2025-11-06 21:42:21.378853: 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 21:42:21.390621: 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 00:00:1762461741.403854 1819997 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762461741.407933 1819997 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762461741.417969 1819997 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461741.417990 1819997 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461741.417992 1819997 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461741.417993 1819997 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:42:21.421015: 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 21:42:28,953	INFO worker.py:1927 -- Started a local Ray instance.
2025-11-06 21:42:29,682	INFO tune.py:253 -- Initializing Ray automatically. For cluster usage or custom Ray initialization, call `ray.init(...)` before `Tuner(...)`.
2025-11-06 21:42:29,751	INFO trial.py:182 -- Creating a new dirname dir_1cb55_7c57 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,754	INFO trial.py:182 -- Creating a new dirname dir_1cb55_e8c9 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,756	INFO trial.py:182 -- Creating a new dirname dir_1cb55_4290 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,759	INFO trial.py:182 -- Creating a new dirname dir_1cb55_2c62 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,762	INFO trial.py:182 -- Creating a new dirname dir_1cb55_b96f because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,764	INFO trial.py:182 -- Creating a new dirname dir_1cb55_a43b because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,767	INFO trial.py:182 -- Creating a new dirname dir_1cb55_bd70 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,769	INFO trial.py:182 -- Creating a new dirname dir_1cb55_fe53 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,773	INFO trial.py:182 -- Creating a new dirname dir_1cb55_80ee because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,775	INFO trial.py:182 -- Creating a new dirname dir_1cb55_e560 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,778	INFO trial.py:182 -- Creating a new dirname dir_1cb55_8535 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,781	INFO trial.py:182 -- Creating a new dirname dir_1cb55_2e32 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,784	INFO trial.py:182 -- Creating a new dirname dir_1cb55_5b7b because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,788	INFO trial.py:182 -- Creating a new dirname dir_1cb55_a6a5 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,791	INFO trial.py:182 -- Creating a new dirname dir_1cb55_a5d9 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,794	INFO trial.py:182 -- Creating a new dirname dir_1cb55_3f78 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,798	INFO trial.py:182 -- Creating a new dirname dir_1cb55_d212 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,804	INFO trial.py:182 -- Creating a new dirname dir_1cb55_8134 because trial dirname 'dir_1cb55' already exists.
2025-11-06 21:42:29,813	INFO trial.py:182 -- Creating a new dirname dir_1cb55_cf10 because trial dirname 'dir_1cb55' 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_M/case_M_XGB_acc_17_classes/XGBoost_hyperparameters_tuning
To visualize your results with TensorBoard, run: `tensorboard --logdir /tmp/ray/session_2025-11-06_21-42-28_245878_1819997/artifacts/2025-11-06_21-42-29/XGBoost_hyperparameters_tuning/driver_artifacts`

Trial status: 20 PENDING
Current time: 2025-11-06 21:42:29. Total running time: 0s
Logical resource usage: 0/20 CPUs, 0/1 GPUs (0.0/1.0 accelerator_type:G)
╭──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ Trial name     status       num_boost_round     max_depth     learning_rate     subsample     colsample_bytree      gamma     min_child_weight     reg_alpha     reg_lambda     random_state │
├──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ trial_1cb55    PENDING                  754             3        0.00708953      0.572333             0.571419   23.2246                    63       1.1888        43.7925              5319 │
│ trial_1cb55    PENDING                  271             3        0.0190181       0.628713             0.644453    5.39879                  116      50.2256        13.9432              1016 │
│ trial_1cb55    PENDING                  420             2        0.0114507       0.674775             0.784948   16.1511                   138       1.94599       25.0934              4910 │
│ trial_1cb55    PENDING                  315             3        0.0185528       0.750404             0.640788   16.2339                   132       5.66557      699.33                4881 │
│ trial_1cb55    PENDING                  671             3        0.00656652      0.840697             0.632676   20.0238                   175     146.659         14.3622              1766 │
│ trial_1cb55    PENDING                  261             3        0.0079232       0.695251             0.679307   14.9999                   149       3.29567      351.316                773 │
│ trial_1cb55    PENDING                  448             3        0.015063        0.548208             0.634636   15.8129                   114     413.067          8.48831             9642 │
│ trial_1cb55    PENDING                  407             3        0.00839124      0.623236             0.585971   14.2771                   141      99.7363        36.3844              8847 │
│ trial_1cb55    PENDING                  533             2        0.0159374       0.671786             0.754294   17.6281                   107      26.8082       366.449               9665 │
│ trial_1cb55    PENDING                  595             3        0.012221        0.64406              0.601166   27.5846                   147      21.8054         8.5704              3985 │
│ trial_1cb55    PENDING                  259             2        0.0162511       0.636471             0.73363    19.5734                    84     200.438        106.568               5001 │
│ trial_1cb55    PENDING                  226             2        0.0109774       0.771305             0.792725   22.4585                    91      46.6636        52.4725              1090 │
│ trial_1cb55    PENDING                  345             2        0.00624441      0.839356             0.5687     19.6342                   156       8.55672       25.9994              7299 │
│ trial_1cb55    PENDING                  545             3        0.0194414       0.759991             0.501904    6.50189                   61     860.959        756.382               6475 │
│ trial_1cb55    PENDING                  672             3        0.018443        0.848987             0.786135   16.1061                   189     250.383        109.728               3866 │
│ trial_1cb55    PENDING                  733             3        0.0143482       0.737584             0.823754   28.6324                   109      71.6413       494.079               1372 │
│ trial_1cb55    PENDING                  720             2        0.015517        0.706389             0.597535   28.2665                   146     322.046         42.6044              9545 │
│ trial_1cb55    PENDING                  718             3        0.00997422      0.696604             0.679719   29.37                      83       6.04013       21.9013              3622 │
│ trial_1cb55    PENDING                  386             2        0.0118711       0.536963             0.683892   14.8021                    69     231.759         24.4769              6579 │
│ trial_1cb55    PENDING                  799             2        0.00999408      0.501305             0.843765   28.8012                   121       6.57783        5.49196             4707 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.78614 │
│ gamma                        16.1061 │
│ learning_rate                0.01844 │
│ max_depth                          3 │
│ min_child_weight                 189 │
│ num_boost_round                  672 │
│ random_state                    3866 │
│ reg_alpha                    250.383 │
│ reg_lambda                   109.728 │
│ subsample                    0.84899 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree              0.5019 │
│ gamma                        6.50189 │
│ learning_rate                0.01944 │
│ max_depth                          3 │
│ min_child_weight                  61 │
│ num_boost_round                  545 │
│ random_state                    6475 │
│ reg_alpha                    860.959 │
│ reg_lambda                   756.382 │
│ subsample                    0.75999 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.67972 │
│ gamma                          29.37 │
│ learning_rate                0.00997 │
│ max_depth                          3 │
│ min_child_weight                  83 │
│ num_boost_round                  718 │
│ random_state                    3622 │
│ reg_alpha                    6.04013 │
│ reg_lambda                   21.9013 │
│ subsample                     0.6966 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.75429 │
│ gamma                        17.6281 │
│ learning_rate                0.01594 │
│ max_depth                          2 │
│ min_child_weight                 107 │
│ num_boost_round                  533 │
│ random_state                    9665 │
│ reg_alpha                    26.8082 │
│ reg_lambda                   366.449 │
│ subsample                    0.67179 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.78495 │
│ gamma                        16.1511 │
│ learning_rate                0.01145 │
│ max_depth                          2 │
│ min_child_weight                 138 │
│ num_boost_round                  420 │
│ random_state                    4910 │
│ reg_alpha                    1.94599 │
│ reg_lambda                   25.0934 │
│ subsample                    0.67478 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.68389 │
│ gamma                        14.8021 │
│ learning_rate                0.01187 │
│ max_depth                          2 │
│ min_child_weight                  69 │
│ num_boost_round                  386 │
│ random_state                    6579 │
│ reg_alpha                    231.759 │
│ reg_lambda                   24.4769 │
│ subsample                    0.53696 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.64445 │
│ gamma                        5.39879 │
│ learning_rate                0.01902 │
│ max_depth                          3 │
│ min_child_weight                 116 │
│ num_boost_round                  271 │
│ random_state                    1016 │
│ reg_alpha                    50.2256 │
│ reg_lambda                   13.9432 │
│ subsample                    0.62871 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.64079 │
│ gamma                        16.2339 │
│ learning_rate                0.01855 │
│ max_depth                          3 │
│ min_child_weight                 132 │
