2025-11-06 14:04:13.920902: 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`.
2025-11-06 14:04:13.932680: 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 00:00:1762434253.946525 1370068 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434253.950779 1370068 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434253.961271 1370068 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434253.961291 1370068 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434253.961294 1370068 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434253.961296 1370068 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:04:13.964550: 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(
2025-11-06 14:04:21,828	INFO worker.py:1927 -- Started a local Ray instance.
2025-11-06 14:04:22,491	INFO tune.py:253 -- Initializing Ray automatically. For cluster usage or custom Ray initialization, call `ray.init(...)` before `Tuner(...)`.
2025-11-06 14:04:22,557	INFO trial.py:182 -- Creating a new dirname dir_1d10d_2f38 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,560	INFO trial.py:182 -- Creating a new dirname dir_1d10d_6b8d because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,562	INFO trial.py:182 -- Creating a new dirname dir_1d10d_5688 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,565	INFO trial.py:182 -- Creating a new dirname dir_1d10d_2b1f because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,567	INFO trial.py:182 -- Creating a new dirname dir_1d10d_4884 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,569	INFO trial.py:182 -- Creating a new dirname dir_1d10d_9012 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,571	INFO trial.py:182 -- Creating a new dirname dir_1d10d_965a because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,574	INFO trial.py:182 -- Creating a new dirname dir_1d10d_2a98 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,577	INFO trial.py:182 -- Creating a new dirname dir_1d10d_fc9a because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,580	INFO trial.py:182 -- Creating a new dirname dir_1d10d_b042 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,583	INFO trial.py:182 -- Creating a new dirname dir_1d10d_a79f because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,586	INFO trial.py:182 -- Creating a new dirname dir_1d10d_5658 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,589	INFO trial.py:182 -- Creating a new dirname dir_1d10d_db70 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,593	INFO trial.py:182 -- Creating a new dirname dir_1d10d_8636 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,596	INFO trial.py:182 -- Creating a new dirname dir_1d10d_b232 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,599	INFO trial.py:182 -- Creating a new dirname dir_1d10d_7977 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,603	INFO trial.py:182 -- Creating a new dirname dir_1d10d_66eb because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,607	INFO trial.py:182 -- Creating a new dirname dir_1d10d_b380 because trial dirname 'dir_1d10d' already exists.
2025-11-06 14:04:22,617	INFO trial.py:182 -- Creating a new dirname dir_1d10d_70b6 because trial dirname 'dir_1d10d' already exists.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
Se lanza la búsqueda de hiperparámetros óptimos del modelo.
╭───────────────────────────────────────────────────────────────────╮
│ Configuration for experiment     XGBoost_hyperparameters_tuning   │
├───────────────────────────────────────────────────────────────────┤
│ Search algorithm                 BasicVariantGenerator            │
│ Scheduler                        AsyncHyperBandScheduler          │
│ Number of trials                 20                               │
╰───────────────────────────────────────────────────────────────────╯

View detailed results here: /mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_PI/case_PI_XGB_acc_17_classes/XGBoost_hyperparameters_tuning
To visualize your results with TensorBoard, run: `tensorboard --logdir /tmp/ray/session_2025-11-06_14-04-20_104561_1370068/artifacts/2025-11-06_14-04-22/XGBoost_hyperparameters_tuning/driver_artifacts`

Trial status: 20 PENDING
Current time: 2025-11-06 14:04:22. Total running time: 0s
Logical resource usage: 18.0/20 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_1d10d    PENDING                  736             3        0.00672781      0.518944             0.847053   25.8745                   133      17.7035        18.1901              7794 │
│ trial_1d10d    PENDING                  630             2        0.0096993       0.700232             0.807142   27.2881                   105     149.378        389.531               3899 │
│ trial_1d10d    PENDING                  216             3        0.0119583       0.849878             0.80138    24.0381                   149     102.201          7.6987              5283 │
│ trial_1d10d    PENDING                  617             3        0.0179237       0.533623             0.847934   19.913                    176     148.862         53.1872               479 │
│ trial_1d10d    PENDING                  631             2        0.0094698       0.843762             0.697157   24.2091                   175      65.1783        15.4702              3650 │
│ trial_1d10d    PENDING                  319             3        0.0121164       0.672751             0.67354     5.06911                  184       1.7707        10.6008              8252 │
│ trial_1d10d    PENDING                  741             2        0.0126543       0.793417             0.541353   23.6833                   153     114.485        299.831               1495 │
│ trial_1d10d    PENDING                  761             2        0.0085859       0.720189             0.81877     5.39026                   53      11.4473         6.57397             9857 │
│ trial_1d10d    PENDING                  619             2        0.0147093       0.716416             0.75808    11.4587                   112      34.1481       381.763               8829 │
│ trial_1d10d    PENDING                  495             2        0.00617581      0.771088             0.555695    6.73036                  107     836.851        757.965               3602 │
│ trial_1d10d    PENDING                  392             2        0.00876909      0.636594             0.762604   13.8642                    54      23.4307         6.87095             1078 │
│ trial_1d10d    PENDING                  370             2        0.0101514       0.636663             0.796814   22.6373                   112      12.6395       809.842               4815 │
│ trial_1d10d    PENDING                  676             3        0.0184132       0.797429             0.717871   29.3403                   127       9.36209      138.236                874 │
│ trial_1d10d    PENDING                  731             3        0.00563236      0.532872             0.685933   28.1517                   110       4.74275       10.1884               799 │
│ trial_1d10d    PENDING                  683             3        0.00674663      0.818934             0.83247    20.9062                   132       4.55489       15.8284              3471 │
│ trial_1d10d    PENDING                  564             3        0.0100275       0.510695             0.610236   11.4704                   150     238.105         15.4943              8834 │
│ trial_1d10d    PENDING                  374             3        0.00901681      0.533349             0.541881   10.6509                    54     624.245        151.746               1137 │
│ trial_1d10d    PENDING                  403             3        0.0137126       0.678732             0.592672   26.9875                    68       1.66332      657.617               8773 │
│ trial_1d10d    PENDING                  281             3        0.0136754       0.770822             0.795709   10.2767                    80      40.9199       343.147               5960 │
│ trial_1d10d    PENDING                  249             2        0.0117756       0.569994             0.593681    8.16291                   93     154.54          48.2581              4887 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.75808 │
│ gamma                        11.4587 │
│ learning_rate                0.01471 │
│ max_depth                          2 │
│ min_child_weight                 112 │
│ num_boost_round                  619 │
│ random_state                    8829 │
│ reg_alpha                    34.1481 │
│ reg_lambda                   381.763 │
│ subsample                    0.71642 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.61024 │
│ gamma                        11.4704 │
│ learning_rate                0.01003 │
│ max_depth                          3 │
│ min_child_weight                 150 │
│ num_boost_round                  564 │
│ random_state                    8834 │
│ reg_alpha                    238.105 │
│ reg_lambda                   15.4943 │
│ subsample                    0.51069 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.71787 │
│ gamma                        29.3403 │
│ learning_rate                0.01841 │
│ max_depth                          3 │
│ min_child_weight                 127 │
│ num_boost_round                  676 │
│ random_state                     874 │
│ reg_alpha                    9.36209 │
│ reg_lambda                   138.236 │
│ subsample                    0.79743 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.67354 │
│ gamma                        5.06911 │
│ learning_rate                0.01212 │
│ max_depth                          3 │
│ min_child_weight                 184 │
│ num_boost_round                  319 │
│ random_state                    8252 │
│ reg_alpha                     1.7707 │
│ reg_lambda                   10.6008 │
│ subsample                    0.67275 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.59267 │
│ gamma                        26.9875 │
│ learning_rate                0.01371 │
│ max_depth                          3 │
│ min_child_weight                  68 │
│ num_boost_round                  403 │
│ random_state                    8773 │
│ reg_alpha                    1.66332 │
│ reg_lambda                   657.617 │
│ subsample                    0.67873 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.80714 │
│ gamma                        27.2881 │
│ learning_rate                 0.0097 │
│ max_depth                          2 │
│ min_child_weight                 105 │
│ num_boost_round                  630 │
│ random_state                    3899 │
│ reg_alpha                    149.378 │
│ reg_lambda                   389.531 │
│ subsample                    0.70023 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.68593 │
│ gamma                        28.1517 │
│ learning_rate                0.00563 │
│ max_depth                          3 │
│ min_child_weight                 110 │
│ num_boost_round                  731 │
│ random_state                     799 │
│ reg_alpha                    4.74275 │
│ reg_lambda                   10.1884 │
│ subsample                    0.53287 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree              0.7626 │
│ gamma                        13.8642 │
│ learning_rate                0.00877 │
│ max_depth                          2 │
│ min_child_weight                  54 │
│ num_boost_round                  392 │
│ random_state                    1078 │
│ reg_alpha                    23.4307 │
│ reg_lambda                   6.87095 │
│ subsample                    0.63659 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.80138 │
│ gamma                        24.0381 │
│ learning_rate                0.01196 │
│ max_depth                          3 │
│ min_child_weight                 149 │
│ num_boost_round                  216 │
│ random_state                    5283 │
│ reg_alpha                    102.201 │
│ reg_lambda                    7.6987 │
│ subsample                    0.84988 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.69716 │
│ gamma                        24.2091 │
│ learning_rate                0.00947 │
│ max_depth                          2 │
│ min_child_weight                 175 │
│ num_boost_round                  631 │
│ random_state                    3650 │
│ reg_alpha                    65.1783 │
│ reg_lambda                   15.4702 │
│ subsample                    0.84376 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.84793 │
│ gamma                         19.913 │
│ learning_rate                0.01792 │
│ max_depth                          3 │
│ min_child_weight                 176 │
│ num_boost_round                  617 │
│ random_state                     479 │
│ reg_alpha                    148.862 │
│ reg_lambda                   53.1872 │
│ subsample                    0.53362 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.83247 │
│ gamma                        20.9062 │
│ learning_rate                0.00675 │
│ max_depth                          3 │
│ min_child_weight                 132 │
│ num_boost_round                  683 │
│ random_state                    3471 │
│ reg_alpha                    4.55489 │
│ reg_lambda                   15.8284 │
│ subsample                    0.81893 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.54135 │
│ gamma                        23.6833 │
│ learning_rate                0.01265 │
│ max_depth                          2 │
│ min_child_weight                 153 │
│ num_boost_round                  741 │
│ random_state                    1495 │
│ reg_alpha                    114.485 │
│ reg_lambda                   299.831 │
│ subsample                    0.79342 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.81877 │
│ gamma                        5.39026 │
│ learning_rate                0.00859 │
│ max_depth                          2 │
│ min_child_weight                  53 │
│ num_boost_round                  761 │
│ random_state                    9857 │
│ reg_alpha                    11.4473 │
│ reg_lambda                   6.57397 │
│ subsample                    0.72019 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.59368 │
│ gamma                        8.16291 │
│ learning_rate                0.01178 │
│ max_depth                          2 │
│ min_child_weight                  93 │
│ num_boost_round                  249 │
│ random_state                    4887 │
│ reg_alpha                     154.54 │
│ reg_lambda                   48.2581 │
│ subsample                    0.56999 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.55569 │
│ gamma                        6.73036 │
│ learning_rate                0.00618 │
│ max_depth                          2 │
│ min_child_weight                 107 │
│ num_boost_round                  495 │
│ random_state                    3602 │
│ reg_alpha                    836.851 │
│ reg_lambda                   757.965 │
│ subsample                    0.77109 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.79681 │
│ gamma                        22.6373 │
│ learning_rate                0.01015 │
│ max_depth                          2 │
│ min_child_weight                 112 │
│ num_boost_round                  370 │
│ random_state                    4815 │
│ reg_alpha                    12.6395 │
│ reg_lambda                   809.842 │
│ subsample                    0.63666 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.84705 │
│ gamma                        25.8745 │
│ learning_rate                0.00673 │
│ max_depth                          3 │
│ min_child_weight                 133 │
│ num_boost_round                  736 │
│ random_state                    7794 │
│ reg_alpha                    17.7035 │
│ reg_lambda                   18.1901 │
│ subsample                    0.51894 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
[36m(train_xgb_ray_tune pid=1371793)[0m 2025-11-06 14:04:25.801523: 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=1371761)[0m 2025-11-06 14:04:25.876746: 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=1371761)[0m WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
[36m(train_xgb_ray_tune pid=1371761)[0m E0000 00:00:1762434265.903758 1372967 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=1371761)[0m E0000 00:00:1762434265.911806 1372967 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=1371796)[0m W0000 00:00:1762434265.904202 1372934 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=1371796)[0m W0000 00:00:1762434265.904230 1372934 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=1371796)[0m W0000 00:00:1762434265.904233 1372934 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=1371796)[0m W0000 00:00:1762434265.904235 1372934 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=1371796)[0m 2025-11-06 14:04:25.909884: 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=1371796)[0m To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.79571 │
│ gamma                        10.2767 │
│ learning_rate                0.01368 │
│ max_depth                          3 │
│ min_child_weight                  80 │
│ num_boost_round                  281 │
│ random_state                    5960 │
│ reg_alpha                    40.9199 │
│ reg_lambda                   343.147 │
│ subsample                    0.77082 │
╰──────────────────────────────────────╯
Trial trial_1d10d started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1d10d config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.54188 │
│ gamma                        10.6509 │
│ learning_rate                0.00902 │
│ max_depth                          3 │
│ min_child_weight                  54 │
│ num_boost_round                  374 │
│ random_state                    1137 │
│ reg_alpha                    624.245 │
│ reg_lambda                   151.746 │
│ subsample                    0.53335 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1371796)[0m [0]	train-mlogloss:2.70469	validation-mlogloss:2.70464
[36m(train_xgb_ray_tune pid=1371796)[0m [1]	train-mlogloss:2.70132	validation-mlogloss:2.70121
[36m(train_xgb_ray_tune pid=1371796)[0m [2]	train-mlogloss:2.69812	validation-mlogloss:2.69773
[36m(train_xgb_ray_tune pid=1371793)[0m [0]	train-mlogloss:2.69887	validation-mlogloss:2.69871
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[36m(train_xgb_ray_tune pid=1371764)[0m [8]	train-mlogloss:2.57992	validation-mlogloss:2.58250
[36m(train_xgb_ray_tune pid=1371781)[0m [9]	train-mlogloss:2.61155	validation-mlogloss:2.60884
[36m(train_xgb_ray_tune pid=1371783)[0m [7]	train-mlogloss:2.61699	validation-mlogloss:2.61827
[36m(train_xgb_ray_tune pid=1371763)[0m [6]	train-mlogloss:2.64080	validation-mlogloss:2.64031
[36m(train_xgb_ray_tune pid=1371793)[0m [13]	train-mlogloss:2.58462	validation-mlogloss:2.58304
[36m(train_xgb_ray_tune pid=1371795)[0m [8]	train-mlogloss:2.54494	validation-mlogloss:2.54684
[36m(train_xgb_ray_tune pid=1371780)[0m [9]	train-mlogloss:2.62427	validation-mlogloss:2.62469
[36m(train_xgb_ray_tune pid=1371754)[0m [5]	train-mlogloss:2.65903	validation-mlogloss:2.65895
[36m(train_xgb_ray_tune pid=1371782)[0m [6]	train-mlogloss:2.63381	validation-mlogloss:2.63476
[36m(train_xgb_ray_tune pid=1371794)[0m [10]	train-mlogloss:2.62744	validation-mlogloss:2.62621
[36m(train_xgb_ray_tune pid=1371786)[0m [5]	train-mlogloss:2.62312	validation-mlogloss:2.62592
[36m(train_xgb_ray_tune pid=1371787)[0m [11]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371755)[0m [11]	train-mlogloss:2.55321	validation-mlogloss:2.55784
[36m(train_xgb_ray_tune pid=1371748)[0m [8]	train-mlogloss:2.67180	validation-mlogloss:2.67060
[36m(train_xgb_ray_tune pid=1371784)[0m [9]	train-mlogloss:2.55938	validation-mlogloss:2.55822
[36m(train_xgb_ray_tune pid=1371766)[0m [8]	train-mlogloss:2.64893	validation-mlogloss:2.64746
[36m(train_xgb_ray_tune pid=1371796)[0m [16]	train-mlogloss:2.65593	validation-mlogloss:2.65486
[36m(train_xgb_ray_tune pid=1371762)[0m [9]	train-mlogloss:2.62822	validation-mlogloss:2.62920
[36m(train_xgb_ray_tune pid=1371761)[0m [12]	train-mlogloss:2.65139	validation-mlogloss:2.64985
[36m(train_xgb_ray_tune pid=1371764)[0m [9]	train-mlogloss:2.56660	validation-mlogloss:2.56948
[36m(train_xgb_ray_tune pid=1371781)[0m [10]	train-mlogloss:2.60254	validation-mlogloss:2.59947
[36m(train_xgb_ray_tune pid=1371754)[0m [6]	train-mlogloss:2.65121	validation-mlogloss:2.65112
[36m(train_xgb_ray_tune pid=1371761)[0m [13]	train-mlogloss:2.64700	validation-mlogloss:2.64534
[36m(train_xgb_ray_tune pid=1371764)[0m [10]	train-mlogloss:2.55318	validation-mlogloss:2.55645
[36m(train_xgb_ray_tune pid=1371781)[0m [11]	train-mlogloss:2.59330	validation-mlogloss:2.59002
[36m(train_xgb_ray_tune pid=1371786)[0m [6]	train-mlogloss:2.61012	validation-mlogloss:2.61355
[36m(train_xgb_ray_tune pid=1371796)[0m [17]	train-mlogloss:2.65284	validation-mlogloss:2.65172
[36m(train_xgb_ray_tune pid=1371796)[0m [18]	train-mlogloss:2.64996	validation-mlogloss:2.64878
[36m(train_xgb_ray_tune pid=1371793)[0m [14]	train-mlogloss:2.57605	validation-mlogloss:2.57411
[36m(train_xgb_ray_tune pid=1371793)[0m [15]	train-mlogloss:2.56753	validation-mlogloss:2.56526
[36m(train_xgb_ray_tune pid=1371748)[0m [9]	train-mlogloss:2.66784	validation-mlogloss:2.66647
[36m(train_xgb_ray_tune pid=1371762)[0m [10]	train-mlogloss:2.62065	validation-mlogloss:2.62169
[36m(train_xgb_ray_tune pid=1371795)[0m [9]	train-mlogloss:2.52804	validation-mlogloss:2.53017
[36m(train_xgb_ray_tune pid=1371787)[0m [12]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371787)[0m [13]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371782)[0m [7]	train-mlogloss:2.62351	validation-mlogloss:2.62485
[36m(train_xgb_ray_tune pid=1371783)[0m [8]	train-mlogloss:2.60605	validation-mlogloss:2.60752
[36m(train_xgb_ray_tune pid=1371783)[0m [9]	train-mlogloss:2.59586	validation-mlogloss:2.59751
[36m(train_xgb_ray_tune pid=1371794)[0m [11]	train-mlogloss:2.62054	validation-mlogloss:2.61910
[36m(train_xgb_ray_tune pid=1371794)[0m [12]	train-mlogloss:2.61389	validation-mlogloss:2.61240
[36m(train_xgb_ray_tune pid=1371755)[0m [12]	train-mlogloss:2.54159	validation-mlogloss:2.54659
[36m(train_xgb_ray_tune pid=1371784)[0m [10]	train-mlogloss:2.54545	validation-mlogloss:2.54387
[36m(train_xgb_ray_tune pid=1371766)[0m [9]	train-mlogloss:2.64273	validation-mlogloss:2.64116
[36m(train_xgb_ray_tune pid=1371785)[0m [0]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371763)[0m [7]	train-mlogloss:2.63165	validation-mlogloss:2.63122
[36m(train_xgb_ray_tune pid=1371763)[0m [8]	train-mlogloss:2.62240	validation-mlogloss:2.62195
[36m(train_xgb_ray_tune pid=1371780)[0m [10]	train-mlogloss:2.61681	validation-mlogloss:2.61749
[36m(train_xgb_ray_tune pid=1371780)[0m [11]	train-mlogloss:2.60878	validation-mlogloss:2.60962
[36m(train_xgb_ray_tune pid=1371786)[0m [7]	train-mlogloss:2.59724	validation-mlogloss:2.60126
[36m(train_xgb_ray_tune pid=1371795)[0m [10]	train-mlogloss:2.51138	validation-mlogloss:2.51364
[36m(train_xgb_ray_tune pid=1371787)[0m [14]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371766)[0m [10]	train-mlogloss:2.63636	validation-mlogloss:2.63451
[36m(train_xgb_ray_tune pid=1371748)[0m [10]	train-mlogloss:2.66390	validation-mlogloss:2.66240
[36m(train_xgb_ray_tune pid=1371782)[0m [8]	train-mlogloss:2.61343	validation-mlogloss:2.61492
[36m(train_xgb_ray_tune pid=1371784)[0m [11]	train-mlogloss:2.53206	validation-mlogloss:2.53041
[36m(train_xgb_ray_tune pid=1371754)[0m [7]	train-mlogloss:2.64334	validation-mlogloss:2.64332
[36m(train_xgb_ray_tune pid=1371761)[0m [14]	train-mlogloss:2.64275	validation-mlogloss:2.64091
[36m(train_xgb_ray_tune pid=1371764)[0m [11]	train-mlogloss:2.54023	validation-mlogloss:2.54398
[36m(train_xgb_ray_tune pid=1371781)[0m [12]	train-mlogloss:2.58450	validation-mlogloss:2.58106
[36m(train_xgb_ray_tune pid=1371796)[0m [19]	train-mlogloss:2.64702	validation-mlogloss:2.64575
[36m(train_xgb_ray_tune pid=1371793)[0m [16]	train-mlogloss:2.55955	validation-mlogloss:2.55738
[36m(train_xgb_ray_tune pid=1371762)[0m [11]	train-mlogloss:2.61324	validation-mlogloss:2.61443
[36m(train_xgb_ray_tune pid=1371783)[0m [10]	train-mlogloss:2.58549	validation-mlogloss:2.58720
[36m(train_xgb_ray_tune pid=1371794)[0m [13]	train-mlogloss:2.60686	validation-mlogloss:2.60537
[36m(train_xgb_ray_tune pid=1371755)[0m [13]	train-mlogloss:2.53003	validation-mlogloss:2.53530
[36m(train_xgb_ray_tune pid=1371766)[0m [11]	train-mlogloss:2.62998	validation-mlogloss:2.62802
[36m(train_xgb_ray_tune pid=1371785)[0m [1]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371763)[0m [9]	train-mlogloss:2.61354	validation-mlogloss:2.61326
[36m(train_xgb_ray_tune pid=1371780)[0m [12]	train-mlogloss:2.60124	validation-mlogloss:2.60227
[36m(train_xgb_ray_tune pid=1371761)[0m [15]	train-mlogloss:2.63867	validation-mlogloss:2.63674
[36m(train_xgb_ray_tune pid=1371786)[0m [8]	train-mlogloss:2.58482	validation-mlogloss:2.58933
[36m(train_xgb_ray_tune pid=1371748)[0m [11]	train-mlogloss:2.66000	validation-mlogloss:2.65837
[36m(train_xgb_ray_tune pid=1371787)[0m [15]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371764)[0m [12]	train-mlogloss:2.52797	validation-mlogloss:2.53199
[36m(train_xgb_ray_tune pid=1371782)[0m [9]	train-mlogloss:2.60369	validation-mlogloss:2.60554
[36m(train_xgb_ray_tune pid=1371794)[0m [14]	train-mlogloss:2.59976	validation-mlogloss:2.59814
[36m(train_xgb_ray_tune pid=1371755)[0m [14]	train-mlogloss:2.51907	validation-mlogloss:2.52482
[36m(train_xgb_ray_tune pid=1371784)[0m [12]	train-mlogloss:2.51832	validation-mlogloss:2.51656
[36m(train_xgb_ray_tune pid=1371785)[0m [2]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371761)[0m [16]	train-mlogloss:2.63463	validation-mlogloss:2.63261
[36m(train_xgb_ray_tune pid=1371796)[0m [20]	train-mlogloss:2.64412	validation-mlogloss:2.64272
[36m(train_xgb_ray_tune pid=1371793)[0m [17]	train-mlogloss:2.55110	validation-mlogloss:2.54862
[36m(train_xgb_ray_tune pid=1371762)[0m [12]	train-mlogloss:2.60583	validation-mlogloss:2.60706
[36m(train_xgb_ray_tune pid=1371783)[0m [11]	train-mlogloss:2.57496	validation-mlogloss:2.57678
[36m(train_xgb_ray_tune pid=1371763)[0m [10]	train-mlogloss:2.60456	validation-mlogloss:2.60437
[36m(train_xgb_ray_tune pid=1371748)[0m [12]	train-mlogloss:2.65604	validation-mlogloss:2.65426
[36m(train_xgb_ray_tune pid=1371787)[0m [16]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371780)[0m [13]	train-mlogloss:2.59371	validation-mlogloss:2.59486
[36m(train_xgb_ray_tune pid=1371754)[0m [8]	train-mlogloss:2.63558	validation-mlogloss:2.63550
[36m(train_xgb_ray_tune pid=1371761)[0m [17]	train-mlogloss:2.63044	validation-mlogloss:2.62836
[36m(train_xgb_ray_tune pid=1371764)[0m [13]	train-mlogloss:2.51563	validation-mlogloss:2.52011
[36m(train_xgb_ray_tune pid=1371781)[0m [13]	train-mlogloss:2.57608	validation-mlogloss:2.57237
[36m(train_xgb_ray_tune pid=1371786)[0m [9]	train-mlogloss:2.57181	validation-mlogloss:2.57699
[36m(train_xgb_ray_tune pid=1371786)[0m [10]	train-mlogloss:2.55980	validation-mlogloss:2.56572
[36m(train_xgb_ray_tune pid=1371796)[0m [21]	train-mlogloss:2.64146	validation-mlogloss:2.64017
[36m(train_xgb_ray_tune pid=1371793)[0m [18]	train-mlogloss:2.54301	validation-mlogloss:2.54050
[36m(train_xgb_ray_tune pid=1371748)[0m [13]	train-mlogloss:2.65211	validation-mlogloss:2.65014
[36m(train_xgb_ray_tune pid=1371762)[0m [13]	train-mlogloss:2.59834	validation-mlogloss:2.59972
[36m(train_xgb_ray_tune pid=1371795)[0m [11]	train-mlogloss:2.49555	validation-mlogloss:2.49780
[36m(train_xgb_ray_tune pid=1371787)[0m [17]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371787)[0m [18]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371782)[0m [10]	train-mlogloss:2.59419	validation-mlogloss:2.59616
[36m(train_xgb_ray_tune pid=1371783)[0m [12]	train-mlogloss:2.56454	validation-mlogloss:2.56672
[36m(train_xgb_ray_tune pid=1371794)[0m [15]	train-mlogloss:2.59298	validation-mlogloss:2.59106
[36m(train_xgb_ray_tune pid=1371794)[0m [16]	train-mlogloss:2.58614	validation-mlogloss:2.58417
[36m(train_xgb_ray_tune pid=1371755)[0m [15]	train-mlogloss:2.50841	validation-mlogloss:2.51473
[36m(train_xgb_ray_tune pid=1371755)[0m [16]	train-mlogloss:2.49766	validation-mlogloss:2.50446
[36m(train_xgb_ray_tune pid=1371784)[0m [13]	train-mlogloss:2.50504	validation-mlogloss:2.50334
[36m(train_xgb_ray_tune pid=1371766)[0m [12]	train-mlogloss:2.62371	validation-mlogloss:2.62156
[36m(train_xgb_ray_tune pid=1371766)[0m [13]	train-mlogloss:2.61714	validation-mlogloss:2.61480
[36m(train_xgb_ray_tune pid=1371785)[0m [3]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371763)[0m [11]	train-mlogloss:2.59552	validation-mlogloss:2.59542
[36m(train_xgb_ray_tune pid=1371780)[0m [14]	train-mlogloss:2.58559	validation-mlogloss:2.58666
[36m(train_xgb_ray_tune pid=1371754)[0m [9]	train-mlogloss:2.62788	validation-mlogloss:2.62779
[36m(train_xgb_ray_tune pid=1371761)[0m [18]	train-mlogloss:2.62646	validation-mlogloss:2.62439
[36m(train_xgb_ray_tune pid=1371764)[0m [14]	train-mlogloss:2.50317	validation-mlogloss:2.50802
[36m(train_xgb_ray_tune pid=1371781)[0m [14]	train-mlogloss:2.56741	validation-mlogloss:2.56345
[36m(train_xgb_ray_tune pid=1371796)[0m [22]	train-mlogloss:2.63822	validation-mlogloss:2.63680
[36m(train_xgb_ray_tune pid=1371795)[0m [12]	train-mlogloss:2.48042	validation-mlogloss:2.48272
[36m(train_xgb_ray_tune pid=1371793)[0m [19]	train-mlogloss:2.53508	validation-mlogloss:2.53261
[36m(train_xgb_ray_tune pid=1371783)[0m [13]	train-mlogloss:2.55412	validation-mlogloss:2.55652
[36m(train_xgb_ray_tune pid=1371785)[0m [4]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371748)[0m [14]	train-mlogloss:2.64821	validation-mlogloss:2.64609
[36m(train_xgb_ray_tune pid=1371762)[0m [14]	train-mlogloss:2.59089	validation-mlogloss:2.59260
[36m(train_xgb_ray_tune pid=1371784)[0m [14]	train-mlogloss:2.49188	validation-mlogloss:2.48992
[36m(train_xgb_ray_tune pid=1371780)[0m [15]	train-mlogloss:2.57822	validation-mlogloss:2.57940
[36m(train_xgb_ray_tune pid=1371782)[0m [11]	train-mlogloss:2.58484	validation-mlogloss:2.58691
[36m(train_xgb_ray_tune pid=1371794)[0m [17]	train-mlogloss:2.57955	validation-mlogloss:2.57750
[36m(train_xgb_ray_tune pid=1371763)[0m [12]	train-mlogloss:2.58656	validation-mlogloss:2.58641
[36m(train_xgb_ray_tune pid=1371787)[0m [19]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371755)[0m [17]	train-mlogloss:2.48706	validation-mlogloss:2.49451
[36m(train_xgb_ray_tune pid=1371766)[0m [14]	train-mlogloss:2.61091	validation-mlogloss:2.60838
[36m(train_xgb_ray_tune pid=1371761)[0m [19]	train-mlogloss:2.62265	validation-mlogloss:2.62051
[36m(train_xgb_ray_tune pid=1371781)[0m [15]	train-mlogloss:2.55877	validation-mlogloss:2.55478
[36m(train_xgb_ray_tune pid=1371786)[0m [11]	train-mlogloss:2.54794	validation-mlogloss:2.55443
[36m(train_xgb_ray_tune pid=1371796)[0m [23]	train-mlogloss:2.63516	validation-mlogloss:2.63359
[36m(train_xgb_ray_tune pid=1371793)[0m [20]	train-mlogloss:2.52685	validation-mlogloss:2.52415
[36m(train_xgb_ray_tune pid=1371783)[0m [14]	train-mlogloss:2.54405	validation-mlogloss:2.54665
[36m(train_xgb_ray_tune pid=1371785)[0m [5]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371754)[0m [10]	train-mlogloss:2.62008	validation-mlogloss:2.61992
[36m(train_xgb_ray_tune pid=1371748)[0m [15]	train-mlogloss:2.64434	validation-mlogloss:2.64206
[36m(train_xgb_ray_tune pid=1371762)[0m [15]	train-mlogloss:2.58377	validation-mlogloss:2.58554
[36m(train_xgb_ray_tune pid=1371794)[0m [18]	train-mlogloss:2.57298	validation-mlogloss:2.57063
[36m(train_xgb_ray_tune pid=1371784)[0m [15]	train-mlogloss:2.47881	validation-mlogloss:2.47679
[36m(train_xgb_ray_tune pid=1371764)[0m [15]	train-mlogloss:2.49150	validation-mlogloss:2.49689
[36m(train_xgb_ray_tune pid=1371785)[0m [6]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371780)[0m [16]	train-mlogloss:2.57068	validation-mlogloss:2.57186
[36m(train_xgb_ray_tune pid=1371787)[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=1371787)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=1371785)[0m 2025-11-06 14:04:26.448633: 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=1371785)[0m 2025-11-06 14:04:26.469286: 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=1371785)[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=1371785)[0m E0000 00:00:1762434266.499010 1373070 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=1371785)[0m E0000 00:00:1762434266.506879 1373070 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=1371785)[0m W0000 00:00:1762434266.527267 1373070 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=1371785)[0m 2025-11-06 14:04:26.533575: 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=1371785)[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=1371761)[0m [20]	train-mlogloss:2.61859	validation-mlogloss:2.61629
[36m(train_xgb_ray_tune pid=1371795)[0m [13]	train-mlogloss:2.46475	validation-mlogloss:2.46733
[36m(train_xgb_ray_tune pid=1371755)[0m [18]	train-mlogloss:2.47657	validation-mlogloss:2.48447
[36m(train_xgb_ray_tune pid=1371766)[0m [15]	train-mlogloss:2.60487	validation-mlogloss:2.60245
[36m(train_xgb_ray_tune pid=1371754)[0m [11]	train-mlogloss:2.61241	validation-mlogloss:2.61222
[36m(train_xgb_ray_tune pid=1371761)[0m [21]	train-mlogloss:2.61439	validation-mlogloss:2.61184
[36m(train_xgb_ray_tune pid=1371764)[0m [16]	train-mlogloss:2.47958	validation-mlogloss:2.48450
[36m(train_xgb_ray_tune pid=1371781)[0m [16]	train-mlogloss:2.55004	validation-mlogloss:2.54600
[36m(train_xgb_ray_tune pid=1371781)[0m [17]	train-mlogloss:2.54177	validation-mlogloss:2.53736
[36m(train_xgb_ray_tune pid=1371786)[0m [12]	train-mlogloss:2.53643	validation-mlogloss:2.54337
[36m(train_xgb_ray_tune pid=1371786)[0m [13]	train-mlogloss:2.52469	validation-mlogloss:2.53206
[36m(train_xgb_ray_tune pid=1371796)[0m [24]	train-mlogloss:2.63249	validation-mlogloss:2.63090
[36m(train_xgb_ray_tune pid=1371796)[0m [25]	train-mlogloss:2.62951	validation-mlogloss:2.62789
[36m(train_xgb_ray_tune pid=1371793)[0m [21]	train-mlogloss:2.51871	validation-mlogloss:2.51567
[36m(train_xgb_ray_tune pid=1371793)[0m [22]	train-mlogloss:2.51085	validation-mlogloss:2.50755
[36m(train_xgb_ray_tune pid=1371748)[0m [16]	train-mlogloss:2.64050	validation-mlogloss:2.63810
[36m(train_xgb_ray_tune pid=1371748)[0m [17]	train-mlogloss:2.63666	validation-mlogloss:2.63413
[36m(train_xgb_ray_tune pid=1371762)[0m [16]	train-mlogloss:2.57661	validation-mlogloss:2.57847
[36m(train_xgb_ray_tune pid=1371795)[0m [14]	train-mlogloss:2.44956	validation-mlogloss:2.45223

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:04:31. Total running time: 8s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             5.54454 │
│ time_total_s                 5.54454 │
│ training_iteration                 1 │
│ validation_accuracy          0.06829 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1371787)[0m [20]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371782)[0m [12]	train-mlogloss:2.57519	validation-mlogloss:2.57750
[36m(train_xgb_ray_tune pid=1371783)[0m [15]	train-mlogloss:2.53432	validation-mlogloss:2.53718
[36m(train_xgb_ray_tune pid=1371783)[0m [16]	train-mlogloss:2.52443	validation-mlogloss:2.52749
[36m(train_xgb_ray_tune pid=1371794)[0m [19]	train-mlogloss:2.56621	validation-mlogloss:2.56352
[36m(train_xgb_ray_tune pid=1371794)[0m [20]	train-mlogloss:2.55964	validation-mlogloss:2.55679
[36m(train_xgb_ray_tune pid=1371755)[0m [19]	train-mlogloss:2.46620	validation-mlogloss:2.47442
[36m(train_xgb_ray_tune pid=1371784)[0m [16]	train-mlogloss:2.46595	validation-mlogloss:2.46368
[36m(train_xgb_ray_tune pid=1371766)[0m [16]	train-mlogloss:2.59865	validation-mlogloss:2.59602
[36m(train_xgb_ray_tune pid=1371785)[0m [7]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371785)[0m [8]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371785)[0m [9]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371763)[0m [13]	train-mlogloss:2.57764	validation-mlogloss:2.57765
[36m(train_xgb_ray_tune pid=1371763)[0m [14]	train-mlogloss:2.56894	validation-mlogloss:2.56875
[36m(train_xgb_ray_tune pid=1371780)[0m [17]	train-mlogloss:2.56292	validation-mlogloss:2.56381
[36m(train_xgb_ray_tune pid=1371754)[0m [12]	train-mlogloss:2.60490	validation-mlogloss:2.60465
[36m(train_xgb_ray_tune pid=1371761)[0m [22]	train-mlogloss:2.61030	validation-mlogloss:2.60758
[36m(train_xgb_ray_tune pid=1371762)[0m [17]	train-mlogloss:2.56950	validation-mlogloss:2.57157
[36m(train_xgb_ray_tune pid=1371784)[0m [17]	train-mlogloss:2.45345	validation-mlogloss:2.45106
[36m(train_xgb_ray_tune pid=1371782)[0m [13]	train-mlogloss:2.56569	validation-mlogloss:2.56830
[36m(train_xgb_ray_tune pid=1371755)[0m [20]	train-mlogloss:2.45616	validation-mlogloss:2.46489
[36m(train_xgb_ray_tune pid=1371766)[0m [17]	train-mlogloss:2.59243	validation-mlogloss:2.58950

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:04:31. Total running time: 8s
[36m(train_xgb_ray_tune pid=1371780)[0m [18]	train-mlogloss:2.55582	validation-mlogloss:2.55683
[36m(train_xgb_ray_tune pid=1371764)[0m [17]	train-mlogloss:2.46814	validation-mlogloss:2.47301
[36m(train_xgb_ray_tune pid=1371781)[0m [18]	train-mlogloss:2.53339	validation-mlogloss:2.52858
[36m(train_xgb_ray_tune pid=1371796)[0m [26]	train-mlogloss:2.62695	validation-mlogloss:2.62521
[36m(train_xgb_ray_tune pid=1371793)[0m [23]	train-mlogloss:2.50329	validation-mlogloss:2.49993
[36m(train_xgb_ray_tune pid=1371783)[0m [17]	train-mlogloss:2.51484	validation-mlogloss:2.51817
[36m(train_xgb_ray_tune pid=1371794)[0m [21]	train-mlogloss:2.55334	validation-mlogloss:2.55038
[36m(train_xgb_ray_tune pid=1371785)[0m [10]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371795)[0m [15]	train-mlogloss:2.43479	validation-mlogloss:2.43803
[36m(train_xgb_ray_tune pid=1371754)[0m [13]	train-mlogloss:2.59736	validation-mlogloss:2.59715
[36m(train_xgb_ray_tune pid=1371761)[0m [23]	train-mlogloss:2.60648	validation-mlogloss:2.60373
[36m(train_xgb_ray_tune pid=1371761)[0m [24]	train-mlogloss:2.60243	validation-mlogloss:2.59949
[36m(train_xgb_ray_tune pid=1371764)[0m [18]	train-mlogloss:2.45757	validation-mlogloss:2.46279
[36m(train_xgb_ray_tune pid=1371781)[0m [19]	train-mlogloss:2.52493	validation-mlogloss:2.52014
[36m(train_xgb_ray_tune pid=1371786)[0m [14]	train-mlogloss:2.51312	validation-mlogloss:2.52090
[36m(train_xgb_ray_tune pid=1371786)[0m [15]	train-mlogloss:2.50187	validation-mlogloss:2.50986
[36m(train_xgb_ray_tune pid=1371796)[0m [27]	train-mlogloss:2.62446	validation-mlogloss:2.62251
[36m(train_xgb_ray_tune pid=1371796)[0m [28]	train-mlogloss:2.62166	validation-mlogloss:2.61956
[36m(train_xgb_ray_tune pid=1371793)[0m [24]	train-mlogloss:2.49521	validation-mlogloss:2.49152
[36m(train_xgb_ray_tune pid=1371748)[0m [18]	train-mlogloss:2.63287	validation-mlogloss:2.63020
[36m(train_xgb_ray_tune pid=1371762)[0m [18]	train-mlogloss:2.56218	validation-mlogloss:2.56438
[36m(train_xgb_ray_tune pid=1371762)[0m [19]	train-mlogloss:2.55566	validation-mlogloss:2.55782
[36m(train_xgb_ray_tune pid=1371795)[0m [16]	train-mlogloss:2.41988	validation-mlogloss:2.42307
[36m(train_xgb_ray_tune pid=1371782)[0m [14]	train-mlogloss:2.55666	validation-mlogloss:2.55956
[36m(train_xgb_ray_tune pid=1371783)[0m [18]	train-mlogloss:2.50539	validation-mlogloss:2.50893
[36m(train_xgb_ray_tune pid=1371794)[0m [22]	train-mlogloss:2.54688	validation-mlogloss:2.54392
[36m(train_xgb_ray_tune pid=1371755)[0m [21]	train-mlogloss:2.44638	validation-mlogloss:2.45535
[36m(train_xgb_ray_tune pid=1371784)[0m [18]	train-mlogloss:2.44117	validation-mlogloss:2.43962
[36m(train_xgb_ray_tune pid=1371766)[0m [18]	train-mlogloss:2.58618	validation-mlogloss:2.58320
[36m(train_xgb_ray_tune pid=1371785)[0m [11]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371785)[0m [12]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371763)[0m [15]	train-mlogloss:2.56049	validation-mlogloss:2.56058
[36m(train_xgb_ray_tune pid=1371763)[0m [16]	train-mlogloss:2.55197	validation-mlogloss:2.55212
[36m(train_xgb_ray_tune pid=1371780)[0m [19]	train-mlogloss:2.54848	validation-mlogloss:2.54912
[36m(train_xgb_ray_tune pid=1371754)[0m [14]	train-mlogloss:2.59016	validation-mlogloss:2.58991
[36m(train_xgb_ray_tune pid=1371781)[0m [20]	train-mlogloss:2.51683	validation-mlogloss:2.51176
[36m(train_xgb_ray_tune pid=1371793)[0m [25]	train-mlogloss:2.48714	validation-mlogloss:2.48306
[36m(train_xgb_ray_tune pid=1371748)[0m [19]	train-mlogloss:2.62916	validation-mlogloss:2.62645
[36m(train_xgb_ray_tune pid=1371783)[0m [19]	train-mlogloss:2.49613	validation-mlogloss:2.50000
[36m(train_xgb_ray_tune pid=1371794)[0m [23]	train-mlogloss:2.54084	validation-mlogloss:2.53788
[36m(train_xgb_ray_tune pid=1371755)[0m [22]	train-mlogloss:2.43671	validation-mlogloss:2.44615
[36m(train_xgb_ray_tune pid=1371784)[0m [19]	train-mlogloss:2.42882	validation-mlogloss:2.42772
[36m(train_xgb_ray_tune pid=1371766)[0m [19]	train-mlogloss:2.58026	validation-mlogloss:2.57714
[36m(train_xgb_ray_tune pid=1371761)[0m [25]	train-mlogloss:2.59826	validation-mlogloss:2.59511
[36m(train_xgb_ray_tune pid=1371764)[0m [19]	train-mlogloss:2.44668	validation-mlogloss:2.45220
[36m(train_xgb_ray_tune pid=1371754)[0m [15]	train-mlogloss:2.58267	validation-mlogloss:2.58249
[36m(train_xgb_ray_tune pid=1371761)[0m [26]	train-mlogloss:2.59418	validation-mlogloss:2.59087
[36m(train_xgb_ray_tune pid=1371761)[0m [27]	train-mlogloss:2.59034	validation-mlogloss:2.58699
[36m(train_xgb_ray_tune pid=1371764)[0m [20]	train-mlogloss:2.43592	validation-mlogloss:2.44152
[36m(train_xgb_ray_tune pid=1371781)[0m [21]	train-mlogloss:2.50891	validation-mlogloss:2.50350
[36m(train_xgb_ray_tune pid=1371786)[0m [16]	train-mlogloss:2.49079	validation-mlogloss:2.49919
[36m(train_xgb_ray_tune pid=1371786)[0m [17]	train-mlogloss:2.47993	validation-mlogloss:2.48866
[36m(train_xgb_ray_tune pid=1371796)[0m [29]	train-mlogloss:2.61929	validation-mlogloss:2.61721
[36m(train_xgb_ray_tune pid=1371796)[0m [30]	train-mlogloss:2.61668	validation-mlogloss:2.61441
[36m(train_xgb_ray_tune pid=1371793)[0m [26]	train-mlogloss:2.47949	validation-mlogloss:2.47521
[36m(train_xgb_ray_tune pid=1371748)[0m [20]	train-mlogloss:2.62548	validation-mlogloss:2.62271
[36m(train_xgb_ray_tune pid=1371762)[0m [20]	train-mlogloss:2.54897	validation-mlogloss:2.55104
[36m(train_xgb_ray_tune pid=1371762)[0m [21]	train-mlogloss:2.54169	validation-mlogloss:2.54380
[36m(train_xgb_ray_tune pid=1371795)[0m [17]	train-mlogloss:2.40537	validation-mlogloss:2.40838
[36m(train_xgb_ray_tune pid=1371795)[0m [18]	train-mlogloss:2.39096	validation-mlogloss:2.39432
[36m(train_xgb_ray_tune pid=1371782)[0m [15]	train-mlogloss:2.54738	validation-mlogloss:2.55056
[36m(train_xgb_ray_tune pid=1371782)[0m [16]	train-mlogloss:2.53840	validation-mlogloss:2.54167
[36m(train_xgb_ray_tune pid=1371783)[0m [20]	train-mlogloss:2.48714	validation-mlogloss:2.49146
[36m(train_xgb_ray_tune pid=1371783)[0m [21]	train-mlogloss:2.47777	validation-mlogloss:2.48205
[36m(train_xgb_ray_tune pid=1371794)[0m [24]	train-mlogloss:2.53460	validation-mlogloss:2.53172
[36m(train_xgb_ray_tune pid=1371794)[0m [25]	train-mlogloss:2.52818	validation-mlogloss:2.52501
[36m(train_xgb_ray_tune pid=1371755)[0m [23]	train-mlogloss:2.42709	validation-mlogloss:2.43696
[36m(train_xgb_ray_tune pid=1371784)[0m [20]	train-mlogloss:2.41684	validation-mlogloss:2.41593
[36m(train_xgb_ray_tune pid=1371766)[0m [20]	train-mlogloss:2.57426	validation-mlogloss:2.57097
[36m(train_xgb_ray_tune pid=1371785)[0m [13]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371785)[0m [14]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371763)[0m [17]	train-mlogloss:2.54339	validation-mlogloss:2.54359
[36m(train_xgb_ray_tune pid=1371780)[0m [20]	train-mlogloss:2.54118	validation-mlogloss:2.54179
[36m(train_xgb_ray_tune pid=1371780)[0m [21]	train-mlogloss:2.53420	validation-mlogloss:2.53446
[36m(train_xgb_ray_tune pid=1371781)[0m [22]	train-mlogloss:2.50177	validation-mlogloss:2.49604
[36m(train_xgb_ray_tune pid=1371748)[0m [21]	train-mlogloss:2.62171	validation-mlogloss:2.61883
[36m(train_xgb_ray_tune pid=1371766)[0m [21]	train-mlogloss:2.56814	validation-mlogloss:2.56466
[36m(train_xgb_ray_tune pid=1371793)[0m [27]	train-mlogloss:2.47179	validation-mlogloss:2.46719
[36m(train_xgb_ray_tune pid=1371785)[0m [15]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371763)[0m [18]	train-mlogloss:2.53499	validation-mlogloss:2.53522
[36m(train_xgb_ray_tune pid=1371754)[0m [16]	train-mlogloss:2.57520	validation-mlogloss:2.57484
[36m(train_xgb_ray_tune pid=1371755)[0m [24]	train-mlogloss:2.41754	validation-mlogloss:2.42755
[36m(train_xgb_ray_tune pid=1371784)[0m [21]	train-mlogloss:2.40491	validation-mlogloss:2.40396
[36m(train_xgb_ray_tune pid=1371761)[0m [28]	train-mlogloss:2.58627	validation-mlogloss:2.58272
[36m(train_xgb_ray_tune pid=1371780)[0m [22]	train-mlogloss:2.52740	validation-mlogloss:2.52787
[36m(train_xgb_ray_tune pid=1371764)[0m [21]	train-mlogloss:2.42532	validation-mlogloss:2.43137
[36m(train_xgb_ray_tune pid=1371794)[0m [26]	train-mlogloss:2.52217	validation-mlogloss:2.51907
[36m(train_xgb_ray_tune pid=1371785)[0m [16]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371796)[0m [31]	train-mlogloss:2.61341	validation-mlogloss:2.61094
[36m(train_xgb_ray_tune pid=1371795)[0m [19]	train-mlogloss:2.37677	validation-mlogloss:2.38044
[36m(train_xgb_ray_tune pid=1371783)[0m [22]	train-mlogloss:2.46858	validation-mlogloss:2.47300
[36m(train_xgb_ray_tune pid=1371781)[0m [23]	train-mlogloss:2.49367	validation-mlogloss:2.48765
[36m(train_xgb_ray_tune pid=1371786)[0m [18]	train-mlogloss:2.46934	validation-mlogloss:2.47842
[36m(train_xgb_ray_tune pid=1371793)[0m [28]	train-mlogloss:2.46410	validation-mlogloss:2.45918
[36m(train_xgb_ray_tune pid=1371762)[0m [22]	train-mlogloss:2.53494	validation-mlogloss:2.53724
[36m(train_xgb_ray_tune pid=1371755)[0m [25]	train-mlogloss:2.40833	validation-mlogloss:2.41872
[36m(train_xgb_ray_tune pid=1371766)[0m [22]	train-mlogloss:2.56207	validation-mlogloss:2.55851
[36m(train_xgb_ray_tune pid=1371763)[0m [19]	train-mlogloss:2.52639	validation-mlogloss:2.52654
[36m(train_xgb_ray_tune pid=1371754)[0m [17]	train-mlogloss:2.56797	validation-mlogloss:2.56759
[36m(train_xgb_ray_tune pid=1371761)[0m [29]	train-mlogloss:2.58219	validation-mlogloss:2.57849
[36m(train_xgb_ray_tune pid=1371748)[0m [22]	train-mlogloss:2.61790	validation-mlogloss:2.61484
[36m(train_xgb_ray_tune pid=1371782)[0m [17]	train-mlogloss:2.52936	validation-mlogloss:2.53292
[36m(train_xgb_ray_tune pid=1371794)[0m [27]	train-mlogloss:2.51553	validation-mlogloss:2.51216
[36m(train_xgb_ray_tune pid=1371785)[0m [17]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371784)[0m [22]	train-mlogloss:2.39304	validation-mlogloss:2.39137
[36m(train_xgb_ray_tune pid=1371780)[0m [23]	train-mlogloss:2.52056	validation-mlogloss:2.52097
[36m(train_xgb_ray_tune pid=1371754)[0m [18]	train-mlogloss:2.56080	validation-mlogloss:2.56044
[36m(train_xgb_ray_tune pid=1371761)[0m [30]	train-mlogloss:2.57828	validation-mlogloss:2.57447
[36m(train_xgb_ray_tune pid=1371764)[0m [22]	train-mlogloss:2.41494	validation-mlogloss:2.42164
[36m(train_xgb_ray_tune pid=1371764)[0m [23]	train-mlogloss:2.40454	validation-mlogloss:2.41149
[36m(train_xgb_ray_tune pid=1371781)[0m [24]	train-mlogloss:2.48529	validation-mlogloss:2.47886
[36m(train_xgb_ray_tune pid=1371781)[0m [25]	train-mlogloss:2.47730	validation-mlogloss:2.47059
[36m(train_xgb_ray_tune pid=1371786)[0m [19]	train-mlogloss:2.45878	validation-mlogloss:2.46819
[36m(train_xgb_ray_tune pid=1371796)[0m [32]	train-mlogloss:2.61072	validation-mlogloss:2.60828
[36m(train_xgb_ray_tune pid=1371796)[0m [33]	train-mlogloss:2.60747	validation-mlogloss:2.60484
[36m(train_xgb_ray_tune pid=1371793)[0m [29]	train-mlogloss:2.45654	validation-mlogloss:2.45134
[36m(train_xgb_ray_tune pid=1371793)[0m [30]	train-mlogloss:2.44919	validation-mlogloss:2.44375
[36m(train_xgb_ray_tune pid=1371748)[0m [23]	train-mlogloss:2.61417	validation-mlogloss:2.61092
[36m(train_xgb_ray_tune pid=1371762)[0m [23]	train-mlogloss:2.52811	validation-mlogloss:2.53059
[36m(train_xgb_ray_tune pid=1371795)[0m [20]	train-mlogloss:2.36254	validation-mlogloss:2.36578
[36m(train_xgb_ray_tune pid=1371795)[0m [21]	train-mlogloss:2.34865	validation-mlogloss:2.35214
[36m(train_xgb_ray_tune pid=1371782)[0m [18]	train-mlogloss:2.52084	validation-mlogloss:2.52456
[36m(train_xgb_ray_tune pid=1371783)[0m [23]	train-mlogloss:2.45974	validation-mlogloss:2.46423
[36m(train_xgb_ray_tune pid=1371783)[0m [24]	train-mlogloss:2.45094	validation-mlogloss:2.45570
[36m(train_xgb_ray_tune pid=1371794)[0m [28]	train-mlogloss:2.50935	validation-mlogloss:2.50565
[36m(train_xgb_ray_tune pid=1371794)[0m [29]	train-mlogloss:2.50323	validation-mlogloss:2.49932
[36m(train_xgb_ray_tune pid=1371755)[0m [26]	train-mlogloss:2.39936	validation-mlogloss:2.41011
[36m(train_xgb_ray_tune pid=1371755)[0m [27]	train-mlogloss:2.39033	validation-mlogloss:2.40131
[36m(train_xgb_ray_tune pid=1371784)[0m [23]	train-mlogloss:2.38146	validation-mlogloss:2.37976
[36m(train_xgb_ray_tune pid=1371766)[0m [23]	train-mlogloss:2.55613	validation-mlogloss:2.55238
[36m(train_xgb_ray_tune pid=1371766)[0m [24]	train-mlogloss:2.55014	validation-mlogloss:2.54615
[36m(train_xgb_ray_tune pid=1371785)[0m [18]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371785)[0m [19]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1371763)[0m [20]	train-mlogloss:2.51780	validation-mlogloss:2.51776
[36m(train_xgb_ray_tune pid=1371763)[0m [21]	train-mlogloss:2.50910	validation-mlogloss:2.50882
[36m(train_xgb_ray_tune pid=1371780)[0m [24]	train-mlogloss:2.51400	validation-mlogloss:2.51439
[36m(train_xgb_ray_tune pid=1371761)[0m [31]	train-mlogloss:2.57425	validation-mlogloss:2.57024
[36m(train_xgb_ray_tune pid=1371786)[0m [20]	train-mlogloss:2.44817	validation-mlogloss:2.45782
[36m(train_xgb_ray_tune pid=1371748)[0m [24]	train-mlogloss:2.61046	validation-mlogloss:2.60711
[36m(train_xgb_ray_tune pid=1371762)[0m [24]	train-mlogloss:2.52164	validation-mlogloss:2.52418
[36m(train_xgb_ray_tune pid=1371783)[0m [25]	train-mlogloss:2.44217	validation-mlogloss:2.44683
[36m(train_xgb_ray_tune pid=1371794)[0m [30]	train-mlogloss:2.49728	validation-mlogloss:2.49338
[36m(train_xgb_ray_tune pid=1371780)[0m [25]	train-mlogloss:2.50702	validation-mlogloss:2.50713
[36m(train_xgb_ray_tune pid=1371754)[0m [19]	train-mlogloss:2.55368	validation-mlogloss:2.55329
[36m(train_xgb_ray_tune pid=1371781)[0m [26]	train-mlogloss:2.46979	validation-mlogloss:2.46313
[36m(train_xgb_ray_tune pid=1371796)[0m [34]	train-mlogloss:2.60494	validation-mlogloss:2.60216
[36m(train_xgb_ray_tune pid=1371782)[0m [19]	train-mlogloss:2.51201	validation-mlogloss:2.51593
[36m(train_xgb_ray_tune pid=1371784)[0m [24]	train-mlogloss:2.37024	validation-mlogloss:2.36823
[36m(train_xgb_ray_tune pid=1371763)[0m [22]	train-mlogloss:2.50082	validation-mlogloss:2.50054
[36m(train_xgb_ray_tune pid=1371786)[0m [21]	train-mlogloss:2.43801	validation-mlogloss:2.44784
[36m(train_xgb_ray_tune pid=1371793)[0m [31]	train-mlogloss:2.44173	validation-mlogloss:2.43606
[36m(train_xgb_ray_tune pid=1371766)[0m [25]	train-mlogloss:2.54414	validation-mlogloss:2.54009
[36m(train_xgb_ray_tune pid=1371764)[0m [24]	train-mlogloss:2.39483	validation-mlogloss:2.40216
[36m(train_xgb_ray_tune pid=1371795)[0m [22]	train-mlogloss:2.33489	validation-mlogloss:2.33807
[36m(train_xgb_ray_tune pid=1371755)[0m [28]	train-mlogloss:2.38140	validation-mlogloss:2.39224
[36m(train_xgb_ray_tune pid=1371761)[0m [32]	train-mlogloss:2.57031	validation-mlogloss:2.56613
[36m(train_xgb_ray_tune pid=1371781)[0m [27]	train-mlogloss:2.46251	validation-mlogloss:2.45598
[36m(train_xgb_ray_tune pid=1371796)[0m [35]	train-mlogloss:2.60197	validation-mlogloss:2.59904
[36m(train_xgb_ray_tune pid=1371748)[0m [25]	train-mlogloss:2.60661	validation-mlogloss:2.60310
[36m(train_xgb_ray_tune pid=1371762)[0m [25]	train-mlogloss:2.51489	validation-mlogloss:2.51777
[36m(train_xgb_ray_tune pid=1371783)[0m [26]	train-mlogloss:2.43423	validation-mlogloss:2.43866
[36m(train_xgb_ray_tune pid=1371794)[0m [31]	train-mlogloss:2.49106	validation-mlogloss:2.48707
[36m(train_xgb_ray_tune pid=1371780)[0m [26]	train-mlogloss:2.50037	validation-mlogloss:2.50039
[36m(train_xgb_ray_tune pid=1371754)[0m [20]	train-mlogloss:2.54648	validation-mlogloss:2.54604

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:04:31. Total running time: 9s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s              6.0377 │
│ time_total_s                  6.0377 │
│ training_iteration                 1 │
│ validation_accuracy          0.06829 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:04:32. Total running time: 9s
[36m(train_xgb_ray_tune pid=1371754)[0m [21]	train-mlogloss:2.53968	validation-mlogloss:2.53950
[36m(train_xgb_ray_tune pid=1371761)[0m [33]	train-mlogloss:2.56651	validation-mlogloss:2.56229
[36m(train_xgb_ray_tune pid=1371764)[0m [25]	train-mlogloss:2.38480	validation-mlogloss:2.39241
[36m(train_xgb_ray_tune pid=1371781)[0m [28]	train-mlogloss:2.45522	validation-mlogloss:2.44836
[36m(train_xgb_ray_tune pid=1371786)[0m [22]	train-mlogloss:2.42815	validation-mlogloss:2.43833
[36m(train_xgb_ray_tune pid=1371786)[0m [23]	train-mlogloss:2.41842	validation-mlogloss:2.42884
[36m(train_xgb_ray_tune pid=1371796)[0m [36]	train-mlogloss:2.59895	validation-mlogloss:2.59587
[36m(train_xgb_ray_tune pid=1371793)[0m [32]	train-mlogloss:2.43455	validation-mlogloss:2.42872
[36m(train_xgb_ray_tune pid=1371793)[0m [33]	train-mlogloss:2.42756	validation-mlogloss:2.42171
[36m(train_xgb_ray_tune pid=1371748)[0m [26]	train-mlogloss:2.60279	validation-mlogloss:2.59917
[36m(train_xgb_ray_tune pid=1371762)[0m [26]	train-mlogloss:2.50803	validation-mlogloss:2.51097
[36m(train_xgb_ray_tune pid=1371795)[0m [23]	train-mlogloss:2.32180	validation-mlogloss:2.32502
[36m(train_xgb_ray_tune pid=1371782)[0m [20]	train-mlogloss:2.50351	validation-mlogloss:2.50762
[36m(train_xgb_ray_tune pid=1371782)[0m [21]	train-mlogloss:2.49489	validation-mlogloss:2.49911
[36m(train_xgb_ray_tune pid=1371783)[0m [27]	train-mlogloss:2.42576	validation-mlogloss:2.43053
[36m(train_xgb_ray_tune pid=1371794)[0m [32]	train-mlogloss:2.48506	validation-mlogloss:2.48079
[36m(train_xgb_ray_tune pid=1371755)[0m [29]	train-mlogloss:2.37281	validation-mlogloss:2.38397
[36m(train_xgb_ray_tune pid=1371755)[0m [30]	train-mlogloss:2.36426	validation-mlogloss:2.37533
[36m(train_xgb_ray_tune pid=1371784)[0m [25]	train-mlogloss:2.35946	validation-mlogloss:2.35729
[36m(train_xgb_ray_tune pid=1371784)[0m [26]	train-mlogloss:2.34842	validation-mlogloss:2.34639
[36m(train_xgb_ray_tune pid=1371766)[0m [26]	train-mlogloss:2.53836	validation-mlogloss:2.53411
[36m(train_xgb_ray_tune pid=1371766)[0m [27]	train-mlogloss:2.53261	validation-mlogloss:2.52821
[36m(train_xgb_ray_tune pid=1371763)[0m [23]	train-mlogloss:2.49242	validation-mlogloss:2.49225
[36m(train_xgb_ray_tune pid=1371763)[0m [24]	train-mlogloss:2.48404	validation-mlogloss:2.48388
[36m(train_xgb_ray_tune pid=1371780)[0m [27]	train-mlogloss:2.49357	validation-mlogloss:2.49372
[36m(train_xgb_ray_tune pid=1371781)[0m [29]	train-mlogloss:2.44802	validation-mlogloss:2.44132
[36m(train_xgb_ray_tune pid=1371796)[0m [37]	train-mlogloss:2.59639	validation-mlogloss:2.59326
[36m(train_xgb_ray_tune pid=1371783)[0m [28]	train-mlogloss:2.41724	validation-mlogloss:2.42215
[36m(train_xgb_ray_tune pid=1371794)[0m [33]	train-mlogloss:2.47886	validation-mlogloss:2.47442
[36m(train_xgb_ray_tune pid=1371761)[0m [34]	train-mlogloss:2.56247	validation-mlogloss:2.55809
[36m(train_xgb_ray_tune pid=1371764)[0m [26]	train-mlogloss:2.37513	validation-mlogloss:2.38289
[36m(train_xgb_ray_tune pid=1371748)[0m [27]	train-mlogloss:2.59907	validation-mlogloss:2.59538
[36m(train_xgb_ray_tune pid=1371762)[0m [27]	train-mlogloss:2.50135	validation-mlogloss:2.50424
[36m(train_xgb_ray_tune pid=1371795)[0m [24]	train-mlogloss:2.30846	validation-mlogloss:2.31185
[36m(train_xgb_ray_tune pid=1371780)[0m [28]	train-mlogloss:2.48669	validation-mlogloss:2.48659
[36m(train_xgb_ray_tune pid=1371754)[0m [22]	train-mlogloss:2.53274	validation-mlogloss:2.53258
[36m(train_xgb_ray_tune pid=1371786)[0m [24]	train-mlogloss:2.40881	validation-mlogloss:2.41938
[36m(train_xgb_ray_tune pid=1371755)[0m [31]	train-mlogloss:2.35590	validation-mlogloss:2.36729
[36m(train_xgb_ray_tune pid=1371754)[0m [23]	train-mlogloss:2.52578	validation-mlogloss:2.52554
[36m(train_xgb_ray_tune pid=1371761)[0m [35]	train-mlogloss:2.55881	validation-mlogloss:2.55436
[36m(train_xgb_ray_tune pid=1371764)[0m [27]	train-mlogloss:2.36537	validation-mlogloss:2.37344
[36m(train_xgb_ray_tune pid=1371781)[0m [30]	train-mlogloss:2.44077	validation-mlogloss:2.43410
[36m(train_xgb_ray_tune pid=1371781)[0m [31]	train-mlogloss:2.43309	validation-mlogloss:2.42632
[36m(train_xgb_ray_tune pid=1371786)[0m [25]	train-mlogloss:2.39936	validation-mlogloss:2.41028
[36m(train_xgb_ray_tune pid=1371796)[0m [38]	train-mlogloss:2.59312	validation-mlogloss:2.58982
[36m(train_xgb_ray_tune pid=1371796)[0m [39]	train-mlogloss:2.59043	validation-mlogloss:2.58698
[36m(train_xgb_ray_tune pid=1371793)[0m [34]	train-mlogloss:2.42009	validation-mlogloss:2.41400
[36m(train_xgb_ray_tune pid=1371793)[0m [35]	train-mlogloss:2.41276	validation-mlogloss:2.40649
[36m(train_xgb_ray_tune pid=1371748)[0m [28]	train-mlogloss:2.59545	validation-mlogloss:2.59164
[36m(train_xgb_ray_tune pid=1371762)[0m [28]	train-mlogloss:2.49505	validation-mlogloss:2.49823
[36m(train_xgb_ray_tune pid=1371762)[0m [29]	train-mlogloss:2.48842	validation-mlogloss:2.49151
[36m(train_xgb_ray_tune pid=1371795)[0m [25]	train-mlogloss:2.29594	validation-mlogloss:2.29954
[36m(train_xgb_ray_tune pid=1371782)[0m [22]	train-mlogloss:2.48651	validation-mlogloss:2.49087
[36m(train_xgb_ray_tune pid=1371782)[0m [23]	train-mlogloss:2.47815	validation-mlogloss:2.48299
[36m(train_xgb_ray_tune pid=1371783)[0m [29]	train-mlogloss:2.40867	validation-mlogloss:2.41350
[36m(train_xgb_ray_tune pid=1371783)[0m [30]	train-mlogloss:2.40084	validation-mlogloss:2.40582
[36m(train_xgb_ray_tune pid=1371794)[0m [34]	train-mlogloss:2.47283	validation-mlogloss:2.46820
[36m(train_xgb_ray_tune pid=1371794)[0m [35]	train-mlogloss:2.46666	validation-mlogloss:2.46193
[36m(train_xgb_ray_tune pid=1371755)[0m [32]	train-mlogloss:2.34728	validation-mlogloss:2.35889
[36m(train_xgb_ray_tune pid=1371784)[0m [27]	train-mlogloss:2.33772	validation-mlogloss:2.33519
[36m(train_xgb_ray_tune pid=1371784)[0m [28]	train-mlogloss:2.32705	validation-mlogloss:2.32462
[36m(train_xgb_ray_tune pid=1371766)[0m [28]	train-mlogloss:2.52650	validation-mlogloss:2.52196
[36m(train_xgb_ray_tune pid=1371766)[0m [29]	train-mlogloss:2.52079	validation-mlogloss:2.51613
[36m(train_xgb_ray_tune pid=1371763)[0m [25]	train-mlogloss:2.47577	validation-mlogloss:2.47533
[36m(train_xgb_ray_tune pid=1371763)[0m [26]	train-mlogloss:2.46766	validation-mlogloss:2.46725
[36m(train_xgb_ray_tune pid=1371780)[0m [29]	train-mlogloss:2.48005	validation-mlogloss:2.47980
[36m(train_xgb_ray_tune pid=1371780)[0m [30]	train-mlogloss:2.47387	validation-mlogloss:2.47380
[36m(train_xgb_ray_tune pid=1371754)[0m [24]	train-mlogloss:2.51905	validation-mlogloss:2.51901
[36m(train_xgb_ray_tune pid=1371761)[0m [36]	train-mlogloss:2.55515	validation-mlogloss:2.55070
[36m(train_xgb_ray_tune pid=1371764)[0m [28]	train-mlogloss:2.35591	validation-mlogloss:2.36387
[36m(train_xgb_ray_tune pid=1371786)[0m [26]	train-mlogloss:2.38998	validation-mlogloss:2.40121
[36m(train_xgb_ray_tune pid=1371748)[0m [29]	train-mlogloss:2.59196	validation-mlogloss:2.58800
[36m(train_xgb_ray_tune pid=1371762)[0m [30]	train-mlogloss:2.48188	validation-mlogloss:2.48520
[36m(train_xgb_ray_tune pid=1371795)[0m [26]	train-mlogloss:2.28300	validation-mlogloss:2.28682
[36m(train_xgb_ray_tune pid=1371782)[0m [24]	train-mlogloss:2.46960	validation-mlogloss:2.47456
[36m(train_xgb_ray_tune pid=1371783)[0m [31]	train-mlogloss:2.39242	validation-mlogloss:2.39749
[36m(train_xgb_ray_tune pid=1371794)[0m [36]	train-mlogloss:2.46095	validation-mlogloss:2.45606
[36m(train_xgb_ray_tune pid=1371755)[0m [33]	train-mlogloss:2.33912	validation-mlogloss:2.35095
[36m(train_xgb_ray_tune pid=1371781)[0m [32]	train-mlogloss:2.42604	validation-mlogloss:2.41948
[36m(train_xgb_ray_tune pid=1371796)[0m [40]	train-mlogloss:2.58778	validation-mlogloss:2.58421
[36m(train_xgb_ray_tune pid=1371793)[0m [36]	train-mlogloss:2.40551	validation-mlogloss:2.39906
[36m(train_xgb_ray_tune pid=1371748)[0m [30]	train-mlogloss:2.58825	validation-mlogloss:2.58419
[36m(train_xgb_ray_tune pid=1371794)[0m [37]	train-mlogloss:2.45532	validation-mlogloss:2.45039
[36m(train_xgb_ray_tune pid=1371784)[0m [29]	train-mlogloss:2.31652	validation-mlogloss:2.31441
[36m(train_xgb_ray_tune pid=1371766)[0m [30]	train-mlogloss:2.51496	validation-mlogloss:2.51020
[36m(train_xgb_ray_tune pid=1371763)[0m [27]	train-mlogloss:2.45971	validation-mlogloss:2.45911
[36m(train_xgb_ray_tune pid=1371780)[0m [31]	train-mlogloss:2.46779	validation-mlogloss:2.46764
[36m(train_xgb_ray_tune pid=1371761)[0m [37]	train-mlogloss:2.55140	validation-mlogloss:2.54680
[36m(train_xgb_ray_tune pid=1371762)[0m [31]	train-mlogloss:2.47548	validation-mlogloss:2.47896
[36m(train_xgb_ray_tune pid=1371786)[0m [27]	train-mlogloss:2.38078	validation-mlogloss:2.39206
[36m(train_xgb_ray_tune pid=1371755)[0m [34]	train-mlogloss:2.33093	validation-mlogloss:2.34290
[36m(train_xgb_ray_tune pid=1371764)[0m [29]	train-mlogloss:2.34702	validation-mlogloss:2.35504
[36m(train_xgb_ray_tune pid=1371754)[0m [25]	train-mlogloss:2.51230	validation-mlogloss:2.51234
[36m(train_xgb_ray_tune pid=1371754)[0m [26]	train-mlogloss:2.50540	validation-mlogloss:2.50540
[36m(train_xgb_ray_tune pid=1371761)[0m [38]	train-mlogloss:2.54759	validation-mlogloss:2.54287
[36m(train_xgb_ray_tune pid=1371764)[0m [30]	train-mlogloss:2.33792	validation-mlogloss:2.34624
[36m(train_xgb_ray_tune pid=1371781)[0m [33]	train-mlogloss:2.41869	validation-mlogloss:2.41177
[36m(train_xgb_ray_tune pid=1371781)[0m [34]	train-mlogloss:2.41185	validation-mlogloss:2.40473
[36m(train_xgb_ray_tune pid=1371786)[0m [28]	train-mlogloss:2.37165	validation-mlogloss:2.38306
[36m(train_xgb_ray_tune pid=1371796)[0m [41]	train-mlogloss:2.58545	validation-mlogloss:2.58193
[36m(train_xgb_ray_tune pid=1371796)[0m [42]	train-mlogloss:2.58309	validation-mlogloss:2.57955
[36m(train_xgb_ray_tune pid=1371793)[0m [37]	train-mlogloss:2.39839	validation-mlogloss:2.39178
[36m(train_xgb_ray_tune pid=1371793)[0m [38]	train-mlogloss:2.39131	validation-mlogloss:2.38446
[36m(train_xgb_ray_tune pid=1371748)[0m [31]	train-mlogloss:2.58457	validation-mlogloss:2.58033
[36m(train_xgb_ray_tune pid=1371748)[0m [32]	train-mlogloss:2.58109	validation-mlogloss:2.57679
[36m(train_xgb_ray_tune pid=1371762)[0m [32]	train-mlogloss:2.46939	validation-mlogloss:2.47285
[36m(train_xgb_ray_tune pid=1371795)[0m [27]	train-mlogloss:2.27072	validation-mlogloss:2.27471
[36m(train_xgb_ray_tune pid=1371795)[0m [28]	train-mlogloss:2.25847	validation-mlogloss:2.26259
[36m(train_xgb_ray_tune pid=1371782)[0m [25]	train-mlogloss:2.46101	validation-mlogloss:2.46630
[36m(train_xgb_ray_tune pid=1371782)[0m [26]	train-mlogloss:2.45276	validation-mlogloss:2.45820
[36m(train_xgb_ray_tune pid=1371783)[0m [32]	train-mlogloss:2.38468	validation-mlogloss:2.38998
[36m(train_xgb_ray_tune pid=1371783)[0m [33]	train-mlogloss:2.37611	validation-mlogloss:2.38138
[36m(train_xgb_ray_tune pid=1371794)[0m [38]	train-mlogloss:2.44918	validation-mlogloss:2.44411
[36m(train_xgb_ray_tune pid=1371794)[0m [39]	train-mlogloss:2.44307	validation-mlogloss:2.43768
[36m(train_xgb_ray_tune pid=1371755)[0m [35]	train-mlogloss:2.32289	validation-mlogloss:2.33495
[36m(train_xgb_ray_tune pid=1371784)[0m [30]	train-mlogloss:2.30614	validation-mlogloss:2.30397
[36m(train_xgb_ray_tune pid=1371766)[0m [31]	train-mlogloss:2.50941	validation-mlogloss:2.50450
[36m(train_xgb_ray_tune pid=1371766)[0m [32]	train-mlogloss:2.50375	validation-mlogloss:2.49871
[36m(train_xgb_ray_tune pid=1371763)[0m [28]	train-mlogloss:2.45159	validation-mlogloss:2.45086
[36m(train_xgb_ray_tune pid=1371763)[0m [29]	train-mlogloss:2.44380	validation-mlogloss:2.44292
[36m(train_xgb_ray_tune pid=1371780)[0m [32]	train-mlogloss:2.46093	validation-mlogloss:2.46045
[36m(train_xgb_ray_tune pid=1371780)[0m [33]	train-mlogloss:2.45508	validation-mlogloss:2.45466
[36m(train_xgb_ray_tune pid=1371761)[0m [39]	train-mlogloss:2.54381	validation-mlogloss:2.53895
[36m(train_xgb_ray_tune pid=1371786)[0m [29]	train-mlogloss:2.36272	validation-mlogloss:2.37459
[36m(train_xgb_ray_tune pid=1371762)[0m [33]	train-mlogloss:2.46317	validation-mlogloss:2.46665
[36m(train_xgb_ray_tune pid=1371755)[0m [36]	train-mlogloss:2.31497	validation-mlogloss:2.32716
[36m(train_xgb_ray_tune pid=1371784)[0m [31]	train-mlogloss:2.29558	validation-mlogloss:2.29373
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[36m(train_xgb_ray_tune pid=1371783)[0m [34]	train-mlogloss:2.36841	validation-mlogloss:2.37366
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[36m(train_xgb_ray_tune pid=1371748)[0m 
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[36m(train_xgb_ray_tune pid=1371784)[0m [39]	train-mlogloss:2.21730	validation-mlogloss:2.21600
[36m(train_xgb_ray_tune pid=1371763)[0m [38]	train-mlogloss:2.37510	validation-mlogloss:2.37422
[36m(train_xgb_ray_tune pid=1371794)[0m [52]	train-mlogloss:2.37049	validation-mlogloss:2.36338
[36m(train_xgb_ray_tune pid=1371793)[0m [49]	train-mlogloss:2.31792	validation-mlogloss:2.30950
[36m(train_xgb_ray_tune pid=1371795)[0m [37]	train-mlogloss:2.15605	validation-mlogloss:2.15971
[36m(train_xgb_ray_tune pid=1371782)[0m [34]	train-mlogloss:2.39056	validation-mlogloss:2.39776
[36m(train_xgb_ray_tune pid=1371761)[0m [49]	train-mlogloss:2.50728	validation-mlogloss:2.50100
[36m(train_xgb_ray_tune pid=1371781)[0m [45]	train-mlogloss:2.33831	validation-mlogloss:2.32929
[36m(train_xgb_ray_tune pid=1371796)[0m [54]	train-mlogloss:2.55144	validation-mlogloss:2.54636
[36m(train_xgb_ray_tune pid=1371754)[0m [35]	train-mlogloss:2.44710	validation-mlogloss:2.44772
[36m(train_xgb_ray_tune pid=1371762)[0m [42]	train-mlogloss:2.40896	validation-mlogloss:2.41382
[36m(train_xgb_ray_tune pid=1371783)[0m [45]	train-mlogloss:2.28862	validation-mlogloss:2.29293
[36m(train_xgb_ray_tune pid=1371766)[0m [43]	train-mlogloss:2.44313	validation-mlogloss:2.43611
[36m(train_xgb_ray_tune pid=1371748)[0m [43]	train-mlogloss:2.54186	validation-mlogloss:2.53619
[36m(train_xgb_ray_tune pid=1371780)[0m [44]	train-mlogloss:2.38989	validation-mlogloss:2.38805
[36m(train_xgb_ray_tune pid=1371764)[0m [40]	train-mlogloss:2.25183	validation-mlogloss:2.26066
[36m(train_xgb_ray_tune pid=1371786)[0m [40]	train-mlogloss:2.27168	validation-mlogloss:2.28624
[36m(train_xgb_ray_tune pid=1371794)[0m [53]	train-mlogloss:2.36519	validation-mlogloss:2.35799
[36m(train_xgb_ray_tune pid=1371763)[0m [39]	train-mlogloss:2.36771	validation-mlogloss:2.36678
[36m(train_xgb_ray_tune pid=1371796)[0m [55]	train-mlogloss:2.54901	validation-mlogloss:2.54393
[36m(train_xgb_ray_tune pid=1371784)[0m [40]	train-mlogloss:2.20820	validation-mlogloss:2.20744
[36m(train_xgb_ray_tune pid=1371793)[0m [50]	train-mlogloss:2.31162	validation-mlogloss:2.30317
[36m(train_xgb_ray_tune pid=1371761)[0m [50]	train-mlogloss:2.50368	validation-mlogloss:2.49724
[36m(train_xgb_ray_tune pid=1371781)[0m [46]	train-mlogloss:2.33156	validation-mlogloss:2.32225
[36m(train_xgb_ray_tune pid=1371795)[0m [38]	train-mlogloss:2.14525	validation-mlogloss:2.14891
[36m(train_xgb_ray_tune pid=1371755)[0m [48]	train-mlogloss:2.22564	validation-mlogloss:2.23871
[36m(train_xgb_ray_tune pid=1371782)[0m [35]	train-mlogloss:2.38317	validation-mlogloss:2.39058
[36m(train_xgb_ray_tune pid=1371766)[0m [44]	train-mlogloss:2.43772	validation-mlogloss:2.43050
[36m(train_xgb_ray_tune pid=1371754)[0m [36]	train-mlogloss:2.44076	validation-mlogloss:2.44142
[36m(train_xgb_ray_tune pid=1371748)[0m [44]	train-mlogloss:2.53829	validation-mlogloss:2.53252
[36m(train_xgb_ray_tune pid=1371762)[0m [43]	train-mlogloss:2.40307	validation-mlogloss:2.40822
[36m(train_xgb_ray_tune pid=1371783)[0m [46]	train-mlogloss:2.28215	validation-mlogloss:2.28642
[36m(train_xgb_ray_tune pid=1371794)[0m [54]	train-mlogloss:2.35992	validation-mlogloss:2.35254
[36m(train_xgb_ray_tune pid=1371780)[0m [45]	train-mlogloss:2.38419	validation-mlogloss:2.38228
[36m(train_xgb_ray_tune pid=1371796)[0m [56]	train-mlogloss:2.54646	validation-mlogloss:2.54126
[36m(train_xgb_ray_tune pid=1371786)[0m [41]	train-mlogloss:2.26388	validation-mlogloss:2.27847
[36m(train_xgb_ray_tune pid=1371763)[0m [40]	train-mlogloss:2.36046	validation-mlogloss:2.35951
[36m(train_xgb_ray_tune pid=1371764)[0m [41]	train-mlogloss:2.24356	validation-mlogloss:2.25239
[36m(train_xgb_ray_tune pid=1371761)[0m [51]	train-mlogloss:2.50014	validation-mlogloss:2.49373
[36m(train_xgb_ray_tune pid=1371781)[0m [47]	train-mlogloss:2.32559	validation-mlogloss:2.31624
[36m(train_xgb_ray_tune pid=1371793)[0m [51]	train-mlogloss:2.30532	validation-mlogloss:2.29662
[36m(train_xgb_ray_tune pid=1371784)[0m [41]	train-mlogloss:2.19804	validation-mlogloss:2.19725
[36m(train_xgb_ray_tune pid=1371754)[0m [37]	train-mlogloss:2.43456	validation-mlogloss:2.43525
[36m(train_xgb_ray_tune pid=1371761)[0m [52]	train-mlogloss:2.49655	validation-mlogloss:2.49003
[36m(train_xgb_ray_tune pid=1371764)[0m [42]	train-mlogloss:2.23554	validation-mlogloss:2.24449
[36m(train_xgb_ray_tune pid=1371781)[0m [48]	train-mlogloss:2.31872	validation-mlogloss:2.30909
[36m(train_xgb_ray_tune pid=1371786)[0m [42]	train-mlogloss:2.25637	validation-mlogloss:2.27106
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[36m(train_xgb_ray_tune pid=1371796)[0m [57]	train-mlogloss:2.54384	validation-mlogloss:2.53854
[36m(train_xgb_ray_tune pid=1371796)[0m [58]	train-mlogloss:2.54149	validation-mlogloss:2.53616
[36m(train_xgb_ray_tune pid=1371793)[0m [52]	train-mlogloss:2.29909	validation-mlogloss:2.29037
[36m(train_xgb_ray_tune pid=1371748)[0m [45]	train-mlogloss:2.53489	validation-mlogloss:2.52901
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[36m(train_xgb_ray_tune pid=1371762)[0m [44]	train-mlogloss:2.39685	validation-mlogloss:2.40194
[36m(train_xgb_ray_tune pid=1371762)[0m [45]	train-mlogloss:2.39118	validation-mlogloss:2.39659
[36m(train_xgb_ray_tune pid=1371795)[0m [39]	train-mlogloss:2.13453	validation-mlogloss:2.13800
[36m(train_xgb_ray_tune pid=1371795)[0m [40]	train-mlogloss:2.12460	validation-mlogloss:2.12817
[36m(train_xgb_ray_tune pid=1371782)[0m [36]	train-mlogloss:2.37576	validation-mlogloss:2.38342
[36m(train_xgb_ray_tune pid=1371782)[0m [37]	train-mlogloss:2.36861	validation-mlogloss:2.37669
[36m(train_xgb_ray_tune pid=1371783)[0m [47]	train-mlogloss:2.27505	validation-mlogloss:2.27916
[36m(train_xgb_ray_tune pid=1371783)[0m [48]	train-mlogloss:2.26827	validation-mlogloss:2.27217
[36m(train_xgb_ray_tune pid=1371794)[0m [55]	train-mlogloss:2.35459	validation-mlogloss:2.34720
[36m(train_xgb_ray_tune pid=1371794)[0m [56]	train-mlogloss:2.34948	validation-mlogloss:2.34197
[36m(train_xgb_ray_tune pid=1371755)[0m [49]	train-mlogloss:2.21891	validation-mlogloss:2.23207
[36m(train_xgb_ray_tune pid=1371755)[0m [50]	train-mlogloss:2.21217	validation-mlogloss:2.22556
[36m(train_xgb_ray_tune pid=1371784)[0m [42]	train-mlogloss:2.18867	validation-mlogloss:2.18745
[36m(train_xgb_ray_tune pid=1371766)[0m [45]	train-mlogloss:2.43251	validation-mlogloss:2.42500
[36m(train_xgb_ray_tune pid=1371766)[0m [46]	train-mlogloss:2.42723	validation-mlogloss:2.41955
[36m(train_xgb_ray_tune pid=1371763)[0m [41]	train-mlogloss:2.35317	validation-mlogloss:2.35201
[36m(train_xgb_ray_tune pid=1371780)[0m [46]	train-mlogloss:2.37894	validation-mlogloss:2.37699
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[36m(train_xgb_ray_tune pid=1371754)[0m [38]	train-mlogloss:2.42837	validation-mlogloss:2.42924
[36m(train_xgb_ray_tune pid=1371793)[0m [53]	train-mlogloss:2.29312	validation-mlogloss:2.28430
[36m(train_xgb_ray_tune pid=1371761)[0m [53]	train-mlogloss:2.49300	validation-mlogloss:2.48630
[36m(train_xgb_ray_tune pid=1371764)[0m [43]	train-mlogloss:2.22811	validation-mlogloss:2.23718
[36m(train_xgb_ray_tune pid=1371781)[0m [49]	train-mlogloss:2.31239	validation-mlogloss:2.30245
[36m(train_xgb_ray_tune pid=1371794)[0m [57]	train-mlogloss:2.34460	validation-mlogloss:2.33699
[36m(train_xgb_ray_tune pid=1371766)[0m [47]	train-mlogloss:2.42182	validation-mlogloss:2.41388
[36m(train_xgb_ray_tune pid=1371763)[0m [42]	train-mlogloss:2.34580	validation-mlogloss:2.34446
[36m(train_xgb_ray_tune pid=1371754)[0m [39]	train-mlogloss:2.42234	validation-mlogloss:2.42347
[36m(train_xgb_ray_tune pid=1371761)[0m [54]	train-mlogloss:2.48951	validation-mlogloss:2.48269
[36m(train_xgb_ray_tune pid=1371764)[0m [44]	train-mlogloss:2.22053	validation-mlogloss:2.22959
[36m(train_xgb_ray_tune pid=1371781)[0m [50]	train-mlogloss:2.30587	validation-mlogloss:2.29582
[36m(train_xgb_ray_tune pid=1371786)[0m [44]	train-mlogloss:2.24147	validation-mlogloss:2.25618
[36m(train_xgb_ray_tune pid=1371786)[0m [45]	train-mlogloss:2.23386	validation-mlogloss:2.24863
[36m(train_xgb_ray_tune pid=1371796)[0m [59]	train-mlogloss:2.53941	validation-mlogloss:2.53401
[36m(train_xgb_ray_tune pid=1371796)[0m [60]	train-mlogloss:2.53696	validation-mlogloss:2.53138
[36m(train_xgb_ray_tune pid=1371793)[0m [54]	train-mlogloss:2.28712	validation-mlogloss:2.27806
[36m(train_xgb_ray_tune pid=1371748)[0m [47]	train-mlogloss:2.52811	validation-mlogloss:2.52206
[36m(train_xgb_ray_tune pid=1371748)[0m [48]	train-mlogloss:2.52461	validation-mlogloss:2.51841
[36m(train_xgb_ray_tune pid=1371762)[0m [46]	train-mlogloss:2.38561	validation-mlogloss:2.39114
[36m(train_xgb_ray_tune pid=1371795)[0m [41]	train-mlogloss:2.11449	validation-mlogloss:2.11828
[36m(train_xgb_ray_tune pid=1371795)[0m [42]	train-mlogloss:2.10400	validation-mlogloss:2.10778
[36m(train_xgb_ray_tune pid=1371782)[0m [38]	train-mlogloss:2.36163	validation-mlogloss:2.36963
[36m(train_xgb_ray_tune pid=1371783)[0m [49]	train-mlogloss:2.26206	validation-mlogloss:2.26616
[36m(train_xgb_ray_tune pid=1371783)[0m [50]	train-mlogloss:2.25582	validation-mlogloss:2.26016
[36m(train_xgb_ray_tune pid=1371794)[0m [58]	train-mlogloss:2.33954	validation-mlogloss:2.33173
[36m(train_xgb_ray_tune pid=1371755)[0m [51]	train-mlogloss:2.20538	validation-mlogloss:2.21883
[36m(train_xgb_ray_tune pid=1371755)[0m [52]	train-mlogloss:2.19884	validation-mlogloss:2.21230
[36m(train_xgb_ray_tune pid=1371784)[0m [43]	train-mlogloss:2.18005	validation-mlogloss:2.17912
[36m(train_xgb_ray_tune pid=1371784)[0m [44]	train-mlogloss:2.17104	validation-mlogloss:2.17001
[36m(train_xgb_ray_tune pid=1371766)[0m [48]	train-mlogloss:2.41664	validation-mlogloss:2.40851
[36m(train_xgb_ray_tune pid=1371763)[0m [43]	train-mlogloss:2.33850	validation-mlogloss:2.33700
[36m(train_xgb_ray_tune pid=1371780)[0m [48]	train-mlogloss:2.36804	validation-mlogloss:2.36600
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[36m(train_xgb_ray_tune pid=1371793)[0m [55]	train-mlogloss:2.28099	validation-mlogloss:2.27182
[36m(train_xgb_ray_tune pid=1371762)[0m [47]	train-mlogloss:2.38027	validation-mlogloss:2.38603
[36m(train_xgb_ray_tune pid=1371794)[0m [59]	train-mlogloss:2.33421	validation-mlogloss:2.32631
[36m(train_xgb_ray_tune pid=1371781)[0m [51]	train-mlogloss:2.30030	validation-mlogloss:2.29003
[36m(train_xgb_ray_tune pid=1371766)[0m [49]	train-mlogloss:2.41133	validation-mlogloss:2.40292
[36m(train_xgb_ray_tune pid=1371761)[0m [55]	train-mlogloss:2.48585	validation-mlogloss:2.47883
[36m(train_xgb_ray_tune pid=1371796)[0m [61]	train-mlogloss:2.53423	validation-mlogloss:2.52848
[36m(train_xgb_ray_tune pid=1371782)[0m [39]	train-mlogloss:2.35474	validation-mlogloss:2.36286
[36m(train_xgb_ray_tune pid=1371755)[0m [53]	train-mlogloss:2.19232	validation-mlogloss:2.20597
[36m(train_xgb_ray_tune pid=1371763)[0m [44]	train-mlogloss:2.33133	validation-mlogloss:2.32988
[36m(train_xgb_ray_tune pid=1371754)[0m [40]	train-mlogloss:2.41641	validation-mlogloss:2.41757
[36m(train_xgb_ray_tune pid=1371764)[0m [45]	train-mlogloss:2.21312	validation-mlogloss:2.22245
[36m(train_xgb_ray_tune pid=1371786)[0m [46]	train-mlogloss:2.22672	validation-mlogloss:2.24183
[36m(train_xgb_ray_tune pid=1371748)[0m [49]	train-mlogloss:2.52115	validation-mlogloss:2.51477
[36m(train_xgb_ray_tune pid=1371783)[0m [51]	train-mlogloss:2.24932	validation-mlogloss:2.25344
[36m(train_xgb_ray_tune pid=1371781)[0m [52]	train-mlogloss:2.29416	validation-mlogloss:2.28366
[36m(train_xgb_ray_tune pid=1371795)[0m [43]	train-mlogloss:2.09462	validation-mlogloss:2.09875
[36m(train_xgb_ray_tune pid=1371780)[0m [50]	train-mlogloss:2.35756	validation-mlogloss:2.35549
[36m(train_xgb_ray_tune pid=1371762)[0m [48]	train-mlogloss:2.37474	validation-mlogloss:2.38066
[36m(train_xgb_ray_tune pid=1371794)[0m [60]	train-mlogloss:2.32901	validation-mlogloss:2.32095
[36m(train_xgb_ray_tune pid=1371784)[0m [45]	train-mlogloss:2.16250	validation-mlogloss:2.16199
[36m(train_xgb_ray_tune pid=1371793)[0m [56]	train-mlogloss:2.27479	validation-mlogloss:2.26550
[36m(train_xgb_ray_tune pid=1371763)[0m [45]	train-mlogloss:2.32416	validation-mlogloss:2.32267
[36m(train_xgb_ray_tune pid=1371796)[0m [62]	train-mlogloss:2.53184	validation-mlogloss:2.52596
[36m(train_xgb_ray_tune pid=1371755)[0m [54]	train-mlogloss:2.18567	validation-mlogloss:2.19918
[36m(train_xgb_ray_tune pid=1371766)[0m [50]	train-mlogloss:2.40624	validation-mlogloss:2.39760
[36m(train_xgb_ray_tune pid=1371761)[0m [56]	train-mlogloss:2.48238	validation-mlogloss:2.47526
[36m(train_xgb_ray_tune pid=1371782)[0m [40]	train-mlogloss:2.34756	validation-mlogloss:2.35574
[36m(train_xgb_ray_tune pid=1371783)[0m [52]	train-mlogloss:2.24273	validation-mlogloss:2.24676
[36m(train_xgb_ray_tune pid=1371754)[0m [41]	train-mlogloss:2.41045	validation-mlogloss:2.41190
[36m(train_xgb_ray_tune pid=1371764)[0m [46]	train-mlogloss:2.20563	validation-mlogloss:2.21506
[36m(train_xgb_ray_tune pid=1371786)[0m [47]	train-mlogloss:2.21947	validation-mlogloss:2.23493
[36m(train_xgb_ray_tune pid=1371748)[0m [50]	train-mlogloss:2.51769	validation-mlogloss:2.51111
[36m(train_xgb_ray_tune pid=1371754)[0m [42]	train-mlogloss:2.40449	validation-mlogloss:2.40598
[36m(train_xgb_ray_tune pid=1371761)[0m [57]	train-mlogloss:2.47901	validation-mlogloss:2.47182
[36m(train_xgb_ray_tune pid=1371764)[0m [47]	train-mlogloss:2.19805	validation-mlogloss:2.20748
[36m(train_xgb_ray_tune pid=1371781)[0m [53]	train-mlogloss:2.28855	validation-mlogloss:2.27784
[36m(train_xgb_ray_tune pid=1371781)[0m [54]	train-mlogloss:2.28268	validation-mlogloss:2.27188
[36m(train_xgb_ray_tune pid=1371786)[0m [48]	train-mlogloss:2.21226	validation-mlogloss:2.22786
[36m(train_xgb_ray_tune pid=1371796)[0m [63]	train-mlogloss:2.52946	validation-mlogloss:2.52346
[36m(train_xgb_ray_tune pid=1371796)[0m [64]	train-mlogloss:2.52697	validation-mlogloss:2.52097
[36m(train_xgb_ray_tune pid=1371793)[0m [57]	train-mlogloss:2.26876	validation-mlogloss:2.25935
[36m(train_xgb_ray_tune pid=1371793)[0m [58]	train-mlogloss:2.26256	validation-mlogloss:2.25303
[36m(train_xgb_ray_tune pid=1371748)[0m [51]	train-mlogloss:2.51432	validation-mlogloss:2.50772
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[36m(train_xgb_ray_tune pid=1371762)[0m [49]	train-mlogloss:2.36929	validation-mlogloss:2.37535
[36m(train_xgb_ray_tune pid=1371762)[0m [50]	train-mlogloss:2.36386	validation-mlogloss:2.37004
[36m(train_xgb_ray_tune pid=1371795)[0m [44]	train-mlogloss:2.08482	validation-mlogloss:2.08900
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[36m(train_xgb_ray_tune pid=1371782)[0m [41]	train-mlogloss:2.34068	validation-mlogloss:2.34902
[36m(train_xgb_ray_tune pid=1371783)[0m [53]	train-mlogloss:2.23646	validation-mlogloss:2.24048
[36m(train_xgb_ray_tune pid=1371783)[0m [54]	train-mlogloss:2.23026	validation-mlogloss:2.23417
[36m(train_xgb_ray_tune pid=1371794)[0m [61]	train-mlogloss:2.32360	validation-mlogloss:2.31526
[36m(train_xgb_ray_tune pid=1371794)[0m [62]	train-mlogloss:2.31883	validation-mlogloss:2.31031
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[36m(train_xgb_ray_tune pid=1371755)[0m [55]	train-mlogloss:2.17919	validation-mlogloss:2.19251
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[36m(train_xgb_ray_tune pid=1371784)[0m [46]	train-mlogloss:2.15345	validation-mlogloss:2.15326
[36m(train_xgb_ray_tune pid=1371766)[0m [51]	train-mlogloss:2.40105	validation-mlogloss:2.39219
[36m(train_xgb_ray_tune pid=1371766)[0m [52]	train-mlogloss:2.39596	validation-mlogloss:2.38694
[36m(train_xgb_ray_tune pid=1371763)[0m [46]	train-mlogloss:2.31714	validation-mlogloss:2.31560
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[36m(train_xgb_ray_tune pid=1371780)[0m [51]	train-mlogloss:2.35230	validation-mlogloss:2.35025
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[36m(train_xgb_ray_tune pid=1371761)[0m [58]	train-mlogloss:2.47551	validation-mlogloss:2.46815
[36m(train_xgb_ray_tune pid=1371764)[0m [48]	train-mlogloss:2.19067	validation-mlogloss:2.20019
[36m(train_xgb_ray_tune pid=1371781)[0m [55]	train-mlogloss:2.27691	validation-mlogloss:2.26601
[36m(train_xgb_ray_tune pid=1371786)[0m [49]	train-mlogloss:2.20523	validation-mlogloss:2.22090
[36m(train_xgb_ray_tune pid=1371796)[0m [65]	train-mlogloss:2.52468	validation-mlogloss:2.51853
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[36m(train_xgb_ray_tune pid=1371761)[0m [66]	train-mlogloss:2.44863	validation-mlogloss:2.44037
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[36m(train_xgb_ray_tune pid=1371755)[0m [102]	train-mlogloss:1.93599	validation-mlogloss:1.94683
[36m(train_xgb_ray_tune pid=1371784)[0m [87]	train-mlogloss:1.86939	validation-mlogloss:1.87353
[36m(train_xgb_ray_tune pid=1371754)[0m [86]	train-mlogloss:2.17880	validation-mlogloss:2.18080
[36m(train_xgb_ray_tune pid=1371761)[0m [106]	train-mlogloss:2.32743	validation-mlogloss:2.31479
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[36m(train_xgb_ray_tune pid=1371764)[0m [90]	train-mlogloss:1.94198	validation-mlogloss:1.94845
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[36m(train_xgb_ray_tune pid=1371764)[0m [98]	train-mlogloss:1.90645	validation-mlogloss:1.91214
[36m(train_xgb_ray_tune pid=1371793)[0m [116]	train-mlogloss:1.97720	validation-mlogloss:1.96033
[36m(train_xgb_ray_tune pid=1371762)[0m [103]	train-mlogloss:2.11793	validation-mlogloss:2.12874
[36m(train_xgb_ray_tune pid=1371754)[0m [94]	train-mlogloss:2.14433	validation-mlogloss:2.14620
[36m(train_xgb_ray_tune pid=1371781)[0m [111]	train-mlogloss:2.04627	validation-mlogloss:2.02646
[36m(train_xgb_ray_tune pid=1371783)[0m [114]	train-mlogloss:1.94140	validation-mlogloss:1.93898
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[36m(train_xgb_ray_tune pid=1371780)[0m [112]	train-mlogloss:2.09729	validation-mlogloss:2.08864
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[36m(train_xgb_ray_tune pid=1371795)[0m [95]	train-mlogloss:1.72175	validation-mlogloss:1.71804
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[36m(train_xgb_ray_tune pid=1371782)[0m [93]	train-mlogloss:2.04610	validation-mlogloss:2.06282
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[36m(train_xgb_ray_tune pid=1371782)[0m [94]	train-mlogloss:2.04137	validation-mlogloss:2.05820
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[36m(train_xgb_ray_tune pid=1371786)[0m [114]	train-mlogloss:1.86801	validation-mlogloss:1.87865
[36m(train_xgb_ray_tune pid=1371795)[0m [101]	train-mlogloss:1.69202	validation-mlogloss:1.68777
[36m(train_xgb_ray_tune pid=1371782)[0m [95]	train-mlogloss:2.03683	validation-mlogloss:2.05377
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[36m(train_xgb_ray_tune pid=1371783)[0m [122]	train-mlogloss:1.91260	validation-mlogloss:1.90941
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[36m(train_xgb_ray_tune pid=1371794)[0m [133]	train-mlogloss:2.03428	validation-mlogloss:2.01800
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[36m(train_xgb_ray_tune pid=1371784)[0m [103]	train-mlogloss:1.78836	validation-mlogloss:1.79380
[36m(train_xgb_ray_tune pid=1371793)[0m [126]	train-mlogloss:1.93866	validation-mlogloss:1.92095
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[36m(train_xgb_ray_tune pid=1371761)[0m [125]	train-mlogloss:2.27742	validation-mlogloss:2.26312
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[36m(train_xgb_ray_tune pid=1371781)[0m [122]	train-mlogloss:2.01778	validation-mlogloss:1.99650
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[36m(train_xgb_ray_tune pid=1371781)[0m [176]	train-mlogloss:1.92932	validation-mlogloss:1.90334
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[36m(train_xgb_ray_tune pid=1371781)[0m [273]	train-mlogloss:1.89520	validation-mlogloss:1.86732
[36m(train_xgb_ray_tune pid=1371781)[0m [274]	train-mlogloss:1.89507	validation-mlogloss:1.86725
[36m(train_xgb_ray_tune pid=1371786)[0m [235]	train-mlogloss:1.54717	validation-mlogloss:1.54277
[36m(train_xgb_ray_tune pid=1371786)[0m [236]	train-mlogloss:1.54538	validation-mlogloss:1.54084
[36m(train_xgb_ray_tune pid=1371796)[0m [292]	train-mlogloss:2.26150	validation-mlogloss:2.24503
[36m(train_xgb_ray_tune pid=1371796)[0m [293]	train-mlogloss:2.26107	validation-mlogloss:2.24456
[36m(train_xgb_ray_tune pid=1371793)[0m [256]	train-mlogloss:1.60723	validation-mlogloss:1.57997
[36m(train_xgb_ray_tune pid=1371793)[0m [257]	train-mlogloss:1.60566	validation-mlogloss:1.57836
[36m(train_xgb_ray_tune pid=1371748)[0m [253]	train-mlogloss:2.00605	validation-mlogloss:1.98234
[36m(train_xgb_ray_tune pid=1371748)[0m [254]	train-mlogloss:2.00411	validation-mlogloss:1.98030
[36m(train_xgb_ray_tune pid=1371762)[0m [228]	train-mlogloss:1.76397	validation-mlogloss:1.77222
[36m(train_xgb_ray_tune pid=1371795)[0m [212]	train-mlogloss:1.41008	validation-mlogloss:1.38817
[36m(train_xgb_ray_tune pid=1371782)[0m [199]	train-mlogloss:1.69215	validation-mlogloss:1.71066
[36m(train_xgb_ray_tune pid=1371783)[0m [244]	train-mlogloss:1.61397	validation-mlogloss:1.59729
[36m(train_xgb_ray_tune pid=1371783)[0m [245]	train-mlogloss:1.61245	validation-mlogloss:1.59569
[36m(train_xgb_ray_tune pid=1371794)[0m [261]	train-mlogloss:1.75539	validation-mlogloss:1.72781
[36m(train_xgb_ray_tune pid=1371794)[0m [262]	train-mlogloss:1.75425	validation-mlogloss:1.72662
[36m(train_xgb_ray_tune pid=1371755)[0m [244]	train-mlogloss:1.55704	validation-mlogloss:1.54831
[36m(train_xgb_ray_tune pid=1371755)[0m [245]	train-mlogloss:1.55540	validation-mlogloss:1.54652
[36m(train_xgb_ray_tune pid=1371755)[0m [246]	train-mlogloss:1.55384	validation-mlogloss:1.54487
[36m(train_xgb_ray_tune pid=1371784)[0m [209]	train-mlogloss:1.44115	validation-mlogloss:1.45044
[36m(train_xgb_ray_tune pid=1371766)[0m [236]	train-mlogloss:1.78492	validation-mlogloss:1.75615
[36m(train_xgb_ray_tune pid=1371766)[0m [237]	train-mlogloss:1.78303	validation-mlogloss:1.75422
[36m(train_xgb_ray_tune pid=1371763)[0m [219]	train-mlogloss:1.62605	validation-mlogloss:1.61752
[36m(train_xgb_ray_tune pid=1371780)[0m [247]	train-mlogloss:1.82093	validation-mlogloss:1.80016
[36m(train_xgb_ray_tune pid=1371780)[0m [248]	train-mlogloss:1.81983	validation-mlogloss:1.79900
[36m(train_xgb_ray_tune pid=1371754)[0m [213]	train-mlogloss:1.78676	validation-mlogloss:1.78403
[36m(train_xgb_ray_tune pid=1371754)[0m [214]	train-mlogloss:1.78434	validation-mlogloss:1.78151
[36m(train_xgb_ray_tune pid=1371761)[0m [253]	train-mlogloss:2.02915	validation-mlogloss:2.00479
[36m(train_xgb_ray_tune pid=1371781)[0m [275]	train-mlogloss:1.89472	validation-mlogloss:1.86691
[36m(train_xgb_ray_tune pid=1371781)[0m [276]	train-mlogloss:1.89472	validation-mlogloss:1.86691
[36m(train_xgb_ray_tune pid=1371786)[0m [237]	train-mlogloss:1.54363	validation-mlogloss:1.53899
[36m(train_xgb_ray_tune pid=1371796)[0m [294]	train-mlogloss:2.26043	validation-mlogloss:2.24384
[36m(train_xgb_ray_tune pid=1371796)[0m [295]	train-mlogloss:2.26018	validation-mlogloss:2.24358
[36m(train_xgb_ray_tune pid=1371793)[0m [258]	train-mlogloss:1.60402	validation-mlogloss:1.57659
[36m(train_xgb_ray_tune pid=1371748)[0m [255]	train-mlogloss:2.00225	validation-mlogloss:1.97836
[36m(train_xgb_ray_tune pid=1371748)[0m [256]	train-mlogloss:2.00044	validation-mlogloss:1.97652
[36m(train_xgb_ray_tune pid=1371762)[0m [229]	train-mlogloss:1.76196	validation-mlogloss:1.77026
[36m(train_xgb_ray_tune pid=1371762)[0m [230]	train-mlogloss:1.75982	validation-mlogloss:1.76814
[36m(train_xgb_ray_tune pid=1371795)[0m [213]	train-mlogloss:1.40879	validation-mlogloss:1.38686
[36m(train_xgb_ray_tune pid=1371795)[0m [214]	train-mlogloss:1.40764	validation-mlogloss:1.38559
[36m(train_xgb_ray_tune pid=1371782)[0m [200]	train-mlogloss:1.68966	validation-mlogloss:1.70805
[36m(train_xgb_ray_tune pid=1371782)[0m [201]	train-mlogloss:1.68718	validation-mlogloss:1.70561
[36m(train_xgb_ray_tune pid=1371783)[0m [246]	train-mlogloss:1.61092	validation-mlogloss:1.59410
[36m(train_xgb_ray_tune pid=1371783)[0m [247]	train-mlogloss:1.60943	validation-mlogloss:1.59248
[36m(train_xgb_ray_tune pid=1371794)[0m [263]	train-mlogloss:1.75302	validation-mlogloss:1.72531
[36m(train_xgb_ray_tune pid=1371794)[0m [264]	train-mlogloss:1.75174	validation-mlogloss:1.72398
[36m(train_xgb_ray_tune pid=1371755)[0m [247]	train-mlogloss:1.55227	validation-mlogloss:1.54318
[36m(train_xgb_ray_tune pid=1371784)[0m [210]	train-mlogloss:1.43910	validation-mlogloss:1.44861
[36m(train_xgb_ray_tune pid=1371784)[0m [211]	train-mlogloss:1.43698	validation-mlogloss:1.44646
[36m(train_xgb_ray_tune pid=1371766)[0m [238]	train-mlogloss:1.78099	validation-mlogloss:1.75214
[36m(train_xgb_ray_tune pid=1371766)[0m [239]	train-mlogloss:1.77896	validation-mlogloss:1.75006
[36m(train_xgb_ray_tune pid=1371766)[0m [240]	train-mlogloss:1.77705	validation-mlogloss:1.74803
[36m(train_xgb_ray_tune pid=1371763)[0m [220]	train-mlogloss:1.62395	validation-mlogloss:1.61547
[36m(train_xgb_ray_tune pid=1371763)[0m [221]	train-mlogloss:1.62194	validation-mlogloss:1.61338
[36m(train_xgb_ray_tune pid=1371761)[0m [254]	train-mlogloss:2.02772	validation-mlogloss:2.00330
[36m(train_xgb_ray_tune pid=1371793)[0m [259]	train-mlogloss:1.60253	validation-mlogloss:1.57508
[36m(train_xgb_ray_tune pid=1371781)[0m [277]	train-mlogloss:1.89472	validation-mlogloss:1.86691
[36m(train_xgb_ray_tune pid=1371796)[0m [296]	train-mlogloss:2.26001	validation-mlogloss:2.24345
[36m(train_xgb_ray_tune pid=1371782)[0m [202]	train-mlogloss:1.68468	validation-mlogloss:1.70299
[36m(train_xgb_ray_tune pid=1371755)[0m [248]	train-mlogloss:1.55073	validation-mlogloss:1.54161
[36m(train_xgb_ray_tune pid=1371754)[0m [215]	train-mlogloss:1.78206	validation-mlogloss:1.77923
[36m(train_xgb_ray_tune pid=1371786)[0m [238]	train-mlogloss:1.54189	validation-mlogloss:1.53722
[36m(train_xgb_ray_tune pid=1371783)[0m [248]	train-mlogloss:1.60784	validation-mlogloss:1.59075
[36m(train_xgb_ray_tune pid=1371794)[0m [265]	train-mlogloss:1.75050	validation-mlogloss:1.72269
[36m(train_xgb_ray_tune pid=1371766)[0m [241]	train-mlogloss:1.77509	validation-mlogloss:1.74602
[36m(train_xgb_ray_tune pid=1371754)[0m [216]	train-mlogloss:1.77975	validation-mlogloss:1.77690
[36m(train_xgb_ray_tune pid=1371761)[0m [255]	train-mlogloss:2.02665	validation-mlogloss:2.00217
[36m(train_xgb_ray_tune pid=1371761)[0m [256]	train-mlogloss:2.02509	validation-mlogloss:2.00059
[36m(train_xgb_ray_tune pid=1371781)[0m [278]	train-mlogloss:1.89462	validation-mlogloss:1.86682
[36m(train_xgb_ray_tune pid=1371781)[0m [279]	train-mlogloss:1.89462	validation-mlogloss:1.86682
[36m(train_xgb_ray_tune pid=1371781)[0m [280]	train-mlogloss:1.89462	validation-mlogloss:1.86682
[36m(train_xgb_ray_tune pid=1371781)[0m [281]	train-mlogloss:1.89462	validation-mlogloss:1.86682
[36m(train_xgb_ray_tune pid=1371786)[0m [239]	train-mlogloss:1.54009	validation-mlogloss:1.53538
[36m(train_xgb_ray_tune pid=1371796)[0m [297]	train-mlogloss:2.25945	validation-mlogloss:2.24285
[36m(train_xgb_ray_tune pid=1371796)[0m [298]	train-mlogloss:2.25905	validation-mlogloss:2.24246
[36m(train_xgb_ray_tune pid=1371793)[0m [260]	train-mlogloss:1.60092	validation-mlogloss:1.57335
[36m(train_xgb_ray_tune pid=1371793)[0m [261]	train-mlogloss:1.59934	validation-mlogloss:1.57172
[36m(train_xgb_ray_tune pid=1371748)[0m [257]	train-mlogloss:1.99860	validation-mlogloss:1.97466
[36m(train_xgb_ray_tune pid=1371748)[0m [258]	train-mlogloss:1.99681	validation-mlogloss:1.97278
[36m(train_xgb_ray_tune pid=1371762)[0m [231]	train-mlogloss:1.75763	validation-mlogloss:1.76598
[36m(train_xgb_ray_tune pid=1371762)[0m [232]	train-mlogloss:1.75571	validation-mlogloss:1.76405
[36m(train_xgb_ray_tune pid=1371795)[0m [215]	train-mlogloss:1.40654	validation-mlogloss:1.38440
[36m(train_xgb_ray_tune pid=1371795)[0m [216]	train-mlogloss:1.40532	validation-mlogloss:1.38308
[36m(train_xgb_ray_tune pid=1371782)[0m [203]	train-mlogloss:1.68226	validation-mlogloss:1.70053
[36m(train_xgb_ray_tune pid=1371783)[0m [249]	train-mlogloss:1.60631	validation-mlogloss:1.58914
[36m(train_xgb_ray_tune pid=1371783)[0m [250]	train-mlogloss:1.60485	validation-mlogloss:1.58766
[36m(train_xgb_ray_tune pid=1371794)[0m [266]	train-mlogloss:1.74929	validation-mlogloss:1.72144
[36m(train_xgb_ray_tune pid=1371794)[0m [267]	train-mlogloss:1.74819	validation-mlogloss:1.72021
[36m(train_xgb_ray_tune pid=1371755)[0m [249]	train-mlogloss:1.54918	validation-mlogloss:1.53995
[36m(train_xgb_ray_tune pid=1371764)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 2x across cluster][0m
[36m(train_xgb_ray_tune pid=1371764)[0m   _log_deprecation_warning([32m [repeated 2x across cluster][0m
[36m(train_xgb_ray_tune pid=1371784)[0m [212]	train-mlogloss:1.43498	validation-mlogloss:1.44445
[36m(train_xgb_ray_tune pid=1371784)[0m [213]	train-mlogloss:1.43297	validation-mlogloss:1.44234
[36m(train_xgb_ray_tune pid=1371766)[0m [242]	train-mlogloss:1.77319	validation-mlogloss:1.74399
[36m(train_xgb_ray_tune pid=1371763)[0m [222]	train-mlogloss:1.61990	validation-mlogloss:1.61133
[36m(train_xgb_ray_tune pid=1371763)[0m [223]	train-mlogloss:1.61788	validation-mlogloss:1.60922
[36m(train_xgb_ray_tune pid=1371754)[0m [217]	train-mlogloss:1.77755	validation-mlogloss:1.77461
[36m(train_xgb_ray_tune pid=1371781)[0m [282]	train-mlogloss:1.89431	validation-mlogloss:1.86643
[36m(train_xgb_ray_tune pid=1371786)[0m [240]	train-mlogloss:1.53840	validation-mlogloss:1.53364
[36m(train_xgb_ray_tune pid=1371783)[0m [251]	train-mlogloss:1.60342	validation-mlogloss:1.58613
[36m(train_xgb_ray_tune pid=1371755)[0m [250]	train-mlogloss:1.54768	validation-mlogloss:1.53841
[36m(train_xgb_ray_tune pid=1371782)[0m [204]	train-mlogloss:1.67986	validation-mlogloss:1.69802
[36m(train_xgb_ray_tune pid=1371766)[0m [243]	train-mlogloss:1.77113	validation-mlogloss:1.74182
[36m(train_xgb_ray_tune pid=1371796)[0m [299]	train-mlogloss:2.25866	validation-mlogloss:2.24206
[36m(train_xgb_ray_tune pid=1371795)[0m [217]	train-mlogloss:1.40407	validation-mlogloss:1.38173
[36m(train_xgb_ray_tune pid=1371794)[0m [268]	train-mlogloss:1.74701	validation-mlogloss:1.71896
[36m(train_xgb_ray_tune pid=1371748)[0m [259]	train-mlogloss:1.99484	validation-mlogloss:1.97070
[36m(train_xgb_ray_tune pid=1371761)[0m [257]	train-mlogloss:2.02390	validation-mlogloss:1.99928
[36m(train_xgb_ray_tune pid=1371781)[0m [283]	train-mlogloss:1.89407	validation-mlogloss:1.86623
[36m(train_xgb_ray_tune pid=1371754)[0m [218]	train-mlogloss:1.77535	validation-mlogloss:1.77233
[36m(train_xgb_ray_tune pid=1371754)[0m [219]	train-mlogloss:1.77317	validation-mlogloss:1.77008
[36m(train_xgb_ray_tune pid=1371761)[0m [258]	train-mlogloss:2.02257	validation-mlogloss:1.99792
[36m(train_xgb_ray_tune pid=1371781)[0m [284]	train-mlogloss:1.89396	validation-mlogloss:1.86613
[36m(train_xgb_ray_tune pid=1371781)[0m [285]	train-mlogloss:1.89385	validation-mlogloss:1.86599
[36m(train_xgb_ray_tune pid=1371786)[0m [241]	train-mlogloss:1.53666	validation-mlogloss:1.53175
[36m(train_xgb_ray_tune pid=1371796)[0m [300]	train-mlogloss:2.25836	validation-mlogloss:2.24170
[36m(train_xgb_ray_tune pid=1371796)[0m [301]	train-mlogloss:2.25821	validation-mlogloss:2.24157
[36m(train_xgb_ray_tune pid=1371793)[0m [262]	train-mlogloss:1.59779	validation-mlogloss:1.57010
[36m(train_xgb_ray_tune pid=1371793)[0m [263]	train-mlogloss:1.59618	validation-mlogloss:1.56843
[36m(train_xgb_ray_tune pid=1371748)[0m [260]	train-mlogloss:1.99304	validation-mlogloss:1.96889
[36m(train_xgb_ray_tune pid=1371748)[0m [261]	train-mlogloss:1.99118	validation-mlogloss:1.96693
[36m(train_xgb_ray_tune pid=1371762)[0m [233]	train-mlogloss:1.75362	validation-mlogloss:1.76193
[36m(train_xgb_ray_tune pid=1371762)[0m [234]	train-mlogloss:1.75149	validation-mlogloss:1.75959
[36m(train_xgb_ray_tune pid=1371795)[0m [218]	train-mlogloss:1.40294	validation-mlogloss:1.38062
[36m(train_xgb_ray_tune pid=1371782)[0m [205]	train-mlogloss:1.67742	validation-mlogloss:1.69557
[36m(train_xgb_ray_tune pid=1371783)[0m [252]	train-mlogloss:1.60200	validation-mlogloss:1.58468
[36m(train_xgb_ray_tune pid=1371783)[0m [253]	train-mlogloss:1.60061	validation-mlogloss:1.58316
[36m(train_xgb_ray_tune pid=1371794)[0m [269]	train-mlogloss:1.74585	validation-mlogloss:1.71770
[36m(train_xgb_ray_tune pid=1371794)[0m [270]	train-mlogloss:1.74469	validation-mlogloss:1.71643
[36m(train_xgb_ray_tune pid=1371755)[0m [251]	train-mlogloss:1.54620	validation-mlogloss:1.53685
[36m(train_xgb_ray_tune pid=1371755)[0m [252]	train-mlogloss:1.54471	validation-mlogloss:1.53521
[36m(train_xgb_ray_tune pid=1371784)[0m [214]	train-mlogloss:1.43097	validation-mlogloss:1.44036
[36m(train_xgb_ray_tune pid=1371784)[0m [215]	train-mlogloss:1.42890	validation-mlogloss:1.43825
[36m(train_xgb_ray_tune pid=1371766)[0m [244]	train-mlogloss:1.76924	validation-mlogloss:1.73988
[36m(train_xgb_ray_tune pid=1371766)[0m [245]	train-mlogloss:1.76740	validation-mlogloss:1.73795
[36m(train_xgb_ray_tune pid=1371763)[0m [224]	train-mlogloss:1.61593	validation-mlogloss:1.60725
[36m(train_xgb_ray_tune pid=1371763)[0m [225]	train-mlogloss:1.61401	validation-mlogloss:1.60523
[36m(train_xgb_ray_tune pid=1371781)[0m [286]	train-mlogloss:1.89385	validation-mlogloss:1.86599
[36m(train_xgb_ray_tune pid=1371786)[0m [242]	train-mlogloss:1.53500	validation-mlogloss:1.52995
[36m(train_xgb_ray_tune pid=1371795)[0m [219]	train-mlogloss:1.40191	validation-mlogloss:1.37951
[36m(train_xgb_ray_tune pid=1371761)[0m [259]	train-mlogloss:2.02138	validation-mlogloss:1.99665
[36m(train_xgb_ray_tune pid=1371748)[0m [262]	train-mlogloss:1.98940	validation-mlogloss:1.96508
[36m(train_xgb_ray_tune pid=1371782)[0m [206]	train-mlogloss:1.67506	validation-mlogloss:1.69313
[36m(train_xgb_ray_tune pid=1371754)[0m [220]	train-mlogloss:1.77098	validation-mlogloss:1.76778

