2025-11-04 10:32:48.826346: 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 10:32:48.837610: 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 00:00:1762248768.850677 1048346 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248768.854687 1048346 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248768.864698 1048346 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248768.864722 1048346 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248768.864724 1048346 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248768.864726 1048346 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:32:48.867841: 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 10:32:55,114	INFO worker.py:1927 -- Started a local Ray instance.
2025-11-04 10:32:55,800	INFO tune.py:253 -- Initializing Ray automatically. For cluster usage or custom Ray initialization, call `ray.init(...)` before `Tuner(...)`.
2025-11-04 10:32:55,873	INFO trial.py:182 -- Creating a new dirname dir_3e61e_dd5e because trial dirname 'dir_3e61e' already exists.
2025-11-04 10:32:55,877	INFO trial.py:182 -- Creating a new dirname dir_3e61e_9bb5 because trial dirname 'dir_3e61e' already exists.
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2025-11-04 10:32:55,881	INFO trial.py:182 -- Creating a new dirname dir_3e61e_e1f1 because trial dirname 'dir_3e61e' already exists.
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2025-11-04 10:32:55,893	INFO trial.py:182 -- Creating a new dirname dir_3e61e_bd92 because trial dirname 'dir_3e61e' already exists.
2025-11-04 10:32:55,895	INFO trial.py:182 -- Creating a new dirname dir_3e61e_be0c because trial dirname 'dir_3e61e' already exists.
2025-11-04 10:32:55,897	INFO trial.py:182 -- Creating a new dirname dir_3e61e_63d2 because trial dirname 'dir_3e61e' already exists.
2025-11-04 10:32:55,900	INFO trial.py:182 -- Creating a new dirname dir_3e61e_6836 because trial dirname 'dir_3e61e' already exists.
2025-11-04 10:32:55,903	INFO trial.py:182 -- Creating a new dirname dir_3e61e_6c42 because trial dirname 'dir_3e61e' already exists.
2025-11-04 10:32:55,906	INFO trial.py:182 -- Creating a new dirname dir_3e61e_14e9 because trial dirname 'dir_3e61e' already exists.
2025-11-04 10:32:55,909	INFO trial.py:182 -- Creating a new dirname dir_3e61e_7114 because trial dirname 'dir_3e61e' already exists.
2025-11-04 10:32:55,913	INFO trial.py:182 -- Creating a new dirname dir_3e61e_db4b because trial dirname 'dir_3e61e' already exists.
2025-11-04 10:32:55,916	INFO trial.py:182 -- Creating a new dirname dir_3e61e_0c66 because trial dirname 'dir_3e61e' already exists.
2025-11-04 10:32:55,928	INFO trial.py:182 -- Creating a new dirname dir_3e61e_0652 because trial dirname 'dir_3e61e' already exists.
2025-11-04 10:32:55,937	INFO trial.py:182 -- Creating a new dirname dir_3e61e_c8e3 because trial dirname 'dir_3e61e' 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_C/case_C_XGB_acc_gyr_17_superclasses_CPA_METs/XGBoost_hyperparameters_tuning
To visualize your results with TensorBoard, run: `tensorboard --logdir /tmp/ray/session_2025-11-04_10-32-54_305049_1048346/artifacts/2025-11-04_10-32-55/XGBoost_hyperparameters_tuning/driver_artifacts`

Trial status: 20 PENDING
Current time: 2025-11-04 10:32:56. 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_3e61e    PENDING                  608             2        0.0195196       0.547785             0.807243   22.4428                    70      58.886         49.7709              7080 │
│ trial_3e61e    PENDING                  278             3        0.0152949       0.750992             0.831092   28.3893                    81     919.466         18.9778              1744 │
│ trial_3e61e    PENDING                  588             3        0.0146662       0.531688             0.643934    6.20981                  146       5.97029       26.442               5860 │
│ trial_3e61e    PENDING                  576             2        0.0198779       0.618591             0.659284   16.4909                   126      25.2645        24.7553              2569 │
│ trial_3e61e    PENDING                  517             2        0.00901737      0.584256             0.525248   22.0358                   111     397.932          7.34405             4069 │
│ trial_3e61e    PENDING                  376             3        0.018019        0.761167             0.623623    5.2294                   135      17.9044       163.812               6412 │
│ trial_3e61e    PENDING                  571             2        0.0183267       0.761875             0.662762   18.6245                   183       5.85826       77.48                7694 │
│ trial_3e61e    PENDING                  728             2        0.00620727      0.587246             0.688072   13.1042                   194     129.418        348.485               6073 │
│ trial_3e61e    PENDING                  503             3        0.0167579       0.700313             0.731405   10.7857                   121       4.21667       22.5949              6614 │
│ trial_3e61e    PENDING                  251             2        0.00589301      0.791274             0.641109   14.7318                   138      12.1911        59.7902              5962 │
│ trial_3e61e    PENDING                  375             2        0.0191749       0.797987             0.526235   16.8837                   148     277.867         21.2496              8750 │
│ trial_3e61e    PENDING                  552             3        0.00518694      0.743033             0.814563   24.1402                   133      55.5009       220.28                9343 │
│ trial_3e61e    PENDING                  757             3        0.0138236       0.587692             0.709206   25.104                     62       3.11279       23.2571              5613 │
│ trial_3e61e    PENDING                  542             3        0.00705996      0.565602             0.623176    6.66706                  150     107.565        101.116               3953 │
│ trial_3e61e    PENDING                  253             3        0.0101395       0.785125             0.642466   28.4619                   186     497.357        117.888               2414 │
│ trial_3e61e    PENDING                  443             3        0.0152383       0.638747             0.501683    6.21693                  161     876.274         12.0761              5987 │
│ trial_3e61e    PENDING                  289             3        0.0196544       0.61134              0.559905    8.51114                  121     622.376        105.44                3210 │
│ trial_3e61e    PENDING                  439             2        0.0106674       0.7374               0.840622   23.4996                    87     363.963        324.87                5050 │
│ trial_3e61e    PENDING                  397             2        0.0134191       0.515726             0.553979    5.02458                   81      33.3285        26.1677              3722 │
│ trial_3e61e    PENDING                  672             3        0.00727831      0.514721             0.670695   11.7282                    73     747.188        139.556               3798 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.64393 │
│ gamma                        6.20981 │
│ learning_rate                0.01467 │
│ max_depth                          3 │
│ min_child_weight                 146 │
│ num_boost_round                  588 │
│ random_state                    5860 │
│ reg_alpha                    5.97029 │
│ reg_lambda                    26.442 │
│ subsample                    0.53169 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.52623 │
│ gamma                        16.8837 │
│ learning_rate                0.01917 │
│ max_depth                          2 │
│ min_child_weight                 148 │
│ num_boost_round                  375 │
│ random_state                    8750 │
│ reg_alpha                    277.867 │
│ reg_lambda                   21.2496 │
│ subsample                    0.79799 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.64111 │
│ gamma                        14.7318 │
│ learning_rate                0.00589 │
│ max_depth                          2 │
│ min_child_weight                 138 │
│ num_boost_round                  251 │
│ random_state                    5962 │
│ reg_alpha                    12.1911 │
│ reg_lambda                   59.7902 │
│ subsample                    0.79127 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.70921 │
│ gamma                         25.104 │
│ learning_rate                0.01382 │
│ max_depth                          3 │
│ min_child_weight                  62 │
│ num_boost_round                  757 │
│ random_state                    5613 │
│ reg_alpha                    3.11279 │
│ reg_lambda                   23.2571 │
│ subsample                    0.58769 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.80724 │
│ gamma                        22.4428 │
│ learning_rate                0.01952 │
│ max_depth                          2 │
│ min_child_weight                  70 │
│ num_boost_round                  608 │
│ random_state                    7080 │
│ reg_alpha                     58.886 │
│ reg_lambda                   49.7709 │
│ subsample                    0.54778 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.55991 │
│ gamma                        8.51114 │
│ learning_rate                0.01965 │
│ max_depth                          3 │
│ min_child_weight                 121 │
│ num_boost_round                  289 │
│ random_state                    3210 │
│ reg_alpha                    622.376 │
│ reg_lambda                    105.44 │
│ subsample                    0.61134 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.52525 │
│ gamma                        22.0358 │
│ learning_rate                0.00902 │
│ max_depth                          2 │
│ min_child_weight                 111 │
│ num_boost_round                  517 │
│ random_state                    4069 │
│ reg_alpha                    397.932 │
│ reg_lambda                   7.34405 │
│ subsample                    0.58426 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.66276 │
│ gamma                        18.6245 │
│ learning_rate                0.01833 │
│ max_depth                          2 │
│ min_child_weight                 183 │
│ num_boost_round                  571 │
│ random_state                    7694 │
│ reg_alpha                    5.85826 │
│ reg_lambda                     77.48 │
│ subsample                    0.76187 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.68807 │
│ gamma                        13.1042 │
│ learning_rate                0.00621 │
│ max_depth                          2 │
│ min_child_weight                 194 │
│ num_boost_round                  728 │
│ random_state                    6073 │
│ reg_alpha                    129.418 │
│ reg_lambda                   348.485 │
│ subsample                    0.58725 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.65928 │
│ gamma                        16.4909 │
│ learning_rate                0.01988 │
│ max_depth                          2 │
│ min_child_weight                 126 │
│ num_boost_round                  576 │
│ random_state                    2569 │
│ reg_alpha                    25.2645 │
│ reg_lambda                   24.7553 │
│ subsample                    0.61859 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.62362 │
│ gamma                         5.2294 │
│ learning_rate                0.01802 │
│ max_depth                          3 │
│ min_child_weight                 135 │
│ num_boost_round                  376 │
│ random_state                    6412 │
│ reg_alpha                    17.9044 │
│ reg_lambda                   163.812 │
│ subsample                    0.76117 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
[36m(train_xgb_ray_tune pid=1050009)[0m 2025-11-04 10:32:58.970303: 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=1050018)[0m 2025-11-04 10:32:59.051568: 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=1050018)[0m WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
[36m(train_xgb_ray_tune pid=1050018)[0m E0000 00:00:1762248779.075829 1051162 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=1050018)[0m E0000 00:00:1762248779.083909 1051162 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=1050013)[0m W0000 00:00:1762248779.066665 1051155 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=1050013)[0m W0000 00:00:1762248779.066695 1051155 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=1050013)[0m W0000 00:00:1762248779.066697 1051155 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=1050013)[0m W0000 00:00:1762248779.066700 1051155 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=1050013)[0m 2025-11-04 10:32:59.072190: 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=1050013)[0m To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.73141 │
│ gamma                        10.7858 │
│ learning_rate                0.01676 │
│ max_depth                          3 │
│ min_child_weight                 121 │
│ num_boost_round                  503 │
│ random_state                    6614 │
│ reg_alpha                    4.21667 │
│ reg_lambda                   22.5949 │
│ subsample                    0.70031 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree              0.6707 │
│ gamma                        11.7282 │
│ learning_rate                0.00728 │
│ max_depth                          3 │
│ min_child_weight                  73 │
│ num_boost_round                  672 │
│ random_state                    3798 │
│ reg_alpha                    747.188 │
│ reg_lambda                   139.556 │
│ subsample                    0.51472 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.81456 │
│ gamma                        24.1402 │
│ learning_rate                0.00519 │
│ max_depth                          3 │
│ min_child_weight                 133 │
│ num_boost_round                  552 │
│ random_state                    9343 │
│ reg_alpha                    55.5009 │
│ reg_lambda                    220.28 │
│ subsample                    0.74303 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.55398 │
│ gamma                        5.02458 │
│ learning_rate                0.01342 │
│ max_depth                          2 │
│ min_child_weight                  81 │
│ num_boost_round                  397 │
│ random_state                    3722 │
│ reg_alpha                    33.3285 │
│ reg_lambda                   26.1677 │
│ subsample                    0.51573 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.84062 │
│ gamma                        23.4996 │
│ learning_rate                0.01067 │
│ max_depth                          2 │
│ min_child_weight                  87 │
│ num_boost_round                  439 │
│ random_state                    5050 │
│ reg_alpha                    363.963 │
│ reg_lambda                    324.87 │
│ subsample                     0.7374 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.64247 │
│ gamma                        28.4619 │
│ learning_rate                0.01014 │
│ max_depth                          3 │
│ min_child_weight                 186 │
│ num_boost_round                  253 │
│ random_state                    2414 │
│ reg_alpha                    497.357 │
│ reg_lambda                   117.888 │
│ subsample                    0.78512 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.83109 │
│ gamma                        28.3893 │
│ learning_rate                0.01529 │
│ max_depth                          3 │
│ min_child_weight                  81 │
│ num_boost_round                  278 │
│ random_state                    1744 │
│ reg_alpha                    919.466 │
│ reg_lambda                   18.9778 │
│ subsample                    0.75099 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.50168 │
│ gamma                        6.21693 │
│ learning_rate                0.01524 │
│ max_depth                          3 │
│ min_child_weight                 161 │
│ num_boost_round                  443 │
│ random_state                    5987 │
│ reg_alpha                    876.274 │
│ reg_lambda                   12.0761 │
│ subsample                    0.63875 │
╰──────────────────────────────────────╯
Trial trial_3e61e started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_3e61e config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.62318 │
│ gamma                        6.66706 │
│ learning_rate                0.00706 │
│ max_depth                          3 │
│ min_child_weight                 150 │
│ num_boost_round                  542 │
│ random_state                    3953 │
│ reg_alpha                    107.565 │
│ reg_lambda                   101.116 │
│ subsample                     0.5656 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1050013)[0m [0]	train-mlogloss:1.37945	validation-mlogloss:1.37909
[36m(train_xgb_ray_tune pid=1050013)[0m [1]	train-mlogloss:1.37286	validation-mlogloss:1.37243
[36m(train_xgb_ray_tune pid=1050018)[0m [0]	train-mlogloss:1.38310	validation-mlogloss:1.38294
[36m(train_xgb_ray_tune pid=1050018)[0m [1]	train-mlogloss:1.37996	validation-mlogloss:1.37963
[36m(train_xgb_ray_tune pid=1050018)[0m [2]	train-mlogloss:1.37682	validation-mlogloss:1.37635
[36m(train_xgb_ray_tune pid=1050007)[0m [0]	train-mlogloss:1.37728	validation-mlogloss:1.37742
[36m(train_xgb_ray_tune pid=1050007)[0m [1]	train-mlogloss:1.36816	validation-mlogloss:1.36812
[36m(train_xgb_ray_tune pid=1050007)[0m [2]	train-mlogloss:1.35944	validation-mlogloss:1.35929
[36m(train_xgb_ray_tune pid=1050013)[0m [2]	train-mlogloss:1.36652	validation-mlogloss:1.36589
[36m(train_xgb_ray_tune pid=1050013)[0m [3]	train-mlogloss:1.36021	validation-mlogloss:1.35940
[36m(train_xgb_ray_tune pid=1050013)[0m [4]	train-mlogloss:1.35437	validation-mlogloss:1.35335
[36m(train_xgb_ray_tune pid=1050013)[0m [5]	train-mlogloss:1.34866	validation-mlogloss:1.34731
[36m(train_xgb_ray_tune pid=1050013)[0m [6]	train-mlogloss:1.34312	validation-mlogloss:1.34178
[36m(train_xgb_ray_tune pid=1050013)[0m [7]	train-mlogloss:1.33683	validation-mlogloss:1.33540
[36m(train_xgb_ray_tune pid=1050013)[0m [8]	train-mlogloss:1.33129	validation-mlogloss:1.32957
[36m(train_xgb_ray_tune pid=1049992)[0m [0]	train-mlogloss:1.37704	validation-mlogloss:1.37673
[36m(train_xgb_ray_tune pid=1049992)[0m [1]	train-mlogloss:1.36784	validation-mlogloss:1.36703
[36m(train_xgb_ray_tune pid=1049992)[0m [2]	train-mlogloss:1.35908	validation-mlogloss:1.35785
[36m(train_xgb_ray_tune pid=1050009)[0m [0]	train-mlogloss:1.37650	validation-mlogloss:1.37693
[36m(train_xgb_ray_tune pid=1050009)[0m [1]	train-mlogloss:1.36724	validation-mlogloss:1.36767
[36m(train_xgb_ray_tune pid=1050009)[0m [2]	train-mlogloss:1.35890	validation-mlogloss:1.35946
[36m(train_xgb_ray_tune pid=1050011)[0m [0]	train-mlogloss:1.38456	validation-mlogloss:1.38451
[36m(train_xgb_ray_tune pid=1050011)[0m [1]	train-mlogloss:1.38274	validation-mlogloss:1.38262
[36m(train_xgb_ray_tune pid=1050011)[0m [2]	train-mlogloss:1.38116	validation-mlogloss:1.38097
[36m(train_xgb_ray_tune pid=1050011)[0m [3]	train-mlogloss:1.37968	validation-mlogloss:1.37943
[36m(train_xgb_ray_tune pid=1050011)[0m [4]	train-mlogloss:1.37799	validation-mlogloss:1.37765
[36m(train_xgb_ray_tune pid=1050011)[0m [5]	train-mlogloss:1.37634	validation-mlogloss:1.37592
[36m(train_xgb_ray_tune pid=1050011)[0m [6]	train-mlogloss:1.37510	validation-mlogloss:1.37461
[36m(train_xgb_ray_tune pid=1050011)[0m [7]	train-mlogloss:1.37351	validation-mlogloss:1.37298
[36m(train_xgb_ray_tune pid=1050018)[0m [3]	train-mlogloss:1.37367	validation-mlogloss:1.37313
[36m(train_xgb_ray_tune pid=1050018)[0m [4]	train-mlogloss:1.37059	validation-mlogloss:1.37003
[36m(train_xgb_ray_tune pid=1050018)[0m [5]	train-mlogloss:1.36762	validation-mlogloss:1.36691
[36m(train_xgb_ray_tune pid=1050018)[0m [6]	train-mlogloss:1.36453	validation-mlogloss:1.36368
[36m(train_xgb_ray_tune pid=1050018)[0m [7]	train-mlogloss:1.36156	validation-mlogloss:1.36067
[36m(train_xgb_ray_tune pid=1050018)[0m [8]	train-mlogloss:1.35855	validation-mlogloss:1.35767
[36m(train_xgb_ray_tune pid=1050018)[0m [9]	train-mlogloss:1.35557	validation-mlogloss:1.35455
[36m(train_xgb_ray_tune pid=1050007)[0m [3]	train-mlogloss:1.35077	validation-mlogloss:1.35058
[36m(train_xgb_ray_tune pid=1050007)[0m [4]	train-mlogloss:1.34222	validation-mlogloss:1.34199
[36m(train_xgb_ray_tune pid=1050007)[0m [5]	train-mlogloss:1.33379	validation-mlogloss:1.33369
[36m(train_xgb_ray_tune pid=1050007)[0m [6]	train-mlogloss:1.32589	validation-mlogloss:1.32561
[36m(train_xgb_ray_tune pid=1050007)[0m [7]	train-mlogloss:1.31770	validation-mlogloss:1.31735
[36m(train_xgb_ray_tune pid=1050007)[0m [8]	train-mlogloss:1.30974	validation-mlogloss:1.30938
[36m(train_xgb_ray_tune pid=1050011)[0m [8]	train-mlogloss:1.37193	validation-mlogloss:1.37137
[36m(train_xgb_ray_tune pid=1050013)[0m [9]	train-mlogloss:1.32584	validation-mlogloss:1.32389
[36m(train_xgb_ray_tune pid=1050013)[0m [10]	train-mlogloss:1.32052	validation-mlogloss:1.31833
[36m(train_xgb_ray_tune pid=1050013)[0m [11]	train-mlogloss:1.31509	validation-mlogloss:1.31274
[36m(train_xgb_ray_tune pid=1050013)[0m [12]	train-mlogloss:1.30991	validation-mlogloss:1.30729
[36m(train_xgb_ray_tune pid=1050013)[0m [13]	train-mlogloss:1.30459	validation-mlogloss:1.30196
[36m(train_xgb_ray_tune pid=1050013)[0m [14]	train-mlogloss:1.29960	validation-mlogloss:1.29666
[36m(train_xgb_ray_tune pid=1050013)[0m [15]	train-mlogloss:1.29477	validation-mlogloss:1.29174
[36m(train_xgb_ray_tune pid=1049992)[0m [3]	train-mlogloss:1.35059	validation-mlogloss:1.34898
[36m(train_xgb_ray_tune pid=1049992)[0m [4]	train-mlogloss:1.34191	validation-mlogloss:1.33998
[36m(train_xgb_ray_tune pid=1049992)[0m [5]	train-mlogloss:1.33369	validation-mlogloss:1.33150
[36m(train_xgb_ray_tune pid=1049992)[0m [6]	train-mlogloss:1.32570	validation-mlogloss:1.32317
[36m(train_xgb_ray_tune pid=1049992)[0m [7]	train-mlogloss:1.31796	validation-mlogloss:1.31490
[36m(train_xgb_ray_tune pid=1049992)[0m [8]	train-mlogloss:1.31040	validation-mlogloss:1.30708
[36m(train_xgb_ray_tune pid=1050009)[0m [3]	train-mlogloss:1.34996	validation-mlogloss:1.35046
[36m(train_xgb_ray_tune pid=1050009)[0m [4]	train-mlogloss:1.34183	validation-mlogloss:1.34230
[36m(train_xgb_ray_tune pid=1050009)[0m [5]	train-mlogloss:1.33310	validation-mlogloss:1.33341
[36m(train_xgb_ray_tune pid=1050009)[0m [6]	train-mlogloss:1.32528	validation-mlogloss:1.32534
[36m(train_xgb_ray_tune pid=1050009)[0m [7]	train-mlogloss:1.31747	validation-mlogloss:1.31803
[36m(train_xgb_ray_tune pid=1050009)[0m [8]	train-mlogloss:1.30959	validation-mlogloss:1.30983
[36m(train_xgb_ray_tune pid=1050014)[0m [0]	train-mlogloss:1.37695	validation-mlogloss:1.37660
[36m(train_xgb_ray_tune pid=1050014)[0m [1]	train-mlogloss:1.36745	validation-mlogloss:1.36646
[36m(train_xgb_ray_tune pid=1050011)[0m [9]	train-mlogloss:1.37051	validation-mlogloss:1.36990
[36m(train_xgb_ray_tune pid=1050011)[0m [10]	train-mlogloss:1.36895	validation-mlogloss:1.36832
[36m(train_xgb_ray_tune pid=1050011)[0m [11]	train-mlogloss:1.36779	validation-mlogloss:1.36712
[36m(train_xgb_ray_tune pid=1050011)[0m [12]	train-mlogloss:1.36640	validation-mlogloss:1.36571
[36m(train_xgb_ray_tune pid=1050011)[0m [13]	train-mlogloss:1.36481	validation-mlogloss:1.36404
[36m(train_xgb_ray_tune pid=1050011)[0m [14]	train-mlogloss:1.36317	validation-mlogloss:1.36233
[36m(train_xgb_ray_tune pid=1050011)[0m [15]	train-mlogloss:1.36194	validation-mlogloss:1.36106
[36m(train_xgb_ray_tune pid=1050011)[0m [16]	train-mlogloss:1.36061	validation-mlogloss:1.35967
[36m(train_xgb_ray_tune pid=1050018)[0m [10]	train-mlogloss:1.35267	validation-mlogloss:1.35152
[36m(train_xgb_ray_tune pid=1050018)[0m [11]	train-mlogloss:1.34973	validation-mlogloss:1.34848
[36m(train_xgb_ray_tune pid=1050018)[0m [12]	train-mlogloss:1.34686	validation-mlogloss:1.34546
[36m(train_xgb_ray_tune pid=1050018)[0m [13]	train-mlogloss:1.34399	validation-mlogloss:1.34263
[36m(train_xgb_ray_tune pid=1050018)[0m [14]	train-mlogloss:1.34117	validation-mlogloss:1.33967
[36m(train_xgb_ray_tune pid=1050018)[0m [15]	train-mlogloss:1.33831	validation-mlogloss:1.33667
[36m(train_xgb_ray_tune pid=1050007)[0m [9]	train-mlogloss:1.30200	validation-mlogloss:1.30154
[36m(train_xgb_ray_tune pid=1050007)[0m [10]	train-mlogloss:1.29430	validation-mlogloss:1.29399
[36m(train_xgb_ray_tune pid=1050007)[0m [11]	train-mlogloss:1.28672	validation-mlogloss:1.28643
[36m(train_xgb_ray_tune pid=1050007)[0m [12]	train-mlogloss:1.27938	validation-mlogloss:1.27876
[36m(train_xgb_ray_tune pid=1050007)[0m [13]	train-mlogloss:1.27234	validation-mlogloss:1.27174
[36m(train_xgb_ray_tune pid=1050003)[0m [0]	train-mlogloss:1.38444	validation-mlogloss:1.38434
[36m(train_xgb_ray_tune pid=1050003)[0m [1]	train-mlogloss:1.38286	validation-mlogloss:1.38267
[36m(train_xgb_ray_tune pid=1050003)[0m [2]	train-mlogloss:1.38123	validation-mlogloss:1.38096
[36m(train_xgb_ray_tune pid=1050003)[0m [3]	train-mlogloss:1.37967	validation-mlogloss:1.37930
[36m(train_xgb_ray_tune pid=1050003)[0m [4]	train-mlogloss:1.37815	validation-mlogloss:1.37773
[36m(train_xgb_ray_tune pid=1050003)[0m [5]	train-mlogloss:1.37666	validation-mlogloss:1.37614
[36m(train_xgb_ray_tune pid=1049992)[0m [9]	train-mlogloss:1.30273	validation-mlogloss:1.29913
[36m(train_xgb_ray_tune pid=1050014)[0m [2]	train-mlogloss:1.35832	validation-mlogloss:1.35687
[36m(train_xgb_ray_tune pid=1050003)[0m [6]	train-mlogloss:1.37509	validation-mlogloss:1.37451
[36m(train_xgb_ray_tune pid=1050018)[0m [16]	train-mlogloss:1.33548	validation-mlogloss:1.33367
[36m(train_xgb_ray_tune pid=1050007)[0m [14]	train-mlogloss:1.26536	validation-mlogloss:1.26456
[36m(train_xgb_ray_tune pid=1050013)[0m [16]	train-mlogloss:1.28997	validation-mlogloss:1.28663
[36m(train_xgb_ray_tune pid=1050011)[0m [17]	train-mlogloss:1.35907	validation-mlogloss:1.35804
[36m(train_xgb_ray_tune pid=1050003)[0m [7]	train-mlogloss:1.37351	validation-mlogloss:1.37287
[36m(train_xgb_ray_tune pid=1050014)[0m [3]	train-mlogloss:1.34945	validation-mlogloss:1.34792
[36m(train_xgb_ray_tune pid=1049992)[0m [10]	train-mlogloss:1.29521	validation-mlogloss:1.29136
[36m(train_xgb_ray_tune pid=1050009)[0m [9]	train-mlogloss:1.30168	validation-mlogloss:1.30207
[36m(train_xgb_ray_tune pid=1050018)[0m [17]	train-mlogloss:1.33267	validation-mlogloss:1.33076
[36m(train_xgb_ray_tune pid=1050003)[0m [8]	train-mlogloss:1.37210	validation-mlogloss:1.37137
[36m(train_xgb_ray_tune pid=1050013)[0m [17]	train-mlogloss:1.28523	validation-mlogloss:1.28167
[36m(train_xgb_ray_tune pid=1050011)[0m [18]	train-mlogloss:1.35785	validation-mlogloss:1.35672
[36m(train_xgb_ray_tune pid=1050007)[0m [15]	train-mlogloss:1.25833	validation-mlogloss:1.25763
[36m(train_xgb_ray_tune pid=1050014)[0m [4]	train-mlogloss:1.34064	validation-mlogloss:1.33881
[36m(train_xgb_ray_tune pid=1050018)[0m [18]	train-mlogloss:1.32996	validation-mlogloss:1.32792
[36m(train_xgb_ray_tune pid=1050003)[0m [9]	train-mlogloss:1.37068	validation-mlogloss:1.36985
[36m(train_xgb_ray_tune pid=1050013)[0m [18]	train-mlogloss:1.28039	validation-mlogloss:1.27663
[36m(train_xgb_ray_tune pid=1049992)[0m [11]	train-mlogloss:1.28808	validation-mlogloss:1.28385
[36m(train_xgb_ray_tune pid=1050009)[0m [10]	train-mlogloss:1.29461	validation-mlogloss:1.29505
[36m(train_xgb_ray_tune pid=1050011)[0m [19]	train-mlogloss:1.35636	validation-mlogloss:1.35521
[36m(train_xgb_ray_tune pid=1050013)[0m [19]	train-mlogloss:1.27591	validation-mlogloss:1.27195
[36m(train_xgb_ray_tune pid=1050013)[0m [20]	train-mlogloss:1.27113	validation-mlogloss:1.26711
[36m(train_xgb_ray_tune pid=1050013)[0m [21]	train-mlogloss:1.26675	validation-mlogloss:1.26249
[36m(train_xgb_ray_tune pid=1050013)[0m [22]	train-mlogloss:1.26243	validation-mlogloss:1.25789
[36m(train_xgb_ray_tune pid=1050013)[0m [23]	train-mlogloss:1.25827	validation-mlogloss:1.25359
[36m(train_xgb_ray_tune pid=1050013)[0m [24]	train-mlogloss:1.25389	validation-mlogloss:1.24897
[36m(train_xgb_ray_tune pid=1050013)[0m [25]	train-mlogloss:1.25000	validation-mlogloss:1.24491
[36m(train_xgb_ray_tune pid=1049992)[0m [12]	train-mlogloss:1.28104	validation-mlogloss:1.27721
[36m(train_xgb_ray_tune pid=1049992)[0m [13]	train-mlogloss:1.27396	validation-mlogloss:1.27014
[36m(train_xgb_ray_tune pid=1049992)[0m [14]	train-mlogloss:1.26678	validation-mlogloss:1.26302
[36m(train_xgb_ray_tune pid=1049992)[0m [15]	train-mlogloss:1.26002	validation-mlogloss:1.25622
[36m(train_xgb_ray_tune pid=1049992)[0m [16]	train-mlogloss:1.25361	validation-mlogloss:1.24953
[36m(train_xgb_ray_tune pid=1050010)[0m [0]	train-mlogloss:1.37563	validation-mlogloss:1.37592
[36m(train_xgb_ray_tune pid=1050009)[0m [11]	train-mlogloss:1.28691	validation-mlogloss:1.28731
[36m(train_xgb_ray_tune pid=1050009)[0m [12]	train-mlogloss:1.27920	validation-mlogloss:1.27983
[36m(train_xgb_ray_tune pid=1050009)[0m [13]	train-mlogloss:1.27183	validation-mlogloss:1.27229
[36m(train_xgb_ray_tune pid=1050009)[0m [14]	train-mlogloss:1.26455	validation-mlogloss:1.26496
[36m(train_xgb_ray_tune pid=1050009)[0m [15]	train-mlogloss:1.25809	validation-mlogloss:1.25860
[36m(train_xgb_ray_tune pid=1050014)[0m [5]	train-mlogloss:1.33203	validation-mlogloss:1.33030
[36m(train_xgb_ray_tune pid=1050014)[0m [6]	train-mlogloss:1.32348	validation-mlogloss:1.32151
[36m(train_xgb_ray_tune pid=1050014)[0m [7]	train-mlogloss:1.31542	validation-mlogloss:1.31296
[36m(train_xgb_ray_tune pid=1050014)[0m [8]	train-mlogloss:1.30754	validation-mlogloss:1.30515
[36m(train_xgb_ray_tune pid=1050014)[0m [9]	train-mlogloss:1.29972	validation-mlogloss:1.29684
[36m(train_xgb_ray_tune pid=1050014)[0m [10]	train-mlogloss:1.29191	validation-mlogloss:1.28884
[36m(train_xgb_ray_tune pid=1050011)[0m [20]	train-mlogloss:1.35518	validation-mlogloss:1.35398
[36m(train_xgb_ray_tune pid=1050011)[0m [21]	train-mlogloss:1.35401	validation-mlogloss:1.35277
[36m(train_xgb_ray_tune pid=1050011)[0m [22]	train-mlogloss:1.35247	validation-mlogloss:1.35116
[36m(train_xgb_ray_tune pid=1050011)[0m [23]	train-mlogloss:1.35138	validation-mlogloss:1.35001
[36m(train_xgb_ray_tune pid=1050011)[0m [24]	train-mlogloss:1.35020	validation-mlogloss:1.34882
[36m(train_xgb_ray_tune pid=1050011)[0m [25]	train-mlogloss:1.34878	validation-mlogloss:1.34731
[36m(train_xgb_ray_tune pid=1050011)[0m [26]	train-mlogloss:1.34748	validation-mlogloss:1.34596
[36m(train_xgb_ray_tune pid=1050018)[0m [19]	train-mlogloss:1.32723	validation-mlogloss:1.32525
[36m(train_xgb_ray_tune pid=1050018)[0m [20]	train-mlogloss:1.32457	validation-mlogloss:1.32264
[36m(train_xgb_ray_tune pid=1050018)[0m [21]	train-mlogloss:1.32183	validation-mlogloss:1.31996
[36m(train_xgb_ray_tune pid=1050018)[0m [22]	train-mlogloss:1.31916	validation-mlogloss:1.31713
[36m(train_xgb_ray_tune pid=1050018)[0m [23]	train-mlogloss:1.31646	validation-mlogloss:1.31440
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[36m(train_xgb_ray_tune pid=1050003)[0m [89]	train-mlogloss:1.29394	validation-mlogloss:1.28903
[36m(train_xgb_ray_tune pid=1050019)[0m [56]	train-mlogloss:1.36422	validation-mlogloss:1.36307
[36m(train_xgb_ray_tune pid=1050016)[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=1050016)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=1050008)[0m 2025-11-04 10:32:59.465587: 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=1050004)[0m 2025-11-04 10:32:59.547459: 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=1050004)[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=1050004)[0m E0000 00:00:1762248779.576913 1051288 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=1050004)[0m E0000 00:00:1762248779.585284 1051288 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=1050008)[0m W0000 00:00:1762248779.542570 1051265 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=1050008)[0m 2025-11-04 10:32:59.548292: 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=1050008)[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=1050005)[0m [40]	train-mlogloss:1.31832	validation-mlogloss:1.31578
[36m(train_xgb_ray_tune pid=1050008)[0m [43]	train-mlogloss:1.30070	validation-mlogloss:1.29729
[36m(train_xgb_ray_tune pid=1050009)[0m [53]	train-mlogloss:1.06352	validation-mlogloss:1.06174
[36m(train_xgb_ray_tune pid=1050014)[0m [62]	train-mlogloss:1.03734	validation-mlogloss:1.03312
[36m(train_xgb_ray_tune pid=1050011)[0m [95]	train-mlogloss:1.28256	validation-mlogloss:1.27767
[36m(train_xgb_ray_tune pid=1049991)[0m [57]	train-mlogloss:1.34657	validation-mlogloss:1.34482
[36m(train_xgb_ray_tune pid=1050017)[0m [68]	train-mlogloss:1.27706	validation-mlogloss:1.27301
[36m(train_xgb_ray_tune pid=1050012)[0m [59]	train-mlogloss:1.03025	validation-mlogloss:1.02486
[36m(train_xgb_ray_tune pid=1050003)[0m [90]	train-mlogloss:1.29338	validation-mlogloss:1.28846
[36m(train_xgb_ray_tune pid=1050019)[0m [57]	train-mlogloss:1.36391	validation-mlogloss:1.36274
[36m(train_xgb_ray_tune pid=1050008)[0m [44]	train-mlogloss:1.29926	validation-mlogloss:1.29584
[36m(train_xgb_ray_tune pid=1049992)[0m [68]	train-mlogloss:1.03925	validation-mlogloss:1.03257
[36m(train_xgb_ray_tune pid=1050006)[0m [42]	train-mlogloss:1.10132	validation-mlogloss:1.09732
[36m(train_xgb_ray_tune pid=1050015)[0m [46]	train-mlogloss:1.15474	validation-mlogloss:1.14922
[36m(train_xgb_ray_tune pid=1050004)[0m [26]	train-mlogloss:1.31308	validation-mlogloss:1.31039
[36m(train_xgb_ray_tune pid=1050005)[0m [41]	train-mlogloss:1.31727	validation-mlogloss:1.31469
[36m(train_xgb_ray_tune pid=1050013)[0m [75]	train-mlogloss:1.11338	validation-mlogloss:1.10517
[36m(train_xgb_ray_tune pid=1050010)[0m [45]	train-mlogloss:1.05499	validation-mlogloss:1.05473
[36m(train_xgb_ray_tune pid=1050009)[0m [54]	train-mlogloss:1.05963	validation-mlogloss:1.05758
[36m(train_xgb_ray_tune pid=1050011)[0m [96]	train-mlogloss:1.28187	validation-mlogloss:1.27695
[36m(train_xgb_ray_tune pid=1050018)[0m [73]	train-mlogloss:1.20379	validation-mlogloss:1.20033
[36m(train_xgb_ray_tune pid=1049991)[0m [58]	train-mlogloss:1.34603	validation-mlogloss:1.34426
[36m(train_xgb_ray_tune pid=1050017)[0m [69]	train-mlogloss:1.27567	validation-mlogloss:1.27158
[36m(train_xgb_ray_tune pid=1050007)[0m [61]	train-mlogloss:1.03543	validation-mlogloss:1.03305
[36m(train_xgb_ray_tune pid=1050012)[0m [60]	train-mlogloss:1.02717	validation-mlogloss:1.02201
[36m(train_xgb_ray_tune pid=1050003)[0m [91]	train-mlogloss:1.29283	validation-mlogloss:1.28786
[36m(train_xgb_ray_tune pid=1050019)[0m [58]	train-mlogloss:1.36360	validation-mlogloss:1.36242
[36m(train_xgb_ray_tune pid=1050008)[0m [45]	train-mlogloss:1.29777	validation-mlogloss:1.29429
[36m(train_xgb_ray_tune pid=1050014)[0m [63]	train-mlogloss:1.03437	validation-mlogloss:1.03014
[36m(train_xgb_ray_tune pid=1050015)[0m [47]	train-mlogloss:1.15124	validation-mlogloss:1.14556
[36m(train_xgb_ray_tune pid=1050003)[0m [92]	train-mlogloss:1.29226	validation-mlogloss:1.28726
[36m(train_xgb_ray_tune pid=1050019)[0m [59]	train-mlogloss:1.36360	validation-mlogloss:1.36242
[36m(train_xgb_ray_tune pid=1049992)[0m [69]	train-mlogloss:1.03694	validation-mlogloss:1.03050
[36m(train_xgb_ray_tune pid=1050006)[0m [43]	train-mlogloss:1.09667	validation-mlogloss:1.09265
[36m(train_xgb_ray_tune pid=1050011)[0m [97]	train-mlogloss:1.28120	validation-mlogloss:1.27626
[36m(train_xgb_ray_tune pid=1049991)[0m [59]	train-mlogloss:1.34554	validation-mlogloss:1.34375
[36m(train_xgb_ray_tune pid=1050017)[0m [70]	train-mlogloss:1.27433	validation-mlogloss:1.27017
[36m(train_xgb_ray_tune pid=1050005)[0m [42]	train-mlogloss:1.31627	validation-mlogloss:1.31362

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:04. Total running time: 8s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             5.32581 │
│ time_total_s                 5.32581 │
│ training_iteration                 1 │
│ validation_accuracy          0.46103 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1050013)[0m [76]	train-mlogloss:1.11141	validation-mlogloss:1.10319
[36m(train_xgb_ray_tune pid=1050010)[0m [46]	train-mlogloss:1.05070	validation-mlogloss:1.05052
[36m(train_xgb_ray_tune pid=1050007)[0m [62]	train-mlogloss:1.03201	validation-mlogloss:1.02965
[36m(train_xgb_ray_tune pid=1050012)[0m [61]	train-mlogloss:1.02401	validation-mlogloss:1.01872

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:04. Total running time: 8s
[36m(train_xgb_ray_tune pid=1050003)[0m [93]	train-mlogloss:1.29163	validation-mlogloss:1.28660
[36m(train_xgb_ray_tune pid=1050004)[0m [27]	train-mlogloss:1.31054	validation-mlogloss:1.30770
[36m(train_xgb_ray_tune pid=1050019)[0m [60]	train-mlogloss:1.36324	validation-mlogloss:1.36204
[36m(train_xgb_ray_tune pid=1050019)[0m [61]	train-mlogloss:1.36294	validation-mlogloss:1.36172
[36m(train_xgb_ray_tune pid=1050005)[0m [43]	train-mlogloss:1.31475	validation-mlogloss:1.31201
[36m(train_xgb_ray_tune pid=1050008)[0m [46]	train-mlogloss:1.29628	validation-mlogloss:1.29274
[36m(train_xgb_ray_tune pid=1050013)[0m [77]	train-mlogloss:1.10980	validation-mlogloss:1.10153
[36m(train_xgb_ray_tune pid=1049992)[0m [70]	train-mlogloss:1.03433	validation-mlogloss:1.02770
[36m(train_xgb_ray_tune pid=1050006)[0m [44]	train-mlogloss:1.09232	validation-mlogloss:1.08804
[36m(train_xgb_ray_tune pid=1050009)[0m [55]	train-mlogloss:1.05586	validation-mlogloss:1.05376
[36m(train_xgb_ray_tune pid=1050014)[0m [64]	train-mlogloss:1.03134	validation-mlogloss:1.02737
[36m(train_xgb_ray_tune pid=1050011)[0m [98]	train-mlogloss:1.28041	validation-mlogloss:1.27545
[36m(train_xgb_ray_tune pid=1050011)[0m [99]	train-mlogloss:1.27970	validation-mlogloss:1.27467
[36m(train_xgb_ray_tune pid=1050018)[0m [74]	train-mlogloss:1.20185	validation-mlogloss:1.19842
[36m(train_xgb_ray_tune pid=1049991)[0m [60]	train-mlogloss:1.34505	validation-mlogloss:1.34324
[36m(train_xgb_ray_tune pid=1049991)[0m [61]	train-mlogloss:1.34459	validation-mlogloss:1.34274
[36m(train_xgb_ray_tune pid=1050017)[0m [71]	train-mlogloss:1.27303	validation-mlogloss:1.26880
[36m(train_xgb_ray_tune pid=1050020)[0m [38]	train-mlogloss:1.30184	validation-mlogloss:1.29891
[36m(train_xgb_ray_tune pid=1050012)[0m [62]	train-mlogloss:1.02062	validation-mlogloss:1.01542
[36m(train_xgb_ray_tune pid=1050015)[0m [48]	train-mlogloss:1.14786	validation-mlogloss:1.14231
[36m(train_xgb_ray_tune pid=1050003)[0m [94]	train-mlogloss:1.29105	validation-mlogloss:1.28599
[36m(train_xgb_ray_tune pid=1050004)[0m [28]	train-mlogloss:1.30812	validation-mlogloss:1.30520
[36m(train_xgb_ray_tune pid=1050019)[0m [62]	train-mlogloss:1.36258	validation-mlogloss:1.36134
[36m(train_xgb_ray_tune pid=1050008)[0m [47]	train-mlogloss:1.29486	validation-mlogloss:1.29130
[36m(train_xgb_ray_tune pid=1049992)[0m [71]	train-mlogloss:1.03219	validation-mlogloss:1.02552
[36m(train_xgb_ray_tune pid=1050010)[0m [47]	train-mlogloss:1.04643	validation-mlogloss:1.04624
[36m(train_xgb_ray_tune pid=1050009)[0m [56]	train-mlogloss:1.05245	validation-mlogloss:1.05060
[36m(train_xgb_ray_tune pid=1050014)[0m [65]	train-mlogloss:1.02832	validation-mlogloss:1.02428
[36m(train_xgb_ray_tune pid=1050018)[0m [75]	train-mlogloss:1.19990	validation-mlogloss:1.19652
[36m(train_xgb_ray_tune pid=1050017)[0m [72]	train-mlogloss:1.27172	validation-mlogloss:1.26747
[36m(train_xgb_ray_tune pid=1050007)[0m [63]	train-mlogloss:1.02872	validation-mlogloss:1.02646
[36m(train_xgb_ray_tune pid=1050003)[0m [95]	train-mlogloss:1.29051	validation-mlogloss:1.28542
[36m(train_xgb_ray_tune pid=1050019)[0m [63]	train-mlogloss:1.36258	validation-mlogloss:1.36134
[36m(train_xgb_ray_tune pid=1050005)[0m [44]	train-mlogloss:1.31327	validation-mlogloss:1.31047
[36m(train_xgb_ray_tune pid=1050008)[0m [48]	train-mlogloss:1.29351	validation-mlogloss:1.28987
[36m(train_xgb_ray_tune pid=1050013)[0m [78]	train-mlogloss:1.10817	validation-mlogloss:1.09983
[36m(train_xgb_ray_tune pid=1050006)[0m [45]	train-mlogloss:1.08790	validation-mlogloss:1.08337
[36m(train_xgb_ray_tune pid=1050011)[0m [100]	train-mlogloss:1.27888	validation-mlogloss:1.27382
[36m(train_xgb_ray_tune pid=1050018)[0m [76]	train-mlogloss:1.19805	validation-mlogloss:1.19462
[36m(train_xgb_ray_tune pid=1050017)[0m [73]	train-mlogloss:1.27036	validation-mlogloss:1.26605
[36m(train_xgb_ray_tune pid=1050015)[0m [49]	train-mlogloss:1.14448	validation-mlogloss:1.13895
[36m(train_xgb_ray_tune pid=1050003)[0m [96]	train-mlogloss:1.29003	validation-mlogloss:1.28490
[36m(train_xgb_ray_tune pid=1050004)[0m [29]	train-mlogloss:1.30562	validation-mlogloss:1.30264
[36m(train_xgb_ray_tune pid=1050019)[0m [64]	train-mlogloss:1.36227	validation-mlogloss:1.36102
[36m(train_xgb_ray_tune pid=1050005)[0m [45]	train-mlogloss:1.31182	validation-mlogloss:1.30897
[36m(train_xgb_ray_tune pid=1050008)[0m [49]	train-mlogloss:1.29207	validation-mlogloss:1.28840
[36m(train_xgb_ray_tune pid=1050013)[0m [79]	train-mlogloss:1.10629	validation-mlogloss:1.09806
[36m(train_xgb_ray_tune pid=1049992)[0m [72]	train-mlogloss:1.02975	validation-mlogloss:1.02325
[36m(train_xgb_ray_tune pid=1050010)[0m [48]	train-mlogloss:1.04201	validation-mlogloss:1.04199
[36m(train_xgb_ray_tune pid=1050011)[0m [101]	train-mlogloss:1.27825	validation-mlogloss:1.27316
[36m(train_xgb_ray_tune pid=1050020)[0m [39]	train-mlogloss:1.29993	validation-mlogloss:1.29691
[36m(train_xgb_ray_tune pid=1050012)[0m [63]	train-mlogloss:1.01757	validation-mlogloss:1.01253
[36m(train_xgb_ray_tune pid=1050003)[0m [97]	train-mlogloss:1.28947	validation-mlogloss:1.28433
[36m(train_xgb_ray_tune pid=1050007)[0m [64]	train-mlogloss:1.02526	validation-mlogloss:1.02299
[36m(train_xgb_ray_tune pid=1050019)[0m [65]	train-mlogloss:1.36197	validation-mlogloss:1.36071
[36m(train_xgb_ray_tune pid=1050006)[0m [46]	train-mlogloss:1.08361	validation-mlogloss:1.07901
[36m(train_xgb_ray_tune pid=1050014)[0m [66]	train-mlogloss:1.02541	validation-mlogloss:1.02145
[36m(train_xgb_ray_tune pid=1050017)[0m [74]	train-mlogloss:1.26907	validation-mlogloss:1.26467
[36m(train_xgb_ray_tune pid=1050005)[0m [46]	train-mlogloss:1.31065	validation-mlogloss:1.30777
[36m(train_xgb_ray_tune pid=1050008)[0m [50]	train-mlogloss:1.29065	validation-mlogloss:1.28693
[36m(train_xgb_ray_tune pid=1050013)[0m [80]	train-mlogloss:1.10478	validation-mlogloss:1.09640
[36m(train_xgb_ray_tune pid=1049992)[0m [73]	train-mlogloss:1.02758	validation-mlogloss:1.02096
[36m(train_xgb_ray_tune pid=1050009)[0m [57]	train-mlogloss:1.04912	validation-mlogloss:1.04752
[36m(train_xgb_ray_tune pid=1050011)[0m [102]	train-mlogloss:1.27764	validation-mlogloss:1.27250
[36m(train_xgb_ray_tune pid=1050018)[0m [77]	train-mlogloss:1.19618	validation-mlogloss:1.19276
[36m(train_xgb_ray_tune pid=1049991)[0m [62]	train-mlogloss:1.34401	validation-mlogloss:1.34214
[36m(train_xgb_ray_tune pid=1050020)[0m [40]	train-mlogloss:1.29791	validation-mlogloss:1.29492
[36m(train_xgb_ray_tune pid=1050015)[0m [50]	train-mlogloss:1.14131	validation-mlogloss:1.13583
[36m(train_xgb_ray_tune pid=1050003)[0m [98]	train-mlogloss:1.28891	validation-mlogloss:1.28375
[36m(train_xgb_ray_tune pid=1050004)[0m [30]	train-mlogloss:1.30315	validation-mlogloss:1.30006
[36m(train_xgb_ray_tune pid=1050019)[0m [66]	train-mlogloss:1.36176	validation-mlogloss:1.36049
[36m(train_xgb_ray_tune pid=1050010)[0m [49]	train-mlogloss:1.03750	validation-mlogloss:1.03747
[36m(train_xgb_ray_tune pid=1050014)[0m [67]	train-mlogloss:1.02244	validation-mlogloss:1.01845
[36m(train_xgb_ray_tune pid=1050011)[0m [103]	train-mlogloss:1.27701	validation-mlogloss:1.27183
[36m(train_xgb_ray_tune pid=1049991)[0m 
[36m(train_xgb_ray_tune pid=1050017)[0m [75]	train-mlogloss:1.26781	validation-mlogloss:1.26337
[36m(train_xgb_ray_tune pid=1050007)[0m [65]	train-mlogloss:1.02194	validation-mlogloss:1.01972
[36m(train_xgb_ray_tune pid=1050012)[0m [64]	train-mlogloss:1.01432	validation-mlogloss:1.00925
[36m(train_xgb_ray_tune pid=1050003)[0m [99]	train-mlogloss:1.28841	validation-mlogloss:1.28323
[36m(train_xgb_ray_tune pid=1050019)[0m [67]	train-mlogloss:1.36151	validation-mlogloss:1.36022
[36m(train_xgb_ray_tune pid=1050005)[0m [47]	train-mlogloss:1.30941	validation-mlogloss:1.30650
[36m(train_xgb_ray_tune pid=1050008)[0m [51]	train-mlogloss:1.28924	validation-mlogloss:1.28548
[36m(train_xgb_ray_tune pid=1050013)[0m [81]	train-mlogloss:1.10309	validation-mlogloss:1.09475
[36m(train_xgb_ray_tune pid=1049992)[0m [74]	train-mlogloss:1.02540	validation-mlogloss:1.01853
[36m(train_xgb_ray_tune pid=1050006)[0m [47]	train-mlogloss:1.07934	validation-mlogloss:1.07481
[36m(train_xgb_ray_tune pid=1050009)[0m [58]	train-mlogloss:1.04552	validation-mlogloss:1.04379
[36m(train_xgb_ray_tune pid=1050018)[0m [78]	train-mlogloss:1.19427	validation-mlogloss:1.19087
[36m(train_xgb_ray_tune pid=1050017)[0m [76]	train-mlogloss:1.26648	validation-mlogloss:1.26198
[36m(train_xgb_ray_tune pid=1050020)[0m [41]	train-mlogloss:1.29604	validation-mlogloss:1.29300
[36m(train_xgb_ray_tune pid=1050015)[0m [51]	train-mlogloss:1.13795	validation-mlogloss:1.13233
[36m(train_xgb_ray_tune pid=1050003)[0m [100]	train-mlogloss:1.28793	validation-mlogloss:1.28270
[36m(train_xgb_ray_tune pid=1050004)[0m [31]	train-mlogloss:1.30080	validation-mlogloss:1.29766
[36m(train_xgb_ray_tune pid=1050019)[0m [68]	train-mlogloss:1.36151	validation-mlogloss:1.36022
[36m(train_xgb_ray_tune pid=1050005)[0m [48]	train-mlogloss:1.30822	validation-mlogloss:1.30527
[36m(train_xgb_ray_tune pid=1050008)[0m [52]	train-mlogloss:1.28782	validation-mlogloss:1.28399
[36m(train_xgb_ray_tune pid=1050013)[0m [82]	train-mlogloss:1.10149	validation-mlogloss:1.09305
[36m(train_xgb_ray_tune pid=1050010)[0m [50]	train-mlogloss:1.03342	validation-mlogloss:1.03349
[36m(train_xgb_ray_tune pid=1050014)[0m [68]	train-mlogloss:1.01961	validation-mlogloss:1.01559
[36m(train_xgb_ray_tune pid=1050018)[0m [79]	train-mlogloss:1.19247	validation-mlogloss:1.18913
[36m(train_xgb_ray_tune pid=1049991)[0m [63]	train-mlogloss:1.34352	validation-mlogloss:1.34163
[36m(train_xgb_ray_tune pid=1050007)[0m [66]	train-mlogloss:1.01901	validation-mlogloss:1.01681
[36m(train_xgb_ray_tune pid=1050012)[0m [65]	train-mlogloss:1.01136	validation-mlogloss:1.00631
[36m(train_xgb_ray_tune pid=1050019)[0m [69]	train-mlogloss:1.36124	validation-mlogloss:1.35993
[36m(train_xgb_ray_tune pid=1049992)[0m [75]	train-mlogloss:1.02315	validation-mlogloss:1.01615
[36m(train_xgb_ray_tune pid=1050011)[0m [104]	train-mlogloss:1.27635	validation-mlogloss:1.27114
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[36m(train_xgb_ray_tune pid=1050011)[0m [182]	train-mlogloss:1.23654	validation-mlogloss:1.22889
[36m(train_xgb_ray_tune pid=1050018)[0m [141]	train-mlogloss:1.09541	validation-mlogloss:1.09235
[36m(train_xgb_ray_tune pid=1049991)[0m [141]	train-mlogloss:1.33036	validation-mlogloss:1.32786
[36m(train_xgb_ray_tune pid=1049991)[0m [142]	train-mlogloss:1.33036	validation-mlogloss:1.32786
[36m(train_xgb_ray_tune pid=1050017)[0m [148]	train-mlogloss:1.18870	validation-mlogloss:1.18091
[36m(train_xgb_ray_tune pid=1050012)[0m [128]	train-mlogloss:0.88628	validation-mlogloss:0.88340
[36m(train_xgb_ray_tune pid=1050003)[0m [183]	train-mlogloss:1.26081	validation-mlogloss:1.25394
[36m(train_xgb_ray_tune pid=1050019)[0m [162]	train-mlogloss:1.34911	validation-mlogloss:1.34723
[36m(train_xgb_ray_tune pid=1050019)[0m [163]	train-mlogloss:1.34886	validation-mlogloss:1.34697
[36m(train_xgb_ray_tune pid=1050005)[0m [122]	train-mlogloss:1.24420	validation-mlogloss:1.23788
[36m(train_xgb_ray_tune pid=1050008)[0m [128]	train-mlogloss:1.20322	validation-mlogloss:1.19663
[36m(train_xgb_ray_tune pid=1050013)[0m [155]	train-mlogloss:1.02308	validation-mlogloss:1.01271
[36m(train_xgb_ray_tune pid=1049992)[0m [123]	train-mlogloss:0.94816	validation-mlogloss:0.94072
[36m(train_xgb_ray_tune pid=1050010)[0m [98]	train-mlogloss:0.89047	validation-mlogloss:0.88987
[36m(train_xgb_ray_tune pid=1050006)[0m [90]	train-mlogloss:0.94755	validation-mlogloss:0.94343
[36m(train_xgb_ray_tune pid=1050014)[0m [135]	train-mlogloss:0.88931	validation-mlogloss:0.88585
[36m(train_xgb_ray_tune pid=1050011)[0m [183]	train-mlogloss:1.23617	validation-mlogloss:1.22849
[36m(train_xgb_ray_tune pid=1049991)[0m [143]	train-mlogloss:1.33036	validation-mlogloss:1.32786
[36m(train_xgb_ray_tune pid=1050007)[0m [110]	train-mlogloss:0.91394	validation-mlogloss:0.91132
[36m(train_xgb_ray_tune pid=1050020)[0m [90]	train-mlogloss:1.21126	validation-mlogloss:1.20675
[36m(train_xgb_ray_tune pid=1050012)[0m [129]	train-mlogloss:0.88507	validation-mlogloss:0.88200
[36m(train_xgb_ray_tune pid=1050015)[0m [109]	train-mlogloss:0.99857	validation-mlogloss:0.99366
[36m(train_xgb_ray_tune pid=1050003)[0m [184]	train-mlogloss:1.26055	validation-mlogloss:1.25367
[36m(train_xgb_ray_tune pid=1050004)[0m [78]	train-mlogloss:1.20414	validation-mlogloss:1.19786
[36m(train_xgb_ray_tune pid=1050019)[0m [164]	train-mlogloss:1.34867	validation-mlogloss:1.34676
[36m(train_xgb_ray_tune pid=1050013)[0m [156]	train-mlogloss:1.02269	validation-mlogloss:1.01233
[36m(train_xgb_ray_tune pid=1050009)[0m [103]	train-mlogloss:0.92419	validation-mlogloss:0.92171
[36m(train_xgb_ray_tune pid=1050014)[0m [136]	train-mlogloss:0.88796	validation-mlogloss:0.88450
[36m(train_xgb_ray_tune pid=1050018)[0m [142]	train-mlogloss:1.09411	validation-mlogloss:1.09116
[36m(train_xgb_ray_tune pid=1050017)[0m [149]	train-mlogloss:1.18780	validation-mlogloss:1.17996
[36m(train_xgb_ray_tune pid=1050019)[0m [165]	train-mlogloss:1.34867	validation-mlogloss:1.34676
[36m(train_xgb_ray_tune pid=1050005)[0m [123]	train-mlogloss:1.24364	validation-mlogloss:1.23728
[36m(train_xgb_ray_tune pid=1050008)[0m [129]	train-mlogloss:1.20226	validation-mlogloss:1.19567
[36m(train_xgb_ray_tune pid=1050006)[0m [91]	train-mlogloss:0.94518	validation-mlogloss:0.94111
[36m(train_xgb_ray_tune pid=1050011)[0m [184]	train-mlogloss:1.23578	validation-mlogloss:1.22808
[36m(train_xgb_ray_tune pid=1050020)[0m [91]	train-mlogloss:1.20976	validation-mlogloss:1.20525
[36m(train_xgb_ray_tune pid=1050012)[0m [130]	train-mlogloss:0.88356	validation-mlogloss:0.88039
[36m(train_xgb_ray_tune pid=1050003)[0m [185]	train-mlogloss:1.26055	validation-mlogloss:1.25367
[36m(train_xgb_ray_tune pid=1050013)[0m [157]	train-mlogloss:1.02223	validation-mlogloss:1.01182
[36m(train_xgb_ray_tune pid=1049992)[0m [124]	train-mlogloss:0.94725	validation-mlogloss:0.93980
[36m(train_xgb_ray_tune pid=1050010)[0m [99]	train-mlogloss:0.88849	validation-mlogloss:0.88792
[36m(train_xgb_ray_tune pid=1050014)[0m [137]	train-mlogloss:0.88663	validation-mlogloss:0.88320
[36m(train_xgb_ray_tune pid=1050011)[0m [185]	train-mlogloss:1.23538	validation-mlogloss:1.22765
[36m(train_xgb_ray_tune pid=1050018)[0m [143]	train-mlogloss:1.09281	validation-mlogloss:1.08987
[36m(train_xgb_ray_tune pid=1050017)[0m [150]	train-mlogloss:1.18695	validation-mlogloss:1.17905
[36m(train_xgb_ray_tune pid=1050007)[0m [111]	train-mlogloss:0.91210	validation-mlogloss:0.90945
[36m(train_xgb_ray_tune pid=1050015)[0m [110]	train-mlogloss:0.99686	validation-mlogloss:0.99195
[36m(train_xgb_ray_tune pid=1050003)[0m [186]	train-mlogloss:1.26025	validation-mlogloss:1.25336
[36m(train_xgb_ray_tune pid=1050004)[0m [79]	train-mlogloss:1.20245	validation-mlogloss:1.19609
[36m(train_xgb_ray_tune pid=1050019)[0m [166]	train-mlogloss:1.34843	validation-mlogloss:1.34651
[36m(train_xgb_ray_tune pid=1050005)[0m [124]	train-mlogloss:1.24305	validation-mlogloss:1.23666
[36m(train_xgb_ray_tune pid=1050008)[0m [130]	train-mlogloss:1.20138	validation-mlogloss:1.19474
[36m(train_xgb_ray_tune pid=1050009)[0m [104]	train-mlogloss:0.92229	validation-mlogloss:0.91989
[36m(train_xgb_ray_tune pid=1050012)[0m [131]	train-mlogloss:0.88220	validation-mlogloss:0.87906
[36m(train_xgb_ray_tune pid=1050005)[0m [125]	train-mlogloss:1.24246	validation-mlogloss:1.23605
[36m(train_xgb_ray_tune pid=1050013)[0m [158]	train-mlogloss:1.02185	validation-mlogloss:1.01141
[36m(train_xgb_ray_tune pid=1050006)[0m [92]	train-mlogloss:0.94291	validation-mlogloss:0.93895
[36m(train_xgb_ray_tune pid=1050011)[0m [186]	train-mlogloss:1.23497	validation-mlogloss:1.22721
[36m(train_xgb_ray_tune pid=1050003)[0m [187]	train-mlogloss:1.25999	validation-mlogloss:1.25307
[36m(train_xgb_ray_tune pid=1050019)[0m [167]	train-mlogloss:1.34843	validation-mlogloss:1.34651
[36m(train_xgb_ray_tune pid=1050008)[0m [131]	train-mlogloss:1.20057	validation-mlogloss:1.19390
[36m(train_xgb_ray_tune pid=1050014)[0m [138]	train-mlogloss:0.88526	validation-mlogloss:0.88178
[36m(train_xgb_ray_tune pid=1050018)[0m [144]	train-mlogloss:1.09154	validation-mlogloss:1.08849
[36m(train_xgb_ray_tune pid=1050017)[0m [151]	train-mlogloss:1.18605	validation-mlogloss:1.17809
[36m(train_xgb_ray_tune pid=1050020)[0m [92]	train-mlogloss:1.20817	validation-mlogloss:1.20363
[36m(train_xgb_ray_tune pid=1050013)[0m [159]	train-mlogloss:1.02147	validation-mlogloss:1.01100
[36m(train_xgb_ray_tune pid=1049992)[0m [125]	train-mlogloss:0.94603	validation-mlogloss:0.93862
[36m(train_xgb_ray_tune pid=1050010)[0m [100]	train-mlogloss:0.88638	validation-mlogloss:0.88592
[36m(train_xgb_ray_tune pid=1050007)[0m [112]	train-mlogloss:0.91022	validation-mlogloss:0.90754
[36m(train_xgb_ray_tune pid=1050015)[0m [111]	train-mlogloss:0.99520	validation-mlogloss:0.99011
[36m(train_xgb_ray_tune pid=1050003)[0m [188]	train-mlogloss:1.25999	validation-mlogloss:1.25307
[36m(train_xgb_ray_tune pid=1050004)[0m [80]	train-mlogloss:1.20065	validation-mlogloss:1.19415
[36m(train_xgb_ray_tune pid=1050019)[0m [168]	train-mlogloss:1.34820	validation-mlogloss:1.34627
[36m(train_xgb_ray_tune pid=1050005)[0m [126]	train-mlogloss:1.24189	validation-mlogloss:1.23545
[36m(train_xgb_ray_tune pid=1050009)[0m [105]	train-mlogloss:0.92020	validation-mlogloss:0.91785
[36m(train_xgb_ray_tune pid=1050014)[0m [139]	train-mlogloss:0.88408	validation-mlogloss:0.88051
[36m(train_xgb_ray_tune pid=1050011)[0m [187]	train-mlogloss:1.23459	validation-mlogloss:1.22681
[36m(train_xgb_ray_tune pid=1050012)[0m [132]	train-mlogloss:0.88089	validation-mlogloss:0.87772
[36m(train_xgb_ray_tune pid=1050008)[0m [132]	train-mlogloss:1.19966	validation-mlogloss:1.19299
[36m(train_xgb_ray_tune pid=1050006)[0m [93]	train-mlogloss:0.94075	validation-mlogloss:0.93688

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:05. Total running time: 9s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             6.62104 │
│ time_total_s                 6.62104 │
│ training_iteration                 1 │
│ validation_accuracy          0.46103 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1050011)[0m [188]	train-mlogloss:1.23424	validation-mlogloss:1.22644

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:05. Total running time: 9s
[36m(train_xgb_ray_tune pid=1050018)[0m [145]	train-mlogloss:1.09025	validation-mlogloss:1.08723
[36m(train_xgb_ray_tune pid=1050020)[0m [93]	train-mlogloss:1.20664	validation-mlogloss:1.20208
[36m(train_xgb_ray_tune pid=1050012)[0m [133]	train-mlogloss:0.87964	validation-mlogloss:0.87649
[36m(train_xgb_ray_tune pid=1050003)[0m [189]	train-mlogloss:1.25999	validation-mlogloss:1.25307
[36m(train_xgb_ray_tune pid=1050019)[0m [169]	train-mlogloss:1.34820	validation-mlogloss:1.34627
[36m(train_xgb_ray_tune pid=1050005)[0m [127]	train-mlogloss:1.24125	validation-mlogloss:1.23477
[36m(train_xgb_ray_tune pid=1050008)[0m [133]	train-mlogloss:1.19885	validation-mlogloss:1.19215
[36m(train_xgb_ray_tune pid=1050013)[0m [160]	train-mlogloss:1.02100	validation-mlogloss:1.01052
[36m(train_xgb_ray_tune pid=1050013)[0m [161]	train-mlogloss:1.02055	validation-mlogloss:1.01005
[36m(train_xgb_ray_tune pid=1049992)[0m [126]	train-mlogloss:0.94497	validation-mlogloss:0.93761
[36m(train_xgb_ray_tune pid=1050010)[0m [101]	train-mlogloss:0.88414	validation-mlogloss:0.88376
[36m(train_xgb_ray_tune pid=1050006)[0m [94]	train-mlogloss:0.93875	validation-mlogloss:0.93495
[36m(train_xgb_ray_tune pid=1050009)[0m [106]	train-mlogloss:0.91825	validation-mlogloss:0.91589
[36m(train_xgb_ray_tune pid=1050014)[0m [140]	train-mlogloss:0.88278	validation-mlogloss:0.87911
[36m(train_xgb_ray_tune pid=1050011)[0m [189]	train-mlogloss:1.23381	validation-mlogloss:1.22599
[36m(train_xgb_ray_tune pid=1050011)[0m [190]	train-mlogloss:1.23343	validation-mlogloss:1.22559
[36m(train_xgb_ray_tune pid=1050018)[0m [146]	train-mlogloss:1.08899	validation-mlogloss:1.08589
[36m(train_xgb_ray_tune pid=1050017)[0m [152]	train-mlogloss:1.18519	validation-mlogloss:1.17717
[36m(train_xgb_ray_tune pid=1050017)[0m [153]	train-mlogloss:1.18425	validation-mlogloss:1.17619
[36m(train_xgb_ray_tune pid=1050007)[0m [113]	train-mlogloss:0.90850	validation-mlogloss:0.90571
[36m(train_xgb_ray_tune pid=1050020)[0m [94]	train-mlogloss:1.20512	validation-mlogloss:1.20054
[36m(train_xgb_ray_tune pid=1050012)[0m [134]	train-mlogloss:0.87840	validation-mlogloss:0.87523
[36m(train_xgb_ray_tune pid=1050015)[0m [112]	train-mlogloss:0.99350	validation-mlogloss:0.98853
[36m(train_xgb_ray_tune pid=1050015)[0m [113]	train-mlogloss:0.99178	validation-mlogloss:0.98680
[36m(train_xgb_ray_tune pid=1050003)[0m [190]	train-mlogloss:1.25999	validation-mlogloss:1.25307
[36m(train_xgb_ray_tune pid=1050003)[0m [191]	train-mlogloss:1.25971	validation-mlogloss:1.25278
[36m(train_xgb_ray_tune pid=1050004)[0m [81]	train-mlogloss:1.19888	validation-mlogloss:1.19222
[36m(train_xgb_ray_tune pid=1050004)[0m [82]	train-mlogloss:1.19724	validation-mlogloss:1.19055
[36m(train_xgb_ray_tune pid=1050019)[0m [170]	train-mlogloss:1.34820	validation-mlogloss:1.34627
[36m(train_xgb_ray_tune pid=1050019)[0m [171]	train-mlogloss:1.34820	validation-mlogloss:1.34627
[36m(train_xgb_ray_tune pid=1050019)[0m [172]	train-mlogloss:1.34820	validation-mlogloss:1.34627
[36m(train_xgb_ray_tune pid=1050005)[0m [128]	train-mlogloss:1.24069	validation-mlogloss:1.23418
[36m(train_xgb_ray_tune pid=1050008)[0m [134]	train-mlogloss:1.19808	validation-mlogloss:1.19135
[36m(train_xgb_ray_tune pid=1050013)[0m [162]	train-mlogloss:1.02007	validation-mlogloss:1.00956
[36m(train_xgb_ray_tune pid=1050013)[0m [163]	train-mlogloss:1.01946	validation-mlogloss:1.00898
[36m(train_xgb_ray_tune pid=1049992)[0m [127]	train-mlogloss:0.94390	validation-mlogloss:0.93654
[36m(train_xgb_ray_tune pid=1049992)[0m [128]	train-mlogloss:0.94290	validation-mlogloss:0.93553
[36m(train_xgb_ray_tune pid=1050010)[0m [102]	train-mlogloss:0.88203	validation-mlogloss:0.88191
[36m(train_xgb_ray_tune pid=1050006)[0m [95]	train-mlogloss:0.93650	validation-mlogloss:0.93276
[36m(train_xgb_ray_tune pid=1050014)[0m [141]	train-mlogloss:0.88130	validation-mlogloss:0.87748
[36m(train_xgb_ray_tune pid=1050014)[0m [142]	train-mlogloss:0.87982	validation-mlogloss:0.87591
[36m(train_xgb_ray_tune pid=1050011)[0m [191]	train-mlogloss:1.23304	validation-mlogloss:1.22517
[36m(train_xgb_ray_tune pid=1050011)[0m [192]	train-mlogloss:1.23264	validation-mlogloss:1.22475
[36m(train_xgb_ray_tune pid=1050018)[0m [147]	train-mlogloss:1.08773	validation-mlogloss:1.08456
[36m(train_xgb_ray_tune pid=1050017)[0m [154]	train-mlogloss:1.18337	validation-mlogloss:1.17525
[36m(train_xgb_ray_tune pid=1050017)[0m [155]	train-mlogloss:1.18247	validation-mlogloss:1.17430
[36m(train_xgb_ray_tune pid=1050007)[0m [114]	train-mlogloss:0.90661	validation-mlogloss:0.90377
[36m(train_xgb_ray_tune pid=1050020)[0m [95]	train-mlogloss:1.20372	validation-mlogloss:1.19910
[36m(train_xgb_ray_tune pid=1050012)[0m [135]	train-mlogloss:0.87691	validation-mlogloss:0.87375
[36m(train_xgb_ray_tune pid=1050012)[0m [136]	train-mlogloss:0.87569	validation-mlogloss:0.87267
[36m(train_xgb_ray_tune pid=1050015)[0m [114]	train-mlogloss:0.99012	validation-mlogloss:0.98514
[36m(train_xgb_ray_tune pid=1050015)[0m [115]	train-mlogloss:0.98851	validation-mlogloss:0.98347
[36m(train_xgb_ray_tune pid=1050003)[0m [192]	train-mlogloss:1.25946	validation-mlogloss:1.25252
[36m(train_xgb_ray_tune pid=1050003)[0m [193]	train-mlogloss:1.25919	validation-mlogloss:1.25224
[36m(train_xgb_ray_tune pid=1050004)[0m [83]	train-mlogloss:1.19548	validation-mlogloss:1.18874
[36m(train_xgb_ray_tune pid=1050019)[0m [173]	train-mlogloss:1.34797	validation-mlogloss:1.34603
[36m(train_xgb_ray_tune pid=1050019)[0m [174]	train-mlogloss:1.34797	validation-mlogloss:1.34603
[36m(train_xgb_ray_tune pid=1050005)[0m [129]	train-mlogloss:1.24007	validation-mlogloss:1.23350
[36m(train_xgb_ray_tune pid=1050005)[0m [130]	train-mlogloss:1.23948	validation-mlogloss:1.23288
[36m(train_xgb_ray_tune pid=1050008)[0m [135]	train-mlogloss:1.19732	validation-mlogloss:1.19054
[36m(train_xgb_ray_tune pid=1050008)[0m [136]	train-mlogloss:1.19644	validation-mlogloss:1.18965
[36m(train_xgb_ray_tune pid=1050013)[0m [164]	train-mlogloss:1.01911	validation-mlogloss:1.00860
[36m(train_xgb_ray_tune pid=1050013)[0m [165]	train-mlogloss:1.01874	validation-mlogloss:1.00820
[36m(train_xgb_ray_tune pid=1049992)[0m [129]	train-mlogloss:0.94193	validation-mlogloss:0.93455
[36m(train_xgb_ray_tune pid=1050010)[0m [103]	train-mlogloss:0.87992	validation-mlogloss:0.87972
[36m(train_xgb_ray_tune pid=1050010)[0m [104]	train-mlogloss:0.87797	validation-mlogloss:0.87769
[36m(train_xgb_ray_tune pid=1050006)[0m [96]	train-mlogloss:0.93433	validation-mlogloss:0.93043
[36m(train_xgb_ray_tune pid=1050009)[0m [107]	train-mlogloss:0.91628	validation-mlogloss:0.91398
[36m(train_xgb_ray_tune pid=1050014)[0m [143]	train-mlogloss:0.87854	validation-mlogloss:0.87483
[36m(train_xgb_ray_tune pid=1050011)[0m [193]	train-mlogloss:1.23223	validation-mlogloss:1.22431
[36m(train_xgb_ray_tune pid=1050011)[0m [194]	train-mlogloss:1.23183	validation-mlogloss:1.22389
[36m(train_xgb_ray_tune pid=1050018)[0m [148]	train-mlogloss:1.08649	validation-mlogloss:1.08333
[36m(train_xgb_ray_tune pid=1050018)[0m [149]	train-mlogloss:1.08523	validation-mlogloss:1.08200
[36m(train_xgb_ray_tune pid=1050017)[0m [156]	train-mlogloss:1.18164	validation-mlogloss:1.17341
[36m(train_xgb_ray_tune pid=1050007)[0m [115]	train-mlogloss:0.90478	validation-mlogloss:0.90183
[36m(train_xgb_ray_tune pid=1050020)[0m [96]	train-mlogloss:1.20226	validation-mlogloss:1.19762
[36m(train_xgb_ray_tune pid=1050012)[0m [137]	train-mlogloss:0.87446	validation-mlogloss:0.87153
[36m(train_xgb_ray_tune pid=1050015)[0m [116]	train-mlogloss:0.98664	validation-mlogloss:0.98152
[36m(train_xgb_ray_tune pid=1050003)[0m [194]	train-mlogloss:1.25919	validation-mlogloss:1.25224
[36m(train_xgb_ray_tune pid=1050004)[0m [84]	train-mlogloss:1.19376	validation-mlogloss:1.18703
[36m(train_xgb_ray_tune pid=1050019)[0m [175]	train-mlogloss:1.34797	validation-mlogloss:1.34603
[36m(train_xgb_ray_tune pid=1050019)[0m [176]	train-mlogloss:1.34797	validation-mlogloss:1.34603
[36m(train_xgb_ray_tune pid=1050005)[0m [131]	train-mlogloss:1.23892	validation-mlogloss:1.23229
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[36m(train_xgb_ray_tune pid=1050013)[0m [166]	train-mlogloss:1.01838	validation-mlogloss:1.00781
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[36m(train_xgb_ray_tune pid=1050014)[0m [190]	train-mlogloss:0.82862	validation-mlogloss:0.82624
[36m(train_xgb_ray_tune pid=1050017)[0m [207]	train-mlogloss:1.14161	validation-mlogloss:1.13208
[36m(train_xgb_ray_tune pid=1050012)[0m [186]	train-mlogloss:0.82959	validation-mlogloss:0.82655
[36m(train_xgb_ray_tune pid=1050003)[0m [264]	train-mlogloss:1.25495	validation-mlogloss:1.24775
[36m(train_xgb_ray_tune pid=1050005)[0m [190]	train-mlogloss:1.21137	validation-mlogloss:1.20301
[36m(train_xgb_ray_tune pid=1050008)[0m [191]	train-mlogloss:1.16101	validation-mlogloss:1.15318
[36m(train_xgb_ray_tune pid=1050013)[0m [219]	train-mlogloss:1.00233	validation-mlogloss:0.99077
[36m(train_xgb_ray_tune pid=1049992)[0m [178]	train-mlogloss:0.90135	validation-mlogloss:0.89365
[36m(train_xgb_ray_tune pid=1050011)[0m [256]	train-mlogloss:1.21160	validation-mlogloss:1.20232
[36m(train_xgb_ray_tune pid=1050017)[0m [208]	train-mlogloss:1.14090	validation-mlogloss:1.13131
[36m(train_xgb_ray_tune pid=1050020)[0m [127]	train-mlogloss:1.15953	validation-mlogloss:1.15391
[36m(train_xgb_ray_tune pid=1050015)[0m [165]	train-mlogloss:0.92188	validation-mlogloss:0.91755
[36m(train_xgb_ray_tune pid=1050005)[0m [191]	train-mlogloss:1.21098	validation-mlogloss:1.20260
[36m(train_xgb_ray_tune pid=1050010)[0m [139]	train-mlogloss:0.81823	validation-mlogloss:0.82028
[36m(train_xgb_ray_tune pid=1050018)[0m [196]	train-mlogloss:1.03239	validation-mlogloss:1.02866
[36m(train_xgb_ray_tune pid=1050007)[0m [149]	train-mlogloss:0.85545	validation-mlogloss:0.85199
[36m(train_xgb_ray_tune pid=1050003)[0m [265]	train-mlogloss:1.25495	validation-mlogloss:1.24775
[36m(train_xgb_ray_tune pid=1050004)[0m [121]	train-mlogloss:1.13744	validation-mlogloss:1.12917
[36m(train_xgb_ray_tune pid=1050013)[0m [220]	train-mlogloss:1.00210	validation-mlogloss:0.99055
[36m(train_xgb_ray_tune pid=1050006)[0m [129]	train-mlogloss:0.87562	validation-mlogloss:0.87199
[36m(train_xgb_ray_tune pid=1050009)[0m [139]	train-mlogloss:0.86273	validation-mlogloss:0.86093
[36m(train_xgb_ray_tune pid=1050014)[0m [191]	train-mlogloss:0.82777	validation-mlogloss:0.82540
[36m(train_xgb_ray_tune pid=1050011)[0m [257]	train-mlogloss:1.21132	validation-mlogloss:1.20201
[36m(train_xgb_ray_tune pid=1050012)[0m [187]	train-mlogloss:0.82886	validation-mlogloss:0.82578
[36m(train_xgb_ray_tune pid=1050015)[0m [166]	train-mlogloss:0.92081	validation-mlogloss:0.91653
[36m(train_xgb_ray_tune pid=1050003)[0m [266]	train-mlogloss:1.25495	validation-mlogloss:1.24775
[36m(train_xgb_ray_tune pid=1050008)[0m [192]	train-mlogloss:1.16061	validation-mlogloss:1.15275
[36m(train_xgb_ray_tune pid=1049992)[0m [179]	train-mlogloss:0.90085	validation-mlogloss:0.89323
[36m(train_xgb_ray_tune pid=1050005)[0m [192]	train-mlogloss:1.21058	validation-mlogloss:1.20219
[36m(train_xgb_ray_tune pid=1050017)[0m [209]	train-mlogloss:1.14021	validation-mlogloss:1.13065
[36m(train_xgb_ray_tune pid=1050013)[0m [221]	train-mlogloss:1.00188	validation-mlogloss:0.99033
[36m(train_xgb_ray_tune pid=1050014)[0m [192]	train-mlogloss:0.82699	validation-mlogloss:0.82466
[36m(train_xgb_ray_tune pid=1050020)[0m [128]	train-mlogloss:1.15825	validation-mlogloss:1.15257
[36m(train_xgb_ray_tune pid=1050012)[0m [188]	train-mlogloss:0.82806	validation-mlogloss:0.82504
[36m(train_xgb_ray_tune pid=1050003)[0m [267]	train-mlogloss:1.25495	validation-mlogloss:1.24775
[36m(train_xgb_ray_tune pid=1050004)[0m [122]	train-mlogloss:1.13608	validation-mlogloss:1.12771
[36m(train_xgb_ray_tune pid=1050008)[0m [193]	train-mlogloss:1.16021	validation-mlogloss:1.15232

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:06. Total running time: 10s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             7.64662 │
│ time_total_s                 7.64662 │
│ training_iteration                 1 │
│ validation_accuracy           0.4526 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1049992)[0m [180]	train-mlogloss:0.89996	validation-mlogloss:0.89233
[36m(train_xgb_ray_tune pid=1050010)[0m [140]	train-mlogloss:0.81676	validation-mlogloss:0.81894
[36m(train_xgb_ray_tune pid=1050011)[0m [258]	train-mlogloss:1.21104	validation-mlogloss:1.20172
[36m(train_xgb_ray_tune pid=1050018)[0m [197]	train-mlogloss:1.03143	validation-mlogloss:1.02775