│ num_boost_round                  315 │
│ random_state                    4881 │
│ reg_alpha                    5.66557 │
│ reg_lambda                    699.33 │
│ subsample                     0.7504 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree              0.5687 │
│ gamma                        19.6342 │
│ learning_rate                0.00624 │
│ max_depth                          2 │
│ min_child_weight                 156 │
│ num_boost_round                  345 │
│ random_state                    7299 │
│ reg_alpha                    8.55672 │
│ reg_lambda                   25.9994 │
│ subsample                    0.83936 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.57142 │
│ gamma                        23.2246 │
│ learning_rate                0.00709 │
│ max_depth                          3 │
│ min_child_weight                  63 │
│ num_boost_round                  754 │
│ random_state                    5319 │
│ reg_alpha                     1.1888 │
│ reg_lambda                   43.7925 │
│ subsample                    0.57233 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.63268 │
│ gamma                        20.0238 │
│ learning_rate                0.00657 │
│ max_depth                          3 │
│ min_child_weight                 175 │
│ num_boost_round                  671 │
│ random_state                    1766 │
│ reg_alpha                    146.659 │
│ reg_lambda                   14.3622 │
│ subsample                     0.8407 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.60117 │
│ gamma                        27.5846 │
│ learning_rate                0.01222 │
│ max_depth                          3 │
│ min_child_weight                 147 │
│ num_boost_round                  595 │
│ random_state                    3985 │
│ reg_alpha                    21.8054 │
│ reg_lambda                    8.5704 │
│ subsample                    0.64406 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.82375 │
│ gamma                        28.6324 │
│ learning_rate                0.01435 │
│ max_depth                          3 │
│ min_child_weight                 109 │
│ num_boost_round                  733 │
│ random_state                    1372 │
│ reg_alpha                    71.6413 │
│ reg_lambda                   494.079 │
│ subsample                    0.73758 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.63464 │
│ gamma                        15.8129 │
│ learning_rate                0.01506 │
│ max_depth                          3 │
│ min_child_weight                 114 │
│ num_boost_round                  448 │
│ random_state                    9642 │
│ reg_alpha                    413.067 │
│ reg_lambda                   8.48831 │
│ subsample                    0.54821 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.58597 │
│ gamma                        14.2771 │
│ learning_rate                0.00839 │
│ max_depth                          3 │
│ min_child_weight                 141 │
│ num_boost_round                  407 │
│ random_state                    8847 │
│ reg_alpha                    99.7363 │
│ reg_lambda                   36.3844 │
│ subsample                    0.62324 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.59753 │
│ gamma                        28.2665 │
│ learning_rate                0.01552 │
│ max_depth                          2 │
│ min_child_weight                 146 │
│ num_boost_round                  720 │
│ random_state                    9545 │
│ reg_alpha                    322.046 │
│ reg_lambda                   42.6044 │
│ subsample                    0.70639 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.73363 │
│ gamma                        19.5734 │
│ learning_rate                0.01625 │
│ max_depth                          2 │
│ min_child_weight                  84 │
│ num_boost_round                  259 │
│ random_state                    5001 │
│ reg_alpha                    200.438 │
│ reg_lambda                   106.568 │
│ subsample                    0.63647 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.84376 │
│ gamma                        28.8012 │
│ learning_rate                0.00999 │
│ max_depth                          2 │
│ min_child_weight                 121 │
│ num_boost_round                  799 │
│ random_state                    4707 │
│ reg_alpha                    6.57783 │
│ reg_lambda                   5.49196 │
│ subsample                     0.5013 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
[36m(train_xgb_ray_tune pid=1821687)[0m 2025-11-06 21:42:33.057622: 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=1821687)[0m 2025-11-06 21:42:33.079320: 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=1821682)[0m WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
[36m(train_xgb_ray_tune pid=1821682)[0m E0000 00:00:1762461753.076424 1822799 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=1821682)[0m E0000 00:00:1762461753.084585 1822799 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=1821682)[0m W0000 00:00:1762461753.104567 1822799 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=1821682)[0m W0000 00:00:1762461753.104616 1822799 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=1821682)[0m W0000 00:00:1762461753.104618 1822799 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=1821682)[0m W0000 00:00:1762461753.104621 1822799 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=1821682)[0m 2025-11-06 21:42:33.110860: 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=1821682)[0m To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.79273 │
│ gamma                        22.4585 │
│ learning_rate                0.01098 │
│ max_depth                          2 │
│ min_child_weight                  91 │
│ num_boost_round                  226 │
│ random_state                    1090 │
│ reg_alpha                    46.6636 │
│ reg_lambda                   52.4725 │
│ subsample                    0.77131 │
╰──────────────────────────────────────╯
Trial trial_1cb55 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_1cb55 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.67931 │
│ gamma                        14.9999 │
│ learning_rate                0.00792 │
│ max_depth                          3 │
│ min_child_weight                 149 │
│ num_boost_round                  261 │
│ random_state                     773 │
│ reg_alpha                    3.29567 │
│ reg_lambda                   351.316 │
│ subsample                    0.69525 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1821682)[0m [0]	train-mlogloss:2.70385	validation-mlogloss:2.70393
[36m(train_xgb_ray_tune pid=1821682)[0m [1]	train-mlogloss:2.69962	validation-mlogloss:2.69995
[36m(train_xgb_ray_tune pid=1821687)[0m [0]	train-mlogloss:2.70307	validation-mlogloss:2.70266
[36m(train_xgb_ray_tune pid=1821687)[0m [1]	train-mlogloss:2.69823	validation-mlogloss:2.69743
[36m(train_xgb_ray_tune pid=1821680)[0m [0]	train-mlogloss:2.69948	validation-mlogloss:2.69883
[36m(train_xgb_ray_tune pid=1821680)[0m [1]	train-mlogloss:2.69107	validation-mlogloss:2.68970
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[36m(train_xgb_ray_tune pid=1821673)[0m [12]	train-mlogloss:2.68870	validation-mlogloss:2.69108
[36m(train_xgb_ray_tune pid=1821688)[0m [5]	train-mlogloss:2.66798	validation-mlogloss:2.66458
[36m(train_xgb_ray_tune pid=1821663)[0m [6]	train-mlogloss:2.67152	validation-mlogloss:2.66761
[36m(train_xgb_ray_tune pid=1821691)[0m [5]	train-mlogloss:2.66170	validation-mlogloss:2.65907
[36m(train_xgb_ray_tune pid=1821680)[0m [12]	train-mlogloss:2.60559	validation-mlogloss:2.59656
[36m(train_xgb_ray_tune pid=1821692)[0m [15]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1821692)[0m [16]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1821689)[0m [9]	train-mlogloss:2.66663	validation-mlogloss:2.66304
[36m(train_xgb_ray_tune pid=1821688)[0m [6]	train-mlogloss:2.66186	validation-mlogloss:2.65767
[36m(train_xgb_ray_tune pid=1821672)[0m [5]	train-mlogloss:2.63732	validation-mlogloss:2.63107
[36m(train_xgb_ray_tune pid=1821671)[0m [7]	train-mlogloss:2.68652	validation-mlogloss:2.68566
[36m(train_xgb_ray_tune pid=1821669)[0m [10]	train-mlogloss:2.65923	validation-mlogloss:2.65698
[36m(train_xgb_ray_tune pid=1821690)[0m [9]	train-mlogloss:2.69177	validation-mlogloss:2.69358
[36m(train_xgb_ray_tune pid=1821690)[0m [10]	train-mlogloss:2.69025	validation-mlogloss:2.69222
[36m(train_xgb_ray_tune pid=1821686)[0m [8]	train-mlogloss:2.68069	validation-mlogloss:2.68008
[36m(train_xgb_ray_tune pid=1821685)[0m [7]	train-mlogloss:2.68477	validation-mlogloss:2.68631
[36m(train_xgb_ray_tune pid=1821673)[0m [13]	train-mlogloss:2.68750	validation-mlogloss:2.69002
[36m(train_xgb_ray_tune pid=1821682)[0m [16]	train-mlogloss:2.64178	validation-mlogloss:2.64407
[36m(train_xgb_ray_tune pid=1821687)[0m [14]	train-mlogloss:2.63877	validation-mlogloss:2.63419
[36m(train_xgb_ray_tune pid=1821687)[0m [15]	train-mlogloss:2.63444	validation-mlogloss:2.62964
[36m(train_xgb_ray_tune pid=1821670)[0m [6]	train-mlogloss:2.65574	validation-mlogloss:2.65135
[36m(train_xgb_ray_tune pid=1821684)[0m [6]	train-mlogloss:2.68354	validation-mlogloss:2.68302
[36m(train_xgb_ray_tune pid=1821684)[0m [7]	train-mlogloss:2.68000	validation-mlogloss:2.67909
[36m(train_xgb_ray_tune pid=1821681)[0m [6]	train-mlogloss:2.70785	validation-mlogloss:2.70785
[36m(train_xgb_ray_tune pid=1821681)[0m [7]	train-mlogloss:2.70785	validation-mlogloss:2.70785
[36m(train_xgb_ray_tune pid=1821674)[0m [6]	train-mlogloss:2.66647	validation-mlogloss:2.66231
[36m(train_xgb_ray_tune pid=1821683)[0m [9]	train-mlogloss:2.67543	validation-mlogloss:2.67398
[36m(train_xgb_ray_tune pid=1821691)[0m [6]	train-mlogloss:2.65455	validation-mlogloss:2.65150
[36m(train_xgb_ray_tune pid=1821680)[0m [13]	train-mlogloss:2.59825	validation-mlogloss:2.58863
[36m(train_xgb_ray_tune pid=1821673)[0m [14]	train-mlogloss:2.68643	validation-mlogloss:2.68914
[36m(train_xgb_ray_tune pid=1821682)[0m [17]	train-mlogloss:2.63838	validation-mlogloss:2.64078
[36m(train_xgb_ray_tune pid=1821674)[0m [7]	train-mlogloss:2.66021	validation-mlogloss:2.65556
[36m(train_xgb_ray_tune pid=1821663)[0m [7]	train-mlogloss:2.66657	validation-mlogloss:2.66210
[36m(train_xgb_ray_tune pid=1821692)[0m [17]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1821689)[0m [10]	train-mlogloss:2.66262	validation-mlogloss:2.65873
[36m(train_xgb_ray_tune pid=1821685)[0m [8]	train-mlogloss:2.68187	validation-mlogloss:2.68357
[36m(train_xgb_ray_tune pid=1821681)[0m [8]	train-mlogloss:2.70785	validation-mlogloss:2.70785
[36m(train_xgb_ray_tune pid=1821670)[0m [7]	train-mlogloss:2.64828	validation-mlogloss:2.64345
[36m(train_xgb_ray_tune pid=1821683)[0m [10]	train-mlogloss:2.67230	validation-mlogloss:2.67071
[36m(train_xgb_ray_tune pid=1821688)[0m [7]	train-mlogloss:2.65573	validation-mlogloss:2.65083
[36m(train_xgb_ray_tune pid=1821672)[0m [6]	train-mlogloss:2.62580	validation-mlogloss:2.61864