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:04:49. Total running time: 27s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             24.2759 │
│ time_total_s                 24.2759 │
│ training_iteration                 1 │
│ validation_accuracy          0.50244 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1371796)[0m [302]	train-mlogloss:2.25797	validation-mlogloss:2.24130
[36m(train_xgb_ray_tune pid=1371793)[0m [264]	train-mlogloss:1.59456	validation-mlogloss:1.56667
[36m(train_xgb_ray_tune pid=1371762)[0m [235]	train-mlogloss:1.74935	validation-mlogloss:1.75738

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:04:49. Total running time: 27s

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:04:49. Total running time: 27s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             24.3102 │
│ time_total_s                 24.3102 │
│ training_iteration                 1 │
│ validation_accuracy          0.46744 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1371754)[0m [221]	train-mlogloss:1.76870	validation-mlogloss:1.76552

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:04:49. Total running time: 27s
[36m(train_xgb_ray_tune pid=1371761)[0m [260]	train-mlogloss:2.02004	validation-mlogloss:1.99522
[36m(train_xgb_ray_tune pid=1371781)[0m [287]	train-mlogloss:1.89350	validation-mlogloss:1.86564
[36m(train_xgb_ray_tune pid=1371781)[0m [288]	train-mlogloss:1.89339	validation-mlogloss:1.86558
[36m(train_xgb_ray_tune pid=1371781)[0m [289]	train-mlogloss:1.89339	validation-mlogloss:1.86558
[36m(train_xgb_ray_tune pid=1371786)[0m [243]	train-mlogloss:1.53331	validation-mlogloss:1.52815
[36m(train_xgb_ray_tune pid=1371786)[0m [244]	train-mlogloss:1.53161	validation-mlogloss:1.52642
[36m(train_xgb_ray_tune pid=1371796)[0m [303]	train-mlogloss:2.25775	validation-mlogloss:2.24104
[36m(train_xgb_ray_tune pid=1371796)[0m [304]	train-mlogloss:2.25759	validation-mlogloss:2.24090
[36m(train_xgb_ray_tune pid=1371793)[0m [265]	train-mlogloss:1.59298	validation-mlogloss:1.56504
[36m(train_xgb_ray_tune pid=1371748)[0m [263]	train-mlogloss:1.98773	validation-mlogloss:1.96342
[36m(train_xgb_ray_tune pid=1371762)[0m [236]	train-mlogloss:1.74735	validation-mlogloss:1.75523
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[36m(train_xgb_ray_tune pid=1371755)[0m [281]	train-mlogloss:1.50315	validation-mlogloss:1.49092
[36m(train_xgb_ray_tune pid=1371755)[0m [282]	train-mlogloss:1.50183	validation-mlogloss:1.48951
[36m(train_xgb_ray_tune pid=1371784)[0m [244]	train-mlogloss:1.37702	validation-mlogloss:1.38761
[36m(train_xgb_ray_tune pid=1371766)[0m [274]	train-mlogloss:1.71753	validation-mlogloss:1.68596
[36m(train_xgb_ray_tune pid=1371766)[0m [275]	train-mlogloss:1.71593	validation-mlogloss:1.68427
[36m(train_xgb_ray_tune pid=1371766)[0m [276]	train-mlogloss:1.71432	validation-mlogloss:1.68252
[36m(train_xgb_ray_tune pid=1371763)[0m [250]	train-mlogloss:1.56908	validation-mlogloss:1.55942
[36m(train_xgb_ray_tune pid=1371763)[0m [251]	train-mlogloss:1.56744	validation-mlogloss:1.55768
[36m(train_xgb_ray_tune pid=1371761)[0m [293]	train-mlogloss:1.97875	validation-mlogloss:1.95163
[36m(train_xgb_ray_tune pid=1371781)[0m [332]	train-mlogloss:1.89019	validation-mlogloss:1.86227
[36m(train_xgb_ray_tune pid=1371795)[0m [250]	train-mlogloss:1.37416	validation-mlogloss:1.35063
[36m(train_xgb_ray_tune pid=1371784)[0m [245]	train-mlogloss:1.37538	validation-mlogloss:1.38599
[36m(train_xgb_ray_tune pid=1371754)[0m [253]	train-mlogloss:1.70491	validation-mlogloss:1.69922
[36m(train_xgb_ray_tune pid=1371754)[0m [254]	train-mlogloss:1.70315	validation-mlogloss:1.69746
[36m(train_xgb_ray_tune pid=1371761)[0m [294]	train-mlogloss:1.97758	validation-mlogloss:1.95039
[36m(train_xgb_ray_tune pid=1371781)[0m [333]	train-mlogloss:1.88983	validation-mlogloss:1.86188
[36m(train_xgb_ray_tune pid=1371781)[0m [334]	train-mlogloss:1.88983	validation-mlogloss:1.86188
[36m(train_xgb_ray_tune pid=1371786)[0m [272]	train-mlogloss:1.48792	validation-mlogloss:1.48076
[36m(train_xgb_ray_tune pid=1371786)[0m [273]	train-mlogloss:1.48651	validation-mlogloss:1.47928
[36m(train_xgb_ray_tune pid=1371796)[0m [343]	train-mlogloss:2.24846	validation-mlogloss:2.23155
[36m(train_xgb_ray_tune pid=1371796)[0m [344]	train-mlogloss:2.24846	validation-mlogloss:2.23155
[36m(train_xgb_ray_tune pid=1371796)[0m [345]	train-mlogloss:2.24792	validation-mlogloss:2.23101
[36m(train_xgb_ray_tune pid=1371793)[0m [296]	train-mlogloss:1.55137	validation-mlogloss:1.52201
[36m(train_xgb_ray_tune pid=1371793)[0m [297]	train-mlogloss:1.55022	validation-mlogloss:1.52078
[36m(train_xgb_ray_tune pid=1371748)[0m [295]	train-mlogloss:1.93369	validation-mlogloss:1.90760
[36m(train_xgb_ray_tune pid=1371748)[0m [296]	train-mlogloss:1.93203	validation-mlogloss:1.90587
[36m(train_xgb_ray_tune pid=1371762)[0m [263]	train-mlogloss:1.69692	validation-mlogloss:1.70325
[36m(train_xgb_ray_tune pid=1371762)[0m [264]	train-mlogloss:1.69519	validation-mlogloss:1.70142
[36m(train_xgb_ray_tune pid=1371795)[0m [251]	train-mlogloss:1.37345	validation-mlogloss:1.34983
[36m(train_xgb_ray_tune pid=1371795)[0m [252]	train-mlogloss:1.37278	validation-mlogloss:1.34911
[36m(train_xgb_ray_tune pid=1371782)[0m [234]	train-mlogloss:1.61308	validation-mlogloss:1.63045
[36m(train_xgb_ray_tune pid=1371783)[0m [286]	train-mlogloss:1.55755	validation-mlogloss:1.53719
[36m(train_xgb_ray_tune pid=1371783)[0m [287]	train-mlogloss:1.55646	validation-mlogloss:1.53606
[36m(train_xgb_ray_tune pid=1371794)[0m [318]	train-mlogloss:1.69927	validation-mlogloss:1.66844
[36m(train_xgb_ray_tune pid=1371794)[0m [319]	train-mlogloss:1.69838	validation-mlogloss:1.66744
[36m(train_xgb_ray_tune pid=1371755)[0m [283]	train-mlogloss:1.50056	validation-mlogloss:1.48823
[36m(train_xgb_ray_tune pid=1371755)[0m [284]	train-mlogloss:1.49925	validation-mlogloss:1.48682
[36m(train_xgb_ray_tune pid=1371784)[0m [246]	train-mlogloss:1.37382	validation-mlogloss:1.38437
[36m(train_xgb_ray_tune pid=1371766)[0m [277]	train-mlogloss:1.71273	validation-mlogloss:1.68087
[36m(train_xgb_ray_tune pid=1371766)[0m [278]	train-mlogloss:1.71111	validation-mlogloss:1.67918
[36m(train_xgb_ray_tune pid=1371766)[0m [279]	train-mlogloss:1.70950	validation-mlogloss:1.67748
[36m(train_xgb_ray_tune pid=1371763)[0m [252]	train-mlogloss:1.56577	validation-mlogloss:1.55592
[36m(train_xgb_ray_tune pid=1371763)[0m [253]	train-mlogloss:1.56408	validation-mlogloss:1.55426
[36m(train_xgb_ray_tune pid=1371761)[0m [295]	train-mlogloss:1.97648	validation-mlogloss:1.94922
[36m(train_xgb_ray_tune pid=1371754)[0m [255]	train-mlogloss:1.70135	validation-mlogloss:1.69568
[36m(train_xgb_ray_tune pid=1371754)[0m [256]	train-mlogloss:1.69955	validation-mlogloss:1.69376
[36m(train_xgb_ray_tune pid=1371761)[0m [296]	train-mlogloss:1.97532	validation-mlogloss:1.94796
[36m(train_xgb_ray_tune pid=1371781)[0m [335]	train-mlogloss:1.88971	validation-mlogloss:1.86180
[36m(train_xgb_ray_tune pid=1371781)[0m [336]	train-mlogloss:1.88961	validation-mlogloss:1.86172
[36m(train_xgb_ray_tune pid=1371786)[0m [274]	train-mlogloss:1.48514	validation-mlogloss:1.47785
[36m(train_xgb_ray_tune pid=1371786)[0m [275]	train-mlogloss:1.48369	validation-mlogloss:1.47623
[36m(train_xgb_ray_tune pid=1371796)[0m [346]	train-mlogloss:2.24779	validation-mlogloss:2.23086
[36m(train_xgb_ray_tune pid=1371796)[0m [347]	train-mlogloss:2.24779	validation-mlogloss:2.23086
[36m(train_xgb_ray_tune pid=1371793)[0m [298]	train-mlogloss:1.54900	validation-mlogloss:1.51951
[36m(train_xgb_ray_tune pid=1371748)[0m [297]	train-mlogloss:1.93048	validation-mlogloss:1.90427
[36m(train_xgb_ray_tune pid=1371748)[0m [298]	train-mlogloss:1.92887	validation-mlogloss:1.90259
[36m(train_xgb_ray_tune pid=1371762)[0m [265]	train-mlogloss:1.69341	validation-mlogloss:1.69956
[36m(train_xgb_ray_tune pid=1371762)[0m [266]	train-mlogloss:1.69172	validation-mlogloss:1.69782
[36m(train_xgb_ray_tune pid=1371795)[0m [253]	train-mlogloss:1.37181	validation-mlogloss:1.34805
[36m(train_xgb_ray_tune pid=1371782)[0m [235]	train-mlogloss:1.61110	validation-mlogloss:1.62840
[36m(train_xgb_ray_tune pid=1371782)[0m [236]	train-mlogloss:1.60906	validation-mlogloss:1.62634
[36m(train_xgb_ray_tune pid=1371783)[0m [288]	train-mlogloss:1.55524	validation-mlogloss:1.53472
[36m(train_xgb_ray_tune pid=1371783)[0m [289]	train-mlogloss:1.55401	validation-mlogloss:1.53339
[36m(train_xgb_ray_tune pid=1371794)[0m [320]	train-mlogloss:1.69761	validation-mlogloss:1.66661
[36m(train_xgb_ray_tune pid=1371794)[0m [321]	train-mlogloss:1.69685	validation-mlogloss:1.66579
[36m(train_xgb_ray_tune pid=1371755)[0m [285]	train-mlogloss:1.49796	validation-mlogloss:1.48540
[36m(train_xgb_ray_tune pid=1371755)[0m [286]	train-mlogloss:1.49671	validation-mlogloss:1.48400
[36m(train_xgb_ray_tune pid=1371784)[0m [247]	train-mlogloss:1.37229	validation-mlogloss:1.38291
[36m(train_xgb_ray_tune pid=1371784)[0m [248]	train-mlogloss:1.37074	validation-mlogloss:1.38139
[36m(train_xgb_ray_tune pid=1371766)[0m [280]	train-mlogloss:1.70787	validation-mlogloss:1.67576
[36m(train_xgb_ray_tune pid=1371766)[0m [281]	train-mlogloss:1.70639	validation-mlogloss:1.67425
[36m(train_xgb_ray_tune pid=1371766)[0m [282]	train-mlogloss:1.70486	validation-mlogloss:1.67269
[36m(train_xgb_ray_tune pid=1371763)[0m [254]	train-mlogloss:1.56246	validation-mlogloss:1.55265
[36m(train_xgb_ray_tune pid=1371761)[0m [297]	train-mlogloss:1.97425	validation-mlogloss:1.94685
[36m(train_xgb_ray_tune pid=1371781)[0m [337]	train-mlogloss:1.88913	validation-mlogloss:1.86121
[36m(train_xgb_ray_tune pid=1371793)[0m [299]	train-mlogloss:1.54772	validation-mlogloss:1.51816
[36m(train_xgb_ray_tune pid=1371795)[0m [254]	train-mlogloss:1.37108	validation-mlogloss:1.34730
[36m(train_xgb_ray_tune pid=1371754)[0m [257]	train-mlogloss:1.69771	validation-mlogloss:1.69191
[36m(train_xgb_ray_tune pid=1371761)[0m [298]	train-mlogloss:1.97317	validation-mlogloss:1.94574
[36m(train_xgb_ray_tune pid=1371781)[0m [338]	train-mlogloss:1.88913	validation-mlogloss:1.86121
[36m(train_xgb_ray_tune pid=1371781)[0m [339]	train-mlogloss:1.88913	validation-mlogloss:1.86121
[36m(train_xgb_ray_tune pid=1371786)[0m [276]	train-mlogloss:1.48230	validation-mlogloss:1.47481
[36m(train_xgb_ray_tune pid=1371796)[0m [348]	train-mlogloss:2.24739	validation-mlogloss:2.23045
[36m(train_xgb_ray_tune pid=1371796)[0m [349]	train-mlogloss:2.24715	validation-mlogloss:2.23023
[36m(train_xgb_ray_tune pid=1371793)[0m [300]	train-mlogloss:1.54652	validation-mlogloss:1.51699
[36m(train_xgb_ray_tune pid=1371748)[0m [299]	train-mlogloss:1.92732	validation-mlogloss:1.90097
[36m(train_xgb_ray_tune pid=1371748)[0m [300]	train-mlogloss:1.92576	validation-mlogloss:1.89938
[36m(train_xgb_ray_tune pid=1371762)[0m [267]	train-mlogloss:1.68986	validation-mlogloss:1.69586
[36m(train_xgb_ray_tune pid=1371762)[0m [268]	train-mlogloss:1.68819	validation-mlogloss:1.69418
[36m(train_xgb_ray_tune pid=1371795)[0m [255]	train-mlogloss:1.37057	validation-mlogloss:1.34685
[36m(train_xgb_ray_tune pid=1371795)[0m [256]	train-mlogloss:1.36998	validation-mlogloss:1.34624
[36m(train_xgb_ray_tune pid=1371782)[0m [237]	train-mlogloss:1.60703	validation-mlogloss:1.62425
[36m(train_xgb_ray_tune pid=1371783)[0m [290]	train-mlogloss:1.55284	validation-mlogloss:1.53217
[36m(train_xgb_ray_tune pid=1371783)[0m [291]	train-mlogloss:1.55161	validation-mlogloss:1.53085
[36m(train_xgb_ray_tune pid=1371794)[0m [322]	train-mlogloss:1.69598	validation-mlogloss:1.66487
[36m(train_xgb_ray_tune pid=1371794)[0m [323]	train-mlogloss:1.69528	validation-mlogloss:1.66416
[36m(train_xgb_ray_tune pid=1371794)[0m [324]	train-mlogloss:1.69449	validation-mlogloss:1.66332
[36m(train_xgb_ray_tune pid=1371755)[0m [287]	train-mlogloss:1.49550	validation-mlogloss:1.48270
[36m(train_xgb_ray_tune pid=1371755)[0m [288]	train-mlogloss:1.49424	validation-mlogloss:1.48130
[36m(train_xgb_ray_tune pid=1371784)[0m [249]	train-mlogloss:1.36910	validation-mlogloss:1.37984
[36m(train_xgb_ray_tune pid=1371784)[0m [250]	train-mlogloss:1.36748	validation-mlogloss:1.37816
[36m(train_xgb_ray_tune pid=1371766)[0m [283]	train-mlogloss:1.70349	validation-mlogloss:1.67123
[36m(train_xgb_ray_tune pid=1371766)[0m [284]	train-mlogloss:1.70208	validation-mlogloss:1.66981
[36m(train_xgb_ray_tune pid=1371766)[0m [285]	train-mlogloss:1.70046	validation-mlogloss:1.66810
[36m(train_xgb_ray_tune pid=1371763)[0m [255]	train-mlogloss:1.56086	validation-mlogloss:1.55099
[36m(train_xgb_ray_tune pid=1371763)[0m [256]	train-mlogloss:1.55926	validation-mlogloss:1.54939
[36m(train_xgb_ray_tune pid=1371754)[0m [258]	train-mlogloss:1.69598	validation-mlogloss:1.69012
[36m(train_xgb_ray_tune pid=1371761)[0m [299]	train-mlogloss:1.97217	validation-mlogloss:1.94469
[36m(train_xgb_ray_tune pid=1371781)[0m [340]	train-mlogloss:1.88902	validation-mlogloss:1.86114
[36m(train_xgb_ray_tune pid=1371786)[0m [277]	train-mlogloss:1.48095	validation-mlogloss:1.47327
[36m(train_xgb_ray_tune pid=1371796)[0m [350]	train-mlogloss:2.24701	validation-mlogloss:2.23008
[36m(train_xgb_ray_tune pid=1371793)[0m [301]	train-mlogloss:1.54536	validation-mlogloss:1.51581
[36m(train_xgb_ray_tune pid=1371782)[0m [238]	train-mlogloss:1.60504	validation-mlogloss:1.62222
[36m(train_xgb_ray_tune pid=1371783)[0m [292]	train-mlogloss:1.55048	validation-mlogloss:1.52964
[36m(train_xgb_ray_tune pid=1371766)[0m [286]	train-mlogloss:1.69896	validation-mlogloss:1.66652
[36m(train_xgb_ray_tune pid=1371763)[0m [257]	train-mlogloss:1.55770	validation-mlogloss:1.54776
[36m(train_xgb_ray_tune pid=1371754)[0m [259]	train-mlogloss:1.69414	validation-mlogloss:1.68821
[36m(train_xgb_ray_tune pid=1371796)[0m [351]	train-mlogloss:2.24677	validation-mlogloss:2.22985
[36m(train_xgb_ray_tune pid=1371761)[0m [300]	train-mlogloss:1.97099	validation-mlogloss:1.94345
[36m(train_xgb_ray_tune pid=1371748)[0m [301]	train-mlogloss:1.92421	validation-mlogloss:1.89778
[36m(train_xgb_ray_tune pid=1371795)[0m [257]	train-mlogloss:1.36946	validation-mlogloss:1.34572
[36m(train_xgb_ray_tune pid=1371754)[0m [260]	train-mlogloss:1.69248	validation-mlogloss:1.68645
[36m(train_xgb_ray_tune pid=1371761)[0m [301]	train-mlogloss:1.97008	validation-mlogloss:1.94245
[36m(train_xgb_ray_tune pid=1371781)[0m [341]	train-mlogloss:1.88902	validation-mlogloss:1.86114
[36m(train_xgb_ray_tune pid=1371781)[0m [342]	train-mlogloss:1.88891	validation-mlogloss:1.86101
[36m(train_xgb_ray_tune pid=1371786)[0m [278]	train-mlogloss:1.47958	validation-mlogloss:1.47184
[36m(train_xgb_ray_tune pid=1371786)[0m [279]	train-mlogloss:1.47824	validation-mlogloss:1.47037
[36m(train_xgb_ray_tune pid=1371796)[0m [352]	train-mlogloss:2.24677	validation-mlogloss:2.22985
[36m(train_xgb_ray_tune pid=1371796)[0m [353]	train-mlogloss:2.24661	validation-mlogloss:2.22971
[36m(train_xgb_ray_tune pid=1371793)[0m [302]	train-mlogloss:1.54411	validation-mlogloss:1.51452
[36m(train_xgb_ray_tune pid=1371793)[0m [303]	train-mlogloss:1.54293	validation-mlogloss:1.51328
[36m(train_xgb_ray_tune pid=1371748)[0m [302]	train-mlogloss:1.92258	validation-mlogloss:1.89608
[36m(train_xgb_ray_tune pid=1371762)[0m [269]	train-mlogloss:1.68642	validation-mlogloss:1.69247
[36m(train_xgb_ray_tune pid=1371762)[0m [270]	train-mlogloss:1.68477	validation-mlogloss:1.69072
[36m(train_xgb_ray_tune pid=1371795)[0m [258]	train-mlogloss:1.36880	validation-mlogloss:1.34506
[36m(train_xgb_ray_tune pid=1371782)[0m [239]	train-mlogloss:1.60304	validation-mlogloss:1.62018
[36m(train_xgb_ray_tune pid=1371782)[0m [240]	train-mlogloss:1.60107	validation-mlogloss:1.61818
[36m(train_xgb_ray_tune pid=1371783)[0m [293]	train-mlogloss:1.54946	validation-mlogloss:1.52850
[36m(train_xgb_ray_tune pid=1371783)[0m [294]	train-mlogloss:1.54834	validation-mlogloss:1.52732
[36m(train_xgb_ray_tune pid=1371794)[0m [325]	train-mlogloss:1.69376	validation-mlogloss:1.66259
[36m(train_xgb_ray_tune pid=1371794)[0m [326]	train-mlogloss:1.69307	validation-mlogloss:1.66184
[36m(train_xgb_ray_tune pid=1371755)[0m [289]	train-mlogloss:1.49293	validation-mlogloss:1.47990
[36m(train_xgb_ray_tune pid=1371755)[0m [290]	train-mlogloss:1.49168	validation-mlogloss:1.47858
[36m(train_xgb_ray_tune pid=1371755)[0m [291]	train-mlogloss:1.49041	validation-mlogloss:1.47726
[36m(train_xgb_ray_tune pid=1371784)[0m [251]	train-mlogloss:1.36591	validation-mlogloss:1.37662
[36m(train_xgb_ray_tune pid=1371784)[0m [252]	train-mlogloss:1.36429	validation-mlogloss:1.37512
[36m(train_xgb_ray_tune pid=1371766)[0m [287]	train-mlogloss:1.69744	validation-mlogloss:1.66491
[36m(train_xgb_ray_tune pid=1371766)[0m [288]	train-mlogloss:1.69599	validation-mlogloss:1.66340
[36m(train_xgb_ray_tune pid=1371763)[0m [258]	train-mlogloss:1.55617	validation-mlogloss:1.54614
[36m(train_xgb_ray_tune pid=1371754)[0m [261]	train-mlogloss:1.69070	validation-mlogloss:1.68456
[36m(train_xgb_ray_tune pid=1371761)[0m [302]	train-mlogloss:1.96912	validation-mlogloss:1.94143
[36m(train_xgb_ray_tune pid=1371781)[0m [343]	train-mlogloss:1.88891	validation-mlogloss:1.86101
[36m(train_xgb_ray_tune pid=1371795)[0m [259]	train-mlogloss:1.36812	validation-mlogloss:1.34434
[36m(train_xgb_ray_tune pid=1371794)[0m [327]	train-mlogloss:1.69235	validation-mlogloss:1.66108
[36m(train_xgb_ray_tune pid=1371766)[0m [289]	train-mlogloss:1.69450	validation-mlogloss:1.66183
[36m(train_xgb_ray_tune pid=1371763)[0m [259]	train-mlogloss:1.55459	validation-mlogloss:1.54450
[36m(train_xgb_ray_tune pid=1371748)[0m [303]	train-mlogloss:1.92102	validation-mlogloss:1.89448
[36m(train_xgb_ray_tune pid=1371796)[0m [354]	train-mlogloss:2.24646	validation-mlogloss:2.22957

Trial status: 16 RUNNING | 4 TERMINATED
Current time: 2025-11-06 14:04:52. Total running time: 30s
Logical resource usage: 16.0/20 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_1d10d    RUNNING                    736             3        0.00672781      0.518944             0.847053   25.8745                   133      17.7035        18.1901              7794                                                     │
│ trial_1d10d    RUNNING                    630             2        0.0096993       0.700232             0.807142   27.2881                   105     149.378        389.531               3899                                                     │
│ trial_1d10d    RUNNING                    617             3        0.0179237       0.533623             0.847934   19.913                    176     148.862         53.1872               479                                                     │
│ trial_1d10d    RUNNING                    631             2        0.0094698       0.843762             0.697157   24.2091                   175      65.1783        15.4702              3650                                                     │
│ trial_1d10d    RUNNING                    319             3        0.0121164       0.672751             0.67354     5.06911                  184       1.7707        10.6008              8252                                                     │
│ trial_1d10d    RUNNING                    741             2        0.0126543       0.793417             0.541353   23.6833                   153     114.485        299.831               1495                                                     │
│ trial_1d10d    RUNNING                    761             2        0.0085859       0.720189             0.81877     5.39026                   53      11.4473         6.57397             9857                                                     │
│ trial_1d10d    RUNNING                    619             2        0.0147093       0.716416             0.75808    11.4587                   112      34.1481       381.763               8829                                                     │
│ trial_1d10d    RUNNING                    392             2        0.00876909      0.636594             0.762604   13.8642                    54      23.4307         6.87095             1078                                                     │
│ trial_1d10d    RUNNING                    370             2        0.0101514       0.636663             0.796814   22.6373                   112      12.6395       809.842               4815                                                     │
│ trial_1d10d    RUNNING                    676             3        0.0184132       0.797429             0.717871   29.3403                   127       9.36209      138.236                874                                                     │
│ trial_1d10d    RUNNING                    731             3        0.00563236      0.532872             0.685933   28.1517                   110       4.74275       10.1884               799                                                     │
│ trial_1d10d    RUNNING                    683             3        0.00674663      0.818934             0.83247    20.9062                   132       4.55489       15.8284              3471                                                     │
│ trial_1d10d    RUNNING                    564             3        0.0100275       0.510695             0.610236   11.4704                   150     238.105         15.4943              8834                                                     │
│ trial_1d10d    RUNNING                    403             3        0.0137126       0.678732             0.592672   26.9875                    68       1.66332      657.617               8773                                                     │
│ trial_1d10d    RUNNING                    281             3        0.0136754       0.770822             0.795709   10.2767                    80      40.9199       343.147               5960                                                     │
│ trial_1d10d    TERMINATED                 216             3        0.0119583       0.849878             0.80138    24.0381                   149     102.201          7.6987              5283        1           24.2759                0.502439  │
│ trial_1d10d    TERMINATED                 495             2        0.00617581      0.771088             0.555695    6.73036                  107     836.851        757.965               3602        1            5.54454               0.0682927 │
│ trial_1d10d    TERMINATED                 374             3        0.00901681      0.533349             0.541881   10.6509                    54     624.245        151.746               1137        1            6.0377                0.0682927 │
│ trial_1d10d    TERMINATED                 249             2        0.0117756       0.569994             0.593681    8.16291                   93     154.54          48.2581              4887        1           24.3102                0.467444  │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1371754)[0m [262]	train-mlogloss:1.68891	validation-mlogloss:1.68271
[36m(train_xgb_ray_tune pid=1371761)[0m [303]	train-mlogloss:1.96807	validation-mlogloss:1.94030
[36m(train_xgb_ray_tune pid=1371761)[0m [304]	train-mlogloss:1.96708	validation-mlogloss:1.93925
[36m(train_xgb_ray_tune pid=1371781)[0m [344]	train-mlogloss:1.88891	validation-mlogloss:1.86101
[36m(train_xgb_ray_tune pid=1371781)[0m [345]	train-mlogloss:1.88878	validation-mlogloss:1.86094
[36m(train_xgb_ray_tune pid=1371781)[0m [346]	train-mlogloss:1.88878	validation-mlogloss:1.86094
[36m(train_xgb_ray_tune pid=1371786)[0m [280]	train-mlogloss:1.47689	validation-mlogloss:1.46905
[36m(train_xgb_ray_tune pid=1371786)[0m [281]	train-mlogloss:1.47551	validation-mlogloss:1.46764
[36m(train_xgb_ray_tune pid=1371796)[0m [355]	train-mlogloss:2.24561	validation-mlogloss:2.22864
[36m(train_xgb_ray_tune pid=1371796)[0m [356]	train-mlogloss:2.24530	validation-mlogloss:2.22833
[36m(train_xgb_ray_tune pid=1371793)[0m [304]	train-mlogloss:1.54168	validation-mlogloss:1.51196
[36m(train_xgb_ray_tune pid=1371793)[0m [305]	train-mlogloss:1.54055	validation-mlogloss:1.51082
[36m(train_xgb_ray_tune pid=1371748)[0m [304]	train-mlogloss:1.91938	validation-mlogloss:1.89279
[36m(train_xgb_ray_tune pid=1371748)[0m [305]	train-mlogloss:1.91780	validation-mlogloss:1.89116
[36m(train_xgb_ray_tune pid=1371762)[0m [271]	train-mlogloss:1.68313	validation-mlogloss:1.68899
[36m(train_xgb_ray_tune pid=1371762)[0m [272]	train-mlogloss:1.68144	validation-mlogloss:1.68732
[36m(train_xgb_ray_tune pid=1371795)[0m [260]	train-mlogloss:1.36749	validation-mlogloss:1.34364
[36m(train_xgb_ray_tune pid=1371795)[0m [261]	train-mlogloss:1.36694	validation-mlogloss:1.34303
[36m(train_xgb_ray_tune pid=1371782)[0m [241]	train-mlogloss:1.59910	validation-mlogloss:1.61619
[36m(train_xgb_ray_tune pid=1371783)[0m [295]	train-mlogloss:1.54732	validation-mlogloss:1.52622
[36m(train_xgb_ray_tune pid=1371783)[0m [296]	train-mlogloss:1.54622	validation-mlogloss:1.52500
[36m(train_xgb_ray_tune pid=1371794)[0m [328]	train-mlogloss:1.69156	validation-mlogloss:1.66023
[36m(train_xgb_ray_tune pid=1371794)[0m [329]	train-mlogloss:1.69075	validation-mlogloss:1.65940
[36m(train_xgb_ray_tune pid=1371755)[0m [292]	train-mlogloss:1.48920	validation-mlogloss:1.47594
[36m(train_xgb_ray_tune pid=1371755)[0m [293]	train-mlogloss:1.48800	validation-mlogloss:1.47465
[36m(train_xgb_ray_tune pid=1371784)[0m [253]	train-mlogloss:1.36276	validation-mlogloss:1.37365
[36m(train_xgb_ray_tune pid=1371784)[0m [254]	train-mlogloss:1.36135	validation-mlogloss:1.37227
[36m(train_xgb_ray_tune pid=1371766)[0m [290]	train-mlogloss:1.69297	validation-mlogloss:1.66016
[36m(train_xgb_ray_tune pid=1371766)[0m [291]	train-mlogloss:1.69155	validation-mlogloss:1.65879
[36m(train_xgb_ray_tune pid=1371763)[0m [260]	train-mlogloss:1.55304	validation-mlogloss:1.54295
[36m(train_xgb_ray_tune pid=1371754)[0m [263]	train-mlogloss:1.68725	validation-mlogloss:1.68101
[36m(train_xgb_ray_tune pid=1371781)[0m [347]	train-mlogloss:1.88878	validation-mlogloss:1.86094
[36m(train_xgb_ray_tune pid=1371748)[0m [306]	train-mlogloss:1.91622	validation-mlogloss:1.88959
[36m(train_xgb_ray_tune pid=1371782)[0m [242]	train-mlogloss:1.59717	validation-mlogloss:1.61424
[36m(train_xgb_ray_tune pid=1371754)[0m [264]	train-mlogloss:1.68551	validation-mlogloss:1.67931
[36m(train_xgb_ray_tune pid=1371754)[0m [265]	train-mlogloss:1.68389	validation-mlogloss:1.67766
[36m(train_xgb_ray_tune pid=1371761)[0m [305]	train-mlogloss:1.96596	validation-mlogloss:1.93805
[36m(train_xgb_ray_tune pid=1371761)[0m [306]	train-mlogloss:1.96501	validation-mlogloss:1.93699
[36m(train_xgb_ray_tune pid=1371781)[0m [348]	train-mlogloss:1.88878	validation-mlogloss:1.86094
[36m(train_xgb_ray_tune pid=1371781)[0m [349]	train-mlogloss:1.88878	validation-mlogloss:1.86094
[36m(train_xgb_ray_tune pid=1371781)[0m [350]	train-mlogloss:1.88878	validation-mlogloss:1.86094
[36m(train_xgb_ray_tune pid=1371781)[0m [351]	train-mlogloss:1.88878	validation-mlogloss:1.86094
[36m(train_xgb_ray_tune pid=1371786)[0m [282]	train-mlogloss:1.47408	validation-mlogloss:1.46613
[36m(train_xgb_ray_tune pid=1371786)[0m [283]	train-mlogloss:1.47275	validation-mlogloss:1.46474
[36m(train_xgb_ray_tune pid=1371796)[0m [357]	train-mlogloss:2.24530	validation-mlogloss:2.22833
[36m(train_xgb_ray_tune pid=1371796)[0m [358]	train-mlogloss:2.24515	validation-mlogloss:2.22819
[36m(train_xgb_ray_tune pid=1371793)[0m [306]	train-mlogloss:1.53945	validation-mlogloss:1.50970
[36m(train_xgb_ray_tune pid=1371793)[0m [307]	train-mlogloss:1.53831	validation-mlogloss:1.50858
[36m(train_xgb_ray_tune pid=1371748)[0m [307]	train-mlogloss:1.91475	validation-mlogloss:1.88809
[36m(train_xgb_ray_tune pid=1371748)[0m [308]	train-mlogloss:1.91322	validation-mlogloss:1.88654
[36m(train_xgb_ray_tune pid=1371762)[0m [273]	train-mlogloss:1.67965	validation-mlogloss:1.68546
[36m(train_xgb_ray_tune pid=1371762)[0m [274]	train-mlogloss:1.67794	validation-mlogloss:1.68371
[36m(train_xgb_ray_tune pid=1371795)[0m [262]	train-mlogloss:1.36639	validation-mlogloss:1.34248
[36m(train_xgb_ray_tune pid=1371795)[0m [263]	train-mlogloss:1.36574	validation-mlogloss:1.34180
[36m(train_xgb_ray_tune pid=1371782)[0m [243]	train-mlogloss:1.59515	validation-mlogloss:1.61223
[36m(train_xgb_ray_tune pid=1371783)[0m [297]	train-mlogloss:1.54516	validation-mlogloss:1.52388
[36m(train_xgb_ray_tune pid=1371783)[0m [298]	train-mlogloss:1.54401	validation-mlogloss:1.52269
[36m(train_xgb_ray_tune pid=1371794)[0m [330]	train-mlogloss:1.69009	validation-mlogloss:1.65868
[36m(train_xgb_ray_tune pid=1371794)[0m [331]	train-mlogloss:1.68927	validation-mlogloss:1.65781
[36m(train_xgb_ray_tune pid=1371794)[0m [332]	train-mlogloss:1.68867	validation-mlogloss:1.65719
[36m(train_xgb_ray_tune pid=1371755)[0m [294]	train-mlogloss:1.48677	validation-mlogloss:1.47336
[36m(train_xgb_ray_tune pid=1371755)[0m [295]	train-mlogloss:1.48558	validation-mlogloss:1.47200
[36m(train_xgb_ray_tune pid=1371784)[0m [255]	train-mlogloss:1.35988	validation-mlogloss:1.37077
[36m(train_xgb_ray_tune pid=1371766)[0m [292]	train-mlogloss:1.69006	validation-mlogloss:1.65732
[36m(train_xgb_ray_tune pid=1371766)[0m [293]	train-mlogloss:1.68860	validation-mlogloss:1.65571
[36m(train_xgb_ray_tune pid=1371763)[0m [261]	train-mlogloss:1.55145	validation-mlogloss:1.54133
[36m(train_xgb_ray_tune pid=1371763)[0m [262]	train-mlogloss:1.54999	validation-mlogloss:1.53988
[36m(train_xgb_ray_tune pid=1371754)[0m [266]	train-mlogloss:1.68221	validation-mlogloss:1.67588
[36m(train_xgb_ray_tune pid=1371796)[0m [359]	train-mlogloss:2.24468	validation-mlogloss:2.22770
[36m(train_xgb_ray_tune pid=1371784)[0m [256]	train-mlogloss:1.35838	validation-mlogloss:1.36930
[36m(train_xgb_ray_tune pid=1371781)[0m [352]	train-mlogloss:1.88878	validation-mlogloss:1.86094
[36m(train_xgb_ray_tune pid=1371793)[0m [308]	train-mlogloss:1.53724	validation-mlogloss:1.50755
[36m(train_xgb_ray_tune pid=1371795)[0m [264]	train-mlogloss:1.36534	validation-mlogloss:1.34139
[36m(train_xgb_ray_tune pid=1371761)[0m [307]	train-mlogloss:1.96390	validation-mlogloss:1.93581
[36m(train_xgb_ray_tune pid=1371786)[0m [284]	train-mlogloss:1.47139	validation-mlogloss:1.46331
[36m(train_xgb_ray_tune pid=1371796)[0m [360]	train-mlogloss:2.24460	validation-mlogloss:2.22761
[36m(train_xgb_ray_tune pid=1371762)[0m [275]	train-mlogloss:1.67629	validation-mlogloss:1.68201
[36m(train_xgb_ray_tune pid=1371782)[0m [244]	train-mlogloss:1.59317	validation-mlogloss:1.61024
[36m(train_xgb_ray_tune pid=1371783)[0m [299]	train-mlogloss:1.54291	validation-mlogloss:1.52151
[36m(train_xgb_ray_tune pid=1371766)[0m [294]	train-mlogloss:1.68729	validation-mlogloss:1.65438
[36m(train_xgb_ray_tune pid=1371763)[0m [263]	train-mlogloss:1.54847	validation-mlogloss:1.53832
[36m(train_xgb_ray_tune pid=1371748)[0m [309]	train-mlogloss:1.91178	validation-mlogloss:1.88504
[36m(train_xgb_ray_tune pid=1371754)[0m [267]	train-mlogloss:1.68050	validation-mlogloss:1.67410
[36m(train_xgb_ray_tune pid=1371754)[0m [268]	train-mlogloss:1.67885	validation-mlogloss:1.67243
[36m(train_xgb_ray_tune pid=1371761)[0m [308]	train-mlogloss:1.96287	validation-mlogloss:1.93472
[36m(train_xgb_ray_tune pid=1371761)[0m [309]	train-mlogloss:1.96182	validation-mlogloss:1.93359
[36m(train_xgb_ray_tune pid=1371781)[0m [353]	train-mlogloss:1.88868	validation-mlogloss:1.86081
[36m(train_xgb_ray_tune pid=1371781)[0m [354]	train-mlogloss:1.88868	validation-mlogloss:1.86081
[36m(train_xgb_ray_tune pid=1371786)[0m [285]	train-mlogloss:1.47007	validation-mlogloss:1.46182
[36m(train_xgb_ray_tune pid=1371796)[0m [361]	train-mlogloss:2.24460	validation-mlogloss:2.22761
[36m(train_xgb_ray_tune pid=1371796)[0m [362]	train-mlogloss:2.24453	validation-mlogloss:2.22754
[36m(train_xgb_ray_tune pid=1371793)[0m [309]	train-mlogloss:1.53610	validation-mlogloss:1.50640
[36m(train_xgb_ray_tune pid=1371793)[0m [310]	train-mlogloss:1.53495	validation-mlogloss:1.50526
[36m(train_xgb_ray_tune pid=1371748)[0m [310]	train-mlogloss:1.91024	validation-mlogloss:1.88343
[36m(train_xgb_ray_tune pid=1371748)[0m [311]	train-mlogloss:1.90874	validation-mlogloss:1.88192
[36m(train_xgb_ray_tune pid=1371762)[0m [276]	train-mlogloss:1.67462	validation-mlogloss:1.68025
[36m(train_xgb_ray_tune pid=1371795)[0m [265]	train-mlogloss:1.36473	validation-mlogloss:1.34080
[36m(train_xgb_ray_tune pid=1371795)[0m [266]	train-mlogloss:1.36409	validation-mlogloss:1.34014
[36m(train_xgb_ray_tune pid=1371782)[0m [245]	train-mlogloss:1.59125	validation-mlogloss:1.60825
[36m(train_xgb_ray_tune pid=1371783)[0m [300]	train-mlogloss:1.54190	validation-mlogloss:1.52042
[36m(train_xgb_ray_tune pid=1371794)[0m [333]	train-mlogloss:1.68806	validation-mlogloss:1.65655
[36m(train_xgb_ray_tune pid=1371794)[0m [334]	train-mlogloss:1.68732	validation-mlogloss:1.65572
[36m(train_xgb_ray_tune pid=1371755)[0m [296]	train-mlogloss:1.48438	validation-mlogloss:1.47073
[36m(train_xgb_ray_tune pid=1371755)[0m [297]	train-mlogloss:1.48316	validation-mlogloss:1.46943
[36m(train_xgb_ray_tune pid=1371784)[0m [257]	train-mlogloss:1.35694	validation-mlogloss:1.36803
[36m(train_xgb_ray_tune pid=1371766)[0m [295]	train-mlogloss:1.68579	validation-mlogloss:1.65284
[36m(train_xgb_ray_tune pid=1371763)[0m [264]	train-mlogloss:1.54695	validation-mlogloss:1.53683
[36m(train_xgb_ray_tune pid=1371754)[0m [269]	train-mlogloss:1.67722	validation-mlogloss:1.67065
[36m(train_xgb_ray_tune pid=1371781)[0m [355]	train-mlogloss:1.88868	validation-mlogloss:1.86081
[36m(train_xgb_ray_tune pid=1371786)[0m [286]	train-mlogloss:1.46868	validation-mlogloss:1.46044
[36m(train_xgb_ray_tune pid=1371748)[0m [312]	train-mlogloss:1.90732	validation-mlogloss:1.88054
[36m(train_xgb_ray_tune pid=1371783)[0m [301]	train-mlogloss:1.54080	validation-mlogloss:1.51919
[36m(train_xgb_ray_tune pid=1371794)[0m [335]	train-mlogloss:1.68666	validation-mlogloss:1.65504
[36m(train_xgb_ray_tune pid=1371784)[0m [258]	train-mlogloss:1.35538	validation-mlogloss:1.36662
[36m(train_xgb_ray_tune pid=1371766)[0m [296]	train-mlogloss:1.68439	validation-mlogloss:1.65140
[36m(train_xgb_ray_tune pid=1371763)[0m [265]	train-mlogloss:1.54558	validation-mlogloss:1.53546
[36m(train_xgb_ray_tune pid=1371796)[0m [363]	train-mlogloss:2.24446	validation-mlogloss:2.22746
[36m(train_xgb_ray_tune pid=1371762)[0m [277]	train-mlogloss:1.67289	validation-mlogloss:1.67849
[36m(train_xgb_ray_tune pid=1371782)[0m [246]	train-mlogloss:1.58935	validation-mlogloss:1.60638
[36m(train_xgb_ray_tune pid=1371755)[0m [298]	train-mlogloss:1.48193	validation-mlogloss:1.46806
[36m(train_xgb_ray_tune pid=1371754)[0m [270]	train-mlogloss:1.67563	validation-mlogloss:1.66896
[36m(train_xgb_ray_tune pid=1371761)[0m [310]	train-mlogloss:1.96087	validation-mlogloss:1.93257
[36m(train_xgb_ray_tune pid=1371748)[0m [313]	train-mlogloss:1.90594	validation-mlogloss:1.87905
[36m(train_xgb_ray_tune pid=1371754)[0m [271]	train-mlogloss:1.67404	validation-mlogloss:1.66731
[36m(train_xgb_ray_tune pid=1371761)[0m [311]	train-mlogloss:1.95997	validation-mlogloss:1.93162
[36m(train_xgb_ray_tune pid=1371781)[0m [356]	train-mlogloss:1.88824	validation-mlogloss:1.86035
[36m(train_xgb_ray_tune pid=1371781)[0m [357]	train-mlogloss:1.88813	validation-mlogloss:1.86027
[36m(train_xgb_ray_tune pid=1371781)[0m [358]	train-mlogloss:1.88813	validation-mlogloss:1.86027
[36m(train_xgb_ray_tune pid=1371786)[0m [287]	train-mlogloss:1.46731	validation-mlogloss:1.45907
[36m(train_xgb_ray_tune pid=1371786)[0m [288]	train-mlogloss:1.46595	validation-mlogloss:1.45771
[36m(train_xgb_ray_tune pid=1371796)[0m [364]	train-mlogloss:2.24437	validation-mlogloss:2.22740
[36m(train_xgb_ray_tune pid=1371796)[0m [365]	train-mlogloss:2.24430	validation-mlogloss:2.22735
[36m(train_xgb_ray_tune pid=1371793)[0m [311]	train-mlogloss:1.53387	validation-mlogloss:1.50417
[36m(train_xgb_ray_tune pid=1371793)[0m [312]	train-mlogloss:1.53281	validation-mlogloss:1.50307
[36m(train_xgb_ray_tune pid=1371748)[0m [314]	train-mlogloss:1.90450	validation-mlogloss:1.87762
[36m(train_xgb_ray_tune pid=1371748)[0m [315]	train-mlogloss:1.90305	validation-mlogloss:1.87612
[36m(train_xgb_ray_tune pid=1371762)[0m [278]	train-mlogloss:1.67122	validation-mlogloss:1.67679
[36m(train_xgb_ray_tune pid=1371795)[0m [267]	train-mlogloss:1.36344	validation-mlogloss:1.33943
[36m(train_xgb_ray_tune pid=1371795)[0m [268]	train-mlogloss:1.36289	validation-mlogloss:1.33879
[36m(train_xgb_ray_tune pid=1371782)[0m [247]	train-mlogloss:1.58739	validation-mlogloss:1.60446
[36m(train_xgb_ray_tune pid=1371783)[0m [302]	train-mlogloss:1.53974	validation-mlogloss:1.51803
[36m(train_xgb_ray_tune pid=1371783)[0m [303]	train-mlogloss:1.53870	validation-mlogloss:1.51694
[36m(train_xgb_ray_tune pid=1371794)[0m [336]	train-mlogloss:1.68586	validation-mlogloss:1.65415
[36m(train_xgb_ray_tune pid=1371794)[0m [337]	train-mlogloss:1.68520	validation-mlogloss:1.65343
[36m(train_xgb_ray_tune pid=1371755)[0m [299]	train-mlogloss:1.48082	validation-mlogloss:1.46682
[36m(train_xgb_ray_tune pid=1371784)[0m [259]	train-mlogloss:1.35401	validation-mlogloss:1.36528
[36m(train_xgb_ray_tune pid=1371784)[0m [260]	train-mlogloss:1.35255	validation-mlogloss:1.36391
[36m(train_xgb_ray_tune pid=1371766)[0m [297]	train-mlogloss:1.68298	validation-mlogloss:1.64999
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[36m(train_xgb_ray_tune pid=1371781)[0m [386]	train-mlogloss:1.88657	validation-mlogloss:1.85857
[36m(train_xgb_ray_tune pid=1371748)[0m [335]	train-mlogloss:1.87414	validation-mlogloss:1.84623
[36m(train_xgb_ray_tune pid=1371795)[0m [290]	train-mlogloss:1.35324	validation-mlogloss:1.32885
[36m(train_xgb_ray_tune pid=1371755)[0m [318]	train-mlogloss:1.45936	validation-mlogloss:1.44400
[36m(train_xgb_ray_tune pid=1371761)[0m [337]	train-mlogloss:1.93509	validation-mlogloss:1.90516
[36m(train_xgb_ray_tune pid=1371786)[0m [307]	train-mlogloss:1.44177	validation-mlogloss:1.43233
[36m(train_xgb_ray_tune pid=1371796)[0m [393]	train-mlogloss:2.24064	validation-mlogloss:2.22357
[36m(train_xgb_ray_tune pid=1371783)[0m [325]	train-mlogloss:1.51744	validation-mlogloss:1.49401
[36m(train_xgb_ray_tune pid=1371794)[0m [366]	train-mlogloss:1.66850	validation-mlogloss:1.63583
[36m(train_xgb_ray_tune pid=1371784)[0m [278]	train-mlogloss:1.32797	validation-mlogloss:1.34065
[36m(train_xgb_ray_tune pid=1371754)[0m [294]	train-mlogloss:1.63858	validation-mlogloss:1.63032
[36m(train_xgb_ray_tune pid=1371793)[0m [333]	train-mlogloss:1.51052	validation-mlogloss:1.47987
[36m(train_xgb_ray_tune pid=1371781)[0m [387]	train-mlogloss:1.88657	validation-mlogloss:1.85857
[36m(train_xgb_ray_tune pid=1371766)[0m [317]	train-mlogloss:1.65642	validation-mlogloss:1.62190
[36m(train_xgb_ray_tune pid=1371795)[0m [291]	train-mlogloss:1.35296	validation-mlogloss:1.32857
[36m(train_xgb_ray_tune pid=1371754)[0m [295]	train-mlogloss:1.63716	validation-mlogloss:1.62885
[36m(train_xgb_ray_tune pid=1371761)[0m [338]	train-mlogloss:1.93414	validation-mlogloss:1.90413
[36m(train_xgb_ray_tune pid=1371761)[0m [339]	train-mlogloss:1.93321	validation-mlogloss:1.90315
[36m(train_xgb_ray_tune pid=1371781)[0m [388]	train-mlogloss:1.88647	validation-mlogloss:1.85848
[36m(train_xgb_ray_tune pid=1371781)[0m [389]	train-mlogloss:1.88636	validation-mlogloss:1.85836
[36m(train_xgb_ray_tune pid=1371781)[0m [390]	train-mlogloss:1.88636	validation-mlogloss:1.85836
[36m(train_xgb_ray_tune pid=1371786)[0m [308]	train-mlogloss:1.44057	validation-mlogloss:1.43103
[36m(train_xgb_ray_tune pid=1371786)[0m [309]	train-mlogloss:1.43931	validation-mlogloss:1.42977
[36m(train_xgb_ray_tune pid=1371786)[0m [310]	train-mlogloss:1.43809	validation-mlogloss:1.42850
[36m(train_xgb_ray_tune pid=1371796)[0m [394]	train-mlogloss:2.24057	validation-mlogloss:2.22351
[36m(train_xgb_ray_tune pid=1371796)[0m [395]	train-mlogloss:2.24036	validation-mlogloss:2.22327
[36m(train_xgb_ray_tune pid=1371793)[0m [334]	train-mlogloss:1.50945	validation-mlogloss:1.47875
[36m(train_xgb_ray_tune pid=1371793)[0m [335]	train-mlogloss:1.50843	validation-mlogloss:1.47767
[36m(train_xgb_ray_tune pid=1371793)[0m [336]	train-mlogloss:1.50731	validation-mlogloss:1.47649
[36m(train_xgb_ray_tune pid=1371748)[0m [336]	train-mlogloss:1.87272	validation-mlogloss:1.84481
[36m(train_xgb_ray_tune pid=1371748)[0m [337]	train-mlogloss:1.87134	validation-mlogloss:1.84335
[36m(train_xgb_ray_tune pid=1371762)[0m [299]	train-mlogloss:1.63755	validation-mlogloss:1.64153
[36m(train_xgb_ray_tune pid=1371762)[0m [300]	train-mlogloss:1.63606	validation-mlogloss:1.63999
[36m(train_xgb_ray_tune pid=1371795)[0m [292]	train-mlogloss:1.35271	validation-mlogloss:1.32833
[36m(train_xgb_ray_tune pid=1371795)[0m [293]	train-mlogloss:1.35230	validation-mlogloss:1.32787
[36m(train_xgb_ray_tune pid=1371782)[0m [265]	train-mlogloss:1.55481	validation-mlogloss:1.57140
[36m(train_xgb_ray_tune pid=1371782)[0m [266]	train-mlogloss:1.55308	validation-mlogloss:1.56967
[36m(train_xgb_ray_tune pid=1371783)[0m [326]	train-mlogloss:1.51653	validation-mlogloss:1.49305
[36m(train_xgb_ray_tune pid=1371783)[0m [327]	train-mlogloss:1.51565	validation-mlogloss:1.49211
[36m(train_xgb_ray_tune pid=1371794)[0m [367]	train-mlogloss:1.66798	validation-mlogloss:1.63531
[36m(train_xgb_ray_tune pid=1371794)[0m [368]	train-mlogloss:1.66757	validation-mlogloss:1.63486
[36m(train_xgb_ray_tune pid=1371755)[0m [319]	train-mlogloss:1.45826	validation-mlogloss:1.44275
[36m(train_xgb_ray_tune pid=1371755)[0m [320]	train-mlogloss:1.45722	validation-mlogloss:1.44169
[36m(train_xgb_ray_tune pid=1371784)[0m [279]	train-mlogloss:1.32671	validation-mlogloss:1.33953
[36m(train_xgb_ray_tune pid=1371766)[0m [318]	train-mlogloss:1.65509	validation-mlogloss:1.62048
[36m(train_xgb_ray_tune pid=1371761)[0m [340]	train-mlogloss:1.93243	validation-mlogloss:1.90236
[36m(train_xgb_ray_tune pid=1371781)[0m [391]	train-mlogloss:1.88603	validation-mlogloss:1.85797
[36m(train_xgb_ray_tune pid=1371796)[0m [396]	train-mlogloss:2.24022	validation-mlogloss:2.22315
[36m(train_xgb_ray_tune pid=1371784)[0m [280]	train-mlogloss:1.32540	validation-mlogloss:1.33833
[36m(train_xgb_ray_tune pid=1371766)[0m [319]	train-mlogloss:1.65380	validation-mlogloss:1.61908
[36m(train_xgb_ray_tune pid=1371754)[0m [296]	train-mlogloss:1.63566	validation-mlogloss:1.62732
[36m(train_xgb_ray_tune pid=1371786)[0m [311]	train-mlogloss:1.43690	validation-mlogloss:1.42720
[36m(train_xgb_ray_tune pid=1371748)[0m [338]	train-mlogloss:1.86987	validation-mlogloss:1.84185
[36m(train_xgb_ray_tune pid=1371795)[0m [294]	train-mlogloss:1.35200	validation-mlogloss:1.32761
[36m(train_xgb_ray_tune pid=1371794)[0m [369]	train-mlogloss:1.66716	validation-mlogloss:1.63445
[36m(train_xgb_ray_tune pid=1371761)[0m [341]	train-mlogloss:1.93153	validation-mlogloss:1.90139
[36m(train_xgb_ray_tune pid=1371781)[0m [392]	train-mlogloss:1.88593	validation-mlogloss:1.85785
[36m(train_xgb_ray_tune pid=1371793)[0m [337]	train-mlogloss:1.50633	validation-mlogloss:1.47547
[36m(train_xgb_ray_tune pid=1371762)[0m [301]	train-mlogloss:1.63450	validation-mlogloss:1.63837
[36m(train_xgb_ray_tune pid=1371783)[0m [328]	train-mlogloss:1.51485	validation-mlogloss:1.49123
[36m(train_xgb_ray_tune pid=1371755)[0m [321]	train-mlogloss:1.45620	validation-mlogloss:1.44053
[36m(train_xgb_ray_tune pid=1371796)[0m [397]	train-mlogloss:2.24008	validation-mlogloss:2.22300
[36m(train_xgb_ray_tune pid=1371782)[0m [267]	train-mlogloss:1.55134	validation-mlogloss:1.56789
[36m(train_xgb_ray_tune pid=1371754)[0m [297]	train-mlogloss:1.63429	validation-mlogloss:1.62584
[36m(train_xgb_ray_tune pid=1371761)[0m [342]	train-mlogloss:1.93069	validation-mlogloss:1.90052
[36m(train_xgb_ray_tune pid=1371761)[0m [343]	train-mlogloss:1.92995	validation-mlogloss:1.89972
[36m(train_xgb_ray_tune pid=1371761)[0m [344]	train-mlogloss:1.92903	validation-mlogloss:1.89876
[36m(train_xgb_ray_tune pid=1371781)[0m [393]	train-mlogloss:1.88593	validation-mlogloss:1.85785
[36m(train_xgb_ray_tune pid=1371781)[0m [394]	train-mlogloss:1.88593	validation-mlogloss:1.85785
[36m(train_xgb_ray_tune pid=1371786)[0m [312]	train-mlogloss:1.43572	validation-mlogloss:1.42607
[36m(train_xgb_ray_tune pid=1371786)[0m [313]	train-mlogloss:1.43456	validation-mlogloss:1.42481
[36m(train_xgb_ray_tune pid=1371786)[0m [314]	train-mlogloss:1.43341	validation-mlogloss:1.42369
[36m(train_xgb_ray_tune pid=1371796)[0m [398]	train-mlogloss:2.24001	validation-mlogloss:2.22293
[36m(train_xgb_ray_tune pid=1371796)[0m [399]	train-mlogloss:2.23994	validation-mlogloss:2.22284
[36m(train_xgb_ray_tune pid=1371793)[0m [338]	train-mlogloss:1.50535	validation-mlogloss:1.47448
[36m(train_xgb_ray_tune pid=1371793)[0m [339]	train-mlogloss:1.50436	validation-mlogloss:1.47342
[36m(train_xgb_ray_tune pid=1371748)[0m [339]	train-mlogloss:1.86852	validation-mlogloss:1.84043
[36m(train_xgb_ray_tune pid=1371748)[0m [340]	train-mlogloss:1.86713	validation-mlogloss:1.83901
[36m(train_xgb_ray_tune pid=1371762)[0m [302]	train-mlogloss:1.63296	validation-mlogloss:1.63670
[36m(train_xgb_ray_tune pid=1371795)[0m [295]	train-mlogloss:1.35168	validation-mlogloss:1.32735
[36m(train_xgb_ray_tune pid=1371795)[0m [296]	train-mlogloss:1.35137	validation-mlogloss:1.32699
[36m(train_xgb_ray_tune pid=1371782)[0m [268]	train-mlogloss:1.54968	validation-mlogloss:1.56619
[36m(train_xgb_ray_tune pid=1371782)[0m [269]	train-mlogloss:1.54802	validation-mlogloss:1.56447
[36m(train_xgb_ray_tune pid=1371783)[0m [329]	train-mlogloss:1.51404	validation-mlogloss:1.49033
[36m(train_xgb_ray_tune pid=1371783)[0m [330]	train-mlogloss:1.51325	validation-mlogloss:1.48946
[36m(train_xgb_ray_tune pid=1371794)[0m [370]	train-mlogloss:1.66683	validation-mlogloss:1.63415
[36m(train_xgb_ray_tune pid=1371794)[0m [371]	train-mlogloss:1.66645	validation-mlogloss:1.63379
[36m(train_xgb_ray_tune pid=1371755)[0m [322]	train-mlogloss:1.45510	validation-mlogloss:1.43933
[36m(train_xgb_ray_tune pid=1371784)[0m [281]	train-mlogloss:1.32411	validation-mlogloss:1.33714
[36m(train_xgb_ray_tune pid=1371766)[0m [320]	train-mlogloss:1.65248	validation-mlogloss:1.61769
[36m(train_xgb_ray_tune pid=1371766)[0m [321]	train-mlogloss:1.65119	validation-mlogloss:1.61634
[36m(train_xgb_ray_tune pid=1371754)[0m [298]	train-mlogloss:1.63291	validation-mlogloss:1.62442
[36m(train_xgb_ray_tune pid=1371784)[0m [282]	train-mlogloss:1.32283	validation-mlogloss:1.33593
[36m(train_xgb_ray_tune pid=1371761)[0m [345]	train-mlogloss:1.92811	validation-mlogloss:1.89777
[36m(train_xgb_ray_tune pid=1371795)[0m [297]	train-mlogloss:1.35105	validation-mlogloss:1.32667
[36m(train_xgb_ray_tune pid=1371794)[0m [372]	train-mlogloss:1.66606	validation-mlogloss:1.63344
[36m(train_xgb_ray_tune pid=1371755)[0m [323]	train-mlogloss:1.45406	validation-mlogloss:1.43823
[36m(train_xgb_ray_tune pid=1371781)[0m [395]	train-mlogloss:1.88573	validation-mlogloss:1.85760
[36m(train_xgb_ray_tune pid=1371793)[0m [340]	train-mlogloss:1.50339	validation-mlogloss:1.47245
[36m(train_xgb_ray_tune pid=1371762)[0m [303]	train-mlogloss:1.63139	validation-mlogloss:1.63508
[36m(train_xgb_ray_tune pid=1371783)[0m [331]	train-mlogloss:1.51249	validation-mlogloss:1.48868
[36m(train_xgb_ray_tune pid=1371754)[0m [299]	train-mlogloss:1.63143	validation-mlogloss:1.62290
[36m(train_xgb_ray_tune pid=1371761)[0m [346]	train-mlogloss:1.92732	validation-mlogloss:1.89696
[36m(train_xgb_ray_tune pid=1371761)[0m [347]	train-mlogloss:1.92655	validation-mlogloss:1.89614
[36m(train_xgb_ray_tune pid=1371761)[0m [348]	train-mlogloss:1.92566	validation-mlogloss:1.89517
[36m(train_xgb_ray_tune pid=1371781)[0m [396]	train-mlogloss:1.88549	validation-mlogloss:1.85739
[36m(train_xgb_ray_tune pid=1371781)[0m [397]	train-mlogloss:1.88549	validation-mlogloss:1.85739
[36m(train_xgb_ray_tune pid=1371786)[0m [315]	train-mlogloss:1.43225	validation-mlogloss:1.42251
[36m(train_xgb_ray_tune pid=1371786)[0m [316]	train-mlogloss:1.43116	validation-mlogloss:1.42142
[36m(train_xgb_ray_tune pid=1371786)[0m [317]	train-mlogloss:1.43001	validation-mlogloss:1.42031
[36m(train_xgb_ray_tune pid=1371796)[0m [400]	train-mlogloss:2.23979	validation-mlogloss:2.22269
[36m(train_xgb_ray_tune pid=1371796)[0m [401]	train-mlogloss:2.23965	validation-mlogloss:2.22254
[36m(train_xgb_ray_tune pid=1371793)[0m [341]	train-mlogloss:1.50239	validation-mlogloss:1.47143
[36m(train_xgb_ray_tune pid=1371748)[0m [341]	train-mlogloss:1.86578	validation-mlogloss:1.83756
[36m(train_xgb_ray_tune pid=1371748)[0m [342]	train-mlogloss:1.86446	validation-mlogloss:1.83623
[36m(train_xgb_ray_tune pid=1371762)[0m [304]	train-mlogloss:1.62990	validation-mlogloss:1.63352
[36m(train_xgb_ray_tune pid=1371795)[0m [298]	train-mlogloss:1.35081	validation-mlogloss:1.32637
[36m(train_xgb_ray_tune pid=1371795)[0m [299]	train-mlogloss:1.35058	validation-mlogloss:1.32617
[36m(train_xgb_ray_tune pid=1371782)[0m [270]	train-mlogloss:1.54638	validation-mlogloss:1.56274
[36m(train_xgb_ray_tune pid=1371782)[0m [271]	train-mlogloss:1.54468	validation-mlogloss:1.56102
[36m(train_xgb_ray_tune pid=1371783)[0m [332]	train-mlogloss:1.51163	validation-mlogloss:1.48778
[36m(train_xgb_ray_tune pid=1371783)[0m [333]	train-mlogloss:1.51088	validation-mlogloss:1.48696
[36m(train_xgb_ray_tune pid=1371794)[0m [373]	train-mlogloss:1.66551	validation-mlogloss:1.63285
[36m(train_xgb_ray_tune pid=1371794)[0m [374]	train-mlogloss:1.66524	validation-mlogloss:1.63256
[36m(train_xgb_ray_tune pid=1371755)[0m [324]	train-mlogloss:1.45303	validation-mlogloss:1.43714
[36m(train_xgb_ray_tune pid=1371784)[0m [283]	train-mlogloss:1.32160	validation-mlogloss:1.33479
[36m(train_xgb_ray_tune pid=1371766)[0m [322]	train-mlogloss:1.64995	validation-mlogloss:1.61494
[36m(train_xgb_ray_tune pid=1371782)[0m [272]	train-mlogloss:1.54301	validation-mlogloss:1.55927
[36m(train_xgb_ray_tune pid=1371783)[0m [334]	train-mlogloss:1.51003	validation-mlogloss:1.48601
[36m(train_xgb_ray_tune pid=1371766)[0m [323]	train-mlogloss:1.64873	validation-mlogloss:1.61370
[36m(train_xgb_ray_tune pid=1371761)[0m [349]	train-mlogloss:1.92484	validation-mlogloss:1.89429
[36m(train_xgb_ray_tune pid=1371796)[0m [402]	train-mlogloss:2.23944	validation-mlogloss:2.22232
[36m(train_xgb_ray_tune pid=1371755)[0m [325]	train-mlogloss:1.45205	validation-mlogloss:1.43612
[36m(train_xgb_ray_tune pid=1371754)[0m [300]	train-mlogloss:1.63004	validation-mlogloss:1.62138
[36m(train_xgb_ray_tune pid=1371793)[0m [342]	train-mlogloss:1.50150	validation-mlogloss:1.47058
[36m(train_xgb_ray_tune pid=1371784)[0m [284]	train-mlogloss:1.32046	validation-mlogloss:1.33367

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:04:55. Total running time: 32s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             29.6988 │
│ time_total_s                 29.6988 │
│ training_iteration                 1 │
│ validation_accuracy          0.52768 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:04:55. Total running time: 32s
[36m(train_xgb_ray_tune pid=1371754)[0m [301]	train-mlogloss:1.62866	validation-mlogloss:1.61993
[36m(train_xgb_ray_tune pid=1371761)[0m [350]	train-mlogloss:1.92396	validation-mlogloss:1.89332
[36m(train_xgb_ray_tune pid=1371761)[0m [351]	train-mlogloss:1.92312	validation-mlogloss:1.89242
[36m(train_xgb_ray_tune pid=1371761)[0m [352]	train-mlogloss:1.92235	validation-mlogloss:1.89160
[36m(train_xgb_ray_tune pid=1371781)[0m [398]	train-mlogloss:1.88549	validation-mlogloss:1.85739
[36m(train_xgb_ray_tune pid=1371781)[0m [399]	train-mlogloss:1.88549	validation-mlogloss:1.85739
[36m(train_xgb_ray_tune pid=1371781)[0m [400]	train-mlogloss:1.88549	validation-mlogloss:1.85739
[36m(train_xgb_ray_tune pid=1371786)[0m [318]	train-mlogloss:1.42886	validation-mlogloss:1.41913
[36m(train_xgb_ray_tune pid=1371786)[0m [319]	train-mlogloss:1.42774	validation-mlogloss:1.41806
[36m(train_xgb_ray_tune pid=1371786)[0m [320]	train-mlogloss:1.42660	validation-mlogloss:1.41688
[36m(train_xgb_ray_tune pid=1371796)[0m [403]	train-mlogloss:2.23929	validation-mlogloss:2.22217
[36m(train_xgb_ray_tune pid=1371796)[0m [404]	train-mlogloss:2.23919	validation-mlogloss:2.22206
[36m(train_xgb_ray_tune pid=1371793)[0m [343]	train-mlogloss:1.50061	validation-mlogloss:1.46959
[36m(train_xgb_ray_tune pid=1371748)[0m [343]	train-mlogloss:1.86318	validation-mlogloss:1.83492
[36m(train_xgb_ray_tune pid=1371748)[0m [344]	train-mlogloss:1.86181	validation-mlogloss:1.83349
[36m(train_xgb_ray_tune pid=1371762)[0m [305]	train-mlogloss:1.62845	validation-mlogloss:1.63202
[36m(train_xgb_ray_tune pid=1371762)[0m [306]	train-mlogloss:1.62690	validation-mlogloss:1.63044
[36m(train_xgb_ray_tune pid=1371795)[0m [300]	train-mlogloss:1.35028	validation-mlogloss:1.32581
[36m(train_xgb_ray_tune pid=1371795)[0m [301]	train-mlogloss:1.34991	validation-mlogloss:1.32540
[36m(train_xgb_ray_tune pid=1371795)[0m [302]	train-mlogloss:1.34965	validation-mlogloss:1.32510
[36m(train_xgb_ray_tune pid=1371782)[0m [273]	train-mlogloss:1.54135	validation-mlogloss:1.55760
[36m(train_xgb_ray_tune pid=1371782)[0m [274]	train-mlogloss:1.53969	validation-mlogloss:1.55592
[36m(train_xgb_ray_tune pid=1371783)[0m [335]	train-mlogloss:1.50924	validation-mlogloss:1.48517
[36m(train_xgb_ray_tune pid=1371783)[0m [336]	train-mlogloss:1.50846	validation-mlogloss:1.48434
[36m(train_xgb_ray_tune pid=1371783)[0m [337]	train-mlogloss:1.50770	validation-mlogloss:1.48349
[36m(train_xgb_ray_tune pid=1371794)[0m [375]	train-mlogloss:1.66488	validation-mlogloss:1.63217
[36m(train_xgb_ray_tune pid=1371794)[0m [376]	train-mlogloss:1.66453	validation-mlogloss:1.63181
[36m(train_xgb_ray_tune pid=1371755)[0m [326]	train-mlogloss:1.45099	validation-mlogloss:1.43497
[36m(train_xgb_ray_tune pid=1371784)[0m [285]	train-mlogloss:1.31920	validation-mlogloss:1.33246
[36m(train_xgb_ray_tune pid=1371766)[0m [324]	train-mlogloss:1.64744	validation-mlogloss:1.61232
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[36m(train_xgb_ray_tune pid=1371763)[0m   _log_deprecation_warning([32m [repeated 2x across cluster][0m
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[36m(train_xgb_ray_tune pid=1371755)[0m [371]	train-mlogloss:1.40968	validation-mlogloss:1.39125
[36m(train_xgb_ray_tune pid=1371784)[0m [316]	train-mlogloss:1.28550	validation-mlogloss:1.30136
[36m(train_xgb_ray_tune pid=1371784)[0m [317]	train-mlogloss:1.28456	validation-mlogloss:1.30057
[36m(train_xgb_ray_tune pid=1371766)[0m [372]	train-mlogloss:1.59541	validation-mlogloss:1.55744
[36m(train_xgb_ray_tune pid=1371766)[0m [373]	train-mlogloss:1.59446	validation-mlogloss:1.55646
[36m(train_xgb_ray_tune pid=1371754)[0m [339]	train-mlogloss:1.58067	validation-mlogloss:1.56929
[36m(train_xgb_ray_tune pid=1371781)[0m [454]	train-mlogloss:1.88290	validation-mlogloss:1.85459
[36m(train_xgb_ray_tune pid=1371755)[0m [372]	train-mlogloss:1.40887	validation-mlogloss:1.39040
[36m(train_xgb_ray_tune pid=1371796)[0m [464]	train-mlogloss:2.23104	validation-mlogloss:2.21359
[36m(train_xgb_ray_tune pid=1371762)[0m [347]	train-mlogloss:1.57286	validation-mlogloss:1.57384
[36m(train_xgb_ray_tune pid=1371795)[0m [360]	train-mlogloss:1.34150	validation-mlogloss:1.31658