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:06. Total running time: 10s
[36m(train_xgb_ray_tune pid=1050007)[0m [150]	train-mlogloss:0.85443	validation-mlogloss:0.85092
[36m(train_xgb_ray_tune pid=1050012)[0m [189]	train-mlogloss:0.82747	validation-mlogloss:0.82440
[36m(train_xgb_ray_tune pid=1050015)[0m [167]	train-mlogloss:0.91971	validation-mlogloss:0.91540
[36m(train_xgb_ray_tune pid=1050003)[0m [268]	train-mlogloss:1.25495	validation-mlogloss:1.24775
[36m(train_xgb_ray_tune pid=1050005)[0m [193]	train-mlogloss:1.21021	validation-mlogloss:1.20178
[36m(train_xgb_ray_tune pid=1050008)[0m [194]	train-mlogloss:1.15975	validation-mlogloss:1.15183
[36m(train_xgb_ray_tune pid=1050013)[0m [222]	train-mlogloss:1.00165	validation-mlogloss:0.99011
[36m(train_xgb_ray_tune pid=1050006)[0m [130]	train-mlogloss:0.87411	validation-mlogloss:0.87044
[36m(train_xgb_ray_tune pid=1050009)[0m [140]	train-mlogloss:0.86130	validation-mlogloss:0.85946
[36m(train_xgb_ray_tune pid=1050014)[0m [193]	train-mlogloss:0.82614	validation-mlogloss:0.82394
[36m(train_xgb_ray_tune pid=1050011)[0m [259]	train-mlogloss:1.21075	validation-mlogloss:1.20141
[36m(train_xgb_ray_tune pid=1050018)[0m [198]	train-mlogloss:1.03044	validation-mlogloss:1.02679
[36m(train_xgb_ray_tune pid=1050017)[0m [210]	train-mlogloss:1.13953	validation-mlogloss:1.12992
[36m(train_xgb_ray_tune pid=1050007)[0m [151]	train-mlogloss:0.85323	validation-mlogloss:0.84967
[36m(train_xgb_ray_tune pid=1050020)[0m [129]	train-mlogloss:1.15691	validation-mlogloss:1.15126
[36m(train_xgb_ray_tune pid=1050012)[0m [190]	train-mlogloss:0.82658	validation-mlogloss:0.82349
[36m(train_xgb_ray_tune pid=1050015)[0m [168]	train-mlogloss:0.91857	validation-mlogloss:0.91410
[36m(train_xgb_ray_tune pid=1050003)[0m [269]	train-mlogloss:1.25495	validation-mlogloss:1.24775
[36m(train_xgb_ray_tune pid=1050004)[0m [123]	train-mlogloss:1.13477	validation-mlogloss:1.12637
[36m(train_xgb_ray_tune pid=1050005)[0m [194]	train-mlogloss:1.20983	validation-mlogloss:1.20137
[36m(train_xgb_ray_tune pid=1050005)[0m [195]	train-mlogloss:1.20944	validation-mlogloss:1.20096
[36m(train_xgb_ray_tune pid=1050008)[0m [195]	train-mlogloss:1.15936	validation-mlogloss:1.15142
[36m(train_xgb_ray_tune pid=1050013)[0m [223]	train-mlogloss:1.00143	validation-mlogloss:0.98987
[36m(train_xgb_ray_tune pid=1049992)[0m [181]	train-mlogloss:0.89927	validation-mlogloss:0.89157
[36m(train_xgb_ray_tune pid=1050006)[0m [131]	train-mlogloss:0.87259	validation-mlogloss:0.86894
[36m(train_xgb_ray_tune pid=1050009)[0m [141]	train-mlogloss:0.85998	validation-mlogloss:0.85819
[36m(train_xgb_ray_tune pid=1050014)[0m [194]	train-mlogloss:0.82522	validation-mlogloss:0.82291
[36m(train_xgb_ray_tune pid=1050011)[0m [260]	train-mlogloss:1.21051	validation-mlogloss:1.20115
[36m(train_xgb_ray_tune pid=1050017)[0m [211]	train-mlogloss:1.13883	validation-mlogloss:1.12920
[36m(train_xgb_ray_tune pid=1050012)[0m [191]	train-mlogloss:0.82570	validation-mlogloss:0.82253
[36m(train_xgb_ray_tune pid=1050015)[0m [169]	train-mlogloss:0.91744	validation-mlogloss:0.91291
[36m(train_xgb_ray_tune pid=1050003)[0m [270]	train-mlogloss:1.25495	validation-mlogloss:1.24775
[36m(train_xgb_ray_tune pid=1050008)[0m [196]	train-mlogloss:1.15897	validation-mlogloss:1.15102
[36m(train_xgb_ray_tune pid=1050013)[0m [224]	train-mlogloss:1.00122	validation-mlogloss:0.98964
[36m(train_xgb_ray_tune pid=1049992)[0m [182]	train-mlogloss:0.89834	validation-mlogloss:0.89060
[36m(train_xgb_ray_tune pid=1050010)[0m [141]	train-mlogloss:0.81541	validation-mlogloss:0.81762
[36m(train_xgb_ray_tune pid=1050014)[0m [195]	train-mlogloss:0.82436	validation-mlogloss:0.82202
[36m(train_xgb_ray_tune pid=1050007)[0m [152]	train-mlogloss:0.85232	validation-mlogloss:0.84875
[36m(train_xgb_ray_tune pid=1050012)[0m [192]	train-mlogloss:0.82522	validation-mlogloss:0.82204
[36m(train_xgb_ray_tune pid=1050005)[0m [196]	train-mlogloss:1.20906	validation-mlogloss:1.20056
[36m(train_xgb_ray_tune pid=1050008)[0m [197]	train-mlogloss:1.15858	validation-mlogloss:1.15060
[36m(train_xgb_ray_tune pid=1050011)[0m [261]	train-mlogloss:1.21025	validation-mlogloss:1.20087
[36m(train_xgb_ray_tune pid=1050018)[0m [199]	train-mlogloss:1.02951	validation-mlogloss:1.02592
[36m(train_xgb_ray_tune pid=1050020)[0m [130]	train-mlogloss:1.15564	validation-mlogloss:1.14995
[36m(train_xgb_ray_tune pid=1050015)[0m [170]	train-mlogloss:0.91644	validation-mlogloss:0.91192
[36m(train_xgb_ray_tune pid=1050003)[0m [271]	train-mlogloss:1.25495	validation-mlogloss:1.24775
[36m(train_xgb_ray_tune pid=1050004)[0m [124]	train-mlogloss:1.13339	validation-mlogloss:1.12488
[36m(train_xgb_ray_tune pid=1050013)[0m [225]	train-mlogloss:1.00101	validation-mlogloss:0.98943
[36m(train_xgb_ray_tune pid=1049992)[0m [183]	train-mlogloss:0.89806	validation-mlogloss:0.89032
[36m(train_xgb_ray_tune pid=1050009)[0m [142]	train-mlogloss:0.85852	validation-mlogloss:0.85679
[36m(train_xgb_ray_tune pid=1050014)[0m [196]	train-mlogloss:0.82350	validation-mlogloss:0.82103
[36m(train_xgb_ray_tune pid=1050017)[0m [212]	train-mlogloss:1.13813	validation-mlogloss:1.12848
[36m(train_xgb_ray_tune pid=1050012)[0m [193]	train-mlogloss:0.82473	validation-mlogloss:0.82165
[36m(train_xgb_ray_tune pid=1050005)[0m [197]	train-mlogloss:1.20869	validation-mlogloss:1.20016
[36m(train_xgb_ray_tune pid=1050015)[0m [171]	train-mlogloss:0.91547	validation-mlogloss:0.91091
[36m(train_xgb_ray_tune pid=1050003)[0m [272]	train-mlogloss:1.25495	validation-mlogloss:1.24775
[36m(train_xgb_ray_tune pid=1050008)[0m [198]	train-mlogloss:1.15818	validation-mlogloss:1.15017
[36m(train_xgb_ray_tune pid=1050013)[0m [226]	train-mlogloss:1.00080	validation-mlogloss:0.98920
[36m(train_xgb_ray_tune pid=1050006)[0m [132]	train-mlogloss:0.87099	validation-mlogloss:0.86735
[36m(train_xgb_ray_tune pid=1050011)[0m [262]	train-mlogloss:1.21001	validation-mlogloss:1.20061
[36m(train_xgb_ray_tune pid=1049992)[0m [184]	train-mlogloss:0.89768	validation-mlogloss:0.88998
[36m(train_xgb_ray_tune pid=1050014)[0m [197]	train-mlogloss:0.82276	validation-mlogloss:0.82020
[36m(train_xgb_ray_tune pid=1050018)[0m [200]	train-mlogloss:1.02849	validation-mlogloss:1.02489
[36m(train_xgb_ray_tune pid=1050017)[0m [213]	train-mlogloss:1.13749	validation-mlogloss:1.12786
[36m(train_xgb_ray_tune pid=1050007)[0m [153]	train-mlogloss:0.85088	validation-mlogloss:0.84749
[36m(train_xgb_ray_tune pid=1050012)[0m [194]	train-mlogloss:0.82424	validation-mlogloss:0.82124
[36m(train_xgb_ray_tune pid=1050015)[0m [172]	train-mlogloss:0.91440	validation-mlogloss:0.90993
[36m(train_xgb_ray_tune pid=1050003)[0m [273]	train-mlogloss:1.25495	validation-mlogloss:1.24775
[36m(train_xgb_ray_tune pid=1050004)[0m [125]	train-mlogloss:1.13206	validation-mlogloss:1.12350
[36m(train_xgb_ray_tune pid=1050005)[0m [198]	train-mlogloss:1.20831	validation-mlogloss:1.19975
[36m(train_xgb_ray_tune pid=1050008)[0m [199]	train-mlogloss:1.15779	validation-mlogloss:1.14975
[36m(train_xgb_ray_tune pid=1050013)[0m [227]	train-mlogloss:1.00060	validation-mlogloss:0.98899
[36m(train_xgb_ray_tune pid=1050010)[0m [142]	train-mlogloss:0.81404	validation-mlogloss:0.81627
[36m(train_xgb_ray_tune pid=1050009)[0m [143]	train-mlogloss:0.85722	validation-mlogloss:0.85566
[36m(train_xgb_ray_tune pid=1050011)[0m [263]	train-mlogloss:1.20974	validation-mlogloss:1.20033
[36m(train_xgb_ray_tune pid=1050020)[0m [131]	train-mlogloss:1.15441	validation-mlogloss:1.14869
[36m(train_xgb_ray_tune pid=1050015)[0m [173]	train-mlogloss:0.91331	validation-mlogloss:0.90875
[36m(train_xgb_ray_tune pid=1050006)[0m [133]	train-mlogloss:0.86962	validation-mlogloss:0.86593
[36m(train_xgb_ray_tune pid=1050014)[0m [198]	train-mlogloss:0.82165	validation-mlogloss:0.81909
[36m(train_xgb_ray_tune pid=1050003)[0m [274]	train-mlogloss:1.25495	validation-mlogloss:1.24775
[36m(train_xgb_ray_tune pid=1050005)[0m [199]	train-mlogloss:1.20791	validation-mlogloss:1.19934
[36m(train_xgb_ray_tune pid=1050008)[0m [200]	train-mlogloss:1.15740	validation-mlogloss:1.14933
[36m(train_xgb_ray_tune pid=1049992)[0m [185]	train-mlogloss:0.89690	validation-mlogloss:0.88922
[36m(train_xgb_ray_tune pid=1050011)[0m [264]	train-mlogloss:1.20947	validation-mlogloss:1.20003
[36m(train_xgb_ray_tune pid=1050018)[0m [201]	train-mlogloss:1.02754	validation-mlogloss:1.02400
[36m(train_xgb_ray_tune pid=1050017)[0m [214]	train-mlogloss:1.13680	validation-mlogloss:1.12719
[36m(train_xgb_ray_tune pid=1050012)[0m [195]	train-mlogloss:0.82365	validation-mlogloss:0.82066
[36m(train_xgb_ray_tune pid=1050015)[0m [174]	train-mlogloss:0.91236	validation-mlogloss:0.90799
[36m(train_xgb_ray_tune pid=1050004)[0m [126]	train-mlogloss:1.13068	validation-mlogloss:1.12211
[36m(train_xgb_ray_tune pid=1050008)[0m [201]	train-mlogloss:1.15700	validation-mlogloss:1.14890
[36m(train_xgb_ray_tune pid=1050013)[0m [228]	train-mlogloss:1.00041	validation-mlogloss:0.98878
[36m(train_xgb_ray_tune pid=1050010)[0m [143]	train-mlogloss:0.81269	validation-mlogloss:0.81492
[36m(train_xgb_ray_tune pid=1050009)[0m [144]	train-mlogloss:0.85586	validation-mlogloss:0.85437
[36m(train_xgb_ray_tune pid=1050014)[0m [199]	train-mlogloss:0.82089	validation-mlogloss:0.81832
[36m(train_xgb_ray_tune pid=1050007)[0m [154]	train-mlogloss:0.84954	validation-mlogloss:0.84622
[36m(train_xgb_ray_tune pid=1050020)[0m [132]	train-mlogloss:1.15317	validation-mlogloss:1.14750
[36m(train_xgb_ray_tune pid=1050012)[0m [196]	train-mlogloss:0.82303	validation-mlogloss:0.81989
[36m(train_xgb_ray_tune pid=1050015)[0m [175]	train-mlogloss:0.91139	validation-mlogloss:0.90721
[36m(train_xgb_ray_tune pid=1050005)[0m [200]	train-mlogloss:1.20753	validation-mlogloss:1.19893
[36m(train_xgb_ray_tune pid=1050013)[0m [229]	train-mlogloss:1.00021	validation-mlogloss:0.98858
[36m(train_xgb_ray_tune pid=1049992)[0m [186]	train-mlogloss:0.89665	validation-mlogloss:0.88894
[36m(train_xgb_ray_tune pid=1050009)[0m [145]	train-mlogloss:0.85472	validation-mlogloss:0.85335
[36m(train_xgb_ray_tune pid=1050014)[0m [200]	train-mlogloss:0.82012	validation-mlogloss:0.81759
[36m(train_xgb_ray_tune pid=1050011)[0m [265]	train-mlogloss:1.20919	validation-mlogloss:1.19974
[36m(train_xgb_ray_tune pid=1050018)[0m [202]	train-mlogloss:1.02661	validation-mlogloss:1.02303
[36m(train_xgb_ray_tune pid=1050017)[0m [215]	train-mlogloss:1.13614	validation-mlogloss:1.12648
[36m(train_xgb_ray_tune pid=1050005)[0m [201]	train-mlogloss:1.20715	validation-mlogloss:1.19852
[36m(train_xgb_ray_tune pid=1050008)[0m [202]	train-mlogloss:1.15661	validation-mlogloss:1.14849
[36m(train_xgb_ray_tune pid=1050006)[0m [134]	train-mlogloss:0.86820	validation-mlogloss:0.86463
[36m(train_xgb_ray_tune pid=1050014)[0m [201]	train-mlogloss:0.81931	validation-mlogloss:0.81671
[36m(train_xgb_ray_tune pid=1050007)[0m [155]	train-mlogloss:0.84848	validation-mlogloss:0.84518
[36m(train_xgb_ray_tune pid=1050015)[0m [176]	train-mlogloss:0.91040	validation-mlogloss:0.90623
[36m(train_xgb_ray_tune pid=1050004)[0m [127]	train-mlogloss:1.12934	validation-mlogloss:1.12067
[36m(train_xgb_ray_tune pid=1050013)[0m [230]	train-mlogloss:0.99999	validation-mlogloss:0.98835
[36m(train_xgb_ray_tune pid=1049992)[0m [187]	train-mlogloss:0.89641	validation-mlogloss:0.88867
[36m(train_xgb_ray_tune pid=1050010)[0m [144]	train-mlogloss:0.81137	validation-mlogloss:0.81387
[36m(train_xgb_ray_tune pid=1050009)[0m [146]	train-mlogloss:0.85339	validation-mlogloss:0.85193
[36m(train_xgb_ray_tune pid=1050014)[0m [202]	train-mlogloss:0.81840	validation-mlogloss:0.81582
[36m(train_xgb_ray_tune pid=1050011)[0m [266]	train-mlogloss:1.20894	validation-mlogloss:1.19948
[36m(train_xgb_ray_tune pid=1050017)[0m [216]	train-mlogloss:1.13544	validation-mlogloss:1.12573
[36m(train_xgb_ray_tune pid=1050020)[0m [133]	train-mlogloss:1.15192	validation-mlogloss:1.14624
[36m(train_xgb_ray_tune pid=1050012)[0m [197]	train-mlogloss:0.82230	validation-mlogloss:0.81915
[36m(train_xgb_ray_tune pid=1050012)[0m [198]	train-mlogloss:0.82186	validation-mlogloss:0.81869
[36m(train_xgb_ray_tune pid=1050015)[0m [177]	train-mlogloss:0.90948	validation-mlogloss:0.90527
[36m(train_xgb_ray_tune pid=1050004)[0m [128]	train-mlogloss:1.12802	validation-mlogloss:1.11929
[36m(train_xgb_ray_tune pid=1050005)[0m [202]	train-mlogloss:1.20678	validation-mlogloss:1.19813
[36m(train_xgb_ray_tune pid=1050008)[0m [203]	train-mlogloss:1.15623	validation-mlogloss:1.14808
[36m(train_xgb_ray_tune pid=1050008)[0m [204]	train-mlogloss:1.15584	validation-mlogloss:1.14768
[36m(train_xgb_ray_tune pid=1050013)[0m [231]	train-mlogloss:0.99980	validation-mlogloss:0.98815
[36m(train_xgb_ray_tune pid=1049992)[0m [188]	train-mlogloss:0.89592	validation-mlogloss:0.88828
[36m(train_xgb_ray_tune pid=1050006)[0m [135]	train-mlogloss:0.86668	validation-mlogloss:0.86317
[36m(train_xgb_ray_tune pid=1050011)[0m [267]	train-mlogloss:1.20869	validation-mlogloss:1.19921
[36m(train_xgb_ray_tune pid=1050018)[0m [203]	train-mlogloss:1.02565	validation-mlogloss:1.02211
[36m(train_xgb_ray_tune pid=1050017)[0m [217]	train-mlogloss:1.13479	validation-mlogloss:1.12504
[36m(train_xgb_ray_tune pid=1050005)[0m [203]	train-mlogloss:1.20642	validation-mlogloss:1.19775
[36m(train_xgb_ray_tune pid=1050007)[0m [156]	train-mlogloss:0.84716	validation-mlogloss:0.84397
[36m(train_xgb_ray_tune pid=1050015)[0m [178]	train-mlogloss:0.90847	validation-mlogloss:0.90424
[36m(train_xgb_ray_tune pid=1050008)[0m [205]	train-mlogloss:1.15541	validation-mlogloss:1.14721
[36m(train_xgb_ray_tune pid=1050013)[0m [232]	train-mlogloss:0.99961	validation-mlogloss:0.98794
[36m(train_xgb_ray_tune pid=1049992)[0m [189]	train-mlogloss:0.89568	validation-mlogloss:0.88802
[36m(train_xgb_ray_tune pid=1050010)[0m [145]	train-mlogloss:0.81017	validation-mlogloss:0.81282
[36m(train_xgb_ray_tune pid=1050009)[0m [147]	train-mlogloss:0.85190	validation-mlogloss:0.85029
[36m(train_xgb_ray_tune pid=1050014)[0m [203]	train-mlogloss:0.81769	validation-mlogloss:0.81499
[36m(train_xgb_ray_tune pid=1050011)[0m [268]	train-mlogloss:1.20846	validation-mlogloss:1.19896
[36m(train_xgb_ray_tune pid=1050020)[0m [134]	train-mlogloss:1.15063	validation-mlogloss:1.14493
[36m(train_xgb_ray_tune pid=1050012)[0m [199]	train-mlogloss:0.82138	validation-mlogloss:0.81828
[36m(train_xgb_ray_tune pid=1050004)[0m [129]	train-mlogloss:1.12670	validation-mlogloss:1.11795
[36m(train_xgb_ray_tune pid=1050005)[0m [204]	train-mlogloss:1.20604	validation-mlogloss:1.19735
[36m(train_xgb_ray_tune pid=1050018)[0m [204]	train-mlogloss:1.02470	validation-mlogloss:1.02113
[36m(train_xgb_ray_tune pid=1050017)[0m [218]	train-mlogloss:1.13410	validation-mlogloss:1.12434
[36m(train_xgb_ray_tune pid=1050015)[0m [179]	train-mlogloss:0.90740	validation-mlogloss:0.90308
[36m(train_xgb_ray_tune pid=1050008)[0m [206]	train-mlogloss:1.15503	validation-mlogloss:1.14681
[36m(train_xgb_ray_tune pid=1050013)[0m [233]	train-mlogloss:0.99942	validation-mlogloss:0.98774
[36m(train_xgb_ray_tune pid=1050006)[0m [136]	train-mlogloss:0.86523	validation-mlogloss:0.86175
[36m(train_xgb_ray_tune pid=1050009)[0m [148]	train-mlogloss:0.85060	validation-mlogloss:0.84910
[36m(train_xgb_ray_tune pid=1050014)[0m [204]	train-mlogloss:0.81680	validation-mlogloss:0.81413
[36m(train_xgb_ray_tune pid=1050011)[0m [269]	train-mlogloss:1.20824	validation-mlogloss:1.19872
[36m(train_xgb_ray_tune pid=1050007)[0m [157]	train-mlogloss:0.84610	validation-mlogloss:0.84292
[36m(train_xgb_ray_tune pid=1050020)[0m [135]	train-mlogloss:1.14930	validation-mlogloss:1.14356
[36m(train_xgb_ray_tune pid=1050012)[0m [200]	train-mlogloss:0.82099	validation-mlogloss:0.81795
[36m(train_xgb_ray_tune pid=1050004)[0m [130]	train-mlogloss:1.12539	validation-mlogloss:1.11654
[36m(train_xgb_ray_tune pid=1050005)[0m [205]	train-mlogloss:1.20568	validation-mlogloss:1.19695
[36m(train_xgb_ray_tune pid=1049992)[0m [190]	train-mlogloss:0.89514	validation-mlogloss:0.88753
[36m(train_xgb_ray_tune pid=1050010)[0m [146]	train-mlogloss:0.80887	validation-mlogloss:0.81169
[36m(train_xgb_ray_tune pid=1050018)[0m [205]	train-mlogloss:1.02377	validation-mlogloss:1.02025
[36m(train_xgb_ray_tune pid=1050017)[0m [219]	train-mlogloss:1.13340	validation-mlogloss:1.12360
[36m(train_xgb_ray_tune pid=1050015)[0m [180]	train-mlogloss:0.90649	validation-mlogloss:0.90222
[36m(train_xgb_ray_tune pid=1050008)[0m [207]	train-mlogloss:1.15455	validation-mlogloss:1.14631
[36m(train_xgb_ray_tune pid=1050013)[0m [234]	train-mlogloss:0.99922	validation-mlogloss:0.98754
[36m(train_xgb_ray_tune pid=1050009)[0m [149]	train-mlogloss:0.84939	validation-mlogloss:0.84802
[36m(train_xgb_ray_tune pid=1050014)[0m [205]	train-mlogloss:0.81601	validation-mlogloss:0.81336
[36m(train_xgb_ray_tune pid=1050011)[0m [270]	train-mlogloss:1.20799	validation-mlogloss:1.19846
[36m(train_xgb_ray_tune pid=1050012)[0m [201]	train-mlogloss:0.82046	validation-mlogloss:0.81746
[36m(train_xgb_ray_tune pid=1050015)[0m [181]	train-mlogloss:0.90556	validation-mlogloss:0.90140
[36m(train_xgb_ray_tune pid=1050005)[0m [206]	train-mlogloss:1.20532	validation-mlogloss:1.19657
[36m(train_xgb_ray_tune pid=1049992)[0m [191]	train-mlogloss:0.89443	validation-mlogloss:0.88677
[36m(train_xgb_ray_tune pid=1050006)[0m [137]	train-mlogloss:0.86382	validation-mlogloss:0.86031
[36m(train_xgb_ray_tune pid=1050004)[0m [131]	train-mlogloss:1.12414	validation-mlogloss:1.11524
[36m(train_xgb_ray_tune pid=1050008)[0m [208]	train-mlogloss:1.15416	validation-mlogloss:1.14590
[36m(train_xgb_ray_tune pid=1050011)[0m [271]	train-mlogloss:1.20772	validation-mlogloss:1.19817
[36m(train_xgb_ray_tune pid=1050017)[0m [220]	train-mlogloss:1.13271	validation-mlogloss:1.12286
[36m(train_xgb_ray_tune pid=1050007)[0m [158]	train-mlogloss:0.84516	validation-mlogloss:0.84205
[36m(train_xgb_ray_tune pid=1050020)[0m [136]	train-mlogloss:1.14806	validation-mlogloss:1.14233
[36m(train_xgb_ray_tune pid=1050012)[0m [202]	train-mlogloss:0.81987	validation-mlogloss:0.81673

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:06. Total running time: 11s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             8.26146 │
│ time_total_s                 8.26146 │
│ training_iteration                 1 │
│ validation_accuracy          0.46103 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1050005)[0m [207]	train-mlogloss:1.20497	validation-mlogloss:1.19619
[36m(train_xgb_ray_tune pid=1050013)[0m [235]	train-mlogloss:0.99904	validation-mlogloss:0.98736
[36m(train_xgb_ray_tune pid=1049992)[0m [192]	train-mlogloss:0.89392	validation-mlogloss:0.88624
[36m(train_xgb_ray_tune pid=1050010)[0m [147]	train-mlogloss:0.80753	validation-mlogloss:0.81054
[36m(train_xgb_ray_tune pid=1050009)[0m [150]	train-mlogloss:0.84797	validation-mlogloss:0.84648
[36m(train_xgb_ray_tune pid=1050014)[0m [206]	train-mlogloss:0.81523	validation-mlogloss:0.81255
[36m(train_xgb_ray_tune pid=1050018)[0m [206]	train-mlogloss:1.02282	validation-mlogloss:1.01925
[36m(train_xgb_ray_tune pid=1050015)[0m [182]	train-mlogloss:0.90460	validation-mlogloss:0.90036
[36m(train_xgb_ray_tune pid=1050008)[0m [209]	train-mlogloss:1.15381	validation-mlogloss:1.14551

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:06. Total running time: 11s
[36m(train_xgb_ray_tune pid=1050013)[0m [236]	train-mlogloss:0.99885	validation-mlogloss:0.98716
[36m(train_xgb_ray_tune pid=1050011)[0m [272]	train-mlogloss:1.20744	validation-mlogloss:1.19787
[36m(train_xgb_ray_tune pid=1050017)[0m [221]	train-mlogloss:1.13204	validation-mlogloss:1.12217
[36m(train_xgb_ray_tune pid=1050012)[0m [203]	train-mlogloss:0.81933	validation-mlogloss:0.81612
[36m(train_xgb_ray_tune pid=1050015)[0m [183]	train-mlogloss:0.90357	validation-mlogloss:0.89940
[36m(train_xgb_ray_tune pid=1050004)[0m [132]	train-mlogloss:1.12292	validation-mlogloss:1.11399
[36m(train_xgb_ray_tune pid=1050005)[0m [208]	train-mlogloss:1.20462	validation-mlogloss:1.19581
[36m(train_xgb_ray_tune pid=1050008)[0m [210]	train-mlogloss:1.15344	validation-mlogloss:1.14512
[36m(train_xgb_ray_tune pid=1050013)[0m [237]	train-mlogloss:0.99867	validation-mlogloss:0.98698
[36m(train_xgb_ray_tune pid=1049992)[0m [193]	train-mlogloss:0.89321	validation-mlogloss:0.88554
[36m(train_xgb_ray_tune pid=1050006)[0m [138]	train-mlogloss:0.86232	validation-mlogloss:0.85899
[36m(train_xgb_ray_tune pid=1050009)[0m [151]	train-mlogloss:0.84671	validation-mlogloss:0.84514
[36m(train_xgb_ray_tune pid=1050014)[0m [207]	train-mlogloss:0.81454	validation-mlogloss:0.81177
[36m(train_xgb_ray_tune pid=1050011)[0m [273]	train-mlogloss:1.20718	validation-mlogloss:1.19759
[36m(train_xgb_ray_tune pid=1050018)[0m [207]	train-mlogloss:1.02185	validation-mlogloss:1.01829
[36m(train_xgb_ray_tune pid=1050017)[0m [222]	train-mlogloss:1.13141	validation-mlogloss:1.12157
[36m(train_xgb_ray_tune pid=1050007)[0m [159]	train-mlogloss:0.84384	validation-mlogloss:0.84070
[36m(train_xgb_ray_tune pid=1050020)[0m [137]	train-mlogloss:1.14682	validation-mlogloss:1.14104
[36m(train_xgb_ray_tune pid=1050012)[0m [204]	train-mlogloss:0.81857	validation-mlogloss:0.81541
[36m(train_xgb_ray_tune pid=1050015)[0m [184]	train-mlogloss:0.90264	validation-mlogloss:0.89864
[36m(train_xgb_ray_tune pid=1050004)[0m [133]	train-mlogloss:1.12160	validation-mlogloss:1.11264
[36m(train_xgb_ray_tune pid=1050005)[0m [209]	train-mlogloss:1.20426	validation-mlogloss:1.19543
[36m(train_xgb_ray_tune pid=1050008)[0m [211]	train-mlogloss:1.15284	validation-mlogloss:1.14450
[36m(train_xgb_ray_tune pid=1050010)[0m [148]	train-mlogloss:0.80632	validation-mlogloss:0.80942
[36m(train_xgb_ray_tune pid=1050009)[0m [152]	train-mlogloss:0.84553	validation-mlogloss:0.84411
[36m(train_xgb_ray_tune pid=1050014)[0m [208]	train-mlogloss:0.81358	validation-mlogloss:0.81079
[36m(train_xgb_ray_tune pid=1050020)[0m [138]	train-mlogloss:1.14560	validation-mlogloss:1.13975
[36m(train_xgb_ray_tune pid=1050013)[0m [238]	train-mlogloss:0.99848	validation-mlogloss:0.98679
[36m(train_xgb_ray_tune pid=1049992)[0m [194]	train-mlogloss:0.89269	validation-mlogloss:0.88500
[36m(train_xgb_ray_tune pid=1050006)[0m [139]	train-mlogloss:0.86113	validation-mlogloss:0.85799
[36m(train_xgb_ray_tune pid=1050011)[0m [274]	train-mlogloss:1.20688	validation-mlogloss:1.19727
[36m(train_xgb_ray_tune pid=1050015)[0m [185]	train-mlogloss:0.90157	validation-mlogloss:0.89752
[36m(train_xgb_ray_tune pid=1050005)[0m [210]	train-mlogloss:1.20391	validation-mlogloss:1.19505
[36m(train_xgb_ray_tune pid=1050008)[0m [212]	train-mlogloss:1.15226	validation-mlogloss:1.14391
[36m(train_xgb_ray_tune pid=1050017)[0m [223]	train-mlogloss:1.13078	validation-mlogloss:1.12094
[36m(train_xgb_ray_tune pid=1050007)[0m [160]	train-mlogloss:0.84263	validation-mlogloss:0.83941
[36m(train_xgb_ray_tune pid=1050012)[0m [205]	train-mlogloss:0.81817	validation-mlogloss:0.81499
[36m(train_xgb_ray_tune pid=1050013)[0m [239]	train-mlogloss:0.99829	validation-mlogloss:0.98658
[36m(train_xgb_ray_tune pid=1050010)[0m [149]	train-mlogloss:0.80497	validation-mlogloss:0.80807
[36m(train_xgb_ray_tune pid=1050014)[0m [209]	train-mlogloss:0.81303	validation-mlogloss:0.81025
[36m(train_xgb_ray_tune pid=1050011)[0m [275]	train-mlogloss:1.20664	validation-mlogloss:1.19701
[36m(train_xgb_ray_tune pid=1050018)[0m [208]	train-mlogloss:1.02093	validation-mlogloss:1.01741
[36m(train_xgb_ray_tune pid=1050020)[0m [139]	train-mlogloss:1.14432	validation-mlogloss:1.13848
[36m(train_xgb_ray_tune pid=1050015)[0m [186]	train-mlogloss:0.90070	validation-mlogloss:0.89663
[36m(train_xgb_ray_tune pid=1050004)[0m [134]	train-mlogloss:1.12040	validation-mlogloss:1.11145
[36m(train_xgb_ray_tune pid=1050005)[0m [211]	train-mlogloss:1.20358	validation-mlogloss:1.19470
[36m(train_xgb_ray_tune pid=1050008)[0m [213]	train-mlogloss:1.15190	validation-mlogloss:1.14351
[36m(train_xgb_ray_tune pid=1049992)[0m [195]	train-mlogloss:0.89235	validation-mlogloss:0.88467
[36m(train_xgb_ray_tune pid=1050009)[0m [153]	train-mlogloss:0.84431	validation-mlogloss:0.84291
[36m(train_xgb_ray_tune pid=1050012)[0m [206]	train-mlogloss:0.81774	validation-mlogloss:0.81455
[36m(train_xgb_ray_tune pid=1050017)[0m [224]	train-mlogloss:1.13012	validation-mlogloss:1.12028
[36m(train_xgb_ray_tune pid=1050015)[0m [187]	train-mlogloss:0.89984	validation-mlogloss:0.89585
[36m(train_xgb_ray_tune pid=1050008)[0m [214]	train-mlogloss:1.15132	validation-mlogloss:1.14291
[36m(train_xgb_ray_tune pid=1050013)[0m [240]	train-mlogloss:0.99810	validation-mlogloss:0.98640
[36m(train_xgb_ray_tune pid=1050006)[0m [140]	train-mlogloss:0.85977	validation-mlogloss:0.85666
[36m(train_xgb_ray_tune pid=1050014)[0m [210]	train-mlogloss:0.81218	validation-mlogloss:0.80947
[36m(train_xgb_ray_tune pid=1050011)[0m [276]	train-mlogloss:1.20638	validation-mlogloss:1.19673
[36m(train_xgb_ray_tune pid=1050018)[0m [209]	train-mlogloss:1.01999	validation-mlogloss:1.01646
[36m(train_xgb_ray_tune pid=1050007)[0m [161]	train-mlogloss:0.84139	validation-mlogloss:0.83819
[36m(train_xgb_ray_tune pid=1050020)[0m [140]	train-mlogloss:1.14306	validation-mlogloss:1.13715
[36m(train_xgb_ray_tune pid=1050005)[0m [212]	train-mlogloss:1.20323	validation-mlogloss:1.19433
[36m(train_xgb_ray_tune pid=1049992)[0m [196]	train-mlogloss:0.89183	validation-mlogloss:0.88415
[36m(train_xgb_ray_tune pid=1050009)[0m [154]	train-mlogloss:0.84303	validation-mlogloss:0.84172
[36m(train_xgb_ray_tune pid=1050012)[0m [207]	train-mlogloss:0.81733	validation-mlogloss:0.81418
[36m(train_xgb_ray_tune pid=1050015)[0m [188]	train-mlogloss:0.89891	validation-mlogloss:0.89498
[36m(train_xgb_ray_tune pid=1050008)[0m [215]	train-mlogloss:1.15090	validation-mlogloss:1.14245
[36m(train_xgb_ray_tune pid=1050013)[0m [241]	train-mlogloss:0.99791	validation-mlogloss:0.98622
[36m(train_xgb_ray_tune pid=1050010)[0m [150]	train-mlogloss:0.80368	validation-mlogloss:0.80670
[36m(train_xgb_ray_tune pid=1050017)[0m [225]	train-mlogloss:1.12947	validation-mlogloss:1.11963
[36m(train_xgb_ray_tune pid=1050004)[0m [135]	train-mlogloss:1.11912	validation-mlogloss:1.11015
[36m(train_xgb_ray_tune pid=1050014)[0m [211]	train-mlogloss:0.81175	validation-mlogloss:0.80899
[36m(train_xgb_ray_tune pid=1050011)[0m [277]	train-mlogloss:1.20615	validation-mlogloss:1.19649
[36m(train_xgb_ray_tune pid=1050020)[0m [141]	train-mlogloss:1.14185	validation-mlogloss:1.13591
[36m(train_xgb_ray_tune pid=1050015)[0m [189]	train-mlogloss:0.89787	validation-mlogloss:0.89388
[36m(train_xgb_ray_tune pid=1050005)[0m [213]	train-mlogloss:1.20287	validation-mlogloss:1.19395
[36m(train_xgb_ray_tune pid=1050008)[0m [216]	train-mlogloss:1.15055	validation-mlogloss:1.14208
[36m(train_xgb_ray_tune pid=1050013)[0m [242]	train-mlogloss:0.99774	validation-mlogloss:0.98605
[36m(train_xgb_ray_tune pid=1049992)[0m [197]	train-mlogloss:0.89095	validation-mlogloss:0.88322
[36m(train_xgb_ray_tune pid=1050006)[0m [141]	train-mlogloss:0.85845	validation-mlogloss:0.85531
[36m(train_xgb_ray_tune pid=1050009)[0m [155]	train-mlogloss:0.84176	validation-mlogloss:0.84045
[36m(train_xgb_ray_tune pid=1050014)[0m [212]	train-mlogloss:0.81110	validation-mlogloss:0.80829
[36m(train_xgb_ray_tune pid=1050011)[0m [278]	train-mlogloss:1.20590	validation-mlogloss:1.19623
[36m(train_xgb_ray_tune pid=1050018)[0m [210]	train-mlogloss:1.01909	validation-mlogloss:1.01561
[36m(train_xgb_ray_tune pid=1050017)[0m [226]	train-mlogloss:1.12879	validation-mlogloss:1.11896
[36m(train_xgb_ray_tune pid=1050007)[0m [162]	train-mlogloss:0.84042	validation-mlogloss:0.83713
[36m(train_xgb_ray_tune pid=1050020)[0m [142]	train-mlogloss:1.14064	validation-mlogloss:1.13464
[36m(train_xgb_ray_tune pid=1050012)[0m [208]	train-mlogloss:0.81672	validation-mlogloss:0.81365
[36m(train_xgb_ray_tune pid=1050005)[0m [214]	train-mlogloss:1.20256	validation-mlogloss:1.19361
[36m(train_xgb_ray_tune pid=1050008)[0m [217]	train-mlogloss:1.15018	validation-mlogloss:1.14170
[36m(train_xgb_ray_tune pid=1049992)[0m [198]	train-mlogloss:0.89071	validation-mlogloss:0.88296
[36m(train_xgb_ray_tune pid=1050010)[0m [151]	train-mlogloss:0.80246	validation-mlogloss:0.80567
[36m(train_xgb_ray_tune pid=1050012)[0m [209]	train-mlogloss:0.81606	validation-mlogloss:0.81297
[36m(train_xgb_ray_tune pid=1050015)[0m [190]	train-mlogloss:0.89694	validation-mlogloss:0.89294
[36m(train_xgb_ray_tune pid=1050013)[0m [243]	train-mlogloss:0.99755	validation-mlogloss:0.98587
[36m(train_xgb_ray_tune pid=1050018)[0m [211]	train-mlogloss:1.01816	validation-mlogloss:1.01465
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[36m(train_xgb_ray_tune pid=1050008)[0m [218]	train-mlogloss:1.14982	validation-mlogloss:1.14131
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[36m(train_xgb_ray_tune pid=1050013)[0m [279]	train-mlogloss:0.99271	validation-mlogloss:0.98086
[36m(train_xgb_ray_tune pid=1050006)[0m [162]	train-mlogloss:0.83260	validation-mlogloss:0.83078
[36m(train_xgb_ray_tune pid=1050018)[0m [237]	train-mlogloss:0.99518	validation-mlogloss:0.99200
[36m(train_xgb_ray_tune pid=1050012)[0m [247]	train-mlogloss:0.79995	validation-mlogloss:0.79675
[36m(train_xgb_ray_tune pid=1050008)[0m [254]	train-mlogloss:1.13750	validation-mlogloss:1.12821
[36m(train_xgb_ray_tune pid=1049992)[0m [232]	train-mlogloss:0.87879	validation-mlogloss:0.87064
[36m(train_xgb_ray_tune pid=1050014)[0m [258]	train-mlogloss:0.78517	validation-mlogloss:0.78278
[36m(train_xgb_ray_tune pid=1050017)[0m [268]	train-mlogloss:1.10325	validation-mlogloss:1.09282
[36m(train_xgb_ray_tune pid=1050020)[0m [165]	train-mlogloss:1.11451	validation-mlogloss:1.10819
[36m(train_xgb_ray_tune pid=1050015)[0m [233]	train-mlogloss:0.86205	validation-mlogloss:0.85906
[36m(train_xgb_ray_tune pid=1050013)[0m [280]	train-mlogloss:0.99271	validation-mlogloss:0.98086
[36m(train_xgb_ray_tune pid=1050011)[0m [317]	train-mlogloss:1.19716	validation-mlogloss:1.18691
[36m(train_xgb_ray_tune pid=1050007)[0m [190]	train-mlogloss:0.81548	validation-mlogloss:0.81313
[36m(train_xgb_ray_tune pid=1050009)[0m [177]	train-mlogloss:0.81657	validation-mlogloss:0.81648
[36m(train_xgb_ray_tune pid=1050014)[0m [259]	train-mlogloss:0.78462	validation-mlogloss:0.78236
[36m(train_xgb_ray_tune pid=1050017)[0m [269]	train-mlogloss:1.10272	validation-mlogloss:1.09227
[36m(train_xgb_ray_tune pid=1050012)[0m [248]	train-mlogloss:0.79946	validation-mlogloss:0.79629
[36m(train_xgb_ray_tune pid=1050015)[0m [234]	train-mlogloss:0.86139	validation-mlogloss:0.85848
[36m(train_xgb_ray_tune pid=1050004)[0m [159]	train-mlogloss:1.09124	validation-mlogloss:1.08151
[36m(train_xgb_ray_tune pid=1050008)[0m [255]	train-mlogloss:1.13719	validation-mlogloss:1.12789
[36m(train_xgb_ray_tune pid=1050013)[0m [281]	train-mlogloss:0.99271	validation-mlogloss:0.98086
[36m(train_xgb_ray_tune pid=1049992)[0m [233]	train-mlogloss:0.87861	validation-mlogloss:0.87045
[36m(train_xgb_ray_tune pid=1050010)[0m [173]	train-mlogloss:0.77734	validation-mlogloss:0.78245
[36m(train_xgb_ray_tune pid=1050006)[0m [163]	train-mlogloss:0.83147	validation-mlogloss:0.82963
[36m(train_xgb_ray_tune pid=1050011)[0m [318]	train-mlogloss:1.19698	validation-mlogloss:1.18672
[36m(train_xgb_ray_tune pid=1050018)[0m [238]	train-mlogloss:0.99438	validation-mlogloss:0.99118
[36m(train_xgb_ray_tune pid=1050017)[0m [270]	train-mlogloss:1.10215	validation-mlogloss:1.09169
[36m(train_xgb_ray_tune pid=1050007)[0m [191]	train-mlogloss:0.81483	validation-mlogloss:0.81240
[36m(train_xgb_ray_tune pid=1050020)[0m [166]	train-mlogloss:1.11336	validation-mlogloss:1.10703
[36m(train_xgb_ray_tune pid=1050012)[0m [249]	train-mlogloss:0.79902	validation-mlogloss:0.79579
[36m(train_xgb_ray_tune pid=1050015)[0m [235]	train-mlogloss:0.86060	validation-mlogloss:0.85756
[36m(train_xgb_ray_tune pid=1050008)[0m [256]	train-mlogloss:1.13671	validation-mlogloss:1.12738
[36m(train_xgb_ray_tune pid=1049992)[0m [234]	train-mlogloss:0.87808	validation-mlogloss:0.86995

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:07. Total running time: 11s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             8.61305 │
│ time_total_s                 8.61305 │
│ training_iteration                 1 │
│ validation_accuracy          0.57549 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1050009)[0m [178]	train-mlogloss:0.81552	validation-mlogloss:0.81549
[36m(train_xgb_ray_tune pid=1050014)[0m [260]	train-mlogloss:0.78426	validation-mlogloss:0.78199
[36m(train_xgb_ray_tune pid=1050014)[0m [261]	train-mlogloss:0.78374	validation-mlogloss:0.78143
[36m(train_xgb_ray_tune pid=1050011)[0m [319]	train-mlogloss:1.19676	validation-mlogloss:1.18649
[36m(train_xgb_ray_tune pid=1050018)[0m [239]	train-mlogloss:0.99358	validation-mlogloss:0.99032
[36m(train_xgb_ray_tune pid=1050017)[0m [271]	train-mlogloss:1.10158	validation-mlogloss:1.09107
[36m(train_xgb_ray_tune pid=1050007)[0m [192]	train-mlogloss:0.81404	validation-mlogloss:0.81166

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:07. Total running time: 11s
[36m(train_xgb_ray_tune pid=1050020)[0m [167]	train-mlogloss:1.11232	validation-mlogloss:1.10599
[36m(train_xgb_ray_tune pid=1050012)[0m [250]	train-mlogloss:0.79865	validation-mlogloss:0.79529
[36m(train_xgb_ray_tune pid=1050012)[0m [251]	train-mlogloss:0.79814	validation-mlogloss:0.79478
[36m(train_xgb_ray_tune pid=1050015)[0m [236]	train-mlogloss:0.85992	validation-mlogloss:0.85691
[36m(train_xgb_ray_tune pid=1050004)[0m [160]	train-mlogloss:1.09009	validation-mlogloss:1.08035
[36m(train_xgb_ray_tune pid=1050008)[0m [257]	train-mlogloss:1.13641	validation-mlogloss:1.12707
[36m(train_xgb_ray_tune pid=1050008)[0m [258]	train-mlogloss:1.13613	validation-mlogloss:1.12677
[36m(train_xgb_ray_tune pid=1050013)[0m [282]	train-mlogloss:0.99256	validation-mlogloss:0.98071
[36m(train_xgb_ray_tune pid=1050013)[0m [283]	train-mlogloss:0.99256	validation-mlogloss:0.98071
[36m(train_xgb_ray_tune pid=1049992)[0m [235]	train-mlogloss:0.87791	validation-mlogloss:0.86974
[36m(train_xgb_ray_tune pid=1049992)[0m [236]	train-mlogloss:0.87774	validation-mlogloss:0.86954
[36m(train_xgb_ray_tune pid=1050010)[0m [174]	train-mlogloss:0.77623	validation-mlogloss:0.78150
[36m(train_xgb_ray_tune pid=1050006)[0m [164]	train-mlogloss:0.83040	validation-mlogloss:0.82871
[36m(train_xgb_ray_tune pid=1050006)[0m [165]	train-mlogloss:0.82937	validation-mlogloss:0.82774
[36m(train_xgb_ray_tune pid=1050009)[0m [179]	train-mlogloss:0.81437	validation-mlogloss:0.81436
[36m(train_xgb_ray_tune pid=1050014)[0m [262]	train-mlogloss:0.78336	validation-mlogloss:0.78109
[36m(train_xgb_ray_tune pid=1050011)[0m [320]	train-mlogloss:1.19654	validation-mlogloss:1.18625
[36m(train_xgb_ray_tune pid=1050011)[0m [321]	train-mlogloss:1.19633	validation-mlogloss:1.18604
[36m(train_xgb_ray_tune pid=1050018)[0m [240]	train-mlogloss:0.99275	validation-mlogloss:0.98941
[36m(train_xgb_ray_tune pid=1050017)[0m [272]	train-mlogloss:1.10096	validation-mlogloss:1.09043
[36m(train_xgb_ray_tune pid=1050017)[0m [273]	train-mlogloss:1.10039	validation-mlogloss:1.08982
[36m(train_xgb_ray_tune pid=1050007)[0m [193]	train-mlogloss:0.81324	validation-mlogloss:0.81095
[36m(train_xgb_ray_tune pid=1050020)[0m [168]	train-mlogloss:1.11128	validation-mlogloss:1.10494
[36m(train_xgb_ray_tune pid=1050012)[0m [252]	train-mlogloss:0.79789	validation-mlogloss:0.79455
[36m(train_xgb_ray_tune pid=1050012)[0m [253]	train-mlogloss:0.79739	validation-mlogloss:0.79407
[36m(train_xgb_ray_tune pid=1050015)[0m [237]	train-mlogloss:0.85925	validation-mlogloss:0.85625
[36m(train_xgb_ray_tune pid=1050015)[0m [238]	train-mlogloss:0.85856	validation-mlogloss:0.85562
[36m(train_xgb_ray_tune pid=1050004)[0m [161]	train-mlogloss:1.08894	validation-mlogloss:1.07917
[36m(train_xgb_ray_tune pid=1050008)[0m [259]	train-mlogloss:1.13583	validation-mlogloss:1.12645
[36m(train_xgb_ray_tune pid=1050013)[0m [284]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1050013)[0m [285]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1049992)[0m [237]	train-mlogloss:0.87758	validation-mlogloss:0.86937
[36m(train_xgb_ray_tune pid=1049992)[0m [238]	train-mlogloss:0.87740	validation-mlogloss:0.86916
[36m(train_xgb_ray_tune pid=1050010)[0m [175]	train-mlogloss:0.77525	validation-mlogloss:0.78045
[36m(train_xgb_ray_tune pid=1050006)[0m [166]	train-mlogloss:0.82837	validation-mlogloss:0.82667
[36m(train_xgb_ray_tune pid=1050009)[0m [180]	train-mlogloss:0.81322	validation-mlogloss:0.81339
[36m(train_xgb_ray_tune pid=1050014)[0m [263]	train-mlogloss:0.78290	validation-mlogloss:0.78072
[36m(train_xgb_ray_tune pid=1050011)[0m [322]	train-mlogloss:1.19613	validation-mlogloss:1.18581
[36m(train_xgb_ray_tune pid=1050018)[0m [241]	train-mlogloss:0.99192	validation-mlogloss:0.98860
[36m(train_xgb_ray_tune pid=1050017)[0m [274]	train-mlogloss:1.09982	validation-mlogloss:1.08926
[36m(train_xgb_ray_tune pid=1050007)[0m [194]	train-mlogloss:0.81234	validation-mlogloss:0.81027
[36m(train_xgb_ray_tune pid=1050012)[0m [254]	train-mlogloss:0.79717	validation-mlogloss:0.79384
[36m(train_xgb_ray_tune pid=1050004)[0m [162]	train-mlogloss:1.08783	validation-mlogloss:1.07802
[36m(train_xgb_ray_tune pid=1050008)[0m [260]	train-mlogloss:1.13533	validation-mlogloss:1.12594
[36m(train_xgb_ray_tune pid=1050013)[0m [286]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1050010)[0m [176]	train-mlogloss:0.77427	validation-mlogloss:0.77953
[36m(train_xgb_ray_tune pid=1050014)[0m [264]	train-mlogloss:0.78254	validation-mlogloss:0.78032
[36m(train_xgb_ray_tune pid=1050020)[0m [169]	train-mlogloss:1.11022	validation-mlogloss:1.10390
[36m(train_xgb_ray_tune pid=1050012)[0m [255]	train-mlogloss:0.79691	validation-mlogloss:0.79358
[36m(train_xgb_ray_tune pid=1050015)[0m [239]	train-mlogloss:0.85791	validation-mlogloss:0.85503
[36m(train_xgb_ray_tune pid=1050013)[0m [287]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1049992)[0m [239]	train-mlogloss:0.87722	validation-mlogloss:0.86903
[36m(train_xgb_ray_tune pid=1050009)[0m [181]	train-mlogloss:0.81216	validation-mlogloss:0.81236
[36m(train_xgb_ray_tune pid=1050011)[0m [323]	train-mlogloss:1.19592	validation-mlogloss:1.18560
[36m(train_xgb_ray_tune pid=1050018)[0m [242]	train-mlogloss:0.99104	validation-mlogloss:0.98776
[36m(train_xgb_ray_tune pid=1050006)[0m [167]	train-mlogloss:0.82727	validation-mlogloss:0.82559
[36m(train_xgb_ray_tune pid=1050017)[0m [275]	train-mlogloss:1.09926	validation-mlogloss:1.08866
[36m(train_xgb_ray_tune pid=1050007)[0m [195]	train-mlogloss:0.81178	validation-mlogloss:0.80979
[36m(train_xgb_ray_tune pid=1050012)[0m [256]	train-mlogloss:0.79647	validation-mlogloss:0.79318
[36m(train_xgb_ray_tune pid=1050004)[0m [163]	train-mlogloss:1.08677	validation-mlogloss:1.07689
[36m(train_xgb_ray_tune pid=1050008)[0m [261]	train-mlogloss:1.13502	validation-mlogloss:1.12562
[36m(train_xgb_ray_tune pid=1050013)[0m [288]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1050014)[0m [265]	train-mlogloss:0.78228	validation-mlogloss:0.78008
[36m(train_xgb_ray_tune pid=1050011)[0m [324]	train-mlogloss:1.19572	validation-mlogloss:1.18538
[36m(train_xgb_ray_tune pid=1050015)[0m [240]	train-mlogloss:0.85716	validation-mlogloss:0.85423
[36m(train_xgb_ray_tune pid=1050013)[0m [289]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1049992)[0m [240]	train-mlogloss:0.87705	validation-mlogloss:0.86884
[36m(train_xgb_ray_tune pid=1050010)[0m [177]	train-mlogloss:0.77322	validation-mlogloss:0.77852
[36m(train_xgb_ray_tune pid=1050009)[0m [182]	train-mlogloss:0.81108	validation-mlogloss:0.81117
[36m(train_xgb_ray_tune pid=1050018)[0m [243]	train-mlogloss:0.99019	validation-mlogloss:0.98693
[36m(train_xgb_ray_tune pid=1050017)[0m [276]	train-mlogloss:1.09871	validation-mlogloss:1.08812
[36m(train_xgb_ray_tune pid=1050020)[0m [170]	train-mlogloss:1.10915	validation-mlogloss:1.10276
[36m(train_xgb_ray_tune pid=1050012)[0m [257]	train-mlogloss:0.79638	validation-mlogloss:0.79312
[36m(train_xgb_ray_tune pid=1050008)[0m [262]	train-mlogloss:1.13474	validation-mlogloss:1.12531
[36m(train_xgb_ray_tune pid=1050013)[0m [290]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1049992)[0m [241]	train-mlogloss:0.87689	validation-mlogloss:0.86867
[36m(train_xgb_ray_tune pid=1050006)[0m [168]	train-mlogloss:0.82634	validation-mlogloss:0.82482
[36m(train_xgb_ray_tune pid=1050014)[0m [266]	train-mlogloss:0.78179	validation-mlogloss:0.77958
[36m(train_xgb_ray_tune pid=1050011)[0m [325]	train-mlogloss:1.19550	validation-mlogloss:1.18515
[36m(train_xgb_ray_tune pid=1050007)[0m [196]	train-mlogloss:0.81134	validation-mlogloss:0.80939
[36m(train_xgb_ray_tune pid=1050012)[0m [258]	train-mlogloss:0.79582	validation-mlogloss:0.79255
[36m(train_xgb_ray_tune pid=1050015)[0m [241]	train-mlogloss:0.85658	validation-mlogloss:0.85369
[36m(train_xgb_ray_tune pid=1050004)[0m [164]	train-mlogloss:1.08564	validation-mlogloss:1.07570
[36m(train_xgb_ray_tune pid=1050008)[0m [263]	train-mlogloss:1.13446	validation-mlogloss:1.12502
[36m(train_xgb_ray_tune pid=1050013)[0m [291]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1049992)[0m [242]	train-mlogloss:0.87672	validation-mlogloss:0.86850
[36m(train_xgb_ray_tune pid=1050010)[0m [178]	train-mlogloss:0.77221	validation-mlogloss:0.77765
[36m(train_xgb_ray_tune pid=1050009)[0m [183]	train-mlogloss:0.81017	validation-mlogloss:0.81044
[36m(train_xgb_ray_tune pid=1050014)[0m [267]	train-mlogloss:0.78140	validation-mlogloss:0.77924
[36m(train_xgb_ray_tune pid=1050011)[0m [326]	train-mlogloss:1.19530	validation-mlogloss:1.18494
[36m(train_xgb_ray_tune pid=1050011)[0m [327]	train-mlogloss:1.19510	validation-mlogloss:1.18473
[36m(train_xgb_ray_tune pid=1050018)[0m [244]	train-mlogloss:0.98940	validation-mlogloss:0.98612
[36m(train_xgb_ray_tune pid=1050017)[0m [277]	train-mlogloss:1.09813	validation-mlogloss:1.08755
[36m(train_xgb_ray_tune pid=1050007)[0m [197]	train-mlogloss:0.81070	validation-mlogloss:0.80885
[36m(train_xgb_ray_tune pid=1050020)[0m [171]	train-mlogloss:1.10808	validation-mlogloss:1.10164
[36m(train_xgb_ray_tune pid=1050012)[0m [259]	train-mlogloss:0.79547	validation-mlogloss:0.79209
[36m(train_xgb_ray_tune pid=1050012)[0m [260]	train-mlogloss:0.79525	validation-mlogloss:0.79184
[36m(train_xgb_ray_tune pid=1050015)[0m [242]	train-mlogloss:0.85597	validation-mlogloss:0.85315
[36m(train_xgb_ray_tune pid=1050004)[0m [165]	train-mlogloss:1.08455	validation-mlogloss:1.07458
[36m(train_xgb_ray_tune pid=1050008)[0m [264]	train-mlogloss:1.13418	validation-mlogloss:1.12471
[36m(train_xgb_ray_tune pid=1050013)[0m [292]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1049992)[0m [243]	train-mlogloss:0.87656	validation-mlogloss:0.86830
[36m(train_xgb_ray_tune pid=1050006)[0m [169]	train-mlogloss:0.82520	validation-mlogloss:0.82376
[36m(train_xgb_ray_tune pid=1050009)[0m [184]	train-mlogloss:0.80910	validation-mlogloss:0.80940
[36m(train_xgb_ray_tune pid=1050017)[0m [278]	train-mlogloss:1.09759	validation-mlogloss:1.08702
[36m(train_xgb_ray_tune pid=1049992)[0m [244]	train-mlogloss:0.87639	validation-mlogloss:0.86810
[36m(train_xgb_ray_tune pid=1050018)[0m [245]	train-mlogloss:0.98863	validation-mlogloss:0.98534
[36m(train_xgb_ray_tune pid=1050013)[0m [293]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1050014)[0m [268]	train-mlogloss:0.78094	validation-mlogloss:0.77883
[36m(train_xgb_ray_tune pid=1050011)[0m [328]	train-mlogloss:1.19489	validation-mlogloss:1.18451
[36m(train_xgb_ray_tune pid=1050012)[0m [261]	train-mlogloss:0.79483	validation-mlogloss:0.79146
[36m(train_xgb_ray_tune pid=1050015)[0m [243]	train-mlogloss:0.85527	validation-mlogloss:0.85246
[36m(train_xgb_ray_tune pid=1050008)[0m [265]	train-mlogloss:1.13389	validation-mlogloss:1.12440
[36m(train_xgb_ray_tune pid=1049992)[0m [245]	train-mlogloss:0.87621	validation-mlogloss:0.86789
[36m(train_xgb_ray_tune pid=1050010)[0m [179]	train-mlogloss:0.77112	validation-mlogloss:0.77665
[36m(train_xgb_ray_tune pid=1050009)[0m [185]	train-mlogloss:0.80813	validation-mlogloss:0.80854
[36m(train_xgb_ray_tune pid=1050011)[0m [329]	train-mlogloss:1.19469	validation-mlogloss:1.18429
[36m(train_xgb_ray_tune pid=1050017)[0m [279]	train-mlogloss:1.09707	validation-mlogloss:1.08648
[36m(train_xgb_ray_tune pid=1050017)[0m [280]	train-mlogloss:1.09656	validation-mlogloss:1.08594
[36m(train_xgb_ray_tune pid=1050007)[0m [198]	train-mlogloss:0.80997	validation-mlogloss:0.80816
[36m(train_xgb_ray_tune pid=1050020)[0m [172]	train-mlogloss:1.10698	validation-mlogloss:1.10060
[36m(train_xgb_ray_tune pid=1050012)[0m [262]	train-mlogloss:0.79466	validation-mlogloss:0.79125
[36m(train_xgb_ray_tune pid=1050004)[0m [166]	train-mlogloss:1.08344	validation-mlogloss:1.07345
[36m(train_xgb_ray_tune pid=1050008)[0m [266]	train-mlogloss:1.13361	validation-mlogloss:1.12410
[36m(train_xgb_ray_tune pid=1050013)[0m [294]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1050013)[0m [295]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1049992)[0m [246]	train-mlogloss:0.87606	validation-mlogloss:0.86774
[36m(train_xgb_ray_tune pid=1050006)[0m [170]	train-mlogloss:0.82409	validation-mlogloss:0.82262
[36m(train_xgb_ray_tune pid=1050014)[0m [269]	train-mlogloss:0.78050	validation-mlogloss:0.77841
[36m(train_xgb_ray_tune pid=1050011)[0m [330]	train-mlogloss:1.19447	validation-mlogloss:1.18406
[36m(train_xgb_ray_tune pid=1050018)[0m [246]	train-mlogloss:0.98783	validation-mlogloss:0.98460
[36m(train_xgb_ray_tune pid=1050017)[0m [281]	train-mlogloss:1.09604	validation-mlogloss:1.08540
[36m(train_xgb_ray_tune pid=1050012)[0m [263]	train-mlogloss:0.79418	validation-mlogloss:0.79088
[36m(train_xgb_ray_tune pid=1050015)[0m [244]	train-mlogloss:0.85454	validation-mlogloss:0.85177
[36m(train_xgb_ray_tune pid=1050013)[0m [296]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1050009)[0m [186]	train-mlogloss:0.80704	validation-mlogloss:0.80746
[36m(train_xgb_ray_tune pid=1050020)[0m [173]	train-mlogloss:1.10598	validation-mlogloss:1.09957
[36m(train_xgb_ray_tune pid=1050008)[0m [267]	train-mlogloss:1.13333	validation-mlogloss:1.12380
[36m(train_xgb_ray_tune pid=1050011)[0m [331]	train-mlogloss:1.19427	validation-mlogloss:1.18384
[36m(train_xgb_ray_tune pid=1050017)[0m [282]	train-mlogloss:1.09548	validation-mlogloss:1.08482
[36m(train_xgb_ray_tune pid=1050007)[0m [199]	train-mlogloss:0.80921	validation-mlogloss:0.80754
[36m(train_xgb_ray_tune pid=1050012)[0m [264]	train-mlogloss:0.79366	validation-mlogloss:0.79052
[36m(train_xgb_ray_tune pid=1050013)[0m [297]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1049992)[0m [247]	train-mlogloss:0.87543	validation-mlogloss:0.86711
[36m(train_xgb_ray_tune pid=1050010)[0m [180]	train-mlogloss:0.77007	validation-mlogloss:0.77578
[36m(train_xgb_ray_tune pid=1050014)[0m [270]	train-mlogloss:0.78004	validation-mlogloss:0.77801
[36m(train_xgb_ray_tune pid=1050018)[0m [247]	train-mlogloss:0.98707	validation-mlogloss:0.98383
[36m(train_xgb_ray_tune pid=1050017)[0m [283]	train-mlogloss:1.09498	validation-mlogloss:1.08430
[36m(train_xgb_ray_tune pid=1050004)[0m [167]	train-mlogloss:1.08246	validation-mlogloss:1.07241
[36m(train_xgb_ray_tune pid=1050013)[0m [298]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1050006)[0m [171]	train-mlogloss:0.82308	validation-mlogloss:0.82165
[36m(train_xgb_ray_tune pid=1050011)[0m [332]	train-mlogloss:1.19407	validation-mlogloss:1.18363
[36m(train_xgb_ray_tune pid=1050012)[0m [265]	train-mlogloss:0.79323	validation-mlogloss:0.79010
[36m(train_xgb_ray_tune pid=1050015)[0m [245]	train-mlogloss:0.85386	validation-mlogloss:0.85115
[36m(train_xgb_ray_tune pid=1050008)[0m [268]	train-mlogloss:1.13304	validation-mlogloss:1.12348
[36m(train_xgb_ray_tune pid=1050009)[0m [187]	train-mlogloss:0.80594	validation-mlogloss:0.80645
[36m(train_xgb_ray_tune pid=1050017)[0m [284]	train-mlogloss:1.09446	validation-mlogloss:1.08377
[36m(train_xgb_ray_tune pid=1050013)[0m [299]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1049992)[0m [248]	train-mlogloss:0.87528	validation-mlogloss:0.86693
[36m(train_xgb_ray_tune pid=1050014)[0m [271]	train-mlogloss:0.77963	validation-mlogloss:0.77764
[36m(train_xgb_ray_tune pid=1050011)[0m [333]	train-mlogloss:1.19390	validation-mlogloss:1.18344
[36m(train_xgb_ray_tune pid=1050007)[0m [200]	train-mlogloss:0.80842	validation-mlogloss:0.80673
[36m(train_xgb_ray_tune pid=1050020)[0m [174]	train-mlogloss:1.10491	validation-mlogloss:1.09842
[36m(train_xgb_ray_tune pid=1050013)[0m [300]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1050018)[0m [248]	train-mlogloss:0.98621	validation-mlogloss:0.98297
[36m(train_xgb_ray_tune pid=1050017)[0m [285]	train-mlogloss:1.09392	validation-mlogloss:1.08322
[36m(train_xgb_ray_tune pid=1050012)[0m [266]	train-mlogloss:0.79308	validation-mlogloss:0.78992
[36m(train_xgb_ray_tune pid=1050004)[0m [168]	train-mlogloss:1.08147	validation-mlogloss:1.07137
[36m(train_xgb_ray_tune pid=1050008)[0m [269]	train-mlogloss:1.13275	validation-mlogloss:1.12318
[36m(train_xgb_ray_tune pid=1050010)[0m [181]	train-mlogloss:0.76896	validation-mlogloss:0.77486
[36m(train_xgb_ray_tune pid=1050011)[0m [334]	train-mlogloss:1.19367	validation-mlogloss:1.18321
[36m(train_xgb_ray_tune pid=1050015)[0m [246]	train-mlogloss:0.85315	validation-mlogloss:0.85043
[36m(train_xgb_ray_tune pid=1050013)[0m [301]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1049992)[0m [249]	train-mlogloss:0.87511	validation-mlogloss:0.86673
[36m(train_xgb_ray_tune pid=1050006)[0m [172]	train-mlogloss:0.82192	validation-mlogloss:0.82049
[36m(train_xgb_ray_tune pid=1050009)[0m [188]	train-mlogloss:0.80505	validation-mlogloss:0.80574
[36m(train_xgb_ray_tune pid=1050014)[0m [272]	train-mlogloss:0.77923	validation-mlogloss:0.77715
[36m(train_xgb_ray_tune pid=1050011)[0m [335]	train-mlogloss:1.19347	validation-mlogloss:1.18299
[36m(train_xgb_ray_tune pid=1050017)[0m [286]	train-mlogloss:1.09336	validation-mlogloss:1.08269
[36m(train_xgb_ray_tune pid=1050012)[0m [267]	train-mlogloss:0.79299	validation-mlogloss:0.78981
[36m(train_xgb_ray_tune pid=1050008)[0m [270]	train-mlogloss:1.13247	validation-mlogloss:1.12288
[36m(train_xgb_ray_tune pid=1050020)[0m [175]	train-mlogloss:1.10391	validation-mlogloss:1.09742
[36m(train_xgb_ray_tune pid=1050013)[0m [302]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1050011)[0m [336]	train-mlogloss:1.19329	validation-mlogloss:1.18281
[36m(train_xgb_ray_tune pid=1050018)[0m [249]	train-mlogloss:0.98543	validation-mlogloss:0.98218
[36m(train_xgb_ray_tune pid=1050017)[0m [287]	train-mlogloss:1.09281	validation-mlogloss:1.08212
[36m(train_xgb_ray_tune pid=1050007)[0m [201]	train-mlogloss:0.80764	validation-mlogloss:0.80612
[36m(train_xgb_ray_tune pid=1050015)[0m [247]	train-mlogloss:0.85233	validation-mlogloss:0.84959
[36m(train_xgb_ray_tune pid=1050004)[0m [169]	train-mlogloss:1.08039	validation-mlogloss:1.07027
[36m(train_xgb_ray_tune pid=1050013)[0m [303]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1049992)[0m [250]	train-mlogloss:0.87495	validation-mlogloss:0.86657
[36m(train_xgb_ray_tune pid=1050010)[0m [182]	train-mlogloss:0.76811	validation-mlogloss:0.77406
[36m(train_xgb_ray_tune pid=1050009)[0m [189]	train-mlogloss:0.80410	validation-mlogloss:0.80473
[36m(train_xgb_ray_tune pid=1050014)[0m [273]	train-mlogloss:0.77869	validation-mlogloss:0.77663
[36m(train_xgb_ray_tune pid=1050017)[0m [288]	train-mlogloss:1.09228	validation-mlogloss:1.08158
[36m(train_xgb_ray_tune pid=1050012)[0m [268]	train-mlogloss:0.79250	validation-mlogloss:0.78931
[36m(train_xgb_ray_tune pid=1050008)[0m [271]	train-mlogloss:1.13220	validation-mlogloss:1.12258
[36m(train_xgb_ray_tune pid=1050011)[0m [337]	train-mlogloss:1.19312	validation-mlogloss:1.18262
[36m(train_xgb_ray_tune pid=1050013)[0m [304]	train-mlogloss:0.99240	validation-mlogloss:0.98053
[36m(train_xgb_ray_tune pid=1050006)[0m [173]	train-mlogloss:0.82086	validation-mlogloss:0.81962
[36m(train_xgb_ray_tune pid=1050018)[0m [250]	train-mlogloss:0.98466	validation-mlogloss:0.98148
[36m(train_xgb_ray_tune pid=1050017)[0m [289]	train-mlogloss:1.09175	validation-mlogloss:1.08103
[36m(train_xgb_ray_tune pid=1050020)[0m [176]	train-mlogloss:1.10287	validation-mlogloss:1.09634
[36m(train_xgb_ray_tune pid=1050015)[0m [248]	train-mlogloss:0.85162	validation-mlogloss:0.84891
[36m(train_xgb_ray_tune pid=1049992)[0m [251]	train-mlogloss:0.87480	validation-mlogloss:0.86639
[36m(train_xgb_ray_tune pid=1050014)[0m [274]	train-mlogloss:0.77836	validation-mlogloss:0.77629
[36m(train_xgb_ray_tune pid=1050011)[0m [338]	train-mlogloss:1.19294	validation-mlogloss:1.18243
[36m(train_xgb_ray_tune pid=1050007)[0m [202]	train-mlogloss:0.80700	validation-mlogloss:0.80554
[36m(train_xgb_ray_tune pid=1050012)[0m [269]	train-mlogloss:0.79211	validation-mlogloss:0.78894
[36m(train_xgb_ray_tune pid=1050004)[0m [170]	train-mlogloss:1.07931	validation-mlogloss:1.06917
[36m(train_xgb_ray_tune pid=1050008)[0m [272]	train-mlogloss:1.13193	validation-mlogloss:1.12229
[36m(train_xgb_ray_tune pid=1050010)[0m [183]	train-mlogloss:0.76716	validation-mlogloss:0.77314
[36m(train_xgb_ray_tune pid=1050009)[0m [190]	train-mlogloss:0.80312	validation-mlogloss:0.80386
[36m(train_xgb_ray_tune pid=1050011)[0m [339]	train-mlogloss:1.19275	validation-mlogloss:1.18223
[36m(train_xgb_ray_tune pid=1050017)[0m [290]	train-mlogloss:1.09119	validation-mlogloss:1.08045
[36m(train_xgb_ray_tune pid=1049992)[0m [252]	train-mlogloss:0.87465	validation-mlogloss:0.86624
[36m(train_xgb_ray_tune pid=1050008)[0m [273]	train-mlogloss:1.13165	validation-mlogloss:1.12199
[36m(train_xgb_ray_tune pid=1050006)[0m [174]	train-mlogloss:0.81987	validation-mlogloss:0.81851
[36m(train_xgb_ray_tune pid=1050014)[0m [275]	train-mlogloss:0.77795	validation-mlogloss:0.77595
[36m(train_xgb_ray_tune pid=1050017)[0m [291]	train-mlogloss:1.09066	validation-mlogloss:1.07988
[36m(train_xgb_ray_tune pid=1050007)[0m [203]	train-mlogloss:0.80642	validation-mlogloss:0.80492
[36m(train_xgb_ray_tune pid=1050020)[0m [177]	train-mlogloss:1.10181	validation-mlogloss:1.09522
[36m(train_xgb_ray_tune pid=1050012)[0m [270]	train-mlogloss:0.79196	validation-mlogloss:0.78878
[36m(train_xgb_ray_tune pid=1050015)[0m [249]	train-mlogloss:0.85109	validation-mlogloss:0.84834
[36m(train_xgb_ray_tune pid=1050009)[0m [191]	train-mlogloss:0.80227	validation-mlogloss:0.80316
[36m(train_xgb_ray_tune pid=1050011)[0m [340]	train-mlogloss:1.19256	validation-mlogloss:1.18203
[36m(train_xgb_ray_tune pid=1050017)[0m [292]	train-mlogloss:1.09016	validation-mlogloss:1.07936
[36m(train_xgb_ray_tune pid=1050012)[0m [271]	train-mlogloss:0.79187	validation-mlogloss:0.78872
[36m(train_xgb_ray_tune pid=1050004)[0m [171]	train-mlogloss:1.07826	validation-mlogloss:1.06813
[36m(train_xgb_ray_tune pid=1050008)[0m [274]	train-mlogloss:1.13137	validation-mlogloss:1.12171
[36m(train_xgb_ray_tune pid=1049992)[0m [253]	train-mlogloss:0.87449	validation-mlogloss:0.86605
[36m(train_xgb_ray_tune pid=1050010)[0m [184]	train-mlogloss:0.76622	validation-mlogloss:0.77236
[36m(train_xgb_ray_tune pid=1050014)[0m [276]	train-mlogloss:0.77751	validation-mlogloss:0.77558
[36m(train_xgb_ray_tune pid=1050011)[0m [341]	train-mlogloss:1.19240	validation-mlogloss:1.18186
[36m(train_xgb_ray_tune pid=1050015)[0m [250]	train-mlogloss:0.85042	validation-mlogloss:0.84768
[36m(train_xgb_ray_tune pid=1050017)[0m [293]	train-mlogloss:1.08963	validation-mlogloss:1.07882
[36m(train_xgb_ray_tune pid=1050007)[0m [204]	train-mlogloss:0.80574	validation-mlogloss:0.80424
[36m(train_xgb_ray_tune pid=1050006)[0m [175]	train-mlogloss:0.81885	validation-mlogloss:0.81750
[36m(train_xgb_ray_tune pid=1050009)[0m [192]	train-mlogloss:0.80135	validation-mlogloss:0.80234
[36m(train_xgb_ray_tune pid=1050011)[0m [342]	train-mlogloss:1.19222	validation-mlogloss:1.18167
[36m(train_xgb_ray_tune pid=1050020)[0m [178]	train-mlogloss:1.10077	validation-mlogloss:1.09413
[36m(train_xgb_ray_tune pid=1050012)[0m [272]	train-mlogloss:0.79164	validation-mlogloss:0.78851
[36m(train_xgb_ray_tune pid=1050008)[0m [275]	train-mlogloss:1.13110	validation-mlogloss:1.12142
[36m(train_xgb_ray_tune pid=1049992)[0m [254]	train-mlogloss:0.87434	validation-mlogloss:0.86587
[36m(train_xgb_ray_tune pid=1050014)[0m [277]	train-mlogloss:0.77715	validation-mlogloss:0.77527
[36m(train_xgb_ray_tune pid=1050017)[0m [294]	train-mlogloss:1.08914	validation-mlogloss:1.07838
[36m(train_xgb_ray_tune pid=1050011)[0m [343]	train-mlogloss:1.19204	validation-mlogloss:1.18147
[36m(train_xgb_ray_tune pid=1050017)[0m [295]	train-mlogloss:1.08865	validation-mlogloss:1.07789
[36m(train_xgb_ray_tune pid=1050015)[0m [251]	train-mlogloss:0.84976	validation-mlogloss:0.84702
[36m(train_xgb_ray_tune pid=1050004)[0m [172]	train-mlogloss:1.07720	validation-mlogloss:1.06701
[36m(train_xgb_ray_tune pid=1050008)[0m [276]	train-mlogloss:1.13083	validation-mlogloss:1.12114
[36m(train_xgb_ray_tune pid=1049992)[0m [255]	train-mlogloss:0.87417	validation-mlogloss:0.86567
[36m(train_xgb_ray_tune pid=1050010)[0m [185]	train-mlogloss:0.76533	validation-mlogloss:0.77166
[36m(train_xgb_ray_tune pid=1050006)[0m [176]	train-mlogloss:0.81781	validation-mlogloss:0.81648
[36m(train_xgb_ray_tune pid=1050009)[0m [193]	train-mlogloss:0.80034	validation-mlogloss:0.80138
[36m(train_xgb_ray_tune pid=1050014)[0m [278]	train-mlogloss:0.77656	validation-mlogloss:0.77463
[36m(train_xgb_ray_tune pid=1050011)[0m [344]	train-mlogloss:1.19188	validation-mlogloss:1.18130
[36m(train_xgb_ray_tune pid=1050017)[0m [296]	train-mlogloss:1.08813	validation-mlogloss:1.07736
[36m(train_xgb_ray_tune pid=1050007)[0m [205]	train-mlogloss:0.80494	validation-mlogloss:0.80343
[36m(train_xgb_ray_tune pid=1050020)[0m [179]	train-mlogloss:1.09968	validation-mlogloss:1.09305
[36m(train_xgb_ray_tune pid=1050012)[0m [273]	train-mlogloss:0.79155	validation-mlogloss:0.78844
[36m(train_xgb_ray_tune pid=1050012)[0m [274]	train-mlogloss:0.79124	validation-mlogloss:0.78812
[36m(train_xgb_ray_tune pid=1050015)[0m [252]	train-mlogloss:0.84924	validation-mlogloss:0.84648
[36m(train_xgb_ray_tune pid=1049992)[0m [256]	train-mlogloss:0.87402	validation-mlogloss:0.86553
[36m(train_xgb_ray_tune pid=1050011)[0m [345]	train-mlogloss:1.19171	validation-mlogloss:1.18111
[36m(train_xgb_ray_tune pid=1050017)[0m [297]	train-mlogloss:1.08762	validation-mlogloss:1.07683
[36m(train_xgb_ray_tune pid=1050007)[0m [206]	train-mlogloss:0.80427	validation-mlogloss:0.80285
[36m(train_xgb_ray_tune pid=1050004)[0m [173]	train-mlogloss:1.07613	validation-mlogloss:1.06587
[36m(train_xgb_ray_tune pid=1050008)[0m [277]	train-mlogloss:1.13056	validation-mlogloss:1.12085
[36m(train_xgb_ray_tune pid=1050010)[0m [186]	train-mlogloss:0.76444	validation-mlogloss:0.77089
[36m(train_xgb_ray_tune pid=1050009)[0m [194]	train-mlogloss:0.79945	validation-mlogloss:0.80056
[36m(train_xgb_ray_tune pid=1050014)[0m [279]	train-mlogloss:0.77623	validation-mlogloss:0.77440
[36m(train_xgb_ray_tune pid=1050011)[0m [346]	train-mlogloss:1.19153	validation-mlogloss:1.18092
[36m(train_xgb_ray_tune pid=1050017)[0m [298]	train-mlogloss:1.08710	validation-mlogloss:1.07632
[36m(train_xgb_ray_tune pid=1050012)[0m [275]	train-mlogloss:0.79084	validation-mlogloss:0.78776
[36m(train_xgb_ray_tune pid=1049992)[0m [257]	train-mlogloss:0.87386	validation-mlogloss:0.86533
[36m(train_xgb_ray_tune pid=1050020)[0m [180]	train-mlogloss:1.09869	validation-mlogloss:1.09206
[36m(train_xgb_ray_tune pid=1050015)[0m [253]	train-mlogloss:0.84861	validation-mlogloss:0.84589
[36m(train_xgb_ray_tune pid=1050008)[0m [278]	train-mlogloss:1.13029	validation-mlogloss:1.12057
[36m(train_xgb_ray_tune pid=1050006)[0m [177]	train-mlogloss:0.81684	validation-mlogloss:0.81554
[36m(train_xgb_ray_tune pid=1050009)[0m [195]	train-mlogloss:0.79852	validation-mlogloss:0.79965
[36m(train_xgb_ray_tune pid=1050014)[0m [280]	train-mlogloss:0.77593	validation-mlogloss:0.77413
[36m(train_xgb_ray_tune pid=1050011)[0m [347]	train-mlogloss:1.19134	validation-mlogloss:1.18072
[36m(train_xgb_ray_tune pid=1050017)[0m [299]	train-mlogloss:1.08658	validation-mlogloss:1.07578
[36m(train_xgb_ray_tune pid=1050007)[0m [207]	train-mlogloss:0.80361	validation-mlogloss:0.80211
[36m(train_xgb_ray_tune pid=1050004)[0m [174]	train-mlogloss:1.07507	validation-mlogloss:1.06479

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:08. Total running time: 12s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             9.44722 │
│ time_total_s                 9.44722 │
│ training_iteration                 1 │
│ validation_accuracy          0.65063 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1049992)[0m [258]	train-mlogloss:0.87371	validation-mlogloss:0.86515
[36m(train_xgb_ray_tune pid=1050011)[0m [348]	train-mlogloss:1.19114	validation-mlogloss:1.18051
[36m(train_xgb_ray_tune pid=1050017)[0m [300]	train-mlogloss:1.08607	validation-mlogloss:1.07527
[36m(train_xgb_ray_tune pid=1050012)[0m [276]	train-mlogloss:0.79069	validation-mlogloss:0.78759
[36m(train_xgb_ray_tune pid=1050008)[0m [279]	train-mlogloss:1.13004	validation-mlogloss:1.12029
[36m(train_xgb_ray_tune pid=1050010)[0m [187]	train-mlogloss:0.76336	validation-mlogloss:0.76995
[36m(train_xgb_ray_tune pid=1050014)[0m [281]	train-mlogloss:0.77558	validation-mlogloss:0.77372
[36m(train_xgb_ray_tune pid=1050020)[0m [181]	train-mlogloss:1.09765	validation-mlogloss:1.09098

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:08. Total running time: 12s
[36m(train_xgb_ray_tune pid=1050015)[0m [254]	train-mlogloss:0.84792	validation-mlogloss:0.84515
[36m(train_xgb_ray_tune pid=1050011)[0m [349]	train-mlogloss:1.19096	validation-mlogloss:1.18032
[36m(train_xgb_ray_tune pid=1050006)[0m [178]	train-mlogloss:0.81577	validation-mlogloss:0.81452
[36m(train_xgb_ray_tune pid=1050009)[0m [196]	train-mlogloss:0.79768	validation-mlogloss:0.79901
[36m(train_xgb_ray_tune pid=1050017)[0m [301]	train-mlogloss:1.08559	validation-mlogloss:1.07476
[36m(train_xgb_ray_tune pid=1050007)[0m [208]	train-mlogloss:0.80276	validation-mlogloss:0.80139
[36m(train_xgb_ray_tune pid=1050012)[0m [277]	train-mlogloss:0.79061	validation-mlogloss:0.78754
[36m(train_xgb_ray_tune pid=1050008)[0m [280]	train-mlogloss:1.12978	validation-mlogloss:1.12001
[36m(train_xgb_ray_tune pid=1049992)[0m [259]	train-mlogloss:0.87356	validation-mlogloss:0.86504
[36m(train_xgb_ray_tune pid=1050010)[0m [188]	train-mlogloss:0.76240	validation-mlogloss:0.76917
[36m(train_xgb_ray_tune pid=1050014)[0m [282]	train-mlogloss:0.77521	validation-mlogloss:0.77331
[36m(train_xgb_ray_tune pid=1050011)[0m [350]	train-mlogloss:1.19077	validation-mlogloss:1.18012

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:08. Total running time: 12s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             9.43546 │
│ time_total_s                 9.43546 │
│ training_iteration                 1 │
│ validation_accuracy          0.66046 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1050017)[0m [302]	train-mlogloss:1.08508	validation-mlogloss:1.07423
[36m(train_xgb_ray_tune pid=1050020)[0m [182]	train-mlogloss:1.09664	validation-mlogloss:1.08995
[36m(train_xgb_ray_tune pid=1050015)[0m [255]	train-mlogloss:0.84716	validation-mlogloss:0.84434
[36m(train_xgb_ray_tune pid=1050004)[0m [175]	train-mlogloss:1.07403	validation-mlogloss:1.06370
[36m(train_xgb_ray_tune pid=1049992)[0m [260]	train-mlogloss:0.87340	validation-mlogloss:0.86492
[36m(train_xgb_ray_tune pid=1050011)[0m [351]	train-mlogloss:1.19058	validation-mlogloss:1.17991
[36m(train_xgb_ray_tune pid=1050012)[0m [278]	train-mlogloss:0.79046	validation-mlogloss:0.78740

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:08. Total running time: 12s
[36m(train_xgb_ray_tune pid=1050008)[0m [281]	train-mlogloss:1.12950	validation-mlogloss:1.11972
[36m(train_xgb_ray_tune pid=1050009)[0m [197]	train-mlogloss:0.79670	validation-mlogloss:0.79812
[36m(train_xgb_ray_tune pid=1050014)[0m [283]	train-mlogloss:0.77474	validation-mlogloss:0.77296
[36m(train_xgb_ray_tune pid=1050017)[0m [303]	train-mlogloss:1.08458	validation-mlogloss:1.07369
[36m(train_xgb_ray_tune pid=1050007)[0m [209]	train-mlogloss:0.80230	validation-mlogloss:0.80101
[36m(train_xgb_ray_tune pid=1050020)[0m [183]	train-mlogloss:1.09562	validation-mlogloss:1.08891
[36m(train_xgb_ray_tune pid=1050010)[0m [189]	train-mlogloss:0.76149	validation-mlogloss:0.76833
[36m(train_xgb_ray_tune pid=1050006)[0m [179]	train-mlogloss:0.81486	validation-mlogloss:0.81370
[36m(train_xgb_ray_tune pid=1050011)[0m [352]	train-mlogloss:1.19041	validation-mlogloss:1.17974
[36m(train_xgb_ray_tune pid=1050015)[0m [256]	train-mlogloss:0.84660	validation-mlogloss:0.84367
[36m(train_xgb_ray_tune pid=1050004)[0m [176]	train-mlogloss:1.07318	validation-mlogloss:1.06286
[36m(train_xgb_ray_tune pid=1049992)[0m [261]	train-mlogloss:0.87325	validation-mlogloss:0.86481
[36m(train_xgb_ray_tune pid=1050017)[0m [304]	train-mlogloss:1.08409	validation-mlogloss:1.07322
[36m(train_xgb_ray_tune pid=1050012)[0m [279]	train-mlogloss:0.79031	validation-mlogloss:0.78724
[36m(train_xgb_ray_tune pid=1050008)[0m [282]	train-mlogloss:1.12925	validation-mlogloss:1.11945
[36m(train_xgb_ray_tune pid=1050009)[0m [198]	train-mlogloss:0.79577	validation-mlogloss:0.79743
[36m(train_xgb_ray_tune pid=1050014)[0m [284]	train-mlogloss:0.77434	validation-mlogloss:0.77254
[36m(train_xgb_ray_tune pid=1050011)[0m [353]	train-mlogloss:1.19025	validation-mlogloss:1.17956
[36m(train_xgb_ray_tune pid=1050017)[0m [305]	train-mlogloss:1.08365	validation-mlogloss:1.07276
[36m(train_xgb_ray_tune pid=1050007)[0m [210]	train-mlogloss:0.80156	validation-mlogloss:0.80033
[36m(train_xgb_ray_tune pid=1050020)[0m [184]	train-mlogloss:1.09458	validation-mlogloss:1.08785
[36m(train_xgb_ray_tune pid=1050012)[0m [280]	train-mlogloss:0.79005	validation-mlogloss:0.78709
[36m(train_xgb_ray_tune pid=1050015)[0m [257]	train-mlogloss:0.84592	validation-mlogloss:0.84305
[36m(train_xgb_ray_tune pid=1049992)[0m [262]	train-mlogloss:0.87309	validation-mlogloss:0.86464
[36m(train_xgb_ray_tune pid=1050010)[0m [190]	train-mlogloss:0.76046	validation-mlogloss:0.76748
[36m(train_xgb_ray_tune pid=1050006)[0m [180]	train-mlogloss:0.81388	validation-mlogloss:0.81282
[36m(train_xgb_ray_tune pid=1050014)[0m [285]	train-mlogloss:0.77373	validation-mlogloss:0.77199
[36m(train_xgb_ray_tune pid=1050011)[0m [354]	train-mlogloss:1.19005	validation-mlogloss:1.17936
[36m(train_xgb_ray_tune pid=1050017)[0m [306]	train-mlogloss:1.08323	validation-mlogloss:1.07234
[36m(train_xgb_ray_tune pid=1050007)[0m [211]	train-mlogloss:0.80089	validation-mlogloss:0.79970
[36m(train_xgb_ray_tune pid=1050015)[0m [258]	train-mlogloss:0.84524	validation-mlogloss:0.84243
[36m(train_xgb_ray_tune pid=1050004)[0m [177]	train-mlogloss:1.07216	validation-mlogloss:1.06178
[36m(train_xgb_ray_tune pid=1050008)[0m [283]	train-mlogloss:1.12899	validation-mlogloss:1.11917
[36m(train_xgb_ray_tune pid=1050009)[0m [199]	train-mlogloss:0.79474	validation-mlogloss:0.79651
[36m(train_xgb_ray_tune pid=1049992)[0m [263]	train-mlogloss:0.87269	validation-mlogloss:0.86425
[36m(train_xgb_ray_tune pid=1050017)[0m [307]	train-mlogloss:1.08273	validation-mlogloss:1.07183
[36m(train_xgb_ray_tune pid=1050020)[0m [185]	train-mlogloss:1.09356	validation-mlogloss:1.08679
[36m(train_xgb_ray_tune pid=1050012)[0m [281]	train-mlogloss:0.78973	validation-mlogloss:0.78673
[36m(train_xgb_ray_tune pid=1050015)[0m [259]	train-mlogloss:0.84453	validation-mlogloss:0.84178
[36m(train_xgb_ray_tune pid=1050008)[0m [284]	train-mlogloss:1.12867	validation-mlogloss:1.11882
[36m(train_xgb_ray_tune pid=1050014)[0m [286]	train-mlogloss:0.77330	validation-mlogloss:0.77160
[36m(train_xgb_ray_tune pid=1050011)[0m [355]	train-mlogloss:1.18990	validation-mlogloss:1.17920
[36m(train_xgb_ray_tune pid=1050007)[0m [212]	train-mlogloss:0.80032	validation-mlogloss:0.79908
[36m(train_xgb_ray_tune pid=1050015)[0m [260]	train-mlogloss:0.84388	validation-mlogloss:0.84115
[36m(train_xgb_ray_tune pid=1050004)[0m [178]	train-mlogloss:1.07115	validation-mlogloss:1.06074
[36m(train_xgb_ray_tune pid=1049992)[0m [264]	train-mlogloss:0.87253	validation-mlogloss:0.86406
[36m(train_xgb_ray_tune pid=1050010)[0m [191]	train-mlogloss:0.75945	validation-mlogloss:0.76675
[36m(train_xgb_ray_tune pid=1050006)[0m [181]	train-mlogloss:0.81271	validation-mlogloss:0.81178
[36m(train_xgb_ray_tune pid=1050009)[0m [200]	train-mlogloss:0.79386	validation-mlogloss:0.79563
[36m(train_xgb_ray_tune pid=1050011)[0m [356]	train-mlogloss:1.18970	validation-mlogloss:1.17900
[36m(train_xgb_ray_tune pid=1050017)[0m [308]	train-mlogloss:1.08224	validation-mlogloss:1.07132
[36m(train_xgb_ray_tune pid=1050020)[0m [186]	train-mlogloss:1.09261	validation-mlogloss:1.08582
[36m(train_xgb_ray_tune pid=1050012)[0m [282]	train-mlogloss:0.78945	validation-mlogloss:0.78652
[36m(train_xgb_ray_tune pid=1050008)[0m [285]	train-mlogloss:1.12841	validation-mlogloss:1.11855
[36m(train_xgb_ray_tune pid=1050014)[0m [287]	train-mlogloss:0.77305	validation-mlogloss:0.77133
[36m(train_xgb_ray_tune pid=1050011)[0m [357]	train-mlogloss:1.18951	validation-mlogloss:1.17879
[36m(train_xgb_ray_tune pid=1050017)[0m [309]	train-mlogloss:1.08180	validation-mlogloss:1.07091
[36m(train_xgb_ray_tune pid=1050007)[0m [213]	train-mlogloss:0.79971	validation-mlogloss:0.79844
[36m(train_xgb_ray_tune pid=1050020)[0m [187]	train-mlogloss:1.09162	validation-mlogloss:1.08477
[36m(train_xgb_ray_tune pid=1050015)[0m [261]	train-mlogloss:0.84318	validation-mlogloss:0.84052
[36m(train_xgb_ray_tune pid=1049992)[0m [265]	train-mlogloss:0.87239	validation-mlogloss:0.86396
[36m(train_xgb_ray_tune pid=1050009)[0m [201]	train-mlogloss:0.79289	validation-mlogloss:0.79469
[36m(train_xgb_ray_tune pid=1050011)[0m [358]	train-mlogloss:1.18951	validation-mlogloss:1.17879
[36m(train_xgb_ray_tune pid=1050017)[0m [310]	train-mlogloss:1.08139	validation-mlogloss:1.07048
[36m(train_xgb_ray_tune pid=1050004)[0m [179]	train-mlogloss:1.07008	validation-mlogloss:1.05966
[36m(train_xgb_ray_tune pid=1050008)[0m [286]	train-mlogloss:1.12817	validation-mlogloss:1.11829
[36m(train_xgb_ray_tune pid=1050010)[0m [192]	train-mlogloss:0.75875	validation-mlogloss:0.76615
[36m(train_xgb_ray_tune pid=1050014)[0m [288]	train-mlogloss:0.77265	validation-mlogloss:0.77081
[36m(train_xgb_ray_tune pid=1050011)[0m [359]	train-mlogloss:1.18934	validation-mlogloss:1.17860
[36m(train_xgb_ray_tune pid=1050015)[0m [262]	train-mlogloss:0.84251	validation-mlogloss:0.83983
[36m(train_xgb_ray_tune pid=1050006)[0m [182]	train-mlogloss:0.81160	validation-mlogloss:0.81082
[36m(train_xgb_ray_tune pid=1050007)[0m [214]	train-mlogloss:0.79905	validation-mlogloss:0.79775
[36m(train_xgb_ray_tune pid=1050020)[0m [188]	train-mlogloss:1.09064	validation-mlogloss:1.08372
[36m(train_xgb_ray_tune pid=1050012)[0m [283]	train-mlogloss:0.78931	validation-mlogloss:0.78633
[36m(train_xgb_ray_tune pid=1049992)[0m [266]	train-mlogloss:0.87224	validation-mlogloss:0.86387
[36m(train_xgb_ray_tune pid=1050009)[0m [202]	train-mlogloss:0.79190	validation-mlogloss:0.79376
[36m(train_xgb_ray_tune pid=1050011)[0m [360]	train-mlogloss:1.18916	validation-mlogloss:1.17842
[36m(train_xgb_ray_tune pid=1050017)[0m [311]	train-mlogloss:1.08089	validation-mlogloss:1.06998
[36m(train_xgb_ray_tune pid=1050008)[0m [287]	train-mlogloss:1.12791	validation-mlogloss:1.11801
[36m(train_xgb_ray_tune pid=1050014)[0m [289]	train-mlogloss:0.77229	validation-mlogloss:0.77048
[36m(train_xgb_ray_tune pid=1050017)[0m [312]	train-mlogloss:1.08046	validation-mlogloss:1.06955
[36m(train_xgb_ray_tune pid=1050020)[0m [189]	train-mlogloss:1.08963	validation-mlogloss:1.08270
[36m(train_xgb_ray_tune pid=1050012)[0m [284]	train-mlogloss:0.78893	validation-mlogloss:0.78600
[36m(train_xgb_ray_tune pid=1050015)[0m [263]	train-mlogloss:0.84187	validation-mlogloss:0.83930
[36m(train_xgb_ray_tune pid=1049992)[0m [267]	train-mlogloss:0.87210	validation-mlogloss:0.86371
[36m(train_xgb_ray_tune pid=1050011)[0m [361]	train-mlogloss:1.18898	validation-mlogloss:1.17823
[36m(train_xgb_ray_tune pid=1050007)[0m [215]	train-mlogloss:0.79843	validation-mlogloss:0.79708
[36m(train_xgb_ray_tune pid=1050004)[0m [180]	train-mlogloss:1.06907	validation-mlogloss:1.05866
[36m(train_xgb_ray_tune pid=1050008)[0m [288]	train-mlogloss:1.12766	validation-mlogloss:1.11775
[36m(train_xgb_ray_tune pid=1050010)[0m [193]	train-mlogloss:0.75787	validation-mlogloss:0.76538
[36m(train_xgb_ray_tune pid=1050009)[0m [203]	train-mlogloss:0.79100	validation-mlogloss:0.79280
[36m(train_xgb_ray_tune pid=1050014)[0m [290]	train-mlogloss:0.77181	validation-mlogloss:0.77003
[36m(train_xgb_ray_tune pid=1050011)[0m [362]	train-mlogloss:1.18882	validation-mlogloss:1.17807
[36m(train_xgb_ray_tune pid=1050017)[0m [313]	train-mlogloss:1.07996	validation-mlogloss:1.06903
[36m(train_xgb_ray_tune pid=1050012)[0m [285]	train-mlogloss:0.78885	validation-mlogloss:0.78591
[36m(train_xgb_ray_tune pid=1050015)[0m [264]	train-mlogloss:0.84122	validation-mlogloss:0.83855
[36m(train_xgb_ray_tune pid=1050006)[0m [183]	train-mlogloss:0.81065	validation-mlogloss:0.81001
[36m(train_xgb_ray_tune pid=1050007)[0m [216]	train-mlogloss:0.79804	validation-mlogloss:0.79667
[36m(train_xgb_ray_tune pid=1050011)[0m [363]	train-mlogloss:1.18882	validation-mlogloss:1.17807
[36m(train_xgb_ray_tune pid=1050017)[0m [314]	train-mlogloss:1.07948	validation-mlogloss:1.06855
[36m(train_xgb_ray_tune pid=1050020)[0m [190]	train-mlogloss:1.08855	validation-mlogloss:1.08161
[36m(train_xgb_ray_tune pid=1050012)[0m [286]	train-mlogloss:0.78870	validation-mlogloss:0.78572
[36m(train_xgb_ray_tune pid=1050008)[0m [289]	train-mlogloss:1.12735	validation-mlogloss:1.11742
[36m(train_xgb_ray_tune pid=1049992)[0m [268]	train-mlogloss:0.87196	validation-mlogloss:0.86361
[36m(train_xgb_ray_tune pid=1050009)[0m [204]	train-mlogloss:0.79015	validation-mlogloss:0.79202
[36m(train_xgb_ray_tune pid=1050014)[0m [291]	train-mlogloss:0.77146	validation-mlogloss:0.76974
[36m(train_xgb_ray_tune pid=1050011)[0m [364]	train-mlogloss:1.18864	validation-mlogloss:1.17787
[36m(train_xgb_ray_tune pid=1050007)[0m [217]	train-mlogloss:0.79743	validation-mlogloss:0.79613
[36m(train_xgb_ray_tune pid=1050015)[0m [265]	train-mlogloss:0.84066	validation-mlogloss:0.83800
[36m(train_xgb_ray_tune pid=1050004)[0m [181]	train-mlogloss:1.06813	validation-mlogloss:1.05770
[36m(train_xgb_ray_tune pid=1050017)[0m [315]	train-mlogloss:1.07906	validation-mlogloss:1.06811
[36m(train_xgb_ray_tune pid=1050010)[0m [194]	train-mlogloss:0.75700	validation-mlogloss:0.76482
[36m(train_xgb_ray_tune pid=1050020)[0m [191]	train-mlogloss:1.08762	validation-mlogloss:1.08067
[36m(train_xgb_ray_tune pid=1050012)[0m [287]	train-mlogloss:0.78863	validation-mlogloss:0.78565
[36m(train_xgb_ray_tune pid=1050015)[0m [266]	train-mlogloss:0.83997	validation-mlogloss:0.83729
[36m(train_xgb_ray_tune pid=1050008)[0m [290]	train-mlogloss:1.12710	validation-mlogloss:1.11715
[36m(train_xgb_ray_tune pid=1049992)[0m [269]	train-mlogloss:0.87181	validation-mlogloss:0.86342
[36m(train_xgb_ray_tune pid=1050006)[0m [184]	train-mlogloss:0.80982	validation-mlogloss:0.80919
[36m(train_xgb_ray_tune pid=1050014)[0m [292]	train-mlogloss:0.77110	validation-mlogloss:0.76949
[36m(train_xgb_ray_tune pid=1050011)[0m [365]	train-mlogloss:1.18848	validation-mlogloss:1.17770
[36m(train_xgb_ray_tune pid=1050017)[0m [316]	train-mlogloss:1.07861	validation-mlogloss:1.06765
[36m(train_xgb_ray_tune pid=1050007)[0m [218]	train-mlogloss:0.79696	validation-mlogloss:0.79562
[36m(train_xgb_ray_tune pid=1050009)[0m [205]	train-mlogloss:0.78928	validation-mlogloss:0.79111
[36m(train_xgb_ray_tune pid=1050011)[0m [366]	train-mlogloss:1.18831	validation-mlogloss:1.17752
[36m(train_xgb_ray_tune pid=1050012)[0m [288]	train-mlogloss:0.78843	validation-mlogloss:0.78544
[36m(train_xgb_ray_tune pid=1050015)[0m [267]	train-mlogloss:0.83938	validation-mlogloss:0.83656
[36m(train_xgb_ray_tune pid=1050004)[0m [182]	train-mlogloss:1.06727	validation-mlogloss:1.05684
[36m(train_xgb_ray_tune pid=1049992)[0m [270]	train-mlogloss:0.87167	validation-mlogloss:0.86331
[36m(train_xgb_ray_tune pid=1050017)[0m [317]	train-mlogloss:1.07819	validation-mlogloss:1.06723
[36m(train_xgb_ray_tune pid=1050020)[0m [192]	train-mlogloss:1.08663	validation-mlogloss:1.07967
[36m(train_xgb_ray_tune pid=1050008)[0m [291]	train-mlogloss:1.12685	validation-mlogloss:1.11688
[36m(train_xgb_ray_tune pid=1050014)[0m [293]	train-mlogloss:0.77067	validation-mlogloss:0.76907
[36m(train_xgb_ray_tune pid=1050011)[0m [367]	train-mlogloss:1.18815	validation-mlogloss:1.17734
[36m(train_xgb_ray_tune pid=1050007)[0m [219]	train-mlogloss:0.79634	validation-mlogloss:0.79510
[36m(train_xgb_ray_tune pid=1050012)[0m [289]	train-mlogloss:0.78819	validation-mlogloss:0.78530
[36m(train_xgb_ray_tune pid=1050015)[0m [268]	train-mlogloss:0.83878	validation-mlogloss:0.83596
[36m(train_xgb_ray_tune pid=1050010)[0m [195]	train-mlogloss:0.75603	validation-mlogloss:0.76392
[36m(train_xgb_ray_tune pid=1050017)[0m [318]	train-mlogloss:1.07776	validation-mlogloss:1.06680
[36m(train_xgb_ray_tune pid=1050020)[0m [193]	train-mlogloss:1.08564	validation-mlogloss:1.07861
[36m(train_xgb_ray_tune pid=1050009)[0m [206]	train-mlogloss:0.78850	validation-mlogloss:0.79053
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[36m(train_xgb_ray_tune pid=1049992)[0m [357]	train-mlogloss:0.86423	validation-mlogloss:0.85583
[36m(train_xgb_ray_tune pid=1050006)[0m [234]	train-mlogloss:0.76927	validation-mlogloss:0.77256
[36m(train_xgb_ray_tune pid=1050012)[0m [390]	train-mlogloss:0.78130	validation-mlogloss:0.77921
[36m(train_xgb_ray_tune pid=1050008)[0m [374]	train-mlogloss:1.10940	validation-mlogloss:1.09830
[36m(train_xgb_ray_tune pid=1050017)[0m [450]	train-mlogloss:1.03053	validation-mlogloss:1.01867
[36m(train_xgb_ray_tune pid=1050007)[0m [334]	train-mlogloss:0.76358	validation-mlogloss:0.76276
[36m(train_xgb_ray_tune pid=1050020)[0m [263]	train-mlogloss:1.02734	validation-mlogloss:1.01942
[36m(train_xgb_ray_tune pid=1050015)[0m [385]	train-mlogloss:0.79055	validation-mlogloss:0.78892
[36m(train_xgb_ray_tune pid=1050009)[0m [288]	train-mlogloss:0.73527	validation-mlogloss:0.74280
[36m(train_xgb_ray_tune pid=1049992)[0m [358]	train-mlogloss:0.86410	validation-mlogloss:0.85574
[36m(train_xgb_ray_tune pid=1050014)[0m [380]	train-mlogloss:0.75366	validation-mlogloss:0.75284
[36m(train_xgb_ray_tune pid=1050017)[0m [451]	train-mlogloss:1.03019	validation-mlogloss:1.01832
[36m(train_xgb_ray_tune pid=1050012)[0m [391]	train-mlogloss:0.78130	validation-mlogloss:0.77920
[36m(train_xgb_ray_tune pid=1050004)[0m [254]	train-mlogloss:1.01127	validation-mlogloss:0.99968
[36m(train_xgb_ray_tune pid=1050010)[0m [245]	train-mlogloss:0.72029	validation-mlogloss:0.73523
[36m(train_xgb_ray_tune pid=1050007)[0m [335]	train-mlogloss:0.76350	validation-mlogloss:0.76267
[36m(train_xgb_ray_tune pid=1050015)[0m [386]	train-mlogloss:0.79027	validation-mlogloss:0.78862
[36m(train_xgb_ray_tune pid=1050008)[0m [375]	train-mlogloss:1.10923	validation-mlogloss:1.09812