[36m(train_xgb_ray_tune pid=1821671)[0m [8]	train-mlogloss:2.68382	validation-mlogloss:2.68292
[36m(train_xgb_ray_tune pid=1821686)[0m [9]	train-mlogloss:2.67780	validation-mlogloss:2.67723
[36m(train_xgb_ray_tune pid=1821684)[0m [8]	train-mlogloss:2.67667	validation-mlogloss:2.67565
[36m(train_xgb_ray_tune pid=1821669)[0m [11]	train-mlogloss:2.65495	validation-mlogloss:2.65251
[36m(train_xgb_ray_tune pid=1821673)[0m [15]	train-mlogloss:2.68512	validation-mlogloss:2.68794
[36m(train_xgb_ray_tune pid=1821692)[0m [18]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1821690)[0m [11]	train-mlogloss:2.68880	validation-mlogloss:2.69086
[36m(train_xgb_ray_tune pid=1821663)[0m [8]	train-mlogloss:2.66163	validation-mlogloss:2.65691
[36m(train_xgb_ray_tune pid=1821691)[0m [7]	train-mlogloss:2.64711	validation-mlogloss:2.64343
[36m(train_xgb_ray_tune pid=1821691)[0m [8]	train-mlogloss:2.63924	validation-mlogloss:2.63496
[36m(train_xgb_ray_tune pid=1821680)[0m [14]	train-mlogloss:2.59102	validation-mlogloss:2.58123
[36m(train_xgb_ray_tune pid=1821692)[0m [19]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1821689)[0m [11]	train-mlogloss:2.65914	validation-mlogloss:2.65484
[36m(train_xgb_ray_tune pid=1821688)[0m [8]	train-mlogloss:2.64972	validation-mlogloss:2.64449
[36m(train_xgb_ray_tune pid=1821672)[0m [7]	train-mlogloss:2.61514	validation-mlogloss:2.60718
[36m(train_xgb_ray_tune pid=1821671)[0m [9]	train-mlogloss:2.68110	validation-mlogloss:2.68009
[36m(train_xgb_ray_tune pid=1821669)[0m [12]	train-mlogloss:2.65078	validation-mlogloss:2.64808
[36m(train_xgb_ray_tune pid=1821690)[0m [12]	train-mlogloss:2.68734	validation-mlogloss:2.68949
[36m(train_xgb_ray_tune pid=1821686)[0m [10]	train-mlogloss:2.67493	validation-mlogloss:2.67432
[36m(train_xgb_ray_tune pid=1821685)[0m [9]	train-mlogloss:2.67890	validation-mlogloss:2.68074
[36m(train_xgb_ray_tune pid=1821692)[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=1821692)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=1821685)[0m [10]	train-mlogloss:2.67640	validation-mlogloss:2.67828
[36m(train_xgb_ray_tune pid=1821673)[0m [16]	train-mlogloss:2.68395	validation-mlogloss:2.68702
[36m(train_xgb_ray_tune pid=1821673)[0m [17]	train-mlogloss:2.68267	validation-mlogloss:2.68593
[36m(train_xgb_ray_tune pid=1821682)[0m [18]	train-mlogloss:2.63500	validation-mlogloss:2.63746
[36m(train_xgb_ray_tune pid=1821682)[0m [19]	train-mlogloss:2.63167	validation-mlogloss:2.63425
[36m(train_xgb_ray_tune pid=1821687)[0m [16]	train-mlogloss:2.63013	validation-mlogloss:2.62507
[36m(train_xgb_ray_tune pid=1821687)[0m [17]	train-mlogloss:2.62572	validation-mlogloss:2.62043
[36m(train_xgb_ray_tune pid=1821670)[0m [8]	train-mlogloss:2.64109	validation-mlogloss:2.63568
[36m(train_xgb_ray_tune pid=1821684)[0m [9]	train-mlogloss:2.67307	validation-mlogloss:2.67187
[36m(train_xgb_ray_tune pid=1821681)[0m [9]	train-mlogloss:2.70785	validation-mlogloss:2.70785
[36m(train_xgb_ray_tune pid=1821681)[0m [10]	train-mlogloss:2.70785	validation-mlogloss:2.70785
[36m(train_xgb_ray_tune pid=1821674)[0m [8]	train-mlogloss:2.65437	validation-mlogloss:2.64961
[36m(train_xgb_ray_tune pid=1821674)[0m [9]	train-mlogloss:2.64836	validation-mlogloss:2.64326
[36m(train_xgb_ray_tune pid=1821683)[0m [11]	train-mlogloss:2.66913	validation-mlogloss:2.66741
[36m(train_xgb_ray_tune pid=1821680)[0m [15]	train-mlogloss:2.58375	validation-mlogloss:2.57344
[36m(train_xgb_ray_tune pid=1821692)[0m [20]	train-mlogloss:2.70805	validation-mlogloss:2.70805
[36m(train_xgb_ray_tune pid=1821689)[0m [12]	train-mlogloss:2.65504	validation-mlogloss:2.65043
[36m(train_xgb_ray_tune pid=1821690)[0m [13]	train-mlogloss:2.68581	validation-mlogloss:2.68812
[36m(train_xgb_ray_tune pid=1821670)[0m [9]	train-mlogloss:2.63389	validation-mlogloss:2.62797
[36m(train_xgb_ray_tune pid=1821663)[0m [9]	train-mlogloss:2.65673	validation-mlogloss:2.65178
[36m(train_xgb_ray_tune pid=1821688)[0m [9]	train-mlogloss:2.64369	validation-mlogloss:2.63758
[36m(train_xgb_ray_tune pid=1821681)[0m [11]	train-mlogloss:2.70785	validation-mlogloss:2.70785
[36m(train_xgb_ray_tune pid=1821683)[0m [12]	train-mlogloss:2.66591	validation-mlogloss:2.66398

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:42:37. Total running time: 8s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             5.32095 │
│ time_total_s                 5.32095 │
│ training_iteration                 1 │
│ validation_accuracy          0.06393 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:42:37. Total running time: 8s
[36m(train_xgb_ray_tune pid=1821663)[0m [10]	train-mlogloss:2.65163	validation-mlogloss:2.64605
[36m(train_xgb_ray_tune pid=1821691)[0m [9]	train-mlogloss:2.63145	validation-mlogloss:2.62625
[36m(train_xgb_ray_tune pid=1821680)[0m [16]	train-mlogloss:2.57698	validation-mlogloss:2.56622
[36m(train_xgb_ray_tune pid=1821689)[0m [13]	train-mlogloss:2.65123	validation-mlogloss:2.64636
[36m(train_xgb_ray_tune pid=1821688)[0m [10]	train-mlogloss:2.63777	validation-mlogloss:2.63090
[36m(train_xgb_ray_tune pid=1821672)[0m [8]	train-mlogloss:2.60476	validation-mlogloss:2.59591
[36m(train_xgb_ray_tune pid=1821671)[0m [10]	train-mlogloss:2.67839	validation-mlogloss:2.67727
[36m(train_xgb_ray_tune pid=1821669)[0m [13]	train-mlogloss:2.64647	validation-mlogloss:2.64351
[36m(train_xgb_ray_tune pid=1821669)[0m [14]	train-mlogloss:2.64218	validation-mlogloss:2.63945
[36m(train_xgb_ray_tune pid=1821690)[0m [14]	train-mlogloss:2.68432	validation-mlogloss:2.68675
[36m(train_xgb_ray_tune pid=1821686)[0m [11]	train-mlogloss:2.67196	validation-mlogloss:2.67132
[36m(train_xgb_ray_tune pid=1821685)[0m [11]	train-mlogloss:2.67405	validation-mlogloss:2.67605
[36m(train_xgb_ray_tune pid=1821685)[0m [12]	train-mlogloss:2.67175	validation-mlogloss:2.67398
[36m(train_xgb_ray_tune pid=1821673)[0m [18]	train-mlogloss:2.68154	validation-mlogloss:2.68503
[36m(train_xgb_ray_tune pid=1821673)[0m [19]	train-mlogloss:2.68040	validation-mlogloss:2.68397
[36m(train_xgb_ray_tune pid=1821682)[0m [20]	train-mlogloss:2.62839	validation-mlogloss:2.63117
[36m(train_xgb_ray_tune pid=1821687)[0m [18]	train-mlogloss:2.62152	validation-mlogloss:2.61587
[36m(train_xgb_ray_tune pid=1821670)[0m [10]	train-mlogloss:2.62730	validation-mlogloss:2.62117
[36m(train_xgb_ray_tune pid=1821684)[0m [10]	train-mlogloss:2.66954	validation-mlogloss:2.66803
[36m(train_xgb_ray_tune pid=1821684)[0m [11]	train-mlogloss:2.66620	validation-mlogloss:2.66470
[36m(train_xgb_ray_tune pid=1821681)[0m [12]	train-mlogloss:2.70785	validation-mlogloss:2.70785
[36m(train_xgb_ray_tune pid=1821674)[0m [10]	train-mlogloss:2.64258	validation-mlogloss:2.63711
[36m(train_xgb_ray_tune pid=1821683)[0m [13]	train-mlogloss:2.66274	validation-mlogloss:2.66069
[36m(train_xgb_ray_tune pid=1821672)[0m [9]	train-mlogloss:2.59372	validation-mlogloss:2.58348
[36m(train_xgb_ray_tune pid=1821671)[0m [11]	train-mlogloss:2.67573	validation-mlogloss:2.67454
[36m(train_xgb_ray_tune pid=1821690)[0m [15]	train-mlogloss:2.68300	validation-mlogloss:2.68564
[36m(train_xgb_ray_tune pid=1821686)[0m [12]	train-mlogloss:2.66896	validation-mlogloss:2.66810
[36m(train_xgb_ray_tune pid=1821682)[0m [21]	train-mlogloss:2.62513	validation-mlogloss:2.62812
[36m(train_xgb_ray_tune pid=1821687)[0m [19]	train-mlogloss:2.61737	validation-mlogloss:2.61162
[36m(train_xgb_ray_tune pid=1821670)[0m [11]	train-mlogloss:2.62069	validation-mlogloss:2.61409
[36m(train_xgb_ray_tune pid=1821681)[0m [13]	train-mlogloss:2.70785	validation-mlogloss:2.70785
[36m(train_xgb_ray_tune pid=1821674)[0m [11]	train-mlogloss:2.63675	validation-mlogloss:2.63081
[36m(train_xgb_ray_tune pid=1821689)[0m [14]	train-mlogloss:2.64730	validation-mlogloss:2.64220
[36m(train_xgb_ray_tune pid=1821663)[0m [11]	train-mlogloss:2.64663	validation-mlogloss:2.64052
[36m(train_xgb_ray_tune pid=1821691)[0m [10]	train-mlogloss:2.62504	validation-mlogloss:2.61898
[36m(train_xgb_ray_tune pid=1821680)[0m [17]	train-mlogloss:2.56974	validation-mlogloss:2.55832
[36m(train_xgb_ray_tune pid=1821689)[0m [15]	train-mlogloss:2.64336	validation-mlogloss:2.63791
[36m(train_xgb_ray_tune pid=1821688)[0m [11]	train-mlogloss:2.63181	validation-mlogloss:2.62436
[36m(train_xgb_ray_tune pid=1821688)[0m [12]	train-mlogloss:2.62598	validation-mlogloss:2.61800
[36m(train_xgb_ray_tune pid=1821672)[0m [10]	train-mlogloss:2.58354	validation-mlogloss:2.57205
[36m(train_xgb_ray_tune pid=1821671)[0m [12]	train-mlogloss:2.67307	validation-mlogloss:2.67181
[36m(train_xgb_ray_tune pid=1821669)[0m [15]	train-mlogloss:2.63808	validation-mlogloss:2.63505
[36m(train_xgb_ray_tune pid=1821690)[0m [16]	train-mlogloss:2.68163	validation-mlogloss:2.68438
[36m(train_xgb_ray_tune pid=1821690)[0m [17]	train-mlogloss:2.68026	validation-mlogloss:2.68315
[36m(train_xgb_ray_tune pid=1821686)[0m [13]	train-mlogloss:2.66615	validation-mlogloss:2.66524
[36m(train_xgb_ray_tune pid=1821686)[0m [14]	train-mlogloss:2.66333	validation-mlogloss:2.66242
[36m(train_xgb_ray_tune pid=1821685)[0m [13]	train-mlogloss:2.66953	validation-mlogloss:2.67182
[36m(train_xgb_ray_tune pid=1821685)[0m [14]	train-mlogloss:2.66734	validation-mlogloss:2.66982
[36m(train_xgb_ray_tune pid=1821673)[0m [20]	train-mlogloss:2.67916	validation-mlogloss:2.68288
[36m(train_xgb_ray_tune pid=1821673)[0m [21]	train-mlogloss:2.67796	validation-mlogloss:2.68186
[36m(train_xgb_ray_tune pid=1821682)[0m [22]	train-mlogloss:2.62185	validation-mlogloss:2.62484
[36m(train_xgb_ray_tune pid=1821682)[0m [23]	train-mlogloss:2.61875	validation-mlogloss:2.62199
[36m(train_xgb_ray_tune pid=1821687)[0m [20]	train-mlogloss:2.61328	validation-mlogloss:2.60731
[36m(train_xgb_ray_tune pid=1821670)[0m [12]	train-mlogloss:2.61369	validation-mlogloss:2.60630
[36m(train_xgb_ray_tune pid=1821684)[0m [12]	train-mlogloss:2.66277	validation-mlogloss:2.66112
[36m(train_xgb_ray_tune pid=1821684)[0m [13]	train-mlogloss:2.65973	validation-mlogloss:2.65815
[36m(train_xgb_ray_tune pid=1821681)[0m [14]	train-mlogloss:2.70785	validation-mlogloss:2.70785
[36m(train_xgb_ray_tune pid=1821674)[0m [12]	train-mlogloss:2.63095	validation-mlogloss:2.62466
[36m(train_xgb_ray_tune pid=1821683)[0m [14]	train-mlogloss:2.65970	validation-mlogloss:2.65754
[36m(train_xgb_ray_tune pid=1821683)[0m [15]	train-mlogloss:2.65662	validation-mlogloss:2.65427
[36m(train_xgb_ray_tune pid=1821663)[0m [12]	train-mlogloss:2.64164	validation-mlogloss:2.63513
[36m(train_xgb_ray_tune pid=1821691)[0m [11]	train-mlogloss:2.61779	validation-mlogloss:2.61126
[36m(train_xgb_ray_tune pid=1821680)[0m [18]	train-mlogloss:2.56275	validation-mlogloss:2.55079
[36m(train_xgb_ray_tune pid=1821671)[0m [13]	train-mlogloss:2.67048	validation-mlogloss:2.66928
[36m(train_xgb_ray_tune pid=1821669)[0m [16]	train-mlogloss:2.63394	validation-mlogloss:2.63072
[36m(train_xgb_ray_tune pid=1821673)[0m [22]	train-mlogloss:2.67672	validation-mlogloss:2.68073
[36m(train_xgb_ray_tune pid=1821681)[0m [15]	train-mlogloss:2.70785	validation-mlogloss:2.70785
[36m(train_xgb_ray_tune pid=1821685)[0m [15]	train-mlogloss:2.66513	validation-mlogloss:2.66778
[36m(train_xgb_ray_tune pid=1821672)[0m [11]	train-mlogloss:2.57353	validation-mlogloss:2.56165