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:04:58. Total running time: 35s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             32.4477 │
│ time_total_s                 32.4477 │
│ training_iteration                 1 │
│ validation_accuracy           0.4439 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:04:58. Total running time: 35s
[36m(train_xgb_ray_tune pid=1371754)[0m [340]	train-mlogloss:1.57961	validation-mlogloss:1.56819
[36m(train_xgb_ray_tune pid=1371761)[0m [400]	train-mlogloss:1.88984	validation-mlogloss:1.85729
[36m(train_xgb_ray_tune pid=1371761)[0m [401]	train-mlogloss:1.88935	validation-mlogloss:1.85677
[36m(train_xgb_ray_tune pid=1371781)[0m [455]	train-mlogloss:1.88279	validation-mlogloss:1.85446
[36m(train_xgb_ray_tune pid=1371781)[0m [456]	train-mlogloss:1.88279	validation-mlogloss:1.85446
[36m(train_xgb_ray_tune pid=1371781)[0m [457]	train-mlogloss:1.88279	validation-mlogloss:1.85446
[36m(train_xgb_ray_tune pid=1371781)[0m [458]	train-mlogloss:1.88279	validation-mlogloss:1.85446
[36m(train_xgb_ray_tune pid=1371786)[0m [367]	train-mlogloss:1.37884	validation-mlogloss:1.36832
[36m(train_xgb_ray_tune pid=1371786)[0m [368]	train-mlogloss:1.37798	validation-mlogloss:1.36744
[36m(train_xgb_ray_tune pid=1371786)[0m [369]	train-mlogloss:1.37706	validation-mlogloss:1.36660
[36m(train_xgb_ray_tune pid=1371796)[0m [465]	train-mlogloss:2.23104	validation-mlogloss:2.21359
[36m(train_xgb_ray_tune pid=1371796)[0m [466]	train-mlogloss:2.23097	validation-mlogloss:2.21354
[36m(train_xgb_ray_tune pid=1371793)[0m [380]	train-mlogloss:1.46864	validation-mlogloss:1.43640
[36m(train_xgb_ray_tune pid=1371793)[0m [381]	train-mlogloss:1.46784	validation-mlogloss:1.43564
[36m(train_xgb_ray_tune pid=1371762)[0m [348]	train-mlogloss:1.57173	validation-mlogloss:1.57259
[36m(train_xgb_ray_tune pid=1371762)[0m [349]	train-mlogloss:1.57053	validation-mlogloss:1.57134
[36m(train_xgb_ray_tune pid=1371795)[0m [361]	train-mlogloss:1.34150	validation-mlogloss:1.31658
[36m(train_xgb_ray_tune pid=1371795)[0m [362]	train-mlogloss:1.34146	validation-mlogloss:1.31654
[36m(train_xgb_ray_tune pid=1371795)[0m [363]	train-mlogloss:1.34137	validation-mlogloss:1.31642
[36m(train_xgb_ray_tune pid=1371782)[0m [313]	train-mlogloss:1.48194	validation-mlogloss:1.49674
[36m(train_xgb_ray_tune pid=1371783)[0m [383]	train-mlogloss:1.47810	validation-mlogloss:1.45184
[36m(train_xgb_ray_tune pid=1371783)[0m [384]	train-mlogloss:1.47752	validation-mlogloss:1.45118
[36m(train_xgb_ray_tune pid=1371794)[0m [439]	train-mlogloss:1.64723	validation-mlogloss:1.61377
[36m(train_xgb_ray_tune pid=1371794)[0m [440]	train-mlogloss:1.64703	validation-mlogloss:1.61358
[36m(train_xgb_ray_tune pid=1371794)[0m [441]	train-mlogloss:1.64688	validation-mlogloss:1.61343
[36m(train_xgb_ray_tune pid=1371794)[0m [442]	train-mlogloss:1.64673	validation-mlogloss:1.61327
[36m(train_xgb_ray_tune pid=1371755)[0m [373]	train-mlogloss:1.40810	validation-mlogloss:1.38963
[36m(train_xgb_ray_tune pid=1371784)[0m [318]	train-mlogloss:1.28362	validation-mlogloss:1.29971
[36m(train_xgb_ray_tune pid=1371766)[0m [374]	train-mlogloss:1.59353	validation-mlogloss:1.55543
[36m(train_xgb_ray_tune pid=1371796)[0m [467]	train-mlogloss:2.23073	validation-mlogloss:2.21328
[36m(train_xgb_ray_tune pid=1371782)[0m [314]	train-mlogloss:1.48060	validation-mlogloss:1.49532
[36m(train_xgb_ray_tune pid=1371755)[0m [374]	train-mlogloss:1.40733	validation-mlogloss:1.38877
[36m(train_xgb_ray_tune pid=1371766)[0m [375]	train-mlogloss:1.59256	validation-mlogloss:1.55430
[36m(train_xgb_ray_tune pid=1371761)[0m [402]	train-mlogloss:1.88873	validation-mlogloss:1.85612
[36m(train_xgb_ray_tune pid=1371781)[0m [459]	train-mlogloss:1.88279	validation-mlogloss:1.85446
[36m(train_xgb_ray_tune pid=1371762)[0m [350]	train-mlogloss:1.56930	validation-mlogloss:1.56999
[36m(train_xgb_ray_tune pid=1371794)[0m [443]	train-mlogloss:1.64654	validation-mlogloss:1.61305
[36m(train_xgb_ray_tune pid=1371754)[0m [341]	train-mlogloss:1.57845	validation-mlogloss:1.56694
[36m(train_xgb_ray_tune pid=1371754)[0m [342]	train-mlogloss:1.57728	validation-mlogloss:1.56579
[36m(train_xgb_ray_tune pid=1371761)[0m [403]	train-mlogloss:1.88819	validation-mlogloss:1.85558
[36m(train_xgb_ray_tune pid=1371781)[0m [460]	train-mlogloss:1.88258	validation-mlogloss:1.85419
[36m(train_xgb_ray_tune pid=1371781)[0m [461]	train-mlogloss:1.88237	validation-mlogloss:1.85393
[36m(train_xgb_ray_tune pid=1371786)[0m [370]	train-mlogloss:1.37617	validation-mlogloss:1.36574
[36m(train_xgb_ray_tune pid=1371786)[0m [371]	train-mlogloss:1.37522	validation-mlogloss:1.36480
[36m(train_xgb_ray_tune pid=1371786)[0m [372]	train-mlogloss:1.37433	validation-mlogloss:1.36392
[36m(train_xgb_ray_tune pid=1371796)[0m [468]	train-mlogloss:2.23050	validation-mlogloss:2.21304
[36m(train_xgb_ray_tune pid=1371796)[0m [469]	train-mlogloss:2.23050	validation-mlogloss:2.21304
[36m(train_xgb_ray_tune pid=1371796)[0m [470]	train-mlogloss:2.23043	validation-mlogloss:2.21295
[36m(train_xgb_ray_tune pid=1371796)[0m [471]	train-mlogloss:2.23043	validation-mlogloss:2.21295
[36m(train_xgb_ray_tune pid=1371793)[0m [382]	train-mlogloss:1.46707	validation-mlogloss:1.43486
[36m(train_xgb_ray_tune pid=1371793)[0m [383]	train-mlogloss:1.46630	validation-mlogloss:1.43408
[36m(train_xgb_ray_tune pid=1371762)[0m [351]	train-mlogloss:1.56814	validation-mlogloss:1.56882
[36m(train_xgb_ray_tune pid=1371762)[0m [352]	train-mlogloss:1.56695	validation-mlogloss:1.56758
[36m(train_xgb_ray_tune pid=1371795)[0m [364]	train-mlogloss:1.34133	validation-mlogloss:1.31637
[36m(train_xgb_ray_tune pid=1371795)[0m [365]	train-mlogloss:1.34124	validation-mlogloss:1.31625
[36m(train_xgb_ray_tune pid=1371782)[0m [315]	train-mlogloss:1.47928	validation-mlogloss:1.49393
[36m(train_xgb_ray_tune pid=1371783)[0m [385]	train-mlogloss:1.47701	validation-mlogloss:1.45068
[36m(train_xgb_ray_tune pid=1371783)[0m [386]	train-mlogloss:1.47653	validation-mlogloss:1.45017
[36m(train_xgb_ray_tune pid=1371794)[0m [444]	train-mlogloss:1.64639	validation-mlogloss:1.61289
[36m(train_xgb_ray_tune pid=1371794)[0m [445]	train-mlogloss:1.64630	validation-mlogloss:1.61277
[36m(train_xgb_ray_tune pid=1371794)[0m [446]	train-mlogloss:1.64610	validation-mlogloss:1.61255
[36m(train_xgb_ray_tune pid=1371794)[0m [447]	train-mlogloss:1.64600	validation-mlogloss:1.61249
[36m(train_xgb_ray_tune pid=1371755)[0m [375]	train-mlogloss:1.40656	validation-mlogloss:1.38795
[36m(train_xgb_ray_tune pid=1371755)[0m [376]	train-mlogloss:1.40585	validation-mlogloss:1.38722
[36m(train_xgb_ray_tune pid=1371766)[0m [376]	train-mlogloss:1.59166	validation-mlogloss:1.55335
[36m(train_xgb_ray_tune pid=1371761)[0m [404]	train-mlogloss:1.88757	validation-mlogloss:1.85489
[36m(train_xgb_ray_tune pid=1371766)[0m [377]	train-mlogloss:1.59080	validation-mlogloss:1.55246
[36m(train_xgb_ray_tune pid=1371795)[0m [366]	train-mlogloss:1.34120	validation-mlogloss:1.31620
[36m(train_xgb_ray_tune pid=1371783)[0m [387]	train-mlogloss:1.47592	validation-mlogloss:1.44951
[36m(train_xgb_ray_tune pid=1371762)[0m [353]	train-mlogloss:1.56577	validation-mlogloss:1.56633
[36m(train_xgb_ray_tune pid=1371786)[0m [373]	train-mlogloss:1.37341	validation-mlogloss:1.36295
[36m(train_xgb_ray_tune pid=1371796)[0m [472]	train-mlogloss:2.23043	validation-mlogloss:2.21295
[36m(train_xgb_ray_tune pid=1371754)[0m [343]	train-mlogloss:1.57610	validation-mlogloss:1.56449
[36m(train_xgb_ray_tune pid=1371754)[0m [344]	train-mlogloss:1.57495	validation-mlogloss:1.56328
[36m(train_xgb_ray_tune pid=1371761)[0m [405]	train-mlogloss:1.88700	validation-mlogloss:1.85428
[36m(train_xgb_ray_tune pid=1371761)[0m [406]	train-mlogloss:1.88640	validation-mlogloss:1.85366
[36m(train_xgb_ray_tune pid=1371781)[0m [462]	train-mlogloss:1.88226	validation-mlogloss:1.85380
[36m(train_xgb_ray_tune pid=1371781)[0m [463]	train-mlogloss:1.88226	validation-mlogloss:1.85380
[36m(train_xgb_ray_tune pid=1371786)[0m [374]	train-mlogloss:1.37248	validation-mlogloss:1.36201
[36m(train_xgb_ray_tune pid=1371786)[0m [375]	train-mlogloss:1.37157	validation-mlogloss:1.36108
[36m(train_xgb_ray_tune pid=1371786)[0m [376]	train-mlogloss:1.37068	validation-mlogloss:1.36019
[36m(train_xgb_ray_tune pid=1371796)[0m [473]	train-mlogloss:2.23036	validation-mlogloss:2.21287
[36m(train_xgb_ray_tune pid=1371796)[0m [474]	train-mlogloss:2.23028	validation-mlogloss:2.21282
[36m(train_xgb_ray_tune pid=1371796)[0m [475]	train-mlogloss:2.23020	validation-mlogloss:2.21277
[36m(train_xgb_ray_tune pid=1371796)[0m [476]	train-mlogloss:2.23020	validation-mlogloss:2.21277
[36m(train_xgb_ray_tune pid=1371793)[0m [384]	train-mlogloss:1.46557	validation-mlogloss:1.43338
[36m(train_xgb_ray_tune pid=1371793)[0m [385]	train-mlogloss:1.46480	validation-mlogloss:1.43261
[36m(train_xgb_ray_tune pid=1371762)[0m [354]	train-mlogloss:1.56459	validation-mlogloss:1.56508
[36m(train_xgb_ray_tune pid=1371762)[0m [355]	train-mlogloss:1.56337	validation-mlogloss:1.56382
[36m(train_xgb_ray_tune pid=1371795)[0m [367]	train-mlogloss:1.34116	validation-mlogloss:1.31617
[36m(train_xgb_ray_tune pid=1371795)[0m [368]	train-mlogloss:1.34108	validation-mlogloss:1.31608
[36m(train_xgb_ray_tune pid=1371782)[0m [316]	train-mlogloss:1.47791	validation-mlogloss:1.49253
[36m(train_xgb_ray_tune pid=1371782)[0m [317]	train-mlogloss:1.47655	validation-mlogloss:1.49116
[36m(train_xgb_ray_tune pid=1371783)[0m [388]	train-mlogloss:1.47553	validation-mlogloss:1.44909
[36m(train_xgb_ray_tune pid=1371783)[0m [389]	train-mlogloss:1.47512	validation-mlogloss:1.44867
[36m(train_xgb_ray_tune pid=1371794)[0m [448]	train-mlogloss:1.64595	validation-mlogloss:1.61243
[36m(train_xgb_ray_tune pid=1371794)[0m [449]	train-mlogloss:1.64573	validation-mlogloss:1.61220
[36m(train_xgb_ray_tune pid=1371794)[0m [450]	train-mlogloss:1.64553	validation-mlogloss:1.61200
[36m(train_xgb_ray_tune pid=1371794)[0m [451]	train-mlogloss:1.64548	validation-mlogloss:1.61193
[36m(train_xgb_ray_tune pid=1371794)[0m [452]	train-mlogloss:1.64543	validation-mlogloss:1.61189
[36m(train_xgb_ray_tune pid=1371755)[0m [377]	train-mlogloss:1.40514	validation-mlogloss:1.38650
[36m(train_xgb_ray_tune pid=1371755)[0m [378]	train-mlogloss:1.40437	validation-mlogloss:1.38566
[36m(train_xgb_ray_tune pid=1371766)[0m [378]	train-mlogloss:1.58990	validation-mlogloss:1.55146
[36m(train_xgb_ray_tune pid=1371766)[0m [379]	train-mlogloss:1.58898	validation-mlogloss:1.55049
[36m(train_xgb_ray_tune pid=1371781)[0m [464]	train-mlogloss:1.88194	validation-mlogloss:1.85341
[36m(train_xgb_ray_tune pid=1371762)[0m [356]	train-mlogloss:1.56225	validation-mlogloss:1.56264
[36m(train_xgb_ray_tune pid=1371754)[0m [345]	train-mlogloss:1.57379	validation-mlogloss:1.56210
[36m(train_xgb_ray_tune pid=1371761)[0m [407]	train-mlogloss:1.88589	validation-mlogloss:1.85313
[36m(train_xgb_ray_tune pid=1371761)[0m [408]	train-mlogloss:1.88544	validation-mlogloss:1.85266
[36m(train_xgb_ray_tune pid=1371781)[0m [465]	train-mlogloss:1.88194	validation-mlogloss:1.85341
[36m(train_xgb_ray_tune pid=1371781)[0m [466]	train-mlogloss:1.88194	validation-mlogloss:1.85341
[36m(train_xgb_ray_tune pid=1371786)[0m [377]	train-mlogloss:1.36984	validation-mlogloss:1.35935
[36m(train_xgb_ray_tune pid=1371786)[0m [378]	train-mlogloss:1.36898	validation-mlogloss:1.35846
[36m(train_xgb_ray_tune pid=1371796)[0m [477]	train-mlogloss:2.23020	validation-mlogloss:2.21277
[36m(train_xgb_ray_tune pid=1371796)[0m [478]	train-mlogloss:2.23012	validation-mlogloss:2.21268
[36m(train_xgb_ray_tune pid=1371796)[0m [479]	train-mlogloss:2.23012	validation-mlogloss:2.21268
[36m(train_xgb_ray_tune pid=1371796)[0m [480]	train-mlogloss:2.23012	validation-mlogloss:2.21268
[36m(train_xgb_ray_tune pid=1371793)[0m [386]	train-mlogloss:1.46409	validation-mlogloss:1.43183
[36m(train_xgb_ray_tune pid=1371762)[0m [357]	train-mlogloss:1.56107	validation-mlogloss:1.56146
[36m(train_xgb_ray_tune pid=1371762)[0m [358]	train-mlogloss:1.55997	validation-mlogloss:1.56032
[36m(train_xgb_ray_tune pid=1371795)[0m [369]	train-mlogloss:1.34108	validation-mlogloss:1.31609
[36m(train_xgb_ray_tune pid=1371795)[0m [370]	train-mlogloss:1.34108	validation-mlogloss:1.31609
[36m(train_xgb_ray_tune pid=1371795)[0m [371]	train-mlogloss:1.34108	validation-mlogloss:1.31608
[36m(train_xgb_ray_tune pid=1371782)[0m [318]	train-mlogloss:1.47525	validation-mlogloss:1.48984
[36m(train_xgb_ray_tune pid=1371783)[0m [390]	train-mlogloss:1.47467	validation-mlogloss:1.44817
[36m(train_xgb_ray_tune pid=1371783)[0m [391]	train-mlogloss:1.47424	validation-mlogloss:1.44771
[36m(train_xgb_ray_tune pid=1371794)[0m [453]	train-mlogloss:1.64530	validation-mlogloss:1.61173
[36m(train_xgb_ray_tune pid=1371794)[0m [454]	train-mlogloss:1.64500	validation-mlogloss:1.61140
[36m(train_xgb_ray_tune pid=1371794)[0m [455]	train-mlogloss:1.64485	validation-mlogloss:1.61127
[36m(train_xgb_ray_tune pid=1371794)[0m [456]	train-mlogloss:1.64461	validation-mlogloss:1.61100
[36m(train_xgb_ray_tune pid=1371755)[0m [379]	train-mlogloss:1.40356	validation-mlogloss:1.38485
[36m(train_xgb_ray_tune pid=1371755)[0m [380]	train-mlogloss:1.40278	validation-mlogloss:1.38407
[36m(train_xgb_ray_tune pid=1371766)[0m [380]	train-mlogloss:1.58810	validation-mlogloss:1.54951
[36m(train_xgb_ray_tune pid=1371754)[0m [346]	train-mlogloss:1.57260	validation-mlogloss:1.56089
[36m(train_xgb_ray_tune pid=1371786)[0m [379]	train-mlogloss:1.36814	validation-mlogloss:1.35768
[36m(train_xgb_ray_tune pid=1371796)[0m [481]	train-mlogloss:2.23012	validation-mlogloss:2.21268
[36m(train_xgb_ray_tune pid=1371762)[0m [359]	train-mlogloss:1.55879	validation-mlogloss:1.55910
[36m(train_xgb_ray_tune pid=1371754)[0m [347]	train-mlogloss:1.57143	validation-mlogloss:1.55964
[36m(train_xgb_ray_tune pid=1371761)[0m [409]	train-mlogloss:1.88478	validation-mlogloss:1.85199
[36m(train_xgb_ray_tune pid=1371761)[0m [410]	train-mlogloss:1.88428	validation-mlogloss:1.85145
[36m(train_xgb_ray_tune pid=1371781)[0m [467]	train-mlogloss:1.88194	validation-mlogloss:1.85341
[36m(train_xgb_ray_tune pid=1371781)[0m [468]	train-mlogloss:1.88194	validation-mlogloss:1.85341
[36m(train_xgb_ray_tune pid=1371781)[0m [469]	train-mlogloss:1.88194	validation-mlogloss:1.85341
[36m(train_xgb_ray_tune pid=1371786)[0m [380]	train-mlogloss:1.36727	validation-mlogloss:1.35673
[36m(train_xgb_ray_tune pid=1371786)[0m [381]	train-mlogloss:1.36639	validation-mlogloss:1.35587
[36m(train_xgb_ray_tune pid=1371786)[0m [382]	train-mlogloss:1.36554	validation-mlogloss:1.35503
[36m(train_xgb_ray_tune pid=1371796)[0m [482]	train-mlogloss:2.23012	validation-mlogloss:2.21268
[36m(train_xgb_ray_tune pid=1371796)[0m [483]	train-mlogloss:2.23005	validation-mlogloss:2.21262
[36m(train_xgb_ray_tune pid=1371796)[0m [484]	train-mlogloss:2.23005	validation-mlogloss:2.21262
[36m(train_xgb_ray_tune pid=1371796)[0m [485]	train-mlogloss:2.23005	validation-mlogloss:2.21262
[36m(train_xgb_ray_tune pid=1371793)[0m [387]	train-mlogloss:1.46338	validation-mlogloss:1.43110
[36m(train_xgb_ray_tune pid=1371793)[0m [388]	train-mlogloss:1.46267	validation-mlogloss:1.43037
[36m(train_xgb_ray_tune pid=1371762)[0m [360]	train-mlogloss:1.55770	validation-mlogloss:1.55790
[36m(train_xgb_ray_tune pid=1371762)[0m [361]	train-mlogloss:1.55663	validation-mlogloss:1.55678
[36m(train_xgb_ray_tune pid=1371762)[0m [362]	train-mlogloss:1.55559	validation-mlogloss:1.55564
[36m(train_xgb_ray_tune pid=1371795)[0m [372]	train-mlogloss:1.34099	validation-mlogloss:1.31598
[36m(train_xgb_ray_tune pid=1371795)[0m [373]	train-mlogloss:1.34087	validation-mlogloss:1.31586
[36m(train_xgb_ray_tune pid=1371782)[0m [319]	train-mlogloss:1.47392	validation-mlogloss:1.48854
[36m(train_xgb_ray_tune pid=1371782)[0m [320]	train-mlogloss:1.47268	validation-mlogloss:1.48716
[36m(train_xgb_ray_tune pid=1371783)[0m [392]	train-mlogloss:1.47378	validation-mlogloss:1.44727
[36m(train_xgb_ray_tune pid=1371783)[0m [393]	train-mlogloss:1.47345	validation-mlogloss:1.44694
[36m(train_xgb_ray_tune pid=1371794)[0m [457]	train-mlogloss:1.64443	validation-mlogloss:1.61082
[36m(train_xgb_ray_tune pid=1371794)[0m [458]	train-mlogloss:1.64429	validation-mlogloss:1.61069
[36m(train_xgb_ray_tune pid=1371794)[0m [459]	train-mlogloss:1.64420	validation-mlogloss:1.61060
[36m(train_xgb_ray_tune pid=1371794)[0m [460]	train-mlogloss:1.64393	validation-mlogloss:1.61031
[36m(train_xgb_ray_tune pid=1371755)[0m [381]	train-mlogloss:1.40198	validation-mlogloss:1.38328
[36m(train_xgb_ray_tune pid=1371755)[0m [382]	train-mlogloss:1.40121	validation-mlogloss:1.38239
[36m(train_xgb_ray_tune pid=1371766)[0m [381]	train-mlogloss:1.58718	validation-mlogloss:1.54856
[36m(train_xgb_ray_tune pid=1371766)[0m [382]	train-mlogloss:1.58629	validation-mlogloss:1.54768
[36m(train_xgb_ray_tune pid=1371754)[0m [348]	train-mlogloss:1.57034	validation-mlogloss:1.55842
[36m(train_xgb_ray_tune pid=1371754)[0m [349]	train-mlogloss:1.56924	validation-mlogloss:1.55717
[36m(train_xgb_ray_tune pid=1371761)[0m [411]	train-mlogloss:1.88376	validation-mlogloss:1.85090
[36m(train_xgb_ray_tune pid=1371761)[0m [412]	train-mlogloss:1.88317	validation-mlogloss:1.85030
[36m(train_xgb_ray_tune pid=1371781)[0m [470]	train-mlogloss:1.88194	validation-mlogloss:1.85341
[36m(train_xgb_ray_tune pid=1371781)[0m [471]	train-mlogloss:1.88194	validation-mlogloss:1.85341
[36m(train_xgb_ray_tune pid=1371786)[0m [383]	train-mlogloss:1.36466	validation-mlogloss:1.35411
[36m(train_xgb_ray_tune pid=1371786)[0m [384]	train-mlogloss:1.36382	validation-mlogloss:1.35329
[36m(train_xgb_ray_tune pid=1371796)[0m [486]	train-mlogloss:2.22998	validation-mlogloss:2.21255
[36m(train_xgb_ray_tune pid=1371796)[0m [487]	train-mlogloss:2.22982	validation-mlogloss:2.21235
[36m(train_xgb_ray_tune pid=1371796)[0m [488]	train-mlogloss:2.22982	validation-mlogloss:2.21235
[36m(train_xgb_ray_tune pid=1371796)[0m [489]	train-mlogloss:2.22946	validation-mlogloss:2.21196
[36m(train_xgb_ray_tune pid=1371793)[0m [389]	train-mlogloss:1.46192	validation-mlogloss:1.42962
[36m(train_xgb_ray_tune pid=1371793)[0m [390]	train-mlogloss:1.46119	validation-mlogloss:1.42886
[36m(train_xgb_ray_tune pid=1371762)[0m [363]	train-mlogloss:1.55445	validation-mlogloss:1.55442
[36m(train_xgb_ray_tune pid=1371762)[0m [364]	train-mlogloss:1.55335	validation-mlogloss:1.55328
[36m(train_xgb_ray_tune pid=1371795)[0m [374]	train-mlogloss:1.34083	validation-mlogloss:1.31580
[36m(train_xgb_ray_tune pid=1371795)[0m [375]	train-mlogloss:1.34082	validation-mlogloss:1.31580
[36m(train_xgb_ray_tune pid=1371782)[0m [321]	train-mlogloss:1.47142	validation-mlogloss:1.48588
[36m(train_xgb_ray_tune pid=1371783)[0m [394]	train-mlogloss:1.47295	validation-mlogloss:1.44643
[36m(train_xgb_ray_tune pid=1371783)[0m [395]	train-mlogloss:1.47248	validation-mlogloss:1.44587
[36m(train_xgb_ray_tune pid=1371794)[0m [461]	train-mlogloss:1.64379	validation-mlogloss:1.61015
[36m(train_xgb_ray_tune pid=1371794)[0m [462]	train-mlogloss:1.64356	validation-mlogloss:1.60990
[36m(train_xgb_ray_tune pid=1371794)[0m [463]	train-mlogloss:1.64328	validation-mlogloss:1.60961
[36m(train_xgb_ray_tune pid=1371794)[0m [464]	train-mlogloss:1.64297	validation-mlogloss:1.60924
[36m(train_xgb_ray_tune pid=1371755)[0m [383]	train-mlogloss:1.40045	validation-mlogloss:1.38164
[36m(train_xgb_ray_tune pid=1371755)[0m [384]	train-mlogloss:1.39970	validation-mlogloss:1.38084
[36m(train_xgb_ray_tune pid=1371766)[0m [383]	train-mlogloss:1.58537	validation-mlogloss:1.54668
[36m(train_xgb_ray_tune pid=1371766)[0m [384]	train-mlogloss:1.58450	validation-mlogloss:1.54570
[36m(train_xgb_ray_tune pid=1371754)[0m [350]	train-mlogloss:1.56821	validation-mlogloss:1.55612
[36m(train_xgb_ray_tune pid=1371761)[0m [413]	train-mlogloss:1.88257	validation-mlogloss:1.84970
[36m(train_xgb_ray_tune pid=1371761)[0m [414]	train-mlogloss:1.88210	validation-mlogloss:1.84924
[36m(train_xgb_ray_tune pid=1371781)[0m [472]	train-mlogloss:1.88182	validation-mlogloss:1.85334
[36m(train_xgb_ray_tune pid=1371781)[0m [473]	train-mlogloss:1.88132	validation-mlogloss:1.85280
[36m(train_xgb_ray_tune pid=1371786)[0m [385]	train-mlogloss:1.36300	validation-mlogloss:1.35243
[36m(train_xgb_ray_tune pid=1371786)[0m [386]	train-mlogloss:1.36220	validation-mlogloss:1.35157
[36m(train_xgb_ray_tune pid=1371786)[0m [387]	train-mlogloss:1.36134	validation-mlogloss:1.35073
[36m(train_xgb_ray_tune pid=1371796)[0m [490]	train-mlogloss:2.22946	validation-mlogloss:2.21196
[36m(train_xgb_ray_tune pid=1371796)[0m [491]	train-mlogloss:2.22946	validation-mlogloss:2.21196
[36m(train_xgb_ray_tune pid=1371796)[0m [492]	train-mlogloss:2.22931	validation-mlogloss:2.21178
[36m(train_xgb_ray_tune pid=1371796)[0m [493]	train-mlogloss:2.22931	validation-mlogloss:2.21178
[36m(train_xgb_ray_tune pid=1371793)[0m [391]	train-mlogloss:1.46044	validation-mlogloss:1.42813
[36m(train_xgb_ray_tune pid=1371793)[0m [392]	train-mlogloss:1.45973	validation-mlogloss:1.42744
[36m(train_xgb_ray_tune pid=1371762)[0m [365]	train-mlogloss:1.55229	validation-mlogloss:1.55218
[36m(train_xgb_ray_tune pid=1371762)[0m [366]	train-mlogloss:1.55117	validation-mlogloss:1.55096
[36m(train_xgb_ray_tune pid=1371762)[0m [367]	train-mlogloss:1.54997	validation-mlogloss:1.54970
[36m(train_xgb_ray_tune pid=1371795)[0m [376]	train-mlogloss:1.34069	validation-mlogloss:1.31563
[36m(train_xgb_ray_tune pid=1371795)[0m [377]	train-mlogloss:1.34047	validation-mlogloss:1.31536
[36m(train_xgb_ray_tune pid=1371782)[0m [322]	train-mlogloss:1.47013	validation-mlogloss:1.48458
[36m(train_xgb_ray_tune pid=1371782)[0m [323]	train-mlogloss:1.46883	validation-mlogloss:1.48326
[36m(train_xgb_ray_tune pid=1371783)[0m [396]	train-mlogloss:1.47201	validation-mlogloss:1.44538
[36m(train_xgb_ray_tune pid=1371783)[0m [397]	train-mlogloss:1.47165	validation-mlogloss:1.44502
[36m(train_xgb_ray_tune pid=1371794)[0m [465]	train-mlogloss:1.64278	validation-mlogloss:1.60903
[36m(train_xgb_ray_tune pid=1371794)[0m [466]	train-mlogloss:1.64261	validation-mlogloss:1.60889
[36m(train_xgb_ray_tune pid=1371794)[0m [467]	train-mlogloss:1.64247	validation-mlogloss:1.60873
[36m(train_xgb_ray_tune pid=1371794)[0m [468]	train-mlogloss:1.64243	validation-mlogloss:1.60868
[36m(train_xgb_ray_tune pid=1371755)[0m [385]	train-mlogloss:1.39896	validation-mlogloss:1.38010
[36m(train_xgb_ray_tune pid=1371755)[0m [386]	train-mlogloss:1.39819	validation-mlogloss:1.37924
[36m(train_xgb_ray_tune pid=1371766)[0m [385]	train-mlogloss:1.58362	validation-mlogloss:1.54470
[36m(train_xgb_ray_tune pid=1371786)[0m [388]	train-mlogloss:1.36048	validation-mlogloss:1.34986
[36m(train_xgb_ray_tune pid=1371795)[0m [378]	train-mlogloss:1.34037	validation-mlogloss:1.31526
[36m(train_xgb_ray_tune pid=1371794)[0m [469]	train-mlogloss:1.64225	validation-mlogloss:1.60849
[36m(train_xgb_ray_tune pid=1371754)[0m [351]	train-mlogloss:1.56711	validation-mlogloss:1.55497
[36m(train_xgb_ray_tune pid=1371754)[0m [352]	train-mlogloss:1.56608	validation-mlogloss:1.55387
[36m(train_xgb_ray_tune pid=1371761)[0m [415]	train-mlogloss:1.88159	validation-mlogloss:1.84869
[36m(train_xgb_ray_tune pid=1371761)[0m [416]	train-mlogloss:1.88103	validation-mlogloss:1.84810
[36m(train_xgb_ray_tune pid=1371781)[0m [474]	train-mlogloss:1.88121	validation-mlogloss:1.85269
[36m(train_xgb_ray_tune pid=1371781)[0m [475]	train-mlogloss:1.88121	validation-mlogloss:1.85269
[36m(train_xgb_ray_tune pid=1371781)[0m [476]	train-mlogloss:1.88121	validation-mlogloss:1.85269
[36m(train_xgb_ray_tune pid=1371786)[0m [389]	train-mlogloss:1.35964	validation-mlogloss:1.34908
[36m(train_xgb_ray_tune pid=1371786)[0m [390]	train-mlogloss:1.35878	validation-mlogloss:1.34818
[36m(train_xgb_ray_tune pid=1371796)[0m [494]	train-mlogloss:2.22931	validation-mlogloss:2.21178
[36m(train_xgb_ray_tune pid=1371796)[0m [495]	train-mlogloss:2.22931	validation-mlogloss:2.21178
[36m(train_xgb_ray_tune pid=1371796)[0m [496]	train-mlogloss:2.22924	validation-mlogloss:2.21171
[36m(train_xgb_ray_tune pid=1371796)[0m [497]	train-mlogloss:2.22924	validation-mlogloss:2.21171
[36m(train_xgb_ray_tune pid=1371796)[0m [498]	train-mlogloss:2.22918	validation-mlogloss:2.21165
[36m(train_xgb_ray_tune pid=1371793)[0m [393]	train-mlogloss:1.45907	validation-mlogloss:1.42684
[36m(train_xgb_ray_tune pid=1371762)[0m [368]	train-mlogloss:1.54886	validation-mlogloss:1.54854
[36m(train_xgb_ray_tune pid=1371762)[0m [369]	train-mlogloss:1.54774	validation-mlogloss:1.54732
[36m(train_xgb_ray_tune pid=1371762)[0m [370]	train-mlogloss:1.54666	validation-mlogloss:1.54610
[36m(train_xgb_ray_tune pid=1371795)[0m [379]	train-mlogloss:1.34037	validation-mlogloss:1.31526
[36m(train_xgb_ray_tune pid=1371795)[0m [380]	train-mlogloss:1.34037	validation-mlogloss:1.31526
[36m(train_xgb_ray_tune pid=1371782)[0m [324]	train-mlogloss:1.46765	validation-mlogloss:1.48202
[36m(train_xgb_ray_tune pid=1371783)[0m [398]	train-mlogloss:1.47113	validation-mlogloss:1.44449
[36m(train_xgb_ray_tune pid=1371783)[0m [399]	train-mlogloss:1.47070	validation-mlogloss:1.44402
[36m(train_xgb_ray_tune pid=1371794)[0m [470]	train-mlogloss:1.64216	validation-mlogloss:1.60836
[36m(train_xgb_ray_tune pid=1371794)[0m [471]	train-mlogloss:1.64191	validation-mlogloss:1.60809
[36m(train_xgb_ray_tune pid=1371794)[0m [472]	train-mlogloss:1.64191	validation-mlogloss:1.60809
[36m(train_xgb_ray_tune pid=1371794)[0m [473]	train-mlogloss:1.64170	validation-mlogloss:1.60783
[36m(train_xgb_ray_tune pid=1371755)[0m [387]	train-mlogloss:1.39749	validation-mlogloss:1.37853
[36m(train_xgb_ray_tune pid=1371755)[0m [388]	train-mlogloss:1.39677	validation-mlogloss:1.37771
[36m(train_xgb_ray_tune pid=1371766)[0m [386]	train-mlogloss:1.58278	validation-mlogloss:1.54382
[36m(train_xgb_ray_tune pid=1371766)[0m [387]	train-mlogloss:1.58199	validation-mlogloss:1.54300
[36m(train_xgb_ray_tune pid=1371786)[0m [391]	train-mlogloss:1.35792	validation-mlogloss:1.34733
[36m(train_xgb_ray_tune pid=1371782)[0m [325]	train-mlogloss:1.46637	validation-mlogloss:1.48073
[36m(train_xgb_ray_tune pid=1371793)[0m [394]	train-mlogloss:1.45840	validation-mlogloss:1.42620

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:04:59. Total running time: 36s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             33.6368 │
│ time_total_s                 33.6368 │
│ training_iteration                 1 │
│ validation_accuracy          0.51919 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:04:59. Total running time: 36s
[36m(train_xgb_ray_tune pid=1371754)[0m [353]	train-mlogloss:1.56504	validation-mlogloss:1.55277
[36m(train_xgb_ray_tune pid=1371754)[0m [354]	train-mlogloss:1.56395	validation-mlogloss:1.55157
[36m(train_xgb_ray_tune pid=1371761)[0m [417]	train-mlogloss:1.88049	validation-mlogloss:1.84754
[36m(train_xgb_ray_tune pid=1371761)[0m [418]	train-mlogloss:1.87990	validation-mlogloss:1.84697
[36m(train_xgb_ray_tune pid=1371781)[0m [477]	train-mlogloss:1.88110	validation-mlogloss:1.85260
[36m(train_xgb_ray_tune pid=1371781)[0m [478]	train-mlogloss:1.88110	validation-mlogloss:1.85260
[36m(train_xgb_ray_tune pid=1371786)[0m [392]	train-mlogloss:1.35709	validation-mlogloss:1.34645
[36m(train_xgb_ray_tune pid=1371786)[0m [393]	train-mlogloss:1.35625	validation-mlogloss:1.34557
[36m(train_xgb_ray_tune pid=1371786)[0m [394]	train-mlogloss:1.35540	validation-mlogloss:1.34464
[36m(train_xgb_ray_tune pid=1371796)[0m [499]	train-mlogloss:2.22918	validation-mlogloss:2.21165
[36m(train_xgb_ray_tune pid=1371796)[0m [500]	train-mlogloss:2.22904	validation-mlogloss:2.21150
[36m(train_xgb_ray_tune pid=1371796)[0m [501]	train-mlogloss:2.22904	validation-mlogloss:2.21150
[36m(train_xgb_ray_tune pid=1371796)[0m [502]	train-mlogloss:2.22898	validation-mlogloss:2.21143
[36m(train_xgb_ray_tune pid=1371793)[0m [395]	train-mlogloss:1.45774	validation-mlogloss:1.42548
[36m(train_xgb_ray_tune pid=1371762)[0m [371]	train-mlogloss:1.54558	validation-mlogloss:1.54493
[36m(train_xgb_ray_tune pid=1371762)[0m [372]	train-mlogloss:1.54454	validation-mlogloss:1.54384
[36m(train_xgb_ray_tune pid=1371795)[0m [381]	train-mlogloss:1.34036	validation-mlogloss:1.31526
[36m(train_xgb_ray_tune pid=1371795)[0m [382]	train-mlogloss:1.34032	validation-mlogloss:1.31521
[36m(train_xgb_ray_tune pid=1371782)[0m [326]	train-mlogloss:1.46520	validation-mlogloss:1.47950
[36m(train_xgb_ray_tune pid=1371783)[0m [400]	train-mlogloss:1.47042	validation-mlogloss:1.44373
[36m(train_xgb_ray_tune pid=1371783)[0m [401]	train-mlogloss:1.46999	validation-mlogloss:1.44328
[36m(train_xgb_ray_tune pid=1371794)[0m [474]	train-mlogloss:1.64147	validation-mlogloss:1.60758
[36m(train_xgb_ray_tune pid=1371794)[0m [475]	train-mlogloss:1.64143	validation-mlogloss:1.60753
[36m(train_xgb_ray_tune pid=1371794)[0m [476]	train-mlogloss:1.64133	validation-mlogloss:1.60743
[36m(train_xgb_ray_tune pid=1371794)[0m [477]	train-mlogloss:1.64124	validation-mlogloss:1.60731
[36m(train_xgb_ray_tune pid=1371794)[0m [478]	train-mlogloss:1.64110	validation-mlogloss:1.60719
[36m(train_xgb_ray_tune pid=1371755)[0m [389]	train-mlogloss:1.39603	validation-mlogloss:1.37700
[36m(train_xgb_ray_tune pid=1371755)[0m [390]	train-mlogloss:1.39530	validation-mlogloss:1.37627
[36m(train_xgb_ray_tune pid=1371766)[0m [388]	train-mlogloss:1.58117	validation-mlogloss:1.54217
[36m(train_xgb_ray_tune pid=1371766)[0m [389]	train-mlogloss:1.58033	validation-mlogloss:1.54129
[36m(train_xgb_ray_tune pid=1371754)[0m [355]	train-mlogloss:1.56281	validation-mlogloss:1.55034
[36m(train_xgb_ray_tune pid=1371761)[0m [419]	train-mlogloss:1.87946	validation-mlogloss:1.84651
[36m(train_xgb_ray_tune pid=1371761)[0m [420]	train-mlogloss:1.87899	validation-mlogloss:1.84602
[36m(train_xgb_ray_tune pid=1371781)[0m [479]	train-mlogloss:1.88110	validation-mlogloss:1.85260
[36m(train_xgb_ray_tune pid=1371781)[0m [480]	train-mlogloss:1.88110	validation-mlogloss:1.85260
[36m(train_xgb_ray_tune pid=1371786)[0m [395]	train-mlogloss:1.35459	validation-mlogloss:1.34382
[36m(train_xgb_ray_tune pid=1371786)[0m [396]	train-mlogloss:1.35379	validation-mlogloss:1.34301
[36m(train_xgb_ray_tune pid=1371786)[0m [397]	train-mlogloss:1.35298	validation-mlogloss:1.34223
[36m(train_xgb_ray_tune pid=1371796)[0m [503]	train-mlogloss:2.22898	validation-mlogloss:2.21143
[36m(train_xgb_ray_tune pid=1371796)[0m [504]	train-mlogloss:2.22898	validation-mlogloss:2.21143
[36m(train_xgb_ray_tune pid=1371796)[0m [505]	train-mlogloss:2.22898	validation-mlogloss:2.21143
[36m(train_xgb_ray_tune pid=1371796)[0m [506]	train-mlogloss:2.22892	validation-mlogloss:2.21136
[36m(train_xgb_ray_tune pid=1371796)[0m [507]	train-mlogloss:2.22877	validation-mlogloss:2.21122
[36m(train_xgb_ray_tune pid=1371793)[0m [396]	train-mlogloss:1.45704	validation-mlogloss:1.42476
[36m(train_xgb_ray_tune pid=1371793)[0m [397]	train-mlogloss:1.45636	validation-mlogloss:1.42411
[36m(train_xgb_ray_tune pid=1371762)[0m [373]	train-mlogloss:1.54345	validation-mlogloss:1.54262
[36m(train_xgb_ray_tune pid=1371762)[0m [374]	train-mlogloss:1.54242	validation-mlogloss:1.54150
[36m(train_xgb_ray_tune pid=1371762)[0m [375]	train-mlogloss:1.54138	validation-mlogloss:1.54037
[36m(train_xgb_ray_tune pid=1371795)[0m [383]	train-mlogloss:1.34024	validation-mlogloss:1.31514
[36m(train_xgb_ray_tune pid=1371795)[0m [384]	train-mlogloss:1.34020	validation-mlogloss:1.31512
[36m(train_xgb_ray_tune pid=1371795)[0m [385]	train-mlogloss:1.34020	validation-mlogloss:1.31512
[36m(train_xgb_ray_tune pid=1371782)[0m [327]	train-mlogloss:1.46398	validation-mlogloss:1.47819
[36m(train_xgb_ray_tune pid=1371782)[0m [328]	train-mlogloss:1.46278	validation-mlogloss:1.47696
[36m(train_xgb_ray_tune pid=1371783)[0m [402]	train-mlogloss:1.46959	validation-mlogloss:1.44287
[36m(train_xgb_ray_tune pid=1371783)[0m [403]	train-mlogloss:1.46909	validation-mlogloss:1.44230
[36m(train_xgb_ray_tune pid=1371794)[0m [479]	train-mlogloss:1.64094	validation-mlogloss:1.60702
[36m(train_xgb_ray_tune pid=1371794)[0m [480]	train-mlogloss:1.64073	validation-mlogloss:1.60679
[36m(train_xgb_ray_tune pid=1371794)[0m [481]	train-mlogloss:1.64065	validation-mlogloss:1.60673
[36m(train_xgb_ray_tune pid=1371794)[0m [482]	train-mlogloss:1.64047	validation-mlogloss:1.60651
[36m(train_xgb_ray_tune pid=1371755)[0m [391]	train-mlogloss:1.39457	validation-mlogloss:1.37548
[36m(train_xgb_ray_tune pid=1371766)[0m [390]	train-mlogloss:1.57957	validation-mlogloss:1.54055
[36m(train_xgb_ray_tune pid=1371766)[0m [391]	train-mlogloss:1.57868	validation-mlogloss:1.53957
[36m(train_xgb_ray_tune pid=1371761)[0m [421]	train-mlogloss:1.87859	validation-mlogloss:1.84560
[36m(train_xgb_ray_tune pid=1371781)[0m [481]	train-mlogloss:1.88110	validation-mlogloss:1.85260
[36m(train_xgb_ray_tune pid=1371754)[0m [356]	train-mlogloss:1.56169	validation-mlogloss:1.54913
[36m(train_xgb_ray_tune pid=1371754)[0m [357]	train-mlogloss:1.56053	validation-mlogloss:1.54787
[36m(train_xgb_ray_tune pid=1371761)[0m [422]	train-mlogloss:1.87806	validation-mlogloss:1.84507
[36m(train_xgb_ray_tune pid=1371761)[0m [423]	train-mlogloss:1.87744	validation-mlogloss:1.84443
[36m(train_xgb_ray_tune pid=1371781)[0m [482]	train-mlogloss:1.88110	validation-mlogloss:1.85260
[36m(train_xgb_ray_tune pid=1371781)[0m [483]	train-mlogloss:1.88099	validation-mlogloss:1.85244
[36m(train_xgb_ray_tune pid=1371786)[0m [398]	train-mlogloss:1.35220	validation-mlogloss:1.34143
[36m(train_xgb_ray_tune pid=1371786)[0m [399]	train-mlogloss:1.35142	validation-mlogloss:1.34063
[36m(train_xgb_ray_tune pid=1371786)[0m [400]	train-mlogloss:1.35064	validation-mlogloss:1.33986
[36m(train_xgb_ray_tune pid=1371796)[0m [508]	train-mlogloss:2.22862	validation-mlogloss:2.21104
[36m(train_xgb_ray_tune pid=1371796)[0m [509]	train-mlogloss:2.22862	validation-mlogloss:2.21104
[36m(train_xgb_ray_tune pid=1371796)[0m [510]	train-mlogloss:2.22854	validation-mlogloss:2.21099
[36m(train_xgb_ray_tune pid=1371796)[0m [511]	train-mlogloss:2.22854	validation-mlogloss:2.21099
[36m(train_xgb_ray_tune pid=1371793)[0m [398]	train-mlogloss:1.45570	validation-mlogloss:1.42347
[36m(train_xgb_ray_tune pid=1371793)[0m [399]	train-mlogloss:1.45502	validation-mlogloss:1.42279
[36m(train_xgb_ray_tune pid=1371762)[0m [376]	train-mlogloss:1.54032	validation-mlogloss:1.53926
[36m(train_xgb_ray_tune pid=1371762)[0m [377]	train-mlogloss:1.53926	validation-mlogloss:1.53805
[36m(train_xgb_ray_tune pid=1371762)[0m [378]	train-mlogloss:1.53818	validation-mlogloss:1.53691
[36m(train_xgb_ray_tune pid=1371795)[0m [386]	train-mlogloss:1.34011	validation-mlogloss:1.31499
[36m(train_xgb_ray_tune pid=1371795)[0m [387]	train-mlogloss:1.34007	validation-mlogloss:1.31492
[36m(train_xgb_ray_tune pid=1371782)[0m [329]	train-mlogloss:1.46152	validation-mlogloss:1.47568
[36m(train_xgb_ray_tune pid=1371783)[0m [404]	train-mlogloss:1.46870	validation-mlogloss:1.44187
[36m(train_xgb_ray_tune pid=1371783)[0m [405]	train-mlogloss:1.46834	validation-mlogloss:1.44152
[36m(train_xgb_ray_tune pid=1371794)[0m [483]	train-mlogloss:1.64042	validation-mlogloss:1.60646
[36m(train_xgb_ray_tune pid=1371794)[0m [484]	train-mlogloss:1.64033	validation-mlogloss:1.60635
[36m(train_xgb_ray_tune pid=1371794)[0m [485]	train-mlogloss:1.64033	validation-mlogloss:1.60635
[36m(train_xgb_ray_tune pid=1371794)[0m [486]	train-mlogloss:1.64029	validation-mlogloss:1.60629
[36m(train_xgb_ray_tune pid=1371794)[0m [487]	train-mlogloss:1.64020	validation-mlogloss:1.60620
[36m(train_xgb_ray_tune pid=1371766)[0m [392]	train-mlogloss:1.57784	validation-mlogloss:1.53869
[36m(train_xgb_ray_tune pid=1371766)[0m [393]	train-mlogloss:1.57701	validation-mlogloss:1.53784
[36m(train_xgb_ray_tune pid=1371754)[0m [358]	train-mlogloss:1.55946	validation-mlogloss:1.54675
[36m(train_xgb_ray_tune pid=1371761)[0m [424]	train-mlogloss:1.87716	validation-mlogloss:1.84412
[36m(train_xgb_ray_tune pid=1371761)[0m [425]	train-mlogloss:1.87686	validation-mlogloss:1.84383
[36m(train_xgb_ray_tune pid=1371781)[0m [484]	train-mlogloss:1.88099	validation-mlogloss:1.85244
[36m(train_xgb_ray_tune pid=1371781)[0m [485]	train-mlogloss:1.88099	validation-mlogloss:1.85244
[36m(train_xgb_ray_tune pid=1371781)[0m [486]	train-mlogloss:1.88088	validation-mlogloss:1.85236
[36m(train_xgb_ray_tune pid=1371786)[0m [401]	train-mlogloss:1.34980	validation-mlogloss:1.33897
[36m(train_xgb_ray_tune pid=1371786)[0m [402]	train-mlogloss:1.34899	validation-mlogloss:1.33811
[36m(train_xgb_ray_tune pid=1371786)[0m [403]	train-mlogloss:1.34820	validation-mlogloss:1.33751
[36m(train_xgb_ray_tune pid=1371796)[0m [512]	train-mlogloss:2.22847	validation-mlogloss:2.21094
[36m(train_xgb_ray_tune pid=1371796)[0m [513]	train-mlogloss:2.22847	validation-mlogloss:2.21094
[36m(train_xgb_ray_tune pid=1371796)[0m [514]	train-mlogloss:2.22847	validation-mlogloss:2.21094
[36m(train_xgb_ray_tune pid=1371796)[0m [515]	train-mlogloss:2.22840	validation-mlogloss:2.21086
[36m(train_xgb_ray_tune pid=1371796)[0m [516]	train-mlogloss:2.22833	validation-mlogloss:2.21078
[36m(train_xgb_ray_tune pid=1371793)[0m [400]	train-mlogloss:1.45429	validation-mlogloss:1.42205
[36m(train_xgb_ray_tune pid=1371793)[0m [401]	train-mlogloss:1.45357	validation-mlogloss:1.42136
[36m(train_xgb_ray_tune pid=1371762)[0m [379]	train-mlogloss:1.53714	validation-mlogloss:1.53579
[36m(train_xgb_ray_tune pid=1371762)[0m [380]	train-mlogloss:1.53608	validation-mlogloss:1.53468
[36m(train_xgb_ray_tune pid=1371762)[0m [381]	train-mlogloss:1.53503	validation-mlogloss:1.53353
[36m(train_xgb_ray_tune pid=1371795)[0m [388]	train-mlogloss:1.34002	validation-mlogloss:1.31487
[36m(train_xgb_ray_tune pid=1371795)[0m [389]	train-mlogloss:1.34002	validation-mlogloss:1.31487
[36m(train_xgb_ray_tune pid=1371795)[0m [390]	train-mlogloss:1.33998	validation-mlogloss:1.31481
[36m(train_xgb_ray_tune pid=1371782)[0m [330]	train-mlogloss:1.46030	validation-mlogloss:1.47451
[36m(train_xgb_ray_tune pid=1371782)[0m [331]	train-mlogloss:1.45904	validation-mlogloss:1.47323
[36m(train_xgb_ray_tune pid=1371783)[0m [406]	train-mlogloss:1.46797	validation-mlogloss:1.44112
[36m(train_xgb_ray_tune pid=1371783)[0m [407]	train-mlogloss:1.46763	validation-mlogloss:1.44075
[36m(train_xgb_ray_tune pid=1371794)[0m [488]	train-mlogloss:1.64016	validation-mlogloss:1.60618
[36m(train_xgb_ray_tune pid=1371794)[0m [489]	train-mlogloss:1.63997	validation-mlogloss:1.60598
[36m(train_xgb_ray_tune pid=1371794)[0m [490]	train-mlogloss:1.63988	validation-mlogloss:1.60589
[36m(train_xgb_ray_tune pid=1371794)[0m [491]	train-mlogloss:1.63984	validation-mlogloss:1.60584
[36m(train_xgb_ray_tune pid=1371794)[0m [492]	train-mlogloss:1.63980	validation-mlogloss:1.60579
[36m(train_xgb_ray_tune pid=1371766)[0m [394]	train-mlogloss:1.57629	validation-mlogloss:1.53712
[36m(train_xgb_ray_tune pid=1371766)[0m [395]	train-mlogloss:1.57545	validation-mlogloss:1.53623
[36m(train_xgb_ray_tune pid=1371754)[0m [359]	train-mlogloss:1.55837	validation-mlogloss:1.54563
[36m(train_xgb_ray_tune pid=1371795)[0m [391]	train-mlogloss:1.33998	validation-mlogloss:1.31481
[36m(train_xgb_ray_tune pid=1371781)[0m [487]	train-mlogloss:1.88088	validation-mlogloss:1.85236
[36m(train_xgb_ray_tune pid=1371754)[0m [360]	train-mlogloss:1.55741	validation-mlogloss:1.54465
[36m(train_xgb_ray_tune pid=1371761)[0m [426]	train-mlogloss:1.87638	validation-mlogloss:1.84332
[36m(train_xgb_ray_tune pid=1371761)[0m [427]	train-mlogloss:1.87585	validation-mlogloss:1.84277
[36m(train_xgb_ray_tune pid=1371781)[0m [488]	train-mlogloss:1.88088	validation-mlogloss:1.85236
[36m(train_xgb_ray_tune pid=1371781)[0m [489]	train-mlogloss:1.88088	validation-mlogloss:1.85236
[36m(train_xgb_ray_tune pid=1371781)[0m [490]	train-mlogloss:1.88078	validation-mlogloss:1.85229
[36m(train_xgb_ray_tune pid=1371781)[0m [491]	train-mlogloss:1.88078	validation-mlogloss:1.85229
[36m(train_xgb_ray_tune pid=1371786)[0m [404]	train-mlogloss:1.34741	validation-mlogloss:1.33676
[36m(train_xgb_ray_tune pid=1371786)[0m [405]	train-mlogloss:1.34664	validation-mlogloss:1.33602
[36m(train_xgb_ray_tune pid=1371786)[0m [406]	train-mlogloss:1.34588	validation-mlogloss:1.33525
[36m(train_xgb_ray_tune pid=1371796)[0m [517]	train-mlogloss:2.22833	validation-mlogloss:2.21078
[36m(train_xgb_ray_tune pid=1371796)[0m [518]	train-mlogloss:2.22826	validation-mlogloss:2.21071
[36m(train_xgb_ray_tune pid=1371796)[0m [519]	train-mlogloss:2.22826	validation-mlogloss:2.21071
[36m(train_xgb_ray_tune pid=1371796)[0m [520]	train-mlogloss:2.22826	validation-mlogloss:2.21071
[36m(train_xgb_ray_tune pid=1371793)[0m [402]	train-mlogloss:1.45295	validation-mlogloss:1.42070
[36m(train_xgb_ray_tune pid=1371793)[0m [403]	train-mlogloss:1.45223	validation-mlogloss:1.41998
[36m(train_xgb_ray_tune pid=1371762)[0m [382]	train-mlogloss:1.53395	validation-mlogloss:1.53238
[36m(train_xgb_ray_tune pid=1371762)[0m [383]	train-mlogloss:1.53300	validation-mlogloss:1.53137
[36m(train_xgb_ray_tune pid=1371762)[0m [384]	train-mlogloss:1.53200	validation-mlogloss:1.53031
[36m(train_xgb_ray_tune pid=1371795)[0m [392]	train-mlogloss:1.33993	validation-mlogloss:1.31476
[36m(train_xgb_ray_tune pid=1371795)[0m [393]	train-mlogloss:1.33981	validation-mlogloss:1.31459
[36m(train_xgb_ray_tune pid=1371795)[0m [394]	train-mlogloss:1.33969	validation-mlogloss:1.31442
[36m(train_xgb_ray_tune pid=1371795)[0m [395]	train-mlogloss:1.33965	validation-mlogloss:1.31437
[36m(train_xgb_ray_tune pid=1371782)[0m [332]	train-mlogloss:1.45782	validation-mlogloss:1.47196
[36m(train_xgb_ray_tune pid=1371783)[0m [408]	train-mlogloss:1.46723	validation-mlogloss:1.44033
[36m(train_xgb_ray_tune pid=1371783)[0m [409]	train-mlogloss:1.46692	validation-mlogloss:1.44000
[36m(train_xgb_ray_tune pid=1371794)[0m [493]	train-mlogloss:1.63975	validation-mlogloss:1.60575
[36m(train_xgb_ray_tune pid=1371794)[0m [494]	train-mlogloss:1.63975	validation-mlogloss:1.60575
[36m(train_xgb_ray_tune pid=1371794)[0m [495]	train-mlogloss:1.63975	validation-mlogloss:1.60575
[36m(train_xgb_ray_tune pid=1371794)[0m [496]	train-mlogloss:1.63964	validation-mlogloss:1.60562
[36m(train_xgb_ray_tune pid=1371794)[0m [497]	train-mlogloss:1.63950	validation-mlogloss:1.60547
[36m(train_xgb_ray_tune pid=1371766)[0m [396]	train-mlogloss:1.57465	validation-mlogloss:1.53542
[36m(train_xgb_ray_tune pid=1371786)[0m [407]	train-mlogloss:1.34511	validation-mlogloss:1.33443
[36m(train_xgb_ray_tune pid=1371783)[0m [410]	train-mlogloss:1.46657	validation-mlogloss:1.43961
[36m(train_xgb_ray_tune pid=1371766)[0m [397]	train-mlogloss:1.57385	validation-mlogloss:1.53457
[36m(train_xgb_ray_tune pid=1371782)[0m [333]	train-mlogloss:1.45666	validation-mlogloss:1.47080
[36m(train_xgb_ray_tune pid=1371781)[0m [492]	train-mlogloss:1.88078	validation-mlogloss:1.85229
[36m(train_xgb_ray_tune pid=1371796)[0m [521]	train-mlogloss:2.22826	validation-mlogloss:2.21071
[36m(train_xgb_ray_tune pid=1371795)[0m [396]	train-mlogloss:1.33953	validation-mlogloss:1.31423
[36m(train_xgb_ray_tune pid=1371754)[0m [361]	train-mlogloss:1.55641	validation-mlogloss:1.54362
[36m(train_xgb_ray_tune pid=1371762)[0m [385]	train-mlogloss:1.53100	validation-mlogloss:1.52926
[36m(train_xgb_ray_tune pid=1371794)[0m [498]	train-mlogloss:1.63941	validation-mlogloss:1.60537
[36m(train_xgb_ray_tune pid=1371761)[0m [428]	train-mlogloss:1.87540	validation-mlogloss:1.84230
[36m(train_xgb_ray_tune pid=1371754)[0m [362]	train-mlogloss:1.55536	validation-mlogloss:1.54253
[36m(train_xgb_ray_tune pid=1371761)[0m [429]	train-mlogloss:1.87512	validation-mlogloss:1.84201
[36m(train_xgb_ray_tune pid=1371761)[0m [430]	train-mlogloss:1.87467	validation-mlogloss:1.84152
[36m(train_xgb_ray_tune pid=1371781)[0m [493]	train-mlogloss:1.88067	validation-mlogloss:1.85217
[36m(train_xgb_ray_tune pid=1371781)[0m [494]	train-mlogloss:1.88067	validation-mlogloss:1.85217
[36m(train_xgb_ray_tune pid=1371781)[0m [495]	train-mlogloss:1.88067	validation-mlogloss:1.85217
[36m(train_xgb_ray_tune pid=1371781)[0m [496]	train-mlogloss:1.88067	validation-mlogloss:1.85217
[36m(train_xgb_ray_tune pid=1371786)[0m [408]	train-mlogloss:1.34425	validation-mlogloss:1.33360
[36m(train_xgb_ray_tune pid=1371786)[0m [409]	train-mlogloss:1.34352	validation-mlogloss:1.33296
[36m(train_xgb_ray_tune pid=1371786)[0m [410]	train-mlogloss:1.34276	validation-mlogloss:1.33220
[36m(train_xgb_ray_tune pid=1371796)[0m [522]	train-mlogloss:2.22826	validation-mlogloss:2.21071
[36m(train_xgb_ray_tune pid=1371796)[0m [523]	train-mlogloss:2.22826	validation-mlogloss:2.21071
[36m(train_xgb_ray_tune pid=1371796)[0m [524]	train-mlogloss:2.22811	validation-mlogloss:2.21059
[36m(train_xgb_ray_tune pid=1371796)[0m [525]	train-mlogloss:2.22811	validation-mlogloss:2.21059
[36m(train_xgb_ray_tune pid=1371793)[0m [404]	train-mlogloss:1.45153	validation-mlogloss:1.41931
[36m(train_xgb_ray_tune pid=1371793)[0m [405]	train-mlogloss:1.45081	validation-mlogloss:1.41851
[36m(train_xgb_ray_tune pid=1371762)[0m [386]	train-mlogloss:1.52997	validation-mlogloss:1.52820
[36m(train_xgb_ray_tune pid=1371762)[0m [387]	train-mlogloss:1.52898	validation-mlogloss:1.52710
[36m(train_xgb_ray_tune pid=1371762)[0m [388]	train-mlogloss:1.52802	validation-mlogloss:1.52607
[36m(train_xgb_ray_tune pid=1371795)[0m [397]	train-mlogloss:1.33949	validation-mlogloss:1.31421
[36m(train_xgb_ray_tune pid=1371795)[0m [398]	train-mlogloss:1.33949	validation-mlogloss:1.31421
[36m(train_xgb_ray_tune pid=1371795)[0m [399]	train-mlogloss:1.33949	validation-mlogloss:1.31421
[36m(train_xgb_ray_tune pid=1371795)[0m [400]	train-mlogloss:1.33949	validation-mlogloss:1.31421
[36m(train_xgb_ray_tune pid=1371782)[0m [334]	train-mlogloss:1.45550	validation-mlogloss:1.46958
[36m(train_xgb_ray_tune pid=1371783)[0m [411]	train-mlogloss:1.46603	validation-mlogloss:1.43906
[36m(train_xgb_ray_tune pid=1371783)[0m [412]	train-mlogloss:1.46575	validation-mlogloss:1.43877
[36m(train_xgb_ray_tune pid=1371794)[0m [499]	train-mlogloss:1.63936	validation-mlogloss:1.60532
[36m(train_xgb_ray_tune pid=1371794)[0m [500]	train-mlogloss:1.63932	validation-mlogloss:1.60528
[36m(train_xgb_ray_tune pid=1371794)[0m [501]	train-mlogloss:1.63919	validation-mlogloss:1.60512
[36m(train_xgb_ray_tune pid=1371794)[0m [502]	train-mlogloss:1.63904	validation-mlogloss:1.60497
[36m(train_xgb_ray_tune pid=1371766)[0m [398]	train-mlogloss:1.57310	validation-mlogloss:1.53378
[36m(train_xgb_ray_tune pid=1371766)[0m [399]	train-mlogloss:1.57224	validation-mlogloss:1.53286

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:04:59. Total running time: 37s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             34.3416 │
│ time_total_s                 34.3416 │
│ training_iteration                 1 │
│ validation_accuracy          0.51835 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:04:59. Total running time: 37s
[36m(train_xgb_ray_tune pid=1371754)[0m [363]	train-mlogloss:1.55432	validation-mlogloss:1.54147
[36m(train_xgb_ray_tune pid=1371754)[0m [364]	train-mlogloss:1.55328	validation-mlogloss:1.54034
[36m(train_xgb_ray_tune pid=1371754)[0m [365]	train-mlogloss:1.55237	validation-mlogloss:1.53927
[36m(train_xgb_ray_tune pid=1371761)[0m [431]	train-mlogloss:1.87409	validation-mlogloss:1.84089
[36m(train_xgb_ray_tune pid=1371761)[0m [432]	train-mlogloss:1.87380	validation-mlogloss:1.84062
[36m(train_xgb_ray_tune pid=1371781)[0m [497]	train-mlogloss:1.88056	validation-mlogloss:1.85204
[36m(train_xgb_ray_tune pid=1371781)[0m [498]	train-mlogloss:1.88056	validation-mlogloss:1.85204
[36m(train_xgb_ray_tune pid=1371781)[0m [499]	train-mlogloss:1.88056	validation-mlogloss:1.85204
[36m(train_xgb_ray_tune pid=1371781)[0m [500]	train-mlogloss:1.88056	validation-mlogloss:1.85204
[36m(train_xgb_ray_tune pid=1371786)[0m [411]	train-mlogloss:1.34200	validation-mlogloss:1.33149
[36m(train_xgb_ray_tune pid=1371786)[0m [412]	train-mlogloss:1.34125	validation-mlogloss:1.33082
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[36m(train_xgb_ray_tune pid=1371796)[0m [526]	train-mlogloss:2.22811	validation-mlogloss:2.21059
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[36m(train_xgb_ray_tune pid=1371794)[0m [523]	train-mlogloss:1.63799	validation-mlogloss:1.60382
[36m(train_xgb_ray_tune pid=1371794)[0m [524]	train-mlogloss:1.63799	validation-mlogloss:1.60382
[36m(train_xgb_ray_tune pid=1371794)[0m [525]	train-mlogloss:1.63787	validation-mlogloss:1.60368
[36m(train_xgb_ray_tune pid=1371794)[0m [526]	train-mlogloss:1.63787	validation-mlogloss:1.60368
[36m(train_xgb_ray_tune pid=1371794)[0m [527]	train-mlogloss:1.63778	validation-mlogloss:1.60356
[36m(train_xgb_ray_tune pid=1371786)[0m [426]	train-mlogloss:1.33095	validation-mlogloss:1.32067
[36m(train_xgb_ray_tune pid=1371793)[0m [415]	train-mlogloss:1.44426	validation-mlogloss:1.41189
[36m(train_xgb_ray_tune pid=1371781)[0m [521]	train-mlogloss:1.88024	validation-mlogloss:1.85163
[36m(train_xgb_ray_tune pid=1371795)[0m [425]	train-mlogloss:1.33865	validation-mlogloss:1.31349
[36m(train_xgb_ray_tune pid=1371761)[0m [442]	train-mlogloss:1.86963	validation-mlogloss:1.83629
[36m(train_xgb_ray_tune pid=1371783)[0m [424]	train-mlogloss:1.46180	validation-mlogloss:1.43459
[36m(train_xgb_ray_tune pid=1371794)[0m [528]	train-mlogloss:1.63778	validation-mlogloss:1.60356
[36m(train_xgb_ray_tune pid=1371754)[0m [378]	train-mlogloss:1.53965	validation-mlogloss:1.52555

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:00. Total running time: 37s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             35.0071 │
│ time_total_s                 35.0071 │
│ training_iteration                 1 │
│ validation_accuracy           0.4859 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:00. Total running time: 37s
[36m(train_xgb_ray_tune pid=1371754)[0m [379]	train-mlogloss:1.53872	validation-mlogloss:1.52458
[36m(train_xgb_ray_tune pid=1371754)[0m [380]	train-mlogloss:1.53775	validation-mlogloss:1.52351
[36m(train_xgb_ray_tune pid=1371761)[0m [443]	train-mlogloss:1.86921	validation-mlogloss:1.83589
[36m(train_xgb_ray_tune pid=1371761)[0m [444]	train-mlogloss:1.86875	validation-mlogloss:1.83541
[36m(train_xgb_ray_tune pid=1371781)[0m [522]	train-mlogloss:1.88014	validation-mlogloss:1.85152
[36m(train_xgb_ray_tune pid=1371781)[0m [523]	train-mlogloss:1.88014	validation-mlogloss:1.85152
[36m(train_xgb_ray_tune pid=1371781)[0m [524]	train-mlogloss:1.88014	validation-mlogloss:1.85152
[36m(train_xgb_ray_tune pid=1371781)[0m [525]	train-mlogloss:1.88014	validation-mlogloss:1.85152
[36m(train_xgb_ray_tune pid=1371786)[0m [427]	train-mlogloss:1.33026	validation-mlogloss:1.32007
[36m(train_xgb_ray_tune pid=1371786)[0m [428]	train-mlogloss:1.32950	validation-mlogloss:1.31936
[36m(train_xgb_ray_tune pid=1371786)[0m [429]	train-mlogloss:1.32880	validation-mlogloss:1.31875
[36m(train_xgb_ray_tune pid=1371796)[0m [548]	train-mlogloss:2.22610	validation-mlogloss:2.20851
[36m(train_xgb_ray_tune pid=1371796)[0m [549]	train-mlogloss:2.22610	validation-mlogloss:2.20851
[36m(train_xgb_ray_tune pid=1371796)[0m [550]	train-mlogloss:2.22601	validation-mlogloss:2.20845
[36m(train_xgb_ray_tune pid=1371796)[0m [551]	train-mlogloss:2.22563	validation-mlogloss:2.20805
[36m(train_xgb_ray_tune pid=1371793)[0m [416]	train-mlogloss:1.44356	validation-mlogloss:1.41122
[36m(train_xgb_ray_tune pid=1371793)[0m [417]	train-mlogloss:1.44286	validation-mlogloss:1.41054
[36m(train_xgb_ray_tune pid=1371762)[0m [405]	train-mlogloss:1.51178	validation-mlogloss:1.50881
[36m(train_xgb_ray_tune pid=1371762)[0m [406]	train-mlogloss:1.51088	validation-mlogloss:1.50791
[36m(train_xgb_ray_tune pid=1371762)[0m [407]	train-mlogloss:1.50988	validation-mlogloss:1.50686
[36m(train_xgb_ray_tune pid=1371795)[0m [426]	train-mlogloss:1.33861	validation-mlogloss:1.31349
[36m(train_xgb_ray_tune pid=1371795)[0m [427]	train-mlogloss:1.33857	validation-mlogloss:1.31351
[36m(train_xgb_ray_tune pid=1371795)[0m [428]	train-mlogloss:1.33849	validation-mlogloss:1.31346
[36m(train_xgb_ray_tune pid=1371766)[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 4x across cluster][0m
[36m(train_xgb_ray_tune pid=1371766)[0m   _log_deprecation_warning([32m [repeated 4x across cluster][0m
[36m(train_xgb_ray_tune pid=1371795)[0m [429]	train-mlogloss:1.33849	validation-mlogloss:1.31345
[36m(train_xgb_ray_tune pid=1371782)[0m [344]	train-mlogloss:1.44382	validation-mlogloss:1.45786
[36m(train_xgb_ray_tune pid=1371783)[0m [425]	train-mlogloss:1.46133	validation-mlogloss:1.43405
[36m(train_xgb_ray_tune pid=1371783)[0m [426]	train-mlogloss:1.46093	validation-mlogloss:1.43360
[36m(train_xgb_ray_tune pid=1371794)[0m [529]	train-mlogloss:1.63765	validation-mlogloss:1.60343
[36m(train_xgb_ray_tune pid=1371794)[0m [530]	train-mlogloss:1.63765	validation-mlogloss:1.60343
[36m(train_xgb_ray_tune pid=1371794)[0m [531]	train-mlogloss:1.63765	validation-mlogloss:1.60343
[36m(train_xgb_ray_tune pid=1371794)[0m [532]	train-mlogloss:1.63760	validation-mlogloss:1.60338
[36m(train_xgb_ray_tune pid=1371781)[0m [526]	train-mlogloss:1.88014	validation-mlogloss:1.85152
[36m(train_xgb_ray_tune pid=1371796)[0m [552]	train-mlogloss:2.22555	validation-mlogloss:2.20800
[36m(train_xgb_ray_tune pid=1371795)[0m [430]	train-mlogloss:1.33840	validation-mlogloss:1.31338
[36m(train_xgb_ray_tune pid=1371782)[0m [345]	train-mlogloss:1.44265	validation-mlogloss:1.45661
[36m(train_xgb_ray_tune pid=1371794)[0m [533]	train-mlogloss:1.63760	validation-mlogloss:1.60338
[36m(train_xgb_ray_tune pid=1371754)[0m [381]	train-mlogloss:1.53685	validation-mlogloss:1.52256
[36m(train_xgb_ray_tune pid=1371762)[0m [408]	train-mlogloss:1.50901	validation-mlogloss:1.50598
[36m(train_xgb_ray_tune pid=1371754)[0m [382]	train-mlogloss:1.53590	validation-mlogloss:1.52159
[36m(train_xgb_ray_tune pid=1371754)[0m [383]	train-mlogloss:1.53483	validation-mlogloss:1.52047
[36m(train_xgb_ray_tune pid=1371761)[0m [445]	train-mlogloss:1.86838	validation-mlogloss:1.83506
[36m(train_xgb_ray_tune pid=1371761)[0m [446]	train-mlogloss:1.86792	validation-mlogloss:1.83457
[36m(train_xgb_ray_tune pid=1371761)[0m [447]	train-mlogloss:1.86759	validation-mlogloss:1.83422
[36m(train_xgb_ray_tune pid=1371761)[0m [448]	train-mlogloss:1.86727	validation-mlogloss:1.83387
[36m(train_xgb_ray_tune pid=1371781)[0m [527]	train-mlogloss:1.88004	validation-mlogloss:1.85145
[36m(train_xgb_ray_tune pid=1371781)[0m [528]	train-mlogloss:1.87993	validation-mlogloss:1.85132
[36m(train_xgb_ray_tune pid=1371781)[0m [529]	train-mlogloss:1.87993	validation-mlogloss:1.85132
[36m(train_xgb_ray_tune pid=1371781)[0m [530]	train-mlogloss:1.87993	validation-mlogloss:1.85132
[36m(train_xgb_ray_tune pid=1371781)[0m [531]	train-mlogloss:1.87966	validation-mlogloss:1.85101
[36m(train_xgb_ray_tune pid=1371786)[0m [430]	train-mlogloss:1.32810	validation-mlogloss:1.31816
[36m(train_xgb_ray_tune pid=1371786)[0m [431]	train-mlogloss:1.32742	validation-mlogloss:1.31749
[36m(train_xgb_ray_tune pid=1371786)[0m [432]	train-mlogloss:1.32665	validation-mlogloss:1.31663
[36m(train_xgb_ray_tune pid=1371796)[0m [553]	train-mlogloss:2.22555	validation-mlogloss:2.20800
[36m(train_xgb_ray_tune pid=1371796)[0m [554]	train-mlogloss:2.22555	validation-mlogloss:2.20800
[36m(train_xgb_ray_tune pid=1371796)[0m [555]	train-mlogloss:2.22543	validation-mlogloss:2.20787
[36m(train_xgb_ray_tune pid=1371796)[0m [556]	train-mlogloss:2.22535	validation-mlogloss:2.20781
[36m(train_xgb_ray_tune pid=1371793)[0m [418]	train-mlogloss:1.44226	validation-mlogloss:1.40993
[36m(train_xgb_ray_tune pid=1371793)[0m [419]	train-mlogloss:1.44164	validation-mlogloss:1.40924
[36m(train_xgb_ray_tune pid=1371762)[0m [409]	train-mlogloss:1.50808	validation-mlogloss:1.50499
[36m(train_xgb_ray_tune pid=1371762)[0m [410]	train-mlogloss:1.50717	validation-mlogloss:1.50400
[36m(train_xgb_ray_tune pid=1371762)[0m [411]	train-mlogloss:1.50625	validation-mlogloss:1.50297
[36m(train_xgb_ray_tune pid=1371795)[0m [431]	train-mlogloss:1.33840	validation-mlogloss:1.31337
[36m(train_xgb_ray_tune pid=1371795)[0m [432]	train-mlogloss:1.33840	validation-mlogloss:1.31337
[36m(train_xgb_ray_tune pid=1371795)[0m [433]	train-mlogloss:1.33840	validation-mlogloss:1.31337
[36m(train_xgb_ray_tune pid=1371795)[0m [434]	train-mlogloss:1.33840	validation-mlogloss:1.31337
[36m(train_xgb_ray_tune pid=1371782)[0m [346]	train-mlogloss:1.44147	validation-mlogloss:1.45538
[36m(train_xgb_ray_tune pid=1371782)[0m [347]	train-mlogloss:1.44039	validation-mlogloss:1.45429
[36m(train_xgb_ray_tune pid=1371783)[0m [427]	train-mlogloss:1.46055	validation-mlogloss:1.43321
[36m(train_xgb_ray_tune pid=1371783)[0m [428]	train-mlogloss:1.46023	validation-mlogloss:1.43290
[36m(train_xgb_ray_tune pid=1371794)[0m [534]	train-mlogloss:1.63760	validation-mlogloss:1.60338
[36m(train_xgb_ray_tune pid=1371794)[0m [535]	train-mlogloss:1.63756	validation-mlogloss:1.60333
[36m(train_xgb_ray_tune pid=1371794)[0m [536]	train-mlogloss:1.63756	validation-mlogloss:1.60333
[36m(train_xgb_ray_tune pid=1371794)[0m [537]	train-mlogloss:1.63756	validation-mlogloss:1.60333
[36m(train_xgb_ray_tune pid=1371796)[0m [557]	train-mlogloss:2.22528	validation-mlogloss:2.20773
[36m(train_xgb_ray_tune pid=1371782)[0m [348]	train-mlogloss:1.43926	validation-mlogloss:1.45313
[36m(train_xgb_ray_tune pid=1371794)[0m [538]	train-mlogloss:1.63756	validation-mlogloss:1.60333
[36m(train_xgb_ray_tune pid=1371754)[0m [384]	train-mlogloss:1.53395	validation-mlogloss:1.51956
[36m(train_xgb_ray_tune pid=1371795)[0m [435]	train-mlogloss:1.33830	validation-mlogloss:1.31326
[36m(train_xgb_ray_tune pid=1371761)[0m [449]	train-mlogloss:1.86694	validation-mlogloss:1.83351
[36m(train_xgb_ray_tune pid=1371754)[0m [385]	train-mlogloss:1.53305	validation-mlogloss:1.51860
[36m(train_xgb_ray_tune pid=1371754)[0m [386]	train-mlogloss:1.53218	validation-mlogloss:1.51769
[36m(train_xgb_ray_tune pid=1371761)[0m [450]	train-mlogloss:1.86662	validation-mlogloss:1.83316
[36m(train_xgb_ray_tune pid=1371761)[0m [451]	train-mlogloss:1.86644	validation-mlogloss:1.83298
[36m(train_xgb_ray_tune pid=1371761)[0m [452]	train-mlogloss:1.86593	validation-mlogloss:1.83246
[36m(train_xgb_ray_tune pid=1371781)[0m [532]	train-mlogloss:1.87966	validation-mlogloss:1.85101
[36m(train_xgb_ray_tune pid=1371781)[0m [533]	train-mlogloss:1.87966	validation-mlogloss:1.85101
[36m(train_xgb_ray_tune pid=1371781)[0m [534]	train-mlogloss:1.87956	validation-mlogloss:1.85091
[36m(train_xgb_ray_tune pid=1371781)[0m [535]	train-mlogloss:1.87956	validation-mlogloss:1.85091
[36m(train_xgb_ray_tune pid=1371786)[0m [433]	train-mlogloss:1.32595	validation-mlogloss:1.31594
[36m(train_xgb_ray_tune pid=1371786)[0m [434]	train-mlogloss:1.32521	validation-mlogloss:1.31521
[36m(train_xgb_ray_tune pid=1371786)[0m [435]	train-mlogloss:1.32452	validation-mlogloss:1.31459
[36m(train_xgb_ray_tune pid=1371796)[0m [558]	train-mlogloss:2.22519	validation-mlogloss:2.20768
[36m(train_xgb_ray_tune pid=1371796)[0m [559]	train-mlogloss:2.22519	validation-mlogloss:2.20768
[36m(train_xgb_ray_tune pid=1371796)[0m [560]	train-mlogloss:2.22519	validation-mlogloss:2.20768
[36m(train_xgb_ray_tune pid=1371796)[0m [561]	train-mlogloss:2.22519	validation-mlogloss:2.20768
[36m(train_xgb_ray_tune pid=1371793)[0m [420]	train-mlogloss:1.44096	validation-mlogloss:1.40851
[36m(train_xgb_ray_tune pid=1371793)[0m [421]	train-mlogloss:1.44031	validation-mlogloss:1.40790
[36m(train_xgb_ray_tune pid=1371762)[0m [412]	train-mlogloss:1.50538	validation-mlogloss:1.50203
[36m(train_xgb_ray_tune pid=1371762)[0m [413]	train-mlogloss:1.50450	validation-mlogloss:1.50111
[36m(train_xgb_ray_tune pid=1371762)[0m [414]	train-mlogloss:1.50355	validation-mlogloss:1.50003
[36m(train_xgb_ray_tune pid=1371795)[0m [436]	train-mlogloss:1.33826	validation-mlogloss:1.31321
[36m(train_xgb_ray_tune pid=1371795)[0m [437]	train-mlogloss:1.33826	validation-mlogloss:1.31321
[36m(train_xgb_ray_tune pid=1371795)[0m [438]	train-mlogloss:1.33826	validation-mlogloss:1.31321
[36m(train_xgb_ray_tune pid=1371795)[0m [439]	train-mlogloss:1.33826	validation-mlogloss:1.31321
[36m(train_xgb_ray_tune pid=1371782)[0m [349]	train-mlogloss:1.43817	validation-mlogloss:1.45202
[36m(train_xgb_ray_tune pid=1371782)[0m [350]	train-mlogloss:1.43706	validation-mlogloss:1.45087
[36m(train_xgb_ray_tune pid=1371782)[0m [351]	train-mlogloss:1.43593	validation-mlogloss:1.44967
[36m(train_xgb_ray_tune pid=1371783)[0m [429]	train-mlogloss:1.45993	validation-mlogloss:1.43259
[36m(train_xgb_ray_tune pid=1371783)[0m [430]	train-mlogloss:1.45961	validation-mlogloss:1.43223
[36m(train_xgb_ray_tune pid=1371794)[0m [539]	train-mlogloss:1.63756	validation-mlogloss:1.60333
[36m(train_xgb_ray_tune pid=1371794)[0m [540]	train-mlogloss:1.63752	validation-mlogloss:1.60327
[36m(train_xgb_ray_tune pid=1371794)[0m [541]	train-mlogloss:1.63752	validation-mlogloss:1.60327
[36m(train_xgb_ray_tune pid=1371794)[0m [542]	train-mlogloss:1.63752	validation-mlogloss:1.60327
[36m(train_xgb_ray_tune pid=1371794)[0m [543]	train-mlogloss:1.63747	validation-mlogloss:1.60323
[36m(train_xgb_ray_tune pid=1371754)[0m [387]	train-mlogloss:1.53129	validation-mlogloss:1.51672
[36m(train_xgb_ray_tune pid=1371761)[0m [453]	train-mlogloss:1.86566	validation-mlogloss:1.83218
[36m(train_xgb_ray_tune pid=1371781)[0m [536]	train-mlogloss:1.87956	validation-mlogloss:1.85091
[36m(train_xgb_ray_tune pid=1371783)[0m [431]	train-mlogloss:1.45927	validation-mlogloss:1.43184
[36m(train_xgb_ray_tune pid=1371754)[0m [388]	train-mlogloss:1.53043	validation-mlogloss:1.51579
[36m(train_xgb_ray_tune pid=1371754)[0m [389]	train-mlogloss:1.52948	validation-mlogloss:1.51474
[36m(train_xgb_ray_tune pid=1371761)[0m [454]	train-mlogloss:1.86518	validation-mlogloss:1.83166
[36m(train_xgb_ray_tune pid=1371761)[0m [455]	train-mlogloss:1.86496	validation-mlogloss:1.83143
[36m(train_xgb_ray_tune pid=1371761)[0m [456]	train-mlogloss:1.86446	validation-mlogloss:1.83090
[36m(train_xgb_ray_tune pid=1371761)[0m [457]	train-mlogloss:1.86419	validation-mlogloss:1.83060
[36m(train_xgb_ray_tune pid=1371781)[0m [537]	train-mlogloss:1.87945	validation-mlogloss:1.85085
[36m(train_xgb_ray_tune pid=1371781)[0m [538]	train-mlogloss:1.87945	validation-mlogloss:1.85085
[36m(train_xgb_ray_tune pid=1371781)[0m [539]	train-mlogloss:1.87945	validation-mlogloss:1.85085
[36m(train_xgb_ray_tune pid=1371781)[0m [540]	train-mlogloss:1.87945	validation-mlogloss:1.85085
[36m(train_xgb_ray_tune pid=1371786)[0m [436]	train-mlogloss:1.32384	validation-mlogloss:1.31392
[36m(train_xgb_ray_tune pid=1371786)[0m [437]	train-mlogloss:1.32316	validation-mlogloss:1.31328
[36m(train_xgb_ray_tune pid=1371786)[0m [438]	train-mlogloss:1.32250	validation-mlogloss:1.31264
[36m(train_xgb_ray_tune pid=1371796)[0m [562]	train-mlogloss:2.22519	validation-mlogloss:2.20768
[36m(train_xgb_ray_tune pid=1371796)[0m [563]	train-mlogloss:2.22512	validation-mlogloss:2.20761
[36m(train_xgb_ray_tune pid=1371793)[0m [422]	train-mlogloss:1.43972	validation-mlogloss:1.40730
[36m(train_xgb_ray_tune pid=1371793)[0m [423]	train-mlogloss:1.43900	validation-mlogloss:1.40660
[36m(train_xgb_ray_tune pid=1371762)[0m [415]	train-mlogloss:1.50267	validation-mlogloss:1.49908
[36m(train_xgb_ray_tune pid=1371762)[0m [416]	train-mlogloss:1.50186	validation-mlogloss:1.49825
[36m(train_xgb_ray_tune pid=1371762)[0m [417]	train-mlogloss:1.50104	validation-mlogloss:1.49740
[36m(train_xgb_ray_tune pid=1371795)[0m [440]	train-mlogloss:1.33826	validation-mlogloss:1.31321
[36m(train_xgb_ray_tune pid=1371795)[0m [441]	train-mlogloss:1.33822	validation-mlogloss:1.31319
[36m(train_xgb_ray_tune pid=1371795)[0m [442]	train-mlogloss:1.33822	validation-mlogloss:1.31318
[36m(train_xgb_ray_tune pid=1371795)[0m [443]	train-mlogloss:1.33818	validation-mlogloss:1.31311
[36m(train_xgb_ray_tune pid=1371795)[0m [444]	train-mlogloss:1.33818	validation-mlogloss:1.31311
[36m(train_xgb_ray_tune pid=1371782)[0m [352]	train-mlogloss:1.43483	validation-mlogloss:1.44849
[36m(train_xgb_ray_tune pid=1371782)[0m [353]	train-mlogloss:1.43367	validation-mlogloss:1.44738
[36m(train_xgb_ray_tune pid=1371782)[0m [354]	train-mlogloss:1.43258	validation-mlogloss:1.44630
[36m(train_xgb_ray_tune pid=1371783)[0m [432]	train-mlogloss:1.45900	validation-mlogloss:1.43153
[36m(train_xgb_ray_tune pid=1371783)[0m [433]	train-mlogloss:1.45873	validation-mlogloss:1.43124
[36m(train_xgb_ray_tune pid=1371794)[0m [544]	train-mlogloss:1.63747	validation-mlogloss:1.60323
[36m(train_xgb_ray_tune pid=1371794)[0m [545]	train-mlogloss:1.63735	validation-mlogloss:1.60312
[36m(train_xgb_ray_tune pid=1371794)[0m [546]	train-mlogloss:1.63717	validation-mlogloss:1.60293
[36m(train_xgb_ray_tune pid=1371794)[0m [547]	train-mlogloss:1.63712	validation-mlogloss:1.60288
[36m(train_xgb_ray_tune pid=1371794)[0m [548]	train-mlogloss:1.63708	validation-mlogloss:1.60284
[36m(train_xgb_ray_tune pid=1371754)[0m [390]	train-mlogloss:1.52862	validation-mlogloss:1.51379
[36m(train_xgb_ray_tune pid=1371781)[0m [541]	train-mlogloss:1.87945	validation-mlogloss:1.85085
[36m(train_xgb_ray_tune pid=1371754)[0m [391]	train-mlogloss:1.52771	validation-mlogloss:1.51284
[36m(train_xgb_ray_tune pid=1371754)[0m [392]	train-mlogloss:1.52676	validation-mlogloss:1.51181
[36m(train_xgb_ray_tune pid=1371761)[0m [458]	train-mlogloss:1.86377	validation-mlogloss:1.83017
[36m(train_xgb_ray_tune pid=1371761)[0m [459]	train-mlogloss:1.86359	validation-mlogloss:1.83001
[36m(train_xgb_ray_tune pid=1371761)[0m [460]	train-mlogloss:1.86324	validation-mlogloss:1.82963
[36m(train_xgb_ray_tune pid=1371761)[0m [461]	train-mlogloss:1.86292	validation-mlogloss:1.82928
[36m(train_xgb_ray_tune pid=1371781)[0m [542]	train-mlogloss:1.87945	validation-mlogloss:1.85085
[36m(train_xgb_ray_tune pid=1371781)[0m [543]	train-mlogloss:1.87945	validation-mlogloss:1.85085
[36m(train_xgb_ray_tune pid=1371781)[0m [544]	train-mlogloss:1.87945	validation-mlogloss:1.85085
[36m(train_xgb_ray_tune pid=1371781)[0m [545]	train-mlogloss:1.87945	validation-mlogloss:1.85085
[36m(train_xgb_ray_tune pid=1371786)[0m [439]	train-mlogloss:1.32175	validation-mlogloss:1.31195
[36m(train_xgb_ray_tune pid=1371786)[0m [440]	train-mlogloss:1.32107	validation-mlogloss:1.31138
[36m(train_xgb_ray_tune pid=1371786)[0m [441]	train-mlogloss:1.32039	validation-mlogloss:1.31072
[36m(train_xgb_ray_tune pid=1371793)[0m [424]	train-mlogloss:1.43833	validation-mlogloss:1.40592
[36m(train_xgb_ray_tune pid=1371793)[0m [425]	train-mlogloss:1.43774	validation-mlogloss:1.40533
[36m(train_xgb_ray_tune pid=1371762)[0m [418]	train-mlogloss:1.50007	validation-mlogloss:1.49635
[36m(train_xgb_ray_tune pid=1371762)[0m [419]	train-mlogloss:1.49918	validation-mlogloss:1.49542
[36m(train_xgb_ray_tune pid=1371762)[0m [420]	train-mlogloss:1.49823	validation-mlogloss:1.49448
[36m(train_xgb_ray_tune pid=1371795)[0m [445]	train-mlogloss:1.33817	validation-mlogloss:1.31311
[36m(train_xgb_ray_tune pid=1371795)[0m [446]	train-mlogloss:1.33817	validation-mlogloss:1.31311
[36m(train_xgb_ray_tune pid=1371795)[0m [447]	train-mlogloss:1.33817	validation-mlogloss:1.31311
[36m(train_xgb_ray_tune pid=1371795)[0m [448]	train-mlogloss:1.33817	validation-mlogloss:1.31311
[36m(train_xgb_ray_tune pid=1371795)[0m [449]	train-mlogloss:1.33813	validation-mlogloss:1.31306
[36m(train_xgb_ray_tune pid=1371782)[0m [355]	train-mlogloss:1.43151	validation-mlogloss:1.44516
[36m(train_xgb_ray_tune pid=1371782)[0m [356]	train-mlogloss:1.43045	validation-mlogloss:1.44405
[36m(train_xgb_ray_tune pid=1371782)[0m [357]	train-mlogloss:1.42938	validation-mlogloss:1.44295
[36m(train_xgb_ray_tune pid=1371783)[0m [434]	train-mlogloss:1.45839	validation-mlogloss:1.43091
[36m(train_xgb_ray_tune pid=1371783)[0m [435]	train-mlogloss:1.45806	validation-mlogloss:1.43053
[36m(train_xgb_ray_tune pid=1371794)[0m [549]	train-mlogloss:1.63708	validation-mlogloss:1.60284
[36m(train_xgb_ray_tune pid=1371794)[0m [550]	train-mlogloss:1.63708	validation-mlogloss:1.60284
[36m(train_xgb_ray_tune pid=1371794)[0m [551]	train-mlogloss:1.63708	validation-mlogloss:1.60284
[36m(train_xgb_ray_tune pid=1371794)[0m [552]	train-mlogloss:1.63703	validation-mlogloss:1.60278
[36m(train_xgb_ray_tune pid=1371794)[0m [553]	train-mlogloss:1.63695	validation-mlogloss:1.60267
[36m(train_xgb_ray_tune pid=1371786)[0m [442]	train-mlogloss:1.31974	validation-mlogloss:1.31007
[36m(train_xgb_ray_tune pid=1371754)[0m [393]	train-mlogloss:1.52579	validation-mlogloss:1.51073
[36m(train_xgb_ray_tune pid=1371781)[0m [546]	train-mlogloss:1.87899	validation-mlogloss:1.85036
[36m(train_xgb_ray_tune pid=1371762)[0m [421]	train-mlogloss:1.49733	validation-mlogloss:1.49348
[36m(train_xgb_ray_tune pid=1371754)[0m [394]	train-mlogloss:1.52494	validation-mlogloss:1.50976
[36m(train_xgb_ray_tune pid=1371754)[0m [395]	train-mlogloss:1.52407	validation-mlogloss:1.50882
[36m(train_xgb_ray_tune pid=1371761)[0m [462]	train-mlogloss:1.86251	validation-mlogloss:1.82884
[36m(train_xgb_ray_tune pid=1371761)[0m [463]	train-mlogloss:1.86219	validation-mlogloss:1.82853
[36m(train_xgb_ray_tune pid=1371761)[0m [464]	train-mlogloss:1.86193	validation-mlogloss:1.82825
[36m(train_xgb_ray_tune pid=1371761)[0m [465]	train-mlogloss:1.86160	validation-mlogloss:1.82790
[36m(train_xgb_ray_tune pid=1371781)[0m [547]	train-mlogloss:1.87889	validation-mlogloss:1.85025
[36m(train_xgb_ray_tune pid=1371781)[0m [548]	train-mlogloss:1.87867	validation-mlogloss:1.85001
[36m(train_xgb_ray_tune pid=1371781)[0m [549]	train-mlogloss:1.87867	validation-mlogloss:1.85001
[36m(train_xgb_ray_tune pid=1371781)[0m [550]	train-mlogloss:1.87867	validation-mlogloss:1.85001
[36m(train_xgb_ray_tune pid=1371786)[0m [443]	train-mlogloss:1.31906	validation-mlogloss:1.30942
[36m(train_xgb_ray_tune pid=1371786)[0m [444]	train-mlogloss:1.31841	validation-mlogloss:1.30881
[36m(train_xgb_ray_tune pid=1371786)[0m [445]	train-mlogloss:1.31773	validation-mlogloss:1.30817
[36m(train_xgb_ray_tune pid=1371793)[0m [426]	train-mlogloss:1.43714	validation-mlogloss:1.40472
[36m(train_xgb_ray_tune pid=1371762)[0m [422]	train-mlogloss:1.49642	validation-mlogloss:1.49241
[36m(train_xgb_ray_tune pid=1371762)[0m [423]	train-mlogloss:1.49558	validation-mlogloss:1.49153
[36m(train_xgb_ray_tune pid=1371762)[0m [424]	train-mlogloss:1.49479	validation-mlogloss:1.49063
[36m(train_xgb_ray_tune pid=1371795)[0m [450]	train-mlogloss:1.33809	validation-mlogloss:1.31301
[36m(train_xgb_ray_tune pid=1371795)[0m [451]	train-mlogloss:1.33805	validation-mlogloss:1.31301
[36m(train_xgb_ray_tune pid=1371795)[0m [452]	train-mlogloss:1.33787	validation-mlogloss:1.31278
[36m(train_xgb_ray_tune pid=1371795)[0m [453]	train-mlogloss:1.33787	validation-mlogloss:1.31278
[36m(train_xgb_ray_tune pid=1371795)[0m [454]	train-mlogloss:1.33783	validation-mlogloss:1.31273
[36m(train_xgb_ray_tune pid=1371782)[0m [358]	train-mlogloss:1.42829	validation-mlogloss:1.44181
[36m(train_xgb_ray_tune pid=1371782)[0m [359]	train-mlogloss:1.42722	validation-mlogloss:1.44077
[36m(train_xgb_ray_tune pid=1371782)[0m [360]	train-mlogloss:1.42614	validation-mlogloss:1.43968
[36m(train_xgb_ray_tune pid=1371783)[0m [436]	train-mlogloss:1.45774	validation-mlogloss:1.43020
[36m(train_xgb_ray_tune pid=1371783)[0m [437]	train-mlogloss:1.45743	validation-mlogloss:1.42987
[36m(train_xgb_ray_tune pid=1371794)[0m [554]	train-mlogloss:1.63686	validation-mlogloss:1.60261
[36m(train_xgb_ray_tune pid=1371794)[0m [555]	train-mlogloss:1.63686	validation-mlogloss:1.60261
[36m(train_xgb_ray_tune pid=1371794)[0m [556]	train-mlogloss:1.63686	validation-mlogloss:1.60261
[36m(train_xgb_ray_tune pid=1371794)[0m [557]	train-mlogloss:1.63682	validation-mlogloss:1.60256
[36m(train_xgb_ray_tune pid=1371794)[0m [558]	train-mlogloss:1.63673	validation-mlogloss:1.60246
[36m(train_xgb_ray_tune pid=1371754)[0m [396]	train-mlogloss:1.52317	validation-mlogloss:1.50793
[36m(train_xgb_ray_tune pid=1371761)[0m [466]	train-mlogloss:1.86125	validation-mlogloss:1.82753
[36m(train_xgb_ray_tune pid=1371793)[0m [427]	train-mlogloss:1.43650	validation-mlogloss:1.40409
[36m(train_xgb_ray_tune pid=1371781)[0m [551]	train-mlogloss:1.87867	validation-mlogloss:1.85001
[36m(train_xgb_ray_tune pid=1371783)[0m [438]	train-mlogloss:1.45718	validation-mlogloss:1.42961
[36m(train_xgb_ray_tune pid=1371754)[0m [397]	train-mlogloss:1.52233	validation-mlogloss:1.50703
[36m(train_xgb_ray_tune pid=1371754)[0m [398]	train-mlogloss:1.52142	validation-mlogloss:1.50603
[36m(train_xgb_ray_tune pid=1371761)[0m [467]	train-mlogloss:1.86093	validation-mlogloss:1.82721
[36m(train_xgb_ray_tune pid=1371761)[0m [468]	train-mlogloss:1.86068	validation-mlogloss:1.82693
[36m(train_xgb_ray_tune pid=1371761)[0m [469]	train-mlogloss:1.86041	validation-mlogloss:1.82667
[36m(train_xgb_ray_tune pid=1371761)[0m [470]	train-mlogloss:1.86015	validation-mlogloss:1.82638
[36m(train_xgb_ray_tune pid=1371781)[0m [552]	train-mlogloss:1.87867	validation-mlogloss:1.85001
[36m(train_xgb_ray_tune pid=1371781)[0m [553]	train-mlogloss:1.87867	validation-mlogloss:1.85001
[36m(train_xgb_ray_tune pid=1371781)[0m [554]	train-mlogloss:1.87867	validation-mlogloss:1.85001
[36m(train_xgb_ray_tune pid=1371781)[0m [555]	train-mlogloss:1.87867	validation-mlogloss:1.85001
[36m(train_xgb_ray_tune pid=1371786)[0m [446]	train-mlogloss:1.31707	validation-mlogloss:1.30756
[36m(train_xgb_ray_tune pid=1371786)[0m [447]	train-mlogloss:1.31643	validation-mlogloss:1.30697
[36m(train_xgb_ray_tune pid=1371786)[0m [448]	train-mlogloss:1.31582	validation-mlogloss:1.30643
[36m(train_xgb_ray_tune pid=1371793)[0m [428]	train-mlogloss:1.43589	validation-mlogloss:1.40347
[36m(train_xgb_ray_tune pid=1371762)[0m [425]	train-mlogloss:1.49393	validation-mlogloss:1.48980
[36m(train_xgb_ray_tune pid=1371762)[0m [426]	train-mlogloss:1.49316	validation-mlogloss:1.48898
[36m(train_xgb_ray_tune pid=1371762)[0m [427]	train-mlogloss:1.49228	validation-mlogloss:1.48800
[36m(train_xgb_ray_tune pid=1371795)[0m [455]	train-mlogloss:1.33779	validation-mlogloss:1.31268
[36m(train_xgb_ray_tune pid=1371795)[0m [456]	train-mlogloss:1.33775	validation-mlogloss:1.31263
[36m(train_xgb_ray_tune pid=1371795)[0m [457]	train-mlogloss:1.33771	validation-mlogloss:1.31262
[36m(train_xgb_ray_tune pid=1371795)[0m [458]	train-mlogloss:1.33767	validation-mlogloss:1.31262
[36m(train_xgb_ray_tune pid=1371782)[0m [361]	train-mlogloss:1.42513	validation-mlogloss:1.43862
[36m(train_xgb_ray_tune pid=1371782)[0m [362]	train-mlogloss:1.42409	validation-mlogloss:1.43753
[36m(train_xgb_ray_tune pid=1371782)[0m [363]	train-mlogloss:1.42307	validation-mlogloss:1.43647
[36m(train_xgb_ray_tune pid=1371783)[0m [439]	train-mlogloss:1.45687	validation-mlogloss:1.42930
[36m(train_xgb_ray_tune pid=1371783)[0m [440]	train-mlogloss:1.45664	validation-mlogloss:1.42906
[36m(train_xgb_ray_tune pid=1371794)[0m [559]	train-mlogloss:1.63665	validation-mlogloss:1.60237
[36m(train_xgb_ray_tune pid=1371794)[0m [560]	train-mlogloss:1.63665	validation-mlogloss:1.60237
[36m(train_xgb_ray_tune pid=1371794)[0m [561]	train-mlogloss:1.63655	validation-mlogloss:1.60227
[36m(train_xgb_ray_tune pid=1371794)[0m [562]	train-mlogloss:1.63651	validation-mlogloss:1.60221
[36m(train_xgb_ray_tune pid=1371794)[0m [563]	train-mlogloss:1.63651	validation-mlogloss:1.60221
[36m(train_xgb_ray_tune pid=1371754)[0m [399]	train-mlogloss:1.52054	validation-mlogloss:1.50510
[36m(train_xgb_ray_tune pid=1371795)[0m [459]	train-mlogloss:1.33767	validation-mlogloss:1.31262
[36m(train_xgb_ray_tune pid=1371793)[0m [429]	train-mlogloss:1.43528	validation-mlogloss:1.40284
[36m(train_xgb_ray_tune pid=1371781)[0m [556]	train-mlogloss:1.87867	validation-mlogloss:1.85001
[36m(train_xgb_ray_tune pid=1371794)[0m [564]	train-mlogloss:1.63647	validation-mlogloss:1.60220
[36m(train_xgb_ray_tune pid=1371786)[0m [449]	train-mlogloss:1.31517	validation-mlogloss:1.30579
[36m(train_xgb_ray_tune pid=1371754)[0m [400]	train-mlogloss:1.51972	validation-mlogloss:1.50426
[36m(train_xgb_ray_tune pid=1371754)[0m [401]	train-mlogloss:1.51879	validation-mlogloss:1.50322
[36m(train_xgb_ray_tune pid=1371754)[0m [402]	train-mlogloss:1.51800	validation-mlogloss:1.50235
[36m(train_xgb_ray_tune pid=1371761)[0m [471]	train-mlogloss:1.85997	validation-mlogloss:1.82618
[36m(train_xgb_ray_tune pid=1371761)[0m [472]	train-mlogloss:1.85972	validation-mlogloss:1.82596
[36m(train_xgb_ray_tune pid=1371761)[0m [473]	train-mlogloss:1.85937	validation-mlogloss:1.82559
[36m(train_xgb_ray_tune pid=1371761)[0m [474]	train-mlogloss:1.85910	validation-mlogloss:1.82532
[36m(train_xgb_ray_tune pid=1371781)[0m [557]	train-mlogloss:1.87856	validation-mlogloss:1.84988
[36m(train_xgb_ray_tune pid=1371781)[0m [558]	train-mlogloss:1.87856	validation-mlogloss:1.84988
[36m(train_xgb_ray_tune pid=1371781)[0m [559]	train-mlogloss:1.87846	validation-mlogloss:1.84976
[36m(train_xgb_ray_tune pid=1371781)[0m [560]	train-mlogloss:1.87846	validation-mlogloss:1.84976
[36m(train_xgb_ray_tune pid=1371786)[0m [450]	train-mlogloss:1.31453	validation-mlogloss:1.30518
[36m(train_xgb_ray_tune pid=1371786)[0m [451]	train-mlogloss:1.31389	validation-mlogloss:1.30464
[36m(train_xgb_ray_tune pid=1371786)[0m [452]	train-mlogloss:1.31323	validation-mlogloss:1.30397
[36m(train_xgb_ray_tune pid=1371793)[0m [430]	train-mlogloss:1.43467	validation-mlogloss:1.40225
[36m(train_xgb_ray_tune pid=1371793)[0m [431]	train-mlogloss:1.43397	validation-mlogloss:1.40159
[36m(train_xgb_ray_tune pid=1371762)[0m [428]	train-mlogloss:1.49133	validation-mlogloss:1.48699
[36m(train_xgb_ray_tune pid=1371762)[0m [429]	train-mlogloss:1.49045	validation-mlogloss:1.48609
[36m(train_xgb_ray_tune pid=1371762)[0m [430]	train-mlogloss:1.48966	validation-mlogloss:1.48523
[36m(train_xgb_ray_tune pid=1371795)[0m [460]	train-mlogloss:1.33767	validation-mlogloss:1.31262
[36m(train_xgb_ray_tune pid=1371795)[0m [461]	train-mlogloss:1.33767	validation-mlogloss:1.31262
[36m(train_xgb_ray_tune pid=1371795)[0m [462]	train-mlogloss:1.33763	validation-mlogloss:1.31256
[36m(train_xgb_ray_tune pid=1371795)[0m [463]	train-mlogloss:1.33759	validation-mlogloss:1.31250
[36m(train_xgb_ray_tune pid=1371795)[0m [464]	train-mlogloss:1.33755	validation-mlogloss:1.31246
[36m(train_xgb_ray_tune pid=1371782)[0m [364]	train-mlogloss:1.42202	validation-mlogloss:1.43536
[36m(train_xgb_ray_tune pid=1371782)[0m [365]	train-mlogloss:1.42095	validation-mlogloss:1.43419
[36m(train_xgb_ray_tune pid=1371782)[0m [366]	train-mlogloss:1.41991	validation-mlogloss:1.43312
[36m(train_xgb_ray_tune pid=1371783)[0m [441]	train-mlogloss:1.45636	validation-mlogloss:1.42877
[36m(train_xgb_ray_tune pid=1371783)[0m [442]	train-mlogloss:1.45617	validation-mlogloss:1.42856
[36m(train_xgb_ray_tune pid=1371794)[0m [565]	train-mlogloss:1.63643	validation-mlogloss:1.60215
[36m(train_xgb_ray_tune pid=1371794)[0m [566]	train-mlogloss:1.63643	validation-mlogloss:1.60215
[36m(train_xgb_ray_tune pid=1371794)[0m [567]	train-mlogloss:1.63643	validation-mlogloss:1.60215
[36m(train_xgb_ray_tune pid=1371794)[0m [568]	train-mlogloss:1.63634	validation-mlogloss:1.60204
[36m(train_xgb_ray_tune pid=1371761)[0m [475]	train-mlogloss:1.85888	validation-mlogloss:1.82509
[36m(train_xgb_ray_tune pid=1371762)[0m [431]	train-mlogloss:1.48882	validation-mlogloss:1.48432
[36m(train_xgb_ray_tune pid=1371794)[0m [569]	train-mlogloss:1.63634	validation-mlogloss:1.60204
[36m(train_xgb_ray_tune pid=1371781)[0m [561]	train-mlogloss:1.87846	validation-mlogloss:1.84976