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:09. Total running time: 13s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             10.7899 │
│ time_total_s                 10.7899 │
│ training_iteration                 1 │
│ validation_accuracy          0.55548 │
╰──────────────────────────────────────╯

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:09. Total running time: 13s
[36m(train_xgb_ray_tune pid=1049992)[0m [359]	train-mlogloss:0.86410	validation-mlogloss:0.85574
[36m(train_xgb_ray_tune pid=1049992)[0m [360]	train-mlogloss:0.86410	validation-mlogloss:0.85574
[36m(train_xgb_ray_tune pid=1049992)[0m [361]	train-mlogloss:0.86410	validation-mlogloss:0.85574
[36m(train_xgb_ray_tune pid=1050011)[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=1050011)[0m   _log_deprecation_warning([32m [repeated 7x across cluster][0m
[36m(train_xgb_ray_tune pid=1049992)[0m [362]	train-mlogloss:0.86410	validation-mlogloss:0.85574
[36m(train_xgb_ray_tune pid=1049992)[0m [363]	train-mlogloss:0.86398	validation-mlogloss:0.85561
[36m(train_xgb_ray_tune pid=1049992)[0m [364]	train-mlogloss:0.86385	validation-mlogloss:0.85552
[36m(train_xgb_ray_tune pid=1049992)[0m [365]	train-mlogloss:0.86385	validation-mlogloss:0.85552
[36m(train_xgb_ray_tune pid=1049992)[0m [366]	train-mlogloss:0.86385	validation-mlogloss:0.85552
[36m(train_xgb_ray_tune pid=1050010)[0m [246]	train-mlogloss:0.71967	validation-mlogloss:0.73474
[36m(train_xgb_ray_tune pid=1050010)[0m [247]	train-mlogloss:0.71919	validation-mlogloss:0.73425
[36m(train_xgb_ray_tune pid=1050010)[0m [248]	train-mlogloss:0.71867	validation-mlogloss:0.73368
[36m(train_xgb_ray_tune pid=1050010)[0m [249]	train-mlogloss:0.71825	validation-mlogloss:0.73339
[36m(train_xgb_ray_tune pid=1050006)[0m [235]	train-mlogloss:0.76857	validation-mlogloss:0.77201
[36m(train_xgb_ray_tune pid=1050006)[0m [236]	train-mlogloss:0.76784	validation-mlogloss:0.77132
[36m(train_xgb_ray_tune pid=1050006)[0m [237]	train-mlogloss:0.76711	validation-mlogloss:0.77073
[36m(train_xgb_ray_tune pid=1050006)[0m [238]	train-mlogloss:0.76645	validation-mlogloss:0.77013
[36m(train_xgb_ray_tune pid=1050006)[0m [239]	train-mlogloss:0.76577	validation-mlogloss:0.76949
[36m(train_xgb_ray_tune pid=1050009)[0m [289]	train-mlogloss:0.73483	validation-mlogloss:0.74240
[36m(train_xgb_ray_tune pid=1050009)[0m [290]	train-mlogloss:0.73439	validation-mlogloss:0.74201
[36m(train_xgb_ray_tune pid=1050009)[0m [291]	train-mlogloss:0.73378	validation-mlogloss:0.74159
[36m(train_xgb_ray_tune pid=1050009)[0m [292]	train-mlogloss:0.73328	validation-mlogloss:0.74118
[36m(train_xgb_ray_tune pid=1050009)[0m [293]	train-mlogloss:0.73269	validation-mlogloss:0.74057
[36m(train_xgb_ray_tune pid=1050009)[0m [294]	train-mlogloss:0.73226	validation-mlogloss:0.74011
[36m(train_xgb_ray_tune pid=1050009)[0m [295]	train-mlogloss:0.73181	validation-mlogloss:0.73965
[36m(train_xgb_ray_tune pid=1050009)[0m [296]	train-mlogloss:0.73141	validation-mlogloss:0.73931
[36m(train_xgb_ray_tune pid=1050009)[0m [297]	train-mlogloss:0.73099	validation-mlogloss:0.73893
[36m(train_xgb_ray_tune pid=1050014)[0m [381]	train-mlogloss:0.75356	validation-mlogloss:0.75280
[36m(train_xgb_ray_tune pid=1050014)[0m [382]	train-mlogloss:0.75351	validation-mlogloss:0.75275
[36m(train_xgb_ray_tune pid=1050014)[0m [383]	train-mlogloss:0.75346	validation-mlogloss:0.75271
[36m(train_xgb_ray_tune pid=1050014)[0m [384]	train-mlogloss:0.75326	validation-mlogloss:0.75263
[36m(train_xgb_ray_tune pid=1050014)[0m [385]	train-mlogloss:0.75306	validation-mlogloss:0.75248
[36m(train_xgb_ray_tune pid=1050014)[0m [386]	train-mlogloss:0.75290	validation-mlogloss:0.75238
[36m(train_xgb_ray_tune pid=1050014)[0m [387]	train-mlogloss:0.75279	validation-mlogloss:0.75234
[36m(train_xgb_ray_tune pid=1050014)[0m [388]	train-mlogloss:0.75261	validation-mlogloss:0.75227
[36m(train_xgb_ray_tune pid=1050014)[0m [389]	train-mlogloss:0.75256	validation-mlogloss:0.75224
[36m(train_xgb_ray_tune pid=1050017)[0m [452]	train-mlogloss:1.02992	validation-mlogloss:1.01803
[36m(train_xgb_ray_tune pid=1050017)[0m [453]	train-mlogloss:1.02962	validation-mlogloss:1.01772
[36m(train_xgb_ray_tune pid=1050017)[0m [454]	train-mlogloss:1.02936	validation-mlogloss:1.01747
[36m(train_xgb_ray_tune pid=1050017)[0m [455]	train-mlogloss:1.02908	validation-mlogloss:1.01719
[36m(train_xgb_ray_tune pid=1050017)[0m [456]	train-mlogloss:1.02877	validation-mlogloss:1.01688
[36m(train_xgb_ray_tune pid=1050017)[0m [457]	train-mlogloss:1.02846	validation-mlogloss:1.01658
[36m(train_xgb_ray_tune pid=1050017)[0m [458]	train-mlogloss:1.02819	validation-mlogloss:1.01629
[36m(train_xgb_ray_tune pid=1050017)[0m [459]	train-mlogloss:1.02790	validation-mlogloss:1.01598
[36m(train_xgb_ray_tune pid=1050017)[0m [460]	train-mlogloss:1.02765	validation-mlogloss:1.01575
[36m(train_xgb_ray_tune pid=1050017)[0m [461]	train-mlogloss:1.02733	validation-mlogloss:1.01542
[36m(train_xgb_ray_tune pid=1050017)[0m [462]	train-mlogloss:1.02697	validation-mlogloss:1.01503
[36m(train_xgb_ray_tune pid=1050017)[0m [463]	train-mlogloss:1.02672	validation-mlogloss:1.01479
[36m(train_xgb_ray_tune pid=1050017)[0m [464]	train-mlogloss:1.02644	validation-mlogloss:1.01451
[36m(train_xgb_ray_tune pid=1050007)[0m [336]	train-mlogloss:0.76335	validation-mlogloss:0.76259
[36m(train_xgb_ray_tune pid=1050007)[0m [337]	train-mlogloss:0.76327	validation-mlogloss:0.76247
[36m(train_xgb_ray_tune pid=1050007)[0m [338]	train-mlogloss:0.76314	validation-mlogloss:0.76234
[36m(train_xgb_ray_tune pid=1050007)[0m [339]	train-mlogloss:0.76301	validation-mlogloss:0.76217
[36m(train_xgb_ray_tune pid=1050007)[0m [340]	train-mlogloss:0.76287	validation-mlogloss:0.76202
[36m(train_xgb_ray_tune pid=1050007)[0m [341]	train-mlogloss:0.76274	validation-mlogloss:0.76192
[36m(train_xgb_ray_tune pid=1050007)[0m [342]	train-mlogloss:0.76266	validation-mlogloss:0.76179
[36m(train_xgb_ray_tune pid=1050007)[0m [343]	train-mlogloss:0.76258	validation-mlogloss:0.76167
[36m(train_xgb_ray_tune pid=1050007)[0m [344]	train-mlogloss:0.76246	validation-mlogloss:0.76151
[36m(train_xgb_ray_tune pid=1050007)[0m [345]	train-mlogloss:0.76238	validation-mlogloss:0.76143
[36m(train_xgb_ray_tune pid=1050007)[0m [346]	train-mlogloss:0.76230	validation-mlogloss:0.76135
[36m(train_xgb_ray_tune pid=1050007)[0m [347]	train-mlogloss:0.76217	validation-mlogloss:0.76121
[36m(train_xgb_ray_tune pid=1050020)[0m [264]	train-mlogloss:1.02661	validation-mlogloss:1.01867
[36m(train_xgb_ray_tune pid=1050020)[0m [265]	train-mlogloss:1.02591	validation-mlogloss:1.01797
[36m(train_xgb_ray_tune pid=1050020)[0m [266]	train-mlogloss:1.02518	validation-mlogloss:1.01723
[36m(train_xgb_ray_tune pid=1050020)[0m [267]	train-mlogloss:1.02442	validation-mlogloss:1.01647
[36m(train_xgb_ray_tune pid=1050020)[0m [268]	train-mlogloss:1.02375	validation-mlogloss:1.01576
[36m(train_xgb_ray_tune pid=1050020)[0m [269]	train-mlogloss:1.02305	validation-mlogloss:1.01504
[36m(train_xgb_ray_tune pid=1050012)[0m [392]	train-mlogloss:0.78130	validation-mlogloss:0.77920
[36m(train_xgb_ray_tune pid=1050012)[0m [393]	train-mlogloss:0.78130	validation-mlogloss:0.77920
[36m(train_xgb_ray_tune pid=1050012)[0m [394]	train-mlogloss:0.78124	validation-mlogloss:0.77913
[36m(train_xgb_ray_tune pid=1050012)[0m [395]	train-mlogloss:0.78124	validation-mlogloss:0.77913
[36m(train_xgb_ray_tune pid=1050012)[0m [396]	train-mlogloss:0.78124	validation-mlogloss:0.77913
[36m(train_xgb_ray_tune pid=1050012)[0m [397]	train-mlogloss:0.78124	validation-mlogloss:0.77913
[36m(train_xgb_ray_tune pid=1050012)[0m [398]	train-mlogloss:0.78103	validation-mlogloss:0.77883
[36m(train_xgb_ray_tune pid=1050012)[0m [399]	train-mlogloss:0.78090	validation-mlogloss:0.77876
[36m(train_xgb_ray_tune pid=1050012)[0m [400]	train-mlogloss:0.78090	validation-mlogloss:0.77876
[36m(train_xgb_ray_tune pid=1050015)[0m [387]	train-mlogloss:0.79000	validation-mlogloss:0.78837
[36m(train_xgb_ray_tune pid=1050015)[0m [388]	train-mlogloss:0.78974	validation-mlogloss:0.78812
[36m(train_xgb_ray_tune pid=1050015)[0m [389]	train-mlogloss:0.78940	validation-mlogloss:0.78781
[36m(train_xgb_ray_tune pid=1050015)[0m [390]	train-mlogloss:0.78911	validation-mlogloss:0.78745
[36m(train_xgb_ray_tune pid=1050015)[0m [391]	train-mlogloss:0.78887	validation-mlogloss:0.78718
[36m(train_xgb_ray_tune pid=1050015)[0m [392]	train-mlogloss:0.78856	validation-mlogloss:0.78684
[36m(train_xgb_ray_tune pid=1050015)[0m [393]	train-mlogloss:0.78822	validation-mlogloss:0.78658
[36m(train_xgb_ray_tune pid=1050015)[0m [394]	train-mlogloss:0.78802	validation-mlogloss:0.78636
[36m(train_xgb_ray_tune pid=1050015)[0m [395]	train-mlogloss:0.78779	validation-mlogloss:0.78615
[36m(train_xgb_ray_tune pid=1050015)[0m [396]	train-mlogloss:0.78746	validation-mlogloss:0.78587
[36m(train_xgb_ray_tune pid=1050004)[0m [255]	train-mlogloss:1.01067	validation-mlogloss:0.99905
[36m(train_xgb_ray_tune pid=1050004)[0m [256]	train-mlogloss:1.01004	validation-mlogloss:0.99844
[36m(train_xgb_ray_tune pid=1050004)[0m [257]	train-mlogloss:1.00939	validation-mlogloss:0.99781
[36m(train_xgb_ray_tune pid=1050004)[0m [258]	train-mlogloss:1.00876	validation-mlogloss:0.99718
[36m(train_xgb_ray_tune pid=1050004)[0m [259]	train-mlogloss:1.00815	validation-mlogloss:0.99660
[36m(train_xgb_ray_tune pid=1050004)[0m [260]	train-mlogloss:1.00753	validation-mlogloss:0.99592
[36m(train_xgb_ray_tune pid=1050004)[0m [261]	train-mlogloss:1.00691	validation-mlogloss:0.99529
[36m(train_xgb_ray_tune pid=1050004)[0m [262]	train-mlogloss:1.00632	validation-mlogloss:0.99473
[36m(train_xgb_ray_tune pid=1050004)[0m [263]	train-mlogloss:1.00572	validation-mlogloss:0.99410
[36m(train_xgb_ray_tune pid=1050008)[0m [376]	train-mlogloss:1.10906	validation-mlogloss:1.09793
[36m(train_xgb_ray_tune pid=1050008)[0m [377]	train-mlogloss:1.10889	validation-mlogloss:1.09775
[36m(train_xgb_ray_tune pid=1050008)[0m [378]	train-mlogloss:1.10872	validation-mlogloss:1.09757
[36m(train_xgb_ray_tune pid=1050008)[0m [379]	train-mlogloss:1.10855	validation-mlogloss:1.09739
[36m(train_xgb_ray_tune pid=1050008)[0m [380]	train-mlogloss:1.10839	validation-mlogloss:1.09723
[36m(train_xgb_ray_tune pid=1050008)[0m [381]	train-mlogloss:1.10823	validation-mlogloss:1.09705
[36m(train_xgb_ray_tune pid=1050008)[0m [382]	train-mlogloss:1.10806	validation-mlogloss:1.09687
[36m(train_xgb_ray_tune pid=1050008)[0m [383]	train-mlogloss:1.10790	validation-mlogloss:1.09670
[36m(train_xgb_ray_tune pid=1049992)[0m [367]	train-mlogloss:0.86385	validation-mlogloss:0.85552
[36m(train_xgb_ray_tune pid=1050010)[0m [250]	train-mlogloss:0.71768	validation-mlogloss:0.73289
[36m(train_xgb_ray_tune pid=1050017)[0m [465]	train-mlogloss:1.02619	validation-mlogloss:1.01426
[36m(train_xgb_ray_tune pid=1050007)[0m [348]	train-mlogloss:0.76210	validation-mlogloss:0.76116
[36m(train_xgb_ray_tune pid=1050008)[0m [384]	train-mlogloss:1.10768	validation-mlogloss:1.09646
[36m(train_xgb_ray_tune pid=1050020)[0m [270]	train-mlogloss:1.02231	validation-mlogloss:1.01428
[36m(train_xgb_ray_tune pid=1050012)[0m [401]	train-mlogloss:0.78090	validation-mlogloss:0.77876
[36m(train_xgb_ray_tune pid=1050004)[0m [264]	train-mlogloss:1.00502	validation-mlogloss:0.99340
[36m(train_xgb_ray_tune pid=1050009)[0m [298]	train-mlogloss:0.73049	validation-mlogloss:0.73846
[36m(train_xgb_ray_tune pid=1050014)[0m [390]	train-mlogloss:0.75242	validation-mlogloss:0.75215
[36m(train_xgb_ray_tune pid=1050017)[0m [466]	train-mlogloss:1.02587	validation-mlogloss:1.01392
[36m(train_xgb_ray_tune pid=1050007)[0m [349]	train-mlogloss:0.76191	validation-mlogloss:0.76094
[36m(train_xgb_ray_tune pid=1050008)[0m [385]	train-mlogloss:1.10751	validation-mlogloss:1.09628
[36m(train_xgb_ray_tune pid=1049992)[0m [368]	train-mlogloss:0.86385	validation-mlogloss:0.85552
[36m(train_xgb_ray_tune pid=1050006)[0m [240]	train-mlogloss:0.76517	validation-mlogloss:0.76904
[36m(train_xgb_ray_tune pid=1050017)[0m [467]	train-mlogloss:1.02559	validation-mlogloss:1.01363
[36m(train_xgb_ray_tune pid=1050010)[0m [251]	train-mlogloss:0.71713	validation-mlogloss:0.73245
[36m(train_xgb_ray_tune pid=1050007)[0m [350]	train-mlogloss:0.76178	validation-mlogloss:0.76083
[36m(train_xgb_ray_tune pid=1050020)[0m [271]	train-mlogloss:1.02159	validation-mlogloss:1.01357
[36m(train_xgb_ray_tune pid=1050012)[0m [402]	train-mlogloss:0.78068	validation-mlogloss:0.77845
[36m(train_xgb_ray_tune pid=1050008)[0m [386]	train-mlogloss:1.10735	validation-mlogloss:1.09611
[36m(train_xgb_ray_tune pid=1050014)[0m [391]	train-mlogloss:0.75233	validation-mlogloss:0.75203
[36m(train_xgb_ray_tune pid=1050004)[0m [265]	train-mlogloss:1.00446	validation-mlogloss:0.99281
[36m(train_xgb_ray_tune pid=1049992)[0m [369]	train-mlogloss:0.86385	validation-mlogloss:0.85552
[36m(train_xgb_ray_tune pid=1050009)[0m [299]	train-mlogloss:0.72994	validation-mlogloss:0.73800
[36m(train_xgb_ray_tune pid=1050017)[0m [468]	train-mlogloss:1.02534	validation-mlogloss:1.01336
[36m(train_xgb_ray_tune pid=1050007)[0m [351]	train-mlogloss:0.76170	validation-mlogloss:0.76078
[36m(train_xgb_ray_tune pid=1050008)[0m [387]	train-mlogloss:1.10719	validation-mlogloss:1.09594

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:09. Total running time: 13s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             10.6391 │
│ time_total_s                 10.6391 │
│ training_iteration                 1 │
│ validation_accuracy          0.69101 │
╰──────────────────────────────────────╯

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:09. Total running time: 13s
[36m(train_xgb_ray_tune pid=1049992)[0m [370]	train-mlogloss:0.86373	validation-mlogloss:0.85536
[36m(train_xgb_ray_tune pid=1049992)[0m [371]	train-mlogloss:0.86373	validation-mlogloss:0.85536
[36m(train_xgb_ray_tune pid=1049992)[0m [372]	train-mlogloss:0.86372	validation-mlogloss:0.85536
[36m(train_xgb_ray_tune pid=1049992)[0m [373]	train-mlogloss:0.86372	validation-mlogloss:0.85536
[36m(train_xgb_ray_tune pid=1049992)[0m [374]	train-mlogloss:0.86372	validation-mlogloss:0.85535
[36m(train_xgb_ray_tune pid=1049992)[0m [375]	train-mlogloss:0.86372	validation-mlogloss:0.85535
[36m(train_xgb_ray_tune pid=1049992)[0m [376]	train-mlogloss:0.86372	validation-mlogloss:0.85535
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[36m(train_xgb_ray_tune pid=1050012)[0m [444]	train-mlogloss:0.77998	validation-mlogloss:0.77774
[36m(train_xgb_ray_tune pid=1050012)[0m [445]	train-mlogloss:0.77998	validation-mlogloss:0.77774
[36m(train_xgb_ray_tune pid=1050012)[0m [446]	train-mlogloss:0.77991	validation-mlogloss:0.77769
[36m(train_xgb_ray_tune pid=1050012)[0m [447]	train-mlogloss:0.77991	validation-mlogloss:0.77769
[36m(train_xgb_ray_tune pid=1050012)[0m [448]	train-mlogloss:0.77971	validation-mlogloss:0.77755
[36m(train_xgb_ray_tune pid=1050012)[0m [449]	train-mlogloss:0.77949	validation-mlogloss:0.77738
[36m(train_xgb_ray_tune pid=1050012)[0m [450]	train-mlogloss:0.77949	validation-mlogloss:0.77738
[36m(train_xgb_ray_tune pid=1050012)[0m [451]	train-mlogloss:0.77949	validation-mlogloss:0.77738
[36m(train_xgb_ray_tune pid=1050004)[0m [289]	train-mlogloss:0.99048	validation-mlogloss:0.97876
[36m(train_xgb_ray_tune pid=1050004)[0m [290]	train-mlogloss:0.98994	validation-mlogloss:0.97819
[36m(train_xgb_ray_tune pid=1050004)[0m [291]	train-mlogloss:0.98939	validation-mlogloss:0.97761
[36m(train_xgb_ray_tune pid=1050004)[0m [292]	train-mlogloss:0.98884	validation-mlogloss:0.97706
[36m(train_xgb_ray_tune pid=1050004)[0m [293]	train-mlogloss:0.98836	validation-mlogloss:0.97657
[36m(train_xgb_ray_tune pid=1050004)[0m [294]	train-mlogloss:0.98787	validation-mlogloss:0.97608
[36m(train_xgb_ray_tune pid=1050004)[0m [295]	train-mlogloss:0.98731	validation-mlogloss:0.97551
[36m(train_xgb_ray_tune pid=1050004)[0m [296]	train-mlogloss:0.98677	validation-mlogloss:0.97494
[36m(train_xgb_ray_tune pid=1050004)[0m [297]	train-mlogloss:0.98628	validation-mlogloss:0.97445
[36m(train_xgb_ray_tune pid=1050004)[0m [298]	train-mlogloss:0.98575	validation-mlogloss:0.97390
[36m(train_xgb_ray_tune pid=1050008)[0m [421]	train-mlogloss:1.10166	validation-mlogloss:1.09018
[36m(train_xgb_ray_tune pid=1050008)[0m [422]	train-mlogloss:1.10152	validation-mlogloss:1.09003
[36m(train_xgb_ray_tune pid=1050008)[0m [423]	train-mlogloss:1.10138	validation-mlogloss:1.08988
[36m(train_xgb_ray_tune pid=1050008)[0m [424]	train-mlogloss:1.10124	validation-mlogloss:1.08974
[36m(train_xgb_ray_tune pid=1050008)[0m [425]	train-mlogloss:1.10111	validation-mlogloss:1.08960
[36m(train_xgb_ray_tune pid=1050008)[0m [426]	train-mlogloss:1.10097	validation-mlogloss:1.08945
[36m(train_xgb_ray_tune pid=1050008)[0m [427]	train-mlogloss:1.10084	validation-mlogloss:1.08932
[36m(train_xgb_ray_tune pid=1050008)[0m [428]	train-mlogloss:1.10070	validation-mlogloss:1.08919
[36m(train_xgb_ray_tune pid=1050008)[0m [429]	train-mlogloss:1.10057	validation-mlogloss:1.08904
[36m(train_xgb_ray_tune pid=1050008)[0m [430]	train-mlogloss:1.10043	validation-mlogloss:1.08891
[36m(train_xgb_ray_tune pid=1050008)[0m [431]	train-mlogloss:1.10030	validation-mlogloss:1.08877
[36m(train_xgb_ray_tune pid=1050008)[0m [432]	train-mlogloss:1.10017	validation-mlogloss:1.08863
[36m(train_xgb_ray_tune pid=1050008)[0m [433]	train-mlogloss:1.10005	validation-mlogloss:1.08849
[36m(train_xgb_ray_tune pid=1050008)[0m [434]	train-mlogloss:1.09991	validation-mlogloss:1.08836
[36m(train_xgb_ray_tune pid=1050010)[0m [273]	train-mlogloss:0.70600	validation-mlogloss:0.72374
[36m(train_xgb_ray_tune pid=1050006)[0m [261]	train-mlogloss:0.75262	validation-mlogloss:0.75852
[36m(train_xgb_ray_tune pid=1050009)[0m [329]	train-mlogloss:0.71715	validation-mlogloss:0.72797
[36m(train_xgb_ray_tune pid=1050007)[0m [394]	train-mlogloss:0.75758	validation-mlogloss:0.75631
[36m(train_xgb_ray_tune pid=1050012)[0m [452]	train-mlogloss:0.77949	validation-mlogloss:0.77738
[36m(train_xgb_ray_tune pid=1050004)[0m [299]	train-mlogloss:0.98522	validation-mlogloss:0.97340
[36m(train_xgb_ray_tune pid=1050017)[0m [514]	train-mlogloss:1.01287	validation-mlogloss:1.00062
[36m(train_xgb_ray_tune pid=1050020)[0m [303]	train-mlogloss:1.00064	validation-mlogloss:0.99230
[36m(train_xgb_ray_tune pid=1050012)[0m [453]	train-mlogloss:0.77949	validation-mlogloss:0.77738
[36m(train_xgb_ray_tune pid=1050008)[0m [435]	train-mlogloss:1.09978	validation-mlogloss:1.08821
[36m(train_xgb_ray_tune pid=1049992)[0m [401]	train-mlogloss:0.86312	validation-mlogloss:0.85476
[36m(train_xgb_ray_tune pid=1050014)[0m [424]	train-mlogloss:0.74972	validation-mlogloss:0.74984
[36m(train_xgb_ray_tune pid=1050007)[0m [395]	train-mlogloss:0.75751	validation-mlogloss:0.75624
[36m(train_xgb_ray_tune pid=1050004)[0m [300]	train-mlogloss:0.98474	validation-mlogloss:0.97290
[36m(train_xgb_ray_tune pid=1050010)[0m [274]	train-mlogloss:0.70555	validation-mlogloss:0.72337
[36m(train_xgb_ray_tune pid=1050006)[0m [262]	train-mlogloss:0.75200	validation-mlogloss:0.75798
[36m(train_xgb_ray_tune pid=1050009)[0m [330]	train-mlogloss:0.71678	validation-mlogloss:0.72769
[36m(train_xgb_ray_tune pid=1050017)[0m [515]	train-mlogloss:1.01260	validation-mlogloss:1.00035
[36m(train_xgb_ray_tune pid=1050012)[0m [454]	train-mlogloss:0.77949	validation-mlogloss:0.77738
[36m(train_xgb_ray_tune pid=1050007)[0m [396]	train-mlogloss:0.75730	validation-mlogloss:0.75615
[36m(train_xgb_ray_tune pid=1050008)[0m [436]	train-mlogloss:1.09965	validation-mlogloss:1.08808
[36m(train_xgb_ray_tune pid=1049992)[0m [402]	train-mlogloss:0.86312	validation-mlogloss:0.85476
[36m(train_xgb_ray_tune pid=1050014)[0m [425]	train-mlogloss:0.74972	validation-mlogloss:0.74984
[36m(train_xgb_ray_tune pid=1050020)[0m [304]	train-mlogloss:1.00004	validation-mlogloss:0.99170
[36m(train_xgb_ray_tune pid=1050012)[0m [455]	train-mlogloss:0.77949	validation-mlogloss:0.77738
[36m(train_xgb_ray_tune pid=1050004)[0m [301]	train-mlogloss:0.98426	validation-mlogloss:0.97243
[36m(train_xgb_ray_tune pid=1050017)[0m [516]	train-mlogloss:1.01242	validation-mlogloss:1.00017
[36m(train_xgb_ray_tune pid=1050010)[0m [275]	train-mlogloss:0.70493	validation-mlogloss:0.72283
[36m(train_xgb_ray_tune pid=1050006)[0m [263]	train-mlogloss:0.75153	validation-mlogloss:0.75762
[36m(train_xgb_ray_tune pid=1050007)[0m [397]	train-mlogloss:0.75724	validation-mlogloss:0.75609
[36m(train_xgb_ray_tune pid=1050012)[0m [456]	train-mlogloss:0.77949	validation-mlogloss:0.77738
[36m(train_xgb_ray_tune pid=1050008)[0m [437]	train-mlogloss:1.09952	validation-mlogloss:1.08794
[36m(train_xgb_ray_tune pid=1049992)[0m [403]	train-mlogloss:0.86312	validation-mlogloss:0.85476
[36m(train_xgb_ray_tune pid=1050009)[0m [331]	train-mlogloss:0.71636	validation-mlogloss:0.72738
[36m(train_xgb_ray_tune pid=1050017)[0m [517]	train-mlogloss:1.01218	validation-mlogloss:0.99994
[36m(train_xgb_ray_tune pid=1050020)[0m [305]	train-mlogloss:0.99954	validation-mlogloss:0.99120
[36m(train_xgb_ray_tune pid=1050014)[0m [426]	train-mlogloss:0.74951	validation-mlogloss:0.74954
[36m(train_xgb_ray_tune pid=1050007)[0m [398]	train-mlogloss:0.75717	validation-mlogloss:0.75601
[36m(train_xgb_ray_tune pid=1050012)[0m [457]	train-mlogloss:0.77949	validation-mlogloss:0.77738
[36m(train_xgb_ray_tune pid=1050004)[0m [302]	train-mlogloss:0.98373	validation-mlogloss:0.97188
[36m(train_xgb_ray_tune pid=1050008)[0m [438]	train-mlogloss:1.09938	validation-mlogloss:1.08779
[36m(train_xgb_ray_tune pid=1050010)[0m [276]	train-mlogloss:0.70458	validation-mlogloss:0.72257
[36m(train_xgb_ray_tune pid=1050006)[0m [264]	train-mlogloss:0.75098	validation-mlogloss:0.75709
[36m(train_xgb_ray_tune pid=1050017)[0m [518]	train-mlogloss:1.01191	validation-mlogloss:0.99966
[36m(train_xgb_ray_tune pid=1050012)[0m [458]	train-mlogloss:0.77949	validation-mlogloss:0.77738
[36m(train_xgb_ray_tune pid=1050009)[0m [332]	train-mlogloss:0.71586	validation-mlogloss:0.72700
[36m(train_xgb_ray_tune pid=1050007)[0m [399]	train-mlogloss:0.75706	validation-mlogloss:0.75591
[36m(train_xgb_ray_tune pid=1049992)[0m [404]	train-mlogloss:0.86299	validation-mlogloss:0.85464
[36m(train_xgb_ray_tune pid=1050010)[0m [277]	train-mlogloss:0.70430	validation-mlogloss:0.72232
[36m(train_xgb_ray_tune pid=1050014)[0m [427]	train-mlogloss:0.74951	validation-mlogloss:0.74955
[36m(train_xgb_ray_tune pid=1050017)[0m [519]	train-mlogloss:1.01169	validation-mlogloss:0.99942
[36m(train_xgb_ray_tune pid=1050020)[0m [306]	train-mlogloss:0.99892	validation-mlogloss:0.99056
[36m(train_xgb_ray_tune pid=1050012)[0m [459]	train-mlogloss:0.77949	validation-mlogloss:0.77737
[36m(train_xgb_ray_tune pid=1050006)[0m [265]	train-mlogloss:0.75039	validation-mlogloss:0.75663
[36m(train_xgb_ray_tune pid=1050007)[0m [400]	train-mlogloss:0.75700	validation-mlogloss:0.75581
[36m(train_xgb_ray_tune pid=1050004)[0m [303]	train-mlogloss:0.98320	validation-mlogloss:0.97134
[36m(train_xgb_ray_tune pid=1050009)[0m [333]	train-mlogloss:0.71542	validation-mlogloss:0.72661
[36m(train_xgb_ray_tune pid=1050017)[0m [520]	train-mlogloss:1.01147	validation-mlogloss:0.99922
[36m(train_xgb_ray_tune pid=1050012)[0m [460]	train-mlogloss:0.77949	validation-mlogloss:0.77737
[36m(train_xgb_ray_tune pid=1049992)[0m [405]	train-mlogloss:0.86299	validation-mlogloss:0.85464
[36m(train_xgb_ray_tune pid=1050010)[0m [278]	train-mlogloss:0.70383	validation-mlogloss:0.72198
[36m(train_xgb_ray_tune pid=1050014)[0m [428]	train-mlogloss:0.74947	validation-mlogloss:0.74955
[36m(train_xgb_ray_tune pid=1050007)[0m [401]	train-mlogloss:0.75700	validation-mlogloss:0.75580
[36m(train_xgb_ray_tune pid=1050017)[0m [521]	train-mlogloss:1.01116	validation-mlogloss:0.99889
[36m(train_xgb_ray_tune pid=1050020)[0m [307]	train-mlogloss:0.99833	validation-mlogloss:0.98992
[36m(train_xgb_ray_tune pid=1050012)[0m [461]	train-mlogloss:0.77949	validation-mlogloss:0.77737
[36m(train_xgb_ray_tune pid=1050004)[0m [304]	train-mlogloss:0.98275	validation-mlogloss:0.97092
[36m(train_xgb_ray_tune pid=1050006)[0m [266]	train-mlogloss:0.74976	validation-mlogloss:0.75608
[36m(train_xgb_ray_tune pid=1050007)[0m [402]	train-mlogloss:0.75694	validation-mlogloss:0.75574
[36m(train_xgb_ray_tune pid=1050012)[0m [462]	train-mlogloss:0.77949	validation-mlogloss:0.77737
[36m(train_xgb_ray_tune pid=1050010)[0m [279]	train-mlogloss:0.70344	validation-mlogloss:0.72170
[36m(train_xgb_ray_tune pid=1050009)[0m [334]	train-mlogloss:0.71497	validation-mlogloss:0.72622
[36m(train_xgb_ray_tune pid=1050014)[0m [429]	train-mlogloss:0.74947	validation-mlogloss:0.74956
[36m(train_xgb_ray_tune pid=1050017)[0m [522]	train-mlogloss:1.01089	validation-mlogloss:0.99861
[36m(train_xgb_ray_tune pid=1049992)[0m [406]	train-mlogloss:0.86299	validation-mlogloss:0.85464
[36m(train_xgb_ray_tune pid=1050006)[0m [267]	train-mlogloss:0.74918	validation-mlogloss:0.75557
[36m(train_xgb_ray_tune pid=1050007)[0m [403]	train-mlogloss:0.75688	validation-mlogloss:0.75565
[36m(train_xgb_ray_tune pid=1050020)[0m [308]	train-mlogloss:0.99772	validation-mlogloss:0.98929
[36m(train_xgb_ray_tune pid=1050012)[0m [463]	train-mlogloss:0.77943	validation-mlogloss:0.77731
[36m(train_xgb_ray_tune pid=1050004)[0m [305]	train-mlogloss:0.98224	validation-mlogloss:0.97042
[36m(train_xgb_ray_tune pid=1050010)[0m [280]	train-mlogloss:0.70314	validation-mlogloss:0.72152
[36m(train_xgb_ray_tune pid=1050014)[0m [430]	train-mlogloss:0.74947	validation-mlogloss:0.74956
[36m(train_xgb_ray_tune pid=1050017)[0m [523]	train-mlogloss:1.01066	validation-mlogloss:0.99839
[36m(train_xgb_ray_tune pid=1050009)[0m [335]	train-mlogloss:0.71459	validation-mlogloss:0.72600
[36m(train_xgb_ray_tune pid=1050007)[0m [404]	train-mlogloss:0.75682	validation-mlogloss:0.75558
[36m(train_xgb_ray_tune pid=1050012)[0m [464]	train-mlogloss:0.77943	validation-mlogloss:0.77731
[36m(train_xgb_ray_tune pid=1049992)[0m [407]	train-mlogloss:0.86288	validation-mlogloss:0.85451
[36m(train_xgb_ray_tune pid=1050017)[0m [524]	train-mlogloss:1.01044	validation-mlogloss:0.99816
[36m(train_xgb_ray_tune pid=1050020)[0m [309]	train-mlogloss:0.99714	validation-mlogloss:0.98871
[36m(train_xgb_ray_tune pid=1050012)[0m [465]	train-mlogloss:0.77943	validation-mlogloss:0.77731
[36m(train_xgb_ray_tune pid=1050010)[0m [281]	train-mlogloss:0.70286	validation-mlogloss:0.72120
[36m(train_xgb_ray_tune pid=1050006)[0m [268]	train-mlogloss:0.74864	validation-mlogloss:0.75508
[36m(train_xgb_ray_tune pid=1050007)[0m [405]	train-mlogloss:0.75676	validation-mlogloss:0.75550
[36m(train_xgb_ray_tune pid=1050004)[0m [306]	train-mlogloss:0.98173	validation-mlogloss:0.96991
[36m(train_xgb_ray_tune pid=1050009)[0m [336]	train-mlogloss:0.71429	validation-mlogloss:0.72570
[36m(train_xgb_ray_tune pid=1050014)[0m [431]	train-mlogloss:0.74932	validation-mlogloss:0.74941
[36m(train_xgb_ray_tune pid=1050017)[0m [525]	train-mlogloss:1.01021	validation-mlogloss:0.99794
[36m(train_xgb_ray_tune pid=1050012)[0m [466]	train-mlogloss:0.77943	validation-mlogloss:0.77731
[36m(train_xgb_ray_tune pid=1049992)[0m [408]	train-mlogloss:0.86288	validation-mlogloss:0.85451
[36m(train_xgb_ray_tune pid=1050010)[0m [282]	train-mlogloss:0.70264	validation-mlogloss:0.72095
[36m(train_xgb_ray_tune pid=1050006)[0m [269]	train-mlogloss:0.74812	validation-mlogloss:0.75461
[36m(train_xgb_ray_tune pid=1050007)[0m [406]	train-mlogloss:0.75670	validation-mlogloss:0.75544
[36m(train_xgb_ray_tune pid=1050020)[0m [310]	train-mlogloss:0.99650	validation-mlogloss:0.98805
[36m(train_xgb_ray_tune pid=1050012)[0m [467]	train-mlogloss:0.77943	validation-mlogloss:0.77731
[36m(train_xgb_ray_tune pid=1050004)[0m [307]	train-mlogloss:0.98131	validation-mlogloss:0.96949
[36m(train_xgb_ray_tune pid=1050009)[0m [337]	train-mlogloss:0.71390	validation-mlogloss:0.72542
[36m(train_xgb_ray_tune pid=1050017)[0m [526]	train-mlogloss:1.00995	validation-mlogloss:0.99768
[36m(train_xgb_ray_tune pid=1050014)[0m [432]	train-mlogloss:0.74928	validation-mlogloss:0.74935
[36m(train_xgb_ray_tune pid=1050012)[0m [468]	train-mlogloss:0.77943	validation-mlogloss:0.77731
[36m(train_xgb_ray_tune pid=1049992)[0m [409]	train-mlogloss:0.86288	validation-mlogloss:0.85451
[36m(train_xgb_ray_tune pid=1050010)[0m [283]	train-mlogloss:0.70217	validation-mlogloss:0.72066
[36m(train_xgb_ray_tune pid=1050017)[0m [527]	train-mlogloss:1.00969	validation-mlogloss:0.99742
[36m(train_xgb_ray_tune pid=1050007)[0m [407]	train-mlogloss:0.75664	validation-mlogloss:0.75536
[36m(train_xgb_ray_tune pid=1050020)[0m [311]	train-mlogloss:0.99592	validation-mlogloss:0.98750
[36m(train_xgb_ray_tune pid=1050004)[0m [308]	train-mlogloss:0.98085	validation-mlogloss:0.96901
[36m(train_xgb_ray_tune pid=1050006)[0m [270]	train-mlogloss:0.74753	validation-mlogloss:0.75410
[36m(train_xgb_ray_tune pid=1050009)[0m [338]	train-mlogloss:0.71356	validation-mlogloss:0.72518
[36m(train_xgb_ray_tune pid=1050012)[0m [469]	train-mlogloss:0.77943	validation-mlogloss:0.77731
[36m(train_xgb_ray_tune pid=1050014)[0m [433]	train-mlogloss:0.74928	validation-mlogloss:0.74935
[36m(train_xgb_ray_tune pid=1050017)[0m [528]	train-mlogloss:1.00946	validation-mlogloss:0.99719
[36m(train_xgb_ray_tune pid=1049992)[0m [410]	train-mlogloss:0.86287	validation-mlogloss:0.85451
[36m(train_xgb_ray_tune pid=1050012)[0m [470]	train-mlogloss:0.77943	validation-mlogloss:0.77731
[36m(train_xgb_ray_tune pid=1050010)[0m [284]	train-mlogloss:0.70160	validation-mlogloss:0.72032

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:10. Total running time: 14s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             11.0466 │
│ time_total_s                 11.0466 │
│ training_iteration                 1 │
│ validation_accuracy          0.64396 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1050006)[0m [271]	train-mlogloss:0.74707	validation-mlogloss:0.75380
[36m(train_xgb_ray_tune pid=1050007)[0m [408]	train-mlogloss:0.75647	validation-mlogloss:0.75523
[36m(train_xgb_ray_tune pid=1050004)[0m [309]	train-mlogloss:0.98034	validation-mlogloss:0.96850
[36m(train_xgb_ray_tune pid=1050009)[0m [339]	train-mlogloss:0.71316	validation-mlogloss:0.72487
[36m(train_xgb_ray_tune pid=1050014)[0m [434]	train-mlogloss:0.74927	validation-mlogloss:0.74935
[36m(train_xgb_ray_tune pid=1050017)[0m [529]	train-mlogloss:1.00923	validation-mlogloss:0.99696
[36m(train_xgb_ray_tune pid=1050020)[0m [312]	train-mlogloss:0.99531	validation-mlogloss:0.98689
[36m(train_xgb_ray_tune pid=1050012)[0m [471]	train-mlogloss:0.77943	validation-mlogloss:0.77731

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:10. Total running time: 14s
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[36m(train_xgb_ray_tune pid=1050012)[0m [574]	train-mlogloss:0.77772	validation-mlogloss:0.77566
[36m(train_xgb_ray_tune pid=1050012)[0m [575]	train-mlogloss:0.77772	validation-mlogloss:0.77566
[36m(train_xgb_ray_tune pid=1050004)[0m [373]	train-mlogloss:0.95384	validation-mlogloss:0.94183
[36m(train_xgb_ray_tune pid=1050004)[0m [374]	train-mlogloss:0.95338	validation-mlogloss:0.94140
[36m(train_xgb_ray_tune pid=1050004)[0m [375]	train-mlogloss:0.95297	validation-mlogloss:0.94098
[36m(train_xgb_ray_tune pid=1050004)[0m [376]	train-mlogloss:0.95259	validation-mlogloss:0.94055
[36m(train_xgb_ray_tune pid=1050004)[0m [377]	train-mlogloss:0.95222	validation-mlogloss:0.94015
[36m(train_xgb_ray_tune pid=1050004)[0m [378]	train-mlogloss:0.95181	validation-mlogloss:0.93974
[36m(train_xgb_ray_tune pid=1050004)[0m [379]	train-mlogloss:0.95146	validation-mlogloss:0.93937
[36m(train_xgb_ray_tune pid=1050004)[0m [380]	train-mlogloss:0.95112	validation-mlogloss:0.93901
[36m(train_xgb_ray_tune pid=1050004)[0m [381]	train-mlogloss:0.95078	validation-mlogloss:0.93866
[36m(train_xgb_ray_tune pid=1050004)[0m [382]	train-mlogloss:0.95046	validation-mlogloss:0.93833
[36m(train_xgb_ray_tune pid=1050004)[0m [383]	train-mlogloss:0.95011	validation-mlogloss:0.93794
[36m(train_xgb_ray_tune pid=1050010)[0m [352]	train-mlogloss:0.68202	validation-mlogloss:0.70499
[36m(train_xgb_ray_tune pid=1050009)[0m [406]	train-mlogloss:0.69188	validation-mlogloss:0.70908
[36m(train_xgb_ray_tune pid=1050014)[0m [548]	train-mlogloss:0.74648	validation-mlogloss:0.74740
[36m(train_xgb_ray_tune pid=1050007)[0m [511]	train-mlogloss:0.75100	validation-mlogloss:0.75118
[36m(train_xgb_ray_tune pid=1050020)[0m [379]	train-mlogloss:0.96187	validation-mlogloss:0.95281
[36m(train_xgb_ray_tune pid=1049992)[0m [513]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1050007)[0m [512]	train-mlogloss:0.75100	validation-mlogloss:0.75118
[36m(train_xgb_ray_tune pid=1050010)[0m [353]	train-mlogloss:0.68189	validation-mlogloss:0.70487
[36m(train_xgb_ray_tune pid=1050006)[0m [337]	train-mlogloss:0.71774	validation-mlogloss:0.72949
[36m(train_xgb_ray_tune pid=1050009)[0m [407]	train-mlogloss:0.69170	validation-mlogloss:0.70896
[36m(train_xgb_ray_tune pid=1050014)[0m [549]	train-mlogloss:0.74648	validation-mlogloss:0.74740
[36m(train_xgb_ray_tune pid=1050017)[0m [626]	train-mlogloss:0.98781	validation-mlogloss:0.97511
[36m(train_xgb_ray_tune pid=1049992)[0m [514]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1050020)[0m [380]	train-mlogloss:0.96145	validation-mlogloss:0.95238
[36m(train_xgb_ray_tune pid=1050004)[0m [384]	train-mlogloss:0.94976	validation-mlogloss:0.93757
[36m(train_xgb_ray_tune pid=1050014)[0m [550]	train-mlogloss:0.74644	validation-mlogloss:0.74737
[36m(train_xgb_ray_tune pid=1050007)[0m [513]	train-mlogloss:0.75100	validation-mlogloss:0.75118
[36m(train_xgb_ray_tune pid=1049992)[0m [515]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1050010)[0m [354]	train-mlogloss:0.68166	validation-mlogloss:0.70470
[36m(train_xgb_ray_tune pid=1050006)[0m [338]	train-mlogloss:0.71745	validation-mlogloss:0.72925
[36m(train_xgb_ray_tune pid=1050009)[0m [408]	train-mlogloss:0.69144	validation-mlogloss:0.70878
[36m(train_xgb_ray_tune pid=1050017)[0m [627]	train-mlogloss:0.98761	validation-mlogloss:0.97489
[36m(train_xgb_ray_tune pid=1050014)[0m [551]	train-mlogloss:0.74644	validation-mlogloss:0.74737
[36m(train_xgb_ray_tune pid=1050007)[0m [514]	train-mlogloss:0.75100	validation-mlogloss:0.75118
[36m(train_xgb_ray_tune pid=1050004)[0m [385]	train-mlogloss:0.94948	validation-mlogloss:0.93729
[36m(train_xgb_ray_tune pid=1049992)[0m [516]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1050017)[0m [628]	train-mlogloss:0.98745	validation-mlogloss:0.97474
[36m(train_xgb_ray_tune pid=1050020)[0m [381]	train-mlogloss:0.96108	validation-mlogloss:0.95199
[36m(train_xgb_ray_tune pid=1050010)[0m [355]	train-mlogloss:0.68145	validation-mlogloss:0.70448
[36m(train_xgb_ray_tune pid=1050014)[0m [552]	train-mlogloss:0.74644	validation-mlogloss:0.74737
[36m(train_xgb_ray_tune pid=1049992)[0m [517]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1050006)[0m [339]	train-mlogloss:0.71703	validation-mlogloss:0.72892
[36m(train_xgb_ray_tune pid=1050009)[0m [409]	train-mlogloss:0.69121	validation-mlogloss:0.70854
[36m(train_xgb_ray_tune pid=1050007)[0m [515]	train-mlogloss:0.75100	validation-mlogloss:0.75119
[36m(train_xgb_ray_tune pid=1050004)[0m [386]	train-mlogloss:0.94909	validation-mlogloss:0.93691
[36m(train_xgb_ray_tune pid=1050010)[0m [356]	train-mlogloss:0.68132	validation-mlogloss:0.70438
[36m(train_xgb_ray_tune pid=1050014)[0m [553]	train-mlogloss:0.74644	validation-mlogloss:0.74737
[36m(train_xgb_ray_tune pid=1050017)[0m [629]	train-mlogloss:0.98727	validation-mlogloss:0.97456
[36m(train_xgb_ray_tune pid=1050020)[0m [382]	train-mlogloss:0.96063	validation-mlogloss:0.95153
[36m(train_xgb_ray_tune pid=1049992)[0m [518]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1050007)[0m [516]	train-mlogloss:0.75100	validation-mlogloss:0.75118

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:10. Total running time: 15s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s               12.08 │
│ time_total_s                   12.08 │
│ training_iteration                 1 │
│ validation_accuracy          0.67591 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1050014)[0m [554]	train-mlogloss:0.74644	validation-mlogloss:0.74737
[36m(train_xgb_ray_tune pid=1050004)[0m [387]	train-mlogloss:0.94880	validation-mlogloss:0.93662
[36m(train_xgb_ray_tune pid=1050006)[0m [340]	train-mlogloss:0.71664	validation-mlogloss:0.72853
[36m(train_xgb_ray_tune pid=1050009)[0m [410]	train-mlogloss:0.69095	validation-mlogloss:0.70833
[36m(train_xgb_ray_tune pid=1050007)[0m [517]	train-mlogloss:0.75100	validation-mlogloss:0.75118

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:10. Total running time: 15s
[36m(train_xgb_ray_tune pid=1049992)[0m [519]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1050010)[0m [357]	train-mlogloss:0.68101	validation-mlogloss:0.70416
[36m(train_xgb_ray_tune pid=1050014)[0m [555]	train-mlogloss:0.74644	validation-mlogloss:0.74737
[36m(train_xgb_ray_tune pid=1050017)[0m [630]	train-mlogloss:0.98710	validation-mlogloss:0.97438
[36m(train_xgb_ray_tune pid=1050020)[0m [383]	train-mlogloss:0.96018	validation-mlogloss:0.95110
[36m(train_xgb_ray_tune pid=1049992)[0m [520]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [521]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [522]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [523]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [524]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [525]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [526]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [527]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [528]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [529]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [530]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [531]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [532]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [533]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [534]	train-mlogloss:0.86161	validation-mlogloss:0.85332
[36m(train_xgb_ray_tune pid=1049992)[0m [535]	train-mlogloss:0.86161	validation-mlogloss:0.85331
[36m(train_xgb_ray_tune pid=1050010)[0m [358]	train-mlogloss:0.68077	validation-mlogloss:0.70399
[36m(train_xgb_ray_tune pid=1050010)[0m [359]	train-mlogloss:0.68053	validation-mlogloss:0.70387
[36m(train_xgb_ray_tune pid=1050010)[0m [360]	train-mlogloss:0.68041	validation-mlogloss:0.70370
[36m(train_xgb_ray_tune pid=1050010)[0m [361]	train-mlogloss:0.68031	validation-mlogloss:0.70362
[36m(train_xgb_ray_tune pid=1050010)[0m [362]	train-mlogloss:0.67998	validation-mlogloss:0.70338
[36m(train_xgb_ray_tune pid=1050010)[0m [363]	train-mlogloss:0.67985	validation-mlogloss:0.70328
[36m(train_xgb_ray_tune pid=1050010)[0m [364]	train-mlogloss:0.67959	validation-mlogloss:0.70318
[36m(train_xgb_ray_tune pid=1050010)[0m [365]	train-mlogloss:0.67939	validation-mlogloss:0.70315
[36m(train_xgb_ray_tune pid=1050010)[0m [366]	train-mlogloss:0.67919	validation-mlogloss:0.70313
[36m(train_xgb_ray_tune pid=1050010)[0m [367]	train-mlogloss:0.67902	validation-mlogloss:0.70298
[36m(train_xgb_ray_tune pid=1050010)[0m [368]	train-mlogloss:0.67879	validation-mlogloss:0.70283
[36m(train_xgb_ray_tune pid=1050010)[0m [369]	train-mlogloss:0.67861	validation-mlogloss:0.70277
[36m(train_xgb_ray_tune pid=1050006)[0m [341]	train-mlogloss:0.71636	validation-mlogloss:0.72826
[36m(train_xgb_ray_tune pid=1050006)[0m [342]	train-mlogloss:0.71597	validation-mlogloss:0.72798
[36m(train_xgb_ray_tune pid=1050006)[0m [343]	train-mlogloss:0.71551	validation-mlogloss:0.72771
[36m(train_xgb_ray_tune pid=1050006)[0m [344]	train-mlogloss:0.71520	validation-mlogloss:0.72748
[36m(train_xgb_ray_tune pid=1050006)[0m [345]	train-mlogloss:0.71477	validation-mlogloss:0.72713
[36m(train_xgb_ray_tune pid=1050006)[0m [346]	train-mlogloss:0.71445	validation-mlogloss:0.72682
[36m(train_xgb_ray_tune pid=1050006)[0m [347]	train-mlogloss:0.71411	validation-mlogloss:0.72645
[36m(train_xgb_ray_tune pid=1050006)[0m [348]	train-mlogloss:0.71372	validation-mlogloss:0.72617
[36m(train_xgb_ray_tune pid=1050006)[0m [349]	train-mlogloss:0.71342	validation-mlogloss:0.72593
[36m(train_xgb_ray_tune pid=1050006)[0m [350]	train-mlogloss:0.71317	validation-mlogloss:0.72573
[36m(train_xgb_ray_tune pid=1050009)[0m [411]	train-mlogloss:0.69070	validation-mlogloss:0.70826
[36m(train_xgb_ray_tune pid=1050009)[0m [412]	train-mlogloss:0.69038	validation-mlogloss:0.70803
[36m(train_xgb_ray_tune pid=1050009)[0m [413]	train-mlogloss:0.69011	validation-mlogloss:0.70778
[36m(train_xgb_ray_tune pid=1050009)[0m [414]	train-mlogloss:0.68990	validation-mlogloss:0.70764
[36m(train_xgb_ray_tune pid=1050009)[0m [415]	train-mlogloss:0.68963	validation-mlogloss:0.70742
[36m(train_xgb_ray_tune pid=1050009)[0m [416]	train-mlogloss:0.68942	validation-mlogloss:0.70724
[36m(train_xgb_ray_tune pid=1050009)[0m [417]	train-mlogloss:0.68919	validation-mlogloss:0.70709
[36m(train_xgb_ray_tune pid=1050009)[0m [418]	train-mlogloss:0.68896	validation-mlogloss:0.70693
[36m(train_xgb_ray_tune pid=1050009)[0m [419]	train-mlogloss:0.68865	validation-mlogloss:0.70675
[36m(train_xgb_ray_tune pid=1050009)[0m [420]	train-mlogloss:0.68840	validation-mlogloss:0.70657
[36m(train_xgb_ray_tune pid=1050014)[0m [556]	train-mlogloss:0.74644	validation-mlogloss:0.74737
[36m(train_xgb_ray_tune pid=1050014)[0m [557]	train-mlogloss:0.74644	validation-mlogloss:0.74738
[36m(train_xgb_ray_tune pid=1050014)[0m [558]	train-mlogloss:0.74644	validation-mlogloss:0.74738
[36m(train_xgb_ray_tune pid=1050014)[0m [559]	train-mlogloss:0.74640	validation-mlogloss:0.74733
[36m(train_xgb_ray_tune pid=1050014)[0m [560]	train-mlogloss:0.74640	validation-mlogloss:0.74733
[36m(train_xgb_ray_tune pid=1050014)[0m [561]	train-mlogloss:0.74640	validation-mlogloss:0.74733
[36m(train_xgb_ray_tune pid=1050014)[0m [562]	train-mlogloss:0.74636	validation-mlogloss:0.74725
[36m(train_xgb_ray_tune pid=1050014)[0m [563]	train-mlogloss:0.74621	validation-mlogloss:0.74720
[36m(train_xgb_ray_tune pid=1050014)[0m [564]	train-mlogloss:0.74621	validation-mlogloss:0.74720
[36m(train_xgb_ray_tune pid=1050014)[0m [565]	train-mlogloss:0.74617	validation-mlogloss:0.74716
[36m(train_xgb_ray_tune pid=1050014)[0m [566]	train-mlogloss:0.74603	validation-mlogloss:0.74708
[36m(train_xgb_ray_tune pid=1050014)[0m [567]	train-mlogloss:0.74603	validation-mlogloss:0.74708
[36m(train_xgb_ray_tune pid=1050014)[0m [568]	train-mlogloss:0.74603	validation-mlogloss:0.74708
[36m(train_xgb_ray_tune pid=1050014)[0m [569]	train-mlogloss:0.74599	validation-mlogloss:0.74700
[36m(train_xgb_ray_tune pid=1050014)[0m [570]	train-mlogloss:0.74599	validation-mlogloss:0.74700
[36m(train_xgb_ray_tune pid=1050017)[0m [631]	train-mlogloss:0.98687	validation-mlogloss:0.97413
[36m(train_xgb_ray_tune pid=1050017)[0m [632]	train-mlogloss:0.98667	validation-mlogloss:0.97393
[36m(train_xgb_ray_tune pid=1050017)[0m [633]	train-mlogloss:0.98650	validation-mlogloss:0.97378
[36m(train_xgb_ray_tune pid=1050017)[0m [634]	train-mlogloss:0.98631	validation-mlogloss:0.97360
[36m(train_xgb_ray_tune pid=1050017)[0m [635]	train-mlogloss:0.98613	validation-mlogloss:0.97343
[36m(train_xgb_ray_tune pid=1050017)[0m [636]	train-mlogloss:0.98596	validation-mlogloss:0.97327
[36m(train_xgb_ray_tune pid=1050017)[0m [637]	train-mlogloss:0.98576	validation-mlogloss:0.97305
[36m(train_xgb_ray_tune pid=1050017)[0m [638]	train-mlogloss:0.98557	validation-mlogloss:0.97285
[36m(train_xgb_ray_tune pid=1050017)[0m [639]	train-mlogloss:0.98544	validation-mlogloss:0.97273
[36m(train_xgb_ray_tune pid=1050017)[0m [640]	train-mlogloss:0.98519	validation-mlogloss:0.97245
[36m(train_xgb_ray_tune pid=1050017)[0m [641]	train-mlogloss:0.98498	validation-mlogloss:0.97224
[36m(train_xgb_ray_tune pid=1050017)[0m [642]	train-mlogloss:0.98477	validation-mlogloss:0.97203
[36m(train_xgb_ray_tune pid=1050017)[0m [643]	train-mlogloss:0.98456	validation-mlogloss:0.97180
[36m(train_xgb_ray_tune pid=1050017)[0m [644]	train-mlogloss:0.98437	validation-mlogloss:0.97164
[36m(train_xgb_ray_tune pid=1050007)[0m [518]	train-mlogloss:0.75100	validation-mlogloss:0.75118
[36m(train_xgb_ray_tune pid=1050007)[0m [519]	train-mlogloss:0.75100	validation-mlogloss:0.75118
[36m(train_xgb_ray_tune pid=1050007)[0m [520]	train-mlogloss:0.75100	validation-mlogloss:0.75118
[36m(train_xgb_ray_tune pid=1050007)[0m [521]	train-mlogloss:0.75100	validation-mlogloss:0.75118
[36m(train_xgb_ray_tune pid=1050007)[0m [522]	train-mlogloss:0.75100	validation-mlogloss:0.75118
[36m(train_xgb_ray_tune pid=1050007)[0m [523]	train-mlogloss:0.75100	validation-mlogloss:0.75118
[36m(train_xgb_ray_tune pid=1050007)[0m [524]	train-mlogloss:0.75100	validation-mlogloss:0.75119
[36m(train_xgb_ray_tune pid=1050007)[0m [525]	train-mlogloss:0.75099	validation-mlogloss:0.75119
[36m(train_xgb_ray_tune pid=1050007)[0m [526]	train-mlogloss:0.75099	validation-mlogloss:0.75119
[36m(train_xgb_ray_tune pid=1050007)[0m [527]	train-mlogloss:0.75099	validation-mlogloss:0.75119
[36m(train_xgb_ray_tune pid=1050007)[0m [528]	train-mlogloss:0.75099	validation-mlogloss:0.75119
[36m(train_xgb_ray_tune pid=1050007)[0m [529]	train-mlogloss:0.75099	validation-mlogloss:0.75119
[36m(train_xgb_ray_tune pid=1050007)[0m [530]	train-mlogloss:0.75094	validation-mlogloss:0.75117
[36m(train_xgb_ray_tune pid=1050007)[0m [531]	train-mlogloss:0.75094	validation-mlogloss:0.75117
[36m(train_xgb_ray_tune pid=1050007)[0m [532]	train-mlogloss:0.75089	validation-mlogloss:0.75111
[36m(train_xgb_ray_tune pid=1050007)[0m [533]	train-mlogloss:0.75089	validation-mlogloss:0.75111
[36m(train_xgb_ray_tune pid=1050020)[0m [384]	train-mlogloss:0.95979	validation-mlogloss:0.95074
[36m(train_xgb_ray_tune pid=1050020)[0m [385]	train-mlogloss:0.95937	validation-mlogloss:0.95029
[36m(train_xgb_ray_tune pid=1050020)[0m [386]	train-mlogloss:0.95892	validation-mlogloss:0.94983
[36m(train_xgb_ray_tune pid=1050020)[0m [387]	train-mlogloss:0.95859	validation-mlogloss:0.94952
[36m(train_xgb_ray_tune pid=1050020)[0m [388]	train-mlogloss:0.95812	validation-mlogloss:0.94905
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[36m(train_xgb_ray_tune pid=1050020)[0m [390]	train-mlogloss:0.95724	validation-mlogloss:0.94811
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[36m(train_xgb_ray_tune pid=1050010)[0m [370]	train-mlogloss:0.67843	validation-mlogloss:0.70261
[36m(train_xgb_ray_tune pid=1050017)[0m [645]	train-mlogloss:0.98413	validation-mlogloss:0.97138
[36m(train_xgb_ray_tune pid=1050020)[0m [394]	train-mlogloss:0.95561	validation-mlogloss:0.94650
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[36m(train_xgb_ray_tune pid=1050017)[0m [646]	train-mlogloss:0.98394	validation-mlogloss:0.97118
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[36m(train_xgb_ray_tune pid=1050010)[0m [374]	train-mlogloss:0.67795	validation-mlogloss:0.70220
[36m(train_xgb_ray_tune pid=1050006)[0m [354]	train-mlogloss:0.71173	validation-mlogloss:0.72463
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[36m(train_xgb_ray_tune pid=1050020)[0m [398]	train-mlogloss:0.95413	validation-mlogloss:0.94503
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[36m(train_xgb_ray_tune pid=1050004)[0m [404]	train-mlogloss:0.94320	validation-mlogloss:0.93097
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[36m(train_xgb_ray_tune pid=1050020)[0m [399]	train-mlogloss:0.95373	validation-mlogloss:0.94466
[36m(train_xgb_ray_tune pid=1049992)[0m [544]	train-mlogloss:0.86160	validation-mlogloss:0.85331
[36m(train_xgb_ray_tune pid=1050017)[0m [652]	train-mlogloss:0.98280	validation-mlogloss:0.97005
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[36m(train_xgb_ray_tune pid=1050010)[0m [377]	train-mlogloss:0.67738	validation-mlogloss:0.70183
[36m(train_xgb_ray_tune pid=1050017)[0m [653]	train-mlogloss:0.98260	validation-mlogloss:0.96985
[36m(train_xgb_ray_tune pid=1050009)[0m [426]	train-mlogloss:0.68696	validation-mlogloss:0.70568
[36m(train_xgb_ray_tune pid=1050007)[0m [543]	train-mlogloss:0.75071	validation-mlogloss:0.75100
[36m(train_xgb_ray_tune pid=1050020)[0m [400]	train-mlogloss:0.95335	validation-mlogloss:0.94426
[36m(train_xgb_ray_tune pid=1050004)[0m [406]	train-mlogloss:0.94263	validation-mlogloss:0.93039
[36m(train_xgb_ray_tune pid=1049992)[0m [546]	train-mlogloss:0.86160	validation-mlogloss:0.85331
[36m(train_xgb_ray_tune pid=1050006)[0m [357]	train-mlogloss:0.71084	validation-mlogloss:0.72398
[36m(train_xgb_ray_tune pid=1050010)[0m [378]	train-mlogloss:0.67710	validation-mlogloss:0.70168
[36m(train_xgb_ray_tune pid=1050017)[0m [654]	train-mlogloss:0.98243	validation-mlogloss:0.96968
[36m(train_xgb_ray_tune pid=1050007)[0m [544]	train-mlogloss:0.75071	validation-mlogloss:0.75100
[36m(train_xgb_ray_tune pid=1049992)[0m [547]	train-mlogloss:0.86160	validation-mlogloss:0.85331
[36m(train_xgb_ray_tune pid=1050020)[0m [401]	train-mlogloss:0.95296	validation-mlogloss:0.94387
[36m(train_xgb_ray_tune pid=1050004)[0m [407]	train-mlogloss:0.94234	validation-mlogloss:0.93010
[36m(train_xgb_ray_tune pid=1050017)[0m [655]	train-mlogloss:0.98222	validation-mlogloss:0.96946
[36m(train_xgb_ray_tune pid=1050007)[0m [545]	train-mlogloss:0.75071	validation-mlogloss:0.75100
[36m(train_xgb_ray_tune pid=1049992)[0m [548]	train-mlogloss:0.86160	validation-mlogloss:0.85331
[36m(train_xgb_ray_tune pid=1050010)[0m [379]	train-mlogloss:0.67698	validation-mlogloss:0.70159
[36m(train_xgb_ray_tune pid=1050006)[0m [358]	train-mlogloss:0.71055	validation-mlogloss:0.72376
[36m(train_xgb_ray_tune pid=1050009)[0m [427]	train-mlogloss:0.68671	validation-mlogloss:0.70551
[36m(train_xgb_ray_tune pid=1050004)[0m [408]	train-mlogloss:0.94208	validation-mlogloss:0.92985

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:11. Total running time: 15s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             12.3744 │
│ time_total_s                 12.3744 │
│ training_iteration                 1 │
│ validation_accuracy          0.69593 │
╰──────────────────────────────────────╯

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:11. Total running time: 15s
[36m(train_xgb_ray_tune pid=1049992)[0m [549]	train-mlogloss:0.86160	validation-mlogloss:0.85331
[36m(train_xgb_ray_tune pid=1049992)[0m [550]	train-mlogloss:0.86160	validation-mlogloss:0.85331
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[36m(train_xgb_ray_tune pid=1050010)[0m [385]	train-mlogloss:0.67604	validation-mlogloss:0.70101
[36m(train_xgb_ray_tune pid=1050010)[0m [386]	train-mlogloss:0.67591	validation-mlogloss:0.70096
[36m(train_xgb_ray_tune pid=1050010)[0m [387]	train-mlogloss:0.67580	validation-mlogloss:0.70090
[36m(train_xgb_ray_tune pid=1050010)[0m [388]	train-mlogloss:0.67567	validation-mlogloss:0.70078
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[36m(train_xgb_ray_tune pid=1050006)[0m [363]	train-mlogloss:0.70913	validation-mlogloss:0.72249
[36m(train_xgb_ray_tune pid=1050006)[0m [364]	train-mlogloss:0.70880	validation-mlogloss:0.72220
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[36m(train_xgb_ray_tune pid=1050009)[0m [428]	train-mlogloss:0.68654	validation-mlogloss:0.70539
[36m(train_xgb_ray_tune pid=1050009)[0m [429]	train-mlogloss:0.68621	validation-mlogloss:0.70517
[36m(train_xgb_ray_tune pid=1050009)[0m [430]	train-mlogloss:0.68593	validation-mlogloss:0.70507
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[36m(train_xgb_ray_tune pid=1050009)[0m [436]	train-mlogloss:0.68450	validation-mlogloss:0.70406
[36m(train_xgb_ray_tune pid=1050009)[0m [437]	train-mlogloss:0.68423	validation-mlogloss:0.70389
[36m(train_xgb_ray_tune pid=1050017)[0m [656]	train-mlogloss:0.98205	validation-mlogloss:0.96929
[36m(train_xgb_ray_tune pid=1050017)[0m [657]	train-mlogloss:0.98186	validation-mlogloss:0.96911
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[36m(train_xgb_ray_tune pid=1050017)[0m [659]	train-mlogloss:0.98148	validation-mlogloss:0.96873
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[36m(train_xgb_ray_tune pid=1050017)[0m [662]	train-mlogloss:0.98088	validation-mlogloss:0.96812
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[36m(train_xgb_ray_tune pid=1050017)[0m [664]	train-mlogloss:0.98053	validation-mlogloss:0.96780
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[36m(train_xgb_ray_tune pid=1050017)[0m [684]	train-mlogloss:0.97703	validation-mlogloss:0.96421
[36m(train_xgb_ray_tune pid=1050017)[0m [685]	train-mlogloss:0.97691	validation-mlogloss:0.96410
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[36m(train_xgb_ray_tune pid=1050017)[0m [687]	train-mlogloss:0.97660	validation-mlogloss:0.96379
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[36m(train_xgb_ray_tune pid=1050007)[0m [581]	train-mlogloss:0.74975	validation-mlogloss:0.75050
[36m(train_xgb_ray_tune pid=1050020)[0m [415]	train-mlogloss:0.94760	validation-mlogloss:0.93838
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[36m(train_xgb_ray_tune pid=1050020)[0m [418]	train-mlogloss:0.94646	validation-mlogloss:0.93723
[36m(train_xgb_ray_tune pid=1050020)[0m [419]	train-mlogloss:0.94609	validation-mlogloss:0.93684
[36m(train_xgb_ray_tune pid=1050020)[0m [420]	train-mlogloss:0.94569	validation-mlogloss:0.93644
[36m(train_xgb_ray_tune pid=1050020)[0m [421]	train-mlogloss:0.94539	validation-mlogloss:0.93614
[36m(train_xgb_ray_tune pid=1050020)[0m [422]	train-mlogloss:0.94502	validation-mlogloss:0.93577
[36m(train_xgb_ray_tune pid=1050020)[0m [423]	train-mlogloss:0.94462	validation-mlogloss:0.93537
[36m(train_xgb_ray_tune pid=1050020)[0m [424]	train-mlogloss:0.94423	validation-mlogloss:0.93499
[36m(train_xgb_ray_tune pid=1050020)[0m [425]	train-mlogloss:0.94386	validation-mlogloss:0.93463
[36m(train_xgb_ray_tune pid=1050004)[0m [424]	train-mlogloss:0.93758	validation-mlogloss:0.92534
[36m(train_xgb_ray_tune pid=1050004)[0m [425]	train-mlogloss:0.93723	validation-mlogloss:0.92499
[36m(train_xgb_ray_tune pid=1050004)[0m [426]	train-mlogloss:0.93695	validation-mlogloss:0.92471
[36m(train_xgb_ray_tune pid=1050004)[0m [427]	train-mlogloss:0.93663	validation-mlogloss:0.92438
[36m(train_xgb_ray_tune pid=1050004)[0m [428]	train-mlogloss:0.93636	validation-mlogloss:0.92409
[36m(train_xgb_ray_tune pid=1050004)[0m [429]	train-mlogloss:0.93604	validation-mlogloss:0.92376
[36m(train_xgb_ray_tune pid=1050004)[0m [430]	train-mlogloss:0.93575	validation-mlogloss:0.92349
[36m(train_xgb_ray_tune pid=1050004)[0m [431]	train-mlogloss:0.93548	validation-mlogloss:0.92320
[36m(train_xgb_ray_tune pid=1050004)[0m [432]	train-mlogloss:0.93520	validation-mlogloss:0.92292
[36m(train_xgb_ray_tune pid=1050004)[0m [433]	train-mlogloss:0.93493	validation-mlogloss:0.92264
[36m(train_xgb_ray_tune pid=1050004)[0m [434]	train-mlogloss:0.93468	validation-mlogloss:0.92239
[36m(train_xgb_ray_tune pid=1050004)[0m [435]	train-mlogloss:0.93441	validation-mlogloss:0.92213
[36m(train_xgb_ray_tune pid=1049992)[0m [584]	train-mlogloss:0.86135	validation-mlogloss:0.85305

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:11. Total running time: 15s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             12.5411 │
│ time_total_s                 12.5411 │
│ training_iteration                 1 │
│ validation_accuracy           0.7184 │
╰──────────────────────────────────────╯

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:11. Total running time: 15s
[36m(train_xgb_ray_tune pid=1049992)[0m [585]	train-mlogloss:0.86135	validation-mlogloss:0.85305
[36m(train_xgb_ray_tune pid=1049992)[0m [586]	train-mlogloss:0.86135	validation-mlogloss:0.85305
[36m(train_xgb_ray_tune pid=1049992)[0m [587]	train-mlogloss:0.86135	validation-mlogloss:0.85305
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[36m(train_xgb_ray_tune pid=1050004)[0m [456]	train-mlogloss:0.92886	validation-mlogloss:0.91639
[36m(train_xgb_ray_tune pid=1050004)[0m [457]	train-mlogloss:0.92864	validation-mlogloss:0.91617
[36m(train_xgb_ray_tune pid=1050004)[0m [458]	train-mlogloss:0.92839	validation-mlogloss:0.91592
[36m(train_xgb_ray_tune pid=1050004)[0m [459]	train-mlogloss:0.92815	validation-mlogloss:0.91567
[36m(train_xgb_ray_tune pid=1050004)[0m [460]	train-mlogloss:0.92793	validation-mlogloss:0.91544
[36m(train_xgb_ray_tune pid=1050004)[0m [461]	train-mlogloss:0.92768	validation-mlogloss:0.91523

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:11. Total running time: 15s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             12.9752 │
│ time_total_s                 12.9752 │
│ training_iteration                 1 │
│ validation_accuracy          0.65765 │
╰──────────────────────────────────────╯

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:11. Total running time: 15s
[36m(train_xgb_ray_tune pid=1050010)[0m [438]	train-mlogloss:0.67029	validation-mlogloss:0.69734
[36m(train_xgb_ray_tune pid=1050010)[0m [439]	train-mlogloss:0.67026	validation-mlogloss:0.69732
[36m(train_xgb_ray_tune pid=1050010)[0m [440]	train-mlogloss:0.67015	validation-mlogloss:0.69733
[36m(train_xgb_ray_tune pid=1050010)[0m [441]	train-mlogloss:0.67006	validation-mlogloss:0.69721
[36m(train_xgb_ray_tune pid=1050010)[0m [442]	train-mlogloss:0.66998	validation-mlogloss:0.69716
[36m(train_xgb_ray_tune pid=1050010)[0m [443]	train-mlogloss:0.66988	validation-mlogloss:0.69712
[36m(train_xgb_ray_tune pid=1050010)[0m [444]	train-mlogloss:0.66979	validation-mlogloss:0.69707
[36m(train_xgb_ray_tune pid=1050010)[0m [445]	train-mlogloss:0.66974	validation-mlogloss:0.69700
[36m(train_xgb_ray_tune pid=1050010)[0m [446]	train-mlogloss:0.66965	validation-mlogloss:0.69688
[36m(train_xgb_ray_tune pid=1050010)[0m [447]	train-mlogloss:0.66963	validation-mlogloss:0.69686
[36m(train_xgb_ray_tune pid=1050010)[0m [448]	train-mlogloss:0.66953	validation-mlogloss:0.69679
[36m(train_xgb_ray_tune pid=1050010)[0m [449]	train-mlogloss:0.66950	validation-mlogloss:0.69676
[36m(train_xgb_ray_tune pid=1050009)[0m [473]	train-mlogloss:0.67707	validation-mlogloss:0.69901
[36m(train_xgb_ray_tune pid=1050009)[0m [474]	train-mlogloss:0.67695	validation-mlogloss:0.69898
[36m(train_xgb_ray_tune pid=1050009)[0m [475]	train-mlogloss:0.67675	validation-mlogloss:0.69881
[36m(train_xgb_ray_tune pid=1050009)[0m [476]	train-mlogloss:0.67654	validation-mlogloss:0.69871
[36m(train_xgb_ray_tune pid=1050009)[0m [477]	train-mlogloss:0.67636	validation-mlogloss:0.69862
[36m(train_xgb_ray_tune pid=1050009)[0m [478]	train-mlogloss:0.67625	validation-mlogloss:0.69851
[36m(train_xgb_ray_tune pid=1050009)[0m [479]	train-mlogloss:0.67609	validation-mlogloss:0.69839
[36m(train_xgb_ray_tune pid=1050009)[0m [480]	train-mlogloss:0.67602	validation-mlogloss:0.69838
[36m(train_xgb_ray_tune pid=1050009)[0m [481]	train-mlogloss:0.67591	validation-mlogloss:0.69834
[36m(train_xgb_ray_tune pid=1050009)[0m [482]	train-mlogloss:0.67585	validation-mlogloss:0.69830
[36m(train_xgb_ray_tune pid=1050009)[0m [483]	train-mlogloss:0.67572	validation-mlogloss:0.69817
[36m(train_xgb_ray_tune pid=1050009)[0m [484]	train-mlogloss:0.67553	validation-mlogloss:0.69801
[36m(train_xgb_ray_tune pid=1050017)[0m [718]	train-mlogloss:0.97186	validation-mlogloss:0.95902
[36m(train_xgb_ray_tune pid=1050017)[0m [719]	train-mlogloss:0.97171	validation-mlogloss:0.95887
[36m(train_xgb_ray_tune pid=1050017)[0m [720]	train-mlogloss:0.97152	validation-mlogloss:0.95867
[36m(train_xgb_ray_tune pid=1050017)[0m [721]	train-mlogloss:0.97133	validation-mlogloss:0.95847
[36m(train_xgb_ray_tune pid=1050017)[0m [722]	train-mlogloss:0.97116	validation-mlogloss:0.95830
[36m(train_xgb_ray_tune pid=1050017)[0m [723]	train-mlogloss:0.97097	validation-mlogloss:0.95810
[36m(train_xgb_ray_tune pid=1050017)[0m [724]	train-mlogloss:0.97082	validation-mlogloss:0.95795
[36m(train_xgb_ray_tune pid=1050017)[0m [725]	train-mlogloss:0.97063	validation-mlogloss:0.95775
[36m(train_xgb_ray_tune pid=1050017)[0m [726]	train-mlogloss:0.97045	validation-mlogloss:0.95756
[36m(train_xgb_ray_tune pid=1050017)[0m [727]	train-mlogloss:0.97031	validation-mlogloss:0.95741
[36m(train_xgb_ray_tune pid=1050007)[0m [616]	train-mlogloss:0.74946	validation-mlogloss:0.75023
[36m(train_xgb_ray_tune pid=1050007)[0m [617]	train-mlogloss:0.74946	validation-mlogloss:0.75023
[36m(train_xgb_ray_tune pid=1050007)[0m [618]	train-mlogloss:0.74946	validation-mlogloss:0.75022
[36m(train_xgb_ray_tune pid=1050007)[0m [619]	train-mlogloss:0.74940	validation-mlogloss:0.75017
[36m(train_xgb_ray_tune pid=1050007)[0m [620]	train-mlogloss:0.74940	validation-mlogloss:0.75017
[36m(train_xgb_ray_tune pid=1050007)[0m [621]	train-mlogloss:0.74940	validation-mlogloss:0.75016
[36m(train_xgb_ray_tune pid=1050007)[0m [622]	train-mlogloss:0.74940	validation-mlogloss:0.75016
[36m(train_xgb_ray_tune pid=1050007)[0m [623]	train-mlogloss:0.74940	validation-mlogloss:0.75016
[36m(train_xgb_ray_tune pid=1050007)[0m [624]	train-mlogloss:0.74940	validation-mlogloss:0.75016
[36m(train_xgb_ray_tune pid=1050007)[0m [625]	train-mlogloss:0.74936	validation-mlogloss:0.75010
[36m(train_xgb_ray_tune pid=1050007)[0m [626]	train-mlogloss:0.74936	validation-mlogloss:0.75010
[36m(train_xgb_ray_tune pid=1050007)[0m [627]	train-mlogloss:0.74936	validation-mlogloss:0.75011
[36m(train_xgb_ray_tune pid=1050007)[0m [628]	train-mlogloss:0.74936	validation-mlogloss:0.75011
[36m(train_xgb_ray_tune pid=1050007)[0m [629]	train-mlogloss:0.74936	validation-mlogloss:0.75011
[36m(train_xgb_ray_tune pid=1050007)[0m [630]	train-mlogloss:0.74936	validation-mlogloss:0.75011
[36m(train_xgb_ray_tune pid=1050007)[0m [631]	train-mlogloss:0.74936	validation-mlogloss:0.75011
[36m(train_xgb_ray_tune pid=1050020)[0m [448]	train-mlogloss:0.93574	validation-mlogloss:0.92642
[36m(train_xgb_ray_tune pid=1050020)[0m [449]	train-mlogloss:0.93542	validation-mlogloss:0.92609
[36m(train_xgb_ray_tune pid=1050020)[0m [450]	train-mlogloss:0.93504	validation-mlogloss:0.92569
[36m(train_xgb_ray_tune pid=1050020)[0m [451]	train-mlogloss:0.93472	validation-mlogloss:0.92538
[36m(train_xgb_ray_tune pid=1050020)[0m [452]	train-mlogloss:0.93439	validation-mlogloss:0.92505
[36m(train_xgb_ray_tune pid=1050020)[0m [453]	train-mlogloss:0.93403	validation-mlogloss:0.92467
[36m(train_xgb_ray_tune pid=1050020)[0m [454]	train-mlogloss:0.93365	validation-mlogloss:0.92430
[36m(train_xgb_ray_tune pid=1050020)[0m [455]	train-mlogloss:0.93331	validation-mlogloss:0.92394
[36m(train_xgb_ray_tune pid=1050004)[0m [462]	train-mlogloss:0.92742	validation-mlogloss:0.91494
[36m(train_xgb_ray_tune pid=1050004)[0m [463]	train-mlogloss:0.92722	validation-mlogloss:0.91475
[36m(train_xgb_ray_tune pid=1050004)[0m [464]	train-mlogloss:0.92692	validation-mlogloss:0.91446
[36m(train_xgb_ray_tune pid=1050004)[0m [465]	train-mlogloss:0.92668	validation-mlogloss:0.91420
[36m(train_xgb_ray_tune pid=1050004)[0m [466]	train-mlogloss:0.92644	validation-mlogloss:0.91395
[36m(train_xgb_ray_tune pid=1050004)[0m [467]	train-mlogloss:0.92622	validation-mlogloss:0.91376
[36m(train_xgb_ray_tune pid=1050004)[0m [468]	train-mlogloss:0.92593	validation-mlogloss:0.91344
[36m(train_xgb_ray_tune pid=1050004)[0m [469]	train-mlogloss:0.92572	validation-mlogloss:0.91322
[36m(train_xgb_ray_tune pid=1050004)[0m [470]	train-mlogloss:0.92543	validation-mlogloss:0.91292
[36m(train_xgb_ray_tune pid=1050004)[0m [471]	train-mlogloss:0.92520	validation-mlogloss:0.91269
[36m(train_xgb_ray_tune pid=1050004)[0m [472]	train-mlogloss:0.92498	validation-mlogloss:0.91244
[36m(train_xgb_ray_tune pid=1050007)[0m [632]	train-mlogloss:0.74936	validation-mlogloss:0.75012
[36m(train_xgb_ray_tune pid=1050004)[0m [473]	train-mlogloss:0.92470	validation-mlogloss:0.91212
[36m(train_xgb_ray_tune pid=1050010)[0m [450]	train-mlogloss:0.66942	validation-mlogloss:0.69670
[36m(train_xgb_ray_tune pid=1050009)[0m [485]	train-mlogloss:0.67532	validation-mlogloss:0.69789
[36m(train_xgb_ray_tune pid=1050007)[0m [633]	train-mlogloss:0.74936	validation-mlogloss:0.75012
[36m(train_xgb_ray_tune pid=1050020)[0m [456]	train-mlogloss:0.93295	validation-mlogloss:0.92360

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:11. Total running time: 15s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             12.9678 │
│ time_total_s                 12.9678 │
│ training_iteration                 1 │
│ validation_accuracy          0.65169 │
╰──────────────────────────────────────╯