[36m(train_xgb_ray_tune pid=1821687)[0m [21]	train-mlogloss:2.60915	validation-mlogloss:2.60296
[36m(train_xgb_ray_tune pid=1821674)[0m [13]	train-mlogloss:2.62501	validation-mlogloss:2.61826
[36m(train_xgb_ray_tune pid=1821663)[0m [13]	train-mlogloss:2.63674	validation-mlogloss:2.62996
[36m(train_xgb_ray_tune pid=1821691)[0m [12]	train-mlogloss:2.61088	validation-mlogloss:2.60398
[36m(train_xgb_ray_tune pid=1821680)[0m [19]	train-mlogloss:2.55576	validation-mlogloss:2.54291
[36m(train_xgb_ray_tune pid=1821689)[0m [16]	train-mlogloss:2.63947	validation-mlogloss:2.63362
[36m(train_xgb_ray_tune pid=1821689)[0m [17]	train-mlogloss:2.63544	validation-mlogloss:2.62915
[36m(train_xgb_ray_tune pid=1821688)[0m [13]	train-mlogloss:2.62017	validation-mlogloss:2.61164
[36m(train_xgb_ray_tune pid=1821688)[0m [14]	train-mlogloss:2.61447	validation-mlogloss:2.60538
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[36m(train_xgb_ray_tune pid=1821680)[0m [26]	train-mlogloss:2.51037	validation-mlogloss:2.49403
[36m(train_xgb_ray_tune pid=1821689)[0m [25]	train-mlogloss:2.60551	validation-mlogloss:2.59607
[36m(train_xgb_ray_tune pid=1821688)[0m [22]	train-mlogloss:2.57127	validation-mlogloss:2.55791
[36m(train_xgb_ray_tune pid=1821669)[0m [24]	train-mlogloss:2.60161	validation-mlogloss:2.59681
[36m(train_xgb_ray_tune pid=1821690)[0m [30]	train-mlogloss:2.66452	validation-mlogloss:2.66999
[36m(train_xgb_ray_tune pid=1821687)[0m [30]	train-mlogloss:2.57311	validation-mlogloss:2.56448
[36m(train_xgb_ray_tune pid=1821674)[0m [22]	train-mlogloss:2.57546	validation-mlogloss:2.56433
[36m(train_xgb_ray_tune pid=1821672)[0m [19]	train-mlogloss:2.49897	validation-mlogloss:2.48013
[36m(train_xgb_ray_tune pid=1821681)[0m [28]	train-mlogloss:2.70705	validation-mlogloss:2.70702
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[36m(train_xgb_ray_tune pid=1821684)[0m [23]	train-mlogloss:2.62720	validation-mlogloss:2.62398
[36m(train_xgb_ray_tune pid=1821686)[0m [24]	train-mlogloss:2.63573	validation-mlogloss:2.63357
[36m(train_xgb_ray_tune pid=1821685)[0m [27]	train-mlogloss:2.63900	validation-mlogloss:2.64359
[36m(train_xgb_ray_tune pid=1821673)[0m [36]	train-mlogloss:2.66184	validation-mlogloss:2.66787
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[36m(train_xgb_ray_tune pid=1821682)[0m [34]	train-mlogloss:2.58703	validation-mlogloss:2.59169
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[36m(train_xgb_ray_tune pid=1821689)[0m [30]	train-mlogloss:2.58774	validation-mlogloss:2.57698
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[36m(train_xgb_ray_tune pid=1821671)[0m [25]	train-mlogloss:2.63953	validation-mlogloss:2.63687
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[36m(train_xgb_ray_tune pid=1821690)[0m [36]	train-mlogloss:2.65795	validation-mlogloss:2.66427
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[36m(train_xgb_ray_tune pid=1821673)[0m [40]	train-mlogloss:2.65779	validation-mlogloss:2.66441
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[36m(train_xgb_ray_tune pid=1821681)[0m [34]	train-mlogloss:2.70666	validation-mlogloss:2.70662
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[36m(train_xgb_ray_tune pid=1821689)[0m [31]	train-mlogloss:2.58429	validation-mlogloss:2.57312
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[36m(train_xgb_ray_tune pid=1821673)[0m [42]	train-mlogloss:2.65596	validation-mlogloss:2.66282
[36m(train_xgb_ray_tune pid=1821682)[0m [40]	train-mlogloss:2.57145	validation-mlogloss:2.57709
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[36m(train_xgb_ray_tune pid=1821690)[0m [38]	train-mlogloss:2.65578	validation-mlogloss:2.66229
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[36m(train_xgb_ray_tune pid=1821681)[0m [36]	train-mlogloss:2.70666	validation-mlogloss:2.70662
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[36m(train_xgb_ray_tune pid=1821680)[0m [32]	train-mlogloss:2.47448	validation-mlogloss:2.45471
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[36m(train_xgb_ray_tune pid=1821682)[0m [41]	train-mlogloss:2.56909	validation-mlogloss:2.57502
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[36m(train_xgb_ray_tune pid=1821673)[0m [44]	train-mlogloss:2.65416	validation-mlogloss:2.66132
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[36m(train_xgb_ray_tune pid=1821685)[0m [37]	train-mlogloss:2.62027	validation-mlogloss:2.62621
[36m(train_xgb_ray_tune pid=1821685)[0m [38]	train-mlogloss:2.61845	validation-mlogloss:2.62453
[36m(train_xgb_ray_tune pid=1821673)[0m [45]	train-mlogloss:2.65325	validation-mlogloss:2.66055
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[36m(train_xgb_ray_tune pid=1821682)[0m [42]	train-mlogloss:2.56667	validation-mlogloss:2.57265
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[36m(train_xgb_ray_tune pid=1821689)[0m [43]	train-mlogloss:2.54459	validation-mlogloss:2.52940
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[36m(train_xgb_ray_tune pid=1821680)[0m [77]	train-mlogloss:2.27294	validation-mlogloss:2.23629
[36m(train_xgb_ray_tune pid=1821689)[0m [88]	train-mlogloss:2.41898	validation-mlogloss:2.39032
[36m(train_xgb_ray_tune pid=1821671)[0m [76]	train-mlogloss:2.52183	validation-mlogloss:2.51408
[36m(train_xgb_ray_tune pid=1821685)[0m [101]	train-mlogloss:2.54234	validation-mlogloss:2.55541
[36m(train_xgb_ray_tune pid=1821687)[0m [89]	train-mlogloss:2.38487	validation-mlogloss:2.36410
[36m(train_xgb_ray_tune pid=1821681)[0m [108]	train-mlogloss:2.70444	validation-mlogloss:2.70434
[36m(train_xgb_ray_tune pid=1821674)[0m [83]	train-mlogloss:2.33397	validation-mlogloss:2.29635
[36m(train_xgb_ray_tune pid=1821688)[0m [83]	train-mlogloss:2.34033	validation-mlogloss:2.30545
[36m(train_xgb_ray_tune pid=1821663)[0m [72]	train-mlogloss:2.40641	validation-mlogloss:2.37993
[36m(train_xgb_ray_tune pid=1821691)[0m [75]	train-mlogloss:2.29819	validation-mlogloss:2.26183
[36m(train_xgb_ray_tune pid=1821680)[0m [78]	train-mlogloss:2.26941	validation-mlogloss:2.23264
[36m(train_xgb_ray_tune pid=1821689)[0m [89]	train-mlogloss:2.41652	validation-mlogloss:2.38752
[36m(train_xgb_ray_tune pid=1821688)[0m [84]	train-mlogloss:2.33748	validation-mlogloss:2.30236
[36m(train_xgb_ray_tune pid=1821672)[0m [71]	train-mlogloss:2.19234	validation-mlogloss:2.15102
[36m(train_xgb_ray_tune pid=1821671)[0m [77]	train-mlogloss:2.51974	validation-mlogloss:2.51188
[36m(train_xgb_ray_tune pid=1821669)[0m [80]	train-mlogloss:2.41474	validation-mlogloss:2.40108
[36m(train_xgb_ray_tune pid=1821690)[0m [109]	train-mlogloss:2.60752	validation-mlogloss:2.62161
[36m(train_xgb_ray_tune pid=1821690)[0m [110]	train-mlogloss:2.60702	validation-mlogloss:2.62125
[36m(train_xgb_ray_tune pid=1821686)[0m [82]	train-mlogloss:2.50813	validation-mlogloss:2.49805
[36m(train_xgb_ray_tune pid=1821685)[0m [102]	train-mlogloss:2.54148	validation-mlogloss:2.55469
[36m(train_xgb_ray_tune pid=1821685)[0m [103]	train-mlogloss:2.54068	validation-mlogloss:2.55402
[36m(train_xgb_ray_tune pid=1821673)[0m [110]	train-mlogloss:2.60818	validation-mlogloss:2.62255
[36m(train_xgb_ray_tune pid=1821673)[0m [111]	train-mlogloss:2.60767	validation-mlogloss:2.62212
[36m(train_xgb_ray_tune pid=1821682)[0m [103]	train-mlogloss:2.47738	validation-mlogloss:2.49146
[36m(train_xgb_ray_tune pid=1821682)[0m [104]	train-mlogloss:2.47642	validation-mlogloss:2.49059
[36m(train_xgb_ray_tune pid=1821682)[0m [105]	train-mlogloss:2.47551	validation-mlogloss:2.48977
[36m(train_xgb_ray_tune pid=1821687)[0m [90]	train-mlogloss:2.38226	validation-mlogloss:2.36114
[36m(train_xgb_ray_tune pid=1821687)[0m [91]	train-mlogloss:2.37972	validation-mlogloss:2.35838
[36m(train_xgb_ray_tune pid=1821670)[0m [83]	train-mlogloss:2.28187	validation-mlogloss:2.24234
[36m(train_xgb_ray_tune pid=1821670)[0m [84]	train-mlogloss:2.27886	validation-mlogloss:2.23907
[36m(train_xgb_ray_tune pid=1821684)[0m [80]	train-mlogloss:2.48278	validation-mlogloss:2.47105
[36m(train_xgb_ray_tune pid=1821684)[0m [81]	train-mlogloss:2.48070	validation-mlogloss:2.46893
[36m(train_xgb_ray_tune pid=1821681)[0m [109]	train-mlogloss:2.70444	validation-mlogloss:2.70434
[36m(train_xgb_ray_tune pid=1821674)[0m [84]	train-mlogloss:2.33105	validation-mlogloss:2.29331
[36m(train_xgb_ray_tune pid=1821683)[0m [86]	train-mlogloss:2.48191	validation-mlogloss:2.47386
[36m(train_xgb_ray_tune pid=1821683)[0m [87]	train-mlogloss:2.47990	validation-mlogloss:2.47181
[36m(train_xgb_ray_tune pid=1821691)[0m [76]	train-mlogloss:2.29440	validation-mlogloss:2.25763
[36m(train_xgb_ray_tune pid=1821689)[0m [90]	train-mlogloss:2.41416	validation-mlogloss:2.38506
[36m(train_xgb_ray_tune pid=1821672)[0m [72]	train-mlogloss:2.18818	validation-mlogloss:2.14651
[36m(train_xgb_ray_tune pid=1821686)[0m [83]	train-mlogloss:2.50636	validation-mlogloss:2.49615
[36m(train_xgb_ray_tune pid=1821684)[0m 
[36m(train_xgb_ray_tune pid=1821680)[0m [79]	train-mlogloss:2.26599	validation-mlogloss:2.22894
[36m(train_xgb_ray_tune pid=1821669)[0m [81]	train-mlogloss:2.41182	validation-mlogloss:2.39809
[36m(train_xgb_ray_tune pid=1821688)[0m 2025-11-06 21:42:33.348371: 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=1821688)[0m 2025-11-06 21:42:33.370484: 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=1821671)[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=1821671)[0m E0000 00:00:1762461753.455127 1822932 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=1821671)[0m E0000 00:00:1762461753.463425 1822932 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=1821671)[0m W0000 00:00:1762461753.483307 1822932 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=1821671)[0m 2025-11-06 21:42:33.489729: 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=1821671)[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=1821681)[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=1821681)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=1821673)[0m [112]	train-mlogloss:2.60719	validation-mlogloss:2.62168
[36m(train_xgb_ray_tune pid=1821663)[0m [73]	train-mlogloss:2.40326	validation-mlogloss:2.37670
[36m(train_xgb_ray_tune pid=1821688)[0m [85]	train-mlogloss:2.33478	validation-mlogloss:2.29939
[36m(train_xgb_ray_tune pid=1821671)[0m [78]	train-mlogloss:2.51767	validation-mlogloss:2.50971
[36m(train_xgb_ray_tune pid=1821690)[0m [111]	train-mlogloss:2.60658	validation-mlogloss:2.62091
[36m(train_xgb_ray_tune pid=1821685)[0m [104]	train-mlogloss:2.53989	validation-mlogloss:2.55319
[36m(train_xgb_ray_tune pid=1821682)[0m [106]	train-mlogloss:2.47474	validation-mlogloss:2.48912
[36m(train_xgb_ray_tune pid=1821670)[0m [85]	train-mlogloss:2.27567	validation-mlogloss:2.23572
[36m(train_xgb_ray_tune pid=1821683)[0m [88]	train-mlogloss:2.47800	validation-mlogloss:2.46992
[36m(train_xgb_ray_tune pid=1821663)[0m [74]	train-mlogloss:2.40009	validation-mlogloss:2.37327
[36m(train_xgb_ray_tune pid=1821691)[0m [77]	train-mlogloss:2.29106	validation-mlogloss:2.25400
[36m(train_xgb_ray_tune pid=1821680)[0m [80]	train-mlogloss:2.26241	validation-mlogloss:2.22516