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:01. Total running time: 38s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             36.1003 │
│ time_total_s                 36.1003 │
│ training_iteration                 1 │
│ validation_accuracy          0.40191 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:01. Total running time: 39s
[36m(train_xgb_ray_tune pid=1371754)[0m [403]	train-mlogloss:1.51714	validation-mlogloss:1.50143
[36m(train_xgb_ray_tune pid=1371754)[0m [404]	train-mlogloss:1.51640	validation-mlogloss:1.50064
[36m(train_xgb_ray_tune pid=1371754)[0m [405]	train-mlogloss:1.51549	validation-mlogloss:1.49964
[36m(train_xgb_ray_tune pid=1371761)[0m [476]	train-mlogloss:1.85862	validation-mlogloss:1.82481
[36m(train_xgb_ray_tune pid=1371761)[0m [477]	train-mlogloss:1.85827	validation-mlogloss:1.82445
[36m(train_xgb_ray_tune pid=1371761)[0m [478]	train-mlogloss:1.85811	validation-mlogloss:1.82428
[36m(train_xgb_ray_tune pid=1371761)[0m [479]	train-mlogloss:1.85799	validation-mlogloss:1.82417
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[36m(train_xgb_ray_tune pid=1371781)[0m [563]	train-mlogloss:1.87846	validation-mlogloss:1.84976
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[36m(train_xgb_ray_tune pid=1371795)[0m [488]	train-mlogloss:1.33701	validation-mlogloss:1.31200
[36m(train_xgb_ray_tune pid=1371795)[0m [489]	train-mlogloss:1.33701	validation-mlogloss:1.31200
[36m(train_xgb_ray_tune pid=1371782)[0m [380]	train-mlogloss:1.40620	validation-mlogloss:1.41881
[36m(train_xgb_ray_tune pid=1371782)[0m [381]	train-mlogloss:1.40526	validation-mlogloss:1.41780
[36m(train_xgb_ray_tune pid=1371782)[0m [382]	train-mlogloss:1.40431	validation-mlogloss:1.41679
[36m(train_xgb_ray_tune pid=1371783)[0m [460]	train-mlogloss:1.45170	validation-mlogloss:1.42397
[36m(train_xgb_ray_tune pid=1371783)[0m [461]	train-mlogloss:1.45141	validation-mlogloss:1.42366
[36m(train_xgb_ray_tune pid=1371783)[0m [462]	train-mlogloss:1.45123	validation-mlogloss:1.42347
[36m(train_xgb_ray_tune pid=1371783)[0m [463]	train-mlogloss:1.45106	validation-mlogloss:1.42333
[36m(train_xgb_ray_tune pid=1371794)[0m [591]	train-mlogloss:1.63574	validation-mlogloss:1.60140
[36m(train_xgb_ray_tune pid=1371794)[0m [592]	train-mlogloss:1.63574	validation-mlogloss:1.60140
[36m(train_xgb_ray_tune pid=1371794)[0m [593]	train-mlogloss:1.63574	validation-mlogloss:1.60140
[36m(train_xgb_ray_tune pid=1371794)[0m [594]	train-mlogloss:1.63574	validation-mlogloss:1.60140
[36m(train_xgb_ray_tune pid=1371794)[0m [595]	train-mlogloss:1.63574	validation-mlogloss:1.60140
[36m(train_xgb_ray_tune pid=1371793)[0m [448]	train-mlogloss:1.42463	validation-mlogloss:1.39208
[36m(train_xgb_ray_tune pid=1371762)[0m [448]	train-mlogloss:1.47500	validation-mlogloss:1.46922
[36m(train_xgb_ray_tune pid=1371754)[0m [418]	train-mlogloss:1.50503	validation-mlogloss:1.48836
[36m(train_xgb_ray_tune pid=1371754)[0m [419]	train-mlogloss:1.50424	validation-mlogloss:1.48752
[36m(train_xgb_ray_tune pid=1371754)[0m [420]	train-mlogloss:1.50348	validation-mlogloss:1.48668
[36m(train_xgb_ray_tune pid=1371761)[0m [498]	train-mlogloss:1.85362	validation-mlogloss:1.81970
[36m(train_xgb_ray_tune pid=1371761)[0m [499]	train-mlogloss:1.85350	validation-mlogloss:1.81959
[36m(train_xgb_ray_tune pid=1371761)[0m [500]	train-mlogloss:1.85320	validation-mlogloss:1.81927
[36m(train_xgb_ray_tune pid=1371761)[0m [501]	train-mlogloss:1.85299	validation-mlogloss:1.81907
[36m(train_xgb_ray_tune pid=1371786)[0m [469]	train-mlogloss:1.30248	validation-mlogloss:1.29414
[36m(train_xgb_ray_tune pid=1371786)[0m [470]	train-mlogloss:1.30188	validation-mlogloss:1.29359
[36m(train_xgb_ray_tune pid=1371786)[0m [471]	train-mlogloss:1.30123	validation-mlogloss:1.29303
[36m(train_xgb_ray_tune pid=1371793)[0m [449]	train-mlogloss:1.42423	validation-mlogloss:1.39165
[36m(train_xgb_ray_tune pid=1371793)[0m [450]	train-mlogloss:1.42374	validation-mlogloss:1.39113
[36m(train_xgb_ray_tune pid=1371793)[0m [451]	train-mlogloss:1.42324	validation-mlogloss:1.39057
[36m(train_xgb_ray_tune pid=1371762)[0m [449]	train-mlogloss:1.47421	validation-mlogloss:1.46834
[36m(train_xgb_ray_tune pid=1371762)[0m [450]	train-mlogloss:1.47339	validation-mlogloss:1.46749
[36m(train_xgb_ray_tune pid=1371762)[0m [451]	train-mlogloss:1.47259	validation-mlogloss:1.46666
[36m(train_xgb_ray_tune pid=1371795)[0m [490]	train-mlogloss:1.33701	validation-mlogloss:1.31200
[36m(train_xgb_ray_tune pid=1371795)[0m [491]	train-mlogloss:1.33697	validation-mlogloss:1.31194
[36m(train_xgb_ray_tune pid=1371795)[0m [492]	train-mlogloss:1.33697	validation-mlogloss:1.31194
[36m(train_xgb_ray_tune pid=1371795)[0m [493]	train-mlogloss:1.33697	validation-mlogloss:1.31194
[36m(train_xgb_ray_tune pid=1371795)[0m [494]	train-mlogloss:1.33697	validation-mlogloss:1.31194
[36m(train_xgb_ray_tune pid=1371782)[0m [383]	train-mlogloss:1.40336	validation-mlogloss:1.41579
[36m(train_xgb_ray_tune pid=1371782)[0m [384]	train-mlogloss:1.40239	validation-mlogloss:1.41479
[36m(train_xgb_ray_tune pid=1371782)[0m [385]	train-mlogloss:1.40149	validation-mlogloss:1.41384
[36m(train_xgb_ray_tune pid=1371783)[0m [464]	train-mlogloss:1.45087	validation-mlogloss:1.42312
[36m(train_xgb_ray_tune pid=1371783)[0m [465]	train-mlogloss:1.45065	validation-mlogloss:1.42289
[36m(train_xgb_ray_tune pid=1371783)[0m [466]	train-mlogloss:1.45052	validation-mlogloss:1.42275
[36m(train_xgb_ray_tune pid=1371783)[0m [467]	train-mlogloss:1.45038	validation-mlogloss:1.42261
[36m(train_xgb_ray_tune pid=1371794)[0m [596]	train-mlogloss:1.63574	validation-mlogloss:1.60140
[36m(train_xgb_ray_tune pid=1371794)[0m [597]	train-mlogloss:1.63561	validation-mlogloss:1.60127
[36m(train_xgb_ray_tune pid=1371794)[0m [598]	train-mlogloss:1.63561	validation-mlogloss:1.60127
[36m(train_xgb_ray_tune pid=1371794)[0m [599]	train-mlogloss:1.63561	validation-mlogloss:1.60127
[36m(train_xgb_ray_tune pid=1371794)[0m [600]	train-mlogloss:1.63561	validation-mlogloss:1.60127
[36m(train_xgb_ray_tune pid=1371761)[0m [502]	train-mlogloss:1.85261	validation-mlogloss:1.81869
[36m(train_xgb_ray_tune pid=1371783)[0m [468]	train-mlogloss:1.45029	validation-mlogloss:1.42249
[36m(train_xgb_ray_tune pid=1371754)[0m [421]	train-mlogloss:1.50265	validation-mlogloss:1.48574
[36m(train_xgb_ray_tune pid=1371754)[0m [422]	train-mlogloss:1.50183	validation-mlogloss:1.48485
[36m(train_xgb_ray_tune pid=1371754)[0m [423]	train-mlogloss:1.50101	validation-mlogloss:1.48392
[36m(train_xgb_ray_tune pid=1371761)[0m [503]	train-mlogloss:1.85241	validation-mlogloss:1.81849
[36m(train_xgb_ray_tune pid=1371761)[0m [504]	train-mlogloss:1.85225	validation-mlogloss:1.81831
[36m(train_xgb_ray_tune pid=1371761)[0m [505]	train-mlogloss:1.85210	validation-mlogloss:1.81815
[36m(train_xgb_ray_tune pid=1371761)[0m [506]	train-mlogloss:1.85185	validation-mlogloss:1.81787
[36m(train_xgb_ray_tune pid=1371786)[0m [472]	train-mlogloss:1.30058	validation-mlogloss:1.29242
[36m(train_xgb_ray_tune pid=1371786)[0m [473]	train-mlogloss:1.29999	validation-mlogloss:1.29186
[36m(train_xgb_ray_tune pid=1371786)[0m [474]	train-mlogloss:1.29939	validation-mlogloss:1.29134
[36m(train_xgb_ray_tune pid=1371786)[0m [475]	train-mlogloss:1.29880	validation-mlogloss:1.29074
[36m(train_xgb_ray_tune pid=1371793)[0m [452]	train-mlogloss:1.42278	validation-mlogloss:1.39013
[36m(train_xgb_ray_tune pid=1371793)[0m [453]	train-mlogloss:1.42229	validation-mlogloss:1.38960
[36m(train_xgb_ray_tune pid=1371793)[0m [454]	train-mlogloss:1.42179	validation-mlogloss:1.38909
[36m(train_xgb_ray_tune pid=1371762)[0m [452]	train-mlogloss:1.47180	validation-mlogloss:1.46586
[36m(train_xgb_ray_tune pid=1371762)[0m [453]	train-mlogloss:1.47109	validation-mlogloss:1.46506
[36m(train_xgb_ray_tune pid=1371762)[0m [454]	train-mlogloss:1.47031	validation-mlogloss:1.46420
[36m(train_xgb_ray_tune pid=1371795)[0m [495]	train-mlogloss:1.33692	validation-mlogloss:1.31188
[36m(train_xgb_ray_tune pid=1371795)[0m [496]	train-mlogloss:1.33688	validation-mlogloss:1.31183
[36m(train_xgb_ray_tune pid=1371795)[0m [497]	train-mlogloss:1.33688	validation-mlogloss:1.31183
[36m(train_xgb_ray_tune pid=1371795)[0m [498]	train-mlogloss:1.33684	validation-mlogloss:1.31178
[36m(train_xgb_ray_tune pid=1371795)[0m [499]	train-mlogloss:1.33684	validation-mlogloss:1.31178
[36m(train_xgb_ray_tune pid=1371782)[0m [386]	train-mlogloss:1.40053	validation-mlogloss:1.41287
[36m(train_xgb_ray_tune pid=1371782)[0m [387]	train-mlogloss:1.39957	validation-mlogloss:1.41190
[36m(train_xgb_ray_tune pid=1371782)[0m [388]	train-mlogloss:1.39861	validation-mlogloss:1.41083
[36m(train_xgb_ray_tune pid=1371783)[0m [469]	train-mlogloss:1.45013	validation-mlogloss:1.42231
[36m(train_xgb_ray_tune pid=1371783)[0m [470]	train-mlogloss:1.44991	validation-mlogloss:1.42207
[36m(train_xgb_ray_tune pid=1371783)[0m [471]	train-mlogloss:1.44976	validation-mlogloss:1.42189
[36m(train_xgb_ray_tune pid=1371783)[0m [472]	train-mlogloss:1.44961	validation-mlogloss:1.42175
[36m(train_xgb_ray_tune pid=1371794)[0m [601]	train-mlogloss:1.63557	validation-mlogloss:1.60121
[36m(train_xgb_ray_tune pid=1371794)[0m [602]	train-mlogloss:1.63557	validation-mlogloss:1.60121
[36m(train_xgb_ray_tune pid=1371794)[0m [603]	train-mlogloss:1.63557	validation-mlogloss:1.60121
[36m(train_xgb_ray_tune pid=1371794)[0m [604]	train-mlogloss:1.63557	validation-mlogloss:1.60121
[36m(train_xgb_ray_tune pid=1371794)[0m [605]	train-mlogloss:1.63557	validation-mlogloss:1.60121
[36m(train_xgb_ray_tune pid=1371793)[0m [455]	train-mlogloss:1.42129	validation-mlogloss:1.38867
[36m(train_xgb_ray_tune pid=1371754)[0m [424]	train-mlogloss:1.50030	validation-mlogloss:1.48312
[36m(train_xgb_ray_tune pid=1371754)[0m [425]	train-mlogloss:1.49959	validation-mlogloss:1.48231
[36m(train_xgb_ray_tune pid=1371754)[0m [426]	train-mlogloss:1.49888	validation-mlogloss:1.48153
[36m(train_xgb_ray_tune pid=1371761)[0m [507]	train-mlogloss:1.85169	validation-mlogloss:1.81771
[36m(train_xgb_ray_tune pid=1371761)[0m [508]	train-mlogloss:1.85149	validation-mlogloss:1.81749
[36m(train_xgb_ray_tune pid=1371761)[0m [509]	train-mlogloss:1.85129	validation-mlogloss:1.81730
[36m(train_xgb_ray_tune pid=1371761)[0m [510]	train-mlogloss:1.85118	validation-mlogloss:1.81720
[36m(train_xgb_ray_tune pid=1371786)[0m [476]	train-mlogloss:1.29823	validation-mlogloss:1.29019
[36m(train_xgb_ray_tune pid=1371786)[0m [477]	train-mlogloss:1.29765	validation-mlogloss:1.28963
[36m(train_xgb_ray_tune pid=1371786)[0m [478]	train-mlogloss:1.29701	validation-mlogloss:1.28897
[36m(train_xgb_ray_tune pid=1371793)[0m [456]	train-mlogloss:1.42087	validation-mlogloss:1.38822
[36m(train_xgb_ray_tune pid=1371793)[0m [457]	train-mlogloss:1.42037	validation-mlogloss:1.38769
[36m(train_xgb_ray_tune pid=1371793)[0m [458]	train-mlogloss:1.41980	validation-mlogloss:1.38706
[36m(train_xgb_ray_tune pid=1371762)[0m [455]	train-mlogloss:1.46950	validation-mlogloss:1.46333
[36m(train_xgb_ray_tune pid=1371762)[0m [456]	train-mlogloss:1.46878	validation-mlogloss:1.46260
[36m(train_xgb_ray_tune pid=1371762)[0m [457]	train-mlogloss:1.46798	validation-mlogloss:1.46171
[36m(train_xgb_ray_tune pid=1371795)[0m [500]	train-mlogloss:1.33680	validation-mlogloss:1.31173
[36m(train_xgb_ray_tune pid=1371795)[0m [501]	train-mlogloss:1.33680	validation-mlogloss:1.31173
[36m(train_xgb_ray_tune pid=1371795)[0m [502]	train-mlogloss:1.33680	validation-mlogloss:1.31173
[36m(train_xgb_ray_tune pid=1371795)[0m [503]	train-mlogloss:1.33680	validation-mlogloss:1.31173
[36m(train_xgb_ray_tune pid=1371795)[0m [504]	train-mlogloss:1.33680	validation-mlogloss:1.31173
[36m(train_xgb_ray_tune pid=1371782)[0m [389]	train-mlogloss:1.39766	validation-mlogloss:1.40986
[36m(train_xgb_ray_tune pid=1371782)[0m [390]	train-mlogloss:1.39674	validation-mlogloss:1.40886
[36m(train_xgb_ray_tune pid=1371782)[0m [391]	train-mlogloss:1.39586	validation-mlogloss:1.40797
[36m(train_xgb_ray_tune pid=1371783)[0m [473]	train-mlogloss:1.44942	validation-mlogloss:1.42154
[36m(train_xgb_ray_tune pid=1371783)[0m [474]	train-mlogloss:1.44918	validation-mlogloss:1.42123
[36m(train_xgb_ray_tune pid=1371783)[0m [475]	train-mlogloss:1.44888	validation-mlogloss:1.42089
[36m(train_xgb_ray_tune pid=1371783)[0m [476]	train-mlogloss:1.44878	validation-mlogloss:1.42077
[36m(train_xgb_ray_tune pid=1371783)[0m [477]	train-mlogloss:1.44860	validation-mlogloss:1.42058
[36m(train_xgb_ray_tune pid=1371794)[0m [606]	train-mlogloss:1.63543	validation-mlogloss:1.60107
[36m(train_xgb_ray_tune pid=1371794)[0m [607]	train-mlogloss:1.63539	validation-mlogloss:1.60102
[36m(train_xgb_ray_tune pid=1371794)[0m [608]	train-mlogloss:1.63530	validation-mlogloss:1.60093
[36m(train_xgb_ray_tune pid=1371794)[0m [609]	train-mlogloss:1.63526	validation-mlogloss:1.60090
[36m(train_xgb_ray_tune pid=1371794)[0m [610]	train-mlogloss:1.63521	validation-mlogloss:1.60084
[36m(train_xgb_ray_tune pid=1371754)[0m [427]	train-mlogloss:1.49811	validation-mlogloss:1.48066
[36m(train_xgb_ray_tune pid=1371761)[0m [511]	train-mlogloss:1.85093	validation-mlogloss:1.81693
[36m(train_xgb_ray_tune pid=1371762)[0m [458]	train-mlogloss:1.46718	validation-mlogloss:1.46082
[36m(train_xgb_ray_tune pid=1371794)[0m [611]	train-mlogloss:1.63521	validation-mlogloss:1.60084

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:02. Total running time: 39s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             36.9089 │
│ time_total_s                 36.9089 │
│ training_iteration                 1 │
│ validation_accuracy          0.43393 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:02. Total running time: 39s
[36m(train_xgb_ray_tune pid=1371754)[0m [428]	train-mlogloss:1.49740	validation-mlogloss:1.47988
[36m(train_xgb_ray_tune pid=1371754)[0m [429]	train-mlogloss:1.49654	validation-mlogloss:1.47896
[36m(train_xgb_ray_tune pid=1371754)[0m [430]	train-mlogloss:1.49581	validation-mlogloss:1.47819
[36m(train_xgb_ray_tune pid=1371761)[0m [512]	train-mlogloss:1.85067	validation-mlogloss:1.81664
[36m(train_xgb_ray_tune pid=1371761)[0m [513]	train-mlogloss:1.85056	validation-mlogloss:1.81654
[36m(train_xgb_ray_tune pid=1371761)[0m [514]	train-mlogloss:1.85040	validation-mlogloss:1.81639
[36m(train_xgb_ray_tune pid=1371761)[0m [515]	train-mlogloss:1.85029	validation-mlogloss:1.81629
[36m(train_xgb_ray_tune pid=1371786)[0m [479]	train-mlogloss:1.29644	validation-mlogloss:1.28840
[36m(train_xgb_ray_tune pid=1371786)[0m [480]	train-mlogloss:1.29585	validation-mlogloss:1.28787
[36m(train_xgb_ray_tune pid=1371786)[0m [481]	train-mlogloss:1.29526	validation-mlogloss:1.28744
[36m(train_xgb_ray_tune pid=1371786)[0m [482]	train-mlogloss:1.29465	validation-mlogloss:1.28693
[36m(train_xgb_ray_tune pid=1371793)[0m [459]	train-mlogloss:1.41932	validation-mlogloss:1.38663
[36m(train_xgb_ray_tune pid=1371793)[0m [460]	train-mlogloss:1.41883	validation-mlogloss:1.38618
[36m(train_xgb_ray_tune pid=1371793)[0m [461]	train-mlogloss:1.41835	validation-mlogloss:1.38565
[36m(train_xgb_ray_tune pid=1371793)[0m [462]	train-mlogloss:1.41781	validation-mlogloss:1.38508
[36m(train_xgb_ray_tune pid=1371762)[0m [459]	train-mlogloss:1.46639	validation-mlogloss:1.45998
[36m(train_xgb_ray_tune pid=1371762)[0m [460]	train-mlogloss:1.46565	validation-mlogloss:1.45916
[36m(train_xgb_ray_tune pid=1371762)[0m [461]	train-mlogloss:1.46484	validation-mlogloss:1.45824
[36m(train_xgb_ray_tune pid=1371795)[0m [505]	train-mlogloss:1.33680	validation-mlogloss:1.31173
[36m(train_xgb_ray_tune pid=1371795)[0m [506]	train-mlogloss:1.33676	validation-mlogloss:1.31168
[36m(train_xgb_ray_tune pid=1371795)[0m [507]	train-mlogloss:1.33672	validation-mlogloss:1.31168
[36m(train_xgb_ray_tune pid=1371795)[0m [508]	train-mlogloss:1.33672	validation-mlogloss:1.31168
[36m(train_xgb_ray_tune pid=1371795)[0m [509]	train-mlogloss:1.33672	validation-mlogloss:1.31167
[36m(train_xgb_ray_tune pid=1371782)[0m [392]	train-mlogloss:1.39496	validation-mlogloss:1.40708
[36m(train_xgb_ray_tune pid=1371782)[0m [393]	train-mlogloss:1.39408	validation-mlogloss:1.40614
[36m(train_xgb_ray_tune pid=1371782)[0m [394]	train-mlogloss:1.39318	validation-mlogloss:1.40521
[36m(train_xgb_ray_tune pid=1371783)[0m [478]	train-mlogloss:1.44849	validation-mlogloss:1.42046
[36m(train_xgb_ray_tune pid=1371783)[0m [479]	train-mlogloss:1.44827	validation-mlogloss:1.42024
[36m(train_xgb_ray_tune pid=1371783)[0m [480]	train-mlogloss:1.44800	validation-mlogloss:1.41996
[36m(train_xgb_ray_tune pid=1371783)[0m [481]	train-mlogloss:1.44785	validation-mlogloss:1.41982
[36m(train_xgb_ray_tune pid=1371794)[0m [612]	train-mlogloss:1.63521	validation-mlogloss:1.60084
[36m(train_xgb_ray_tune pid=1371794)[0m [613]	train-mlogloss:1.63517	validation-mlogloss:1.60079
[36m(train_xgb_ray_tune pid=1371794)[0m [614]	train-mlogloss:1.63509	validation-mlogloss:1.60070
[36m(train_xgb_ray_tune pid=1371794)[0m [615]	train-mlogloss:1.63509	validation-mlogloss:1.60070
[36m(train_xgb_ray_tune pid=1371754)[0m [431]	train-mlogloss:1.49510	validation-mlogloss:1.47746
[36m(train_xgb_ray_tune pid=1371754)[0m [432]	train-mlogloss:1.49432	validation-mlogloss:1.47666
[36m(train_xgb_ray_tune pid=1371754)[0m [433]	train-mlogloss:1.49369	validation-mlogloss:1.47600
[36m(train_xgb_ray_tune pid=1371761)[0m [516]	train-mlogloss:1.85019	validation-mlogloss:1.81619
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[36m(train_xgb_ray_tune pid=1371761)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=1371761)[0m   _log_deprecation_warning([32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=1371762)[0m [557]	train-mlogloss:1.40570	validation-mlogloss:1.39335
[36m(train_xgb_ray_tune pid=1371762)[0m [558]	train-mlogloss:1.40515	validation-mlogloss:1.39271
[36m(train_xgb_ray_tune pid=1371762)[0m [559]	train-mlogloss:1.40462	validation-mlogloss:1.39214
[36m(train_xgb_ray_tune pid=1371795)[0m [647]	train-mlogloss:1.33459	validation-mlogloss:1.30939
[36m(train_xgb_ray_tune pid=1371795)[0m [648]	train-mlogloss:1.33455	validation-mlogloss:1.30935
[36m(train_xgb_ray_tune pid=1371795)[0m [649]	train-mlogloss:1.33455	validation-mlogloss:1.30935
[36m(train_xgb_ray_tune pid=1371795)[0m [650]	train-mlogloss:1.33455	validation-mlogloss:1.30935
[36m(train_xgb_ray_tune pid=1371795)[0m [651]	train-mlogloss:1.33445	validation-mlogloss:1.30925
[36m(train_xgb_ray_tune pid=1371782)[0m [485]	train-mlogloss:1.32560	validation-mlogloss:1.33419
[36m(train_xgb_ray_tune pid=1371782)[0m [486]	train-mlogloss:1.32497	validation-mlogloss:1.33352
[36m(train_xgb_ray_tune pid=1371782)[0m [487]	train-mlogloss:1.32435	validation-mlogloss:1.33284
[36m(train_xgb_ray_tune pid=1371783)[0m [618]	train-mlogloss:1.43861	validation-mlogloss:1.40984
[36m(train_xgb_ray_tune pid=1371783)[0m [619]	train-mlogloss:1.43858	validation-mlogloss:1.40981
[36m(train_xgb_ray_tune pid=1371783)[0m [620]	train-mlogloss:1.43855	validation-mlogloss:1.40979
[36m(train_xgb_ray_tune pid=1371783)[0m [621]	train-mlogloss:1.43849	validation-mlogloss:1.40971
[36m(train_xgb_ray_tune pid=1371783)[0m [622]	train-mlogloss:1.43849	validation-mlogloss:1.40971
[36m(train_xgb_ray_tune pid=1371762)[0m [560]	train-mlogloss:1.40416	validation-mlogloss:1.39160
[36m(train_xgb_ray_tune pid=1371783)[0m [623]	train-mlogloss:1.43849	validation-mlogloss:1.40971
[36m(train_xgb_ray_tune pid=1371754)[0m [528]	train-mlogloss:1.44133	validation-mlogloss:1.41904
[36m(train_xgb_ray_tune pid=1371754)[0m [529]	train-mlogloss:1.44098	validation-mlogloss:1.41866
[36m(train_xgb_ray_tune pid=1371754)[0m [530]	train-mlogloss:1.44068	validation-mlogloss:1.41829
[36m(train_xgb_ray_tune pid=1371754)[0m [531]	train-mlogloss:1.44033	validation-mlogloss:1.41790
[36m(train_xgb_ray_tune pid=1371786)[0m [582]	train-mlogloss:1.24453	validation-mlogloss:1.24429
[36m(train_xgb_ray_tune pid=1371786)[0m [583]	train-mlogloss:1.24412	validation-mlogloss:1.24401
[36m(train_xgb_ray_tune pid=1371786)[0m [584]	train-mlogloss:1.24372	validation-mlogloss:1.24371
[36m(train_xgb_ray_tune pid=1371786)[0m [585]	train-mlogloss:1.24325	validation-mlogloss:1.24334
[36m(train_xgb_ray_tune pid=1371793)[0m [580]	train-mlogloss:1.38389	validation-mlogloss:1.35189
[36m(train_xgb_ray_tune pid=1371793)[0m [581]	train-mlogloss:1.38372	validation-mlogloss:1.35171
[36m(train_xgb_ray_tune pid=1371793)[0m [582]	train-mlogloss:1.38356	validation-mlogloss:1.35155
[36m(train_xgb_ray_tune pid=1371793)[0m [583]	train-mlogloss:1.38339	validation-mlogloss:1.35138
[36m(train_xgb_ray_tune pid=1371762)[0m [561]	train-mlogloss:1.40362	validation-mlogloss:1.39099
[36m(train_xgb_ray_tune pid=1371762)[0m [562]	train-mlogloss:1.40312	validation-mlogloss:1.39043
[36m(train_xgb_ray_tune pid=1371762)[0m [563]	train-mlogloss:1.40267	validation-mlogloss:1.38993
[36m(train_xgb_ray_tune pid=1371795)[0m [652]	train-mlogloss:1.33441	validation-mlogloss:1.30921
[36m(train_xgb_ray_tune pid=1371795)[0m [653]	train-mlogloss:1.33441	validation-mlogloss:1.30921
[36m(train_xgb_ray_tune pid=1371795)[0m [654]	train-mlogloss:1.33441	validation-mlogloss:1.30921
[36m(train_xgb_ray_tune pid=1371795)[0m [655]	train-mlogloss:1.33441	validation-mlogloss:1.30921
[36m(train_xgb_ray_tune pid=1371795)[0m [656]	train-mlogloss:1.33441	validation-mlogloss:1.30921
[36m(train_xgb_ray_tune pid=1371782)[0m [488]	train-mlogloss:1.32371	validation-mlogloss:1.33217
[36m(train_xgb_ray_tune pid=1371782)[0m [489]	train-mlogloss:1.32309	validation-mlogloss:1.33155
[36m(train_xgb_ray_tune pid=1371782)[0m [490]	train-mlogloss:1.32250	validation-mlogloss:1.33089
[36m(train_xgb_ray_tune pid=1371783)[0m [624]	train-mlogloss:1.43849	validation-mlogloss:1.40971
[36m(train_xgb_ray_tune pid=1371783)[0m [625]	train-mlogloss:1.43846	validation-mlogloss:1.40968
[36m(train_xgb_ray_tune pid=1371783)[0m [626]	train-mlogloss:1.43844	validation-mlogloss:1.40967
[36m(train_xgb_ray_tune pid=1371783)[0m [627]	train-mlogloss:1.43841	validation-mlogloss:1.40963
[36m(train_xgb_ray_tune pid=1371783)[0m [628]	train-mlogloss:1.43835	validation-mlogloss:1.40958

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:05. Total running time: 43s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             40.3183 │
│ time_total_s                 40.3183 │
│ training_iteration                 1 │
│ validation_accuracy          0.45133 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:05. Total running time: 43s

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:05. Total running time: 43s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             40.3019 │
│ time_total_s                 40.3019 │
│ training_iteration                 1 │
│ validation_accuracy          0.46426 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1371754)[0m [532]	train-mlogloss:1.43999	validation-mlogloss:1.41755
[36m(train_xgb_ray_tune pid=1371754)[0m [533]	train-mlogloss:1.43954	validation-mlogloss:1.41709
[36m(train_xgb_ray_tune pid=1371754)[0m [534]	train-mlogloss:1.43915	validation-mlogloss:1.41667
[36m(train_xgb_ray_tune pid=1371754)[0m [535]	train-mlogloss:1.43870	validation-mlogloss:1.41617
[36m(train_xgb_ray_tune pid=1371786)[0m [586]	train-mlogloss:1.24277	validation-mlogloss:1.24299
[36m(train_xgb_ray_tune pid=1371786)[0m [587]	train-mlogloss:1.24233	validation-mlogloss:1.24268
[36m(train_xgb_ray_tune pid=1371786)[0m [588]	train-mlogloss:1.24188	validation-mlogloss:1.24233
[36m(train_xgb_ray_tune pid=1371793)[0m [584]	train-mlogloss:1.38321	validation-mlogloss:1.35122
[36m(train_xgb_ray_tune pid=1371793)[0m [585]	train-mlogloss:1.38299	validation-mlogloss:1.35099
[36m(train_xgb_ray_tune pid=1371793)[0m [586]	train-mlogloss:1.38276	validation-mlogloss:1.35077
[36m(train_xgb_ray_tune pid=1371793)[0m [587]	train-mlogloss:1.38260	validation-mlogloss:1.35060
[36m(train_xgb_ray_tune pid=1371762)[0m [564]	train-mlogloss:1.40216	validation-mlogloss:1.38934
[36m(train_xgb_ray_tune pid=1371762)[0m [565]	train-mlogloss:1.40167	validation-mlogloss:1.38883
[36m(train_xgb_ray_tune pid=1371762)[0m [566]	train-mlogloss:1.40124	validation-mlogloss:1.38836
[36m(train_xgb_ray_tune pid=1371762)[0m [567]	train-mlogloss:1.40067	validation-mlogloss:1.38773
[36m(train_xgb_ray_tune pid=1371795)[0m [657]	train-mlogloss:1.33441	validation-mlogloss:1.30921
[36m(train_xgb_ray_tune pid=1371795)[0m [658]	train-mlogloss:1.33437	validation-mlogloss:1.30922
[36m(train_xgb_ray_tune pid=1371795)[0m [659]	train-mlogloss:1.33437	validation-mlogloss:1.30922
[36m(train_xgb_ray_tune pid=1371795)[0m [660]	train-mlogloss:1.33433	validation-mlogloss:1.30917
[36m(train_xgb_ray_tune pid=1371795)[0m [661]	train-mlogloss:1.33433	validation-mlogloss:1.30917
[36m(train_xgb_ray_tune pid=1371782)[0m [491]	train-mlogloss:1.32189	validation-mlogloss:1.33023
[36m(train_xgb_ray_tune pid=1371782)[0m [492]	train-mlogloss:1.32123	validation-mlogloss:1.32953
[36m(train_xgb_ray_tune pid=1371782)[0m [493]	train-mlogloss:1.32068	validation-mlogloss:1.32894
[36m(train_xgb_ray_tune pid=1371782)[0m [494]	train-mlogloss:1.32007	validation-mlogloss:1.32826
[36m(train_xgb_ray_tune pid=1371783)[0m [629]	train-mlogloss:1.43835	validation-mlogloss:1.40958
[36m(train_xgb_ray_tune pid=1371783)[0m [630]	train-mlogloss:1.43832	validation-mlogloss:1.40954

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:05. Total running time: 43s
[36m(train_xgb_ray_tune pid=1371793)[0m [588]	train-mlogloss:1.38235	validation-mlogloss:1.35033
[36m(train_xgb_ray_tune pid=1371795)[0m [662]	train-mlogloss:1.33433	validation-mlogloss:1.30917
[36m(train_xgb_ray_tune pid=1371754)[0m [536]	train-mlogloss:1.43835	validation-mlogloss:1.41579
[36m(train_xgb_ray_tune pid=1371754)[0m [537]	train-mlogloss:1.43800	validation-mlogloss:1.41542
[36m(train_xgb_ray_tune pid=1371754)[0m [538]	train-mlogloss:1.43762	validation-mlogloss:1.41500
[36m(train_xgb_ray_tune pid=1371754)[0m [539]	train-mlogloss:1.43722	validation-mlogloss:1.41457
[36m(train_xgb_ray_tune pid=1371786)[0m [589]	train-mlogloss:1.24146	validation-mlogloss:1.24205
[36m(train_xgb_ray_tune pid=1371786)[0m [590]	train-mlogloss:1.24099	validation-mlogloss:1.24167
[36m(train_xgb_ray_tune pid=1371786)[0m [591]	train-mlogloss:1.24057	validation-mlogloss:1.24133
[36m(train_xgb_ray_tune pid=1371786)[0m [592]	train-mlogloss:1.24014	validation-mlogloss:1.24108
[36m(train_xgb_ray_tune pid=1371793)[0m [589]	train-mlogloss:1.38213	validation-mlogloss:1.35012
[36m(train_xgb_ray_tune pid=1371793)[0m [590]	train-mlogloss:1.38200	validation-mlogloss:1.35001
[36m(train_xgb_ray_tune pid=1371793)[0m [591]	train-mlogloss:1.38184	validation-mlogloss:1.34987
[36m(train_xgb_ray_tune pid=1371793)[0m [592]	train-mlogloss:1.38169	validation-mlogloss:1.34971
[36m(train_xgb_ray_tune pid=1371762)[0m [568]	train-mlogloss:1.40022	validation-mlogloss:1.38724
[36m(train_xgb_ray_tune pid=1371762)[0m [569]	train-mlogloss:1.39978	validation-mlogloss:1.38672
[36m(train_xgb_ray_tune pid=1371762)[0m [570]	train-mlogloss:1.39932	validation-mlogloss:1.38625
[36m(train_xgb_ray_tune pid=1371762)[0m [571]	train-mlogloss:1.39891	validation-mlogloss:1.38578
[36m(train_xgb_ray_tune pid=1371795)[0m [663]	train-mlogloss:1.33429	validation-mlogloss:1.30910
[36m(train_xgb_ray_tune pid=1371795)[0m [664]	train-mlogloss:1.33429	validation-mlogloss:1.30910
[36m(train_xgb_ray_tune pid=1371795)[0m [665]	train-mlogloss:1.33429	validation-mlogloss:1.30910
[36m(train_xgb_ray_tune pid=1371795)[0m [666]	train-mlogloss:1.33429	validation-mlogloss:1.30910
[36m(train_xgb_ray_tune pid=1371795)[0m [667]	train-mlogloss:1.33429	validation-mlogloss:1.30910
[36m(train_xgb_ray_tune pid=1371782)[0m [495]	train-mlogloss:1.31947	validation-mlogloss:1.32764
[36m(train_xgb_ray_tune pid=1371782)[0m [496]	train-mlogloss:1.31890	validation-mlogloss:1.32710
[36m(train_xgb_ray_tune pid=1371782)[0m [497]	train-mlogloss:1.31829	validation-mlogloss:1.32642
[36m(train_xgb_ray_tune pid=1371754)[0m [540]	train-mlogloss:1.43677	validation-mlogloss:1.41407
[36m(train_xgb_ray_tune pid=1371754)[0m [541]	train-mlogloss:1.43634	validation-mlogloss:1.41357
[36m(train_xgb_ray_tune pid=1371754)[0m [542]	train-mlogloss:1.43595	validation-mlogloss:1.41319
[36m(train_xgb_ray_tune pid=1371754)[0m [543]	train-mlogloss:1.43558	validation-mlogloss:1.41281
[36m(train_xgb_ray_tune pid=1371786)[0m [593]	train-mlogloss:1.23967	validation-mlogloss:1.24074
[36m(train_xgb_ray_tune pid=1371786)[0m [594]	train-mlogloss:1.23925	validation-mlogloss:1.24041
[36m(train_xgb_ray_tune pid=1371786)[0m [595]	train-mlogloss:1.23884	validation-mlogloss:1.24010
[36m(train_xgb_ray_tune pid=1371786)[0m [596]	train-mlogloss:1.23840	validation-mlogloss:1.23979
[36m(train_xgb_ray_tune pid=1371793)[0m [593]	train-mlogloss:1.38156	validation-mlogloss:1.34956
[36m(train_xgb_ray_tune pid=1371793)[0m [594]	train-mlogloss:1.38143	validation-mlogloss:1.34946
[36m(train_xgb_ray_tune pid=1371793)[0m [595]	train-mlogloss:1.38123	validation-mlogloss:1.34925
[36m(train_xgb_ray_tune pid=1371793)[0m [596]	train-mlogloss:1.38100	validation-mlogloss:1.34902
[36m(train_xgb_ray_tune pid=1371793)[0m [597]	train-mlogloss:1.38077	validation-mlogloss:1.34881
[36m(train_xgb_ray_tune pid=1371762)[0m [572]	train-mlogloss:1.39847	validation-mlogloss:1.38527
[36m(train_xgb_ray_tune pid=1371762)[0m [573]	train-mlogloss:1.39799	validation-mlogloss:1.38472
[36m(train_xgb_ray_tune pid=1371762)[0m [574]	train-mlogloss:1.39753	validation-mlogloss:1.38422
[36m(train_xgb_ray_tune pid=1371762)[0m [575]	train-mlogloss:1.39705	validation-mlogloss:1.38369
[36m(train_xgb_ray_tune pid=1371795)[0m [668]	train-mlogloss:1.33429	validation-mlogloss:1.30910
[36m(train_xgb_ray_tune pid=1371795)[0m [669]	train-mlogloss:1.33429	validation-mlogloss:1.30909
[36m(train_xgb_ray_tune pid=1371795)[0m [670]	train-mlogloss:1.33429	validation-mlogloss:1.30910
[36m(train_xgb_ray_tune pid=1371795)[0m [671]	train-mlogloss:1.33429	validation-mlogloss:1.30909
[36m(train_xgb_ray_tune pid=1371795)[0m [672]	train-mlogloss:1.33429	validation-mlogloss:1.30909
[36m(train_xgb_ray_tune pid=1371782)[0m [498]	train-mlogloss:1.31773	validation-mlogloss:1.32585
[36m(train_xgb_ray_tune pid=1371782)[0m [499]	train-mlogloss:1.31714	validation-mlogloss:1.32527
[36m(train_xgb_ray_tune pid=1371782)[0m [500]	train-mlogloss:1.31655	validation-mlogloss:1.32460
[36m(train_xgb_ray_tune pid=1371782)[0m [501]	train-mlogloss:1.31596	validation-mlogloss:1.32397
[36m(train_xgb_ray_tune pid=1371754)[0m [544]	train-mlogloss:1.43529	validation-mlogloss:1.41248
[36m(train_xgb_ray_tune pid=1371754)[0m [545]	train-mlogloss:1.43493	validation-mlogloss:1.41209
[36m(train_xgb_ray_tune pid=1371754)[0m [546]	train-mlogloss:1.43468	validation-mlogloss:1.41184
[36m(train_xgb_ray_tune pid=1371754)[0m [547]	train-mlogloss:1.43435	validation-mlogloss:1.41149
[36m(train_xgb_ray_tune pid=1371786)[0m [597]	train-mlogloss:1.23799	validation-mlogloss:1.23952
[36m(train_xgb_ray_tune pid=1371786)[0m [598]	train-mlogloss:1.23759	validation-mlogloss:1.23922
[36m(train_xgb_ray_tune pid=1371786)[0m [599]	train-mlogloss:1.23719	validation-mlogloss:1.23894
[36m(train_xgb_ray_tune pid=1371786)[0m [600]	train-mlogloss:1.23675	validation-mlogloss:1.23855
[36m(train_xgb_ray_tune pid=1371793)[0m [598]	train-mlogloss:1.38073	validation-mlogloss:1.34876
[36m(train_xgb_ray_tune pid=1371793)[0m [599]	train-mlogloss:1.38060	validation-mlogloss:1.34864
[36m(train_xgb_ray_tune pid=1371793)[0m [600]	train-mlogloss:1.38045	validation-mlogloss:1.34852
[36m(train_xgb_ray_tune pid=1371793)[0m [601]	train-mlogloss:1.38037	validation-mlogloss:1.34843
[36m(train_xgb_ray_tune pid=1371793)[0m [602]	train-mlogloss:1.38016	validation-mlogloss:1.34820
[36m(train_xgb_ray_tune pid=1371762)[0m [576]	train-mlogloss:1.39656	validation-mlogloss:1.38313
[36m(train_xgb_ray_tune pid=1371762)[0m [577]	train-mlogloss:1.39609	validation-mlogloss:1.38263
[36m(train_xgb_ray_tune pid=1371762)[0m [578]	train-mlogloss:1.39569	validation-mlogloss:1.38222
[36m(train_xgb_ray_tune pid=1371762)[0m [579]	train-mlogloss:1.39514	validation-mlogloss:1.38159
[36m(train_xgb_ray_tune pid=1371795)[0m [673]	train-mlogloss:1.33429	validation-mlogloss:1.30909
[36m(train_xgb_ray_tune pid=1371795)[0m [674]	train-mlogloss:1.33425	validation-mlogloss:1.30906
[36m(train_xgb_ray_tune pid=1371795)[0m [675]	train-mlogloss:1.33425	validation-mlogloss:1.30906
[36m(train_xgb_ray_tune pid=1371782)[0m [502]	train-mlogloss:1.31530	validation-mlogloss:1.32327
[36m(train_xgb_ray_tune pid=1371782)[0m [503]	train-mlogloss:1.31472	validation-mlogloss:1.32270
[36m(train_xgb_ray_tune pid=1371782)[0m [504]	train-mlogloss:1.31418	validation-mlogloss:1.32213
[36m(train_xgb_ray_tune pid=1371782)[0m [505]	train-mlogloss:1.31360	validation-mlogloss:1.32150
[36m(train_xgb_ray_tune pid=1371754)[0m [548]	train-mlogloss:1.43398	validation-mlogloss:1.41109
[36m(train_xgb_ray_tune pid=1371754)[0m [549]	train-mlogloss:1.43353	validation-mlogloss:1.41060
[36m(train_xgb_ray_tune pid=1371754)[0m [550]	train-mlogloss:1.43319	validation-mlogloss:1.41025
[36m(train_xgb_ray_tune pid=1371754)[0m [551]	train-mlogloss:1.43289	validation-mlogloss:1.40994
[36m(train_xgb_ray_tune pid=1371786)[0m [601]	train-mlogloss:1.23632	validation-mlogloss:1.23823
[36m(train_xgb_ray_tune pid=1371786)[0m [602]	train-mlogloss:1.23588	validation-mlogloss:1.23795
[36m(train_xgb_ray_tune pid=1371786)[0m [603]	train-mlogloss:1.23545	validation-mlogloss:1.23761
[36m(train_xgb_ray_tune pid=1371793)[0m [603]	train-mlogloss:1.37996	validation-mlogloss:1.34802
[36m(train_xgb_ray_tune pid=1371793)[0m [604]	train-mlogloss:1.37971	validation-mlogloss:1.34775
[36m(train_xgb_ray_tune pid=1371793)[0m [605]	train-mlogloss:1.37958	validation-mlogloss:1.34763
[36m(train_xgb_ray_tune pid=1371793)[0m [606]	train-mlogloss:1.37937	validation-mlogloss:1.34747
[36m(train_xgb_ray_tune pid=1371793)[0m [607]	train-mlogloss:1.37919	validation-mlogloss:1.34734
[36m(train_xgb_ray_tune pid=1371762)[0m [580]	train-mlogloss:1.39472	validation-mlogloss:1.38110
[36m(train_xgb_ray_tune pid=1371762)[0m [581]	train-mlogloss:1.39429	validation-mlogloss:1.38059
[36m(train_xgb_ray_tune pid=1371762)[0m [582]	train-mlogloss:1.39390	validation-mlogloss:1.38016
[36m(train_xgb_ray_tune pid=1371762)[0m [583]	train-mlogloss:1.39341	validation-mlogloss:1.37961
[36m(train_xgb_ray_tune pid=1371782)[0m [506]	train-mlogloss:1.31303	validation-mlogloss:1.32088
[36m(train_xgb_ray_tune pid=1371782)[0m [507]	train-mlogloss:1.31246	validation-mlogloss:1.32028
[36m(train_xgb_ray_tune pid=1371782)[0m [508]	train-mlogloss:1.31190	validation-mlogloss:1.31969
[36m(train_xgb_ray_tune pid=1371782)[0m [509]	train-mlogloss:1.31134	validation-mlogloss:1.31909

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:06. Total running time: 43s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             40.8409 │
│ time_total_s                 40.8409 │
│ training_iteration                 1 │
│ validation_accuracy          0.50753 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:06. Total running time: 43s
[36m(train_xgb_ray_tune pid=1371754)[0m [552]	train-mlogloss:1.43244	validation-mlogloss:1.40951
[36m(train_xgb_ray_tune pid=1371754)[0m [553]	train-mlogloss:1.43212	validation-mlogloss:1.40919
[36m(train_xgb_ray_tune pid=1371754)[0m [554]	train-mlogloss:1.43183	validation-mlogloss:1.40884
[36m(train_xgb_ray_tune pid=1371754)[0m [555]	train-mlogloss:1.43140	validation-mlogloss:1.40839
[36m(train_xgb_ray_tune pid=1371786)[0m [604]	train-mlogloss:1.23505	validation-mlogloss:1.23733
[36m(train_xgb_ray_tune pid=1371786)[0m [605]	train-mlogloss:1.23464	validation-mlogloss:1.23696
[36m(train_xgb_ray_tune pid=1371786)[0m [606]	train-mlogloss:1.23426	validation-mlogloss:1.23666
[36m(train_xgb_ray_tune pid=1371786)[0m [607]	train-mlogloss:1.23383	validation-mlogloss:1.23632
[36m(train_xgb_ray_tune pid=1371793)[0m [608]	train-mlogloss:1.37908	validation-mlogloss:1.34720
[36m(train_xgb_ray_tune pid=1371793)[0m [609]	train-mlogloss:1.37884	validation-mlogloss:1.34696
[36m(train_xgb_ray_tune pid=1371793)[0m [610]	train-mlogloss:1.37864	validation-mlogloss:1.34672
[36m(train_xgb_ray_tune pid=1371793)[0m [611]	train-mlogloss:1.37850	validation-mlogloss:1.34662
[36m(train_xgb_ray_tune pid=1371762)[0m [584]	train-mlogloss:1.39291	validation-mlogloss:1.37906
[36m(train_xgb_ray_tune pid=1371762)[0m [585]	train-mlogloss:1.39249	validation-mlogloss:1.37864
[36m(train_xgb_ray_tune pid=1371762)[0m [586]	train-mlogloss:1.39215	validation-mlogloss:1.37824
[36m(train_xgb_ray_tune pid=1371762)[0m [587]	train-mlogloss:1.39171	validation-mlogloss:1.37778
[36m(train_xgb_ray_tune pid=1371782)[0m [510]	train-mlogloss:1.31081	validation-mlogloss:1.31854
[36m(train_xgb_ray_tune pid=1371782)[0m [511]	train-mlogloss:1.31024	validation-mlogloss:1.31797
[36m(train_xgb_ray_tune pid=1371782)[0m [512]	train-mlogloss:1.30971	validation-mlogloss:1.31750
[36m(train_xgb_ray_tune pid=1371754)[0m [556]	train-mlogloss:1.43107	validation-mlogloss:1.40805
[36m(train_xgb_ray_tune pid=1371754)[0m [557]	train-mlogloss:1.43079	validation-mlogloss:1.40775
[36m(train_xgb_ray_tune pid=1371754)[0m [558]	train-mlogloss:1.43041	validation-mlogloss:1.40730
[36m(train_xgb_ray_tune pid=1371754)[0m [559]	train-mlogloss:1.42997	validation-mlogloss:1.40679
[36m(train_xgb_ray_tune pid=1371786)[0m [608]	train-mlogloss:1.23342	validation-mlogloss:1.23602
[36m(train_xgb_ray_tune pid=1371786)[0m [609]	train-mlogloss:1.23305	validation-mlogloss:1.23575
[36m(train_xgb_ray_tune pid=1371786)[0m [610]	train-mlogloss:1.23266	validation-mlogloss:1.23547
[36m(train_xgb_ray_tune pid=1371786)[0m [611]	train-mlogloss:1.23226	validation-mlogloss:1.23522
[36m(train_xgb_ray_tune pid=1371793)[0m [612]	train-mlogloss:1.37840	validation-mlogloss:1.34656
[36m(train_xgb_ray_tune pid=1371793)[0m [613]	train-mlogloss:1.37826	validation-mlogloss:1.34644
[36m(train_xgb_ray_tune pid=1371793)[0m [614]	train-mlogloss:1.37817	validation-mlogloss:1.34636
[36m(train_xgb_ray_tune pid=1371793)[0m [615]	train-mlogloss:1.37809	validation-mlogloss:1.34626
[36m(train_xgb_ray_tune pid=1371793)[0m [616]	train-mlogloss:1.37794	validation-mlogloss:1.34612
[36m(train_xgb_ray_tune pid=1371762)[0m [588]	train-mlogloss:1.39134	validation-mlogloss:1.37740
[36m(train_xgb_ray_tune pid=1371762)[0m [589]	train-mlogloss:1.39091	validation-mlogloss:1.37692
[36m(train_xgb_ray_tune pid=1371762)[0m [590]	train-mlogloss:1.39043	validation-mlogloss:1.37636
[36m(train_xgb_ray_tune pid=1371782)[0m [513]	train-mlogloss:1.30921	validation-mlogloss:1.31691
[36m(train_xgb_ray_tune pid=1371782)[0m [514]	train-mlogloss:1.30864	validation-mlogloss:1.31634
[36m(train_xgb_ray_tune pid=1371782)[0m [515]	train-mlogloss:1.30816	validation-mlogloss:1.31582
[36m(train_xgb_ray_tune pid=1371782)[0m [516]	train-mlogloss:1.30766	validation-mlogloss:1.31527
[36m(train_xgb_ray_tune pid=1371754)[0m [560]	train-mlogloss:1.42972	validation-mlogloss:1.40649
[36m(train_xgb_ray_tune pid=1371754)[0m [561]	train-mlogloss:1.42943	validation-mlogloss:1.40621
[36m(train_xgb_ray_tune pid=1371754)[0m [562]	train-mlogloss:1.42913	validation-mlogloss:1.40589
[36m(train_xgb_ray_tune pid=1371754)[0m [563]	train-mlogloss:1.42885	validation-mlogloss:1.40559
[36m(train_xgb_ray_tune pid=1371786)[0m [612]	train-mlogloss:1.23189	validation-mlogloss:1.23490
[36m(train_xgb_ray_tune pid=1371786)[0m [613]	train-mlogloss:1.23150	validation-mlogloss:1.23467
[36m(train_xgb_ray_tune pid=1371786)[0m [614]	train-mlogloss:1.23110	validation-mlogloss:1.23442
[36m(train_xgb_ray_tune pid=1371786)[0m [615]	train-mlogloss:1.23071	validation-mlogloss:1.23411
[36m(train_xgb_ray_tune pid=1371793)[0m [617]	train-mlogloss:1.37781	validation-mlogloss:1.34597
[36m(train_xgb_ray_tune pid=1371793)[0m [618]	train-mlogloss:1.37768	validation-mlogloss:1.34583
[36m(train_xgb_ray_tune pid=1371762)[0m [591]	train-mlogloss:1.39002	validation-mlogloss:1.37587
[36m(train_xgb_ray_tune pid=1371762)[0m [592]	train-mlogloss:1.38957	validation-mlogloss:1.37538
[36m(train_xgb_ray_tune pid=1371762)[0m [593]	train-mlogloss:1.38912	validation-mlogloss:1.37492
[36m(train_xgb_ray_tune pid=1371762)[0m [594]	train-mlogloss:1.38871	validation-mlogloss:1.37445
[36m(train_xgb_ray_tune pid=1371782)[0m [517]	train-mlogloss:1.30710	validation-mlogloss:1.31476
[36m(train_xgb_ray_tune pid=1371782)[0m [518]	train-mlogloss:1.30659	validation-mlogloss:1.31423
[36m(train_xgb_ray_tune pid=1371782)[0m [519]	train-mlogloss:1.30605	validation-mlogloss:1.31369
[36m(train_xgb_ray_tune pid=1371782)[0m [520]	train-mlogloss:1.30558	validation-mlogloss:1.31324
[36m(train_xgb_ray_tune pid=1371762)[0m [595]	train-mlogloss:1.38837	validation-mlogloss:1.37409
[36m(train_xgb_ray_tune pid=1371754)[0m [564]	train-mlogloss:1.42857	validation-mlogloss:1.40529

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:06. Total running time: 44s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             41.2502 │
│ time_total_s                 41.2502 │
│ training_iteration                 1 │
│ validation_accuracy          0.53404 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:06. Total running time: 44s
[36m(train_xgb_ray_tune pid=1371754)[0m [565]	train-mlogloss:1.42828	validation-mlogloss:1.40495
[36m(train_xgb_ray_tune pid=1371754)[0m [566]	train-mlogloss:1.42805	validation-mlogloss:1.40470
[36m(train_xgb_ray_tune pid=1371754)[0m [567]	train-mlogloss:1.42773	validation-mlogloss:1.40433
[36m(train_xgb_ray_tune pid=1371754)[0m [568]	train-mlogloss:1.42739	validation-mlogloss:1.40399
[36m(train_xgb_ray_tune pid=1371786)[0m [616]	train-mlogloss:1.23026	validation-mlogloss:1.23374
[36m(train_xgb_ray_tune pid=1371786)[0m [617]	train-mlogloss:1.22987	validation-mlogloss:1.23340
[36m(train_xgb_ray_tune pid=1371786)[0m [618]	train-mlogloss:1.22947	validation-mlogloss:1.23310
[36m(train_xgb_ray_tune pid=1371786)[0m [619]	train-mlogloss:1.22906	validation-mlogloss:1.23285
[36m(train_xgb_ray_tune pid=1371762)[0m [596]	train-mlogloss:1.38791	validation-mlogloss:1.37362
[36m(train_xgb_ray_tune pid=1371762)[0m [597]	train-mlogloss:1.38754	validation-mlogloss:1.37319
[36m(train_xgb_ray_tune pid=1371762)[0m [598]	train-mlogloss:1.38717	validation-mlogloss:1.37275
[36m(train_xgb_ray_tune pid=1371762)[0m [599]	train-mlogloss:1.38674	validation-mlogloss:1.37229
[36m(train_xgb_ray_tune pid=1371782)[0m [521]	train-mlogloss:1.30509	validation-mlogloss:1.31269
[36m(train_xgb_ray_tune pid=1371782)[0m [522]	train-mlogloss:1.30456	validation-mlogloss:1.31212
[36m(train_xgb_ray_tune pid=1371782)[0m [523]	train-mlogloss:1.30403	validation-mlogloss:1.31156
[36m(train_xgb_ray_tune pid=1371782)[0m [524]	train-mlogloss:1.30341	validation-mlogloss:1.31094
[36m(train_xgb_ray_tune pid=1371754)[0m [569]	train-mlogloss:1.42713	validation-mlogloss:1.40372
[36m(train_xgb_ray_tune pid=1371754)[0m [570]	train-mlogloss:1.42687	validation-mlogloss:1.40344
[36m(train_xgb_ray_tune pid=1371754)[0m [571]	train-mlogloss:1.42652	validation-mlogloss:1.40306
[36m(train_xgb_ray_tune pid=1371754)[0m [572]	train-mlogloss:1.42620	validation-mlogloss:1.40273
[36m(train_xgb_ray_tune pid=1371786)[0m [620]	train-mlogloss:1.22864	validation-mlogloss:1.23259
[36m(train_xgb_ray_tune pid=1371786)[0m [621]	train-mlogloss:1.22824	validation-mlogloss:1.23222
[36m(train_xgb_ray_tune pid=1371786)[0m [622]	train-mlogloss:1.22778	validation-mlogloss:1.23185
[36m(train_xgb_ray_tune pid=1371786)[0m [623]	train-mlogloss:1.22738	validation-mlogloss:1.23162
[36m(train_xgb_ray_tune pid=1371762)[0m [600]	train-mlogloss:1.38630	validation-mlogloss:1.37180
[36m(train_xgb_ray_tune pid=1371762)[0m [601]	train-mlogloss:1.38587	validation-mlogloss:1.37135
[36m(train_xgb_ray_tune pid=1371762)[0m [602]	train-mlogloss:1.38552	validation-mlogloss:1.37095
[36m(train_xgb_ray_tune pid=1371762)[0m [603]	train-mlogloss:1.38516	validation-mlogloss:1.37055
[36m(train_xgb_ray_tune pid=1371782)[0m [525]	train-mlogloss:1.30293	validation-mlogloss:1.31039
[36m(train_xgb_ray_tune pid=1371782)[0m [526]	train-mlogloss:1.30244	validation-mlogloss:1.30988
[36m(train_xgb_ray_tune pid=1371782)[0m [527]	train-mlogloss:1.30192	validation-mlogloss:1.30934
[36m(train_xgb_ray_tune pid=1371782)[0m [528]	train-mlogloss:1.30138	validation-mlogloss:1.30881
[36m(train_xgb_ray_tune pid=1371754)[0m [573]	train-mlogloss:1.42584	validation-mlogloss:1.40236
[36m(train_xgb_ray_tune pid=1371754)[0m [574]	train-mlogloss:1.42564	validation-mlogloss:1.40214
[36m(train_xgb_ray_tune pid=1371754)[0m [575]	train-mlogloss:1.42540	validation-mlogloss:1.40187
[36m(train_xgb_ray_tune pid=1371754)[0m [576]	train-mlogloss:1.42518	validation-mlogloss:1.40168
[36m(train_xgb_ray_tune pid=1371754)[0m [577]	train-mlogloss:1.42494	validation-mlogloss:1.40140
[36m(train_xgb_ray_tune pid=1371786)[0m [624]	train-mlogloss:1.22696	validation-mlogloss:1.23140
[36m(train_xgb_ray_tune pid=1371786)[0m [625]	train-mlogloss:1.22655	validation-mlogloss:1.23120
[36m(train_xgb_ray_tune pid=1371786)[0m [626]	train-mlogloss:1.22617	validation-mlogloss:1.23089
[36m(train_xgb_ray_tune pid=1371786)[0m [627]	train-mlogloss:1.22576	validation-mlogloss:1.23056
[36m(train_xgb_ray_tune pid=1371786)[0m [628]	train-mlogloss:1.22539	validation-mlogloss:1.23025
[36m(train_xgb_ray_tune pid=1371762)[0m [604]	train-mlogloss:1.38488	validation-mlogloss:1.37024
[36m(train_xgb_ray_tune pid=1371762)[0m [605]	train-mlogloss:1.38457	validation-mlogloss:1.36993
[36m(train_xgb_ray_tune pid=1371762)[0m [606]	train-mlogloss:1.38412	validation-mlogloss:1.36941
[36m(train_xgb_ray_tune pid=1371762)[0m [607]	train-mlogloss:1.38372	validation-mlogloss:1.36898
[36m(train_xgb_ray_tune pid=1371782)[0m [529]	train-mlogloss:1.30086	validation-mlogloss:1.30827
[36m(train_xgb_ray_tune pid=1371782)[0m [530]	train-mlogloss:1.30032	validation-mlogloss:1.30777
[36m(train_xgb_ray_tune pid=1371782)[0m [531]	train-mlogloss:1.29984	validation-mlogloss:1.30723
[36m(train_xgb_ray_tune pid=1371782)[0m [532]	train-mlogloss:1.29935	validation-mlogloss:1.30672
[36m(train_xgb_ray_tune pid=1371754)[0m [578]	train-mlogloss:1.42468	validation-mlogloss:1.40113
[36m(train_xgb_ray_tune pid=1371754)[0m [579]	train-mlogloss:1.42446	validation-mlogloss:1.40092
[36m(train_xgb_ray_tune pid=1371754)[0m [580]	train-mlogloss:1.42427	validation-mlogloss:1.40072
[36m(train_xgb_ray_tune pid=1371754)[0m [581]	train-mlogloss:1.42395	validation-mlogloss:1.40037
[36m(train_xgb_ray_tune pid=1371786)[0m [629]	train-mlogloss:1.22500	validation-mlogloss:1.22995
[36m(train_xgb_ray_tune pid=1371786)[0m [630]	train-mlogloss:1.22460	validation-mlogloss:1.22965
[36m(train_xgb_ray_tune pid=1371786)[0m [631]	train-mlogloss:1.22425	validation-mlogloss:1.22941
[36m(train_xgb_ray_tune pid=1371786)[0m [632]	train-mlogloss:1.22389	validation-mlogloss:1.22907
[36m(train_xgb_ray_tune pid=1371762)[0m [608]	train-mlogloss:1.38337	validation-mlogloss:1.36858
[36m(train_xgb_ray_tune pid=1371762)[0m [609]	train-mlogloss:1.38295	validation-mlogloss:1.36807
[36m(train_xgb_ray_tune pid=1371762)[0m [610]	train-mlogloss:1.38258	validation-mlogloss:1.36765
[36m(train_xgb_ray_tune pid=1371762)[0m [611]	train-mlogloss:1.38221	validation-mlogloss:1.36723
[36m(train_xgb_ray_tune pid=1371782)[0m [533]	train-mlogloss:1.29883	validation-mlogloss:1.30621
[36m(train_xgb_ray_tune pid=1371782)[0m [534]	train-mlogloss:1.29835	validation-mlogloss:1.30572
[36m(train_xgb_ray_tune pid=1371782)[0m [535]	train-mlogloss:1.29783	validation-mlogloss:1.30519
[36m(train_xgb_ray_tune pid=1371782)[0m [536]	train-mlogloss:1.29735	validation-mlogloss:1.30466

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:07. Total running time: 44s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             41.7823 │
│ time_total_s                 41.7823 │
│ training_iteration                 1 │
│ validation_accuracy          0.51877 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:07. Total running time: 44s
[36m(train_xgb_ray_tune pid=1371754)[0m [582]	train-mlogloss:1.42377	validation-mlogloss:1.40018
[36m(train_xgb_ray_tune pid=1371754)[0m [583]	train-mlogloss:1.42348	validation-mlogloss:1.39988
[36m(train_xgb_ray_tune pid=1371754)[0m [584]	train-mlogloss:1.42325	validation-mlogloss:1.39963
[36m(train_xgb_ray_tune pid=1371754)[0m [585]	train-mlogloss:1.42295	validation-mlogloss:1.39930
[36m(train_xgb_ray_tune pid=1371786)[0m [633]	train-mlogloss:1.22352	validation-mlogloss:1.22878
[36m(train_xgb_ray_tune pid=1371786)[0m [634]	train-mlogloss:1.22317	validation-mlogloss:1.22851
[36m(train_xgb_ray_tune pid=1371786)[0m [635]	train-mlogloss:1.22278	validation-mlogloss:1.22822
[36m(train_xgb_ray_tune pid=1371786)[0m [636]	train-mlogloss:1.22245	validation-mlogloss:1.22806
[36m(train_xgb_ray_tune pid=1371762)[0m [612]	train-mlogloss:1.38183	validation-mlogloss:1.36682
[36m(train_xgb_ray_tune pid=1371762)[0m [613]	train-mlogloss:1.38145	validation-mlogloss:1.36640
[36m(train_xgb_ray_tune pid=1371762)[0m [614]	train-mlogloss:1.38116	validation-mlogloss:1.36613
[36m(train_xgb_ray_tune pid=1371762)[0m [615]	train-mlogloss:1.38083	validation-mlogloss:1.36577
[36m(train_xgb_ray_tune pid=1371782)[0m [537]	train-mlogloss:1.29689	validation-mlogloss:1.30417
[36m(train_xgb_ray_tune pid=1371782)[0m [538]	train-mlogloss:1.29637	validation-mlogloss:1.30359
[36m(train_xgb_ray_tune pid=1371782)[0m [539]	train-mlogloss:1.29587	validation-mlogloss:1.30311
[36m(train_xgb_ray_tune pid=1371782)[0m [540]	train-mlogloss:1.29538	validation-mlogloss:1.30260
[36m(train_xgb_ray_tune pid=1371754)[0m [586]	train-mlogloss:1.42273	validation-mlogloss:1.39907
[36m(train_xgb_ray_tune pid=1371762)[0m [616]	train-mlogloss:1.38048	validation-mlogloss:1.36538
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[36m(train_xgb_ray_tune pid=1371782)[0m [617]	train-mlogloss:1.26346	validation-mlogloss:1.27051
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[36m(train_xgb_ray_tune pid=1371754)[0m [678]	train-mlogloss:1.40677	validation-mlogloss:1.38184
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[36m(train_xgb_ray_tune pid=1371754)[0m [683]	train-mlogloss:1.40633	validation-mlogloss:1.38133
[36m(train_xgb_ray_tune pid=1371786)[0m [718]	train-mlogloss:1.19375	validation-mlogloss:1.20886
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[36m(train_xgb_ray_tune pid=1371762)[0m [707]	train-mlogloss:1.35492	validation-mlogloss:1.33814
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[36m(train_xgb_ray_tune pid=1371782)[0m [621]	train-mlogloss:1.26205	validation-mlogloss:1.26914
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[36m(train_xgb_ray_tune pid=1371786)[0m [722]	train-mlogloss:1.19250	validation-mlogloss:1.20804
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[36m(train_xgb_ray_tune pid=1371754)[0m [689]	train-mlogloss:1.40579	validation-mlogloss:1.38074
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[36m(train_xgb_ray_tune pid=1371754)[0m [693]	train-mlogloss:1.40538	validation-mlogloss:1.38032
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[36m(train_xgb_ray_tune pid=1371782)[0m [630]	train-mlogloss:1.25904	validation-mlogloss:1.26604
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[36m(train_xgb_ray_tune pid=1371754)[0m [698]	train-mlogloss:1.40496	validation-mlogloss:1.37979
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[36m(train_xgb_ray_tune pid=1371786)[0m [735]	train-mlogloss:1.18862	validation-mlogloss:1.20550
[36m(train_xgb_ray_tune pid=1371762)[0m [722]	train-mlogloss:1.35206	validation-mlogloss:1.33514
[36m(train_xgb_ray_tune pid=1371762)[0m [723]	train-mlogloss:1.35187	validation-mlogloss:1.33493
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[36m(train_xgb_ray_tune pid=1371762)[0m [726]	train-mlogloss:1.35135	validation-mlogloss:1.33441
[36m(train_xgb_ray_tune pid=1371782)[0m [635]	train-mlogloss:1.25745	validation-mlogloss:1.26448
[36m(train_xgb_ray_tune pid=1371782)[0m [636]	train-mlogloss:1.25709	validation-mlogloss:1.26413
[36m(train_xgb_ray_tune pid=1371782)[0m [637]	train-mlogloss:1.25680	validation-mlogloss:1.26388
[36m(train_xgb_ray_tune pid=1371782)[0m [638]	train-mlogloss:1.25645	validation-mlogloss:1.26351
[36m(train_xgb_ray_tune pid=1371754)[0m [699]	train-mlogloss:1.40489	validation-mlogloss:1.37973
[36m(train_xgb_ray_tune pid=1371754)[0m [700]	train-mlogloss:1.40480	validation-mlogloss:1.37962
[36m(train_xgb_ray_tune pid=1371754)[0m [701]	train-mlogloss:1.40475	validation-mlogloss:1.37956
[36m(train_xgb_ray_tune pid=1371754)[0m [702]	train-mlogloss:1.40459	validation-mlogloss:1.37941
[36m(train_xgb_ray_tune pid=1371754)[0m [703]	train-mlogloss:1.40448	validation-mlogloss:1.37929
[36m(train_xgb_ray_tune pid=1371786)[0m [736]	train-mlogloss:1.18834	validation-mlogloss:1.20531
[36m(train_xgb_ray_tune pid=1371786)[0m [737]	train-mlogloss:1.18797	validation-mlogloss:1.20509
[36m(train_xgb_ray_tune pid=1371786)[0m [738]	train-mlogloss:1.18767	validation-mlogloss:1.20499
[36m(train_xgb_ray_tune pid=1371786)[0m [739]	train-mlogloss:1.18739	validation-mlogloss:1.20483
[36m(train_xgb_ray_tune pid=1371762)[0m [727]	train-mlogloss:1.35111	validation-mlogloss:1.33413
[36m(train_xgb_ray_tune pid=1371762)[0m [728]	train-mlogloss:1.35093	validation-mlogloss:1.33395
[36m(train_xgb_ray_tune pid=1371762)[0m [729]	train-mlogloss:1.35081	validation-mlogloss:1.33379
[36m(train_xgb_ray_tune pid=1371762)[0m [730]	train-mlogloss:1.35063	validation-mlogloss:1.33358
[36m(train_xgb_ray_tune pid=1371782)[0m [639]	train-mlogloss:1.25613	validation-mlogloss:1.26319
[36m(train_xgb_ray_tune pid=1371782)[0m [640]	train-mlogloss:1.25582	validation-mlogloss:1.26285
[36m(train_xgb_ray_tune pid=1371782)[0m [641]	train-mlogloss:1.25549	validation-mlogloss:1.26255
[36m(train_xgb_ray_tune pid=1371782)[0m [642]	train-mlogloss:1.25518	validation-mlogloss:1.26226
[36m(train_xgb_ray_tune pid=1371754)[0m [704]	train-mlogloss:1.40440	validation-mlogloss:1.37919
[36m(train_xgb_ray_tune pid=1371754)[0m [705]	train-mlogloss:1.40431	validation-mlogloss:1.37909
[36m(train_xgb_ray_tune pid=1371754)[0m [706]	train-mlogloss:1.40423	validation-mlogloss:1.37900
[36m(train_xgb_ray_tune pid=1371754)[0m [707]	train-mlogloss:1.40419	validation-mlogloss:1.37895
[36m(train_xgb_ray_tune pid=1371754)[0m [708]	train-mlogloss:1.40409	validation-mlogloss:1.37883
[36m(train_xgb_ray_tune pid=1371786)[0m [740]	train-mlogloss:1.18708	validation-mlogloss:1.20466
[36m(train_xgb_ray_tune pid=1371786)[0m [741]	train-mlogloss:1.18677	validation-mlogloss:1.20447
[36m(train_xgb_ray_tune pid=1371786)[0m [742]	train-mlogloss:1.18647	validation-mlogloss:1.20436
[36m(train_xgb_ray_tune pid=1371786)[0m [743]	train-mlogloss:1.18612	validation-mlogloss:1.20417
[36m(train_xgb_ray_tune pid=1371782)[0m [643]	train-mlogloss:1.25486	validation-mlogloss:1.26194
[36m(train_xgb_ray_tune pid=1371782)[0m [644]	train-mlogloss:1.25451	validation-mlogloss:1.26162
[36m(train_xgb_ray_tune pid=1371782)[0m [645]	train-mlogloss:1.25423	validation-mlogloss:1.26137
[36m(train_xgb_ray_tune pid=1371782)[0m [646]	train-mlogloss:1.25387	validation-mlogloss:1.26106
[36m(train_xgb_ray_tune pid=1371782)[0m [647]	train-mlogloss:1.25358	validation-mlogloss:1.26078
[36m(train_xgb_ray_tune pid=1371754)[0m [709]	train-mlogloss:1.40397	validation-mlogloss:1.37875
[36m(train_xgb_ray_tune pid=1371754)[0m [710]	train-mlogloss:1.40378	validation-mlogloss:1.37852
[36m(train_xgb_ray_tune pid=1371754)[0m [711]	train-mlogloss:1.40373	validation-mlogloss:1.37846
[36m(train_xgb_ray_tune pid=1371754)[0m [712]	train-mlogloss:1.40368	validation-mlogloss:1.37840
[36m(train_xgb_ray_tune pid=1371754)[0m [713]	train-mlogloss:1.40347	validation-mlogloss:1.37819
[36m(train_xgb_ray_tune pid=1371786)[0m [744]	train-mlogloss:1.18580	validation-mlogloss:1.20395
[36m(train_xgb_ray_tune pid=1371786)[0m [745]	train-mlogloss:1.18549	validation-mlogloss:1.20378
[36m(train_xgb_ray_tune pid=1371786)[0m [746]	train-mlogloss:1.18519	validation-mlogloss:1.20352
[36m(train_xgb_ray_tune pid=1371786)[0m [747]	train-mlogloss:1.18487	validation-mlogloss:1.20329
[36m(train_xgb_ray_tune pid=1371782)[0m [648]	train-mlogloss:1.25329	validation-mlogloss:1.26047
[36m(train_xgb_ray_tune pid=1371782)[0m [649]	train-mlogloss:1.25294	validation-mlogloss:1.26012
[36m(train_xgb_ray_tune pid=1371782)[0m [650]	train-mlogloss:1.25265	validation-mlogloss:1.25982
[36m(train_xgb_ray_tune pid=1371782)[0m [651]	train-mlogloss:1.25237	validation-mlogloss:1.25957
[36m(train_xgb_ray_tune pid=1371786)[0m [748]	train-mlogloss:1.18458	validation-mlogloss:1.20309
[36m(train_xgb_ray_tune pid=1371754)[0m [714]	train-mlogloss:1.40340	validation-mlogloss:1.37811
[36m(train_xgb_ray_tune pid=1371754)[0m [715]	train-mlogloss:1.40326	validation-mlogloss:1.37796
[36m(train_xgb_ray_tune pid=1371754)[0m [716]	train-mlogloss:1.40319	validation-mlogloss:1.37792
[36m(train_xgb_ray_tune pid=1371754)[0m [717]	train-mlogloss:1.40303	validation-mlogloss:1.37774
[36m(train_xgb_ray_tune pid=1371754)[0m [718]	train-mlogloss:1.40301	validation-mlogloss:1.37770
[36m(train_xgb_ray_tune pid=1371786)[0m [749]	train-mlogloss:1.18428	validation-mlogloss:1.20280
[36m(train_xgb_ray_tune pid=1371786)[0m [750]	train-mlogloss:1.18400	validation-mlogloss:1.20263
[36m(train_xgb_ray_tune pid=1371786)[0m [751]	train-mlogloss:1.18369	validation-mlogloss:1.20248
[36m(train_xgb_ray_tune pid=1371786)[0m [752]	train-mlogloss:1.18336	validation-mlogloss:1.20234
[36m(train_xgb_ray_tune pid=1371782)[0m [652]	train-mlogloss:1.25202	validation-mlogloss:1.25924
[36m(train_xgb_ray_tune pid=1371782)[0m [653]	train-mlogloss:1.25167	validation-mlogloss:1.25891
[36m(train_xgb_ray_tune pid=1371782)[0m [654]	train-mlogloss:1.25140	validation-mlogloss:1.25862
[36m(train_xgb_ray_tune pid=1371782)[0m [655]	train-mlogloss:1.25108	validation-mlogloss:1.25834
[36m(train_xgb_ray_tune pid=1371754)[0m [719]	train-mlogloss:1.40294	validation-mlogloss:1.37762
[36m(train_xgb_ray_tune pid=1371754)[0m [720]	train-mlogloss:1.40289	validation-mlogloss:1.37759
[36m(train_xgb_ray_tune pid=1371754)[0m [721]	train-mlogloss:1.40282	validation-mlogloss:1.37751
[36m(train_xgb_ray_tune pid=1371754)[0m [722]	train-mlogloss:1.40271	validation-mlogloss:1.37744
[36m(train_xgb_ray_tune pid=1371754)[0m [723]	train-mlogloss:1.40263	validation-mlogloss:1.37734
[36m(train_xgb_ray_tune pid=1371786)[0m [753]	train-mlogloss:1.18308	validation-mlogloss:1.20218
[36m(train_xgb_ray_tune pid=1371786)[0m [754]	train-mlogloss:1.18281	validation-mlogloss:1.20204
[36m(train_xgb_ray_tune pid=1371786)[0m [755]	train-mlogloss:1.18255	validation-mlogloss:1.20191
[36m(train_xgb_ray_tune pid=1371786)[0m [756]	train-mlogloss:1.18226	validation-mlogloss:1.20175
[36m(train_xgb_ray_tune pid=1371782)[0m [656]	train-mlogloss:1.25079	validation-mlogloss:1.25806
[36m(train_xgb_ray_tune pid=1371782)[0m [657]	train-mlogloss:1.25050	validation-mlogloss:1.25777
[36m(train_xgb_ray_tune pid=1371782)[0m [658]	train-mlogloss:1.25022	validation-mlogloss:1.25747
[36m(train_xgb_ray_tune pid=1371782)[0m [659]	train-mlogloss:1.24991	validation-mlogloss:1.25715
[36m(train_xgb_ray_tune pid=1371782)[0m [660]	train-mlogloss:1.24963	validation-mlogloss:1.25687
[36m(train_xgb_ray_tune pid=1371754)[0m [724]	train-mlogloss:1.40253	validation-mlogloss:1.37724
[36m(train_xgb_ray_tune pid=1371754)[0m [725]	train-mlogloss:1.40246	validation-mlogloss:1.37715
[36m(train_xgb_ray_tune pid=1371754)[0m [726]	train-mlogloss:1.40243	validation-mlogloss:1.37711
[36m(train_xgb_ray_tune pid=1371754)[0m [727]	train-mlogloss:1.40234	validation-mlogloss:1.37701
[36m(train_xgb_ray_tune pid=1371754)[0m [728]	train-mlogloss:1.40222	validation-mlogloss:1.37689
[36m(train_xgb_ray_tune pid=1371786)[0m [757]	train-mlogloss:1.18196	validation-mlogloss:1.20152
[36m(train_xgb_ray_tune pid=1371786)[0m [758]	train-mlogloss:1.18164	validation-mlogloss:1.20130
[36m(train_xgb_ray_tune pid=1371786)[0m [759]	train-mlogloss:1.18134	validation-mlogloss:1.20115
[36m(train_xgb_ray_tune pid=1371786)[0m [760]	train-mlogloss:1.18103	validation-mlogloss:1.20092
[36m(train_xgb_ray_tune pid=1371782)[0m [661]	train-mlogloss:1.24937	validation-mlogloss:1.25664
[36m(train_xgb_ray_tune pid=1371782)[0m [662]	train-mlogloss:1.24910	validation-mlogloss:1.25639
[36m(train_xgb_ray_tune pid=1371782)[0m [663]	train-mlogloss:1.24878	validation-mlogloss:1.25605
[36m(train_xgb_ray_tune pid=1371782)[0m [664]	train-mlogloss:1.24852	validation-mlogloss:1.25575

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:10. Total running time: 47s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             44.9746 │
│ time_total_s                 44.9746 │
│ training_iteration                 1 │
│ validation_accuracy          0.51007 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:10. Total running time: 47s
[36m(train_xgb_ray_tune pid=1371754)[0m [729]	train-mlogloss:1.40219	validation-mlogloss:1.37688
[36m(train_xgb_ray_tune pid=1371754)[0m [730]	train-mlogloss:1.40213	validation-mlogloss:1.37680
[36m(train_xgb_ray_tune pid=1371754)[0m [731]	train-mlogloss:1.40206	validation-mlogloss:1.37675
[36m(train_xgb_ray_tune pid=1371754)[0m [732]	train-mlogloss:1.40191	validation-mlogloss:1.37662
[36m(train_xgb_ray_tune pid=1371754)[0m [733]	train-mlogloss:1.40184	validation-mlogloss:1.37654
[36m(train_xgb_ray_tune pid=1371782)[0m [665]	train-mlogloss:1.24825	validation-mlogloss:1.25550
[36m(train_xgb_ray_tune pid=1371782)[0m [666]	train-mlogloss:1.24802	validation-mlogloss:1.25529
[36m(train_xgb_ray_tune pid=1371782)[0m [667]	train-mlogloss:1.24773	validation-mlogloss:1.25505
[36m(train_xgb_ray_tune pid=1371782)[0m [668]	train-mlogloss:1.24751	validation-mlogloss:1.25481
[36m(train_xgb_ray_tune pid=1371754)[0m [734]	train-mlogloss:1.40179	validation-mlogloss:1.37647
[36m(train_xgb_ray_tune pid=1371754)[0m [735]	train-mlogloss:1.40174	validation-mlogloss:1.37642
[36m(train_xgb_ray_tune pid=1371782)[0m [669]	train-mlogloss:1.24723	validation-mlogloss:1.25452
[36m(train_xgb_ray_tune pid=1371782)[0m [670]	train-mlogloss:1.24697	validation-mlogloss:1.25429
[36m(train_xgb_ray_tune pid=1371782)[0m [671]	train-mlogloss:1.24671	validation-mlogloss:1.25404
[36m(train_xgb_ray_tune pid=1371782)[0m [672]	train-mlogloss:1.24643	validation-mlogloss:1.25383
[36m(train_xgb_ray_tune pid=1371782)[0m [673]	train-mlogloss:1.24617	validation-mlogloss:1.25356
[36m(train_xgb_ray_tune pid=1371782)[0m [674]	train-mlogloss:1.24592	validation-mlogloss:1.25330
[36m(train_xgb_ray_tune pid=1371782)[0m [675]	train-mlogloss:1.24566	validation-mlogloss:1.25310
[36m(train_xgb_ray_tune pid=1371782)[0m [676]	train-mlogloss:1.24542	validation-mlogloss:1.25285
[36m(train_xgb_ray_tune pid=1371782)[0m [677]	train-mlogloss:1.24519	validation-mlogloss:1.25260
[36m(train_xgb_ray_tune pid=1371782)[0m [678]	train-mlogloss:1.24496	validation-mlogloss:1.25241
[36m(train_xgb_ray_tune pid=1371782)[0m [679]	train-mlogloss:1.24471	validation-mlogloss:1.25217
[36m(train_xgb_ray_tune pid=1371782)[0m [680]	train-mlogloss:1.24452	validation-mlogloss:1.25199
[36m(train_xgb_ray_tune pid=1371782)[0m [681]	train-mlogloss:1.24438	validation-mlogloss:1.25186
[36m(train_xgb_ray_tune pid=1371782)[0m [682]	train-mlogloss:1.24410	validation-mlogloss:1.25161

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:11. Total running time: 48s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s               45.45 │
│ time_total_s                   45.45 │
│ training_iteration                 1 │
│ validation_accuracy          0.54019 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:11. Total running time: 48s

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:11. Total running time: 48s
[36m(train_xgb_ray_tune pid=1371754)[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 6x across cluster][0m
[36m(train_xgb_ray_tune pid=1371754)[0m   _log_deprecation_warning([32m [repeated 6x across cluster][0m
2025-11-06 14:05:11,454	INFO tune.py:1009 -- Wrote the latest version of all result files and experiment state to '/mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_PI/case_PI_XGB_acc_17_classes/XGBoost_hyperparameters_tuning' in 0.0099s.
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             45.3854 │
│ time_total_s                 45.3854 │
│ training_iteration                 1 │
│ validation_accuracy          0.50159 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:11. Total running time: 48s

Trial trial_1d10d finished iteration 1 at 2025-11-06 14:05:11. Total running time: 48s
╭──────────────────────────────────────╮
│ Trial trial_1d10d result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             45.8653 │
│ time_total_s                 45.8653 │
│ training_iteration                 1 │
│ validation_accuracy           0.5351 │
╰──────────────────────────────────────╯

Trial trial_1d10d completed after 1 iterations at 2025-11-06 14:05:11. Total running time: 48s

Trial status: 20 TERMINATED
Current time: 2025-11-06 14:05:11. Total running time: 48s
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_1d10d    TERMINATED                 736             3        0.00672781      0.518944             0.847053   25.8745                   133      17.7035        18.1901              7794        1           45.3854                0.501591  │
│ trial_1d10d    TERMINATED                 630             2        0.0096993       0.700232             0.807142   27.2881                   105     149.378        389.531               3899        1           40.3183                0.451326  │
│ trial_1d10d    TERMINATED                 216             3        0.0119583       0.849878             0.80138    24.0381                   149     102.201          7.6987              5283        1           24.2759                0.502439  │
│ trial_1d10d    TERMINATED                 617             3        0.0179237       0.533623             0.847934   19.913                    176     148.862         53.1872               479        1           36.9089                0.433934  │
│ trial_1d10d    TERMINATED                 631             2        0.0094698       0.843762             0.697157   24.2091                   175      65.1783        15.4702              3650        1           40.8409                0.507529  │
│ trial_1d10d    TERMINATED                 319             3        0.0121164       0.672751             0.67354     5.06911                  184       1.7707        10.6008              8252        1           33.6368                0.519194  │
│ trial_1d10d    TERMINATED                 741             2        0.0126543       0.793417             0.541353   23.6833                   153     114.485        299.831               1495        1           40.3019                0.464263  │
│ trial_1d10d    TERMINATED                 761             2        0.0085859       0.720189             0.81877     5.39026                   53      11.4473         6.57397             9857        1           45.45                  0.540191  │
│ trial_1d10d    TERMINATED                 619             2        0.0147093       0.716416             0.75808    11.4587                   112      34.1481       381.763               8829        1           41.7823                0.51877   │
│ trial_1d10d    TERMINATED                 495             2        0.00617581      0.771088             0.555695    6.73036                  107     836.851        757.965               3602        1            5.54454               0.0682927 │
│ trial_1d10d    TERMINATED                 392             2        0.00876909      0.636594             0.762604   13.8642                    54      23.4307         6.87095             1078        1           34.3416                0.518346  │
│ trial_1d10d    TERMINATED                 370             2        0.0101514       0.636663             0.796814   22.6373                   112      12.6395       809.842               4815        1           32.4477                0.443902  │
│ trial_1d10d    TERMINATED                 676             3        0.0184132       0.797429             0.717871   29.3403                   127       9.36209      138.236                874        1           41.2502                0.53404   │
│ trial_1d10d    TERMINATED                 731             3        0.00563236      0.532872             0.685933   28.1517                   110       4.74275       10.1884               799        1           44.9746                0.510074  │
│ trial_1d10d    TERMINATED                 683             3        0.00674663      0.818934             0.83247    20.9062                   132       4.55489       15.8284              3471        1           45.8653                0.535101  │
│ trial_1d10d    TERMINATED                 564             3        0.0100275       0.510695             0.610236   11.4704                   150     238.105         15.4943              8834        1           36.1003                0.401909  │
│ trial_1d10d    TERMINATED                 374             3        0.00901681      0.533349             0.541881   10.6509                    54     624.245        151.746               1137        1            6.0377                0.0682927 │
│ trial_1d10d    TERMINATED                 403             3        0.0137126       0.678732             0.592672   26.9875                    68       1.66332      657.617               8773        1           35.0071                0.485896  │
│ trial_1d10d    TERMINATED                 281             3        0.0136754       0.770822             0.795709   10.2767                    80      40.9199       343.147               5960        1           29.6988                0.527678  │
│ trial_1d10d    TERMINATED                 249             2        0.0117756       0.569994             0.593681    8.16291                   93     154.54          48.2581              4887        1           24.3102                0.467444  │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Mejores hiperparámetros XGBoost: {'num_boost_round': 761, 'max_depth': 2, 'learning_rate': 0.008585897745899178, 'subsample': 0.7201887667504905, 'colsample_bytree': 0.8187704854481974, 'gamma': 5.390259407384189, 'min_child_weight': 53, 'reg_alpha': 11.447292516105698, 'reg_lambda': 6.573967457712866, 'random_state': 9857}
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[10]	train-mlogloss:2.56018	validation-mlogloss:2.56532
[11]	train-mlogloss:2.54819	validation-mlogloss:2.55382
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[14]	train-mlogloss:2.51347	validation-mlogloss:2.52010
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[16]	train-mlogloss:2.49056	validation-mlogloss:2.49775
[17]	train-mlogloss:2.47979	validation-mlogloss:2.48725
[18]	train-mlogloss:2.46887	validation-mlogloss:2.47689
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[20]	train-mlogloss:2.44780	validation-mlogloss:2.45623
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[38]	train-mlogloss:2.28703	validation-mlogloss:2.30026
[39]	train-mlogloss:2.27907	validation-mlogloss:2.29260
[40]	train-mlogloss:2.27133	validation-mlogloss:2.28510
[41]	train-mlogloss:2.26380	validation-mlogloss:2.27755
[42]	train-mlogloss:2.25614	validation-mlogloss:2.27005
[43]	train-mlogloss:2.24875	validation-mlogloss:2.26277
[44]	train-mlogloss:2.24124	validation-mlogloss:2.25534
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[98]	train-mlogloss:1.93378	validation-mlogloss:1.94649
[99]	train-mlogloss:1.92939	validation-mlogloss:1.94200
[100]	train-mlogloss:1.92502	validation-mlogloss:1.93736
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[126]	train-mlogloss:1.82350	validation-mlogloss:1.83267
[127]	train-mlogloss:1.82007	validation-mlogloss:1.82916
[128]	train-mlogloss:1.81667	validation-mlogloss:1.82559
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[130]	train-mlogloss:1.80981	validation-mlogloss:1.81858
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[138]	train-mlogloss:1.78370	validation-mlogloss:1.79174
[139]	train-mlogloss:1.78038	validation-mlogloss:1.78838
[140]	train-mlogloss:1.77720	validation-mlogloss:1.78512
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[144]	train-mlogloss:1.76424	validation-mlogloss:1.77163
[145]	train-mlogloss:1.76124	validation-mlogloss:1.76851
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[151]	train-mlogloss:1.74330	validation-mlogloss:1.74971
[152]	train-mlogloss:1.74045	validation-mlogloss:1.74676
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[756]	train-mlogloss:1.18306	validation-mlogloss:1.20242
[757]	train-mlogloss:1.18278	validation-mlogloss:1.20224
[758]	train-mlogloss:1.18251	validation-mlogloss:1.20206
[759]	train-mlogloss:1.18222	validation-mlogloss:1.20185
[760]	train-mlogloss:1.18198	validation-mlogloss:1.20167
Saved model to disk.
[36m(train_xgb_ray_tune pid=1371782)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 2x across cluster][0m
[36m(train_xgb_ray_tune pid=1371782)[0m   _log_deprecation_warning([32m [repeated 2x across cluster][0m
2025-11-06 14:05:31.654853: 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`.
2025-11-06 14:05:31.666743: 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 00:00:1762434331.681290 1374000 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434331.685554 1374000 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434331.696241 1374000 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434331.696261 1374000 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434331.696263 1374000 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434331.696264 1374000 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:05:31.699596: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
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[611]	train-mlogloss:1.23213	validation-mlogloss:1.23495
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[711]	train-mlogloss:1.19653	validation-mlogloss:1.21036
[712]	train-mlogloss:1.19619	validation-mlogloss:1.21014
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[715]	train-mlogloss:1.19529	validation-mlogloss:1.20969
[716]	train-mlogloss:1.19493	validation-mlogloss:1.20945
[717]	train-mlogloss:1.19461	validation-mlogloss:1.20921
[718]	train-mlogloss:1.19429	validation-mlogloss:1.20902
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[720]	train-mlogloss:1.19363	validation-mlogloss:1.20853
[721]	train-mlogloss:1.19334	validation-mlogloss:1.20834
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[727]	train-mlogloss:1.19141	validation-mlogloss:1.20708
[728]	train-mlogloss:1.19112	validation-mlogloss:1.20688
[729]	train-mlogloss:1.19083	validation-mlogloss:1.20669
[730]	train-mlogloss:1.19046	validation-mlogloss:1.20644
[731]	train-mlogloss:1.19017	validation-mlogloss:1.20625
[732]	train-mlogloss:1.18983	validation-mlogloss:1.20609
[733]	train-mlogloss:1.18949	validation-mlogloss:1.20595
[734]	train-mlogloss:1.18913	validation-mlogloss:1.20577
[735]	train-mlogloss:1.18883	validation-mlogloss:1.20559
[736]	train-mlogloss:1.18855	validation-mlogloss:1.20543
[737]	train-mlogloss:1.18824	validation-mlogloss:1.20522
[738]	train-mlogloss:1.18792	validation-mlogloss:1.20508
[739]	train-mlogloss:1.18759	validation-mlogloss:1.20496
[740]	train-mlogloss:1.18731	validation-mlogloss:1.20482
[741]	train-mlogloss:1.18701	validation-mlogloss:1.20465
[742]	train-mlogloss:1.18670	validation-mlogloss:1.20451
[743]	train-mlogloss:1.18638	validation-mlogloss:1.20430
[744]	train-mlogloss:1.18604	validation-mlogloss:1.20410
[745]	train-mlogloss:1.18575	validation-mlogloss:1.20392
[746]	train-mlogloss:1.18547	validation-mlogloss:1.20374
[747]	train-mlogloss:1.18515	validation-mlogloss:1.20356
[748]	train-mlogloss:1.18483	validation-mlogloss:1.20334
[749]	train-mlogloss:1.18449	validation-mlogloss:1.20318
[750]	train-mlogloss:1.18417	validation-mlogloss:1.20302
[751]	train-mlogloss:1.18382	validation-mlogloss:1.20275
[752]	train-mlogloss:1.18354	validation-mlogloss:1.20255
[753]	train-mlogloss:1.18324	validation-mlogloss:1.20237
[754]	train-mlogloss:1.18298	validation-mlogloss:1.20220
[755]	train-mlogloss:1.18269	validation-mlogloss:1.20207
[756]	train-mlogloss:1.18240	validation-mlogloss:1.20191
[757]	train-mlogloss:1.18209	validation-mlogloss:1.20176
[758]	train-mlogloss:1.18180	validation-mlogloss:1.20159
[759]	train-mlogloss:1.18153	validation-mlogloss:1.20143
[760]	train-mlogloss:1.18124	validation-mlogloss:1.20123
Saved model to disk.
2025-11-06 14:05:56.103192: 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`.
2025-11-06 14:05:56.114592: 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 00:00:1762434356.127831 1374413 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434356.132010 1374413 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434356.142003 1374413 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434356.142023 1374413 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434356.142024 1374413 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434356.142026 1374413 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:05:56.145257: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69331	validation-mlogloss:2.69376
[1]	train-mlogloss:2.67850	validation-mlogloss:2.67942
[2]	train-mlogloss:2.66443	validation-mlogloss:2.66595
[3]	train-mlogloss:2.65077	validation-mlogloss:2.65273
[4]	train-mlogloss:2.63680	validation-mlogloss:2.63935
[5]	train-mlogloss:2.62348	validation-mlogloss:2.62686
[6]	train-mlogloss:2.61020	validation-mlogloss:2.61450
[7]	train-mlogloss:2.59699	validation-mlogloss:2.60152
[8]	train-mlogloss:2.58417	validation-mlogloss:2.58930
[9]	train-mlogloss:2.57175	validation-mlogloss:2.57750
[10]	train-mlogloss:2.55976	validation-mlogloss:2.56619
[11]	train-mlogloss:2.54797	validation-mlogloss:2.55467
[12]	train-mlogloss:2.53595	validation-mlogloss:2.54306
[13]	train-mlogloss:2.52419	validation-mlogloss:2.53171
[14]	train-mlogloss:2.51290	validation-mlogloss:2.52093
[15]	train-mlogloss:2.50176	validation-mlogloss:2.51029
[16]	train-mlogloss:2.49049	validation-mlogloss:2.49933
[17]	train-mlogloss:2.47961	validation-mlogloss:2.48900
[18]	train-mlogloss:2.46888	validation-mlogloss:2.47878
[19]	train-mlogloss:2.45843	validation-mlogloss:2.46894
[20]	train-mlogloss:2.44834	validation-mlogloss:2.45930
[21]	train-mlogloss:2.43819	validation-mlogloss:2.44940
[22]	train-mlogloss:2.42813	validation-mlogloss:2.43952
[23]	train-mlogloss:2.41825	validation-mlogloss:2.42984
[24]	train-mlogloss:2.40848	validation-mlogloss:2.42048
[25]	train-mlogloss:2.39908	validation-mlogloss:2.41147
[26]	train-mlogloss:2.38977	validation-mlogloss:2.40249
[27]	train-mlogloss:2.38066	validation-mlogloss:2.39357
[28]	train-mlogloss:2.37166	validation-mlogloss:2.38491
[29]	train-mlogloss:2.36285	validation-mlogloss:2.37652
[30]	train-mlogloss:2.35395	validation-mlogloss:2.36785
[31]	train-mlogloss:2.34544	validation-mlogloss:2.35939
[32]	train-mlogloss:2.33650	validation-mlogloss:2.35069
[33]	train-mlogloss:2.32794	validation-mlogloss:2.34231
[34]	train-mlogloss:2.31963	validation-mlogloss:2.33417
[35]	train-mlogloss:2.31124	validation-mlogloss:2.32585
[36]	train-mlogloss:2.30264	validation-mlogloss:2.31712
[37]	train-mlogloss:2.29446	validation-mlogloss:2.30904
[38]	train-mlogloss:2.28665	validation-mlogloss:2.30160
[39]	train-mlogloss:2.27861	validation-mlogloss:2.29366
[40]	train-mlogloss:2.27083	validation-mlogloss:2.28612
[41]	train-mlogloss:2.26321	validation-mlogloss:2.27860
[42]	train-mlogloss:2.25547	validation-mlogloss:2.27110
[43]	train-mlogloss:2.24809	validation-mlogloss:2.26389
[44]	train-mlogloss:2.24066	validation-mlogloss:2.25662
[45]	train-mlogloss:2.23331	validation-mlogloss:2.24949
[46]	train-mlogloss:2.22610	validation-mlogloss:2.24264
[47]	train-mlogloss:2.21897	validation-mlogloss:2.23573
[48]	train-mlogloss:2.21185	validation-mlogloss:2.22866
[49]	train-mlogloss:2.20496	validation-mlogloss:2.22177
[50]	train-mlogloss:2.19817	validation-mlogloss:2.21514
[51]	train-mlogloss:2.19138	validation-mlogloss:2.20832
[52]	train-mlogloss:2.18431	validation-mlogloss:2.20117
[53]	train-mlogloss:2.17764	validation-mlogloss:2.19470
[54]	train-mlogloss:2.17123	validation-mlogloss:2.18846
[55]	train-mlogloss:2.16476	validation-mlogloss:2.18216
[56]	train-mlogloss:2.15817	validation-mlogloss:2.17559
[57]	train-mlogloss:2.15167	validation-mlogloss:2.16881
[58]	train-mlogloss:2.14540	validation-mlogloss:2.16258
[59]	train-mlogloss:2.13896	validation-mlogloss:2.15595
[60]	train-mlogloss:2.13272	validation-mlogloss:2.14984
[61]	train-mlogloss:2.12640	validation-mlogloss:2.14335
[62]	train-mlogloss:2.12015	validation-mlogloss:2.13706
[63]	train-mlogloss:2.11401	validation-mlogloss:2.13069
[64]	train-mlogloss:2.10782	validation-mlogloss:2.12443
[65]	train-mlogloss:2.10162	validation-mlogloss:2.11807
[66]	train-mlogloss:2.09593	validation-mlogloss:2.11245
[67]	train-mlogloss:2.09017	validation-mlogloss:2.10663
[68]	train-mlogloss:2.08452	validation-mlogloss:2.10099
[69]	train-mlogloss:2.07879	validation-mlogloss:2.09519
[70]	train-mlogloss:2.07304	validation-mlogloss:2.08926
[71]	train-mlogloss:2.06745	validation-mlogloss:2.08366
[72]	train-mlogloss:2.06170	validation-mlogloss:2.07776
[73]	train-mlogloss:2.05617	validation-mlogloss:2.07208
[74]	train-mlogloss:2.05067	validation-mlogloss:2.06645
[75]	train-mlogloss:2.04522	validation-mlogloss:2.06082
[76]	train-mlogloss:2.03981	validation-mlogloss:2.05540
[77]	train-mlogloss:2.03457	validation-mlogloss:2.05009
[78]	train-mlogloss:2.02930	validation-mlogloss:2.04487
[79]	train-mlogloss:2.02420	validation-mlogloss:2.03960
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[681]	train-mlogloss:1.20678	validation-mlogloss:1.21708
[682]	train-mlogloss:1.20644	validation-mlogloss:1.21685
[683]	train-mlogloss:1.20606	validation-mlogloss:1.21667
[684]	train-mlogloss:1.20567	validation-mlogloss:1.21644
[685]	train-mlogloss:1.20532	validation-mlogloss:1.21630
[686]	train-mlogloss:1.20496	validation-mlogloss:1.21608
[687]	train-mlogloss:1.20465	validation-mlogloss:1.21588
[688]	train-mlogloss:1.20432	validation-mlogloss:1.21569
[689]	train-mlogloss:1.20398	validation-mlogloss:1.21548
[690]	train-mlogloss:1.20367	validation-mlogloss:1.21531
[691]	train-mlogloss:1.20331	validation-mlogloss:1.21510
[692]	train-mlogloss:1.20296	validation-mlogloss:1.21487
[693]	train-mlogloss:1.20265	validation-mlogloss:1.21476
[694]	train-mlogloss:1.20237	validation-mlogloss:1.21457
[695]	train-mlogloss:1.20206	validation-mlogloss:1.21432
[696]	train-mlogloss:1.20172	validation-mlogloss:1.21413
[697]	train-mlogloss:1.20139	validation-mlogloss:1.21392
[698]	train-mlogloss:1.20104	validation-mlogloss:1.21372
[699]	train-mlogloss:1.20073	validation-mlogloss:1.21349
[700]	train-mlogloss:1.20039	validation-mlogloss:1.21326
[701]	train-mlogloss:1.20005	validation-mlogloss:1.21300
[702]	train-mlogloss:1.19973	validation-mlogloss:1.21283
[703]	train-mlogloss:1.19940	validation-mlogloss:1.21262
[704]	train-mlogloss:1.19907	validation-mlogloss:1.21242
[705]	train-mlogloss:1.19872	validation-mlogloss:1.21225
[706]	train-mlogloss:1.19839	validation-mlogloss:1.21212
[707]	train-mlogloss:1.19806	validation-mlogloss:1.21192
[708]	train-mlogloss:1.19775	validation-mlogloss:1.21177
[709]	train-mlogloss:1.19739	validation-mlogloss:1.21160
[710]	train-mlogloss:1.19703	validation-mlogloss:1.21138
[711]	train-mlogloss:1.19674	validation-mlogloss:1.21119
[712]	train-mlogloss:1.19641	validation-mlogloss:1.21098
[713]	train-mlogloss:1.19609	validation-mlogloss:1.21082
[714]	train-mlogloss:1.19581	validation-mlogloss:1.21058
[715]	train-mlogloss:1.19549	validation-mlogloss:1.21037
[716]	train-mlogloss:1.19520	validation-mlogloss:1.21018
[717]	train-mlogloss:1.19486	validation-mlogloss:1.20991
[718]	train-mlogloss:1.19455	validation-mlogloss:1.20976
[719]	train-mlogloss:1.19427	validation-mlogloss:1.20954
[720]	train-mlogloss:1.19390	validation-mlogloss:1.20930
[721]	train-mlogloss:1.19356	validation-mlogloss:1.20911
[722]	train-mlogloss:1.19321	validation-mlogloss:1.20892
[723]	train-mlogloss:1.19289	validation-mlogloss:1.20873
[724]	train-mlogloss:1.19260	validation-mlogloss:1.20853
[725]	train-mlogloss:1.19226	validation-mlogloss:1.20826
[726]	train-mlogloss:1.19193	validation-mlogloss:1.20808
[727]	train-mlogloss:1.19158	validation-mlogloss:1.20787
[728]	train-mlogloss:1.19131	validation-mlogloss:1.20772
[729]	train-mlogloss:1.19099	validation-mlogloss:1.20755
[730]	train-mlogloss:1.19067	validation-mlogloss:1.20734
[731]	train-mlogloss:1.19036	validation-mlogloss:1.20712
[732]	train-mlogloss:1.19007	validation-mlogloss:1.20696
[733]	train-mlogloss:1.18977	validation-mlogloss:1.20675
[734]	train-mlogloss:1.18947	validation-mlogloss:1.20661
[735]	train-mlogloss:1.18917	validation-mlogloss:1.20644
[736]	train-mlogloss:1.18890	validation-mlogloss:1.20626
[737]	train-mlogloss:1.18866	validation-mlogloss:1.20614
[738]	train-mlogloss:1.18836	validation-mlogloss:1.20595
[739]	train-mlogloss:1.18804	validation-mlogloss:1.20574
[740]	train-mlogloss:1.18774	validation-mlogloss:1.20552
[741]	train-mlogloss:1.18743	validation-mlogloss:1.20535
[742]	train-mlogloss:1.18709	validation-mlogloss:1.20516
[743]	train-mlogloss:1.18679	validation-mlogloss:1.20499
[744]	train-mlogloss:1.18646	validation-mlogloss:1.20476
[745]	train-mlogloss:1.18620	validation-mlogloss:1.20458
[746]	train-mlogloss:1.18586	validation-mlogloss:1.20437
[747]	train-mlogloss:1.18556	validation-mlogloss:1.20420
[748]	train-mlogloss:1.18528	validation-mlogloss:1.20402
[749]	train-mlogloss:1.18498	validation-mlogloss:1.20388
[750]	train-mlogloss:1.18465	validation-mlogloss:1.20375
[751]	train-mlogloss:1.18436	validation-mlogloss:1.20358
[752]	train-mlogloss:1.18406	validation-mlogloss:1.20337
[753]	train-mlogloss:1.18374	validation-mlogloss:1.20323
[754]	train-mlogloss:1.18344	validation-mlogloss:1.20311
[755]	train-mlogloss:1.18316	validation-mlogloss:1.20291
[756]	train-mlogloss:1.18288	validation-mlogloss:1.20274
[757]	train-mlogloss:1.18259	validation-mlogloss:1.20256
[758]	train-mlogloss:1.18230	validation-mlogloss:1.20237
[759]	train-mlogloss:1.18200	validation-mlogloss:1.20222
[760]	train-mlogloss:1.18169	validation-mlogloss:1.20205
Saved model to disk.
2025-11-06 14:06:20.449407: 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`.
2025-11-06 14:06:20.460684: 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 00:00:1762434380.473960 1374818 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434380.478080 1374818 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434380.487931 1374818 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434380.487948 1374818 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434380.487950 1374818 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434380.487952 1374818 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:06:20.491084: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69305	validation-mlogloss:2.69360
[1]	train-mlogloss:2.67899	validation-mlogloss:2.67990
[2]	train-mlogloss:2.66443	validation-mlogloss:2.66575
[3]	train-mlogloss:2.65049	validation-mlogloss:2.65225
[4]	train-mlogloss:2.63691	validation-mlogloss:2.63932
[5]	train-mlogloss:2.62327	validation-mlogloss:2.62613
[6]	train-mlogloss:2.61000	validation-mlogloss:2.61368
[7]	train-mlogloss:2.59697	validation-mlogloss:2.60112
[8]	train-mlogloss:2.58417	validation-mlogloss:2.58901
[9]	train-mlogloss:2.57201	validation-mlogloss:2.57725
[10]	train-mlogloss:2.56009	validation-mlogloss:2.56582
[11]	train-mlogloss:2.54802	validation-mlogloss:2.55436
[12]	train-mlogloss:2.53594	validation-mlogloss:2.54267
[13]	train-mlogloss:2.52416	validation-mlogloss:2.53152
[14]	train-mlogloss:2.51257	validation-mlogloss:2.52037
[15]	train-mlogloss:2.50132	validation-mlogloss:2.50932
[16]	train-mlogloss:2.49023	validation-mlogloss:2.49849
[17]	train-mlogloss:2.47921	validation-mlogloss:2.48795
[18]	train-mlogloss:2.46876	validation-mlogloss:2.47789
[19]	train-mlogloss:2.45826	validation-mlogloss:2.46770
[20]	train-mlogloss:2.44792	validation-mlogloss:2.45758
[21]	train-mlogloss:2.43783	validation-mlogloss:2.44777
[22]	train-mlogloss:2.42784	validation-mlogloss:2.43820
[23]	train-mlogloss:2.41768	validation-mlogloss:2.42837
[24]	train-mlogloss:2.40799	validation-mlogloss:2.41895
[25]	train-mlogloss:2.39864	validation-mlogloss:2.40985
[26]	train-mlogloss:2.38909	validation-mlogloss:2.40065
[27]	train-mlogloss:2.37992	validation-mlogloss:2.39151
[28]	train-mlogloss:2.37084	validation-mlogloss:2.38255
[29]	train-mlogloss:2.36215	validation-mlogloss:2.37404
[30]	train-mlogloss:2.35311	validation-mlogloss:2.36528
[31]	train-mlogloss:2.34437	validation-mlogloss:2.35681
[32]	train-mlogloss:2.33585	validation-mlogloss:2.34855
[33]	train-mlogloss:2.32738	validation-mlogloss:2.34013
[34]	train-mlogloss:2.31894	validation-mlogloss:2.33193
[35]	train-mlogloss:2.31074	validation-mlogloss:2.32366
[36]	train-mlogloss:2.30282	validation-mlogloss:2.31624
[37]	train-mlogloss:2.29470	validation-mlogloss:2.30820
[38]	train-mlogloss:2.28681	validation-mlogloss:2.30035
[39]	train-mlogloss:2.27881	validation-mlogloss:2.29263
[40]	train-mlogloss:2.27121	validation-mlogloss:2.28538
[41]	train-mlogloss:2.26345	validation-mlogloss:2.27789
[42]	train-mlogloss:2.25581	validation-mlogloss:2.27051
[43]	train-mlogloss:2.24806	validation-mlogloss:2.26284
[44]	train-mlogloss:2.24072	validation-mlogloss:2.25577
[45]	train-mlogloss:2.23332	validation-mlogloss:2.24862
[46]	train-mlogloss:2.22590	validation-mlogloss:2.24120
[47]	train-mlogloss:2.21877	validation-mlogloss:2.23417
[48]	train-mlogloss:2.21178	validation-mlogloss:2.22731
[49]	train-mlogloss:2.20467	validation-mlogloss:2.22002
[50]	train-mlogloss:2.19797	validation-mlogloss:2.21359
[51]	train-mlogloss:2.19092	validation-mlogloss:2.20647
[52]	train-mlogloss:2.18401	validation-mlogloss:2.19964
[53]	train-mlogloss:2.17733	validation-mlogloss:2.19322
[54]	train-mlogloss:2.17073	validation-mlogloss:2.18669
[55]	train-mlogloss:2.16422	validation-mlogloss:2.18005
[56]	train-mlogloss:2.15752	validation-mlogloss:2.17322
[57]	train-mlogloss:2.15111	validation-mlogloss:2.16682
[58]	train-mlogloss:2.14476	validation-mlogloss:2.16037
[59]	train-mlogloss:2.13834	validation-mlogloss:2.15391
[60]	train-mlogloss:2.13232	validation-mlogloss:2.14801
[61]	train-mlogloss:2.12589	validation-mlogloss:2.14140
[62]	train-mlogloss:2.11973	validation-mlogloss:2.13501
[63]	train-mlogloss:2.11379	validation-mlogloss:2.12895
[64]	train-mlogloss:2.10770	validation-mlogloss:2.12265
[65]	train-mlogloss:2.10198	validation-mlogloss:2.11687
[66]	train-mlogloss:2.09607	validation-mlogloss:2.11105
[67]	train-mlogloss:2.09018	validation-mlogloss:2.10492
[68]	train-mlogloss:2.08464	validation-mlogloss:2.09948
[69]	train-mlogloss:2.07877	validation-mlogloss:2.09366
[70]	train-mlogloss:2.07313	validation-mlogloss:2.08801
[71]	train-mlogloss:2.06754	validation-mlogloss:2.08225
[72]	train-mlogloss:2.06204	validation-mlogloss:2.07680
[73]	train-mlogloss:2.05655	validation-mlogloss:2.07137
[74]	train-mlogloss:2.05117	validation-mlogloss:2.06607
[75]	train-mlogloss:2.04576	validation-mlogloss:2.06053
[76]	train-mlogloss:2.04033	validation-mlogloss:2.05500
[77]	train-mlogloss:2.03510	validation-mlogloss:2.04964
[78]	train-mlogloss:2.02984	validation-mlogloss:2.04427
[79]	train-mlogloss:2.02451	validation-mlogloss:2.03889
[80]	train-mlogloss:2.01936	validation-mlogloss:2.03356
[81]	train-mlogloss:2.01436	validation-mlogloss:2.02850
[82]	train-mlogloss:2.00924	validation-mlogloss:2.02324
[83]	train-mlogloss:2.00412	validation-mlogloss:2.01793
[84]	train-mlogloss:1.99902	validation-mlogloss:2.01261
[85]	train-mlogloss:1.99395	validation-mlogloss:2.00747
[86]	train-mlogloss:1.98908	validation-mlogloss:2.00248
[87]	train-mlogloss:1.98422	validation-mlogloss:1.99744
[88]	train-mlogloss:1.97940	validation-mlogloss:1.99261
[89]	train-mlogloss:1.97466	validation-mlogloss:1.98780
[90]	train-mlogloss:1.96993	validation-mlogloss:1.98294
[91]	train-mlogloss:1.96529	validation-mlogloss:1.97845
[92]	train-mlogloss:1.96075	validation-mlogloss:1.97401
[93]	train-mlogloss:1.95622	validation-mlogloss:1.96946
[94]	train-mlogloss:1.95164	validation-mlogloss:1.96475
[95]	train-mlogloss:1.94707	validation-mlogloss:1.95991
[96]	train-mlogloss:1.94263	validation-mlogloss:1.95530
[97]	train-mlogloss:1.93804	validation-mlogloss:1.95059
[98]	train-mlogloss:1.93367	validation-mlogloss:1.94607
[99]	train-mlogloss:1.92924	validation-mlogloss:1.94147
[100]	train-mlogloss:1.92499	validation-mlogloss:1.93695
[101]	train-mlogloss:1.92062	validation-mlogloss:1.93249
[102]	train-mlogloss:1.91635	validation-mlogloss:1.92797
[103]	train-mlogloss:1.91216	validation-mlogloss:1.92370
[104]	train-mlogloss:1.90801	validation-mlogloss:1.91937
[105]	train-mlogloss:1.90390	validation-mlogloss:1.91497
[106]	train-mlogloss:1.89987	validation-mlogloss:1.91069
[107]	train-mlogloss:1.89577	validation-mlogloss:1.90636
[108]	train-mlogloss:1.89140	validation-mlogloss:1.90186
[109]	train-mlogloss:1.88738	validation-mlogloss:1.89775
[110]	train-mlogloss:1.88350	validation-mlogloss:1.89372
[111]	train-mlogloss:1.87944	validation-mlogloss:1.88944
[112]	train-mlogloss:1.87526	validation-mlogloss:1.88507
[113]	train-mlogloss:1.87146	validation-mlogloss:1.88110
[114]	train-mlogloss:1.86751	validation-mlogloss:1.87698
[115]	train-mlogloss:1.86347	validation-mlogloss:1.87267
[116]	train-mlogloss:1.85936	validation-mlogloss:1.86843
[117]	train-mlogloss:1.85553	validation-mlogloss:1.86441
[118]	train-mlogloss:1.85190	validation-mlogloss:1.86063
[119]	train-mlogloss:1.84818	validation-mlogloss:1.85674
[120]	train-mlogloss:1.84421	validation-mlogloss:1.85272
[121]	train-mlogloss:1.84033	validation-mlogloss:1.84853
[122]	train-mlogloss:1.83683	validation-mlogloss:1.84497
[123]	train-mlogloss:1.83296	validation-mlogloss:1.84098
[124]	train-mlogloss:1.82939	validation-mlogloss:1.83724
[125]	train-mlogloss:1.82589	validation-mlogloss:1.83358
[126]	train-mlogloss:1.82234	validation-mlogloss:1.82984
[127]	train-mlogloss:1.81862	validation-mlogloss:1.82602
[128]	train-mlogloss:1.81514	validation-mlogloss:1.82233
[129]	train-mlogloss:1.81178	validation-mlogloss:1.81892
[130]	train-mlogloss:1.80829	validation-mlogloss:1.81534
[131]	train-mlogloss:1.80484	validation-mlogloss:1.81173
[132]	train-mlogloss:1.80145	validation-mlogloss:1.80828
[133]	train-mlogloss:1.79821	validation-mlogloss:1.80495
[134]	train-mlogloss:1.79492	validation-mlogloss:1.80152
[135]	train-mlogloss:1.79162	validation-mlogloss:1.79812
[136]	train-mlogloss:1.78820	validation-mlogloss:1.79459
[137]	train-mlogloss:1.78504	validation-mlogloss:1.79133
[138]	train-mlogloss:1.78182	validation-mlogloss:1.78803
[139]	train-mlogloss:1.77843	validation-mlogloss:1.78445
[140]	train-mlogloss:1.77527	validation-mlogloss:1.78117
[141]	train-mlogloss:1.77218	validation-mlogloss:1.77799
[142]	train-mlogloss:1.76914	validation-mlogloss:1.77487
[143]	train-mlogloss:1.76619	validation-mlogloss:1.77179
[144]	train-mlogloss:1.76314	validation-mlogloss:1.76855
[145]	train-mlogloss:1.76001	validation-mlogloss:1.76520
[146]	train-mlogloss:1.75701	validation-mlogloss:1.76210
[147]	train-mlogloss:1.75371	validation-mlogloss:1.75866
[148]	train-mlogloss:1.75072	validation-mlogloss:1.75571
[149]	train-mlogloss:1.74756	validation-mlogloss:1.75238
[150]	train-mlogloss:1.74444	validation-mlogloss:1.74918
[151]	train-mlogloss:1.74131	validation-mlogloss:1.74603
[152]	train-mlogloss:1.73823	validation-mlogloss:1.74290
[153]	train-mlogloss:1.73543	validation-mlogloss:1.73995
[154]	train-mlogloss:1.73236	validation-mlogloss:1.73678
[155]	train-mlogloss:1.72960	validation-mlogloss:1.73387
[156]	train-mlogloss:1.72678	validation-mlogloss:1.73093
[157]	train-mlogloss:1.72404	validation-mlogloss:1.72808
[158]	train-mlogloss:1.72137	validation-mlogloss:1.72526
[159]	train-mlogloss:1.71861	validation-mlogloss:1.72234
[160]	train-mlogloss:1.71586	validation-mlogloss:1.71954
[161]	train-mlogloss:1.71304	validation-mlogloss:1.71666
[162]	train-mlogloss:1.71018	validation-mlogloss:1.71362
[163]	train-mlogloss:1.70734	validation-mlogloss:1.71064
[164]	train-mlogloss:1.70447	validation-mlogloss:1.70763
[165]	train-mlogloss:1.70166	validation-mlogloss:1.70467
[166]	train-mlogloss:1.69889	validation-mlogloss:1.70182
[167]	train-mlogloss:1.69605	validation-mlogloss:1.69894
[168]	train-mlogloss:1.69330	validation-mlogloss:1.69605
[169]	train-mlogloss:1.69061	validation-mlogloss:1.69326
[170]	train-mlogloss:1.68791	validation-mlogloss:1.69043
[171]	train-mlogloss:1.68524	validation-mlogloss:1.68772
[172]	train-mlogloss:1.68263	validation-mlogloss:1.68496
[173]	train-mlogloss:1.67995	validation-mlogloss:1.68215
[174]	train-mlogloss:1.67734	validation-mlogloss:1.67925
[175]	train-mlogloss:1.67475	validation-mlogloss:1.67659
[176]	train-mlogloss:1.67214	validation-mlogloss:1.67378
[177]	train-mlogloss:1.66964	validation-mlogloss:1.67115
[178]	train-mlogloss:1.66708	validation-mlogloss:1.66839
[179]	train-mlogloss:1.66454	validation-mlogloss:1.66575
[180]	train-mlogloss:1.66206	validation-mlogloss:1.66297
[181]	train-mlogloss:1.65949	validation-mlogloss:1.66036
[182]	train-mlogloss:1.65701	validation-mlogloss:1.65775
[183]	train-mlogloss:1.65449	validation-mlogloss:1.65506
[184]	train-mlogloss:1.65204	validation-mlogloss:1.65245
[185]	train-mlogloss:1.64962	validation-mlogloss:1.65001
[186]	train-mlogloss:1.64721	validation-mlogloss:1.64734
[187]	train-mlogloss:1.64479	validation-mlogloss:1.64488
[188]	train-mlogloss:1.64239	validation-mlogloss:1.64226
[189]	train-mlogloss:1.63992	validation-mlogloss:1.63978
[190]	train-mlogloss:1.63757	validation-mlogloss:1.63730
[191]	train-mlogloss:1.63524	validation-mlogloss:1.63479
[192]	train-mlogloss:1.63287	validation-mlogloss:1.63231
[193]	train-mlogloss:1.63051	validation-mlogloss:1.62981
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[503]	train-mlogloss:1.28230	validation-mlogloss:1.27504
[504]	train-mlogloss:1.28172	validation-mlogloss:1.27450
[505]	train-mlogloss:1.28117	validation-mlogloss:1.27398
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[730]	train-mlogloss:1.19063	validation-mlogloss:1.20692
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[744]	train-mlogloss:1.18635	validation-mlogloss:1.20428
[745]	train-mlogloss:1.18608	validation-mlogloss:1.20410
[746]	train-mlogloss:1.18581	validation-mlogloss:1.20393
[747]	train-mlogloss:1.18552	validation-mlogloss:1.20375
[748]	train-mlogloss:1.18524	validation-mlogloss:1.20354
[749]	train-mlogloss:1.18491	validation-mlogloss:1.20340
[750]	train-mlogloss:1.18459	validation-mlogloss:1.20324
[751]	train-mlogloss:1.18430	validation-mlogloss:1.20307
[752]	train-mlogloss:1.18397	validation-mlogloss:1.20289
[753]	train-mlogloss:1.18369	validation-mlogloss:1.20270
[754]	train-mlogloss:1.18332	validation-mlogloss:1.20249
[755]	train-mlogloss:1.18305	validation-mlogloss:1.20233
[756]	train-mlogloss:1.18277	validation-mlogloss:1.20213
[757]	train-mlogloss:1.18248	validation-mlogloss:1.20193
[758]	train-mlogloss:1.18218	validation-mlogloss:1.20174
[759]	train-mlogloss:1.18186	validation-mlogloss:1.20166
[760]	train-mlogloss:1.18157	validation-mlogloss:1.20148
Saved model to disk.