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:11. Total running time: 15s
[36m(train_xgb_ray_tune pid=1050010)[0m [451]	train-mlogloss:0.66940	validation-mlogloss:0.69667
[36m(train_xgb_ray_tune pid=1050010)[0m [452]	train-mlogloss:0.66930	validation-mlogloss:0.69657
[36m(train_xgb_ray_tune pid=1050010)[0m [453]	train-mlogloss:0.66908	validation-mlogloss:0.69642
[36m(train_xgb_ray_tune pid=1050010)[0m [454]	train-mlogloss:0.66905	validation-mlogloss:0.69639
[36m(train_xgb_ray_tune pid=1050010)[0m [455]	train-mlogloss:0.66895	validation-mlogloss:0.69629
[36m(train_xgb_ray_tune pid=1050010)[0m [456]	train-mlogloss:0.66880	validation-mlogloss:0.69628
[36m(train_xgb_ray_tune pid=1050010)[0m [457]	train-mlogloss:0.66876	validation-mlogloss:0.69632
[36m(train_xgb_ray_tune pid=1050010)[0m [458]	train-mlogloss:0.66868	validation-mlogloss:0.69624
[36m(train_xgb_ray_tune pid=1050010)[0m [459]	train-mlogloss:0.66848	validation-mlogloss:0.69613
[36m(train_xgb_ray_tune pid=1050010)[0m [460]	train-mlogloss:0.66848	validation-mlogloss:0.69613
[36m(train_xgb_ray_tune pid=1050010)[0m [461]	train-mlogloss:0.66834	validation-mlogloss:0.69601
[36m(train_xgb_ray_tune pid=1050010)[0m [462]	train-mlogloss:0.66834	validation-mlogloss:0.69601
[36m(train_xgb_ray_tune pid=1050010)[0m [463]	train-mlogloss:0.66831	validation-mlogloss:0.69598
[36m(train_xgb_ray_tune pid=1050010)[0m [464]	train-mlogloss:0.66826	validation-mlogloss:0.69593
[36m(train_xgb_ray_tune pid=1050009)[0m [486]	train-mlogloss:0.67513	validation-mlogloss:0.69772
[36m(train_xgb_ray_tune pid=1050009)[0m [487]	train-mlogloss:0.67500	validation-mlogloss:0.69761
[36m(train_xgb_ray_tune pid=1050009)[0m [488]	train-mlogloss:0.67484	validation-mlogloss:0.69753
[36m(train_xgb_ray_tune pid=1050009)[0m [489]	train-mlogloss:0.67467	validation-mlogloss:0.69745
[36m(train_xgb_ray_tune pid=1050009)[0m [490]	train-mlogloss:0.67453	validation-mlogloss:0.69731
[36m(train_xgb_ray_tune pid=1050009)[0m [491]	train-mlogloss:0.67420	validation-mlogloss:0.69703
[36m(train_xgb_ray_tune pid=1050009)[0m [492]	train-mlogloss:0.67415	validation-mlogloss:0.69695
[36m(train_xgb_ray_tune pid=1050009)[0m [493]	train-mlogloss:0.67391	validation-mlogloss:0.69688
[36m(train_xgb_ray_tune pid=1050009)[0m [494]	train-mlogloss:0.67380	validation-mlogloss:0.69679
[36m(train_xgb_ray_tune pid=1050009)[0m [495]	train-mlogloss:0.67354	validation-mlogloss:0.69660
[36m(train_xgb_ray_tune pid=1050009)[0m [496]	train-mlogloss:0.67335	validation-mlogloss:0.69646
[36m(train_xgb_ray_tune pid=1050007)[0m [634]	train-mlogloss:0.74931	validation-mlogloss:0.75010
[36m(train_xgb_ray_tune pid=1050007)[0m [635]	train-mlogloss:0.74931	validation-mlogloss:0.75010
[36m(train_xgb_ray_tune pid=1050007)[0m [636]	train-mlogloss:0.74931	validation-mlogloss:0.75010
[36m(train_xgb_ray_tune pid=1050007)[0m [637]	train-mlogloss:0.74931	validation-mlogloss:0.75010
[36m(train_xgb_ray_tune pid=1050007)[0m [638]	train-mlogloss:0.74931	validation-mlogloss:0.75010
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[36m(train_xgb_ray_tune pid=1050007)[0m [640]	train-mlogloss:0.74931	validation-mlogloss:0.75009
[36m(train_xgb_ray_tune pid=1050007)[0m [641]	train-mlogloss:0.74919	validation-mlogloss:0.75006
[36m(train_xgb_ray_tune pid=1050007)[0m [642]	train-mlogloss:0.74919	validation-mlogloss:0.75006
[36m(train_xgb_ray_tune pid=1050007)[0m [643]	train-mlogloss:0.74919	validation-mlogloss:0.75006
[36m(train_xgb_ray_tune pid=1050007)[0m [644]	train-mlogloss:0.74919	validation-mlogloss:0.75006
[36m(train_xgb_ray_tune pid=1050007)[0m [645]	train-mlogloss:0.74919	validation-mlogloss:0.75006
[36m(train_xgb_ray_tune pid=1050007)[0m [646]	train-mlogloss:0.74919	validation-mlogloss:0.75006
[36m(train_xgb_ray_tune pid=1050007)[0m [647]	train-mlogloss:0.74919	validation-mlogloss:0.75005
[36m(train_xgb_ray_tune pid=1050007)[0m [648]	train-mlogloss:0.74919	validation-mlogloss:0.75005
[36m(train_xgb_ray_tune pid=1050007)[0m [649]	train-mlogloss:0.74919	validation-mlogloss:0.75006
[36m(train_xgb_ray_tune pid=1050020)[0m [457]	train-mlogloss:0.93263	validation-mlogloss:0.92327
[36m(train_xgb_ray_tune pid=1050020)[0m [458]	train-mlogloss:0.93234	validation-mlogloss:0.92300
[36m(train_xgb_ray_tune pid=1050020)[0m [459]	train-mlogloss:0.93201	validation-mlogloss:0.92267
[36m(train_xgb_ray_tune pid=1050020)[0m [460]	train-mlogloss:0.93172	validation-mlogloss:0.92243
[36m(train_xgb_ray_tune pid=1050020)[0m [461]	train-mlogloss:0.93137	validation-mlogloss:0.92205
[36m(train_xgb_ray_tune pid=1050020)[0m [462]	train-mlogloss:0.93104	validation-mlogloss:0.92171
[36m(train_xgb_ray_tune pid=1050020)[0m [463]	train-mlogloss:0.93070	validation-mlogloss:0.92135
[36m(train_xgb_ray_tune pid=1050020)[0m [464]	train-mlogloss:0.93041	validation-mlogloss:0.92109
[36m(train_xgb_ray_tune pid=1050020)[0m [465]	train-mlogloss:0.93013	validation-mlogloss:0.92080
[36m(train_xgb_ray_tune pid=1050020)[0m [466]	train-mlogloss:0.92987	validation-mlogloss:0.92056
[36m(train_xgb_ray_tune pid=1050020)[0m [467]	train-mlogloss:0.92952	validation-mlogloss:0.92021
[36m(train_xgb_ray_tune pid=1050004)[0m [474]	train-mlogloss:0.92447	validation-mlogloss:0.91190
[36m(train_xgb_ray_tune pid=1050004)[0m [475]	train-mlogloss:0.92425	validation-mlogloss:0.91170
[36m(train_xgb_ray_tune pid=1050004)[0m [476]	train-mlogloss:0.92397	validation-mlogloss:0.91140
[36m(train_xgb_ray_tune pid=1050004)[0m [477]	train-mlogloss:0.92374	validation-mlogloss:0.91115
[36m(train_xgb_ray_tune pid=1050004)[0m [478]	train-mlogloss:0.92352	validation-mlogloss:0.91092
[36m(train_xgb_ray_tune pid=1050004)[0m [479]	train-mlogloss:0.92332	validation-mlogloss:0.91071
[36m(train_xgb_ray_tune pid=1050004)[0m [480]	train-mlogloss:0.92304	validation-mlogloss:0.91044
[36m(train_xgb_ray_tune pid=1050004)[0m [481]	train-mlogloss:0.92281	validation-mlogloss:0.91022
[36m(train_xgb_ray_tune pid=1050004)[0m [482]	train-mlogloss:0.92258	validation-mlogloss:0.90998
[36m(train_xgb_ray_tune pid=1050004)[0m [483]	train-mlogloss:0.92236	validation-mlogloss:0.90978
[36m(train_xgb_ray_tune pid=1050004)[0m [484]	train-mlogloss:0.92211	validation-mlogloss:0.90954
[36m(train_xgb_ray_tune pid=1050004)[0m [485]	train-mlogloss:0.92189	validation-mlogloss:0.90933
[36m(train_xgb_ray_tune pid=1050004)[0m [486]	train-mlogloss:0.92167	validation-mlogloss:0.90909
[36m(train_xgb_ray_tune pid=1050009)[0m [497]	train-mlogloss:0.67324	validation-mlogloss:0.69645
[36m(train_xgb_ray_tune pid=1050010)[0m [465]	train-mlogloss:0.66814	validation-mlogloss:0.69577
[36m(train_xgb_ray_tune pid=1050007)[0m [650]	train-mlogloss:0.74914	validation-mlogloss:0.74999
[36m(train_xgb_ray_tune pid=1050010)[0m [466]	train-mlogloss:0.66809	validation-mlogloss:0.69572
[36m(train_xgb_ray_tune pid=1050010)[0m [467]	train-mlogloss:0.66804	validation-mlogloss:0.69571
[36m(train_xgb_ray_tune pid=1050010)[0m [468]	train-mlogloss:0.66804	validation-mlogloss:0.69571
[36m(train_xgb_ray_tune pid=1050010)[0m [469]	train-mlogloss:0.66797	validation-mlogloss:0.69567
[36m(train_xgb_ray_tune pid=1050010)[0m [470]	train-mlogloss:0.66792	validation-mlogloss:0.69560
[36m(train_xgb_ray_tune pid=1050010)[0m [471]	train-mlogloss:0.66785	validation-mlogloss:0.69557
[36m(train_xgb_ray_tune pid=1050010)[0m [472]	train-mlogloss:0.66781	validation-mlogloss:0.69555
[36m(train_xgb_ray_tune pid=1050010)[0m [473]	train-mlogloss:0.66781	validation-mlogloss:0.69554
[36m(train_xgb_ray_tune pid=1050010)[0m [474]	train-mlogloss:0.66771	validation-mlogloss:0.69550
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[36m(train_xgb_ray_tune pid=1050007)[0m [696]	train-mlogloss:0.74873	validation-mlogloss:0.74962
[36m(train_xgb_ray_tune pid=1050007)[0m [697]	train-mlogloss:0.74873	validation-mlogloss:0.74962
[36m(train_xgb_ray_tune pid=1050007)[0m [698]	train-mlogloss:0.74873	validation-mlogloss:0.74962
[36m(train_xgb_ray_tune pid=1050007)[0m [699]	train-mlogloss:0.74873	validation-mlogloss:0.74962
[36m(train_xgb_ray_tune pid=1050007)[0m [700]	train-mlogloss:0.74873	validation-mlogloss:0.74962
[36m(train_xgb_ray_tune pid=1050007)[0m [701]	train-mlogloss:0.74873	validation-mlogloss:0.74962
[36m(train_xgb_ray_tune pid=1050007)[0m [702]	train-mlogloss:0.74873	validation-mlogloss:0.74962
[36m(train_xgb_ray_tune pid=1050007)[0m [703]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [704]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [705]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050020)[0m [493]	train-mlogloss:0.92180	validation-mlogloss:0.91227
[36m(train_xgb_ray_tune pid=1050020)[0m [494]	train-mlogloss:0.92147	validation-mlogloss:0.91196
[36m(train_xgb_ray_tune pid=1050020)[0m [495]	train-mlogloss:0.92119	validation-mlogloss:0.91165
[36m(train_xgb_ray_tune pid=1050020)[0m [496]	train-mlogloss:0.92089	validation-mlogloss:0.91132
[36m(train_xgb_ray_tune pid=1050020)[0m [497]	train-mlogloss:0.92068	validation-mlogloss:0.91113
[36m(train_xgb_ray_tune pid=1050020)[0m [498]	train-mlogloss:0.92046	validation-mlogloss:0.91093
[36m(train_xgb_ray_tune pid=1050020)[0m [499]	train-mlogloss:0.92027	validation-mlogloss:0.91075
[36m(train_xgb_ray_tune pid=1050020)[0m [500]	train-mlogloss:0.91999	validation-mlogloss:0.91046
[36m(train_xgb_ray_tune pid=1050020)[0m [501]	train-mlogloss:0.91969	validation-mlogloss:0.91013
[36m(train_xgb_ray_tune pid=1050020)[0m [502]	train-mlogloss:0.91942	validation-mlogloss:0.90986
[36m(train_xgb_ray_tune pid=1050020)[0m [503]	train-mlogloss:0.91914	validation-mlogloss:0.90958
[36m(train_xgb_ray_tune pid=1050020)[0m [504]	train-mlogloss:0.91887	validation-mlogloss:0.90929
[36m(train_xgb_ray_tune pid=1050004)[0m [517]	train-mlogloss:0.91483	validation-mlogloss:0.90221
[36m(train_xgb_ray_tune pid=1050004)[0m [518]	train-mlogloss:0.91464	validation-mlogloss:0.90204
[36m(train_xgb_ray_tune pid=1050004)[0m [519]	train-mlogloss:0.91445	validation-mlogloss:0.90185
[36m(train_xgb_ray_tune pid=1050004)[0m [520]	train-mlogloss:0.91423	validation-mlogloss:0.90165
[36m(train_xgb_ray_tune pid=1050004)[0m [521]	train-mlogloss:0.91399	validation-mlogloss:0.90140
[36m(train_xgb_ray_tune pid=1050004)[0m [522]	train-mlogloss:0.91379	validation-mlogloss:0.90118
[36m(train_xgb_ray_tune pid=1050004)[0m [523]	train-mlogloss:0.91356	validation-mlogloss:0.90096
[36m(train_xgb_ray_tune pid=1050004)[0m [524]	train-mlogloss:0.91335	validation-mlogloss:0.90074
[36m(train_xgb_ray_tune pid=1050004)[0m [525]	train-mlogloss:0.91312	validation-mlogloss:0.90052
[36m(train_xgb_ray_tune pid=1050004)[0m [526]	train-mlogloss:0.91293	validation-mlogloss:0.90035
[36m(train_xgb_ray_tune pid=1050004)[0m [527]	train-mlogloss:0.91269	validation-mlogloss:0.90011
[36m(train_xgb_ray_tune pid=1050004)[0m [528]	train-mlogloss:0.91248	validation-mlogloss:0.89988
[36m(train_xgb_ray_tune pid=1050004)[0m [529]	train-mlogloss:0.91224	validation-mlogloss:0.89963
[36m(train_xgb_ray_tune pid=1050004)[0m [530]	train-mlogloss:0.91205	validation-mlogloss:0.89942
[36m(train_xgb_ray_tune pid=1050009)[0m [539]	train-mlogloss:0.66773	validation-mlogloss:0.69258
[36m(train_xgb_ray_tune pid=1050007)[0m [706]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050020)[0m [505]	train-mlogloss:0.91855	validation-mlogloss:0.90898
[36m(train_xgb_ray_tune pid=1050004)[0m [531]	train-mlogloss:0.91179	validation-mlogloss:0.89915

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:12. Total running time: 16s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             13.2888 │
│ time_total_s                 13.2888 │
│ training_iteration                 1 │
│ validation_accuracy          0.71103 │
╰──────────────────────────────────────╯

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:12. Total running time: 16s
[36m(train_xgb_ray_tune pid=1050009)[0m [540]	train-mlogloss:0.66763	validation-mlogloss:0.69251
[36m(train_xgb_ray_tune pid=1050009)[0m [541]	train-mlogloss:0.66762	validation-mlogloss:0.69252
[36m(train_xgb_ray_tune pid=1050009)[0m [542]	train-mlogloss:0.66737	validation-mlogloss:0.69243
[36m(train_xgb_ray_tune pid=1050009)[0m [543]	train-mlogloss:0.66718	validation-mlogloss:0.69233
[36m(train_xgb_ray_tune pid=1050009)[0m [544]	train-mlogloss:0.66701	validation-mlogloss:0.69217
[36m(train_xgb_ray_tune pid=1050009)[0m [545]	train-mlogloss:0.66696	validation-mlogloss:0.69216
[36m(train_xgb_ray_tune pid=1050009)[0m [546]	train-mlogloss:0.66679	validation-mlogloss:0.69201
[36m(train_xgb_ray_tune pid=1050009)[0m [547]	train-mlogloss:0.66670	validation-mlogloss:0.69196
[36m(train_xgb_ray_tune pid=1050009)[0m [548]	train-mlogloss:0.66649	validation-mlogloss:0.69187
[36m(train_xgb_ray_tune pid=1050009)[0m [549]	train-mlogloss:0.66634	validation-mlogloss:0.69181
[36m(train_xgb_ray_tune pid=1050009)[0m [550]	train-mlogloss:0.66619	validation-mlogloss:0.69164
[36m(train_xgb_ray_tune pid=1050009)[0m [551]	train-mlogloss:0.66596	validation-mlogloss:0.69153
[36m(train_xgb_ray_tune pid=1050009)[0m [552]	train-mlogloss:0.66584	validation-mlogloss:0.69141
[36m(train_xgb_ray_tune pid=1050007)[0m [707]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [708]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [709]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [710]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [711]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [712]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [713]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [714]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [715]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [716]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [717]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [718]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [719]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [720]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [721]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [722]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050007)[0m [723]	train-mlogloss:0.74850	validation-mlogloss:0.74940
[36m(train_xgb_ray_tune pid=1050020)[0m [506]	train-mlogloss:0.91829	validation-mlogloss:0.90872
[36m(train_xgb_ray_tune pid=1050020)[0m [507]	train-mlogloss:0.91802	validation-mlogloss:0.90847
[36m(train_xgb_ray_tune pid=1050020)[0m [508]	train-mlogloss:0.91769	validation-mlogloss:0.90814
[36m(train_xgb_ray_tune pid=1050020)[0m [509]	train-mlogloss:0.91742	validation-mlogloss:0.90787
[36m(train_xgb_ray_tune pid=1050020)[0m [510]	train-mlogloss:0.91714	validation-mlogloss:0.90758
[36m(train_xgb_ray_tune pid=1050020)[0m [511]	train-mlogloss:0.91686	validation-mlogloss:0.90732
[36m(train_xgb_ray_tune pid=1050020)[0m [512]	train-mlogloss:0.91663	validation-mlogloss:0.90706
[36m(train_xgb_ray_tune pid=1050020)[0m [513]	train-mlogloss:0.91639	validation-mlogloss:0.90682
[36m(train_xgb_ray_tune pid=1050020)[0m [514]	train-mlogloss:0.91613	validation-mlogloss:0.90657
[36m(train_xgb_ray_tune pid=1050020)[0m [515]	train-mlogloss:0.91584	validation-mlogloss:0.90628
[36m(train_xgb_ray_tune pid=1050020)[0m [516]	train-mlogloss:0.91562	validation-mlogloss:0.90605
[36m(train_xgb_ray_tune pid=1050020)[0m [517]	train-mlogloss:0.91536	validation-mlogloss:0.90575
[36m(train_xgb_ray_tune pid=1050004)[0m [532]	train-mlogloss:0.91162	validation-mlogloss:0.89897
[36m(train_xgb_ray_tune pid=1050004)[0m [533]	train-mlogloss:0.91137	validation-mlogloss:0.89870
[36m(train_xgb_ray_tune pid=1050004)[0m [534]	train-mlogloss:0.91120	validation-mlogloss:0.89851
[36m(train_xgb_ray_tune pid=1050004)[0m [535]	train-mlogloss:0.91102	validation-mlogloss:0.89835
[36m(train_xgb_ray_tune pid=1050004)[0m [536]	train-mlogloss:0.91085	validation-mlogloss:0.89818
[36m(train_xgb_ray_tune pid=1050004)[0m [537]	train-mlogloss:0.91064	validation-mlogloss:0.89798
[36m(train_xgb_ray_tune pid=1050004)[0m [538]	train-mlogloss:0.91043	validation-mlogloss:0.89778
[36m(train_xgb_ray_tune pid=1050004)[0m [539]	train-mlogloss:0.91020	validation-mlogloss:0.89752
[36m(train_xgb_ray_tune pid=1050004)[0m [540]	train-mlogloss:0.90997	validation-mlogloss:0.89728
[36m(train_xgb_ray_tune pid=1050004)[0m [541]	train-mlogloss:0.90973	validation-mlogloss:0.89703

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:12. Total running time: 16s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             13.2271 │
│ time_total_s                 13.2271 │
│ training_iteration                 1 │
│ validation_accuracy          0.66362 │
╰──────────────────────────────────────╯

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:12. Total running time: 16s
[36m(train_xgb_ray_tune pid=1050009)[0m [553]	train-mlogloss:0.66562	validation-mlogloss:0.69137
[36m(train_xgb_ray_tune pid=1050009)[0m [554]	train-mlogloss:0.66558	validation-mlogloss:0.69132
[36m(train_xgb_ray_tune pid=1050009)[0m [555]	train-mlogloss:0.66551	validation-mlogloss:0.69127
[36m(train_xgb_ray_tune pid=1050009)[0m [556]	train-mlogloss:0.66539	validation-mlogloss:0.69114
[36m(train_xgb_ray_tune pid=1050009)[0m [557]	train-mlogloss:0.66524	validation-mlogloss:0.69099
[36m(train_xgb_ray_tune pid=1050009)[0m [558]	train-mlogloss:0.66513	validation-mlogloss:0.69095
[36m(train_xgb_ray_tune pid=1050009)[0m [559]	train-mlogloss:0.66504	validation-mlogloss:0.69090
[36m(train_xgb_ray_tune pid=1050009)[0m [560]	train-mlogloss:0.66489	validation-mlogloss:0.69078
[36m(train_xgb_ray_tune pid=1050009)[0m [561]	train-mlogloss:0.66473	validation-mlogloss:0.69074
[36m(train_xgb_ray_tune pid=1050009)[0m [562]	train-mlogloss:0.66461	validation-mlogloss:0.69073
[36m(train_xgb_ray_tune pid=1050009)[0m [563]	train-mlogloss:0.66455	validation-mlogloss:0.69069
[36m(train_xgb_ray_tune pid=1050009)[0m [564]	train-mlogloss:0.66440	validation-mlogloss:0.69062
[36m(train_xgb_ray_tune pid=1050009)[0m [565]	train-mlogloss:0.66432	validation-mlogloss:0.69057
[36m(train_xgb_ray_tune pid=1050020)[0m [518]	train-mlogloss:0.91513	validation-mlogloss:0.90556
[36m(train_xgb_ray_tune pid=1050020)[0m [519]	train-mlogloss:0.91483	validation-mlogloss:0.90525
[36m(train_xgb_ray_tune pid=1050020)[0m [520]	train-mlogloss:0.91459	validation-mlogloss:0.90499
[36m(train_xgb_ray_tune pid=1050020)[0m [521]	train-mlogloss:0.91431	validation-mlogloss:0.90472
[36m(train_xgb_ray_tune pid=1050020)[0m [522]	train-mlogloss:0.91406	validation-mlogloss:0.90447
[36m(train_xgb_ray_tune pid=1050020)[0m [523]	train-mlogloss:0.91376	validation-mlogloss:0.90417
[36m(train_xgb_ray_tune pid=1050020)[0m [524]	train-mlogloss:0.91350	validation-mlogloss:0.90390
[36m(train_xgb_ray_tune pid=1050020)[0m [525]	train-mlogloss:0.91326	validation-mlogloss:0.90365
[36m(train_xgb_ray_tune pid=1050020)[0m [526]	train-mlogloss:0.91299	validation-mlogloss:0.90340
[36m(train_xgb_ray_tune pid=1050020)[0m [527]	train-mlogloss:0.91276	validation-mlogloss:0.90318
[36m(train_xgb_ray_tune pid=1050020)[0m [528]	train-mlogloss:0.91250	validation-mlogloss:0.90294
[36m(train_xgb_ray_tune pid=1050020)[0m [529]	train-mlogloss:0.91221	validation-mlogloss:0.90266
[36m(train_xgb_ray_tune pid=1050009)[0m [566]	train-mlogloss:0.66426	validation-mlogloss:0.69058

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:12. Total running time: 16s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             13.7518 │
│ time_total_s                 13.7518 │
│ training_iteration                 1 │
│ validation_accuracy          0.69803 │
╰──────────────────────────────────────╯

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:12. Total running time: 16s
[36m(train_xgb_ray_tune pid=1050009)[0m [567]	train-mlogloss:0.66415	validation-mlogloss:0.69055
[36m(train_xgb_ray_tune pid=1050009)[0m [568]	train-mlogloss:0.66399	validation-mlogloss:0.69059
[36m(train_xgb_ray_tune pid=1050009)[0m [569]	train-mlogloss:0.66390	validation-mlogloss:0.69050
[36m(train_xgb_ray_tune pid=1050009)[0m [570]	train-mlogloss:0.66383	validation-mlogloss:0.69043
[36m(train_xgb_ray_tune pid=1050009)[0m [571]	train-mlogloss:0.66377	validation-mlogloss:0.69036
[36m(train_xgb_ray_tune pid=1050009)[0m [572]	train-mlogloss:0.66360	validation-mlogloss:0.69014
[36m(train_xgb_ray_tune pid=1050009)[0m [573]	train-mlogloss:0.66341	validation-mlogloss:0.69007
[36m(train_xgb_ray_tune pid=1050009)[0m [574]	train-mlogloss:0.66328	validation-mlogloss:0.68992
[36m(train_xgb_ray_tune pid=1050009)[0m [575]	train-mlogloss:0.66322	validation-mlogloss:0.68985
[36m(train_xgb_ray_tune pid=1050009)[0m [576]	train-mlogloss:0.66313	validation-mlogloss:0.68976
[36m(train_xgb_ray_tune pid=1050009)[0m [577]	train-mlogloss:0.66312	validation-mlogloss:0.68971
[36m(train_xgb_ray_tune pid=1050009)[0m [578]	train-mlogloss:0.66298	validation-mlogloss:0.68963
[36m(train_xgb_ray_tune pid=1050009)[0m [579]	train-mlogloss:0.66283	validation-mlogloss:0.68952
[36m(train_xgb_ray_tune pid=1050009)[0m [580]	train-mlogloss:0.66267	validation-mlogloss:0.68934
[36m(train_xgb_ray_tune pid=1050020)[0m [530]	train-mlogloss:0.91201	validation-mlogloss:0.90248
[36m(train_xgb_ray_tune pid=1050020)[0m [531]	train-mlogloss:0.91173	validation-mlogloss:0.90220
[36m(train_xgb_ray_tune pid=1050020)[0m [532]	train-mlogloss:0.91151	validation-mlogloss:0.90203
[36m(train_xgb_ray_tune pid=1050020)[0m [533]	train-mlogloss:0.91129	validation-mlogloss:0.90181
[36m(train_xgb_ray_tune pid=1050020)[0m [534]	train-mlogloss:0.91107	validation-mlogloss:0.90162
[36m(train_xgb_ray_tune pid=1050020)[0m [535]	train-mlogloss:0.91079	validation-mlogloss:0.90134
[36m(train_xgb_ray_tune pid=1050020)[0m [536]	train-mlogloss:0.91053	validation-mlogloss:0.90109
[36m(train_xgb_ray_tune pid=1050020)[0m [537]	train-mlogloss:0.91027	validation-mlogloss:0.90085
[36m(train_xgb_ray_tune pid=1050020)[0m [538]	train-mlogloss:0.90998	validation-mlogloss:0.90057
[36m(train_xgb_ray_tune pid=1050020)[0m [539]	train-mlogloss:0.90967	validation-mlogloss:0.90028
[36m(train_xgb_ray_tune pid=1050020)[0m [540]	train-mlogloss:0.90942	validation-mlogloss:0.90004
[36m(train_xgb_ray_tune pid=1050020)[0m [541]	train-mlogloss:0.90922	validation-mlogloss:0.89984
[36m(train_xgb_ray_tune pid=1050020)[0m [542]	train-mlogloss:0.90900	validation-mlogloss:0.89962
[36m(train_xgb_ray_tune pid=1050009)[0m [581]	train-mlogloss:0.66253	validation-mlogloss:0.68926
[36m(train_xgb_ray_tune pid=1050009)[0m [582]	train-mlogloss:0.66235	validation-mlogloss:0.68911
[36m(train_xgb_ray_tune pid=1050009)[0m [583]	train-mlogloss:0.66229	validation-mlogloss:0.68905
[36m(train_xgb_ray_tune pid=1050009)[0m [584]	train-mlogloss:0.66223	validation-mlogloss:0.68897
[36m(train_xgb_ray_tune pid=1050009)[0m [585]	train-mlogloss:0.66216	validation-mlogloss:0.68892
[36m(train_xgb_ray_tune pid=1050009)[0m [586]	train-mlogloss:0.66198	validation-mlogloss:0.68879
[36m(train_xgb_ray_tune pid=1050009)[0m [587]	train-mlogloss:0.66197	validation-mlogloss:0.68879
[36m(train_xgb_ray_tune pid=1050020)[0m [543]	train-mlogloss:0.90877	validation-mlogloss:0.89935
[36m(train_xgb_ray_tune pid=1050020)[0m [544]	train-mlogloss:0.90854	validation-mlogloss:0.89917
[36m(train_xgb_ray_tune pid=1050020)[0m [545]	train-mlogloss:0.90828	validation-mlogloss:0.89889
[36m(train_xgb_ray_tune pid=1050020)[0m [546]	train-mlogloss:0.90809	validation-mlogloss:0.89872
[36m(train_xgb_ray_tune pid=1050020)[0m [547]	train-mlogloss:0.90784	validation-mlogloss:0.89849
[36m(train_xgb_ray_tune pid=1050020)[0m [548]	train-mlogloss:0.90756	validation-mlogloss:0.89824
2025-11-04 10:33:12,692	INFO tune.py:1009 -- Wrote the latest version of all result files and experiment state to '/mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_C/case_C_XGB_acc_gyr_17_superclasses_CPA_METs/XGBoost_hyperparameters_tuning' in 0.0179s.
[36m(train_xgb_ray_tune pid=1050020)[0m [549]	train-mlogloss:0.90728	validation-mlogloss:0.89796
[36m(train_xgb_ray_tune pid=1050020)[0m [550]	train-mlogloss:0.90709	validation-mlogloss:0.89777
[36m(train_xgb_ray_tune pid=1050020)[0m [551]	train-mlogloss:0.90690	validation-mlogloss:0.89761

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:12. Total running time: 16s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             13.7386 │
│ time_total_s                 13.7386 │
│ training_iteration                 1 │
│ validation_accuracy          0.66397 │
╰──────────────────────────────────────╯

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:12. Total running time: 16s

Trial trial_3e61e finished iteration 1 at 2025-11-04 10:33:12. Total running time: 16s
╭──────────────────────────────────────╮
│ Trial trial_3e61e result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             14.0934 │
│ time_total_s                 14.0934 │
│ training_iteration                 1 │
│ validation_accuracy          0.71805 │
╰──────────────────────────────────────╯

Trial trial_3e61e completed after 1 iterations at 2025-11-04 10:33:12. Total running time: 16s

Trial status: 20 TERMINATED
Current time: 2025-11-04 10:33:12. Total running time: 16s
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_3e61e    TERMINATED                 608             2        0.0195196       0.547785             0.807243   22.4428                    70      58.886         49.7709              7080        1           12.9752                 0.657654 │
│ trial_3e61e    TERMINATED                 278             3        0.0152949       0.750992             0.831092   28.3893                    81     919.466         18.9778              1744        1            6.62104                0.461025 │
│ trial_3e61e    TERMINATED                 588             3        0.0146662       0.531688             0.643934    6.20981                  146       5.97029       26.442               5860        1           14.0934                 0.718048 │
│ trial_3e61e    TERMINATED                 576             2        0.0198779       0.618591             0.659284   16.4909                   126      25.2645        24.7553              2569        1           12.08                   0.675913 │
│ trial_3e61e    TERMINATED                 517             2        0.00901737      0.584256             0.525248   22.0358                   111     397.932          7.34405             4069        1           10.7899                 0.555478 │
│ trial_3e61e    TERMINATED                 376             3        0.018019        0.761167             0.623623    5.2294                   135      17.9044       163.812               6412        1           12.5411                 0.718399 │
│ trial_3e61e    TERMINATED                 571             2        0.0183267       0.761875             0.662762   18.6245                   183       5.85826       77.48                7694        1           12.3744                 0.695927 │
│ trial_3e61e    TERMINATED                 728             2        0.00620727      0.587246             0.688072   13.1042                   194     129.418        348.485               6073        1           12.9678                 0.651685 │
│ trial_3e61e    TERMINATED                 503             3        0.0167579       0.700313             0.731405   10.7857                   121       4.21667       22.5949              6614        1           13.2888                 0.711025 │
│ trial_3e61e    TERMINATED                 251             2        0.00589301      0.791274             0.641109   14.7318                   138      12.1911        59.7902              5962        1            9.43546                0.660463 │
│ trial_3e61e    TERMINATED                 375             2        0.0191749       0.797987             0.526235   16.8837                   148     277.867         21.2496              8750        1            9.44722                0.650632 │
│ trial_3e61e    TERMINATED                 552             3        0.00518694      0.743033             0.814563   24.1402                   133      55.5009       220.28                9343        1           13.7386                 0.663975 │
│ trial_3e61e    TERMINATED                 757             3        0.0138236       0.587692             0.709206   25.104                     62       3.11279       23.2571              5613        1           13.7518                 0.698034 │
│ trial_3e61e    TERMINATED                 542             3        0.00705996      0.565602             0.623176    6.66706                  150     107.565        101.116               3953        1           13.2271                 0.663624 │
│ trial_3e61e    TERMINATED                 253             3        0.0101395       0.785125             0.642466   28.4619                   186     497.357        117.888               2414        1            8.61305                0.575492 │
│ trial_3e61e    TERMINATED                 443             3        0.0152383       0.638747             0.501683    6.21693                  161     876.274         12.0761              5987        1            7.64662                0.452598 │
│ trial_3e61e    TERMINATED                 289             3        0.0196544       0.61134              0.559905    8.51114                  121     622.376        105.44                3210        1            8.26146                0.461025 │
│ trial_3e61e    TERMINATED                 439             2        0.0106674       0.7374               0.840622   23.4996                    87     363.963        324.87                5050        1           11.0466                 0.643961 │
│ trial_3e61e    TERMINATED                 397             2        0.0134191       0.515726             0.553979    5.02458                   81      33.3285        26.1677              3722        1           10.6391                 0.691011 │
│ trial_3e61e    TERMINATED                 672             3        0.00727831      0.514721             0.670695   11.7282                    73     747.188        139.556               3798        1            5.32581                0.461025 │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Mejores hiperparámetros XGBoost: {'num_boost_round': 376, 'max_depth': 3, 'learning_rate': 0.018019002856647443, 'subsample': 0.7611665890244015, 'colsample_bytree': 0.623623021333269, 'gamma': 5.229398570026093, 'min_child_weight': 135, 'reg_alpha': 17.90439148036489, 'reg_lambda': 163.81167608500917, 'random_state': 6412}
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[374]	train-mlogloss:0.70509	validation-mlogloss:0.71908
[375]	train-mlogloss:0.70486	validation-mlogloss:0.71889
Saved model to disk.
[36m(train_xgb_ray_tune pid=1050009)[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 12x across cluster][0m
[36m(train_xgb_ray_tune pid=1050009)[0m   _log_deprecation_warning([32m [repeated 12x across cluster][0m
2025-11-04 10:33:25.428273: 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 10:33:25.439979: 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 00:00:1762248805.453279 1051787 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248805.457435 1051787 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248805.467572 1051787 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248805.467590 1051787 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248805.467592 1051787 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248805.467593 1051787 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:33:25.470716: 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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[49]	train-mlogloss:1.07131	validation-mlogloss:1.06380
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[352]	train-mlogloss:0.70579	validation-mlogloss:0.71291
[353]	train-mlogloss:0.70548	validation-mlogloss:0.71277
[354]	train-mlogloss:0.70521	validation-mlogloss:0.71249
[355]	train-mlogloss:0.70485	validation-mlogloss:0.71224
[356]	train-mlogloss:0.70453	validation-mlogloss:0.71200
[357]	train-mlogloss:0.70426	validation-mlogloss:0.71174
[358]	train-mlogloss:0.70382	validation-mlogloss:0.71148
[359]	train-mlogloss:0.70352	validation-mlogloss:0.71123
[360]	train-mlogloss:0.70318	validation-mlogloss:0.71098
[361]	train-mlogloss:0.70285	validation-mlogloss:0.71080
[362]	train-mlogloss:0.70240	validation-mlogloss:0.71043
[363]	train-mlogloss:0.70203	validation-mlogloss:0.71020
[364]	train-mlogloss:0.70175	validation-mlogloss:0.70994
[365]	train-mlogloss:0.70144	validation-mlogloss:0.70963
[366]	train-mlogloss:0.70111	validation-mlogloss:0.70937
[367]	train-mlogloss:0.70076	validation-mlogloss:0.70906
[368]	train-mlogloss:0.70038	validation-mlogloss:0.70877
[369]	train-mlogloss:0.69998	validation-mlogloss:0.70836
[370]	train-mlogloss:0.69967	validation-mlogloss:0.70804
[371]	train-mlogloss:0.69935	validation-mlogloss:0.70785
[372]	train-mlogloss:0.69904	validation-mlogloss:0.70765
[373]	train-mlogloss:0.69882	validation-mlogloss:0.70748
[374]	train-mlogloss:0.69857	validation-mlogloss:0.70726
[375]	train-mlogloss:0.69832	validation-mlogloss:0.70701
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.7 [%]
Global accuracy score (test) = 72.49 [%]
Global F1 score (train) = 73.61 [%]
Global F1 score (test) = 72.78 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.48      0.55       400
MODERATE-INTENSITY       0.59      0.84      0.69       400
         SEDENTARY       0.84      0.85      0.84       400
VIGOROUS-INTENSITY       0.96      0.73      0.83       345

          accuracy                           0.72      1545
         macro avg       0.75      0.73      0.73      1545
      weighted avg       0.75      0.72      0.72      1545


Accuracy capturado en la ejecución 1: 72.49 [%]
F1-score capturado en la ejecución 1: 72.78 [%]

=== EJECUCIÓN 2 ===

--- TRAIN (ejecución 2) ---

--- TEST (ejecución 2) ---
2025-11-04 10:33:41.473412: 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 10:33:41.484419: 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 00:00:1762248821.497119 1052091 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248821.500995 1052091 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248821.510667 1052091 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248821.510683 1052091 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248821.510685 1052091 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248821.510686 1052091 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:33:41.513633: 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:1.37730	validation-mlogloss:1.37692
[1]	train-mlogloss:1.36784	validation-mlogloss:1.36697
[2]	train-mlogloss:1.35854	validation-mlogloss:1.35689
[3]	train-mlogloss:1.34925	validation-mlogloss:1.34712
[4]	train-mlogloss:1.34027	validation-mlogloss:1.33775
[5]	train-mlogloss:1.33139	validation-mlogloss:1.32842
[6]	train-mlogloss:1.32318	validation-mlogloss:1.31999
[7]	train-mlogloss:1.31463	validation-mlogloss:1.31124
[8]	train-mlogloss:1.30626	validation-mlogloss:1.30242
[9]	train-mlogloss:1.29822	validation-mlogloss:1.29378
[10]	train-mlogloss:1.29067	validation-mlogloss:1.28602
[11]	train-mlogloss:1.28323	validation-mlogloss:1.27842
[12]	train-mlogloss:1.27558	validation-mlogloss:1.27043
[13]	train-mlogloss:1.26841	validation-mlogloss:1.26345
[14]	train-mlogloss:1.26138	validation-mlogloss:1.25620
[15]	train-mlogloss:1.25437	validation-mlogloss:1.24876
[16]	train-mlogloss:1.24744	validation-mlogloss:1.24183
[17]	train-mlogloss:1.24033	validation-mlogloss:1.23447
[18]	train-mlogloss:1.23378	validation-mlogloss:1.22805
[19]	train-mlogloss:1.22703	validation-mlogloss:1.22134
[20]	train-mlogloss:1.22056	validation-mlogloss:1.21448
[21]	train-mlogloss:1.21418	validation-mlogloss:1.20794
[22]	train-mlogloss:1.20768	validation-mlogloss:1.20126
[23]	train-mlogloss:1.20163	validation-mlogloss:1.19543
[24]	train-mlogloss:1.19543	validation-mlogloss:1.18878
[25]	train-mlogloss:1.18958	validation-mlogloss:1.18281
[26]	train-mlogloss:1.18382	validation-mlogloss:1.17694
[27]	train-mlogloss:1.17783	validation-mlogloss:1.17050
[28]	train-mlogloss:1.17206	validation-mlogloss:1.16453
[29]	train-mlogloss:1.16630	validation-mlogloss:1.15858
[30]	train-mlogloss:1.16085	validation-mlogloss:1.15308
[31]	train-mlogloss:1.15542	validation-mlogloss:1.14763
[32]	train-mlogloss:1.15045	validation-mlogloss:1.14259
[33]	train-mlogloss:1.14546	validation-mlogloss:1.13787
[34]	train-mlogloss:1.14039	validation-mlogloss:1.13276
[35]	train-mlogloss:1.13509	validation-mlogloss:1.12715
[36]	train-mlogloss:1.13036	validation-mlogloss:1.12214
[37]	train-mlogloss:1.12549	validation-mlogloss:1.11712
[38]	train-mlogloss:1.12040	validation-mlogloss:1.11213
[39]	train-mlogloss:1.11555	validation-mlogloss:1.10718
[40]	train-mlogloss:1.11109	validation-mlogloss:1.10268
[41]	train-mlogloss:1.10642	validation-mlogloss:1.09798
[42]	train-mlogloss:1.10168	validation-mlogloss:1.09311
[43]	train-mlogloss:1.09733	validation-mlogloss:1.08872
[44]	train-mlogloss:1.09294	validation-mlogloss:1.08415
[45]	train-mlogloss:1.08860	validation-mlogloss:1.07965
[46]	train-mlogloss:1.08458	validation-mlogloss:1.07549
[47]	train-mlogloss:1.08038	validation-mlogloss:1.07130
[48]	train-mlogloss:1.07640	validation-mlogloss:1.06729
[49]	train-mlogloss:1.07234	validation-mlogloss:1.06303
[50]	train-mlogloss:1.06839	validation-mlogloss:1.05897
[51]	train-mlogloss:1.06450	validation-mlogloss:1.05478
[52]	train-mlogloss:1.06056	validation-mlogloss:1.05060
[53]	train-mlogloss:1.05665	validation-mlogloss:1.04676
[54]	train-mlogloss:1.05303	validation-mlogloss:1.04320
[55]	train-mlogloss:1.04940	validation-mlogloss:1.03951
[56]	train-mlogloss:1.04546	validation-mlogloss:1.03568
[57]	train-mlogloss:1.04184	validation-mlogloss:1.03208
[58]	train-mlogloss:1.03847	validation-mlogloss:1.02861
[59]	train-mlogloss:1.03510	validation-mlogloss:1.02524
[60]	train-mlogloss:1.03152	validation-mlogloss:1.02152
[61]	train-mlogloss:1.02834	validation-mlogloss:1.01838
[62]	train-mlogloss:1.02506	validation-mlogloss:1.01509
[63]	train-mlogloss:1.02156	validation-mlogloss:1.01133
[64]	train-mlogloss:1.01817	validation-mlogloss:1.00773
[65]	train-mlogloss:1.01516	validation-mlogloss:1.00455
[66]	train-mlogloss:1.01198	validation-mlogloss:1.00138
[67]	train-mlogloss:1.00873	validation-mlogloss:0.99792
[68]	train-mlogloss:1.00562	validation-mlogloss:0.99457
[69]	train-mlogloss:1.00267	validation-mlogloss:0.99137
[70]	train-mlogloss:0.99946	validation-mlogloss:0.98820
[71]	train-mlogloss:0.99648	validation-mlogloss:0.98527
[72]	train-mlogloss:0.99362	validation-mlogloss:0.98227
[73]	train-mlogloss:0.99077	validation-mlogloss:0.97947
[74]	train-mlogloss:0.98795	validation-mlogloss:0.97659
[75]	train-mlogloss:0.98522	validation-mlogloss:0.97372
[76]	train-mlogloss:0.98235	validation-mlogloss:0.97093
[77]	train-mlogloss:0.97944	validation-mlogloss:0.96789
[78]	train-mlogloss:0.97680	validation-mlogloss:0.96514
[79]	train-mlogloss:0.97435	validation-mlogloss:0.96257
[80]	train-mlogloss:0.97174	validation-mlogloss:0.95987
[81]	train-mlogloss:0.96891	validation-mlogloss:0.95698
[82]	train-mlogloss:0.96624	validation-mlogloss:0.95428
[83]	train-mlogloss:0.96372	validation-mlogloss:0.95157
[84]	train-mlogloss:0.96124	validation-mlogloss:0.94912
[85]	train-mlogloss:0.95888	validation-mlogloss:0.94675
[86]	train-mlogloss:0.95648	validation-mlogloss:0.94433
[87]	train-mlogloss:0.95399	validation-mlogloss:0.94193
[88]	train-mlogloss:0.95174	validation-mlogloss:0.93943
[89]	train-mlogloss:0.94921	validation-mlogloss:0.93670
[90]	train-mlogloss:0.94694	validation-mlogloss:0.93445
[91]	train-mlogloss:0.94464	validation-mlogloss:0.93208
[92]	train-mlogloss:0.94253	validation-mlogloss:0.92996
[93]	train-mlogloss:0.94030	validation-mlogloss:0.92785
[94]	train-mlogloss:0.93805	validation-mlogloss:0.92558
[95]	train-mlogloss:0.93600	validation-mlogloss:0.92347
[96]	train-mlogloss:0.93396	validation-mlogloss:0.92150
[97]	train-mlogloss:0.93188	validation-mlogloss:0.91919
[98]	train-mlogloss:0.92985	validation-mlogloss:0.91721
[99]	train-mlogloss:0.92769	validation-mlogloss:0.91502
[100]	train-mlogloss:0.92573	validation-mlogloss:0.91303
[101]	train-mlogloss:0.92370	validation-mlogloss:0.91101
[102]	train-mlogloss:0.92177	validation-mlogloss:0.90894
[103]	train-mlogloss:0.91967	validation-mlogloss:0.90677
[104]	train-mlogloss:0.91768	validation-mlogloss:0.90470
[105]	train-mlogloss:0.91580	validation-mlogloss:0.90275
[106]	train-mlogloss:0.91395	validation-mlogloss:0.90076
[107]	train-mlogloss:0.91193	validation-mlogloss:0.89867
[108]	train-mlogloss:0.91005	validation-mlogloss:0.89692
[109]	train-mlogloss:0.90810	validation-mlogloss:0.89493
[110]	train-mlogloss:0.90642	validation-mlogloss:0.89327
[111]	train-mlogloss:0.90480	validation-mlogloss:0.89169
[112]	train-mlogloss:0.90308	validation-mlogloss:0.88984
[113]	train-mlogloss:0.90141	validation-mlogloss:0.88821
[114]	train-mlogloss:0.89954	validation-mlogloss:0.88619
[115]	train-mlogloss:0.89790	validation-mlogloss:0.88451
[116]	train-mlogloss:0.89628	validation-mlogloss:0.88295
[117]	train-mlogloss:0.89447	validation-mlogloss:0.88106
[118]	train-mlogloss:0.89284	validation-mlogloss:0.87943
[119]	train-mlogloss:0.89108	validation-mlogloss:0.87758
[120]	train-mlogloss:0.88934	validation-mlogloss:0.87575
[121]	train-mlogloss:0.88749	validation-mlogloss:0.87383
[122]	train-mlogloss:0.88580	validation-mlogloss:0.87223
[123]	train-mlogloss:0.88428	validation-mlogloss:0.87079
[124]	train-mlogloss:0.88281	validation-mlogloss:0.86944
[125]	train-mlogloss:0.88121	validation-mlogloss:0.86776
[126]	train-mlogloss:0.87950	validation-mlogloss:0.86610
[127]	train-mlogloss:0.87790	validation-mlogloss:0.86442
[128]	train-mlogloss:0.87629	validation-mlogloss:0.86274
[129]	train-mlogloss:0.87465	validation-mlogloss:0.86110
[130]	train-mlogloss:0.87311	validation-mlogloss:0.85956
[131]	train-mlogloss:0.87151	validation-mlogloss:0.85806
[132]	train-mlogloss:0.87002	validation-mlogloss:0.85674
[133]	train-mlogloss:0.86843	validation-mlogloss:0.85506
[134]	train-mlogloss:0.86697	validation-mlogloss:0.85362
[135]	train-mlogloss:0.86545	validation-mlogloss:0.85204
[136]	train-mlogloss:0.86408	validation-mlogloss:0.85073
[137]	train-mlogloss:0.86264	validation-mlogloss:0.84929
[138]	train-mlogloss:0.86115	validation-mlogloss:0.84779
[139]	train-mlogloss:0.85972	validation-mlogloss:0.84638
[140]	train-mlogloss:0.85825	validation-mlogloss:0.84483
[141]	train-mlogloss:0.85683	validation-mlogloss:0.84343
[142]	train-mlogloss:0.85572	validation-mlogloss:0.84230
[143]	train-mlogloss:0.85426	validation-mlogloss:0.84084
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[358]	train-mlogloss:0.70706	validation-mlogloss:0.70389
[359]	train-mlogloss:0.70674	validation-mlogloss:0.70356
[360]	train-mlogloss:0.70646	validation-mlogloss:0.70327
[361]	train-mlogloss:0.70616	validation-mlogloss:0.70301
[362]	train-mlogloss:0.70579	validation-mlogloss:0.70275
[363]	train-mlogloss:0.70552	validation-mlogloss:0.70249
[364]	train-mlogloss:0.70514	validation-mlogloss:0.70217
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[366]	train-mlogloss:0.70449	validation-mlogloss:0.70169
[367]	train-mlogloss:0.70419	validation-mlogloss:0.70149
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[369]	train-mlogloss:0.70356	validation-mlogloss:0.70106
[370]	train-mlogloss:0.70331	validation-mlogloss:0.70080
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[374]	train-mlogloss:0.70211	validation-mlogloss:0.69979
[375]	train-mlogloss:0.70190	validation-mlogloss:0.69953
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.23 [%]
Global accuracy score (test) = 71.59 [%]
Global F1 score (train) = 73.22 [%]
Global F1 score (test) = 72.08 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.60      0.48      0.54       400
MODERATE-INTENSITY       0.58      0.82      0.68       400
         SEDENTARY       0.85      0.81      0.83       400
VIGOROUS-INTENSITY       0.95      0.75      0.83       345

          accuracy                           0.72      1545
         macro avg       0.74      0.72      0.72      1545
      weighted avg       0.74      0.72      0.72      1545


Accuracy capturado en la ejecución 2: 71.59 [%]
F1-score capturado en la ejecución 2: 72.08 [%]

=== EJECUCIÓN 3 ===

--- TRAIN (ejecución 3) ---

--- TEST (ejecución 3) ---
2025-11-04 10:33:57.380018: 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 10:33:57.391969: 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 00:00:1762248837.406000 1052395 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248837.410212 1052395 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248837.420790 1052395 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248837.420806 1052395 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248837.420808 1052395 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248837.420809 1052395 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:33:57.424140: 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:1.37653	validation-mlogloss:1.37603
[1]	train-mlogloss:1.36700	validation-mlogloss:1.36626
[2]	train-mlogloss:1.35756	validation-mlogloss:1.35648
[3]	train-mlogloss:1.34885	validation-mlogloss:1.34769
[4]	train-mlogloss:1.33967	validation-mlogloss:1.33819
[5]	train-mlogloss:1.33120	validation-mlogloss:1.32935
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[7]	train-mlogloss:1.31441	validation-mlogloss:1.31193
[8]	train-mlogloss:1.30638	validation-mlogloss:1.30370
[9]	train-mlogloss:1.29801	validation-mlogloss:1.29504
[10]	train-mlogloss:1.29045	validation-mlogloss:1.28743
[11]	train-mlogloss:1.28284	validation-mlogloss:1.27972
[12]	train-mlogloss:1.27514	validation-mlogloss:1.27165
[13]	train-mlogloss:1.26785	validation-mlogloss:1.26430
[14]	train-mlogloss:1.26031	validation-mlogloss:1.25660
[15]	train-mlogloss:1.25300	validation-mlogloss:1.24888
[16]	train-mlogloss:1.24564	validation-mlogloss:1.24146
[17]	train-mlogloss:1.23877	validation-mlogloss:1.23426
[18]	train-mlogloss:1.23159	validation-mlogloss:1.22712
[19]	train-mlogloss:1.22507	validation-mlogloss:1.22032
[20]	train-mlogloss:1.21845	validation-mlogloss:1.21336
[21]	train-mlogloss:1.21235	validation-mlogloss:1.20728
[22]	train-mlogloss:1.20581	validation-mlogloss:1.20062
[23]	train-mlogloss:1.19973	validation-mlogloss:1.19470
[24]	train-mlogloss:1.19349	validation-mlogloss:1.18827
[25]	train-mlogloss:1.18767	validation-mlogloss:1.18260
[26]	train-mlogloss:1.18171	validation-mlogloss:1.17671
[27]	train-mlogloss:1.17607	validation-mlogloss:1.17094
[28]	train-mlogloss:1.17064	validation-mlogloss:1.16538
[29]	train-mlogloss:1.16515	validation-mlogloss:1.15972
[30]	train-mlogloss:1.15953	validation-mlogloss:1.15405
[31]	train-mlogloss:1.15414	validation-mlogloss:1.14875
[32]	train-mlogloss:1.14872	validation-mlogloss:1.14315
[33]	train-mlogloss:1.14334	validation-mlogloss:1.13770
[34]	train-mlogloss:1.13812	validation-mlogloss:1.13237
[35]	train-mlogloss:1.13330	validation-mlogloss:1.12758
[36]	train-mlogloss:1.12866	validation-mlogloss:1.12314
[37]	train-mlogloss:1.12399	validation-mlogloss:1.11861
[38]	train-mlogloss:1.11921	validation-mlogloss:1.11372
[39]	train-mlogloss:1.11430	validation-mlogloss:1.10867
[40]	train-mlogloss:1.10931	validation-mlogloss:1.10347
[41]	train-mlogloss:1.10489	validation-mlogloss:1.09917
[42]	train-mlogloss:1.10033	validation-mlogloss:1.09472
[43]	train-mlogloss:1.09588	validation-mlogloss:1.09021
[44]	train-mlogloss:1.09139	validation-mlogloss:1.08559
[45]	train-mlogloss:1.08723	validation-mlogloss:1.08140
[46]	train-mlogloss:1.08284	validation-mlogloss:1.07687
[47]	train-mlogloss:1.07862	validation-mlogloss:1.07251
[48]	train-mlogloss:1.07460	validation-mlogloss:1.06832
[49]	train-mlogloss:1.07069	validation-mlogloss:1.06425
[50]	train-mlogloss:1.06702	validation-mlogloss:1.06063
[51]	train-mlogloss:1.06339	validation-mlogloss:1.05697
[52]	train-mlogloss:1.05960	validation-mlogloss:1.05339
[53]	train-mlogloss:1.05606	validation-mlogloss:1.04991
[54]	train-mlogloss:1.05229	validation-mlogloss:1.04610
[55]	train-mlogloss:1.04842	validation-mlogloss:1.04204
[56]	train-mlogloss:1.04483	validation-mlogloss:1.03834
[57]	train-mlogloss:1.04123	validation-mlogloss:1.03462
[58]	train-mlogloss:1.03762	validation-mlogloss:1.03094
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[61]	train-mlogloss:1.02689	validation-mlogloss:1.02000
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[63]	train-mlogloss:1.02010	validation-mlogloss:1.01319
[64]	train-mlogloss:1.01692	validation-mlogloss:1.00987
[65]	train-mlogloss:1.01387	validation-mlogloss:1.00680
[66]	train-mlogloss:1.01044	validation-mlogloss:1.00327
[67]	train-mlogloss:1.00726	validation-mlogloss:1.00011
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[70]	train-mlogloss:0.99785	validation-mlogloss:0.99048
[71]	train-mlogloss:0.99498	validation-mlogloss:0.98771
[72]	train-mlogloss:0.99199	validation-mlogloss:0.98481
[73]	train-mlogloss:0.98911	validation-mlogloss:0.98195
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[75]	train-mlogloss:0.98352	validation-mlogloss:0.97650
[76]	train-mlogloss:0.98077	validation-mlogloss:0.97382
[77]	train-mlogloss:0.97810	validation-mlogloss:0.97119
[78]	train-mlogloss:0.97545	validation-mlogloss:0.96834
[79]	train-mlogloss:0.97300	validation-mlogloss:0.96579
[80]	train-mlogloss:0.97059	validation-mlogloss:0.96341
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[82]	train-mlogloss:0.96554	validation-mlogloss:0.95817
[83]	train-mlogloss:0.96300	validation-mlogloss:0.95559
[84]	train-mlogloss:0.96063	validation-mlogloss:0.95315
[85]	train-mlogloss:0.95798	validation-mlogloss:0.95038
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[90]	train-mlogloss:0.94613	validation-mlogloss:0.93855
[91]	train-mlogloss:0.94381	validation-mlogloss:0.93625
[92]	train-mlogloss:0.94155	validation-mlogloss:0.93391
[93]	train-mlogloss:0.93940	validation-mlogloss:0.93187
[94]	train-mlogloss:0.93718	validation-mlogloss:0.92963
[95]	train-mlogloss:0.93502	validation-mlogloss:0.92747
[96]	train-mlogloss:0.93288	validation-mlogloss:0.92535
[97]	train-mlogloss:0.93084	validation-mlogloss:0.92321
[98]	train-mlogloss:0.92871	validation-mlogloss:0.92119
[99]	train-mlogloss:0.92652	validation-mlogloss:0.91884
[100]	train-mlogloss:0.92452	validation-mlogloss:0.91681
[101]	train-mlogloss:0.92256	validation-mlogloss:0.91487
[102]	train-mlogloss:0.92051	validation-mlogloss:0.91283
[103]	train-mlogloss:0.91866	validation-mlogloss:0.91087
[104]	train-mlogloss:0.91659	validation-mlogloss:0.90898
[105]	train-mlogloss:0.91474	validation-mlogloss:0.90716
[106]	train-mlogloss:0.91289	validation-mlogloss:0.90528
[107]	train-mlogloss:0.91097	validation-mlogloss:0.90328
[108]	train-mlogloss:0.90912	validation-mlogloss:0.90143
[109]	train-mlogloss:0.90741	validation-mlogloss:0.89985
[110]	train-mlogloss:0.90553	validation-mlogloss:0.89801
[111]	train-mlogloss:0.90372	validation-mlogloss:0.89608
[112]	train-mlogloss:0.90201	validation-mlogloss:0.89445
[113]	train-mlogloss:0.90019	validation-mlogloss:0.89264
[114]	train-mlogloss:0.89860	validation-mlogloss:0.89126
[115]	train-mlogloss:0.89683	validation-mlogloss:0.88941
[116]	train-mlogloss:0.89511	validation-mlogloss:0.88773
[117]	train-mlogloss:0.89330	validation-mlogloss:0.88593
[118]	train-mlogloss:0.89171	validation-mlogloss:0.88445
[119]	train-mlogloss:0.88991	validation-mlogloss:0.88273
[120]	train-mlogloss:0.88817	validation-mlogloss:0.88106
[121]	train-mlogloss:0.88642	validation-mlogloss:0.87932
[122]	train-mlogloss:0.88482	validation-mlogloss:0.87761
[123]	train-mlogloss:0.88324	validation-mlogloss:0.87613
[124]	train-mlogloss:0.88161	validation-mlogloss:0.87447
[125]	train-mlogloss:0.88002	validation-mlogloss:0.87299
[126]	train-mlogloss:0.87844	validation-mlogloss:0.87155
[127]	train-mlogloss:0.87691	validation-mlogloss:0.87010
[128]	train-mlogloss:0.87530	validation-mlogloss:0.86853
[129]	train-mlogloss:0.87389	validation-mlogloss:0.86723
[130]	train-mlogloss:0.87234	validation-mlogloss:0.86567
[131]	train-mlogloss:0.87081	validation-mlogloss:0.86405
[132]	train-mlogloss:0.86942	validation-mlogloss:0.86273
[133]	train-mlogloss:0.86798	validation-mlogloss:0.86126
[134]	train-mlogloss:0.86656	validation-mlogloss:0.85997
[135]	train-mlogloss:0.86513	validation-mlogloss:0.85864
[136]	train-mlogloss:0.86379	validation-mlogloss:0.85739
[137]	train-mlogloss:0.86239	validation-mlogloss:0.85609
[138]	train-mlogloss:0.86116	validation-mlogloss:0.85503
[139]	train-mlogloss:0.85984	validation-mlogloss:0.85368
[140]	train-mlogloss:0.85848	validation-mlogloss:0.85233
[141]	train-mlogloss:0.85707	validation-mlogloss:0.85087
[142]	train-mlogloss:0.85579	validation-mlogloss:0.84969
[143]	train-mlogloss:0.85446	validation-mlogloss:0.84846
[144]	train-mlogloss:0.85317	validation-mlogloss:0.84712
[145]	train-mlogloss:0.85187	validation-mlogloss:0.84578
[146]	train-mlogloss:0.85067	validation-mlogloss:0.84448
[147]	train-mlogloss:0.84938	validation-mlogloss:0.84326
[148]	train-mlogloss:0.84814	validation-mlogloss:0.84204
[149]	train-mlogloss:0.84687	validation-mlogloss:0.84078
[150]	train-mlogloss:0.84554	validation-mlogloss:0.83937
[151]	train-mlogloss:0.84427	validation-mlogloss:0.83790
[152]	train-mlogloss:0.84301	validation-mlogloss:0.83662
[153]	train-mlogloss:0.84182	validation-mlogloss:0.83537
[154]	train-mlogloss:0.84062	validation-mlogloss:0.83426
[155]	train-mlogloss:0.83949	validation-mlogloss:0.83322
[156]	train-mlogloss:0.83818	validation-mlogloss:0.83201
[157]	train-mlogloss:0.83705	validation-mlogloss:0.83097
[158]	train-mlogloss:0.83588	validation-mlogloss:0.82971
[159]	train-mlogloss:0.83475	validation-mlogloss:0.82863
[160]	train-mlogloss:0.83364	validation-mlogloss:0.82731
[161]	train-mlogloss:0.83243	validation-mlogloss:0.82604
[162]	train-mlogloss:0.83125	validation-mlogloss:0.82491
[163]	train-mlogloss:0.83027	validation-mlogloss:0.82393
[164]	train-mlogloss:0.82914	validation-mlogloss:0.82273
[165]	train-mlogloss:0.82796	validation-mlogloss:0.82148
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[169]	train-mlogloss:0.82371	validation-mlogloss:0.81745
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[171]	train-mlogloss:0.82157	validation-mlogloss:0.81541
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[186]	train-mlogloss:0.80668	validation-mlogloss:0.80090
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[188]	train-mlogloss:0.80479	validation-mlogloss:0.79911
[189]	train-mlogloss:0.80382	validation-mlogloss:0.79824
[190]	train-mlogloss:0.80285	validation-mlogloss:0.79725
[191]	train-mlogloss:0.80200	validation-mlogloss:0.79640
[192]	train-mlogloss:0.80109	validation-mlogloss:0.79551
[193]	train-mlogloss:0.80016	validation-mlogloss:0.79455
[194]	train-mlogloss:0.79919	validation-mlogloss:0.79368
[195]	train-mlogloss:0.79839	validation-mlogloss:0.79293
[196]	train-mlogloss:0.79746	validation-mlogloss:0.79199
[197]	train-mlogloss:0.79657	validation-mlogloss:0.79124
[198]	train-mlogloss:0.79571	validation-mlogloss:0.79036
[199]	train-mlogloss:0.79481	validation-mlogloss:0.78953
[200]	train-mlogloss:0.79391	validation-mlogloss:0.78866
[201]	train-mlogloss:0.79319	validation-mlogloss:0.78808
[202]	train-mlogloss:0.79247	validation-mlogloss:0.78749
[203]	train-mlogloss:0.79162	validation-mlogloss:0.78665
[204]	train-mlogloss:0.79079	validation-mlogloss:0.78589
[205]	train-mlogloss:0.78991	validation-mlogloss:0.78513
[206]	train-mlogloss:0.78921	validation-mlogloss:0.78448
[207]	train-mlogloss:0.78833	validation-mlogloss:0.78355
[208]	train-mlogloss:0.78753	validation-mlogloss:0.78273
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[210]	train-mlogloss:0.78588	validation-mlogloss:0.78126
[211]	train-mlogloss:0.78503	validation-mlogloss:0.78056
[212]	train-mlogloss:0.78416	validation-mlogloss:0.77970
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[214]	train-mlogloss:0.78248	validation-mlogloss:0.77814
[215]	train-mlogloss:0.78176	validation-mlogloss:0.77746
[216]	train-mlogloss:0.78102	validation-mlogloss:0.77677
[217]	train-mlogloss:0.78020	validation-mlogloss:0.77600
[218]	train-mlogloss:0.77941	validation-mlogloss:0.77521
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[220]	train-mlogloss:0.77789	validation-mlogloss:0.77361
[221]	train-mlogloss:0.77716	validation-mlogloss:0.77296
[222]	train-mlogloss:0.77632	validation-mlogloss:0.77218
[223]	train-mlogloss:0.77553	validation-mlogloss:0.77140
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[225]	train-mlogloss:0.77414	validation-mlogloss:0.77023
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[228]	train-mlogloss:0.77190	validation-mlogloss:0.76808
[229]	train-mlogloss:0.77125	validation-mlogloss:0.76739
[230]	train-mlogloss:0.77063	validation-mlogloss:0.76684
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[265]	train-mlogloss:0.74887	validation-mlogloss:0.74774
[266]	train-mlogloss:0.74831	validation-mlogloss:0.74722
[267]	train-mlogloss:0.74767	validation-mlogloss:0.74662
[268]	train-mlogloss:0.74711	validation-mlogloss:0.74620
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[270]	train-mlogloss:0.74599	validation-mlogloss:0.74504
[271]	train-mlogloss:0.74536	validation-mlogloss:0.74441
[272]	train-mlogloss:0.74476	validation-mlogloss:0.74379
[273]	train-mlogloss:0.74425	validation-mlogloss:0.74341
[274]	train-mlogloss:0.74371	validation-mlogloss:0.74292
[275]	train-mlogloss:0.74313	validation-mlogloss:0.74242
[276]	train-mlogloss:0.74261	validation-mlogloss:0.74200
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[278]	train-mlogloss:0.74152	validation-mlogloss:0.74126
[279]	train-mlogloss:0.74107	validation-mlogloss:0.74092
[280]	train-mlogloss:0.74055	validation-mlogloss:0.74044
[281]	train-mlogloss:0.74002	validation-mlogloss:0.73995
[282]	train-mlogloss:0.73957	validation-mlogloss:0.73949
[283]	train-mlogloss:0.73896	validation-mlogloss:0.73898
[284]	train-mlogloss:0.73842	validation-mlogloss:0.73850
[285]	train-mlogloss:0.73800	validation-mlogloss:0.73816
[286]	train-mlogloss:0.73751	validation-mlogloss:0.73781
[287]	train-mlogloss:0.73702	validation-mlogloss:0.73732
[288]	train-mlogloss:0.73652	validation-mlogloss:0.73684
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[290]	train-mlogloss:0.73557	validation-mlogloss:0.73600
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[294]	train-mlogloss:0.73365	validation-mlogloss:0.73450
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[297]	train-mlogloss:0.73223	validation-mlogloss:0.73325
[298]	train-mlogloss:0.73176	validation-mlogloss:0.73293
[299]	train-mlogloss:0.73130	validation-mlogloss:0.73260
[300]	train-mlogloss:0.73089	validation-mlogloss:0.73230
[301]	train-mlogloss:0.73046	validation-mlogloss:0.73203
[302]	train-mlogloss:0.72998	validation-mlogloss:0.73154
[303]	train-mlogloss:0.72959	validation-mlogloss:0.73128
[304]	train-mlogloss:0.72908	validation-mlogloss:0.73090
[305]	train-mlogloss:0.72870	validation-mlogloss:0.73058
[306]	train-mlogloss:0.72825	validation-mlogloss:0.73016
[307]	train-mlogloss:0.72791	validation-mlogloss:0.72981
[308]	train-mlogloss:0.72747	validation-mlogloss:0.72955
[309]	train-mlogloss:0.72705	validation-mlogloss:0.72928
[310]	train-mlogloss:0.72653	validation-mlogloss:0.72875
[311]	train-mlogloss:0.72621	validation-mlogloss:0.72849
[312]	train-mlogloss:0.72576	validation-mlogloss:0.72813
[313]	train-mlogloss:0.72538	validation-mlogloss:0.72777
[314]	train-mlogloss:0.72498	validation-mlogloss:0.72746
[315]	train-mlogloss:0.72459	validation-mlogloss:0.72716
[316]	train-mlogloss:0.72408	validation-mlogloss:0.72675
[317]	train-mlogloss:0.72371	validation-mlogloss:0.72640
[318]	train-mlogloss:0.72326	validation-mlogloss:0.72612
[319]	train-mlogloss:0.72288	validation-mlogloss:0.72587
[320]	train-mlogloss:0.72240	validation-mlogloss:0.72550
[321]	train-mlogloss:0.72201	validation-mlogloss:0.72517
[322]	train-mlogloss:0.72164	validation-mlogloss:0.72490
[323]	train-mlogloss:0.72118	validation-mlogloss:0.72449
[324]	train-mlogloss:0.72078	validation-mlogloss:0.72406
[325]	train-mlogloss:0.72040	validation-mlogloss:0.72379
[326]	train-mlogloss:0.71995	validation-mlogloss:0.72342
[327]	train-mlogloss:0.71954	validation-mlogloss:0.72303
[328]	train-mlogloss:0.71917	validation-mlogloss:0.72273
[329]	train-mlogloss:0.71869	validation-mlogloss:0.72243
[330]	train-mlogloss:0.71839	validation-mlogloss:0.72221
[331]	train-mlogloss:0.71804	validation-mlogloss:0.72198
[332]	train-mlogloss:0.71767	validation-mlogloss:0.72161
[333]	train-mlogloss:0.71717	validation-mlogloss:0.72119
[334]	train-mlogloss:0.71683	validation-mlogloss:0.72093
[335]	train-mlogloss:0.71649	validation-mlogloss:0.72063
[336]	train-mlogloss:0.71610	validation-mlogloss:0.72033
[337]	train-mlogloss:0.71575	validation-mlogloss:0.72003
[338]	train-mlogloss:0.71546	validation-mlogloss:0.71981
[339]	train-mlogloss:0.71501	validation-mlogloss:0.71936
[340]	train-mlogloss:0.71469	validation-mlogloss:0.71910
[341]	train-mlogloss:0.71430	validation-mlogloss:0.71880
[342]	train-mlogloss:0.71401	validation-mlogloss:0.71855
[343]	train-mlogloss:0.71362	validation-mlogloss:0.71823
[344]	train-mlogloss:0.71328	validation-mlogloss:0.71792
[345]	train-mlogloss:0.71294	validation-mlogloss:0.71768
[346]	train-mlogloss:0.71260	validation-mlogloss:0.71740
[347]	train-mlogloss:0.71227	validation-mlogloss:0.71707
[348]	train-mlogloss:0.71194	validation-mlogloss:0.71679
[349]	train-mlogloss:0.71162	validation-mlogloss:0.71653
[350]	train-mlogloss:0.71137	validation-mlogloss:0.71631
[351]	train-mlogloss:0.71108	validation-mlogloss:0.71616
[352]	train-mlogloss:0.71073	validation-mlogloss:0.71589
[353]	train-mlogloss:0.71041	validation-mlogloss:0.71561
[354]	train-mlogloss:0.71004	validation-mlogloss:0.71533
[355]	train-mlogloss:0.70983	validation-mlogloss:0.71513
[356]	train-mlogloss:0.70949	validation-mlogloss:0.71493
[357]	train-mlogloss:0.70918	validation-mlogloss:0.71472
[358]	train-mlogloss:0.70886	validation-mlogloss:0.71447
[359]	train-mlogloss:0.70863	validation-mlogloss:0.71433
[360]	train-mlogloss:0.70838	validation-mlogloss:0.71413
[361]	train-mlogloss:0.70804	validation-mlogloss:0.71389
[362]	train-mlogloss:0.70775	validation-mlogloss:0.71361
[363]	train-mlogloss:0.70756	validation-mlogloss:0.71353
[364]	train-mlogloss:0.70718	validation-mlogloss:0.71326
[365]	train-mlogloss:0.70684	validation-mlogloss:0.71299
[366]	train-mlogloss:0.70656	validation-mlogloss:0.71274
[367]	train-mlogloss:0.70624	validation-mlogloss:0.71246
[368]	train-mlogloss:0.70599	validation-mlogloss:0.71222
[369]	train-mlogloss:0.70574	validation-mlogloss:0.71195
[370]	train-mlogloss:0.70539	validation-mlogloss:0.71154
[371]	train-mlogloss:0.70511	validation-mlogloss:0.71133
[372]	train-mlogloss:0.70477	validation-mlogloss:0.71108
[373]	train-mlogloss:0.70453	validation-mlogloss:0.71086
[374]	train-mlogloss:0.70422	validation-mlogloss:0.71062
[375]	train-mlogloss:0.70391	validation-mlogloss:0.71038
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.25 [%]
Global accuracy score (test) = 70.49 [%]
Global F1 score (train) = 73.11 [%]
Global F1 score (test) = 70.62 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.59      0.43      0.50       400
MODERATE-INTENSITY       0.57      0.84      0.68       400
         SEDENTARY       0.82      0.82      0.82       400
VIGOROUS-INTENSITY       0.94      0.73      0.82       345

          accuracy                           0.70      1545
         macro avg       0.73      0.71      0.71      1545
      weighted avg       0.72      0.70      0.70      1545


Accuracy capturado en la ejecución 3: 70.49 [%]
F1-score capturado en la ejecución 3: 70.62 [%]

=== EJECUCIÓN 4 ===

--- TRAIN (ejecución 4) ---

--- TEST (ejecución 4) ---
2025-11-04 10:34:13.312702: 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 10:34:13.323792: 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 00:00:1762248853.336939 1052695 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248853.340845 1052695 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248853.351015 1052695 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248853.351032 1052695 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248853.351041 1052695 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248853.351042 1052695 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:34:13.354005: 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:1.37688	validation-mlogloss:1.37628
[1]	train-mlogloss:1.36738	validation-mlogloss:1.36649
[2]	train-mlogloss:1.35805	validation-mlogloss:1.35670
[3]	train-mlogloss:1.34934	validation-mlogloss:1.34720
[4]	train-mlogloss:1.34125	validation-mlogloss:1.33872
[5]	train-mlogloss:1.33278	validation-mlogloss:1.33006
[6]	train-mlogloss:1.32433	validation-mlogloss:1.32137
[7]	train-mlogloss:1.31647	validation-mlogloss:1.31333
[8]	train-mlogloss:1.30848	validation-mlogloss:1.30469
[9]	train-mlogloss:1.30066	validation-mlogloss:1.29671
[10]	train-mlogloss:1.29271	validation-mlogloss:1.28826
[11]	train-mlogloss:1.28495	validation-mlogloss:1.28042
[12]	train-mlogloss:1.27739	validation-mlogloss:1.27262
[13]	train-mlogloss:1.26981	validation-mlogloss:1.26473
[14]	train-mlogloss:1.26234	validation-mlogloss:1.25696
[15]	train-mlogloss:1.25547	validation-mlogloss:1.24974
[16]	train-mlogloss:1.24855	validation-mlogloss:1.24310
[17]	train-mlogloss:1.24192	validation-mlogloss:1.23629
[18]	train-mlogloss:1.23549	validation-mlogloss:1.22994
[19]	train-mlogloss:1.22876	validation-mlogloss:1.22303
[20]	train-mlogloss:1.22235	validation-mlogloss:1.21651
[21]	train-mlogloss:1.21617	validation-mlogloss:1.21043
[22]	train-mlogloss:1.20990	validation-mlogloss:1.20413
[23]	train-mlogloss:1.20380	validation-mlogloss:1.19800
[24]	train-mlogloss:1.19746	validation-mlogloss:1.19173
[25]	train-mlogloss:1.19180	validation-mlogloss:1.18582
[26]	train-mlogloss:1.18570	validation-mlogloss:1.17970
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[325]	train-mlogloss:0.71964	validation-mlogloss:0.72162
[326]	train-mlogloss:0.71924	validation-mlogloss:0.72137
[327]	train-mlogloss:0.71884	validation-mlogloss:0.72096
[328]	train-mlogloss:0.71844	validation-mlogloss:0.72066
[329]	train-mlogloss:0.71806	validation-mlogloss:0.72036
[330]	train-mlogloss:0.71771	validation-mlogloss:0.72010
[331]	train-mlogloss:0.71720	validation-mlogloss:0.71969
[332]	train-mlogloss:0.71687	validation-mlogloss:0.71943
[333]	train-mlogloss:0.71643	validation-mlogloss:0.71906
[334]	train-mlogloss:0.71603	validation-mlogloss:0.71870
[335]	train-mlogloss:0.71568	validation-mlogloss:0.71839
[336]	train-mlogloss:0.71548	validation-mlogloss:0.71819
[337]	train-mlogloss:0.71520	validation-mlogloss:0.71797
[338]	train-mlogloss:0.71484	validation-mlogloss:0.71763
[339]	train-mlogloss:0.71452	validation-mlogloss:0.71740
[340]	train-mlogloss:0.71421	validation-mlogloss:0.71714
[341]	train-mlogloss:0.71394	validation-mlogloss:0.71691
[342]	train-mlogloss:0.71364	validation-mlogloss:0.71669
[343]	train-mlogloss:0.71326	validation-mlogloss:0.71638
[344]	train-mlogloss:0.71283	validation-mlogloss:0.71606
[345]	train-mlogloss:0.71247	validation-mlogloss:0.71578
[346]	train-mlogloss:0.71216	validation-mlogloss:0.71543
[347]	train-mlogloss:0.71185	validation-mlogloss:0.71513
[348]	train-mlogloss:0.71156	validation-mlogloss:0.71491
[349]	train-mlogloss:0.71111	validation-mlogloss:0.71458
[350]	train-mlogloss:0.71072	validation-mlogloss:0.71425
[351]	train-mlogloss:0.71029	validation-mlogloss:0.71398
[352]	train-mlogloss:0.71004	validation-mlogloss:0.71379
[353]	train-mlogloss:0.70964	validation-mlogloss:0.71356
[354]	train-mlogloss:0.70910	validation-mlogloss:0.71323
[355]	train-mlogloss:0.70880	validation-mlogloss:0.71300
[356]	train-mlogloss:0.70844	validation-mlogloss:0.71275
[357]	train-mlogloss:0.70813	validation-mlogloss:0.71253
[358]	train-mlogloss:0.70782	validation-mlogloss:0.71233
[359]	train-mlogloss:0.70755	validation-mlogloss:0.71216
[360]	train-mlogloss:0.70724	validation-mlogloss:0.71197
[361]	train-mlogloss:0.70701	validation-mlogloss:0.71176
[362]	train-mlogloss:0.70664	validation-mlogloss:0.71155
[363]	train-mlogloss:0.70623	validation-mlogloss:0.71134
[364]	train-mlogloss:0.70592	validation-mlogloss:0.71111
[365]	train-mlogloss:0.70555	validation-mlogloss:0.71086
[366]	train-mlogloss:0.70524	validation-mlogloss:0.71058
[367]	train-mlogloss:0.70496	validation-mlogloss:0.71038
[368]	train-mlogloss:0.70470	validation-mlogloss:0.71021
[369]	train-mlogloss:0.70437	validation-mlogloss:0.70992
[370]	train-mlogloss:0.70405	validation-mlogloss:0.70965
[371]	train-mlogloss:0.70375	validation-mlogloss:0.70938
[372]	train-mlogloss:0.70342	validation-mlogloss:0.70916
[373]	train-mlogloss:0.70325	validation-mlogloss:0.70902
[374]	train-mlogloss:0.70292	validation-mlogloss:0.70880
[375]	train-mlogloss:0.70261	validation-mlogloss:0.70851
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.45 [%]
Global accuracy score (test) = 71.65 [%]
Global F1 score (train) = 73.38 [%]
Global F1 score (test) = 71.75 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.45      0.52       400
MODERATE-INTENSITY       0.58      0.85      0.69       400
         SEDENTARY       0.84      0.84      0.84       400
VIGOROUS-INTENSITY       0.94      0.73      0.82       345

          accuracy                           0.72      1545
         macro avg       0.74      0.72      0.72      1545
      weighted avg       0.74      0.72      0.71      1545


Accuracy capturado en la ejecución 4: 71.65 [%]
F1-score capturado en la ejecución 4: 71.75 [%]

=== EJECUCIÓN 5 ===

--- TRAIN (ejecución 5) ---

--- TEST (ejecución 5) ---
2025-11-04 10:34:29.276111: 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 10:34:29.287701: 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 00:00:1762248869.300794 1053037 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248869.304871 1053037 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248869.314777 1053037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248869.314795 1053037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248869.314796 1053037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248869.314798 1053037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:34:29.317881: 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:1.37671	validation-mlogloss:1.37634
[1]	train-mlogloss:1.36778	validation-mlogloss:1.36709
[2]	train-mlogloss:1.35864	validation-mlogloss:1.35752
[3]	train-mlogloss:1.34970	validation-mlogloss:1.34796
[4]	train-mlogloss:1.34092	validation-mlogloss:1.33860
[5]	train-mlogloss:1.33222	validation-mlogloss:1.32914
[6]	train-mlogloss:1.32395	validation-mlogloss:1.32063
[7]	train-mlogloss:1.31568	validation-mlogloss:1.31214
[8]	train-mlogloss:1.30735	validation-mlogloss:1.30369
[9]	train-mlogloss:1.29975	validation-mlogloss:1.29616
[10]	train-mlogloss:1.29192	validation-mlogloss:1.28800
[11]	train-mlogloss:1.28424	validation-mlogloss:1.28015
[12]	train-mlogloss:1.27637	validation-mlogloss:1.27202
[13]	train-mlogloss:1.26921	validation-mlogloss:1.26481
[14]	train-mlogloss:1.26221	validation-mlogloss:1.25755
[15]	train-mlogloss:1.25507	validation-mlogloss:1.25030
[16]	train-mlogloss:1.24809	validation-mlogloss:1.24327
[17]	train-mlogloss:1.24095	validation-mlogloss:1.23590
[18]	train-mlogloss:1.23463	validation-mlogloss:1.22930
[19]	train-mlogloss:1.22806	validation-mlogloss:1.22258
[20]	train-mlogloss:1.22130	validation-mlogloss:1.21557
[21]	train-mlogloss:1.21509	validation-mlogloss:1.20915
[22]	train-mlogloss:1.20892	validation-mlogloss:1.20298
[23]	train-mlogloss:1.20257	validation-mlogloss:1.19621
[24]	train-mlogloss:1.19632	validation-mlogloss:1.18971
[25]	train-mlogloss:1.19023	validation-mlogloss:1.18322
[26]	train-mlogloss:1.18457	validation-mlogloss:1.17728
[27]	train-mlogloss:1.17865	validation-mlogloss:1.17124
[28]	train-mlogloss:1.17317	validation-mlogloss:1.16552
[29]	train-mlogloss:1.16749	validation-mlogloss:1.15966
[30]	train-mlogloss:1.16196	validation-mlogloss:1.15386
[31]	train-mlogloss:1.15653	validation-mlogloss:1.14835
[32]	train-mlogloss:1.15133	validation-mlogloss:1.14328
[33]	train-mlogloss:1.14593	validation-mlogloss:1.13751
[34]	train-mlogloss:1.14100	validation-mlogloss:1.13248
[35]	train-mlogloss:1.13585	validation-mlogloss:1.12721
[36]	train-mlogloss:1.13112	validation-mlogloss:1.12257
[37]	train-mlogloss:1.12632	validation-mlogloss:1.11794
[38]	train-mlogloss:1.12153	validation-mlogloss:1.11312
[39]	train-mlogloss:1.11663	validation-mlogloss:1.10823
[40]	train-mlogloss:1.11200	validation-mlogloss:1.10362
[41]	train-mlogloss:1.10732	validation-mlogloss:1.09885
[42]	train-mlogloss:1.10277	validation-mlogloss:1.09417
[43]	train-mlogloss:1.09836	validation-mlogloss:1.08982
[44]	train-mlogloss:1.09404	validation-mlogloss:1.08549
[45]	train-mlogloss:1.08977	validation-mlogloss:1.08112
[46]	train-mlogloss:1.08544	validation-mlogloss:1.07662
[47]	train-mlogloss:1.08143	validation-mlogloss:1.07271
[48]	train-mlogloss:1.07720	validation-mlogloss:1.06845
[49]	train-mlogloss:1.07324	validation-mlogloss:1.06418
[50]	train-mlogloss:1.06918	validation-mlogloss:1.05997
[51]	train-mlogloss:1.06529	validation-mlogloss:1.05614
[52]	train-mlogloss:1.06137	validation-mlogloss:1.05197
[53]	train-mlogloss:1.05754	validation-mlogloss:1.04817
[54]	train-mlogloss:1.05382	validation-mlogloss:1.04434
[55]	train-mlogloss:1.05026	validation-mlogloss:1.04074
[56]	train-mlogloss:1.04663	validation-mlogloss:1.03717
[57]	train-mlogloss:1.04308	validation-mlogloss:1.03371
[58]	train-mlogloss:1.03961	validation-mlogloss:1.03024
[59]	train-mlogloss:1.03613	validation-mlogloss:1.02660
[60]	train-mlogloss:1.03272	validation-mlogloss:1.02312
[61]	train-mlogloss:1.02922	validation-mlogloss:1.01960
[62]	train-mlogloss:1.02583	validation-mlogloss:1.01624
[63]	train-mlogloss:1.02250	validation-mlogloss:1.01276
[64]	train-mlogloss:1.01923	validation-mlogloss:1.00942
[65]	train-mlogloss:1.01605	validation-mlogloss:1.00611
[66]	train-mlogloss:1.01299	validation-mlogloss:1.00304
[67]	train-mlogloss:1.01008	validation-mlogloss:0.99993
[68]	train-mlogloss:1.00701	validation-mlogloss:0.99664
[69]	train-mlogloss:1.00383	validation-mlogloss:0.99341
[70]	train-mlogloss:1.00078	validation-mlogloss:0.99007
[71]	train-mlogloss:0.99809	validation-mlogloss:0.98733
[72]	train-mlogloss:0.99503	validation-mlogloss:0.98404
[73]	train-mlogloss:0.99214	validation-mlogloss:0.98111
[74]	train-mlogloss:0.98922	validation-mlogloss:0.97836
[75]	train-mlogloss:0.98647	validation-mlogloss:0.97549
[76]	train-mlogloss:0.98363	validation-mlogloss:0.97263
[77]	train-mlogloss:0.98098	validation-mlogloss:0.96994
[78]	train-mlogloss:0.97828	validation-mlogloss:0.96713
[79]	train-mlogloss:0.97575	validation-mlogloss:0.96477
[80]	train-mlogloss:0.97324	validation-mlogloss:0.96225
[81]	train-mlogloss:0.97068	validation-mlogloss:0.95952
[82]	train-mlogloss:0.96816	validation-mlogloss:0.95699
[83]	train-mlogloss:0.96569	validation-mlogloss:0.95455
[84]	train-mlogloss:0.96323	validation-mlogloss:0.95189
[85]	train-mlogloss:0.96076	validation-mlogloss:0.94936
[86]	train-mlogloss:0.95816	validation-mlogloss:0.94661
[87]	train-mlogloss:0.95584	validation-mlogloss:0.94427
[88]	train-mlogloss:0.95345	validation-mlogloss:0.94196
[89]	train-mlogloss:0.95129	validation-mlogloss:0.93976
[90]	train-mlogloss:0.94912	validation-mlogloss:0.93749
[91]	train-mlogloss:0.94688	validation-mlogloss:0.93523
[92]	train-mlogloss:0.94447	validation-mlogloss:0.93284
[93]	train-mlogloss:0.94237	validation-mlogloss:0.93061
[94]	train-mlogloss:0.94025	validation-mlogloss:0.92837
[95]	train-mlogloss:0.93812	validation-mlogloss:0.92604
[96]	train-mlogloss:0.93591	validation-mlogloss:0.92390
[97]	train-mlogloss:0.93381	validation-mlogloss:0.92195
[98]	train-mlogloss:0.93187	validation-mlogloss:0.92025
[99]	train-mlogloss:0.92997	validation-mlogloss:0.91842
[100]	train-mlogloss:0.92780	validation-mlogloss:0.91619
[101]	train-mlogloss:0.92590	validation-mlogloss:0.91437
[102]	train-mlogloss:0.92380	validation-mlogloss:0.91220
[103]	train-mlogloss:0.92189	validation-mlogloss:0.91014
[104]	train-mlogloss:0.91989	validation-mlogloss:0.90814
[105]	train-mlogloss:0.91797	validation-mlogloss:0.90617
[106]	train-mlogloss:0.91610	validation-mlogloss:0.90428
[107]	train-mlogloss:0.91424	validation-mlogloss:0.90250
[108]	train-mlogloss:0.91237	validation-mlogloss:0.90057
[109]	train-mlogloss:0.91056	validation-mlogloss:0.89868
[110]	train-mlogloss:0.90881	validation-mlogloss:0.89672
[111]	train-mlogloss:0.90680	validation-mlogloss:0.89470
[112]	train-mlogloss:0.90513	validation-mlogloss:0.89292
[113]	train-mlogloss:0.90328	validation-mlogloss:0.89107
[114]	train-mlogloss:0.90147	validation-mlogloss:0.88923
[115]	train-mlogloss:0.89973	validation-mlogloss:0.88756
[116]	train-mlogloss:0.89795	validation-mlogloss:0.88572
[117]	train-mlogloss:0.89624	validation-mlogloss:0.88403
[118]	train-mlogloss:0.89455	validation-mlogloss:0.88242
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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}
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Training a non-convolutional model.
Loaded model from disk.
(1545, 91)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[0 1 0 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 72.72 [%]
Global accuracy score (test) = 71.07 [%]
Global F1 score (train) = 72.6 [%]
Global F1 score (test) = 71.27 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.59      0.45      0.51       400
MODERATE-INTENSITY       0.58      0.82      0.68       400
         SEDENTARY       0.84      0.84      0.84       400
VIGOROUS-INTENSITY       0.92      0.73      0.82       345

          accuracy                           0.71      1545
         macro avg       0.73      0.71      0.71      1545
      weighted avg       0.73      0.71      0.71      1545


Accuracy capturado en la ejecución 5: 71.07 [%]
F1-score capturado en la ejecución 5: 71.27 [%]