[36m(train_xgb_ray_tune pid=1821689)[0m [91]	train-mlogloss:2.41175	validation-mlogloss:2.38247
[36m(train_xgb_ray_tune pid=1821689)[0m [92]	train-mlogloss:2.40942	validation-mlogloss:2.38002
[36m(train_xgb_ray_tune pid=1821688)[0m [86]	train-mlogloss:2.33207	validation-mlogloss:2.29663
[36m(train_xgb_ray_tune pid=1821672)[0m [73]	train-mlogloss:2.18430	validation-mlogloss:2.14232
[36m(train_xgb_ray_tune pid=1821671)[0m [79]	train-mlogloss:2.51557	validation-mlogloss:2.50751
[36m(train_xgb_ray_tune pid=1821669)[0m [82]	train-mlogloss:2.40904	validation-mlogloss:2.39508
[36m(train_xgb_ray_tune pid=1821669)[0m [83]	train-mlogloss:2.40634	validation-mlogloss:2.39209
[36m(train_xgb_ray_tune pid=1821690)[0m [112]	train-mlogloss:2.60604	validation-mlogloss:2.62045
[36m(train_xgb_ray_tune pid=1821690)[0m [113]	train-mlogloss:2.60590	validation-mlogloss:2.62034
[36m(train_xgb_ray_tune pid=1821686)[0m [84]	train-mlogloss:2.50449	validation-mlogloss:2.49414
[36m(train_xgb_ray_tune pid=1821686)[0m [85]	train-mlogloss:2.50274	validation-mlogloss:2.49229
[36m(train_xgb_ray_tune pid=1821685)[0m [105]	train-mlogloss:2.53887	validation-mlogloss:2.55222
[36m(train_xgb_ray_tune pid=1821685)[0m [106]	train-mlogloss:2.53826	validation-mlogloss:2.55177
[36m(train_xgb_ray_tune pid=1821673)[0m [113]	train-mlogloss:2.60668	validation-mlogloss:2.62127
[36m(train_xgb_ray_tune pid=1821673)[0m [114]	train-mlogloss:2.60616	validation-mlogloss:2.62086
[36m(train_xgb_ray_tune pid=1821682)[0m [107]	train-mlogloss:2.47382	validation-mlogloss:2.48826
[36m(train_xgb_ray_tune pid=1821682)[0m [108]	train-mlogloss:2.47298	validation-mlogloss:2.48748
[36m(train_xgb_ray_tune pid=1821687)[0m [92]	train-mlogloss:2.37721	validation-mlogloss:2.35591
[36m(train_xgb_ray_tune pid=1821687)[0m [93]	train-mlogloss:2.37458	validation-mlogloss:2.35302
[36m(train_xgb_ray_tune pid=1821670)[0m [86]	train-mlogloss:2.27232	validation-mlogloss:2.23208
[36m(train_xgb_ray_tune pid=1821684)[0m [82]	train-mlogloss:2.47868	validation-mlogloss:2.46687
[36m(train_xgb_ray_tune pid=1821674)[0m [85]	train-mlogloss:2.32800	validation-mlogloss:2.28967
[36m(train_xgb_ray_tune pid=1821674)[0m [86]	train-mlogloss:2.32483	validation-mlogloss:2.28590
[36m(train_xgb_ray_tune pid=1821683)[0m [89]	train-mlogloss:2.47606	validation-mlogloss:2.46794
[36m(train_xgb_ray_tune pid=1821691)[0m [78]	train-mlogloss:2.28769	validation-mlogloss:2.25062

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:42:44. Total running time: 14s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s              11.826 │
│ time_total_s                  11.826 │
│ training_iteration                 1 │
│ validation_accuracy          0.12428 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:42:44. Total running time: 14s
[36m(train_xgb_ray_tune pid=1821663)[0m [75]	train-mlogloss:2.39698	validation-mlogloss:2.36997
[36m(train_xgb_ray_tune pid=1821691)[0m [79]	train-mlogloss:2.28423	validation-mlogloss:2.24683
[36m(train_xgb_ray_tune pid=1821680)[0m [81]	train-mlogloss:2.25906	validation-mlogloss:2.22121
[36m(train_xgb_ray_tune pid=1821689)[0m [93]	train-mlogloss:2.40691	validation-mlogloss:2.37721
[36m(train_xgb_ray_tune pid=1821688)[0m [87]	train-mlogloss:2.32938	validation-mlogloss:2.29365
[36m(train_xgb_ray_tune pid=1821688)[0m [88]	train-mlogloss:2.32662	validation-mlogloss:2.29059
[36m(train_xgb_ray_tune pid=1821672)[0m [74]	train-mlogloss:2.18052	validation-mlogloss:2.13871
[36m(train_xgb_ray_tune pid=1821672)[0m [75]	train-mlogloss:2.17675	validation-mlogloss:2.13466
[36m(train_xgb_ray_tune pid=1821671)[0m [80]	train-mlogloss:2.51358	validation-mlogloss:2.50531
[36m(train_xgb_ray_tune pid=1821669)[0m [84]	train-mlogloss:2.40349	validation-mlogloss:2.38906
[36m(train_xgb_ray_tune pid=1821690)[0m [114]	train-mlogloss:2.60545	validation-mlogloss:2.61994
[36m(train_xgb_ray_tune pid=1821690)[0m [115]	train-mlogloss:2.60490	validation-mlogloss:2.61951
[36m(train_xgb_ray_tune pid=1821686)[0m [86]	train-mlogloss:2.50096	validation-mlogloss:2.49038
[36m(train_xgb_ray_tune pid=1821685)[0m [107]	train-mlogloss:2.53750	validation-mlogloss:2.55112
[36m(train_xgb_ray_tune pid=1821685)[0m [108]	train-mlogloss:2.53666	validation-mlogloss:2.55036
[36m(train_xgb_ray_tune pid=1821673)[0m [115]	train-mlogloss:2.60569	validation-mlogloss:2.62042
[36m(train_xgb_ray_tune pid=1821673)[0m [116]	train-mlogloss:2.60533	validation-mlogloss:2.62012
[36m(train_xgb_ray_tune pid=1821682)[0m [109]	train-mlogloss:2.47205	validation-mlogloss:2.48659
[36m(train_xgb_ray_tune pid=1821687)[0m [94]	train-mlogloss:2.37210	validation-mlogloss:2.35025
[36m(train_xgb_ray_tune pid=1821670)[0m [87]	train-mlogloss:2.26911	validation-mlogloss:2.22885
[36m(train_xgb_ray_tune pid=1821670)[0m [88]	train-mlogloss:2.26590	validation-mlogloss:2.22520
[36m(train_xgb_ray_tune pid=1821684)[0m [83]	train-mlogloss:2.47643	validation-mlogloss:2.46452
[36m(train_xgb_ray_tune pid=1821684)[0m [84]	train-mlogloss:2.47436	validation-mlogloss:2.46252
[36m(train_xgb_ray_tune pid=1821674)[0m [87]	train-mlogloss:2.32204	validation-mlogloss:2.28271
[36m(train_xgb_ray_tune pid=1821674)[0m [88]	train-mlogloss:2.31897	validation-mlogloss:2.27936
[36m(train_xgb_ray_tune pid=1821683)[0m [90]	train-mlogloss:2.47404	validation-mlogloss:2.46585
[36m(train_xgb_ray_tune pid=1821683)[0m [91]	train-mlogloss:2.47223	validation-mlogloss:2.46388
[36m(train_xgb_ray_tune pid=1821663)[0m [76]	train-mlogloss:2.39373	validation-mlogloss:2.36654
[36m(train_xgb_ray_tune pid=1821680)[0m [82]	train-mlogloss:2.25567	validation-mlogloss:2.21759
[36m(train_xgb_ray_tune pid=1821671)[0m [81]	train-mlogloss:2.51151	validation-mlogloss:2.50321
[36m(train_xgb_ray_tune pid=1821673)[0m [117]	train-mlogloss:2.60471	validation-mlogloss:2.61952
[36m(train_xgb_ray_tune pid=1821682)[0m [110]	train-mlogloss:2.47102	validation-mlogloss:2.48573
[36m(train_xgb_ray_tune pid=1821687)[0m [95]	train-mlogloss:2.36966	validation-mlogloss:2.34748
[36m(train_xgb_ray_tune pid=1821689)[0m [94]	train-mlogloss:2.40464	validation-mlogloss:2.37470
[36m(train_xgb_ray_tune pid=1821669)[0m [85]	train-mlogloss:2.40069	validation-mlogloss:2.38613
[36m(train_xgb_ray_tune pid=1821686)[0m [87]	train-mlogloss:2.49912	validation-mlogloss:2.48837
[36m(train_xgb_ray_tune pid=1821685)[0m [109]	train-mlogloss:2.53590	validation-mlogloss:2.54971
[36m(train_xgb_ray_tune pid=1821690)[0m [116]	train-mlogloss:2.60443	validation-mlogloss:2.61915
[36m(train_xgb_ray_tune pid=1821684)[0m [85]	train-mlogloss:2.47243	validation-mlogloss:2.46040
[36m(train_xgb_ray_tune pid=1821691)[0m [80]	train-mlogloss:2.28050	validation-mlogloss:2.24279
[36m(train_xgb_ray_tune pid=1821670)[0m [89]	train-mlogloss:2.26269	validation-mlogloss:2.22152
[36m(train_xgb_ray_tune pid=1821672)[0m [76]	train-mlogloss:2.17292	validation-mlogloss:2.13062
[36m(train_xgb_ray_tune pid=1821673)[0m [118]	train-mlogloss:2.60421	validation-mlogloss:2.61912
[36m(train_xgb_ray_tune pid=1821683)[0m [92]	train-mlogloss:2.47030	validation-mlogloss:2.46192
[36m(train_xgb_ray_tune pid=1821663)[0m [77]	train-mlogloss:2.39072	validation-mlogloss:2.36337
[36m(train_xgb_ray_tune pid=1821691)[0m [81]	train-mlogloss:2.27707	validation-mlogloss:2.23930
[36m(train_xgb_ray_tune pid=1821680)[0m [83]	train-mlogloss:2.25246	validation-mlogloss:2.21425
[36m(train_xgb_ray_tune pid=1821689)[0m [95]	train-mlogloss:2.40229	validation-mlogloss:2.37208
[36m(train_xgb_ray_tune pid=1821689)[0m [96]	train-mlogloss:2.39980	validation-mlogloss:2.36932
[36m(train_xgb_ray_tune pid=1821688)[0m [89]	train-mlogloss:2.32397	validation-mlogloss:2.28774
[36m(train_xgb_ray_tune pid=1821688)[0m [90]	train-mlogloss:2.32119	validation-mlogloss:2.28471
[36m(train_xgb_ray_tune pid=1821672)[0m [77]	train-mlogloss:2.16921	validation-mlogloss:2.12673
[36m(train_xgb_ray_tune pid=1821671)[0m [82]	train-mlogloss:2.50947	validation-mlogloss:2.50114
[36m(train_xgb_ray_tune pid=1821669)[0m [86]	train-mlogloss:2.39799	validation-mlogloss:2.38312
[36m(train_xgb_ray_tune pid=1821690)[0m [117]	train-mlogloss:2.60422	validation-mlogloss:2.61897
[36m(train_xgb_ray_tune pid=1821690)[0m [118]	train-mlogloss:2.60382	validation-mlogloss:2.61869
[36m(train_xgb_ray_tune pid=1821690)[0m [119]	train-mlogloss:2.60328	validation-mlogloss:2.61824
[36m(train_xgb_ray_tune pid=1821686)[0m [88]	train-mlogloss:2.49734	validation-mlogloss:2.48647
[36m(train_xgb_ray_tune pid=1821685)[0m [110]	train-mlogloss:2.53512	validation-mlogloss:2.54897
[36m(train_xgb_ray_tune pid=1821685)[0m [111]	train-mlogloss:2.53407	validation-mlogloss:2.54798
[36m(train_xgb_ray_tune pid=1821673)[0m [119]	train-mlogloss:2.60361	validation-mlogloss:2.61855
[36m(train_xgb_ray_tune pid=1821673)[0m [120]	train-mlogloss:2.60312	validation-mlogloss:2.61818
[36m(train_xgb_ray_tune pid=1821673)[0m [121]	train-mlogloss:2.60269	validation-mlogloss:2.61782
[36m(train_xgb_ray_tune pid=1821682)[0m [111]	train-mlogloss:2.47026	validation-mlogloss:2.48512
[36m(train_xgb_ray_tune pid=1821682)[0m [112]	train-mlogloss:2.46938	validation-mlogloss:2.48430
[36m(train_xgb_ray_tune pid=1821687)[0m [96]	train-mlogloss:2.36711	validation-mlogloss:2.34472
[36m(train_xgb_ray_tune pid=1821687)[0m [97]	train-mlogloss:2.36461	validation-mlogloss:2.34208
[36m(train_xgb_ray_tune pid=1821670)[0m [90]	train-mlogloss:2.25964	validation-mlogloss:2.21849
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[36m(train_xgb_ray_tune pid=1821671)[0m [191]	train-mlogloss:2.32157	validation-mlogloss:2.30269
[36m(train_xgb_ray_tune pid=1821669)[0m [192]	train-mlogloss:2.18024	validation-mlogloss:2.15333
[36m(train_xgb_ray_tune pid=1821690)[0m [272]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821690)[0m [273]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821686)[0m [210]	train-mlogloss:2.33737	validation-mlogloss:2.32022
[36m(train_xgb_ray_tune pid=1821686)[0m [211]	train-mlogloss:2.33641	validation-mlogloss:2.31933
[36m(train_xgb_ray_tune pid=1821685)[0m [258]	train-mlogloss:2.47393	validation-mlogloss:2.49474
[36m(train_xgb_ray_tune pid=1821673)[0m [273]	train-mlogloss:2.56737	validation-mlogloss:2.58859
[36m(train_xgb_ray_tune pid=1821673)[0m [274]	train-mlogloss:2.56721	validation-mlogloss:2.58843
[36m(train_xgb_ray_tune pid=1821682)[0m [262]	train-mlogloss:2.40820	validation-mlogloss:2.42907
[36m(train_xgb_ray_tune pid=1821687)[0m [220]	train-mlogloss:2.15359	validation-mlogloss:2.11987
[36m(train_xgb_ray_tune pid=1821687)[0m [221]	train-mlogloss:2.15239	validation-mlogloss:2.11861
[36m(train_xgb_ray_tune pid=1821670)[0m [205]	train-mlogloss:2.02058	validation-mlogloss:1.97708
[36m(train_xgb_ray_tune pid=1821684)[0m [207]	train-mlogloss:2.29259	validation-mlogloss:2.27208
[36m(train_xgb_ray_tune pid=1821684)[0m [208]	train-mlogloss:2.29154	validation-mlogloss:2.27096
[36m(train_xgb_ray_tune pid=1821684)[0m [209]	train-mlogloss:2.29061	validation-mlogloss:2.27019
[36m(train_xgb_ray_tune pid=1821674)[0m [204]	train-mlogloss:2.09071	validation-mlogloss:2.03418
[36m(train_xgb_ray_tune pid=1821674)[0m [205]	train-mlogloss:2.08944	validation-mlogloss:2.03296