=== EJECUCIÓN 1 ===

--- TRAIN (ejecución 1) ---

--- TEST (ejecución 1) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.49 [%]
Global accuracy score (test) = 58.59 [%]
Global F1 score (train) = 61.03 [%]
Global F1 score (test) = 57.49 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.37      0.22      0.28       161
 CAMINAR CON MÓVIL O LIBRO       0.36      0.52      0.43       161
       CAMINAR USUAL SPEED       0.40      0.34      0.37       161
            CAMINAR ZIGZAG       0.42      0.39      0.41       161
          DE PIE BARRIENDO       0.66      0.73      0.70       161
   DE PIE DOBLANDO TOALLAS       0.39      0.40      0.40       161
    DE PIE MOVIENDO LIBROS       0.48      0.50      0.49       161
          DE PIE USANDO PC       0.84      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.52      0.36      0.42       161
         SENTADO USANDO PC       0.50      0.53      0.51       161
      SENTADO VIENDO LA TV       0.42      0.28      0.33       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.89      0.73       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.57      2415
              weighted avg       0.58      0.59      0.57      2415


Accuracy capturado en la ejecución 1: 58.59 [%]
F1-score capturado en la ejecución 1: 57.49 [%]

=== EJECUCIÓN 2 ===

--- TRAIN (ejecución 2) ---

--- TEST (ejecución 2) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.51 [%]
Global accuracy score (test) = 58.67 [%]
Global F1 score (train) = 61.06 [%]
Global F1 score (test) = 57.62 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.37      0.24      0.29       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.54      0.45       161
       CAMINAR USUAL SPEED       0.42      0.35      0.38       161
            CAMINAR ZIGZAG       0.42      0.40      0.41       161
          DE PIE BARRIENDO       0.66      0.73      0.69       161
   DE PIE DOBLANDO TOALLAS       0.39      0.40      0.40       161
    DE PIE MOVIENDO LIBROS       0.49      0.49      0.49       161
          DE PIE USANDO PC       0.84      0.87      0.85       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.50      0.36      0.42       161
         SENTADO USANDO PC       0.51      0.53      0.52       161
      SENTADO VIENDO LA TV       0.42      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.61      0.86      0.71       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 2: 58.67 [%]
F1-score capturado en la ejecución 2: 57.62 [%]

=== EJECUCIÓN 3 ===

--- TRAIN (ejecución 3) ---

--- TEST (ejecución 3) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.6 [%]
Global accuracy score (test) = 58.47 [%]
Global F1 score (train) = 61.15 [%]
Global F1 score (test) = 57.28 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.34      0.19      0.25       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.52      0.43       161
       CAMINAR USUAL SPEED       0.39      0.35      0.37       161
            CAMINAR ZIGZAG       0.45      0.43      0.44       161
          DE PIE BARRIENDO       0.67      0.75      0.70       161
   DE PIE DOBLANDO TOALLAS       0.38      0.39      0.38       161
    DE PIE MOVIENDO LIBROS       0.49      0.49      0.49       161
          DE PIE USANDO PC       0.84      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.50      0.34      0.41       161
         SENTADO USANDO PC       0.49      0.52      0.50       161
      SENTADO VIENDO LA TV       0.41      0.28      0.33       161
   SUBIR Y BAJAR ESCALERAS       0.63      0.89      0.74       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.58      2415
                 macro avg       0.58      0.58      0.57      2415
              weighted avg       0.58      0.58      0.57      2415


Accuracy capturado en la ejecución 3: 58.47 [%]
F1-score capturado en la ejecución 3: 57.28 [%]

=== EJECUCIÓN 4 ===

--- TRAIN (ejecución 4) ---

--- TEST (ejecución 4) ---
2025-11-06 14:06:44.740923: 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`.
2025-11-06 14:06:44.752148: 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 00:00:1762434404.765332 1375220 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434404.769442 1375220 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434404.779346 1375220 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434404.779363 1375220 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434404.779365 1375220 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434404.779366 1375220 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:06:44.782503: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69308	validation-mlogloss:2.69352
[1]	train-mlogloss:2.67870	validation-mlogloss:2.67965
[2]	train-mlogloss:2.66487	validation-mlogloss:2.66590
[3]	train-mlogloss:2.65077	validation-mlogloss:2.65223
[4]	train-mlogloss:2.63699	validation-mlogloss:2.63910
[5]	train-mlogloss:2.62351	validation-mlogloss:2.62638
[6]	train-mlogloss:2.61044	validation-mlogloss:2.61401
[7]	train-mlogloss:2.59756	validation-mlogloss:2.60174
[8]	train-mlogloss:2.58476	validation-mlogloss:2.58943
[9]	train-mlogloss:2.57205	validation-mlogloss:2.57689
[10]	train-mlogloss:2.55995	validation-mlogloss:2.56521
[11]	train-mlogloss:2.54795	validation-mlogloss:2.55399
[12]	train-mlogloss:2.53608	validation-mlogloss:2.54290
[13]	train-mlogloss:2.52420	validation-mlogloss:2.53137
[14]	train-mlogloss:2.51271	validation-mlogloss:2.52030
[15]	train-mlogloss:2.50150	validation-mlogloss:2.50956
[16]	train-mlogloss:2.49025	validation-mlogloss:2.49848
[17]	train-mlogloss:2.47912	validation-mlogloss:2.48788
[18]	train-mlogloss:2.46822	validation-mlogloss:2.47748
[19]	train-mlogloss:2.45785	validation-mlogloss:2.46738
[20]	train-mlogloss:2.44743	validation-mlogloss:2.45723
[21]	train-mlogloss:2.43704	validation-mlogloss:2.44735
[22]	train-mlogloss:2.42715	validation-mlogloss:2.43774
[23]	train-mlogloss:2.41733	validation-mlogloss:2.42826
[24]	train-mlogloss:2.40755	validation-mlogloss:2.41872
[25]	train-mlogloss:2.39836	validation-mlogloss:2.40974
[26]	train-mlogloss:2.38878	validation-mlogloss:2.40034
[27]	train-mlogloss:2.37948	validation-mlogloss:2.39130
[28]	train-mlogloss:2.37037	validation-mlogloss:2.38202
[29]	train-mlogloss:2.36132	validation-mlogloss:2.37337
[30]	train-mlogloss:2.35252	validation-mlogloss:2.36487
[31]	train-mlogloss:2.34364	validation-mlogloss:2.35611
[32]	train-mlogloss:2.33513	validation-mlogloss:2.34781
[33]	train-mlogloss:2.32670	validation-mlogloss:2.33966
[34]	train-mlogloss:2.31816	validation-mlogloss:2.33125
[35]	train-mlogloss:2.30990	validation-mlogloss:2.32316
[36]	train-mlogloss:2.30173	validation-mlogloss:2.31516
[37]	train-mlogloss:2.29386	validation-mlogloss:2.30755
[38]	train-mlogloss:2.28559	validation-mlogloss:2.29908
[39]	train-mlogloss:2.27779	validation-mlogloss:2.29149
[40]	train-mlogloss:2.26968	validation-mlogloss:2.28355
[41]	train-mlogloss:2.26206	validation-mlogloss:2.27598
[42]	train-mlogloss:2.25435	validation-mlogloss:2.26838
[43]	train-mlogloss:2.24686	validation-mlogloss:2.26090
[44]	train-mlogloss:2.23966	validation-mlogloss:2.25403
[45]	train-mlogloss:2.23230	validation-mlogloss:2.24678
[46]	train-mlogloss:2.22491	validation-mlogloss:2.23942
[47]	train-mlogloss:2.21783	validation-mlogloss:2.23237
[48]	train-mlogloss:2.21080	validation-mlogloss:2.22552
[49]	train-mlogloss:2.20376	validation-mlogloss:2.21838
[50]	train-mlogloss:2.19697	validation-mlogloss:2.21158
[51]	train-mlogloss:2.19010	validation-mlogloss:2.20479
[52]	train-mlogloss:2.18332	validation-mlogloss:2.19810
[53]	train-mlogloss:2.17649	validation-mlogloss:2.19123
[54]	train-mlogloss:2.16982	validation-mlogloss:2.18457
[55]	train-mlogloss:2.16323	validation-mlogloss:2.17809
[56]	train-mlogloss:2.15648	validation-mlogloss:2.17126
[57]	train-mlogloss:2.15016	validation-mlogloss:2.16513
[58]	train-mlogloss:2.14367	validation-mlogloss:2.15845
[59]	train-mlogloss:2.13752	validation-mlogloss:2.15247
[60]	train-mlogloss:2.13109	validation-mlogloss:2.14598
[61]	train-mlogloss:2.12498	validation-mlogloss:2.14014
[62]	train-mlogloss:2.11892	validation-mlogloss:2.13399
[63]	train-mlogloss:2.11288	validation-mlogloss:2.12794
[64]	train-mlogloss:2.10683	validation-mlogloss:2.12149
[65]	train-mlogloss:2.10089	validation-mlogloss:2.11545
[66]	train-mlogloss:2.09501	validation-mlogloss:2.10944
[67]	train-mlogloss:2.08916	validation-mlogloss:2.10366
[68]	train-mlogloss:2.08325	validation-mlogloss:2.09755
[69]	train-mlogloss:2.07759	validation-mlogloss:2.09204
[70]	train-mlogloss:2.07191	validation-mlogloss:2.08623
[71]	train-mlogloss:2.06653	validation-mlogloss:2.08097
[72]	train-mlogloss:2.06094	validation-mlogloss:2.07514
[73]	train-mlogloss:2.05548	validation-mlogloss:2.06942
[74]	train-mlogloss:2.04989	validation-mlogloss:2.06381
[75]	train-mlogloss:2.04445	validation-mlogloss:2.05843
[76]	train-mlogloss:2.03900	validation-mlogloss:2.05292
[77]	train-mlogloss:2.03373	validation-mlogloss:2.04742
[78]	train-mlogloss:2.02844	validation-mlogloss:2.04217
[79]	train-mlogloss:2.02332	validation-mlogloss:2.03691
[80]	train-mlogloss:2.01814	validation-mlogloss:2.03141
[81]	train-mlogloss:2.01318	validation-mlogloss:2.02640
[82]	train-mlogloss:2.00818	validation-mlogloss:2.02124
[83]	train-mlogloss:2.00336	validation-mlogloss:2.01640
[84]	train-mlogloss:1.99827	validation-mlogloss:2.01124
[85]	train-mlogloss:1.99339	validation-mlogloss:2.00627
[86]	train-mlogloss:1.98847	validation-mlogloss:2.00121
[87]	train-mlogloss:1.98352	validation-mlogloss:1.99610
[88]	train-mlogloss:1.97888	validation-mlogloss:1.99171
[89]	train-mlogloss:1.97413	validation-mlogloss:1.98693
[90]	train-mlogloss:1.96941	validation-mlogloss:1.98213
[91]	train-mlogloss:1.96478	validation-mlogloss:1.97742
[92]	train-mlogloss:1.96025	validation-mlogloss:1.97286
[93]	train-mlogloss:1.95567	validation-mlogloss:1.96816
[94]	train-mlogloss:1.95115	validation-mlogloss:1.96352
[95]	train-mlogloss:1.94638	validation-mlogloss:1.95859
[96]	train-mlogloss:1.94194	validation-mlogloss:1.95406
[97]	train-mlogloss:1.93748	validation-mlogloss:1.94945
[98]	train-mlogloss:1.93309	validation-mlogloss:1.94490
[99]	train-mlogloss:1.92885	validation-mlogloss:1.94056
[100]	train-mlogloss:1.92454	validation-mlogloss:1.93610
[101]	train-mlogloss:1.92013	validation-mlogloss:1.93157
[102]	train-mlogloss:1.91598	validation-mlogloss:1.92726
[103]	train-mlogloss:1.91165	validation-mlogloss:1.92279
[104]	train-mlogloss:1.90758	validation-mlogloss:1.91858
[105]	train-mlogloss:1.90350	validation-mlogloss:1.91432
[106]	train-mlogloss:1.89949	validation-mlogloss:1.91020
[107]	train-mlogloss:1.89539	validation-mlogloss:1.90608
[108]	train-mlogloss:1.89124	validation-mlogloss:1.90184
[109]	train-mlogloss:1.88735	validation-mlogloss:1.89776
[110]	train-mlogloss:1.88339	validation-mlogloss:1.89373
[111]	train-mlogloss:1.87953	validation-mlogloss:1.88984
[112]	train-mlogloss:1.87562	validation-mlogloss:1.88570
[113]	train-mlogloss:1.87173	validation-mlogloss:1.88170
[114]	train-mlogloss:1.86792	validation-mlogloss:1.87777
[115]	train-mlogloss:1.86412	validation-mlogloss:1.87386
[116]	train-mlogloss:1.86038	validation-mlogloss:1.87006
[117]	train-mlogloss:1.85647	validation-mlogloss:1.86600
[118]	train-mlogloss:1.85273	validation-mlogloss:1.86202
[119]	train-mlogloss:1.84900	validation-mlogloss:1.85817
[120]	train-mlogloss:1.84533	validation-mlogloss:1.85430
[121]	train-mlogloss:1.84166	validation-mlogloss:1.85054
[122]	train-mlogloss:1.83806	validation-mlogloss:1.84681
[123]	train-mlogloss:1.83449	validation-mlogloss:1.84320
[124]	train-mlogloss:1.83095	validation-mlogloss:1.83953
[125]	train-mlogloss:1.82746	validation-mlogloss:1.83586
[126]	train-mlogloss:1.82399	validation-mlogloss:1.83230
[127]	train-mlogloss:1.82052	validation-mlogloss:1.82872
[128]	train-mlogloss:1.81709	validation-mlogloss:1.82524
[129]	train-mlogloss:1.81344	validation-mlogloss:1.82131
[130]	train-mlogloss:1.80998	validation-mlogloss:1.81769
[131]	train-mlogloss:1.80662	validation-mlogloss:1.81416
[132]	train-mlogloss:1.80325	validation-mlogloss:1.81067
[133]	train-mlogloss:1.79965	validation-mlogloss:1.80700
[134]	train-mlogloss:1.79641	validation-mlogloss:1.80371
[135]	train-mlogloss:1.79298	validation-mlogloss:1.80011
[136]	train-mlogloss:1.78968	validation-mlogloss:1.79672
[137]	train-mlogloss:1.78643	validation-mlogloss:1.79326
[138]	train-mlogloss:1.78326	validation-mlogloss:1.79004
[139]	train-mlogloss:1.78011	validation-mlogloss:1.78675
[140]	train-mlogloss:1.77697	validation-mlogloss:1.78354
[141]	train-mlogloss:1.77386	validation-mlogloss:1.78030
[142]	train-mlogloss:1.77051	validation-mlogloss:1.77671
[143]	train-mlogloss:1.76723	validation-mlogloss:1.77321
[144]	train-mlogloss:1.76418	validation-mlogloss:1.77017
[145]	train-mlogloss:1.76100	validation-mlogloss:1.76693
[146]	train-mlogloss:1.75779	validation-mlogloss:1.76357
[147]	train-mlogloss:1.75476	validation-mlogloss:1.76039
[148]	train-mlogloss:1.75180	validation-mlogloss:1.75727
[149]	train-mlogloss:1.74876	validation-mlogloss:1.75413
[150]	train-mlogloss:1.74587	validation-mlogloss:1.75103
[151]	train-mlogloss:1.74273	validation-mlogloss:1.74778
[152]	train-mlogloss:1.73983	validation-mlogloss:1.74483
[153]	train-mlogloss:1.73698	validation-mlogloss:1.74189
[154]	train-mlogloss:1.73397	validation-mlogloss:1.73861
[155]	train-mlogloss:1.73093	validation-mlogloss:1.73532
[156]	train-mlogloss:1.72813	validation-mlogloss:1.73238
[157]	train-mlogloss:1.72532	validation-mlogloss:1.72952
[158]	train-mlogloss:1.72229	validation-mlogloss:1.72633
[159]	train-mlogloss:1.71936	validation-mlogloss:1.72317
[160]	train-mlogloss:1.71642	validation-mlogloss:1.72012
[161]	train-mlogloss:1.71370	validation-mlogloss:1.71731
[162]	train-mlogloss:1.71098	validation-mlogloss:1.71440
[163]	train-mlogloss:1.70807	validation-mlogloss:1.71131
[164]	train-mlogloss:1.70534	validation-mlogloss:1.70845
[165]	train-mlogloss:1.70249	validation-mlogloss:1.70542
[166]	train-mlogloss:1.69968	validation-mlogloss:1.70252
[167]	train-mlogloss:1.69692	validation-mlogloss:1.69969
[168]	train-mlogloss:1.69441	validation-mlogloss:1.69698
[169]	train-mlogloss:1.69162	validation-mlogloss:1.69407
[170]	train-mlogloss:1.68903	validation-mlogloss:1.69140
[171]	train-mlogloss:1.68629	validation-mlogloss:1.68843
[172]	train-mlogloss:1.68353	validation-mlogloss:1.68563
[173]	train-mlogloss:1.68081	validation-mlogloss:1.68286
[174]	train-mlogloss:1.67817	validation-mlogloss:1.68012
[175]	train-mlogloss:1.67553	validation-mlogloss:1.67734
[176]	train-mlogloss:1.67297	validation-mlogloss:1.67479
[177]	train-mlogloss:1.67035	validation-mlogloss:1.67203
[178]	train-mlogloss:1.66774	validation-mlogloss:1.66930
[179]	train-mlogloss:1.66539	validation-mlogloss:1.66686
[180]	train-mlogloss:1.66291	validation-mlogloss:1.66426
[181]	train-mlogloss:1.66039	validation-mlogloss:1.66165
[182]	train-mlogloss:1.65797	validation-mlogloss:1.65903
[183]	train-mlogloss:1.65550	validation-mlogloss:1.65635
[184]	train-mlogloss:1.65307	validation-mlogloss:1.65378
[185]	train-mlogloss:1.65060	validation-mlogloss:1.65124
[186]	train-mlogloss:1.64822	validation-mlogloss:1.64875
[187]	train-mlogloss:1.64579	validation-mlogloss:1.64625
[188]	train-mlogloss:1.64338	validation-mlogloss:1.64373
[189]	train-mlogloss:1.64102	validation-mlogloss:1.64126
[190]	train-mlogloss:1.63867	validation-mlogloss:1.63891
[191]	train-mlogloss:1.63636	validation-mlogloss:1.63654
[192]	train-mlogloss:1.63400	validation-mlogloss:1.63400
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[744]	train-mlogloss:1.18627	validation-mlogloss:1.20381
[745]	train-mlogloss:1.18599	validation-mlogloss:1.20365
[746]	train-mlogloss:1.18568	validation-mlogloss:1.20347
[747]	train-mlogloss:1.18542	validation-mlogloss:1.20326
[748]	train-mlogloss:1.18512	validation-mlogloss:1.20308
[749]	train-mlogloss:1.18483	validation-mlogloss:1.20294
[750]	train-mlogloss:1.18453	validation-mlogloss:1.20276
[751]	train-mlogloss:1.18423	validation-mlogloss:1.20260
[752]	train-mlogloss:1.18396	validation-mlogloss:1.20239
[753]	train-mlogloss:1.18365	validation-mlogloss:1.20224
[754]	train-mlogloss:1.18339	validation-mlogloss:1.20211
[755]	train-mlogloss:1.18311	validation-mlogloss:1.20197
[756]	train-mlogloss:1.18282	validation-mlogloss:1.20182
[757]	train-mlogloss:1.18254	validation-mlogloss:1.20169
[758]	train-mlogloss:1.18228	validation-mlogloss:1.20151
[759]	train-mlogloss:1.18200	validation-mlogloss:1.20130
[760]	train-mlogloss:1.18169	validation-mlogloss:1.20118
Saved model to disk.
2025-11-06 14:07:08.979484: 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`.
2025-11-06 14:07:08.990642: 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 00:00:1762434429.003844 1375624 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434429.007821 1375624 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434429.017886 1375624 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434429.017904 1375624 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434429.017906 1375624 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434429.017908 1375624 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:07:09.021054: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69307	validation-mlogloss:2.69370
[1]	train-mlogloss:2.67839	validation-mlogloss:2.67975
[2]	train-mlogloss:2.66425	validation-mlogloss:2.66616
[3]	train-mlogloss:2.65055	validation-mlogloss:2.65321
[4]	train-mlogloss:2.63673	validation-mlogloss:2.63989
[5]	train-mlogloss:2.62351	validation-mlogloss:2.62678
[6]	train-mlogloss:2.61026	validation-mlogloss:2.61386
[7]	train-mlogloss:2.59730	validation-mlogloss:2.60153
[8]	train-mlogloss:2.58432	validation-mlogloss:2.58911
[9]	train-mlogloss:2.57196	validation-mlogloss:2.57738
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[734]	train-mlogloss:1.18943	validation-mlogloss:1.20580
[735]	train-mlogloss:1.18916	validation-mlogloss:1.20561
[736]	train-mlogloss:1.18884	validation-mlogloss:1.20537
[737]	train-mlogloss:1.18853	validation-mlogloss:1.20523
[738]	train-mlogloss:1.18825	validation-mlogloss:1.20509
[739]	train-mlogloss:1.18793	validation-mlogloss:1.20492
[740]	train-mlogloss:1.18763	validation-mlogloss:1.20473
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[742]	train-mlogloss:1.18702	validation-mlogloss:1.20440
[743]	train-mlogloss:1.18671	validation-mlogloss:1.20424
[744]	train-mlogloss:1.18640	validation-mlogloss:1.20407
[745]	train-mlogloss:1.18607	validation-mlogloss:1.20396
[746]	train-mlogloss:1.18577	validation-mlogloss:1.20378
[747]	train-mlogloss:1.18550	validation-mlogloss:1.20365
[748]	train-mlogloss:1.18522	validation-mlogloss:1.20348
[749]	train-mlogloss:1.18493	validation-mlogloss:1.20334
[750]	train-mlogloss:1.18461	validation-mlogloss:1.20319
[751]	train-mlogloss:1.18433	validation-mlogloss:1.20296
[752]	train-mlogloss:1.18405	validation-mlogloss:1.20281
[753]	train-mlogloss:1.18376	validation-mlogloss:1.20266
[754]	train-mlogloss:1.18346	validation-mlogloss:1.20251
[755]	train-mlogloss:1.18315	validation-mlogloss:1.20235
[756]	train-mlogloss:1.18289	validation-mlogloss:1.20223
[757]	train-mlogloss:1.18258	validation-mlogloss:1.20203
[758]	train-mlogloss:1.18229	validation-mlogloss:1.20185
[759]	train-mlogloss:1.18204	validation-mlogloss:1.20173
[760]	train-mlogloss:1.18174	validation-mlogloss:1.20156
Saved model to disk.
2025-11-06 14:07:33.471372: 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`.
2025-11-06 14:07:33.482500: 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 00:00:1762434453.495692 1376005 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434453.499762 1376005 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434453.510040 1376005 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434453.510057 1376005 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434453.510059 1376005 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434453.510061 1376005 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:07:33.513165: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
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[2]	train-mlogloss:2.66486	validation-mlogloss:2.66650
[3]	train-mlogloss:2.65048	validation-mlogloss:2.65267
[4]	train-mlogloss:2.63674	validation-mlogloss:2.63947
[5]	train-mlogloss:2.62322	validation-mlogloss:2.62656
[6]	train-mlogloss:2.61002	validation-mlogloss:2.61394
[7]	train-mlogloss:2.59667	validation-mlogloss:2.60126
[8]	train-mlogloss:2.58358	validation-mlogloss:2.58867
[9]	train-mlogloss:2.57097	validation-mlogloss:2.57637
[10]	train-mlogloss:2.55866	validation-mlogloss:2.56432
[11]	train-mlogloss:2.54630	validation-mlogloss:2.55223
[12]	train-mlogloss:2.53422	validation-mlogloss:2.54072
[13]	train-mlogloss:2.52268	validation-mlogloss:2.52977
[14]	train-mlogloss:2.51159	validation-mlogloss:2.51933
[15]	train-mlogloss:2.50027	validation-mlogloss:2.50833
[16]	train-mlogloss:2.48913	validation-mlogloss:2.49759
[17]	train-mlogloss:2.47841	validation-mlogloss:2.48722
[18]	train-mlogloss:2.46783	validation-mlogloss:2.47687
[19]	train-mlogloss:2.45725	validation-mlogloss:2.46661
[20]	train-mlogloss:2.44680	validation-mlogloss:2.45655
[21]	train-mlogloss:2.43664	validation-mlogloss:2.44677
[22]	train-mlogloss:2.42669	validation-mlogloss:2.43710
[23]	train-mlogloss:2.41689	validation-mlogloss:2.42778
[24]	train-mlogloss:2.40726	validation-mlogloss:2.41853
[25]	train-mlogloss:2.39806	validation-mlogloss:2.40942
[26]	train-mlogloss:2.38850	validation-mlogloss:2.40022
[27]	train-mlogloss:2.37908	validation-mlogloss:2.39098
[28]	train-mlogloss:2.37014	validation-mlogloss:2.38207
[29]	train-mlogloss:2.36083	validation-mlogloss:2.37259
[30]	train-mlogloss:2.35177	validation-mlogloss:2.36368
[31]	train-mlogloss:2.34309	validation-mlogloss:2.35522
[32]	train-mlogloss:2.33452	validation-mlogloss:2.34695
[33]	train-mlogloss:2.32607	validation-mlogloss:2.33867
[34]	train-mlogloss:2.31774	validation-mlogloss:2.33090
[35]	train-mlogloss:2.30923	validation-mlogloss:2.32274
[36]	train-mlogloss:2.30107	validation-mlogloss:2.31495
[37]	train-mlogloss:2.29284	validation-mlogloss:2.30701
[38]	train-mlogloss:2.28483	validation-mlogloss:2.29929
[39]	train-mlogloss:2.27702	validation-mlogloss:2.29164
[40]	train-mlogloss:2.26920	validation-mlogloss:2.28380
[41]	train-mlogloss:2.26161	validation-mlogloss:2.27623
[42]	train-mlogloss:2.25401	validation-mlogloss:2.26866
[43]	train-mlogloss:2.24651	validation-mlogloss:2.26129
[44]	train-mlogloss:2.23911	validation-mlogloss:2.25405
[45]	train-mlogloss:2.23172	validation-mlogloss:2.24682
[46]	train-mlogloss:2.22442	validation-mlogloss:2.23943
[47]	train-mlogloss:2.21715	validation-mlogloss:2.23202
[48]	train-mlogloss:2.21004	validation-mlogloss:2.22474
[49]	train-mlogloss:2.20304	validation-mlogloss:2.21776
[50]	train-mlogloss:2.19592	validation-mlogloss:2.21068
[51]	train-mlogloss:2.18910	validation-mlogloss:2.20404
[52]	train-mlogloss:2.18234	validation-mlogloss:2.19724
[53]	train-mlogloss:2.17575	validation-mlogloss:2.19073
[54]	train-mlogloss:2.16919	validation-mlogloss:2.18410
[55]	train-mlogloss:2.16267	validation-mlogloss:2.17768
[56]	train-mlogloss:2.15608	validation-mlogloss:2.17105
[57]	train-mlogloss:2.14980	validation-mlogloss:2.16491
[58]	train-mlogloss:2.14361	validation-mlogloss:2.15882
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[60]	train-mlogloss:2.13115	validation-mlogloss:2.14631
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[62]	train-mlogloss:2.11905	validation-mlogloss:2.13418
[63]	train-mlogloss:2.11317	validation-mlogloss:2.12838
[64]	train-mlogloss:2.10716	validation-mlogloss:2.12242
[65]	train-mlogloss:2.10123	validation-mlogloss:2.11647
[66]	train-mlogloss:2.09537	validation-mlogloss:2.11053
[67]	train-mlogloss:2.08975	validation-mlogloss:2.10498
[68]	train-mlogloss:2.08424	validation-mlogloss:2.09967
[69]	train-mlogloss:2.07840	validation-mlogloss:2.09404
[70]	train-mlogloss:2.07279	validation-mlogloss:2.08834
[71]	train-mlogloss:2.06714	validation-mlogloss:2.08260
[72]	train-mlogloss:2.06159	validation-mlogloss:2.07688
[73]	train-mlogloss:2.05627	validation-mlogloss:2.07164
[74]	train-mlogloss:2.05088	validation-mlogloss:2.06616
[75]	train-mlogloss:2.04553	validation-mlogloss:2.06079
[76]	train-mlogloss:2.04000	validation-mlogloss:2.05523
[77]	train-mlogloss:2.03463	validation-mlogloss:2.04975
[78]	train-mlogloss:2.02925	validation-mlogloss:2.04423
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[80]	train-mlogloss:2.01891	validation-mlogloss:2.03338
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[82]	train-mlogloss:2.00876	validation-mlogloss:2.02306
[83]	train-mlogloss:2.00380	validation-mlogloss:2.01819
[84]	train-mlogloss:1.99884	validation-mlogloss:2.01318
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[96]	train-mlogloss:1.94209	validation-mlogloss:1.95488
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[102]	train-mlogloss:1.91608	validation-mlogloss:1.92830
[103]	train-mlogloss:1.91191	validation-mlogloss:1.92402
[104]	train-mlogloss:1.90774	validation-mlogloss:1.91979
[105]	train-mlogloss:1.90359	validation-mlogloss:1.91557
[106]	train-mlogloss:1.89952	validation-mlogloss:1.91148
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[109]	train-mlogloss:1.88725	validation-mlogloss:1.89878
[110]	train-mlogloss:1.88332	validation-mlogloss:1.89474
[111]	train-mlogloss:1.87934	validation-mlogloss:1.89064
[112]	train-mlogloss:1.87543	validation-mlogloss:1.88652
[113]	train-mlogloss:1.87154	validation-mlogloss:1.88243
[114]	train-mlogloss:1.86758	validation-mlogloss:1.87835
[115]	train-mlogloss:1.86366	validation-mlogloss:1.87434
[116]	train-mlogloss:1.85984	validation-mlogloss:1.87043
[117]	train-mlogloss:1.85605	validation-mlogloss:1.86646
[118]	train-mlogloss:1.85234	validation-mlogloss:1.86251
[119]	train-mlogloss:1.84873	validation-mlogloss:1.85879
[120]	train-mlogloss:1.84503	validation-mlogloss:1.85498
[121]	train-mlogloss:1.84131	validation-mlogloss:1.85113
[122]	train-mlogloss:1.83742	validation-mlogloss:1.84702
[123]	train-mlogloss:1.83382	validation-mlogloss:1.84344
[124]	train-mlogloss:1.83026	validation-mlogloss:1.83988
[125]	train-mlogloss:1.82682	validation-mlogloss:1.83638
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[728]	train-mlogloss:1.19038	validation-mlogloss:1.20681
[729]	train-mlogloss:1.19010	validation-mlogloss:1.20660
[730]	train-mlogloss:1.18979	validation-mlogloss:1.20640
[731]	train-mlogloss:1.18948	validation-mlogloss:1.20616
[732]	train-mlogloss:1.18916	validation-mlogloss:1.20597
[733]	train-mlogloss:1.18880	validation-mlogloss:1.20576
[734]	train-mlogloss:1.18848	validation-mlogloss:1.20551
[735]	train-mlogloss:1.18821	validation-mlogloss:1.20535
[736]	train-mlogloss:1.18792	validation-mlogloss:1.20515
[737]	train-mlogloss:1.18763	validation-mlogloss:1.20497
[738]	train-mlogloss:1.18731	validation-mlogloss:1.20475
[739]	train-mlogloss:1.18701	validation-mlogloss:1.20452
[740]	train-mlogloss:1.18666	validation-mlogloss:1.20431
[741]	train-mlogloss:1.18638	validation-mlogloss:1.20412
[742]	train-mlogloss:1.18610	validation-mlogloss:1.20396
[743]	train-mlogloss:1.18583	validation-mlogloss:1.20378
[744]	train-mlogloss:1.18550	validation-mlogloss:1.20367
[745]	train-mlogloss:1.18520	validation-mlogloss:1.20349
[746]	train-mlogloss:1.18492	validation-mlogloss:1.20333
[747]	train-mlogloss:1.18461	validation-mlogloss:1.20314
[748]	train-mlogloss:1.18428	validation-mlogloss:1.20297
[749]	train-mlogloss:1.18400	validation-mlogloss:1.20281
[750]	train-mlogloss:1.18365	validation-mlogloss:1.20267
[751]	train-mlogloss:1.18339	validation-mlogloss:1.20255
[752]	train-mlogloss:1.18311	validation-mlogloss:1.20233
[753]	train-mlogloss:1.18282	validation-mlogloss:1.20216
[754]	train-mlogloss:1.18253	validation-mlogloss:1.20200
[755]	train-mlogloss:1.18224	validation-mlogloss:1.20180
[756]	train-mlogloss:1.18197	validation-mlogloss:1.20169
[757]	train-mlogloss:1.18169	validation-mlogloss:1.20156
[758]	train-mlogloss:1.18141	validation-mlogloss:1.20137
[759]	train-mlogloss:1.18107	validation-mlogloss:1.20123
[760]	train-mlogloss:1.18078	validation-mlogloss:1.20103
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.53 [%]
Global accuracy score (test) = 58.26 [%]
Global F1 score (train) = 61.08 [%]
Global F1 score (test) = 57.1 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.34      0.19      0.25       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.53      0.44       161
       CAMINAR USUAL SPEED       0.38      0.34      0.36       161
            CAMINAR ZIGZAG       0.41      0.39      0.40       161
          DE PIE BARRIENDO       0.66      0.73      0.69       161
   DE PIE DOBLANDO TOALLAS       0.40      0.40      0.40       161
    DE PIE MOVIENDO LIBROS       0.49      0.51      0.50       161
          DE PIE USANDO PC       0.85      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.51      0.34      0.41       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.42      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.58      2415
                 macro avg       0.57      0.58      0.57      2415
              weighted avg       0.57      0.58      0.57      2415


Accuracy capturado en la ejecución 4: 58.26 [%]
F1-score capturado en la ejecución 4: 57.1 [%]

=== EJECUCIÓN 5 ===

--- TRAIN (ejecución 5) ---

--- TEST (ejecución 5) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.66 [%]
Global accuracy score (test) = 58.55 [%]
Global F1 score (train) = 61.21 [%]
Global F1 score (test) = 57.41 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.34      0.19      0.24       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.52      0.44       161
       CAMINAR USUAL SPEED       0.39      0.35      0.37       161
            CAMINAR ZIGZAG       0.42      0.41      0.42       161
          DE PIE BARRIENDO       0.66      0.73      0.70       161
   DE PIE DOBLANDO TOALLAS       0.39      0.40      0.40       161
    DE PIE MOVIENDO LIBROS       0.49      0.50      0.50       161
          DE PIE USANDO PC       0.86      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.51      0.36      0.42       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.42      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.87      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.57      2415
              weighted avg       0.58      0.59      0.57      2415


Accuracy capturado en la ejecución 5: 58.55 [%]
F1-score capturado en la ejecución 5: 57.41 [%]

=== EJECUCIÓN 6 ===

--- TRAIN (ejecución 6) ---

--- TEST (ejecución 6) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.64 [%]
Global accuracy score (test) = 58.63 [%]
Global F1 score (train) = 61.17 [%]
Global F1 score (test) = 57.51 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.35      0.19      0.25       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.52      0.43       161
       CAMINAR USUAL SPEED       0.39      0.35      0.37       161
            CAMINAR ZIGZAG       0.41      0.39      0.40       161
          DE PIE BARRIENDO       0.66      0.75      0.70       161
   DE PIE DOBLANDO TOALLAS       0.40      0.41      0.41       161
    DE PIE MOVIENDO LIBROS       0.49      0.50      0.50       161
          DE PIE USANDO PC       0.85      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.54      0.38      0.45       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.44      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 6: 58.63 [%]
F1-score capturado en la ejecución 6: 57.51 [%]

=== EJECUCIÓN 7 ===

--- TRAIN (ejecución 7) ---

--- TEST (ejecución 7) ---
2025-11-06 14:07:58.200106: 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`.
2025-11-06 14:07:58.211293: 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 00:00:1762434478.224410 1376416 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434478.228466 1376416 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434478.238153 1376416 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434478.238170 1376416 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434478.238171 1376416 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434478.238173 1376416 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:07:58.241276: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69265	validation-mlogloss:2.69326
[1]	train-mlogloss:2.67832	validation-mlogloss:2.67906
[2]	train-mlogloss:2.66411	validation-mlogloss:2.66504
[3]	train-mlogloss:2.65035	validation-mlogloss:2.65129
[4]	train-mlogloss:2.63644	validation-mlogloss:2.63810
[5]	train-mlogloss:2.62284	validation-mlogloss:2.62507
[6]	train-mlogloss:2.60947	validation-mlogloss:2.61268
[7]	train-mlogloss:2.59642	validation-mlogloss:2.60038
[8]	train-mlogloss:2.58365	validation-mlogloss:2.58802
[9]	train-mlogloss:2.57092	validation-mlogloss:2.57604
[10]	train-mlogloss:2.55857	validation-mlogloss:2.56432
[11]	train-mlogloss:2.54650	validation-mlogloss:2.55262
[12]	train-mlogloss:2.53491	validation-mlogloss:2.54142
[13]	train-mlogloss:2.52331	validation-mlogloss:2.53050
[14]	train-mlogloss:2.51192	validation-mlogloss:2.51963
[15]	train-mlogloss:2.50075	validation-mlogloss:2.50872
[16]	train-mlogloss:2.48953	validation-mlogloss:2.49771
[17]	train-mlogloss:2.47848	validation-mlogloss:2.48688
[18]	train-mlogloss:2.46772	validation-mlogloss:2.47631
[19]	train-mlogloss:2.45732	validation-mlogloss:2.46628
[20]	train-mlogloss:2.44707	validation-mlogloss:2.45636
[21]	train-mlogloss:2.43700	validation-mlogloss:2.44669
[22]	train-mlogloss:2.42716	validation-mlogloss:2.43722
[23]	train-mlogloss:2.41737	validation-mlogloss:2.42768
[24]	train-mlogloss:2.40755	validation-mlogloss:2.41814
[25]	train-mlogloss:2.39787	validation-mlogloss:2.40861
[26]	train-mlogloss:2.38875	validation-mlogloss:2.39989
[27]	train-mlogloss:2.37955	validation-mlogloss:2.39104
[28]	train-mlogloss:2.37050	validation-mlogloss:2.38223
[29]	train-mlogloss:2.36142	validation-mlogloss:2.37325
[30]	train-mlogloss:2.35245	validation-mlogloss:2.36450
[31]	train-mlogloss:2.34352	validation-mlogloss:2.35586
[32]	train-mlogloss:2.33461	validation-mlogloss:2.34695
[33]	train-mlogloss:2.32611	validation-mlogloss:2.33881
[34]	train-mlogloss:2.31765	validation-mlogloss:2.33052
[35]	train-mlogloss:2.30934	validation-mlogloss:2.32266
[36]	train-mlogloss:2.30126	validation-mlogloss:2.31467
[37]	train-mlogloss:2.29305	validation-mlogloss:2.30673
[38]	train-mlogloss:2.28496	validation-mlogloss:2.29871
[39]	train-mlogloss:2.27699	validation-mlogloss:2.29090
[40]	train-mlogloss:2.26929	validation-mlogloss:2.28320
[41]	train-mlogloss:2.26150	validation-mlogloss:2.27566
[42]	train-mlogloss:2.25407	validation-mlogloss:2.26848
[43]	train-mlogloss:2.24635	validation-mlogloss:2.26056
[44]	train-mlogloss:2.23864	validation-mlogloss:2.25289
[45]	train-mlogloss:2.23145	validation-mlogloss:2.24569
[46]	train-mlogloss:2.22410	validation-mlogloss:2.23847
[47]	train-mlogloss:2.21690	validation-mlogloss:2.23125
[48]	train-mlogloss:2.20983	validation-mlogloss:2.22432
[49]	train-mlogloss:2.20280	validation-mlogloss:2.21737
[50]	train-mlogloss:2.19587	validation-mlogloss:2.21039
[51]	train-mlogloss:2.18913	validation-mlogloss:2.20366
[52]	train-mlogloss:2.18241	validation-mlogloss:2.19714
[53]	train-mlogloss:2.17548	validation-mlogloss:2.19006
[54]	train-mlogloss:2.16884	validation-mlogloss:2.18357
[55]	train-mlogloss:2.16224	validation-mlogloss:2.17691
[56]	train-mlogloss:2.15556	validation-mlogloss:2.17001
[57]	train-mlogloss:2.14925	validation-mlogloss:2.16388
[58]	train-mlogloss:2.14293	validation-mlogloss:2.15785
[59]	train-mlogloss:2.13642	validation-mlogloss:2.15122
[60]	train-mlogloss:2.13017	validation-mlogloss:2.14479
[61]	train-mlogloss:2.12395	validation-mlogloss:2.13835
[62]	train-mlogloss:2.11800	validation-mlogloss:2.13242
[63]	train-mlogloss:2.11187	validation-mlogloss:2.12617
[64]	train-mlogloss:2.10606	validation-mlogloss:2.12040
[65]	train-mlogloss:2.09999	validation-mlogloss:2.11414
[66]	train-mlogloss:2.09419	validation-mlogloss:2.10821
[67]	train-mlogloss:2.08842	validation-mlogloss:2.10246
[68]	train-mlogloss:2.08260	validation-mlogloss:2.09646
[69]	train-mlogloss:2.07704	validation-mlogloss:2.09097
[70]	train-mlogloss:2.07142	validation-mlogloss:2.08545
[71]	train-mlogloss:2.06588	validation-mlogloss:2.07966
[72]	train-mlogloss:2.06034	validation-mlogloss:2.07392
[73]	train-mlogloss:2.05469	validation-mlogloss:2.06837
[74]	train-mlogloss:2.04932	validation-mlogloss:2.06283
[75]	train-mlogloss:2.04411	validation-mlogloss:2.05769
[76]	train-mlogloss:2.03879	validation-mlogloss:2.05223
[77]	train-mlogloss:2.03350	validation-mlogloss:2.04700
[78]	train-mlogloss:2.02835	validation-mlogloss:2.04188
[79]	train-mlogloss:2.02330	validation-mlogloss:2.03665
[80]	train-mlogloss:2.01821	validation-mlogloss:2.03147
[81]	train-mlogloss:2.01304	validation-mlogloss:2.02614
[82]	train-mlogloss:2.00796	validation-mlogloss:2.02089
[83]	train-mlogloss:2.00294	validation-mlogloss:2.01571
[84]	train-mlogloss:1.99785	validation-mlogloss:2.01054
[85]	train-mlogloss:1.99267	validation-mlogloss:2.00525
[86]	train-mlogloss:1.98789	validation-mlogloss:2.00031
[87]	train-mlogloss:1.98304	validation-mlogloss:1.99527
[88]	train-mlogloss:1.97816	validation-mlogloss:1.99035
[89]	train-mlogloss:1.97349	validation-mlogloss:1.98566
[90]	train-mlogloss:1.96869	validation-mlogloss:1.98069
[91]	train-mlogloss:1.96404	validation-mlogloss:1.97604
[92]	train-mlogloss:1.95928	validation-mlogloss:1.97112
[93]	train-mlogloss:1.95460	validation-mlogloss:1.96632
[94]	train-mlogloss:1.95011	validation-mlogloss:1.96168
[95]	train-mlogloss:1.94562	validation-mlogloss:1.95706
[96]	train-mlogloss:1.94129	validation-mlogloss:1.95268
[97]	train-mlogloss:1.93694	validation-mlogloss:1.94831
[98]	train-mlogloss:1.93270	validation-mlogloss:1.94405
[99]	train-mlogloss:1.92827	validation-mlogloss:1.93952
[100]	train-mlogloss:1.92377	validation-mlogloss:1.93490
[101]	train-mlogloss:1.91960	validation-mlogloss:1.93051
[102]	train-mlogloss:1.91542	validation-mlogloss:1.92625
[103]	train-mlogloss:1.91118	validation-mlogloss:1.92186
[104]	train-mlogloss:1.90691	validation-mlogloss:1.91739
[105]	train-mlogloss:1.90269	validation-mlogloss:1.91297
[106]	train-mlogloss:1.89865	validation-mlogloss:1.90876
[107]	train-mlogloss:1.89453	validation-mlogloss:1.90438
[108]	train-mlogloss:1.89046	validation-mlogloss:1.90015
[109]	train-mlogloss:1.88648	validation-mlogloss:1.89604
[110]	train-mlogloss:1.88252	validation-mlogloss:1.89210
[111]	train-mlogloss:1.87850	validation-mlogloss:1.88799
[112]	train-mlogloss:1.87460	validation-mlogloss:1.88381
[113]	train-mlogloss:1.87081	validation-mlogloss:1.87992
[114]	train-mlogloss:1.86698	validation-mlogloss:1.87589
[115]	train-mlogloss:1.86315	validation-mlogloss:1.87199
[116]	train-mlogloss:1.85937	validation-mlogloss:1.86810
[117]	train-mlogloss:1.85542	validation-mlogloss:1.86406
[118]	train-mlogloss:1.85169	validation-mlogloss:1.86024
[119]	train-mlogloss:1.84806	validation-mlogloss:1.85658
[120]	train-mlogloss:1.84441	validation-mlogloss:1.85289
[121]	train-mlogloss:1.84075	validation-mlogloss:1.84912
[122]	train-mlogloss:1.83688	validation-mlogloss:1.84512
[123]	train-mlogloss:1.83323	validation-mlogloss:1.84123
[124]	train-mlogloss:1.82971	validation-mlogloss:1.83781
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[727]	train-mlogloss:1.19144	validation-mlogloss:1.20717
[728]	train-mlogloss:1.19112	validation-mlogloss:1.20694
[729]	train-mlogloss:1.19083	validation-mlogloss:1.20672
[730]	train-mlogloss:1.19047	validation-mlogloss:1.20658
[731]	train-mlogloss:1.19012	validation-mlogloss:1.20638
[732]	train-mlogloss:1.18979	validation-mlogloss:1.20613
[733]	train-mlogloss:1.18947	validation-mlogloss:1.20599
[734]	train-mlogloss:1.18919	validation-mlogloss:1.20579
[735]	train-mlogloss:1.18891	validation-mlogloss:1.20558
[736]	train-mlogloss:1.18860	validation-mlogloss:1.20536
[737]	train-mlogloss:1.18827	validation-mlogloss:1.20513
[738]	train-mlogloss:1.18799	validation-mlogloss:1.20495
[739]	train-mlogloss:1.18768	validation-mlogloss:1.20471
[740]	train-mlogloss:1.18739	validation-mlogloss:1.20453
[741]	train-mlogloss:1.18710	validation-mlogloss:1.20434
[742]	train-mlogloss:1.18678	validation-mlogloss:1.20413
[743]	train-mlogloss:1.18648	validation-mlogloss:1.20395
[744]	train-mlogloss:1.18618	validation-mlogloss:1.20380
[745]	train-mlogloss:1.18589	validation-mlogloss:1.20366
[746]	train-mlogloss:1.18562	validation-mlogloss:1.20351
[747]	train-mlogloss:1.18532	validation-mlogloss:1.20340
[748]	train-mlogloss:1.18502	validation-mlogloss:1.20321
[749]	train-mlogloss:1.18476	validation-mlogloss:1.20309
[750]	train-mlogloss:1.18441	validation-mlogloss:1.20289
[751]	train-mlogloss:1.18409	validation-mlogloss:1.20271
[752]	train-mlogloss:1.18380	validation-mlogloss:1.20257
[753]	train-mlogloss:1.18349	validation-mlogloss:1.20242
[754]	train-mlogloss:1.18320	validation-mlogloss:1.20222
[755]	train-mlogloss:1.18293	validation-mlogloss:1.20208
[756]	train-mlogloss:1.18266	validation-mlogloss:1.20194
[757]	train-mlogloss:1.18237	validation-mlogloss:1.20181
[758]	train-mlogloss:1.18207	validation-mlogloss:1.20169
[759]	train-mlogloss:1.18181	validation-mlogloss:1.20147
[760]	train-mlogloss:1.18153	validation-mlogloss:1.20131
Saved model to disk.
2025-11-06 14:08:22.252552: 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`.
2025-11-06 14:08:22.264019: 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 00:00:1762434502.277457 1376820 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434502.281683 1376820 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434502.291530 1376820 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434502.291548 1376820 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434502.291550 1376820 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434502.291552 1376820 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:08:22.294717: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69308	validation-mlogloss:2.69362
[1]	train-mlogloss:2.67843	validation-mlogloss:2.67963
[2]	train-mlogloss:2.66422	validation-mlogloss:2.66582
[3]	train-mlogloss:2.65006	validation-mlogloss:2.65182
[4]	train-mlogloss:2.63632	validation-mlogloss:2.63861
[5]	train-mlogloss:2.62273	validation-mlogloss:2.62567
[6]	train-mlogloss:2.60919	validation-mlogloss:2.61277
[7]	train-mlogloss:2.59665	validation-mlogloss:2.60051
[8]	train-mlogloss:2.58400	validation-mlogloss:2.58849
[9]	train-mlogloss:2.57175	validation-mlogloss:2.57692
[10]	train-mlogloss:2.55920	validation-mlogloss:2.56476
[11]	train-mlogloss:2.54720	validation-mlogloss:2.55316
[12]	train-mlogloss:2.53514	validation-mlogloss:2.54161
[13]	train-mlogloss:2.52315	validation-mlogloss:2.53000
[14]	train-mlogloss:2.51196	validation-mlogloss:2.51922
[15]	train-mlogloss:2.50079	validation-mlogloss:2.50849
[16]	train-mlogloss:2.48965	validation-mlogloss:2.49761
[17]	train-mlogloss:2.47869	validation-mlogloss:2.48688
[18]	train-mlogloss:2.46786	validation-mlogloss:2.47624
[19]	train-mlogloss:2.45718	validation-mlogloss:2.46605
[20]	train-mlogloss:2.44699	validation-mlogloss:2.45612
[21]	train-mlogloss:2.43682	validation-mlogloss:2.44643
[22]	train-mlogloss:2.42697	validation-mlogloss:2.43684
[23]	train-mlogloss:2.41718	validation-mlogloss:2.42745
[24]	train-mlogloss:2.40753	validation-mlogloss:2.41813
[25]	train-mlogloss:2.39805	validation-mlogloss:2.40898
[26]	train-mlogloss:2.38880	validation-mlogloss:2.40034
[27]	train-mlogloss:2.37956	validation-mlogloss:2.39138
[28]	train-mlogloss:2.37038	validation-mlogloss:2.38241
[29]	train-mlogloss:2.36146	validation-mlogloss:2.37373
[30]	train-mlogloss:2.35259	validation-mlogloss:2.36508
[31]	train-mlogloss:2.34366	validation-mlogloss:2.35626
[32]	train-mlogloss:2.33497	validation-mlogloss:2.34785
[33]	train-mlogloss:2.32665	validation-mlogloss:2.33956
[34]	train-mlogloss:2.31820	validation-mlogloss:2.33144
[35]	train-mlogloss:2.30998	validation-mlogloss:2.32342
[36]	train-mlogloss:2.30180	validation-mlogloss:2.31537
[37]	train-mlogloss:2.29379	validation-mlogloss:2.30737
[38]	train-mlogloss:2.28584	validation-mlogloss:2.29975
[39]	train-mlogloss:2.27781	validation-mlogloss:2.29198
[40]	train-mlogloss:2.27006	validation-mlogloss:2.28442
[41]	train-mlogloss:2.26233	validation-mlogloss:2.27656
[42]	train-mlogloss:2.25471	validation-mlogloss:2.26896
[43]	train-mlogloss:2.24692	validation-mlogloss:2.26106
[44]	train-mlogloss:2.23960	validation-mlogloss:2.25383
[45]	train-mlogloss:2.23239	validation-mlogloss:2.24696
[46]	train-mlogloss:2.22508	validation-mlogloss:2.23972
[47]	train-mlogloss:2.21787	validation-mlogloss:2.23268
[48]	train-mlogloss:2.21068	validation-mlogloss:2.22533
[49]	train-mlogloss:2.20362	validation-mlogloss:2.21843
[50]	train-mlogloss:2.19682	validation-mlogloss:2.21165
[51]	train-mlogloss:2.19000	validation-mlogloss:2.20485
[52]	train-mlogloss:2.18340	validation-mlogloss:2.19836
[53]	train-mlogloss:2.17663	validation-mlogloss:2.19179
[54]	train-mlogloss:2.17004	validation-mlogloss:2.18511
[55]	train-mlogloss:2.16345	validation-mlogloss:2.17876
[56]	train-mlogloss:2.15673	validation-mlogloss:2.17193
[57]	train-mlogloss:2.15045	validation-mlogloss:2.16575
[58]	train-mlogloss:2.14404	validation-mlogloss:2.15931
[59]	train-mlogloss:2.13770	validation-mlogloss:2.15304
[60]	train-mlogloss:2.13151	validation-mlogloss:2.14685
[61]	train-mlogloss:2.12512	validation-mlogloss:2.14028
[62]	train-mlogloss:2.11887	validation-mlogloss:2.13391
[63]	train-mlogloss:2.11277	validation-mlogloss:2.12767
[64]	train-mlogloss:2.10683	validation-mlogloss:2.12171
[65]	train-mlogloss:2.10082	validation-mlogloss:2.11550
[66]	train-mlogloss:2.09487	validation-mlogloss:2.10953
[67]	train-mlogloss:2.08909	validation-mlogloss:2.10377
[68]	train-mlogloss:2.08337	validation-mlogloss:2.09794
[69]	train-mlogloss:2.07756	validation-mlogloss:2.09181
[70]	train-mlogloss:2.07184	validation-mlogloss:2.08595
[71]	train-mlogloss:2.06634	validation-mlogloss:2.08024
[72]	train-mlogloss:2.06045	validation-mlogloss:2.07434
[73]	train-mlogloss:2.05514	validation-mlogloss:2.06908
[74]	train-mlogloss:2.04987	validation-mlogloss:2.06386
[75]	train-mlogloss:2.04451	validation-mlogloss:2.05832
[76]	train-mlogloss:2.03915	validation-mlogloss:2.05283
[77]	train-mlogloss:2.03391	validation-mlogloss:2.04762
[78]	train-mlogloss:2.02872	validation-mlogloss:2.04240
[79]	train-mlogloss:2.02365	validation-mlogloss:2.03728
[80]	train-mlogloss:2.01869	validation-mlogloss:2.03218
[81]	train-mlogloss:2.01363	validation-mlogloss:2.02697
[82]	train-mlogloss:2.00850	validation-mlogloss:2.02168
[83]	train-mlogloss:2.00334	validation-mlogloss:2.01654
[84]	train-mlogloss:1.99832	validation-mlogloss:2.01147
[85]	train-mlogloss:1.99329	validation-mlogloss:2.00624
[86]	train-mlogloss:1.98852	validation-mlogloss:2.00138
[87]	train-mlogloss:1.98376	validation-mlogloss:1.99658
[88]	train-mlogloss:1.97903	validation-mlogloss:1.99182
[89]	train-mlogloss:1.97429	validation-mlogloss:1.98685
[90]	train-mlogloss:1.96963	validation-mlogloss:1.98202
[91]	train-mlogloss:1.96484	validation-mlogloss:1.97695
[92]	train-mlogloss:1.96018	validation-mlogloss:1.97210
[93]	train-mlogloss:1.95563	validation-mlogloss:1.96733
[94]	train-mlogloss:1.95112	validation-mlogloss:1.96265
[95]	train-mlogloss:1.94667	validation-mlogloss:1.95815
[96]	train-mlogloss:1.94229	validation-mlogloss:1.95359
[97]	train-mlogloss:1.93782	validation-mlogloss:1.94904
[98]	train-mlogloss:1.93349	validation-mlogloss:1.94469
[99]	train-mlogloss:1.92915	validation-mlogloss:1.94012
[100]	train-mlogloss:1.92482	validation-mlogloss:1.93580
[101]	train-mlogloss:1.92054	validation-mlogloss:1.93150
[102]	train-mlogloss:1.91628	validation-mlogloss:1.92713
[103]	train-mlogloss:1.91210	validation-mlogloss:1.92291
[104]	train-mlogloss:1.90794	validation-mlogloss:1.91847
[105]	train-mlogloss:1.90381	validation-mlogloss:1.91425
[106]	train-mlogloss:1.89972	validation-mlogloss:1.91005
[107]	train-mlogloss:1.89562	validation-mlogloss:1.90593
[108]	train-mlogloss:1.89158	validation-mlogloss:1.90184
[109]	train-mlogloss:1.88755	validation-mlogloss:1.89767
[110]	train-mlogloss:1.88371	validation-mlogloss:1.89370
[111]	train-mlogloss:1.87978	validation-mlogloss:1.88959
[112]	train-mlogloss:1.87589	validation-mlogloss:1.88568
[113]	train-mlogloss:1.87201	validation-mlogloss:1.88168
[114]	train-mlogloss:1.86820	validation-mlogloss:1.87771
[115]	train-mlogloss:1.86441	validation-mlogloss:1.87386
[116]	train-mlogloss:1.86038	validation-mlogloss:1.86957
[117]	train-mlogloss:1.85662	validation-mlogloss:1.86565
[118]	train-mlogloss:1.85298	validation-mlogloss:1.86187
[119]	train-mlogloss:1.84930	validation-mlogloss:1.85810
[120]	train-mlogloss:1.84553	validation-mlogloss:1.85412
[121]	train-mlogloss:1.84191	validation-mlogloss:1.85032
[122]	train-mlogloss:1.83824	validation-mlogloss:1.84648
[123]	train-mlogloss:1.83460	validation-mlogloss:1.84272
[124]	train-mlogloss:1.83098	validation-mlogloss:1.83901
[125]	train-mlogloss:1.82724	validation-mlogloss:1.83514
[126]	train-mlogloss:1.82338	validation-mlogloss:1.83111
[127]	train-mlogloss:1.81987	validation-mlogloss:1.82748
[128]	train-mlogloss:1.81645	validation-mlogloss:1.82387
[129]	train-mlogloss:1.81312	validation-mlogloss:1.82033
[130]	train-mlogloss:1.80974	validation-mlogloss:1.81681
[131]	train-mlogloss:1.80640	validation-mlogloss:1.81344
[132]	train-mlogloss:1.80317	validation-mlogloss:1.81011
[133]	train-mlogloss:1.79983	validation-mlogloss:1.80664
[134]	train-mlogloss:1.79655	validation-mlogloss:1.80320
[135]	train-mlogloss:1.79330	validation-mlogloss:1.79964
[136]	train-mlogloss:1.79002	validation-mlogloss:1.79621
[137]	train-mlogloss:1.78686	validation-mlogloss:1.79290
[138]	train-mlogloss:1.78364	validation-mlogloss:1.78954
[139]	train-mlogloss:1.78015	validation-mlogloss:1.78599
[140]	train-mlogloss:1.77702	validation-mlogloss:1.78277
[141]	train-mlogloss:1.77390	validation-mlogloss:1.77950
[142]	train-mlogloss:1.77086	validation-mlogloss:1.77640
[143]	train-mlogloss:1.76781	validation-mlogloss:1.77329
[144]	train-mlogloss:1.76477	validation-mlogloss:1.77010
[145]	train-mlogloss:1.76151	validation-mlogloss:1.76666
[146]	train-mlogloss:1.75863	validation-mlogloss:1.76357
[147]	train-mlogloss:1.75562	validation-mlogloss:1.76041
[148]	train-mlogloss:1.75262	validation-mlogloss:1.75734
[149]	train-mlogloss:1.74971	validation-mlogloss:1.75429
[150]	train-mlogloss:1.74655	validation-mlogloss:1.75102
[151]	train-mlogloss:1.74364	validation-mlogloss:1.74799
[152]	train-mlogloss:1.74085	validation-mlogloss:1.74515
[153]	train-mlogloss:1.73794	validation-mlogloss:1.74210
[154]	train-mlogloss:1.73516	validation-mlogloss:1.73932
[155]	train-mlogloss:1.73215	validation-mlogloss:1.73617
[156]	train-mlogloss:1.72938	validation-mlogloss:1.73323
[157]	train-mlogloss:1.72643	validation-mlogloss:1.73002
[158]	train-mlogloss:1.72359	validation-mlogloss:1.72707
[159]	train-mlogloss:1.72063	validation-mlogloss:1.72399
[160]	train-mlogloss:1.71773	validation-mlogloss:1.72091
[161]	train-mlogloss:1.71500	validation-mlogloss:1.71806
[162]	train-mlogloss:1.71211	validation-mlogloss:1.71500
[163]	train-mlogloss:1.70924	validation-mlogloss:1.71210
[164]	train-mlogloss:1.70637	validation-mlogloss:1.70902
[165]	train-mlogloss:1.70355	validation-mlogloss:1.70607
[166]	train-mlogloss:1.70098	validation-mlogloss:1.70338
[167]	train-mlogloss:1.69823	validation-mlogloss:1.70057
[168]	train-mlogloss:1.69542	validation-mlogloss:1.69758
[169]	train-mlogloss:1.69275	validation-mlogloss:1.69471
[170]	train-mlogloss:1.69001	validation-mlogloss:1.69183
[171]	train-mlogloss:1.68727	validation-mlogloss:1.68897
[172]	train-mlogloss:1.68466	validation-mlogloss:1.68620
[173]	train-mlogloss:1.68201	validation-mlogloss:1.68349
[174]	train-mlogloss:1.67937	validation-mlogloss:1.68079
[175]	train-mlogloss:1.67677	validation-mlogloss:1.67814
[176]	train-mlogloss:1.67423	validation-mlogloss:1.67545
[177]	train-mlogloss:1.67168	validation-mlogloss:1.67276
[178]	train-mlogloss:1.66911	validation-mlogloss:1.67008
[179]	train-mlogloss:1.66660	validation-mlogloss:1.66735
[180]	train-mlogloss:1.66426	validation-mlogloss:1.66495
[181]	train-mlogloss:1.66165	validation-mlogloss:1.66239
[182]	train-mlogloss:1.65911	validation-mlogloss:1.65977
[183]	train-mlogloss:1.65661	validation-mlogloss:1.65725
[184]	train-mlogloss:1.65415	validation-mlogloss:1.65475
[185]	train-mlogloss:1.65174	validation-mlogloss:1.65225
[186]	train-mlogloss:1.64929	validation-mlogloss:1.64961
[187]	train-mlogloss:1.64687	validation-mlogloss:1.64696
[188]	train-mlogloss:1.64453	validation-mlogloss:1.64448
[189]	train-mlogloss:1.64214	validation-mlogloss:1.64195
[190]	train-mlogloss:1.63975	validation-mlogloss:1.63942
[191]	train-mlogloss:1.63748	validation-mlogloss:1.63699
[192]	train-mlogloss:1.63516	validation-mlogloss:1.63449
[193]	train-mlogloss:1.63277	validation-mlogloss:1.63199
[194]	train-mlogloss:1.63048	validation-mlogloss:1.62960
[195]	train-mlogloss:1.62820	validation-mlogloss:1.62723
[196]	train-mlogloss:1.62590	validation-mlogloss:1.62486
[197]	train-mlogloss:1.62357	validation-mlogloss:1.62245
[198]	train-mlogloss:1.62139	validation-mlogloss:1.62010
[199]	train-mlogloss:1.61918	validation-mlogloss:1.61778
[200]	train-mlogloss:1.61700	validation-mlogloss:1.61544
[201]	train-mlogloss:1.61479	validation-mlogloss:1.61307
[202]	train-mlogloss:1.61258	validation-mlogloss:1.61064
[203]	train-mlogloss:1.61040	validation-mlogloss:1.60834
[204]	train-mlogloss:1.60828	validation-mlogloss:1.60606
[205]	train-mlogloss:1.60615	validation-mlogloss:1.60380
[206]	train-mlogloss:1.60408	validation-mlogloss:1.60158
[207]	train-mlogloss:1.60183	validation-mlogloss:1.59925
[208]	train-mlogloss:1.59968	validation-mlogloss:1.59691
[209]	train-mlogloss:1.59763	validation-mlogloss:1.59473
[210]	train-mlogloss:1.59555	validation-mlogloss:1.59248
[211]	train-mlogloss:1.59355	validation-mlogloss:1.59046
[212]	train-mlogloss:1.59138	validation-mlogloss:1.58826
[213]	train-mlogloss:1.58926	validation-mlogloss:1.58604
[214]	train-mlogloss:1.58719	validation-mlogloss:1.58390
[215]	train-mlogloss:1.58519	validation-mlogloss:1.58195
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[217]	train-mlogloss:1.58123	validation-mlogloss:1.57787
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[219]	train-mlogloss:1.57728	validation-mlogloss:1.57359
[220]	train-mlogloss:1.57528	validation-mlogloss:1.57143
[221]	train-mlogloss:1.57334	validation-mlogloss:1.56939
[222]	train-mlogloss:1.57146	validation-mlogloss:1.56737
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[229]	train-mlogloss:1.55820	validation-mlogloss:1.55349
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[610]	train-mlogloss:1.23261	validation-mlogloss:1.23419
[611]	train-mlogloss:1.23217	validation-mlogloss:1.23394
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[629]	train-mlogloss:1.22514	validation-mlogloss:1.22873
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[692]	train-mlogloss:1.20253	validation-mlogloss:1.21387
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[711]	train-mlogloss:1.19626	validation-mlogloss:1.20990
[712]	train-mlogloss:1.19592	validation-mlogloss:1.20973
[713]	train-mlogloss:1.19559	validation-mlogloss:1.20958
[714]	train-mlogloss:1.19524	validation-mlogloss:1.20938
[715]	train-mlogloss:1.19489	validation-mlogloss:1.20913
[716]	train-mlogloss:1.19461	validation-mlogloss:1.20896
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[718]	train-mlogloss:1.19394	validation-mlogloss:1.20865
[719]	train-mlogloss:1.19358	validation-mlogloss:1.20844
[720]	train-mlogloss:1.19326	validation-mlogloss:1.20826
[721]	train-mlogloss:1.19293	validation-mlogloss:1.20807
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[725]	train-mlogloss:1.19165	validation-mlogloss:1.20730
[726]	train-mlogloss:1.19129	validation-mlogloss:1.20712
[727]	train-mlogloss:1.19097	validation-mlogloss:1.20699
[728]	train-mlogloss:1.19068	validation-mlogloss:1.20682
[729]	train-mlogloss:1.19034	validation-mlogloss:1.20661
[730]	train-mlogloss:1.19004	validation-mlogloss:1.20640
[731]	train-mlogloss:1.18973	validation-mlogloss:1.20623
[732]	train-mlogloss:1.18944	validation-mlogloss:1.20604
[733]	train-mlogloss:1.18915	validation-mlogloss:1.20587
[734]	train-mlogloss:1.18885	validation-mlogloss:1.20568
[735]	train-mlogloss:1.18857	validation-mlogloss:1.20547
[736]	train-mlogloss:1.18826	validation-mlogloss:1.20530
[737]	train-mlogloss:1.18796	validation-mlogloss:1.20513
[738]	train-mlogloss:1.18767	validation-mlogloss:1.20499
[739]	train-mlogloss:1.18735	validation-mlogloss:1.20473
[740]	train-mlogloss:1.18704	validation-mlogloss:1.20457
[741]	train-mlogloss:1.18675	validation-mlogloss:1.20434
[742]	train-mlogloss:1.18648	validation-mlogloss:1.20414
[743]	train-mlogloss:1.18613	validation-mlogloss:1.20397
[744]	train-mlogloss:1.18580	validation-mlogloss:1.20376
[745]	train-mlogloss:1.18550	validation-mlogloss:1.20362
[746]	train-mlogloss:1.18516	validation-mlogloss:1.20336
[747]	train-mlogloss:1.18489	validation-mlogloss:1.20318
[748]	train-mlogloss:1.18457	validation-mlogloss:1.20295
[749]	train-mlogloss:1.18427	validation-mlogloss:1.20272
[750]	train-mlogloss:1.18397	validation-mlogloss:1.20247
[751]	train-mlogloss:1.18371	validation-mlogloss:1.20235
[752]	train-mlogloss:1.18343	validation-mlogloss:1.20221
[753]	train-mlogloss:1.18315	validation-mlogloss:1.20200
[754]	train-mlogloss:1.18286	validation-mlogloss:1.20184
[755]	train-mlogloss:1.18256	validation-mlogloss:1.20165
[756]	train-mlogloss:1.18226	validation-mlogloss:1.20149
[757]	train-mlogloss:1.18197	validation-mlogloss:1.20129
[758]	train-mlogloss:1.18165	validation-mlogloss:1.20111
[759]	train-mlogloss:1.18136	validation-mlogloss:1.20099
[760]	train-mlogloss:1.18105	validation-mlogloss:1.20081
Saved model to disk.
2025-11-06 14:08:46.800596: 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`.
2025-11-06 14:08:46.811650: 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 00:00:1762434526.824464 1377226 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434526.828403 1377226 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434526.838116 1377226 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434526.838132 1377226 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434526.838134 1377226 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434526.838136 1377226 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:08:46.841141: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69334	validation-mlogloss:2.69363
[1]	train-mlogloss:2.67889	validation-mlogloss:2.67995
[2]	train-mlogloss:2.66476	validation-mlogloss:2.66618
[3]	train-mlogloss:2.65067	validation-mlogloss:2.65270
[4]	train-mlogloss:2.63706	validation-mlogloss:2.63984
[5]	train-mlogloss:2.62348	validation-mlogloss:2.62674
[6]	train-mlogloss:2.61036	validation-mlogloss:2.61390
[7]	train-mlogloss:2.59717	validation-mlogloss:2.60122
[8]	train-mlogloss:2.58417	validation-mlogloss:2.58892
[9]	train-mlogloss:2.57169	validation-mlogloss:2.57712
[10]	train-mlogloss:2.55932	validation-mlogloss:2.56506
[11]	train-mlogloss:2.54744	validation-mlogloss:2.55349
[12]	train-mlogloss:2.53618	validation-mlogloss:2.54290
[13]	train-mlogloss:2.52454	validation-mlogloss:2.53163
[14]	train-mlogloss:2.51305	validation-mlogloss:2.52062
[15]	train-mlogloss:2.50184	validation-mlogloss:2.50965
[16]	train-mlogloss:2.49064	validation-mlogloss:2.49894
[17]	train-mlogloss:2.47966	validation-mlogloss:2.48864
[18]	train-mlogloss:2.46903	validation-mlogloss:2.47868
[19]	train-mlogloss:2.45854	validation-mlogloss:2.46847
[20]	train-mlogloss:2.44832	validation-mlogloss:2.45836
[21]	train-mlogloss:2.43830	validation-mlogloss:2.44859
[22]	train-mlogloss:2.42838	validation-mlogloss:2.43906
[23]	train-mlogloss:2.41866	validation-mlogloss:2.42960
[24]	train-mlogloss:2.40903	validation-mlogloss:2.42028
[25]	train-mlogloss:2.39931	validation-mlogloss:2.41077
[26]	train-mlogloss:2.38981	validation-mlogloss:2.40162
[27]	train-mlogloss:2.38040	validation-mlogloss:2.39259
[28]	train-mlogloss:2.37124	validation-mlogloss:2.38348
[29]	train-mlogloss:2.36229	validation-mlogloss:2.37476
[30]	train-mlogloss:2.35346	validation-mlogloss:2.36615
[31]	train-mlogloss:2.34458	validation-mlogloss:2.35712
[32]	train-mlogloss:2.33593	validation-mlogloss:2.34868
[33]	train-mlogloss:2.32760	validation-mlogloss:2.34054
[34]	train-mlogloss:2.31905	validation-mlogloss:2.33197
[35]	train-mlogloss:2.31086	validation-mlogloss:2.32407
[36]	train-mlogloss:2.30275	validation-mlogloss:2.31634
[37]	train-mlogloss:2.29486	validation-mlogloss:2.30857
[38]	train-mlogloss:2.28707	validation-mlogloss:2.30103
[39]	train-mlogloss:2.27908	validation-mlogloss:2.29303
[40]	train-mlogloss:2.27129	validation-mlogloss:2.28522
[41]	train-mlogloss:2.26355	validation-mlogloss:2.27753
[42]	train-mlogloss:2.25588	validation-mlogloss:2.26994
[43]	train-mlogloss:2.24835	validation-mlogloss:2.26251
[44]	train-mlogloss:2.24112	validation-mlogloss:2.25530
[45]	train-mlogloss:2.23367	validation-mlogloss:2.24788
[46]	train-mlogloss:2.22658	validation-mlogloss:2.24089
[47]	train-mlogloss:2.21958	validation-mlogloss:2.23410
[48]	train-mlogloss:2.21241	validation-mlogloss:2.22687
[49]	train-mlogloss:2.20529	validation-mlogloss:2.21981
[50]	train-mlogloss:2.19819	validation-mlogloss:2.21285
[51]	train-mlogloss:2.19130	validation-mlogloss:2.20595
[52]	train-mlogloss:2.18453	validation-mlogloss:2.19914
[53]	train-mlogloss:2.17808	validation-mlogloss:2.19291
[54]	train-mlogloss:2.17144	validation-mlogloss:2.18639
[55]	train-mlogloss:2.16490	validation-mlogloss:2.17987
[56]	train-mlogloss:2.15840	validation-mlogloss:2.17343
[57]	train-mlogloss:2.15180	validation-mlogloss:2.16668
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[659]	train-mlogloss:1.21527	validation-mlogloss:1.22239
[660]	train-mlogloss:1.21493	validation-mlogloss:1.22215
[661]	train-mlogloss:1.21458	validation-mlogloss:1.22187
[662]	train-mlogloss:1.21422	validation-mlogloss:1.22170
[663]	train-mlogloss:1.21386	validation-mlogloss:1.22143
[664]	train-mlogloss:1.21345	validation-mlogloss:1.22127
[665]	train-mlogloss:1.21310	validation-mlogloss:1.22105
[666]	train-mlogloss:1.21278	validation-mlogloss:1.22083
[667]	train-mlogloss:1.21245	validation-mlogloss:1.22063
[668]	train-mlogloss:1.21212	validation-mlogloss:1.22036
[669]	train-mlogloss:1.21175	validation-mlogloss:1.22007
[670]	train-mlogloss:1.21137	validation-mlogloss:1.21985
[671]	train-mlogloss:1.21104	validation-mlogloss:1.21963
[672]	train-mlogloss:1.21068	validation-mlogloss:1.21939
[673]	train-mlogloss:1.21033	validation-mlogloss:1.21915
[674]	train-mlogloss:1.20995	validation-mlogloss:1.21893
[675]	train-mlogloss:1.20960	validation-mlogloss:1.21873
[676]	train-mlogloss:1.20925	validation-mlogloss:1.21845
[677]	train-mlogloss:1.20889	validation-mlogloss:1.21820
[678]	train-mlogloss:1.20853	validation-mlogloss:1.21800
[679]	train-mlogloss:1.20818	validation-mlogloss:1.21772
[680]	train-mlogloss:1.20783	validation-mlogloss:1.21749
[681]	train-mlogloss:1.20746	validation-mlogloss:1.21726
[682]	train-mlogloss:1.20708	validation-mlogloss:1.21702
[683]	train-mlogloss:1.20673	validation-mlogloss:1.21679
[684]	train-mlogloss:1.20637	validation-mlogloss:1.21657
[685]	train-mlogloss:1.20605	validation-mlogloss:1.21634
[686]	train-mlogloss:1.20569	validation-mlogloss:1.21608
[687]	train-mlogloss:1.20535	validation-mlogloss:1.21588
[688]	train-mlogloss:1.20504	validation-mlogloss:1.21574
[689]	train-mlogloss:1.20472	validation-mlogloss:1.21554
[690]	train-mlogloss:1.20438	validation-mlogloss:1.21532
[691]	train-mlogloss:1.20404	validation-mlogloss:1.21510
[692]	train-mlogloss:1.20370	validation-mlogloss:1.21492
[693]	train-mlogloss:1.20338	validation-mlogloss:1.21468
[694]	train-mlogloss:1.20298	validation-mlogloss:1.21439
[695]	train-mlogloss:1.20264	validation-mlogloss:1.21418
[696]	train-mlogloss:1.20225	validation-mlogloss:1.21395
[697]	train-mlogloss:1.20193	validation-mlogloss:1.21371
[698]	train-mlogloss:1.20162	validation-mlogloss:1.21352
[699]	train-mlogloss:1.20128	validation-mlogloss:1.21335
[700]	train-mlogloss:1.20093	validation-mlogloss:1.21313
[701]	train-mlogloss:1.20062	validation-mlogloss:1.21294
[702]	train-mlogloss:1.20030	validation-mlogloss:1.21270
[703]	train-mlogloss:1.20001	validation-mlogloss:1.21246
[704]	train-mlogloss:1.19966	validation-mlogloss:1.21216
[705]	train-mlogloss:1.19929	validation-mlogloss:1.21187
[706]	train-mlogloss:1.19896	validation-mlogloss:1.21163
[707]	train-mlogloss:1.19865	validation-mlogloss:1.21152
[708]	train-mlogloss:1.19834	validation-mlogloss:1.21131
[709]	train-mlogloss:1.19803	validation-mlogloss:1.21116
[710]	train-mlogloss:1.19770	validation-mlogloss:1.21092
[711]	train-mlogloss:1.19737	validation-mlogloss:1.21077
[712]	train-mlogloss:1.19704	validation-mlogloss:1.21057
[713]	train-mlogloss:1.19674	validation-mlogloss:1.21034
[714]	train-mlogloss:1.19643	validation-mlogloss:1.21010
[715]	train-mlogloss:1.19613	validation-mlogloss:1.20993
[716]	train-mlogloss:1.19582	validation-mlogloss:1.20971
[717]	train-mlogloss:1.19548	validation-mlogloss:1.20950
[718]	train-mlogloss:1.19520	validation-mlogloss:1.20932
[719]	train-mlogloss:1.19491	validation-mlogloss:1.20916
[720]	train-mlogloss:1.19456	validation-mlogloss:1.20900
[721]	train-mlogloss:1.19425	validation-mlogloss:1.20876
[722]	train-mlogloss:1.19398	validation-mlogloss:1.20862
[723]	train-mlogloss:1.19364	validation-mlogloss:1.20840
[724]	train-mlogloss:1.19331	validation-mlogloss:1.20819
[725]	train-mlogloss:1.19302	validation-mlogloss:1.20805
[726]	train-mlogloss:1.19270	validation-mlogloss:1.20788
[727]	train-mlogloss:1.19241	validation-mlogloss:1.20771
[728]	train-mlogloss:1.19208	validation-mlogloss:1.20752
[729]	train-mlogloss:1.19179	validation-mlogloss:1.20730
[730]	train-mlogloss:1.19149	validation-mlogloss:1.20710
[731]	train-mlogloss:1.19117	validation-mlogloss:1.20689
[732]	train-mlogloss:1.19087	validation-mlogloss:1.20670
[733]	train-mlogloss:1.19058	validation-mlogloss:1.20653
[734]	train-mlogloss:1.19028	validation-mlogloss:1.20638
[735]	train-mlogloss:1.18999	validation-mlogloss:1.20622
[736]	train-mlogloss:1.18965	validation-mlogloss:1.20597
[737]	train-mlogloss:1.18937	validation-mlogloss:1.20583
[738]	train-mlogloss:1.18906	validation-mlogloss:1.20560
[739]	train-mlogloss:1.18878	validation-mlogloss:1.20541
[740]	train-mlogloss:1.18850	validation-mlogloss:1.20524
[741]	train-mlogloss:1.18822	validation-mlogloss:1.20508
[742]	train-mlogloss:1.18790	validation-mlogloss:1.20483
[743]	train-mlogloss:1.18762	validation-mlogloss:1.20464
[744]	train-mlogloss:1.18731	validation-mlogloss:1.20446
[745]	train-mlogloss:1.18696	validation-mlogloss:1.20427
[746]	train-mlogloss:1.18661	validation-mlogloss:1.20412
[747]	train-mlogloss:1.18627	validation-mlogloss:1.20394
[748]	train-mlogloss:1.18596	validation-mlogloss:1.20380
[749]	train-mlogloss:1.18567	validation-mlogloss:1.20364
[750]	train-mlogloss:1.18538	validation-mlogloss:1.20349
[751]	train-mlogloss:1.18511	validation-mlogloss:1.20335
[752]	train-mlogloss:1.18482	validation-mlogloss:1.20310
[753]	train-mlogloss:1.18454	validation-mlogloss:1.20288
[754]	train-mlogloss:1.18424	validation-mlogloss:1.20268
[755]	train-mlogloss:1.18392	validation-mlogloss:1.20247
[756]	train-mlogloss:1.18360	validation-mlogloss:1.20234
[757]	train-mlogloss:1.18330	validation-mlogloss:1.20220
[758]	train-mlogloss:1.18298	validation-mlogloss:1.20203
[759]	train-mlogloss:1.18268	validation-mlogloss:1.20186
[760]	train-mlogloss:1.18235	validation-mlogloss:1.20168
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.58 [%]
Global accuracy score (test) = 58.88 [%]
Global F1 score (train) = 61.11 [%]
Global F1 score (test) = 57.76 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.34      0.19      0.25       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.52      0.44       161
       CAMINAR USUAL SPEED       0.41      0.37      0.39       161
            CAMINAR ZIGZAG       0.42      0.40      0.41       161
          DE PIE BARRIENDO       0.66      0.73      0.69       161
   DE PIE DOBLANDO TOALLAS       0.40      0.41      0.41       161
    DE PIE MOVIENDO LIBROS       0.49      0.48      0.49       161
          DE PIE USANDO PC       0.86      0.89      0.87       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.50      0.36      0.42       161
         SENTADO USANDO PC       0.51      0.53      0.52       161
      SENTADO VIENDO LA TV       0.44      0.30      0.36       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.87      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 7: 58.88 [%]
F1-score capturado en la ejecución 7: 57.76 [%]

=== EJECUCIÓN 8 ===

--- TRAIN (ejecución 8) ---

--- TEST (ejecución 8) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.67 [%]
Global accuracy score (test) = 58.67 [%]
Global F1 score (train) = 61.23 [%]
Global F1 score (test) = 57.57 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.36      0.19      0.25       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.52      0.43       161
       CAMINAR USUAL SPEED       0.38      0.35      0.36       161
            CAMINAR ZIGZAG       0.42      0.39      0.41       161
          DE PIE BARRIENDO       0.66      0.75      0.70       161
   DE PIE DOBLANDO TOALLAS       0.40      0.41      0.40       161
    DE PIE MOVIENDO LIBROS       0.50      0.50      0.50       161
          DE PIE USANDO PC       0.87      0.87      0.87       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.53      0.39      0.45       161
         SENTADO USANDO PC       0.50      0.53      0.51       161
      SENTADO VIENDO LA TV       0.42      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.61      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 8: 58.67 [%]
F1-score capturado en la ejecución 8: 57.57 [%]

=== EJECUCIÓN 9 ===

--- TRAIN (ejecución 9) ---

--- TEST (ejecución 9) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.49 [%]
Global accuracy score (test) = 58.84 [%]
Global F1 score (train) = 61.06 [%]
Global F1 score (test) = 57.87 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.40      0.24      0.30       161
 CAMINAR CON MÓVIL O LIBRO       0.35      0.51      0.42       161
       CAMINAR USUAL SPEED       0.41      0.35      0.38       161
            CAMINAR ZIGZAG       0.41      0.39      0.39       161
          DE PIE BARRIENDO       0.67      0.73      0.70       161
   DE PIE DOBLANDO TOALLAS       0.40      0.41      0.40       161
    DE PIE MOVIENDO LIBROS       0.49      0.50      0.49       161
          DE PIE USANDO PC       0.85      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.53      0.39      0.45       161
         SENTADO USANDO PC       0.50      0.53      0.51       161
      SENTADO VIENDO LA TV       0.45      0.29      0.35       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 9: 58.84 [%]
F1-score capturado en la ejecución 9: 57.87 [%]

