlogloss:1.17347	validation-mlogloss:1.16751
[62]	train-mlogloss:1.17139	validation-mlogloss:1.16531
[63]	train-mlogloss:1.16892	validation-mlogloss:1.16258
[64]	train-mlogloss:1.16687	validation-mlogloss:1.16057
[65]	train-mlogloss:1.16480	validation-mlogloss:1.15846
[66]	train-mlogloss:1.16279	validation-mlogloss:1.15643
[67]	train-mlogloss:1.16080	validation-mlogloss:1.15445
[68]	train-mlogloss:1.15875	validation-mlogloss:1.15231
[69]	train-mlogloss:1.15667	validation-mlogloss:1.15008
[70]	train-mlogloss:1.15467	validation-mlogloss:1.14791
[71]	train-mlogloss:1.15266	validation-mlogloss:1.14617
[72]	train-mlogloss:1.15039	validation-mlogloss:1.14365
[73]	train-mlogloss:1.14841	validation-mlogloss:1.14164
[74]	train-mlogloss:1.14641	validation-mlogloss:1.13950
[75]	train-mlogloss:1.14448	validation-mlogloss:1.13760
[76]	train-mlogloss:1.14275	validation-mlogloss:1.13571
[77]	train-mlogloss:1.14097	validation-mlogloss:1.13389
[78]	train-mlogloss:1.13906	validation-mlogloss:1.13189
[79]	train-mlogloss:1.13716	validation-mlogloss:1.12993
[80]	train-mlogloss:1.13533	validation-mlogloss:1.12811
[81]	train-mlogloss:1.13329	validation-mlogloss:1.12596
[82]	train-mlogloss:1.13129	validation-mlogloss:1.12421
[83]	train-mlogloss:1.12957	validation-mlogloss:1.12231
[84]	train-mlogloss:1.12783	validation-mlogloss:1.12058
[85]	train-mlogloss:1.12588	validation-mlogloss:1.11869
[86]	train-mlogloss:1.12417	validation-mlogloss:1.11692
[87]	train-mlogloss:1.12235	validation-mlogloss:1.11497
[88]	train-mlogloss:1.12047	validation-mlogloss:1.11319
[89]	train-mlogloss:1.11884	validation-mlogloss:1.11145
[90]	train-mlogloss:1.11717	validation-mlogloss:1.10991
[91]	train-mlogloss:1.11538	validation-mlogloss:1.10809
[92]	train-mlogloss:1.11376	validation-mlogloss:1.10650
[93]	train-mlogloss:1.11234	validation-mlogloss:1.10509
[94]	train-mlogloss:1.11069	validation-mlogloss:1.10344
[95]	train-mlogloss:1.10912	validation-mlogloss:1.10194
[96]	train-mlogloss:1.10752	validation-mlogloss:1.10012
[97]	train-mlogloss:1.10594	validation-mlogloss:1.09835
[98]	train-mlogloss:1.10447	validation-mlogloss:1.09695
[99]	train-mlogloss:1.10289	validation-mlogloss:1.09516
[100]	train-mlogloss:1.10138	validation-mlogloss:1.09369
[101]	train-mlogloss:1.09992	validation-mlogloss:1.09225
[102]	train-mlogloss:1.09840	validation-mlogloss:1.09070
[103]	train-mlogloss:1.09674	validation-mlogloss:1.08916
[104]	train-mlogloss:1.09514	validation-mlogloss:1.08769
[105]	train-mlogloss:1.09372	validation-mlogloss:1.08634
[106]	train-mlogloss:1.09232	validation-mlogloss:1.08508
[107]	train-mlogloss:1.09091	validation-mlogloss:1.08358
[108]	train-mlogloss:1.08957	validation-mlogloss:1.08230
[109]	train-mlogloss:1.08825	validation-mlogloss:1.08113
[110]	train-mlogloss:1.08688	validation-mlogloss:1.07968
[111]	train-mlogloss:1.08558	validation-mlogloss:1.07855
[112]	train-mlogloss:1.08431	validation-mlogloss:1.07738
[113]	train-mlogloss:1.08304	validation-mlogloss:1.07621
[114]	train-mlogloss:1.08182	validation-mlogloss:1.07492
[115]	train-mlogloss:1.08055	validation-mlogloss:1.07365
[116]	train-mlogloss:1.07934	validation-mlogloss:1.07249
[117]	train-mlogloss:1.07806	validation-mlogloss:1.07132
[118]	train-mlogloss:1.07682	validation-mlogloss:1.07011
[119]	train-mlogloss:1.07559	validation-mlogloss:1.06878
[120]	train-mlogloss:1.07438	validation-mlogloss:1.06741
[121]	train-mlogloss:1.07324	validation-mlogloss:1.06628