=== EJECUCIÓN 6 ===

--- TRAIN (ejecución 6) ---

--- TEST (ejecución 6) ---
2025-11-04 10:34:45.422416: 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 10:34:45.433631: 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 00:00:1762248885.446799 1053342 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248885.450919 1053342 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248885.460819 1053342 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248885.460839 1053342 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248885.460840 1053342 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248885.460841 1053342 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:34:45.463998: 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:1.37685	validation-mlogloss:1.37682
[1]	train-mlogloss:1.36733	validation-mlogloss:1.36714
[2]	train-mlogloss:1.35819	validation-mlogloss:1.35754
[3]	train-mlogloss:1.34920	validation-mlogloss:1.34835
[4]	train-mlogloss:1.34025	validation-mlogloss:1.33924
[5]	train-mlogloss:1.33208	validation-mlogloss:1.33065
[6]	train-mlogloss:1.32340	validation-mlogloss:1.32184
[7]	train-mlogloss:1.31498	validation-mlogloss:1.31342
[8]	train-mlogloss:1.30682	validation-mlogloss:1.30494
[9]	train-mlogloss:1.29879	validation-mlogloss:1.29695
[10]	train-mlogloss:1.29106	validation-mlogloss:1.28903
[11]	train-mlogloss:1.28320	validation-mlogloss:1.28121
[12]	train-mlogloss:1.27596	validation-mlogloss:1.27424
[13]	train-mlogloss:1.26859	validation-mlogloss:1.26678
[14]	train-mlogloss:1.26128	validation-mlogloss:1.25942
[15]	train-mlogloss:1.25410	validation-mlogloss:1.25186
[16]	train-mlogloss:1.24699	validation-mlogloss:1.24444
[17]	train-mlogloss:1.24043	validation-mlogloss:1.23786
[18]	train-mlogloss:1.23348	validation-mlogloss:1.23050
[19]	train-mlogloss:1.22697	validation-mlogloss:1.22415
[20]	train-mlogloss:1.22085	validation-mlogloss:1.21831
[21]	train-mlogloss:1.21435	validation-mlogloss:1.21144
[22]	train-mlogloss:1.20787	validation-mlogloss:1.20480
[23]	train-mlogloss:1.20150	validation-mlogloss:1.19817
[24]	train-mlogloss:1.19568	validation-mlogloss:1.19218
[25]	train-mlogloss:1.18967	validation-mlogloss:1.18624
[26]	train-mlogloss:1.18352	validation-mlogloss:1.18007
[27]	train-mlogloss:1.17765	validation-mlogloss:1.17399
[28]	train-mlogloss:1.17180	validation-mlogloss:1.16796
[29]	train-mlogloss:1.16617	validation-mlogloss:1.16207
[30]	train-mlogloss:1.16059	validation-mlogloss:1.15636
[31]	train-mlogloss:1.15507	validation-mlogloss:1.15082
[32]	train-mlogloss:1.14992	validation-mlogloss:1.14564
[33]	train-mlogloss:1.14486	validation-mlogloss:1.14024
[34]	train-mlogloss:1.13963	validation-mlogloss:1.13490
[35]	train-mlogloss:1.13451	validation-mlogloss:1.12967
[36]	train-mlogloss:1.12953	validation-mlogloss:1.12469
[37]	train-mlogloss:1.12459	validation-mlogloss:1.11951
[38]	train-mlogloss:1.11981	validation-mlogloss:1.11480
[39]	train-mlogloss:1.11524	validation-mlogloss:1.11016
[40]	train-mlogloss:1.11057	validation-mlogloss:1.10535
[41]	train-mlogloss:1.10618	validation-mlogloss:1.10104
[42]	train-mlogloss:1.10143	validation-mlogloss:1.09617
[43]	train-mlogloss:1.09662	validation-mlogloss:1.09136
[44]	train-mlogloss:1.09205	validation-mlogloss:1.08671
[45]	train-mlogloss:1.08760	validation-mlogloss:1.08235
[46]	train-mlogloss:1.08365	validation-mlogloss:1.07833
[47]	train-mlogloss:1.07938	validation-mlogloss:1.07398
[48]	train-mlogloss:1.07530	validation-mlogloss:1.07002
[49]	train-mlogloss:1.07116	validation-mlogloss:1.06585
[50]	train-mlogloss:1.06706	validation-mlogloss:1.06183
[51]	train-mlogloss:1.06326	validation-mlogloss:1.05801
[52]	train-mlogloss:1.05941	validation-mlogloss:1.05417
[53]	train-mlogloss:1.05556	validation-mlogloss:1.05023
[54]	train-mlogloss:1.05179	validation-mlogloss:1.04617
[55]	train-mlogloss:1.04805	validation-mlogloss:1.04247
[56]	train-mlogloss:1.04448	validation-mlogloss:1.03889
[57]	train-mlogloss:1.04089	validation-mlogloss:1.03513
[58]	train-mlogloss:1.03727	validation-mlogloss:1.03171
[59]	train-mlogloss:1.03386	validation-mlogloss:1.02816
[60]	train-mlogloss:1.03045	validation-mlogloss:1.02476
[61]	train-mlogloss:1.02705	validation-mlogloss:1.02142
[62]	train-mlogloss:1.02343	validation-mlogloss:1.01784
[63]	train-mlogloss:1.02009	validation-mlogloss:1.01456
[64]	train-mlogloss:1.01657	validation-mlogloss:1.01128
[65]	train-mlogloss:1.01338	validation-mlogloss:1.00797
[66]	train-mlogloss:1.01025	validation-mlogloss:1.00506
[67]	train-mlogloss:1.00687	validation-mlogloss:1.00157
[68]	train-mlogloss:1.00378	validation-mlogloss:0.99847
[69]	train-mlogloss:1.00089	validation-mlogloss:0.99543
[70]	train-mlogloss:0.99793	validation-mlogloss:0.99263
[71]	train-mlogloss:0.99505	validation-mlogloss:0.98969
[72]	train-mlogloss:0.99215	validation-mlogloss:0.98685
[73]	train-mlogloss:0.98919	validation-mlogloss:0.98406
[74]	train-mlogloss:0.98642	validation-mlogloss:0.98117
[75]	train-mlogloss:0.98365	validation-mlogloss:0.97835
[76]	train-mlogloss:0.98075	validation-mlogloss:0.97565
[77]	train-mlogloss:0.97804	validation-mlogloss:0.97289
[78]	train-mlogloss:0.97530	validation-mlogloss:0.97023
[79]	train-mlogloss:0.97258	validation-mlogloss:0.96745
[80]	train-mlogloss:0.96998	validation-mlogloss:0.96491
[81]	train-mlogloss:0.96719	validation-mlogloss:0.96206
[82]	train-mlogloss:0.96456	validation-mlogloss:0.95923
[83]	train-mlogloss:0.96208	validation-mlogloss:0.95677
[84]	train-mlogloss:0.95963	validation-mlogloss:0.95445
[85]	train-mlogloss:0.95716	validation-mlogloss:0.95195
[86]	train-mlogloss:0.95475	validation-mlogloss:0.94940
[87]	train-mlogloss:0.95220	validation-mlogloss:0.94699
[88]	train-mlogloss:0.94981	validation-mlogloss:0.94467
[89]	train-mlogloss:0.94737	validation-mlogloss:0.94229
[90]	train-mlogloss:0.94525	validation-mlogloss:0.94022
[91]	train-mlogloss:0.94314	validation-mlogloss:0.93826
[92]	train-mlogloss:0.94092	validation-mlogloss:0.93600
[93]	train-mlogloss:0.93864	validation-mlogloss:0.93381
[94]	train-mlogloss:0.93646	validation-mlogloss:0.93158
[95]	train-mlogloss:0.93430	validation-mlogloss:0.92947
[96]	train-mlogloss:0.93221	validation-mlogloss:0.92739
[97]	train-mlogloss:0.93016	validation-mlogloss:0.92553
[98]	train-mlogloss:0.92803	validation-mlogloss:0.92336
[99]	train-mlogloss:0.92603	validation-mlogloss:0.92126
[100]	train-mlogloss:0.92392	validation-mlogloss:0.91921
[101]	train-mlogloss:0.92192	validation-mlogloss:0.91727
[102]	train-mlogloss:0.91981	validation-mlogloss:0.91514
[103]	train-mlogloss:0.91777	validation-mlogloss:0.91303
[104]	train-mlogloss:0.91598	validation-mlogloss:0.91121
[105]	train-mlogloss:0.91402	validation-mlogloss:0.90921
[106]	train-mlogloss:0.91214	validation-mlogloss:0.90734
[107]	train-mlogloss:0.91003	validation-mlogloss:0.90518
[108]	train-mlogloss:0.90809	validation-mlogloss:0.90340
[109]	train-mlogloss:0.90624	validation-mlogloss:0.90153
[110]	train-mlogloss:0.90434	validation-mlogloss:0.89965
[111]	train-mlogloss:0.90225	validation-mlogloss:0.89757
[112]	train-mlogloss:0.90039	validation-mlogloss:0.89579
[113]	train-mlogloss:0.89867	validation-mlogloss:0.89416
[114]	train-mlogloss:0.89680	validation-mlogloss:0.89245
[115]	train-mlogloss:0.89500	validation-mlogloss:0.89063
[116]	train-mlogloss:0.89331	validation-mlogloss:0.88899
[117]	train-mlogloss:0.89145	validation-mlogloss:0.88708
[118]	train-mlogloss:0.88981	validation-mlogloss:0.88538
[119]	train-mlogloss:0.88793	validation-mlogloss:0.88362
[120]	train-mlogloss:0.88631	validation-mlogloss:0.88213
[121]	train-mlogloss:0.88468	validation-mlogloss:0.88044
[122]	train-mlogloss:0.88297	validation-mlogloss:0.87882
[123]	train-mlogloss:0.88148	validation-mlogloss:0.87738
[124]	train-mlogloss:0.87976	validation-mlogloss:0.87562
[125]	train-mlogloss:0.87810	validation-mlogloss:0.87387
[126]	train-mlogloss:0.87660	validation-mlogloss:0.87239
[127]	train-mlogloss:0.87503	validation-mlogloss:0.87073
[128]	train-mlogloss:0.87369	validation-mlogloss:0.86944
[129]	train-mlogloss:0.87228	validation-mlogloss:0.86795
[130]	train-mlogloss:0.87061	validation-mlogloss:0.86639
[131]	train-mlogloss:0.86886	validation-mlogloss:0.86477
[132]	train-mlogloss:0.86716	validation-mlogloss:0.86318
[133]	train-mlogloss:0.86569	validation-mlogloss:0.86168
[134]	train-mlogloss:0.86431	validation-mlogloss:0.86034
[135]	train-mlogloss:0.86293	validation-mlogloss:0.85914
[136]	train-mlogloss:0.86149	validation-mlogloss:0.85765
[137]	train-mlogloss:0.86019	validation-mlogloss:0.85623
[138]	train-mlogloss:0.85884	validation-mlogloss:0.85494
[139]	train-mlogloss:0.85740	validation-mlogloss:0.85348
[140]	train-mlogloss:0.85610	validation-mlogloss:0.85239
[141]	train-mlogloss:0.85485	validation-mlogloss:0.85127
[142]	train-mlogloss:0.85349	validation-mlogloss:0.85000
[143]	train-mlogloss:0.85216	validation-mlogloss:0.84885
[144]	train-mlogloss:0.85080	validation-mlogloss:0.84738
[145]	train-mlogloss:0.84927	validation-mlogloss:0.84594
[146]	train-mlogloss:0.84799	validation-mlogloss:0.84464
[147]	train-mlogloss:0.84677	validation-mlogloss:0.84358
[148]	train-mlogloss:0.84567	validation-mlogloss:0.84255
[149]	train-mlogloss:0.84432	validation-mlogloss:0.84122
[150]	train-mlogloss:0.84309	validation-mlogloss:0.84011
[151]	train-mlogloss:0.84195	validation-mlogloss:0.83905
[152]	train-mlogloss:0.84070	validation-mlogloss:0.83790
[153]	train-mlogloss:0.83933	validation-mlogloss:0.83667
[154]	train-mlogloss:0.83790	validation-mlogloss:0.83551
[155]	train-mlogloss:0.83672	validation-mlogloss:0.83423
[156]	train-mlogloss:0.83541	validation-mlogloss:0.83288
[157]	train-mlogloss:0.83412	validation-mlogloss:0.83166
[158]	train-mlogloss:0.83282	validation-mlogloss:0.83041
[159]	train-mlogloss:0.83161	validation-mlogloss:0.82932
[160]	train-mlogloss:0.83033	validation-mlogloss:0.82821
[161]	train-mlogloss:0.82929	validation-mlogloss:0.82711
[162]	train-mlogloss:0.82813	validation-mlogloss:0.82616
[163]	train-mlogloss:0.82685	validation-mlogloss:0.82496
[164]	train-mlogloss:0.82564	validation-mlogloss:0.82392
[165]	train-mlogloss:0.82451	validation-mlogloss:0.82284
[166]	train-mlogloss:0.82341	validation-mlogloss:0.82188
[167]	train-mlogloss:0.82230	validation-mlogloss:0.82098
[168]	train-mlogloss:0.82104	validation-mlogloss:0.81990
[169]	train-mlogloss:0.81989	validation-mlogloss:0.81874
[170]	train-mlogloss:0.81884	validation-mlogloss:0.81769
[171]	train-mlogloss:0.81769	validation-mlogloss:0.81665
[172]	train-mlogloss:0.81655	validation-mlogloss:0.81543
[173]	train-mlogloss:0.81539	validation-mlogloss:0.81445
[174]	train-mlogloss:0.81434	validation-mlogloss:0.81350
[175]	train-mlogloss:0.81338	validation-mlogloss:0.81260
[176]	train-mlogloss:0.81236	validation-mlogloss:0.81165
[177]	train-mlogloss:0.81121	validation-mlogloss:0.81054
[178]	train-mlogloss:0.81024	validation-mlogloss:0.80965
[179]	train-mlogloss:0.80919	validation-mlogloss:0.80874
[180]	train-mlogloss:0.80805	validation-mlogloss:0.80774
[181]	train-mlogloss:0.80708	validation-mlogloss:0.80691
[182]	train-mlogloss:0.80598	validation-mlogloss:0.80593
[183]	train-mlogloss:0.80483	validation-mlogloss:0.80484
[184]	train-mlogloss:0.80381	validation-mlogloss:0.80380
[185]	train-mlogloss:0.80276	validation-mlogloss:0.80292
[186]	train-mlogloss:0.80183	validation-mlogloss:0.80217
[187]	train-mlogloss:0.80094	validation-mlogloss:0.80140
[188]	train-mlogloss:0.79995	validation-mlogloss:0.80044
[189]	train-mlogloss:0.79887	validation-mlogloss:0.79944
[190]	train-mlogloss:0.79797	validation-mlogloss:0.79854
[191]	train-mlogloss:0.79721	validation-mlogloss:0.79793
[192]	train-mlogloss:0.79619	validation-mlogloss:0.79702
[193]	train-mlogloss:0.79519	validation-mlogloss:0.79609
[194]	train-mlogloss:0.79427	validation-mlogloss:0.79520
[195]	train-mlogloss:0.79334	validation-mlogloss:0.79428
[196]	train-mlogloss:0.79254	validation-mlogloss:0.79357
[197]	train-mlogloss:0.79167	validation-mlogloss:0.79273
[198]	train-mlogloss:0.79082	validation-mlogloss:0.79196
[199]	train-mlogloss:0.78990	validation-mlogloss:0.79114
[200]	train-mlogloss:0.78907	validation-mlogloss:0.79033
[201]	train-mlogloss:0.78822	validation-mlogloss:0.78964
[202]	train-mlogloss:0.78732	validation-mlogloss:0.78885
[203]	train-mlogloss:0.78652	validation-mlogloss:0.78820
[204]	train-mlogloss:0.78561	validation-mlogloss:0.78728
[205]	train-mlogloss:0.78475	validation-mlogloss:0.78642
[206]	train-mlogloss:0.78382	validation-mlogloss:0.78564
[207]	train-mlogloss:0.78303	validation-mlogloss:0.78501
[208]	train-mlogloss:0.78216	validation-mlogloss:0.78432
[209]	train-mlogloss:0.78136	validation-mlogloss:0.78367
[210]	train-mlogloss:0.78044	validation-mlogloss:0.78279
[211]	train-mlogloss:0.77957	validation-mlogloss:0.78198
[212]	train-mlogloss:0.77880	validation-mlogloss:0.78139
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[226]	train-mlogloss:0.76841	validation-mlogloss:0.77222
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[245]	train-mlogloss:0.75523	validation-mlogloss:0.76116
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[260]	train-mlogloss:0.74585	validation-mlogloss:0.75300
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[262]	train-mlogloss:0.74469	validation-mlogloss:0.75207
[263]	train-mlogloss:0.74402	validation-mlogloss:0.75149
[264]	train-mlogloss:0.74339	validation-mlogloss:0.75093
[265]	train-mlogloss:0.74278	validation-mlogloss:0.75035
[266]	train-mlogloss:0.74223	validation-mlogloss:0.74986
[267]	train-mlogloss:0.74173	validation-mlogloss:0.74948
[268]	train-mlogloss:0.74115	validation-mlogloss:0.74901
[269]	train-mlogloss:0.74064	validation-mlogloss:0.74862
[270]	train-mlogloss:0.74017	validation-mlogloss:0.74815
[271]	train-mlogloss:0.73966	validation-mlogloss:0.74772
[272]	train-mlogloss:0.73911	validation-mlogloss:0.74728
[273]	train-mlogloss:0.73864	validation-mlogloss:0.74689
[274]	train-mlogloss:0.73812	validation-mlogloss:0.74658
[275]	train-mlogloss:0.73754	validation-mlogloss:0.74612
[276]	train-mlogloss:0.73696	validation-mlogloss:0.74562
[277]	train-mlogloss:0.73634	validation-mlogloss:0.74518
[278]	train-mlogloss:0.73579	validation-mlogloss:0.74476
[279]	train-mlogloss:0.73530	validation-mlogloss:0.74435
[280]	train-mlogloss:0.73484	validation-mlogloss:0.74399
[281]	train-mlogloss:0.73432	validation-mlogloss:0.74355
[282]	train-mlogloss:0.73380	validation-mlogloss:0.74313
[283]	train-mlogloss:0.73336	validation-mlogloss:0.74275
[284]	train-mlogloss:0.73273	validation-mlogloss:0.74221
[285]	train-mlogloss:0.73219	validation-mlogloss:0.74172
[286]	train-mlogloss:0.73170	validation-mlogloss:0.74128
[287]	train-mlogloss:0.73118	validation-mlogloss:0.74087
[288]	train-mlogloss:0.73068	validation-mlogloss:0.74048
[289]	train-mlogloss:0.73018	validation-mlogloss:0.74008
[290]	train-mlogloss:0.72966	validation-mlogloss:0.73970
[291]	train-mlogloss:0.72919	validation-mlogloss:0.73929
[292]	train-mlogloss:0.72856	validation-mlogloss:0.73887
[293]	train-mlogloss:0.72807	validation-mlogloss:0.73855
[294]	train-mlogloss:0.72761	validation-mlogloss:0.73821
[295]	train-mlogloss:0.72712	validation-mlogloss:0.73785
[296]	train-mlogloss:0.72669	validation-mlogloss:0.73745
[297]	train-mlogloss:0.72619	validation-mlogloss:0.73707
[298]	train-mlogloss:0.72565	validation-mlogloss:0.73670
[299]	train-mlogloss:0.72526	validation-mlogloss:0.73633
[300]	train-mlogloss:0.72481	validation-mlogloss:0.73596
[301]	train-mlogloss:0.72425	validation-mlogloss:0.73546
[302]	train-mlogloss:0.72380	validation-mlogloss:0.73512
[303]	train-mlogloss:0.72329	validation-mlogloss:0.73476
[304]	train-mlogloss:0.72280	validation-mlogloss:0.73433
[305]	train-mlogloss:0.72233	validation-mlogloss:0.73398
[306]	train-mlogloss:0.72185	validation-mlogloss:0.73361
[307]	train-mlogloss:0.72135	validation-mlogloss:0.73320
[308]	train-mlogloss:0.72088	validation-mlogloss:0.73282
[309]	train-mlogloss:0.72054	validation-mlogloss:0.73253
[310]	train-mlogloss:0.72005	validation-mlogloss:0.73213
[311]	train-mlogloss:0.71955	validation-mlogloss:0.73170
[312]	train-mlogloss:0.71908	validation-mlogloss:0.73133
[313]	train-mlogloss:0.71858	validation-mlogloss:0.73092
[314]	train-mlogloss:0.71822	validation-mlogloss:0.73074
[315]	train-mlogloss:0.71773	validation-mlogloss:0.73042
[316]	train-mlogloss:0.71733	validation-mlogloss:0.73008
[317]	train-mlogloss:0.71689	validation-mlogloss:0.72982
[318]	train-mlogloss:0.71654	validation-mlogloss:0.72955
[319]	train-mlogloss:0.71612	validation-mlogloss:0.72932
[320]	train-mlogloss:0.71576	validation-mlogloss:0.72898
[321]	train-mlogloss:0.71540	validation-mlogloss:0.72871
[322]	train-mlogloss:0.71505	validation-mlogloss:0.72842
[323]	train-mlogloss:0.71472	validation-mlogloss:0.72817
[324]	train-mlogloss:0.71433	validation-mlogloss:0.72781
[325]	train-mlogloss:0.71398	validation-mlogloss:0.72748
[326]	train-mlogloss:0.71355	validation-mlogloss:0.72717
[327]	train-mlogloss:0.71314	validation-mlogloss:0.72678
[328]	train-mlogloss:0.71281	validation-mlogloss:0.72641
[329]	train-mlogloss:0.71246	validation-mlogloss:0.72612
[330]	train-mlogloss:0.71216	validation-mlogloss:0.72584
[331]	train-mlogloss:0.71174	validation-mlogloss:0.72553
[332]	train-mlogloss:0.71148	validation-mlogloss:0.72532
[333]	train-mlogloss:0.71108	validation-mlogloss:0.72501
[334]	train-mlogloss:0.71065	validation-mlogloss:0.72471
[335]	train-mlogloss:0.71022	validation-mlogloss:0.72437
[336]	train-mlogloss:0.70989	validation-mlogloss:0.72406
[337]	train-mlogloss:0.70959	validation-mlogloss:0.72379
[338]	train-mlogloss:0.70925	validation-mlogloss:0.72352
[339]	train-mlogloss:0.70880	validation-mlogloss:0.72329
[340]	train-mlogloss:0.70844	validation-mlogloss:0.72303
[341]	train-mlogloss:0.70812	validation-mlogloss:0.72276
[342]	train-mlogloss:0.70769	validation-mlogloss:0.72244
[343]	train-mlogloss:0.70742	validation-mlogloss:0.72228
[344]	train-mlogloss:0.70716	validation-mlogloss:0.72205
[345]	train-mlogloss:0.70678	validation-mlogloss:0.72175
[346]	train-mlogloss:0.70640	validation-mlogloss:0.72150
[347]	train-mlogloss:0.70605	validation-mlogloss:0.72127
[348]	train-mlogloss:0.70569	validation-mlogloss:0.72099
[349]	train-mlogloss:0.70535	validation-mlogloss:0.72071
[350]	train-mlogloss:0.70504	validation-mlogloss:0.72050
[351]	train-mlogloss:0.70479	validation-mlogloss:0.72030
[352]	train-mlogloss:0.70458	validation-mlogloss:0.72011
[353]	train-mlogloss:0.70437	validation-mlogloss:0.71996
[354]	train-mlogloss:0.70409	validation-mlogloss:0.71977
[355]	train-mlogloss:0.70368	validation-mlogloss:0.71947
[356]	train-mlogloss:0.70340	validation-mlogloss:0.71924
[357]	train-mlogloss:0.70317	validation-mlogloss:0.71903
[358]	train-mlogloss:0.70281	validation-mlogloss:0.71877
[359]	train-mlogloss:0.70251	validation-mlogloss:0.71859
[360]	train-mlogloss:0.70217	validation-mlogloss:0.71841
[361]	train-mlogloss:0.70179	validation-mlogloss:0.71812
[362]	train-mlogloss:0.70151	validation-mlogloss:0.71788
[363]	train-mlogloss:0.70116	validation-mlogloss:0.71754
[364]	train-mlogloss:0.70082	validation-mlogloss:0.71730
[365]	train-mlogloss:0.70053	validation-mlogloss:0.71711
[366]	train-mlogloss:0.70027	validation-mlogloss:0.71690
[367]	train-mlogloss:0.70000	validation-mlogloss:0.71673
[368]	train-mlogloss:0.69974	validation-mlogloss:0.71644
[369]	train-mlogloss:0.69947	validation-mlogloss:0.71620
[370]	train-mlogloss:0.69917	validation-mlogloss:0.71597
[371]	train-mlogloss:0.69883	validation-mlogloss:0.71572
[372]	train-mlogloss:0.69852	validation-mlogloss:0.71555
[373]	train-mlogloss:0.69822	validation-mlogloss:0.71528
[374]	train-mlogloss:0.69800	validation-mlogloss:0.71511
[375]	train-mlogloss:0.69776	validation-mlogloss:0.71487
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.75 [%]
Global accuracy score (test) = 72.88 [%]
Global F1 score (train) = 73.65 [%]
Global F1 score (test) = 72.95 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.64      0.46      0.54       400
MODERATE-INTENSITY       0.59      0.85      0.70       400
         SEDENTARY       0.84      0.85      0.85       400
VIGOROUS-INTENSITY       0.94      0.75      0.84       345

          accuracy                           0.73      1545
         macro avg       0.75      0.73      0.73      1545
      weighted avg       0.75      0.73      0.73      1545


Accuracy capturado en la ejecución 6: 72.88 [%]
F1-score capturado en la ejecución 6: 72.95 [%]

=== EJECUCIÓN 7 ===

--- TRAIN (ejecución 7) ---

--- TEST (ejecución 7) ---
2025-11-04 10:35:01.327105: 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 10:35:01.338548: 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 00:00:1762248901.351636 1053646 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248901.355808 1053646 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248901.365585 1053646 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248901.365600 1053646 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248901.365602 1053646 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248901.365603 1053646 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:35:01.368706: 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:1.37642	validation-mlogloss:1.37614
[1]	train-mlogloss:1.36686	validation-mlogloss:1.36615
[2]	train-mlogloss:1.35761	validation-mlogloss:1.35684
[3]	train-mlogloss:1.34879	validation-mlogloss:1.34797
[4]	train-mlogloss:1.33978	validation-mlogloss:1.33867
[5]	train-mlogloss:1.33090	validation-mlogloss:1.32931
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[304]	train-mlogloss:0.73169	validation-mlogloss:0.73283
[305]	train-mlogloss:0.73120	validation-mlogloss:0.73243
[306]	train-mlogloss:0.73064	validation-mlogloss:0.73195
[307]	train-mlogloss:0.73026	validation-mlogloss:0.73160
[308]	train-mlogloss:0.72981	validation-mlogloss:0.73124
[309]	train-mlogloss:0.72937	validation-mlogloss:0.73086
[310]	train-mlogloss:0.72892	validation-mlogloss:0.73049
[311]	train-mlogloss:0.72843	validation-mlogloss:0.73005
[312]	train-mlogloss:0.72790	validation-mlogloss:0.72969
[313]	train-mlogloss:0.72748	validation-mlogloss:0.72921
[314]	train-mlogloss:0.72704	validation-mlogloss:0.72891
[315]	train-mlogloss:0.72667	validation-mlogloss:0.72865
[316]	train-mlogloss:0.72624	validation-mlogloss:0.72839
[317]	train-mlogloss:0.72580	validation-mlogloss:0.72801
[318]	train-mlogloss:0.72540	validation-mlogloss:0.72756
[319]	train-mlogloss:0.72496	validation-mlogloss:0.72720
[320]	train-mlogloss:0.72459	validation-mlogloss:0.72699
[321]	train-mlogloss:0.72418	validation-mlogloss:0.72661
[322]	train-mlogloss:0.72385	validation-mlogloss:0.72635
[323]	train-mlogloss:0.72344	validation-mlogloss:0.72602
[324]	train-mlogloss:0.72304	validation-mlogloss:0.72561
[325]	train-mlogloss:0.72256	validation-mlogloss:0.72536
[326]	train-mlogloss:0.72208	validation-mlogloss:0.72495
[327]	train-mlogloss:0.72175	validation-mlogloss:0.72474
[328]	train-mlogloss:0.72131	validation-mlogloss:0.72440
[329]	train-mlogloss:0.72094	validation-mlogloss:0.72415
[330]	train-mlogloss:0.72062	validation-mlogloss:0.72389
[331]	train-mlogloss:0.72020	validation-mlogloss:0.72358
[332]	train-mlogloss:0.71988	validation-mlogloss:0.72336
[333]	train-mlogloss:0.71945	validation-mlogloss:0.72298
[334]	train-mlogloss:0.71907	validation-mlogloss:0.72261
[335]	train-mlogloss:0.71872	validation-mlogloss:0.72228
[336]	train-mlogloss:0.71838	validation-mlogloss:0.72202
[337]	train-mlogloss:0.71808	validation-mlogloss:0.72173
[338]	train-mlogloss:0.71771	validation-mlogloss:0.72135
[339]	train-mlogloss:0.71739	validation-mlogloss:0.72110
[340]	train-mlogloss:0.71709	validation-mlogloss:0.72090
[341]	train-mlogloss:0.71675	validation-mlogloss:0.72060
[342]	train-mlogloss:0.71637	validation-mlogloss:0.72029
[343]	train-mlogloss:0.71601	validation-mlogloss:0.72008
[344]	train-mlogloss:0.71566	validation-mlogloss:0.71978
[345]	train-mlogloss:0.71536	validation-mlogloss:0.71955
[346]	train-mlogloss:0.71507	validation-mlogloss:0.71929
[347]	train-mlogloss:0.71469	validation-mlogloss:0.71901
[348]	train-mlogloss:0.71437	validation-mlogloss:0.71874
[349]	train-mlogloss:0.71409	validation-mlogloss:0.71851
[350]	train-mlogloss:0.71371	validation-mlogloss:0.71827
[351]	train-mlogloss:0.71335	validation-mlogloss:0.71797
[352]	train-mlogloss:0.71303	validation-mlogloss:0.71768
[353]	train-mlogloss:0.71266	validation-mlogloss:0.71733
[354]	train-mlogloss:0.71226	validation-mlogloss:0.71711
[355]	train-mlogloss:0.71185	validation-mlogloss:0.71675
[356]	train-mlogloss:0.71149	validation-mlogloss:0.71644
[357]	train-mlogloss:0.71121	validation-mlogloss:0.71620
[358]	train-mlogloss:0.71078	validation-mlogloss:0.71584
[359]	train-mlogloss:0.71056	validation-mlogloss:0.71564
[360]	train-mlogloss:0.71020	validation-mlogloss:0.71542
[361]	train-mlogloss:0.70988	validation-mlogloss:0.71519
[362]	train-mlogloss:0.70965	validation-mlogloss:0.71503
[363]	train-mlogloss:0.70944	validation-mlogloss:0.71483
[364]	train-mlogloss:0.70906	validation-mlogloss:0.71451
[365]	train-mlogloss:0.70873	validation-mlogloss:0.71422
[366]	train-mlogloss:0.70834	validation-mlogloss:0.71398
[367]	train-mlogloss:0.70806	validation-mlogloss:0.71373
[368]	train-mlogloss:0.70778	validation-mlogloss:0.71350
[369]	train-mlogloss:0.70742	validation-mlogloss:0.71334
[370]	train-mlogloss:0.70719	validation-mlogloss:0.71318
[371]	train-mlogloss:0.70689	validation-mlogloss:0.71301
[372]	train-mlogloss:0.70661	validation-mlogloss:0.71287
[373]	train-mlogloss:0.70630	validation-mlogloss:0.71259
[374]	train-mlogloss:0.70606	validation-mlogloss:0.71239
[375]	train-mlogloss:0.70579	validation-mlogloss:0.71217
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[0 1 1 ... 2 2 0]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.55 [%]
Global accuracy score (test) = 71.2 [%]
Global F1 score (train) = 73.57 [%]
Global F1 score (test) = 71.75 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.58      0.49      0.53       400
MODERATE-INTENSITY       0.58      0.79      0.67       400
         SEDENTARY       0.85      0.83      0.84       400
VIGOROUS-INTENSITY       0.95      0.74      0.83       345

          accuracy                           0.71      1545
         macro avg       0.74      0.71      0.72      1545
      weighted avg       0.73      0.71      0.71      1545


Accuracy capturado en la ejecución 7: 71.2 [%]
F1-score capturado en la ejecución 7: 71.75 [%]

=== EJECUCIÓN 8 ===

--- TRAIN (ejecución 8) ---

--- TEST (ejecución 8) ---
2025-11-04 10:35:17.444535: 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 10:35:17.455998: 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 00:00:1762248917.469285 1053957 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248917.473456 1053957 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248917.483259 1053957 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248917.483275 1053957 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248917.483277 1053957 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248917.483278 1053957 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:35:17.486406: 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:1.37643	validation-mlogloss:1.37644
[1]	train-mlogloss:1.36722	validation-mlogloss:1.36697
[2]	train-mlogloss:1.35766	validation-mlogloss:1.35693
[3]	train-mlogloss:1.34848	validation-mlogloss:1.34742
[4]	train-mlogloss:1.33935	validation-mlogloss:1.33813
[5]	train-mlogloss:1.33104	validation-mlogloss:1.32947
[6]	train-mlogloss:1.32282	validation-mlogloss:1.32104
[7]	train-mlogloss:1.31440	validation-mlogloss:1.31210
[8]	train-mlogloss:1.30596	validation-mlogloss:1.30353
[9]	train-mlogloss:1.29816	validation-mlogloss:1.29527
[10]	train-mlogloss:1.29045	validation-mlogloss:1.28705
[11]	train-mlogloss:1.28236	validation-mlogloss:1.27870
[12]	train-mlogloss:1.27491	validation-mlogloss:1.27123
[13]	train-mlogloss:1.26756	validation-mlogloss:1.26345
[14]	train-mlogloss:1.26012	validation-mlogloss:1.25597
[15]	train-mlogloss:1.25329	validation-mlogloss:1.24912
[16]	train-mlogloss:1.24619	validation-mlogloss:1.24189
[17]	train-mlogloss:1.23943	validation-mlogloss:1.23496
[18]	train-mlogloss:1.23250	validation-mlogloss:1.22788
[19]	train-mlogloss:1.22571	validation-mlogloss:1.22073
[20]	train-mlogloss:1.21899	validation-mlogloss:1.21398
[21]	train-mlogloss:1.21296	validation-mlogloss:1.20808
[22]	train-mlogloss:1.20683	validation-mlogloss:1.20180
[23]	train-mlogloss:1.20101	validation-mlogloss:1.19579
[24]	train-mlogloss:1.19474	validation-mlogloss:1.18941
[25]	train-mlogloss:1.18857	validation-mlogloss:1.18298
[26]	train-mlogloss:1.18305	validation-mlogloss:1.17739
[27]	train-mlogloss:1.17732	validation-mlogloss:1.17129
[28]	train-mlogloss:1.17172	validation-mlogloss:1.16533
[29]	train-mlogloss:1.16650	validation-mlogloss:1.16019
[30]	train-mlogloss:1.16099	validation-mlogloss:1.15456
[31]	train-mlogloss:1.15578	validation-mlogloss:1.14938
[32]	train-mlogloss:1.15017	validation-mlogloss:1.14373
[33]	train-mlogloss:1.14501	validation-mlogloss:1.13841
[34]	train-mlogloss:1.13995	validation-mlogloss:1.13324
[35]	train-mlogloss:1.13513	validation-mlogloss:1.12844
[36]	train-mlogloss:1.13033	validation-mlogloss:1.12363
[37]	train-mlogloss:1.12543	validation-mlogloss:1.11866
[38]	train-mlogloss:1.12060	validation-mlogloss:1.11384
[39]	train-mlogloss:1.11575	validation-mlogloss:1.10868
[40]	train-mlogloss:1.11112	validation-mlogloss:1.10388
[41]	train-mlogloss:1.10634	validation-mlogloss:1.09885
[42]	train-mlogloss:1.10176	validation-mlogloss:1.09407
[43]	train-mlogloss:1.09737	validation-mlogloss:1.08969
[44]	train-mlogloss:1.09337	validation-mlogloss:1.08572
[45]	train-mlogloss:1.08912	validation-mlogloss:1.08159
[46]	train-mlogloss:1.08512	validation-mlogloss:1.07741
[47]	train-mlogloss:1.08099	validation-mlogloss:1.07336
[48]	train-mlogloss:1.07717	validation-mlogloss:1.06968
[49]	train-mlogloss:1.07306	validation-mlogloss:1.06545
[50]	train-mlogloss:1.06902	validation-mlogloss:1.06120
[51]	train-mlogloss:1.06507	validation-mlogloss:1.05719
[52]	train-mlogloss:1.06134	validation-mlogloss:1.05333
[53]	train-mlogloss:1.05758	validation-mlogloss:1.04938
[54]	train-mlogloss:1.05399	validation-mlogloss:1.04561
[55]	train-mlogloss:1.05055	validation-mlogloss:1.04221
[56]	train-mlogloss:1.04690	validation-mlogloss:1.03836
[57]	train-mlogloss:1.04322	validation-mlogloss:1.03454
[58]	train-mlogloss:1.03971	validation-mlogloss:1.03076
[59]	train-mlogloss:1.03630	validation-mlogloss:1.02717
[60]	train-mlogloss:1.03283	validation-mlogloss:1.02363
[61]	train-mlogloss:1.02946	validation-mlogloss:1.02034
[62]	train-mlogloss:1.02617	validation-mlogloss:1.01711
[63]	train-mlogloss:1.02284	validation-mlogloss:1.01366
[64]	train-mlogloss:1.01962	validation-mlogloss:1.01020
[65]	train-mlogloss:1.01625	validation-mlogloss:1.00670
[66]	train-mlogloss:1.01320	validation-mlogloss:1.00353
[67]	train-mlogloss:1.01006	validation-mlogloss:1.00046
[68]	train-mlogloss:1.00704	validation-mlogloss:0.99725
[69]	train-mlogloss:1.00420	validation-mlogloss:0.99427
[70]	train-mlogloss:1.00148	validation-mlogloss:0.99153
[71]	train-mlogloss:0.99875	validation-mlogloss:0.98882
[72]	train-mlogloss:0.99590	validation-mlogloss:0.98602
[73]	train-mlogloss:0.99307	validation-mlogloss:0.98303
[74]	train-mlogloss:0.99031	validation-mlogloss:0.98021
[75]	train-mlogloss:0.98746	validation-mlogloss:0.97718
[76]	train-mlogloss:0.98459	validation-mlogloss:0.97432
[77]	train-mlogloss:0.98186	validation-mlogloss:0.97165
[78]	train-mlogloss:0.97923	validation-mlogloss:0.96878
[79]	train-mlogloss:0.97664	validation-mlogloss:0.96616
[80]	train-mlogloss:0.97425	validation-mlogloss:0.96392
[81]	train-mlogloss:0.97178	validation-mlogloss:0.96150
[82]	train-mlogloss:0.96921	validation-mlogloss:0.95892
[83]	train-mlogloss:0.96694	validation-mlogloss:0.95656
[84]	train-mlogloss:0.96453	validation-mlogloss:0.95408
[85]	train-mlogloss:0.96187	validation-mlogloss:0.95133
[86]	train-mlogloss:0.95953	validation-mlogloss:0.94894
[87]	train-mlogloss:0.95712	validation-mlogloss:0.94660
[88]	train-mlogloss:0.95492	validation-mlogloss:0.94439
[89]	train-mlogloss:0.95260	validation-mlogloss:0.94197
[90]	train-mlogloss:0.95041	validation-mlogloss:0.93979
[91]	train-mlogloss:0.94816	validation-mlogloss:0.93746
[92]	train-mlogloss:0.94602	validation-mlogloss:0.93545
[93]	train-mlogloss:0.94382	validation-mlogloss:0.93306
[94]	train-mlogloss:0.94176	validation-mlogloss:0.93089
[95]	train-mlogloss:0.93961	validation-mlogloss:0.92853
[96]	train-mlogloss:0.93727	validation-mlogloss:0.92608
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Saved model to disk.
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[0 1 0 ... 2 2 0]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.52 [%]
Global accuracy score (test) = 69.45 [%]
Global F1 score (train) = 73.34 [%]
Global F1 score (test) = 70.04 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.54      0.44      0.48       400
MODERATE-INTENSITY       0.56      0.77      0.64       400
         SEDENTARY       0.85      0.84      0.84       400
VIGOROUS-INTENSITY       0.95      0.74      0.83       345

          accuracy                           0.69      1545
         macro avg       0.72      0.70      0.70      1545
      weighted avg       0.71      0.69      0.70      1545


Accuracy capturado en la ejecución 8: 69.45 [%]
F1-score capturado en la ejecución 8: 70.04 [%]

=== EJECUCIÓN 9 ===

--- TRAIN (ejecución 9) ---

--- TEST (ejecución 9) ---
2025-11-04 10:35:33.539725: 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 10:35:33.551239: 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 00:00:1762248933.564369 1054260 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248933.568500 1054260 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248933.578272 1054260 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248933.578287 1054260 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248933.578289 1054260 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248933.578290 1054260 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:35:33.581414: 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:1.37663	validation-mlogloss:1.37619
[1]	train-mlogloss:1.36686	validation-mlogloss:1.36614
[2]	train-mlogloss:1.35773	validation-mlogloss:1.35678
[3]	train-mlogloss:1.34870	validation-mlogloss:1.34728
[4]	train-mlogloss:1.33971	validation-mlogloss:1.33812
[5]	train-mlogloss:1.33074	validation-mlogloss:1.32898
[6]	train-mlogloss:1.32209	validation-mlogloss:1.32007
[7]	train-mlogloss:1.31359	validation-mlogloss:1.31145
[8]	train-mlogloss:1.30515	validation-mlogloss:1.30251
[9]	train-mlogloss:1.29695	validation-mlogloss:1.29410
[10]	train-mlogloss:1.28899	validation-mlogloss:1.28577
[11]	train-mlogloss:1.28113	validation-mlogloss:1.27760
[12]	train-mlogloss:1.27348	validation-mlogloss:1.26977
[13]	train-mlogloss:1.26648	validation-mlogloss:1.26262
[14]	train-mlogloss:1.25942	validation-mlogloss:1.25526
[15]	train-mlogloss:1.25243	validation-mlogloss:1.24810
[16]	train-mlogloss:1.24536	validation-mlogloss:1.24087
[17]	train-mlogloss:1.23838	validation-mlogloss:1.23363
[18]	train-mlogloss:1.23169	validation-mlogloss:1.22702
[19]	train-mlogloss:1.22500	validation-mlogloss:1.21990
[20]	train-mlogloss:1.21864	validation-mlogloss:1.21370
[21]	train-mlogloss:1.21239	validation-mlogloss:1.20745
[22]	train-mlogloss:1.20590	validation-mlogloss:1.20088
[23]	train-mlogloss:1.19962	validation-mlogloss:1.19452
[24]	train-mlogloss:1.19351	validation-mlogloss:1.18845
[25]	train-mlogloss:1.18749	validation-mlogloss:1.18241
[26]	train-mlogloss:1.18177	validation-mlogloss:1.17661
[27]	train-mlogloss:1.17576	validation-mlogloss:1.17052
[28]	train-mlogloss:1.17004	validation-mlogloss:1.16466
[29]	train-mlogloss:1.16441	validation-mlogloss:1.15888
[30]	train-mlogloss:1.15897	validation-mlogloss:1.15344
[31]	train-mlogloss:1.15369	validation-mlogloss:1.14810
[32]	train-mlogloss:1.14845	validation-mlogloss:1.14278
[33]	train-mlogloss:1.14310	validation-mlogloss:1.13717
[34]	train-mlogloss:1.13791	validation-mlogloss:1.13179
[35]	train-mlogloss:1.13276	validation-mlogloss:1.12632
[36]	train-mlogloss:1.12792	validation-mlogloss:1.12138
[37]	train-mlogloss:1.12348	validation-mlogloss:1.11681
[38]	train-mlogloss:1.11886	validation-mlogloss:1.11214
[39]	train-mlogloss:1.11412	validation-mlogloss:1.10717
[40]	train-mlogloss:1.10958	validation-mlogloss:1.10258
[41]	train-mlogloss:1.10514	validation-mlogloss:1.09808
[42]	train-mlogloss:1.10058	validation-mlogloss:1.09341
[43]	train-mlogloss:1.09608	validation-mlogloss:1.08868
[44]	train-mlogloss:1.09174	validation-mlogloss:1.08431
[45]	train-mlogloss:1.08729	validation-mlogloss:1.07969
[46]	train-mlogloss:1.08326	validation-mlogloss:1.07560
[47]	train-mlogloss:1.07909	validation-mlogloss:1.07137
[48]	train-mlogloss:1.07487	validation-mlogloss:1.06715
[49]	train-mlogloss:1.07080	validation-mlogloss:1.06293
[50]	train-mlogloss:1.06686	validation-mlogloss:1.05879
[51]	train-mlogloss:1.06288	validation-mlogloss:1.05478
[52]	train-mlogloss:1.05898	validation-mlogloss:1.05082
[53]	train-mlogloss:1.05541	validation-mlogloss:1.04722
[54]	train-mlogloss:1.05166	validation-mlogloss:1.04326
[55]	train-mlogloss:1.04791	validation-mlogloss:1.03936
[56]	train-mlogloss:1.04418	validation-mlogloss:1.03536
[57]	train-mlogloss:1.04052	validation-mlogloss:1.03152
[58]	train-mlogloss:1.03695	validation-mlogloss:1.02795
[59]	train-mlogloss:1.03353	validation-mlogloss:1.02445
[60]	train-mlogloss:1.03002	validation-mlogloss:1.02079
[61]	train-mlogloss:1.02657	validation-mlogloss:1.01704
[62]	train-mlogloss:1.02303	validation-mlogloss:1.01357
[63]	train-mlogloss:1.01969	validation-mlogloss:1.01007
[64]	train-mlogloss:1.01653	validation-mlogloss:1.00681
[65]	train-mlogloss:1.01323	validation-mlogloss:1.00338
[66]	train-mlogloss:1.01007	validation-mlogloss:1.00024
[67]	train-mlogloss:1.00702	validation-mlogloss:0.99715
[68]	train-mlogloss:1.00388	validation-mlogloss:0.99386
[69]	train-mlogloss:1.00092	validation-mlogloss:0.99077
[70]	train-mlogloss:0.99789	validation-mlogloss:0.98789
[71]	train-mlogloss:0.99473	validation-mlogloss:0.98466
[72]	train-mlogloss:0.99201	validation-mlogloss:0.98202
[73]	train-mlogloss:0.98918	validation-mlogloss:0.97901
[74]	train-mlogloss:0.98618	validation-mlogloss:0.97591
[75]	train-mlogloss:0.98334	validation-mlogloss:0.97297
[76]	train-mlogloss:0.98051	validation-mlogloss:0.97028
[77]	train-mlogloss:0.97798	validation-mlogloss:0.96768
[78]	train-mlogloss:0.97506	validation-mlogloss:0.96456
[79]	train-mlogloss:0.97243	validation-mlogloss:0.96178
[80]	train-mlogloss:0.96965	validation-mlogloss:0.95899
[81]	train-mlogloss:0.96714	validation-mlogloss:0.95626
[82]	train-mlogloss:0.96473	validation-mlogloss:0.95385
[83]	train-mlogloss:0.96203	validation-mlogloss:0.95120
[84]	train-mlogloss:0.95943	validation-mlogloss:0.94848
[85]	train-mlogloss:0.95701	validation-mlogloss:0.94594
[86]	train-mlogloss:0.95459	validation-mlogloss:0.94339
[87]	train-mlogloss:0.95223	validation-mlogloss:0.94102
[88]	train-mlogloss:0.94998	validation-mlogloss:0.93870
[89]	train-mlogloss:0.94755	validation-mlogloss:0.93617
[90]	train-mlogloss:0.94525	validation-mlogloss:0.93382
[91]	train-mlogloss:0.94304	validation-mlogloss:0.93143
[92]	train-mlogloss:0.94086	validation-mlogloss:0.92922
[93]	train-mlogloss:0.93874	validation-mlogloss:0.92703
[94]	train-mlogloss:0.93658	validation-mlogloss:0.92496
[95]	train-mlogloss:0.93435	validation-mlogloss:0.92263
[96]	train-mlogloss:0.93214	validation-mlogloss:0.92040
[97]	train-mlogloss:0.93009	validation-mlogloss:0.91835
[98]	train-mlogloss:0.92804	validation-mlogloss:0.91625
[99]	train-mlogloss:0.92574	validation-mlogloss:0.91391
[100]	train-mlogloss:0.92383	validation-mlogloss:0.91199
[101]	train-mlogloss:0.92162	validation-mlogloss:0.90966
[102]	train-mlogloss:0.91979	validation-mlogloss:0.90777
[103]	train-mlogloss:0.91781	validation-mlogloss:0.90586
[104]	train-mlogloss:0.91582	validation-mlogloss:0.90386
[105]	train-mlogloss:0.91402	validation-mlogloss:0.90218
[106]	train-mlogloss:0.91205	validation-mlogloss:0.90035
[107]	train-mlogloss:0.91024	validation-mlogloss:0.89880
[108]	train-mlogloss:0.90840	validation-mlogloss:0.89689
[109]	train-mlogloss:0.90648	validation-mlogloss:0.89488
[110]	train-mlogloss:0.90471	validation-mlogloss:0.89318
[111]	train-mlogloss:0.90282	validation-mlogloss:0.89124
[112]	train-mlogloss:0.90085	validation-mlogloss:0.88933
[113]	train-mlogloss:0.89911	validation-mlogloss:0.88753
[114]	train-mlogloss:0.89727	validation-mlogloss:0.88578
[115]	train-mlogloss:0.89553	validation-mlogloss:0.88384
[116]	train-mlogloss:0.89393	validation-mlogloss:0.88214
[117]	train-mlogloss:0.89219	validation-mlogloss:0.88034
[118]	train-mlogloss:0.89056	validation-mlogloss:0.87862
[119]	train-mlogloss:0.88891	validation-mlogloss:0.87689
[120]	train-mlogloss:0.88721	validation-mlogloss:0.87519
[121]	train-mlogloss:0.88559	validation-mlogloss:0.87359
[122]	train-mlogloss:0.88388	validation-mlogloss:0.87192
[123]	train-mlogloss:0.88224	validation-mlogloss:0.87033
[124]	train-mlogloss:0.88059	validation-mlogloss:0.86867
[125]	train-mlogloss:0.87917	validation-mlogloss:0.86743
[126]	train-mlogloss:0.87766	validation-mlogloss:0.86594
[127]	train-mlogloss:0.87622	validation-mlogloss:0.86456
[128]	train-mlogloss:0.87485	validation-mlogloss:0.86317
[129]	train-mlogloss:0.87327	validation-mlogloss:0.86153
[130]	train-mlogloss:0.87189	validation-mlogloss:0.86019
[131]	train-mlogloss:0.87054	validation-mlogloss:0.85885
[132]	train-mlogloss:0.86914	validation-mlogloss:0.85756
[133]	train-mlogloss:0.86769	validation-mlogloss:0.85603
[134]	train-mlogloss:0.86620	validation-mlogloss:0.85451
[135]	train-mlogloss:0.86469	validation-mlogloss:0.85299
[136]	train-mlogloss:0.86328	validation-mlogloss:0.85155
[137]	train-mlogloss:0.86186	validation-mlogloss:0.84997
[138]	train-mlogloss:0.86052	validation-mlogloss:0.84867
[139]	train-mlogloss:0.85918	validation-mlogloss:0.84722
[140]	train-mlogloss:0.85802	validation-mlogloss:0.84605
[141]	train-mlogloss:0.85664	validation-mlogloss:0.84472
[142]	train-mlogloss:0.85515	validation-mlogloss:0.84331
[143]	train-mlogloss:0.85374	validation-mlogloss:0.84204
[144]	train-mlogloss:0.85240	validation-mlogloss:0.84066
[145]	train-mlogloss:0.85107	validation-mlogloss:0.83940
[146]	train-mlogloss:0.84975	validation-mlogloss:0.83812
[147]	train-mlogloss:0.84835	validation-mlogloss:0.83674
[148]	train-mlogloss:0.84679	validation-mlogloss:0.83536
[149]	train-mlogloss:0.84549	validation-mlogloss:0.83406
[150]	train-mlogloss:0.84433	validation-mlogloss:0.83300
[151]	train-mlogloss:0.84306	validation-mlogloss:0.83165
[152]	train-mlogloss:0.84173	validation-mlogloss:0.83021
[153]	train-mlogloss:0.84045	validation-mlogloss:0.82895
[154]	train-mlogloss:0.83927	validation-mlogloss:0.82789
[155]	train-mlogloss:0.83802	validation-mlogloss:0.82674
[156]	train-mlogloss:0.83678	validation-mlogloss:0.82547
[157]	train-mlogloss:0.83550	validation-mlogloss:0.82413
[158]	train-mlogloss:0.83424	validation-mlogloss:0.82292
[159]	train-mlogloss:0.83307	validation-mlogloss:0.82169
[160]	train-mlogloss:0.83188	validation-mlogloss:0.82051
[161]	train-mlogloss:0.83061	validation-mlogloss:0.81942
[162]	train-mlogloss:0.82955	validation-mlogloss:0.81838
[163]	train-mlogloss:0.82835	validation-mlogloss:0.81705
[164]	train-mlogloss:0.82730	validation-mlogloss:0.81612
[165]	train-mlogloss:0.82623	validation-mlogloss:0.81520
[166]	train-mlogloss:0.82500	validation-mlogloss:0.81401
[167]	train-mlogloss:0.82390	validation-mlogloss:0.81289
[168]	train-mlogloss:0.82277	validation-mlogloss:0.81188
[169]	train-mlogloss:0.82169	validation-mlogloss:0.81082
[170]	train-mlogloss:0.82056	validation-mlogloss:0.80977
[171]	train-mlogloss:0.81960	validation-mlogloss:0.80896
[172]	train-mlogloss:0.81845	validation-mlogloss:0.80783
[173]	train-mlogloss:0.81722	validation-mlogloss:0.80665
[174]	train-mlogloss:0.81624	validation-mlogloss:0.80591
[175]	train-mlogloss:0.81518	validation-mlogloss:0.80491
[176]	train-mlogloss:0.81414	validation-mlogloss:0.80383
[177]	train-mlogloss:0.81314	validation-mlogloss:0.80287
[178]	train-mlogloss:0.81211	validation-mlogloss:0.80193
[179]	train-mlogloss:0.81115	validation-mlogloss:0.80104
[180]	train-mlogloss:0.81009	validation-mlogloss:0.80005
[181]	train-mlogloss:0.80901	validation-mlogloss:0.79909
[182]	train-mlogloss:0.80794	validation-mlogloss:0.79815
[183]	train-mlogloss:0.80695	validation-mlogloss:0.79716
[184]	train-mlogloss:0.80595	validation-mlogloss:0.79610
[185]	train-mlogloss:0.80489	validation-mlogloss:0.79502
[186]	train-mlogloss:0.80402	validation-mlogloss:0.79424
[187]	train-mlogloss:0.80297	validation-mlogloss:0.79335
[188]	train-mlogloss:0.80200	validation-mlogloss:0.79233
[189]	train-mlogloss:0.80095	validation-mlogloss:0.79131
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[191]	train-mlogloss:0.79909	validation-mlogloss:0.78950
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[312]	train-mlogloss:0.72193	validation-mlogloss:0.72196
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[317]	train-mlogloss:0.72004	validation-mlogloss:0.72051
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[332]	train-mlogloss:0.71422	validation-mlogloss:0.71578
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[339]	train-mlogloss:0.71179	validation-mlogloss:0.71385
[340]	train-mlogloss:0.71135	validation-mlogloss:0.71349
[341]	train-mlogloss:0.71098	validation-mlogloss:0.71324
[342]	train-mlogloss:0.71057	validation-mlogloss:0.71296
[343]	train-mlogloss:0.71027	validation-mlogloss:0.71276
[344]	train-mlogloss:0.70996	validation-mlogloss:0.71249
[345]	train-mlogloss:0.70967	validation-mlogloss:0.71232
[346]	train-mlogloss:0.70928	validation-mlogloss:0.71208
[347]	train-mlogloss:0.70896	validation-mlogloss:0.71180
[348]	train-mlogloss:0.70861	validation-mlogloss:0.71153
[349]	train-mlogloss:0.70833	validation-mlogloss:0.71129
[350]	train-mlogloss:0.70797	validation-mlogloss:0.71101
[351]	train-mlogloss:0.70763	validation-mlogloss:0.71073
[352]	train-mlogloss:0.70731	validation-mlogloss:0.71049
[353]	train-mlogloss:0.70699	validation-mlogloss:0.71022
[354]	train-mlogloss:0.70667	validation-mlogloss:0.70989
[355]	train-mlogloss:0.70644	validation-mlogloss:0.70969
[356]	train-mlogloss:0.70610	validation-mlogloss:0.70939
[357]	train-mlogloss:0.70581	validation-mlogloss:0.70914
[358]	train-mlogloss:0.70547	validation-mlogloss:0.70887
[359]	train-mlogloss:0.70514	validation-mlogloss:0.70862
[360]	train-mlogloss:0.70480	validation-mlogloss:0.70846
[361]	train-mlogloss:0.70443	validation-mlogloss:0.70811
[362]	train-mlogloss:0.70414	validation-mlogloss:0.70786
[363]	train-mlogloss:0.70384	validation-mlogloss:0.70759
[364]	train-mlogloss:0.70366	validation-mlogloss:0.70742
[365]	train-mlogloss:0.70331	validation-mlogloss:0.70722
[366]	train-mlogloss:0.70299	validation-mlogloss:0.70693
[367]	train-mlogloss:0.70264	validation-mlogloss:0.70674
[368]	train-mlogloss:0.70228	validation-mlogloss:0.70651
[369]	train-mlogloss:0.70191	validation-mlogloss:0.70615
[370]	train-mlogloss:0.70167	validation-mlogloss:0.70593
[371]	train-mlogloss:0.70139	validation-mlogloss:0.70574
[372]	train-mlogloss:0.70114	validation-mlogloss:0.70547
[373]	train-mlogloss:0.70081	validation-mlogloss:0.70524
[374]	train-mlogloss:0.70056	validation-mlogloss:0.70506
[375]	train-mlogloss:0.70033	validation-mlogloss:0.70488
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 0 1 ... 2 0 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.65 [%]
Global accuracy score (test) = 72.1 [%]
Global F1 score (train) = 73.62 [%]
Global F1 score (test) = 72.35 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.61      0.48      0.54       400
MODERATE-INTENSITY       0.59      0.81      0.69       400
         SEDENTARY       0.84      0.85      0.85       400
VIGOROUS-INTENSITY       0.92      0.74      0.82       345

          accuracy                           0.72      1545
         macro avg       0.74      0.72      0.72      1545
      weighted avg       0.74      0.72      0.72      1545


Accuracy capturado en la ejecución 9: 72.1 [%]
F1-score capturado en la ejecución 9: 72.35 [%]

=== EJECUCIÓN 10 ===

--- TRAIN (ejecución 10) ---

--- TEST (ejecución 10) ---
2025-11-04 10:35:49.741074: 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 10:35:49.752449: 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 00:00:1762248949.765981 1054584 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248949.770114 1054584 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248949.779945 1054584 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248949.779963 1054584 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248949.779972 1054584 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248949.779973 1054584 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:35:49.783260: 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:1.37649	validation-mlogloss:1.37608
[1]	train-mlogloss:1.36692	validation-mlogloss:1.36600
[2]	train-mlogloss:1.35786	validation-mlogloss:1.35619
[3]	train-mlogloss:1.34855	validation-mlogloss:1.34666
[4]	train-mlogloss:1.33956	validation-mlogloss:1.33746
[5]	train-mlogloss:1.33092	validation-mlogloss:1.32848
[6]	train-mlogloss:1.32217	validation-mlogloss:1.31931
[7]	train-mlogloss:1.31347	validation-mlogloss:1.31043
[8]	train-mlogloss:1.30512	validation-mlogloss:1.30194
[9]	train-mlogloss:1.29719	validation-mlogloss:1.29367
[10]	train-mlogloss:1.28944	validation-mlogloss:1.28585
[11]	train-mlogloss:1.28164	validation-mlogloss:1.27786
[12]	train-mlogloss:1.27394	validation-mlogloss:1.26988
[13]	train-mlogloss:1.26637	validation-mlogloss:1.26211
[14]	train-mlogloss:1.25875	validation-mlogloss:1.25437
[15]	train-mlogloss:1.25109	validation-mlogloss:1.24680
[16]	train-mlogloss:1.24420	validation-mlogloss:1.24001
[17]	train-mlogloss:1.23725	validation-mlogloss:1.23291
[18]	train-mlogloss:1.23045	validation-mlogloss:1.22589
[19]	train-mlogloss:1.22401	validation-mlogloss:1.21945
[20]	train-mlogloss:1.21741	validation-mlogloss:1.21275
[21]	train-mlogloss:1.21126	validation-mlogloss:1.20633
[22]	train-mlogloss:1.20513	validation-mlogloss:1.20016
[23]	train-mlogloss:1.19878	validation-mlogloss:1.19371
[24]	train-mlogloss:1.19277	validation-mlogloss:1.18765
[25]	train-mlogloss:1.18684	validation-mlogloss:1.18160
[26]	train-mlogloss:1.18102	validation-mlogloss:1.17573
[27]	train-mlogloss:1.17515	validation-mlogloss:1.16973
[28]	train-mlogloss:1.16925	validation-mlogloss:1.16381
[29]	train-mlogloss:1.16348	validation-mlogloss:1.15814
[30]	train-mlogloss:1.15789	validation-mlogloss:1.15265
[31]	train-mlogloss:1.15257	validation-mlogloss:1.14739
[32]	train-mlogloss:1.14751	validation-mlogloss:1.14202
[33]	train-mlogloss:1.14253	validation-mlogloss:1.13699
[34]	train-mlogloss:1.13721	validation-mlogloss:1.13144
[35]	train-mlogloss:1.13215	validation-mlogloss:1.12629
[36]	train-mlogloss:1.12741	validation-mlogloss:1.12130
[37]	train-mlogloss:1.12248	validation-mlogloss:1.11620
[38]	train-mlogloss:1.11777	validation-mlogloss:1.11148
[39]	train-mlogloss:1.11319	validation-mlogloss:1.10719
[40]	train-mlogloss:1.10870	validation-mlogloss:1.10273
[41]	train-mlogloss:1.10399	validation-mlogloss:1.09786
[42]	train-mlogloss:1.09956	validation-mlogloss:1.09333
[43]	train-mlogloss:1.09532	validation-mlogloss:1.08922
[44]	train-mlogloss:1.09099	validation-mlogloss:1.08470
[45]	train-mlogloss:1.08656	validation-mlogloss:1.08030
[46]	train-mlogloss:1.08236	validation-mlogloss:1.07593
[47]	train-mlogloss:1.07802	validation-mlogloss:1.07128
[48]	train-mlogloss:1.07402	validation-mlogloss:1.06734
[49]	train-mlogloss:1.06989	validation-mlogloss:1.06315
[50]	train-mlogloss:1.06563	validation-mlogloss:1.05864
[51]	train-mlogloss:1.06198	validation-mlogloss:1.05500
[52]	train-mlogloss:1.05820	validation-mlogloss:1.05116
[53]	train-mlogloss:1.05460	validation-mlogloss:1.04754
[54]	train-mlogloss:1.05091	validation-mlogloss:1.04372
[55]	train-mlogloss:1.04686	validation-mlogloss:1.03949
[56]	train-mlogloss:1.04349	validation-mlogloss:1.03580
[57]	train-mlogloss:1.04007	validation-mlogloss:1.03253
[58]	train-mlogloss:1.03662	validation-mlogloss:1.02897
[59]	train-mlogloss:1.03307	validation-mlogloss:1.02545
[60]	train-mlogloss:1.02961	validation-mlogloss:1.02189
[61]	train-mlogloss:1.02630	validation-mlogloss:1.01853
[62]	train-mlogloss:1.02307	validation-mlogloss:1.01512
[63]	train-mlogloss:1.01966	validation-mlogloss:1.01166
[64]	train-mlogloss:1.01646	validation-mlogloss:1.00838
[65]	train-mlogloss:1.01317	validation-mlogloss:1.00475
[66]	train-mlogloss:1.00993	validation-mlogloss:1.00149
[67]	train-mlogloss:1.00667	validation-mlogloss:0.99829
[68]	train-mlogloss:1.00346	validation-mlogloss:0.99506
[69]	train-mlogloss:1.00050	validation-mlogloss:0.99196
[70]	train-mlogloss:0.99734	validation-mlogloss:0.98864
[71]	train-mlogloss:0.99436	validation-mlogloss:0.98543
[72]	train-mlogloss:0.99145	validation-mlogloss:0.98234
[73]	train-mlogloss:0.98830	validation-mlogloss:0.97920
[74]	train-mlogloss:0.98550	validation-mlogloss:0.97637
[75]	train-mlogloss:0.98261	validation-mlogloss:0.97368
[76]	train-mlogloss:0.97986	validation-mlogloss:0.97091
[77]	train-mlogloss:0.97704	validation-mlogloss:0.96814
[78]	train-mlogloss:0.97429	validation-mlogloss:0.96547
[79]	train-mlogloss:0.97178	validation-mlogloss:0.96306
[80]	train-mlogloss:0.96921	validation-mlogloss:0.96032
[81]	train-mlogloss:0.96666	validation-mlogloss:0.95771
[82]	train-mlogloss:0.96416	validation-mlogloss:0.95532
[83]	train-mlogloss:0.96155	validation-mlogloss:0.95273
[84]	train-mlogloss:0.95903	validation-mlogloss:0.95032
[85]	train-mlogloss:0.95661	validation-mlogloss:0.94773
[86]	train-mlogloss:0.95435	validation-mlogloss:0.94541
[87]	train-mlogloss:0.95203	validation-mlogloss:0.94306
[88]	train-mlogloss:0.94970	validation-mlogloss:0.94072
[89]	train-mlogloss:0.94751	validation-mlogloss:0.93856
[90]	train-mlogloss:0.94508	validation-mlogloss:0.93601
[91]	train-mlogloss:0.94276	validation-mlogloss:0.93368
[92]	train-mlogloss:0.94052	validation-mlogloss:0.93123
[93]	train-mlogloss:0.93827	validation-mlogloss:0.92886
[94]	train-mlogloss:0.93619	validation-mlogloss:0.92702
[95]	train-mlogloss:0.93413	validation-mlogloss:0.92498
[96]	train-mlogloss:0.93178	validation-mlogloss:0.92250
[97]	train-mlogloss:0.92964	validation-mlogloss:0.92039
[98]	train-mlogloss:0.92751	validation-mlogloss:0.91819
[99]	train-mlogloss:0.92559	validation-mlogloss:0.91633
[100]	train-mlogloss:0.92370	validation-mlogloss:0.91444
[101]	train-mlogloss:0.92172	validation-mlogloss:0.91223
[102]	train-mlogloss:0.91971	validation-mlogloss:0.91019
[103]	train-mlogloss:0.91761	validation-mlogloss:0.90794
[104]	train-mlogloss:0.91563	validation-mlogloss:0.90589
[105]	train-mlogloss:0.91359	validation-mlogloss:0.90366
[106]	train-mlogloss:0.91179	validation-mlogloss:0.90189
[107]	train-mlogloss:0.91012	validation-mlogloss:0.90032
[108]	train-mlogloss:0.90838	validation-mlogloss:0.89868
[109]	train-mlogloss:0.90660	validation-mlogloss:0.89681
[110]	train-mlogloss:0.90479	validation-mlogloss:0.89496
[111]	train-mlogloss:0.90302	validation-mlogloss:0.89314
[112]	train-mlogloss:0.90122	validation-mlogloss:0.89136
[113]	train-mlogloss:0.89935	validation-mlogloss:0.88950
[114]	train-mlogloss:0.89763	validation-mlogloss:0.88769
[115]	train-mlogloss:0.89584	validation-mlogloss:0.88577
[116]	train-mlogloss:0.89397	validation-mlogloss:0.88413
[117]	train-mlogloss:0.89214	validation-mlogloss:0.88220
[118]	train-mlogloss:0.89038	validation-mlogloss:0.88039
[119]	train-mlogloss:0.88875	validation-mlogloss:0.87886
[120]	train-mlogloss:0.88699	validation-mlogloss:0.87693
[121]	train-mlogloss:0.88537	validation-mlogloss:0.87524
[122]	train-mlogloss:0.88381	validation-mlogloss:0.87355
[123]	train-mlogloss:0.88223	validation-mlogloss:0.87187
[124]	train-mlogloss:0.88048	validation-mlogloss:0.87006
[125]	train-mlogloss:0.87894	validation-mlogloss:0.86859
[126]	train-mlogloss:0.87738	validation-mlogloss:0.86697
[127]	train-mlogloss:0.87583	validation-mlogloss:0.86548
[128]	train-mlogloss:0.87439	validation-mlogloss:0.86404
[129]	train-mlogloss:0.87301	validation-mlogloss:0.86261
[130]	train-mlogloss:0.87147	validation-mlogloss:0.86106
[131]	train-mlogloss:0.86994	validation-mlogloss:0.85947
[132]	train-mlogloss:0.86852	validation-mlogloss:0.85796
[133]	train-mlogloss:0.86708	validation-mlogloss:0.85655
[134]	train-mlogloss:0.86578	validation-mlogloss:0.85538
[135]	train-mlogloss:0.86449	validation-mlogloss:0.85416
[136]	train-mlogloss:0.86299	validation-mlogloss:0.85267
[137]	train-mlogloss:0.86167	validation-mlogloss:0.85140
[138]	train-mlogloss:0.86046	validation-mlogloss:0.85024
[139]	train-mlogloss:0.85919	validation-mlogloss:0.84887
[140]	train-mlogloss:0.85777	validation-mlogloss:0.84734
[141]	train-mlogloss:0.85635	validation-mlogloss:0.84599
[142]	train-mlogloss:0.85502	validation-mlogloss:0.84472
[143]	train-mlogloss:0.85368	validation-mlogloss:0.84346
[144]	train-mlogloss:0.85233	validation-mlogloss:0.84217
[145]	train-mlogloss:0.85095	validation-mlogloss:0.84080
[146]	train-mlogloss:0.84967	validation-mlogloss:0.83951
[147]	train-mlogloss:0.84826	validation-mlogloss:0.83815
[148]	train-mlogloss:0.84706	validation-mlogloss:0.83695
[149]	train-mlogloss:0.84587	validation-mlogloss:0.83596
[150]	train-mlogloss:0.84457	validation-mlogloss:0.83468
[151]	train-mlogloss:0.84321	validation-mlogloss:0.83332
[152]	train-mlogloss:0.84198	validation-mlogloss:0.83204
[153]	train-mlogloss:0.84069	validation-mlogloss:0.83065
[154]	train-mlogloss:0.83960	validation-mlogloss:0.82961
[155]	train-mlogloss:0.83836	validation-mlogloss:0.82858
[156]	train-mlogloss:0.83719	validation-mlogloss:0.82730
[157]	train-mlogloss:0.83603	validation-mlogloss:0.82629
[158]	train-mlogloss:0.83489	validation-mlogloss:0.82502
[159]	train-mlogloss:0.83355	validation-mlogloss:0.82375
[160]	train-mlogloss:0.83240	validation-mlogloss:0.82263
[161]	train-mlogloss:0.83144	validation-mlogloss:0.82171
[162]	train-mlogloss:0.83023	validation-mlogloss:0.82048
[163]	train-mlogloss:0.82916	validation-mlogloss:0.81944
[164]	train-mlogloss:0.82811	validation-mlogloss:0.81852
[165]	train-mlogloss:0.82699	validation-mlogloss:0.81736
[166]	train-mlogloss:0.82596	validation-mlogloss:0.81622
[167]	train-mlogloss:0.82490	validation-mlogloss:0.81521
[168]	train-mlogloss:0.82401	validation-mlogloss:0.81434
[169]	train-mlogloss:0.82305	validation-mlogloss:0.81345
[170]	train-mlogloss:0.82209	validation-mlogloss:0.81270
[171]	train-mlogloss:0.82117	validation-mlogloss:0.81193
[172]	train-mlogloss:0.82015	validation-mlogloss:0.81090
[173]	train-mlogloss:0.81910	validation-mlogloss:0.80998
[174]	train-mlogloss:0.81801	validation-mlogloss:0.80880
[175]	train-mlogloss:0.81692	validation-mlogloss:0.80772
[176]	train-mlogloss:0.81599	validation-mlogloss:0.80686
[177]	train-mlogloss:0.81490	validation-mlogloss:0.80564
[178]	train-mlogloss:0.81374	validation-mlogloss:0.80448
[179]	train-mlogloss:0.81272	validation-mlogloss:0.80348
[180]	train-mlogloss:0.81167	validation-mlogloss:0.80245
[181]	train-mlogloss:0.81068	validation-mlogloss:0.80154
[182]	train-mlogloss:0.80971	validation-mlogloss:0.80063
[183]	train-mlogloss:0.80872	validation-mlogloss:0.79986
[184]	train-mlogloss:0.80780	validation-mlogloss:0.79906
[185]	train-mlogloss:0.80684	validation-mlogloss:0.79821
[186]	train-mlogloss:0.80578	validation-mlogloss:0.79720
[187]	train-mlogloss:0.80475	validation-mlogloss:0.79618
[188]	train-mlogloss:0.80394	validation-mlogloss:0.79544
[189]	train-mlogloss:0.80292	validation-mlogloss:0.79445
[190]	train-mlogloss:0.80194	validation-mlogloss:0.79360
[191]	train-mlogloss:0.80100	validation-mlogloss:0.79260
[192]	train-mlogloss:0.80007	validation-mlogloss:0.79175
[193]	train-mlogloss:0.79921	validation-mlogloss:0.79081
[194]	train-mlogloss:0.79833	validation-mlogloss:0.78985
[195]	train-mlogloss:0.79739	validation-mlogloss:0.78894
[196]	train-mlogloss:0.79652	validation-mlogloss:0.78807
[197]	train-mlogloss:0.79563	validation-mlogloss:0.78727
[198]	train-mlogloss:0.79475	validation-mlogloss:0.78646
[199]	train-mlogloss:0.79386	validation-mlogloss:0.78557
[200]	train-mlogloss:0.79315	validation-mlogloss:0.78486
[201]	train-mlogloss:0.79227	validation-mlogloss:0.78404
[202]	train-mlogloss:0.79147	validation-mlogloss:0.78321
[203]	train-mlogloss:0.79065	validation-mlogloss:0.78233
[204]	train-mlogloss:0.78975	validation-mlogloss:0.78139
[205]	train-mlogloss:0.78888	validation-mlogloss:0.78055
[206]	train-mlogloss:0.78797	validation-mlogloss:0.77965
[207]	train-mlogloss:0.78711	validation-mlogloss:0.77884
[208]	train-mlogloss:0.78631	validation-mlogloss:0.77807
[209]	train-mlogloss:0.78558	validation-mlogloss:0.77745
[210]	train-mlogloss:0.78474	validation-mlogloss:0.77671
[211]	train-mlogloss:0.78395	validation-mlogloss:0.77595
[212]	train-mlogloss:0.78311	validation-mlogloss:0.77510
[213]	train-mlogloss:0.78232	validation-mlogloss:0.77438
[214]	train-mlogloss:0.78156	validation-mlogloss:0.77354
[215]	train-mlogloss:0.78075	validation-mlogloss:0.77281
[216]	train-mlogloss:0.77995	validation-mlogloss:0.77212
[217]	train-mlogloss:0.77915	validation-mlogloss:0.77133
[218]	train-mlogloss:0.77846	validation-mlogloss:0.77085
[219]	train-mlogloss:0.77769	validation-mlogloss:0.77023
[220]	train-mlogloss:0.77682	validation-mlogloss:0.76943
[221]	train-mlogloss:0.77598	validation-mlogloss:0.76865
[222]	train-mlogloss:0.77511	validation-mlogloss:0.76776
[223]	train-mlogloss:0.77439	validation-mlogloss:0.76704
[224]	train-mlogloss:0.77367	validation-mlogloss:0.76632
[225]	train-mlogloss:0.77296	validation-mlogloss:0.76562
[226]	train-mlogloss:0.77227	validation-mlogloss:0.76503
[227]	train-mlogloss:0.77161	validation-mlogloss:0.76435
[228]	train-mlogloss:0.77096	validation-mlogloss:0.76393
[229]	train-mlogloss:0.77031	validation-mlogloss:0.76348
[230]	train-mlogloss:0.76960	validation-mlogloss:0.76282
[231]	train-mlogloss:0.76898	validation-mlogloss:0.76232
[232]	train-mlogloss:0.76825	validation-mlogloss:0.76167
[233]	train-mlogloss:0.76757	validation-mlogloss:0.76103
[234]	train-mlogloss:0.76689	validation-mlogloss:0.76037
[235]	train-mlogloss:0.76619	validation-mlogloss:0.75978
[236]	train-mlogloss:0.76554	validation-mlogloss:0.75911
[237]	train-mlogloss:0.76482	validation-mlogloss:0.75846
[238]	train-mlogloss:0.76406	validation-mlogloss:0.75771
[239]	train-mlogloss:0.76346	validation-mlogloss:0.75711
[240]	train-mlogloss:0.76284	validation-mlogloss:0.75645
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[276]	train-mlogloss:0.74154	validation-mlogloss:0.73728
[277]	train-mlogloss:0.74093	validation-mlogloss:0.73678
[278]	train-mlogloss:0.74035	validation-mlogloss:0.73627
[279]	train-mlogloss:0.73975	validation-mlogloss:0.73592
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[281]	train-mlogloss:0.73879	validation-mlogloss:0.73502
[282]	train-mlogloss:0.73830	validation-mlogloss:0.73458
[283]	train-mlogloss:0.73790	validation-mlogloss:0.73429
[284]	train-mlogloss:0.73725	validation-mlogloss:0.73370
[285]	train-mlogloss:0.73675	validation-mlogloss:0.73323
[286]	train-mlogloss:0.73623	validation-mlogloss:0.73280
[287]	train-mlogloss:0.73575	validation-mlogloss:0.73243
[288]	train-mlogloss:0.73517	validation-mlogloss:0.73191
[289]	train-mlogloss:0.73470	validation-mlogloss:0.73157
[290]	train-mlogloss:0.73423	validation-mlogloss:0.73108
[291]	train-mlogloss:0.73375	validation-mlogloss:0.73067
[292]	train-mlogloss:0.73325	validation-mlogloss:0.73023
[293]	train-mlogloss:0.73280	validation-mlogloss:0.72979
[294]	train-mlogloss:0.73232	validation-mlogloss:0.72933
[295]	train-mlogloss:0.73186	validation-mlogloss:0.72887
[296]	train-mlogloss:0.73134	validation-mlogloss:0.72842
[297]	train-mlogloss:0.73075	validation-mlogloss:0.72789
[298]	train-mlogloss:0.73027	validation-mlogloss:0.72741
[299]	train-mlogloss:0.72980	validation-mlogloss:0.72703
[300]	train-mlogloss:0.72944	validation-mlogloss:0.72674
[301]	train-mlogloss:0.72898	validation-mlogloss:0.72637
[302]	train-mlogloss:0.72853	validation-mlogloss:0.72604
[303]	train-mlogloss:0.72803	validation-mlogloss:0.72559
[304]	train-mlogloss:0.72751	validation-mlogloss:0.72513
[305]	train-mlogloss:0.72703	validation-mlogloss:0.72474
[306]	train-mlogloss:0.72663	validation-mlogloss:0.72443
[307]	train-mlogloss:0.72625	validation-mlogloss:0.72410
[308]	train-mlogloss:0.72572	validation-mlogloss:0.72368
[309]	train-mlogloss:0.72532	validation-mlogloss:0.72339
[310]	train-mlogloss:0.72490	validation-mlogloss:0.72302
[311]	train-mlogloss:0.72452	validation-mlogloss:0.72271
[312]	train-mlogloss:0.72409	validation-mlogloss:0.72239
[313]	train-mlogloss:0.72366	validation-mlogloss:0.72208
[314]	train-mlogloss:0.72328	validation-mlogloss:0.72175
[315]	train-mlogloss:0.72282	validation-mlogloss:0.72131
[316]	train-mlogloss:0.72236	validation-mlogloss:0.72092
[317]	train-mlogloss:0.72194	validation-mlogloss:0.72050
[318]	train-mlogloss:0.72154	validation-mlogloss:0.72016
[319]	train-mlogloss:0.72119	validation-mlogloss:0.71991
[320]	train-mlogloss:0.72074	validation-mlogloss:0.71961
[321]	train-mlogloss:0.72029	validation-mlogloss:0.71917
[322]	train-mlogloss:0.71993	validation-mlogloss:0.71892
[323]	train-mlogloss:0.71952	validation-mlogloss:0.71851
[324]	train-mlogloss:0.71911	validation-mlogloss:0.71822
[325]	train-mlogloss:0.71870	validation-mlogloss:0.71786
[326]	train-mlogloss:0.71828	validation-mlogloss:0.71749
[327]	train-mlogloss:0.71787	validation-mlogloss:0.71714
[328]	train-mlogloss:0.71750	validation-mlogloss:0.71680
[329]	train-mlogloss:0.71717	validation-mlogloss:0.71658
[330]	train-mlogloss:0.71686	validation-mlogloss:0.71636
[331]	train-mlogloss:0.71642	validation-mlogloss:0.71611
[332]	train-mlogloss:0.71592	validation-mlogloss:0.71565
[333]	train-mlogloss:0.71552	validation-mlogloss:0.71533
[334]	train-mlogloss:0.71518	validation-mlogloss:0.71507
[335]	train-mlogloss:0.71477	validation-mlogloss:0.71473
[336]	train-mlogloss:0.71442	validation-mlogloss:0.71444
[337]	train-mlogloss:0.71397	validation-mlogloss:0.71406
[338]	train-mlogloss:0.71365	validation-mlogloss:0.71379
[339]	train-mlogloss:0.71336	validation-mlogloss:0.71353
[340]	train-mlogloss:0.71304	validation-mlogloss:0.71334
[341]	train-mlogloss:0.71265	validation-mlogloss:0.71308
[342]	train-mlogloss:0.71238	validation-mlogloss:0.71291
[343]	train-mlogloss:0.71197	validation-mlogloss:0.71260
[344]	train-mlogloss:0.71166	validation-mlogloss:0.71235
[345]	train-mlogloss:0.71137	validation-mlogloss:0.71201
[346]	train-mlogloss:0.71095	validation-mlogloss:0.71162
[347]	train-mlogloss:0.71068	validation-mlogloss:0.71136
[348]	train-mlogloss:0.71040	validation-mlogloss:0.71108
[349]	train-mlogloss:0.71002	validation-mlogloss:0.71091
[350]	train-mlogloss:0.70974	validation-mlogloss:0.71067
[351]	train-mlogloss:0.70947	validation-mlogloss:0.71038
[352]	train-mlogloss:0.70916	validation-mlogloss:0.71008
[353]	train-mlogloss:0.70880	validation-mlogloss:0.70990
[354]	train-mlogloss:0.70847	validation-mlogloss:0.70962
[355]	train-mlogloss:0.70802	validation-mlogloss:0.70925
[356]	train-mlogloss:0.70775	validation-mlogloss:0.70903
[357]	train-mlogloss:0.70740	validation-mlogloss:0.70865
[358]	train-mlogloss:0.70712	validation-mlogloss:0.70843
[359]	train-mlogloss:0.70675	validation-mlogloss:0.70818
[360]	train-mlogloss:0.70650	validation-mlogloss:0.70799
[361]	train-mlogloss:0.70609	validation-mlogloss:0.70777
[362]	train-mlogloss:0.70590	validation-mlogloss:0.70762
[363]	train-mlogloss:0.70551	validation-mlogloss:0.70722
[364]	train-mlogloss:0.70521	validation-mlogloss:0.70702
[365]	train-mlogloss:0.70499	validation-mlogloss:0.70684
[366]	train-mlogloss:0.70470	validation-mlogloss:0.70656
[367]	train-mlogloss:0.70439	validation-mlogloss:0.70635
[368]	train-mlogloss:0.70411	validation-mlogloss:0.70609
[369]	train-mlogloss:0.70386	validation-mlogloss:0.70584
[370]	train-mlogloss:0.70362	validation-mlogloss:0.70567
[371]	train-mlogloss:0.70334	validation-mlogloss:0.70541
[372]	train-mlogloss:0.70307	validation-mlogloss:0.70518
[373]	train-mlogloss:0.70279	validation-mlogloss:0.70487
[374]	train-mlogloss:0.70260	validation-mlogloss:0.70475
[375]	train-mlogloss:0.70225	validation-mlogloss:0.70439
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.57 [%]
Global accuracy score (test) = 72.04 [%]
Global F1 score (train) = 73.46 [%]
Global F1 score (test) = 72.36 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.60      0.48      0.53       400
MODERATE-INTENSITY       0.59      0.83      0.69       400
         SEDENTARY       0.85      0.84      0.84       400
VIGOROUS-INTENSITY       0.94      0.74      0.83       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.72      1545
      weighted avg       0.74      0.72      0.72      1545


Accuracy capturado en la ejecución 10: 72.04 [%]
F1-score capturado en la ejecución 10: 72.36 [%]

=== EJECUCIÓN 11 ===

--- TRAIN (ejecución 11) ---

--- TEST (ejecución 11) ---
2025-11-04 10:36:05.821023: 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 10:36:05.832284: 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 00:00:1762248965.845247 1054893 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248965.849325 1054893 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248965.859196 1054893 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248965.859211 1054893 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248965.859213 1054893 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248965.859214 1054893 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:36:05.862368: 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:1.37709	validation-mlogloss:1.37677
[1]	train-mlogloss:1.36763	validation-mlogloss:1.36710
[2]	train-mlogloss:1.35883	validation-mlogloss:1.35777
[3]	train-mlogloss:1.34977	validation-mlogloss:1.34878
[4]	train-mlogloss:1.34090	validation-mlogloss:1.33933
[5]	train-mlogloss:1.33206	validation-mlogloss:1.33010
[6]	train-mlogloss:1.32410	validation-mlogloss:1.32200
[7]	train-mlogloss:1.31551	validation-mlogloss:1.31330
[8]	train-mlogloss:1.30787	validation-mlogloss:1.30510
[9]	train-mlogloss:1.29977	validation-mlogloss:1.29670
[10]	train-mlogloss:1.29201	validation-mlogloss:1.28881
[11]	train-mlogloss:1.28469	validation-mlogloss:1.28123
[12]	train-mlogloss:1.27753	validation-mlogloss:1.27382
[13]	train-mlogloss:1.27029	validation-mlogloss:1.26623
[14]	train-mlogloss:1.26303	validation-mlogloss:1.25886
[15]	train-mlogloss:1.25614	validation-mlogloss:1.25165
[16]	train-mlogloss:1.24911	validation-mlogloss:1.24462
[17]	train-mlogloss:1.24202	validation-mlogloss:1.23724
[18]	train-mlogloss:1.23543	validation-mlogloss:1.23062
[19]	train-mlogloss:1.22865	validation-mlogloss:1.22361
[20]	train-mlogloss:1.22233	validation-mlogloss:1.21730
[21]	train-mlogloss:1.21622	validation-mlogloss:1.21063
[22]	train-mlogloss:1.21012	validation-mlogloss:1.20433
[23]	train-mlogloss:1.20422	validation-mlogloss:1.19835
[24]	train-mlogloss:1.19826	validation-mlogloss:1.19227
[25]	train-mlogloss:1.19240	validation-mlogloss:1.18634
[26]	train-mlogloss:1.18673	validation-mlogloss:1.18069
[27]	train-mlogloss:1.18141	validation-mlogloss:1.17516
[28]	train-mlogloss:1.17558	validation-mlogloss:1.16920
[29]	train-mlogloss:1.16987	validation-mlogloss:1.16337
[30]	train-mlogloss:1.16457	validation-mlogloss:1.15800
[31]	train-mlogloss:1.15912	validation-mlogloss:1.15231
[32]	train-mlogloss:1.15352	validation-mlogloss:1.14654
[33]	train-mlogloss:1.14823	validation-mlogloss:1.14095
[34]	train-mlogloss:1.14300	validation-mlogloss:1.13554
[35]	train-mlogloss:1.13798	validation-mlogloss:1.13015
[36]	train-mlogloss:1.13310	validation-mlogloss:1.12501
[37]	train-mlogloss:1.12842	validation-mlogloss:1.12008
[38]	train-mlogloss:1.12360	validation-mlogloss:1.11529
[39]	train-mlogloss:1.11896	validation-mlogloss:1.11054
[40]	train-mlogloss:1.11423	validation-mlogloss:1.10588
[41]	train-mlogloss:1.10967	validation-mlogloss:1.10123
[42]	train-mlogloss:1.10538	validation-mlogloss:1.09687
[43]	train-mlogloss:1.10099	validation-mlogloss:1.09236
[44]	train-mlogloss:1.09650	validation-mlogloss:1.08780
[45]	train-mlogloss:1.09246	validation-mlogloss:1.08369
[46]	train-mlogloss:1.08807	validation-mlogloss:1.07921
[47]	train-mlogloss:1.08370	validation-mlogloss:1.07481
[48]	train-mlogloss:1.07963	validation-mlogloss:1.07055
[49]	train-mlogloss:1.07557	validation-mlogloss:1.06629
[50]	train-mlogloss:1.07171	validation-mlogloss:1.06225
[51]	train-mlogloss:1.06779	validation-mlogloss:1.05812
[52]	train-mlogloss:1.06406	validation-mlogloss:1.05421
[53]	train-mlogloss:1.06042	validation-mlogloss:1.05036
[54]	train-mlogloss:1.05668	validation-mlogloss:1.04657
[55]	train-mlogloss:1.05308	validation-mlogloss:1.04287
[56]	train-mlogloss:1.04953	validation-mlogloss:1.03901
[57]	train-mlogloss:1.04594	validation-mlogloss:1.03547
[58]	train-mlogloss:1.04245	validation-mlogloss:1.03178
[59]	train-mlogloss:1.03896	validation-mlogloss:1.02829
[60]	train-mlogloss:1.03553	validation-mlogloss:1.02487
[61]	train-mlogloss:1.03207	validation-mlogloss:1.02155
[62]	train-mlogloss:1.02890	validation-mlogloss:1.01829
[63]	train-mlogloss:1.02587	validation-mlogloss:1.01527
[64]	train-mlogloss:1.02271	validation-mlogloss:1.01204
[65]	train-mlogloss:1.01966	validation-mlogloss:1.00898
[66]	train-mlogloss:1.01665	validation-mlogloss:1.00585
[67]	train-mlogloss:1.01357	validation-mlogloss:1.00279
[68]	train-mlogloss:1.01058	validation-mlogloss:0.99966
[69]	train-mlogloss:1.00744	validation-mlogloss:0.99666
[70]	train-mlogloss:1.00462	validation-mlogloss:0.99379
[71]	train-mlogloss:1.00175	validation-mlogloss:0.99097
[72]	train-mlogloss:0.99880	validation-mlogloss:0.98783
[73]	train-mlogloss:0.99597	validation-mlogloss:0.98498
[74]	train-mlogloss:0.99322	validation-mlogloss:0.98220
[75]	train-mlogloss:0.99061	validation-mlogloss:0.97948
[76]	train-mlogloss:0.98804	validation-mlogloss:0.97705
[77]	train-mlogloss:0.98542	validation-mlogloss:0.97453
[78]	train-mlogloss:0.98271	validation-mlogloss:0.97176
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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}
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Training a non-convolutional model.
Loaded model from disk.
(1545, 91)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.26 [%]
Global accuracy score (test) = 72.23 [%]
Global F1 score (train) = 73.13 [%]
Global F1 score (test) = 72.15 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.65      0.43      0.51       400
MODERATE-INTENSITY       0.57      0.86      0.69       400
         SEDENTARY       0.86      0.86      0.86       400
VIGOROUS-INTENSITY       0.94      0.73      0.82       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.72      1545
      weighted avg       0.75      0.72      0.72      1545


Accuracy capturado en la ejecución 11: 72.23 [%]
F1-score capturado en la ejecución 11: 72.15 [%]