=== EJECUCIÓN 10 ===

--- TRAIN (ejecución 10) ---

--- TEST (ejecución 10) ---
2025-11-06 14:09:11.065341: 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`.
2025-11-06 14:09:11.076470: 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 00:00:1762434551.089525 1377630 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434551.093629 1377630 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434551.103292 1377630 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434551.103308 1377630 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434551.103310 1377630 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434551.103311 1377630 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:09:11.106465: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69325	validation-mlogloss:2.69376
[1]	train-mlogloss:2.67874	validation-mlogloss:2.67976
[2]	train-mlogloss:2.66451	validation-mlogloss:2.66576
[3]	train-mlogloss:2.64996	validation-mlogloss:2.65174
[4]	train-mlogloss:2.63625	validation-mlogloss:2.63877
[5]	train-mlogloss:2.62272	validation-mlogloss:2.62573
[6]	train-mlogloss:2.60937	validation-mlogloss:2.61296
[7]	train-mlogloss:2.59648	validation-mlogloss:2.60064
[8]	train-mlogloss:2.58359	validation-mlogloss:2.58799
[9]	train-mlogloss:2.57142	validation-mlogloss:2.57613
[10]	train-mlogloss:2.55932	validation-mlogloss:2.56449
[11]	train-mlogloss:2.54749	validation-mlogloss:2.55345
[12]	train-mlogloss:2.53535	validation-mlogloss:2.54155
[13]	train-mlogloss:2.52377	validation-mlogloss:2.53044
[14]	train-mlogloss:2.51266	validation-mlogloss:2.51963
[15]	train-mlogloss:2.50142	validation-mlogloss:2.50870
[16]	train-mlogloss:2.49027	validation-mlogloss:2.49799
[17]	train-mlogloss:2.47943	validation-mlogloss:2.48729
[18]	train-mlogloss:2.46917	validation-mlogloss:2.47693
[19]	train-mlogloss:2.45882	validation-mlogloss:2.46683
[20]	train-mlogloss:2.44878	validation-mlogloss:2.45730
[21]	train-mlogloss:2.43856	validation-mlogloss:2.44709
[22]	train-mlogloss:2.42850	validation-mlogloss:2.43739
[23]	train-mlogloss:2.41865	validation-mlogloss:2.42777
[24]	train-mlogloss:2.40894	validation-mlogloss:2.41852
[25]	train-mlogloss:2.39958	validation-mlogloss:2.40944
[26]	train-mlogloss:2.39033	validation-mlogloss:2.40036
[27]	train-mlogloss:2.38093	validation-mlogloss:2.39119
[28]	train-mlogloss:2.37172	validation-mlogloss:2.38224
[29]	train-mlogloss:2.36257	validation-mlogloss:2.37326
[30]	train-mlogloss:2.35361	validation-mlogloss:2.36441
[31]	train-mlogloss:2.34475	validation-mlogloss:2.35599
[32]	train-mlogloss:2.33613	validation-mlogloss:2.34756
[33]	train-mlogloss:2.32773	validation-mlogloss:2.33965
[34]	train-mlogloss:2.31954	validation-mlogloss:2.33159
[35]	train-mlogloss:2.31142	validation-mlogloss:2.32364
[36]	train-mlogloss:2.30331	validation-mlogloss:2.31571
[37]	train-mlogloss:2.29535	validation-mlogloss:2.30780
[38]	train-mlogloss:2.28751	validation-mlogloss:2.30014
[39]	train-mlogloss:2.27963	validation-mlogloss:2.29254
[40]	train-mlogloss:2.27183	validation-mlogloss:2.28500
[41]	train-mlogloss:2.26428	validation-mlogloss:2.27763
[42]	train-mlogloss:2.25642	validation-mlogloss:2.26973
[43]	train-mlogloss:2.24889	validation-mlogloss:2.26242
[44]	train-mlogloss:2.24138	validation-mlogloss:2.25507
[45]	train-mlogloss:2.23415	validation-mlogloss:2.24793
[46]	train-mlogloss:2.22666	validation-mlogloss:2.24037
[47]	train-mlogloss:2.21946	validation-mlogloss:2.23313
[48]	train-mlogloss:2.21231	validation-mlogloss:2.22615
[49]	train-mlogloss:2.20542	validation-mlogloss:2.21960
[50]	train-mlogloss:2.19845	validation-mlogloss:2.21265
[51]	train-mlogloss:2.19156	validation-mlogloss:2.20597
[52]	train-mlogloss:2.18473	validation-mlogloss:2.19899
[53]	train-mlogloss:2.17804	validation-mlogloss:2.19241
[54]	train-mlogloss:2.17147	validation-mlogloss:2.18612
[55]	train-mlogloss:2.16486	validation-mlogloss:2.17959
[56]	train-mlogloss:2.15825	validation-mlogloss:2.17277
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[730]	train-mlogloss:1.19014	validation-mlogloss:1.20626
[731]	train-mlogloss:1.18983	validation-mlogloss:1.20603
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[733]	train-mlogloss:1.18921	validation-mlogloss:1.20567
[734]	train-mlogloss:1.18890	validation-mlogloss:1.20553
[735]	train-mlogloss:1.18862	validation-mlogloss:1.20539
[736]	train-mlogloss:1.18833	validation-mlogloss:1.20523
[737]	train-mlogloss:1.18802	validation-mlogloss:1.20503
[738]	train-mlogloss:1.18773	validation-mlogloss:1.20485
[739]	train-mlogloss:1.18745	validation-mlogloss:1.20470
[740]	train-mlogloss:1.18718	validation-mlogloss:1.20459
[741]	train-mlogloss:1.18683	validation-mlogloss:1.20433
[742]	train-mlogloss:1.18653	validation-mlogloss:1.20416
[743]	train-mlogloss:1.18622	validation-mlogloss:1.20399
[744]	train-mlogloss:1.18592	validation-mlogloss:1.20381
[745]	train-mlogloss:1.18562	validation-mlogloss:1.20361
[746]	train-mlogloss:1.18534	validation-mlogloss:1.20338
[747]	train-mlogloss:1.18505	validation-mlogloss:1.20324
[748]	train-mlogloss:1.18479	validation-mlogloss:1.20312
[749]	train-mlogloss:1.18448	validation-mlogloss:1.20298
[750]	train-mlogloss:1.18419	validation-mlogloss:1.20284
[751]	train-mlogloss:1.18386	validation-mlogloss:1.20281
[752]	train-mlogloss:1.18359	validation-mlogloss:1.20272
[753]	train-mlogloss:1.18325	validation-mlogloss:1.20262
[754]	train-mlogloss:1.18295	validation-mlogloss:1.20240
[755]	train-mlogloss:1.18264	validation-mlogloss:1.20227
[756]	train-mlogloss:1.18238	validation-mlogloss:1.20204
[757]	train-mlogloss:1.18210	validation-mlogloss:1.20189
[758]	train-mlogloss:1.18183	validation-mlogloss:1.20175
[759]	train-mlogloss:1.18152	validation-mlogloss:1.20158
[760]	train-mlogloss:1.18123	validation-mlogloss:1.20147
Saved model to disk.
2025-11-06 14:09:35.925125: 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`.
2025-11-06 14:09:35.936367: 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 00:00:1762434575.949417 1378057 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434575.953589 1378057 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434575.963565 1378057 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434575.963583 1378057 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434575.963585 1378057 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434575.963586 1378057 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:09:35.966742: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
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[1]	train-mlogloss:2.67856	validation-mlogloss:2.67918
[2]	train-mlogloss:2.66413	validation-mlogloss:2.66532
[3]	train-mlogloss:2.64965	validation-mlogloss:2.65159
[4]	train-mlogloss:2.63596	validation-mlogloss:2.63850
[5]	train-mlogloss:2.62211	validation-mlogloss:2.62534
[6]	train-mlogloss:2.60884	validation-mlogloss:2.61240
[7]	train-mlogloss:2.59599	validation-mlogloss:2.60023
[8]	train-mlogloss:2.58341	validation-mlogloss:2.58818
[9]	train-mlogloss:2.57114	validation-mlogloss:2.57649
[10]	train-mlogloss:2.55900	validation-mlogloss:2.56504
[11]	train-mlogloss:2.54675	validation-mlogloss:2.55334
[12]	train-mlogloss:2.53484	validation-mlogloss:2.54212
[13]	train-mlogloss:2.52341	validation-mlogloss:2.53061
[14]	train-mlogloss:2.51207	validation-mlogloss:2.51942
[15]	train-mlogloss:2.50084	validation-mlogloss:2.50844
[16]	train-mlogloss:2.48978	validation-mlogloss:2.49781
[17]	train-mlogloss:2.47892	validation-mlogloss:2.48740
[18]	train-mlogloss:2.46810	validation-mlogloss:2.47716
[19]	train-mlogloss:2.45752	validation-mlogloss:2.46708
[20]	train-mlogloss:2.44729	validation-mlogloss:2.45722
[21]	train-mlogloss:2.43725	validation-mlogloss:2.44760
[22]	train-mlogloss:2.42737	validation-mlogloss:2.43806
[23]	train-mlogloss:2.41752	validation-mlogloss:2.42842
[24]	train-mlogloss:2.40767	validation-mlogloss:2.41907
[25]	train-mlogloss:2.39826	validation-mlogloss:2.40988
[26]	train-mlogloss:2.38875	validation-mlogloss:2.40074
[27]	train-mlogloss:2.37946	validation-mlogloss:2.39166
[28]	train-mlogloss:2.37043	validation-mlogloss:2.38276
[29]	train-mlogloss:2.36152	validation-mlogloss:2.37412
[30]	train-mlogloss:2.35266	validation-mlogloss:2.36537
[31]	train-mlogloss:2.34394	validation-mlogloss:2.35673
[32]	train-mlogloss:2.33530	validation-mlogloss:2.34837
[33]	train-mlogloss:2.32680	validation-mlogloss:2.33996
[34]	train-mlogloss:2.31839	validation-mlogloss:2.33194
[35]	train-mlogloss:2.31006	validation-mlogloss:2.32378
[36]	train-mlogloss:2.30198	validation-mlogloss:2.31605
[37]	train-mlogloss:2.29401	validation-mlogloss:2.30834
[38]	train-mlogloss:2.28603	validation-mlogloss:2.30044
[39]	train-mlogloss:2.27820	validation-mlogloss:2.29281
[40]	train-mlogloss:2.27021	validation-mlogloss:2.28486
[41]	train-mlogloss:2.26240	validation-mlogloss:2.27727
[42]	train-mlogloss:2.25493	validation-mlogloss:2.26983
[43]	train-mlogloss:2.24744	validation-mlogloss:2.26261
[44]	train-mlogloss:2.23977	validation-mlogloss:2.25480
[45]	train-mlogloss:2.23235	validation-mlogloss:2.24753
[46]	train-mlogloss:2.22516	validation-mlogloss:2.24037
[47]	train-mlogloss:2.21815	validation-mlogloss:2.23344
[48]	train-mlogloss:2.21099	validation-mlogloss:2.22646
[49]	train-mlogloss:2.20404	validation-mlogloss:2.21970
[50]	train-mlogloss:2.19716	validation-mlogloss:2.21292
[51]	train-mlogloss:2.19033	validation-mlogloss:2.20613
[52]	train-mlogloss:2.18366	validation-mlogloss:2.19955
[53]	train-mlogloss:2.17702	validation-mlogloss:2.19295
[54]	train-mlogloss:2.17037	validation-mlogloss:2.18628
[55]	train-mlogloss:2.16392	validation-mlogloss:2.17976
[56]	train-mlogloss:2.15755	validation-mlogloss:2.17346
[57]	train-mlogloss:2.15105	validation-mlogloss:2.16686
[58]	train-mlogloss:2.14451	validation-mlogloss:2.16022
[59]	train-mlogloss:2.13839	validation-mlogloss:2.15419
[60]	train-mlogloss:2.13210	validation-mlogloss:2.14774
[61]	train-mlogloss:2.12585	validation-mlogloss:2.14144
[62]	train-mlogloss:2.11993	validation-mlogloss:2.13563
[63]	train-mlogloss:2.11370	validation-mlogloss:2.12917
[64]	train-mlogloss:2.10757	validation-mlogloss:2.12288
[65]	train-mlogloss:2.10171	validation-mlogloss:2.11708
[66]	train-mlogloss:2.09555	validation-mlogloss:2.11094
[67]	train-mlogloss:2.08964	validation-mlogloss:2.10489
[68]	train-mlogloss:2.08394	validation-mlogloss:2.09913
[69]	train-mlogloss:2.07810	validation-mlogloss:2.09326
[70]	train-mlogloss:2.07261	validation-mlogloss:2.08794
[71]	train-mlogloss:2.06707	validation-mlogloss:2.08226
[72]	train-mlogloss:2.06138	validation-mlogloss:2.07641
[73]	train-mlogloss:2.05581	validation-mlogloss:2.07086
[74]	train-mlogloss:2.05037	validation-mlogloss:2.06529
[75]	train-mlogloss:2.04486	validation-mlogloss:2.05961
[76]	train-mlogloss:2.03953	validation-mlogloss:2.05424
[77]	train-mlogloss:2.03413	validation-mlogloss:2.04866
[78]	train-mlogloss:2.02882	validation-mlogloss:2.04334
[79]	train-mlogloss:2.02352	validation-mlogloss:2.03794
[80]	train-mlogloss:2.01842	validation-mlogloss:2.03262
[81]	train-mlogloss:2.01325	validation-mlogloss:2.02725
[82]	train-mlogloss:2.00826	validation-mlogloss:2.02221
[83]	train-mlogloss:2.00320	validation-mlogloss:2.01696
[84]	train-mlogloss:1.99841	validation-mlogloss:2.01224
[85]	train-mlogloss:1.99356	validation-mlogloss:2.00737
[86]	train-mlogloss:1.98873	validation-mlogloss:2.00228
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[88]	train-mlogloss:1.97915	validation-mlogloss:1.99271
[89]	train-mlogloss:1.97444	validation-mlogloss:1.98796
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[91]	train-mlogloss:1.96481	validation-mlogloss:1.97806
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[93]	train-mlogloss:1.95568	validation-mlogloss:1.96860
[94]	train-mlogloss:1.95123	validation-mlogloss:1.96407
[95]	train-mlogloss:1.94668	validation-mlogloss:1.95942
[96]	train-mlogloss:1.94220	validation-mlogloss:1.95471
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[102]	train-mlogloss:1.91599	validation-mlogloss:1.92794
[103]	train-mlogloss:1.91184	validation-mlogloss:1.92381
[104]	train-mlogloss:1.90762	validation-mlogloss:1.91937
[105]	train-mlogloss:1.90334	validation-mlogloss:1.91501
[106]	train-mlogloss:1.89907	validation-mlogloss:1.91068
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[108]	train-mlogloss:1.89093	validation-mlogloss:1.90225
[109]	train-mlogloss:1.88702	validation-mlogloss:1.89826
[110]	train-mlogloss:1.88271	validation-mlogloss:1.89378
[111]	train-mlogloss:1.87876	validation-mlogloss:1.88977
[112]	train-mlogloss:1.87485	validation-mlogloss:1.88575
[113]	train-mlogloss:1.87085	validation-mlogloss:1.88156
[114]	train-mlogloss:1.86699	validation-mlogloss:1.87763
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[117]	train-mlogloss:1.85576	validation-mlogloss:1.86599
[118]	train-mlogloss:1.85207	validation-mlogloss:1.86215
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[121]	train-mlogloss:1.84071	validation-mlogloss:1.85019
[122]	train-mlogloss:1.83710	validation-mlogloss:1.84645
[123]	train-mlogloss:1.83326	validation-mlogloss:1.84251
[124]	train-mlogloss:1.82952	validation-mlogloss:1.83855
[125]	train-mlogloss:1.82593	validation-mlogloss:1.83477
[126]	train-mlogloss:1.82244	validation-mlogloss:1.83116
[127]	train-mlogloss:1.81895	validation-mlogloss:1.82756
[128]	train-mlogloss:1.81535	validation-mlogloss:1.82379
[129]	train-mlogloss:1.81187	validation-mlogloss:1.82027
[130]	train-mlogloss:1.80857	validation-mlogloss:1.81683
[131]	train-mlogloss:1.80497	validation-mlogloss:1.81305
[132]	train-mlogloss:1.80131	validation-mlogloss:1.80926
[133]	train-mlogloss:1.79774	validation-mlogloss:1.80548
[134]	train-mlogloss:1.79441	validation-mlogloss:1.80205
[135]	train-mlogloss:1.79113	validation-mlogloss:1.79870
[136]	train-mlogloss:1.78786	validation-mlogloss:1.79533
[137]	train-mlogloss:1.78467	validation-mlogloss:1.79202
[138]	train-mlogloss:1.78152	validation-mlogloss:1.78873
[139]	train-mlogloss:1.77813	validation-mlogloss:1.78517
[140]	train-mlogloss:1.77500	validation-mlogloss:1.78188
[141]	train-mlogloss:1.77198	validation-mlogloss:1.77865
[142]	train-mlogloss:1.76894	validation-mlogloss:1.77554
[143]	train-mlogloss:1.76584	validation-mlogloss:1.77232
[144]	train-mlogloss:1.76283	validation-mlogloss:1.76922
[145]	train-mlogloss:1.75985	validation-mlogloss:1.76604
[146]	train-mlogloss:1.75681	validation-mlogloss:1.76291
[147]	train-mlogloss:1.75366	validation-mlogloss:1.75953
[148]	train-mlogloss:1.75069	validation-mlogloss:1.75645
[149]	train-mlogloss:1.74781	validation-mlogloss:1.75346
[150]	train-mlogloss:1.74496	validation-mlogloss:1.75045
[151]	train-mlogloss:1.74185	validation-mlogloss:1.74718
[152]	train-mlogloss:1.73901	validation-mlogloss:1.74421
[153]	train-mlogloss:1.73597	validation-mlogloss:1.74103
[154]	train-mlogloss:1.73323	validation-mlogloss:1.73818
[155]	train-mlogloss:1.73041	validation-mlogloss:1.73524
[156]	train-mlogloss:1.72765	validation-mlogloss:1.73245
[157]	train-mlogloss:1.72487	validation-mlogloss:1.72957
[158]	train-mlogloss:1.72222	validation-mlogloss:1.72687
[159]	train-mlogloss:1.71951	validation-mlogloss:1.72402
[160]	train-mlogloss:1.71662	validation-mlogloss:1.72096
[161]	train-mlogloss:1.71370	validation-mlogloss:1.71778
[162]	train-mlogloss:1.71078	validation-mlogloss:1.71477
[163]	train-mlogloss:1.70820	validation-mlogloss:1.71201
[164]	train-mlogloss:1.70544	validation-mlogloss:1.70903
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[166]	train-mlogloss:1.69994	validation-mlogloss:1.70336
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[169]	train-mlogloss:1.69192	validation-mlogloss:1.69481
[170]	train-mlogloss:1.68917	validation-mlogloss:1.69187
[171]	train-mlogloss:1.68651	validation-mlogloss:1.68908
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Saved model to disk.
2025-11-06 14:10:00.173811: 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`.
2025-11-06 14:10:00.184943: 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 00:00:1762434600.197872 1378438 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434600.201778 1378438 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434600.211475 1378438 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434600.211498 1378438 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434600.211500 1378438 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434600.211509 1378438 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:10:00.214581: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69336	validation-mlogloss:2.69353
[1]	train-mlogloss:2.67828	validation-mlogloss:2.67921
[2]	train-mlogloss:2.66425	validation-mlogloss:2.66570
[3]	train-mlogloss:2.65036	validation-mlogloss:2.65224
[4]	train-mlogloss:2.63669	validation-mlogloss:2.63917
[5]	train-mlogloss:2.62321	validation-mlogloss:2.62608
[6]	train-mlogloss:2.60974	validation-mlogloss:2.61321
[7]	train-mlogloss:2.59677	validation-mlogloss:2.60118
[8]	train-mlogloss:2.58415	validation-mlogloss:2.58888
[9]	train-mlogloss:2.57177	validation-mlogloss:2.57697
[10]	train-mlogloss:2.55980	validation-mlogloss:2.56527
[11]	train-mlogloss:2.54760	validation-mlogloss:2.55327
[12]	train-mlogloss:2.53589	validation-mlogloss:2.54230
[13]	train-mlogloss:2.52441	validation-mlogloss:2.53116
[14]	train-mlogloss:2.51294	validation-mlogloss:2.52014
[15]	train-mlogloss:2.50175	validation-mlogloss:2.50953
[16]	train-mlogloss:2.49072	validation-mlogloss:2.49890
[17]	train-mlogloss:2.47998	validation-mlogloss:2.48863
[18]	train-mlogloss:2.46927	validation-mlogloss:2.47809
[19]	train-mlogloss:2.45900	validation-mlogloss:2.46819
[20]	train-mlogloss:2.44846	validation-mlogloss:2.45807
[21]	train-mlogloss:2.43815	validation-mlogloss:2.44807
[22]	train-mlogloss:2.42792	validation-mlogloss:2.43815
[23]	train-mlogloss:2.41818	validation-mlogloss:2.42868
[24]	train-mlogloss:2.40836	validation-mlogloss:2.41916
[25]	train-mlogloss:2.39884	validation-mlogloss:2.40993
[26]	train-mlogloss:2.38948	validation-mlogloss:2.40088
[27]	train-mlogloss:2.38008	validation-mlogloss:2.39161
[28]	train-mlogloss:2.37097	validation-mlogloss:2.38296
[29]	train-mlogloss:2.36203	validation-mlogloss:2.37441
[30]	train-mlogloss:2.35300	validation-mlogloss:2.36564
[31]	train-mlogloss:2.34433	validation-mlogloss:2.35716
[32]	train-mlogloss:2.33562	validation-mlogloss:2.34870
[33]	train-mlogloss:2.32695	validation-mlogloss:2.34030
[34]	train-mlogloss:2.31858	validation-mlogloss:2.33186
[35]	train-mlogloss:2.31025	validation-mlogloss:2.32358
[36]	train-mlogloss:2.30176	validation-mlogloss:2.31501
[37]	train-mlogloss:2.29377	validation-mlogloss:2.30720
[38]	train-mlogloss:2.28585	validation-mlogloss:2.29957
[39]	train-mlogloss:2.27809	validation-mlogloss:2.29201
[40]	train-mlogloss:2.27038	validation-mlogloss:2.28452
[41]	train-mlogloss:2.26257	validation-mlogloss:2.27672
[42]	train-mlogloss:2.25478	validation-mlogloss:2.26913
[43]	train-mlogloss:2.24715	validation-mlogloss:2.26172
[44]	train-mlogloss:2.23971	validation-mlogloss:2.25457
[45]	train-mlogloss:2.23241	validation-mlogloss:2.24735
[46]	train-mlogloss:2.22501	validation-mlogloss:2.23985
[47]	train-mlogloss:2.21782	validation-mlogloss:2.23251
[48]	train-mlogloss:2.21049	validation-mlogloss:2.22523
[49]	train-mlogloss:2.20357	validation-mlogloss:2.21843
[50]	train-mlogloss:2.19659	validation-mlogloss:2.21140
[51]	train-mlogloss:2.18972	validation-mlogloss:2.20468
[52]	train-mlogloss:2.18274	validation-mlogloss:2.19743
[53]	train-mlogloss:2.17600	validation-mlogloss:2.19083
[54]	train-mlogloss:2.16943	validation-mlogloss:2.18448
[55]	train-mlogloss:2.16294	validation-mlogloss:2.17805
[56]	train-mlogloss:2.15654	validation-mlogloss:2.17144
[57]	train-mlogloss:2.15017	validation-mlogloss:2.16513
[58]	train-mlogloss:2.14389	validation-mlogloss:2.15899
[59]	train-mlogloss:2.13755	validation-mlogloss:2.15256
[60]	train-mlogloss:2.13136	validation-mlogloss:2.14629
[61]	train-mlogloss:2.12522	validation-mlogloss:2.14003
[62]	train-mlogloss:2.11924	validation-mlogloss:2.13390
[63]	train-mlogloss:2.11334	validation-mlogloss:2.12826
[64]	train-mlogloss:2.10733	validation-mlogloss:2.12226
[65]	train-mlogloss:2.10143	validation-mlogloss:2.11644
[66]	train-mlogloss:2.09544	validation-mlogloss:2.11048
[67]	train-mlogloss:2.08965	validation-mlogloss:2.10452
[68]	train-mlogloss:2.08392	validation-mlogloss:2.09881
[69]	train-mlogloss:2.07822	validation-mlogloss:2.09315
[70]	train-mlogloss:2.07250	validation-mlogloss:2.08725
[71]	train-mlogloss:2.06680	validation-mlogloss:2.08165
[72]	train-mlogloss:2.06123	validation-mlogloss:2.07592
[73]	train-mlogloss:2.05566	validation-mlogloss:2.07028
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[75]	train-mlogloss:2.04496	validation-mlogloss:2.05974
[76]	train-mlogloss:2.03981	validation-mlogloss:2.05455
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[84]	train-mlogloss:1.99865	validation-mlogloss:2.01292
[85]	train-mlogloss:1.99379	validation-mlogloss:2.00800
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[88]	train-mlogloss:1.97924	validation-mlogloss:1.99307
[89]	train-mlogloss:1.97471	validation-mlogloss:1.98849
[90]	train-mlogloss:1.97004	validation-mlogloss:1.98374
[91]	train-mlogloss:1.96524	validation-mlogloss:1.97880
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[93]	train-mlogloss:1.95598	validation-mlogloss:1.96937
[94]	train-mlogloss:1.95139	validation-mlogloss:1.96463
[95]	train-mlogloss:1.94692	validation-mlogloss:1.96005
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[97]	train-mlogloss:1.93816	validation-mlogloss:1.95116
[98]	train-mlogloss:1.93383	validation-mlogloss:1.94664
[99]	train-mlogloss:1.92956	validation-mlogloss:1.94230
[100]	train-mlogloss:1.92525	validation-mlogloss:1.93786
[101]	train-mlogloss:1.92095	validation-mlogloss:1.93340
[102]	train-mlogloss:1.91662	validation-mlogloss:1.92884
[103]	train-mlogloss:1.91228	validation-mlogloss:1.92431
[104]	train-mlogloss:1.90808	validation-mlogloss:1.91998
[105]	train-mlogloss:1.90405	validation-mlogloss:1.91586
[106]	train-mlogloss:1.89985	validation-mlogloss:1.91163
[107]	train-mlogloss:1.89556	validation-mlogloss:1.90703
[108]	train-mlogloss:1.89151	validation-mlogloss:1.90279
[109]	train-mlogloss:1.88748	validation-mlogloss:1.89859
[110]	train-mlogloss:1.88321	validation-mlogloss:1.89419
[111]	train-mlogloss:1.87931	validation-mlogloss:1.89011
[112]	train-mlogloss:1.87537	validation-mlogloss:1.88591
[113]	train-mlogloss:1.87151	validation-mlogloss:1.88214
[114]	train-mlogloss:1.86756	validation-mlogloss:1.87804
[115]	train-mlogloss:1.86367	validation-mlogloss:1.87400
[116]	train-mlogloss:1.85979	validation-mlogloss:1.87007
[117]	train-mlogloss:1.85599	validation-mlogloss:1.86605
[118]	train-mlogloss:1.85202	validation-mlogloss:1.86190
[119]	train-mlogloss:1.84833	validation-mlogloss:1.85802
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[121]	train-mlogloss:1.84110	validation-mlogloss:1.85053
[122]	train-mlogloss:1.83753	validation-mlogloss:1.84681
[123]	train-mlogloss:1.83388	validation-mlogloss:1.84323
[124]	train-mlogloss:1.83029	validation-mlogloss:1.83944
[125]	train-mlogloss:1.82680	validation-mlogloss:1.83577
[126]	train-mlogloss:1.82335	validation-mlogloss:1.83221
[127]	train-mlogloss:1.81989	validation-mlogloss:1.82861
[128]	train-mlogloss:1.81654	validation-mlogloss:1.82512
[129]	train-mlogloss:1.81290	validation-mlogloss:1.82136
[130]	train-mlogloss:1.80952	validation-mlogloss:1.81794
[131]	train-mlogloss:1.80609	validation-mlogloss:1.81436
[132]	train-mlogloss:1.80272	validation-mlogloss:1.81089
[133]	train-mlogloss:1.79943	validation-mlogloss:1.80755
[134]	train-mlogloss:1.79616	validation-mlogloss:1.80403
[135]	train-mlogloss:1.79294	validation-mlogloss:1.80071
[136]	train-mlogloss:1.78977	validation-mlogloss:1.79743
[137]	train-mlogloss:1.78663	validation-mlogloss:1.79424
[138]	train-mlogloss:1.78342	validation-mlogloss:1.79091
[139]	train-mlogloss:1.78004	validation-mlogloss:1.78737
[140]	train-mlogloss:1.77686	validation-mlogloss:1.78404
[141]	train-mlogloss:1.77382	validation-mlogloss:1.78085
[142]	train-mlogloss:1.77070	validation-mlogloss:1.77773
[143]	train-mlogloss:1.76738	validation-mlogloss:1.77429
[144]	train-mlogloss:1.76429	validation-mlogloss:1.77106
[145]	train-mlogloss:1.76111	validation-mlogloss:1.76772
[146]	train-mlogloss:1.75820	validation-mlogloss:1.76479
[147]	train-mlogloss:1.75526	validation-mlogloss:1.76181
[148]	train-mlogloss:1.75229	validation-mlogloss:1.75867
[149]	train-mlogloss:1.74925	validation-mlogloss:1.75542
[150]	train-mlogloss:1.74609	validation-mlogloss:1.75201
[151]	train-mlogloss:1.74295	validation-mlogloss:1.74874
[152]	train-mlogloss:1.73998	validation-mlogloss:1.74568
[153]	train-mlogloss:1.73709	validation-mlogloss:1.74272
[154]	train-mlogloss:1.73432	validation-mlogloss:1.73979
[155]	train-mlogloss:1.73131	validation-mlogloss:1.73668
[156]	train-mlogloss:1.72837	validation-mlogloss:1.73363
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[589]	train-mlogloss:1.24150	validation-mlogloss:1.24172
[590]	train-mlogloss:1.24109	validation-mlogloss:1.24149
[591]	train-mlogloss:1.24070	validation-mlogloss:1.24126
[592]	train-mlogloss:1.24031	validation-mlogloss:1.24093
[593]	train-mlogloss:1.23993	validation-mlogloss:1.24058
[594]	train-mlogloss:1.23949	validation-mlogloss:1.24027
[595]	train-mlogloss:1.23905	validation-mlogloss:1.24006
[596]	train-mlogloss:1.23867	validation-mlogloss:1.23967
[597]	train-mlogloss:1.23826	validation-mlogloss:1.23941
[598]	train-mlogloss:1.23783	validation-mlogloss:1.23902
[599]	train-mlogloss:1.23748	validation-mlogloss:1.23874
[600]	train-mlogloss:1.23710	validation-mlogloss:1.23846
[601]	train-mlogloss:1.23666	validation-mlogloss:1.23815
[602]	train-mlogloss:1.23622	validation-mlogloss:1.23779
[603]	train-mlogloss:1.23581	validation-mlogloss:1.23752
[604]	train-mlogloss:1.23541	validation-mlogloss:1.23724
[605]	train-mlogloss:1.23501	validation-mlogloss:1.23696
[606]	train-mlogloss:1.23462	validation-mlogloss:1.23669
[607]	train-mlogloss:1.23422	validation-mlogloss:1.23641
[608]	train-mlogloss:1.23379	validation-mlogloss:1.23612
[609]	train-mlogloss:1.23335	validation-mlogloss:1.23581
[610]	train-mlogloss:1.23294	validation-mlogloss:1.23543
[611]	train-mlogloss:1.23251	validation-mlogloss:1.23511
[612]	train-mlogloss:1.23213	validation-mlogloss:1.23485
[613]	train-mlogloss:1.23173	validation-mlogloss:1.23456
[614]	train-mlogloss:1.23129	validation-mlogloss:1.23417
[615]	train-mlogloss:1.23091	validation-mlogloss:1.23389
[616]	train-mlogloss:1.23052	validation-mlogloss:1.23362
[617]	train-mlogloss:1.23011	validation-mlogloss:1.23331
[618]	train-mlogloss:1.22974	validation-mlogloss:1.23305
[619]	train-mlogloss:1.22933	validation-mlogloss:1.23270
[620]	train-mlogloss:1.22895	validation-mlogloss:1.23245
[621]	train-mlogloss:1.22856	validation-mlogloss:1.23216
[622]	train-mlogloss:1.22815	validation-mlogloss:1.23181
[623]	train-mlogloss:1.22774	validation-mlogloss:1.23156
[624]	train-mlogloss:1.22735	validation-mlogloss:1.23122
[625]	train-mlogloss:1.22698	validation-mlogloss:1.23099
[626]	train-mlogloss:1.22661	validation-mlogloss:1.23065
[627]	train-mlogloss:1.22620	validation-mlogloss:1.23040
[628]	train-mlogloss:1.22581	validation-mlogloss:1.23016
[629]	train-mlogloss:1.22546	validation-mlogloss:1.22990
[630]	train-mlogloss:1.22509	validation-mlogloss:1.22958
[631]	train-mlogloss:1.22470	validation-mlogloss:1.22927
[632]	train-mlogloss:1.22434	validation-mlogloss:1.22905
[633]	train-mlogloss:1.22396	validation-mlogloss:1.22876
[634]	train-mlogloss:1.22358	validation-mlogloss:1.22852
[635]	train-mlogloss:1.22319	validation-mlogloss:1.22830
[636]	train-mlogloss:1.22277	validation-mlogloss:1.22798
[637]	train-mlogloss:1.22240	validation-mlogloss:1.22769
[638]	train-mlogloss:1.22201	validation-mlogloss:1.22739
[639]	train-mlogloss:1.22165	validation-mlogloss:1.22719
[640]	train-mlogloss:1.22130	validation-mlogloss:1.22692
[641]	train-mlogloss:1.22088	validation-mlogloss:1.22660
[642]	train-mlogloss:1.22052	validation-mlogloss:1.22634
[643]	train-mlogloss:1.22016	validation-mlogloss:1.22604
[644]	train-mlogloss:1.21980	validation-mlogloss:1.22582
[645]	train-mlogloss:1.21943	validation-mlogloss:1.22560
[646]	train-mlogloss:1.21905	validation-mlogloss:1.22535
[647]	train-mlogloss:1.21869	validation-mlogloss:1.22509
[648]	train-mlogloss:1.21836	validation-mlogloss:1.22489
[649]	train-mlogloss:1.21796	validation-mlogloss:1.22466
[650]	train-mlogloss:1.21760	validation-mlogloss:1.22448
[651]	train-mlogloss:1.21723	validation-mlogloss:1.22426
[652]	train-mlogloss:1.21689	validation-mlogloss:1.22404
[653]	train-mlogloss:1.21653	validation-mlogloss:1.22385
[654]	train-mlogloss:1.21619	validation-mlogloss:1.22357
[655]	train-mlogloss:1.21582	validation-mlogloss:1.22332
[656]	train-mlogloss:1.21546	validation-mlogloss:1.22307
[657]	train-mlogloss:1.21509	validation-mlogloss:1.22278
[658]	train-mlogloss:1.21473	validation-mlogloss:1.22259
[659]	train-mlogloss:1.21437	validation-mlogloss:1.22233
[660]	train-mlogloss:1.21402	validation-mlogloss:1.22209
[661]	train-mlogloss:1.21367	validation-mlogloss:1.22180
[662]	train-mlogloss:1.21331	validation-mlogloss:1.22153
[663]	train-mlogloss:1.21292	validation-mlogloss:1.22126
[664]	train-mlogloss:1.21256	validation-mlogloss:1.22101
[665]	train-mlogloss:1.21223	validation-mlogloss:1.22077
[666]	train-mlogloss:1.21189	validation-mlogloss:1.22052
[667]	train-mlogloss:1.21154	validation-mlogloss:1.22028
[668]	train-mlogloss:1.21120	validation-mlogloss:1.22008
[669]	train-mlogloss:1.21084	validation-mlogloss:1.21979
[670]	train-mlogloss:1.21050	validation-mlogloss:1.21957
[671]	train-mlogloss:1.21017	validation-mlogloss:1.21932
[672]	train-mlogloss:1.20984	validation-mlogloss:1.21909
[673]	train-mlogloss:1.20946	validation-mlogloss:1.21887
[674]	train-mlogloss:1.20910	validation-mlogloss:1.21862
[675]	train-mlogloss:1.20874	validation-mlogloss:1.21840
[676]	train-mlogloss:1.20838	validation-mlogloss:1.21814
[677]	train-mlogloss:1.20804	validation-mlogloss:1.21786
[678]	train-mlogloss:1.20768	validation-mlogloss:1.21760
[679]	train-mlogloss:1.20733	validation-mlogloss:1.21739
[680]	train-mlogloss:1.20700	validation-mlogloss:1.21712
[681]	train-mlogloss:1.20666	validation-mlogloss:1.21689
[682]	train-mlogloss:1.20630	validation-mlogloss:1.21664
[683]	train-mlogloss:1.20596	validation-mlogloss:1.21646
[684]	train-mlogloss:1.20559	validation-mlogloss:1.21622
[685]	train-mlogloss:1.20523	validation-mlogloss:1.21603
[686]	train-mlogloss:1.20491	validation-mlogloss:1.21579
[687]	train-mlogloss:1.20458	validation-mlogloss:1.21564
[688]	train-mlogloss:1.20426	validation-mlogloss:1.21544
[689]	train-mlogloss:1.20393	validation-mlogloss:1.21519
[690]	train-mlogloss:1.20358	validation-mlogloss:1.21496
[691]	train-mlogloss:1.20325	validation-mlogloss:1.21477
[692]	train-mlogloss:1.20287	validation-mlogloss:1.21463
[693]	train-mlogloss:1.20252	validation-mlogloss:1.21440
[694]	train-mlogloss:1.20217	validation-mlogloss:1.21414
[695]	train-mlogloss:1.20180	validation-mlogloss:1.21390
[696]	train-mlogloss:1.20150	validation-mlogloss:1.21367
[697]	train-mlogloss:1.20119	validation-mlogloss:1.21346
[698]	train-mlogloss:1.20086	validation-mlogloss:1.21326
[699]	train-mlogloss:1.20049	validation-mlogloss:1.21305
[700]	train-mlogloss:1.20016	validation-mlogloss:1.21282
[701]	train-mlogloss:1.19984	validation-mlogloss:1.21262
[702]	train-mlogloss:1.19950	validation-mlogloss:1.21240
[703]	train-mlogloss:1.19914	validation-mlogloss:1.21221
[704]	train-mlogloss:1.19883	validation-mlogloss:1.21206
[705]	train-mlogloss:1.19851	validation-mlogloss:1.21187
[706]	train-mlogloss:1.19814	validation-mlogloss:1.21163
[707]	train-mlogloss:1.19783	validation-mlogloss:1.21145
[708]	train-mlogloss:1.19753	validation-mlogloss:1.21129
[709]	train-mlogloss:1.19723	validation-mlogloss:1.21113
[710]	train-mlogloss:1.19689	validation-mlogloss:1.21093
[711]	train-mlogloss:1.19658	validation-mlogloss:1.21069
[712]	train-mlogloss:1.19629	validation-mlogloss:1.21050
[713]	train-mlogloss:1.19594	validation-mlogloss:1.21031
[714]	train-mlogloss:1.19557	validation-mlogloss:1.21009
[715]	train-mlogloss:1.19524	validation-mlogloss:1.20988
[716]	train-mlogloss:1.19495	validation-mlogloss:1.20965
[717]	train-mlogloss:1.19466	validation-mlogloss:1.20943
[718]	train-mlogloss:1.19434	validation-mlogloss:1.20931
[719]	train-mlogloss:1.19404	validation-mlogloss:1.20914
[720]	train-mlogloss:1.19368	validation-mlogloss:1.20899
[721]	train-mlogloss:1.19337	validation-mlogloss:1.20877
[722]	train-mlogloss:1.19307	validation-mlogloss:1.20863
[723]	train-mlogloss:1.19278	validation-mlogloss:1.20843
[724]	train-mlogloss:1.19245	validation-mlogloss:1.20823
[725]	train-mlogloss:1.19215	validation-mlogloss:1.20804
[726]	train-mlogloss:1.19184	validation-mlogloss:1.20781
[727]	train-mlogloss:1.19148	validation-mlogloss:1.20759
[728]	train-mlogloss:1.19116	validation-mlogloss:1.20740
[729]	train-mlogloss:1.19086	validation-mlogloss:1.20728
[730]	train-mlogloss:1.19054	validation-mlogloss:1.20699
[731]	train-mlogloss:1.19025	validation-mlogloss:1.20687
[732]	train-mlogloss:1.18995	validation-mlogloss:1.20668
[733]	train-mlogloss:1.18962	validation-mlogloss:1.20653
[734]	train-mlogloss:1.18932	validation-mlogloss:1.20635
[735]	train-mlogloss:1.18900	validation-mlogloss:1.20617
[736]	train-mlogloss:1.18869	validation-mlogloss:1.20604
[737]	train-mlogloss:1.18837	validation-mlogloss:1.20592
[738]	train-mlogloss:1.18807	validation-mlogloss:1.20576
[739]	train-mlogloss:1.18780	validation-mlogloss:1.20564
[740]	train-mlogloss:1.18750	validation-mlogloss:1.20543
[741]	train-mlogloss:1.18717	validation-mlogloss:1.20523
[742]	train-mlogloss:1.18686	validation-mlogloss:1.20498
[743]	train-mlogloss:1.18657	validation-mlogloss:1.20474
[744]	train-mlogloss:1.18626	validation-mlogloss:1.20457
[745]	train-mlogloss:1.18594	validation-mlogloss:1.20432
[746]	train-mlogloss:1.18567	validation-mlogloss:1.20425
[747]	train-mlogloss:1.18537	validation-mlogloss:1.20407
[748]	train-mlogloss:1.18509	validation-mlogloss:1.20383
[749]	train-mlogloss:1.18480	validation-mlogloss:1.20368
[750]	train-mlogloss:1.18452	validation-mlogloss:1.20352
[751]	train-mlogloss:1.18424	validation-mlogloss:1.20335
[752]	train-mlogloss:1.18398	validation-mlogloss:1.20317
[753]	train-mlogloss:1.18368	validation-mlogloss:1.20300
[754]	train-mlogloss:1.18342	validation-mlogloss:1.20285
[755]	train-mlogloss:1.18317	validation-mlogloss:1.20265
[756]	train-mlogloss:1.18289	validation-mlogloss:1.20246
[757]	train-mlogloss:1.18257	validation-mlogloss:1.20224
[758]	train-mlogloss:1.18228	validation-mlogloss:1.20211
[759]	train-mlogloss:1.18194	validation-mlogloss:1.20192
[760]	train-mlogloss:1.18164	validation-mlogloss:1.20178
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.53 [%]
Global accuracy score (test) = 58.67 [%]
Global F1 score (train) = 61.08 [%]
Global F1 score (test) = 57.53 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.37      0.20      0.26       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.53      0.43       161
       CAMINAR USUAL SPEED       0.40      0.35      0.38       161
            CAMINAR ZIGZAG       0.43      0.41      0.42       161
          DE PIE BARRIENDO       0.67      0.74      0.70       161
   DE PIE DOBLANDO TOALLAS       0.40      0.42      0.41       161
    DE PIE MOVIENDO LIBROS       0.50      0.51      0.51       161
          DE PIE USANDO PC       0.85      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.51      0.34      0.41       161
         SENTADO USANDO PC       0.48      0.53      0.50       161
      SENTADO VIENDO LA TV       0.41      0.27      0.32       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 10: 58.67 [%]
F1-score capturado en la ejecución 10: 57.53 [%]

=== EJECUCIÓN 11 ===

--- TRAIN (ejecución 11) ---

--- TEST (ejecución 11) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.7 [%]
Global accuracy score (test) = 59.01 [%]
Global F1 score (train) = 61.25 [%]
Global F1 score (test) = 57.83 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.34      0.18      0.23       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.52      0.44       161
       CAMINAR USUAL SPEED       0.38      0.37      0.37       161
            CAMINAR ZIGZAG       0.43      0.41      0.42       161
          DE PIE BARRIENDO       0.66      0.73      0.69       161
   DE PIE DOBLANDO TOALLAS       0.42      0.42      0.42       161
    DE PIE MOVIENDO LIBROS       0.50      0.50      0.50       161
          DE PIE USANDO PC       0.84      0.89      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.54      0.39      0.45       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.45      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 11: 59.01 [%]
F1-score capturado en la ejecución 11: 57.83 [%]

=== EJECUCIÓN 12 ===

--- TRAIN (ejecución 12) ---

--- TEST (ejecución 12) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.46 [%]
Global accuracy score (test) = 59.01 [%]
Global F1 score (train) = 61.0 [%]
Global F1 score (test) = 57.79 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.35      0.18      0.24       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.54      0.44       161
       CAMINAR USUAL SPEED       0.39      0.35      0.37       161
            CAMINAR ZIGZAG       0.44      0.43      0.44       161
          DE PIE BARRIENDO       0.66      0.73      0.70       161
   DE PIE DOBLANDO TOALLAS       0.40      0.40      0.40       161
    DE PIE MOVIENDO LIBROS       0.49      0.51      0.50       161
          DE PIE USANDO PC       0.86      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.53      0.37      0.44       161
         SENTADO USANDO PC       0.48      0.53      0.50       161
      SENTADO VIENDO LA TV       0.45      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.63      0.89      0.74       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 12: 59.01 [%]
F1-score capturado en la ejecución 12: 57.79 [%]

=== EJECUCIÓN 13 ===

--- TRAIN (ejecución 13) ---

--- TEST (ejecución 13) ---
2025-11-06 14:10:24.324622: 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`.
2025-11-06 14:10:24.335849: 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 00:00:1762434624.348914 1378845 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434624.353115 1378845 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434624.362941 1378845 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434624.362960 1378845 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434624.362961 1378845 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434624.362970 1378845 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:10:24.366107: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69305	validation-mlogloss:2.69363
[1]	train-mlogloss:2.67848	validation-mlogloss:2.67943
[2]	train-mlogloss:2.66333	validation-mlogloss:2.66485
[3]	train-mlogloss:2.64884	validation-mlogloss:2.65101
[4]	train-mlogloss:2.63497	validation-mlogloss:2.63734
[5]	train-mlogloss:2.62133	validation-mlogloss:2.62422
[6]	train-mlogloss:2.60792	validation-mlogloss:2.61136
[7]	train-mlogloss:2.59516	validation-mlogloss:2.59884
[8]	train-mlogloss:2.58253	validation-mlogloss:2.58667
[9]	train-mlogloss:2.57030	validation-mlogloss:2.57514
[10]	train-mlogloss:2.55781	validation-mlogloss:2.56306
[11]	train-mlogloss:2.54599	validation-mlogloss:2.55176
[12]	train-mlogloss:2.53440	validation-mlogloss:2.54077
[13]	train-mlogloss:2.52305	validation-mlogloss:2.52990
[14]	train-mlogloss:2.51143	validation-mlogloss:2.51869
[15]	train-mlogloss:2.50010	validation-mlogloss:2.50788
[16]	train-mlogloss:2.48926	validation-mlogloss:2.49747
[17]	train-mlogloss:2.47853	validation-mlogloss:2.48715
[18]	train-mlogloss:2.46780	validation-mlogloss:2.47657
[19]	train-mlogloss:2.45746	validation-mlogloss:2.46650
[20]	train-mlogloss:2.44753	validation-mlogloss:2.45673
[21]	train-mlogloss:2.43742	validation-mlogloss:2.44692
[22]	train-mlogloss:2.42726	validation-mlogloss:2.43679
[23]	train-mlogloss:2.41741	validation-mlogloss:2.42707
[24]	train-mlogloss:2.40766	validation-mlogloss:2.41760
[25]	train-mlogloss:2.39821	validation-mlogloss:2.40819
[26]	train-mlogloss:2.38877	validation-mlogloss:2.39884
[27]	train-mlogloss:2.37954	validation-mlogloss:2.39004
[28]	train-mlogloss:2.37049	validation-mlogloss:2.38144
[29]	train-mlogloss:2.36160	validation-mlogloss:2.37296
[30]	train-mlogloss:2.35294	validation-mlogloss:2.36476
[31]	train-mlogloss:2.34431	validation-mlogloss:2.35620
[32]	train-mlogloss:2.33573	validation-mlogloss:2.34767
[33]	train-mlogloss:2.32712	validation-mlogloss:2.33921
[34]	train-mlogloss:2.31897	validation-mlogloss:2.33123
[35]	train-mlogloss:2.31084	validation-mlogloss:2.32328
[36]	train-mlogloss:2.30285	validation-mlogloss:2.31563
[37]	train-mlogloss:2.29461	validation-mlogloss:2.30782
[38]	train-mlogloss:2.28669	validation-mlogloss:2.30024
[39]	train-mlogloss:2.27879	validation-mlogloss:2.29253
[40]	train-mlogloss:2.27085	validation-mlogloss:2.28484
[41]	train-mlogloss:2.26333	validation-mlogloss:2.27735
[42]	train-mlogloss:2.25564	validation-mlogloss:2.26938
[43]	train-mlogloss:2.24815	validation-mlogloss:2.26217
[44]	train-mlogloss:2.24083	validation-mlogloss:2.25501
[45]	train-mlogloss:2.23342	validation-mlogloss:2.24771
[46]	train-mlogloss:2.22591	validation-mlogloss:2.24023
[47]	train-mlogloss:2.21871	validation-mlogloss:2.23309
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[49]	train-mlogloss:2.20436	validation-mlogloss:2.21907
[50]	train-mlogloss:2.19728	validation-mlogloss:2.21196
[51]	train-mlogloss:2.19036	validation-mlogloss:2.20507
[52]	train-mlogloss:2.18352	validation-mlogloss:2.19837
[53]	train-mlogloss:2.17668	validation-mlogloss:2.19139
[54]	train-mlogloss:2.16994	validation-mlogloss:2.18461
[55]	train-mlogloss:2.16321	validation-mlogloss:2.17777
[56]	train-mlogloss:2.15685	validation-mlogloss:2.17165
[57]	train-mlogloss:2.15040	validation-mlogloss:2.16506
[58]	train-mlogloss:2.14412	validation-mlogloss:2.15891
[59]	train-mlogloss:2.13788	validation-mlogloss:2.15282
[60]	train-mlogloss:2.13158	validation-mlogloss:2.14653
[61]	train-mlogloss:2.12548	validation-mlogloss:2.14057
[62]	train-mlogloss:2.11945	validation-mlogloss:2.13467
[63]	train-mlogloss:2.11345	validation-mlogloss:2.12884
[64]	train-mlogloss:2.10745	validation-mlogloss:2.12296
[65]	train-mlogloss:2.10147	validation-mlogloss:2.11703
[66]	train-mlogloss:2.09542	validation-mlogloss:2.11084
[67]	train-mlogloss:2.08939	validation-mlogloss:2.10445
[68]	train-mlogloss:2.08379	validation-mlogloss:2.09886
[69]	train-mlogloss:2.07813	validation-mlogloss:2.09322
[70]	train-mlogloss:2.07238	validation-mlogloss:2.08749
[71]	train-mlogloss:2.06704	validation-mlogloss:2.08228
[72]	train-mlogloss:2.06145	validation-mlogloss:2.07637
[73]	train-mlogloss:2.05588	validation-mlogloss:2.07068
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[75]	train-mlogloss:2.04494	validation-mlogloss:2.05932
[76]	train-mlogloss:2.03959	validation-mlogloss:2.05388
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[84]	train-mlogloss:1.99834	validation-mlogloss:2.01188
[85]	train-mlogloss:1.99323	validation-mlogloss:2.00664
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[89]	train-mlogloss:1.97421	validation-mlogloss:1.98726
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[91]	train-mlogloss:1.96472	validation-mlogloss:1.97765
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[93]	train-mlogloss:1.95553	validation-mlogloss:1.96798
[94]	train-mlogloss:1.95094	validation-mlogloss:1.96322
[95]	train-mlogloss:1.94635	validation-mlogloss:1.95863
[96]	train-mlogloss:1.94173	validation-mlogloss:1.95382
[97]	train-mlogloss:1.93722	validation-mlogloss:1.94933
[98]	train-mlogloss:1.93272	validation-mlogloss:1.94477
[99]	train-mlogloss:1.92836	validation-mlogloss:1.94016
[100]	train-mlogloss:1.92398	validation-mlogloss:1.93567
[101]	train-mlogloss:1.91972	validation-mlogloss:1.93127
[102]	train-mlogloss:1.91551	validation-mlogloss:1.92696
[103]	train-mlogloss:1.91126	validation-mlogloss:1.92254
[104]	train-mlogloss:1.90709	validation-mlogloss:1.91823
[105]	train-mlogloss:1.90298	validation-mlogloss:1.91399
[106]	train-mlogloss:1.89855	validation-mlogloss:1.90941
[107]	train-mlogloss:1.89446	validation-mlogloss:1.90519
[108]	train-mlogloss:1.89023	validation-mlogloss:1.90086
[109]	train-mlogloss:1.88626	validation-mlogloss:1.89686
[110]	train-mlogloss:1.88202	validation-mlogloss:1.89256
[111]	train-mlogloss:1.87813	validation-mlogloss:1.88860
[112]	train-mlogloss:1.87420	validation-mlogloss:1.88449
[113]	train-mlogloss:1.87033	validation-mlogloss:1.88047
[114]	train-mlogloss:1.86640	validation-mlogloss:1.87645
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[117]	train-mlogloss:1.85469	validation-mlogloss:1.86453
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[123]	train-mlogloss:1.83213	validation-mlogloss:1.84115
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[125]	train-mlogloss:1.82484	validation-mlogloss:1.83363
[126]	train-mlogloss:1.82133	validation-mlogloss:1.83003
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[129]	train-mlogloss:1.81111	validation-mlogloss:1.81941
[130]	train-mlogloss:1.80780	validation-mlogloss:1.81592
[131]	train-mlogloss:1.80441	validation-mlogloss:1.81240
[132]	train-mlogloss:1.80111	validation-mlogloss:1.80892
[133]	train-mlogloss:1.79782	validation-mlogloss:1.80547
[134]	train-mlogloss:1.79445	validation-mlogloss:1.80201
[135]	train-mlogloss:1.79127	validation-mlogloss:1.79865
[136]	train-mlogloss:1.78804	validation-mlogloss:1.79524
[137]	train-mlogloss:1.78479	validation-mlogloss:1.79179
[138]	train-mlogloss:1.78164	validation-mlogloss:1.78843
[139]	train-mlogloss:1.77855	validation-mlogloss:1.78514
[140]	train-mlogloss:1.77525	validation-mlogloss:1.78166
[141]	train-mlogloss:1.77206	validation-mlogloss:1.77834
[142]	train-mlogloss:1.76897	validation-mlogloss:1.77514
[143]	train-mlogloss:1.76588	validation-mlogloss:1.77201
[144]	train-mlogloss:1.76289	validation-mlogloss:1.76880
[145]	train-mlogloss:1.75988	validation-mlogloss:1.76577
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[147]	train-mlogloss:1.75390	validation-mlogloss:1.75956
[148]	train-mlogloss:1.75102	validation-mlogloss:1.75661
[149]	train-mlogloss:1.74806	validation-mlogloss:1.75350
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[151]	train-mlogloss:1.74201	validation-mlogloss:1.74709
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[730]	train-mlogloss:1.19019	validation-mlogloss:1.20728
[731]	train-mlogloss:1.18991	validation-mlogloss:1.20708
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[733]	train-mlogloss:1.18933	validation-mlogloss:1.20666
[734]	train-mlogloss:1.18903	validation-mlogloss:1.20646
[735]	train-mlogloss:1.18871	validation-mlogloss:1.20623
[736]	train-mlogloss:1.18834	validation-mlogloss:1.20605
[737]	train-mlogloss:1.18805	validation-mlogloss:1.20586
[738]	train-mlogloss:1.18778	validation-mlogloss:1.20575
[739]	train-mlogloss:1.18748	validation-mlogloss:1.20556
[740]	train-mlogloss:1.18719	validation-mlogloss:1.20535
[741]	train-mlogloss:1.18690	validation-mlogloss:1.20513
[742]	train-mlogloss:1.18657	validation-mlogloss:1.20495
[743]	train-mlogloss:1.18627	validation-mlogloss:1.20473
[744]	train-mlogloss:1.18596	validation-mlogloss:1.20454
[745]	train-mlogloss:1.18567	validation-mlogloss:1.20433
[746]	train-mlogloss:1.18536	validation-mlogloss:1.20414
[747]	train-mlogloss:1.18507	validation-mlogloss:1.20399
[748]	train-mlogloss:1.18478	validation-mlogloss:1.20380
[749]	train-mlogloss:1.18452	validation-mlogloss:1.20360
[750]	train-mlogloss:1.18421	validation-mlogloss:1.20343
[751]	train-mlogloss:1.18392	validation-mlogloss:1.20324
[752]	train-mlogloss:1.18365	validation-mlogloss:1.20308
[753]	train-mlogloss:1.18330	validation-mlogloss:1.20282
[754]	train-mlogloss:1.18298	validation-mlogloss:1.20270
[755]	train-mlogloss:1.18267	validation-mlogloss:1.20250
[756]	train-mlogloss:1.18239	validation-mlogloss:1.20234
[757]	train-mlogloss:1.18212	validation-mlogloss:1.20218
[758]	train-mlogloss:1.18182	validation-mlogloss:1.20198
[759]	train-mlogloss:1.18155	validation-mlogloss:1.20180
[760]	train-mlogloss:1.18125	validation-mlogloss:1.20158
Saved model to disk.
2025-11-06 14:10:48.760894: 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`.
2025-11-06 14:10:48.772188: 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 00:00:1762434648.785361 1379250 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434648.789325 1379250 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434648.799420 1379250 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434648.799440 1379250 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434648.799449 1379250 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434648.799450 1379250 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:10:48.802466: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69350	validation-mlogloss:2.69409
[1]	train-mlogloss:2.67895	validation-mlogloss:2.67991
[2]	train-mlogloss:2.66471	validation-mlogloss:2.66637
[3]	train-mlogloss:2.65060	validation-mlogloss:2.65262
[4]	train-mlogloss:2.63738	validation-mlogloss:2.63992
[5]	train-mlogloss:2.62361	validation-mlogloss:2.62660
[6]	train-mlogloss:2.61053	validation-mlogloss:2.61413
[7]	train-mlogloss:2.59745	validation-mlogloss:2.60168
[8]	train-mlogloss:2.58472	validation-mlogloss:2.58931
[9]	train-mlogloss:2.57225	validation-mlogloss:2.57745
[10]	train-mlogloss:2.55989	validation-mlogloss:2.56560
[11]	train-mlogloss:2.54745	validation-mlogloss:2.55363
[12]	train-mlogloss:2.53558	validation-mlogloss:2.54230
[13]	train-mlogloss:2.52377	validation-mlogloss:2.53074
[14]	train-mlogloss:2.51258	validation-mlogloss:2.51986
[15]	train-mlogloss:2.50132	validation-mlogloss:2.50926
[16]	train-mlogloss:2.49016	validation-mlogloss:2.49860
[17]	train-mlogloss:2.47914	validation-mlogloss:2.48797
[18]	train-mlogloss:2.46841	validation-mlogloss:2.47762
[19]	train-mlogloss:2.45786	validation-mlogloss:2.46749
[20]	train-mlogloss:2.44739	validation-mlogloss:2.45720
[21]	train-mlogloss:2.43742	validation-mlogloss:2.44763
[22]	train-mlogloss:2.42755	validation-mlogloss:2.43809
[23]	train-mlogloss:2.41803	validation-mlogloss:2.42882
[24]	train-mlogloss:2.40840	validation-mlogloss:2.41939
[25]	train-mlogloss:2.39871	validation-mlogloss:2.40994
[26]	train-mlogloss:2.38926	validation-mlogloss:2.40078
[27]	train-mlogloss:2.37997	validation-mlogloss:2.39156
[28]	train-mlogloss:2.37095	validation-mlogloss:2.38260
[29]	train-mlogloss:2.36193	validation-mlogloss:2.37395
[30]	train-mlogloss:2.35300	validation-mlogloss:2.36547
[31]	train-mlogloss:2.34420	validation-mlogloss:2.35681
[32]	train-mlogloss:2.33560	validation-mlogloss:2.34843
[33]	train-mlogloss:2.32705	validation-mlogloss:2.34012
[34]	train-mlogloss:2.31865	validation-mlogloss:2.33184
[35]	train-mlogloss:2.31038	validation-mlogloss:2.32384
[36]	train-mlogloss:2.30230	validation-mlogloss:2.31603
[37]	train-mlogloss:2.29419	validation-mlogloss:2.30790
[38]	train-mlogloss:2.28596	validation-mlogloss:2.29978
[39]	train-mlogloss:2.27809	validation-mlogloss:2.29215
[40]	train-mlogloss:2.27043	validation-mlogloss:2.28482
[41]	train-mlogloss:2.26282	validation-mlogloss:2.27761
[42]	train-mlogloss:2.25527	validation-mlogloss:2.27036
[43]	train-mlogloss:2.24776	validation-mlogloss:2.26311
[44]	train-mlogloss:2.24027	validation-mlogloss:2.25567
[45]	train-mlogloss:2.23279	validation-mlogloss:2.24802
[46]	train-mlogloss:2.22554	validation-mlogloss:2.24107
[47]	train-mlogloss:2.21831	validation-mlogloss:2.23382
[48]	train-mlogloss:2.21122	validation-mlogloss:2.22672
[49]	train-mlogloss:2.20401	validation-mlogloss:2.21949
[50]	train-mlogloss:2.19705	validation-mlogloss:2.21280
[51]	train-mlogloss:2.19027	validation-mlogloss:2.20614
[52]	train-mlogloss:2.18342	validation-mlogloss:2.19948
[53]	train-mlogloss:2.17663	validation-mlogloss:2.19275
[54]	train-mlogloss:2.17019	validation-mlogloss:2.18654
[55]	train-mlogloss:2.16372	validation-mlogloss:2.18005
[56]	train-mlogloss:2.15723	validation-mlogloss:2.17358
[57]	train-mlogloss:2.15051	validation-mlogloss:2.16674
[58]	train-mlogloss:2.14383	validation-mlogloss:2.15987
[59]	train-mlogloss:2.13757	validation-mlogloss:2.15357
[60]	train-mlogloss:2.13124	validation-mlogloss:2.14729
[61]	train-mlogloss:2.12510	validation-mlogloss:2.14140
[62]	train-mlogloss:2.11903	validation-mlogloss:2.13517
[63]	train-mlogloss:2.11308	validation-mlogloss:2.12932
[64]	train-mlogloss:2.10726	validation-mlogloss:2.12354
[65]	train-mlogloss:2.10127	validation-mlogloss:2.11734
[66]	train-mlogloss:2.09553	validation-mlogloss:2.11150
[67]	train-mlogloss:2.08974	validation-mlogloss:2.10564
[68]	train-mlogloss:2.08392	validation-mlogloss:2.09981
[69]	train-mlogloss:2.07810	validation-mlogloss:2.09391
[70]	train-mlogloss:2.07235	validation-mlogloss:2.08793
[71]	train-mlogloss:2.06680	validation-mlogloss:2.08240
[72]	train-mlogloss:2.06105	validation-mlogloss:2.07642
[73]	train-mlogloss:2.05571	validation-mlogloss:2.07089
[74]	train-mlogloss:2.05019	validation-mlogloss:2.06527
[75]	train-mlogloss:2.04474	validation-mlogloss:2.05965
[76]	train-mlogloss:2.03937	validation-mlogloss:2.05422
[77]	train-mlogloss:2.03407	validation-mlogloss:2.04883
[78]	train-mlogloss:2.02877	validation-mlogloss:2.04333
[79]	train-mlogloss:2.02362	validation-mlogloss:2.03822
[80]	train-mlogloss:2.01851	validation-mlogloss:2.03297
[81]	train-mlogloss:2.01345	validation-mlogloss:2.02782
[82]	train-mlogloss:2.00852	validation-mlogloss:2.02264
[83]	train-mlogloss:2.00351	validation-mlogloss:2.01755
[84]	train-mlogloss:1.99841	validation-mlogloss:2.01230
[85]	train-mlogloss:1.99349	validation-mlogloss:2.00738
[86]	train-mlogloss:1.98863	validation-mlogloss:2.00250
[87]	train-mlogloss:1.98375	validation-mlogloss:1.99763
[88]	train-mlogloss:1.97884	validation-mlogloss:1.99265
[89]	train-mlogloss:1.97417	validation-mlogloss:1.98788
[90]	train-mlogloss:1.96948	validation-mlogloss:1.98311
[91]	train-mlogloss:1.96480	validation-mlogloss:1.97851
[92]	train-mlogloss:1.96029	validation-mlogloss:1.97407
[93]	train-mlogloss:1.95566	validation-mlogloss:1.96932
[94]	train-mlogloss:1.95129	validation-mlogloss:1.96480
[95]	train-mlogloss:1.94671	validation-mlogloss:1.96007
[96]	train-mlogloss:1.94222	validation-mlogloss:1.95541
[97]	train-mlogloss:1.93786	validation-mlogloss:1.95097
[98]	train-mlogloss:1.93314	validation-mlogloss:1.94625
[99]	train-mlogloss:1.92882	validation-mlogloss:1.94193
[100]	train-mlogloss:1.92459	validation-mlogloss:1.93741
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[703]	train-mlogloss:1.19941	validation-mlogloss:1.21197
[704]	train-mlogloss:1.19909	validation-mlogloss:1.21177
[705]	train-mlogloss:1.19873	validation-mlogloss:1.21150
[706]	train-mlogloss:1.19841	validation-mlogloss:1.21131
[707]	train-mlogloss:1.19807	validation-mlogloss:1.21107
[708]	train-mlogloss:1.19772	validation-mlogloss:1.21090
[709]	train-mlogloss:1.19739	validation-mlogloss:1.21066
[710]	train-mlogloss:1.19706	validation-mlogloss:1.21045
[711]	train-mlogloss:1.19670	validation-mlogloss:1.21024
[712]	train-mlogloss:1.19640	validation-mlogloss:1.21003
[713]	train-mlogloss:1.19597	validation-mlogloss:1.20977
[714]	train-mlogloss:1.19566	validation-mlogloss:1.20959
[715]	train-mlogloss:1.19533	validation-mlogloss:1.20938
[716]	train-mlogloss:1.19501	validation-mlogloss:1.20918
[717]	train-mlogloss:1.19468	validation-mlogloss:1.20901
[718]	train-mlogloss:1.19436	validation-mlogloss:1.20885
[719]	train-mlogloss:1.19406	validation-mlogloss:1.20867
[720]	train-mlogloss:1.19371	validation-mlogloss:1.20842
[721]	train-mlogloss:1.19344	validation-mlogloss:1.20821
[722]	train-mlogloss:1.19313	validation-mlogloss:1.20801
[723]	train-mlogloss:1.19281	validation-mlogloss:1.20782
[724]	train-mlogloss:1.19247	validation-mlogloss:1.20756
[725]	train-mlogloss:1.19216	validation-mlogloss:1.20744
[726]	train-mlogloss:1.19187	validation-mlogloss:1.20724
[727]	train-mlogloss:1.19155	validation-mlogloss:1.20703
[728]	train-mlogloss:1.19125	validation-mlogloss:1.20684
[729]	train-mlogloss:1.19093	validation-mlogloss:1.20669
[730]	train-mlogloss:1.19060	validation-mlogloss:1.20645
[731]	train-mlogloss:1.19029	validation-mlogloss:1.20630
[732]	train-mlogloss:1.18998	validation-mlogloss:1.20615
[733]	train-mlogloss:1.18967	validation-mlogloss:1.20600
[734]	train-mlogloss:1.18934	validation-mlogloss:1.20585
[735]	train-mlogloss:1.18901	validation-mlogloss:1.20568
[736]	train-mlogloss:1.18872	validation-mlogloss:1.20550
[737]	train-mlogloss:1.18840	validation-mlogloss:1.20531
[738]	train-mlogloss:1.18812	validation-mlogloss:1.20515
[739]	train-mlogloss:1.18785	validation-mlogloss:1.20492
[740]	train-mlogloss:1.18756	validation-mlogloss:1.20471
[741]	train-mlogloss:1.18730	validation-mlogloss:1.20456
[742]	train-mlogloss:1.18699	validation-mlogloss:1.20439
[743]	train-mlogloss:1.18667	validation-mlogloss:1.20416
[744]	train-mlogloss:1.18630	validation-mlogloss:1.20399
[745]	train-mlogloss:1.18604	validation-mlogloss:1.20382
[746]	train-mlogloss:1.18577	validation-mlogloss:1.20364
[747]	train-mlogloss:1.18548	validation-mlogloss:1.20344
[748]	train-mlogloss:1.18520	validation-mlogloss:1.20327
[749]	train-mlogloss:1.18489	validation-mlogloss:1.20307
[750]	train-mlogloss:1.18460	validation-mlogloss:1.20286
[751]	train-mlogloss:1.18430	validation-mlogloss:1.20274
[752]	train-mlogloss:1.18402	validation-mlogloss:1.20259
[753]	train-mlogloss:1.18370	validation-mlogloss:1.20235
[754]	train-mlogloss:1.18339	validation-mlogloss:1.20218
[755]	train-mlogloss:1.18309	validation-mlogloss:1.20198
[756]	train-mlogloss:1.18279	validation-mlogloss:1.20187
[757]	train-mlogloss:1.18253	validation-mlogloss:1.20168
[758]	train-mlogloss:1.18223	validation-mlogloss:1.20157
[759]	train-mlogloss:1.18192	validation-mlogloss:1.20140
[760]	train-mlogloss:1.18165	validation-mlogloss:1.20118
Saved model to disk.
2025-11-06 14:11:13.081030: 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`.
2025-11-06 14:11:13.092304: 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 00:00:1762434673.105476 1379660 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434673.109574 1379660 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434673.119276 1379660 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434673.119293 1379660 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434673.119295 1379660 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434673.119296 1379660 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:11:13.122268: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69342	validation-mlogloss:2.69367
[1]	train-mlogloss:2.67922	validation-mlogloss:2.67985
[2]	train-mlogloss:2.66509	validation-mlogloss:2.66630
[3]	train-mlogloss:2.65068	validation-mlogloss:2.65247
[4]	train-mlogloss:2.63656	validation-mlogloss:2.63929
[5]	train-mlogloss:2.62276	validation-mlogloss:2.62586
[6]	train-mlogloss:2.60947	validation-mlogloss:2.61308
[7]	train-mlogloss:2.59667	validation-mlogloss:2.60100
[8]	train-mlogloss:2.58401	validation-mlogloss:2.58868
[9]	train-mlogloss:2.57130	validation-mlogloss:2.57628
[10]	train-mlogloss:2.55886	validation-mlogloss:2.56445
[11]	train-mlogloss:2.54679	validation-mlogloss:2.55311
[12]	train-mlogloss:2.53506	validation-mlogloss:2.54193
[13]	train-mlogloss:2.52346	validation-mlogloss:2.53095
[14]	train-mlogloss:2.51201	validation-mlogloss:2.52008
[15]	train-mlogloss:2.50100	validation-mlogloss:2.50950
[16]	train-mlogloss:2.48982	validation-mlogloss:2.49830
[17]	train-mlogloss:2.47888	validation-mlogloss:2.48772
[18]	train-mlogloss:2.46858	validation-mlogloss:2.47786
[19]	train-mlogloss:2.45842	validation-mlogloss:2.46808
[20]	train-mlogloss:2.44802	validation-mlogloss:2.45792
[21]	train-mlogloss:2.43805	validation-mlogloss:2.44845
[22]	train-mlogloss:2.42805	validation-mlogloss:2.43869
[23]	train-mlogloss:2.41814	validation-mlogloss:2.42904
[24]	train-mlogloss:2.40834	validation-mlogloss:2.41936
[25]	train-mlogloss:2.39886	validation-mlogloss:2.41003
[26]	train-mlogloss:2.38939	validation-mlogloss:2.40088
[27]	train-mlogloss:2.38026	validation-mlogloss:2.39204
[28]	train-mlogloss:2.37117	validation-mlogloss:2.38301
[29]	train-mlogloss:2.36204	validation-mlogloss:2.37431
[30]	train-mlogloss:2.35313	validation-mlogloss:2.36582
[31]	train-mlogloss:2.34433	validation-mlogloss:2.35718
[32]	train-mlogloss:2.33579	validation-mlogloss:2.34903
[33]	train-mlogloss:2.32718	validation-mlogloss:2.34049
[34]	train-mlogloss:2.31885	validation-mlogloss:2.33261
[35]	train-mlogloss:2.31051	validation-mlogloss:2.32456
[36]	train-mlogloss:2.30232	validation-mlogloss:2.31669
[37]	train-mlogloss:2.29419	validation-mlogloss:2.30862
[38]	train-mlogloss:2.28631	validation-mlogloss:2.30096
[39]	train-mlogloss:2.27856	validation-mlogloss:2.29352
[40]	train-mlogloss:2.27079	validation-mlogloss:2.28564
[41]	train-mlogloss:2.26306	validation-mlogloss:2.27796
[42]	train-mlogloss:2.25541	validation-mlogloss:2.27042
[43]	train-mlogloss:2.24793	validation-mlogloss:2.26300
[44]	train-mlogloss:2.24037	validation-mlogloss:2.25543
[45]	train-mlogloss:2.23299	validation-mlogloss:2.24815
[46]	train-mlogloss:2.22573	validation-mlogloss:2.24117
[47]	train-mlogloss:2.21838	validation-mlogloss:2.23364
[48]	train-mlogloss:2.21119	validation-mlogloss:2.22631
[49]	train-mlogloss:2.20424	validation-mlogloss:2.21965
[50]	train-mlogloss:2.19736	validation-mlogloss:2.21303
[51]	train-mlogloss:2.19043	validation-mlogloss:2.20638
[52]	train-mlogloss:2.18372	validation-mlogloss:2.19990
[53]	train-mlogloss:2.17681	validation-mlogloss:2.19277
[54]	train-mlogloss:2.17011	validation-mlogloss:2.18626
[55]	train-mlogloss:2.16356	validation-mlogloss:2.17975
[56]	train-mlogloss:2.15700	validation-mlogloss:2.17322
[57]	train-mlogloss:2.15044	validation-mlogloss:2.16642
[58]	train-mlogloss:2.14402	validation-mlogloss:2.16004
[59]	train-mlogloss:2.13774	validation-mlogloss:2.15365
[60]	train-mlogloss:2.13157	validation-mlogloss:2.14738
[61]	train-mlogloss:2.12538	validation-mlogloss:2.14096
[62]	train-mlogloss:2.11927	validation-mlogloss:2.13499
[63]	train-mlogloss:2.11327	validation-mlogloss:2.12897
[64]	train-mlogloss:2.10724	validation-mlogloss:2.12281
[65]	train-mlogloss:2.10145	validation-mlogloss:2.11724
[66]	train-mlogloss:2.09580	validation-mlogloss:2.11167
[67]	train-mlogloss:2.08994	validation-mlogloss:2.10569
[68]	train-mlogloss:2.08421	validation-mlogloss:2.09991
[69]	train-mlogloss:2.07847	validation-mlogloss:2.09402
[70]	train-mlogloss:2.07291	validation-mlogloss:2.08861
[71]	train-mlogloss:2.06739	validation-mlogloss:2.08305
[72]	train-mlogloss:2.06169	validation-mlogloss:2.07708
[73]	train-mlogloss:2.05618	validation-mlogloss:2.07166
[74]	train-mlogloss:2.05063	validation-mlogloss:2.06599
[75]	train-mlogloss:2.04508	validation-mlogloss:2.06030
[76]	train-mlogloss:2.03973	validation-mlogloss:2.05488
[77]	train-mlogloss:2.03447	validation-mlogloss:2.04963
[78]	train-mlogloss:2.02920	validation-mlogloss:2.04428
[79]	train-mlogloss:2.02397	validation-mlogloss:2.03891
[80]	train-mlogloss:2.01888	validation-mlogloss:2.03374
[81]	train-mlogloss:2.01388	validation-mlogloss:2.02873
[82]	train-mlogloss:2.00889	validation-mlogloss:2.02351
[83]	train-mlogloss:2.00393	validation-mlogloss:2.01863
[84]	train-mlogloss:1.99907	validation-mlogloss:2.01351
[85]	train-mlogloss:1.99414	validation-mlogloss:2.00846
[86]	train-mlogloss:1.98922	validation-mlogloss:2.00346
[87]	train-mlogloss:1.98452	validation-mlogloss:1.99881
[88]	train-mlogloss:1.97981	validation-mlogloss:1.99412
[89]	train-mlogloss:1.97502	validation-mlogloss:1.98924
[90]	train-mlogloss:1.97012	validation-mlogloss:1.98418
[91]	train-mlogloss:1.96529	validation-mlogloss:1.97919
[92]	train-mlogloss:1.96059	validation-mlogloss:1.97454
[93]	train-mlogloss:1.95601	validation-mlogloss:1.96973
[94]	train-mlogloss:1.95150	validation-mlogloss:1.96516
[95]	train-mlogloss:1.94701	validation-mlogloss:1.96055
[96]	train-mlogloss:1.94256	validation-mlogloss:1.95584
[97]	train-mlogloss:1.93816	validation-mlogloss:1.95126
[98]	train-mlogloss:1.93374	validation-mlogloss:1.94679
[99]	train-mlogloss:1.92946	validation-mlogloss:1.94241
[100]	train-mlogloss:1.92507	validation-mlogloss:1.93793
[101]	train-mlogloss:1.92074	validation-mlogloss:1.93361
[102]	train-mlogloss:1.91653	validation-mlogloss:1.92919
[103]	train-mlogloss:1.91213	validation-mlogloss:1.92460
[104]	train-mlogloss:1.90799	validation-mlogloss:1.92045
[105]	train-mlogloss:1.90385	validation-mlogloss:1.91608
[106]	train-mlogloss:1.89967	validation-mlogloss:1.91189
[107]	train-mlogloss:1.89558	validation-mlogloss:1.90781
[108]	train-mlogloss:1.89147	validation-mlogloss:1.90358
[109]	train-mlogloss:1.88748	validation-mlogloss:1.89936
[110]	train-mlogloss:1.88318	validation-mlogloss:1.89499
[111]	train-mlogloss:1.87925	validation-mlogloss:1.89086
[112]	train-mlogloss:1.87536	validation-mlogloss:1.88683
[113]	train-mlogloss:1.87147	validation-mlogloss:1.88280
[114]	train-mlogloss:1.86763	validation-mlogloss:1.87875
[115]	train-mlogloss:1.86379	validation-mlogloss:1.87467
[116]	train-mlogloss:1.85962	validation-mlogloss:1.87029
[117]	train-mlogloss:1.85578	validation-mlogloss:1.86633
[118]	train-mlogloss:1.85195	validation-mlogloss:1.86228
[119]	train-mlogloss:1.84816	validation-mlogloss:1.85830
[120]	train-mlogloss:1.84439	validation-mlogloss:1.85434
[121]	train-mlogloss:1.84073	validation-mlogloss:1.85063
[122]	train-mlogloss:1.83710	validation-mlogloss:1.84674
[123]	train-mlogloss:1.83347	validation-mlogloss:1.84310
[124]	train-mlogloss:1.82996	validation-mlogloss:1.83950
[125]	train-mlogloss:1.82642	validation-mlogloss:1.83585
[126]	train-mlogloss:1.82282	validation-mlogloss:1.83222
[127]	train-mlogloss:1.81929	validation-mlogloss:1.82864
[128]	train-mlogloss:1.81560	validation-mlogloss:1.82473
[129]	train-mlogloss:1.81222	validation-mlogloss:1.82135
[130]	train-mlogloss:1.80887	validation-mlogloss:1.81795
[131]	train-mlogloss:1.80554	validation-mlogloss:1.81458
[132]	train-mlogloss:1.80219	validation-mlogloss:1.81109
[133]	train-mlogloss:1.79893	validation-mlogloss:1.80778
[134]	train-mlogloss:1.79560	validation-mlogloss:1.80429
[135]	train-mlogloss:1.79233	validation-mlogloss:1.80083
[136]	train-mlogloss:1.78911	validation-mlogloss:1.79742
[137]	train-mlogloss:1.78594	validation-mlogloss:1.79409
[138]	train-mlogloss:1.78277	validation-mlogloss:1.79082
[139]	train-mlogloss:1.77955	validation-mlogloss:1.78754
[140]	train-mlogloss:1.77624	validation-mlogloss:1.78409
[141]	train-mlogloss:1.77320	validation-mlogloss:1.78084
[142]	train-mlogloss:1.76997	validation-mlogloss:1.77744
[143]	train-mlogloss:1.76692	validation-mlogloss:1.77422
[144]	train-mlogloss:1.76392	validation-mlogloss:1.77104
[145]	train-mlogloss:1.76089	validation-mlogloss:1.76801
[146]	train-mlogloss:1.75790	validation-mlogloss:1.76508
[147]	train-mlogloss:1.75486	validation-mlogloss:1.76197
[148]	train-mlogloss:1.75194	validation-mlogloss:1.75896
[149]	train-mlogloss:1.74902	validation-mlogloss:1.75592
[150]	train-mlogloss:1.74609	validation-mlogloss:1.75290
[151]	train-mlogloss:1.74302	validation-mlogloss:1.74955
[152]	train-mlogloss:1.74022	validation-mlogloss:1.74672
[153]	train-mlogloss:1.73736	validation-mlogloss:1.74382
[154]	train-mlogloss:1.73423	validation-mlogloss:1.74051
[155]	train-mlogloss:1.73136	validation-mlogloss:1.73748
[156]	train-mlogloss:1.72856	validation-mlogloss:1.73456
[157]	train-mlogloss:1.72588	validation-mlogloss:1.73181
[158]	train-mlogloss:1.72312	validation-mlogloss:1.72899
[159]	train-mlogloss:1.72030	validation-mlogloss:1.72607
[160]	train-mlogloss:1.71736	validation-mlogloss:1.72300
[161]	train-mlogloss:1.71439	validation-mlogloss:1.71975
[162]	train-mlogloss:1.71153	validation-mlogloss:1.71655
[163]	train-mlogloss:1.70871	validation-mlogloss:1.71358
[164]	train-mlogloss:1.70583	validation-mlogloss:1.71047
[165]	train-mlogloss:1.70303	validation-mlogloss:1.70753
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[169]	train-mlogloss:1.69213	validation-mlogloss:1.69608
[170]	train-mlogloss:1.68939	validation-mlogloss:1.69315
[171]	train-mlogloss:1.68674	validation-mlogloss:1.69038
[172]	train-mlogloss:1.68406	validation-mlogloss:1.68764
[173]	train-mlogloss:1.68143	validation-mlogloss:1.68488
[174]	train-mlogloss:1.67877	validation-mlogloss:1.68197
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[177]	train-mlogloss:1.67094	validation-mlogloss:1.67362
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[181]	train-mlogloss:1.66080	validation-mlogloss:1.66293
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[189]	train-mlogloss:1.64147	validation-mlogloss:1.64265
[190]	train-mlogloss:1.63908	validation-mlogloss:1.64013
[191]	train-mlogloss:1.63669	validation-mlogloss:1.63760
[192]	train-mlogloss:1.63430	validation-mlogloss:1.63506
[193]	train-mlogloss:1.63192	validation-mlogloss:1.63258
[194]	train-mlogloss:1.62962	validation-mlogloss:1.63016
[195]	train-mlogloss:1.62733	validation-mlogloss:1.62785
[196]	train-mlogloss:1.62500	validation-mlogloss:1.62539
[197]	train-mlogloss:1.62268	validation-mlogloss:1.62303
[198]	train-mlogloss:1.62043	validation-mlogloss:1.62074
[199]	train-mlogloss:1.61823	validation-mlogloss:1.61841
[200]	train-mlogloss:1.61598	validation-mlogloss:1.61608
[201]	train-mlogloss:1.61378	validation-mlogloss:1.61383
[202]	train-mlogloss:1.61161	validation-mlogloss:1.61151
[203]	train-mlogloss:1.60944	validation-mlogloss:1.60923
[204]	train-mlogloss:1.60716	validation-mlogloss:1.60690
[205]	train-mlogloss:1.60498	validation-mlogloss:1.60467
[206]	train-mlogloss:1.60282	validation-mlogloss:1.60243
[207]	train-mlogloss:1.60072	validation-mlogloss:1.60022
[208]	train-mlogloss:1.59858	validation-mlogloss:1.59793
[209]	train-mlogloss:1.59650	validation-mlogloss:1.59574
[210]	train-mlogloss:1.59438	validation-mlogloss:1.59353
[211]	train-mlogloss:1.59226	validation-mlogloss:1.59130
[212]	train-mlogloss:1.59020	validation-mlogloss:1.58911
[213]	train-mlogloss:1.58812	validation-mlogloss:1.58686
[214]	train-mlogloss:1.58612	validation-mlogloss:1.58474
[215]	train-mlogloss:1.58412	validation-mlogloss:1.58264
[216]	train-mlogloss:1.58212	validation-mlogloss:1.58057
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[520]	train-mlogloss:1.27284	validation-mlogloss:1.26828
[521]	train-mlogloss:1.27233	validation-mlogloss:1.26786
[522]	train-mlogloss:1.27185	validation-mlogloss:1.26742
[523]	train-mlogloss:1.27136	validation-mlogloss:1.26693
[524]	train-mlogloss:1.27086	validation-mlogloss:1.26656
[525]	train-mlogloss:1.27039	validation-mlogloss:1.26612
[526]	train-mlogloss:1.26991	validation-mlogloss:1.26579
[527]	train-mlogloss:1.26942	validation-mlogloss:1.26533
[528]	train-mlogloss:1.26892	validation-mlogloss:1.26486
[529]	train-mlogloss:1.26842	validation-mlogloss:1.26438
[530]	train-mlogloss:1.26791	validation-mlogloss:1.26398
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[532]	train-mlogloss:1.26693	validation-mlogloss:1.26316
[533]	train-mlogloss:1.26643	validation-mlogloss:1.26273
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[539]	train-mlogloss:1.26331	validation-mlogloss:1.26001
[540]	train-mlogloss:1.26281	validation-mlogloss:1.25961
[541]	train-mlogloss:1.26236	validation-mlogloss:1.25925
[542]	train-mlogloss:1.26187	validation-mlogloss:1.25889
[543]	train-mlogloss:1.26138	validation-mlogloss:1.25847
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[624]	train-mlogloss:1.22656	validation-mlogloss:1.23190
[625]	train-mlogloss:1.22618	validation-mlogloss:1.23160
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[627]	train-mlogloss:1.22539	validation-mlogloss:1.23091
[628]	train-mlogloss:1.22503	validation-mlogloss:1.23063
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[645]	train-mlogloss:1.21862	validation-mlogloss:1.22613
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[649]	train-mlogloss:1.21723	validation-mlogloss:1.22521
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[651]	train-mlogloss:1.21653	validation-mlogloss:1.22473
[652]	train-mlogloss:1.21617	validation-mlogloss:1.22450
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[654]	train-mlogloss:1.21538	validation-mlogloss:1.22393
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[657]	train-mlogloss:1.21430	validation-mlogloss:1.22328
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[660]	train-mlogloss:1.21324	validation-mlogloss:1.22262
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[662]	train-mlogloss:1.21257	validation-mlogloss:1.22211
[663]	train-mlogloss:1.21225	validation-mlogloss:1.22185
[664]	train-mlogloss:1.21191	validation-mlogloss:1.22161
[665]	train-mlogloss:1.21155	validation-mlogloss:1.22136
[666]	train-mlogloss:1.21118	validation-mlogloss:1.22108
[667]	train-mlogloss:1.21081	validation-mlogloss:1.22075
[668]	train-mlogloss:1.21047	validation-mlogloss:1.22046
[669]	train-mlogloss:1.21011	validation-mlogloss:1.22024
[670]	train-mlogloss:1.20976	validation-mlogloss:1.22001
[671]	train-mlogloss:1.20941	validation-mlogloss:1.21976
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[683]	train-mlogloss:1.20516	validation-mlogloss:1.21716
[684]	train-mlogloss:1.20483	validation-mlogloss:1.21690
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[703]	train-mlogloss:1.19851	validation-mlogloss:1.21268
[704]	train-mlogloss:1.19818	validation-mlogloss:1.21243
[705]	train-mlogloss:1.19789	validation-mlogloss:1.21221
[706]	train-mlogloss:1.19754	validation-mlogloss:1.21196
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[708]	train-mlogloss:1.19697	validation-mlogloss:1.21154
[709]	train-mlogloss:1.19668	validation-mlogloss:1.21143
[710]	train-mlogloss:1.19634	validation-mlogloss:1.21116
[711]	train-mlogloss:1.19604	validation-mlogloss:1.21106
[712]	train-mlogloss:1.19573	validation-mlogloss:1.21086
[713]	train-mlogloss:1.19542	validation-mlogloss:1.21070
[714]	train-mlogloss:1.19510	validation-mlogloss:1.21050
[715]	train-mlogloss:1.19475	validation-mlogloss:1.21033
[716]	train-mlogloss:1.19445	validation-mlogloss:1.21017
[717]	train-mlogloss:1.19412	validation-mlogloss:1.20993
[718]	train-mlogloss:1.19377	validation-mlogloss:1.20972
[719]	train-mlogloss:1.19346	validation-mlogloss:1.20953
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[721]	train-mlogloss:1.19284	validation-mlogloss:1.20917
[722]	train-mlogloss:1.19253	validation-mlogloss:1.20899
[723]	train-mlogloss:1.19221	validation-mlogloss:1.20880
[724]	train-mlogloss:1.19190	validation-mlogloss:1.20862
[725]	train-mlogloss:1.19159	validation-mlogloss:1.20840
[726]	train-mlogloss:1.19124	validation-mlogloss:1.20817
[727]	train-mlogloss:1.19095	validation-mlogloss:1.20796
[728]	train-mlogloss:1.19060	validation-mlogloss:1.20777
[729]	train-mlogloss:1.19027	validation-mlogloss:1.20756
[730]	train-mlogloss:1.18994	validation-mlogloss:1.20739
[731]	train-mlogloss:1.18963	validation-mlogloss:1.20720
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[735]	train-mlogloss:1.18840	validation-mlogloss:1.20640
[736]	train-mlogloss:1.18809	validation-mlogloss:1.20623
[737]	train-mlogloss:1.18776	validation-mlogloss:1.20601
[738]	train-mlogloss:1.18744	validation-mlogloss:1.20584
[739]	train-mlogloss:1.18717	validation-mlogloss:1.20577
[740]	train-mlogloss:1.18688	validation-mlogloss:1.20558
[741]	train-mlogloss:1.18656	validation-mlogloss:1.20541
[742]	train-mlogloss:1.18627	validation-mlogloss:1.20526
[743]	train-mlogloss:1.18597	validation-mlogloss:1.20514
[744]	train-mlogloss:1.18567	validation-mlogloss:1.20497
[745]	train-mlogloss:1.18535	validation-mlogloss:1.20480
[746]	train-mlogloss:1.18503	validation-mlogloss:1.20463
[747]	train-mlogloss:1.18473	validation-mlogloss:1.20444
[748]	train-mlogloss:1.18444	validation-mlogloss:1.20434
[749]	train-mlogloss:1.18410	validation-mlogloss:1.20423
[750]	train-mlogloss:1.18382	validation-mlogloss:1.20405
[751]	train-mlogloss:1.18353	validation-mlogloss:1.20387
[752]	train-mlogloss:1.18324	validation-mlogloss:1.20371
[753]	train-mlogloss:1.18295	validation-mlogloss:1.20360
[754]	train-mlogloss:1.18263	validation-mlogloss:1.20334
[755]	train-mlogloss:1.18235	validation-mlogloss:1.20320
[756]	train-mlogloss:1.18201	validation-mlogloss:1.20303
[757]	train-mlogloss:1.18173	validation-mlogloss:1.20289
[758]	train-mlogloss:1.18143	validation-mlogloss:1.20273
[759]	train-mlogloss:1.18114	validation-mlogloss:1.20251
[760]	train-mlogloss:1.18083	validation-mlogloss:1.20232
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.54 [%]
Global accuracy score (test) = 58.55 [%]
Global F1 score (train) = 61.1 [%]
Global F1 score (test) = 57.41 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.40      0.22      0.29       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.53      0.44       161
       CAMINAR USUAL SPEED       0.40      0.34      0.37       161
            CAMINAR ZIGZAG       0.42      0.41      0.42       161
          DE PIE BARRIENDO       0.67      0.73      0.70       161
   DE PIE DOBLANDO TOALLAS       0.40      0.40      0.40       161
    DE PIE MOVIENDO LIBROS       0.48      0.49      0.49       161
          DE PIE USANDO PC       0.84      0.89      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.50      0.34      0.40       161
         SENTADO USANDO PC       0.48      0.52      0.50       161
      SENTADO VIENDO LA TV       0.42      0.28      0.33       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.57      2415
              weighted avg       0.58      0.59      0.57      2415


Accuracy capturado en la ejecución 13: 58.55 [%]
F1-score capturado en la ejecución 13: 57.41 [%]

=== EJECUCIÓN 14 ===

--- TRAIN (ejecución 14) ---

--- TEST (ejecución 14) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.58 [%]
Global accuracy score (test) = 58.3 [%]
Global F1 score (train) = 61.14 [%]
Global F1 score (test) = 57.1 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.34      0.19      0.25       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.51      0.43       161
       CAMINAR USUAL SPEED       0.39      0.35      0.37       161
            CAMINAR ZIGZAG       0.43      0.40      0.42       161
          DE PIE BARRIENDO       0.66      0.73      0.69       161
   DE PIE DOBLANDO TOALLAS       0.39      0.40      0.39       161
    DE PIE MOVIENDO LIBROS       0.49      0.50      0.50       161
          DE PIE USANDO PC       0.84      0.87      0.85       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.51      0.35      0.41       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.41      0.27      0.32       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.88      0.73       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.58      2415
                 macro avg       0.57      0.58      0.57      2415
              weighted avg       0.57      0.58      0.57      2415


Accuracy capturado en la ejecución 14: 58.3 [%]
F1-score capturado en la ejecución 14: 57.1 [%]

=== EJECUCIÓN 15 ===

--- TRAIN (ejecución 15) ---

--- TEST (ejecución 15) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.75 [%]
Global accuracy score (test) = 58.8 [%]
Global F1 score (train) = 61.31 [%]
Global F1 score (test) = 57.61 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.38      0.22      0.28       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.53      0.44       161
       CAMINAR USUAL SPEED       0.41      0.34      0.37       161
            CAMINAR ZIGZAG       0.43      0.42      0.43       161
          DE PIE BARRIENDO       0.67      0.73      0.70       161
   DE PIE DOBLANDO TOALLAS       0.41      0.42      0.42       161
    DE PIE MOVIENDO LIBROS       0.50      0.50      0.50       161
          DE PIE USANDO PC       0.84      0.89      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.50      0.34      0.40       161
         SENTADO USANDO PC       0.48      0.53      0.50       161
      SENTADO VIENDO LA TV       0.41      0.27      0.32       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.87      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 15: 58.8 [%]
F1-score capturado en la ejecución 15: 57.61 [%]