[122]	train-mlogloss:1.07211	validation-mlogloss:1.06510
[123]	train-mlogloss:1.07087	validation-mlogloss:1.06391
[124]	train-mlogloss:1.06966	validation-mlogloss:1.06298
[125]	train-mlogloss:1.06840	validation-mlogloss:1.06166
[126]	train-mlogloss:1.06718	validation-mlogloss:1.06062
[127]	train-mlogloss:1.06595	validation-mlogloss:1.05941
[128]	train-mlogloss:1.06481	validation-mlogloss:1.05849
[129]	train-mlogloss:1.06359	validation-mlogloss:1.05735
[130]	train-mlogloss:1.06234	validation-mlogloss:1.05616
[131]	train-mlogloss:1.06127	validation-mlogloss:1.05533
[132]	train-mlogloss:1.06013	validation-mlogloss:1.05426
[133]	train-mlogloss:1.05909	validation-mlogloss:1.05345
[134]	train-mlogloss:1.05800	validation-mlogloss:1.05242
[135]	train-mlogloss:1.05693	validation-mlogloss:1.05119
[136]	train-mlogloss:1.05588	validation-mlogloss:1.05007
[137]	train-mlogloss:1.05483	validation-mlogloss:1.04922
[138]	train-mlogloss:1.05368	validation-mlogloss:1.04801
[139]	train-mlogloss:1.05260	validation-mlogloss:1.04702
[140]	train-mlogloss:1.05155	validation-mlogloss:1.04614
[141]	train-mlogloss:1.05051	validation-mlogloss:1.04528
[142]	train-mlogloss:1.04955	validation-mlogloss:1.04446
[143]	train-mlogloss:1.04850	validation-mlogloss:1.04345
[144]	train-mlogloss:1.04750	validation-mlogloss:1.04267
[145]	train-mlogloss:1.04650	validation-mlogloss:1.04187
[146]	train-mlogloss:1.04547	validation-mlogloss:1.04093
[147]	train-mlogloss:1.04459	validation-mlogloss:1.04013
[148]	train-mlogloss:1.04363	validation-mlogloss:1.03930
[149]	train-mlogloss:1.04267	validation-mlogloss:1.03831
[150]	train-mlogloss:1.04158	validation-mlogloss:1.03753
[151]	train-mlogloss:1.04059	validation-mlogloss:1.03658
[152]	train-mlogloss:1.03972	validation-mlogloss:1.03592
[153]	train-mlogloss:1.03886	validation-mlogloss:1.03533
[154]	train-mlogloss:1.03798	validation-mlogloss:1.03456
[155]	train-mlogloss:1.03700	validation-mlogloss:1.03377
[156]	train-mlogloss:1.03620	validation-mlogloss:1.03305
[157]	train-mlogloss:1.03541	validation-mlogloss:1.03242
[158]	train-mlogloss:1.03452	validation-mlogloss:1.03177
[159]	train-mlogloss:1.03366	validation-mlogloss:1.03094
[160]	train-mlogloss:1.03275	validation-mlogloss:1.03024
[161]	train-mlogloss:1.03178	validation-mlogloss:1.02930
[162]	train-mlogloss:1.03099	validation-mlogloss:1.02847
[163]	train-mlogloss:1.03015	validation-mlogloss:1.02759
[164]	train-mlogloss:1.02930	validation-mlogloss:1.02686
[165]	train-mlogloss:1.02843	validation-mlogloss:1.02601
[166]	train-mlogloss:1.02774	validation-mlogloss:1.02537
[167]	train-mlogloss:1.02700	validation-mlogloss:1.02478
[168]	train-mlogloss:1.02618	validation-mlogloss:1.02419
[169]	train-mlogloss:1.02536	validation-mlogloss:1.02350
[170]	train-mlogloss:1.02460	validation-mlogloss:1.02278
[171]	train-mlogloss:1.02379	validation-mlogloss:1.02200
[172]	train-mlogloss:1.02307	validation-mlogloss:1.02139
[173]	train-mlogloss:1.02228	validation-mlogloss:1.02076
[174]	train-mlogloss:1.02150	validation-mlogloss:1.02017
[175]	train-mlogloss:1.02071	validation-mlogloss:1.01933
[176]	train-mlogloss:1.01986	validation-mlogloss:1.01861
[177]	train-mlogloss:1.01912	validation-mlogloss:1.01802
[178]	train-mlogloss:1.01826	validation-mlogloss:1.01742
[179]	train-mlogloss:1.01753	validation-mlogloss:1.01691
[180]	train-mlogloss:1.01683	validation-mlogloss:1.01640
[181]	train-mlogloss:1.01609	validation-mlogloss:1.01573