=== EJECUCIÓN 12 ===

--- TRAIN (ejecución 12) ---

--- TEST (ejecución 12) ---
2025-11-04 10:36:21.887657: 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 10:36:21.899046: 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 00:00:1762248981.912148 1055196 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248981.916330 1055196 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248981.926145 1055196 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248981.926161 1055196 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248981.926162 1055196 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248981.926164 1055196 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:36:21.929381: 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:1.37649	validation-mlogloss:1.37622
[1]	train-mlogloss:1.36703	validation-mlogloss:1.36632
[2]	train-mlogloss:1.35782	validation-mlogloss:1.35674
[3]	train-mlogloss:1.34901	validation-mlogloss:1.34740
[4]	train-mlogloss:1.33996	validation-mlogloss:1.33786
[5]	train-mlogloss:1.33117	validation-mlogloss:1.32875
[6]	train-mlogloss:1.32265	validation-mlogloss:1.31975
[7]	train-mlogloss:1.31424	validation-mlogloss:1.31089
[8]	train-mlogloss:1.30592	validation-mlogloss:1.30230
[9]	train-mlogloss:1.29783	validation-mlogloss:1.29373
[10]	train-mlogloss:1.28993	validation-mlogloss:1.28543
[11]	train-mlogloss:1.28214	validation-mlogloss:1.27745
[12]	train-mlogloss:1.27483	validation-mlogloss:1.27034
[13]	train-mlogloss:1.26749	validation-mlogloss:1.26271
[14]	train-mlogloss:1.26066	validation-mlogloss:1.25596
[15]	train-mlogloss:1.25360	validation-mlogloss:1.24856
[16]	train-mlogloss:1.24663	validation-mlogloss:1.24167
[17]	train-mlogloss:1.23969	validation-mlogloss:1.23439
[18]	train-mlogloss:1.23315	validation-mlogloss:1.22793
[19]	train-mlogloss:1.22659	validation-mlogloss:1.22141
[20]	train-mlogloss:1.22008	validation-mlogloss:1.21471
[21]	train-mlogloss:1.21376	validation-mlogloss:1.20846
[22]	train-mlogloss:1.20758	validation-mlogloss:1.20228
[23]	train-mlogloss:1.20175	validation-mlogloss:1.19640
[24]	train-mlogloss:1.19594	validation-mlogloss:1.19057
[25]	train-mlogloss:1.18982	validation-mlogloss:1.18417
[26]	train-mlogloss:1.18387	validation-mlogloss:1.17804
[27]	train-mlogloss:1.17830	validation-mlogloss:1.17241
[28]	train-mlogloss:1.17286	validation-mlogloss:1.16690
[29]	train-mlogloss:1.16736	validation-mlogloss:1.16155
[30]	train-mlogloss:1.16192	validation-mlogloss:1.15613
[31]	train-mlogloss:1.15662	validation-mlogloss:1.15062
[32]	train-mlogloss:1.15117	validation-mlogloss:1.14497
[33]	train-mlogloss:1.14591	validation-mlogloss:1.13939
[34]	train-mlogloss:1.14092	validation-mlogloss:1.13439
[35]	train-mlogloss:1.13595	validation-mlogloss:1.12914
[36]	train-mlogloss:1.13121	validation-mlogloss:1.12440
[37]	train-mlogloss:1.12630	validation-mlogloss:1.11928
[38]	train-mlogloss:1.12139	validation-mlogloss:1.11429
[39]	train-mlogloss:1.11668	validation-mlogloss:1.10974
[40]	train-mlogloss:1.11190	validation-mlogloss:1.10479
[41]	train-mlogloss:1.10718	validation-mlogloss:1.09997
[42]	train-mlogloss:1.10287	validation-mlogloss:1.09543
[43]	train-mlogloss:1.09850	validation-mlogloss:1.09094
[44]	train-mlogloss:1.09414	validation-mlogloss:1.08649
[45]	train-mlogloss:1.09004	validation-mlogloss:1.08254
[46]	train-mlogloss:1.08586	validation-mlogloss:1.07835
[47]	train-mlogloss:1.08169	validation-mlogloss:1.07409
[48]	train-mlogloss:1.07762	validation-mlogloss:1.06992
[49]	train-mlogloss:1.07358	validation-mlogloss:1.06589
[50]	train-mlogloss:1.06971	validation-mlogloss:1.06199
[51]	train-mlogloss:1.06585	validation-mlogloss:1.05814
[52]	train-mlogloss:1.06178	validation-mlogloss:1.05400
[53]	train-mlogloss:1.05790	validation-mlogloss:1.04990
[54]	train-mlogloss:1.05424	validation-mlogloss:1.04638
[55]	train-mlogloss:1.05052	validation-mlogloss:1.04266
[56]	train-mlogloss:1.04689	validation-mlogloss:1.03894
[57]	train-mlogloss:1.04335	validation-mlogloss:1.03527
[58]	train-mlogloss:1.03978	validation-mlogloss:1.03162
[59]	train-mlogloss:1.03630	validation-mlogloss:1.02799
[60]	train-mlogloss:1.03272	validation-mlogloss:1.02446
[61]	train-mlogloss:1.02924	validation-mlogloss:1.02085
[62]	train-mlogloss:1.02599	validation-mlogloss:1.01767
[63]	train-mlogloss:1.02270	validation-mlogloss:1.01431
[64]	train-mlogloss:1.01961	validation-mlogloss:1.01113
[65]	train-mlogloss:1.01638	validation-mlogloss:1.00779
[66]	train-mlogloss:1.01325	validation-mlogloss:1.00473
[67]	train-mlogloss:1.01020	validation-mlogloss:1.00160
[68]	train-mlogloss:1.00722	validation-mlogloss:0.99865
[69]	train-mlogloss:1.00421	validation-mlogloss:0.99572
[70]	train-mlogloss:1.00115	validation-mlogloss:0.99252
[71]	train-mlogloss:0.99829	validation-mlogloss:0.98968
[72]	train-mlogloss:0.99533	validation-mlogloss:0.98676
[73]	train-mlogloss:0.99270	validation-mlogloss:0.98429
[74]	train-mlogloss:0.99017	validation-mlogloss:0.98191
[75]	train-mlogloss:0.98746	validation-mlogloss:0.97909
[76]	train-mlogloss:0.98449	validation-mlogloss:0.97619
[77]	train-mlogloss:0.98179	validation-mlogloss:0.97325
[78]	train-mlogloss:0.97934	validation-mlogloss:0.97085
[79]	train-mlogloss:0.97672	validation-mlogloss:0.96825
[80]	train-mlogloss:0.97421	validation-mlogloss:0.96565
[81]	train-mlogloss:0.97137	validation-mlogloss:0.96259
[82]	train-mlogloss:0.96884	validation-mlogloss:0.96008
[83]	train-mlogloss:0.96643	validation-mlogloss:0.95769
[84]	train-mlogloss:0.96397	validation-mlogloss:0.95535
[85]	train-mlogloss:0.96159	validation-mlogloss:0.95300
[86]	train-mlogloss:0.95925	validation-mlogloss:0.95060
[87]	train-mlogloss:0.95686	validation-mlogloss:0.94824
[88]	train-mlogloss:0.95451	validation-mlogloss:0.94588
[89]	train-mlogloss:0.95208	validation-mlogloss:0.94358
[90]	train-mlogloss:0.94982	validation-mlogloss:0.94127
[91]	train-mlogloss:0.94756	validation-mlogloss:0.93908
[92]	train-mlogloss:0.94543	validation-mlogloss:0.93704
[93]	train-mlogloss:0.94294	validation-mlogloss:0.93447
[94]	train-mlogloss:0.94076	validation-mlogloss:0.93222
[95]	train-mlogloss:0.93862	validation-mlogloss:0.93022
[96]	train-mlogloss:0.93644	validation-mlogloss:0.92814
[97]	train-mlogloss:0.93414	validation-mlogloss:0.92577
[98]	train-mlogloss:0.93183	validation-mlogloss:0.92337
[99]	train-mlogloss:0.92971	validation-mlogloss:0.92120
[100]	train-mlogloss:0.92778	validation-mlogloss:0.91930
[101]	train-mlogloss:0.92568	validation-mlogloss:0.91724
[102]	train-mlogloss:0.92354	validation-mlogloss:0.91519
[103]	train-mlogloss:0.92168	validation-mlogloss:0.91332
[104]	train-mlogloss:0.91968	validation-mlogloss:0.91132
[105]	train-mlogloss:0.91777	validation-mlogloss:0.90934
[106]	train-mlogloss:0.91586	validation-mlogloss:0.90723
[107]	train-mlogloss:0.91395	validation-mlogloss:0.90511
[108]	train-mlogloss:0.91198	validation-mlogloss:0.90308
[109]	train-mlogloss:0.90997	validation-mlogloss:0.90095
[110]	train-mlogloss:0.90817	validation-mlogloss:0.89912
[111]	train-mlogloss:0.90635	validation-mlogloss:0.89728
[112]	train-mlogloss:0.90465	validation-mlogloss:0.89579
[113]	train-mlogloss:0.90292	validation-mlogloss:0.89408
[114]	train-mlogloss:0.90131	validation-mlogloss:0.89261
[115]	train-mlogloss:0.89945	validation-mlogloss:0.89070
[116]	train-mlogloss:0.89788	validation-mlogloss:0.88919
[117]	train-mlogloss:0.89629	validation-mlogloss:0.88758
[118]	train-mlogloss:0.89466	validation-mlogloss:0.88609
[119]	train-mlogloss:0.89315	validation-mlogloss:0.88462
[120]	train-mlogloss:0.89157	validation-mlogloss:0.88309
[121]	train-mlogloss:0.88984	validation-mlogloss:0.88140
[122]	train-mlogloss:0.88826	validation-mlogloss:0.88006
[123]	train-mlogloss:0.88658	validation-mlogloss:0.87870
[124]	train-mlogloss:0.88511	validation-mlogloss:0.87705
[125]	train-mlogloss:0.88375	validation-mlogloss:0.87573
[126]	train-mlogloss:0.88224	validation-mlogloss:0.87420
[127]	train-mlogloss:0.88066	validation-mlogloss:0.87255
[128]	train-mlogloss:0.87912	validation-mlogloss:0.87098
[129]	train-mlogloss:0.87755	validation-mlogloss:0.86933
[130]	train-mlogloss:0.87612	validation-mlogloss:0.86785
[131]	train-mlogloss:0.87470	validation-mlogloss:0.86637
[132]	train-mlogloss:0.87311	validation-mlogloss:0.86467
[133]	train-mlogloss:0.87151	validation-mlogloss:0.86304
[134]	train-mlogloss:0.87003	validation-mlogloss:0.86151
[135]	train-mlogloss:0.86860	validation-mlogloss:0.85990
[136]	train-mlogloss:0.86711	validation-mlogloss:0.85849
[137]	train-mlogloss:0.86577	validation-mlogloss:0.85708
[138]	train-mlogloss:0.86439	validation-mlogloss:0.85576
[139]	train-mlogloss:0.86304	validation-mlogloss:0.85440
[140]	train-mlogloss:0.86158	validation-mlogloss:0.85289
[141]	train-mlogloss:0.86003	validation-mlogloss:0.85146
[142]	train-mlogloss:0.85874	validation-mlogloss:0.85024
[143]	train-mlogloss:0.85723	validation-mlogloss:0.84880
[144]	train-mlogloss:0.85599	validation-mlogloss:0.84754
[145]	train-mlogloss:0.85478	validation-mlogloss:0.84634
[146]	train-mlogloss:0.85335	validation-mlogloss:0.84490
[147]	train-mlogloss:0.85206	validation-mlogloss:0.84360
[148]	train-mlogloss:0.85090	validation-mlogloss:0.84235
[149]	train-mlogloss:0.84973	validation-mlogloss:0.84121
[150]	train-mlogloss:0.84859	validation-mlogloss:0.84012
[151]	train-mlogloss:0.84741	validation-mlogloss:0.83900
[152]	train-mlogloss:0.84620	validation-mlogloss:0.83777
[153]	train-mlogloss:0.84491	validation-mlogloss:0.83633
[154]	train-mlogloss:0.84372	validation-mlogloss:0.83516
[155]	train-mlogloss:0.84245	validation-mlogloss:0.83380
[156]	train-mlogloss:0.84111	validation-mlogloss:0.83247
[157]	train-mlogloss:0.84002	validation-mlogloss:0.83132
[158]	train-mlogloss:0.83886	validation-mlogloss:0.83016
[159]	train-mlogloss:0.83762	validation-mlogloss:0.82888
[160]	train-mlogloss:0.83648	validation-mlogloss:0.82782
[161]	train-mlogloss:0.83532	validation-mlogloss:0.82664
[162]	train-mlogloss:0.83411	validation-mlogloss:0.82559
[163]	train-mlogloss:0.83279	validation-mlogloss:0.82439
[164]	train-mlogloss:0.83182	validation-mlogloss:0.82344
[165]	train-mlogloss:0.83058	validation-mlogloss:0.82221
[166]	train-mlogloss:0.82953	validation-mlogloss:0.82113
[167]	train-mlogloss:0.82843	validation-mlogloss:0.82013
[168]	train-mlogloss:0.82745	validation-mlogloss:0.81920
[169]	train-mlogloss:0.82626	validation-mlogloss:0.81812
[170]	train-mlogloss:0.82518	validation-mlogloss:0.81714
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[342]	train-mlogloss:0.71726	validation-mlogloss:0.71773
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[346]	train-mlogloss:0.71585	validation-mlogloss:0.71664
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[348]	train-mlogloss:0.71521	validation-mlogloss:0.71606
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[350]	train-mlogloss:0.71457	validation-mlogloss:0.71540
[351]	train-mlogloss:0.71423	validation-mlogloss:0.71514
[352]	train-mlogloss:0.71390	validation-mlogloss:0.71493
[353]	train-mlogloss:0.71360	validation-mlogloss:0.71465
[354]	train-mlogloss:0.71338	validation-mlogloss:0.71439
[355]	train-mlogloss:0.71305	validation-mlogloss:0.71402
[356]	train-mlogloss:0.71272	validation-mlogloss:0.71377
[357]	train-mlogloss:0.71228	validation-mlogloss:0.71345
[358]	train-mlogloss:0.71211	validation-mlogloss:0.71327
[359]	train-mlogloss:0.71183	validation-mlogloss:0.71303
[360]	train-mlogloss:0.71147	validation-mlogloss:0.71276
[361]	train-mlogloss:0.71116	validation-mlogloss:0.71248
[362]	train-mlogloss:0.71075	validation-mlogloss:0.71211
[363]	train-mlogloss:0.71039	validation-mlogloss:0.71179
[364]	train-mlogloss:0.71003	validation-mlogloss:0.71157
[365]	train-mlogloss:0.70978	validation-mlogloss:0.71140
[366]	train-mlogloss:0.70946	validation-mlogloss:0.71119
[367]	train-mlogloss:0.70927	validation-mlogloss:0.71101
[368]	train-mlogloss:0.70894	validation-mlogloss:0.71075
[369]	train-mlogloss:0.70856	validation-mlogloss:0.71049
[370]	train-mlogloss:0.70839	validation-mlogloss:0.71036
[371]	train-mlogloss:0.70804	validation-mlogloss:0.71014
[372]	train-mlogloss:0.70779	validation-mlogloss:0.70991
[373]	train-mlogloss:0.70743	validation-mlogloss:0.70974
[374]	train-mlogloss:0.70711	validation-mlogloss:0.70948
[375]	train-mlogloss:0.70687	validation-mlogloss:0.70920
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[0 1 1 ... 0 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.64 [%]
Global accuracy score (test) = 71.13 [%]
Global F1 score (train) = 73.57 [%]
Global F1 score (test) = 71.3 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.59      0.44      0.50       400
MODERATE-INTENSITY       0.58      0.85      0.69       400
         SEDENTARY       0.85      0.82      0.84       400
VIGOROUS-INTENSITY       0.94      0.74      0.83       345

          accuracy                           0.71      1545
         macro avg       0.74      0.71      0.71      1545
      weighted avg       0.73      0.71      0.71      1545


Accuracy capturado en la ejecución 12: 71.13 [%]
F1-score capturado en la ejecución 12: 71.3 [%]

=== EJECUCIÓN 13 ===

--- TRAIN (ejecución 13) ---

--- TEST (ejecución 13) ---
2025-11-04 10:36:37.890984: 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 10:36:37.902360: 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 00:00:1762248997.915444 1055500 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762248997.919341 1055500 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762248997.929307 1055500 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248997.929323 1055500 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248997.929325 1055500 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762248997.929326 1055500 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:36:37.932389: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (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:1.37675	validation-mlogloss:1.37634
[1]	train-mlogloss:1.36730	validation-mlogloss:1.36633
[2]	train-mlogloss:1.35785	validation-mlogloss:1.35649
[3]	train-mlogloss:1.34909	validation-mlogloss:1.34781
[4]	train-mlogloss:1.34039	validation-mlogloss:1.33871
[5]	train-mlogloss:1.33178	validation-mlogloss:1.32991
[6]	train-mlogloss:1.32320	validation-mlogloss:1.32109
[7]	train-mlogloss:1.31483	validation-mlogloss:1.31244
[8]	train-mlogloss:1.30661	validation-mlogloss:1.30399
[9]	train-mlogloss:1.29828	validation-mlogloss:1.29543
[10]	train-mlogloss:1.29035	validation-mlogloss:1.28720
[11]	train-mlogloss:1.28264	validation-mlogloss:1.27906
[12]	train-mlogloss:1.27506	validation-mlogloss:1.27123
[13]	train-mlogloss:1.26777	validation-mlogloss:1.26404
[14]	train-mlogloss:1.26050	validation-mlogloss:1.25643
[15]	train-mlogloss:1.25319	validation-mlogloss:1.24903
[16]	train-mlogloss:1.24639	validation-mlogloss:1.24174
[17]	train-mlogloss:1.23944	validation-mlogloss:1.23458
[18]	train-mlogloss:1.23267	validation-mlogloss:1.22774
[19]	train-mlogloss:1.22639	validation-mlogloss:1.22162
[20]	train-mlogloss:1.22010	validation-mlogloss:1.21545
[21]	train-mlogloss:1.21368	validation-mlogloss:1.20889
[22]	train-mlogloss:1.20734	validation-mlogloss:1.20241
[23]	train-mlogloss:1.20098	validation-mlogloss:1.19582
[24]	train-mlogloss:1.19484	validation-mlogloss:1.18959
[25]	train-mlogloss:1.18908	validation-mlogloss:1.18367
[26]	train-mlogloss:1.18320	validation-mlogloss:1.17784
[27]	train-mlogloss:1.17743	validation-mlogloss:1.17185
[28]	train-mlogloss:1.17214	validation-mlogloss:1.16672
[29]	train-mlogloss:1.16655	validation-mlogloss:1.16123
[30]	train-mlogloss:1.16112	validation-mlogloss:1.15569
[31]	train-mlogloss:1.15584	validation-mlogloss:1.15023
[32]	train-mlogloss:1.15074	validation-mlogloss:1.14485
[33]	train-mlogloss:1.14540	validation-mlogloss:1.13948
[34]	train-mlogloss:1.14024	validation-mlogloss:1.13425
[35]	train-mlogloss:1.13512	validation-mlogloss:1.12885
[36]	train-mlogloss:1.13042	validation-mlogloss:1.12399
[37]	train-mlogloss:1.12535	validation-mlogloss:1.11894
[38]	train-mlogloss:1.12087	validation-mlogloss:1.11428
[39]	train-mlogloss:1.11597	validation-mlogloss:1.10948
[40]	train-mlogloss:1.11104	validation-mlogloss:1.10444
[41]	train-mlogloss:1.10625	validation-mlogloss:1.09971
[42]	train-mlogloss:1.10163	validation-mlogloss:1.09502
[43]	train-mlogloss:1.09709	validation-mlogloss:1.09052
[44]	train-mlogloss:1.09283	validation-mlogloss:1.08626
[45]	train-mlogloss:1.08866	validation-mlogloss:1.08217
[46]	train-mlogloss:1.08445	validation-mlogloss:1.07787
[47]	train-mlogloss:1.08024	validation-mlogloss:1.07343
[48]	train-mlogloss:1.07619	validation-mlogloss:1.06903
[49]	train-mlogloss:1.07199	validation-mlogloss:1.06493
[50]	train-mlogloss:1.06817	validation-mlogloss:1.06109
[51]	train-mlogloss:1.06443	validation-mlogloss:1.05739
[52]	train-mlogloss:1.06056	validation-mlogloss:1.05348
[53]	train-mlogloss:1.05651	validation-mlogloss:1.04948
[54]	train-mlogloss:1.05267	validation-mlogloss:1.04548
[55]	train-mlogloss:1.04901	validation-mlogloss:1.04168
[56]	train-mlogloss:1.04540	validation-mlogloss:1.03815
[57]	train-mlogloss:1.04177	validation-mlogloss:1.03439
[58]	train-mlogloss:1.03821	validation-mlogloss:1.03069
[59]	train-mlogloss:1.03470	validation-mlogloss:1.02703
[60]	train-mlogloss:1.03121	validation-mlogloss:1.02343
[61]	train-mlogloss:1.02769	validation-mlogloss:1.01985
[62]	train-mlogloss:1.02437	validation-mlogloss:1.01637
[63]	train-mlogloss:1.02117	validation-mlogloss:1.01320
[64]	train-mlogloss:1.01816	validation-mlogloss:1.01033
[65]	train-mlogloss:1.01519	validation-mlogloss:1.00743
[66]	train-mlogloss:1.01192	validation-mlogloss:1.00415
[67]	train-mlogloss:1.00878	validation-mlogloss:1.00096
[68]	train-mlogloss:1.00576	validation-mlogloss:0.99788
[69]	train-mlogloss:1.00297	validation-mlogloss:0.99528
[70]	train-mlogloss:0.99995	validation-mlogloss:0.99207
[71]	train-mlogloss:0.99725	validation-mlogloss:0.98930
[72]	train-mlogloss:0.99444	validation-mlogloss:0.98640
[73]	train-mlogloss:0.99138	validation-mlogloss:0.98314
[74]	train-mlogloss:0.98852	validation-mlogloss:0.98004
[75]	train-mlogloss:0.98570	validation-mlogloss:0.97732
[76]	train-mlogloss:0.98321	validation-mlogloss:0.97477
[77]	train-mlogloss:0.98041	validation-mlogloss:0.97191
[78]	train-mlogloss:0.97777	validation-mlogloss:0.96913
[79]	train-mlogloss:0.97510	validation-mlogloss:0.96653
[80]	train-mlogloss:0.97248	validation-mlogloss:0.96399
[81]	train-mlogloss:0.96996	validation-mlogloss:0.96131
[82]	train-mlogloss:0.96752	validation-mlogloss:0.95896
[83]	train-mlogloss:0.96511	validation-mlogloss:0.95648
[84]	train-mlogloss:0.96269	validation-mlogloss:0.95393
[85]	train-mlogloss:0.96046	validation-mlogloss:0.95166
[86]	train-mlogloss:0.95783	validation-mlogloss:0.94900
[87]	train-mlogloss:0.95551	validation-mlogloss:0.94660
[88]	train-mlogloss:0.95316	validation-mlogloss:0.94426
[89]	train-mlogloss:0.95089	validation-mlogloss:0.94192
[90]	train-mlogloss:0.94857	validation-mlogloss:0.93957
[91]	train-mlogloss:0.94630	validation-mlogloss:0.93735
[92]	train-mlogloss:0.94395	validation-mlogloss:0.93490
[93]	train-mlogloss:0.94187	validation-mlogloss:0.93276
[94]	train-mlogloss:0.93970	validation-mlogloss:0.93041
[95]	train-mlogloss:0.93737	validation-mlogloss:0.92796
[96]	train-mlogloss:0.93520	validation-mlogloss:0.92580
[97]	train-mlogloss:0.93316	validation-mlogloss:0.92356
[98]	train-mlogloss:0.93099	validation-mlogloss:0.92144
[99]	train-mlogloss:0.92876	validation-mlogloss:0.91920
[100]	train-mlogloss:0.92673	validation-mlogloss:0.91703
[101]	train-mlogloss:0.92469	validation-mlogloss:0.91504
[102]	train-mlogloss:0.92286	validation-mlogloss:0.91338
[103]	train-mlogloss:0.92090	validation-mlogloss:0.91143
[104]	train-mlogloss:0.91876	validation-mlogloss:0.90931
[105]	train-mlogloss:0.91685	validation-mlogloss:0.90743
[106]	train-mlogloss:0.91483	validation-mlogloss:0.90529
[107]	train-mlogloss:0.91300	validation-mlogloss:0.90348
[108]	train-mlogloss:0.91122	validation-mlogloss:0.90160
[109]	train-mlogloss:0.90938	validation-mlogloss:0.89960
[110]	train-mlogloss:0.90740	validation-mlogloss:0.89776
[111]	train-mlogloss:0.90569	validation-mlogloss:0.89609
[112]	train-mlogloss:0.90391	validation-mlogloss:0.89442
[113]	train-mlogloss:0.90218	validation-mlogloss:0.89260
[114]	train-mlogloss:0.90043	validation-mlogloss:0.89082
[115]	train-mlogloss:0.89864	validation-mlogloss:0.88899
[116]	train-mlogloss:0.89696	validation-mlogloss:0.88731
[117]	train-mlogloss:0.89528	validation-mlogloss:0.88552
[118]	train-mlogloss:0.89365	validation-mlogloss:0.88379
[119]	train-mlogloss:0.89184	validation-mlogloss:0.88192
[120]	train-mlogloss:0.89012	validation-mlogloss:0.88028
[121]	train-mlogloss:0.88863	validation-mlogloss:0.87892
[122]	train-mlogloss:0.88697	validation-mlogloss:0.87736
[123]	train-mlogloss:0.88548	validation-mlogloss:0.87587
[124]	train-mlogloss:0.88397	validation-mlogloss:0.87425
[125]	train-mlogloss:0.88229	validation-mlogloss:0.87257
[126]	train-mlogloss:0.88055	validation-mlogloss:0.87086
[127]	train-mlogloss:0.87897	validation-mlogloss:0.86939
[128]	train-mlogloss:0.87742	validation-mlogloss:0.86789
[129]	train-mlogloss:0.87607	validation-mlogloss:0.86663
[130]	train-mlogloss:0.87469	validation-mlogloss:0.86512
[131]	train-mlogloss:0.87323	validation-mlogloss:0.86380
[132]	train-mlogloss:0.87176	validation-mlogloss:0.86239
[133]	train-mlogloss:0.87030	validation-mlogloss:0.86094
[134]	train-mlogloss:0.86888	validation-mlogloss:0.85938
[135]	train-mlogloss:0.86747	validation-mlogloss:0.85796
[136]	train-mlogloss:0.86608	validation-mlogloss:0.85661
[137]	train-mlogloss:0.86466	validation-mlogloss:0.85511
[138]	train-mlogloss:0.86335	validation-mlogloss:0.85383
[139]	train-mlogloss:0.86207	validation-mlogloss:0.85262
[140]	train-mlogloss:0.86087	validation-mlogloss:0.85142
[141]	train-mlogloss:0.85949	validation-mlogloss:0.85006
[142]	train-mlogloss:0.85825	validation-mlogloss:0.84871
[143]	train-mlogloss:0.85697	validation-mlogloss:0.84745
[144]	train-mlogloss:0.85551	validation-mlogloss:0.84609
[145]	train-mlogloss:0.85425	validation-mlogloss:0.84488
[146]	train-mlogloss:0.85294	validation-mlogloss:0.84353
[147]	train-mlogloss:0.85173	validation-mlogloss:0.84228
[148]	train-mlogloss:0.85038	validation-mlogloss:0.84099
[149]	train-mlogloss:0.84905	validation-mlogloss:0.83964
[150]	train-mlogloss:0.84782	validation-mlogloss:0.83849
[151]	train-mlogloss:0.84644	validation-mlogloss:0.83709
[152]	train-mlogloss:0.84526	validation-mlogloss:0.83595
[153]	train-mlogloss:0.84390	validation-mlogloss:0.83451
[154]	train-mlogloss:0.84259	validation-mlogloss:0.83321
[155]	train-mlogloss:0.84119	validation-mlogloss:0.83184
[156]	train-mlogloss:0.83993	validation-mlogloss:0.83068
[157]	train-mlogloss:0.83865	validation-mlogloss:0.82942
[158]	train-mlogloss:0.83763	validation-mlogloss:0.82852
[159]	train-mlogloss:0.83645	validation-mlogloss:0.82723
[160]	train-mlogloss:0.83530	validation-mlogloss:0.82615
[161]	train-mlogloss:0.83416	validation-mlogloss:0.82511
[162]	train-mlogloss:0.83311	validation-mlogloss:0.82406
[163]	train-mlogloss:0.83208	validation-mlogloss:0.82300
[164]	train-mlogloss:0.83085	validation-mlogloss:0.82192
[165]	train-mlogloss:0.82970	validation-mlogloss:0.82076
[166]	train-mlogloss:0.82867	validation-mlogloss:0.81978
[167]	train-mlogloss:0.82739	validation-mlogloss:0.81851
[168]	train-mlogloss:0.82632	validation-mlogloss:0.81754
[169]	train-mlogloss:0.82517	validation-mlogloss:0.81648
[170]	train-mlogloss:0.82413	validation-mlogloss:0.81542
[171]	train-mlogloss:0.82308	validation-mlogloss:0.81453
[172]	train-mlogloss:0.82198	validation-mlogloss:0.81352
[173]	train-mlogloss:0.82089	validation-mlogloss:0.81244
[174]	train-mlogloss:0.81968	validation-mlogloss:0.81131
[175]	train-mlogloss:0.81865	validation-mlogloss:0.81035
[176]	train-mlogloss:0.81769	validation-mlogloss:0.80928
[177]	train-mlogloss:0.81668	validation-mlogloss:0.80830
[178]	train-mlogloss:0.81571	validation-mlogloss:0.80741
[179]	train-mlogloss:0.81469	validation-mlogloss:0.80648
[180]	train-mlogloss:0.81363	validation-mlogloss:0.80556
[181]	train-mlogloss:0.81260	validation-mlogloss:0.80463
[182]	train-mlogloss:0.81166	validation-mlogloss:0.80375
[183]	train-mlogloss:0.81061	validation-mlogloss:0.80285
[184]	train-mlogloss:0.80956	validation-mlogloss:0.80190
[185]	train-mlogloss:0.80872	validation-mlogloss:0.80111
[186]	train-mlogloss:0.80785	validation-mlogloss:0.80034
[187]	train-mlogloss:0.80681	validation-mlogloss:0.79946
[188]	train-mlogloss:0.80570	validation-mlogloss:0.79835
[189]	train-mlogloss:0.80472	validation-mlogloss:0.79745
[190]	train-mlogloss:0.80394	validation-mlogloss:0.79683
[191]	train-mlogloss:0.80303	validation-mlogloss:0.79577
[192]	train-mlogloss:0.80219	validation-mlogloss:0.79491
[193]	train-mlogloss:0.80109	validation-mlogloss:0.79393
[194]	train-mlogloss:0.80037	validation-mlogloss:0.79318
[195]	train-mlogloss:0.79940	validation-mlogloss:0.79225
[196]	train-mlogloss:0.79844	validation-mlogloss:0.79138
[197]	train-mlogloss:0.79761	validation-mlogloss:0.79064
[198]	train-mlogloss:0.79667	validation-mlogloss:0.78978
[199]	train-mlogloss:0.79591	validation-mlogloss:0.78913
[200]	train-mlogloss:0.79499	validation-mlogloss:0.78821
[201]	train-mlogloss:0.79417	validation-mlogloss:0.78740
[202]	train-mlogloss:0.79314	validation-mlogloss:0.78640
[203]	train-mlogloss:0.79230	validation-mlogloss:0.78561
[204]	train-mlogloss:0.79132	validation-mlogloss:0.78471
[205]	train-mlogloss:0.79049	validation-mlogloss:0.78396
[206]	train-mlogloss:0.78952	validation-mlogloss:0.78311
[207]	train-mlogloss:0.78885	validation-mlogloss:0.78242
[208]	train-mlogloss:0.78800	validation-mlogloss:0.78159
[209]	train-mlogloss:0.78727	validation-mlogloss:0.78085
[210]	train-mlogloss:0.78634	validation-mlogloss:0.77996
[211]	train-mlogloss:0.78561	validation-mlogloss:0.77926
[212]	train-mlogloss:0.78481	validation-mlogloss:0.77862
[213]	train-mlogloss:0.78401	validation-mlogloss:0.77788
[214]	train-mlogloss:0.78328	validation-mlogloss:0.77715
[215]	train-mlogloss:0.78246	validation-mlogloss:0.77641
[216]	train-mlogloss:0.78172	validation-mlogloss:0.77582
[217]	train-mlogloss:0.78090	validation-mlogloss:0.77502
[218]	train-mlogloss:0.78018	validation-mlogloss:0.77452
[219]	train-mlogloss:0.77938	validation-mlogloss:0.77363
[220]	train-mlogloss:0.77871	validation-mlogloss:0.77298
[221]	train-mlogloss:0.77788	validation-mlogloss:0.77224
[222]	train-mlogloss:0.77716	validation-mlogloss:0.77161
[223]	train-mlogloss:0.77641	validation-mlogloss:0.77088
[224]	train-mlogloss:0.77561	validation-mlogloss:0.77014
[225]	train-mlogloss:0.77497	validation-mlogloss:0.76956
[226]	train-mlogloss:0.77429	validation-mlogloss:0.76897
[227]	train-mlogloss:0.77352	validation-mlogloss:0.76822
[228]	train-mlogloss:0.77286	validation-mlogloss:0.76767
[229]	train-mlogloss:0.77220	validation-mlogloss:0.76715
[230]	train-mlogloss:0.77155	validation-mlogloss:0.76659
[231]	train-mlogloss:0.77080	validation-mlogloss:0.76608
[232]	train-mlogloss:0.77011	validation-mlogloss:0.76546
[233]	train-mlogloss:0.76946	validation-mlogloss:0.76488
[234]	train-mlogloss:0.76885	validation-mlogloss:0.76434
[235]	train-mlogloss:0.76811	validation-mlogloss:0.76366
[236]	train-mlogloss:0.76733	validation-mlogloss:0.76298
[237]	train-mlogloss:0.76668	validation-mlogloss:0.76237
[238]	train-mlogloss:0.76604	validation-mlogloss:0.76179
[239]	train-mlogloss:0.76540	validation-mlogloss:0.76126
[240]	train-mlogloss:0.76484	validation-mlogloss:0.76083
[241]	train-mlogloss:0.76421	validation-mlogloss:0.76027
[242]	train-mlogloss:0.76358	validation-mlogloss:0.75975
[243]	train-mlogloss:0.76277	validation-mlogloss:0.75891
[244]	train-mlogloss:0.76199	validation-mlogloss:0.75827
[245]	train-mlogloss:0.76136	validation-mlogloss:0.75768
[246]	train-mlogloss:0.76069	validation-mlogloss:0.75713
[247]	train-mlogloss:0.76000	validation-mlogloss:0.75653
[248]	train-mlogloss:0.75928	validation-mlogloss:0.75593
[249]	train-mlogloss:0.75875	validation-mlogloss:0.75538
[250]	train-mlogloss:0.75802	validation-mlogloss:0.75473
[251]	train-mlogloss:0.75741	validation-mlogloss:0.75423
[252]	train-mlogloss:0.75683	validation-mlogloss:0.75365
[253]	train-mlogloss:0.75622	validation-mlogloss:0.75311
[254]	train-mlogloss:0.75566	validation-mlogloss:0.75261
[255]	train-mlogloss:0.75508	validation-mlogloss:0.75206
[256]	train-mlogloss:0.75452	validation-mlogloss:0.75157
[257]	train-mlogloss:0.75396	validation-mlogloss:0.75105
[258]	train-mlogloss:0.75339	validation-mlogloss:0.75045
[259]	train-mlogloss:0.75281	validation-mlogloss:0.74987
[260]	train-mlogloss:0.75217	validation-mlogloss:0.74927
[261]	train-mlogloss:0.75155	validation-mlogloss:0.74877
[262]	train-mlogloss:0.75098	validation-mlogloss:0.74818
[263]	train-mlogloss:0.75042	validation-mlogloss:0.74768
[264]	train-mlogloss:0.74975	validation-mlogloss:0.74703
[265]	train-mlogloss:0.74920	validation-mlogloss:0.74651
[266]	train-mlogloss:0.74865	validation-mlogloss:0.74598
[267]	train-mlogloss:0.74810	validation-mlogloss:0.74550
[268]	train-mlogloss:0.74754	validation-mlogloss:0.74503
[269]	train-mlogloss:0.74699	validation-mlogloss:0.74458
[270]	train-mlogloss:0.74650	validation-mlogloss:0.74415
[271]	train-mlogloss:0.74601	validation-mlogloss:0.74379
[272]	train-mlogloss:0.74545	validation-mlogloss:0.74325
[273]	train-mlogloss:0.74486	validation-mlogloss:0.74269
[274]	train-mlogloss:0.74423	validation-mlogloss:0.74213
[275]	train-mlogloss:0.74369	validation-mlogloss:0.74162
[276]	train-mlogloss:0.74314	validation-mlogloss:0.74110
[277]	train-mlogloss:0.74257	validation-mlogloss:0.74059
[278]	train-mlogloss:0.74207	validation-mlogloss:0.74024
[279]	train-mlogloss:0.74164	validation-mlogloss:0.73977
[280]	train-mlogloss:0.74114	validation-mlogloss:0.73934
[281]	train-mlogloss:0.74061	validation-mlogloss:0.73885
[282]	train-mlogloss:0.74010	validation-mlogloss:0.73840
[283]	train-mlogloss:0.73961	validation-mlogloss:0.73796
[284]	train-mlogloss:0.73912	validation-mlogloss:0.73762
[285]	train-mlogloss:0.73850	validation-mlogloss:0.73698
[286]	train-mlogloss:0.73800	validation-mlogloss:0.73660
[287]	train-mlogloss:0.73761	validation-mlogloss:0.73624
[288]	train-mlogloss:0.73715	validation-mlogloss:0.73583
[289]	train-mlogloss:0.73664	validation-mlogloss:0.73536
[290]	train-mlogloss:0.73623	validation-mlogloss:0.73493
[291]	train-mlogloss:0.73581	validation-mlogloss:0.73459
[292]	train-mlogloss:0.73526	validation-mlogloss:0.73397
[293]	train-mlogloss:0.73468	validation-mlogloss:0.73344
[294]	train-mlogloss:0.73422	validation-mlogloss:0.73295
[295]	train-mlogloss:0.73368	validation-mlogloss:0.73248
[296]	train-mlogloss:0.73323	validation-mlogloss:0.73206
[297]	train-mlogloss:0.73283	validation-mlogloss:0.73180
[298]	train-mlogloss:0.73227	validation-mlogloss:0.73133
[299]	train-mlogloss:0.73171	validation-mlogloss:0.73089
[300]	train-mlogloss:0.73116	validation-mlogloss:0.73038
[301]	train-mlogloss:0.73074	validation-mlogloss:0.72994
[302]	train-mlogloss:0.73025	validation-mlogloss:0.72948
[303]	train-mlogloss:0.72965	validation-mlogloss:0.72900
[304]	train-mlogloss:0.72925	validation-mlogloss:0.72869
[305]	train-mlogloss:0.72885	validation-mlogloss:0.72838
[306]	train-mlogloss:0.72847	validation-mlogloss:0.72805
[307]	train-mlogloss:0.72810	validation-mlogloss:0.72777
[308]	train-mlogloss:0.72767	validation-mlogloss:0.72740
[309]	train-mlogloss:0.72716	validation-mlogloss:0.72689
[310]	train-mlogloss:0.72664	validation-mlogloss:0.72647
[311]	train-mlogloss:0.72624	validation-mlogloss:0.72611
[312]	train-mlogloss:0.72581	validation-mlogloss:0.72583
[313]	train-mlogloss:0.72536	validation-mlogloss:0.72549
[314]	train-mlogloss:0.72499	validation-mlogloss:0.72524
[315]	train-mlogloss:0.72464	validation-mlogloss:0.72500
[316]	train-mlogloss:0.72419	validation-mlogloss:0.72466
[317]	train-mlogloss:0.72383	validation-mlogloss:0.72431
[318]	train-mlogloss:0.72348	validation-mlogloss:0.72404
[319]	train-mlogloss:0.72308	validation-mlogloss:0.72369
[320]	train-mlogloss:0.72275	validation-mlogloss:0.72344
[321]	train-mlogloss:0.72234	validation-mlogloss:0.72310
[322]	train-mlogloss:0.72204	validation-mlogloss:0.72285
[323]	train-mlogloss:0.72169	validation-mlogloss:0.72257
[324]	train-mlogloss:0.72130	validation-mlogloss:0.72226
[325]	train-mlogloss:0.72092	validation-mlogloss:0.72192
[326]	train-mlogloss:0.72052	validation-mlogloss:0.72155
[327]	train-mlogloss:0.72004	validation-mlogloss:0.72125
[328]	train-mlogloss:0.71958	validation-mlogloss:0.72086
[329]	train-mlogloss:0.71928	validation-mlogloss:0.72068
[330]	train-mlogloss:0.71891	validation-mlogloss:0.72042
[331]	train-mlogloss:0.71854	validation-mlogloss:0.72009
[332]	train-mlogloss:0.71813	validation-mlogloss:0.71979
[333]	train-mlogloss:0.71780	validation-mlogloss:0.71941
[334]	train-mlogloss:0.71750	validation-mlogloss:0.71918
[335]	train-mlogloss:0.71723	validation-mlogloss:0.71894
[336]	train-mlogloss:0.71688	validation-mlogloss:0.71866
[337]	train-mlogloss:0.71654	validation-mlogloss:0.71839
[338]	train-mlogloss:0.71612	validation-mlogloss:0.71800
[339]	train-mlogloss:0.71578	validation-mlogloss:0.71770
[340]	train-mlogloss:0.71544	validation-mlogloss:0.71745
[341]	train-mlogloss:0.71507	validation-mlogloss:0.71716
[342]	train-mlogloss:0.71476	validation-mlogloss:0.71694
[343]	train-mlogloss:0.71439	validation-mlogloss:0.71668
[344]	train-mlogloss:0.71405	validation-mlogloss:0.71634
[345]	train-mlogloss:0.71368	validation-mlogloss:0.71600
[346]	train-mlogloss:0.71331	validation-mlogloss:0.71567
[347]	train-mlogloss:0.71294	validation-mlogloss:0.71539
[348]	train-mlogloss:0.71257	validation-mlogloss:0.71507
[349]	train-mlogloss:0.71221	validation-mlogloss:0.71486
[350]	train-mlogloss:0.71187	validation-mlogloss:0.71462
[351]	train-mlogloss:0.71159	validation-mlogloss:0.71444
[352]	train-mlogloss:0.71132	validation-mlogloss:0.71421
[353]	train-mlogloss:0.71101	validation-mlogloss:0.71396
[354]	train-mlogloss:0.71052	validation-mlogloss:0.71368
[355]	train-mlogloss:0.71016	validation-mlogloss:0.71343
[356]	train-mlogloss:0.70983	validation-mlogloss:0.71311
[357]	train-mlogloss:0.70946	validation-mlogloss:0.71284
[358]	train-mlogloss:0.70908	validation-mlogloss:0.71251
[359]	train-mlogloss:0.70879	validation-mlogloss:0.71236
[360]	train-mlogloss:0.70844	validation-mlogloss:0.71212
[361]	train-mlogloss:0.70813	validation-mlogloss:0.71191
[362]	train-mlogloss:0.70784	validation-mlogloss:0.71169
[363]	train-mlogloss:0.70758	validation-mlogloss:0.71144
[364]	train-mlogloss:0.70732	validation-mlogloss:0.71123
[365]	train-mlogloss:0.70698	validation-mlogloss:0.71095
[366]	train-mlogloss:0.70668	validation-mlogloss:0.71066
[367]	train-mlogloss:0.70636	validation-mlogloss:0.71047
[368]	train-mlogloss:0.70597	validation-mlogloss:0.71023
[369]	train-mlogloss:0.70565	validation-mlogloss:0.70997
[370]	train-mlogloss:0.70536	validation-mlogloss:0.70977
[371]	train-mlogloss:0.70498	validation-mlogloss:0.70957
[372]	train-mlogloss:0.70470	validation-mlogloss:0.70939
[373]	train-mlogloss:0.70435	validation-mlogloss:0.70915
[374]	train-mlogloss:0.70404	validation-mlogloss:0.70885
[375]	train-mlogloss:0.70371	validation-mlogloss:0.70866
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 0 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.32 [%]
Global accuracy score (test) = 72.62 [%]
Global F1 score (train) = 73.25 [%]
Global F1 score (test) = 72.95 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.61      0.49      0.54       400
MODERATE-INTENSITY       0.60      0.83      0.69       400
         SEDENTARY       0.85      0.84      0.84       400
VIGOROUS-INTENSITY       0.95      0.75      0.84       345

          accuracy                           0.73      1545
         macro avg       0.75      0.73      0.73      1545
      weighted avg       0.74      0.73      0.73      1545


Accuracy capturado en la ejecución 13: 72.62 [%]
F1-score capturado en la ejecución 13: 72.95 [%]

=== EJECUCIÓN 14 ===

--- TRAIN (ejecución 14) ---

--- TEST (ejecución 14) ---
2025-11-04 10:36:54.016522: 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 10:36:54.027733: 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 00:00:1762249014.040742 1055805 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249014.044847 1055805 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249014.054502 1055805 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249014.054517 1055805 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249014.054518 1055805 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249014.054520 1055805 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:36:54.057596: 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:1.37659	validation-mlogloss:1.37621
[1]	train-mlogloss:1.36705	validation-mlogloss:1.36631
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[3]	train-mlogloss:1.34870	validation-mlogloss:1.34770
[4]	train-mlogloss:1.34017	validation-mlogloss:1.33849
[5]	train-mlogloss:1.33135	validation-mlogloss:1.32940
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[7]	train-mlogloss:1.31400	validation-mlogloss:1.31126
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[9]	train-mlogloss:1.29792	validation-mlogloss:1.29503
[10]	train-mlogloss:1.29043	validation-mlogloss:1.28759
[11]	train-mlogloss:1.28261	validation-mlogloss:1.27957
[12]	train-mlogloss:1.27539	validation-mlogloss:1.27233
[13]	train-mlogloss:1.26814	validation-mlogloss:1.26473
[14]	train-mlogloss:1.26104	validation-mlogloss:1.25737
[15]	train-mlogloss:1.25380	validation-mlogloss:1.25018
[16]	train-mlogloss:1.24654	validation-mlogloss:1.24288
[17]	train-mlogloss:1.23960	validation-mlogloss:1.23584
[18]	train-mlogloss:1.23296	validation-mlogloss:1.22917
[19]	train-mlogloss:1.22662	validation-mlogloss:1.22289
[20]	train-mlogloss:1.22001	validation-mlogloss:1.21608
[21]	train-mlogloss:1.21328	validation-mlogloss:1.20940
[22]	train-mlogloss:1.20723	validation-mlogloss:1.20325
[23]	train-mlogloss:1.20124	validation-mlogloss:1.19709
[24]	train-mlogloss:1.19503	validation-mlogloss:1.19079
[25]	train-mlogloss:1.18909	validation-mlogloss:1.18479
[26]	train-mlogloss:1.18347	validation-mlogloss:1.17923
[27]	train-mlogloss:1.17764	validation-mlogloss:1.17333
[28]	train-mlogloss:1.17204	validation-mlogloss:1.16778
[29]	train-mlogloss:1.16623	validation-mlogloss:1.16192
[30]	train-mlogloss:1.16074	validation-mlogloss:1.15650
[31]	train-mlogloss:1.15525	validation-mlogloss:1.15099
[32]	train-mlogloss:1.15013	validation-mlogloss:1.14574
[33]	train-mlogloss:1.14490	validation-mlogloss:1.14064
[34]	train-mlogloss:1.14000	validation-mlogloss:1.13575
[35]	train-mlogloss:1.13503	validation-mlogloss:1.13067
[36]	train-mlogloss:1.13015	validation-mlogloss:1.12568
[37]	train-mlogloss:1.12519	validation-mlogloss:1.12090
[38]	train-mlogloss:1.12036	validation-mlogloss:1.11593
[39]	train-mlogloss:1.11570	validation-mlogloss:1.11121
[40]	train-mlogloss:1.11114	validation-mlogloss:1.10671
[41]	train-mlogloss:1.10649	validation-mlogloss:1.10199
[42]	train-mlogloss:1.10188	validation-mlogloss:1.09719
[43]	train-mlogloss:1.09724	validation-mlogloss:1.09259
[44]	train-mlogloss:1.09312	validation-mlogloss:1.08878
[45]	train-mlogloss:1.08884	validation-mlogloss:1.08440
[46]	train-mlogloss:1.08481	validation-mlogloss:1.08050
[47]	train-mlogloss:1.08023	validation-mlogloss:1.07602
[48]	train-mlogloss:1.07623	validation-mlogloss:1.07211
[49]	train-mlogloss:1.07244	validation-mlogloss:1.06845
[50]	train-mlogloss:1.06847	validation-mlogloss:1.06447
[51]	train-mlogloss:1.06451	validation-mlogloss:1.06063
[52]	train-mlogloss:1.06070	validation-mlogloss:1.05692
[53]	train-mlogloss:1.05680	validation-mlogloss:1.05294
[54]	train-mlogloss:1.05320	validation-mlogloss:1.04932
[55]	train-mlogloss:1.04949	validation-mlogloss:1.04562
[56]	train-mlogloss:1.04597	validation-mlogloss:1.04195
[57]	train-mlogloss:1.04232	validation-mlogloss:1.03820
[58]	train-mlogloss:1.03890	validation-mlogloss:1.03467
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[357]	train-mlogloss:0.70854	validation-mlogloss:0.71737
[358]	train-mlogloss:0.70821	validation-mlogloss:0.71724
[359]	train-mlogloss:0.70783	validation-mlogloss:0.71693
[360]	train-mlogloss:0.70755	validation-mlogloss:0.71669
[361]	train-mlogloss:0.70729	validation-mlogloss:0.71645
[362]	train-mlogloss:0.70694	validation-mlogloss:0.71616
[363]	train-mlogloss:0.70675	validation-mlogloss:0.71602
[364]	train-mlogloss:0.70650	validation-mlogloss:0.71581
[365]	train-mlogloss:0.70623	validation-mlogloss:0.71559
[366]	train-mlogloss:0.70596	validation-mlogloss:0.71539
[367]	train-mlogloss:0.70572	validation-mlogloss:0.71524
[368]	train-mlogloss:0.70548	validation-mlogloss:0.71506
[369]	train-mlogloss:0.70508	validation-mlogloss:0.71475
[370]	train-mlogloss:0.70481	validation-mlogloss:0.71459
[371]	train-mlogloss:0.70456	validation-mlogloss:0.71436
[372]	train-mlogloss:0.70434	validation-mlogloss:0.71417
[373]	train-mlogloss:0.70410	validation-mlogloss:0.71395
[374]	train-mlogloss:0.70380	validation-mlogloss:0.71379
[375]	train-mlogloss:0.70360	validation-mlogloss:0.71363
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 0 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.2 [%]
Global accuracy score (test) = 71.46 [%]
Global F1 score (train) = 73.08 [%]
Global F1 score (test) = 71.75 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.61      0.47      0.53       400
MODERATE-INTENSITY       0.57      0.82      0.67       400
         SEDENTARY       0.85      0.84      0.85       400
VIGOROUS-INTENSITY       0.93      0.73      0.82       345

          accuracy                           0.71      1545
         macro avg       0.74      0.72      0.72      1545
      weighted avg       0.73      0.71      0.71      1545


Accuracy capturado en la ejecución 14: 71.46 [%]
F1-score capturado en la ejecución 14: 71.75 [%]

=== EJECUCIÓN 15 ===

--- TRAIN (ejecución 15) ---

--- TEST (ejecución 15) ---
2025-11-04 10:37:09.948330: 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 10:37:09.960280: 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 00:00:1762249029.974238 1056108 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249029.978638 1056108 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249029.989022 1056108 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249029.989041 1056108 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249029.989043 1056108 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249029.989044 1056108 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:37:09.992354: 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:1.37649	validation-mlogloss:1.37616
[1]	train-mlogloss:1.36704	validation-mlogloss:1.36615
[2]	train-mlogloss:1.35836	validation-mlogloss:1.35723
[3]	train-mlogloss:1.34953	validation-mlogloss:1.34796
[4]	train-mlogloss:1.34072	validation-mlogloss:1.33852
[5]	train-mlogloss:1.33209	validation-mlogloss:1.32958
[6]	train-mlogloss:1.32338	validation-mlogloss:1.32053
[7]	train-mlogloss:1.31488	validation-mlogloss:1.31163
[8]	train-mlogloss:1.30698	validation-mlogloss:1.30328
[9]	train-mlogloss:1.29930	validation-mlogloss:1.29506
[10]	train-mlogloss:1.29113	validation-mlogloss:1.28653
[11]	train-mlogloss:1.28330	validation-mlogloss:1.27820
[12]	train-mlogloss:1.27600	validation-mlogloss:1.27112
[13]	train-mlogloss:1.26870	validation-mlogloss:1.26381
[14]	train-mlogloss:1.26163	validation-mlogloss:1.25631
[15]	train-mlogloss:1.25425	validation-mlogloss:1.24863
[16]	train-mlogloss:1.24717	validation-mlogloss:1.24134
[17]	train-mlogloss:1.24010	validation-mlogloss:1.23416
[18]	train-mlogloss:1.23363	validation-mlogloss:1.22733
[19]	train-mlogloss:1.22710	validation-mlogloss:1.22031
[20]	train-mlogloss:1.22089	validation-mlogloss:1.21402
[21]	train-mlogloss:1.21482	validation-mlogloss:1.20795
[22]	train-mlogloss:1.20843	validation-mlogloss:1.20145
[23]	train-mlogloss:1.20251	validation-mlogloss:1.19538
[24]	train-mlogloss:1.19656	validation-mlogloss:1.18950
[25]	train-mlogloss:1.19067	validation-mlogloss:1.18358
[26]	train-mlogloss:1.18475	validation-mlogloss:1.17740
[27]	train-mlogloss:1.17924	validation-mlogloss:1.17189
[28]	train-mlogloss:1.17392	validation-mlogloss:1.16631
[29]	train-mlogloss:1.16828	validation-mlogloss:1.16067
[30]	train-mlogloss:1.16267	validation-mlogloss:1.15492
[31]	train-mlogloss:1.15759	validation-mlogloss:1.14985
[32]	train-mlogloss:1.15249	validation-mlogloss:1.14443
[33]	train-mlogloss:1.14714	validation-mlogloss:1.13887
[34]	train-mlogloss:1.14221	validation-mlogloss:1.13356
[35]	train-mlogloss:1.13731	validation-mlogloss:1.12878
[36]	train-mlogloss:1.13271	validation-mlogloss:1.12415
[37]	train-mlogloss:1.12778	validation-mlogloss:1.11916
[38]	train-mlogloss:1.12291	validation-mlogloss:1.11390
[39]	train-mlogloss:1.11799	validation-mlogloss:1.10885
[40]	train-mlogloss:1.11328	validation-mlogloss:1.10389
[41]	train-mlogloss:1.10873	validation-mlogloss:1.09921
[42]	train-mlogloss:1.10445	validation-mlogloss:1.09491
[43]	train-mlogloss:1.10028	validation-mlogloss:1.09069
[44]	train-mlogloss:1.09585	validation-mlogloss:1.08622
[45]	train-mlogloss:1.09181	validation-mlogloss:1.08191
[46]	train-mlogloss:1.08746	validation-mlogloss:1.07759
[47]	train-mlogloss:1.08333	validation-mlogloss:1.07340
[48]	train-mlogloss:1.07917	validation-mlogloss:1.06905
[49]	train-mlogloss:1.07515	validation-mlogloss:1.06489
[50]	train-mlogloss:1.07120	validation-mlogloss:1.06065
[51]	train-mlogloss:1.06727	validation-mlogloss:1.05652
[52]	train-mlogloss:1.06338	validation-mlogloss:1.05245
[53]	train-mlogloss:1.05960	validation-mlogloss:1.04841
[54]	train-mlogloss:1.05592	validation-mlogloss:1.04457
[55]	train-mlogloss:1.05234	validation-mlogloss:1.04084
[56]	train-mlogloss:1.04885	validation-mlogloss:1.03721
[57]	train-mlogloss:1.04528	validation-mlogloss:1.03352
[58]	train-mlogloss:1.04166	validation-mlogloss:1.02984
[59]	train-mlogloss:1.03828	validation-mlogloss:1.02647
[60]	train-mlogloss:1.03500	validation-mlogloss:1.02306
[61]	train-mlogloss:1.03147	validation-mlogloss:1.01938
[62]	train-mlogloss:1.02812	validation-mlogloss:1.01577
[63]	train-mlogloss:1.02464	validation-mlogloss:1.01218
[64]	train-mlogloss:1.02147	validation-mlogloss:1.00878
[65]	train-mlogloss:1.01831	validation-mlogloss:1.00547
[66]	train-mlogloss:1.01508	validation-mlogloss:1.00220
[67]	train-mlogloss:1.01201	validation-mlogloss:0.99912
[68]	train-mlogloss:1.00911	validation-mlogloss:0.99618
[69]	train-mlogloss:1.00598	validation-mlogloss:0.99305
[70]	train-mlogloss:1.00294	validation-mlogloss:0.98997
[71]	train-mlogloss:1.00014	validation-mlogloss:0.98713
[72]	train-mlogloss:0.99712	validation-mlogloss:0.98406
[73]	train-mlogloss:0.99408	validation-mlogloss:0.98098
[74]	train-mlogloss:0.99146	validation-mlogloss:0.97826
[75]	train-mlogloss:0.98851	validation-mlogloss:0.97515
[76]	train-mlogloss:0.98578	validation-mlogloss:0.97216
[77]	train-mlogloss:0.98310	validation-mlogloss:0.96928
[78]	train-mlogloss:0.98042	validation-mlogloss:0.96658
[79]	train-mlogloss:0.97791	validation-mlogloss:0.96397
[80]	train-mlogloss:0.97530	validation-mlogloss:0.96130
[81]	train-mlogloss:0.97286	validation-mlogloss:0.95892
[82]	train-mlogloss:0.97025	validation-mlogloss:0.95642
[83]	train-mlogloss:0.96779	validation-mlogloss:0.95386
[84]	train-mlogloss:0.96533	validation-mlogloss:0.95151
[85]	train-mlogloss:0.96297	validation-mlogloss:0.94925
[86]	train-mlogloss:0.96064	validation-mlogloss:0.94699
[87]	train-mlogloss:0.95834	validation-mlogloss:0.94469
[88]	train-mlogloss:0.95584	validation-mlogloss:0.94202
[89]	train-mlogloss:0.95347	validation-mlogloss:0.93952
[90]	train-mlogloss:0.95121	validation-mlogloss:0.93721
[91]	train-mlogloss:0.94880	validation-mlogloss:0.93463
[92]	train-mlogloss:0.94663	validation-mlogloss:0.93230
[93]	train-mlogloss:0.94423	validation-mlogloss:0.92979
[94]	train-mlogloss:0.94200	validation-mlogloss:0.92766
[95]	train-mlogloss:0.93980	validation-mlogloss:0.92537
[96]	train-mlogloss:0.93758	validation-mlogloss:0.92301
[97]	train-mlogloss:0.93538	validation-mlogloss:0.92072
[98]	train-mlogloss:0.93325	validation-mlogloss:0.91841
[99]	train-mlogloss:0.93120	validation-mlogloss:0.91639
[100]	train-mlogloss:0.92914	validation-mlogloss:0.91428
[101]	train-mlogloss:0.92733	validation-mlogloss:0.91238
[102]	train-mlogloss:0.92542	validation-mlogloss:0.91036
[103]	train-mlogloss:0.92331	validation-mlogloss:0.90831
[104]	train-mlogloss:0.92125	validation-mlogloss:0.90619
[105]	train-mlogloss:0.91940	validation-mlogloss:0.90437
[106]	train-mlogloss:0.91756	validation-mlogloss:0.90244
[107]	train-mlogloss:0.91580	validation-mlogloss:0.90066
[108]	train-mlogloss:0.91394	validation-mlogloss:0.89867
[109]	train-mlogloss:0.91215	validation-mlogloss:0.89677
[110]	train-mlogloss:0.91021	validation-mlogloss:0.89496
[111]	train-mlogloss:0.90847	validation-mlogloss:0.89312
[112]	train-mlogloss:0.90692	validation-mlogloss:0.89155
[113]	train-mlogloss:0.90520	validation-mlogloss:0.88968
[114]	train-mlogloss:0.90350	validation-mlogloss:0.88804
[115]	train-mlogloss:0.90203	validation-mlogloss:0.88659
[116]	train-mlogloss:0.90022	validation-mlogloss:0.88485
[117]	train-mlogloss:0.89846	validation-mlogloss:0.88305
[118]	train-mlogloss:0.89663	validation-mlogloss:0.88115
[119]	train-mlogloss:0.89502	validation-mlogloss:0.87946
[120]	train-mlogloss:0.89332	validation-mlogloss:0.87775
[121]	train-mlogloss:0.89180	validation-mlogloss:0.87623
[122]	train-mlogloss:0.89024	validation-mlogloss:0.87460
[123]	train-mlogloss:0.88860	validation-mlogloss:0.87294
[124]	train-mlogloss:0.88701	validation-mlogloss:0.87113
[125]	train-mlogloss:0.88550	validation-mlogloss:0.86958
[126]	train-mlogloss:0.88396	validation-mlogloss:0.86811
[127]	train-mlogloss:0.88238	validation-mlogloss:0.86653
[128]	train-mlogloss:0.88085	validation-mlogloss:0.86513
[129]	train-mlogloss:0.87932	validation-mlogloss:0.86338
[130]	train-mlogloss:0.87780	validation-mlogloss:0.86172
[131]	train-mlogloss:0.87628	validation-mlogloss:0.86017
[132]	train-mlogloss:0.87483	validation-mlogloss:0.85870
[133]	train-mlogloss:0.87337	validation-mlogloss:0.85720
[134]	train-mlogloss:0.87173	validation-mlogloss:0.85562
[135]	train-mlogloss:0.87021	validation-mlogloss:0.85395
[136]	train-mlogloss:0.86889	validation-mlogloss:0.85248
[137]	train-mlogloss:0.86749	validation-mlogloss:0.85103
[138]	train-mlogloss:0.86609	validation-mlogloss:0.84969
[139]	train-mlogloss:0.86452	validation-mlogloss:0.84815
[140]	train-mlogloss:0.86303	validation-mlogloss:0.84652
[141]	train-mlogloss:0.86167	validation-mlogloss:0.84502
[142]	train-mlogloss:0.86029	validation-mlogloss:0.84365
[143]	train-mlogloss:0.85894	validation-mlogloss:0.84226
[144]	train-mlogloss:0.85759	validation-mlogloss:0.84094
[145]	train-mlogloss:0.85638	validation-mlogloss:0.83984
[146]	train-mlogloss:0.85502	validation-mlogloss:0.83856
[147]	train-mlogloss:0.85371	validation-mlogloss:0.83724
[148]	train-mlogloss:0.85224	validation-mlogloss:0.83573
[149]	train-mlogloss:0.85105	validation-mlogloss:0.83459
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[151]	train-mlogloss:0.84859	validation-mlogloss:0.83212
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[339]	train-mlogloss:0.71869	validation-mlogloss:0.70943
[340]	train-mlogloss:0.71839	validation-mlogloss:0.70916
[341]	train-mlogloss:0.71801	validation-mlogloss:0.70885
[342]	train-mlogloss:0.71768	validation-mlogloss:0.70867
[343]	train-mlogloss:0.71746	validation-mlogloss:0.70853
[344]	train-mlogloss:0.71718	validation-mlogloss:0.70825
[345]	train-mlogloss:0.71687	validation-mlogloss:0.70795
[346]	train-mlogloss:0.71647	validation-mlogloss:0.70771
[347]	train-mlogloss:0.71609	validation-mlogloss:0.70740
[348]	train-mlogloss:0.71561	validation-mlogloss:0.70707
[349]	train-mlogloss:0.71528	validation-mlogloss:0.70681
[350]	train-mlogloss:0.71492	validation-mlogloss:0.70649
[351]	train-mlogloss:0.71462	validation-mlogloss:0.70630
[352]	train-mlogloss:0.71432	validation-mlogloss:0.70606
[353]	train-mlogloss:0.71394	validation-mlogloss:0.70583
[354]	train-mlogloss:0.71365	validation-mlogloss:0.70554
[355]	train-mlogloss:0.71333	validation-mlogloss:0.70528
[356]	train-mlogloss:0.71293	validation-mlogloss:0.70491
[357]	train-mlogloss:0.71252	validation-mlogloss:0.70462
[358]	train-mlogloss:0.71219	validation-mlogloss:0.70433
[359]	train-mlogloss:0.71191	validation-mlogloss:0.70407
[360]	train-mlogloss:0.71153	validation-mlogloss:0.70370
[361]	train-mlogloss:0.71128	validation-mlogloss:0.70352
[362]	train-mlogloss:0.71104	validation-mlogloss:0.70329
[363]	train-mlogloss:0.71071	validation-mlogloss:0.70301
[364]	train-mlogloss:0.71049	validation-mlogloss:0.70281
[365]	train-mlogloss:0.71023	validation-mlogloss:0.70265
[366]	train-mlogloss:0.70988	validation-mlogloss:0.70230
[367]	train-mlogloss:0.70956	validation-mlogloss:0.70200
[368]	train-mlogloss:0.70927	validation-mlogloss:0.70179
[369]	train-mlogloss:0.70898	validation-mlogloss:0.70158
[370]	train-mlogloss:0.70871	validation-mlogloss:0.70130
[371]	train-mlogloss:0.70842	validation-mlogloss:0.70108
[372]	train-mlogloss:0.70809	validation-mlogloss:0.70083
[373]	train-mlogloss:0.70787	validation-mlogloss:0.70062
[374]	train-mlogloss:0.70757	validation-mlogloss:0.70040
[375]	train-mlogloss:0.70729	validation-mlogloss:0.70002
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 0 0 ... 2 2 0]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.02 [%]
Global accuracy score (test) = 72.43 [%]
Global F1 score (train) = 72.94 [%]
Global F1 score (test) = 72.72 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.48      0.54       400
MODERATE-INTENSITY       0.59      0.85      0.70       400
         SEDENTARY       0.85      0.83      0.84       400
VIGOROUS-INTENSITY       0.94      0.74      0.83       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.73      1545
      weighted avg       0.75      0.72      0.72      1545


Accuracy capturado en la ejecución 15: 72.43 [%]
F1-score capturado en la ejecución 15: 72.72 [%]

=== EJECUCIÓN 16 ===

--- TRAIN (ejecución 16) ---

--- TEST (ejecución 16) ---
2025-11-04 10:37:25.998467: 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 10:37:26.010178: 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 00:00:1762249046.024320 1056431 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249046.028420 1056431 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249046.038476 1056431 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249046.038503 1056431 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249046.038504 1056431 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249046.038506 1056431 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:37:26.041446: 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:1.37662	validation-mlogloss:1.37594
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[10]	train-mlogloss:1.29089	validation-mlogloss:1.28685
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[19]	train-mlogloss:1.22638	validation-mlogloss:1.22129
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[22]	train-mlogloss:1.20725	validation-mlogloss:1.20173
[23]	train-mlogloss:1.20107	validation-mlogloss:1.19550
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[25]	train-mlogloss:1.18908	validation-mlogloss:1.18370
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[43]	train-mlogloss:1.09834	validation-mlogloss:1.09055
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[47]	train-mlogloss:1.08123	validation-mlogloss:1.07294
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[49]	train-mlogloss:1.07333	validation-mlogloss:1.06474
[50]	train-mlogloss:1.06959	validation-mlogloss:1.06097
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[91]	train-mlogloss:0.94753	validation-mlogloss:0.93675
[92]	train-mlogloss:0.94532	validation-mlogloss:0.93440
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[98]	train-mlogloss:0.93222	validation-mlogloss:0.92124
[99]	train-mlogloss:0.93011	validation-mlogloss:0.91916
[100]	train-mlogloss:0.92802	validation-mlogloss:0.91711
[101]	train-mlogloss:0.92611	validation-mlogloss:0.91509
[102]	train-mlogloss:0.92412	validation-mlogloss:0.91326
[103]	train-mlogloss:0.92211	validation-mlogloss:0.91131
[104]	train-mlogloss:0.92025	validation-mlogloss:0.90942
[105]	train-mlogloss:0.91838	validation-mlogloss:0.90737
[106]	train-mlogloss:0.91647	validation-mlogloss:0.90558
[107]	train-mlogloss:0.91457	validation-mlogloss:0.90373
[108]	train-mlogloss:0.91270	validation-mlogloss:0.90176
[109]	train-mlogloss:0.91090	validation-mlogloss:0.89995
[110]	train-mlogloss:0.90906	validation-mlogloss:0.89802
[111]	train-mlogloss:0.90736	validation-mlogloss:0.89616
[112]	train-mlogloss:0.90564	validation-mlogloss:0.89445
[113]	train-mlogloss:0.90378	validation-mlogloss:0.89243
[114]	train-mlogloss:0.90200	validation-mlogloss:0.89055
[115]	train-mlogloss:0.90039	validation-mlogloss:0.88884
[116]	train-mlogloss:0.89871	validation-mlogloss:0.88721
[117]	train-mlogloss:0.89703	validation-mlogloss:0.88540
[118]	train-mlogloss:0.89523	validation-mlogloss:0.88355
[119]	train-mlogloss:0.89365	validation-mlogloss:0.88192
[120]	train-mlogloss:0.89204	validation-mlogloss:0.88027
[121]	train-mlogloss:0.89021	validation-mlogloss:0.87855
[122]	train-mlogloss:0.88867	validation-mlogloss:0.87703
[123]	train-mlogloss:0.88710	validation-mlogloss:0.87560
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[125]	train-mlogloss:0.88409	validation-mlogloss:0.87278
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[129]	train-mlogloss:0.87823	validation-mlogloss:0.86700
[130]	train-mlogloss:0.87669	validation-mlogloss:0.86536
[131]	train-mlogloss:0.87507	validation-mlogloss:0.86366
[132]	train-mlogloss:0.87377	validation-mlogloss:0.86240
[133]	train-mlogloss:0.87242	validation-mlogloss:0.86119
[134]	train-mlogloss:0.87106	validation-mlogloss:0.85990
[135]	train-mlogloss:0.86976	validation-mlogloss:0.85843
[136]	train-mlogloss:0.86813	validation-mlogloss:0.85696
[137]	train-mlogloss:0.86687	validation-mlogloss:0.85589
[138]	train-mlogloss:0.86558	validation-mlogloss:0.85457
[139]	train-mlogloss:0.86416	validation-mlogloss:0.85318
[140]	train-mlogloss:0.86291	validation-mlogloss:0.85206
[141]	train-mlogloss:0.86158	validation-mlogloss:0.85075
[142]	train-mlogloss:0.86019	validation-mlogloss:0.84940
[143]	train-mlogloss:0.85888	validation-mlogloss:0.84819
[144]	train-mlogloss:0.85737	validation-mlogloss:0.84675
[145]	train-mlogloss:0.85606	validation-mlogloss:0.84563
[146]	train-mlogloss:0.85470	validation-mlogloss:0.84437
[147]	train-mlogloss:0.85338	validation-mlogloss:0.84309
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[149]	train-mlogloss:0.85070	validation-mlogloss:0.84031
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[151]	train-mlogloss:0.84834	validation-mlogloss:0.83810
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[157]	train-mlogloss:0.84116	validation-mlogloss:0.83092
[158]	train-mlogloss:0.84008	validation-mlogloss:0.82978
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[189]	train-mlogloss:0.80794	validation-mlogloss:0.79881
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[195]	train-mlogloss:0.80252	validation-mlogloss:0.79356
[196]	train-mlogloss:0.80162	validation-mlogloss:0.79274
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[198]	train-mlogloss:0.79997	validation-mlogloss:0.79125
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[200]	train-mlogloss:0.79838	validation-mlogloss:0.78971
[201]	train-mlogloss:0.79741	validation-mlogloss:0.78881
[202]	train-mlogloss:0.79654	validation-mlogloss:0.78808
[203]	train-mlogloss:0.79576	validation-mlogloss:0.78743
[204]	train-mlogloss:0.79489	validation-mlogloss:0.78675
[205]	train-mlogloss:0.79399	validation-mlogloss:0.78597
[206]	train-mlogloss:0.79310	validation-mlogloss:0.78514
[207]	train-mlogloss:0.79226	validation-mlogloss:0.78434
[208]	train-mlogloss:0.79146	validation-mlogloss:0.78364
[209]	train-mlogloss:0.79053	validation-mlogloss:0.78281
[210]	train-mlogloss:0.78976	validation-mlogloss:0.78208
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[216]	train-mlogloss:0.78474	validation-mlogloss:0.77746
[217]	train-mlogloss:0.78399	validation-mlogloss:0.77682
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[220]	train-mlogloss:0.78177	validation-mlogloss:0.77484
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[222]	train-mlogloss:0.78036	validation-mlogloss:0.77354
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[227]	train-mlogloss:0.77654	validation-mlogloss:0.76995
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[229]	train-mlogloss:0.77509	validation-mlogloss:0.76874
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[276]	train-mlogloss:0.74680	validation-mlogloss:0.74339
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[278]	train-mlogloss:0.74568	validation-mlogloss:0.74241
[279]	train-mlogloss:0.74515	validation-mlogloss:0.74199
[280]	train-mlogloss:0.74472	validation-mlogloss:0.74165
[281]	train-mlogloss:0.74424	validation-mlogloss:0.74133
[282]	train-mlogloss:0.74377	validation-mlogloss:0.74096
[283]	train-mlogloss:0.74339	validation-mlogloss:0.74055
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[285]	train-mlogloss:0.74243	validation-mlogloss:0.73983
[286]	train-mlogloss:0.74200	validation-mlogloss:0.73953
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[301]	train-mlogloss:0.73546	validation-mlogloss:0.73413
[302]	train-mlogloss:0.73506	validation-mlogloss:0.73380
[303]	train-mlogloss:0.73460	validation-mlogloss:0.73341
[304]	train-mlogloss:0.73421	validation-mlogloss:0.73319
[305]	train-mlogloss:0.73379	validation-mlogloss:0.73281
[306]	train-mlogloss:0.73345	validation-mlogloss:0.73249
[307]	train-mlogloss:0.73306	validation-mlogloss:0.73219
[308]	train-mlogloss:0.73266	validation-mlogloss:0.73191
[309]	train-mlogloss:0.73226	validation-mlogloss:0.73151
[310]	train-mlogloss:0.73182	validation-mlogloss:0.73117
[311]	train-mlogloss:0.73139	validation-mlogloss:0.73084
[312]	train-mlogloss:0.73101	validation-mlogloss:0.73054
[313]	train-mlogloss:0.73054	validation-mlogloss:0.73013
[314]	train-mlogloss:0.73009	validation-mlogloss:0.72970
[315]	train-mlogloss:0.72970	validation-mlogloss:0.72935
[316]	train-mlogloss:0.72931	validation-mlogloss:0.72903
[317]	train-mlogloss:0.72889	validation-mlogloss:0.72869
[318]	train-mlogloss:0.72848	validation-mlogloss:0.72837
[319]	train-mlogloss:0.72802	validation-mlogloss:0.72799
[320]	train-mlogloss:0.72769	validation-mlogloss:0.72778
[321]	train-mlogloss:0.72727	validation-mlogloss:0.72744
[322]	train-mlogloss:0.72684	validation-mlogloss:0.72706
[323]	train-mlogloss:0.72635	validation-mlogloss:0.72665
[324]	train-mlogloss:0.72594	validation-mlogloss:0.72623
[325]	train-mlogloss:0.72542	validation-mlogloss:0.72584
[326]	train-mlogloss:0.72504	validation-mlogloss:0.72551
[327]	train-mlogloss:0.72459	validation-mlogloss:0.72516
[328]	train-mlogloss:0.72412	validation-mlogloss:0.72479
[329]	train-mlogloss:0.72380	validation-mlogloss:0.72459
[330]	train-mlogloss:0.72343	validation-mlogloss:0.72429
[331]	train-mlogloss:0.72299	validation-mlogloss:0.72388
[332]	train-mlogloss:0.72270	validation-mlogloss:0.72361
[333]	train-mlogloss:0.72236	validation-mlogloss:0.72331
[334]	train-mlogloss:0.72203	validation-mlogloss:0.72302
[335]	train-mlogloss:0.72174	validation-mlogloss:0.72272
[336]	train-mlogloss:0.72136	validation-mlogloss:0.72242
[337]	train-mlogloss:0.72103	validation-mlogloss:0.72209
[338]	train-mlogloss:0.72063	validation-mlogloss:0.72177
[339]	train-mlogloss:0.72031	validation-mlogloss:0.72145
[340]	train-mlogloss:0.71994	validation-mlogloss:0.72120
[341]	train-mlogloss:0.71959	validation-mlogloss:0.72100
[342]	train-mlogloss:0.71923	validation-mlogloss:0.72070
[343]	train-mlogloss:0.71892	validation-mlogloss:0.72040
[344]	train-mlogloss:0.71854	validation-mlogloss:0.72005
[345]	train-mlogloss:0.71820	validation-mlogloss:0.71986
[346]	train-mlogloss:0.71786	validation-mlogloss:0.71963
[347]	train-mlogloss:0.71748	validation-mlogloss:0.71931
[348]	train-mlogloss:0.71718	validation-mlogloss:0.71901
[349]	train-mlogloss:0.71684	validation-mlogloss:0.71875
[350]	train-mlogloss:0.71650	validation-mlogloss:0.71848
[351]	train-mlogloss:0.71611	validation-mlogloss:0.71814
[352]	train-mlogloss:0.71579	validation-mlogloss:0.71777
[353]	train-mlogloss:0.71543	validation-mlogloss:0.71751
[354]	train-mlogloss:0.71508	validation-mlogloss:0.71721
[355]	train-mlogloss:0.71480	validation-mlogloss:0.71694
[356]	train-mlogloss:0.71460	validation-mlogloss:0.71675
[357]	train-mlogloss:0.71428	validation-mlogloss:0.71648
[358]	train-mlogloss:0.71399	validation-mlogloss:0.71629
[359]	train-mlogloss:0.71377	validation-mlogloss:0.71611
[360]	train-mlogloss:0.71346	validation-mlogloss:0.71581
[361]	train-mlogloss:0.71317	validation-mlogloss:0.71557
[362]	train-mlogloss:0.71288	validation-mlogloss:0.71529
[363]	train-mlogloss:0.71261	validation-mlogloss:0.71505
[364]	train-mlogloss:0.71228	validation-mlogloss:0.71485
[365]	train-mlogloss:0.71201	validation-mlogloss:0.71459
[366]	train-mlogloss:0.71179	validation-mlogloss:0.71451
[367]	train-mlogloss:0.71148	validation-mlogloss:0.71419
[368]	train-mlogloss:0.71119	validation-mlogloss:0.71401
[369]	train-mlogloss:0.71092	validation-mlogloss:0.71380
[370]	train-mlogloss:0.71063	validation-mlogloss:0.71345
[371]	train-mlogloss:0.71029	validation-mlogloss:0.71317
[372]	train-mlogloss:0.70991	validation-mlogloss:0.71296
[373]	train-mlogloss:0.70953	validation-mlogloss:0.71267
[374]	train-mlogloss:0.70925	validation-mlogloss:0.71249
[375]	train-mlogloss:0.70906	validation-mlogloss:0.71233
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 0 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.3 [%]
Global accuracy score (test) = 72.3 [%]
Global F1 score (train) = 73.12 [%]
Global F1 score (test) = 72.54 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.46      0.53       400
MODERATE-INTENSITY       0.58      0.83      0.69       400
         SEDENTARY       0.84      0.85      0.85       400
VIGOROUS-INTENSITY       0.96      0.74      0.84       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.73      1545
      weighted avg       0.74      0.72      0.72      1545


Accuracy capturado en la ejecución 16: 72.3 [%]
F1-score capturado en la ejecución 16: 72.54 [%]

=== EJECUCIÓN 17 ===

--- TRAIN (ejecución 17) ---

--- TEST (ejecución 17) ---
2025-11-04 10:37:41.909582: 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 10:37:41.920967: 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 00:00:1762249061.934263 1056739 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249061.938465 1056739 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249061.948606 1056739 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249061.948627 1056739 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249061.948628 1056739 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249061.948630 1056739 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:37:41.952086: 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:1.37660	validation-mlogloss:1.37634
[1]	train-mlogloss:1.36691	validation-mlogloss:1.36624
[2]	train-mlogloss:1.35733	validation-mlogloss:1.35654
[3]	train-mlogloss:1.34793	validation-mlogloss:1.34718
[4]	train-mlogloss:1.33882	validation-mlogloss:1.33784
[5]	train-mlogloss:1.33079	validation-mlogloss:1.32947
[6]	train-mlogloss:1.32238	validation-mlogloss:1.32076
[7]	train-mlogloss:1.31385	validation-mlogloss:1.31163
[8]	train-mlogloss:1.30597	validation-mlogloss:1.30353
[9]	train-mlogloss:1.29790	validation-mlogloss:1.29522
[10]	train-mlogloss:1.29040	validation-mlogloss:1.28785
[11]	train-mlogloss:1.28233	validation-mlogloss:1.27980
[12]	train-mlogloss:1.27477	validation-mlogloss:1.27188
[13]	train-mlogloss:1.26711	validation-mlogloss:1.26415
[14]	train-mlogloss:1.25960	validation-mlogloss:1.25654
[15]	train-mlogloss:1.25224	validation-mlogloss:1.24900
[16]	train-mlogloss:1.24503	validation-mlogloss:1.24156
[17]	train-mlogloss:1.23837	validation-mlogloss:1.23450
[18]	train-mlogloss:1.23156	validation-mlogloss:1.22738
[19]	train-mlogloss:1.22527	validation-mlogloss:1.22116
[20]	train-mlogloss:1.21866	validation-mlogloss:1.21462
[21]	train-mlogloss:1.21237	validation-mlogloss:1.20827
[22]	train-mlogloss:1.20631	validation-mlogloss:1.20187
[23]	train-mlogloss:1.20055	validation-mlogloss:1.19621
[24]	train-mlogloss:1.19465	validation-mlogloss:1.19000
[25]	train-mlogloss:1.18866	validation-mlogloss:1.18433
[26]	train-mlogloss:1.18307	validation-mlogloss:1.17870
[27]	train-mlogloss:1.17738	validation-mlogloss:1.17274
[28]	train-mlogloss:1.17154	validation-mlogloss:1.16685
[29]	train-mlogloss:1.16629	validation-mlogloss:1.16143
[30]	train-mlogloss:1.16105	validation-mlogloss:1.15621
[31]	train-mlogloss:1.15559	validation-mlogloss:1.15076
[32]	train-mlogloss:1.15052	validation-mlogloss:1.14559
[33]	train-mlogloss:1.14530	validation-mlogloss:1.14007
[34]	train-mlogloss:1.14019	validation-mlogloss:1.13500
[35]	train-mlogloss:1.13528	validation-mlogloss:1.13003
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[334]	train-mlogloss:0.71713	validation-mlogloss:0.71370
[335]	train-mlogloss:0.71675	validation-mlogloss:0.71333
[336]	train-mlogloss:0.71643	validation-mlogloss:0.71309
[337]	train-mlogloss:0.71608	validation-mlogloss:0.71285
[338]	train-mlogloss:0.71572	validation-mlogloss:0.71252
[339]	train-mlogloss:0.71537	validation-mlogloss:0.71216
[340]	train-mlogloss:0.71496	validation-mlogloss:0.71193
[341]	train-mlogloss:0.71448	validation-mlogloss:0.71157
[342]	train-mlogloss:0.71413	validation-mlogloss:0.71124
[343]	train-mlogloss:0.71374	validation-mlogloss:0.71090
[344]	train-mlogloss:0.71338	validation-mlogloss:0.71050
[345]	train-mlogloss:0.71297	validation-mlogloss:0.71008
[346]	train-mlogloss:0.71260	validation-mlogloss:0.70978
[347]	train-mlogloss:0.71224	validation-mlogloss:0.70947
[348]	train-mlogloss:0.71195	validation-mlogloss:0.70926
[349]	train-mlogloss:0.71158	validation-mlogloss:0.70901
[350]	train-mlogloss:0.71114	validation-mlogloss:0.70864
[351]	train-mlogloss:0.71075	validation-mlogloss:0.70828
[352]	train-mlogloss:0.71039	validation-mlogloss:0.70800
[353]	train-mlogloss:0.70995	validation-mlogloss:0.70762
[354]	train-mlogloss:0.70961	validation-mlogloss:0.70729
[355]	train-mlogloss:0.70928	validation-mlogloss:0.70707
[356]	train-mlogloss:0.70904	validation-mlogloss:0.70688
[357]	train-mlogloss:0.70868	validation-mlogloss:0.70656
[358]	train-mlogloss:0.70835	validation-mlogloss:0.70628
[359]	train-mlogloss:0.70798	validation-mlogloss:0.70607
[360]	train-mlogloss:0.70761	validation-mlogloss:0.70585
[361]	train-mlogloss:0.70723	validation-mlogloss:0.70551
[362]	train-mlogloss:0.70687	validation-mlogloss:0.70513
[363]	train-mlogloss:0.70644	validation-mlogloss:0.70477
[364]	train-mlogloss:0.70610	validation-mlogloss:0.70446
[365]	train-mlogloss:0.70577	validation-mlogloss:0.70413
[366]	train-mlogloss:0.70548	validation-mlogloss:0.70395
[367]	train-mlogloss:0.70525	validation-mlogloss:0.70373
[368]	train-mlogloss:0.70493	validation-mlogloss:0.70348
[369]	train-mlogloss:0.70453	validation-mlogloss:0.70309
[370]	train-mlogloss:0.70425	validation-mlogloss:0.70284
[371]	train-mlogloss:0.70399	validation-mlogloss:0.70264
[372]	train-mlogloss:0.70374	validation-mlogloss:0.70246
[373]	train-mlogloss:0.70342	validation-mlogloss:0.70219
[374]	train-mlogloss:0.70315	validation-mlogloss:0.70193
[375]	train-mlogloss:0.70283	validation-mlogloss:0.70169
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 72.65 [%]
Global accuracy score (test) = 72.56 [%]
Global F1 score (train) = 72.49 [%]
Global F1 score (test) = 72.62 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.46      0.53       400
MODERATE-INTENSITY       0.60      0.88      0.71       400
         SEDENTARY       0.83      0.82      0.83       400
VIGOROUS-INTENSITY       0.94      0.74      0.83       345

          accuracy                           0.73      1545
         macro avg       0.75      0.73      0.73      1545
      weighted avg       0.74      0.73      0.72      1545


Accuracy capturado en la ejecución 17: 72.56 [%]
F1-score capturado en la ejecución 17: 72.62 [%]

=== EJECUCIÓN 18 ===

--- TRAIN (ejecución 18) ---

--- TEST (ejecución 18) ---
2025-11-04 10:37:57.975435: 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 10:37:57.986789: 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 00:00:1762249077.999830 1057042 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249078.004087 1057042 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249078.014352 1057042 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249078.014368 1057042 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249078.014369 1057042 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249078.014371 1057042 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:37:58.017696: 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:1.37641	validation-mlogloss:1.37602
[1]	train-mlogloss:1.36712	validation-mlogloss:1.36632
[2]	train-mlogloss:1.35798	validation-mlogloss:1.35680
[3]	train-mlogloss:1.34879	validation-mlogloss:1.34735
[4]	train-mlogloss:1.33999	validation-mlogloss:1.33802
[5]	train-mlogloss:1.33154	validation-mlogloss:1.32911
[6]	train-mlogloss:1.32313	validation-mlogloss:1.32024
[7]	train-mlogloss:1.31502	validation-mlogloss:1.31167
[8]	train-mlogloss:1.30675	validation-mlogloss:1.30297
[9]	train-mlogloss:1.29861	validation-mlogloss:1.29428
[10]	train-mlogloss:1.29053	validation-mlogloss:1.28596
[11]	train-mlogloss:1.28267	validation-mlogloss:1.27811
[12]	train-mlogloss:1.27489	validation-mlogloss:1.27009
[13]	train-mlogloss:1.26759	validation-mlogloss:1.26235
[14]	train-mlogloss:1.26030	validation-mlogloss:1.25474
[15]	train-mlogloss:1.25282	validation-mlogloss:1.24705
[16]	train-mlogloss:1.24584	validation-mlogloss:1.24006
[17]	train-mlogloss:1.23900	validation-mlogloss:1.23305
[18]	train-mlogloss:1.23211	validation-mlogloss:1.22587
[19]	train-mlogloss:1.22551	validation-mlogloss:1.21912
[20]	train-mlogloss:1.21882	validation-mlogloss:1.21246
[21]	train-mlogloss:1.21266	validation-mlogloss:1.20635
[22]	train-mlogloss:1.20622	validation-mlogloss:1.19979
[23]	train-mlogloss:1.20002	validation-mlogloss:1.19344
[24]	train-mlogloss:1.19365	validation-mlogloss:1.18697
[25]	train-mlogloss:1.18778	validation-mlogloss:1.18075
[26]	train-mlogloss:1.18198	validation-mlogloss:1.17490
[27]	train-mlogloss:1.17628	validation-mlogloss:1.16927
[28]	train-mlogloss:1.17045	validation-mlogloss:1.16301
[29]	train-mlogloss:1.16506	validation-mlogloss:1.15763
[30]	train-mlogloss:1.15931	validation-mlogloss:1.15181
[31]	train-mlogloss:1.15403	validation-mlogloss:1.14647
[32]	train-mlogloss:1.14853	validation-mlogloss:1.14084
[33]	train-mlogloss:1.14293	validation-mlogloss:1.13525
[34]	train-mlogloss:1.13773	validation-mlogloss:1.12995
[35]	train-mlogloss:1.13300	validation-mlogloss:1.12531
[36]	train-mlogloss:1.12798	validation-mlogloss:1.11982
[37]	train-mlogloss:1.12325	validation-mlogloss:1.11486
[38]	train-mlogloss:1.11848	validation-mlogloss:1.11012
[39]	train-mlogloss:1.11379	validation-mlogloss:1.10539
[40]	train-mlogloss:1.10927	validation-mlogloss:1.10073
[41]	train-mlogloss:1.10460	validation-mlogloss:1.09595
[42]	train-mlogloss:1.10012	validation-mlogloss:1.09134
[43]	train-mlogloss:1.09576	validation-mlogloss:1.08699
[44]	train-mlogloss:1.09128	validation-mlogloss:1.08249
[45]	train-mlogloss:1.08680	validation-mlogloss:1.07798
[46]	train-mlogloss:1.08274	validation-mlogloss:1.07383
[47]	train-mlogloss:1.07863	validation-mlogloss:1.06979
[48]	train-mlogloss:1.07467	validation-mlogloss:1.06551
[49]	train-mlogloss:1.07060	validation-mlogloss:1.06122
[50]	train-mlogloss:1.06668	validation-mlogloss:1.05731
[51]	train-mlogloss:1.06275	validation-mlogloss:1.05300
[52]	train-mlogloss:1.05875	validation-mlogloss:1.04899
[53]	train-mlogloss:1.05498	validation-mlogloss:1.04527
[54]	train-mlogloss:1.05138	validation-mlogloss:1.04160
[55]	train-mlogloss:1.04784	validation-mlogloss:1.03789
[56]	train-mlogloss:1.04435	validation-mlogloss:1.03420
[57]	train-mlogloss:1.04060	validation-mlogloss:1.03046
[58]	train-mlogloss:1.03678	validation-mlogloss:1.02648
[59]	train-mlogloss:1.03345	validation-mlogloss:1.02303
[60]	train-mlogloss:1.02991	validation-mlogloss:1.01955
[61]	train-mlogloss:1.02652	validation-mlogloss:1.01612
[62]	train-mlogloss:1.02319	validation-mlogloss:1.01238
[63]	train-mlogloss:1.01994	validation-mlogloss:1.00904
[64]	train-mlogloss:1.01693	validation-mlogloss:1.00604
[65]	train-mlogloss:1.01382	validation-mlogloss:1.00297
[66]	train-mlogloss:1.01062	validation-mlogloss:0.99962
[67]	train-mlogloss:1.00736	validation-mlogloss:0.99628
[68]	train-mlogloss:1.00409	validation-mlogloss:0.99283
[69]	train-mlogloss:1.00112	validation-mlogloss:0.99003
[70]	train-mlogloss:0.99812	validation-mlogloss:0.98689
[71]	train-mlogloss:0.99532	validation-mlogloss:0.98414
[72]	train-mlogloss:0.99243	validation-mlogloss:0.98123
[73]	train-mlogloss:0.98958	validation-mlogloss:0.97811
[74]	train-mlogloss:0.98669	validation-mlogloss:0.97505
[75]	train-mlogloss:0.98381	validation-mlogloss:0.97227
[76]	train-mlogloss:0.98097	validation-mlogloss:0.96937
[77]	train-mlogloss:0.97833	validation-mlogloss:0.96672
[78]	train-mlogloss:0.97564	validation-mlogloss:0.96386
[79]	train-mlogloss:0.97283	validation-mlogloss:0.96097
[80]	train-mlogloss:0.97036	validation-mlogloss:0.95844
[81]	train-mlogloss:0.96789	validation-mlogloss:0.95585
[82]	train-mlogloss:0.96543	validation-mlogloss:0.95352
[83]	train-mlogloss:0.96282	validation-mlogloss:0.95089
[84]	train-mlogloss:0.96038	validation-mlogloss:0.94854
[85]	train-mlogloss:0.95793	validation-mlogloss:0.94592
[86]	train-mlogloss:0.95546	validation-mlogloss:0.94349
[87]	train-mlogloss:0.95310	validation-mlogloss:0.94097
[88]	train-mlogloss:0.95064	validation-mlogloss:0.93851
[89]	train-mlogloss:0.94825	validation-mlogloss:0.93599
[90]	train-mlogloss:0.94595	validation-mlogloss:0.93368
[91]	train-mlogloss:0.94375	validation-mlogloss:0.93128
[92]	train-mlogloss:0.94161	validation-mlogloss:0.92900
[93]	train-mlogloss:0.93934	validation-mlogloss:0.92676
[94]	train-mlogloss:0.93708	validation-mlogloss:0.92435
[95]	train-mlogloss:0.93508	validation-mlogloss:0.92236
[96]	train-mlogloss:0.93293	validation-mlogloss:0.91998
[97]	train-mlogloss:0.93087	validation-mlogloss:0.91776
[98]	train-mlogloss:0.92887	validation-mlogloss:0.91560
[99]	train-mlogloss:0.92668	validation-mlogloss:0.91334
[100]	train-mlogloss:0.92480	validation-mlogloss:0.91136
[101]	train-mlogloss:0.92285	validation-mlogloss:0.90930
[102]	train-mlogloss:0.92087	validation-mlogloss:0.90734
[103]	train-mlogloss:0.91887	validation-mlogloss:0.90542
[104]	train-mlogloss:0.91687	validation-mlogloss:0.90336
[105]	train-mlogloss:0.91483	validation-mlogloss:0.90134
[106]	train-mlogloss:0.91284	validation-mlogloss:0.89940
[107]	train-mlogloss:0.91091	validation-mlogloss:0.89740
[108]	train-mlogloss:0.90893	validation-mlogloss:0.89541
[109]	train-mlogloss:0.90710	validation-mlogloss:0.89365
[110]	train-mlogloss:0.90533	validation-mlogloss:0.89186
[111]	train-mlogloss:0.90342	validation-mlogloss:0.88979
[112]	train-mlogloss:0.90168	validation-mlogloss:0.88795
[113]	train-mlogloss:0.89993	validation-mlogloss:0.88618
[114]	train-mlogloss:0.89832	validation-mlogloss:0.88452
[115]	train-mlogloss:0.89658	validation-mlogloss:0.88269
[116]	train-mlogloss:0.89476	validation-mlogloss:0.88073
[117]	train-mlogloss:0.89306	validation-mlogloss:0.87883
[118]	train-mlogloss:0.89137	validation-mlogloss:0.87713
[119]	train-mlogloss:0.88977	validation-mlogloss:0.87535
[120]	train-mlogloss:0.88816	validation-mlogloss:0.87373
[121]	train-mlogloss:0.88649	validation-mlogloss:0.87189
[122]	train-mlogloss:0.88498	validation-mlogloss:0.87016
[123]	train-mlogloss:0.88353	validation-mlogloss:0.86871
[124]	train-mlogloss:0.88193	validation-mlogloss:0.86703
[125]	train-mlogloss:0.88035	validation-mlogloss:0.86544
[126]	train-mlogloss:0.87876	validation-mlogloss:0.86379
[127]	train-mlogloss:0.87726	validation-mlogloss:0.86230
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[360]	train-mlogloss:0.71093	validation-mlogloss:0.70712
[361]	train-mlogloss:0.71063	validation-mlogloss:0.70695
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[370]	train-mlogloss:0.70802	validation-mlogloss:0.70478
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[373]	train-mlogloss:0.70722	validation-mlogloss:0.70414
[374]	train-mlogloss:0.70693	validation-mlogloss:0.70393
[375]	train-mlogloss:0.70664	validation-mlogloss:0.70368
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)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.38 [%]
Global accuracy score (test) = 72.94 [%]
Global F1 score (train) = 73.23 [%]
Global F1 score (test) = 73.15 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.65      0.48      0.56       400
MODERATE-INTENSITY       0.59      0.87      0.70       400
         SEDENTARY       0.85      0.83      0.84       400
VIGOROUS-INTENSITY       0.94      0.74      0.83       345

          accuracy                           0.73      1545
         macro avg       0.76      0.73      0.73      1545
      weighted avg       0.75      0.73      0.73      1545


Accuracy capturado en la ejecución 18: 72.94 [%]
F1-score capturado en la ejecución 18: 73.15 [%]