[36m(train_xgb_ray_tune pid=1821683)[0m [214]	train-mlogloss:2.31338	validation-mlogloss:2.30228
[36m(train_xgb_ray_tune pid=1821683)[0m [215]	train-mlogloss:2.31263	validation-mlogloss:2.30150
[36m(train_xgb_ray_tune pid=1821680)[0m [187]	train-mlogloss:2.02481	validation-mlogloss:1.98136
[36m(train_xgb_ray_tune pid=1821671)[0m [192]	train-mlogloss:2.32019	validation-mlogloss:2.30119
[36m(train_xgb_ray_tune pid=1821682)[0m [263]	train-mlogloss:2.40820	validation-mlogloss:2.42907
[36m(train_xgb_ray_tune pid=1821691)[0m [196]	train-mlogloss:2.04444	validation-mlogloss:1.99839
[36m(train_xgb_ray_tune pid=1821669)[0m [193]	train-mlogloss:2.17873	validation-mlogloss:2.15167
[36m(train_xgb_ray_tune pid=1821663)[0m [178]	train-mlogloss:2.16261	validation-mlogloss:2.12167
[36m(train_xgb_ray_tune pid=1821688)[0m [207]	train-mlogloss:2.11410	validation-mlogloss:2.06774
[36m(train_xgb_ray_tune pid=1821670)[0m [206]	train-mlogloss:2.01920	validation-mlogloss:1.97581
[36m(train_xgb_ray_tune pid=1821663)[0m [179]	train-mlogloss:2.16092	validation-mlogloss:2.11998
[36m(train_xgb_ray_tune pid=1821691)[0m [197]	train-mlogloss:2.04329	validation-mlogloss:1.99720
[36m(train_xgb_ray_tune pid=1821680)[0m [188]	train-mlogloss:2.02334	validation-mlogloss:1.97998
[36m(train_xgb_ray_tune pid=1821689)[0m [219]	train-mlogloss:2.18476	validation-mlogloss:2.13847
[36m(train_xgb_ray_tune pid=1821689)[0m [220]	train-mlogloss:2.18351	validation-mlogloss:2.13728
[36m(train_xgb_ray_tune pid=1821688)[0m [208]	train-mlogloss:2.11300	validation-mlogloss:2.06679
[36m(train_xgb_ray_tune pid=1821672)[0m [180]	train-mlogloss:1.94173	validation-mlogloss:1.90655
[36m(train_xgb_ray_tune pid=1821672)[0m [181]	train-mlogloss:1.94046	validation-mlogloss:1.90539
[36m(train_xgb_ray_tune pid=1821671)[0m [193]	train-mlogloss:2.31878	validation-mlogloss:2.29956
[36m(train_xgb_ray_tune pid=1821669)[0m [194]	train-mlogloss:2.17726	validation-mlogloss:2.15005
[36m(train_xgb_ray_tune pid=1821690)[0m [274]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821690)[0m [275]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821686)[0m [212]	train-mlogloss:2.33549	validation-mlogloss:2.31847
[36m(train_xgb_ray_tune pid=1821686)[0m [213]	train-mlogloss:2.33462	validation-mlogloss:2.31755
[36m(train_xgb_ray_tune pid=1821673)[0m [275]	train-mlogloss:2.56708	validation-mlogloss:2.58833
[36m(train_xgb_ray_tune pid=1821673)[0m [276]	train-mlogloss:2.56708	validation-mlogloss:2.58833
[36m(train_xgb_ray_tune pid=1821682)[0m [264]	train-mlogloss:2.40820	validation-mlogloss:2.42907
[36m(train_xgb_ray_tune pid=1821682)[0m [265]	train-mlogloss:2.40820	validation-mlogloss:2.42907
[36m(train_xgb_ray_tune pid=1821687)[0m [222]	train-mlogloss:2.15131	validation-mlogloss:2.11759
[36m(train_xgb_ray_tune pid=1821687)[0m [223]	train-mlogloss:2.15030	validation-mlogloss:2.11658
[36m(train_xgb_ray_tune pid=1821670)[0m [207]	train-mlogloss:2.01781	validation-mlogloss:1.97462
[36m(train_xgb_ray_tune pid=1821684)[0m [210]	train-mlogloss:2.28959	validation-mlogloss:2.26932
[36m(train_xgb_ray_tune pid=1821684)[0m [211]	train-mlogloss:2.28851	validation-mlogloss:2.26817
[36m(train_xgb_ray_tune pid=1821674)[0m [206]	train-mlogloss:2.08811	validation-mlogloss:2.03165
[36m(train_xgb_ray_tune pid=1821674)[0m [207]	train-mlogloss:2.08687	validation-mlogloss:2.03050
[36m(train_xgb_ray_tune pid=1821683)[0m [216]	train-mlogloss:2.31187	validation-mlogloss:2.30073
[36m(train_xgb_ray_tune pid=1821683)[0m [217]	train-mlogloss:2.31100	validation-mlogloss:2.29986
[36m(train_xgb_ray_tune pid=1821691)[0m [198]	train-mlogloss:2.04223	validation-mlogloss:1.99649
[36m(train_xgb_ray_tune pid=1821680)[0m [189]	train-mlogloss:2.02192	validation-mlogloss:1.97870
[36m(train_xgb_ray_tune pid=1821688)[0m [209]	train-mlogloss:2.11194	validation-mlogloss:2.06565
[36m(train_xgb_ray_tune pid=1821669)[0m [195]	train-mlogloss:2.17591	validation-mlogloss:2.14855
[36m(train_xgb_ray_tune pid=1821690)[0m [276]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821673)[0m [277]	train-mlogloss:2.56708	validation-mlogloss:2.58833
[36m(train_xgb_ray_tune pid=1821682)[0m [266]	train-mlogloss:2.40810	validation-mlogloss:2.42894
[36m(train_xgb_ray_tune pid=1821670)[0m [208]	train-mlogloss:2.01636	validation-mlogloss:1.97329
[36m(train_xgb_ray_tune pid=1821671)[0m [194]	train-mlogloss:2.31734	validation-mlogloss:2.29815
[36m(train_xgb_ray_tune pid=1821674)[0m [208]	train-mlogloss:2.08560	validation-mlogloss:2.02933
[36m(train_xgb_ray_tune pid=1821663)[0m [180]	train-mlogloss:2.15940	validation-mlogloss:2.11829
[36m(train_xgb_ray_tune pid=1821683)[0m [218]	train-mlogloss:2.31018	validation-mlogloss:2.29901
[36m(train_xgb_ray_tune pid=1821684)[0m [212]	train-mlogloss:2.28751	validation-mlogloss:2.26723
[36m(train_xgb_ray_tune pid=1821663)[0m [181]	train-mlogloss:2.15773	validation-mlogloss:2.11643
[36m(train_xgb_ray_tune pid=1821691)[0m [199]	train-mlogloss:2.04113	validation-mlogloss:1.99536
[36m(train_xgb_ray_tune pid=1821680)[0m [190]	train-mlogloss:2.02052	validation-mlogloss:1.97756
[36m(train_xgb_ray_tune pid=1821689)[0m [221]	train-mlogloss:2.18216	validation-mlogloss:2.13592
[36m(train_xgb_ray_tune pid=1821689)[0m [222]	train-mlogloss:2.18089	validation-mlogloss:2.13471
[36m(train_xgb_ray_tune pid=1821688)[0m [210]	train-mlogloss:2.11073	validation-mlogloss:2.06428
[36m(train_xgb_ray_tune pid=1821688)[0m [211]	train-mlogloss:2.10959	validation-mlogloss:2.06317
[36m(train_xgb_ray_tune pid=1821688)[0m [212]	train-mlogloss:2.10850	validation-mlogloss:2.06210
[36m(train_xgb_ray_tune pid=1821672)[0m [182]	train-mlogloss:1.93923	validation-mlogloss:1.90436
[36m(train_xgb_ray_tune pid=1821671)[0m [195]	train-mlogloss:2.31595	validation-mlogloss:2.29663
[36m(train_xgb_ray_tune pid=1821669)[0m [196]	train-mlogloss:2.17438	validation-mlogloss:2.14699
[36m(train_xgb_ray_tune pid=1821690)[0m [277]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821690)[0m [278]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821686)[0m [214]	train-mlogloss:2.33362	validation-mlogloss:2.31645
[36m(train_xgb_ray_tune pid=1821686)[0m [215]	train-mlogloss:2.33272	validation-mlogloss:2.31543
[36m(train_xgb_ray_tune pid=1821673)[0m [278]	train-mlogloss:2.56708	validation-mlogloss:2.58833
[36m(train_xgb_ray_tune pid=1821673)[0m [279]	train-mlogloss:2.56708	validation-mlogloss:2.58833
[36m(train_xgb_ray_tune pid=1821673)[0m [280]	train-mlogloss:2.56687	validation-mlogloss:2.58816
[36m(train_xgb_ray_tune pid=1821682)[0m [267]	train-mlogloss:2.40800	validation-mlogloss:2.42882
[36m(train_xgb_ray_tune pid=1821685)[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=1821685)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=1821682)[0m [268]	train-mlogloss:2.40800	validation-mlogloss:2.42882
[36m(train_xgb_ray_tune pid=1821687)[0m [224]	train-mlogloss:2.14917	validation-mlogloss:2.11538
[36m(train_xgb_ray_tune pid=1821687)[0m [225]	train-mlogloss:2.14800	validation-mlogloss:2.11406
[36m(train_xgb_ray_tune pid=1821670)[0m [209]	train-mlogloss:2.01502	validation-mlogloss:1.97219
[36m(train_xgb_ray_tune pid=1821670)[0m [210]	train-mlogloss:2.01372	validation-mlogloss:1.97096
[36m(train_xgb_ray_tune pid=1821684)[0m [213]	train-mlogloss:2.28654	validation-mlogloss:2.26619
[36m(train_xgb_ray_tune pid=1821674)[0m [209]	train-mlogloss:2.08443	validation-mlogloss:2.02825
[36m(train_xgb_ray_tune pid=1821683)[0m [219]	train-mlogloss:2.30938	validation-mlogloss:2.29827
[36m(train_xgb_ray_tune pid=1821691)[0m [200]	train-mlogloss:2.04008	validation-mlogloss:1.99435
[36m(train_xgb_ray_tune pid=1821672)[0m [183]	train-mlogloss:1.93800	validation-mlogloss:1.90316
[36m(train_xgb_ray_tune pid=1821683)[0m [220]	train-mlogloss:2.30865	validation-mlogloss:2.29757
[36m(train_xgb_ray_tune pid=1821674)[0m [210]	train-mlogloss:2.08319	validation-mlogloss:2.02706
[36m(train_xgb_ray_tune pid=1821690)[0m [279]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821669)[0m [197]	train-mlogloss:2.17288	validation-mlogloss:2.14541
[36m(train_xgb_ray_tune pid=1821682)[0m [269]	train-mlogloss:2.40800	validation-mlogloss:2.42882
[36m(train_xgb_ray_tune pid=1821680)[0m [191]	train-mlogloss:2.01906	validation-mlogloss:1.97619
[36m(train_xgb_ray_tune pid=1821671)[0m [196]	train-mlogloss:2.31459	validation-mlogloss:2.29524
[36m(train_xgb_ray_tune pid=1821686)[0m [216]	train-mlogloss:2.33184	validation-mlogloss:2.31454

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:42:54. Total running time: 25s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             22.1076 │
│ time_total_s                 22.1076 │
│ training_iteration                 1 │
│ validation_accuracy          0.26802 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1821684)[0m [214]	train-mlogloss:2.28536	validation-mlogloss:2.26486
[36m(train_xgb_ray_tune pid=1821663)[0m [182]	train-mlogloss:2.15609	validation-mlogloss:2.11476
[36m(train_xgb_ray_tune pid=1821689)[0m [223]	train-mlogloss:2.17962	validation-mlogloss:2.13339
[36m(train_xgb_ray_tune pid=1821673)[0m [281]	train-mlogloss:2.56687	validation-mlogloss:2.58816
[36m(train_xgb_ray_tune pid=1821687)[0m [226]	train-mlogloss:2.14685	validation-mlogloss:2.11295

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:42:55. Total running time: 25s
[36m(train_xgb_ray_tune pid=1821688)[0m [213]	train-mlogloss:2.10739	validation-mlogloss:2.06111
[36m(train_xgb_ray_tune pid=1821672)[0m [184]	train-mlogloss:1.93670	validation-mlogloss:1.90194
[36m(train_xgb_ray_tune pid=1821670)[0m [211]	train-mlogloss:2.01236	validation-mlogloss:1.96964
[36m(train_xgb_ray_tune pid=1821690)[0m [280]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821674)[0m [211]	train-mlogloss:2.08205	validation-mlogloss:2.02593
[36m(train_xgb_ray_tune pid=1821683)[0m [221]	train-mlogloss:2.30799	validation-mlogloss:2.29696
[36m(train_xgb_ray_tune pid=1821691)[0m [201]	train-mlogloss:2.03891	validation-mlogloss:1.99313
[36m(train_xgb_ray_tune pid=1821682)[0m [270]	train-mlogloss:2.40793	validation-mlogloss:2.42876
[36m(train_xgb_ray_tune pid=1821663)[0m [183]	train-mlogloss:2.15450	validation-mlogloss:2.11301
[36m(train_xgb_ray_tune pid=1821691)[0m [202]	train-mlogloss:2.03796	validation-mlogloss:1.99229
[36m(train_xgb_ray_tune pid=1821680)[0m [192]	train-mlogloss:2.01771	validation-mlogloss:1.97507
[36m(train_xgb_ray_tune pid=1821689)[0m [224]	train-mlogloss:2.17834	validation-mlogloss:2.13197
[36m(train_xgb_ray_tune pid=1821689)[0m [225]	train-mlogloss:2.17705	validation-mlogloss:2.13053
[36m(train_xgb_ray_tune pid=1821688)[0m [214]	train-mlogloss:2.10625	validation-mlogloss:2.05992
[36m(train_xgb_ray_tune pid=1821672)[0m [185]	train-mlogloss:1.93532	validation-mlogloss:1.90074
[36m(train_xgb_ray_tune pid=1821672)[0m [186]	train-mlogloss:1.93411	validation-mlogloss:1.89995
[36m(train_xgb_ray_tune pid=1821671)[0m [197]	train-mlogloss:2.31312	validation-mlogloss:2.29353
[36m(train_xgb_ray_tune pid=1821669)[0m [198]	train-mlogloss:2.17146	validation-mlogloss:2.14403
[36m(train_xgb_ray_tune pid=1821669)[0m [199]	train-mlogloss:2.17000	validation-mlogloss:2.14239