[182]	train-mlogloss:1.01538	validation-mlogloss:1.01506
[183]	train-mlogloss:1.01461	validation-mlogloss:1.01432
[184]	train-mlogloss:1.01393	validation-mlogloss:1.01359
[185]	train-mlogloss:1.01323	validation-mlogloss:1.01303
[186]	train-mlogloss:1.01261	validation-mlogloss:1.01258
[187]	train-mlogloss:1.01184	validation-mlogloss:1.01197
[188]	train-mlogloss:1.01114	validation-mlogloss:1.01143
[189]	train-mlogloss:1.01042	validation-mlogloss:1.01063
[190]	train-mlogloss:1.00965	validation-mlogloss:1.01011
[191]	train-mlogloss:1.00896	validation-mlogloss:1.00942
[192]	train-mlogloss:1.00825	validation-mlogloss:1.00888
[193]	train-mlogloss:1.00759	validation-mlogloss:1.00839
[194]	train-mlogloss:1.00693	validation-mlogloss:1.00785
[195]	train-mlogloss:1.00625	validation-mlogloss:1.00730
[196]	train-mlogloss:1.00564	validation-mlogloss:1.00687
[197]	train-mlogloss:1.00499	validation-mlogloss:1.00635
[198]	train-mlogloss:1.00435	validation-mlogloss:1.00582
[199]	train-mlogloss:1.00375	validation-mlogloss:1.00535
[200]	train-mlogloss:1.00305	validation-mlogloss:1.00473
[201]	train-mlogloss:1.00230	validation-mlogloss:1.00407
[202]	train-mlogloss:1.00162	validation-mlogloss:1.00334
[203]	train-mlogloss:1.00100	validation-mlogloss:1.00287
[204]	train-mlogloss:1.00031	validation-mlogloss:1.00230
[205]	train-mlogloss:0.99965	validation-mlogloss:1.00173
[206]	train-mlogloss:0.99903	validation-mlogloss:1.00128
[207]	train-mlogloss:0.99841	validation-mlogloss:1.00075
[208]	train-mlogloss:0.99775	validation-mlogloss:1.00030
[209]	train-mlogloss:0.99711	validation-mlogloss:0.99982
[210]	train-mlogloss:0.99643	validation-mlogloss:0.99925
[211]	train-mlogloss:0.99581	validation-mlogloss:0.99852
[212]	train-mlogloss:0.99522	validation-mlogloss:0.99815
[213]	train-mlogloss:0.99462	validation-mlogloss:0.99775
[214]	train-mlogloss:0.99407	validation-mlogloss:0.99734
[215]	train-mlogloss:0.99347	validation-mlogloss:0.99690
[216]	train-mlogloss:0.99285	validation-mlogloss:0.99648
[217]	train-mlogloss:0.99225	validation-mlogloss:0.99590
[218]	train-mlogloss:0.99173	validation-mlogloss:0.99555
[219]	train-mlogloss:0.99101	validation-mlogloss:0.99508
[220]	train-mlogloss:0.99042	validation-mlogloss:0.99459
[221]	train-mlogloss:0.98979	validation-mlogloss:0.99406
[222]	train-mlogloss:0.98918	validation-mlogloss:0.99359
[223]	train-mlogloss:0.98857	validation-mlogloss:0.99296
[224]	train-mlogloss:0.98797	validation-mlogloss:0.99252
[225]	train-mlogloss:0.98744	validation-mlogloss:0.99209
[226]	train-mlogloss:0.98690	validation-mlogloss:0.99164
[227]	train-mlogloss:0.98638	validation-mlogloss:0.99134
[228]	train-mlogloss:0.98582	validation-mlogloss:0.99081
[229]	train-mlogloss:0.98522	validation-mlogloss:0.99039
[230]	train-mlogloss:0.98462	validation-mlogloss:0.98995
[231]	train-mlogloss:0.98410	validation-mlogloss:0.98952
[232]	train-mlogloss:0.98351	validation-mlogloss:0.98896
[233]	train-mlogloss:0.98304	validation-mlogloss:0.98861
[234]	train-mlogloss:0.98254	validation-mlogloss:0.98826
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[549]	train-mlogloss:0.89184	validation-mlogloss:0.92738
[550]	train-mlogloss:0.89170	validation-mlogloss:0.92728
[551]	train-mlogloss:0.89156	validation-mlogloss:0.92711
[552]	train-mlogloss:0.89142	validation-mlogloss:0.92698
[553]	train-mlogloss:0.89137	validation-mlogloss:0.92698
[554]	train-mlogloss:0.89116	validation-mlogloss:0.92688
[555]	train-mlogloss:0.89101	validation-mlogloss:0.92689