=== EJECUCIÓN 16 ===

--- TRAIN (ejecución 16) ---

--- TEST (ejecución 16) ---
2025-11-06 14:11:37.749926: 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`.
2025-11-06 14:11:37.761403: 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 00:00:1762434697.774790 1380065 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434697.778734 1380065 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434697.788848 1380065 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434697.788866 1380065 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434697.788867 1380065 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434697.788868 1380065 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:11:37.791854: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69336	validation-mlogloss:2.69364
[1]	train-mlogloss:2.67863	validation-mlogloss:2.67955
[2]	train-mlogloss:2.66465	validation-mlogloss:2.66601
[3]	train-mlogloss:2.65078	validation-mlogloss:2.65281
[4]	train-mlogloss:2.63664	validation-mlogloss:2.63925
[5]	train-mlogloss:2.62300	validation-mlogloss:2.62626
[6]	train-mlogloss:2.60962	validation-mlogloss:2.61346
[7]	train-mlogloss:2.59652	validation-mlogloss:2.60107
[8]	train-mlogloss:2.58406	validation-mlogloss:2.58906
[9]	train-mlogloss:2.57163	validation-mlogloss:2.57742
[10]	train-mlogloss:2.55930	validation-mlogloss:2.56561
[11]	train-mlogloss:2.54765	validation-mlogloss:2.55401
[12]	train-mlogloss:2.53575	validation-mlogloss:2.54217
[13]	train-mlogloss:2.52389	validation-mlogloss:2.53083
[14]	train-mlogloss:2.51249	validation-mlogloss:2.51994
[15]	train-mlogloss:2.50124	validation-mlogloss:2.50918
[16]	train-mlogloss:2.49019	validation-mlogloss:2.49857
[17]	train-mlogloss:2.47936	validation-mlogloss:2.48797
[18]	train-mlogloss:2.46905	validation-mlogloss:2.47768
[19]	train-mlogloss:2.45858	validation-mlogloss:2.46752
[20]	train-mlogloss:2.44812	validation-mlogloss:2.45758
[21]	train-mlogloss:2.43797	validation-mlogloss:2.44774
[22]	train-mlogloss:2.42824	validation-mlogloss:2.43860
[23]	train-mlogloss:2.41848	validation-mlogloss:2.42893
[24]	train-mlogloss:2.40872	validation-mlogloss:2.41959
[25]	train-mlogloss:2.39920	validation-mlogloss:2.41041
[26]	train-mlogloss:2.38992	validation-mlogloss:2.40166
[27]	train-mlogloss:2.38076	validation-mlogloss:2.39291
[28]	train-mlogloss:2.37162	validation-mlogloss:2.38407
[29]	train-mlogloss:2.36275	validation-mlogloss:2.37531
[30]	train-mlogloss:2.35404	validation-mlogloss:2.36667
[31]	train-mlogloss:2.34529	validation-mlogloss:2.35820
[32]	train-mlogloss:2.33676	validation-mlogloss:2.34985
[33]	train-mlogloss:2.32817	validation-mlogloss:2.34152
[34]	train-mlogloss:2.31952	validation-mlogloss:2.33284
[35]	train-mlogloss:2.31122	validation-mlogloss:2.32493
[36]	train-mlogloss:2.30304	validation-mlogloss:2.31684
[37]	train-mlogloss:2.29476	validation-mlogloss:2.30867
[38]	train-mlogloss:2.28673	validation-mlogloss:2.30086
[39]	train-mlogloss:2.27894	validation-mlogloss:2.29320
[40]	train-mlogloss:2.27105	validation-mlogloss:2.28530
[41]	train-mlogloss:2.26343	validation-mlogloss:2.27780
[42]	train-mlogloss:2.25589	validation-mlogloss:2.27047
[43]	train-mlogloss:2.24840	validation-mlogloss:2.26323
[44]	train-mlogloss:2.24094	validation-mlogloss:2.25607
[45]	train-mlogloss:2.23366	validation-mlogloss:2.24901
[46]	train-mlogloss:2.22643	validation-mlogloss:2.24171
[47]	train-mlogloss:2.21901	validation-mlogloss:2.23437
[48]	train-mlogloss:2.21183	validation-mlogloss:2.22691
[49]	train-mlogloss:2.20467	validation-mlogloss:2.21967
[50]	train-mlogloss:2.19774	validation-mlogloss:2.21272
[51]	train-mlogloss:2.19095	validation-mlogloss:2.20599
[52]	train-mlogloss:2.18399	validation-mlogloss:2.19903
[53]	train-mlogloss:2.17742	validation-mlogloss:2.19259
[54]	train-mlogloss:2.17073	validation-mlogloss:2.18601
[55]	train-mlogloss:2.16405	validation-mlogloss:2.17921
[56]	train-mlogloss:2.15758	validation-mlogloss:2.17262
[57]	train-mlogloss:2.15113	validation-mlogloss:2.16637
[58]	train-mlogloss:2.14478	validation-mlogloss:2.16012
[59]	train-mlogloss:2.13866	validation-mlogloss:2.15413
[60]	train-mlogloss:2.13233	validation-mlogloss:2.14776
[61]	train-mlogloss:2.12623	validation-mlogloss:2.14170
[62]	train-mlogloss:2.12004	validation-mlogloss:2.13535
[63]	train-mlogloss:2.11395	validation-mlogloss:2.12905
[64]	train-mlogloss:2.10801	validation-mlogloss:2.12306
[65]	train-mlogloss:2.10213	validation-mlogloss:2.11715
[66]	train-mlogloss:2.09629	validation-mlogloss:2.11119
[67]	train-mlogloss:2.09037	validation-mlogloss:2.10512
[68]	train-mlogloss:2.08463	validation-mlogloss:2.09947
[69]	train-mlogloss:2.07869	validation-mlogloss:2.09348
[70]	train-mlogloss:2.07301	validation-mlogloss:2.08768
[71]	train-mlogloss:2.06745	validation-mlogloss:2.08217
[72]	train-mlogloss:2.06192	validation-mlogloss:2.07649
[73]	train-mlogloss:2.05633	validation-mlogloss:2.07081
[74]	train-mlogloss:2.05089	validation-mlogloss:2.06522
[75]	train-mlogloss:2.04558	validation-mlogloss:2.05977
[76]	train-mlogloss:2.04007	validation-mlogloss:2.05410
[77]	train-mlogloss:2.03491	validation-mlogloss:2.04898
[78]	train-mlogloss:2.02950	validation-mlogloss:2.04350
[79]	train-mlogloss:2.02436	validation-mlogloss:2.03820
[80]	train-mlogloss:2.01934	validation-mlogloss:2.03311
[81]	train-mlogloss:2.01427	validation-mlogloss:2.02800
[82]	train-mlogloss:2.00925	validation-mlogloss:2.02275
[83]	train-mlogloss:2.00430	validation-mlogloss:2.01766
[84]	train-mlogloss:1.99940	validation-mlogloss:2.01277
[85]	train-mlogloss:1.99446	validation-mlogloss:2.00784
[86]	train-mlogloss:1.98941	validation-mlogloss:2.00273
[87]	train-mlogloss:1.98471	validation-mlogloss:1.99783
[88]	train-mlogloss:1.97994	validation-mlogloss:1.99300
[89]	train-mlogloss:1.97505	validation-mlogloss:1.98803
[90]	train-mlogloss:1.97033	validation-mlogloss:1.98323
[91]	train-mlogloss:1.96564	validation-mlogloss:1.97842
[92]	train-mlogloss:1.96100	validation-mlogloss:1.97371
[93]	train-mlogloss:1.95644	validation-mlogloss:1.96902
[94]	train-mlogloss:1.95190	validation-mlogloss:1.96460
[95]	train-mlogloss:1.94751	validation-mlogloss:1.96012
[96]	train-mlogloss:1.94309	validation-mlogloss:1.95559
[97]	train-mlogloss:1.93857	validation-mlogloss:1.95091
[98]	train-mlogloss:1.93438	validation-mlogloss:1.94648
[99]	train-mlogloss:1.92991	validation-mlogloss:1.94175
[100]	train-mlogloss:1.92553	validation-mlogloss:1.93722
[101]	train-mlogloss:1.92121	validation-mlogloss:1.93281
[102]	train-mlogloss:1.91704	validation-mlogloss:1.92841
[103]	train-mlogloss:1.91284	validation-mlogloss:1.92411
[104]	train-mlogloss:1.90861	validation-mlogloss:1.91962
[105]	train-mlogloss:1.90449	validation-mlogloss:1.91544
[106]	train-mlogloss:1.90044	validation-mlogloss:1.91130
[107]	train-mlogloss:1.89633	validation-mlogloss:1.90700
[108]	train-mlogloss:1.89224	validation-mlogloss:1.90265
[109]	train-mlogloss:1.88834	validation-mlogloss:1.89860
[110]	train-mlogloss:1.88434	validation-mlogloss:1.89439
[111]	train-mlogloss:1.88040	validation-mlogloss:1.89037
[112]	train-mlogloss:1.87623	validation-mlogloss:1.88614
[113]	train-mlogloss:1.87225	validation-mlogloss:1.88197
[114]	train-mlogloss:1.86841	validation-mlogloss:1.87809
[115]	train-mlogloss:1.86463	validation-mlogloss:1.87414
[116]	train-mlogloss:1.86089	validation-mlogloss:1.87030
[117]	train-mlogloss:1.85723	validation-mlogloss:1.86653
[118]	train-mlogloss:1.85352	validation-mlogloss:1.86265
[119]	train-mlogloss:1.84973	validation-mlogloss:1.85893
[120]	train-mlogloss:1.84579	validation-mlogloss:1.85484
[121]	train-mlogloss:1.84184	validation-mlogloss:1.85076
[122]	train-mlogloss:1.83812	validation-mlogloss:1.84686
[123]	train-mlogloss:1.83448	validation-mlogloss:1.84298
[124]	train-mlogloss:1.83089	validation-mlogloss:1.83936
[125]	train-mlogloss:1.82735	validation-mlogloss:1.83563
[126]	train-mlogloss:1.82386	validation-mlogloss:1.83194
[127]	train-mlogloss:1.82022	validation-mlogloss:1.82808
[128]	train-mlogloss:1.81655	validation-mlogloss:1.82423
[129]	train-mlogloss:1.81309	validation-mlogloss:1.82071
[130]	train-mlogloss:1.80966	validation-mlogloss:1.81720
[131]	train-mlogloss:1.80629	validation-mlogloss:1.81372
[132]	train-mlogloss:1.80298	validation-mlogloss:1.81021
[133]	train-mlogloss:1.79972	validation-mlogloss:1.80679
[134]	train-mlogloss:1.79641	validation-mlogloss:1.80333
[135]	train-mlogloss:1.79288	validation-mlogloss:1.79965
[136]	train-mlogloss:1.78966	validation-mlogloss:1.79633
[137]	train-mlogloss:1.78642	validation-mlogloss:1.79287
[138]	train-mlogloss:1.78319	validation-mlogloss:1.78951
[139]	train-mlogloss:1.77997	validation-mlogloss:1.78613
[140]	train-mlogloss:1.77660	validation-mlogloss:1.78260
[141]	train-mlogloss:1.77347	validation-mlogloss:1.77932
[142]	train-mlogloss:1.77030	validation-mlogloss:1.77612
[143]	train-mlogloss:1.76696	validation-mlogloss:1.77267
[144]	train-mlogloss:1.76386	validation-mlogloss:1.76952
[145]	train-mlogloss:1.76054	validation-mlogloss:1.76612
[146]	train-mlogloss:1.75752	validation-mlogloss:1.76296
[147]	train-mlogloss:1.75453	validation-mlogloss:1.75981
[148]	train-mlogloss:1.75141	validation-mlogloss:1.75660
[149]	train-mlogloss:1.74843	validation-mlogloss:1.75368
[150]	train-mlogloss:1.74556	validation-mlogloss:1.75072
[151]	train-mlogloss:1.74262	validation-mlogloss:1.74769
[152]	train-mlogloss:1.73979	validation-mlogloss:1.74472
[153]	train-mlogloss:1.73681	validation-mlogloss:1.74150
[154]	train-mlogloss:1.73374	validation-mlogloss:1.73825
[155]	train-mlogloss:1.73079	validation-mlogloss:1.73520
[156]	train-mlogloss:1.72785	validation-mlogloss:1.73213
[157]	train-mlogloss:1.72493	validation-mlogloss:1.72909
[158]	train-mlogloss:1.72222	validation-mlogloss:1.72641
[159]	train-mlogloss:1.71947	validation-mlogloss:1.72341
[160]	train-mlogloss:1.71652	validation-mlogloss:1.72028
[161]	train-mlogloss:1.71363	validation-mlogloss:1.71731
[162]	train-mlogloss:1.71100	validation-mlogloss:1.71456
[163]	train-mlogloss:1.70816	validation-mlogloss:1.71157
[164]	train-mlogloss:1.70529	validation-mlogloss:1.70859
[165]	train-mlogloss:1.70271	validation-mlogloss:1.70585
[166]	train-mlogloss:1.69990	validation-mlogloss:1.70296
[167]	train-mlogloss:1.69714	validation-mlogloss:1.69998
[168]	train-mlogloss:1.69436	validation-mlogloss:1.69708
[169]	train-mlogloss:1.69162	validation-mlogloss:1.69430
[170]	train-mlogloss:1.68894	validation-mlogloss:1.69153
[171]	train-mlogloss:1.68641	validation-mlogloss:1.68888
[172]	train-mlogloss:1.68393	validation-mlogloss:1.68627
[173]	train-mlogloss:1.68148	validation-mlogloss:1.68369
[174]	train-mlogloss:1.67882	validation-mlogloss:1.68085
[175]	train-mlogloss:1.67622	validation-mlogloss:1.67805
[176]	train-mlogloss:1.67354	validation-mlogloss:1.67534
[177]	train-mlogloss:1.67096	validation-mlogloss:1.67268
[178]	train-mlogloss:1.66837	validation-mlogloss:1.66990
[179]	train-mlogloss:1.66589	validation-mlogloss:1.66730
[180]	train-mlogloss:1.66339	validation-mlogloss:1.66468
[181]	train-mlogloss:1.66095	validation-mlogloss:1.66219
[182]	train-mlogloss:1.65845	validation-mlogloss:1.65975
[183]	train-mlogloss:1.65589	validation-mlogloss:1.65701
[184]	train-mlogloss:1.65335	validation-mlogloss:1.65435
[185]	train-mlogloss:1.65090	validation-mlogloss:1.65178
[186]	train-mlogloss:1.64849	validation-mlogloss:1.64937
[187]	train-mlogloss:1.64605	validation-mlogloss:1.64680
[188]	train-mlogloss:1.64373	validation-mlogloss:1.64437
[189]	train-mlogloss:1.64128	validation-mlogloss:1.64178
[190]	train-mlogloss:1.63891	validation-mlogloss:1.63915
[191]	train-mlogloss:1.63654	validation-mlogloss:1.63656
[192]	train-mlogloss:1.63424	validation-mlogloss:1.63413
[193]	train-mlogloss:1.63196	validation-mlogloss:1.63175
[194]	train-mlogloss:1.62969	validation-mlogloss:1.62926
[195]	train-mlogloss:1.62735	validation-mlogloss:1.62677
[196]	train-mlogloss:1.62505	validation-mlogloss:1.62449
[197]	train-mlogloss:1.62274	validation-mlogloss:1.62195
[198]	train-mlogloss:1.62052	validation-mlogloss:1.61951
[199]	train-mlogloss:1.61830	validation-mlogloss:1.61726
[200]	train-mlogloss:1.61617	validation-mlogloss:1.61504
[201]	train-mlogloss:1.61398	validation-mlogloss:1.61271
[202]	train-mlogloss:1.61177	validation-mlogloss:1.61030
[203]	train-mlogloss:1.60966	validation-mlogloss:1.60799
[204]	train-mlogloss:1.60751	validation-mlogloss:1.60561
[205]	train-mlogloss:1.60538	validation-mlogloss:1.60335
[206]	train-mlogloss:1.60329	validation-mlogloss:1.60107
[207]	train-mlogloss:1.60114	validation-mlogloss:1.59882
[208]	train-mlogloss:1.59898	validation-mlogloss:1.59651
[209]	train-mlogloss:1.59692	validation-mlogloss:1.59437
[210]	train-mlogloss:1.59479	validation-mlogloss:1.59209
[211]	train-mlogloss:1.59278	validation-mlogloss:1.59000
[212]	train-mlogloss:1.59071	validation-mlogloss:1.58779
[213]	train-mlogloss:1.58869	validation-mlogloss:1.58557
[214]	train-mlogloss:1.58665	validation-mlogloss:1.58344
[215]	train-mlogloss:1.58467	validation-mlogloss:1.58137
[216]	train-mlogloss:1.58271	validation-mlogloss:1.57940
[217]	train-mlogloss:1.58066	validation-mlogloss:1.57722
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[610]	train-mlogloss:1.23247	validation-mlogloss:1.23481
[611]	train-mlogloss:1.23207	validation-mlogloss:1.23453
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[712]	train-mlogloss:1.19619	validation-mlogloss:1.21067
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[714]	train-mlogloss:1.19550	validation-mlogloss:1.21015
[715]	train-mlogloss:1.19518	validation-mlogloss:1.20995
[716]	train-mlogloss:1.19483	validation-mlogloss:1.20967
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[718]	train-mlogloss:1.19423	validation-mlogloss:1.20921
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[726]	train-mlogloss:1.19171	validation-mlogloss:1.20752
[727]	train-mlogloss:1.19141	validation-mlogloss:1.20732
[728]	train-mlogloss:1.19111	validation-mlogloss:1.20714
[729]	train-mlogloss:1.19081	validation-mlogloss:1.20699
[730]	train-mlogloss:1.19050	validation-mlogloss:1.20686
[731]	train-mlogloss:1.19019	validation-mlogloss:1.20668
[732]	train-mlogloss:1.18986	validation-mlogloss:1.20651
[733]	train-mlogloss:1.18956	validation-mlogloss:1.20628
[734]	train-mlogloss:1.18927	validation-mlogloss:1.20614
[735]	train-mlogloss:1.18897	validation-mlogloss:1.20592
[736]	train-mlogloss:1.18868	validation-mlogloss:1.20570
[737]	train-mlogloss:1.18838	validation-mlogloss:1.20549
[738]	train-mlogloss:1.18807	validation-mlogloss:1.20531
[739]	train-mlogloss:1.18775	validation-mlogloss:1.20509
[740]	train-mlogloss:1.18742	validation-mlogloss:1.20490
[741]	train-mlogloss:1.18715	validation-mlogloss:1.20474
[742]	train-mlogloss:1.18683	validation-mlogloss:1.20450
[743]	train-mlogloss:1.18654	validation-mlogloss:1.20427
[744]	train-mlogloss:1.18621	validation-mlogloss:1.20413
[745]	train-mlogloss:1.18594	validation-mlogloss:1.20388
[746]	train-mlogloss:1.18565	validation-mlogloss:1.20376
[747]	train-mlogloss:1.18535	validation-mlogloss:1.20357
[748]	train-mlogloss:1.18504	validation-mlogloss:1.20336
[749]	train-mlogloss:1.18474	validation-mlogloss:1.20314
[750]	train-mlogloss:1.18446	validation-mlogloss:1.20298
[751]	train-mlogloss:1.18417	validation-mlogloss:1.20282
[752]	train-mlogloss:1.18390	validation-mlogloss:1.20263
[753]	train-mlogloss:1.18363	validation-mlogloss:1.20245
[754]	train-mlogloss:1.18335	validation-mlogloss:1.20230
[755]	train-mlogloss:1.18305	validation-mlogloss:1.20215
[756]	train-mlogloss:1.18279	validation-mlogloss:1.20196
[757]	train-mlogloss:1.18250	validation-mlogloss:1.20185
[758]	train-mlogloss:1.18224	validation-mlogloss:1.20164
[759]	train-mlogloss:1.18194	validation-mlogloss:1.20151
[760]	train-mlogloss:1.18166	validation-mlogloss:1.20133
Saved model to disk.
2025-11-06 14:12:01.995366: 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`.
2025-11-06 14:12:02.007148: 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 00:00:1762434722.021473 1380445 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434722.025862 1380445 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434722.035995 1380445 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434722.036014 1380445 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434722.036015 1380445 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434722.036016 1380445 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:12:02.039150: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69322	validation-mlogloss:2.69397
[1]	train-mlogloss:2.67766	validation-mlogloss:2.67895
[2]	train-mlogloss:2.66345	validation-mlogloss:2.66546
[3]	train-mlogloss:2.64934	validation-mlogloss:2.65177
[4]	train-mlogloss:2.63553	validation-mlogloss:2.63858
[5]	train-mlogloss:2.62210	validation-mlogloss:2.62572
[6]	train-mlogloss:2.60923	validation-mlogloss:2.61330
[7]	train-mlogloss:2.59614	validation-mlogloss:2.60065
[8]	train-mlogloss:2.58336	validation-mlogloss:2.58845
[9]	train-mlogloss:2.57087	validation-mlogloss:2.57628
[10]	train-mlogloss:2.55861	validation-mlogloss:2.56446
[11]	train-mlogloss:2.54639	validation-mlogloss:2.55243
[12]	train-mlogloss:2.53469	validation-mlogloss:2.54146
[13]	train-mlogloss:2.52322	validation-mlogloss:2.53058
[14]	train-mlogloss:2.51210	validation-mlogloss:2.51956
[15]	train-mlogloss:2.50097	validation-mlogloss:2.50880
[16]	train-mlogloss:2.48975	validation-mlogloss:2.49773
[17]	train-mlogloss:2.47905	validation-mlogloss:2.48737
[18]	train-mlogloss:2.46828	validation-mlogloss:2.47701
[19]	train-mlogloss:2.45795	validation-mlogloss:2.46689
[20]	train-mlogloss:2.44759	validation-mlogloss:2.45693
[21]	train-mlogloss:2.43746	validation-mlogloss:2.44711
[22]	train-mlogloss:2.42745	validation-mlogloss:2.43758
[23]	train-mlogloss:2.41764	validation-mlogloss:2.42813
[24]	train-mlogloss:2.40799	validation-mlogloss:2.41868
[25]	train-mlogloss:2.39830	validation-mlogloss:2.40916
[26]	train-mlogloss:2.38899	validation-mlogloss:2.39996
[27]	train-mlogloss:2.37984	validation-mlogloss:2.39111
[28]	train-mlogloss:2.37058	validation-mlogloss:2.38209
[29]	train-mlogloss:2.36162	validation-mlogloss:2.37332
[30]	train-mlogloss:2.35295	validation-mlogloss:2.36478
[31]	train-mlogloss:2.34417	validation-mlogloss:2.35627
[32]	train-mlogloss:2.33549	validation-mlogloss:2.34816
[33]	train-mlogloss:2.32712	validation-mlogloss:2.34014
[34]	train-mlogloss:2.31861	validation-mlogloss:2.33165
[35]	train-mlogloss:2.31031	validation-mlogloss:2.32375
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[730]	train-mlogloss:1.19053	validation-mlogloss:1.20593
[731]	train-mlogloss:1.19020	validation-mlogloss:1.20576
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[733]	train-mlogloss:1.18954	validation-mlogloss:1.20548
[734]	train-mlogloss:1.18922	validation-mlogloss:1.20529
[735]	train-mlogloss:1.18889	validation-mlogloss:1.20513
[736]	train-mlogloss:1.18858	validation-mlogloss:1.20499
[737]	train-mlogloss:1.18825	validation-mlogloss:1.20477
[738]	train-mlogloss:1.18794	validation-mlogloss:1.20463
[739]	train-mlogloss:1.18763	validation-mlogloss:1.20442
[740]	train-mlogloss:1.18731	validation-mlogloss:1.20422
[741]	train-mlogloss:1.18703	validation-mlogloss:1.20402
[742]	train-mlogloss:1.18676	validation-mlogloss:1.20385
[743]	train-mlogloss:1.18647	validation-mlogloss:1.20370
[744]	train-mlogloss:1.18614	validation-mlogloss:1.20353
[745]	train-mlogloss:1.18587	validation-mlogloss:1.20332
[746]	train-mlogloss:1.18558	validation-mlogloss:1.20317
[747]	train-mlogloss:1.18526	validation-mlogloss:1.20296
[748]	train-mlogloss:1.18495	validation-mlogloss:1.20274
[749]	train-mlogloss:1.18464	validation-mlogloss:1.20247
[750]	train-mlogloss:1.18431	validation-mlogloss:1.20231
[751]	train-mlogloss:1.18399	validation-mlogloss:1.20214
[752]	train-mlogloss:1.18373	validation-mlogloss:1.20202
[753]	train-mlogloss:1.18343	validation-mlogloss:1.20189
[754]	train-mlogloss:1.18315	validation-mlogloss:1.20170
[755]	train-mlogloss:1.18287	validation-mlogloss:1.20143
[756]	train-mlogloss:1.18252	validation-mlogloss:1.20126
[757]	train-mlogloss:1.18224	validation-mlogloss:1.20105
[758]	train-mlogloss:1.18197	validation-mlogloss:1.20090
[759]	train-mlogloss:1.18163	validation-mlogloss:1.20072
[760]	train-mlogloss:1.18135	validation-mlogloss:1.20057
Saved model to disk.
2025-11-06 14:12:26.165081: 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`.
2025-11-06 14:12:26.176425: 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 00:00:1762434746.189500 1380850 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434746.193574 1380850 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434746.203400 1380850 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434746.203417 1380850 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434746.203418 1380850 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434746.203419 1380850 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:12:26.206556: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
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[1]	train-mlogloss:2.67873	validation-mlogloss:2.67967
[2]	train-mlogloss:2.66449	validation-mlogloss:2.66595
[3]	train-mlogloss:2.65042	validation-mlogloss:2.65257
[4]	train-mlogloss:2.63703	validation-mlogloss:2.63961
[5]	train-mlogloss:2.62352	validation-mlogloss:2.62647
[6]	train-mlogloss:2.61032	validation-mlogloss:2.61398
[7]	train-mlogloss:2.59725	validation-mlogloss:2.60139
[8]	train-mlogloss:2.58412	validation-mlogloss:2.58853
[9]	train-mlogloss:2.57145	validation-mlogloss:2.57654
[10]	train-mlogloss:2.55915	validation-mlogloss:2.56454
[11]	train-mlogloss:2.54700	validation-mlogloss:2.55288
[12]	train-mlogloss:2.53489	validation-mlogloss:2.54111
[13]	train-mlogloss:2.52317	validation-mlogloss:2.52971
[14]	train-mlogloss:2.51188	validation-mlogloss:2.51874
[15]	train-mlogloss:2.50092	validation-mlogloss:2.50798
[16]	train-mlogloss:2.48979	validation-mlogloss:2.49727
[17]	train-mlogloss:2.47909	validation-mlogloss:2.48683
[18]	train-mlogloss:2.46833	validation-mlogloss:2.47629
[19]	train-mlogloss:2.45767	validation-mlogloss:2.46616
[20]	train-mlogloss:2.44732	validation-mlogloss:2.45611
[21]	train-mlogloss:2.43699	validation-mlogloss:2.44614
[22]	train-mlogloss:2.42699	validation-mlogloss:2.43644
[23]	train-mlogloss:2.41720	validation-mlogloss:2.42678
[24]	train-mlogloss:2.40758	validation-mlogloss:2.41737
[25]	train-mlogloss:2.39818	validation-mlogloss:2.40842
[26]	train-mlogloss:2.38889	validation-mlogloss:2.39936
[27]	train-mlogloss:2.37967	validation-mlogloss:2.39046
[28]	train-mlogloss:2.37069	validation-mlogloss:2.38170
[29]	train-mlogloss:2.36174	validation-mlogloss:2.37305
[30]	train-mlogloss:2.35309	validation-mlogloss:2.36462
[31]	train-mlogloss:2.34405	validation-mlogloss:2.35588
[32]	train-mlogloss:2.33543	validation-mlogloss:2.34754
[33]	train-mlogloss:2.32674	validation-mlogloss:2.33880
[34]	train-mlogloss:2.31836	validation-mlogloss:2.33078
[35]	train-mlogloss:2.31020	validation-mlogloss:2.32282
[36]	train-mlogloss:2.30215	validation-mlogloss:2.31503
[37]	train-mlogloss:2.29423	validation-mlogloss:2.30745
[38]	train-mlogloss:2.28626	validation-mlogloss:2.29957
[39]	train-mlogloss:2.27855	validation-mlogloss:2.29206
[40]	train-mlogloss:2.27064	validation-mlogloss:2.28417
[41]	train-mlogloss:2.26304	validation-mlogloss:2.27681
[42]	train-mlogloss:2.25551	validation-mlogloss:2.26931
[43]	train-mlogloss:2.24797	validation-mlogloss:2.26202
[44]	train-mlogloss:2.24048	validation-mlogloss:2.25454
[45]	train-mlogloss:2.23318	validation-mlogloss:2.24742
[46]	train-mlogloss:2.22603	validation-mlogloss:2.24036
[47]	train-mlogloss:2.21901	validation-mlogloss:2.23360
[48]	train-mlogloss:2.21193	validation-mlogloss:2.22678
[49]	train-mlogloss:2.20492	validation-mlogloss:2.21995
[50]	train-mlogloss:2.19799	validation-mlogloss:2.21305
[51]	train-mlogloss:2.19103	validation-mlogloss:2.20625
[52]	train-mlogloss:2.18422	validation-mlogloss:2.19973
[53]	train-mlogloss:2.17753	validation-mlogloss:2.19310
[54]	train-mlogloss:2.17089	validation-mlogloss:2.18654
[55]	train-mlogloss:2.16422	validation-mlogloss:2.17972
[56]	train-mlogloss:2.15787	validation-mlogloss:2.17344
[57]	train-mlogloss:2.15121	validation-mlogloss:2.16657
[58]	train-mlogloss:2.14469	validation-mlogloss:2.15976
[59]	train-mlogloss:2.13853	validation-mlogloss:2.15367
[60]	train-mlogloss:2.13217	validation-mlogloss:2.14717
[61]	train-mlogloss:2.12603	validation-mlogloss:2.14114
[62]	train-mlogloss:2.11989	validation-mlogloss:2.13491
[63]	train-mlogloss:2.11388	validation-mlogloss:2.12902
[64]	train-mlogloss:2.10791	validation-mlogloss:2.12287
[65]	train-mlogloss:2.10174	validation-mlogloss:2.11666
[66]	train-mlogloss:2.09606	validation-mlogloss:2.11111
[67]	train-mlogloss:2.09033	validation-mlogloss:2.10545
[68]	train-mlogloss:2.08451	validation-mlogloss:2.09949
[69]	train-mlogloss:2.07880	validation-mlogloss:2.09365
[70]	train-mlogloss:2.07319	validation-mlogloss:2.08785
[71]	train-mlogloss:2.06767	validation-mlogloss:2.08230
[72]	train-mlogloss:2.06220	validation-mlogloss:2.07658
[73]	train-mlogloss:2.05669	validation-mlogloss:2.07109
[74]	train-mlogloss:2.05118	validation-mlogloss:2.06535
[75]	train-mlogloss:2.04558	validation-mlogloss:2.05985
[76]	train-mlogloss:2.04035	validation-mlogloss:2.05456
[77]	train-mlogloss:2.03506	validation-mlogloss:2.04917
[78]	train-mlogloss:2.02978	validation-mlogloss:2.04375
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[80]	train-mlogloss:2.01919	validation-mlogloss:2.03313
[81]	train-mlogloss:2.01409	validation-mlogloss:2.02799
[82]	train-mlogloss:2.00905	validation-mlogloss:2.02273
[83]	train-mlogloss:2.00396	validation-mlogloss:2.01756
[84]	train-mlogloss:1.99893	validation-mlogloss:2.01241
[85]	train-mlogloss:1.99391	validation-mlogloss:2.00729
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[90]	train-mlogloss:1.96969	validation-mlogloss:1.98260
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[92]	train-mlogloss:1.96039	validation-mlogloss:1.97326
[93]	train-mlogloss:1.95592	validation-mlogloss:1.96867
[94]	train-mlogloss:1.95140	validation-mlogloss:1.96397
[95]	train-mlogloss:1.94690	validation-mlogloss:1.95927
[96]	train-mlogloss:1.94230	validation-mlogloss:1.95459
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[99]	train-mlogloss:1.92890	validation-mlogloss:1.94085
[100]	train-mlogloss:1.92457	validation-mlogloss:1.93640
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[102]	train-mlogloss:1.91586	validation-mlogloss:1.92740
[103]	train-mlogloss:1.91170	validation-mlogloss:1.92306
[104]	train-mlogloss:1.90761	validation-mlogloss:1.91876
[105]	train-mlogloss:1.90350	validation-mlogloss:1.91449
[106]	train-mlogloss:1.89938	validation-mlogloss:1.91023
[107]	train-mlogloss:1.89519	validation-mlogloss:1.90591
[108]	train-mlogloss:1.89124	validation-mlogloss:1.90183
[109]	train-mlogloss:1.88711	validation-mlogloss:1.89759
[110]	train-mlogloss:1.88307	validation-mlogloss:1.89338
[111]	train-mlogloss:1.87918	validation-mlogloss:1.88926
[112]	train-mlogloss:1.87528	validation-mlogloss:1.88542
[113]	train-mlogloss:1.87117	validation-mlogloss:1.88113
[114]	train-mlogloss:1.86742	validation-mlogloss:1.87731
[115]	train-mlogloss:1.86361	validation-mlogloss:1.87344
[116]	train-mlogloss:1.85987	validation-mlogloss:1.86977
[117]	train-mlogloss:1.85615	validation-mlogloss:1.86588
[118]	train-mlogloss:1.85240	validation-mlogloss:1.86192
[119]	train-mlogloss:1.84872	validation-mlogloss:1.85814
[120]	train-mlogloss:1.84512	validation-mlogloss:1.85429
[121]	train-mlogloss:1.84153	validation-mlogloss:1.85062
[122]	train-mlogloss:1.83767	validation-mlogloss:1.84647
[123]	train-mlogloss:1.83408	validation-mlogloss:1.84278
[124]	train-mlogloss:1.83032	validation-mlogloss:1.83889
[125]	train-mlogloss:1.82686	validation-mlogloss:1.83523
[126]	train-mlogloss:1.82351	validation-mlogloss:1.83180
[127]	train-mlogloss:1.82004	validation-mlogloss:1.82829
[128]	train-mlogloss:1.81666	validation-mlogloss:1.82474
[129]	train-mlogloss:1.81324	validation-mlogloss:1.82122
[130]	train-mlogloss:1.80985	validation-mlogloss:1.81776
[131]	train-mlogloss:1.80657	validation-mlogloss:1.81448
[132]	train-mlogloss:1.80336	validation-mlogloss:1.81115
[133]	train-mlogloss:1.79987	validation-mlogloss:1.80765
[134]	train-mlogloss:1.79661	validation-mlogloss:1.80431
[135]	train-mlogloss:1.79338	validation-mlogloss:1.80094
[136]	train-mlogloss:1.78991	validation-mlogloss:1.79723
[137]	train-mlogloss:1.78669	validation-mlogloss:1.79390
[138]	train-mlogloss:1.78333	validation-mlogloss:1.79043
[139]	train-mlogloss:1.78018	validation-mlogloss:1.78713
[140]	train-mlogloss:1.77681	validation-mlogloss:1.78363
[141]	train-mlogloss:1.77348	validation-mlogloss:1.78028
[142]	train-mlogloss:1.77037	validation-mlogloss:1.77705
[143]	train-mlogloss:1.76706	validation-mlogloss:1.77362
[144]	train-mlogloss:1.76399	validation-mlogloss:1.77035
[145]	train-mlogloss:1.76099	validation-mlogloss:1.76719
[146]	train-mlogloss:1.75797	validation-mlogloss:1.76393
[147]	train-mlogloss:1.75502	validation-mlogloss:1.76092
[148]	train-mlogloss:1.75211	validation-mlogloss:1.75789
[149]	train-mlogloss:1.74914	validation-mlogloss:1.75485
[150]	train-mlogloss:1.74631	validation-mlogloss:1.75196
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[753]	train-mlogloss:1.18372	validation-mlogloss:1.20274
[754]	train-mlogloss:1.18345	validation-mlogloss:1.20260
[755]	train-mlogloss:1.18309	validation-mlogloss:1.20238
[756]	train-mlogloss:1.18280	validation-mlogloss:1.20222
[757]	train-mlogloss:1.18253	validation-mlogloss:1.20207
[758]	train-mlogloss:1.18224	validation-mlogloss:1.20190
[759]	train-mlogloss:1.18198	validation-mlogloss:1.20172
[760]	train-mlogloss:1.18165	validation-mlogloss:1.20154
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.61 [%]
Global accuracy score (test) = 58.88 [%]
Global F1 score (train) = 61.14 [%]
Global F1 score (test) = 57.82 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.36      0.21      0.27       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.50      0.43       161
       CAMINAR USUAL SPEED       0.41      0.35      0.38       161
            CAMINAR ZIGZAG       0.44      0.43      0.44       161
          DE PIE BARRIENDO       0.66      0.73      0.69       161
   DE PIE DOBLANDO TOALLAS       0.39      0.39      0.39       161
    DE PIE MOVIENDO LIBROS       0.48      0.50      0.49       161
          DE PIE USANDO PC       0.85      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.54      0.39      0.45       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.45      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.87      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 16: 58.88 [%]
F1-score capturado en la ejecución 16: 57.82 [%]

=== EJECUCIÓN 17 ===

--- TRAIN (ejecución 17) ---

--- TEST (ejecución 17) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.46 [%]
Global accuracy score (test) = 58.67 [%]
Global F1 score (train) = 61.0 [%]
Global F1 score (test) = 57.51 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.38      0.21      0.27       161
 CAMINAR CON MÓVIL O LIBRO       0.36      0.52      0.43       161
       CAMINAR USUAL SPEED       0.40      0.34      0.37       161
            CAMINAR ZIGZAG       0.43      0.42      0.42       161
          DE PIE BARRIENDO       0.66      0.73      0.70       161
   DE PIE DOBLANDO TOALLAS       0.40      0.40      0.40       161
    DE PIE MOVIENDO LIBROS       0.49      0.50      0.50       161
          DE PIE USANDO PC       0.85      0.89      0.87       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.50      0.35      0.41       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.42      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.61      0.87      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 17: 58.67 [%]
F1-score capturado en la ejecución 17: 57.51 [%]

=== EJECUCIÓN 18 ===

--- TRAIN (ejecución 18) ---

--- TEST (ejecución 18) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.63 [%]
Global accuracy score (test) = 59.01 [%]
Global F1 score (train) = 61.19 [%]
Global F1 score (test) = 57.86 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.38      0.24      0.29       161
 CAMINAR CON MÓVIL O LIBRO       0.39      0.55      0.45       161
       CAMINAR USUAL SPEED       0.42      0.36      0.39       161
            CAMINAR ZIGZAG       0.43      0.37      0.40       161
          DE PIE BARRIENDO       0.67      0.73      0.70       161
   DE PIE DOBLANDO TOALLAS       0.41      0.42      0.42       161
    DE PIE MOVIENDO LIBROS       0.49      0.50      0.50       161
          DE PIE USANDO PC       0.84      0.87      0.85       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.53      0.34      0.42       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.41      0.28      0.33       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.89      0.73       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 18: 59.01 [%]
F1-score capturado en la ejecución 18: 57.86 [%]

=== EJECUCIÓN 19 ===

--- TRAIN (ejecución 19) ---

--- TEST (ejecución 19) ---
2025-11-06 14:12:50.687852: 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`.
2025-11-06 14:12:50.699074: 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 00:00:1762434770.712288 1381252 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434770.716208 1381252 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434770.726145 1381252 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434770.726163 1381252 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434770.726165 1381252 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434770.726166 1381252 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:12:50.729310: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69318	validation-mlogloss:2.69371
[1]	train-mlogloss:2.67815	validation-mlogloss:2.67930
[2]	train-mlogloss:2.66400	validation-mlogloss:2.66563
[3]	train-mlogloss:2.64989	validation-mlogloss:2.65226
[4]	train-mlogloss:2.63628	validation-mlogloss:2.63958
[5]	train-mlogloss:2.62281	validation-mlogloss:2.62671
[6]	train-mlogloss:2.60971	validation-mlogloss:2.61411
[7]	train-mlogloss:2.59681	validation-mlogloss:2.60152
[8]	train-mlogloss:2.58411	validation-mlogloss:2.58956
[9]	train-mlogloss:2.57165	validation-mlogloss:2.57769
[10]	train-mlogloss:2.55920	validation-mlogloss:2.56565
[11]	train-mlogloss:2.54718	validation-mlogloss:2.55429
[12]	train-mlogloss:2.53564	validation-mlogloss:2.54350
[13]	train-mlogloss:2.52402	validation-mlogloss:2.53204
[14]	train-mlogloss:2.51269	validation-mlogloss:2.52125
[15]	train-mlogloss:2.50161	validation-mlogloss:2.51056
[16]	train-mlogloss:2.49081	validation-mlogloss:2.50030
[17]	train-mlogloss:2.48001	validation-mlogloss:2.48992
[18]	train-mlogloss:2.46950	validation-mlogloss:2.47978
[19]	train-mlogloss:2.45900	validation-mlogloss:2.46964
[20]	train-mlogloss:2.44862	validation-mlogloss:2.45954
[21]	train-mlogloss:2.43865	validation-mlogloss:2.44997
[22]	train-mlogloss:2.42867	validation-mlogloss:2.44015
[23]	train-mlogloss:2.41863	validation-mlogloss:2.43052
[24]	train-mlogloss:2.40878	validation-mlogloss:2.42097
[25]	train-mlogloss:2.39940	validation-mlogloss:2.41187
[26]	train-mlogloss:2.38994	validation-mlogloss:2.40261
[27]	train-mlogloss:2.38076	validation-mlogloss:2.39352
[28]	train-mlogloss:2.37150	validation-mlogloss:2.38452
[29]	train-mlogloss:2.36260	validation-mlogloss:2.37593
[30]	train-mlogloss:2.35349	validation-mlogloss:2.36683
[31]	train-mlogloss:2.34457	validation-mlogloss:2.35782
[32]	train-mlogloss:2.33587	validation-mlogloss:2.34930
[33]	train-mlogloss:2.32736	validation-mlogloss:2.34106
[34]	train-mlogloss:2.31913	validation-mlogloss:2.33282
[35]	train-mlogloss:2.31082	validation-mlogloss:2.32473
[36]	train-mlogloss:2.30257	validation-mlogloss:2.31653
[37]	train-mlogloss:2.29461	validation-mlogloss:2.30901
[38]	train-mlogloss:2.28660	validation-mlogloss:2.30108
[39]	train-mlogloss:2.27862	validation-mlogloss:2.29295
[40]	train-mlogloss:2.27093	validation-mlogloss:2.28548
[41]	train-mlogloss:2.26336	validation-mlogloss:2.27810
[42]	train-mlogloss:2.25571	validation-mlogloss:2.27044
[43]	train-mlogloss:2.24823	validation-mlogloss:2.26325
[44]	train-mlogloss:2.24085	validation-mlogloss:2.25563
[45]	train-mlogloss:2.23351	validation-mlogloss:2.24837
[46]	train-mlogloss:2.22642	validation-mlogloss:2.24147
[47]	train-mlogloss:2.21912	validation-mlogloss:2.23423
[48]	train-mlogloss:2.21214	validation-mlogloss:2.22728
[49]	train-mlogloss:2.20520	validation-mlogloss:2.22048
[50]	train-mlogloss:2.19810	validation-mlogloss:2.21349
[51]	train-mlogloss:2.19131	validation-mlogloss:2.20677
[52]	train-mlogloss:2.18454	validation-mlogloss:2.20004
[53]	train-mlogloss:2.17794	validation-mlogloss:2.19362
[54]	train-mlogloss:2.17123	validation-mlogloss:2.18699
[55]	train-mlogloss:2.16473	validation-mlogloss:2.18059
[56]	train-mlogloss:2.15833	validation-mlogloss:2.17417
[57]	train-mlogloss:2.15182	validation-mlogloss:2.16754
[58]	train-mlogloss:2.14544	validation-mlogloss:2.16126
[59]	train-mlogloss:2.13917	validation-mlogloss:2.15523
[60]	train-mlogloss:2.13290	validation-mlogloss:2.14886
[61]	train-mlogloss:2.12683	validation-mlogloss:2.14277
[62]	train-mlogloss:2.12062	validation-mlogloss:2.13655
[63]	train-mlogloss:2.11450	validation-mlogloss:2.13028
[64]	train-mlogloss:2.10846	validation-mlogloss:2.12410
[65]	train-mlogloss:2.10233	validation-mlogloss:2.11779
[66]	train-mlogloss:2.09655	validation-mlogloss:2.11202
[67]	train-mlogloss:2.09076	validation-mlogloss:2.10633
[68]	train-mlogloss:2.08507	validation-mlogloss:2.10084
[69]	train-mlogloss:2.07938	validation-mlogloss:2.09508
[70]	train-mlogloss:2.07373	validation-mlogloss:2.08932
[71]	train-mlogloss:2.06811	validation-mlogloss:2.08352
[72]	train-mlogloss:2.06240	validation-mlogloss:2.07765
[73]	train-mlogloss:2.05680	validation-mlogloss:2.07182
[74]	train-mlogloss:2.05130	validation-mlogloss:2.06640
[75]	train-mlogloss:2.04594	validation-mlogloss:2.06079
[76]	train-mlogloss:2.04045	validation-mlogloss:2.05513
[77]	train-mlogloss:2.03506	validation-mlogloss:2.04959
[78]	train-mlogloss:2.02973	validation-mlogloss:2.04431
[79]	train-mlogloss:2.02464	validation-mlogloss:2.03914
[80]	train-mlogloss:2.01955	validation-mlogloss:2.03406
[81]	train-mlogloss:2.01441	validation-mlogloss:2.02878
[82]	train-mlogloss:2.00928	validation-mlogloss:2.02351
[83]	train-mlogloss:2.00433	validation-mlogloss:2.01845
[84]	train-mlogloss:1.99910	validation-mlogloss:2.01315
[85]	train-mlogloss:1.99416	validation-mlogloss:2.00802
[86]	train-mlogloss:1.98926	validation-mlogloss:2.00299
[87]	train-mlogloss:1.98459	validation-mlogloss:1.99812
[88]	train-mlogloss:1.97986	validation-mlogloss:1.99325
[89]	train-mlogloss:1.97507	validation-mlogloss:1.98826
[90]	train-mlogloss:1.97046	validation-mlogloss:1.98365
[91]	train-mlogloss:1.96576	validation-mlogloss:1.97882
[92]	train-mlogloss:1.96116	validation-mlogloss:1.97423
[93]	train-mlogloss:1.95671	validation-mlogloss:1.96967
[94]	train-mlogloss:1.95201	validation-mlogloss:1.96473
[95]	train-mlogloss:1.94757	validation-mlogloss:1.96028
[96]	train-mlogloss:1.94316	validation-mlogloss:1.95589
[97]	train-mlogloss:1.93866	validation-mlogloss:1.95113
[98]	train-mlogloss:1.93427	validation-mlogloss:1.94657
[99]	train-mlogloss:1.92986	validation-mlogloss:1.94193
[100]	train-mlogloss:1.92565	validation-mlogloss:1.93760
[101]	train-mlogloss:1.92140	validation-mlogloss:1.93315
[102]	train-mlogloss:1.91709	validation-mlogloss:1.92879
[103]	train-mlogloss:1.91292	validation-mlogloss:1.92461
[104]	train-mlogloss:1.90875	validation-mlogloss:1.92022
[105]	train-mlogloss:1.90457	validation-mlogloss:1.91589
[106]	train-mlogloss:1.90042	validation-mlogloss:1.91155
[107]	train-mlogloss:1.89643	validation-mlogloss:1.90739
[108]	train-mlogloss:1.89232	validation-mlogloss:1.90317
[109]	train-mlogloss:1.88833	validation-mlogloss:1.89911
[110]	train-mlogloss:1.88433	validation-mlogloss:1.89488
[111]	train-mlogloss:1.88033	validation-mlogloss:1.89073
[112]	train-mlogloss:1.87648	validation-mlogloss:1.88672
[113]	train-mlogloss:1.87259	validation-mlogloss:1.88268
[114]	train-mlogloss:1.86880	validation-mlogloss:1.87879
[115]	train-mlogloss:1.86491	validation-mlogloss:1.87473
[116]	train-mlogloss:1.86111	validation-mlogloss:1.87077
[117]	train-mlogloss:1.85732	validation-mlogloss:1.86684
[118]	train-mlogloss:1.85365	validation-mlogloss:1.86310
[119]	train-mlogloss:1.84993	validation-mlogloss:1.85928
[120]	train-mlogloss:1.84620	validation-mlogloss:1.85535
[121]	train-mlogloss:1.84255	validation-mlogloss:1.85143
[122]	train-mlogloss:1.83892	validation-mlogloss:1.84763
[123]	train-mlogloss:1.83516	validation-mlogloss:1.84389
[124]	train-mlogloss:1.83155	validation-mlogloss:1.84005
[125]	train-mlogloss:1.82801	validation-mlogloss:1.83635
[126]	train-mlogloss:1.82447	validation-mlogloss:1.83268
[127]	train-mlogloss:1.82099	validation-mlogloss:1.82909
[128]	train-mlogloss:1.81761	validation-mlogloss:1.82559
[129]	train-mlogloss:1.81418	validation-mlogloss:1.82193
[130]	train-mlogloss:1.81049	validation-mlogloss:1.81811
[131]	train-mlogloss:1.80717	validation-mlogloss:1.81469
[132]	train-mlogloss:1.80359	validation-mlogloss:1.81088
[133]	train-mlogloss:1.79998	validation-mlogloss:1.80706
[134]	train-mlogloss:1.79669	validation-mlogloss:1.80357
[135]	train-mlogloss:1.79353	validation-mlogloss:1.80030
[136]	train-mlogloss:1.79018	validation-mlogloss:1.79687
[137]	train-mlogloss:1.78677	validation-mlogloss:1.79336
[138]	train-mlogloss:1.78352	validation-mlogloss:1.78997
[139]	train-mlogloss:1.78038	validation-mlogloss:1.78669
[140]	train-mlogloss:1.77735	validation-mlogloss:1.78352
[141]	train-mlogloss:1.77401	validation-mlogloss:1.77999
[142]	train-mlogloss:1.77088	validation-mlogloss:1.77669
[143]	train-mlogloss:1.76773	validation-mlogloss:1.77341
[144]	train-mlogloss:1.76472	validation-mlogloss:1.77032
[145]	train-mlogloss:1.76170	validation-mlogloss:1.76714
[146]	train-mlogloss:1.75873	validation-mlogloss:1.76415
[147]	train-mlogloss:1.75577	validation-mlogloss:1.76101
[148]	train-mlogloss:1.75281	validation-mlogloss:1.75793
[149]	train-mlogloss:1.74983	validation-mlogloss:1.75486
[150]	train-mlogloss:1.74694	validation-mlogloss:1.75184
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[753]	train-mlogloss:1.18440	validation-mlogloss:1.20404
[754]	train-mlogloss:1.18411	validation-mlogloss:1.20385
[755]	train-mlogloss:1.18382	validation-mlogloss:1.20368
[756]	train-mlogloss:1.18352	validation-mlogloss:1.20354
[757]	train-mlogloss:1.18320	validation-mlogloss:1.20327
[758]	train-mlogloss:1.18290	validation-mlogloss:1.20304
[759]	train-mlogloss:1.18264	validation-mlogloss:1.20289
[760]	train-mlogloss:1.18231	validation-mlogloss:1.20278
Saved model to disk.
2025-11-06 14:13:15.082249: 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`.
2025-11-06 14:13:15.093500: 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 00:00:1762434795.106833 1381661 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434795.111229 1381661 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434795.121608 1381661 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434795.121627 1381661 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434795.121629 1381661 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434795.121630 1381661 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:13:15.124830: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69301	validation-mlogloss:2.69367
[1]	train-mlogloss:2.67819	validation-mlogloss:2.67952
[2]	train-mlogloss:2.66357	validation-mlogloss:2.66545
[3]	train-mlogloss:2.64987	validation-mlogloss:2.65221
[4]	train-mlogloss:2.63607	validation-mlogloss:2.63906
[5]	train-mlogloss:2.62228	validation-mlogloss:2.62571
[6]	train-mlogloss:2.60950	validation-mlogloss:2.61337
[7]	train-mlogloss:2.59654	validation-mlogloss:2.60091
[8]	train-mlogloss:2.58406	validation-mlogloss:2.58913
[9]	train-mlogloss:2.57199	validation-mlogloss:2.57774
[10]	train-mlogloss:2.55962	validation-mlogloss:2.56574
[11]	train-mlogloss:2.54749	validation-mlogloss:2.55417
[12]	train-mlogloss:2.53598	validation-mlogloss:2.54296
[13]	train-mlogloss:2.52451	validation-mlogloss:2.53176
[14]	train-mlogloss:2.51326	validation-mlogloss:2.52101
[15]	train-mlogloss:2.50237	validation-mlogloss:2.51047
[16]	train-mlogloss:2.49139	validation-mlogloss:2.49998
[17]	train-mlogloss:2.48030	validation-mlogloss:2.48940
[18]	train-mlogloss:2.46974	validation-mlogloss:2.47925
[19]	train-mlogloss:2.45943	validation-mlogloss:2.46906
[20]	train-mlogloss:2.44924	validation-mlogloss:2.45922
[21]	train-mlogloss:2.43914	validation-mlogloss:2.44948
[22]	train-mlogloss:2.42911	validation-mlogloss:2.43987
[23]	train-mlogloss:2.41927	validation-mlogloss:2.43047
[24]	train-mlogloss:2.40945	validation-mlogloss:2.42073
[25]	train-mlogloss:2.39992	validation-mlogloss:2.41130
[26]	train-mlogloss:2.39054	validation-mlogloss:2.40253
[27]	train-mlogloss:2.38116	validation-mlogloss:2.39329
[28]	train-mlogloss:2.37194	validation-mlogloss:2.38425
[29]	train-mlogloss:2.36287	validation-mlogloss:2.37534
[30]	train-mlogloss:2.35396	validation-mlogloss:2.36670
[31]	train-mlogloss:2.34497	validation-mlogloss:2.35790
[32]	train-mlogloss:2.33644	validation-mlogloss:2.34969
[33]	train-mlogloss:2.32797	validation-mlogloss:2.34151
[34]	train-mlogloss:2.31954	validation-mlogloss:2.33324
[35]	train-mlogloss:2.31138	validation-mlogloss:2.32533
[36]	train-mlogloss:2.30326	validation-mlogloss:2.31753
[37]	train-mlogloss:2.29513	validation-mlogloss:2.30969
[38]	train-mlogloss:2.28716	validation-mlogloss:2.30171
[39]	train-mlogloss:2.27921	validation-mlogloss:2.29399
[40]	train-mlogloss:2.27134	validation-mlogloss:2.28604
[41]	train-mlogloss:2.26358	validation-mlogloss:2.27850
[42]	train-mlogloss:2.25612	validation-mlogloss:2.27123
[43]	train-mlogloss:2.24856	validation-mlogloss:2.26377
[44]	train-mlogloss:2.24120	validation-mlogloss:2.25677
[45]	train-mlogloss:2.23374	validation-mlogloss:2.24953
[46]	train-mlogloss:2.22637	validation-mlogloss:2.24221
[47]	train-mlogloss:2.21917	validation-mlogloss:2.23505
[48]	train-mlogloss:2.21209	validation-mlogloss:2.22803
[49]	train-mlogloss:2.20512	validation-mlogloss:2.22119
[50]	train-mlogloss:2.19813	validation-mlogloss:2.21431
[51]	train-mlogloss:2.19136	validation-mlogloss:2.20753
[52]	train-mlogloss:2.18447	validation-mlogloss:2.20040
[53]	train-mlogloss:2.17780	validation-mlogloss:2.19394
[54]	train-mlogloss:2.17113	validation-mlogloss:2.18747
[55]	train-mlogloss:2.16443	validation-mlogloss:2.18063
[56]	train-mlogloss:2.15793	validation-mlogloss:2.17399
[57]	train-mlogloss:2.15146	validation-mlogloss:2.16741
[58]	train-mlogloss:2.14511	validation-mlogloss:2.16097
[59]	train-mlogloss:2.13894	validation-mlogloss:2.15473
[60]	train-mlogloss:2.13247	validation-mlogloss:2.14805
[61]	train-mlogloss:2.12632	validation-mlogloss:2.14179
[62]	train-mlogloss:2.12014	validation-mlogloss:2.13561
[63]	train-mlogloss:2.11401	validation-mlogloss:2.12941
[64]	train-mlogloss:2.10798	validation-mlogloss:2.12331
[65]	train-mlogloss:2.10198	validation-mlogloss:2.11750
[66]	train-mlogloss:2.09612	validation-mlogloss:2.11184
[67]	train-mlogloss:2.09033	validation-mlogloss:2.10613
[68]	train-mlogloss:2.08447	validation-mlogloss:2.10049
[69]	train-mlogloss:2.07888	validation-mlogloss:2.09505
[70]	train-mlogloss:2.07330	validation-mlogloss:2.08941
[71]	train-mlogloss:2.06761	validation-mlogloss:2.08357
[72]	train-mlogloss:2.06197	validation-mlogloss:2.07780
[73]	train-mlogloss:2.05646	validation-mlogloss:2.07219
[74]	train-mlogloss:2.05107	validation-mlogloss:2.06667
[75]	train-mlogloss:2.04571	validation-mlogloss:2.06135
[76]	train-mlogloss:2.04041	validation-mlogloss:2.05592
[77]	train-mlogloss:2.03522	validation-mlogloss:2.05085
[78]	train-mlogloss:2.02999	validation-mlogloss:2.04556
[79]	train-mlogloss:2.02457	validation-mlogloss:2.03998
[80]	train-mlogloss:2.01937	validation-mlogloss:2.03449
[81]	train-mlogloss:2.01422	validation-mlogloss:2.02934
[82]	train-mlogloss:2.00906	validation-mlogloss:2.02414
[83]	train-mlogloss:2.00398	validation-mlogloss:2.01881
[84]	train-mlogloss:1.99889	validation-mlogloss:2.01359
[85]	train-mlogloss:1.99369	validation-mlogloss:2.00833
[86]	train-mlogloss:1.98875	validation-mlogloss:2.00323
[87]	train-mlogloss:1.98384	validation-mlogloss:1.99836
[88]	train-mlogloss:1.97893	validation-mlogloss:1.99338
[89]	train-mlogloss:1.97428	validation-mlogloss:1.98855
[90]	train-mlogloss:1.96970	validation-mlogloss:1.98410
[91]	train-mlogloss:1.96500	validation-mlogloss:1.97936
[92]	train-mlogloss:1.96028	validation-mlogloss:1.97450
[93]	train-mlogloss:1.95562	validation-mlogloss:1.96978
[94]	train-mlogloss:1.95110	validation-mlogloss:1.96507
[95]	train-mlogloss:1.94647	validation-mlogloss:1.96029
[96]	train-mlogloss:1.94208	validation-mlogloss:1.95566
[97]	train-mlogloss:1.93762	validation-mlogloss:1.95091
[98]	train-mlogloss:1.93318	validation-mlogloss:1.94630
[99]	train-mlogloss:1.92879	validation-mlogloss:1.94190
[100]	train-mlogloss:1.92449	validation-mlogloss:1.93760
[101]	train-mlogloss:1.92023	validation-mlogloss:1.93330
[102]	train-mlogloss:1.91571	validation-mlogloss:1.92862
[103]	train-mlogloss:1.91156	validation-mlogloss:1.92440
[104]	train-mlogloss:1.90741	validation-mlogloss:1.92006
[105]	train-mlogloss:1.90335	validation-mlogloss:1.91589
[106]	train-mlogloss:1.89919	validation-mlogloss:1.91162
[107]	train-mlogloss:1.89505	validation-mlogloss:1.90741
[108]	train-mlogloss:1.89081	validation-mlogloss:1.90300
[109]	train-mlogloss:1.88685	validation-mlogloss:1.89894
[110]	train-mlogloss:1.88301	validation-mlogloss:1.89494
[111]	train-mlogloss:1.87893	validation-mlogloss:1.89067
[112]	train-mlogloss:1.87503	validation-mlogloss:1.88661
[113]	train-mlogloss:1.87111	validation-mlogloss:1.88269
[114]	train-mlogloss:1.86727	validation-mlogloss:1.87868
[115]	train-mlogloss:1.86317	validation-mlogloss:1.87444
[116]	train-mlogloss:1.85919	validation-mlogloss:1.87041
[117]	train-mlogloss:1.85542	validation-mlogloss:1.86648
[118]	train-mlogloss:1.85168	validation-mlogloss:1.86252
[119]	train-mlogloss:1.84808	validation-mlogloss:1.85882
[120]	train-mlogloss:1.84442	validation-mlogloss:1.85496
[121]	train-mlogloss:1.84080	validation-mlogloss:1.85121
[122]	train-mlogloss:1.83712	validation-mlogloss:1.84740
[123]	train-mlogloss:1.83362	validation-mlogloss:1.84375
[124]	train-mlogloss:1.83013	validation-mlogloss:1.84013
[125]	train-mlogloss:1.82643	validation-mlogloss:1.83614
[126]	train-mlogloss:1.82287	validation-mlogloss:1.83253
[127]	train-mlogloss:1.81940	validation-mlogloss:1.82891
[128]	train-mlogloss:1.81585	validation-mlogloss:1.82529
[129]	train-mlogloss:1.81238	validation-mlogloss:1.82172
[130]	train-mlogloss:1.80905	validation-mlogloss:1.81824
[131]	train-mlogloss:1.80542	validation-mlogloss:1.81438
[132]	train-mlogloss:1.80210	validation-mlogloss:1.81086
[133]	train-mlogloss:1.79880	validation-mlogloss:1.80736
[134]	train-mlogloss:1.79546	validation-mlogloss:1.80384
[135]	train-mlogloss:1.79229	validation-mlogloss:1.80059
[136]	train-mlogloss:1.78901	validation-mlogloss:1.79720
[137]	train-mlogloss:1.78575	validation-mlogloss:1.79381
[138]	train-mlogloss:1.78258	validation-mlogloss:1.79045
[139]	train-mlogloss:1.77942	validation-mlogloss:1.78725
[140]	train-mlogloss:1.77623	validation-mlogloss:1.78384
[141]	train-mlogloss:1.77306	validation-mlogloss:1.78039
[142]	train-mlogloss:1.76999	validation-mlogloss:1.77720
[143]	train-mlogloss:1.76669	validation-mlogloss:1.77390
[144]	train-mlogloss:1.76343	validation-mlogloss:1.77053
[145]	train-mlogloss:1.76040	validation-mlogloss:1.76740
[146]	train-mlogloss:1.75739	validation-mlogloss:1.76426
[147]	train-mlogloss:1.75416	validation-mlogloss:1.76090
[148]	train-mlogloss:1.75103	validation-mlogloss:1.75772
[149]	train-mlogloss:1.74784	validation-mlogloss:1.75443
[150]	train-mlogloss:1.74487	validation-mlogloss:1.75126
[151]	train-mlogloss:1.74183	validation-mlogloss:1.74813
[152]	train-mlogloss:1.73895	validation-mlogloss:1.74510
[153]	train-mlogloss:1.73591	validation-mlogloss:1.74191
[154]	train-mlogloss:1.73298	validation-mlogloss:1.73878
[155]	train-mlogloss:1.72994	validation-mlogloss:1.73560
[156]	train-mlogloss:1.72713	validation-mlogloss:1.73274
[157]	train-mlogloss:1.72423	validation-mlogloss:1.72962
[158]	train-mlogloss:1.72146	validation-mlogloss:1.72668
[159]	train-mlogloss:1.71879	validation-mlogloss:1.72382
[160]	train-mlogloss:1.71611	validation-mlogloss:1.72109
[161]	train-mlogloss:1.71335	validation-mlogloss:1.71820
[162]	train-mlogloss:1.71046	validation-mlogloss:1.71518
[163]	train-mlogloss:1.70785	validation-mlogloss:1.71255
[164]	train-mlogloss:1.70506	validation-mlogloss:1.70960
[165]	train-mlogloss:1.70240	validation-mlogloss:1.70682
[166]	train-mlogloss:1.69984	validation-mlogloss:1.70406
[167]	train-mlogloss:1.69710	validation-mlogloss:1.70124
[168]	train-mlogloss:1.69442	validation-mlogloss:1.69836
[169]	train-mlogloss:1.69177	validation-mlogloss:1.69559
[170]	train-mlogloss:1.68907	validation-mlogloss:1.69275
[171]	train-mlogloss:1.68641	validation-mlogloss:1.68997
[172]	train-mlogloss:1.68378	validation-mlogloss:1.68721
[173]	train-mlogloss:1.68103	validation-mlogloss:1.68433
[174]	train-mlogloss:1.67853	validation-mlogloss:1.68170
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[176]	train-mlogloss:1.67325	validation-mlogloss:1.67613
[177]	train-mlogloss:1.67071	validation-mlogloss:1.67337
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[179]	train-mlogloss:1.66567	validation-mlogloss:1.66803
[180]	train-mlogloss:1.66308	validation-mlogloss:1.66521
[181]	train-mlogloss:1.66056	validation-mlogloss:1.66253
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[183]	train-mlogloss:1.65559	validation-mlogloss:1.65727
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[186]	train-mlogloss:1.64839	validation-mlogloss:1.64981
[187]	train-mlogloss:1.64598	validation-mlogloss:1.64734
[188]	train-mlogloss:1.64360	validation-mlogloss:1.64478
[189]	train-mlogloss:1.64124	validation-mlogloss:1.64234
[190]	train-mlogloss:1.63890	validation-mlogloss:1.63995
[191]	train-mlogloss:1.63655	validation-mlogloss:1.63737
[192]	train-mlogloss:1.63426	validation-mlogloss:1.63495
[193]	train-mlogloss:1.63198	validation-mlogloss:1.63245
[194]	train-mlogloss:1.62973	validation-mlogloss:1.63005
[195]	train-mlogloss:1.62740	validation-mlogloss:1.62756
[196]	train-mlogloss:1.62507	validation-mlogloss:1.62503
[197]	train-mlogloss:1.62282	validation-mlogloss:1.62259
[198]	train-mlogloss:1.62053	validation-mlogloss:1.62017
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[200]	train-mlogloss:1.61599	validation-mlogloss:1.61541
[201]	train-mlogloss:1.61369	validation-mlogloss:1.61297
[202]	train-mlogloss:1.61146	validation-mlogloss:1.61053
[203]	train-mlogloss:1.60927	validation-mlogloss:1.60827
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[206]	train-mlogloss:1.60292	validation-mlogloss:1.60163
[207]	train-mlogloss:1.60075	validation-mlogloss:1.59936
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[209]	train-mlogloss:1.59649	validation-mlogloss:1.59484
[210]	train-mlogloss:1.59443	validation-mlogloss:1.59276
[211]	train-mlogloss:1.59236	validation-mlogloss:1.59052
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[609]	train-mlogloss:1.23279	validation-mlogloss:1.23596
[610]	train-mlogloss:1.23242	validation-mlogloss:1.23571
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[631]	train-mlogloss:1.22442	validation-mlogloss:1.22994
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[715]	train-mlogloss:1.19517	validation-mlogloss:1.21041
[716]	train-mlogloss:1.19487	validation-mlogloss:1.21015
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[719]	train-mlogloss:1.19393	validation-mlogloss:1.20957
[720]	train-mlogloss:1.19365	validation-mlogloss:1.20937
[721]	train-mlogloss:1.19331	validation-mlogloss:1.20916
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[728]	train-mlogloss:1.19106	validation-mlogloss:1.20777
[729]	train-mlogloss:1.19077	validation-mlogloss:1.20757
[730]	train-mlogloss:1.19047	validation-mlogloss:1.20740
[731]	train-mlogloss:1.19016	validation-mlogloss:1.20727
[732]	train-mlogloss:1.18983	validation-mlogloss:1.20711
[733]	train-mlogloss:1.18951	validation-mlogloss:1.20694
[734]	train-mlogloss:1.18920	validation-mlogloss:1.20678
[735]	train-mlogloss:1.18892	validation-mlogloss:1.20664
[736]	train-mlogloss:1.18861	validation-mlogloss:1.20642
[737]	train-mlogloss:1.18831	validation-mlogloss:1.20618
[738]	train-mlogloss:1.18803	validation-mlogloss:1.20601
[739]	train-mlogloss:1.18771	validation-mlogloss:1.20591
[740]	train-mlogloss:1.18740	validation-mlogloss:1.20570
[741]	train-mlogloss:1.18710	validation-mlogloss:1.20548
[742]	train-mlogloss:1.18682	validation-mlogloss:1.20533
[743]	train-mlogloss:1.18652	validation-mlogloss:1.20517
[744]	train-mlogloss:1.18623	validation-mlogloss:1.20496
[745]	train-mlogloss:1.18594	validation-mlogloss:1.20487
[746]	train-mlogloss:1.18561	validation-mlogloss:1.20468
[747]	train-mlogloss:1.18533	validation-mlogloss:1.20452
[748]	train-mlogloss:1.18500	validation-mlogloss:1.20439
[749]	train-mlogloss:1.18470	validation-mlogloss:1.20427
[750]	train-mlogloss:1.18440	validation-mlogloss:1.20405
[751]	train-mlogloss:1.18406	validation-mlogloss:1.20386
[752]	train-mlogloss:1.18376	validation-mlogloss:1.20369
[753]	train-mlogloss:1.18348	validation-mlogloss:1.20350
[754]	train-mlogloss:1.18317	validation-mlogloss:1.20331
[755]	train-mlogloss:1.18288	validation-mlogloss:1.20314
[756]	train-mlogloss:1.18262	validation-mlogloss:1.20300
[757]	train-mlogloss:1.18231	validation-mlogloss:1.20278
[758]	train-mlogloss:1.18201	validation-mlogloss:1.20254
[759]	train-mlogloss:1.18167	validation-mlogloss:1.20239
[760]	train-mlogloss:1.18134	validation-mlogloss:1.20223
Saved model to disk.
2025-11-06 14:13:39.749424: 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`.
2025-11-06 14:13:39.760529: 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 00:00:1762434819.773663 1382066 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434819.777782 1382066 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434819.787848 1382066 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434819.787866 1382066 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434819.787868 1382066 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434819.787869 1382066 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:13:39.790963: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69338	validation-mlogloss:2.69413
[1]	train-mlogloss:2.67916	validation-mlogloss:2.68029
[2]	train-mlogloss:2.66521	validation-mlogloss:2.66677
[3]	train-mlogloss:2.65106	validation-mlogloss:2.65331
[4]	train-mlogloss:2.63715	validation-mlogloss:2.64029
[5]	train-mlogloss:2.62370	validation-mlogloss:2.62730
[6]	train-mlogloss:2.61037	validation-mlogloss:2.61467
[7]	train-mlogloss:2.59752	validation-mlogloss:2.60232
[8]	train-mlogloss:2.58485	validation-mlogloss:2.59043
[9]	train-mlogloss:2.57190	validation-mlogloss:2.57783
[10]	train-mlogloss:2.55942	validation-mlogloss:2.56572
[11]	train-mlogloss:2.54750	validation-mlogloss:2.55422
[12]	train-mlogloss:2.53546	validation-mlogloss:2.54243
[13]	train-mlogloss:2.52392	validation-mlogloss:2.53171
[14]	train-mlogloss:2.51216	validation-mlogloss:2.52030
[15]	train-mlogloss:2.50089	validation-mlogloss:2.50929
[16]	train-mlogloss:2.48968	validation-mlogloss:2.49838
[17]	train-mlogloss:2.47872	validation-mlogloss:2.48769
[18]	train-mlogloss:2.46800	validation-mlogloss:2.47747
[19]	train-mlogloss:2.45741	validation-mlogloss:2.46727
[20]	train-mlogloss:2.44692	validation-mlogloss:2.45698
[21]	train-mlogloss:2.43694	validation-mlogloss:2.44711
[22]	train-mlogloss:2.42700	validation-mlogloss:2.43766
[23]	train-mlogloss:2.41719	validation-mlogloss:2.42807
[24]	train-mlogloss:2.40736	validation-mlogloss:2.41864
[25]	train-mlogloss:2.39795	validation-mlogloss:2.40963
[26]	train-mlogloss:2.38845	validation-mlogloss:2.40039
[27]	train-mlogloss:2.37913	validation-mlogloss:2.39124
[28]	train-mlogloss:2.37021	validation-mlogloss:2.38235
[29]	train-mlogloss:2.36122	validation-mlogloss:2.37349
[30]	train-mlogloss:2.35239	validation-mlogloss:2.36486
[31]	train-mlogloss:2.34379	validation-mlogloss:2.35641
[32]	train-mlogloss:2.33521	validation-mlogloss:2.34813
[33]	train-mlogloss:2.32654	validation-mlogloss:2.33953
[34]	train-mlogloss:2.31823	validation-mlogloss:2.33127
[35]	train-mlogloss:2.30997	validation-mlogloss:2.32307
[36]	train-mlogloss:2.30168	validation-mlogloss:2.31521
[37]	train-mlogloss:2.29378	validation-mlogloss:2.30750
[38]	train-mlogloss:2.28599	validation-mlogloss:2.29999
[39]	train-mlogloss:2.27810	validation-mlogloss:2.29219
[40]	train-mlogloss:2.27044	validation-mlogloss:2.28475
[41]	train-mlogloss:2.26280	validation-mlogloss:2.27739
[42]	train-mlogloss:2.25507	validation-mlogloss:2.26955
[43]	train-mlogloss:2.24757	validation-mlogloss:2.26204
[44]	train-mlogloss:2.24026	validation-mlogloss:2.25496
[45]	train-mlogloss:2.23296	validation-mlogloss:2.24778
[46]	train-mlogloss:2.22567	validation-mlogloss:2.24033
[47]	train-mlogloss:2.21852	validation-mlogloss:2.23323
[48]	train-mlogloss:2.21135	validation-mlogloss:2.22587
[49]	train-mlogloss:2.20423	validation-mlogloss:2.21878
[50]	train-mlogloss:2.19735	validation-mlogloss:2.21188
[51]	train-mlogloss:2.19065	validation-mlogloss:2.20517
[52]	train-mlogloss:2.18365	validation-mlogloss:2.19838
[53]	train-mlogloss:2.17711	validation-mlogloss:2.19178
[54]	train-mlogloss:2.17046	validation-mlogloss:2.18538
[55]	train-mlogloss:2.16372	validation-mlogloss:2.17861
[56]	train-mlogloss:2.15721	validation-mlogloss:2.17241
[57]	train-mlogloss:2.15087	validation-mlogloss:2.16614
[58]	train-mlogloss:2.14450	validation-mlogloss:2.16022
[59]	train-mlogloss:2.13812	validation-mlogloss:2.15384
[60]	train-mlogloss:2.13202	validation-mlogloss:2.14764
[61]	train-mlogloss:2.12584	validation-mlogloss:2.14161
[62]	train-mlogloss:2.11980	validation-mlogloss:2.13564
[63]	train-mlogloss:2.11377	validation-mlogloss:2.12959
[64]	train-mlogloss:2.10783	validation-mlogloss:2.12360
[65]	train-mlogloss:2.10175	validation-mlogloss:2.11730
[66]	train-mlogloss:2.09574	validation-mlogloss:2.11120
[67]	train-mlogloss:2.08985	validation-mlogloss:2.10527
[68]	train-mlogloss:2.08407	validation-mlogloss:2.09927
[69]	train-mlogloss:2.07827	validation-mlogloss:2.09332
[70]	train-mlogloss:2.07261	validation-mlogloss:2.08756
[71]	train-mlogloss:2.06704	validation-mlogloss:2.08186
[72]	train-mlogloss:2.06155	validation-mlogloss:2.07619
[73]	train-mlogloss:2.05614	validation-mlogloss:2.07068
[74]	train-mlogloss:2.05062	validation-mlogloss:2.06500
[75]	train-mlogloss:2.04512	validation-mlogloss:2.05938
[76]	train-mlogloss:2.03957	validation-mlogloss:2.05376
[77]	train-mlogloss:2.03429	validation-mlogloss:2.04842
[78]	train-mlogloss:2.02914	validation-mlogloss:2.04321
[79]	train-mlogloss:2.02393	validation-mlogloss:2.03780
[80]	train-mlogloss:2.01876	validation-mlogloss:2.03266
[81]	train-mlogloss:2.01365	validation-mlogloss:2.02744
[82]	train-mlogloss:2.00869	validation-mlogloss:2.02258
[83]	train-mlogloss:2.00366	validation-mlogloss:2.01760
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[685]	train-mlogloss:1.20456	validation-mlogloss:1.21724
[686]	train-mlogloss:1.20420	validation-mlogloss:1.21702
[687]	train-mlogloss:1.20383	validation-mlogloss:1.21679
[688]	train-mlogloss:1.20347	validation-mlogloss:1.21653
[689]	train-mlogloss:1.20312	validation-mlogloss:1.21623
[690]	train-mlogloss:1.20280	validation-mlogloss:1.21600
[691]	train-mlogloss:1.20247	validation-mlogloss:1.21582
[692]	train-mlogloss:1.20216	validation-mlogloss:1.21564
[693]	train-mlogloss:1.20186	validation-mlogloss:1.21543
[694]	train-mlogloss:1.20153	validation-mlogloss:1.21525
[695]	train-mlogloss:1.20122	validation-mlogloss:1.21504
[696]	train-mlogloss:1.20086	validation-mlogloss:1.21488
[697]	train-mlogloss:1.20053	validation-mlogloss:1.21474
[698]	train-mlogloss:1.20021	validation-mlogloss:1.21457
[699]	train-mlogloss:1.19987	validation-mlogloss:1.21436
[700]	train-mlogloss:1.19958	validation-mlogloss:1.21411
[701]	train-mlogloss:1.19928	validation-mlogloss:1.21390
[702]	train-mlogloss:1.19898	validation-mlogloss:1.21371
[703]	train-mlogloss:1.19862	validation-mlogloss:1.21348
[704]	train-mlogloss:1.19831	validation-mlogloss:1.21327
[705]	train-mlogloss:1.19797	validation-mlogloss:1.21299
[706]	train-mlogloss:1.19766	validation-mlogloss:1.21274
[707]	train-mlogloss:1.19734	validation-mlogloss:1.21255
[708]	train-mlogloss:1.19702	validation-mlogloss:1.21240
[709]	train-mlogloss:1.19670	validation-mlogloss:1.21220
[710]	train-mlogloss:1.19640	validation-mlogloss:1.21200
[711]	train-mlogloss:1.19608	validation-mlogloss:1.21176
[712]	train-mlogloss:1.19575	validation-mlogloss:1.21155
[713]	train-mlogloss:1.19538	validation-mlogloss:1.21137
[714]	train-mlogloss:1.19510	validation-mlogloss:1.21124
[715]	train-mlogloss:1.19479	validation-mlogloss:1.21103
[716]	train-mlogloss:1.19450	validation-mlogloss:1.21084
[717]	train-mlogloss:1.19419	validation-mlogloss:1.21061
[718]	train-mlogloss:1.19390	validation-mlogloss:1.21043
[719]	train-mlogloss:1.19361	validation-mlogloss:1.21026
[720]	train-mlogloss:1.19329	validation-mlogloss:1.21009
[721]	train-mlogloss:1.19300	validation-mlogloss:1.20988
[722]	train-mlogloss:1.19265	validation-mlogloss:1.20970
[723]	train-mlogloss:1.19235	validation-mlogloss:1.20949
[724]	train-mlogloss:1.19204	validation-mlogloss:1.20930
[725]	train-mlogloss:1.19171	validation-mlogloss:1.20913
[726]	train-mlogloss:1.19137	validation-mlogloss:1.20897
[727]	train-mlogloss:1.19103	validation-mlogloss:1.20872
[728]	train-mlogloss:1.19073	validation-mlogloss:1.20856
[729]	train-mlogloss:1.19039	validation-mlogloss:1.20834
[730]	train-mlogloss:1.19004	validation-mlogloss:1.20817
[731]	train-mlogloss:1.18976	validation-mlogloss:1.20801
[732]	train-mlogloss:1.18943	validation-mlogloss:1.20783
[733]	train-mlogloss:1.18914	validation-mlogloss:1.20763
[734]	train-mlogloss:1.18881	validation-mlogloss:1.20744
[735]	train-mlogloss:1.18850	validation-mlogloss:1.20722
[736]	train-mlogloss:1.18820	validation-mlogloss:1.20703
[737]	train-mlogloss:1.18783	validation-mlogloss:1.20681
[738]	train-mlogloss:1.18749	validation-mlogloss:1.20662
[739]	train-mlogloss:1.18717	validation-mlogloss:1.20646
[740]	train-mlogloss:1.18689	validation-mlogloss:1.20633
[741]	train-mlogloss:1.18658	validation-mlogloss:1.20608
[742]	train-mlogloss:1.18628	validation-mlogloss:1.20588
[743]	train-mlogloss:1.18601	validation-mlogloss:1.20571
[744]	train-mlogloss:1.18573	validation-mlogloss:1.20561
[745]	train-mlogloss:1.18543	validation-mlogloss:1.20537
[746]	train-mlogloss:1.18513	validation-mlogloss:1.20522
[747]	train-mlogloss:1.18482	validation-mlogloss:1.20507
[748]	train-mlogloss:1.18448	validation-mlogloss:1.20484
[749]	train-mlogloss:1.18420	validation-mlogloss:1.20464
[750]	train-mlogloss:1.18391	validation-mlogloss:1.20446
[751]	train-mlogloss:1.18361	validation-mlogloss:1.20430
[752]	train-mlogloss:1.18334	validation-mlogloss:1.20416
[753]	train-mlogloss:1.18304	validation-mlogloss:1.20400
[754]	train-mlogloss:1.18276	validation-mlogloss:1.20382
[755]	train-mlogloss:1.18247	validation-mlogloss:1.20363
[756]	train-mlogloss:1.18219	validation-mlogloss:1.20343
[757]	train-mlogloss:1.18184	validation-mlogloss:1.20331
[758]	train-mlogloss:1.18151	validation-mlogloss:1.20314
[759]	train-mlogloss:1.18122	validation-mlogloss:1.20297
[760]	train-mlogloss:1.18093	validation-mlogloss:1.20283
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.6 [%]
Global accuracy score (test) = 58.84 [%]
Global F1 score (train) = 61.15 [%]
Global F1 score (test) = 57.71 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.37      0.24      0.29       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.51      0.43       161
       CAMINAR USUAL SPEED       0.40      0.35      0.37       161
            CAMINAR ZIGZAG       0.45      0.41      0.43       161
          DE PIE BARRIENDO       0.66      0.74      0.70       161
   DE PIE DOBLANDO TOALLAS       0.40      0.40      0.40       161
    DE PIE MOVIENDO LIBROS       0.49      0.50      0.50       161
          DE PIE USANDO PC       0.84      0.87      0.85       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.50      0.35      0.41       161
         SENTADO USANDO PC       0.50      0.53      0.51       161
      SENTADO VIENDO LA TV       0.42      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.89      0.73       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 19: 58.84 [%]
F1-score capturado en la ejecución 19: 57.71 [%]

=== EJECUCIÓN 20 ===

--- TRAIN (ejecución 20) ---

--- TEST (ejecución 20) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.42 [%]
Global accuracy score (test) = 59.05 [%]
Global F1 score (train) = 60.96 [%]
Global F1 score (test) = 57.99 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.40      0.22      0.28       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.53      0.44       161
       CAMINAR USUAL SPEED       0.39      0.36      0.37       161
            CAMINAR ZIGZAG       0.43      0.41      0.42       161
          DE PIE BARRIENDO       0.65      0.73      0.69       161
   DE PIE DOBLANDO TOALLAS       0.40      0.39      0.40       161
    DE PIE MOVIENDO LIBROS       0.47      0.50      0.48       161
          DE PIE USANDO PC       0.88      0.89      0.88       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.54      0.40      0.46       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.45      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.59      0.59      0.58      2415
              weighted avg       0.59      0.59      0.58      2415


Accuracy capturado en la ejecución 20: 59.05 [%]
F1-score capturado en la ejecución 20: 57.99 [%]

=== EJECUCIÓN 21 ===

--- TRAIN (ejecución 21) ---

--- TEST (ejecución 21) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.58 [%]
Global accuracy score (test) = 58.34 [%]
Global F1 score (train) = 61.12 [%]
Global F1 score (test) = 57.32 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.37      0.24      0.29       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.52      0.43       161
       CAMINAR USUAL SPEED       0.41      0.35      0.38       161
            CAMINAR ZIGZAG       0.41      0.37      0.39       161
          DE PIE BARRIENDO       0.65      0.74      0.69       161
   DE PIE DOBLANDO TOALLAS       0.38      0.39      0.38       161
    DE PIE MOVIENDO LIBROS       0.48      0.49      0.48       161
          DE PIE USANDO PC       0.85      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.52      0.36      0.43       161
         SENTADO USANDO PC       0.49      0.52      0.50       161
      SENTADO VIENDO LA TV       0.44      0.29      0.35       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.58      2415
                 macro avg       0.58      0.58      0.57      2415
              weighted avg       0.58      0.58      0.57      2415


Accuracy capturado en la ejecución 21: 58.34 [%]
F1-score capturado en la ejecución 21: 57.32 [%]

=== EJECUCIÓN 22 ===

--- TRAIN (ejecución 22) ---

--- TEST (ejecución 22) ---
2025-11-06 14:14:04.030690: 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`.
2025-11-06 14:14:04.042154: 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 00:00:1762434844.055464 1382470 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434844.059625 1382470 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434844.069509 1382470 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434844.069527 1382470 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434844.069529 1382470 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434844.069530 1382470 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:14:04.072617: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69263	validation-mlogloss:2.69320
[1]	train-mlogloss:2.67776	validation-mlogloss:2.67893
[2]	train-mlogloss:2.66345	validation-mlogloss:2.66550
[3]	train-mlogloss:2.64977	validation-mlogloss:2.65207
[4]	train-mlogloss:2.63586	validation-mlogloss:2.63841
[5]	train-mlogloss:2.62211	validation-mlogloss:2.62530
[6]	train-mlogloss:2.60870	validation-mlogloss:2.61271
[7]	train-mlogloss:2.59535	validation-mlogloss:2.59987
[8]	train-mlogloss:2.58271	validation-mlogloss:2.58788
[9]	train-mlogloss:2.57022	validation-mlogloss:2.57576
[10]	train-mlogloss:2.55790	validation-mlogloss:2.56390
[11]	train-mlogloss:2.54599	validation-mlogloss:2.55241
[12]	train-mlogloss:2.53414	validation-mlogloss:2.54093
[13]	train-mlogloss:2.52267	validation-mlogloss:2.52981
[14]	train-mlogloss:2.51107	validation-mlogloss:2.51845
[15]	train-mlogloss:2.49977	validation-mlogloss:2.50731
[16]	train-mlogloss:2.48894	validation-mlogloss:2.49672
[17]	train-mlogloss:2.47813	validation-mlogloss:2.48634
[18]	train-mlogloss:2.46752	validation-mlogloss:2.47616
[19]	train-mlogloss:2.45712	validation-mlogloss:2.46608
[20]	train-mlogloss:2.44656	validation-mlogloss:2.45572
[21]	train-mlogloss:2.43642	validation-mlogloss:2.44584
[22]	train-mlogloss:2.42652	validation-mlogloss:2.43651
[23]	train-mlogloss:2.41677	validation-mlogloss:2.42710
[24]	train-mlogloss:2.40724	validation-mlogloss:2.41804
[25]	train-mlogloss:2.39779	validation-mlogloss:2.40894
[26]	train-mlogloss:2.38804	validation-mlogloss:2.39914
[27]	train-mlogloss:2.37874	validation-mlogloss:2.39003
[28]	train-mlogloss:2.36963	validation-mlogloss:2.38124
[29]	train-mlogloss:2.36047	validation-mlogloss:2.37254
[30]	train-mlogloss:2.35170	validation-mlogloss:2.36409
[31]	train-mlogloss:2.34324	validation-mlogloss:2.35554
[32]	train-mlogloss:2.33431	validation-mlogloss:2.34654
[33]	train-mlogloss:2.32566	validation-mlogloss:2.33811
[34]	train-mlogloss:2.31724	validation-mlogloss:2.32985
[35]	train-mlogloss:2.30897	validation-mlogloss:2.32194
[36]	train-mlogloss:2.30109	validation-mlogloss:2.31423
[37]	train-mlogloss:2.29327	validation-mlogloss:2.30655
[38]	train-mlogloss:2.28535	validation-mlogloss:2.29885
[39]	train-mlogloss:2.27761	validation-mlogloss:2.29149
[40]	train-mlogloss:2.26956	validation-mlogloss:2.28334
[41]	train-mlogloss:2.26169	validation-mlogloss:2.27558
[42]	train-mlogloss:2.25394	validation-mlogloss:2.26782
[43]	train-mlogloss:2.24624	validation-mlogloss:2.26029
[44]	train-mlogloss:2.23874	validation-mlogloss:2.25311
[45]	train-mlogloss:2.23149	validation-mlogloss:2.24606
[46]	train-mlogloss:2.22416	validation-mlogloss:2.23882
[47]	train-mlogloss:2.21705	validation-mlogloss:2.23187
[48]	train-mlogloss:2.20984	validation-mlogloss:2.22465
[49]	train-mlogloss:2.20307	validation-mlogloss:2.21800
[50]	train-mlogloss:2.19626	validation-mlogloss:2.21140
[51]	train-mlogloss:2.18950	validation-mlogloss:2.20473
[52]	train-mlogloss:2.18265	validation-mlogloss:2.19777
[53]	train-mlogloss:2.17594	validation-mlogloss:2.19116
[54]	train-mlogloss:2.16933	validation-mlogloss:2.18463
[55]	train-mlogloss:2.16296	validation-mlogloss:2.17838
[56]	train-mlogloss:2.15634	validation-mlogloss:2.17150
[57]	train-mlogloss:2.14998	validation-mlogloss:2.16523
[58]	train-mlogloss:2.14363	validation-mlogloss:2.15896
[59]	train-mlogloss:2.13725	validation-mlogloss:2.15247
[60]	train-mlogloss:2.13114	validation-mlogloss:2.14659
[61]	train-mlogloss:2.12483	validation-mlogloss:2.14027
[62]	train-mlogloss:2.11883	validation-mlogloss:2.13403
[63]	train-mlogloss:2.11258	validation-mlogloss:2.12758
[64]	train-mlogloss:2.10653	validation-mlogloss:2.12142
[65]	train-mlogloss:2.10052	validation-mlogloss:2.11540
[66]	train-mlogloss:2.09472	validation-mlogloss:2.10957
[67]	train-mlogloss:2.08900	validation-mlogloss:2.10374
[68]	train-mlogloss:2.08309	validation-mlogloss:2.09770
[69]	train-mlogloss:2.07741	validation-mlogloss:2.09184
[70]	train-mlogloss:2.07184	validation-mlogloss:2.08630
[71]	train-mlogloss:2.06618	validation-mlogloss:2.08055
[72]	train-mlogloss:2.06046	validation-mlogloss:2.07482
[73]	train-mlogloss:2.05503	validation-mlogloss:2.06942
[74]	train-mlogloss:2.04962	validation-mlogloss:2.06389
[75]	train-mlogloss:2.04429	validation-mlogloss:2.05852
[76]	train-mlogloss:2.03882	validation-mlogloss:2.05277
[77]	train-mlogloss:2.03359	validation-mlogloss:2.04754
[78]	train-mlogloss:2.02859	validation-mlogloss:2.04258
[79]	train-mlogloss:2.02353	validation-mlogloss:2.03762
[80]	train-mlogloss:2.01826	validation-mlogloss:2.03226
[81]	train-mlogloss:2.01320	validation-mlogloss:2.02704
[82]	train-mlogloss:2.00814	validation-mlogloss:2.02192
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[684]	train-mlogloss:1.20566	validation-mlogloss:1.21631
[685]	train-mlogloss:1.20534	validation-mlogloss:1.21606
[686]	train-mlogloss:1.20499	validation-mlogloss:1.21581
[687]	train-mlogloss:1.20464	validation-mlogloss:1.21560
[688]	train-mlogloss:1.20430	validation-mlogloss:1.21537
[689]	train-mlogloss:1.20398	validation-mlogloss:1.21518
[690]	train-mlogloss:1.20365	validation-mlogloss:1.21503
[691]	train-mlogloss:1.20325	validation-mlogloss:1.21489
[692]	train-mlogloss:1.20290	validation-mlogloss:1.21467
[693]	train-mlogloss:1.20255	validation-mlogloss:1.21446
[694]	train-mlogloss:1.20219	validation-mlogloss:1.21429
[695]	train-mlogloss:1.20186	validation-mlogloss:1.21411
[696]	train-mlogloss:1.20153	validation-mlogloss:1.21390
[697]	train-mlogloss:1.20118	validation-mlogloss:1.21367
[698]	train-mlogloss:1.20084	validation-mlogloss:1.21348
[699]	train-mlogloss:1.20053	validation-mlogloss:1.21329
[700]	train-mlogloss:1.20017	validation-mlogloss:1.21310
[701]	train-mlogloss:1.19981	validation-mlogloss:1.21288
[702]	train-mlogloss:1.19947	validation-mlogloss:1.21271
[703]	train-mlogloss:1.19913	validation-mlogloss:1.21244
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[705]	train-mlogloss:1.19848	validation-mlogloss:1.21198
[706]	train-mlogloss:1.19811	validation-mlogloss:1.21170
[707]	train-mlogloss:1.19782	validation-mlogloss:1.21149
[708]	train-mlogloss:1.19751	validation-mlogloss:1.21127
[709]	train-mlogloss:1.19719	validation-mlogloss:1.21108
[710]	train-mlogloss:1.19688	validation-mlogloss:1.21086
[711]	train-mlogloss:1.19657	validation-mlogloss:1.21065
[712]	train-mlogloss:1.19625	validation-mlogloss:1.21042
[713]	train-mlogloss:1.19589	validation-mlogloss:1.21021
[714]	train-mlogloss:1.19554	validation-mlogloss:1.20991
[715]	train-mlogloss:1.19518	validation-mlogloss:1.20969
[716]	train-mlogloss:1.19488	validation-mlogloss:1.20943
[717]	train-mlogloss:1.19456	validation-mlogloss:1.20928
[718]	train-mlogloss:1.19426	validation-mlogloss:1.20917
[719]	train-mlogloss:1.19394	validation-mlogloss:1.20894
[720]	train-mlogloss:1.19361	validation-mlogloss:1.20872
[721]	train-mlogloss:1.19328	validation-mlogloss:1.20850
[722]	train-mlogloss:1.19302	validation-mlogloss:1.20829
[723]	train-mlogloss:1.19269	validation-mlogloss:1.20808
[724]	train-mlogloss:1.19236	validation-mlogloss:1.20792
[725]	train-mlogloss:1.19201	validation-mlogloss:1.20778
[726]	train-mlogloss:1.19169	validation-mlogloss:1.20761
[727]	train-mlogloss:1.19137	validation-mlogloss:1.20742
[728]	train-mlogloss:1.19108	validation-mlogloss:1.20721
[729]	train-mlogloss:1.19076	validation-mlogloss:1.20694
[730]	train-mlogloss:1.19048	validation-mlogloss:1.20676
[731]	train-mlogloss:1.19015	validation-mlogloss:1.20658
[732]	train-mlogloss:1.18984	validation-mlogloss:1.20645
[733]	train-mlogloss:1.18953	validation-mlogloss:1.20627
[734]	train-mlogloss:1.18923	validation-mlogloss:1.20617
[735]	train-mlogloss:1.18892	validation-mlogloss:1.20594
[736]	train-mlogloss:1.18863	validation-mlogloss:1.20582
[737]	train-mlogloss:1.18829	validation-mlogloss:1.20566
[738]	train-mlogloss:1.18795	validation-mlogloss:1.20543
[739]	train-mlogloss:1.18765	validation-mlogloss:1.20530
[740]	train-mlogloss:1.18735	validation-mlogloss:1.20513
[741]	train-mlogloss:1.18707	validation-mlogloss:1.20496
[742]	train-mlogloss:1.18679	validation-mlogloss:1.20474
[743]	train-mlogloss:1.18644	validation-mlogloss:1.20451
[744]	train-mlogloss:1.18614	validation-mlogloss:1.20436
[745]	train-mlogloss:1.18584	validation-mlogloss:1.20421
[746]	train-mlogloss:1.18554	validation-mlogloss:1.20404
[747]	train-mlogloss:1.18524	validation-mlogloss:1.20388
[748]	train-mlogloss:1.18492	validation-mlogloss:1.20369
[749]	train-mlogloss:1.18462	validation-mlogloss:1.20353
[750]	train-mlogloss:1.18434	validation-mlogloss:1.20337
[751]	train-mlogloss:1.18403	validation-mlogloss:1.20316
[752]	train-mlogloss:1.18373	validation-mlogloss:1.20303
[753]	train-mlogloss:1.18346	validation-mlogloss:1.20282
[754]	train-mlogloss:1.18317	validation-mlogloss:1.20264
[755]	train-mlogloss:1.18286	validation-mlogloss:1.20242
[756]	train-mlogloss:1.18257	validation-mlogloss:1.20224
[757]	train-mlogloss:1.18229	validation-mlogloss:1.20210
[758]	train-mlogloss:1.18198	validation-mlogloss:1.20189
[759]	train-mlogloss:1.18174	validation-mlogloss:1.20175
[760]	train-mlogloss:1.18142	validation-mlogloss:1.20171
Saved model to disk.
2025-11-06 14:14:28.531275: 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`.
2025-11-06 14:14:28.542860: 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 00:00:1762434868.556016 1382874 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434868.559988 1382874 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434868.569944 1382874 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434868.569960 1382874 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434868.569962 1382874 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434868.569963 1382874 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:14:28.573066: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69317	validation-mlogloss:2.69349
[1]	train-mlogloss:2.67854	validation-mlogloss:2.67938
[2]	train-mlogloss:2.66430	validation-mlogloss:2.66561
[3]	train-mlogloss:2.65003	validation-mlogloss:2.65177
[4]	train-mlogloss:2.63612	validation-mlogloss:2.63848
[5]	train-mlogloss:2.62283	validation-mlogloss:2.62575
[6]	train-mlogloss:2.60946	validation-mlogloss:2.61284
[7]	train-mlogloss:2.59665	validation-mlogloss:2.60054
[8]	train-mlogloss:2.58423	validation-mlogloss:2.58844
[9]	train-mlogloss:2.57172	validation-mlogloss:2.57625
[10]	train-mlogloss:2.55925	validation-mlogloss:2.56438
[11]	train-mlogloss:2.54711	validation-mlogloss:2.55263
[12]	train-mlogloss:2.53554	validation-mlogloss:2.54162
[13]	train-mlogloss:2.52405	validation-mlogloss:2.53063
[14]	train-mlogloss:2.51248	validation-mlogloss:2.51939
[15]	train-mlogloss:2.50135	validation-mlogloss:2.50857
[16]	train-mlogloss:2.49021	validation-mlogloss:2.49788
[17]	train-mlogloss:2.47955	validation-mlogloss:2.48740
[18]	train-mlogloss:2.46882	validation-mlogloss:2.47696
[19]	train-mlogloss:2.45853	validation-mlogloss:2.46709
[20]	train-mlogloss:2.44807	validation-mlogloss:2.45709
[21]	train-mlogloss:2.43802	validation-mlogloss:2.44750
[22]	train-mlogloss:2.42809	validation-mlogloss:2.43804
[23]	train-mlogloss:2.41832	validation-mlogloss:2.42866
[24]	train-mlogloss:2.40876	validation-mlogloss:2.41934
[25]	train-mlogloss:2.39910	validation-mlogloss:2.40987
[26]	train-mlogloss:2.38982	validation-mlogloss:2.40104
[27]	train-mlogloss:2.38063	validation-mlogloss:2.39215
[28]	train-mlogloss:2.37152	validation-mlogloss:2.38332
[29]	train-mlogloss:2.36237	validation-mlogloss:2.37434
[30]	train-mlogloss:2.35354	validation-mlogloss:2.36570
[31]	train-mlogloss:2.34493	validation-mlogloss:2.35750
[32]	train-mlogloss:2.33635	validation-mlogloss:2.34921
[33]	train-mlogloss:2.32762	validation-mlogloss:2.34065
[34]	train-mlogloss:2.31925	validation-mlogloss:2.33258
[35]	train-mlogloss:2.31083	validation-mlogloss:2.32435
[36]	train-mlogloss:2.30263	validation-mlogloss:2.31630
[37]	train-mlogloss:2.29449	validation-mlogloss:2.30841
[38]	train-mlogloss:2.28660	validation-mlogloss:2.30058
[39]	train-mlogloss:2.27885	validation-mlogloss:2.29301
[40]	train-mlogloss:2.27115	validation-mlogloss:2.28561
[41]	train-mlogloss:2.26340	validation-mlogloss:2.27778
[42]	train-mlogloss:2.25580	validation-mlogloss:2.27032
[43]	train-mlogloss:2.24819	validation-mlogloss:2.26281
[44]	train-mlogloss:2.24072	validation-mlogloss:2.25559
[45]	train-mlogloss:2.23319	validation-mlogloss:2.24821
[46]	train-mlogloss:2.22607	validation-mlogloss:2.24150
[47]	train-mlogloss:2.21890	validation-mlogloss:2.23440
[48]	train-mlogloss:2.21165	validation-mlogloss:2.22728
[49]	train-mlogloss:2.20462	validation-mlogloss:2.22045
[50]	train-mlogloss:2.19760	validation-mlogloss:2.21353
[51]	train-mlogloss:2.19037	validation-mlogloss:2.20616
[52]	train-mlogloss:2.18362	validation-mlogloss:2.19949
[53]	train-mlogloss:2.17698	validation-mlogloss:2.19290
[54]	train-mlogloss:2.17039	validation-mlogloss:2.18641
[55]	train-mlogloss:2.16389	validation-mlogloss:2.17997
[56]	train-mlogloss:2.15736	validation-mlogloss:2.17332
[57]	train-mlogloss:2.15103	validation-mlogloss:2.16720
[58]	train-mlogloss:2.14488	validation-mlogloss:2.16106
[59]	train-mlogloss:2.13867	validation-mlogloss:2.15486
[60]	train-mlogloss:2.13237	validation-mlogloss:2.14847
[61]	train-mlogloss:2.12591	validation-mlogloss:2.14200
[62]	train-mlogloss:2.11990	validation-mlogloss:2.13626
[63]	train-mlogloss:2.11389	validation-mlogloss:2.13027
[64]	train-mlogloss:2.10790	validation-mlogloss:2.12421
[65]	train-mlogloss:2.10183	validation-mlogloss:2.11803
[66]	train-mlogloss:2.09623	validation-mlogloss:2.11268
[67]	train-mlogloss:2.09043	validation-mlogloss:2.10685
[68]	train-mlogloss:2.08456	validation-mlogloss:2.10086
[69]	train-mlogloss:2.07896	validation-mlogloss:2.09513
[70]	train-mlogloss:2.07334	validation-mlogloss:2.08959
[71]	train-mlogloss:2.06780	validation-mlogloss:2.08408
[72]	train-mlogloss:2.06237	validation-mlogloss:2.07868
[73]	train-mlogloss:2.05669	validation-mlogloss:2.07290
[74]	train-mlogloss:2.05130	validation-mlogloss:2.06750
[75]	train-mlogloss:2.04586	validation-mlogloss:2.06190
[76]	train-mlogloss:2.04058	validation-mlogloss:2.05657
[77]	train-mlogloss:2.03525	validation-mlogloss:2.05130
[78]	train-mlogloss:2.02997	validation-mlogloss:2.04612
[79]	train-mlogloss:2.02456	validation-mlogloss:2.04044
[80]	train-mlogloss:2.01930	validation-mlogloss:2.03505
[81]	train-mlogloss:2.01404	validation-mlogloss:2.02953
[82]	train-mlogloss:2.00877	validation-mlogloss:2.02403
[83]	train-mlogloss:2.00372	validation-mlogloss:2.01886
[84]	train-mlogloss:1.99896	validation-mlogloss:2.01428
[85]	train-mlogloss:1.99394	validation-mlogloss:2.00896
[86]	train-mlogloss:1.98900	validation-mlogloss:2.00404
[87]	train-mlogloss:1.98414	validation-mlogloss:1.99898
[88]	train-mlogloss:1.97936	validation-mlogloss:1.99427
[89]	train-mlogloss:1.97467	validation-mlogloss:1.98951
[90]	train-mlogloss:1.97003	validation-mlogloss:1.98481
[91]	train-mlogloss:1.96523	validation-mlogloss:1.97991
[92]	train-mlogloss:1.96057	validation-mlogloss:1.97522
[93]	train-mlogloss:1.95597	validation-mlogloss:1.97052
[94]	train-mlogloss:1.95140	validation-mlogloss:1.96598
[95]	train-mlogloss:1.94688	validation-mlogloss:1.96125
[96]	train-mlogloss:1.94222	validation-mlogloss:1.95648
[97]	train-mlogloss:1.93780	validation-mlogloss:1.95197
[98]	train-mlogloss:1.93344	validation-mlogloss:1.94742
[99]	train-mlogloss:1.92902	validation-mlogloss:1.94298
[100]	train-mlogloss:1.92470	validation-mlogloss:1.93849
[101]	train-mlogloss:1.92031	validation-mlogloss:1.93402
[102]	train-mlogloss:1.91611	validation-mlogloss:1.92956
[103]	train-mlogloss:1.91186	validation-mlogloss:1.92535
[104]	train-mlogloss:1.90784	validation-mlogloss:1.92129
[105]	train-mlogloss:1.90373	validation-mlogloss:1.91715
[106]	train-mlogloss:1.89974	validation-mlogloss:1.91301
[107]	train-mlogloss:1.89531	validation-mlogloss:1.90829
[108]	train-mlogloss:1.89124	validation-mlogloss:1.90414
[109]	train-mlogloss:1.88724	validation-mlogloss:1.90007
[110]	train-mlogloss:1.88304	validation-mlogloss:1.89580
[111]	train-mlogloss:1.87884	validation-mlogloss:1.89141
[112]	train-mlogloss:1.87488	validation-mlogloss:1.88740
[113]	train-mlogloss:1.87101	validation-mlogloss:1.88333
[114]	train-mlogloss:1.86712	validation-mlogloss:1.87934
[115]	train-mlogloss:1.86330	validation-mlogloss:1.87538
[116]	train-mlogloss:1.85925	validation-mlogloss:1.87117
[117]	train-mlogloss:1.85544	validation-mlogloss:1.86718
[118]	train-mlogloss:1.85162	validation-mlogloss:1.86321
[119]	train-mlogloss:1.84794	validation-mlogloss:1.85937
[120]	train-mlogloss:1.84431	validation-mlogloss:1.85561
[121]	train-mlogloss:1.84067	validation-mlogloss:1.85179
[122]	train-mlogloss:1.83705	validation-mlogloss:1.84795
[123]	train-mlogloss:1.83309	validation-mlogloss:1.84387
[124]	train-mlogloss:1.82958	validation-mlogloss:1.84035
[125]	train-mlogloss:1.82603	validation-mlogloss:1.83656
[126]	train-mlogloss:1.82237	validation-mlogloss:1.83280
[127]	train-mlogloss:1.81874	validation-mlogloss:1.82884
[128]	train-mlogloss:1.81525	validation-mlogloss:1.82525
[129]	train-mlogloss:1.81160	validation-mlogloss:1.82136
[130]	train-mlogloss:1.80817	validation-mlogloss:1.81778
[131]	train-mlogloss:1.80476	validation-mlogloss:1.81429
[132]	train-mlogloss:1.80134	validation-mlogloss:1.81071
[133]	train-mlogloss:1.79788	validation-mlogloss:1.80697
[134]	train-mlogloss:1.79464	validation-mlogloss:1.80361
[135]	train-mlogloss:1.79126	validation-mlogloss:1.80019
[136]	train-mlogloss:1.78809	validation-mlogloss:1.79683
[137]	train-mlogloss:1.78481	validation-mlogloss:1.79347
[138]	train-mlogloss:1.78145	validation-mlogloss:1.78989
[139]	train-mlogloss:1.77809	validation-mlogloss:1.78629
[140]	train-mlogloss:1.77497	validation-mlogloss:1.78311
[141]	train-mlogloss:1.77169	validation-mlogloss:1.77952
[142]	train-mlogloss:1.76863	validation-mlogloss:1.77626
[143]	train-mlogloss:1.76545	validation-mlogloss:1.77305
[144]	train-mlogloss:1.76242	validation-mlogloss:1.76985
[145]	train-mlogloss:1.75918	validation-mlogloss:1.76637
[146]	train-mlogloss:1.75621	validation-mlogloss:1.76324
[147]	train-mlogloss:1.75314	validation-mlogloss:1.76002
[148]	train-mlogloss:1.75025	validation-mlogloss:1.75705
[149]	train-mlogloss:1.74732	validation-mlogloss:1.75394
[150]	train-mlogloss:1.74427	validation-mlogloss:1.75075
[151]	train-mlogloss:1.74147	validation-mlogloss:1.74787
[152]	train-mlogloss:1.73836	validation-mlogloss:1.74453
[153]	train-mlogloss:1.73554	validation-mlogloss:1.74157
[154]	train-mlogloss:1.73262	validation-mlogloss:1.73854
[155]	train-mlogloss:1.72977	validation-mlogloss:1.73551
[156]	train-mlogloss:1.72682	validation-mlogloss:1.73233
[157]	train-mlogloss:1.72407	validation-mlogloss:1.72942
[158]	train-mlogloss:1.72115	validation-mlogloss:1.72633
[159]	train-mlogloss:1.71813	validation-mlogloss:1.72322
[160]	train-mlogloss:1.71519	validation-mlogloss:1.72022
[161]	train-mlogloss:1.71248	validation-mlogloss:1.71752
[162]	train-mlogloss:1.70983	validation-mlogloss:1.71468
[163]	train-mlogloss:1.70700	validation-mlogloss:1.71167
[164]	train-mlogloss:1.70418	validation-mlogloss:1.70877
[165]	train-mlogloss:1.70140	validation-mlogloss:1.70574
[166]	train-mlogloss:1.69866	validation-mlogloss:1.70284
[167]	train-mlogloss:1.69585	validation-mlogloss:1.69991
[168]	train-mlogloss:1.69317	validation-mlogloss:1.69713
[169]	train-mlogloss:1.69058	validation-mlogloss:1.69441
[170]	train-mlogloss:1.68782	validation-mlogloss:1.69144
[171]	train-mlogloss:1.68511	validation-mlogloss:1.68856
[172]	train-mlogloss:1.68244	validation-mlogloss:1.68570
[173]	train-mlogloss:1.67977	validation-mlogloss:1.68287
[174]	train-mlogloss:1.67718	validation-mlogloss:1.68010
[175]	train-mlogloss:1.67459	validation-mlogloss:1.67746
[176]	train-mlogloss:1.67203	validation-mlogloss:1.67479
[177]	train-mlogloss:1.66955	validation-mlogloss:1.67208
[178]	train-mlogloss:1.66698	validation-mlogloss:1.66943
[179]	train-mlogloss:1.66444	validation-mlogloss:1.66689
[180]	train-mlogloss:1.66187	validation-mlogloss:1.66404
[181]	train-mlogloss:1.65943	validation-mlogloss:1.66146
[182]	train-mlogloss:1.65699	validation-mlogloss:1.65894
[183]	train-mlogloss:1.65456	validation-mlogloss:1.65638
[184]	train-mlogloss:1.65215	validation-mlogloss:1.65389
[185]	train-mlogloss:1.64969	validation-mlogloss:1.65128
[186]	train-mlogloss:1.64722	validation-mlogloss:1.64865
[187]	train-mlogloss:1.64484	validation-mlogloss:1.64609
[188]	train-mlogloss:1.64243	validation-mlogloss:1.64360
[189]	train-mlogloss:1.64011	validation-mlogloss:1.64111
[190]	train-mlogloss:1.63776	validation-mlogloss:1.63855
[191]	train-mlogloss:1.63544	validation-mlogloss:1.63616
[192]	train-mlogloss:1.63313	validation-mlogloss:1.63373
[193]	train-mlogloss:1.63078	validation-mlogloss:1.63129
[194]	train-mlogloss:1.62846	validation-mlogloss:1.62878
[195]	train-mlogloss:1.62623	validation-mlogloss:1.62641
[196]	train-mlogloss:1.62395	validation-mlogloss:1.62395
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[735]	train-mlogloss:1.18918	validation-mlogloss:1.20679
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[743]	train-mlogloss:1.18676	validation-mlogloss:1.20523
[744]	train-mlogloss:1.18644	validation-mlogloss:1.20510
[745]	train-mlogloss:1.18612	validation-mlogloss:1.20491
[746]	train-mlogloss:1.18577	validation-mlogloss:1.20479
[747]	train-mlogloss:1.18544	validation-mlogloss:1.20455
[748]	train-mlogloss:1.18514	validation-mlogloss:1.20436
[749]	train-mlogloss:1.18488	validation-mlogloss:1.20423
[750]	train-mlogloss:1.18457	validation-mlogloss:1.20407
[751]	train-mlogloss:1.18428	validation-mlogloss:1.20390
[752]	train-mlogloss:1.18397	validation-mlogloss:1.20379
[753]	train-mlogloss:1.18362	validation-mlogloss:1.20364
[754]	train-mlogloss:1.18328	validation-mlogloss:1.20350
[755]	train-mlogloss:1.18299	validation-mlogloss:1.20335
[756]	train-mlogloss:1.18264	validation-mlogloss:1.20317
[757]	train-mlogloss:1.18229	validation-mlogloss:1.20300
[758]	train-mlogloss:1.18199	validation-mlogloss:1.20280
[759]	train-mlogloss:1.18170	validation-mlogloss:1.20259
[760]	train-mlogloss:1.18139	validation-mlogloss:1.20241
Saved model to disk.
2025-11-06 14:14:53.011949: 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`.
2025-11-06 14:14:53.023234: 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 00:00:1762434893.036292 1383288 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434893.040185 1383288 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434893.050131 1383288 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434893.050147 1383288 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434893.050149 1383288 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434893.050150 1383288 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:14:53.053243: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69346	validation-mlogloss:2.69400
[1]	train-mlogloss:2.67909	validation-mlogloss:2.68013
[2]	train-mlogloss:2.66479	validation-mlogloss:2.66669
[3]	train-mlogloss:2.65050	validation-mlogloss:2.65291
[4]	train-mlogloss:2.63687	validation-mlogloss:2.63962
[5]	train-mlogloss:2.62349	validation-mlogloss:2.62665
[6]	train-mlogloss:2.60985	validation-mlogloss:2.61393
[7]	train-mlogloss:2.59685	validation-mlogloss:2.60143
[8]	train-mlogloss:2.58431	validation-mlogloss:2.58959
[9]	train-mlogloss:2.57171	validation-mlogloss:2.57730
[10]	train-mlogloss:2.55938	validation-mlogloss:2.56536
[11]	train-mlogloss:2.54753	validation-mlogloss:2.55371
[12]	train-mlogloss:2.53583	validation-mlogloss:2.54231
[13]	train-mlogloss:2.52442	validation-mlogloss:2.53132
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[616]	train-mlogloss:1.23007	validation-mlogloss:1.23362
[617]	train-mlogloss:1.22967	validation-mlogloss:1.23328
[618]	train-mlogloss:1.22930	validation-mlogloss:1.23299
[619]	train-mlogloss:1.22890	validation-mlogloss:1.23270
[620]	train-mlogloss:1.22851	validation-mlogloss:1.23245
[621]	train-mlogloss:1.22808	validation-mlogloss:1.23215
[622]	train-mlogloss:1.22771	validation-mlogloss:1.23186
[623]	train-mlogloss:1.22733	validation-mlogloss:1.23155
[624]	train-mlogloss:1.22692	validation-mlogloss:1.23119
[625]	train-mlogloss:1.22656	validation-mlogloss:1.23097
[626]	train-mlogloss:1.22611	validation-mlogloss:1.23068
[627]	train-mlogloss:1.22573	validation-mlogloss:1.23041
[628]	train-mlogloss:1.22535	validation-mlogloss:1.23014
[629]	train-mlogloss:1.22497	validation-mlogloss:1.22981
[630]	train-mlogloss:1.22459	validation-mlogloss:1.22948
[631]	train-mlogloss:1.22419	validation-mlogloss:1.22918
[632]	train-mlogloss:1.22384	validation-mlogloss:1.22896
[633]	train-mlogloss:1.22346	validation-mlogloss:1.22875
[634]	train-mlogloss:1.22306	validation-mlogloss:1.22846
[635]	train-mlogloss:1.22271	validation-mlogloss:1.22820
[636]	train-mlogloss:1.22229	validation-mlogloss:1.22792
[637]	train-mlogloss:1.22193	validation-mlogloss:1.22770
[638]	train-mlogloss:1.22155	validation-mlogloss:1.22747
[639]	train-mlogloss:1.22120	validation-mlogloss:1.22716
[640]	train-mlogloss:1.22083	validation-mlogloss:1.22684
[641]	train-mlogloss:1.22047	validation-mlogloss:1.22657
[642]	train-mlogloss:1.22010	validation-mlogloss:1.22629
[643]	train-mlogloss:1.21971	validation-mlogloss:1.22601
[644]	train-mlogloss:1.21934	validation-mlogloss:1.22581
[645]	train-mlogloss:1.21898	validation-mlogloss:1.22558
[646]	train-mlogloss:1.21861	validation-mlogloss:1.22534
[647]	train-mlogloss:1.21824	validation-mlogloss:1.22506
[648]	train-mlogloss:1.21790	validation-mlogloss:1.22476
[649]	train-mlogloss:1.21752	validation-mlogloss:1.22457
[650]	train-mlogloss:1.21717	validation-mlogloss:1.22432
[651]	train-mlogloss:1.21681	validation-mlogloss:1.22404
[652]	train-mlogloss:1.21645	validation-mlogloss:1.22385
[653]	train-mlogloss:1.21609	validation-mlogloss:1.22359
[654]	train-mlogloss:1.21573	validation-mlogloss:1.22339
[655]	train-mlogloss:1.21540	validation-mlogloss:1.22312
[656]	train-mlogloss:1.21506	validation-mlogloss:1.22286
[657]	train-mlogloss:1.21471	validation-mlogloss:1.22262
[658]	train-mlogloss:1.21438	validation-mlogloss:1.22236
[659]	train-mlogloss:1.21405	validation-mlogloss:1.22213
[660]	train-mlogloss:1.21372	validation-mlogloss:1.22188
[661]	train-mlogloss:1.21331	validation-mlogloss:1.22160
[662]	train-mlogloss:1.21295	validation-mlogloss:1.22140
[663]	train-mlogloss:1.21262	validation-mlogloss:1.22115
[664]	train-mlogloss:1.21228	validation-mlogloss:1.22092
[665]	train-mlogloss:1.21191	validation-mlogloss:1.22065
[666]	train-mlogloss:1.21153	validation-mlogloss:1.22038
[667]	train-mlogloss:1.21121	validation-mlogloss:1.22018
[668]	train-mlogloss:1.21086	validation-mlogloss:1.21995
[669]	train-mlogloss:1.21047	validation-mlogloss:1.21964
[670]	train-mlogloss:1.21012	validation-mlogloss:1.21934
[671]	train-mlogloss:1.20978	validation-mlogloss:1.21912
[672]	train-mlogloss:1.20945	validation-mlogloss:1.21889
[673]	train-mlogloss:1.20911	validation-mlogloss:1.21860
[674]	train-mlogloss:1.20878	validation-mlogloss:1.21837
[675]	train-mlogloss:1.20843	validation-mlogloss:1.21809
[676]	train-mlogloss:1.20809	validation-mlogloss:1.21783
[677]	train-mlogloss:1.20778	validation-mlogloss:1.21763
[678]	train-mlogloss:1.20743	validation-mlogloss:1.21742
[679]	train-mlogloss:1.20713	validation-mlogloss:1.21721
[680]	train-mlogloss:1.20679	validation-mlogloss:1.21695
[681]	train-mlogloss:1.20645	validation-mlogloss:1.21670
[682]	train-mlogloss:1.20614	validation-mlogloss:1.21648
[683]	train-mlogloss:1.20581	validation-mlogloss:1.21633
[684]	train-mlogloss:1.20549	validation-mlogloss:1.21607
[685]	train-mlogloss:1.20518	validation-mlogloss:1.21584
[686]	train-mlogloss:1.20487	validation-mlogloss:1.21568
[687]	train-mlogloss:1.20451	validation-mlogloss:1.21547
[688]	train-mlogloss:1.20420	validation-mlogloss:1.21525
[689]	train-mlogloss:1.20390	validation-mlogloss:1.21507
[690]	train-mlogloss:1.20359	validation-mlogloss:1.21485
[691]	train-mlogloss:1.20327	validation-mlogloss:1.21465
[692]	train-mlogloss:1.20296	validation-mlogloss:1.21448
[693]	train-mlogloss:1.20260	validation-mlogloss:1.21426
[694]	train-mlogloss:1.20223	validation-mlogloss:1.21408
[695]	train-mlogloss:1.20187	validation-mlogloss:1.21383
[696]	train-mlogloss:1.20155	validation-mlogloss:1.21359
[697]	train-mlogloss:1.20120	validation-mlogloss:1.21341
[698]	train-mlogloss:1.20089	validation-mlogloss:1.21324
[699]	train-mlogloss:1.20051	validation-mlogloss:1.21302
[700]	train-mlogloss:1.20022	validation-mlogloss:1.21283
[701]	train-mlogloss:1.19988	validation-mlogloss:1.21262
[702]	train-mlogloss:1.19958	validation-mlogloss:1.21248
[703]	train-mlogloss:1.19924	validation-mlogloss:1.21228
[704]	train-mlogloss:1.19888	validation-mlogloss:1.21208
[705]	train-mlogloss:1.19852	validation-mlogloss:1.21192
[706]	train-mlogloss:1.19819	validation-mlogloss:1.21164
[707]	train-mlogloss:1.19787	validation-mlogloss:1.21146
[708]	train-mlogloss:1.19752	validation-mlogloss:1.21116
[709]	train-mlogloss:1.19721	validation-mlogloss:1.21096
[710]	train-mlogloss:1.19693	validation-mlogloss:1.21074
[711]	train-mlogloss:1.19658	validation-mlogloss:1.21051
[712]	train-mlogloss:1.19623	validation-mlogloss:1.21033
[713]	train-mlogloss:1.19589	validation-mlogloss:1.21006
[714]	train-mlogloss:1.19558	validation-mlogloss:1.20988
[715]	train-mlogloss:1.19525	validation-mlogloss:1.20965
[716]	train-mlogloss:1.19494	validation-mlogloss:1.20947
[717]	train-mlogloss:1.19459	validation-mlogloss:1.20922
[718]	train-mlogloss:1.19429	validation-mlogloss:1.20903
[719]	train-mlogloss:1.19394	validation-mlogloss:1.20881
[720]	train-mlogloss:1.19362	validation-mlogloss:1.20860
[721]	train-mlogloss:1.19332	validation-mlogloss:1.20841
[722]	train-mlogloss:1.19301	validation-mlogloss:1.20820
[723]	train-mlogloss:1.19266	validation-mlogloss:1.20809
[724]	train-mlogloss:1.19234	validation-mlogloss:1.20795
[725]	train-mlogloss:1.19204	validation-mlogloss:1.20775
[726]	train-mlogloss:1.19174	validation-mlogloss:1.20753
[727]	train-mlogloss:1.19144	validation-mlogloss:1.20735
[728]	train-mlogloss:1.19113	validation-mlogloss:1.20718
[729]	train-mlogloss:1.19083	validation-mlogloss:1.20697
[730]	train-mlogloss:1.19051	validation-mlogloss:1.20677
[731]	train-mlogloss:1.19019	validation-mlogloss:1.20657
[732]	train-mlogloss:1.18990	validation-mlogloss:1.20635
[733]	train-mlogloss:1.18961	validation-mlogloss:1.20615
[734]	train-mlogloss:1.18927	validation-mlogloss:1.20593
[735]	train-mlogloss:1.18898	validation-mlogloss:1.20569
[736]	train-mlogloss:1.18866	validation-mlogloss:1.20553
[737]	train-mlogloss:1.18831	validation-mlogloss:1.20535
[738]	train-mlogloss:1.18801	validation-mlogloss:1.20516
[739]	train-mlogloss:1.18768	validation-mlogloss:1.20499
[740]	train-mlogloss:1.18740	validation-mlogloss:1.20480
[741]	train-mlogloss:1.18712	validation-mlogloss:1.20472
[742]	train-mlogloss:1.18683	validation-mlogloss:1.20460
[743]	train-mlogloss:1.18652	validation-mlogloss:1.20445
[744]	train-mlogloss:1.18623	validation-mlogloss:1.20427
[745]	train-mlogloss:1.18597	validation-mlogloss:1.20409
[746]	train-mlogloss:1.18569	validation-mlogloss:1.20390
[747]	train-mlogloss:1.18538	validation-mlogloss:1.20364
[748]	train-mlogloss:1.18509	validation-mlogloss:1.20336
[749]	train-mlogloss:1.18479	validation-mlogloss:1.20314
[750]	train-mlogloss:1.18450	validation-mlogloss:1.20296
[751]	train-mlogloss:1.18422	validation-mlogloss:1.20276
[752]	train-mlogloss:1.18393	validation-mlogloss:1.20253
[753]	train-mlogloss:1.18362	validation-mlogloss:1.20235
[754]	train-mlogloss:1.18329	validation-mlogloss:1.20219
[755]	train-mlogloss:1.18300	validation-mlogloss:1.20204
[756]	train-mlogloss:1.18270	validation-mlogloss:1.20185
[757]	train-mlogloss:1.18240	validation-mlogloss:1.20168
[758]	train-mlogloss:1.18212	validation-mlogloss:1.20155
[759]	train-mlogloss:1.18183	validation-mlogloss:1.20139
[760]	train-mlogloss:1.18150	validation-mlogloss:1.20115
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.54 [%]
Global accuracy score (test) = 58.72 [%]
Global F1 score (train) = 61.09 [%]
Global F1 score (test) = 57.69 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.39      0.22      0.28       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.51      0.43       161
       CAMINAR USUAL SPEED       0.40      0.35      0.38       161
            CAMINAR ZIGZAG       0.43      0.41      0.42       161
          DE PIE BARRIENDO       0.66      0.73      0.70       161
   DE PIE DOBLANDO TOALLAS       0.39      0.41      0.40       161
    DE PIE MOVIENDO LIBROS       0.48      0.49      0.49       161
          DE PIE USANDO PC       0.87      0.87      0.87       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.52      0.36      0.42       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.42      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.61      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 22: 58.72 [%]
F1-score capturado en la ejecución 22: 57.69 [%]