[36m(train_xgb_ray_tune pid=1821690)[0m [281]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821690)[0m [282]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821686)[0m [217]	train-mlogloss:2.33085	validation-mlogloss:2.31363
[36m(train_xgb_ray_tune pid=1821686)[0m [218]	train-mlogloss:2.32988	validation-mlogloss:2.31262
[36m(train_xgb_ray_tune pid=1821673)[0m [282]	train-mlogloss:2.56659	validation-mlogloss:2.58788
[36m(train_xgb_ray_tune pid=1821673)[0m [283]	train-mlogloss:2.56659	validation-mlogloss:2.58788
[36m(train_xgb_ray_tune pid=1821682)[0m [271]	train-mlogloss:2.40779	validation-mlogloss:2.42860
[36m(train_xgb_ray_tune pid=1821682)[0m [272]	train-mlogloss:2.40779	validation-mlogloss:2.42860
[36m(train_xgb_ray_tune pid=1821687)[0m [227]	train-mlogloss:2.14570	validation-mlogloss:2.11180
[36m(train_xgb_ray_tune pid=1821670)[0m [212]	train-mlogloss:2.01095	validation-mlogloss:1.96826
[36m(train_xgb_ray_tune pid=1821670)[0m [213]	train-mlogloss:2.00953	validation-mlogloss:1.96692
[36m(train_xgb_ray_tune pid=1821684)[0m [215]	train-mlogloss:2.28448	validation-mlogloss:2.26399
[36m(train_xgb_ray_tune pid=1821684)[0m [216]	train-mlogloss:2.28344	validation-mlogloss:2.26293
[36m(train_xgb_ray_tune pid=1821674)[0m [212]	train-mlogloss:2.08089	validation-mlogloss:2.02478
[36m(train_xgb_ray_tune pid=1821683)[0m [222]	train-mlogloss:2.30727	validation-mlogloss:2.29627
[36m(train_xgb_ray_tune pid=1821680)[0m [193]	train-mlogloss:2.01632	validation-mlogloss:1.97386
[36m(train_xgb_ray_tune pid=1821669)[0m [200]	train-mlogloss:2.16853	validation-mlogloss:2.14087
[36m(train_xgb_ray_tune pid=1821687)[0m [228]	train-mlogloss:2.14462	validation-mlogloss:2.11084
[36m(train_xgb_ray_tune pid=1821683)[0m [223]	train-mlogloss:2.30641	validation-mlogloss:2.29537
[36m(train_xgb_ray_tune pid=1821663)[0m [184]	train-mlogloss:2.15290	validation-mlogloss:2.11145
[36m(train_xgb_ray_tune pid=1821688)[0m [215]	train-mlogloss:2.10508	validation-mlogloss:2.05868
[36m(train_xgb_ray_tune pid=1821671)[0m [198]	train-mlogloss:2.31172	validation-mlogloss:2.29202
[36m(train_xgb_ray_tune pid=1821673)[0m [284]	train-mlogloss:2.56659	validation-mlogloss:2.58788
[36m(train_xgb_ray_tune pid=1821674)[0m [213]	train-mlogloss:2.07982	validation-mlogloss:2.02361
[36m(train_xgb_ray_tune pid=1821691)[0m [203]	train-mlogloss:2.03704	validation-mlogloss:1.99147
[36m(train_xgb_ray_tune pid=1821690)[0m [283]	train-mlogloss:2.58839	validation-mlogloss:2.60584
[36m(train_xgb_ray_tune pid=1821670)[0m [214]	train-mlogloss:2.00820	validation-mlogloss:1.96572
[36m(train_xgb_ray_tune pid=1821663)[0m [185]	train-mlogloss:2.15127	validation-mlogloss:2.10979
[36m(train_xgb_ray_tune pid=1821691)[0m [204]	train-mlogloss:2.03599	validation-mlogloss:1.99037
[36m(train_xgb_ray_tune pid=1821680)[0m [194]	train-mlogloss:2.01502	validation-mlogloss:1.97282
[36m(train_xgb_ray_tune pid=1821689)[0m [226]	train-mlogloss:2.17577	validation-mlogloss:2.12914
[36m(train_xgb_ray_tune pid=1821688)[0m [216]	train-mlogloss:2.10408	validation-mlogloss:2.05780
[36m(train_xgb_ray_tune pid=1821672)[0m [187]	train-mlogloss:1.93299	validation-mlogloss:1.89900
[36m(train_xgb_ray_tune pid=1821672)[0m [188]	train-mlogloss:1.93174	validation-mlogloss:1.89820
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[36m(train_xgb_ray_tune pid=1821686)[0m [228]	train-mlogloss:2.32099	validation-mlogloss:2.30356
[36m(train_xgb_ray_tune pid=1821673)[0m [296]	train-mlogloss:2.56617	validation-mlogloss:2.58749
[36m(train_xgb_ray_tune pid=1821673)[0m [297]	train-mlogloss:2.56602	validation-mlogloss:2.58736
[36m(train_xgb_ray_tune pid=1821682)[0m [285]	train-mlogloss:2.40640	validation-mlogloss:2.42703
[36m(train_xgb_ray_tune pid=1821682)[0m [286]	train-mlogloss:2.40640	validation-mlogloss:2.42703
[36m(train_xgb_ray_tune pid=1821687)[0m [238]	train-mlogloss:2.13422	validation-mlogloss:2.09961
[36m(train_xgb_ray_tune pid=1821670)[0m [224]	train-mlogloss:1.99516	validation-mlogloss:1.95371
[36m(train_xgb_ray_tune pid=1821684)[0m [226]	train-mlogloss:2.27399	validation-mlogloss:2.25360
[36m(train_xgb_ray_tune pid=1821684)[0m [227]	train-mlogloss:2.27317	validation-mlogloss:2.25281
[36m(train_xgb_ray_tune pid=1821674)[0m [223]	train-mlogloss:2.06842	validation-mlogloss:2.01218
[36m(train_xgb_ray_tune pid=1821674)[0m [224]	train-mlogloss:2.06727	validation-mlogloss:2.01108
[36m(train_xgb_ray_tune pid=1821683)[0m [233]	train-mlogloss:2.29931	validation-mlogloss:2.28792
[36m(train_xgb_ray_tune pid=1821683)[0m [234]	train-mlogloss:2.29875	validation-mlogloss:2.28737
[36m(train_xgb_ray_tune pid=1821691)[0m [213]	train-mlogloss:2.02685	validation-mlogloss:1.98165
[36m(train_xgb_ray_tune pid=1821680)[0m [202]	train-mlogloss:2.00460	validation-mlogloss:1.96337
[36m(train_xgb_ray_tune pid=1821672)[0m [196]	train-mlogloss:1.92266	validation-mlogloss:1.89079
[36m(train_xgb_ray_tune pid=1821687)[0m [239]	train-mlogloss:2.13307	validation-mlogloss:2.09850
[36m(train_xgb_ray_tune pid=1821670)[0m [225]	train-mlogloss:1.99392	validation-mlogloss:1.95255
[36m(train_xgb_ray_tune pid=1821671)[0m [209]	train-mlogloss:2.29650	validation-mlogloss:2.27586
[36m(train_xgb_ray_tune pid=1821669)[0m [213]	train-mlogloss:2.15072	validation-mlogloss:2.12266
[36m(train_xgb_ray_tune pid=1821686)[0m [229]	train-mlogloss:2.32008	validation-mlogloss:2.30275
[36m(train_xgb_ray_tune pid=1821673)[0m [298]	train-mlogloss:2.56594	validation-mlogloss:2.58729
[36m(train_xgb_ray_tune pid=1821689)[0m [236]	train-mlogloss:2.16351	validation-mlogloss:2.11649
[36m(train_xgb_ray_tune pid=1821690)[0m [301]	train-mlogloss:2.58779	validation-mlogloss:2.60543
[36m(train_xgb_ray_tune pid=1821682)[0m [287]	train-mlogloss:2.40640	validation-mlogloss:2.42703
[36m(train_xgb_ray_tune pid=1821683)[0m [235]	train-mlogloss:2.29798	validation-mlogloss:2.28661
[36m(train_xgb_ray_tune pid=1821663)[0m [196]	train-mlogloss:2.13422	validation-mlogloss:2.09253
[36m(train_xgb_ray_tune pid=1821663)[0m [197]	train-mlogloss:2.13261	validation-mlogloss:2.09071
[36m(train_xgb_ray_tune pid=1821691)[0m [214]	train-mlogloss:2.02581	validation-mlogloss:1.98067
[36m(train_xgb_ray_tune pid=1821691)[0m [215]	train-mlogloss:2.02502	validation-mlogloss:1.97982
[36m(train_xgb_ray_tune pid=1821680)[0m [203]	train-mlogloss:2.00335	validation-mlogloss:1.96220
[36m(train_xgb_ray_tune pid=1821689)[0m [237]	train-mlogloss:2.16228	validation-mlogloss:2.11522
[36m(train_xgb_ray_tune pid=1821689)[0m [238]	train-mlogloss:2.16104	validation-mlogloss:2.11385
[36m(train_xgb_ray_tune pid=1821672)[0m [197]	train-mlogloss:1.92157	validation-mlogloss:1.88982
[36m(train_xgb_ray_tune pid=1821671)[0m [210]	train-mlogloss:2.29510	validation-mlogloss:2.27446
[36m(train_xgb_ray_tune pid=1821669)[0m [214]	train-mlogloss:2.14939	validation-mlogloss:2.12124
[36m(train_xgb_ray_tune pid=1821690)[0m [302]	train-mlogloss:2.58779	validation-mlogloss:2.60543
[36m(train_xgb_ray_tune pid=1821690)[0m [303]	train-mlogloss:2.58779	validation-mlogloss:2.60543
[36m(train_xgb_ray_tune pid=1821686)[0m [230]	train-mlogloss:2.31926	validation-mlogloss:2.30193
[36m(train_xgb_ray_tune pid=1821686)[0m [231]	train-mlogloss:2.31841	validation-mlogloss:2.30101
[36m(train_xgb_ray_tune pid=1821673)[0m [299]	train-mlogloss:2.56594	validation-mlogloss:2.58729
[36m(train_xgb_ray_tune pid=1821673)[0m [300]	train-mlogloss:2.56594	validation-mlogloss:2.58729
[36m(train_xgb_ray_tune pid=1821682)[0m [288]	train-mlogloss:2.40640	validation-mlogloss:2.42703
[36m(train_xgb_ray_tune pid=1821682)[0m [289]	train-mlogloss:2.40633	validation-mlogloss:2.42699
[36m(train_xgb_ray_tune pid=1821682)[0m [290]	train-mlogloss:2.40623	validation-mlogloss:2.42686
[36m(train_xgb_ray_tune pid=1821687)[0m [240]	train-mlogloss:2.13199	validation-mlogloss:2.09735
[36m(train_xgb_ray_tune pid=1821687)[0m [241]	train-mlogloss:2.13093	validation-mlogloss:2.09624
[36m(train_xgb_ray_tune pid=1821670)[0m [226]	train-mlogloss:1.99271	validation-mlogloss:1.95138
[36m(train_xgb_ray_tune pid=1821670)[0m [227]	train-mlogloss:1.99132	validation-mlogloss:1.95002
[36m(train_xgb_ray_tune pid=1821684)[0m [228]	train-mlogloss:2.27222	validation-mlogloss:2.25185
[36m(train_xgb_ray_tune pid=1821684)[0m [229]	train-mlogloss:2.27135	validation-mlogloss:2.25106
[36m(train_xgb_ray_tune pid=1821674)[0m [225]	train-mlogloss:2.06615	validation-mlogloss:2.00986
[36m(train_xgb_ray_tune pid=1821674)[0m [226]	train-mlogloss:2.06508	validation-mlogloss:2.00875
[36m(train_xgb_ray_tune pid=1821683)[0m [236]	train-mlogloss:2.29734	validation-mlogloss:2.28599
[36m(train_xgb_ray_tune pid=1821683)[0m [237]	train-mlogloss:2.29671	validation-mlogloss:2.28536
[36m(train_xgb_ray_tune pid=1821680)[0m [204]	train-mlogloss:2.00216	validation-mlogloss:1.96127
[36m(train_xgb_ray_tune pid=1821672)[0m [198]	train-mlogloss:1.92054	validation-mlogloss:1.88896
[36m(train_xgb_ray_tune pid=1821671)[0m [211]	train-mlogloss:2.29371	validation-mlogloss:2.27314
[36m(train_xgb_ray_tune pid=1821669)[0m [215]	train-mlogloss:2.14811	validation-mlogloss:2.11992
[36m(train_xgb_ray_tune pid=1821690)[0m [304]	train-mlogloss:2.58779	validation-mlogloss:2.60543
[36m(train_xgb_ray_tune pid=1821673)[0m [301]	train-mlogloss:2.56594	validation-mlogloss:2.58729
[36m(train_xgb_ray_tune pid=1821682)[0m [291]	train-mlogloss:2.40593	validation-mlogloss:2.42653
[36m(train_xgb_ray_tune pid=1821689)[0m [239]	train-mlogloss:2.15980	validation-mlogloss:2.11256
[36m(train_xgb_ray_tune pid=1821684)[0m [230]	train-mlogloss:2.27055	validation-mlogloss:2.25026
[36m(train_xgb_ray_tune pid=1821663)[0m [198]	train-mlogloss:2.13114	validation-mlogloss:2.08914
[36m(train_xgb_ray_tune pid=1821674)[0m [227]	train-mlogloss:2.06401	validation-mlogloss:2.00769
[36m(train_xgb_ray_tune pid=1821691)[0m [216]	train-mlogloss:2.02408	validation-mlogloss:1.97911
[36m(train_xgb_ray_tune pid=1821690)[0m [305]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821686)[0m [232]	train-mlogloss:2.31760	validation-mlogloss:2.30020
[36m(train_xgb_ray_tune pid=1821682)[0m [292]	train-mlogloss:2.40585	validation-mlogloss:2.42648
[36m(train_xgb_ray_tune pid=1821687)[0m [242]	train-mlogloss:2.12997	validation-mlogloss:2.09523
[36m(train_xgb_ray_tune pid=1821670)[0m [228]	train-mlogloss:1.99008	validation-mlogloss:1.94890
[36m(train_xgb_ray_tune pid=1821680)[0m [205]	train-mlogloss:2.00093	validation-mlogloss:1.96018
[36m(train_xgb_ray_tune pid=1821672)[0m [199]	train-mlogloss:1.91950	validation-mlogloss:1.88818
[36m(train_xgb_ray_tune pid=1821673)[0m [302]	train-mlogloss:2.56594	validation-mlogloss:2.58729
[36m(train_xgb_ray_tune pid=1821683)[0m [238]	train-mlogloss:2.29607	validation-mlogloss:2.28472
[36m(train_xgb_ray_tune pid=1821669)[0m [216]	train-mlogloss:2.14675	validation-mlogloss:2.11856
[36m(train_xgb_ray_tune pid=1821663)[0m [199]	train-mlogloss:2.12967	validation-mlogloss:2.08770
[36m(train_xgb_ray_tune pid=1821691)[0m [217]	train-mlogloss:2.02306	validation-mlogloss:1.97820
[36m(train_xgb_ray_tune pid=1821680)[0m [206]	train-mlogloss:1.99957	validation-mlogloss:1.95895
[36m(train_xgb_ray_tune pid=1821689)[0m [240]	train-mlogloss:2.15860	validation-mlogloss:2.11140