[556]	train-mlogloss:0.89093	validation-mlogloss:0.92686
[557]	train-mlogloss:0.89077	validation-mlogloss:0.92666
[558]	train-mlogloss:0.89061	validation-mlogloss:0.92654
[559]	train-mlogloss:0.89048	validation-mlogloss:0.92648
[560]	train-mlogloss:0.89040	validation-mlogloss:0.92644
[561]	train-mlogloss:0.89026	validation-mlogloss:0.92628
[562]	train-mlogloss:0.89020	validation-mlogloss:0.92624
[563]	train-mlogloss:0.89013	validation-mlogloss:0.92617
[564]	train-mlogloss:0.89008	validation-mlogloss:0.92612
[565]	train-mlogloss:0.88993	validation-mlogloss:0.92601
[566]	train-mlogloss:0.88987	validation-mlogloss:0.92598
[567]	train-mlogloss:0.88972	validation-mlogloss:0.92582
[568]	train-mlogloss:0.88961	validation-mlogloss:0.92574
[569]	train-mlogloss:0.88955	validation-mlogloss:0.92570
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[571]	train-mlogloss:0.88924	validation-mlogloss:0.92551
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[574]	train-mlogloss:0.88890	validation-mlogloss:0.92521
[575]	train-mlogloss:0.88873	validation-mlogloss:0.92502
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[580]	train-mlogloss:0.88823	validation-mlogloss:0.92461
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[597]	train-mlogloss:0.88672	validation-mlogloss:0.92352
[598]	train-mlogloss:0.88665	validation-mlogloss:0.92343
[599]	train-mlogloss:0.88653	validation-mlogloss:0.92326
[600]	train-mlogloss:0.88635	validation-mlogloss:0.92315
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[602]	train-mlogloss:0.88614	validation-mlogloss:0.92296
[603]	train-mlogloss:0.88607	validation-mlogloss:0.92290
[604]	train-mlogloss:0.88593	validation-mlogloss:0.92279
[605]	train-mlogloss:0.88581	validation-mlogloss:0.92278
[606]	train-mlogloss:0.88569	validation-mlogloss:0.92271
[607]	train-mlogloss:0.88553	validation-mlogloss:0.92266
[608]	train-mlogloss:0.88544	validation-mlogloss:0.92260
[609]	train-mlogloss:0.88536	validation-mlogloss:0.92257
[610]	train-mlogloss:0.88524	validation-mlogloss:0.92253
[611]	train-mlogloss:0.88518	validation-mlogloss:0.92253
[612]	train-mlogloss:0.88511	validation-mlogloss:0.92249
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[614]	train-mlogloss:0.88498	validation-mlogloss:0.92247
[615]	train-mlogloss:0.88487	validation-mlogloss:0.92244
[616]	train-mlogloss:0.88481	validation-mlogloss:0.92240
[617]	train-mlogloss:0.88476	validation-mlogloss:0.92233
[618]	train-mlogloss:0.88460	validation-mlogloss:0.92216
[619]	train-mlogloss:0.88446	validation-mlogloss:0.92209
[620]	train-mlogloss:0.88434	validation-mlogloss:0.92201
[621]	train-mlogloss:0.88426	validation-mlogloss:0.92199
[622]	train-mlogloss:0.88424	validation-mlogloss:0.92198
[623]	train-mlogloss:0.88407	validation-mlogloss:0.92199
[624]	train-mlogloss:0.88402	validation-mlogloss:0.92199
[625]	train-mlogloss:0.88391	validation-mlogloss:0.92189
[626]	train-mlogloss:0.88385	validation-mlogloss:0.92185
[627]	train-mlogloss:0.88374	validation-mlogloss:0.92180
[628]	train-mlogloss:0.88359	validation-mlogloss:0.92170
[629]	train-mlogloss:0.88349	validation-mlogloss:0.92161
[630]	train-mlogloss:0.88338	validation-mlogloss:0.92151
[631]	train-mlogloss:0.88329	validation-mlogloss:0.92152
[632]	train-mlogloss:0.88318	validation-mlogloss:0.92140
[633]	train-mlogloss:0.88309	validation-mlogloss:0.92131
[634]	train-mlogloss:0.88304	validation-mlogloss:0.92127