=== EJECUCIÓN 23 ===

--- TRAIN (ejecución 23) ---

--- TEST (ejecución 23) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.69 [%]
Global accuracy score (test) = 59.09 [%]
Global F1 score (train) = 61.23 [%]
Global F1 score (test) = 58.01 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.41      0.24      0.30       161
 CAMINAR CON MÓVIL O LIBRO       0.36      0.52      0.42       161
       CAMINAR USUAL SPEED       0.43      0.35      0.38       161
            CAMINAR ZIGZAG       0.45      0.42      0.43       161
          DE PIE BARRIENDO       0.66      0.75      0.70       161
   DE PIE DOBLANDO TOALLAS       0.40      0.39      0.39       161
    DE PIE MOVIENDO LIBROS       0.48      0.50      0.49       161
          DE PIE USANDO PC       0.87      0.87      0.87       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.51      0.36      0.42       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.42      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.89      0.73       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.59      0.59      0.58      2415
              weighted avg       0.59      0.59      0.58      2415


Accuracy capturado en la ejecución 23: 59.09 [%]
F1-score capturado en la ejecución 23: 58.01 [%]

=== EJECUCIÓN 24 ===

--- TRAIN (ejecución 24) ---

--- TEST (ejecución 24) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.56 [%]
Global accuracy score (test) = 59.13 [%]
Global F1 score (train) = 61.12 [%]
Global F1 score (test) = 58.12 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.40      0.24      0.30       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.53      0.44       161
       CAMINAR USUAL SPEED       0.39      0.34      0.36       161
            CAMINAR ZIGZAG       0.43      0.42      0.43       161
          DE PIE BARRIENDO       0.65      0.73      0.69       161
   DE PIE DOBLANDO TOALLAS       0.40      0.40      0.40       161
    DE PIE MOVIENDO LIBROS       0.49      0.50      0.50       161
          DE PIE USANDO PC       0.84      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.55      0.41      0.47       161
         SENTADO USANDO PC       0.49      0.52      0.50       161
      SENTADO VIENDO LA TV       0.46      0.29      0.35       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.59      0.59      0.58      2415
              weighted avg       0.59      0.59      0.58      2415


Accuracy capturado en la ejecución 24: 59.13 [%]
F1-score capturado en la ejecución 24: 58.12 [%]

=== EJECUCIÓN 25 ===

--- TRAIN (ejecución 25) ---

--- TEST (ejecución 25) ---
2025-11-06 14:15:17.481264: 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`.
2025-11-06 14:15:17.492318: 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 00:00:1762434917.505301 1383696 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434917.509491 1383696 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434917.519226 1383696 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434917.519243 1383696 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434917.519244 1383696 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434917.519245 1383696 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:15:17.522334: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69302	validation-mlogloss:2.69372
[1]	train-mlogloss:2.67860	validation-mlogloss:2.67978
[2]	train-mlogloss:2.66492	validation-mlogloss:2.66607
[3]	train-mlogloss:2.65076	validation-mlogloss:2.65265
[4]	train-mlogloss:2.63723	validation-mlogloss:2.63986
[5]	train-mlogloss:2.62345	validation-mlogloss:2.62663
[6]	train-mlogloss:2.61027	validation-mlogloss:2.61372
[7]	train-mlogloss:2.59719	validation-mlogloss:2.60091
[8]	train-mlogloss:2.58455	validation-mlogloss:2.58899
[9]	train-mlogloss:2.57212	validation-mlogloss:2.57698
[10]	train-mlogloss:2.55976	validation-mlogloss:2.56519
[11]	train-mlogloss:2.54771	validation-mlogloss:2.55362
[12]	train-mlogloss:2.53575	validation-mlogloss:2.54183
[13]	train-mlogloss:2.52442	validation-mlogloss:2.53090
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[734]	train-mlogloss:1.19039	validation-mlogloss:1.20694
[735]	train-mlogloss:1.19002	validation-mlogloss:1.20667
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[737]	train-mlogloss:1.18941	validation-mlogloss:1.20627
[738]	train-mlogloss:1.18913	validation-mlogloss:1.20605
[739]	train-mlogloss:1.18882	validation-mlogloss:1.20584
[740]	train-mlogloss:1.18851	validation-mlogloss:1.20569
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[742]	train-mlogloss:1.18786	validation-mlogloss:1.20531
[743]	train-mlogloss:1.18757	validation-mlogloss:1.20515
[744]	train-mlogloss:1.18731	validation-mlogloss:1.20503
[745]	train-mlogloss:1.18700	validation-mlogloss:1.20486
[746]	train-mlogloss:1.18669	validation-mlogloss:1.20465
[747]	train-mlogloss:1.18640	validation-mlogloss:1.20446
[748]	train-mlogloss:1.18605	validation-mlogloss:1.20429
[749]	train-mlogloss:1.18577	validation-mlogloss:1.20412
[750]	train-mlogloss:1.18542	validation-mlogloss:1.20394
[751]	train-mlogloss:1.18514	validation-mlogloss:1.20381
[752]	train-mlogloss:1.18482	validation-mlogloss:1.20355
[753]	train-mlogloss:1.18455	validation-mlogloss:1.20333
[754]	train-mlogloss:1.18425	validation-mlogloss:1.20315
[755]	train-mlogloss:1.18390	validation-mlogloss:1.20297
[756]	train-mlogloss:1.18363	validation-mlogloss:1.20277
[757]	train-mlogloss:1.18336	validation-mlogloss:1.20266
[758]	train-mlogloss:1.18306	validation-mlogloss:1.20247
[759]	train-mlogloss:1.18272	validation-mlogloss:1.20227
[760]	train-mlogloss:1.18245	validation-mlogloss:1.20214
Saved model to disk.
2025-11-06 14:15:42.254350: 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`.
2025-11-06 14:15:42.265397: 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 00:00:1762434942.278391 1384106 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434942.282449 1384106 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434942.292225 1384106 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434942.292243 1384106 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434942.292245 1384106 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434942.292246 1384106 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:15:42.295368: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
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[1]	train-mlogloss:2.67867	validation-mlogloss:2.67973
[2]	train-mlogloss:2.66429	validation-mlogloss:2.66586
[3]	train-mlogloss:2.65057	validation-mlogloss:2.65262
[4]	train-mlogloss:2.63688	validation-mlogloss:2.64000
[5]	train-mlogloss:2.62332	validation-mlogloss:2.62691
[6]	train-mlogloss:2.61030	validation-mlogloss:2.61429
[7]	train-mlogloss:2.59740	validation-mlogloss:2.60203
[8]	train-mlogloss:2.58452	validation-mlogloss:2.58964
[9]	train-mlogloss:2.57198	validation-mlogloss:2.57747
[10]	train-mlogloss:2.55952	validation-mlogloss:2.56550
[11]	train-mlogloss:2.54738	validation-mlogloss:2.55374
[12]	train-mlogloss:2.53590	validation-mlogloss:2.54277
[13]	train-mlogloss:2.52431	validation-mlogloss:2.53128
[14]	train-mlogloss:2.51274	validation-mlogloss:2.52018
[15]	train-mlogloss:2.50147	validation-mlogloss:2.50924
[16]	train-mlogloss:2.49057	validation-mlogloss:2.49857
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[18]	train-mlogloss:2.46880	validation-mlogloss:2.47777
[19]	train-mlogloss:2.45848	validation-mlogloss:2.46762
[20]	train-mlogloss:2.44776	validation-mlogloss:2.45676
[21]	train-mlogloss:2.43733	validation-mlogloss:2.44681
[22]	train-mlogloss:2.42715	validation-mlogloss:2.43704
[23]	train-mlogloss:2.41731	validation-mlogloss:2.42739
[24]	train-mlogloss:2.40777	validation-mlogloss:2.41805
[25]	train-mlogloss:2.39821	validation-mlogloss:2.40884
[26]	train-mlogloss:2.38866	validation-mlogloss:2.39956
[27]	train-mlogloss:2.37928	validation-mlogloss:2.39066
[28]	train-mlogloss:2.37033	validation-mlogloss:2.38198
[29]	train-mlogloss:2.36135	validation-mlogloss:2.37337
[30]	train-mlogloss:2.35260	validation-mlogloss:2.36464
[31]	train-mlogloss:2.34370	validation-mlogloss:2.35587
[32]	train-mlogloss:2.33518	validation-mlogloss:2.34775
[33]	train-mlogloss:2.32685	validation-mlogloss:2.33964
[34]	train-mlogloss:2.31845	validation-mlogloss:2.33151
[35]	train-mlogloss:2.31031	validation-mlogloss:2.32377
[36]	train-mlogloss:2.30211	validation-mlogloss:2.31579
[37]	train-mlogloss:2.29387	validation-mlogloss:2.30742
[38]	train-mlogloss:2.28593	validation-mlogloss:2.29957
[39]	train-mlogloss:2.27805	validation-mlogloss:2.29180
[40]	train-mlogloss:2.27029	validation-mlogloss:2.28431
[41]	train-mlogloss:2.26273	validation-mlogloss:2.27693
[42]	train-mlogloss:2.25510	validation-mlogloss:2.26948
[43]	train-mlogloss:2.24760	validation-mlogloss:2.26221
[44]	train-mlogloss:2.24025	validation-mlogloss:2.25508
[45]	train-mlogloss:2.23292	validation-mlogloss:2.24783
[46]	train-mlogloss:2.22563	validation-mlogloss:2.24051
[47]	train-mlogloss:2.21819	validation-mlogloss:2.23295
[48]	train-mlogloss:2.21119	validation-mlogloss:2.22612
[49]	train-mlogloss:2.20416	validation-mlogloss:2.21914
[50]	train-mlogloss:2.19707	validation-mlogloss:2.21217
[51]	train-mlogloss:2.19026	validation-mlogloss:2.20535
[52]	train-mlogloss:2.18353	validation-mlogloss:2.19892
[53]	train-mlogloss:2.17677	validation-mlogloss:2.19215
[54]	train-mlogloss:2.16997	validation-mlogloss:2.18523
[55]	train-mlogloss:2.16343	validation-mlogloss:2.17865
[56]	train-mlogloss:2.15690	validation-mlogloss:2.17222
[57]	train-mlogloss:2.15046	validation-mlogloss:2.16577
[58]	train-mlogloss:2.14416	validation-mlogloss:2.15937
[59]	train-mlogloss:2.13804	validation-mlogloss:2.15330
[60]	train-mlogloss:2.13163	validation-mlogloss:2.14662
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[62]	train-mlogloss:2.11937	validation-mlogloss:2.13454
[63]	train-mlogloss:2.11336	validation-mlogloss:2.12850
[64]	train-mlogloss:2.10728	validation-mlogloss:2.12245
[65]	train-mlogloss:2.10130	validation-mlogloss:2.11627
[66]	train-mlogloss:2.09558	validation-mlogloss:2.11045
[67]	train-mlogloss:2.08979	validation-mlogloss:2.10472
[68]	train-mlogloss:2.08408	validation-mlogloss:2.09901
[69]	train-mlogloss:2.07842	validation-mlogloss:2.09311
[70]	train-mlogloss:2.07280	validation-mlogloss:2.08761
[71]	train-mlogloss:2.06716	validation-mlogloss:2.08176
[72]	train-mlogloss:2.06144	validation-mlogloss:2.07599
[73]	train-mlogloss:2.05589	validation-mlogloss:2.07054
[74]	train-mlogloss:2.05054	validation-mlogloss:2.06534
[75]	train-mlogloss:2.04526	validation-mlogloss:2.06001
[76]	train-mlogloss:2.03996	validation-mlogloss:2.05464
[77]	train-mlogloss:2.03475	validation-mlogloss:2.04937
[78]	train-mlogloss:2.02941	validation-mlogloss:2.04397
[79]	train-mlogloss:2.02411	validation-mlogloss:2.03855
[80]	train-mlogloss:2.01897	validation-mlogloss:2.03327
[81]	train-mlogloss:2.01398	validation-mlogloss:2.02828
[82]	train-mlogloss:2.00893	validation-mlogloss:2.02310
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[84]	train-mlogloss:1.99889	validation-mlogloss:2.01294
[85]	train-mlogloss:1.99401	validation-mlogloss:2.00796
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[93]	train-mlogloss:1.95620	validation-mlogloss:1.96930
[94]	train-mlogloss:1.95168	validation-mlogloss:1.96478
[95]	train-mlogloss:1.94709	validation-mlogloss:1.96015
[96]	train-mlogloss:1.94271	validation-mlogloss:1.95565
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[100]	train-mlogloss:1.92519	validation-mlogloss:1.93735
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[102]	train-mlogloss:1.91685	validation-mlogloss:1.92861
[103]	train-mlogloss:1.91260	validation-mlogloss:1.92445
[104]	train-mlogloss:1.90853	validation-mlogloss:1.92021
[105]	train-mlogloss:1.90433	validation-mlogloss:1.91594
[106]	train-mlogloss:1.90017	validation-mlogloss:1.91161
[107]	train-mlogloss:1.89616	validation-mlogloss:1.90756
[108]	train-mlogloss:1.89211	validation-mlogloss:1.90344
[109]	train-mlogloss:1.88771	validation-mlogloss:1.89881
[110]	train-mlogloss:1.88371	validation-mlogloss:1.89458
[111]	train-mlogloss:1.87976	validation-mlogloss:1.89056
[112]	train-mlogloss:1.87577	validation-mlogloss:1.88668
[113]	train-mlogloss:1.87186	validation-mlogloss:1.88267
[114]	train-mlogloss:1.86776	validation-mlogloss:1.87835
[115]	train-mlogloss:1.86373	validation-mlogloss:1.87404
[116]	train-mlogloss:1.86000	validation-mlogloss:1.87027
[117]	train-mlogloss:1.85625	validation-mlogloss:1.86641
[118]	train-mlogloss:1.85256	validation-mlogloss:1.86268
[119]	train-mlogloss:1.84864	validation-mlogloss:1.85854
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[121]	train-mlogloss:1.84150	validation-mlogloss:1.85108
[122]	train-mlogloss:1.83790	validation-mlogloss:1.84742
[123]	train-mlogloss:1.83434	validation-mlogloss:1.84363
[124]	train-mlogloss:1.83090	validation-mlogloss:1.84024
[125]	train-mlogloss:1.82729	validation-mlogloss:1.83646
[126]	train-mlogloss:1.82355	validation-mlogloss:1.83250
[127]	train-mlogloss:1.81980	validation-mlogloss:1.82859
[128]	train-mlogloss:1.81615	validation-mlogloss:1.82473
[129]	train-mlogloss:1.81250	validation-mlogloss:1.82105
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[732]	train-mlogloss:1.19012	validation-mlogloss:1.20659
[733]	train-mlogloss:1.18979	validation-mlogloss:1.20645
[734]	train-mlogloss:1.18947	validation-mlogloss:1.20627
[735]	train-mlogloss:1.18916	validation-mlogloss:1.20609
[736]	train-mlogloss:1.18886	validation-mlogloss:1.20589
[737]	train-mlogloss:1.18855	validation-mlogloss:1.20576
[738]	train-mlogloss:1.18826	validation-mlogloss:1.20555
[739]	train-mlogloss:1.18791	validation-mlogloss:1.20527
[740]	train-mlogloss:1.18760	validation-mlogloss:1.20509
[741]	train-mlogloss:1.18733	validation-mlogloss:1.20498
[742]	train-mlogloss:1.18704	validation-mlogloss:1.20479
[743]	train-mlogloss:1.18675	validation-mlogloss:1.20461
[744]	train-mlogloss:1.18646	validation-mlogloss:1.20443
[745]	train-mlogloss:1.18615	validation-mlogloss:1.20437
[746]	train-mlogloss:1.18587	validation-mlogloss:1.20427
[747]	train-mlogloss:1.18557	validation-mlogloss:1.20408
[748]	train-mlogloss:1.18523	validation-mlogloss:1.20388
[749]	train-mlogloss:1.18490	validation-mlogloss:1.20373
[750]	train-mlogloss:1.18461	validation-mlogloss:1.20352
[751]	train-mlogloss:1.18429	validation-mlogloss:1.20336
[752]	train-mlogloss:1.18401	validation-mlogloss:1.20317
[753]	train-mlogloss:1.18373	validation-mlogloss:1.20300
[754]	train-mlogloss:1.18346	validation-mlogloss:1.20278
[755]	train-mlogloss:1.18314	validation-mlogloss:1.20266
[756]	train-mlogloss:1.18284	validation-mlogloss:1.20251
[757]	train-mlogloss:1.18255	validation-mlogloss:1.20240
[758]	train-mlogloss:1.18225	validation-mlogloss:1.20228
[759]	train-mlogloss:1.18196	validation-mlogloss:1.20207
[760]	train-mlogloss:1.18163	validation-mlogloss:1.20188
Saved model to disk.
2025-11-06 14:16:06.615733: 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`.
2025-11-06 14:16:06.626967: 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 00:00:1762434966.639960 1384510 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434966.643842 1384510 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434966.653958 1384510 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434966.653974 1384510 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434966.653976 1384510 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434966.653978 1384510 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:16:06.657105: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69308	validation-mlogloss:2.69381
[1]	train-mlogloss:2.67865	validation-mlogloss:2.68005
[2]	train-mlogloss:2.66497	validation-mlogloss:2.66685
[3]	train-mlogloss:2.65106	validation-mlogloss:2.65342
[4]	train-mlogloss:2.63779	validation-mlogloss:2.64045
[5]	train-mlogloss:2.62442	validation-mlogloss:2.62762
[6]	train-mlogloss:2.61132	validation-mlogloss:2.61516
[7]	train-mlogloss:2.59814	validation-mlogloss:2.60300
[8]	train-mlogloss:2.58547	validation-mlogloss:2.59099
[9]	train-mlogloss:2.57268	validation-mlogloss:2.57872
[10]	train-mlogloss:2.56058	validation-mlogloss:2.56703
[11]	train-mlogloss:2.54840	validation-mlogloss:2.55521
[12]	train-mlogloss:2.53659	validation-mlogloss:2.54330
[13]	train-mlogloss:2.52495	validation-mlogloss:2.53190
[14]	train-mlogloss:2.51355	validation-mlogloss:2.52111
[15]	train-mlogloss:2.50227	validation-mlogloss:2.51034
[16]	train-mlogloss:2.49102	validation-mlogloss:2.49942
[17]	train-mlogloss:2.48015	validation-mlogloss:2.48883
[18]	train-mlogloss:2.46957	validation-mlogloss:2.47861
[19]	train-mlogloss:2.45913	validation-mlogloss:2.46851
[20]	train-mlogloss:2.44897	validation-mlogloss:2.45853
[21]	train-mlogloss:2.43884	validation-mlogloss:2.44883
[22]	train-mlogloss:2.42880	validation-mlogloss:2.43893
[23]	train-mlogloss:2.41883	validation-mlogloss:2.42927
[24]	train-mlogloss:2.40899	validation-mlogloss:2.41997
[25]	train-mlogloss:2.39943	validation-mlogloss:2.41086
[26]	train-mlogloss:2.39010	validation-mlogloss:2.40193
[27]	train-mlogloss:2.38078	validation-mlogloss:2.39282
[28]	train-mlogloss:2.37153	validation-mlogloss:2.38375
[29]	train-mlogloss:2.36242	validation-mlogloss:2.37490
[30]	train-mlogloss:2.35335	validation-mlogloss:2.36589
[31]	train-mlogloss:2.34458	validation-mlogloss:2.35735
[32]	train-mlogloss:2.33586	validation-mlogloss:2.34873
[33]	train-mlogloss:2.32746	validation-mlogloss:2.34043
[34]	train-mlogloss:2.31890	validation-mlogloss:2.33204
[35]	train-mlogloss:2.31033	validation-mlogloss:2.32354
[36]	train-mlogloss:2.30198	validation-mlogloss:2.31532
[37]	train-mlogloss:2.29409	validation-mlogloss:2.30751
[38]	train-mlogloss:2.28593	validation-mlogloss:2.29952
[39]	train-mlogloss:2.27817	validation-mlogloss:2.29207
[40]	train-mlogloss:2.27039	validation-mlogloss:2.28424
[41]	train-mlogloss:2.26251	validation-mlogloss:2.27646
[42]	train-mlogloss:2.25481	validation-mlogloss:2.26899
[43]	train-mlogloss:2.24741	validation-mlogloss:2.26172
[44]	train-mlogloss:2.24004	validation-mlogloss:2.25436
[45]	train-mlogloss:2.23257	validation-mlogloss:2.24712
[46]	train-mlogloss:2.22529	validation-mlogloss:2.24007
[47]	train-mlogloss:2.21818	validation-mlogloss:2.23311
[48]	train-mlogloss:2.21074	validation-mlogloss:2.22574
[49]	train-mlogloss:2.20375	validation-mlogloss:2.21885
[50]	train-mlogloss:2.19677	validation-mlogloss:2.21188
[51]	train-mlogloss:2.18997	validation-mlogloss:2.20519
[52]	train-mlogloss:2.18307	validation-mlogloss:2.19835
[53]	train-mlogloss:2.17650	validation-mlogloss:2.19203
[54]	train-mlogloss:2.16992	validation-mlogloss:2.18539
[55]	train-mlogloss:2.16337	validation-mlogloss:2.17862
[56]	train-mlogloss:2.15667	validation-mlogloss:2.17216
[57]	train-mlogloss:2.15031	validation-mlogloss:2.16600
[58]	train-mlogloss:2.14398	validation-mlogloss:2.15981
[59]	train-mlogloss:2.13765	validation-mlogloss:2.15335
[60]	train-mlogloss:2.13130	validation-mlogloss:2.14699
[61]	train-mlogloss:2.12529	validation-mlogloss:2.14097
[62]	train-mlogloss:2.11907	validation-mlogloss:2.13456
[63]	train-mlogloss:2.11303	validation-mlogloss:2.12862
[64]	train-mlogloss:2.10718	validation-mlogloss:2.12267
[65]	train-mlogloss:2.10130	validation-mlogloss:2.11680
[66]	train-mlogloss:2.09552	validation-mlogloss:2.11101
[67]	train-mlogloss:2.08977	validation-mlogloss:2.10529
[68]	train-mlogloss:2.08398	validation-mlogloss:2.09948
[69]	train-mlogloss:2.07810	validation-mlogloss:2.09344
[70]	train-mlogloss:2.07222	validation-mlogloss:2.08744
[71]	train-mlogloss:2.06671	validation-mlogloss:2.08198
[72]	train-mlogloss:2.06108	validation-mlogloss:2.07625
[73]	train-mlogloss:2.05558	validation-mlogloss:2.07066
[74]	train-mlogloss:2.05009	validation-mlogloss:2.06502
[75]	train-mlogloss:2.04461	validation-mlogloss:2.05934
[76]	train-mlogloss:2.03933	validation-mlogloss:2.05410
[77]	train-mlogloss:2.03384	validation-mlogloss:2.04844
[78]	train-mlogloss:2.02833	validation-mlogloss:2.04286
[79]	train-mlogloss:2.02307	validation-mlogloss:2.03756
[80]	train-mlogloss:2.01804	validation-mlogloss:2.03239
[81]	train-mlogloss:2.01289	validation-mlogloss:2.02712
[82]	train-mlogloss:2.00790	validation-mlogloss:2.02202
[83]	train-mlogloss:2.00287	validation-mlogloss:2.01686
[84]	train-mlogloss:1.99810	validation-mlogloss:2.01219
[85]	train-mlogloss:1.99318	validation-mlogloss:2.00734
[86]	train-mlogloss:1.98821	validation-mlogloss:2.00230
[87]	train-mlogloss:1.98339	validation-mlogloss:1.99734
[88]	train-mlogloss:1.97871	validation-mlogloss:1.99264
[89]	train-mlogloss:1.97402	validation-mlogloss:1.98785
[90]	train-mlogloss:1.96937	validation-mlogloss:1.98302
[91]	train-mlogloss:1.96479	validation-mlogloss:1.97855
[92]	train-mlogloss:1.96030	validation-mlogloss:1.97410
[93]	train-mlogloss:1.95568	validation-mlogloss:1.96938
[94]	train-mlogloss:1.95119	validation-mlogloss:1.96483
[95]	train-mlogloss:1.94657	validation-mlogloss:1.96012
[96]	train-mlogloss:1.94209	validation-mlogloss:1.95561
[97]	train-mlogloss:1.93764	validation-mlogloss:1.95103
[98]	train-mlogloss:1.93333	validation-mlogloss:1.94661
[99]	train-mlogloss:1.92906	validation-mlogloss:1.94216
[100]	train-mlogloss:1.92473	validation-mlogloss:1.93759
[101]	train-mlogloss:1.92039	validation-mlogloss:1.93309
[102]	train-mlogloss:1.91617	validation-mlogloss:1.92863
[103]	train-mlogloss:1.91192	validation-mlogloss:1.92412
[104]	train-mlogloss:1.90768	validation-mlogloss:1.91982
[105]	train-mlogloss:1.90350	validation-mlogloss:1.91546
[106]	train-mlogloss:1.89936	validation-mlogloss:1.91107
[107]	train-mlogloss:1.89532	validation-mlogloss:1.90683
[108]	train-mlogloss:1.89131	validation-mlogloss:1.90270
[109]	train-mlogloss:1.88728	validation-mlogloss:1.89851
[110]	train-mlogloss:1.88322	validation-mlogloss:1.89439
[111]	train-mlogloss:1.87931	validation-mlogloss:1.89036
[112]	train-mlogloss:1.87541	validation-mlogloss:1.88649
[113]	train-mlogloss:1.87141	validation-mlogloss:1.88246
[114]	train-mlogloss:1.86745	validation-mlogloss:1.87824
[115]	train-mlogloss:1.86369	validation-mlogloss:1.87443
[116]	train-mlogloss:1.85986	validation-mlogloss:1.87062
[117]	train-mlogloss:1.85625	validation-mlogloss:1.86674
[118]	train-mlogloss:1.85247	validation-mlogloss:1.86285
[119]	train-mlogloss:1.84869	validation-mlogloss:1.85910
[120]	train-mlogloss:1.84471	validation-mlogloss:1.85489
[121]	train-mlogloss:1.84112	validation-mlogloss:1.85116
[122]	train-mlogloss:1.83753	validation-mlogloss:1.84740
[123]	train-mlogloss:1.83396	validation-mlogloss:1.84380
[124]	train-mlogloss:1.83038	validation-mlogloss:1.83995
[125]	train-mlogloss:1.82681	validation-mlogloss:1.83623
[126]	train-mlogloss:1.82324	validation-mlogloss:1.83257
[127]	train-mlogloss:1.81979	validation-mlogloss:1.82913
[128]	train-mlogloss:1.81628	validation-mlogloss:1.82543
[129]	train-mlogloss:1.81288	validation-mlogloss:1.82183
[130]	train-mlogloss:1.80948	validation-mlogloss:1.81825
[131]	train-mlogloss:1.80587	validation-mlogloss:1.81441
[132]	train-mlogloss:1.80254	validation-mlogloss:1.81090
[133]	train-mlogloss:1.79924	validation-mlogloss:1.80750
[134]	train-mlogloss:1.79592	validation-mlogloss:1.80401
[135]	train-mlogloss:1.79238	validation-mlogloss:1.80028
[136]	train-mlogloss:1.78919	validation-mlogloss:1.79695
[137]	train-mlogloss:1.78581	validation-mlogloss:1.79341
[138]	train-mlogloss:1.78237	validation-mlogloss:1.78977
[139]	train-mlogloss:1.77902	validation-mlogloss:1.78638
[140]	train-mlogloss:1.77566	validation-mlogloss:1.78280
[141]	train-mlogloss:1.77252	validation-mlogloss:1.77954
[142]	train-mlogloss:1.76940	validation-mlogloss:1.77625
[143]	train-mlogloss:1.76610	validation-mlogloss:1.77281
[144]	train-mlogloss:1.76284	validation-mlogloss:1.76926
[145]	train-mlogloss:1.75988	validation-mlogloss:1.76619
[146]	train-mlogloss:1.75694	validation-mlogloss:1.76307
[147]	train-mlogloss:1.75399	validation-mlogloss:1.76004
[148]	train-mlogloss:1.75110	validation-mlogloss:1.75711
[149]	train-mlogloss:1.74798	validation-mlogloss:1.75390
[150]	train-mlogloss:1.74486	validation-mlogloss:1.75055
[151]	train-mlogloss:1.74170	validation-mlogloss:1.74723
[152]	train-mlogloss:1.73867	validation-mlogloss:1.74409
[153]	train-mlogloss:1.73590	validation-mlogloss:1.74128
[154]	train-mlogloss:1.73313	validation-mlogloss:1.73841
[155]	train-mlogloss:1.73008	validation-mlogloss:1.73519
[156]	train-mlogloss:1.72732	validation-mlogloss:1.73237
[157]	train-mlogloss:1.72455	validation-mlogloss:1.72952
[158]	train-mlogloss:1.72190	validation-mlogloss:1.72668
[159]	train-mlogloss:1.71900	validation-mlogloss:1.72365
[160]	train-mlogloss:1.71621	validation-mlogloss:1.72068
[161]	train-mlogloss:1.71351	validation-mlogloss:1.71779
[162]	train-mlogloss:1.71096	validation-mlogloss:1.71510
[163]	train-mlogloss:1.70813	validation-mlogloss:1.71219
[164]	train-mlogloss:1.70527	validation-mlogloss:1.70912
[165]	train-mlogloss:1.70249	validation-mlogloss:1.70610
[166]	train-mlogloss:1.69970	validation-mlogloss:1.70307
[167]	train-mlogloss:1.69711	validation-mlogloss:1.70037
[168]	train-mlogloss:1.69460	validation-mlogloss:1.69787
[169]	train-mlogloss:1.69186	validation-mlogloss:1.69492
[170]	train-mlogloss:1.68913	validation-mlogloss:1.69207
[171]	train-mlogloss:1.68642	validation-mlogloss:1.68913
[172]	train-mlogloss:1.68384	validation-mlogloss:1.68640
[173]	train-mlogloss:1.68112	validation-mlogloss:1.68358
[174]	train-mlogloss:1.67848	validation-mlogloss:1.68079
[175]	train-mlogloss:1.67585	validation-mlogloss:1.67810
[176]	train-mlogloss:1.67324	validation-mlogloss:1.67543
[177]	train-mlogloss:1.67088	validation-mlogloss:1.67289
[178]	train-mlogloss:1.66825	validation-mlogloss:1.67009
[179]	train-mlogloss:1.66564	validation-mlogloss:1.66733
[180]	train-mlogloss:1.66305	validation-mlogloss:1.66469
[181]	train-mlogloss:1.66055	validation-mlogloss:1.66212
[182]	train-mlogloss:1.65808	validation-mlogloss:1.65950
[183]	train-mlogloss:1.65564	validation-mlogloss:1.65689
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[185]	train-mlogloss:1.65081	validation-mlogloss:1.65188
[186]	train-mlogloss:1.64838	validation-mlogloss:1.64926
[187]	train-mlogloss:1.64602	validation-mlogloss:1.64683
[188]	train-mlogloss:1.64365	validation-mlogloss:1.64430
[189]	train-mlogloss:1.64129	validation-mlogloss:1.64183
[190]	train-mlogloss:1.63897	validation-mlogloss:1.63949
[191]	train-mlogloss:1.63666	validation-mlogloss:1.63708
[192]	train-mlogloss:1.63432	validation-mlogloss:1.63464
[193]	train-mlogloss:1.63192	validation-mlogloss:1.63205
[194]	train-mlogloss:1.62954	validation-mlogloss:1.62954
[195]	train-mlogloss:1.62729	validation-mlogloss:1.62715
[196]	train-mlogloss:1.62497	validation-mlogloss:1.62468
[197]	train-mlogloss:1.62266	validation-mlogloss:1.62220
[198]	train-mlogloss:1.62035	validation-mlogloss:1.61978
[199]	train-mlogloss:1.61814	validation-mlogloss:1.61734
[200]	train-mlogloss:1.61600	validation-mlogloss:1.61508
[201]	train-mlogloss:1.61379	validation-mlogloss:1.61275
[202]	train-mlogloss:1.61157	validation-mlogloss:1.61033
[203]	train-mlogloss:1.60943	validation-mlogloss:1.60803
[204]	train-mlogloss:1.60726	validation-mlogloss:1.60580
[205]	train-mlogloss:1.60511	validation-mlogloss:1.60356
[206]	train-mlogloss:1.60304	validation-mlogloss:1.60138
[207]	train-mlogloss:1.60093	validation-mlogloss:1.59914
[208]	train-mlogloss:1.59878	validation-mlogloss:1.59686
[209]	train-mlogloss:1.59665	validation-mlogloss:1.59459
[210]	train-mlogloss:1.59455	validation-mlogloss:1.59236
[211]	train-mlogloss:1.59247	validation-mlogloss:1.59028
[212]	train-mlogloss:1.59047	validation-mlogloss:1.58815
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[214]	train-mlogloss:1.58633	validation-mlogloss:1.58395
[215]	train-mlogloss:1.58433	validation-mlogloss:1.58196
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[220]	train-mlogloss:1.57452	validation-mlogloss:1.57163
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[549]	train-mlogloss:1.25981	validation-mlogloss:1.25579
[550]	train-mlogloss:1.25933	validation-mlogloss:1.25536
[551]	train-mlogloss:1.25889	validation-mlogloss:1.25507
[552]	train-mlogloss:1.25843	validation-mlogloss:1.25467
[553]	train-mlogloss:1.25797	validation-mlogloss:1.25428
[554]	train-mlogloss:1.25749	validation-mlogloss:1.25392
[555]	train-mlogloss:1.25704	validation-mlogloss:1.25358
[556]	train-mlogloss:1.25660	validation-mlogloss:1.25321
[557]	train-mlogloss:1.25614	validation-mlogloss:1.25286
[558]	train-mlogloss:1.25568	validation-mlogloss:1.25250
[559]	train-mlogloss:1.25524	validation-mlogloss:1.25213
[560]	train-mlogloss:1.25478	validation-mlogloss:1.25180
[561]	train-mlogloss:1.25431	validation-mlogloss:1.25143
[562]	train-mlogloss:1.25386	validation-mlogloss:1.25108
[563]	train-mlogloss:1.25340	validation-mlogloss:1.25075
[564]	train-mlogloss:1.25292	validation-mlogloss:1.25040
[565]	train-mlogloss:1.25249	validation-mlogloss:1.25005
[566]	train-mlogloss:1.25207	validation-mlogloss:1.24967
[567]	train-mlogloss:1.25165	validation-mlogloss:1.24934
[568]	train-mlogloss:1.25121	validation-mlogloss:1.24904
[569]	train-mlogloss:1.25075	validation-mlogloss:1.24870
[570]	train-mlogloss:1.25028	validation-mlogloss:1.24832
[571]	train-mlogloss:1.24984	validation-mlogloss:1.24804
[572]	train-mlogloss:1.24942	validation-mlogloss:1.24770
[573]	train-mlogloss:1.24899	validation-mlogloss:1.24737
[574]	train-mlogloss:1.24857	validation-mlogloss:1.24704
[575]	train-mlogloss:1.24812	validation-mlogloss:1.24667
[576]	train-mlogloss:1.24768	validation-mlogloss:1.24637
[577]	train-mlogloss:1.24725	validation-mlogloss:1.24607
[578]	train-mlogloss:1.24679	validation-mlogloss:1.24574
[579]	train-mlogloss:1.24636	validation-mlogloss:1.24541
[580]	train-mlogloss:1.24585	validation-mlogloss:1.24504
[581]	train-mlogloss:1.24543	validation-mlogloss:1.24473
[582]	train-mlogloss:1.24498	validation-mlogloss:1.24441
[583]	train-mlogloss:1.24452	validation-mlogloss:1.24415
[584]	train-mlogloss:1.24410	validation-mlogloss:1.24378
[585]	train-mlogloss:1.24365	validation-mlogloss:1.24348
[586]	train-mlogloss:1.24317	validation-mlogloss:1.24312
[587]	train-mlogloss:1.24278	validation-mlogloss:1.24285
[588]	train-mlogloss:1.24236	validation-mlogloss:1.24256
[589]	train-mlogloss:1.24192	validation-mlogloss:1.24221
[590]	train-mlogloss:1.24150	validation-mlogloss:1.24184
[591]	train-mlogloss:1.24106	validation-mlogloss:1.24148
[592]	train-mlogloss:1.24057	validation-mlogloss:1.24109
[593]	train-mlogloss:1.24016	validation-mlogloss:1.24075
[594]	train-mlogloss:1.23974	validation-mlogloss:1.24039
[595]	train-mlogloss:1.23932	validation-mlogloss:1.24008
[596]	train-mlogloss:1.23892	validation-mlogloss:1.23975
[597]	train-mlogloss:1.23852	validation-mlogloss:1.23944
[598]	train-mlogloss:1.23807	validation-mlogloss:1.23910
[599]	train-mlogloss:1.23764	validation-mlogloss:1.23874
[600]	train-mlogloss:1.23724	validation-mlogloss:1.23852
[601]	train-mlogloss:1.23682	validation-mlogloss:1.23816
[602]	train-mlogloss:1.23640	validation-mlogloss:1.23787
[603]	train-mlogloss:1.23599	validation-mlogloss:1.23758
[604]	train-mlogloss:1.23556	validation-mlogloss:1.23721
[605]	train-mlogloss:1.23512	validation-mlogloss:1.23687
[606]	train-mlogloss:1.23472	validation-mlogloss:1.23659
[607]	train-mlogloss:1.23433	validation-mlogloss:1.23629
[608]	train-mlogloss:1.23392	validation-mlogloss:1.23594
[609]	train-mlogloss:1.23350	validation-mlogloss:1.23563
[610]	train-mlogloss:1.23313	validation-mlogloss:1.23536
[611]	train-mlogloss:1.23276	validation-mlogloss:1.23511
[612]	train-mlogloss:1.23239	validation-mlogloss:1.23486
[613]	train-mlogloss:1.23198	validation-mlogloss:1.23453
[614]	train-mlogloss:1.23153	validation-mlogloss:1.23419
[615]	train-mlogloss:1.23113	validation-mlogloss:1.23384
[616]	train-mlogloss:1.23076	validation-mlogloss:1.23359
[617]	train-mlogloss:1.23036	validation-mlogloss:1.23331
[618]	train-mlogloss:1.22997	validation-mlogloss:1.23308
[619]	train-mlogloss:1.22961	validation-mlogloss:1.23285
[620]	train-mlogloss:1.22923	validation-mlogloss:1.23251
[621]	train-mlogloss:1.22887	validation-mlogloss:1.23228
[622]	train-mlogloss:1.22847	validation-mlogloss:1.23199
[623]	train-mlogloss:1.22807	validation-mlogloss:1.23172
[624]	train-mlogloss:1.22768	validation-mlogloss:1.23150
[625]	train-mlogloss:1.22729	validation-mlogloss:1.23123
[626]	train-mlogloss:1.22685	validation-mlogloss:1.23091
[627]	train-mlogloss:1.22647	validation-mlogloss:1.23062
[628]	train-mlogloss:1.22610	validation-mlogloss:1.23029
[629]	train-mlogloss:1.22570	validation-mlogloss:1.23004
[630]	train-mlogloss:1.22532	validation-mlogloss:1.22982
[631]	train-mlogloss:1.22492	validation-mlogloss:1.22954
[632]	train-mlogloss:1.22453	validation-mlogloss:1.22924
[633]	train-mlogloss:1.22413	validation-mlogloss:1.22898
[634]	train-mlogloss:1.22375	validation-mlogloss:1.22874
[635]	train-mlogloss:1.22334	validation-mlogloss:1.22846
[636]	train-mlogloss:1.22294	validation-mlogloss:1.22815
[637]	train-mlogloss:1.22252	validation-mlogloss:1.22782
[638]	train-mlogloss:1.22213	validation-mlogloss:1.22753
[639]	train-mlogloss:1.22177	validation-mlogloss:1.22730
[640]	train-mlogloss:1.22135	validation-mlogloss:1.22696
[641]	train-mlogloss:1.22097	validation-mlogloss:1.22662
[642]	train-mlogloss:1.22061	validation-mlogloss:1.22641
[643]	train-mlogloss:1.22025	validation-mlogloss:1.22613
[644]	train-mlogloss:1.21992	validation-mlogloss:1.22586
[645]	train-mlogloss:1.21956	validation-mlogloss:1.22558
[646]	train-mlogloss:1.21918	validation-mlogloss:1.22533
[647]	train-mlogloss:1.21882	validation-mlogloss:1.22509
[648]	train-mlogloss:1.21845	validation-mlogloss:1.22483
[649]	train-mlogloss:1.21808	validation-mlogloss:1.22456
[650]	train-mlogloss:1.21770	validation-mlogloss:1.22428
[651]	train-mlogloss:1.21735	validation-mlogloss:1.22402
[652]	train-mlogloss:1.21700	validation-mlogloss:1.22377
[653]	train-mlogloss:1.21664	validation-mlogloss:1.22356
[654]	train-mlogloss:1.21624	validation-mlogloss:1.22326
[655]	train-mlogloss:1.21585	validation-mlogloss:1.22307
[656]	train-mlogloss:1.21548	validation-mlogloss:1.22281
[657]	train-mlogloss:1.21513	validation-mlogloss:1.22256
[658]	train-mlogloss:1.21481	validation-mlogloss:1.22229
[659]	train-mlogloss:1.21450	validation-mlogloss:1.22206
[660]	train-mlogloss:1.21413	validation-mlogloss:1.22182
[661]	train-mlogloss:1.21377	validation-mlogloss:1.22160
[662]	train-mlogloss:1.21340	validation-mlogloss:1.22137
[663]	train-mlogloss:1.21304	validation-mlogloss:1.22122
[664]	train-mlogloss:1.21269	validation-mlogloss:1.22090
[665]	train-mlogloss:1.21237	validation-mlogloss:1.22067
[666]	train-mlogloss:1.21198	validation-mlogloss:1.22041
[667]	train-mlogloss:1.21162	validation-mlogloss:1.22017
[668]	train-mlogloss:1.21125	validation-mlogloss:1.21996
[669]	train-mlogloss:1.21090	validation-mlogloss:1.21973
[670]	train-mlogloss:1.21060	validation-mlogloss:1.21956
[671]	train-mlogloss:1.21021	validation-mlogloss:1.21930
[672]	train-mlogloss:1.20985	validation-mlogloss:1.21906
[673]	train-mlogloss:1.20951	validation-mlogloss:1.21888
[674]	train-mlogloss:1.20914	validation-mlogloss:1.21865
[675]	train-mlogloss:1.20876	validation-mlogloss:1.21843
[676]	train-mlogloss:1.20840	validation-mlogloss:1.21822
[677]	train-mlogloss:1.20798	validation-mlogloss:1.21791
[678]	train-mlogloss:1.20764	validation-mlogloss:1.21772
[679]	train-mlogloss:1.20733	validation-mlogloss:1.21752
[680]	train-mlogloss:1.20698	validation-mlogloss:1.21726
[681]	train-mlogloss:1.20663	validation-mlogloss:1.21700
[682]	train-mlogloss:1.20626	validation-mlogloss:1.21676
[683]	train-mlogloss:1.20593	validation-mlogloss:1.21658
[684]	train-mlogloss:1.20559	validation-mlogloss:1.21640
[685]	train-mlogloss:1.20525	validation-mlogloss:1.21619
[686]	train-mlogloss:1.20488	validation-mlogloss:1.21597
[687]	train-mlogloss:1.20449	validation-mlogloss:1.21580
[688]	train-mlogloss:1.20416	validation-mlogloss:1.21558
[689]	train-mlogloss:1.20385	validation-mlogloss:1.21541
[690]	train-mlogloss:1.20351	validation-mlogloss:1.21521
[691]	train-mlogloss:1.20314	validation-mlogloss:1.21498
[692]	train-mlogloss:1.20283	validation-mlogloss:1.21478
[693]	train-mlogloss:1.20254	validation-mlogloss:1.21457
[694]	train-mlogloss:1.20223	validation-mlogloss:1.21435
[695]	train-mlogloss:1.20191	validation-mlogloss:1.21415
[696]	train-mlogloss:1.20162	validation-mlogloss:1.21398
[697]	train-mlogloss:1.20131	validation-mlogloss:1.21376
[698]	train-mlogloss:1.20097	validation-mlogloss:1.21348
[699]	train-mlogloss:1.20058	validation-mlogloss:1.21330
[700]	train-mlogloss:1.20022	validation-mlogloss:1.21309
[701]	train-mlogloss:1.19987	validation-mlogloss:1.21291
[702]	train-mlogloss:1.19957	validation-mlogloss:1.21268
[703]	train-mlogloss:1.19924	validation-mlogloss:1.21248
[704]	train-mlogloss:1.19891	validation-mlogloss:1.21225
[705]	train-mlogloss:1.19861	validation-mlogloss:1.21204
[706]	train-mlogloss:1.19826	validation-mlogloss:1.21187
[707]	train-mlogloss:1.19797	validation-mlogloss:1.21166
[708]	train-mlogloss:1.19765	validation-mlogloss:1.21149
[709]	train-mlogloss:1.19734	validation-mlogloss:1.21131
[710]	train-mlogloss:1.19697	validation-mlogloss:1.21115
[711]	train-mlogloss:1.19667	validation-mlogloss:1.21095
[712]	train-mlogloss:1.19632	validation-mlogloss:1.21069
[713]	train-mlogloss:1.19599	validation-mlogloss:1.21043
[714]	train-mlogloss:1.19570	validation-mlogloss:1.21021
[715]	train-mlogloss:1.19538	validation-mlogloss:1.21005
[716]	train-mlogloss:1.19507	validation-mlogloss:1.20992
[717]	train-mlogloss:1.19476	validation-mlogloss:1.20963
[718]	train-mlogloss:1.19445	validation-mlogloss:1.20945
[719]	train-mlogloss:1.19413	validation-mlogloss:1.20926
[720]	train-mlogloss:1.19379	validation-mlogloss:1.20897
[721]	train-mlogloss:1.19345	validation-mlogloss:1.20877
[722]	train-mlogloss:1.19316	validation-mlogloss:1.20858
[723]	train-mlogloss:1.19279	validation-mlogloss:1.20831
[724]	train-mlogloss:1.19244	validation-mlogloss:1.20817
[725]	train-mlogloss:1.19213	validation-mlogloss:1.20797
[726]	train-mlogloss:1.19180	validation-mlogloss:1.20779
[727]	train-mlogloss:1.19151	validation-mlogloss:1.20754
[728]	train-mlogloss:1.19121	validation-mlogloss:1.20735
[729]	train-mlogloss:1.19091	validation-mlogloss:1.20723
[730]	train-mlogloss:1.19059	validation-mlogloss:1.20699
[731]	train-mlogloss:1.19029	validation-mlogloss:1.20676
[732]	train-mlogloss:1.18994	validation-mlogloss:1.20649
[733]	train-mlogloss:1.18960	validation-mlogloss:1.20626
[734]	train-mlogloss:1.18926	validation-mlogloss:1.20609
[735]	train-mlogloss:1.18894	validation-mlogloss:1.20594
[736]	train-mlogloss:1.18866	validation-mlogloss:1.20577
[737]	train-mlogloss:1.18835	validation-mlogloss:1.20559
[738]	train-mlogloss:1.18802	validation-mlogloss:1.20535
[739]	train-mlogloss:1.18772	validation-mlogloss:1.20517
[740]	train-mlogloss:1.18740	validation-mlogloss:1.20499
[741]	train-mlogloss:1.18710	validation-mlogloss:1.20474
[742]	train-mlogloss:1.18678	validation-mlogloss:1.20459
[743]	train-mlogloss:1.18647	validation-mlogloss:1.20433
[744]	train-mlogloss:1.18619	validation-mlogloss:1.20412
[745]	train-mlogloss:1.18591	validation-mlogloss:1.20394
[746]	train-mlogloss:1.18563	validation-mlogloss:1.20377
[747]	train-mlogloss:1.18537	validation-mlogloss:1.20357
[748]	train-mlogloss:1.18505	validation-mlogloss:1.20338
[749]	train-mlogloss:1.18473	validation-mlogloss:1.20321
[750]	train-mlogloss:1.18440	validation-mlogloss:1.20299
[751]	train-mlogloss:1.18412	validation-mlogloss:1.20278
[752]	train-mlogloss:1.18385	validation-mlogloss:1.20258
[753]	train-mlogloss:1.18351	validation-mlogloss:1.20234
[754]	train-mlogloss:1.18322	validation-mlogloss:1.20211
[755]	train-mlogloss:1.18293	validation-mlogloss:1.20200
[756]	train-mlogloss:1.18266	validation-mlogloss:1.20188
[757]	train-mlogloss:1.18240	validation-mlogloss:1.20180
[758]	train-mlogloss:1.18209	validation-mlogloss:1.20163
[759]	train-mlogloss:1.18183	validation-mlogloss:1.20150
[760]	train-mlogloss:1.18154	validation-mlogloss:1.20133
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.56 [%]
Global accuracy score (test) = 58.39 [%]
Global F1 score (train) = 61.11 [%]
Global F1 score (test) = 57.18 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.34      0.19      0.25       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.53      0.44       161
       CAMINAR USUAL SPEED       0.39      0.35      0.37       161
            CAMINAR ZIGZAG       0.43      0.41      0.42       161
          DE PIE BARRIENDO       0.66      0.73      0.69       161
   DE PIE DOBLANDO TOALLAS       0.41      0.42      0.41       161
    DE PIE MOVIENDO LIBROS       0.49      0.50      0.50       161
          DE PIE USANDO PC       0.84      0.87      0.85       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.50      0.34      0.40       161
         SENTADO USANDO PC       0.48      0.53      0.50       161
      SENTADO VIENDO LA TV       0.41      0.27      0.32       161
   SUBIR Y BAJAR ESCALERAS       0.61      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.58      2415
                 macro avg       0.58      0.58      0.57      2415
              weighted avg       0.58      0.58      0.57      2415


Accuracy capturado en la ejecución 25: 58.39 [%]
F1-score capturado en la ejecución 25: 57.18 [%]

=== EJECUCIÓN 26 ===

--- TRAIN (ejecución 26) ---

--- TEST (ejecución 26) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.53 [%]
Global accuracy score (test) = 58.3 [%]
Global F1 score (train) = 61.07 [%]
Global F1 score (test) = 57.21 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.37      0.22      0.28       161
 CAMINAR CON MÓVIL O LIBRO       0.36      0.52      0.42       161
       CAMINAR USUAL SPEED       0.41      0.34      0.37       161
            CAMINAR ZIGZAG       0.41      0.37      0.39       161
          DE PIE BARRIENDO       0.66      0.73      0.70       161
   DE PIE DOBLANDO TOALLAS       0.40      0.41      0.40       161
    DE PIE MOVIENDO LIBROS       0.49      0.50      0.49       161
          DE PIE USANDO PC       0.84      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.95      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.50      0.34      0.41       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.42      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.87      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.58      2415
                 macro avg       0.58      0.58      0.57      2415
              weighted avg       0.58      0.58      0.57      2415


Accuracy capturado en la ejecución 26: 58.3 [%]
F1-score capturado en la ejecución 26: 57.21 [%]

=== EJECUCIÓN 27 ===

--- TRAIN (ejecución 27) ---

--- TEST (ejecución 27) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.61 [%]
Global accuracy score (test) = 58.39 [%]
Global F1 score (train) = 61.19 [%]
Global F1 score (test) = 57.22 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.35      0.20      0.25       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.55      0.45       161
       CAMINAR USUAL SPEED       0.40      0.35      0.37       161
            CAMINAR ZIGZAG       0.44      0.42      0.43       161
          DE PIE BARRIENDO       0.65      0.73      0.69       161
   DE PIE DOBLANDO TOALLAS       0.38      0.39      0.39       161
    DE PIE MOVIENDO LIBROS       0.48      0.50      0.49       161
          DE PIE USANDO PC       0.84      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.81       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.50      0.34      0.41       161
         SENTADO USANDO PC       0.49      0.52      0.50       161
      SENTADO VIENDO LA TV       0.41      0.28      0.33       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.58      2415
                 macro avg       0.58      0.58      0.57      2415
              weighted avg       0.58      0.58      0.57      2415


Accuracy capturado en la ejecución 27: 58.39 [%]
F1-score capturado en la ejecución 27: 57.22 [%]

=== EJECUCIÓN 28 ===

--- TRAIN (ejecución 28) ---

--- TEST (ejecución 28) ---
2025-11-06 14:16:30.993102: 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`.
2025-11-06 14:16:31.004402: 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 00:00:1762434991.017559 1384913 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762434991.021721 1384913 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762434991.031352 1384913 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434991.031370 1384913 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434991.031371 1384913 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762434991.031372 1384913 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:16:31.034505: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69320	validation-mlogloss:2.69364
[1]	train-mlogloss:2.67824	validation-mlogloss:2.67949
[2]	train-mlogloss:2.66405	validation-mlogloss:2.66561
[3]	train-mlogloss:2.65027	validation-mlogloss:2.65250
[4]	train-mlogloss:2.63619	validation-mlogloss:2.63888
[5]	train-mlogloss:2.62279	validation-mlogloss:2.62615
[6]	train-mlogloss:2.60964	validation-mlogloss:2.61360
[7]	train-mlogloss:2.59669	validation-mlogloss:2.60111
[8]	train-mlogloss:2.58395	validation-mlogloss:2.58890
[9]	train-mlogloss:2.57176	validation-mlogloss:2.57738
[10]	train-mlogloss:2.55954	validation-mlogloss:2.56570
[11]	train-mlogloss:2.54737	validation-mlogloss:2.55392
[12]	train-mlogloss:2.53548	validation-mlogloss:2.54258
[13]	train-mlogloss:2.52391	validation-mlogloss:2.53138
[14]	train-mlogloss:2.51254	validation-mlogloss:2.52030
[15]	train-mlogloss:2.50157	validation-mlogloss:2.50948
[16]	train-mlogloss:2.49064	validation-mlogloss:2.49897
[17]	train-mlogloss:2.47985	validation-mlogloss:2.48850
[18]	train-mlogloss:2.46916	validation-mlogloss:2.47834
[19]	train-mlogloss:2.45849	validation-mlogloss:2.46798
[20]	train-mlogloss:2.44795	validation-mlogloss:2.45763
[21]	train-mlogloss:2.43794	validation-mlogloss:2.44802
[22]	train-mlogloss:2.42800	validation-mlogloss:2.43864
[23]	train-mlogloss:2.41797	validation-mlogloss:2.42866
[24]	train-mlogloss:2.40828	validation-mlogloss:2.41944
[25]	train-mlogloss:2.39893	validation-mlogloss:2.41062
[26]	train-mlogloss:2.38938	validation-mlogloss:2.40124
[27]	train-mlogloss:2.37997	validation-mlogloss:2.39174
[28]	train-mlogloss:2.37068	validation-mlogloss:2.38267
[29]	train-mlogloss:2.36160	validation-mlogloss:2.37391
[30]	train-mlogloss:2.35271	validation-mlogloss:2.36531
[31]	train-mlogloss:2.34410	validation-mlogloss:2.35687
[32]	train-mlogloss:2.33555	validation-mlogloss:2.34885
[33]	train-mlogloss:2.32687	validation-mlogloss:2.34035
[34]	train-mlogloss:2.31833	validation-mlogloss:2.33216
[35]	train-mlogloss:2.31010	validation-mlogloss:2.32420
[36]	train-mlogloss:2.30201	validation-mlogloss:2.31634
[37]	train-mlogloss:2.29398	validation-mlogloss:2.30840
[38]	train-mlogloss:2.28606	validation-mlogloss:2.30068
[39]	train-mlogloss:2.27791	validation-mlogloss:2.29233
[40]	train-mlogloss:2.27009	validation-mlogloss:2.28471
[41]	train-mlogloss:2.26241	validation-mlogloss:2.27740
[42]	train-mlogloss:2.25477	validation-mlogloss:2.27011
[43]	train-mlogloss:2.24750	validation-mlogloss:2.26310
[44]	train-mlogloss:2.24013	validation-mlogloss:2.25578
[45]	train-mlogloss:2.23281	validation-mlogloss:2.24879
[46]	train-mlogloss:2.22531	validation-mlogloss:2.24101
[47]	train-mlogloss:2.21823	validation-mlogloss:2.23414
[48]	train-mlogloss:2.21113	validation-mlogloss:2.22722
[49]	train-mlogloss:2.20412	validation-mlogloss:2.22036
[50]	train-mlogloss:2.19740	validation-mlogloss:2.21370
[51]	train-mlogloss:2.19059	validation-mlogloss:2.20692
[52]	train-mlogloss:2.18382	validation-mlogloss:2.20000
[53]	train-mlogloss:2.17707	validation-mlogloss:2.19332
[54]	train-mlogloss:2.17017	validation-mlogloss:2.18654
[55]	train-mlogloss:2.16354	validation-mlogloss:2.17995
[56]	train-mlogloss:2.15707	validation-mlogloss:2.17371
[57]	train-mlogloss:2.15078	validation-mlogloss:2.16763
[58]	train-mlogloss:2.14452	validation-mlogloss:2.16114
[59]	train-mlogloss:2.13823	validation-mlogloss:2.15469
[60]	train-mlogloss:2.13192	validation-mlogloss:2.14835
[61]	train-mlogloss:2.12563	validation-mlogloss:2.14178
[62]	train-mlogloss:2.11941	validation-mlogloss:2.13548
[63]	train-mlogloss:2.11348	validation-mlogloss:2.12973
[64]	train-mlogloss:2.10770	validation-mlogloss:2.12408
[65]	train-mlogloss:2.10182	validation-mlogloss:2.11810
[66]	train-mlogloss:2.09602	validation-mlogloss:2.11225
[67]	train-mlogloss:2.09030	validation-mlogloss:2.10664
[68]	train-mlogloss:2.08467	validation-mlogloss:2.10085
[69]	train-mlogloss:2.07880	validation-mlogloss:2.09492
[70]	train-mlogloss:2.07306	validation-mlogloss:2.08888
[71]	train-mlogloss:2.06742	validation-mlogloss:2.08321
[72]	train-mlogloss:2.06197	validation-mlogloss:2.07783
[73]	train-mlogloss:2.05635	validation-mlogloss:2.07202
[74]	train-mlogloss:2.05098	validation-mlogloss:2.06657
[75]	train-mlogloss:2.04567	validation-mlogloss:2.06136
[76]	train-mlogloss:2.04036	validation-mlogloss:2.05594
[77]	train-mlogloss:2.03504	validation-mlogloss:2.05041
[78]	train-mlogloss:2.02985	validation-mlogloss:2.04532
[79]	train-mlogloss:2.02455	validation-mlogloss:2.03975
[80]	train-mlogloss:2.01941	validation-mlogloss:2.03446
[81]	train-mlogloss:2.01403	validation-mlogloss:2.02889
[82]	train-mlogloss:2.00890	validation-mlogloss:2.02357
[83]	train-mlogloss:2.00391	validation-mlogloss:2.01840
[84]	train-mlogloss:1.99880	validation-mlogloss:2.01307
[85]	train-mlogloss:1.99376	validation-mlogloss:2.00795
[86]	train-mlogloss:1.98891	validation-mlogloss:2.00306
[87]	train-mlogloss:1.98415	validation-mlogloss:1.99824
[88]	train-mlogloss:1.97935	validation-mlogloss:1.99352
[89]	train-mlogloss:1.97454	validation-mlogloss:1.98859
[90]	train-mlogloss:1.96971	validation-mlogloss:1.98366
[91]	train-mlogloss:1.96508	validation-mlogloss:1.97891
[92]	train-mlogloss:1.96046	validation-mlogloss:1.97404
[93]	train-mlogloss:1.95589	validation-mlogloss:1.96938
[94]	train-mlogloss:1.95132	validation-mlogloss:1.96477
[95]	train-mlogloss:1.94680	validation-mlogloss:1.96012
[96]	train-mlogloss:1.94226	validation-mlogloss:1.95550
[97]	train-mlogloss:1.93793	validation-mlogloss:1.95100
[98]	train-mlogloss:1.93360	validation-mlogloss:1.94646
[99]	train-mlogloss:1.92925	validation-mlogloss:1.94200
[100]	train-mlogloss:1.92504	validation-mlogloss:1.93760
[101]	train-mlogloss:1.92079	validation-mlogloss:1.93324
[102]	train-mlogloss:1.91658	validation-mlogloss:1.92881
[103]	train-mlogloss:1.91225	validation-mlogloss:1.92434
[104]	train-mlogloss:1.90808	validation-mlogloss:1.92013
[105]	train-mlogloss:1.90392	validation-mlogloss:1.91594
[106]	train-mlogloss:1.89981	validation-mlogloss:1.91166
[107]	train-mlogloss:1.89579	validation-mlogloss:1.90770
[108]	train-mlogloss:1.89169	validation-mlogloss:1.90348
[109]	train-mlogloss:1.88771	validation-mlogloss:1.89949
[110]	train-mlogloss:1.88380	validation-mlogloss:1.89559
[111]	train-mlogloss:1.87978	validation-mlogloss:1.89145
[112]	train-mlogloss:1.87588	validation-mlogloss:1.88749
[113]	train-mlogloss:1.87188	validation-mlogloss:1.88336
[114]	train-mlogloss:1.86796	validation-mlogloss:1.87924
[115]	train-mlogloss:1.86426	validation-mlogloss:1.87532
[116]	train-mlogloss:1.86047	validation-mlogloss:1.87131
[117]	train-mlogloss:1.85664	validation-mlogloss:1.86730
[118]	train-mlogloss:1.85291	validation-mlogloss:1.86355
[119]	train-mlogloss:1.84920	validation-mlogloss:1.85970
[120]	train-mlogloss:1.84557	validation-mlogloss:1.85595
[121]	train-mlogloss:1.84193	validation-mlogloss:1.85215
[122]	train-mlogloss:1.83828	validation-mlogloss:1.84844
[123]	train-mlogloss:1.83469	validation-mlogloss:1.84485
[124]	train-mlogloss:1.83116	validation-mlogloss:1.84116
[125]	train-mlogloss:1.82762	validation-mlogloss:1.83750
[126]	train-mlogloss:1.82403	validation-mlogloss:1.83385
[127]	train-mlogloss:1.82033	validation-mlogloss:1.82997
[128]	train-mlogloss:1.81669	validation-mlogloss:1.82610
[129]	train-mlogloss:1.81328	validation-mlogloss:1.82253
[130]	train-mlogloss:1.80957	validation-mlogloss:1.81862
[131]	train-mlogloss:1.80620	validation-mlogloss:1.81512
[132]	train-mlogloss:1.80263	validation-mlogloss:1.81142
[133]	train-mlogloss:1.79912	validation-mlogloss:1.80768
[134]	train-mlogloss:1.79552	validation-mlogloss:1.80401
[135]	train-mlogloss:1.79228	validation-mlogloss:1.80048
[136]	train-mlogloss:1.78906	validation-mlogloss:1.79707
[137]	train-mlogloss:1.78585	validation-mlogloss:1.79367
[138]	train-mlogloss:1.78263	validation-mlogloss:1.79022
[139]	train-mlogloss:1.77926	validation-mlogloss:1.78666
[140]	train-mlogloss:1.77611	validation-mlogloss:1.78347
[141]	train-mlogloss:1.77302	validation-mlogloss:1.78021
[142]	train-mlogloss:1.76995	validation-mlogloss:1.77715
[143]	train-mlogloss:1.76677	validation-mlogloss:1.77387
[144]	train-mlogloss:1.76377	validation-mlogloss:1.77072
[145]	train-mlogloss:1.76069	validation-mlogloss:1.76748
[146]	train-mlogloss:1.75767	validation-mlogloss:1.76421
[147]	train-mlogloss:1.75449	validation-mlogloss:1.76080
[148]	train-mlogloss:1.75124	validation-mlogloss:1.75745
[149]	train-mlogloss:1.74833	validation-mlogloss:1.75438
[150]	train-mlogloss:1.74542	validation-mlogloss:1.75133
[151]	train-mlogloss:1.74256	validation-mlogloss:1.74834
[152]	train-mlogloss:1.73955	validation-mlogloss:1.74525
[153]	train-mlogloss:1.73657	validation-mlogloss:1.74219
[154]	train-mlogloss:1.73375	validation-mlogloss:1.73922
[155]	train-mlogloss:1.73070	validation-mlogloss:1.73604
[156]	train-mlogloss:1.72785	validation-mlogloss:1.73299
[157]	train-mlogloss:1.72491	validation-mlogloss:1.72999
[158]	train-mlogloss:1.72216	validation-mlogloss:1.72719
[159]	train-mlogloss:1.71922	validation-mlogloss:1.72403
[160]	train-mlogloss:1.71649	validation-mlogloss:1.72126
[161]	train-mlogloss:1.71367	validation-mlogloss:1.71828
[162]	train-mlogloss:1.71082	validation-mlogloss:1.71524
[163]	train-mlogloss:1.70824	validation-mlogloss:1.71240
[164]	train-mlogloss:1.70535	validation-mlogloss:1.70931
[165]	train-mlogloss:1.70252	validation-mlogloss:1.70638
[166]	train-mlogloss:1.69965	validation-mlogloss:1.70334
[167]	train-mlogloss:1.69680	validation-mlogloss:1.70033
[168]	train-mlogloss:1.69410	validation-mlogloss:1.69756
[169]	train-mlogloss:1.69142	validation-mlogloss:1.69461
[170]	train-mlogloss:1.68865	validation-mlogloss:1.69181
[171]	train-mlogloss:1.68601	validation-mlogloss:1.68901
[172]	train-mlogloss:1.68332	validation-mlogloss:1.68614
[173]	train-mlogloss:1.68068	validation-mlogloss:1.68339
[174]	train-mlogloss:1.67798	validation-mlogloss:1.68062
[175]	train-mlogloss:1.67530	validation-mlogloss:1.67786
[176]	train-mlogloss:1.67272	validation-mlogloss:1.67511
[177]	train-mlogloss:1.67010	validation-mlogloss:1.67241
[178]	train-mlogloss:1.66754	validation-mlogloss:1.66983
[179]	train-mlogloss:1.66499	validation-mlogloss:1.66719
[180]	train-mlogloss:1.66246	validation-mlogloss:1.66449
[181]	train-mlogloss:1.65996	validation-mlogloss:1.66185
[182]	train-mlogloss:1.65743	validation-mlogloss:1.65912
[183]	train-mlogloss:1.65492	validation-mlogloss:1.65647
[184]	train-mlogloss:1.65237	validation-mlogloss:1.65371
[185]	train-mlogloss:1.64992	validation-mlogloss:1.65114
[186]	train-mlogloss:1.64750	validation-mlogloss:1.64854
[187]	train-mlogloss:1.64504	validation-mlogloss:1.64596
[188]	train-mlogloss:1.64269	validation-mlogloss:1.64355
[189]	train-mlogloss:1.64033	validation-mlogloss:1.64104
[190]	train-mlogloss:1.63810	validation-mlogloss:1.63867
[191]	train-mlogloss:1.63579	validation-mlogloss:1.63624
[192]	train-mlogloss:1.63346	validation-mlogloss:1.63372
[193]	train-mlogloss:1.63121	validation-mlogloss:1.63138
[194]	train-mlogloss:1.62891	validation-mlogloss:1.62897
[195]	train-mlogloss:1.62667	validation-mlogloss:1.62654
[196]	train-mlogloss:1.62434	validation-mlogloss:1.62425
[197]	train-mlogloss:1.62211	validation-mlogloss:1.62194
[198]	train-mlogloss:1.61984	validation-mlogloss:1.61950
[199]	train-mlogloss:1.61757	validation-mlogloss:1.61710
[200]	train-mlogloss:1.61528	validation-mlogloss:1.61483
[201]	train-mlogloss:1.61307	validation-mlogloss:1.61246
[202]	train-mlogloss:1.61089	validation-mlogloss:1.61011
[203]	train-mlogloss:1.60872	validation-mlogloss:1.60774
[204]	train-mlogloss:1.60654	validation-mlogloss:1.60543
[205]	train-mlogloss:1.60437	validation-mlogloss:1.60324
[206]	train-mlogloss:1.60223	validation-mlogloss:1.60101
[207]	train-mlogloss:1.60011	validation-mlogloss:1.59874
[208]	train-mlogloss:1.59794	validation-mlogloss:1.59659
[209]	train-mlogloss:1.59586	validation-mlogloss:1.59435
[210]	train-mlogloss:1.59376	validation-mlogloss:1.59217
[211]	train-mlogloss:1.59173	validation-mlogloss:1.59009
[212]	train-mlogloss:1.58970	validation-mlogloss:1.58803
[213]	train-mlogloss:1.58758	validation-mlogloss:1.58588
[214]	train-mlogloss:1.58551	validation-mlogloss:1.58364
[215]	train-mlogloss:1.58344	validation-mlogloss:1.58152
[216]	train-mlogloss:1.58142	validation-mlogloss:1.57928
[217]	train-mlogloss:1.57942	validation-mlogloss:1.57722
[218]	train-mlogloss:1.57748	validation-mlogloss:1.57514
[219]	train-mlogloss:1.57547	validation-mlogloss:1.57300
[220]	train-mlogloss:1.57354	validation-mlogloss:1.57089
[221]	train-mlogloss:1.57164	validation-mlogloss:1.56888
[222]	train-mlogloss:1.56978	validation-mlogloss:1.56697
[223]	train-mlogloss:1.56787	validation-mlogloss:1.56493
[224]	train-mlogloss:1.56597	validation-mlogloss:1.56294
[225]	train-mlogloss:1.56406	validation-mlogloss:1.56095
[226]	train-mlogloss:1.56211	validation-mlogloss:1.55883
[227]	train-mlogloss:1.56021	validation-mlogloss:1.55671
[228]	train-mlogloss:1.55839	validation-mlogloss:1.55478
[229]	train-mlogloss:1.55657	validation-mlogloss:1.55277
[230]	train-mlogloss:1.55474	validation-mlogloss:1.55082
[231]	train-mlogloss:1.55291	validation-mlogloss:1.54885
[232]	train-mlogloss:1.55111	validation-mlogloss:1.54696
[233]	train-mlogloss:1.54927	validation-mlogloss:1.54502
[234]	train-mlogloss:1.54753	validation-mlogloss:1.54317
[235]	train-mlogloss:1.54573	validation-mlogloss:1.54123
[236]	train-mlogloss:1.54398	validation-mlogloss:1.53938
[237]	train-mlogloss:1.54226	validation-mlogloss:1.53762
[238]	train-mlogloss:1.54055	validation-mlogloss:1.53586
[239]	train-mlogloss:1.53883	validation-mlogloss:1.53411
[240]	train-mlogloss:1.53713	validation-mlogloss:1.53238
[241]	train-mlogloss:1.53544	validation-mlogloss:1.53065
[242]	train-mlogloss:1.53369	validation-mlogloss:1.52884
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[713]	train-mlogloss:1.19596	validation-mlogloss:1.21029
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[716]	train-mlogloss:1.19492	validation-mlogloss:1.20965
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[720]	train-mlogloss:1.19364	validation-mlogloss:1.20891
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[725]	train-mlogloss:1.19205	validation-mlogloss:1.20794
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[728]	train-mlogloss:1.19110	validation-mlogloss:1.20738
[729]	train-mlogloss:1.19078	validation-mlogloss:1.20723
[730]	train-mlogloss:1.19042	validation-mlogloss:1.20694
[731]	train-mlogloss:1.19011	validation-mlogloss:1.20674
[732]	train-mlogloss:1.18981	validation-mlogloss:1.20650
[733]	train-mlogloss:1.18952	validation-mlogloss:1.20633
[734]	train-mlogloss:1.18925	validation-mlogloss:1.20616
[735]	train-mlogloss:1.18894	validation-mlogloss:1.20600
[736]	train-mlogloss:1.18860	validation-mlogloss:1.20587
[737]	train-mlogloss:1.18831	validation-mlogloss:1.20573
[738]	train-mlogloss:1.18797	validation-mlogloss:1.20558
[739]	train-mlogloss:1.18768	validation-mlogloss:1.20541
[740]	train-mlogloss:1.18738	validation-mlogloss:1.20523
[741]	train-mlogloss:1.18708	validation-mlogloss:1.20499
[742]	train-mlogloss:1.18679	validation-mlogloss:1.20483
[743]	train-mlogloss:1.18654	validation-mlogloss:1.20462
[744]	train-mlogloss:1.18624	validation-mlogloss:1.20438
[745]	train-mlogloss:1.18596	validation-mlogloss:1.20420
[746]	train-mlogloss:1.18568	validation-mlogloss:1.20405
[747]	train-mlogloss:1.18544	validation-mlogloss:1.20387
[748]	train-mlogloss:1.18516	validation-mlogloss:1.20373
[749]	train-mlogloss:1.18485	validation-mlogloss:1.20360
[750]	train-mlogloss:1.18453	validation-mlogloss:1.20342
[751]	train-mlogloss:1.18421	validation-mlogloss:1.20326
[752]	train-mlogloss:1.18393	validation-mlogloss:1.20310
[753]	train-mlogloss:1.18363	validation-mlogloss:1.20300
[754]	train-mlogloss:1.18332	validation-mlogloss:1.20281
[755]	train-mlogloss:1.18301	validation-mlogloss:1.20266
[756]	train-mlogloss:1.18269	validation-mlogloss:1.20248
[757]	train-mlogloss:1.18242	validation-mlogloss:1.20235
[758]	train-mlogloss:1.18213	validation-mlogloss:1.20222
[759]	train-mlogloss:1.18184	validation-mlogloss:1.20206
[760]	train-mlogloss:1.18157	validation-mlogloss:1.20187
Saved model to disk.
2025-11-06 14:16:55.151586: 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`.
2025-11-06 14:16:55.162957: 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 00:00:1762435015.177150 1385300 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762435015.181584 1385300 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762435015.192108 1385300 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762435015.192126 1385300 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762435015.192128 1385300 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762435015.192130 1385300 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 14:16:55.195414: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
1 GPU(s) detected and VRAM set to crossover mode..
Training a non-convolutional model.
[0]	train-mlogloss:2.69341	validation-mlogloss:2.69367
[1]	train-mlogloss:2.67943	validation-mlogloss:2.67993
[2]	train-mlogloss:2.66500	validation-mlogloss:2.66613
[3]	train-mlogloss:2.65114	validation-mlogloss:2.65274
[4]	train-mlogloss:2.63750	validation-mlogloss:2.63971
[5]	train-mlogloss:2.62378	validation-mlogloss:2.62643
[6]	train-mlogloss:2.61070	validation-mlogloss:2.61369
[7]	train-mlogloss:2.59761	validation-mlogloss:2.60115
[8]	train-mlogloss:2.58478	validation-mlogloss:2.58871
[9]	train-mlogloss:2.57225	validation-mlogloss:2.57679
[10]	train-mlogloss:2.55984	validation-mlogloss:2.56498
[11]	train-mlogloss:2.54788	validation-mlogloss:2.55356
[12]	train-mlogloss:2.53594	validation-mlogloss:2.54222
[13]	train-mlogloss:2.52404	validation-mlogloss:2.53080
[14]	train-mlogloss:2.51240	validation-mlogloss:2.51964
[15]	train-mlogloss:2.50139	validation-mlogloss:2.50891
[16]	train-mlogloss:2.49025	validation-mlogloss:2.49801
[17]	train-mlogloss:2.47948	validation-mlogloss:2.48763
[18]	train-mlogloss:2.46894	validation-mlogloss:2.47747
[19]	train-mlogloss:2.45829	validation-mlogloss:2.46692
[20]	train-mlogloss:2.44783	validation-mlogloss:2.45685
[21]	train-mlogloss:2.43764	validation-mlogloss:2.44686
[22]	train-mlogloss:2.42768	validation-mlogloss:2.43750
[23]	train-mlogloss:2.41785	validation-mlogloss:2.42805
[24]	train-mlogloss:2.40822	validation-mlogloss:2.41881
[25]	train-mlogloss:2.39850	validation-mlogloss:2.40922
[26]	train-mlogloss:2.38905	validation-mlogloss:2.39992
[27]	train-mlogloss:2.37976	validation-mlogloss:2.39101
[28]	train-mlogloss:2.37079	validation-mlogloss:2.38239
[29]	train-mlogloss:2.36195	validation-mlogloss:2.37376
[30]	train-mlogloss:2.35310	validation-mlogloss:2.36512
[31]	train-mlogloss:2.34447	validation-mlogloss:2.35669
[32]	train-mlogloss:2.33588	validation-mlogloss:2.34853
[33]	train-mlogloss:2.32733	validation-mlogloss:2.34038
[34]	train-mlogloss:2.31889	validation-mlogloss:2.33227
[35]	train-mlogloss:2.31068	validation-mlogloss:2.32418
[36]	train-mlogloss:2.30238	validation-mlogloss:2.31614
[37]	train-mlogloss:2.29445	validation-mlogloss:2.30834
[38]	train-mlogloss:2.28649	validation-mlogloss:2.30049
[39]	train-mlogloss:2.27884	validation-mlogloss:2.29307
[40]	train-mlogloss:2.27118	validation-mlogloss:2.28542
[41]	train-mlogloss:2.26323	validation-mlogloss:2.27746
[42]	train-mlogloss:2.25552	validation-mlogloss:2.26971
[43]	train-mlogloss:2.24801	validation-mlogloss:2.26229
[44]	train-mlogloss:2.24052	validation-mlogloss:2.25492
[45]	train-mlogloss:2.23287	validation-mlogloss:2.24725
[46]	train-mlogloss:2.22551	validation-mlogloss:2.24022
[47]	train-mlogloss:2.21830	validation-mlogloss:2.23326
[48]	train-mlogloss:2.21119	validation-mlogloss:2.22622
[49]	train-mlogloss:2.20403	validation-mlogloss:2.21932
[50]	train-mlogloss:2.19693	validation-mlogloss:2.21231
[51]	train-mlogloss:2.19008	validation-mlogloss:2.20567
[52]	train-mlogloss:2.18354	validation-mlogloss:2.19937
[53]	train-mlogloss:2.17682	validation-mlogloss:2.19279
[54]	train-mlogloss:2.17049	validation-mlogloss:2.18676
[55]	train-mlogloss:2.16391	validation-mlogloss:2.18025
[56]	train-mlogloss:2.15745	validation-mlogloss:2.17400
[57]	train-mlogloss:2.15107	validation-mlogloss:2.16752
[58]	train-mlogloss:2.14487	validation-mlogloss:2.16129
[59]	train-mlogloss:2.13859	validation-mlogloss:2.15513
[60]	train-mlogloss:2.13229	validation-mlogloss:2.14871
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[662]	train-mlogloss:1.21318	validation-mlogloss:1.22163
[663]	train-mlogloss:1.21283	validation-mlogloss:1.22144
[664]	train-mlogloss:1.21250	validation-mlogloss:1.22121
[665]	train-mlogloss:1.21213	validation-mlogloss:1.22092
[666]	train-mlogloss:1.21177	validation-mlogloss:1.22073
[667]	train-mlogloss:1.21143	validation-mlogloss:1.22047
[668]	train-mlogloss:1.21108	validation-mlogloss:1.22025
[669]	train-mlogloss:1.21074	validation-mlogloss:1.21996
[670]	train-mlogloss:1.21042	validation-mlogloss:1.21973
[671]	train-mlogloss:1.21009	validation-mlogloss:1.21954
[672]	train-mlogloss:1.20975	validation-mlogloss:1.21929
[673]	train-mlogloss:1.20943	validation-mlogloss:1.21908
[674]	train-mlogloss:1.20910	validation-mlogloss:1.21883
[675]	train-mlogloss:1.20876	validation-mlogloss:1.21857
[676]	train-mlogloss:1.20844	validation-mlogloss:1.21836
[677]	train-mlogloss:1.20811	validation-mlogloss:1.21818
[678]	train-mlogloss:1.20775	validation-mlogloss:1.21787
[679]	train-mlogloss:1.20740	validation-mlogloss:1.21762
[680]	train-mlogloss:1.20707	validation-mlogloss:1.21742
[681]	train-mlogloss:1.20676	validation-mlogloss:1.21714
[682]	train-mlogloss:1.20644	validation-mlogloss:1.21690
[683]	train-mlogloss:1.20608	validation-mlogloss:1.21665
[684]	train-mlogloss:1.20572	validation-mlogloss:1.21652
[685]	train-mlogloss:1.20538	validation-mlogloss:1.21633
[686]	train-mlogloss:1.20507	validation-mlogloss:1.21610
[687]	train-mlogloss:1.20472	validation-mlogloss:1.21593
[688]	train-mlogloss:1.20439	validation-mlogloss:1.21569
[689]	train-mlogloss:1.20407	validation-mlogloss:1.21545
[690]	train-mlogloss:1.20373	validation-mlogloss:1.21517
[691]	train-mlogloss:1.20341	validation-mlogloss:1.21500
[692]	train-mlogloss:1.20305	validation-mlogloss:1.21476
[693]	train-mlogloss:1.20274	validation-mlogloss:1.21453
[694]	train-mlogloss:1.20240	validation-mlogloss:1.21429
[695]	train-mlogloss:1.20204	validation-mlogloss:1.21404
[696]	train-mlogloss:1.20170	validation-mlogloss:1.21374
[697]	train-mlogloss:1.20135	validation-mlogloss:1.21358
[698]	train-mlogloss:1.20103	validation-mlogloss:1.21337
[699]	train-mlogloss:1.20069	validation-mlogloss:1.21313
[700]	train-mlogloss:1.20036	validation-mlogloss:1.21292
[701]	train-mlogloss:1.19999	validation-mlogloss:1.21268
[702]	train-mlogloss:1.19966	validation-mlogloss:1.21245
[703]	train-mlogloss:1.19934	validation-mlogloss:1.21224
[704]	train-mlogloss:1.19900	validation-mlogloss:1.21210
[705]	train-mlogloss:1.19869	validation-mlogloss:1.21185
[706]	train-mlogloss:1.19839	validation-mlogloss:1.21162
[707]	train-mlogloss:1.19808	validation-mlogloss:1.21153
[708]	train-mlogloss:1.19775	validation-mlogloss:1.21142
[709]	train-mlogloss:1.19745	validation-mlogloss:1.21121
[710]	train-mlogloss:1.19714	validation-mlogloss:1.21101
[711]	train-mlogloss:1.19684	validation-mlogloss:1.21081
[712]	train-mlogloss:1.19652	validation-mlogloss:1.21061
[713]	train-mlogloss:1.19618	validation-mlogloss:1.21045
[714]	train-mlogloss:1.19587	validation-mlogloss:1.21032
[715]	train-mlogloss:1.19554	validation-mlogloss:1.21010
[716]	train-mlogloss:1.19520	validation-mlogloss:1.20992
[717]	train-mlogloss:1.19490	validation-mlogloss:1.20967
[718]	train-mlogloss:1.19452	validation-mlogloss:1.20953
[719]	train-mlogloss:1.19419	validation-mlogloss:1.20935
[720]	train-mlogloss:1.19387	validation-mlogloss:1.20914
[721]	train-mlogloss:1.19352	validation-mlogloss:1.20896
[722]	train-mlogloss:1.19321	validation-mlogloss:1.20876
[723]	train-mlogloss:1.19292	validation-mlogloss:1.20862
[724]	train-mlogloss:1.19264	validation-mlogloss:1.20841
[725]	train-mlogloss:1.19228	validation-mlogloss:1.20821
[726]	train-mlogloss:1.19196	validation-mlogloss:1.20800
[727]	train-mlogloss:1.19165	validation-mlogloss:1.20788
[728]	train-mlogloss:1.19133	validation-mlogloss:1.20775
[729]	train-mlogloss:1.19103	validation-mlogloss:1.20761
[730]	train-mlogloss:1.19071	validation-mlogloss:1.20740
[731]	train-mlogloss:1.19039	validation-mlogloss:1.20714
[732]	train-mlogloss:1.19006	validation-mlogloss:1.20692
[733]	train-mlogloss:1.18978	validation-mlogloss:1.20674
[734]	train-mlogloss:1.18948	validation-mlogloss:1.20654
[735]	train-mlogloss:1.18917	validation-mlogloss:1.20635
[736]	train-mlogloss:1.18891	validation-mlogloss:1.20619
[737]	train-mlogloss:1.18856	validation-mlogloss:1.20591
[738]	train-mlogloss:1.18826	validation-mlogloss:1.20575
[739]	train-mlogloss:1.18796	validation-mlogloss:1.20560
[740]	train-mlogloss:1.18767	validation-mlogloss:1.20541
[741]	train-mlogloss:1.18735	validation-mlogloss:1.20524
[742]	train-mlogloss:1.18709	validation-mlogloss:1.20506
[743]	train-mlogloss:1.18682	validation-mlogloss:1.20486
[744]	train-mlogloss:1.18651	validation-mlogloss:1.20470
[745]	train-mlogloss:1.18626	validation-mlogloss:1.20456
[746]	train-mlogloss:1.18597	validation-mlogloss:1.20435
[747]	train-mlogloss:1.18573	validation-mlogloss:1.20420
[748]	train-mlogloss:1.18539	validation-mlogloss:1.20391
[749]	train-mlogloss:1.18508	validation-mlogloss:1.20376
[750]	train-mlogloss:1.18481	validation-mlogloss:1.20348
[751]	train-mlogloss:1.18453	validation-mlogloss:1.20330
[752]	train-mlogloss:1.18424	validation-mlogloss:1.20315
[753]	train-mlogloss:1.18397	validation-mlogloss:1.20297
[754]	train-mlogloss:1.18369	validation-mlogloss:1.20277
[755]	train-mlogloss:1.18337	validation-mlogloss:1.20267
[756]	train-mlogloss:1.18309	validation-mlogloss:1.20253
[757]	train-mlogloss:1.18282	validation-mlogloss:1.20235
[758]	train-mlogloss:1.18249	validation-mlogloss:1.20216
[759]	train-mlogloss:1.18217	validation-mlogloss:1.20201
[760]	train-mlogloss:1.18188	validation-mlogloss:1.20184
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.63 [%]
Global accuracy score (test) = 58.72 [%]
Global F1 score (train) = 61.17 [%]
Global F1 score (test) = 57.5 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.36      0.19      0.25       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.53      0.44       161
       CAMINAR USUAL SPEED       0.40      0.36      0.38       161
            CAMINAR ZIGZAG       0.42      0.41      0.42       161
          DE PIE BARRIENDO       0.66      0.74      0.70       161
   DE PIE DOBLANDO TOALLAS       0.41      0.42      0.41       161
    DE PIE MOVIENDO LIBROS       0.49      0.50      0.50       161
          DE PIE USANDO PC       0.85      0.89      0.87       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.50      0.35      0.41       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.41      0.27      0.32       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 28: 58.72 [%]
F1-score capturado en la ejecución 28: 57.5 [%]

=== EJECUCIÓN 29 ===

--- TRAIN (ejecución 29) ---

--- TEST (ejecución 29) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.55 [%]
Global accuracy score (test) = 58.8 [%]
Global F1 score (train) = 61.1 [%]
Global F1 score (test) = 57.77 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.36      0.23      0.28       161
 CAMINAR CON MÓVIL O LIBRO       0.37      0.51      0.43       161
       CAMINAR USUAL SPEED       0.40      0.34      0.37       161
            CAMINAR ZIGZAG       0.43      0.41      0.42       161
          DE PIE BARRIENDO       0.66      0.73      0.69       161
   DE PIE DOBLANDO TOALLAS       0.40      0.39      0.39       161
    DE PIE MOVIENDO LIBROS       0.49      0.51      0.50       161
          DE PIE USANDO PC       0.87      0.89      0.88       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.53      0.38      0.44       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.43      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.86      0.72       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.59      2415
                 macro avg       0.58      0.59      0.58      2415
              weighted avg       0.58      0.59      0.58      2415


Accuracy capturado en la ejecución 29: 58.8 [%]
F1-score capturado en la ejecución 29: 57.77 [%]

=== EJECUCIÓN 30 ===

--- TRAIN (ejecución 30) ---

--- TEST (ejecución 30) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2415, 42)
(17135, 42)
[[ 8.]
 [ 8.]
 [ 8.]
 ...
 [11.]
 [11.]
 [11.]]
(2415, 1)
[ 8  8  8 ... 12  5  7]
(2415,)
-------------------------------------------------

Global accuracy score (train) = 61.6 [%]
Global accuracy score (test) = 58.47 [%]
Global F1 score (train) = 61.15 [%]
Global F1 score (test) = 57.35 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.35      0.20      0.26       161
 CAMINAR CON MÓVIL O LIBRO       0.38      0.53      0.44       161
       CAMINAR USUAL SPEED       0.40      0.35      0.38       161
            CAMINAR ZIGZAG       0.42      0.39      0.40       161
          DE PIE BARRIENDO       0.66      0.74      0.70       161
   DE PIE DOBLANDO TOALLAS       0.38      0.39      0.39       161
    DE PIE MOVIENDO LIBROS       0.48      0.48      0.48       161
          DE PIE USANDO PC       0.86      0.87      0.86       161
        FASE REPOSO CON K5       0.71      0.96      0.82       161
INCREMENTAL CICLOERGOMETRO       0.99      0.98      0.98       161
           SENTADO LEYENDO       0.52      0.36      0.43       161
         SENTADO USANDO PC       0.49      0.53      0.51       161
      SENTADO VIENDO LA TV       0.42      0.28      0.34       161
   SUBIR Y BAJAR ESCALERAS       0.62      0.87      0.73       161
                    TROTAR       0.98      0.83      0.90       161

                  accuracy                           0.58      2415
                 macro avg       0.58      0.58      0.57      2415
              weighted avg       0.58      0.58      0.57      2415


Accuracy capturado en la ejecución 30: 58.47 [%]
F1-score capturado en la ejecución 30: 57.35 [%]

=== RESUMEN FINAL ===
Accuracies: [58.59, 58.67, 58.47, 58.26, 58.55, 58.63, 58.88, 58.67, 58.84, 58.67, 59.01, 59.01, 58.55, 58.3, 58.8, 58.88, 58.67, 59.01, 58.84, 59.05, 58.34, 58.72, 59.09, 59.13, 58.39, 58.3, 58.39, 58.72, 58.8, 58.47]
F1-scores: [57.49, 57.62, 57.28, 57.1, 57.41, 57.51, 57.76, 57.57, 57.87, 57.53, 57.83, 57.79, 57.41, 57.1, 57.61, 57.82, 57.51, 57.86, 57.71, 57.99, 57.32, 57.69, 58.01, 58.12, 57.18, 57.21, 57.22, 57.5, 57.77, 57.35]
Accuracy mean: 58.6900 | std: 0.2501
F1 mean: 57.5713 | std: 0.2740

Resultados guardados en /mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_PI/case_PI_XGB_acc_17_classes/metrics_test.npz