=== EJECUCIÓN 19 ===

--- TRAIN (ejecución 19) ---

--- TEST (ejecución 19) ---
2025-11-04 10:38:14.110150: 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 10:38:14.121282: 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 00:00:1762249094.134291 1057348 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249094.138202 1057348 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249094.147957 1057348 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249094.147974 1057348 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249094.147975 1057348 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249094.147977 1057348 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:38:14.150948: 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:1.37665	validation-mlogloss:1.37640
[1]	train-mlogloss:1.36723	validation-mlogloss:1.36647
[2]	train-mlogloss:1.35817	validation-mlogloss:1.35708
[3]	train-mlogloss:1.34895	validation-mlogloss:1.34758
[4]	train-mlogloss:1.34010	validation-mlogloss:1.33852
[5]	train-mlogloss:1.33139	validation-mlogloss:1.32944
[6]	train-mlogloss:1.32271	validation-mlogloss:1.32056
[7]	train-mlogloss:1.31466	validation-mlogloss:1.31231
[8]	train-mlogloss:1.30666	validation-mlogloss:1.30381
[9]	train-mlogloss:1.29853	validation-mlogloss:1.29529
[10]	train-mlogloss:1.29047	validation-mlogloss:1.28696
[11]	train-mlogloss:1.28266	validation-mlogloss:1.27877
[12]	train-mlogloss:1.27487	validation-mlogloss:1.27078
[13]	train-mlogloss:1.26755	validation-mlogloss:1.26297
[14]	train-mlogloss:1.26045	validation-mlogloss:1.25588
[15]	train-mlogloss:1.25328	validation-mlogloss:1.24837
[16]	train-mlogloss:1.24604	validation-mlogloss:1.24098
[17]	train-mlogloss:1.23897	validation-mlogloss:1.23393
[18]	train-mlogloss:1.23221	validation-mlogloss:1.22710
[19]	train-mlogloss:1.22582	validation-mlogloss:1.22024
[20]	train-mlogloss:1.21960	validation-mlogloss:1.21408
[21]	train-mlogloss:1.21323	validation-mlogloss:1.20743
[22]	train-mlogloss:1.20667	validation-mlogloss:1.20079
[23]	train-mlogloss:1.20020	validation-mlogloss:1.19438
[24]	train-mlogloss:1.19394	validation-mlogloss:1.18777
[25]	train-mlogloss:1.18823	validation-mlogloss:1.18226
[26]	train-mlogloss:1.18273	validation-mlogloss:1.17687
[27]	train-mlogloss:1.17703	validation-mlogloss:1.17127
[28]	train-mlogloss:1.17124	validation-mlogloss:1.16545
[29]	train-mlogloss:1.16584	validation-mlogloss:1.15972
[30]	train-mlogloss:1.16052	validation-mlogloss:1.15436
[31]	train-mlogloss:1.15502	validation-mlogloss:1.14868
[32]	train-mlogloss:1.14961	validation-mlogloss:1.14323
[33]	train-mlogloss:1.14441	validation-mlogloss:1.13785
[34]	train-mlogloss:1.13951	validation-mlogloss:1.13271
[35]	train-mlogloss:1.13445	validation-mlogloss:1.12755
[36]	train-mlogloss:1.12957	validation-mlogloss:1.12262
[37]	train-mlogloss:1.12489	validation-mlogloss:1.11771
[38]	train-mlogloss:1.12009	validation-mlogloss:1.11264
[39]	train-mlogloss:1.11564	validation-mlogloss:1.10845
[40]	train-mlogloss:1.11090	validation-mlogloss:1.10366
[41]	train-mlogloss:1.10650	validation-mlogloss:1.09903
[42]	train-mlogloss:1.10198	validation-mlogloss:1.09440
[43]	train-mlogloss:1.09773	validation-mlogloss:1.09022
[44]	train-mlogloss:1.09336	validation-mlogloss:1.08601
[45]	train-mlogloss:1.08941	validation-mlogloss:1.08182
[46]	train-mlogloss:1.08511	validation-mlogloss:1.07757
[47]	train-mlogloss:1.08110	validation-mlogloss:1.07353
[48]	train-mlogloss:1.07694	validation-mlogloss:1.06916
[49]	train-mlogloss:1.07275	validation-mlogloss:1.06486
[50]	train-mlogloss:1.06882	validation-mlogloss:1.06076
[51]	train-mlogloss:1.06488	validation-mlogloss:1.05666
[52]	train-mlogloss:1.06095	validation-mlogloss:1.05250
[53]	train-mlogloss:1.05717	validation-mlogloss:1.04870
[54]	train-mlogloss:1.05352	validation-mlogloss:1.04496
[55]	train-mlogloss:1.04982	validation-mlogloss:1.04111
[56]	train-mlogloss:1.04650	validation-mlogloss:1.03787
[57]	train-mlogloss:1.04327	validation-mlogloss:1.03473
[58]	train-mlogloss:1.03986	validation-mlogloss:1.03142
[59]	train-mlogloss:1.03643	validation-mlogloss:1.02790
[60]	train-mlogloss:1.03299	validation-mlogloss:1.02444
[61]	train-mlogloss:1.02965	validation-mlogloss:1.02093
[62]	train-mlogloss:1.02628	validation-mlogloss:1.01761
[63]	train-mlogloss:1.02295	validation-mlogloss:1.01410
[64]	train-mlogloss:1.01966	validation-mlogloss:1.01083
[65]	train-mlogloss:1.01656	validation-mlogloss:1.00756
[66]	train-mlogloss:1.01343	validation-mlogloss:1.00434
[67]	train-mlogloss:1.01027	validation-mlogloss:1.00104
[68]	train-mlogloss:1.00713	validation-mlogloss:0.99776
[69]	train-mlogloss:1.00414	validation-mlogloss:0.99460
[70]	train-mlogloss:1.00105	validation-mlogloss:0.99159
[71]	train-mlogloss:0.99816	validation-mlogloss:0.98854
[72]	train-mlogloss:0.99508	validation-mlogloss:0.98529
[73]	train-mlogloss:0.99228	validation-mlogloss:0.98243
[74]	train-mlogloss:0.98947	validation-mlogloss:0.97952
[75]	train-mlogloss:0.98663	validation-mlogloss:0.97650
[76]	train-mlogloss:0.98414	validation-mlogloss:0.97415
[77]	train-mlogloss:0.98126	validation-mlogloss:0.97125
[78]	train-mlogloss:0.97854	validation-mlogloss:0.96830
[79]	train-mlogloss:0.97593	validation-mlogloss:0.96559
[80]	train-mlogloss:0.97331	validation-mlogloss:0.96284
[81]	train-mlogloss:0.97062	validation-mlogloss:0.95998
[82]	train-mlogloss:0.96813	validation-mlogloss:0.95742
[83]	train-mlogloss:0.96544	validation-mlogloss:0.95462
[84]	train-mlogloss:0.96287	validation-mlogloss:0.95210
[85]	train-mlogloss:0.96042	validation-mlogloss:0.94952
[86]	train-mlogloss:0.95813	validation-mlogloss:0.94730
[87]	train-mlogloss:0.95550	validation-mlogloss:0.94456
[88]	train-mlogloss:0.95329	validation-mlogloss:0.94230
[89]	train-mlogloss:0.95077	validation-mlogloss:0.93980
[90]	train-mlogloss:0.94851	validation-mlogloss:0.93735
[91]	train-mlogloss:0.94630	validation-mlogloss:0.93514
[92]	train-mlogloss:0.94409	validation-mlogloss:0.93273
[93]	train-mlogloss:0.94195	validation-mlogloss:0.93055
[94]	train-mlogloss:0.93978	validation-mlogloss:0.92827
[95]	train-mlogloss:0.93772	validation-mlogloss:0.92620
[96]	train-mlogloss:0.93570	validation-mlogloss:0.92405
[97]	train-mlogloss:0.93351	validation-mlogloss:0.92194
[98]	train-mlogloss:0.93147	validation-mlogloss:0.91983
[99]	train-mlogloss:0.92936	validation-mlogloss:0.91776
[100]	train-mlogloss:0.92754	validation-mlogloss:0.91596
[101]	train-mlogloss:0.92567	validation-mlogloss:0.91400
[102]	train-mlogloss:0.92372	validation-mlogloss:0.91207
[103]	train-mlogloss:0.92172	validation-mlogloss:0.91001
[104]	train-mlogloss:0.91973	validation-mlogloss:0.90804
[105]	train-mlogloss:0.91790	validation-mlogloss:0.90630
[106]	train-mlogloss:0.91613	validation-mlogloss:0.90428
[107]	train-mlogloss:0.91415	validation-mlogloss:0.90226
[108]	train-mlogloss:0.91222	validation-mlogloss:0.90045
[109]	train-mlogloss:0.91048	validation-mlogloss:0.89855
[110]	train-mlogloss:0.90874	validation-mlogloss:0.89688
[111]	train-mlogloss:0.90700	validation-mlogloss:0.89527
[112]	train-mlogloss:0.90521	validation-mlogloss:0.89344
[113]	train-mlogloss:0.90344	validation-mlogloss:0.89162
[114]	train-mlogloss:0.90157	validation-mlogloss:0.88970
[115]	train-mlogloss:0.89975	validation-mlogloss:0.88788
[116]	train-mlogloss:0.89781	validation-mlogloss:0.88581
[117]	train-mlogloss:0.89627	validation-mlogloss:0.88425
[118]	train-mlogloss:0.89452	validation-mlogloss:0.88245
[119]	train-mlogloss:0.89289	validation-mlogloss:0.88087
[120]	train-mlogloss:0.89132	validation-mlogloss:0.87929
[121]	train-mlogloss:0.88960	validation-mlogloss:0.87748
[122]	train-mlogloss:0.88794	validation-mlogloss:0.87570
[123]	train-mlogloss:0.88629	validation-mlogloss:0.87411
[124]	train-mlogloss:0.88465	validation-mlogloss:0.87238
[125]	train-mlogloss:0.88315	validation-mlogloss:0.87086
[126]	train-mlogloss:0.88154	validation-mlogloss:0.86937
[127]	train-mlogloss:0.87993	validation-mlogloss:0.86765
[128]	train-mlogloss:0.87851	validation-mlogloss:0.86621
[129]	train-mlogloss:0.87695	validation-mlogloss:0.86469
[130]	train-mlogloss:0.87541	validation-mlogloss:0.86295
[131]	train-mlogloss:0.87407	validation-mlogloss:0.86183
[132]	train-mlogloss:0.87241	validation-mlogloss:0.85994
[133]	train-mlogloss:0.87096	validation-mlogloss:0.85850
[134]	train-mlogloss:0.86951	validation-mlogloss:0.85697
[135]	train-mlogloss:0.86819	validation-mlogloss:0.85565
[136]	train-mlogloss:0.86684	validation-mlogloss:0.85426
[137]	train-mlogloss:0.86526	validation-mlogloss:0.85268
[138]	train-mlogloss:0.86379	validation-mlogloss:0.85122
[139]	train-mlogloss:0.86259	validation-mlogloss:0.85012
[140]	train-mlogloss:0.86117	validation-mlogloss:0.84854
[141]	train-mlogloss:0.85985	validation-mlogloss:0.84719
[142]	train-mlogloss:0.85846	validation-mlogloss:0.84578
[143]	train-mlogloss:0.85715	validation-mlogloss:0.84443
[144]	train-mlogloss:0.85575	validation-mlogloss:0.84295
[145]	train-mlogloss:0.85449	validation-mlogloss:0.84173
[146]	train-mlogloss:0.85312	validation-mlogloss:0.84042
[147]	train-mlogloss:0.85174	validation-mlogloss:0.83889
[148]	train-mlogloss:0.85038	validation-mlogloss:0.83737
[149]	train-mlogloss:0.84914	validation-mlogloss:0.83624
[150]	train-mlogloss:0.84795	validation-mlogloss:0.83502
[151]	train-mlogloss:0.84672	validation-mlogloss:0.83373
[152]	train-mlogloss:0.84566	validation-mlogloss:0.83261
[153]	train-mlogloss:0.84430	validation-mlogloss:0.83129
[154]	train-mlogloss:0.84291	validation-mlogloss:0.82999
[155]	train-mlogloss:0.84172	validation-mlogloss:0.82877
[156]	train-mlogloss:0.84047	validation-mlogloss:0.82756
[157]	train-mlogloss:0.83919	validation-mlogloss:0.82629
[158]	train-mlogloss:0.83797	validation-mlogloss:0.82503
[159]	train-mlogloss:0.83664	validation-mlogloss:0.82370
[160]	train-mlogloss:0.83553	validation-mlogloss:0.82265
[161]	train-mlogloss:0.83440	validation-mlogloss:0.82147
[162]	train-mlogloss:0.83324	validation-mlogloss:0.82033
[163]	train-mlogloss:0.83213	validation-mlogloss:0.81921
[164]	train-mlogloss:0.83097	validation-mlogloss:0.81785
[165]	train-mlogloss:0.82979	validation-mlogloss:0.81675
[166]	train-mlogloss:0.82882	validation-mlogloss:0.81585
[167]	train-mlogloss:0.82765	validation-mlogloss:0.81464
[168]	train-mlogloss:0.82669	validation-mlogloss:0.81367
[169]	train-mlogloss:0.82557	validation-mlogloss:0.81269
[170]	train-mlogloss:0.82461	validation-mlogloss:0.81168
[171]	train-mlogloss:0.82360	validation-mlogloss:0.81070
[172]	train-mlogloss:0.82253	validation-mlogloss:0.80970
[173]	train-mlogloss:0.82147	validation-mlogloss:0.80867
[174]	train-mlogloss:0.82049	validation-mlogloss:0.80773
[175]	train-mlogloss:0.81936	validation-mlogloss:0.80665
[176]	train-mlogloss:0.81831	validation-mlogloss:0.80575
[177]	train-mlogloss:0.81725	validation-mlogloss:0.80481
[178]	train-mlogloss:0.81617	validation-mlogloss:0.80378
[179]	train-mlogloss:0.81503	validation-mlogloss:0.80266
[180]	train-mlogloss:0.81400	validation-mlogloss:0.80175
[181]	train-mlogloss:0.81301	validation-mlogloss:0.80064
[182]	train-mlogloss:0.81204	validation-mlogloss:0.79983
[183]	train-mlogloss:0.81112	validation-mlogloss:0.79892
[184]	train-mlogloss:0.81007	validation-mlogloss:0.79794
[185]	train-mlogloss:0.80900	validation-mlogloss:0.79695
[186]	train-mlogloss:0.80791	validation-mlogloss:0.79594
[187]	train-mlogloss:0.80684	validation-mlogloss:0.79491
[188]	train-mlogloss:0.80579	validation-mlogloss:0.79398
[189]	train-mlogloss:0.80478	validation-mlogloss:0.79290
[190]	train-mlogloss:0.80392	validation-mlogloss:0.79210
[191]	train-mlogloss:0.80306	validation-mlogloss:0.79132
[192]	train-mlogloss:0.80209	validation-mlogloss:0.79044
[193]	train-mlogloss:0.80121	validation-mlogloss:0.78959
[194]	train-mlogloss:0.80025	validation-mlogloss:0.78865
[195]	train-mlogloss:0.79938	validation-mlogloss:0.78779
[196]	train-mlogloss:0.79860	validation-mlogloss:0.78704
[197]	train-mlogloss:0.79777	validation-mlogloss:0.78627
[198]	train-mlogloss:0.79688	validation-mlogloss:0.78542
[199]	train-mlogloss:0.79603	validation-mlogloss:0.78460
[200]	train-mlogloss:0.79518	validation-mlogloss:0.78384
[201]	train-mlogloss:0.79425	validation-mlogloss:0.78285
[202]	train-mlogloss:0.79328	validation-mlogloss:0.78195
[203]	train-mlogloss:0.79231	validation-mlogloss:0.78099
[204]	train-mlogloss:0.79139	validation-mlogloss:0.78009
[205]	train-mlogloss:0.79069	validation-mlogloss:0.77944
[206]	train-mlogloss:0.78979	validation-mlogloss:0.77856
[207]	train-mlogloss:0.78901	validation-mlogloss:0.77780
[208]	train-mlogloss:0.78817	validation-mlogloss:0.77697
[209]	train-mlogloss:0.78726	validation-mlogloss:0.77609
[210]	train-mlogloss:0.78636	validation-mlogloss:0.77520
[211]	train-mlogloss:0.78563	validation-mlogloss:0.77457
[212]	train-mlogloss:0.78477	validation-mlogloss:0.77365
[213]	train-mlogloss:0.78387	validation-mlogloss:0.77286
[214]	train-mlogloss:0.78305	validation-mlogloss:0.77208
[215]	train-mlogloss:0.78224	validation-mlogloss:0.77132
[216]	train-mlogloss:0.78153	validation-mlogloss:0.77068
[217]	train-mlogloss:0.78094	validation-mlogloss:0.77019
[218]	train-mlogloss:0.78011	validation-mlogloss:0.76941
[219]	train-mlogloss:0.77944	validation-mlogloss:0.76880
[220]	train-mlogloss:0.77874	validation-mlogloss:0.76815
[221]	train-mlogloss:0.77795	validation-mlogloss:0.76746
[222]	train-mlogloss:0.77735	validation-mlogloss:0.76696
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[263]	train-mlogloss:0.75028	validation-mlogloss:0.74234
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[266]	train-mlogloss:0.74847	validation-mlogloss:0.74077
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[272]	train-mlogloss:0.74512	validation-mlogloss:0.73802
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[275]	train-mlogloss:0.74348	validation-mlogloss:0.73651
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[278]	train-mlogloss:0.74196	validation-mlogloss:0.73513
[279]	train-mlogloss:0.74150	validation-mlogloss:0.73474
[280]	train-mlogloss:0.74101	validation-mlogloss:0.73431
[281]	train-mlogloss:0.74052	validation-mlogloss:0.73378
[282]	train-mlogloss:0.73998	validation-mlogloss:0.73330
[283]	train-mlogloss:0.73947	validation-mlogloss:0.73279
[284]	train-mlogloss:0.73899	validation-mlogloss:0.73243
[285]	train-mlogloss:0.73860	validation-mlogloss:0.73216
[286]	train-mlogloss:0.73811	validation-mlogloss:0.73180
[287]	train-mlogloss:0.73771	validation-mlogloss:0.73148
[288]	train-mlogloss:0.73717	validation-mlogloss:0.73111
[289]	train-mlogloss:0.73658	validation-mlogloss:0.73061
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[291]	train-mlogloss:0.73556	validation-mlogloss:0.72970
[292]	train-mlogloss:0.73519	validation-mlogloss:0.72939
[293]	train-mlogloss:0.73472	validation-mlogloss:0.72897
[294]	train-mlogloss:0.73423	validation-mlogloss:0.72853
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[297]	train-mlogloss:0.73288	validation-mlogloss:0.72754
[298]	train-mlogloss:0.73248	validation-mlogloss:0.72719
[299]	train-mlogloss:0.73205	validation-mlogloss:0.72690
[300]	train-mlogloss:0.73157	validation-mlogloss:0.72667
[301]	train-mlogloss:0.73113	validation-mlogloss:0.72635
[302]	train-mlogloss:0.73077	validation-mlogloss:0.72609
[303]	train-mlogloss:0.73034	validation-mlogloss:0.72571
[304]	train-mlogloss:0.72987	validation-mlogloss:0.72528
[305]	train-mlogloss:0.72948	validation-mlogloss:0.72497
[306]	train-mlogloss:0.72907	validation-mlogloss:0.72467
[307]	train-mlogloss:0.72870	validation-mlogloss:0.72438
[308]	train-mlogloss:0.72822	validation-mlogloss:0.72397
[309]	train-mlogloss:0.72779	validation-mlogloss:0.72366
[310]	train-mlogloss:0.72740	validation-mlogloss:0.72333
[311]	train-mlogloss:0.72697	validation-mlogloss:0.72292
[312]	train-mlogloss:0.72654	validation-mlogloss:0.72260
[313]	train-mlogloss:0.72622	validation-mlogloss:0.72226
[314]	train-mlogloss:0.72575	validation-mlogloss:0.72187
[315]	train-mlogloss:0.72530	validation-mlogloss:0.72153
[316]	train-mlogloss:0.72484	validation-mlogloss:0.72118
[317]	train-mlogloss:0.72448	validation-mlogloss:0.72081
[318]	train-mlogloss:0.72401	validation-mlogloss:0.72044
[319]	train-mlogloss:0.72356	validation-mlogloss:0.72011
[320]	train-mlogloss:0.72314	validation-mlogloss:0.71974
[321]	train-mlogloss:0.72277	validation-mlogloss:0.71945
[322]	train-mlogloss:0.72246	validation-mlogloss:0.71914
[323]	train-mlogloss:0.72203	validation-mlogloss:0.71882
[324]	train-mlogloss:0.72164	validation-mlogloss:0.71844
[325]	train-mlogloss:0.72117	validation-mlogloss:0.71812
[326]	train-mlogloss:0.72074	validation-mlogloss:0.71773
[327]	train-mlogloss:0.72041	validation-mlogloss:0.71744
[328]	train-mlogloss:0.71999	validation-mlogloss:0.71716
[329]	train-mlogloss:0.71966	validation-mlogloss:0.71682
[330]	train-mlogloss:0.71939	validation-mlogloss:0.71658
[331]	train-mlogloss:0.71905	validation-mlogloss:0.71633
[332]	train-mlogloss:0.71866	validation-mlogloss:0.71606
[333]	train-mlogloss:0.71828	validation-mlogloss:0.71570
[334]	train-mlogloss:0.71793	validation-mlogloss:0.71543
[335]	train-mlogloss:0.71757	validation-mlogloss:0.71518
[336]	train-mlogloss:0.71721	validation-mlogloss:0.71492
[337]	train-mlogloss:0.71692	validation-mlogloss:0.71472
[338]	train-mlogloss:0.71654	validation-mlogloss:0.71446
[339]	train-mlogloss:0.71610	validation-mlogloss:0.71423
[340]	train-mlogloss:0.71572	validation-mlogloss:0.71391
[341]	train-mlogloss:0.71536	validation-mlogloss:0.71370
[342]	train-mlogloss:0.71505	validation-mlogloss:0.71341
[343]	train-mlogloss:0.71477	validation-mlogloss:0.71322
[344]	train-mlogloss:0.71449	validation-mlogloss:0.71290
[345]	train-mlogloss:0.71411	validation-mlogloss:0.71262
[346]	train-mlogloss:0.71372	validation-mlogloss:0.71238
[347]	train-mlogloss:0.71331	validation-mlogloss:0.71211
[348]	train-mlogloss:0.71303	validation-mlogloss:0.71183
[349]	train-mlogloss:0.71272	validation-mlogloss:0.71153
[350]	train-mlogloss:0.71232	validation-mlogloss:0.71122
[351]	train-mlogloss:0.71193	validation-mlogloss:0.71089
[352]	train-mlogloss:0.71158	validation-mlogloss:0.71056
[353]	train-mlogloss:0.71114	validation-mlogloss:0.71023
[354]	train-mlogloss:0.71077	validation-mlogloss:0.70990
[355]	train-mlogloss:0.71050	validation-mlogloss:0.70965
[356]	train-mlogloss:0.71026	validation-mlogloss:0.70942
[357]	train-mlogloss:0.70983	validation-mlogloss:0.70909
[358]	train-mlogloss:0.70949	validation-mlogloss:0.70883
[359]	train-mlogloss:0.70921	validation-mlogloss:0.70864
[360]	train-mlogloss:0.70878	validation-mlogloss:0.70835
[361]	train-mlogloss:0.70845	validation-mlogloss:0.70814
[362]	train-mlogloss:0.70815	validation-mlogloss:0.70784
[363]	train-mlogloss:0.70784	validation-mlogloss:0.70755
[364]	train-mlogloss:0.70763	validation-mlogloss:0.70744
[365]	train-mlogloss:0.70731	validation-mlogloss:0.70720
[366]	train-mlogloss:0.70694	validation-mlogloss:0.70683
[367]	train-mlogloss:0.70667	validation-mlogloss:0.70660
[368]	train-mlogloss:0.70638	validation-mlogloss:0.70635
[369]	train-mlogloss:0.70610	validation-mlogloss:0.70611
[370]	train-mlogloss:0.70587	validation-mlogloss:0.70597
[371]	train-mlogloss:0.70558	validation-mlogloss:0.70577
[372]	train-mlogloss:0.70525	validation-mlogloss:0.70557
[373]	train-mlogloss:0.70493	validation-mlogloss:0.70531
[374]	train-mlogloss:0.70454	validation-mlogloss:0.70502
[375]	train-mlogloss:0.70435	validation-mlogloss:0.70490
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[0 1 1 ... 0 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.13 [%]
Global accuracy score (test) = 72.1 [%]
Global F1 score (train) = 73.02 [%]
Global F1 score (test) = 72.36 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.47      0.53       400
MODERATE-INTENSITY       0.59      0.85      0.69       400
         SEDENTARY       0.84      0.83      0.84       400
VIGOROUS-INTENSITY       0.94      0.74      0.83       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.72      1545
      weighted avg       0.74      0.72      0.72      1545


Accuracy capturado en la ejecución 19: 72.1 [%]
F1-score capturado en la ejecución 19: 72.36 [%]

=== EJECUCIÓN 20 ===

--- TRAIN (ejecución 20) ---

--- TEST (ejecución 20) ---
2025-11-04 10:38:30.208744: 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 10:38:30.220463: 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 00:00:1762249110.233795 1057652 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249110.237898 1057652 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249110.247729 1057652 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249110.247746 1057652 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249110.247747 1057652 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249110.247748 1057652 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:38:30.250889: 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:1.37686	validation-mlogloss:1.37626
[1]	train-mlogloss:1.36768	validation-mlogloss:1.36675
[2]	train-mlogloss:1.35842	validation-mlogloss:1.35688
[3]	train-mlogloss:1.34978	validation-mlogloss:1.34791
[4]	train-mlogloss:1.34078	validation-mlogloss:1.33862
[5]	train-mlogloss:1.33246	validation-mlogloss:1.32998
[6]	train-mlogloss:1.32408	validation-mlogloss:1.32180
[7]	train-mlogloss:1.31563	validation-mlogloss:1.31310
[8]	train-mlogloss:1.30727	validation-mlogloss:1.30460
[9]	train-mlogloss:1.29917	validation-mlogloss:1.29625
[10]	train-mlogloss:1.29161	validation-mlogloss:1.28862
[11]	train-mlogloss:1.28366	validation-mlogloss:1.28057
[12]	train-mlogloss:1.27594	validation-mlogloss:1.27285
[13]	train-mlogloss:1.26872	validation-mlogloss:1.26556
[14]	train-mlogloss:1.26143	validation-mlogloss:1.25796
[15]	train-mlogloss:1.25456	validation-mlogloss:1.25090
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[315]	train-mlogloss:0.72546	validation-mlogloss:0.73193
[316]	train-mlogloss:0.72509	validation-mlogloss:0.73161
[317]	train-mlogloss:0.72470	validation-mlogloss:0.73134
[318]	train-mlogloss:0.72426	validation-mlogloss:0.73097
[319]	train-mlogloss:0.72392	validation-mlogloss:0.73071
[320]	train-mlogloss:0.72356	validation-mlogloss:0.73041
[321]	train-mlogloss:0.72317	validation-mlogloss:0.73010
[322]	train-mlogloss:0.72277	validation-mlogloss:0.72982
[323]	train-mlogloss:0.72242	validation-mlogloss:0.72954
[324]	train-mlogloss:0.72200	validation-mlogloss:0.72923
[325]	train-mlogloss:0.72162	validation-mlogloss:0.72891
[326]	train-mlogloss:0.72121	validation-mlogloss:0.72865
[327]	train-mlogloss:0.72084	validation-mlogloss:0.72830
[328]	train-mlogloss:0.72041	validation-mlogloss:0.72794
[329]	train-mlogloss:0.72002	validation-mlogloss:0.72765
[330]	train-mlogloss:0.71954	validation-mlogloss:0.72739
[331]	train-mlogloss:0.71912	validation-mlogloss:0.72710
[332]	train-mlogloss:0.71881	validation-mlogloss:0.72679
[333]	train-mlogloss:0.71850	validation-mlogloss:0.72652
[334]	train-mlogloss:0.71806	validation-mlogloss:0.72617
[335]	train-mlogloss:0.71767	validation-mlogloss:0.72581
[336]	train-mlogloss:0.71719	validation-mlogloss:0.72537
[337]	train-mlogloss:0.71677	validation-mlogloss:0.72515
[338]	train-mlogloss:0.71640	validation-mlogloss:0.72487
[339]	train-mlogloss:0.71606	validation-mlogloss:0.72450
[340]	train-mlogloss:0.71572	validation-mlogloss:0.72423
[341]	train-mlogloss:0.71534	validation-mlogloss:0.72391
[342]	train-mlogloss:0.71504	validation-mlogloss:0.72356
[343]	train-mlogloss:0.71474	validation-mlogloss:0.72334
[344]	train-mlogloss:0.71437	validation-mlogloss:0.72302
[345]	train-mlogloss:0.71396	validation-mlogloss:0.72270
[346]	train-mlogloss:0.71363	validation-mlogloss:0.72247
[347]	train-mlogloss:0.71330	validation-mlogloss:0.72227
[348]	train-mlogloss:0.71295	validation-mlogloss:0.72192
[349]	train-mlogloss:0.71270	validation-mlogloss:0.72167
[350]	train-mlogloss:0.71236	validation-mlogloss:0.72144
[351]	train-mlogloss:0.71203	validation-mlogloss:0.72124
[352]	train-mlogloss:0.71163	validation-mlogloss:0.72094
[353]	train-mlogloss:0.71142	validation-mlogloss:0.72073
[354]	train-mlogloss:0.71111	validation-mlogloss:0.72052
[355]	train-mlogloss:0.71079	validation-mlogloss:0.72029
[356]	train-mlogloss:0.71049	validation-mlogloss:0.72006
[357]	train-mlogloss:0.71016	validation-mlogloss:0.71973
[358]	train-mlogloss:0.70978	validation-mlogloss:0.71949
[359]	train-mlogloss:0.70947	validation-mlogloss:0.71923
[360]	train-mlogloss:0.70914	validation-mlogloss:0.71897
[361]	train-mlogloss:0.70881	validation-mlogloss:0.71870
[362]	train-mlogloss:0.70840	validation-mlogloss:0.71853
[363]	train-mlogloss:0.70817	validation-mlogloss:0.71832
[364]	train-mlogloss:0.70785	validation-mlogloss:0.71806
[365]	train-mlogloss:0.70769	validation-mlogloss:0.71795
[366]	train-mlogloss:0.70741	validation-mlogloss:0.71778
[367]	train-mlogloss:0.70706	validation-mlogloss:0.71755
[368]	train-mlogloss:0.70680	validation-mlogloss:0.71735
[369]	train-mlogloss:0.70651	validation-mlogloss:0.71708
[370]	train-mlogloss:0.70613	validation-mlogloss:0.71676
[371]	train-mlogloss:0.70580	validation-mlogloss:0.71646
[372]	train-mlogloss:0.70551	validation-mlogloss:0.71620
[373]	train-mlogloss:0.70522	validation-mlogloss:0.71596
[374]	train-mlogloss:0.70498	validation-mlogloss:0.71581
[375]	train-mlogloss:0.70466	validation-mlogloss:0.71548
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[0 1 0 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 72.9 [%]
Global accuracy score (test) = 71.52 [%]
Global F1 score (train) = 72.66 [%]
Global F1 score (test) = 71.58 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.44      0.52       400
MODERATE-INTENSITY       0.57      0.86      0.69       400
         SEDENTARY       0.85      0.84      0.84       400
VIGOROUS-INTENSITY       0.94      0.72      0.82       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.72      1545
      weighted avg       0.74      0.72      0.71      1545


Accuracy capturado en la ejecución 20: 71.52 [%]
F1-score capturado en la ejecución 20: 71.58 [%]

=== EJECUCIÓN 21 ===

--- TRAIN (ejecución 21) ---

--- TEST (ejecución 21) ---
2025-11-04 10:38:46.105072: 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 10:38:46.116571: 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 00:00:1762249126.130046 1057947 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249126.135947 1057947 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249126.148777 1057947 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249126.148795 1057947 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249126.148797 1057947 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249126.148798 1057947 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:38:46.152142: 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:1.37670	validation-mlogloss:1.37621
[1]	train-mlogloss:1.36705	validation-mlogloss:1.36608
[2]	train-mlogloss:1.35802	validation-mlogloss:1.35674
[3]	train-mlogloss:1.34893	validation-mlogloss:1.34708
[4]	train-mlogloss:1.33990	validation-mlogloss:1.33764
[5]	train-mlogloss:1.33146	validation-mlogloss:1.32886
[6]	train-mlogloss:1.32299	validation-mlogloss:1.32002
[7]	train-mlogloss:1.31473	validation-mlogloss:1.31134
[8]	train-mlogloss:1.30665	validation-mlogloss:1.30300
[9]	train-mlogloss:1.29853	validation-mlogloss:1.29451
[10]	train-mlogloss:1.29035	validation-mlogloss:1.28620
[11]	train-mlogloss:1.28308	validation-mlogloss:1.27887
[12]	train-mlogloss:1.27572	validation-mlogloss:1.27102
[13]	train-mlogloss:1.26829	validation-mlogloss:1.26311
[14]	train-mlogloss:1.26142	validation-mlogloss:1.25599
[15]	train-mlogloss:1.25389	validation-mlogloss:1.24829
[16]	train-mlogloss:1.24667	validation-mlogloss:1.24107
[17]	train-mlogloss:1.23964	validation-mlogloss:1.23401
[18]	train-mlogloss:1.23295	validation-mlogloss:1.22686
[19]	train-mlogloss:1.22675	validation-mlogloss:1.22040
[20]	train-mlogloss:1.22017	validation-mlogloss:1.21351
[21]	train-mlogloss:1.21360	validation-mlogloss:1.20673
[22]	train-mlogloss:1.20740	validation-mlogloss:1.20085
[23]	train-mlogloss:1.20095	validation-mlogloss:1.19432
[24]	train-mlogloss:1.19515	validation-mlogloss:1.18849
[25]	train-mlogloss:1.18933	validation-mlogloss:1.18273
[26]	train-mlogloss:1.18350	validation-mlogloss:1.17672
[27]	train-mlogloss:1.17757	validation-mlogloss:1.17054
[28]	train-mlogloss:1.17181	validation-mlogloss:1.16457
[29]	train-mlogloss:1.16625	validation-mlogloss:1.15907
[30]	train-mlogloss:1.16105	validation-mlogloss:1.15384
[31]	train-mlogloss:1.15550	validation-mlogloss:1.14815
[32]	train-mlogloss:1.15052	validation-mlogloss:1.14352
[33]	train-mlogloss:1.14541	validation-mlogloss:1.13823
[34]	train-mlogloss:1.14072	validation-mlogloss:1.13364
[35]	train-mlogloss:1.13543	validation-mlogloss:1.12831
[36]	train-mlogloss:1.13030	validation-mlogloss:1.12302
[37]	train-mlogloss:1.12530	validation-mlogloss:1.11788
[38]	train-mlogloss:1.12052	validation-mlogloss:1.11308
[39]	train-mlogloss:1.11578	validation-mlogloss:1.10831
[40]	train-mlogloss:1.11118	validation-mlogloss:1.10373
[41]	train-mlogloss:1.10658	validation-mlogloss:1.09909
[42]	train-mlogloss:1.10221	validation-mlogloss:1.09488
[43]	train-mlogloss:1.09753	validation-mlogloss:1.09035
[44]	train-mlogloss:1.09314	validation-mlogloss:1.08596
[45]	train-mlogloss:1.08884	validation-mlogloss:1.08166
[46]	train-mlogloss:1.08452	validation-mlogloss:1.07704
[47]	train-mlogloss:1.08048	validation-mlogloss:1.07279
[48]	train-mlogloss:1.07641	validation-mlogloss:1.06871
[49]	train-mlogloss:1.07245	validation-mlogloss:1.06454
[50]	train-mlogloss:1.06847	validation-mlogloss:1.06031
[51]	train-mlogloss:1.06456	validation-mlogloss:1.05626
[52]	train-mlogloss:1.06081	validation-mlogloss:1.05247
[53]	train-mlogloss:1.05719	validation-mlogloss:1.04868
[54]	train-mlogloss:1.05348	validation-mlogloss:1.04505
[55]	train-mlogloss:1.04959	validation-mlogloss:1.04090
[56]	train-mlogloss:1.04628	validation-mlogloss:1.03749
[57]	train-mlogloss:1.04278	validation-mlogloss:1.03381
[58]	train-mlogloss:1.03911	validation-mlogloss:1.03013
[59]	train-mlogloss:1.03557	validation-mlogloss:1.02642
[60]	train-mlogloss:1.03207	validation-mlogloss:1.02297
[61]	train-mlogloss:1.02872	validation-mlogloss:1.01945
[62]	train-mlogloss:1.02538	validation-mlogloss:1.01592
[63]	train-mlogloss:1.02229	validation-mlogloss:1.01290
[64]	train-mlogloss:1.01909	validation-mlogloss:1.00956
[65]	train-mlogloss:1.01592	validation-mlogloss:1.00633
[66]	train-mlogloss:1.01293	validation-mlogloss:1.00340
[67]	train-mlogloss:1.00990	validation-mlogloss:1.00020
[68]	train-mlogloss:1.00685	validation-mlogloss:0.99723
[69]	train-mlogloss:1.00381	validation-mlogloss:0.99429
[70]	train-mlogloss:1.00066	validation-mlogloss:0.99101
[71]	train-mlogloss:0.99795	validation-mlogloss:0.98828
[72]	train-mlogloss:0.99505	validation-mlogloss:0.98518
[73]	train-mlogloss:0.99240	validation-mlogloss:0.98252
[74]	train-mlogloss:0.98966	validation-mlogloss:0.97969
[75]	train-mlogloss:0.98688	validation-mlogloss:0.97676
[76]	train-mlogloss:0.98414	validation-mlogloss:0.97394
[77]	train-mlogloss:0.98143	validation-mlogloss:0.97129
[78]	train-mlogloss:0.97867	validation-mlogloss:0.96851
[79]	train-mlogloss:0.97616	validation-mlogloss:0.96594
[80]	train-mlogloss:0.97357	validation-mlogloss:0.96326
[81]	train-mlogloss:0.97086	validation-mlogloss:0.96043
[82]	train-mlogloss:0.96825	validation-mlogloss:0.95759
[83]	train-mlogloss:0.96573	validation-mlogloss:0.95497
[84]	train-mlogloss:0.96324	validation-mlogloss:0.95249
[85]	train-mlogloss:0.96093	validation-mlogloss:0.95006
[86]	train-mlogloss:0.95843	validation-mlogloss:0.94754
[87]	train-mlogloss:0.95602	validation-mlogloss:0.94505
[88]	train-mlogloss:0.95381	validation-mlogloss:0.94273
[89]	train-mlogloss:0.95151	validation-mlogloss:0.94055
[90]	train-mlogloss:0.94923	validation-mlogloss:0.93819
[91]	train-mlogloss:0.94675	validation-mlogloss:0.93571
[92]	train-mlogloss:0.94451	validation-mlogloss:0.93362
[93]	train-mlogloss:0.94233	validation-mlogloss:0.93140
[94]	train-mlogloss:0.94015	validation-mlogloss:0.92928
[95]	train-mlogloss:0.93786	validation-mlogloss:0.92689
[96]	train-mlogloss:0.93589	validation-mlogloss:0.92496
[97]	train-mlogloss:0.93391	validation-mlogloss:0.92307
[98]	train-mlogloss:0.93183	validation-mlogloss:0.92088
[99]	train-mlogloss:0.92974	validation-mlogloss:0.91881
[100]	train-mlogloss:0.92777	validation-mlogloss:0.91677
[101]	train-mlogloss:0.92561	validation-mlogloss:0.91447
[102]	train-mlogloss:0.92361	validation-mlogloss:0.91241
[103]	train-mlogloss:0.92163	validation-mlogloss:0.91044
[104]	train-mlogloss:0.91958	validation-mlogloss:0.90841
[105]	train-mlogloss:0.91767	validation-mlogloss:0.90650
[106]	train-mlogloss:0.91598	validation-mlogloss:0.90494
[107]	train-mlogloss:0.91434	validation-mlogloss:0.90338
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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}
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Training a non-convolutional model.
Loaded model from disk.
(1545, 91)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[0 1 0 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.22 [%]
Global accuracy score (test) = 71.59 [%]
Global F1 score (train) = 73.13 [%]
Global F1 score (test) = 71.81 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.60      0.45      0.51       400
MODERATE-INTENSITY       0.58      0.85      0.69       400
         SEDENTARY       0.84      0.83      0.84       400
VIGOROUS-INTENSITY       0.97      0.73      0.83       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.72      1545
      weighted avg       0.74      0.72      0.71      1545


Accuracy capturado en la ejecución 21: 71.59 [%]
F1-score capturado en la ejecución 21: 71.81 [%]

=== EJECUCIÓN 22 ===

--- TRAIN (ejecución 22) ---

--- TEST (ejecución 22) ---
2025-11-04 10:39:02.162926: 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 10:39:02.174009: 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 00:00:1762249142.187018 1058249 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249142.191105 1058249 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249142.200796 1058249 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249142.200813 1058249 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249142.200814 1058249 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249142.200815 1058249 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:39:02.203901: 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:1.37673	validation-mlogloss:1.37618
[1]	train-mlogloss:1.36723	validation-mlogloss:1.36624
[2]	train-mlogloss:1.35783	validation-mlogloss:1.35643
[3]	train-mlogloss:1.34889	validation-mlogloss:1.34725
[4]	train-mlogloss:1.33984	validation-mlogloss:1.33774
[5]	train-mlogloss:1.33107	validation-mlogloss:1.32851
[6]	train-mlogloss:1.32253	validation-mlogloss:1.31954
[7]	train-mlogloss:1.31402	validation-mlogloss:1.31090
[8]	train-mlogloss:1.30579	validation-mlogloss:1.30223
[9]	train-mlogloss:1.29781	validation-mlogloss:1.29393
[10]	train-mlogloss:1.28990	validation-mlogloss:1.28558
[11]	train-mlogloss:1.28186	validation-mlogloss:1.27745
[12]	train-mlogloss:1.27459	validation-mlogloss:1.27031
[13]	train-mlogloss:1.26719	validation-mlogloss:1.26239
[14]	train-mlogloss:1.26008	validation-mlogloss:1.25496
[15]	train-mlogloss:1.25280	validation-mlogloss:1.24725
[16]	train-mlogloss:1.24602	validation-mlogloss:1.24039
[17]	train-mlogloss:1.23921	validation-mlogloss:1.23305
[18]	train-mlogloss:1.23241	validation-mlogloss:1.22579
[19]	train-mlogloss:1.22562	validation-mlogloss:1.21853
[20]	train-mlogloss:1.21920	validation-mlogloss:1.21184
[21]	train-mlogloss:1.21252	validation-mlogloss:1.20495
[22]	train-mlogloss:1.20609	validation-mlogloss:1.19822
[23]	train-mlogloss:1.19970	validation-mlogloss:1.19149
[24]	train-mlogloss:1.19349	validation-mlogloss:1.18489
[25]	train-mlogloss:1.18779	validation-mlogloss:1.17905
[26]	train-mlogloss:1.18204	validation-mlogloss:1.17316
[27]	train-mlogloss:1.17636	validation-mlogloss:1.16712
[28]	train-mlogloss:1.17074	validation-mlogloss:1.16143
[29]	train-mlogloss:1.16513	validation-mlogloss:1.15565
[30]	train-mlogloss:1.15976	validation-mlogloss:1.15021
[31]	train-mlogloss:1.15423	validation-mlogloss:1.14449
[32]	train-mlogloss:1.14904	validation-mlogloss:1.13948
[33]	train-mlogloss:1.14381	validation-mlogloss:1.13395
[34]	train-mlogloss:1.13836	validation-mlogloss:1.12838
[35]	train-mlogloss:1.13321	validation-mlogloss:1.12296
[36]	train-mlogloss:1.12852	validation-mlogloss:1.11838
[37]	train-mlogloss:1.12371	validation-mlogloss:1.11347
[38]	train-mlogloss:1.11870	validation-mlogloss:1.10817
[39]	train-mlogloss:1.11397	validation-mlogloss:1.10345
[40]	train-mlogloss:1.10933	validation-mlogloss:1.09860
[41]	train-mlogloss:1.10469	validation-mlogloss:1.09370
[42]	train-mlogloss:1.10031	validation-mlogloss:1.08925
[43]	train-mlogloss:1.09593	validation-mlogloss:1.08488
[44]	train-mlogloss:1.09167	validation-mlogloss:1.08044
[45]	train-mlogloss:1.08736	validation-mlogloss:1.07599
[46]	train-mlogloss:1.08315	validation-mlogloss:1.07171
[47]	train-mlogloss:1.07924	validation-mlogloss:1.06779
[48]	train-mlogloss:1.07506	validation-mlogloss:1.06351
[49]	train-mlogloss:1.07080	validation-mlogloss:1.05890
[50]	train-mlogloss:1.06680	validation-mlogloss:1.05469
[51]	train-mlogloss:1.06275	validation-mlogloss:1.05046
[52]	train-mlogloss:1.05865	validation-mlogloss:1.04630
[53]	train-mlogloss:1.05492	validation-mlogloss:1.04241
[54]	train-mlogloss:1.05113	validation-mlogloss:1.03854
[55]	train-mlogloss:1.04741	validation-mlogloss:1.03454
[56]	train-mlogloss:1.04374	validation-mlogloss:1.03067
[57]	train-mlogloss:1.04034	validation-mlogloss:1.02734
[58]	train-mlogloss:1.03714	validation-mlogloss:1.02427
[59]	train-mlogloss:1.03370	validation-mlogloss:1.02081
[60]	train-mlogloss:1.03037	validation-mlogloss:1.01724
[61]	train-mlogloss:1.02691	validation-mlogloss:1.01367
[62]	train-mlogloss:1.02359	validation-mlogloss:1.01023
[63]	train-mlogloss:1.02025	validation-mlogloss:1.00662
[64]	train-mlogloss:1.01703	validation-mlogloss:1.00310
[65]	train-mlogloss:1.01374	validation-mlogloss:0.99967
[66]	train-mlogloss:1.01063	validation-mlogloss:0.99651
[67]	train-mlogloss:1.00751	validation-mlogloss:0.99322
[68]	train-mlogloss:1.00436	validation-mlogloss:0.98994
[69]	train-mlogloss:1.00119	validation-mlogloss:0.98686
[70]	train-mlogloss:0.99827	validation-mlogloss:0.98401
[71]	train-mlogloss:0.99520	validation-mlogloss:0.98109
[72]	train-mlogloss:0.99218	validation-mlogloss:0.97812
[73]	train-mlogloss:0.98915	validation-mlogloss:0.97501
[74]	train-mlogloss:0.98656	validation-mlogloss:0.97228
[75]	train-mlogloss:0.98368	validation-mlogloss:0.96926
[76]	train-mlogloss:0.98098	validation-mlogloss:0.96661
[77]	train-mlogloss:0.97851	validation-mlogloss:0.96419
[78]	train-mlogloss:0.97592	validation-mlogloss:0.96145
[79]	train-mlogloss:0.97326	validation-mlogloss:0.95856
[80]	train-mlogloss:0.97049	validation-mlogloss:0.95574
[81]	train-mlogloss:0.96775	validation-mlogloss:0.95285
[82]	train-mlogloss:0.96521	validation-mlogloss:0.95040
[83]	train-mlogloss:0.96278	validation-mlogloss:0.94794
[84]	train-mlogloss:0.96036	validation-mlogloss:0.94524
[85]	train-mlogloss:0.95789	validation-mlogloss:0.94290
[86]	train-mlogloss:0.95533	validation-mlogloss:0.94015
[87]	train-mlogloss:0.95284	validation-mlogloss:0.93759
[88]	train-mlogloss:0.95044	validation-mlogloss:0.93508
[89]	train-mlogloss:0.94813	validation-mlogloss:0.93284
[90]	train-mlogloss:0.94592	validation-mlogloss:0.93057
[91]	train-mlogloss:0.94382	validation-mlogloss:0.92862
[92]	train-mlogloss:0.94146	validation-mlogloss:0.92607
[93]	train-mlogloss:0.93941	validation-mlogloss:0.92411
[94]	train-mlogloss:0.93736	validation-mlogloss:0.92198
[95]	train-mlogloss:0.93513	validation-mlogloss:0.91963
[96]	train-mlogloss:0.93274	validation-mlogloss:0.91713
[97]	train-mlogloss:0.93059	validation-mlogloss:0.91501
[98]	train-mlogloss:0.92857	validation-mlogloss:0.91281
[99]	train-mlogloss:0.92629	validation-mlogloss:0.91061
[100]	train-mlogloss:0.92413	validation-mlogloss:0.90847
[101]	train-mlogloss:0.92213	validation-mlogloss:0.90630
[102]	train-mlogloss:0.92025	validation-mlogloss:0.90435
[103]	train-mlogloss:0.91815	validation-mlogloss:0.90220
[104]	train-mlogloss:0.91639	validation-mlogloss:0.90058
[105]	train-mlogloss:0.91439	validation-mlogloss:0.89840
[106]	train-mlogloss:0.91236	validation-mlogloss:0.89627
[107]	train-mlogloss:0.91027	validation-mlogloss:0.89414
[108]	train-mlogloss:0.90843	validation-mlogloss:0.89223
[109]	train-mlogloss:0.90653	validation-mlogloss:0.89028
[110]	train-mlogloss:0.90478	validation-mlogloss:0.88850
[111]	train-mlogloss:0.90304	validation-mlogloss:0.88668
[112]	train-mlogloss:0.90111	validation-mlogloss:0.88473
[113]	train-mlogloss:0.89944	validation-mlogloss:0.88308
[114]	train-mlogloss:0.89780	validation-mlogloss:0.88127
[115]	train-mlogloss:0.89600	validation-mlogloss:0.87932
[116]	train-mlogloss:0.89418	validation-mlogloss:0.87747
[117]	train-mlogloss:0.89248	validation-mlogloss:0.87590
[118]	train-mlogloss:0.89091	validation-mlogloss:0.87428
[119]	train-mlogloss:0.88944	validation-mlogloss:0.87286
[120]	train-mlogloss:0.88765	validation-mlogloss:0.87109
[121]	train-mlogloss:0.88602	validation-mlogloss:0.86943
[122]	train-mlogloss:0.88443	validation-mlogloss:0.86763
[123]	train-mlogloss:0.88288	validation-mlogloss:0.86602
[124]	train-mlogloss:0.88140	validation-mlogloss:0.86460
[125]	train-mlogloss:0.87996	validation-mlogloss:0.86342
[126]	train-mlogloss:0.87841	validation-mlogloss:0.86185
[127]	train-mlogloss:0.87684	validation-mlogloss:0.86025
[128]	train-mlogloss:0.87525	validation-mlogloss:0.85854
[129]	train-mlogloss:0.87350	validation-mlogloss:0.85686
[130]	train-mlogloss:0.87193	validation-mlogloss:0.85528
[131]	train-mlogloss:0.87037	validation-mlogloss:0.85375
[132]	train-mlogloss:0.86889	validation-mlogloss:0.85232
[133]	train-mlogloss:0.86744	validation-mlogloss:0.85088
[134]	train-mlogloss:0.86592	validation-mlogloss:0.84925
[135]	train-mlogloss:0.86434	validation-mlogloss:0.84763
[136]	train-mlogloss:0.86283	validation-mlogloss:0.84614
[137]	train-mlogloss:0.86129	validation-mlogloss:0.84454
[138]	train-mlogloss:0.85983	validation-mlogloss:0.84310
[139]	train-mlogloss:0.85843	validation-mlogloss:0.84152
[140]	train-mlogloss:0.85703	validation-mlogloss:0.84006
[141]	train-mlogloss:0.85570	validation-mlogloss:0.83859
[142]	train-mlogloss:0.85431	validation-mlogloss:0.83718
[143]	train-mlogloss:0.85288	validation-mlogloss:0.83577
[144]	train-mlogloss:0.85151	validation-mlogloss:0.83438
[145]	train-mlogloss:0.85007	validation-mlogloss:0.83283
[146]	train-mlogloss:0.84890	validation-mlogloss:0.83178
[147]	train-mlogloss:0.84756	validation-mlogloss:0.83045
[148]	train-mlogloss:0.84634	validation-mlogloss:0.82907
[149]	train-mlogloss:0.84508	validation-mlogloss:0.82788
[150]	train-mlogloss:0.84401	validation-mlogloss:0.82682
[151]	train-mlogloss:0.84292	validation-mlogloss:0.82583
[152]	train-mlogloss:0.84171	validation-mlogloss:0.82454
[153]	train-mlogloss:0.84044	validation-mlogloss:0.82335
[154]	train-mlogloss:0.83910	validation-mlogloss:0.82199
[155]	train-mlogloss:0.83791	validation-mlogloss:0.82078
[156]	train-mlogloss:0.83664	validation-mlogloss:0.81956
[157]	train-mlogloss:0.83564	validation-mlogloss:0.81865
[158]	train-mlogloss:0.83457	validation-mlogloss:0.81761
[159]	train-mlogloss:0.83337	validation-mlogloss:0.81635
[160]	train-mlogloss:0.83219	validation-mlogloss:0.81511
[161]	train-mlogloss:0.83102	validation-mlogloss:0.81392
[162]	train-mlogloss:0.83004	validation-mlogloss:0.81296
[163]	train-mlogloss:0.82895	validation-mlogloss:0.81175
[164]	train-mlogloss:0.82795	validation-mlogloss:0.81098
[165]	train-mlogloss:0.82673	validation-mlogloss:0.80981
[166]	train-mlogloss:0.82565	validation-mlogloss:0.80875
[167]	train-mlogloss:0.82455	validation-mlogloss:0.80776
[168]	train-mlogloss:0.82357	validation-mlogloss:0.80691
[169]	train-mlogloss:0.82258	validation-mlogloss:0.80584
[170]	train-mlogloss:0.82153	validation-mlogloss:0.80477
[171]	train-mlogloss:0.82045	validation-mlogloss:0.80365
[172]	train-mlogloss:0.81942	validation-mlogloss:0.80264
[173]	train-mlogloss:0.81844	validation-mlogloss:0.80172
[174]	train-mlogloss:0.81749	validation-mlogloss:0.80085
[175]	train-mlogloss:0.81639	validation-mlogloss:0.79972
[176]	train-mlogloss:0.81539	validation-mlogloss:0.79879
[177]	train-mlogloss:0.81417	validation-mlogloss:0.79764
[178]	train-mlogloss:0.81308	validation-mlogloss:0.79653
[179]	train-mlogloss:0.81203	validation-mlogloss:0.79547
[180]	train-mlogloss:0.81119	validation-mlogloss:0.79468
[181]	train-mlogloss:0.81033	validation-mlogloss:0.79398
[182]	train-mlogloss:0.80945	validation-mlogloss:0.79315
[183]	train-mlogloss:0.80836	validation-mlogloss:0.79209
[184]	train-mlogloss:0.80733	validation-mlogloss:0.79108
[185]	train-mlogloss:0.80635	validation-mlogloss:0.79011
[186]	train-mlogloss:0.80544	validation-mlogloss:0.78929
[187]	train-mlogloss:0.80456	validation-mlogloss:0.78837
[188]	train-mlogloss:0.80355	validation-mlogloss:0.78731
[189]	train-mlogloss:0.80265	validation-mlogloss:0.78653
[190]	train-mlogloss:0.80170	validation-mlogloss:0.78549
[191]	train-mlogloss:0.80080	validation-mlogloss:0.78465
[192]	train-mlogloss:0.80005	validation-mlogloss:0.78393
[193]	train-mlogloss:0.79922	validation-mlogloss:0.78306
[194]	train-mlogloss:0.79835	validation-mlogloss:0.78225
[195]	train-mlogloss:0.79746	validation-mlogloss:0.78138
[196]	train-mlogloss:0.79655	validation-mlogloss:0.78042
[197]	train-mlogloss:0.79568	validation-mlogloss:0.77950
[198]	train-mlogloss:0.79482	validation-mlogloss:0.77865
[199]	train-mlogloss:0.79400	validation-mlogloss:0.77783
[200]	train-mlogloss:0.79308	validation-mlogloss:0.77695
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[202]	train-mlogloss:0.79151	validation-mlogloss:0.77555
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[312]	train-mlogloss:0.72622	validation-mlogloss:0.71665
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[325]	train-mlogloss:0.72096	validation-mlogloss:0.71230
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[332]	train-mlogloss:0.71805	validation-mlogloss:0.70996
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[338]	train-mlogloss:0.71586	validation-mlogloss:0.70827
[339]	train-mlogloss:0.71545	validation-mlogloss:0.70791
[340]	train-mlogloss:0.71512	validation-mlogloss:0.70763
[341]	train-mlogloss:0.71481	validation-mlogloss:0.70736
[342]	train-mlogloss:0.71445	validation-mlogloss:0.70703
[343]	train-mlogloss:0.71412	validation-mlogloss:0.70668
[344]	train-mlogloss:0.71380	validation-mlogloss:0.70637
[345]	train-mlogloss:0.71344	validation-mlogloss:0.70615
[346]	train-mlogloss:0.71317	validation-mlogloss:0.70591
[347]	train-mlogloss:0.71285	validation-mlogloss:0.70562
[348]	train-mlogloss:0.71238	validation-mlogloss:0.70523
[349]	train-mlogloss:0.71214	validation-mlogloss:0.70500
[350]	train-mlogloss:0.71183	validation-mlogloss:0.70488
[351]	train-mlogloss:0.71157	validation-mlogloss:0.70468
[352]	train-mlogloss:0.71124	validation-mlogloss:0.70443
[353]	train-mlogloss:0.71100	validation-mlogloss:0.70419
[354]	train-mlogloss:0.71064	validation-mlogloss:0.70385
[355]	train-mlogloss:0.71021	validation-mlogloss:0.70359
[356]	train-mlogloss:0.70986	validation-mlogloss:0.70338
[357]	train-mlogloss:0.70952	validation-mlogloss:0.70309
[358]	train-mlogloss:0.70913	validation-mlogloss:0.70269
[359]	train-mlogloss:0.70878	validation-mlogloss:0.70244
[360]	train-mlogloss:0.70849	validation-mlogloss:0.70214
[361]	train-mlogloss:0.70823	validation-mlogloss:0.70198
[362]	train-mlogloss:0.70788	validation-mlogloss:0.70171
[363]	train-mlogloss:0.70753	validation-mlogloss:0.70143
[364]	train-mlogloss:0.70726	validation-mlogloss:0.70121
[365]	train-mlogloss:0.70696	validation-mlogloss:0.70099
[366]	train-mlogloss:0.70662	validation-mlogloss:0.70068
[367]	train-mlogloss:0.70633	validation-mlogloss:0.70048
[368]	train-mlogloss:0.70599	validation-mlogloss:0.70031
[369]	train-mlogloss:0.70560	validation-mlogloss:0.70003
[370]	train-mlogloss:0.70531	validation-mlogloss:0.69981
[371]	train-mlogloss:0.70502	validation-mlogloss:0.69961
[372]	train-mlogloss:0.70471	validation-mlogloss:0.69943
[373]	train-mlogloss:0.70440	validation-mlogloss:0.69912
[374]	train-mlogloss:0.70413	validation-mlogloss:0.69893
[375]	train-mlogloss:0.70394	validation-mlogloss:0.69875
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 0 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.25 [%]
Global accuracy score (test) = 71.78 [%]
Global F1 score (train) = 73.2 [%]
Global F1 score (test) = 72.02 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.45      0.52       400
MODERATE-INTENSITY       0.57      0.84      0.68       400
         SEDENTARY       0.85      0.85      0.85       400
VIGOROUS-INTENSITY       0.96      0.74      0.84       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.72      1545
      weighted avg       0.74      0.72      0.72      1545


Accuracy capturado en la ejecución 22: 71.78 [%]
F1-score capturado en la ejecución 22: 72.02 [%]

=== EJECUCIÓN 23 ===

--- TRAIN (ejecución 23) ---

--- TEST (ejecución 23) ---
2025-11-04 10:39:18.121861: 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 10:39:18.133360: 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 00:00:1762249158.147024 1058573 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249158.150929 1058573 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249158.160898 1058573 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249158.160916 1058573 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249158.160918 1058573 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249158.160919 1058573 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:39:18.164060: 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)
Training a non-convolutional model.
[0]	train-mlogloss:1.37640	validation-mlogloss:1.37610
[1]	train-mlogloss:1.36672	validation-mlogloss:1.36630
[2]	train-mlogloss:1.35756	validation-mlogloss:1.35675
[3]	train-mlogloss:1.34820	validation-mlogloss:1.34688
[4]	train-mlogloss:1.33899	validation-mlogloss:1.33731
[5]	train-mlogloss:1.33049	validation-mlogloss:1.32840
[6]	train-mlogloss:1.32181	validation-mlogloss:1.31937
[7]	train-mlogloss:1.31326	validation-mlogloss:1.31052
[8]	train-mlogloss:1.30483	validation-mlogloss:1.30211
[9]	train-mlogloss:1.29668	validation-mlogloss:1.29380
[10]	train-mlogloss:1.28868	validation-mlogloss:1.28546
[11]	train-mlogloss:1.28109	validation-mlogloss:1.27783
[12]	train-mlogloss:1.27335	validation-mlogloss:1.26987
[13]	train-mlogloss:1.26604	validation-mlogloss:1.26242
[14]	train-mlogloss:1.25871	validation-mlogloss:1.25495
[15]	train-mlogloss:1.25168	validation-mlogloss:1.24775
[16]	train-mlogloss:1.24509	validation-mlogloss:1.24119
[17]	train-mlogloss:1.23847	validation-mlogloss:1.23458
[18]	train-mlogloss:1.23174	validation-mlogloss:1.22747
[19]	train-mlogloss:1.22526	validation-mlogloss:1.22084
[20]	train-mlogloss:1.21892	validation-mlogloss:1.21450
[21]	train-mlogloss:1.21247	validation-mlogloss:1.20808
[22]	train-mlogloss:1.20600	validation-mlogloss:1.20164
[23]	train-mlogloss:1.19967	validation-mlogloss:1.19499
[24]	train-mlogloss:1.19362	validation-mlogloss:1.18859
[25]	train-mlogloss:1.18776	validation-mlogloss:1.18274
[26]	train-mlogloss:1.18207	validation-mlogloss:1.17687
[27]	train-mlogloss:1.17618	validation-mlogloss:1.17090
[28]	train-mlogloss:1.17044	validation-mlogloss:1.16496
[29]	train-mlogloss:1.16493	validation-mlogloss:1.15932
[30]	train-mlogloss:1.15937	validation-mlogloss:1.15332
[31]	train-mlogloss:1.15446	validation-mlogloss:1.14829
[32]	train-mlogloss:1.14921	validation-mlogloss:1.14278
[33]	train-mlogloss:1.14391	validation-mlogloss:1.13721
[34]	train-mlogloss:1.13887	validation-mlogloss:1.13216
[35]	train-mlogloss:1.13377	validation-mlogloss:1.12667
[36]	train-mlogloss:1.12883	validation-mlogloss:1.12157
[37]	train-mlogloss:1.12407	validation-mlogloss:1.11679
[38]	train-mlogloss:1.11935	validation-mlogloss:1.11194
[39]	train-mlogloss:1.11449	validation-mlogloss:1.10690
[40]	train-mlogloss:1.10976	validation-mlogloss:1.10201
[41]	train-mlogloss:1.10479	validation-mlogloss:1.09682
[42]	train-mlogloss:1.10033	validation-mlogloss:1.09215
[43]	train-mlogloss:1.09603	validation-mlogloss:1.08778
[44]	train-mlogloss:1.09155	validation-mlogloss:1.08305
[45]	train-mlogloss:1.08708	validation-mlogloss:1.07855
[46]	train-mlogloss:1.08278	validation-mlogloss:1.07413
[47]	train-mlogloss:1.07857	validation-mlogloss:1.06975
[48]	train-mlogloss:1.07450	validation-mlogloss:1.06554
[49]	train-mlogloss:1.07067	validation-mlogloss:1.06159
[50]	train-mlogloss:1.06675	validation-mlogloss:1.05750
[51]	train-mlogloss:1.06290	validation-mlogloss:1.05358
[52]	train-mlogloss:1.05925	validation-mlogloss:1.04982
[53]	train-mlogloss:1.05537	validation-mlogloss:1.04571
[54]	train-mlogloss:1.05177	validation-mlogloss:1.04232
[55]	train-mlogloss:1.04822	validation-mlogloss:1.03879
[56]	train-mlogloss:1.04454	validation-mlogloss:1.03502
[57]	train-mlogloss:1.04080	validation-mlogloss:1.03130
[58]	train-mlogloss:1.03705	validation-mlogloss:1.02753
[59]	train-mlogloss:1.03349	validation-mlogloss:1.02388
[60]	train-mlogloss:1.02993	validation-mlogloss:1.02016
[61]	train-mlogloss:1.02655	validation-mlogloss:1.01657
[62]	train-mlogloss:1.02327	validation-mlogloss:1.01311
[63]	train-mlogloss:1.02025	validation-mlogloss:1.01012
[64]	train-mlogloss:1.01701	validation-mlogloss:1.00681
[65]	train-mlogloss:1.01375	validation-mlogloss:1.00356
[66]	train-mlogloss:1.01046	validation-mlogloss:1.00017
[67]	train-mlogloss:1.00738	validation-mlogloss:0.99690
[68]	train-mlogloss:1.00436	validation-mlogloss:0.99388
[69]	train-mlogloss:1.00145	validation-mlogloss:0.99107
[70]	train-mlogloss:0.99844	validation-mlogloss:0.98809
[71]	train-mlogloss:0.99546	validation-mlogloss:0.98513
[72]	train-mlogloss:0.99272	validation-mlogloss:0.98238
[73]	train-mlogloss:0.98997	validation-mlogloss:0.97969
[74]	train-mlogloss:0.98720	validation-mlogloss:0.97688
[75]	train-mlogloss:0.98446	validation-mlogloss:0.97406
[76]	train-mlogloss:0.98173	validation-mlogloss:0.97118
[77]	train-mlogloss:0.97900	validation-mlogloss:0.96830
[78]	train-mlogloss:0.97624	validation-mlogloss:0.96554
[79]	train-mlogloss:0.97351	validation-mlogloss:0.96281
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[84]	train-mlogloss:0.96104	validation-mlogloss:0.95009
[85]	train-mlogloss:0.95857	validation-mlogloss:0.94763
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[90]	train-mlogloss:0.94685	validation-mlogloss:0.93561
[91]	train-mlogloss:0.94463	validation-mlogloss:0.93325
[92]	train-mlogloss:0.94244	validation-mlogloss:0.93103
[93]	train-mlogloss:0.94025	validation-mlogloss:0.92881
[94]	train-mlogloss:0.93813	validation-mlogloss:0.92670
[95]	train-mlogloss:0.93591	validation-mlogloss:0.92443
[96]	train-mlogloss:0.93365	validation-mlogloss:0.92214
[97]	train-mlogloss:0.93138	validation-mlogloss:0.91973
[98]	train-mlogloss:0.92930	validation-mlogloss:0.91760
[99]	train-mlogloss:0.92724	validation-mlogloss:0.91555
[100]	train-mlogloss:0.92537	validation-mlogloss:0.91377
[101]	train-mlogloss:0.92331	validation-mlogloss:0.91168
[102]	train-mlogloss:0.92128	validation-mlogloss:0.90971
[103]	train-mlogloss:0.91936	validation-mlogloss:0.90778
[104]	train-mlogloss:0.91712	validation-mlogloss:0.90550
[105]	train-mlogloss:0.91514	validation-mlogloss:0.90363
[106]	train-mlogloss:0.91326	validation-mlogloss:0.90162
[107]	train-mlogloss:0.91140	validation-mlogloss:0.89959
[108]	train-mlogloss:0.90965	validation-mlogloss:0.89771
[109]	train-mlogloss:0.90767	validation-mlogloss:0.89572
[110]	train-mlogloss:0.90596	validation-mlogloss:0.89397
[111]	train-mlogloss:0.90424	validation-mlogloss:0.89239
[112]	train-mlogloss:0.90238	validation-mlogloss:0.89042
[113]	train-mlogloss:0.90067	validation-mlogloss:0.88875
[114]	train-mlogloss:0.89889	validation-mlogloss:0.88697
[115]	train-mlogloss:0.89716	validation-mlogloss:0.88520
[116]	train-mlogloss:0.89556	validation-mlogloss:0.88370
[117]	train-mlogloss:0.89394	validation-mlogloss:0.88209
[118]	train-mlogloss:0.89221	validation-mlogloss:0.88017
[119]	train-mlogloss:0.89055	validation-mlogloss:0.87840
[120]	train-mlogloss:0.88881	validation-mlogloss:0.87664
[121]	train-mlogloss:0.88712	validation-mlogloss:0.87499
[122]	train-mlogloss:0.88573	validation-mlogloss:0.87353
[123]	train-mlogloss:0.88429	validation-mlogloss:0.87223
[124]	train-mlogloss:0.88272	validation-mlogloss:0.87066
[125]	train-mlogloss:0.88099	validation-mlogloss:0.86885
[126]	train-mlogloss:0.87949	validation-mlogloss:0.86736
[127]	train-mlogloss:0.87807	validation-mlogloss:0.86618
[128]	train-mlogloss:0.87654	validation-mlogloss:0.86455
[129]	train-mlogloss:0.87498	validation-mlogloss:0.86290
[130]	train-mlogloss:0.87334	validation-mlogloss:0.86132
[131]	train-mlogloss:0.87162	validation-mlogloss:0.85953
[132]	train-mlogloss:0.87024	validation-mlogloss:0.85821
[133]	train-mlogloss:0.86884	validation-mlogloss:0.85703
[134]	train-mlogloss:0.86740	validation-mlogloss:0.85556
[135]	train-mlogloss:0.86580	validation-mlogloss:0.85399
[136]	train-mlogloss:0.86436	validation-mlogloss:0.85275
[137]	train-mlogloss:0.86309	validation-mlogloss:0.85145
[138]	train-mlogloss:0.86151	validation-mlogloss:0.84991
[139]	train-mlogloss:0.85999	validation-mlogloss:0.84835
[140]	train-mlogloss:0.85853	validation-mlogloss:0.84690
[141]	train-mlogloss:0.85704	validation-mlogloss:0.84540
[142]	train-mlogloss:0.85578	validation-mlogloss:0.84419
[143]	train-mlogloss:0.85433	validation-mlogloss:0.84279
[144]	train-mlogloss:0.85296	validation-mlogloss:0.84142
[145]	train-mlogloss:0.85160	validation-mlogloss:0.84013
[146]	train-mlogloss:0.85036	validation-mlogloss:0.83903
[147]	train-mlogloss:0.84912	validation-mlogloss:0.83795
[148]	train-mlogloss:0.84772	validation-mlogloss:0.83675
[149]	train-mlogloss:0.84662	validation-mlogloss:0.83586
[150]	train-mlogloss:0.84528	validation-mlogloss:0.83454
[151]	train-mlogloss:0.84391	validation-mlogloss:0.83326
[152]	train-mlogloss:0.84263	validation-mlogloss:0.83192
[153]	train-mlogloss:0.84140	validation-mlogloss:0.83056
[154]	train-mlogloss:0.84024	validation-mlogloss:0.82937
[155]	train-mlogloss:0.83891	validation-mlogloss:0.82811
[156]	train-mlogloss:0.83750	validation-mlogloss:0.82691
[157]	train-mlogloss:0.83648	validation-mlogloss:0.82591
[158]	train-mlogloss:0.83536	validation-mlogloss:0.82482
[159]	train-mlogloss:0.83428	validation-mlogloss:0.82394
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[294]	train-mlogloss:0.73123	validation-mlogloss:0.73294
[295]	train-mlogloss:0.73058	validation-mlogloss:0.73237
[296]	train-mlogloss:0.73015	validation-mlogloss:0.73204
[297]	train-mlogloss:0.72973	validation-mlogloss:0.73173
[298]	train-mlogloss:0.72934	validation-mlogloss:0.73147
[299]	train-mlogloss:0.72881	validation-mlogloss:0.73096
[300]	train-mlogloss:0.72833	validation-mlogloss:0.73058
[301]	train-mlogloss:0.72787	validation-mlogloss:0.73017
[302]	train-mlogloss:0.72736	validation-mlogloss:0.72970
[303]	train-mlogloss:0.72689	validation-mlogloss:0.72927
[304]	train-mlogloss:0.72647	validation-mlogloss:0.72895
[305]	train-mlogloss:0.72608	validation-mlogloss:0.72864
[306]	train-mlogloss:0.72548	validation-mlogloss:0.72812
[307]	train-mlogloss:0.72505	validation-mlogloss:0.72775
[308]	train-mlogloss:0.72461	validation-mlogloss:0.72732
[309]	train-mlogloss:0.72403	validation-mlogloss:0.72678
[310]	train-mlogloss:0.72363	validation-mlogloss:0.72644
[311]	train-mlogloss:0.72318	validation-mlogloss:0.72602
[312]	train-mlogloss:0.72270	validation-mlogloss:0.72569
[313]	train-mlogloss:0.72222	validation-mlogloss:0.72535
[314]	train-mlogloss:0.72180	validation-mlogloss:0.72506
[315]	train-mlogloss:0.72144	validation-mlogloss:0.72478
[316]	train-mlogloss:0.72103	validation-mlogloss:0.72447
[317]	train-mlogloss:0.72065	validation-mlogloss:0.72414
[318]	train-mlogloss:0.72012	validation-mlogloss:0.72375
[319]	train-mlogloss:0.71966	validation-mlogloss:0.72333
[320]	train-mlogloss:0.71915	validation-mlogloss:0.72296
[321]	train-mlogloss:0.71886	validation-mlogloss:0.72264
[322]	train-mlogloss:0.71842	validation-mlogloss:0.72229
[323]	train-mlogloss:0.71809	validation-mlogloss:0.72208
[324]	train-mlogloss:0.71772	validation-mlogloss:0.72184
[325]	train-mlogloss:0.71734	validation-mlogloss:0.72145
[326]	train-mlogloss:0.71697	validation-mlogloss:0.72120
[327]	train-mlogloss:0.71657	validation-mlogloss:0.72083
[328]	train-mlogloss:0.71616	validation-mlogloss:0.72053
[329]	train-mlogloss:0.71581	validation-mlogloss:0.72031
[330]	train-mlogloss:0.71542	validation-mlogloss:0.71992
[331]	train-mlogloss:0.71505	validation-mlogloss:0.71959
[332]	train-mlogloss:0.71457	validation-mlogloss:0.71919
[333]	train-mlogloss:0.71430	validation-mlogloss:0.71900
[334]	train-mlogloss:0.71394	validation-mlogloss:0.71865
[335]	train-mlogloss:0.71359	validation-mlogloss:0.71834
[336]	train-mlogloss:0.71312	validation-mlogloss:0.71796
[337]	train-mlogloss:0.71271	validation-mlogloss:0.71775
[338]	train-mlogloss:0.71239	validation-mlogloss:0.71755
[339]	train-mlogloss:0.71198	validation-mlogloss:0.71729
[340]	train-mlogloss:0.71165	validation-mlogloss:0.71698
[341]	train-mlogloss:0.71122	validation-mlogloss:0.71659
[342]	train-mlogloss:0.71097	validation-mlogloss:0.71636
[343]	train-mlogloss:0.71055	validation-mlogloss:0.71604
[344]	train-mlogloss:0.71024	validation-mlogloss:0.71572
[345]	train-mlogloss:0.70991	validation-mlogloss:0.71541
[346]	train-mlogloss:0.70954	validation-mlogloss:0.71518
[347]	train-mlogloss:0.70921	validation-mlogloss:0.71491
[348]	train-mlogloss:0.70885	validation-mlogloss:0.71473
[349]	train-mlogloss:0.70848	validation-mlogloss:0.71446
[350]	train-mlogloss:0.70820	validation-mlogloss:0.71418
[351]	train-mlogloss:0.70791	validation-mlogloss:0.71393
[352]	train-mlogloss:0.70749	validation-mlogloss:0.71356
[353]	train-mlogloss:0.70713	validation-mlogloss:0.71329
[354]	train-mlogloss:0.70675	validation-mlogloss:0.71307
[355]	train-mlogloss:0.70645	validation-mlogloss:0.71277
[356]	train-mlogloss:0.70610	validation-mlogloss:0.71257
[357]	train-mlogloss:0.70570	validation-mlogloss:0.71232
[358]	train-mlogloss:0.70542	validation-mlogloss:0.71211
[359]	train-mlogloss:0.70517	validation-mlogloss:0.71188
[360]	train-mlogloss:0.70490	validation-mlogloss:0.71162
[361]	train-mlogloss:0.70459	validation-mlogloss:0.71141
[362]	train-mlogloss:0.70426	validation-mlogloss:0.71120
[363]	train-mlogloss:0.70390	validation-mlogloss:0.71093
[364]	train-mlogloss:0.70364	validation-mlogloss:0.71068
[365]	train-mlogloss:0.70332	validation-mlogloss:0.71040
[366]	train-mlogloss:0.70297	validation-mlogloss:0.71012
[367]	train-mlogloss:0.70260	validation-mlogloss:0.70990
[368]	train-mlogloss:0.70229	validation-mlogloss:0.70972
[369]	train-mlogloss:0.70194	validation-mlogloss:0.70942
[370]	train-mlogloss:0.70157	validation-mlogloss:0.70921
[371]	train-mlogloss:0.70127	validation-mlogloss:0.70901
[372]	train-mlogloss:0.70096	validation-mlogloss:0.70879
[373]	train-mlogloss:0.70071	validation-mlogloss:0.70866
[374]	train-mlogloss:0.70048	validation-mlogloss:0.70848
[375]	train-mlogloss:0.70013	validation-mlogloss:0.70824
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 72.99 [%]
Global accuracy score (test) = 71.91 [%]
Global F1 score (train) = 72.82 [%]
Global F1 score (test) = 72.04 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.61      0.43      0.51       400
MODERATE-INTENSITY       0.57      0.86      0.69       400
         SEDENTARY       0.85      0.84      0.85       400
VIGOROUS-INTENSITY       0.97      0.74      0.84       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.72      1545
      weighted avg       0.74      0.72      0.72      1545


Accuracy capturado en la ejecución 23: 71.91 [%]
F1-score capturado en la ejecución 23: 72.04 [%]

=== EJECUCIÓN 24 ===

--- TRAIN (ejecución 24) ---

--- TEST (ejecución 24) ---
2025-11-04 10:39:34.305108: 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 10:39:34.316396: 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 00:00:1762249174.329442 1058892 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249174.333624 1058892 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249174.343426 1058892 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249174.343444 1058892 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249174.343445 1058892 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249174.343446 1058892 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:39:34.346589: 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:1.37630	validation-mlogloss:1.37585
[1]	train-mlogloss:1.36663	validation-mlogloss:1.36562
[2]	train-mlogloss:1.35717	validation-mlogloss:1.35574
[3]	train-mlogloss:1.34791	validation-mlogloss:1.34592
[4]	train-mlogloss:1.33956	validation-mlogloss:1.33742
[5]	train-mlogloss:1.33101	validation-mlogloss:1.32860
[6]	train-mlogloss:1.32225	validation-mlogloss:1.31974
[7]	train-mlogloss:1.31379	validation-mlogloss:1.31096
[8]	train-mlogloss:1.30526	validation-mlogloss:1.30214
[9]	train-mlogloss:1.29771	validation-mlogloss:1.29434
[10]	train-mlogloss:1.28964	validation-mlogloss:1.28576
[11]	train-mlogloss:1.28212	validation-mlogloss:1.27814
[12]	train-mlogloss:1.27437	validation-mlogloss:1.27005
[13]	train-mlogloss:1.26711	validation-mlogloss:1.26276
[14]	train-mlogloss:1.25991	validation-mlogloss:1.25548
[15]	train-mlogloss:1.25297	validation-mlogloss:1.24864
[16]	train-mlogloss:1.24582	validation-mlogloss:1.24112
[17]	train-mlogloss:1.23906	validation-mlogloss:1.23414
[18]	train-mlogloss:1.23223	validation-mlogloss:1.22712
[19]	train-mlogloss:1.22579	validation-mlogloss:1.22067
[20]	train-mlogloss:1.21942	validation-mlogloss:1.21409
[21]	train-mlogloss:1.21293	validation-mlogloss:1.20743
[22]	train-mlogloss:1.20677	validation-mlogloss:1.20117
[23]	train-mlogloss:1.20049	validation-mlogloss:1.19446
[24]	train-mlogloss:1.19446	validation-mlogloss:1.18838
[25]	train-mlogloss:1.18865	validation-mlogloss:1.18230
[26]	train-mlogloss:1.18292	validation-mlogloss:1.17656
[27]	train-mlogloss:1.17752	validation-mlogloss:1.17122
[28]	train-mlogloss:1.17168	validation-mlogloss:1.16531
[29]	train-mlogloss:1.16628	validation-mlogloss:1.16006
[30]	train-mlogloss:1.16103	validation-mlogloss:1.15473
[31]	train-mlogloss:1.15580	validation-mlogloss:1.14967
[32]	train-mlogloss:1.15054	validation-mlogloss:1.14430
[33]	train-mlogloss:1.14528	validation-mlogloss:1.13910
[34]	train-mlogloss:1.14002	validation-mlogloss:1.13379
[35]	train-mlogloss:1.13507	validation-mlogloss:1.12888
[36]	train-mlogloss:1.13005	validation-mlogloss:1.12369
[37]	train-mlogloss:1.12515	validation-mlogloss:1.11852
[38]	train-mlogloss:1.12043	validation-mlogloss:1.11377
[39]	train-mlogloss:1.11604	validation-mlogloss:1.10964
[40]	train-mlogloss:1.11117	validation-mlogloss:1.10446
[41]	train-mlogloss:1.10639	validation-mlogloss:1.09960
[42]	train-mlogloss:1.10206	validation-mlogloss:1.09532
[43]	train-mlogloss:1.09773	validation-mlogloss:1.09116
[44]	train-mlogloss:1.09358	validation-mlogloss:1.08694
[45]	train-mlogloss:1.08947	validation-mlogloss:1.08269
[46]	train-mlogloss:1.08514	validation-mlogloss:1.07828
[47]	train-mlogloss:1.08091	validation-mlogloss:1.07400
[48]	train-mlogloss:1.07687	validation-mlogloss:1.06990
[49]	train-mlogloss:1.07305	validation-mlogloss:1.06606
[50]	train-mlogloss:1.06906	validation-mlogloss:1.06200
[51]	train-mlogloss:1.06500	validation-mlogloss:1.05792
[52]	train-mlogloss:1.06135	validation-mlogloss:1.05446
[53]	train-mlogloss:1.05749	validation-mlogloss:1.05063
[54]	train-mlogloss:1.05362	validation-mlogloss:1.04668
[55]	train-mlogloss:1.04989	validation-mlogloss:1.04283
[56]	train-mlogloss:1.04626	validation-mlogloss:1.03905
[57]	train-mlogloss:1.04278	validation-mlogloss:1.03550
[58]	train-mlogloss:1.03924	validation-mlogloss:1.03170
[59]	train-mlogloss:1.03573	validation-mlogloss:1.02817
[60]	train-mlogloss:1.03230	validation-mlogloss:1.02462
[61]	train-mlogloss:1.02895	validation-mlogloss:1.02109
[62]	train-mlogloss:1.02573	validation-mlogloss:1.01794
[63]	train-mlogloss:1.02265	validation-mlogloss:1.01495
[64]	train-mlogloss:1.01942	validation-mlogloss:1.01158
[65]	train-mlogloss:1.01648	validation-mlogloss:1.00873
[66]	train-mlogloss:1.01338	validation-mlogloss:1.00549
[67]	train-mlogloss:1.01025	validation-mlogloss:1.00217
[68]	train-mlogloss:1.00721	validation-mlogloss:0.99899
[69]	train-mlogloss:1.00424	validation-mlogloss:0.99585
[70]	train-mlogloss:1.00140	validation-mlogloss:0.99305
[71]	train-mlogloss:0.99852	validation-mlogloss:0.98997
[72]	train-mlogloss:0.99556	validation-mlogloss:0.98685
[73]	train-mlogloss:0.99280	validation-mlogloss:0.98395
[74]	train-mlogloss:0.99014	validation-mlogloss:0.98138
[75]	train-mlogloss:0.98721	validation-mlogloss:0.97856
[76]	train-mlogloss:0.98446	validation-mlogloss:0.97553
[77]	train-mlogloss:0.98198	validation-mlogloss:0.97317
[78]	train-mlogloss:0.97925	validation-mlogloss:0.97052
[79]	train-mlogloss:0.97643	validation-mlogloss:0.96762
[80]	train-mlogloss:0.97358	validation-mlogloss:0.96477
[81]	train-mlogloss:0.97104	validation-mlogloss:0.96219
[82]	train-mlogloss:0.96842	validation-mlogloss:0.95940
[83]	train-mlogloss:0.96616	validation-mlogloss:0.95716
[84]	train-mlogloss:0.96351	validation-mlogloss:0.95439
[85]	train-mlogloss:0.96099	validation-mlogloss:0.95192
[86]	train-mlogloss:0.95856	validation-mlogloss:0.94945
[87]	train-mlogloss:0.95630	validation-mlogloss:0.94723
[88]	train-mlogloss:0.95375	validation-mlogloss:0.94470
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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)
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Training a non-convolutional model.
Loaded model from disk.
(1545, 91)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.01 [%]
Global accuracy score (test) = 71.78 [%]
Global F1 score (train) = 73.03 [%]
Global F1 score (test) = 71.96 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.61      0.46      0.52       400
MODERATE-INTENSITY       0.58      0.84      0.69       400
         SEDENTARY       0.85      0.84      0.85       400
VIGOROUS-INTENSITY       0.93      0.74      0.82       345

          accuracy                           0.72      1545
         macro avg       0.74      0.72      0.72      1545
      weighted avg       0.74      0.72      0.72      1545


Accuracy capturado en la ejecución 24: 71.78 [%]
F1-score capturado en la ejecución 24: 71.96 [%]