[635]	train-mlogloss:0.88298	validation-mlogloss:0.92119
[636]	train-mlogloss:0.88287	validation-mlogloss:0.92111
[637]	train-mlogloss:0.88280	validation-mlogloss:0.92106
[638]	train-mlogloss:0.88268	validation-mlogloss:0.92097
[639]	train-mlogloss:0.88256	validation-mlogloss:0.92088
[640]	train-mlogloss:0.88246	validation-mlogloss:0.92086
[641]	train-mlogloss:0.88233	validation-mlogloss:0.92078
[642]	train-mlogloss:0.88225	validation-mlogloss:0.92081
[643]	train-mlogloss:0.88220	validation-mlogloss:0.92077
[644]	train-mlogloss:0.88215	validation-mlogloss:0.92074
[645]	train-mlogloss:0.88201	validation-mlogloss:0.92065
[646]	train-mlogloss:0.88193	validation-mlogloss:0.92067
[647]	train-mlogloss:0.88184	validation-mlogloss:0.92056
[648]	train-mlogloss:0.88179	validation-mlogloss:0.92056
[649]	train-mlogloss:0.88168	validation-mlogloss:0.92051
[650]	train-mlogloss:0.88163	validation-mlogloss:0.92045
[651]	train-mlogloss:0.88155	validation-mlogloss:0.92037
[652]	train-mlogloss:0.88150	validation-mlogloss:0.92037
[653]	train-mlogloss:0.88141	validation-mlogloss:0.92030
[654]	train-mlogloss:0.88136	validation-mlogloss:0.92028
[655]	train-mlogloss:0.88123	validation-mlogloss:0.92017
[656]	train-mlogloss:0.88114	validation-mlogloss:0.92007
[657]	train-mlogloss:0.88105	validation-mlogloss:0.92005
[658]	train-mlogloss:0.88094	validation-mlogloss:0.91993
[659]	train-mlogloss:0.88084	validation-mlogloss:0.91975
[660]	train-mlogloss:0.88078	validation-mlogloss:0.91970
[661]	train-mlogloss:0.88072	validation-mlogloss:0.91963
[662]	train-mlogloss:0.88066	validation-mlogloss:0.91960
[663]	train-mlogloss:0.88056	validation-mlogloss:0.91950
[664]	train-mlogloss:0.88048	validation-mlogloss:0.91945
[665]	train-mlogloss:0.88033	validation-mlogloss:0.91928
[666]	train-mlogloss:0.88025	validation-mlogloss:0.91925
[667]	train-mlogloss:0.88023	validation-mlogloss:0.91924
[668]	train-mlogloss:0.88016	validation-mlogloss:0.91917
[669]	train-mlogloss:0.88009	validation-mlogloss:0.91912
[670]	train-mlogloss:0.88004	validation-mlogloss:0.91908
[671]	train-mlogloss:0.87998	validation-mlogloss:0.91904
[672]	train-mlogloss:0.87996	validation-mlogloss:0.91903
[673]	train-mlogloss:0.87987	validation-mlogloss:0.91899
[674]	train-mlogloss:0.87984	validation-mlogloss:0.91895
[675]	train-mlogloss:0.87981	validation-mlogloss:0.91894
[676]	train-mlogloss:0.87975	validation-mlogloss:0.91890
[677]	train-mlogloss:0.87970	validation-mlogloss:0.91883
[678]	train-mlogloss:0.87964	validation-mlogloss:0.91876
[679]	train-mlogloss:0.87952	validation-mlogloss:0.91868
[680]	train-mlogloss:0.87941	validation-mlogloss:0.91862
[681]	train-mlogloss:0.87937	validation-mlogloss:0.91858
[682]	train-mlogloss:0.87932	validation-mlogloss:0.91858
[683]	train-mlogloss:0.87923	validation-mlogloss:0.91849
[684]	train-mlogloss:0.87918	validation-mlogloss:0.91847
[685]	train-mlogloss:0.87914	validation-mlogloss:0.91846
[686]	train-mlogloss:0.87906	validation-mlogloss:0.91835
[687]	train-mlogloss:0.87899	validation-mlogloss:0.91830
[688]	train-mlogloss:0.87894	validation-mlogloss:0.91830
[689]	train-mlogloss:0.87887	validation-mlogloss:0.91822
[690]	train-mlogloss:0.87878	validation-mlogloss:0.91816
[691]	train-mlogloss:0.87872	validation-mlogloss:0.91806
[692]	train-mlogloss:0.87866	validation-mlogloss:0.91799
[693]	train-mlogloss:0.87856	validation-mlogloss:0.91793
[694]	train-mlogloss:0.87850	validation-mlogloss:0.91785
[695]	train-mlogloss:0.87844	validation-mlogloss:0.91784
[696]	train-mlogloss:0.87840	validation-mlogloss:0.91787
[697]	train-mlogloss:0.87833	validation-mlogloss:0.91780
[698]	train-mlogloss:0.87823	validation-mlogloss:0.91770
[699]	train-mlogloss:0.87818	validation-mlogloss:0.91763
[700]	train-mlogloss:0.87812	validation-mlogloss:0.91762
[701]	train-mlogloss:0.87797	validation-mlogloss:0.91753
[702]	train-mlogloss:0.87788	validation-mlogloss:0.91744
[703]	train-mlogloss:0.87782	validation-mlogloss:0.91740
[704]	train-mlogloss:0.87774	validation-mlogloss:0.91733
[705]	train-mlogloss:0.87768	validation-mlogloss:0.91730
[706]	train-mlogloss:0.87758	validation-mlogloss:0.91726
[707]	train-mlogloss:0.87744	validation-mlogloss:0.91717
[708]	train-mlogloss:0.87733	validation-mlogloss:0.91711
[709]	train-mlogloss:0.87720	validation-mlogloss:0.91701
[710]	train-mlogloss:0.87709	validation-mlogloss:0.91691
[711]	train-mlogloss:0.87705	validation-mlogloss:0.91687
[712]	train-mlogloss:0.87698	validation-mlogloss:0.91681
[713]	train-mlogloss:0.87694	validation-mlogloss:0.91679
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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.74 [%]
Global accuracy score (test) = 62.39 [%]
Global F1 score (train) = 63.93 [%]
Global F1 score (test) = 63.08 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.47      0.50      0.48       400
MODERATE-INTENSITY       0.59      0.65      0.61       400
         SEDENTARY       0.68      0.73      0.71       400
VIGOROUS-INTENSITY       0.87      0.62      0.72       345

          accuracy                           0.62      1545
         macro avg       0.65      0.62      0.63      1545
      weighted avg       0.64      0.62      0.63      1545


Accuracy capturado en la ejecución 29: 62.39 [%]
F1-score capturado en la ejecución 29: 63.08 [%]

=== 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)
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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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.
(1545, 91)
(10469, 91)
[[2.]
 [2.]
 [2.]
 ...
 [3.]
 [3.]
 [3.]]
(1545, 1)
[2 2 2 ... 3 0 1]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 63.94 [%]
Global accuracy score (test) = 60.65 [%]
Global F1 score (train) = 64.14 [%]
Global F1 score (test) = 61.4 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.46      0.47      0.47       400
MODERATE-INTENSITY       0.54      0.61      0.57       400
         SEDENTARY       0.68      0.72      0.70       400
VIGOROUS-INTENSITY       0.85      0.61      0.72       345

          accuracy                           0.61      1545
         macro avg       0.63      0.61      0.61      1545
      weighted avg       0.62      0.61      0.61      1545


Accuracy capturado en la ejecución 30: 60.65 [%]
F1-score capturado en la ejecución 30: 61.4 [%]

=== RESUMEN FINAL ===
Accuracies: [58.96, 60.58, 60.58, 60.06, 61.75, 62.72, 60.26, 60.84, 60.13, 61.23, 59.81, 60.06, 61.1, 61.49, 58.96, 59.29, 58.38, 58.64, 61.88, 59.94, 60.0, 60.39, 60.52, 61.1, 60.45, 58.83, 61.04, 60.65, 62.39, 60.65]
F1-scores: [59.98, 61.23, 61.47, 60.86, 62.31, 63.13, 61.0, 61.48, 60.64, 61.76, 60.68, 60.82, 61.9, 62.27, 59.6, 59.98, 59.15, 59.49, 62.46, 60.71, 60.74, 61.14, 61.23, 61.53, 61.29, 59.77, 61.82, 61.5, 63.08, 61.4]
Accuracy mean: 60.4227 | std: 1.0500
F1 mean: 61.1473 | std: 0.9794

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