=== EJECUCIÓN 25 ===

--- TRAIN (ejecución 25) ---

--- TEST (ejecución 25) ---
2025-11-04 10:39:50.252729: 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 10:39:50.264149: 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 00:00:1762249190.277358 1059198 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249190.281426 1059198 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249190.291114 1059198 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249190.291130 1059198 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249190.291131 1059198 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249190.291132 1059198 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:39:50.294260: 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:1.37650	validation-mlogloss:1.37633
[1]	train-mlogloss:1.36677	validation-mlogloss:1.36651
[2]	train-mlogloss:1.35727	validation-mlogloss:1.35663
[3]	train-mlogloss:1.34797	validation-mlogloss:1.34728
[4]	train-mlogloss:1.33961	validation-mlogloss:1.33891
[5]	train-mlogloss:1.33108	validation-mlogloss:1.32997
[6]	train-mlogloss:1.32232	validation-mlogloss:1.32082
[7]	train-mlogloss:1.31401	validation-mlogloss:1.31261
[8]	train-mlogloss:1.30622	validation-mlogloss:1.30473
[9]	train-mlogloss:1.29805	validation-mlogloss:1.29630
[10]	train-mlogloss:1.29002	validation-mlogloss:1.28823
[11]	train-mlogloss:1.28212	validation-mlogloss:1.27994
[12]	train-mlogloss:1.27453	validation-mlogloss:1.27234
[13]	train-mlogloss:1.26715	validation-mlogloss:1.26457
[14]	train-mlogloss:1.25977	validation-mlogloss:1.25719
[15]	train-mlogloss:1.25237	validation-mlogloss:1.24973
[16]	train-mlogloss:1.24515	validation-mlogloss:1.24239
[17]	train-mlogloss:1.23835	validation-mlogloss:1.23539
[18]	train-mlogloss:1.23144	validation-mlogloss:1.22840
[19]	train-mlogloss:1.22485	validation-mlogloss:1.22182
[20]	train-mlogloss:1.21828	validation-mlogloss:1.21529
[21]	train-mlogloss:1.21176	validation-mlogloss:1.20845
[22]	train-mlogloss:1.20579	validation-mlogloss:1.20276
[23]	train-mlogloss:1.19990	validation-mlogloss:1.19677
[24]	train-mlogloss:1.19392	validation-mlogloss:1.19101
[25]	train-mlogloss:1.18783	validation-mlogloss:1.18503
[26]	train-mlogloss:1.18163	validation-mlogloss:1.17887
[27]	train-mlogloss:1.17555	validation-mlogloss:1.17254
[28]	train-mlogloss:1.16967	validation-mlogloss:1.16659
[29]	train-mlogloss:1.16391	validation-mlogloss:1.16071
[30]	train-mlogloss:1.15841	validation-mlogloss:1.15520
[31]	train-mlogloss:1.15303	validation-mlogloss:1.14997
[32]	train-mlogloss:1.14805	validation-mlogloss:1.14518
[33]	train-mlogloss:1.14315	validation-mlogloss:1.14034
[34]	train-mlogloss:1.13792	validation-mlogloss:1.13504
[35]	train-mlogloss:1.13293	validation-mlogloss:1.13018
[36]	train-mlogloss:1.12792	validation-mlogloss:1.12504
[37]	train-mlogloss:1.12296	validation-mlogloss:1.11995
[38]	train-mlogloss:1.11819	validation-mlogloss:1.11494
[39]	train-mlogloss:1.11334	validation-mlogloss:1.11002
[40]	train-mlogloss:1.10856	validation-mlogloss:1.10495
[41]	train-mlogloss:1.10372	validation-mlogloss:1.09992
[42]	train-mlogloss:1.09923	validation-mlogloss:1.09561
[43]	train-mlogloss:1.09479	validation-mlogloss:1.09112
[44]	train-mlogloss:1.09073	validation-mlogloss:1.08724
[45]	train-mlogloss:1.08655	validation-mlogloss:1.08297
[46]	train-mlogloss:1.08252	validation-mlogloss:1.07890
[47]	train-mlogloss:1.07854	validation-mlogloss:1.07503
[48]	train-mlogloss:1.07438	validation-mlogloss:1.07102
[49]	train-mlogloss:1.07026	validation-mlogloss:1.06674
[50]	train-mlogloss:1.06611	validation-mlogloss:1.06256
[51]	train-mlogloss:1.06224	validation-mlogloss:1.05865
[52]	train-mlogloss:1.05875	validation-mlogloss:1.05514
[53]	train-mlogloss:1.05466	validation-mlogloss:1.05094
[54]	train-mlogloss:1.05107	validation-mlogloss:1.04766
[55]	train-mlogloss:1.04756	validation-mlogloss:1.04404
[56]	train-mlogloss:1.04413	validation-mlogloss:1.04060
[57]	train-mlogloss:1.04061	validation-mlogloss:1.03707
[58]	train-mlogloss:1.03693	validation-mlogloss:1.03325
[59]	train-mlogloss:1.03351	validation-mlogloss:1.02992
[60]	train-mlogloss:1.02994	validation-mlogloss:1.02629
[61]	train-mlogloss:1.02679	validation-mlogloss:1.02324
[62]	train-mlogloss:1.02336	validation-mlogloss:1.01966
[63]	train-mlogloss:1.01998	validation-mlogloss:1.01624
[64]	train-mlogloss:1.01671	validation-mlogloss:1.01295
[65]	train-mlogloss:1.01337	validation-mlogloss:1.00964
[66]	train-mlogloss:1.01004	validation-mlogloss:1.00632
[67]	train-mlogloss:1.00687	validation-mlogloss:1.00295
[68]	train-mlogloss:1.00380	validation-mlogloss:1.00005
[69]	train-mlogloss:1.00061	validation-mlogloss:0.99691
[70]	train-mlogloss:0.99766	validation-mlogloss:0.99386
[71]	train-mlogloss:0.99471	validation-mlogloss:0.99092
[72]	train-mlogloss:0.99183	validation-mlogloss:0.98797
[73]	train-mlogloss:0.98900	validation-mlogloss:0.98522
[74]	train-mlogloss:0.98610	validation-mlogloss:0.98217
[75]	train-mlogloss:0.98338	validation-mlogloss:0.97944
[76]	train-mlogloss:0.98062	validation-mlogloss:0.97665
[77]	train-mlogloss:0.97786	validation-mlogloss:0.97385
[78]	train-mlogloss:0.97539	validation-mlogloss:0.97154
[79]	train-mlogloss:0.97280	validation-mlogloss:0.96888
[80]	train-mlogloss:0.97027	validation-mlogloss:0.96617
[81]	train-mlogloss:0.96796	validation-mlogloss:0.96377
[82]	train-mlogloss:0.96549	validation-mlogloss:0.96137
[83]	train-mlogloss:0.96294	validation-mlogloss:0.95890
[84]	train-mlogloss:0.96055	validation-mlogloss:0.95653
[85]	train-mlogloss:0.95815	validation-mlogloss:0.95409
[86]	train-mlogloss:0.95578	validation-mlogloss:0.95175
[87]	train-mlogloss:0.95334	validation-mlogloss:0.94924
[88]	train-mlogloss:0.95083	validation-mlogloss:0.94672
[89]	train-mlogloss:0.94857	validation-mlogloss:0.94444
[90]	train-mlogloss:0.94623	validation-mlogloss:0.94218
[91]	train-mlogloss:0.94398	validation-mlogloss:0.93988
[92]	train-mlogloss:0.94182	validation-mlogloss:0.93766
[93]	train-mlogloss:0.93935	validation-mlogloss:0.93522
[94]	train-mlogloss:0.93718	validation-mlogloss:0.93307
[95]	train-mlogloss:0.93505	validation-mlogloss:0.93108
[96]	train-mlogloss:0.93287	validation-mlogloss:0.92891
[97]	train-mlogloss:0.93074	validation-mlogloss:0.92680
[98]	train-mlogloss:0.92878	validation-mlogloss:0.92500
[99]	train-mlogloss:0.92667	validation-mlogloss:0.92292
[100]	train-mlogloss:0.92442	validation-mlogloss:0.92054
[101]	train-mlogloss:0.92243	validation-mlogloss:0.91851
[102]	train-mlogloss:0.92033	validation-mlogloss:0.91642
[103]	train-mlogloss:0.91824	validation-mlogloss:0.91431
[104]	train-mlogloss:0.91627	validation-mlogloss:0.91233
[105]	train-mlogloss:0.91442	validation-mlogloss:0.91063
[106]	train-mlogloss:0.91249	validation-mlogloss:0.90866
[107]	train-mlogloss:0.91038	validation-mlogloss:0.90650
[108]	train-mlogloss:0.90834	validation-mlogloss:0.90448
[109]	train-mlogloss:0.90653	validation-mlogloss:0.90279
[110]	train-mlogloss:0.90459	validation-mlogloss:0.90083
[111]	train-mlogloss:0.90291	validation-mlogloss:0.89921
[112]	train-mlogloss:0.90120	validation-mlogloss:0.89739
[113]	train-mlogloss:0.89931	validation-mlogloss:0.89542
[114]	train-mlogloss:0.89755	validation-mlogloss:0.89356
[115]	train-mlogloss:0.89568	validation-mlogloss:0.89162
[116]	train-mlogloss:0.89397	validation-mlogloss:0.88992
[117]	train-mlogloss:0.89233	validation-mlogloss:0.88815
[118]	train-mlogloss:0.89064	validation-mlogloss:0.88637
[119]	train-mlogloss:0.88887	validation-mlogloss:0.88463
[120]	train-mlogloss:0.88720	validation-mlogloss:0.88307
[121]	train-mlogloss:0.88556	validation-mlogloss:0.88145
[122]	train-mlogloss:0.88395	validation-mlogloss:0.87979
[123]	train-mlogloss:0.88236	validation-mlogloss:0.87814
[124]	train-mlogloss:0.88085	validation-mlogloss:0.87671
[125]	train-mlogloss:0.87924	validation-mlogloss:0.87508
[126]	train-mlogloss:0.87784	validation-mlogloss:0.87362
[127]	train-mlogloss:0.87627	validation-mlogloss:0.87209
[128]	train-mlogloss:0.87475	validation-mlogloss:0.87052
[129]	train-mlogloss:0.87331	validation-mlogloss:0.86901
[130]	train-mlogloss:0.87192	validation-mlogloss:0.86760
[131]	train-mlogloss:0.87040	validation-mlogloss:0.86593
[132]	train-mlogloss:0.86899	validation-mlogloss:0.86448
[133]	train-mlogloss:0.86739	validation-mlogloss:0.86288
[134]	train-mlogloss:0.86593	validation-mlogloss:0.86139
[135]	train-mlogloss:0.86446	validation-mlogloss:0.85984
[136]	train-mlogloss:0.86310	validation-mlogloss:0.85843
[137]	train-mlogloss:0.86183	validation-mlogloss:0.85722
[138]	train-mlogloss:0.86034	validation-mlogloss:0.85562
[139]	train-mlogloss:0.85907	validation-mlogloss:0.85446
[140]	train-mlogloss:0.85776	validation-mlogloss:0.85301
[141]	train-mlogloss:0.85644	validation-mlogloss:0.85168
[142]	train-mlogloss:0.85518	validation-mlogloss:0.85062
[143]	train-mlogloss:0.85383	validation-mlogloss:0.84924
[144]	train-mlogloss:0.85237	validation-mlogloss:0.84790
[145]	train-mlogloss:0.85113	validation-mlogloss:0.84666
[146]	train-mlogloss:0.84989	validation-mlogloss:0.84546
[147]	train-mlogloss:0.84860	validation-mlogloss:0.84430
[148]	train-mlogloss:0.84754	validation-mlogloss:0.84340
[149]	train-mlogloss:0.84643	validation-mlogloss:0.84239
[150]	train-mlogloss:0.84527	validation-mlogloss:0.84139
[151]	train-mlogloss:0.84404	validation-mlogloss:0.84044
[152]	train-mlogloss:0.84269	validation-mlogloss:0.83899
[153]	train-mlogloss:0.84161	validation-mlogloss:0.83804
[154]	train-mlogloss:0.84034	validation-mlogloss:0.83681
[155]	train-mlogloss:0.83919	validation-mlogloss:0.83557
[156]	train-mlogloss:0.83801	validation-mlogloss:0.83436
[157]	train-mlogloss:0.83676	validation-mlogloss:0.83300
[158]	train-mlogloss:0.83560	validation-mlogloss:0.83190
[159]	train-mlogloss:0.83445	validation-mlogloss:0.83071
[160]	train-mlogloss:0.83324	validation-mlogloss:0.82945
[161]	train-mlogloss:0.83196	validation-mlogloss:0.82823
[162]	train-mlogloss:0.83071	validation-mlogloss:0.82705
[163]	train-mlogloss:0.82950	validation-mlogloss:0.82600
[164]	train-mlogloss:0.82835	validation-mlogloss:0.82484
[165]	train-mlogloss:0.82745	validation-mlogloss:0.82391
[166]	train-mlogloss:0.82630	validation-mlogloss:0.82285
[167]	train-mlogloss:0.82520	validation-mlogloss:0.82176
[168]	train-mlogloss:0.82409	validation-mlogloss:0.82047
[169]	train-mlogloss:0.82318	validation-mlogloss:0.81954
[170]	train-mlogloss:0.82220	validation-mlogloss:0.81863
[171]	train-mlogloss:0.82115	validation-mlogloss:0.81765
[172]	train-mlogloss:0.82005	validation-mlogloss:0.81659
[173]	train-mlogloss:0.81894	validation-mlogloss:0.81544
[174]	train-mlogloss:0.81776	validation-mlogloss:0.81425
[175]	train-mlogloss:0.81662	validation-mlogloss:0.81314
[176]	train-mlogloss:0.81563	validation-mlogloss:0.81222
[177]	train-mlogloss:0.81466	validation-mlogloss:0.81135
[178]	train-mlogloss:0.81362	validation-mlogloss:0.81025
[179]	train-mlogloss:0.81253	validation-mlogloss:0.80912
[180]	train-mlogloss:0.81160	validation-mlogloss:0.80823
[181]	train-mlogloss:0.81063	validation-mlogloss:0.80724
[182]	train-mlogloss:0.80979	validation-mlogloss:0.80653
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[318]	train-mlogloss:0.72279	validation-mlogloss:0.72829
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[339]	train-mlogloss:0.71518	validation-mlogloss:0.72122
[340]	train-mlogloss:0.71489	validation-mlogloss:0.72090
[341]	train-mlogloss:0.71452	validation-mlogloss:0.72062
[342]	train-mlogloss:0.71414	validation-mlogloss:0.72022
[343]	train-mlogloss:0.71384	validation-mlogloss:0.71989
[344]	train-mlogloss:0.71351	validation-mlogloss:0.71960
[345]	train-mlogloss:0.71318	validation-mlogloss:0.71927
[346]	train-mlogloss:0.71284	validation-mlogloss:0.71894
[347]	train-mlogloss:0.71248	validation-mlogloss:0.71869
[348]	train-mlogloss:0.71213	validation-mlogloss:0.71836
[349]	train-mlogloss:0.71177	validation-mlogloss:0.71801
[350]	train-mlogloss:0.71152	validation-mlogloss:0.71781
[351]	train-mlogloss:0.71121	validation-mlogloss:0.71751
[352]	train-mlogloss:0.71092	validation-mlogloss:0.71724
[353]	train-mlogloss:0.71058	validation-mlogloss:0.71695
[354]	train-mlogloss:0.71040	validation-mlogloss:0.71675
[355]	train-mlogloss:0.71000	validation-mlogloss:0.71650
[356]	train-mlogloss:0.70972	validation-mlogloss:0.71627
[357]	train-mlogloss:0.70937	validation-mlogloss:0.71599
[358]	train-mlogloss:0.70903	validation-mlogloss:0.71575
[359]	train-mlogloss:0.70865	validation-mlogloss:0.71543
[360]	train-mlogloss:0.70828	validation-mlogloss:0.71511
[361]	train-mlogloss:0.70795	validation-mlogloss:0.71472
[362]	train-mlogloss:0.70754	validation-mlogloss:0.71438
[363]	train-mlogloss:0.70725	validation-mlogloss:0.71418
[364]	train-mlogloss:0.70698	validation-mlogloss:0.71397
[365]	train-mlogloss:0.70664	validation-mlogloss:0.71363
[366]	train-mlogloss:0.70633	validation-mlogloss:0.71341
[367]	train-mlogloss:0.70606	validation-mlogloss:0.71309
[368]	train-mlogloss:0.70567	validation-mlogloss:0.71283
[369]	train-mlogloss:0.70544	validation-mlogloss:0.71262
[370]	train-mlogloss:0.70508	validation-mlogloss:0.71233
[371]	train-mlogloss:0.70482	validation-mlogloss:0.71207
[372]	train-mlogloss:0.70449	validation-mlogloss:0.71176
[373]	train-mlogloss:0.70427	validation-mlogloss:0.71154
[374]	train-mlogloss:0.70401	validation-mlogloss:0.71130
[375]	train-mlogloss:0.70371	validation-mlogloss:0.71106
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 0 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.61 [%]
Global accuracy score (test) = 72.17 [%]
Global F1 score (train) = 73.56 [%]
Global F1 score (test) = 72.42 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.61      0.47      0.53       400
MODERATE-INTENSITY       0.59      0.84      0.69       400
         SEDENTARY       0.84      0.84      0.84       400
VIGOROUS-INTENSITY       0.95      0.74      0.83       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.72      1545
      weighted avg       0.74      0.72      0.72      1545


Accuracy capturado en la ejecución 25: 72.17 [%]
F1-score capturado en la ejecución 25: 72.42 [%]

=== EJECUCIÓN 26 ===

--- TRAIN (ejecución 26) ---

--- TEST (ejecución 26) ---
2025-11-04 10:40:06.325372: 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 10:40:06.336924: 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 00:00:1762249206.350466 1059504 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249206.354699 1059504 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249206.364750 1059504 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249206.364766 1059504 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249206.364768 1059504 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249206.364769 1059504 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:40:06.367920: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (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:1.37709	validation-mlogloss:1.37709
[1]	train-mlogloss:1.36751	validation-mlogloss:1.36698
[2]	train-mlogloss:1.35813	validation-mlogloss:1.35744
[3]	train-mlogloss:1.34899	validation-mlogloss:1.34808
[4]	train-mlogloss:1.34015	validation-mlogloss:1.33867
[5]	train-mlogloss:1.33130	validation-mlogloss:1.32975
[6]	train-mlogloss:1.32313	validation-mlogloss:1.32151
[7]	train-mlogloss:1.31469	validation-mlogloss:1.31254
[8]	train-mlogloss:1.30652	validation-mlogloss:1.30417
[9]	train-mlogloss:1.29828	validation-mlogloss:1.29578
[10]	train-mlogloss:1.29043	validation-mlogloss:1.28771
[11]	train-mlogloss:1.28258	validation-mlogloss:1.27964
[12]	train-mlogloss:1.27484	validation-mlogloss:1.27155
[13]	train-mlogloss:1.26726	validation-mlogloss:1.26391
[14]	train-mlogloss:1.26012	validation-mlogloss:1.25677
[15]	train-mlogloss:1.25306	validation-mlogloss:1.24929
[16]	train-mlogloss:1.24586	validation-mlogloss:1.24163
[17]	train-mlogloss:1.23898	validation-mlogloss:1.23451
[18]	train-mlogloss:1.23259	validation-mlogloss:1.22788
[19]	train-mlogloss:1.22596	validation-mlogloss:1.22145
[20]	train-mlogloss:1.21912	validation-mlogloss:1.21460
[21]	train-mlogloss:1.21253	validation-mlogloss:1.20770
[22]	train-mlogloss:1.20604	validation-mlogloss:1.20094
[23]	train-mlogloss:1.19985	validation-mlogloss:1.19444
[24]	train-mlogloss:1.19350	validation-mlogloss:1.18792
[25]	train-mlogloss:1.18747	validation-mlogloss:1.18174
[26]	train-mlogloss:1.18200	validation-mlogloss:1.17623
[27]	train-mlogloss:1.17604	validation-mlogloss:1.16996
[28]	train-mlogloss:1.17058	validation-mlogloss:1.16444
[29]	train-mlogloss:1.16483	validation-mlogloss:1.15863
[30]	train-mlogloss:1.15941	validation-mlogloss:1.15334
[31]	train-mlogloss:1.15382	validation-mlogloss:1.14773
[32]	train-mlogloss:1.14848	validation-mlogloss:1.14217
[33]	train-mlogloss:1.14329	validation-mlogloss:1.13674
[34]	train-mlogloss:1.13819	validation-mlogloss:1.13163
[35]	train-mlogloss:1.13313	validation-mlogloss:1.12645
[36]	train-mlogloss:1.12814	validation-mlogloss:1.12169
[37]	train-mlogloss:1.12326	validation-mlogloss:1.11671
[38]	train-mlogloss:1.11826	validation-mlogloss:1.11174
[39]	train-mlogloss:1.11341	validation-mlogloss:1.10660
[40]	train-mlogloss:1.10887	validation-mlogloss:1.10222
[41]	train-mlogloss:1.10413	validation-mlogloss:1.09747
[42]	train-mlogloss:1.09959	validation-mlogloss:1.09281
[43]	train-mlogloss:1.09498	validation-mlogloss:1.08810
[44]	train-mlogloss:1.09038	validation-mlogloss:1.08330
[45]	train-mlogloss:1.08592	validation-mlogloss:1.07890
[46]	train-mlogloss:1.08148	validation-mlogloss:1.07437
[47]	train-mlogloss:1.07719	validation-mlogloss:1.07003
[48]	train-mlogloss:1.07314	validation-mlogloss:1.06610
[49]	train-mlogloss:1.06899	validation-mlogloss:1.06183
[50]	train-mlogloss:1.06489	validation-mlogloss:1.05760
[51]	train-mlogloss:1.06088	validation-mlogloss:1.05376
[52]	train-mlogloss:1.05680	validation-mlogloss:1.04986
[53]	train-mlogloss:1.05306	validation-mlogloss:1.04616
[54]	train-mlogloss:1.04943	validation-mlogloss:1.04252
[55]	train-mlogloss:1.04572	validation-mlogloss:1.03893
[56]	train-mlogloss:1.04194	validation-mlogloss:1.03524
[57]	train-mlogloss:1.03838	validation-mlogloss:1.03162
[58]	train-mlogloss:1.03473	validation-mlogloss:1.02793
[59]	train-mlogloss:1.03115	validation-mlogloss:1.02452
[60]	train-mlogloss:1.02781	validation-mlogloss:1.02118
[61]	train-mlogloss:1.02441	validation-mlogloss:1.01778
[62]	train-mlogloss:1.02105	validation-mlogloss:1.01446
[63]	train-mlogloss:1.01776	validation-mlogloss:1.01103
[64]	train-mlogloss:1.01453	validation-mlogloss:1.00772
[65]	train-mlogloss:1.01129	validation-mlogloss:1.00443
[66]	train-mlogloss:1.00813	validation-mlogloss:1.00120
[67]	train-mlogloss:1.00497	validation-mlogloss:0.99803
[68]	train-mlogloss:1.00188	validation-mlogloss:0.99484
[69]	train-mlogloss:0.99867	validation-mlogloss:0.99163
[70]	train-mlogloss:0.99553	validation-mlogloss:0.98832
[71]	train-mlogloss:0.99264	validation-mlogloss:0.98546
[72]	train-mlogloss:0.98975	validation-mlogloss:0.98261
[73]	train-mlogloss:0.98691	validation-mlogloss:0.97951
[74]	train-mlogloss:0.98387	validation-mlogloss:0.97649
[75]	train-mlogloss:0.98114	validation-mlogloss:0.97389
[76]	train-mlogloss:0.97836	validation-mlogloss:0.97106
[77]	train-mlogloss:0.97572	validation-mlogloss:0.96836
[78]	train-mlogloss:0.97315	validation-mlogloss:0.96563
[79]	train-mlogloss:0.97047	validation-mlogloss:0.96299
[80]	train-mlogloss:0.96764	validation-mlogloss:0.96023
[81]	train-mlogloss:0.96501	validation-mlogloss:0.95756
[82]	train-mlogloss:0.96260	validation-mlogloss:0.95511
[83]	train-mlogloss:0.96024	validation-mlogloss:0.95280
[84]	train-mlogloss:0.95778	validation-mlogloss:0.95040
[85]	train-mlogloss:0.95533	validation-mlogloss:0.94796
[86]	train-mlogloss:0.95306	validation-mlogloss:0.94576
[87]	train-mlogloss:0.95046	validation-mlogloss:0.94312
[88]	train-mlogloss:0.94807	validation-mlogloss:0.94071
[89]	train-mlogloss:0.94578	validation-mlogloss:0.93852
[90]	train-mlogloss:0.94347	validation-mlogloss:0.93615
[91]	train-mlogloss:0.94111	validation-mlogloss:0.93374
[92]	train-mlogloss:0.93886	validation-mlogloss:0.93148
[93]	train-mlogloss:0.93650	validation-mlogloss:0.92915
[94]	train-mlogloss:0.93424	validation-mlogloss:0.92693
[95]	train-mlogloss:0.93196	validation-mlogloss:0.92459
[96]	train-mlogloss:0.92984	validation-mlogloss:0.92236
[97]	train-mlogloss:0.92772	validation-mlogloss:0.92039
[98]	train-mlogloss:0.92549	validation-mlogloss:0.91801
[99]	train-mlogloss:0.92346	validation-mlogloss:0.91585
[100]	train-mlogloss:0.92130	validation-mlogloss:0.91363
[101]	train-mlogloss:0.91929	validation-mlogloss:0.91160
[102]	train-mlogloss:0.91738	validation-mlogloss:0.90961
[103]	train-mlogloss:0.91542	validation-mlogloss:0.90745
[104]	train-mlogloss:0.91351	validation-mlogloss:0.90556
[105]	train-mlogloss:0.91161	validation-mlogloss:0.90378
[106]	train-mlogloss:0.90982	validation-mlogloss:0.90189
[107]	train-mlogloss:0.90799	validation-mlogloss:0.90003
[108]	train-mlogloss:0.90612	validation-mlogloss:0.89813
[109]	train-mlogloss:0.90429	validation-mlogloss:0.89617
[110]	train-mlogloss:0.90258	validation-mlogloss:0.89458
[111]	train-mlogloss:0.90075	validation-mlogloss:0.89286
[112]	train-mlogloss:0.89910	validation-mlogloss:0.89107
[113]	train-mlogloss:0.89738	validation-mlogloss:0.88941
[114]	train-mlogloss:0.89572	validation-mlogloss:0.88790
[115]	train-mlogloss:0.89395	validation-mlogloss:0.88629
[116]	train-mlogloss:0.89228	validation-mlogloss:0.88467
[117]	train-mlogloss:0.89057	validation-mlogloss:0.88301
[118]	train-mlogloss:0.88882	validation-mlogloss:0.88127
[119]	train-mlogloss:0.88703	validation-mlogloss:0.87949
[120]	train-mlogloss:0.88552	validation-mlogloss:0.87806
[121]	train-mlogloss:0.88390	validation-mlogloss:0.87649
[122]	train-mlogloss:0.88232	validation-mlogloss:0.87492
[123]	train-mlogloss:0.88071	validation-mlogloss:0.87328
[124]	train-mlogloss:0.87901	validation-mlogloss:0.87158
[125]	train-mlogloss:0.87740	validation-mlogloss:0.87000
[126]	train-mlogloss:0.87589	validation-mlogloss:0.86865
[127]	train-mlogloss:0.87429	validation-mlogloss:0.86706
[128]	train-mlogloss:0.87282	validation-mlogloss:0.86569
[129]	train-mlogloss:0.87124	validation-mlogloss:0.86396
[130]	train-mlogloss:0.86975	validation-mlogloss:0.86240
[131]	train-mlogloss:0.86822	validation-mlogloss:0.86087
[132]	train-mlogloss:0.86675	validation-mlogloss:0.85942
[133]	train-mlogloss:0.86527	validation-mlogloss:0.85787
[134]	train-mlogloss:0.86381	validation-mlogloss:0.85630
[135]	train-mlogloss:0.86233	validation-mlogloss:0.85476
[136]	train-mlogloss:0.86106	validation-mlogloss:0.85346
[137]	train-mlogloss:0.85979	validation-mlogloss:0.85215
[138]	train-mlogloss:0.85843	validation-mlogloss:0.85071
[139]	train-mlogloss:0.85721	validation-mlogloss:0.84957
[140]	train-mlogloss:0.85585	validation-mlogloss:0.84831
[141]	train-mlogloss:0.85448	validation-mlogloss:0.84687
[142]	train-mlogloss:0.85322	validation-mlogloss:0.84576
[143]	train-mlogloss:0.85183	validation-mlogloss:0.84441
[144]	train-mlogloss:0.85058	validation-mlogloss:0.84317
[145]	train-mlogloss:0.84937	validation-mlogloss:0.84197
[146]	train-mlogloss:0.84809	validation-mlogloss:0.84079
[147]	train-mlogloss:0.84700	validation-mlogloss:0.83979
[148]	train-mlogloss:0.84571	validation-mlogloss:0.83842
[149]	train-mlogloss:0.84464	validation-mlogloss:0.83751
[150]	train-mlogloss:0.84332	validation-mlogloss:0.83635
[151]	train-mlogloss:0.84205	validation-mlogloss:0.83536
[152]	train-mlogloss:0.84081	validation-mlogloss:0.83409
[153]	train-mlogloss:0.83960	validation-mlogloss:0.83298
[154]	train-mlogloss:0.83845	validation-mlogloss:0.83189
[155]	train-mlogloss:0.83730	validation-mlogloss:0.83073
[156]	train-mlogloss:0.83620	validation-mlogloss:0.82971
[157]	train-mlogloss:0.83503	validation-mlogloss:0.82861
[158]	train-mlogloss:0.83390	validation-mlogloss:0.82759
[159]	train-mlogloss:0.83267	validation-mlogloss:0.82658
[160]	train-mlogloss:0.83159	validation-mlogloss:0.82539
[161]	train-mlogloss:0.83063	validation-mlogloss:0.82433
[162]	train-mlogloss:0.82965	validation-mlogloss:0.82343
[163]	train-mlogloss:0.82858	validation-mlogloss:0.82236
[164]	train-mlogloss:0.82749	validation-mlogloss:0.82121
[165]	train-mlogloss:0.82648	validation-mlogloss:0.82018
[166]	train-mlogloss:0.82537	validation-mlogloss:0.81937
[167]	train-mlogloss:0.82429	validation-mlogloss:0.81839
[168]	train-mlogloss:0.82313	validation-mlogloss:0.81732
[169]	train-mlogloss:0.82206	validation-mlogloss:0.81623
[170]	train-mlogloss:0.82108	validation-mlogloss:0.81525
[171]	train-mlogloss:0.81991	validation-mlogloss:0.81410
[172]	train-mlogloss:0.81884	validation-mlogloss:0.81305
[173]	train-mlogloss:0.81789	validation-mlogloss:0.81212
[174]	train-mlogloss:0.81699	validation-mlogloss:0.81114
[175]	train-mlogloss:0.81590	validation-mlogloss:0.80998
[176]	train-mlogloss:0.81479	validation-mlogloss:0.80881
[177]	train-mlogloss:0.81386	validation-mlogloss:0.80798
[178]	train-mlogloss:0.81285	validation-mlogloss:0.80705
[179]	train-mlogloss:0.81168	validation-mlogloss:0.80600
[180]	train-mlogloss:0.81068	validation-mlogloss:0.80516
[181]	train-mlogloss:0.80968	validation-mlogloss:0.80414
[182]	train-mlogloss:0.80869	validation-mlogloss:0.80319
[183]	train-mlogloss:0.80766	validation-mlogloss:0.80216
[184]	train-mlogloss:0.80669	validation-mlogloss:0.80125
[185]	train-mlogloss:0.80579	validation-mlogloss:0.80039
[186]	train-mlogloss:0.80483	validation-mlogloss:0.79950
[187]	train-mlogloss:0.80396	validation-mlogloss:0.79870
[188]	train-mlogloss:0.80316	validation-mlogloss:0.79801
[189]	train-mlogloss:0.80232	validation-mlogloss:0.79722
[190]	train-mlogloss:0.80137	validation-mlogloss:0.79644
[191]	train-mlogloss:0.80029	validation-mlogloss:0.79548
[192]	train-mlogloss:0.79940	validation-mlogloss:0.79480
[193]	train-mlogloss:0.79837	validation-mlogloss:0.79394
[194]	train-mlogloss:0.79756	validation-mlogloss:0.79323
[195]	train-mlogloss:0.79671	validation-mlogloss:0.79234
[196]	train-mlogloss:0.79589	validation-mlogloss:0.79147
[197]	train-mlogloss:0.79488	validation-mlogloss:0.79051
[198]	train-mlogloss:0.79403	validation-mlogloss:0.78975
[199]	train-mlogloss:0.79319	validation-mlogloss:0.78900
[200]	train-mlogloss:0.79232	validation-mlogloss:0.78824
[201]	train-mlogloss:0.79161	validation-mlogloss:0.78767
[202]	train-mlogloss:0.79073	validation-mlogloss:0.78677
[203]	train-mlogloss:0.78977	validation-mlogloss:0.78587
[204]	train-mlogloss:0.78905	validation-mlogloss:0.78525
[205]	train-mlogloss:0.78813	validation-mlogloss:0.78430
[206]	train-mlogloss:0.78733	validation-mlogloss:0.78346
[207]	train-mlogloss:0.78641	validation-mlogloss:0.78272
[208]	train-mlogloss:0.78552	validation-mlogloss:0.78186
[209]	train-mlogloss:0.78471	validation-mlogloss:0.78124
[210]	train-mlogloss:0.78380	validation-mlogloss:0.78037
[211]	train-mlogloss:0.78285	validation-mlogloss:0.77957
[212]	train-mlogloss:0.78218	validation-mlogloss:0.77903
[213]	train-mlogloss:0.78145	validation-mlogloss:0.77838
[214]	train-mlogloss:0.78062	validation-mlogloss:0.77762
[215]	train-mlogloss:0.77990	validation-mlogloss:0.77698
[216]	train-mlogloss:0.77912	validation-mlogloss:0.77621
[217]	train-mlogloss:0.77837	validation-mlogloss:0.77555
[218]	train-mlogloss:0.77757	validation-mlogloss:0.77487
[219]	train-mlogloss:0.77675	validation-mlogloss:0.77402
[220]	train-mlogloss:0.77604	validation-mlogloss:0.77334
[221]	train-mlogloss:0.77520	validation-mlogloss:0.77258
[222]	train-mlogloss:0.77440	validation-mlogloss:0.77185
[223]	train-mlogloss:0.77365	validation-mlogloss:0.77118
[224]	train-mlogloss:0.77296	validation-mlogloss:0.77055
[225]	train-mlogloss:0.77225	validation-mlogloss:0.76987
[226]	train-mlogloss:0.77158	validation-mlogloss:0.76937
[227]	train-mlogloss:0.77084	validation-mlogloss:0.76871
[228]	train-mlogloss:0.77016	validation-mlogloss:0.76811
[229]	train-mlogloss:0.76946	validation-mlogloss:0.76743
[230]	train-mlogloss:0.76876	validation-mlogloss:0.76683
[231]	train-mlogloss:0.76814	validation-mlogloss:0.76636
[232]	train-mlogloss:0.76752	validation-mlogloss:0.76584
[233]	train-mlogloss:0.76681	validation-mlogloss:0.76526
[234]	train-mlogloss:0.76619	validation-mlogloss:0.76479
[235]	train-mlogloss:0.76554	validation-mlogloss:0.76418
[236]	train-mlogloss:0.76481	validation-mlogloss:0.76341
[237]	train-mlogloss:0.76416	validation-mlogloss:0.76289
[238]	train-mlogloss:0.76337	validation-mlogloss:0.76219
[239]	train-mlogloss:0.76272	validation-mlogloss:0.76161
[240]	train-mlogloss:0.76204	validation-mlogloss:0.76099
[241]	train-mlogloss:0.76142	validation-mlogloss:0.76055
[242]	train-mlogloss:0.76065	validation-mlogloss:0.75983
[243]	train-mlogloss:0.76005	validation-mlogloss:0.75927
[244]	train-mlogloss:0.75952	validation-mlogloss:0.75875
[245]	train-mlogloss:0.75892	validation-mlogloss:0.75815
[246]	train-mlogloss:0.75833	validation-mlogloss:0.75758
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[248]	train-mlogloss:0.75713	validation-mlogloss:0.75646
[249]	train-mlogloss:0.75656	validation-mlogloss:0.75598
[250]	train-mlogloss:0.75593	validation-mlogloss:0.75536
[251]	train-mlogloss:0.75527	validation-mlogloss:0.75481
[252]	train-mlogloss:0.75467	validation-mlogloss:0.75417
[253]	train-mlogloss:0.75411	validation-mlogloss:0.75372
[254]	train-mlogloss:0.75344	validation-mlogloss:0.75317
[255]	train-mlogloss:0.75289	validation-mlogloss:0.75275
[256]	train-mlogloss:0.75225	validation-mlogloss:0.75216
[257]	train-mlogloss:0.75174	validation-mlogloss:0.75177
[258]	train-mlogloss:0.75120	validation-mlogloss:0.75132
[259]	train-mlogloss:0.75067	validation-mlogloss:0.75082
[260]	train-mlogloss:0.75012	validation-mlogloss:0.75037
[261]	train-mlogloss:0.74958	validation-mlogloss:0.74990
[262]	train-mlogloss:0.74904	validation-mlogloss:0.74944
[263]	train-mlogloss:0.74843	validation-mlogloss:0.74896
[264]	train-mlogloss:0.74780	validation-mlogloss:0.74844
[265]	train-mlogloss:0.74724	validation-mlogloss:0.74789
[266]	train-mlogloss:0.74677	validation-mlogloss:0.74753
[267]	train-mlogloss:0.74628	validation-mlogloss:0.74714
[268]	train-mlogloss:0.74582	validation-mlogloss:0.74680
[269]	train-mlogloss:0.74527	validation-mlogloss:0.74629
[270]	train-mlogloss:0.74476	validation-mlogloss:0.74588
[271]	train-mlogloss:0.74423	validation-mlogloss:0.74558
[272]	train-mlogloss:0.74370	validation-mlogloss:0.74515
[273]	train-mlogloss:0.74313	validation-mlogloss:0.74463
[274]	train-mlogloss:0.74252	validation-mlogloss:0.74418
[275]	train-mlogloss:0.74192	validation-mlogloss:0.74375
[276]	train-mlogloss:0.74139	validation-mlogloss:0.74336
[277]	train-mlogloss:0.74087	validation-mlogloss:0.74294
[278]	train-mlogloss:0.74030	validation-mlogloss:0.74242
[279]	train-mlogloss:0.73986	validation-mlogloss:0.74199
[280]	train-mlogloss:0.73924	validation-mlogloss:0.74148
[281]	train-mlogloss:0.73880	validation-mlogloss:0.74117
[282]	train-mlogloss:0.73829	validation-mlogloss:0.74075
[283]	train-mlogloss:0.73765	validation-mlogloss:0.74016
[284]	train-mlogloss:0.73718	validation-mlogloss:0.73975
[285]	train-mlogloss:0.73659	validation-mlogloss:0.73931
[286]	train-mlogloss:0.73610	validation-mlogloss:0.73889
[287]	train-mlogloss:0.73564	validation-mlogloss:0.73850
[288]	train-mlogloss:0.73514	validation-mlogloss:0.73819
[289]	train-mlogloss:0.73464	validation-mlogloss:0.73770
[290]	train-mlogloss:0.73413	validation-mlogloss:0.73725
[291]	train-mlogloss:0.73366	validation-mlogloss:0.73691
[292]	train-mlogloss:0.73320	validation-mlogloss:0.73659
[293]	train-mlogloss:0.73270	validation-mlogloss:0.73622
[294]	train-mlogloss:0.73228	validation-mlogloss:0.73582
[295]	train-mlogloss:0.73179	validation-mlogloss:0.73532
[296]	train-mlogloss:0.73132	validation-mlogloss:0.73492
[297]	train-mlogloss:0.73082	validation-mlogloss:0.73446
[298]	train-mlogloss:0.73037	validation-mlogloss:0.73405
[299]	train-mlogloss:0.72979	validation-mlogloss:0.73362
[300]	train-mlogloss:0.72939	validation-mlogloss:0.73318
[301]	train-mlogloss:0.72904	validation-mlogloss:0.73286
[302]	train-mlogloss:0.72860	validation-mlogloss:0.73257
[303]	train-mlogloss:0.72808	validation-mlogloss:0.73213
[304]	train-mlogloss:0.72762	validation-mlogloss:0.73178
[305]	train-mlogloss:0.72721	validation-mlogloss:0.73134
[306]	train-mlogloss:0.72685	validation-mlogloss:0.73106
[307]	train-mlogloss:0.72640	validation-mlogloss:0.73072
[308]	train-mlogloss:0.72598	validation-mlogloss:0.73035
[309]	train-mlogloss:0.72552	validation-mlogloss:0.72998
[310]	train-mlogloss:0.72518	validation-mlogloss:0.72970
[311]	train-mlogloss:0.72471	validation-mlogloss:0.72932
[312]	train-mlogloss:0.72426	validation-mlogloss:0.72887
[313]	train-mlogloss:0.72386	validation-mlogloss:0.72859
[314]	train-mlogloss:0.72349	validation-mlogloss:0.72829
[315]	train-mlogloss:0.72306	validation-mlogloss:0.72790
[316]	train-mlogloss:0.72270	validation-mlogloss:0.72760
[317]	train-mlogloss:0.72225	validation-mlogloss:0.72721
[318]	train-mlogloss:0.72178	validation-mlogloss:0.72689
[319]	train-mlogloss:0.72145	validation-mlogloss:0.72662
[320]	train-mlogloss:0.72109	validation-mlogloss:0.72634
[321]	train-mlogloss:0.72062	validation-mlogloss:0.72595
[322]	train-mlogloss:0.72027	validation-mlogloss:0.72574
[323]	train-mlogloss:0.71992	validation-mlogloss:0.72548
[324]	train-mlogloss:0.71959	validation-mlogloss:0.72519
[325]	train-mlogloss:0.71925	validation-mlogloss:0.72492
[326]	train-mlogloss:0.71885	validation-mlogloss:0.72463
[327]	train-mlogloss:0.71838	validation-mlogloss:0.72424
[328]	train-mlogloss:0.71811	validation-mlogloss:0.72401
[329]	train-mlogloss:0.71777	validation-mlogloss:0.72371
[330]	train-mlogloss:0.71741	validation-mlogloss:0.72337
[331]	train-mlogloss:0.71699	validation-mlogloss:0.72298
[332]	train-mlogloss:0.71664	validation-mlogloss:0.72269
[333]	train-mlogloss:0.71631	validation-mlogloss:0.72252
[334]	train-mlogloss:0.71595	validation-mlogloss:0.72221
[335]	train-mlogloss:0.71557	validation-mlogloss:0.72192
[336]	train-mlogloss:0.71525	validation-mlogloss:0.72165
[337]	train-mlogloss:0.71490	validation-mlogloss:0.72133
[338]	train-mlogloss:0.71458	validation-mlogloss:0.72100
[339]	train-mlogloss:0.71423	validation-mlogloss:0.72071
[340]	train-mlogloss:0.71391	validation-mlogloss:0.72045
[341]	train-mlogloss:0.71354	validation-mlogloss:0.72022
[342]	train-mlogloss:0.71324	validation-mlogloss:0.71988
[343]	train-mlogloss:0.71295	validation-mlogloss:0.71962
[344]	train-mlogloss:0.71255	validation-mlogloss:0.71930
[345]	train-mlogloss:0.71218	validation-mlogloss:0.71908
[346]	train-mlogloss:0.71187	validation-mlogloss:0.71884
[347]	train-mlogloss:0.71148	validation-mlogloss:0.71855
[348]	train-mlogloss:0.71106	validation-mlogloss:0.71812
[349]	train-mlogloss:0.71076	validation-mlogloss:0.71782
[350]	train-mlogloss:0.71038	validation-mlogloss:0.71753
[351]	train-mlogloss:0.71005	validation-mlogloss:0.71726
[352]	train-mlogloss:0.70962	validation-mlogloss:0.71690
[353]	train-mlogloss:0.70930	validation-mlogloss:0.71666
[354]	train-mlogloss:0.70893	validation-mlogloss:0.71641
[355]	train-mlogloss:0.70859	validation-mlogloss:0.71616
[356]	train-mlogloss:0.70820	validation-mlogloss:0.71595
[357]	train-mlogloss:0.70791	validation-mlogloss:0.71575
[358]	train-mlogloss:0.70761	validation-mlogloss:0.71556
[359]	train-mlogloss:0.70726	validation-mlogloss:0.71527
[360]	train-mlogloss:0.70688	validation-mlogloss:0.71497
[361]	train-mlogloss:0.70658	validation-mlogloss:0.71481
[362]	train-mlogloss:0.70634	validation-mlogloss:0.71460
[363]	train-mlogloss:0.70593	validation-mlogloss:0.71428
[364]	train-mlogloss:0.70563	validation-mlogloss:0.71399
[365]	train-mlogloss:0.70531	validation-mlogloss:0.71378
[366]	train-mlogloss:0.70498	validation-mlogloss:0.71353
[367]	train-mlogloss:0.70475	validation-mlogloss:0.71332
[368]	train-mlogloss:0.70441	validation-mlogloss:0.71317
[369]	train-mlogloss:0.70417	validation-mlogloss:0.71306
[370]	train-mlogloss:0.70386	validation-mlogloss:0.71288
[371]	train-mlogloss:0.70358	validation-mlogloss:0.71261
[372]	train-mlogloss:0.70320	validation-mlogloss:0.71231
[373]	train-mlogloss:0.70292	validation-mlogloss:0.71213
[374]	train-mlogloss:0.70258	validation-mlogloss:0.71183
[375]	train-mlogloss:0.70224	validation-mlogloss:0.71155
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.64 [%]
Global accuracy score (test) = 71.78 [%]
Global F1 score (train) = 73.57 [%]
Global F1 score (test) = 71.96 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.62      0.45      0.52       400
MODERATE-INTENSITY       0.58      0.84      0.69       400
         SEDENTARY       0.84      0.84      0.84       400
VIGOROUS-INTENSITY       0.94      0.74      0.83       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.72      1545
      weighted avg       0.74      0.72      0.72      1545


Accuracy capturado en la ejecución 26: 71.78 [%]
F1-score capturado en la ejecución 26: 71.96 [%]

=== EJECUCIÓN 27 ===

--- TRAIN (ejecución 27) ---

--- TEST (ejecución 27) ---
2025-11-04 10:40:22.410137: 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 10:40:22.422108: 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 00:00:1762249222.436159 1059810 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249222.440564 1059810 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249222.451028 1059810 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249222.451047 1059810 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249222.451049 1059810 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249222.451050 1059810 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:40:22.454395: 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:1.37657	validation-mlogloss:1.37639
[1]	train-mlogloss:1.36692	validation-mlogloss:1.36652
[2]	train-mlogloss:1.35769	validation-mlogloss:1.35706
[3]	train-mlogloss:1.34845	validation-mlogloss:1.34765
[4]	train-mlogloss:1.33933	validation-mlogloss:1.33843
[5]	train-mlogloss:1.33122	validation-mlogloss:1.33035
[6]	train-mlogloss:1.32248	validation-mlogloss:1.32139
[7]	train-mlogloss:1.31388	validation-mlogloss:1.31299
[8]	train-mlogloss:1.30557	validation-mlogloss:1.30460
[9]	train-mlogloss:1.29749	validation-mlogloss:1.29630
[10]	train-mlogloss:1.28949	validation-mlogloss:1.28840
[11]	train-mlogloss:1.28192	validation-mlogloss:1.28072
[12]	train-mlogloss:1.27437	validation-mlogloss:1.27302
[13]	train-mlogloss:1.26712	validation-mlogloss:1.26557
[14]	train-mlogloss:1.26016	validation-mlogloss:1.25896
[15]	train-mlogloss:1.25319	validation-mlogloss:1.25155
[16]	train-mlogloss:1.24611	validation-mlogloss:1.24441
[17]	train-mlogloss:1.23907	validation-mlogloss:1.23745
[18]	train-mlogloss:1.23210	validation-mlogloss:1.23042
[19]	train-mlogloss:1.22556	validation-mlogloss:1.22385
[20]	train-mlogloss:1.21891	validation-mlogloss:1.21715
[21]	train-mlogloss:1.21245	validation-mlogloss:1.21046
[22]	train-mlogloss:1.20605	validation-mlogloss:1.20418
[23]	train-mlogloss:1.19994	validation-mlogloss:1.19828
[24]	train-mlogloss:1.19386	validation-mlogloss:1.19216
[25]	train-mlogloss:1.18777	validation-mlogloss:1.18594
[26]	train-mlogloss:1.18190	validation-mlogloss:1.17987
[27]	train-mlogloss:1.17624	validation-mlogloss:1.17431
[28]	train-mlogloss:1.17024	validation-mlogloss:1.16825
[29]	train-mlogloss:1.16474	validation-mlogloss:1.16284
[30]	train-mlogloss:1.15893	validation-mlogloss:1.15691
[31]	train-mlogloss:1.15354	validation-mlogloss:1.15156
[32]	train-mlogloss:1.14842	validation-mlogloss:1.14628
[33]	train-mlogloss:1.14312	validation-mlogloss:1.14121
[34]	train-mlogloss:1.13792	validation-mlogloss:1.13593
[35]	train-mlogloss:1.13282	validation-mlogloss:1.13074
[36]	train-mlogloss:1.12812	validation-mlogloss:1.12640
[37]	train-mlogloss:1.12311	validation-mlogloss:1.12153
[38]	train-mlogloss:1.11860	validation-mlogloss:1.11696
[39]	train-mlogloss:1.11371	validation-mlogloss:1.11199
[40]	train-mlogloss:1.10922	validation-mlogloss:1.10753
[41]	train-mlogloss:1.10452	validation-mlogloss:1.10279
[42]	train-mlogloss:1.10016	validation-mlogloss:1.09836
[43]	train-mlogloss:1.09569	validation-mlogloss:1.09413
[44]	train-mlogloss:1.09126	validation-mlogloss:1.08953
[45]	train-mlogloss:1.08686	validation-mlogloss:1.08513
[46]	train-mlogloss:1.08276	validation-mlogloss:1.08111
[47]	train-mlogloss:1.07859	validation-mlogloss:1.07691
[48]	train-mlogloss:1.07429	validation-mlogloss:1.07249
[49]	train-mlogloss:1.07024	validation-mlogloss:1.06857
[50]	train-mlogloss:1.06645	validation-mlogloss:1.06482
[51]	train-mlogloss:1.06241	validation-mlogloss:1.06067
[52]	train-mlogloss:1.05860	validation-mlogloss:1.05672
[53]	train-mlogloss:1.05487	validation-mlogloss:1.05278
[54]	train-mlogloss:1.05115	validation-mlogloss:1.04912
[55]	train-mlogloss:1.04751	validation-mlogloss:1.04532
[56]	train-mlogloss:1.04397	validation-mlogloss:1.04160
[57]	train-mlogloss:1.04010	validation-mlogloss:1.03771
[58]	train-mlogloss:1.03657	validation-mlogloss:1.03418
[59]	train-mlogloss:1.03284	validation-mlogloss:1.03054
[60]	train-mlogloss:1.02921	validation-mlogloss:1.02685
[61]	train-mlogloss:1.02578	validation-mlogloss:1.02362
[62]	train-mlogloss:1.02257	validation-mlogloss:1.02035
[63]	train-mlogloss:1.01922	validation-mlogloss:1.01697
[64]	train-mlogloss:1.01602	validation-mlogloss:1.01368
[65]	train-mlogloss:1.01304	validation-mlogloss:1.01070
[66]	train-mlogloss:1.01004	validation-mlogloss:1.00748
[67]	train-mlogloss:1.00679	validation-mlogloss:1.00415
[68]	train-mlogloss:1.00349	validation-mlogloss:1.00086
[69]	train-mlogloss:1.00053	validation-mlogloss:0.99790
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[369]	train-mlogloss:0.70203	validation-mlogloss:0.71079
[370]	train-mlogloss:0.70173	validation-mlogloss:0.71049
[371]	train-mlogloss:0.70155	validation-mlogloss:0.71031
[372]	train-mlogloss:0.70130	validation-mlogloss:0.71003
[373]	train-mlogloss:0.70108	validation-mlogloss:0.70980
[374]	train-mlogloss:0.70073	validation-mlogloss:0.70949
[375]	train-mlogloss:0.70042	validation-mlogloss:0.70921
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[0 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.2 [%]
Global accuracy score (test) = 72.69 [%]
Global F1 score (train) = 73.12 [%]
Global F1 score (test) = 72.86 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.47      0.54       400
MODERATE-INTENSITY       0.59      0.85      0.69       400
         SEDENTARY       0.85      0.85      0.85       400
VIGOROUS-INTENSITY       0.94      0.74      0.83       345

          accuracy                           0.73      1545
         macro avg       0.75      0.73      0.73      1545
      weighted avg       0.75      0.73      0.72      1545


Accuracy capturado en la ejecución 27: 72.69 [%]
F1-score capturado en la ejecución 27: 72.86 [%]

=== EJECUCIÓN 28 ===

--- TRAIN (ejecución 28) ---

--- TEST (ejecución 28) ---
2025-11-04 10:40:38.716322: 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 10:40:38.727965: 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 00:00:1762249238.741279 1060136 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249238.745400 1060136 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249238.755288 1060136 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249238.755305 1060136 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249238.755306 1060136 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249238.755308 1060136 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:40:38.758416: 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:1.37702	validation-mlogloss:1.37648
[1]	train-mlogloss:1.36765	validation-mlogloss:1.36645
[2]	train-mlogloss:1.35844	validation-mlogloss:1.35689
[3]	train-mlogloss:1.34919	validation-mlogloss:1.34720
[4]	train-mlogloss:1.34007	validation-mlogloss:1.33793
[5]	train-mlogloss:1.33102	validation-mlogloss:1.32858
[6]	train-mlogloss:1.32285	validation-mlogloss:1.32044
[7]	train-mlogloss:1.31446	validation-mlogloss:1.31201
[8]	train-mlogloss:1.30634	validation-mlogloss:1.30399
[9]	train-mlogloss:1.29807	validation-mlogloss:1.29563
[10]	train-mlogloss:1.28999	validation-mlogloss:1.28720
[11]	train-mlogloss:1.28242	validation-mlogloss:1.27928
[12]	train-mlogloss:1.27486	validation-mlogloss:1.27120
[13]	train-mlogloss:1.26760	validation-mlogloss:1.26368
[14]	train-mlogloss:1.26012	validation-mlogloss:1.25600
[15]	train-mlogloss:1.25324	validation-mlogloss:1.24881
[16]	train-mlogloss:1.24634	validation-mlogloss:1.24191
[17]	train-mlogloss:1.23915	validation-mlogloss:1.23436
[18]	train-mlogloss:1.23219	validation-mlogloss:1.22698
[19]	train-mlogloss:1.22551	validation-mlogloss:1.22012
[20]	train-mlogloss:1.21888	validation-mlogloss:1.21325
[21]	train-mlogloss:1.21247	validation-mlogloss:1.20666
[22]	train-mlogloss:1.20586	validation-mlogloss:1.19977
[23]	train-mlogloss:1.19962	validation-mlogloss:1.19316
[24]	train-mlogloss:1.19336	validation-mlogloss:1.18684
[25]	train-mlogloss:1.18734	validation-mlogloss:1.18072
[26]	train-mlogloss:1.18166	validation-mlogloss:1.17500
[27]	train-mlogloss:1.17601	validation-mlogloss:1.16931
[28]	train-mlogloss:1.17041	validation-mlogloss:1.16359
[29]	train-mlogloss:1.16506	validation-mlogloss:1.15816
[30]	train-mlogloss:1.15958	validation-mlogloss:1.15244
[31]	train-mlogloss:1.15378	validation-mlogloss:1.14664
[32]	train-mlogloss:1.14860	validation-mlogloss:1.14164
[33]	train-mlogloss:1.14349	validation-mlogloss:1.13642
[34]	train-mlogloss:1.13841	validation-mlogloss:1.13132
[35]	train-mlogloss:1.13339	validation-mlogloss:1.12623
[36]	train-mlogloss:1.12851	validation-mlogloss:1.12120
[37]	train-mlogloss:1.12352	validation-mlogloss:1.11634
[38]	train-mlogloss:1.11893	validation-mlogloss:1.11153
[39]	train-mlogloss:1.11435	validation-mlogloss:1.10690
[40]	train-mlogloss:1.10960	validation-mlogloss:1.10188
[41]	train-mlogloss:1.10498	validation-mlogloss:1.09716
[42]	train-mlogloss:1.10015	validation-mlogloss:1.09236
[43]	train-mlogloss:1.09577	validation-mlogloss:1.08792
[44]	train-mlogloss:1.09161	validation-mlogloss:1.08371
[45]	train-mlogloss:1.08730	validation-mlogloss:1.07927
[46]	train-mlogloss:1.08303	validation-mlogloss:1.07487
[47]	train-mlogloss:1.07891	validation-mlogloss:1.07089
[48]	train-mlogloss:1.07468	validation-mlogloss:1.06694
[49]	train-mlogloss:1.07095	validation-mlogloss:1.06348
[50]	train-mlogloss:1.06682	validation-mlogloss:1.05920
[51]	train-mlogloss:1.06319	validation-mlogloss:1.05570
[52]	train-mlogloss:1.05934	validation-mlogloss:1.05177
[53]	train-mlogloss:1.05571	validation-mlogloss:1.04804
[54]	train-mlogloss:1.05181	validation-mlogloss:1.04437
[55]	train-mlogloss:1.04809	validation-mlogloss:1.04044
[56]	train-mlogloss:1.04440	validation-mlogloss:1.03675
[57]	train-mlogloss:1.04082	validation-mlogloss:1.03313
[58]	train-mlogloss:1.03735	validation-mlogloss:1.02974
[59]	train-mlogloss:1.03385	validation-mlogloss:1.02605
[60]	train-mlogloss:1.03025	validation-mlogloss:1.02226
[61]	train-mlogloss:1.02687	validation-mlogloss:1.01882
[62]	train-mlogloss:1.02368	validation-mlogloss:1.01559
[63]	train-mlogloss:1.02041	validation-mlogloss:1.01232
[64]	train-mlogloss:1.01740	validation-mlogloss:1.00930
[65]	train-mlogloss:1.01417	validation-mlogloss:1.00614
[66]	train-mlogloss:1.01109	validation-mlogloss:1.00279
[67]	train-mlogloss:1.00823	validation-mlogloss:1.00006
[68]	train-mlogloss:1.00519	validation-mlogloss:0.99696
[69]	train-mlogloss:1.00224	validation-mlogloss:0.99401
[70]	train-mlogloss:0.99937	validation-mlogloss:0.99101
[71]	train-mlogloss:0.99644	validation-mlogloss:0.98791
[72]	train-mlogloss:0.99352	validation-mlogloss:0.98493
[73]	train-mlogloss:0.99065	validation-mlogloss:0.98204
[74]	train-mlogloss:0.98782	validation-mlogloss:0.97918
[75]	train-mlogloss:0.98502	validation-mlogloss:0.97617
[76]	train-mlogloss:0.98217	validation-mlogloss:0.97336
[77]	train-mlogloss:0.97952	validation-mlogloss:0.97070
[78]	train-mlogloss:0.97661	validation-mlogloss:0.96755
[79]	train-mlogloss:0.97376	validation-mlogloss:0.96472
[80]	train-mlogloss:0.97121	validation-mlogloss:0.96209
[81]	train-mlogloss:0.96867	validation-mlogloss:0.95945
[82]	train-mlogloss:0.96618	validation-mlogloss:0.95684
[83]	train-mlogloss:0.96373	validation-mlogloss:0.95444
[84]	train-mlogloss:0.96120	validation-mlogloss:0.95190
[85]	train-mlogloss:0.95891	validation-mlogloss:0.94954
[86]	train-mlogloss:0.95656	validation-mlogloss:0.94716
[87]	train-mlogloss:0.95410	validation-mlogloss:0.94463
[88]	train-mlogloss:0.95168	validation-mlogloss:0.94221
[89]	train-mlogloss:0.94940	validation-mlogloss:0.93985
[90]	train-mlogloss:0.94726	validation-mlogloss:0.93762
[91]	train-mlogloss:0.94501	validation-mlogloss:0.93542
[92]	train-mlogloss:0.94289	validation-mlogloss:0.93318
[93]	train-mlogloss:0.94075	validation-mlogloss:0.93115
[94]	train-mlogloss:0.93857	validation-mlogloss:0.92890
[95]	train-mlogloss:0.93621	validation-mlogloss:0.92651
[96]	train-mlogloss:0.93403	validation-mlogloss:0.92419
[97]	train-mlogloss:0.93188	validation-mlogloss:0.92200
[98]	train-mlogloss:0.92962	validation-mlogloss:0.91954
[99]	train-mlogloss:0.92743	validation-mlogloss:0.91750
[100]	train-mlogloss:0.92552	validation-mlogloss:0.91554
[101]	train-mlogloss:0.92366	validation-mlogloss:0.91352
[102]	train-mlogloss:0.92168	validation-mlogloss:0.91147
[103]	train-mlogloss:0.91988	validation-mlogloss:0.90970
[104]	train-mlogloss:0.91788	validation-mlogloss:0.90782
[105]	train-mlogloss:0.91587	validation-mlogloss:0.90576
[106]	train-mlogloss:0.91380	validation-mlogloss:0.90368
[107]	train-mlogloss:0.91181	validation-mlogloss:0.90166
[108]	train-mlogloss:0.90999	validation-mlogloss:0.89982
[109]	train-mlogloss:0.90816	validation-mlogloss:0.89802
[110]	train-mlogloss:0.90633	validation-mlogloss:0.89604
[111]	train-mlogloss:0.90452	validation-mlogloss:0.89414
[112]	train-mlogloss:0.90250	validation-mlogloss:0.89210
[113]	train-mlogloss:0.90057	validation-mlogloss:0.89016
[114]	train-mlogloss:0.89897	validation-mlogloss:0.88861
[115]	train-mlogloss:0.89717	validation-mlogloss:0.88673
[116]	train-mlogloss:0.89540	validation-mlogloss:0.88486
[117]	train-mlogloss:0.89384	validation-mlogloss:0.88320
[118]	train-mlogloss:0.89224	validation-mlogloss:0.88152
[119]	train-mlogloss:0.89040	validation-mlogloss:0.87971
[120]	train-mlogloss:0.88880	validation-mlogloss:0.87806
[121]	train-mlogloss:0.88722	validation-mlogloss:0.87654
[122]	train-mlogloss:0.88567	validation-mlogloss:0.87490
[123]	train-mlogloss:0.88425	validation-mlogloss:0.87351
[124]	train-mlogloss:0.88270	validation-mlogloss:0.87200
[125]	train-mlogloss:0.88128	validation-mlogloss:0.87055
[126]	train-mlogloss:0.87990	validation-mlogloss:0.86912
[127]	train-mlogloss:0.87839	validation-mlogloss:0.86770
[128]	train-mlogloss:0.87690	validation-mlogloss:0.86614
[129]	train-mlogloss:0.87547	validation-mlogloss:0.86466
[130]	train-mlogloss:0.87404	validation-mlogloss:0.86320
[131]	train-mlogloss:0.87273	validation-mlogloss:0.86211
[132]	train-mlogloss:0.87121	validation-mlogloss:0.86070
[133]	train-mlogloss:0.86981	validation-mlogloss:0.85921
[134]	train-mlogloss:0.86823	validation-mlogloss:0.85755
[135]	train-mlogloss:0.86672	validation-mlogloss:0.85601
[136]	train-mlogloss:0.86520	validation-mlogloss:0.85448
[137]	train-mlogloss:0.86370	validation-mlogloss:0.85301
[138]	train-mlogloss:0.86244	validation-mlogloss:0.85188
[139]	train-mlogloss:0.86097	validation-mlogloss:0.85056
[140]	train-mlogloss:0.85962	validation-mlogloss:0.84919
[141]	train-mlogloss:0.85814	validation-mlogloss:0.84756
[142]	train-mlogloss:0.85676	validation-mlogloss:0.84602
[143]	train-mlogloss:0.85536	validation-mlogloss:0.84466
[144]	train-mlogloss:0.85402	validation-mlogloss:0.84339
[145]	train-mlogloss:0.85278	validation-mlogloss:0.84217
[146]	train-mlogloss:0.85141	validation-mlogloss:0.84083
[147]	train-mlogloss:0.85024	validation-mlogloss:0.83966
[148]	train-mlogloss:0.84908	validation-mlogloss:0.83858
[149]	train-mlogloss:0.84771	validation-mlogloss:0.83715
[150]	train-mlogloss:0.84648	validation-mlogloss:0.83583
[151]	train-mlogloss:0.84545	validation-mlogloss:0.83489
[152]	train-mlogloss:0.84438	validation-mlogloss:0.83381
[153]	train-mlogloss:0.84306	validation-mlogloss:0.83243
[154]	train-mlogloss:0.84179	validation-mlogloss:0.83122
[155]	train-mlogloss:0.84052	validation-mlogloss:0.82994
[156]	train-mlogloss:0.83916	validation-mlogloss:0.82865
[157]	train-mlogloss:0.83800	validation-mlogloss:0.82754
[158]	train-mlogloss:0.83669	validation-mlogloss:0.82614
[159]	train-mlogloss:0.83548	validation-mlogloss:0.82496
[160]	train-mlogloss:0.83419	validation-mlogloss:0.82376
[161]	train-mlogloss:0.83297	validation-mlogloss:0.82247
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[163]	train-mlogloss:0.83090	validation-mlogloss:0.82034
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[345]	train-mlogloss:0.71623	validation-mlogloss:0.71559
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[350]	train-mlogloss:0.71450	validation-mlogloss:0.71434
[351]	train-mlogloss:0.71412	validation-mlogloss:0.71409
[352]	train-mlogloss:0.71374	validation-mlogloss:0.71372
[353]	train-mlogloss:0.71343	validation-mlogloss:0.71343
[354]	train-mlogloss:0.71309	validation-mlogloss:0.71312
[355]	train-mlogloss:0.71271	validation-mlogloss:0.71279
[356]	train-mlogloss:0.71248	validation-mlogloss:0.71264
[357]	train-mlogloss:0.71216	validation-mlogloss:0.71231
[358]	train-mlogloss:0.71189	validation-mlogloss:0.71206
[359]	train-mlogloss:0.71154	validation-mlogloss:0.71177
[360]	train-mlogloss:0.71126	validation-mlogloss:0.71155
[361]	train-mlogloss:0.71098	validation-mlogloss:0.71130
[362]	train-mlogloss:0.71067	validation-mlogloss:0.71107
[363]	train-mlogloss:0.71034	validation-mlogloss:0.71087
[364]	train-mlogloss:0.71009	validation-mlogloss:0.71059
[365]	train-mlogloss:0.70983	validation-mlogloss:0.71037
[366]	train-mlogloss:0.70951	validation-mlogloss:0.71010
[367]	train-mlogloss:0.70930	validation-mlogloss:0.70987
[368]	train-mlogloss:0.70908	validation-mlogloss:0.70965
[369]	train-mlogloss:0.70883	validation-mlogloss:0.70942
[370]	train-mlogloss:0.70859	validation-mlogloss:0.70919
[371]	train-mlogloss:0.70828	validation-mlogloss:0.70888
[372]	train-mlogloss:0.70806	validation-mlogloss:0.70872
[373]	train-mlogloss:0.70781	validation-mlogloss:0.70846
[374]	train-mlogloss:0.70759	validation-mlogloss:0.70829
[375]	train-mlogloss:0.70740	validation-mlogloss:0.70812
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 0 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.47 [%]
Global accuracy score (test) = 70.36 [%]
Global F1 score (train) = 73.48 [%]
Global F1 score (test) = 70.62 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.58      0.44      0.50       400
MODERATE-INTENSITY       0.57      0.82      0.68       400
         SEDENTARY       0.83      0.82      0.82       400
VIGOROUS-INTENSITY       0.94      0.73      0.82       345

          accuracy                           0.70      1545
         macro avg       0.73      0.70      0.71      1545
      weighted avg       0.72      0.70      0.70      1545


Accuracy capturado en la ejecución 28: 70.36 [%]
F1-score capturado en la ejecución 28: 70.62 [%]

=== EJECUCIÓN 29 ===

--- TRAIN (ejecución 29) ---

--- TEST (ejecución 29) ---
2025-11-04 10:40:54.609798: 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 10:40:54.620807: 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 00:00:1762249254.634061 1060441 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762249254.638088 1060441 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762249254.648250 1060441 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249254.648267 1060441 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249254.648268 1060441 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762249254.648270 1060441 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-04 10:40:54.651192: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (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:1.37681	validation-mlogloss:1.37642
[1]	train-mlogloss:1.36746	validation-mlogloss:1.36706
[2]	train-mlogloss:1.35805	validation-mlogloss:1.35747
[3]	train-mlogloss:1.34950	validation-mlogloss:1.34863
[4]	train-mlogloss:1.34053	validation-mlogloss:1.33923
[5]	train-mlogloss:1.33200	validation-mlogloss:1.33049
[6]	train-mlogloss:1.32375	validation-mlogloss:1.32202
[7]	train-mlogloss:1.31539	validation-mlogloss:1.31339
[8]	train-mlogloss:1.30727	validation-mlogloss:1.30491
[9]	train-mlogloss:1.29907	validation-mlogloss:1.29625
[10]	train-mlogloss:1.29163	validation-mlogloss:1.28905
[11]	train-mlogloss:1.28375	validation-mlogloss:1.28101
[12]	train-mlogloss:1.27655	validation-mlogloss:1.27386
[13]	train-mlogloss:1.26897	validation-mlogloss:1.26635
[14]	train-mlogloss:1.26160	validation-mlogloss:1.25867
[15]	train-mlogloss:1.25481	validation-mlogloss:1.25179
[16]	train-mlogloss:1.24794	validation-mlogloss:1.24507
[17]	train-mlogloss:1.24143	validation-mlogloss:1.23845
[18]	train-mlogloss:1.23493	validation-mlogloss:1.23208
[19]	train-mlogloss:1.22843	validation-mlogloss:1.22540
[20]	train-mlogloss:1.22184	validation-mlogloss:1.21862
[21]	train-mlogloss:1.21516	validation-mlogloss:1.21177
[22]	train-mlogloss:1.20901	validation-mlogloss:1.20544
[23]	train-mlogloss:1.20251	validation-mlogloss:1.19885
[24]	train-mlogloss:1.19669	validation-mlogloss:1.19293
[25]	train-mlogloss:1.19079	validation-mlogloss:1.18693
[26]	train-mlogloss:1.18485	validation-mlogloss:1.18110
[27]	train-mlogloss:1.17899	validation-mlogloss:1.17508
[28]	train-mlogloss:1.17347	validation-mlogloss:1.16945
[29]	train-mlogloss:1.16758	validation-mlogloss:1.16349
[30]	train-mlogloss:1.16233	validation-mlogloss:1.15824
[31]	train-mlogloss:1.15674	validation-mlogloss:1.15241
[32]	train-mlogloss:1.15105	validation-mlogloss:1.14640
[33]	train-mlogloss:1.14559	validation-mlogloss:1.14071
[34]	train-mlogloss:1.14065	validation-mlogloss:1.13571
[35]	train-mlogloss:1.13556	validation-mlogloss:1.13071
[36]	train-mlogloss:1.13047	validation-mlogloss:1.12554
[37]	train-mlogloss:1.12573	validation-mlogloss:1.12071
[38]	train-mlogloss:1.12063	validation-mlogloss:1.11542
[39]	train-mlogloss:1.11607	validation-mlogloss:1.11084
[40]	train-mlogloss:1.11129	validation-mlogloss:1.10606
[41]	train-mlogloss:1.10671	validation-mlogloss:1.10133
[42]	train-mlogloss:1.10210	validation-mlogloss:1.09667
[43]	train-mlogloss:1.09760	validation-mlogloss:1.09188
[44]	train-mlogloss:1.09308	validation-mlogloss:1.08716
[45]	train-mlogloss:1.08846	validation-mlogloss:1.08238
[46]	train-mlogloss:1.08451	validation-mlogloss:1.07835
[47]	train-mlogloss:1.08053	validation-mlogloss:1.07427
[48]	train-mlogloss:1.07618	validation-mlogloss:1.06988
[49]	train-mlogloss:1.07208	validation-mlogloss:1.06559
[50]	train-mlogloss:1.06815	validation-mlogloss:1.06177
[51]	train-mlogloss:1.06448	validation-mlogloss:1.05806
[52]	train-mlogloss:1.06064	validation-mlogloss:1.05415
[53]	train-mlogloss:1.05657	validation-mlogloss:1.05023
[54]	train-mlogloss:1.05288	validation-mlogloss:1.04646
[55]	train-mlogloss:1.04904	validation-mlogloss:1.04261
[56]	train-mlogloss:1.04557	validation-mlogloss:1.03940
[57]	train-mlogloss:1.04187	validation-mlogloss:1.03562
[58]	train-mlogloss:1.03843	validation-mlogloss:1.03222
[59]	train-mlogloss:1.03486	validation-mlogloss:1.02843
[60]	train-mlogloss:1.03126	validation-mlogloss:1.02470
[61]	train-mlogloss:1.02784	validation-mlogloss:1.02133
[62]	train-mlogloss:1.02439	validation-mlogloss:1.01783
[63]	train-mlogloss:1.02113	validation-mlogloss:1.01433
[64]	train-mlogloss:1.01792	validation-mlogloss:1.01095
[65]	train-mlogloss:1.01473	validation-mlogloss:1.00773
[66]	train-mlogloss:1.01165	validation-mlogloss:1.00444
[67]	train-mlogloss:1.00850	validation-mlogloss:1.00103
[68]	train-mlogloss:1.00552	validation-mlogloss:0.99791
[69]	train-mlogloss:1.00249	validation-mlogloss:0.99467
[70]	train-mlogloss:0.99948	validation-mlogloss:0.99163
[71]	train-mlogloss:0.99651	validation-mlogloss:0.98859
[72]	train-mlogloss:0.99344	validation-mlogloss:0.98548
[73]	train-mlogloss:0.99060	validation-mlogloss:0.98261
[74]	train-mlogloss:0.98770	validation-mlogloss:0.97976
[75]	train-mlogloss:0.98496	validation-mlogloss:0.97693
[76]	train-mlogloss:0.98214	validation-mlogloss:0.97398
[77]	train-mlogloss:0.97928	validation-mlogloss:0.97107
[78]	train-mlogloss:0.97664	validation-mlogloss:0.96835
[79]	train-mlogloss:0.97381	validation-mlogloss:0.96575
[80]	train-mlogloss:0.97115	validation-mlogloss:0.96327
[81]	train-mlogloss:0.96872	validation-mlogloss:0.96094
[82]	train-mlogloss:0.96622	validation-mlogloss:0.95826
[83]	train-mlogloss:0.96357	validation-mlogloss:0.95548
[84]	train-mlogloss:0.96122	validation-mlogloss:0.95294
[85]	train-mlogloss:0.95877	validation-mlogloss:0.95059
[86]	train-mlogloss:0.95630	validation-mlogloss:0.94791
[87]	train-mlogloss:0.95392	validation-mlogloss:0.94560
[88]	train-mlogloss:0.95154	validation-mlogloss:0.94339
[89]	train-mlogloss:0.94921	validation-mlogloss:0.94088
[90]	train-mlogloss:0.94694	validation-mlogloss:0.93844
[91]	train-mlogloss:0.94466	validation-mlogloss:0.93624
[92]	train-mlogloss:0.94235	validation-mlogloss:0.93392
[93]	train-mlogloss:0.94015	validation-mlogloss:0.93173
[94]	train-mlogloss:0.93785	validation-mlogloss:0.92937
[95]	train-mlogloss:0.93562	validation-mlogloss:0.92699
[96]	train-mlogloss:0.93359	validation-mlogloss:0.92500
[97]	train-mlogloss:0.93147	validation-mlogloss:0.92300
[98]	train-mlogloss:0.92928	validation-mlogloss:0.92086
[99]	train-mlogloss:0.92716	validation-mlogloss:0.91856
[100]	train-mlogloss:0.92515	validation-mlogloss:0.91658
[101]	train-mlogloss:0.92298	validation-mlogloss:0.91440
[102]	train-mlogloss:0.92113	validation-mlogloss:0.91248
[103]	train-mlogloss:0.91901	validation-mlogloss:0.91040
[104]	train-mlogloss:0.91713	validation-mlogloss:0.90835
[105]	train-mlogloss:0.91524	validation-mlogloss:0.90642
[106]	train-mlogloss:0.91317	validation-mlogloss:0.90438
[107]	train-mlogloss:0.91123	validation-mlogloss:0.90248
[108]	train-mlogloss:0.90936	validation-mlogloss:0.90060
[109]	train-mlogloss:0.90736	validation-mlogloss:0.89861
[110]	train-mlogloss:0.90536	validation-mlogloss:0.89652
[111]	train-mlogloss:0.90356	validation-mlogloss:0.89466
[112]	train-mlogloss:0.90176	validation-mlogloss:0.89282
[113]	train-mlogloss:0.90024	validation-mlogloss:0.89135
[114]	train-mlogloss:0.89845	validation-mlogloss:0.88950
[115]	train-mlogloss:0.89669	validation-mlogloss:0.88808
[116]	train-mlogloss:0.89491	validation-mlogloss:0.88621
[117]	train-mlogloss:0.89312	validation-mlogloss:0.88438
[118]	train-mlogloss:0.89149	validation-mlogloss:0.88282
[119]	train-mlogloss:0.88982	validation-mlogloss:0.88098
[120]	train-mlogloss:0.88823	validation-mlogloss:0.87950
[121]	train-mlogloss:0.88634	validation-mlogloss:0.87756
[122]	train-mlogloss:0.88477	validation-mlogloss:0.87605
[123]	train-mlogloss:0.88324	validation-mlogloss:0.87454
[124]	train-mlogloss:0.88171	validation-mlogloss:0.87300
[125]	train-mlogloss:0.88010	validation-mlogloss:0.87139
[126]	train-mlogloss:0.87856	validation-mlogloss:0.86979
[127]	train-mlogloss:0.87701	validation-mlogloss:0.86827
[128]	train-mlogloss:0.87542	validation-mlogloss:0.86667
[129]	train-mlogloss:0.87384	validation-mlogloss:0.86510
[130]	train-mlogloss:0.87232	validation-mlogloss:0.86383
[131]	train-mlogloss:0.87083	validation-mlogloss:0.86228
[132]	train-mlogloss:0.86930	validation-mlogloss:0.86068
[133]	train-mlogloss:0.86775	validation-mlogloss:0.85918
[134]	train-mlogloss:0.86627	validation-mlogloss:0.85758
[135]	train-mlogloss:0.86482	validation-mlogloss:0.85627
[136]	train-mlogloss:0.86319	validation-mlogloss:0.85481
[137]	train-mlogloss:0.86178	validation-mlogloss:0.85334
[138]	train-mlogloss:0.86038	validation-mlogloss:0.85215
[139]	train-mlogloss:0.85903	validation-mlogloss:0.85109
[140]	train-mlogloss:0.85763	validation-mlogloss:0.84956
[141]	train-mlogloss:0.85638	validation-mlogloss:0.84817
[142]	train-mlogloss:0.85486	validation-mlogloss:0.84671
[143]	train-mlogloss:0.85350	validation-mlogloss:0.84540
[144]	train-mlogloss:0.85221	validation-mlogloss:0.84416
[145]	train-mlogloss:0.85087	validation-mlogloss:0.84270
[146]	train-mlogloss:0.84945	validation-mlogloss:0.84137
[147]	train-mlogloss:0.84816	validation-mlogloss:0.84004
[148]	train-mlogloss:0.84688	validation-mlogloss:0.83878
[149]	train-mlogloss:0.84541	validation-mlogloss:0.83729
[150]	train-mlogloss:0.84405	validation-mlogloss:0.83583
[151]	train-mlogloss:0.84281	validation-mlogloss:0.83467
[152]	train-mlogloss:0.84159	validation-mlogloss:0.83340
[153]	train-mlogloss:0.84046	validation-mlogloss:0.83221
[154]	train-mlogloss:0.83935	validation-mlogloss:0.83124
[155]	train-mlogloss:0.83804	validation-mlogloss:0.82996
[156]	train-mlogloss:0.83661	validation-mlogloss:0.82861
[157]	train-mlogloss:0.83537	validation-mlogloss:0.82740
[158]	train-mlogloss:0.83421	validation-mlogloss:0.82625
[159]	train-mlogloss:0.83289	validation-mlogloss:0.82494
[160]	train-mlogloss:0.83165	validation-mlogloss:0.82375
[161]	train-mlogloss:0.83050	validation-mlogloss:0.82268
[162]	train-mlogloss:0.82932	validation-mlogloss:0.82129
[163]	train-mlogloss:0.82826	validation-mlogloss:0.82031
[164]	train-mlogloss:0.82708	validation-mlogloss:0.81915
[165]	train-mlogloss:0.82599	validation-mlogloss:0.81813
[166]	train-mlogloss:0.82483	validation-mlogloss:0.81695
[167]	train-mlogloss:0.82367	validation-mlogloss:0.81587
[168]	train-mlogloss:0.82262	validation-mlogloss:0.81493
[169]	train-mlogloss:0.82136	validation-mlogloss:0.81369
[170]	train-mlogloss:0.82023	validation-mlogloss:0.81254
[171]	train-mlogloss:0.81914	validation-mlogloss:0.81150
[172]	train-mlogloss:0.81792	validation-mlogloss:0.81025
[173]	train-mlogloss:0.81692	validation-mlogloss:0.80928
[174]	train-mlogloss:0.81584	validation-mlogloss:0.80821
[175]	train-mlogloss:0.81477	validation-mlogloss:0.80715
[176]	train-mlogloss:0.81373	validation-mlogloss:0.80614
[177]	train-mlogloss:0.81284	validation-mlogloss:0.80528
[178]	train-mlogloss:0.81190	validation-mlogloss:0.80441
[179]	train-mlogloss:0.81093	validation-mlogloss:0.80345
[180]	train-mlogloss:0.80998	validation-mlogloss:0.80249
[181]	train-mlogloss:0.80899	validation-mlogloss:0.80149
[182]	train-mlogloss:0.80809	validation-mlogloss:0.80068
[183]	train-mlogloss:0.80713	validation-mlogloss:0.79961
[184]	train-mlogloss:0.80615	validation-mlogloss:0.79865
[185]	train-mlogloss:0.80524	validation-mlogloss:0.79783
[186]	train-mlogloss:0.80444	validation-mlogloss:0.79709
[187]	train-mlogloss:0.80356	validation-mlogloss:0.79623
[188]	train-mlogloss:0.80259	validation-mlogloss:0.79524
[189]	train-mlogloss:0.80160	validation-mlogloss:0.79421
[190]	train-mlogloss:0.80061	validation-mlogloss:0.79336
[191]	train-mlogloss:0.79972	validation-mlogloss:0.79250
[192]	train-mlogloss:0.79875	validation-mlogloss:0.79155
[193]	train-mlogloss:0.79778	validation-mlogloss:0.79058
[194]	train-mlogloss:0.79682	validation-mlogloss:0.78959
[195]	train-mlogloss:0.79570	validation-mlogloss:0.78847
[196]	train-mlogloss:0.79469	validation-mlogloss:0.78755
[197]	train-mlogloss:0.79371	validation-mlogloss:0.78651
[198]	train-mlogloss:0.79289	validation-mlogloss:0.78575
[199]	train-mlogloss:0.79207	validation-mlogloss:0.78486
[200]	train-mlogloss:0.79130	validation-mlogloss:0.78415
[201]	train-mlogloss:0.79046	validation-mlogloss:0.78340
[202]	train-mlogloss:0.78969	validation-mlogloss:0.78267
[203]	train-mlogloss:0.78881	validation-mlogloss:0.78181
[204]	train-mlogloss:0.78801	validation-mlogloss:0.78103
[205]	train-mlogloss:0.78721	validation-mlogloss:0.78033
[206]	train-mlogloss:0.78641	validation-mlogloss:0.77970
[207]	train-mlogloss:0.78564	validation-mlogloss:0.77897
[208]	train-mlogloss:0.78469	validation-mlogloss:0.77807
[209]	train-mlogloss:0.78381	validation-mlogloss:0.77726
[210]	train-mlogloss:0.78312	validation-mlogloss:0.77664
[211]	train-mlogloss:0.78229	validation-mlogloss:0.77582
[212]	train-mlogloss:0.78148	validation-mlogloss:0.77511
[213]	train-mlogloss:0.78070	validation-mlogloss:0.77432
[214]	train-mlogloss:0.77998	validation-mlogloss:0.77365
[215]	train-mlogloss:0.77913	validation-mlogloss:0.77275
[216]	train-mlogloss:0.77837	validation-mlogloss:0.77201
[217]	train-mlogloss:0.77752	validation-mlogloss:0.77120
[218]	train-mlogloss:0.77674	validation-mlogloss:0.77047
[219]	train-mlogloss:0.77597	validation-mlogloss:0.76975
[220]	train-mlogloss:0.77525	validation-mlogloss:0.76912
[221]	train-mlogloss:0.77456	validation-mlogloss:0.76845
[222]	train-mlogloss:0.77387	validation-mlogloss:0.76769
[223]	train-mlogloss:0.77313	validation-mlogloss:0.76697
[224]	train-mlogloss:0.77245	validation-mlogloss:0.76639
[225]	train-mlogloss:0.77179	validation-mlogloss:0.76570
[226]	train-mlogloss:0.77116	validation-mlogloss:0.76513
[227]	train-mlogloss:0.77056	validation-mlogloss:0.76466
[228]	train-mlogloss:0.76981	validation-mlogloss:0.76392
[229]	train-mlogloss:0.76897	validation-mlogloss:0.76311
[230]	train-mlogloss:0.76829	validation-mlogloss:0.76263
[231]	train-mlogloss:0.76757	validation-mlogloss:0.76194
[232]	train-mlogloss:0.76689	validation-mlogloss:0.76134
[233]	train-mlogloss:0.76616	validation-mlogloss:0.76070
[234]	train-mlogloss:0.76545	validation-mlogloss:0.76007
[235]	train-mlogloss:0.76472	validation-mlogloss:0.75933
[236]	train-mlogloss:0.76402	validation-mlogloss:0.75874
[237]	train-mlogloss:0.76338	validation-mlogloss:0.75812
[238]	train-mlogloss:0.76275	validation-mlogloss:0.75752
[239]	train-mlogloss:0.76203	validation-mlogloss:0.75681
[240]	train-mlogloss:0.76132	validation-mlogloss:0.75621
[241]	train-mlogloss:0.76064	validation-mlogloss:0.75545
[242]	train-mlogloss:0.75999	validation-mlogloss:0.75485
[243]	train-mlogloss:0.75925	validation-mlogloss:0.75411
[244]	train-mlogloss:0.75856	validation-mlogloss:0.75351
[245]	train-mlogloss:0.75790	validation-mlogloss:0.75282
[246]	train-mlogloss:0.75719	validation-mlogloss:0.75213
[247]	train-mlogloss:0.75652	validation-mlogloss:0.75150
[248]	train-mlogloss:0.75592	validation-mlogloss:0.75096
[249]	train-mlogloss:0.75529	validation-mlogloss:0.75035
[250]	train-mlogloss:0.75463	validation-mlogloss:0.74968
[251]	train-mlogloss:0.75401	validation-mlogloss:0.74908
[252]	train-mlogloss:0.75340	validation-mlogloss:0.74847
[253]	train-mlogloss:0.75273	validation-mlogloss:0.74773
[254]	train-mlogloss:0.75219	validation-mlogloss:0.74722
[255]	train-mlogloss:0.75156	validation-mlogloss:0.74658
[256]	train-mlogloss:0.75087	validation-mlogloss:0.74603
[257]	train-mlogloss:0.75035	validation-mlogloss:0.74560
[258]	train-mlogloss:0.74965	validation-mlogloss:0.74499
[259]	train-mlogloss:0.74915	validation-mlogloss:0.74455
[260]	train-mlogloss:0.74855	validation-mlogloss:0.74400
[261]	train-mlogloss:0.74811	validation-mlogloss:0.74358
[262]	train-mlogloss:0.74759	validation-mlogloss:0.74314
[263]	train-mlogloss:0.74693	validation-mlogloss:0.74253
[264]	train-mlogloss:0.74627	validation-mlogloss:0.74195
[265]	train-mlogloss:0.74563	validation-mlogloss:0.74139
[266]	train-mlogloss:0.74511	validation-mlogloss:0.74091
[267]	train-mlogloss:0.74457	validation-mlogloss:0.74037
[268]	train-mlogloss:0.74396	validation-mlogloss:0.73981
[269]	train-mlogloss:0.74341	validation-mlogloss:0.73938
[270]	train-mlogloss:0.74277	validation-mlogloss:0.73883
[271]	train-mlogloss:0.74227	validation-mlogloss:0.73841
[272]	train-mlogloss:0.74177	validation-mlogloss:0.73797
[273]	train-mlogloss:0.74111	validation-mlogloss:0.73733
[274]	train-mlogloss:0.74056	validation-mlogloss:0.73685
[275]	train-mlogloss:0.73997	validation-mlogloss:0.73628
[276]	train-mlogloss:0.73946	validation-mlogloss:0.73583
[277]	train-mlogloss:0.73899	validation-mlogloss:0.73539
[278]	train-mlogloss:0.73857	validation-mlogloss:0.73499
[279]	train-mlogloss:0.73805	validation-mlogloss:0.73451
[280]	train-mlogloss:0.73751	validation-mlogloss:0.73405
[281]	train-mlogloss:0.73694	validation-mlogloss:0.73357
[282]	train-mlogloss:0.73649	validation-mlogloss:0.73324
[283]	train-mlogloss:0.73599	validation-mlogloss:0.73276
[284]	train-mlogloss:0.73558	validation-mlogloss:0.73240
[285]	train-mlogloss:0.73508	validation-mlogloss:0.73197
[286]	train-mlogloss:0.73452	validation-mlogloss:0.73150
[287]	train-mlogloss:0.73408	validation-mlogloss:0.73118
[288]	train-mlogloss:0.73361	validation-mlogloss:0.73071
[289]	train-mlogloss:0.73314	validation-mlogloss:0.73044
[290]	train-mlogloss:0.73272	validation-mlogloss:0.73012
[291]	train-mlogloss:0.73227	validation-mlogloss:0.72971
[292]	train-mlogloss:0.73177	validation-mlogloss:0.72921
[293]	train-mlogloss:0.73136	validation-mlogloss:0.72888
[294]	train-mlogloss:0.73096	validation-mlogloss:0.72848
[295]	train-mlogloss:0.73051	validation-mlogloss:0.72813
[296]	train-mlogloss:0.73003	validation-mlogloss:0.72776
[297]	train-mlogloss:0.72956	validation-mlogloss:0.72730
[298]	train-mlogloss:0.72912	validation-mlogloss:0.72696
[299]	train-mlogloss:0.72864	validation-mlogloss:0.72655
[300]	train-mlogloss:0.72824	validation-mlogloss:0.72619
[301]	train-mlogloss:0.72777	validation-mlogloss:0.72577
[302]	train-mlogloss:0.72736	validation-mlogloss:0.72545
[303]	train-mlogloss:0.72685	validation-mlogloss:0.72510
[304]	train-mlogloss:0.72643	validation-mlogloss:0.72469
[305]	train-mlogloss:0.72596	validation-mlogloss:0.72422
[306]	train-mlogloss:0.72559	validation-mlogloss:0.72391
[307]	train-mlogloss:0.72519	validation-mlogloss:0.72346
[308]	train-mlogloss:0.72485	validation-mlogloss:0.72313
[309]	train-mlogloss:0.72443	validation-mlogloss:0.72273
[310]	train-mlogloss:0.72398	validation-mlogloss:0.72241
[311]	train-mlogloss:0.72352	validation-mlogloss:0.72208
[312]	train-mlogloss:0.72308	validation-mlogloss:0.72158
[313]	train-mlogloss:0.72264	validation-mlogloss:0.72124
[314]	train-mlogloss:0.72231	validation-mlogloss:0.72094
[315]	train-mlogloss:0.72187	validation-mlogloss:0.72060
[316]	train-mlogloss:0.72143	validation-mlogloss:0.72020
[317]	train-mlogloss:0.72096	validation-mlogloss:0.71984
[318]	train-mlogloss:0.72060	validation-mlogloss:0.71953
[319]	train-mlogloss:0.72028	validation-mlogloss:0.71922
[320]	train-mlogloss:0.71992	validation-mlogloss:0.71894
[321]	train-mlogloss:0.71958	validation-mlogloss:0.71859
[322]	train-mlogloss:0.71912	validation-mlogloss:0.71813
[323]	train-mlogloss:0.71870	validation-mlogloss:0.71770
[324]	train-mlogloss:0.71837	validation-mlogloss:0.71746
[325]	train-mlogloss:0.71800	validation-mlogloss:0.71718
[326]	train-mlogloss:0.71763	validation-mlogloss:0.71683
[327]	train-mlogloss:0.71730	validation-mlogloss:0.71658
[328]	train-mlogloss:0.71689	validation-mlogloss:0.71628
[329]	train-mlogloss:0.71654	validation-mlogloss:0.71598
[330]	train-mlogloss:0.71625	validation-mlogloss:0.71572
[331]	train-mlogloss:0.71585	validation-mlogloss:0.71536
[332]	train-mlogloss:0.71547	validation-mlogloss:0.71498
[333]	train-mlogloss:0.71509	validation-mlogloss:0.71461
[334]	train-mlogloss:0.71462	validation-mlogloss:0.71424
[335]	train-mlogloss:0.71422	validation-mlogloss:0.71388
[336]	train-mlogloss:0.71388	validation-mlogloss:0.71357
[337]	train-mlogloss:0.71354	validation-mlogloss:0.71328
[338]	train-mlogloss:0.71312	validation-mlogloss:0.71298
[339]	train-mlogloss:0.71278	validation-mlogloss:0.71278
[340]	train-mlogloss:0.71243	validation-mlogloss:0.71245
[341]	train-mlogloss:0.71204	validation-mlogloss:0.71217
[342]	train-mlogloss:0.71165	validation-mlogloss:0.71180
[343]	train-mlogloss:0.71130	validation-mlogloss:0.71152
[344]	train-mlogloss:0.71103	validation-mlogloss:0.71127
[345]	train-mlogloss:0.71066	validation-mlogloss:0.71094
[346]	train-mlogloss:0.71035	validation-mlogloss:0.71067
[347]	train-mlogloss:0.70996	validation-mlogloss:0.71031
[348]	train-mlogloss:0.70958	validation-mlogloss:0.70995
[349]	train-mlogloss:0.70926	validation-mlogloss:0.70971
[350]	train-mlogloss:0.70894	validation-mlogloss:0.70945
[351]	train-mlogloss:0.70864	validation-mlogloss:0.70922
[352]	train-mlogloss:0.70825	validation-mlogloss:0.70887
[353]	train-mlogloss:0.70798	validation-mlogloss:0.70864
[354]	train-mlogloss:0.70769	validation-mlogloss:0.70843
[355]	train-mlogloss:0.70734	validation-mlogloss:0.70817
[356]	train-mlogloss:0.70699	validation-mlogloss:0.70783
[357]	train-mlogloss:0.70671	validation-mlogloss:0.70759
[358]	train-mlogloss:0.70645	validation-mlogloss:0.70744
[359]	train-mlogloss:0.70620	validation-mlogloss:0.70730
[360]	train-mlogloss:0.70583	validation-mlogloss:0.70696
[361]	train-mlogloss:0.70555	validation-mlogloss:0.70669
[362]	train-mlogloss:0.70525	validation-mlogloss:0.70641
[363]	train-mlogloss:0.70498	validation-mlogloss:0.70621
[364]	train-mlogloss:0.70468	validation-mlogloss:0.70593
[365]	train-mlogloss:0.70434	validation-mlogloss:0.70563
[366]	train-mlogloss:0.70406	validation-mlogloss:0.70536
[367]	train-mlogloss:0.70380	validation-mlogloss:0.70517
[368]	train-mlogloss:0.70353	validation-mlogloss:0.70504
[369]	train-mlogloss:0.70325	validation-mlogloss:0.70475
[370]	train-mlogloss:0.70293	validation-mlogloss:0.70454
[371]	train-mlogloss:0.70268	validation-mlogloss:0.70431
[372]	train-mlogloss:0.70239	validation-mlogloss:0.70401
[373]	train-mlogloss:0.70214	validation-mlogloss:0.70383
[374]	train-mlogloss:0.70189	validation-mlogloss:0.70361
[375]	train-mlogloss:0.70157	validation-mlogloss:0.70344
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)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 0 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.54 [%]
Global accuracy score (test) = 71.84 [%]
Global F1 score (train) = 73.48 [%]
Global F1 score (test) = 72.15 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.60      0.47      0.52       400
MODERATE-INTENSITY       0.59      0.84      0.69       400
         SEDENTARY       0.84      0.83      0.83       400
VIGOROUS-INTENSITY       0.96      0.74      0.84       345

          accuracy                           0.72      1545
         macro avg       0.75      0.72      0.72      1545
      weighted avg       0.74      0.72      0.72      1545


Accuracy capturado en la ejecución 29: 71.84 [%]
F1-score capturado en la ejecución 29: 72.15 [%]

=== 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}
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Training a non-convolutional model.
Loaded model from disk.
(1545, 91)
(10438, 91)
[[1.]
 [1.]
 [1.]
 ...
 [2.]
 [2.]
 [2.]]
(1545, 1)
[1 1 1 ... 2 2 2]
(1545,)
-------------------------------------------------

Global accuracy score (train) = 73.17 [%]
Global accuracy score (test) = 70.87 [%]
Global F1 score (train) = 73.03 [%]
Global F1 score (test) = 71.36 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.58      0.48      0.53       400
MODERATE-INTENSITY       0.58      0.79      0.67       400
         SEDENTARY       0.84      0.83      0.84       400
VIGOROUS-INTENSITY       0.94      0.73      0.82       345

          accuracy                           0.71      1545
         macro avg       0.73      0.71      0.71      1545
      weighted avg       0.73      0.71      0.71      1545


Accuracy capturado en la ejecución 30: 70.87 [%]
F1-score capturado en la ejecución 30: 71.36 [%]

=== RESUMEN FINAL ===
Accuracies: [72.49, 71.59, 70.49, 71.65, 71.07, 72.88, 71.2, 69.45, 72.1, 72.04, 72.23, 71.13, 72.62, 71.46, 72.43, 72.3, 72.56, 72.94, 72.1, 71.52, 71.59, 71.78, 71.91, 71.78, 72.17, 71.78, 72.69, 70.36, 71.84, 70.87]
F1-scores: [72.78, 72.08, 70.62, 71.75, 71.27, 72.95, 71.75, 70.04, 72.35, 72.36, 72.15, 71.3, 72.95, 71.75, 72.72, 72.54, 72.62, 73.15, 72.36, 71.58, 71.81, 72.02, 72.04, 71.96, 72.42, 71.96, 72.86, 70.62, 72.15, 71.36]
Accuracy mean: 71.7673 | std: 0.7745
F1 mean: 72.0090 | std: 0.7249

Resultados guardados en /mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_C/case_C_XGB_acc_gyr_17_superclasses_CPA_METs/metrics_test.npz