[36m(train_xgb_ray_tune pid=1821689)[0m [241]	train-mlogloss:2.15739	validation-mlogloss:2.11006
[36m(train_xgb_ray_tune pid=1821672)[0m [200]	train-mlogloss:1.91844	validation-mlogloss:1.88739
[36m(train_xgb_ray_tune pid=1821671)[0m [212]	train-mlogloss:2.29233	validation-mlogloss:2.27174
[36m(train_xgb_ray_tune pid=1821671)[0m [213]	train-mlogloss:2.29100	validation-mlogloss:2.27020
[36m(train_xgb_ray_tune pid=1821669)[0m [217]	train-mlogloss:2.14533	validation-mlogloss:2.11698
[36m(train_xgb_ray_tune pid=1821690)[0m [306]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821690)[0m [307]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821686)[0m [233]	train-mlogloss:2.31673	validation-mlogloss:2.29932
[36m(train_xgb_ray_tune pid=1821686)[0m [234]	train-mlogloss:2.31587	validation-mlogloss:2.29847
[36m(train_xgb_ray_tune pid=1821673)[0m [303]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821673)[0m [304]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821682)[0m [293]	train-mlogloss:2.40585	validation-mlogloss:2.42648
[36m(train_xgb_ray_tune pid=1821682)[0m [294]	train-mlogloss:2.40585	validation-mlogloss:2.42648
[36m(train_xgb_ray_tune pid=1821682)[0m [295]	train-mlogloss:2.40585	validation-mlogloss:2.42648
[36m(train_xgb_ray_tune pid=1821687)[0m [243]	train-mlogloss:2.12898	validation-mlogloss:2.09430
[36m(train_xgb_ray_tune pid=1821670)[0m [229]	train-mlogloss:1.98884	validation-mlogloss:1.94788
[36m(train_xgb_ray_tune pid=1821684)[0m [231]	train-mlogloss:2.26958	validation-mlogloss:2.24930
[36m(train_xgb_ray_tune pid=1821684)[0m [232]	train-mlogloss:2.26878	validation-mlogloss:2.24853
[36m(train_xgb_ray_tune pid=1821684)[0m [233]	train-mlogloss:2.26793	validation-mlogloss:2.24772
[36m(train_xgb_ray_tune pid=1821674)[0m [228]	train-mlogloss:2.06285	validation-mlogloss:2.00655
[36m(train_xgb_ray_tune pid=1821674)[0m [229]	train-mlogloss:2.06183	validation-mlogloss:2.00560
[36m(train_xgb_ray_tune pid=1821683)[0m [239]	train-mlogloss:2.29543	validation-mlogloss:2.28405
[36m(train_xgb_ray_tune pid=1821683)[0m [240]	train-mlogloss:2.29482	validation-mlogloss:2.28339
[36m(train_xgb_ray_tune pid=1821683)[0m [241]	train-mlogloss:2.29434	validation-mlogloss:2.28298
[36m(train_xgb_ray_tune pid=1821691)[0m [218]	train-mlogloss:2.02215	validation-mlogloss:1.97735
[36m(train_xgb_ray_tune pid=1821687)[0m [244]	train-mlogloss:2.12800	validation-mlogloss:2.09328
[36m(train_xgb_ray_tune pid=1821663)[0m [200]	train-mlogloss:2.12816	validation-mlogloss:2.08609
[36m(train_xgb_ray_tune pid=1821670)[0m [230]	train-mlogloss:1.98759	validation-mlogloss:1.94675
[36m(train_xgb_ray_tune pid=1821690)[0m [308]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821684)[0m [234]	train-mlogloss:2.26707	validation-mlogloss:2.24679
[36m(train_xgb_ray_tune pid=1821663)[0m [201]	train-mlogloss:2.12661	validation-mlogloss:2.08451
[36m(train_xgb_ray_tune pid=1821691)[0m [219]	train-mlogloss:2.02125	validation-mlogloss:1.97639
[36m(train_xgb_ray_tune pid=1821680)[0m [207]	train-mlogloss:1.99832	validation-mlogloss:1.95773
[36m(train_xgb_ray_tune pid=1821680)[0m [208]	train-mlogloss:1.99700	validation-mlogloss:1.95641
[36m(train_xgb_ray_tune pid=1821689)[0m [242]	train-mlogloss:2.15628	validation-mlogloss:2.10901
[36m(train_xgb_ray_tune pid=1821689)[0m [243]	train-mlogloss:2.15512	validation-mlogloss:2.10789
[36m(train_xgb_ray_tune pid=1821672)[0m [201]	train-mlogloss:1.91743	validation-mlogloss:1.88649
[36m(train_xgb_ray_tune pid=1821672)[0m [202]	train-mlogloss:1.91632	validation-mlogloss:1.88536
[36m(train_xgb_ray_tune pid=1821671)[0m [214]	train-mlogloss:2.28964	validation-mlogloss:2.26883
[36m(train_xgb_ray_tune pid=1821671)[0m [215]	train-mlogloss:2.28829	validation-mlogloss:2.26730
[36m(train_xgb_ray_tune pid=1821669)[0m [218]	train-mlogloss:2.14403	validation-mlogloss:2.11555
[36m(train_xgb_ray_tune pid=1821669)[0m [219]	train-mlogloss:2.14264	validation-mlogloss:2.11408
[36m(train_xgb_ray_tune pid=1821690)[0m [309]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821690)[0m [310]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821686)[0m [235]	train-mlogloss:2.31505	validation-mlogloss:2.29762
[36m(train_xgb_ray_tune pid=1821686)[0m [236]	train-mlogloss:2.31427	validation-mlogloss:2.29688
[36m(train_xgb_ray_tune pid=1821673)[0m [305]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821673)[0m [306]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821673)[0m [307]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821682)[0m [296]	train-mlogloss:2.40585	validation-mlogloss:2.42648
[36m(train_xgb_ray_tune pid=1821682)[0m [297]	train-mlogloss:2.40585	validation-mlogloss:2.42648
[36m(train_xgb_ray_tune pid=1821682)[0m [298]	train-mlogloss:2.40585	validation-mlogloss:2.42648
[36m(train_xgb_ray_tune pid=1821687)[0m [245]	train-mlogloss:2.12700	validation-mlogloss:2.09231
[36m(train_xgb_ray_tune pid=1821687)[0m [246]	train-mlogloss:2.12596	validation-mlogloss:2.09133
[36m(train_xgb_ray_tune pid=1821670)[0m [231]	train-mlogloss:1.98636	validation-mlogloss:1.94560
[36m(train_xgb_ray_tune pid=1821670)[0m [232]	train-mlogloss:1.98514	validation-mlogloss:1.94459
[36m(train_xgb_ray_tune pid=1821684)[0m [235]	train-mlogloss:2.26619	validation-mlogloss:2.24592
[36m(train_xgb_ray_tune pid=1821684)[0m [236]	train-mlogloss:2.26525	validation-mlogloss:2.24496
[36m(train_xgb_ray_tune pid=1821674)[0m [230]	train-mlogloss:2.06090	validation-mlogloss:2.00475
[36m(train_xgb_ray_tune pid=1821674)[0m [231]	train-mlogloss:2.06001	validation-mlogloss:2.00405
[36m(train_xgb_ray_tune pid=1821683)[0m [242]	train-mlogloss:2.29363	validation-mlogloss:2.28225
[36m(train_xgb_ray_tune pid=1821683)[0m [243]	train-mlogloss:2.29296	validation-mlogloss:2.28158
[36m(train_xgb_ray_tune pid=1821683)[0m [244]	train-mlogloss:2.29252	validation-mlogloss:2.28115
[36m(train_xgb_ray_tune pid=1821683)[0m [245]	train-mlogloss:2.29201	validation-mlogloss:2.28065
[36m(train_xgb_ray_tune pid=1821691)[0m [220]	train-mlogloss:2.02024	validation-mlogloss:1.97547
[36m(train_xgb_ray_tune pid=1821663)[0m [202]	train-mlogloss:2.12515	validation-mlogloss:2.08289
[36m(train_xgb_ray_tune pid=1821684)[0m [237]	train-mlogloss:2.26438	validation-mlogloss:2.24400
[36m(train_xgb_ray_tune pid=1821663)[0m [203]	train-mlogloss:2.12365	validation-mlogloss:2.08131

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:42:56. Total running time: 27s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             23.7949 │
│ time_total_s                 23.7949 │
│ training_iteration                 1 │
│ validation_accuracy          0.46099 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1821691)[0m [221]	train-mlogloss:2.01940	validation-mlogloss:1.97473
[36m(train_xgb_ray_tune pid=1821680)[0m [209]	train-mlogloss:1.99578	validation-mlogloss:1.95546
[36m(train_xgb_ray_tune pid=1821680)[0m [210]	train-mlogloss:1.99462	validation-mlogloss:1.95435
[36m(train_xgb_ray_tune pid=1821689)[0m [244]	train-mlogloss:2.15395	validation-mlogloss:2.10678
[36m(train_xgb_ray_tune pid=1821672)[0m [203]	train-mlogloss:1.91538	validation-mlogloss:1.88460
[36m(train_xgb_ray_tune pid=1821672)[0m [204]	train-mlogloss:1.91442	validation-mlogloss:1.88397
[36m(train_xgb_ray_tune pid=1821671)[0m [216]	train-mlogloss:2.28697	validation-mlogloss:2.26596
[36m(train_xgb_ray_tune pid=1821669)[0m [220]	train-mlogloss:2.14131	validation-mlogloss:2.11277
[36m(train_xgb_ray_tune pid=1821669)[0m [221]	train-mlogloss:2.13997	validation-mlogloss:2.11136
[36m(train_xgb_ray_tune pid=1821690)[0m [311]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821690)[0m [312]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821686)[0m [237]	train-mlogloss:2.31337	validation-mlogloss:2.29600
[36m(train_xgb_ray_tune pid=1821686)[0m [238]	train-mlogloss:2.31257	validation-mlogloss:2.29526
[36m(train_xgb_ray_tune pid=1821673)[0m [308]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821673)[0m [309]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821682)[0m [299]	train-mlogloss:2.40585	validation-mlogloss:2.42648
[36m(train_xgb_ray_tune pid=1821682)[0m [300]	train-mlogloss:2.40585	validation-mlogloss:2.42648
[36m(train_xgb_ray_tune pid=1821682)[0m [301]	train-mlogloss:2.40585	validation-mlogloss:2.42648
[36m(train_xgb_ray_tune pid=1821687)[0m [247]	train-mlogloss:2.12504	validation-mlogloss:2.09058
[36m(train_xgb_ray_tune pid=1821687)[0m [248]	train-mlogloss:2.12403	validation-mlogloss:2.08947
[36m(train_xgb_ray_tune pid=1821670)[0m [233]	train-mlogloss:1.98396	validation-mlogloss:1.94355
[36m(train_xgb_ray_tune pid=1821684)[0m [238]	train-mlogloss:2.26357	validation-mlogloss:2.24323
[36m(train_xgb_ray_tune pid=1821684)[0m [239]	train-mlogloss:2.26268	validation-mlogloss:2.24231
[36m(train_xgb_ray_tune pid=1821674)[0m [232]	train-mlogloss:2.05910	validation-mlogloss:2.00318
[36m(train_xgb_ray_tune pid=1821674)[0m [233]	train-mlogloss:2.05800	validation-mlogloss:2.00219
[36m(train_xgb_ray_tune pid=1821683)[0m [246]	train-mlogloss:2.29144	validation-mlogloss:2.28011
[36m(train_xgb_ray_tune pid=1821683)[0m [247]	train-mlogloss:2.29092	validation-mlogloss:2.27957
[36m(train_xgb_ray_tune pid=1821691)[0m [222]	train-mlogloss:2.01841	validation-mlogloss:1.97382
[36m(train_xgb_ray_tune pid=1821689)[0m [245]	train-mlogloss:2.15277	validation-mlogloss:2.10549
[36m(train_xgb_ray_tune pid=1821690)[0m [313]	train-mlogloss:2.58765	validation-mlogloss:2.60532

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:42:56. Total running time: 27s
[36m(train_xgb_ray_tune pid=1821674)[0m [234]	train-mlogloss:2.05692	validation-mlogloss:2.00110
[36m(train_xgb_ray_tune pid=1821663)[0m [204]	train-mlogloss:2.12215	validation-mlogloss:2.07969
[36m(train_xgb_ray_tune pid=1821691)[0m [223]	train-mlogloss:2.01776	validation-mlogloss:1.97335
[36m(train_xgb_ray_tune pid=1821680)[0m [211]	train-mlogloss:1.99350	validation-mlogloss:1.95325
[36m(train_xgb_ray_tune pid=1821689)[0m [246]	train-mlogloss:2.15159	validation-mlogloss:2.10429
[36m(train_xgb_ray_tune pid=1821672)[0m [205]	train-mlogloss:1.91335	validation-mlogloss:1.88306
[36m(train_xgb_ray_tune pid=1821671)[0m [217]	train-mlogloss:2.28556	validation-mlogloss:2.26449
[36m(train_xgb_ray_tune pid=1821671)[0m [218]	train-mlogloss:2.28424	validation-mlogloss:2.26306
[36m(train_xgb_ray_tune pid=1821669)[0m [222]	train-mlogloss:2.13874	validation-mlogloss:2.11029
[36m(train_xgb_ray_tune pid=1821690)[0m [314]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821690)[0m [315]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821686)[0m [239]	train-mlogloss:2.31170	validation-mlogloss:2.29440
[36m(train_xgb_ray_tune pid=1821686)[0m [240]	train-mlogloss:2.31095	validation-mlogloss:2.29371
[36m(train_xgb_ray_tune pid=1821686)[0m [241]	train-mlogloss:2.31007	validation-mlogloss:2.29290
[36m(train_xgb_ray_tune pid=1821673)[0m [310]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821673)[0m [311]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821682)[0m [302]	train-mlogloss:2.40576	validation-mlogloss:2.42636
[36m(train_xgb_ray_tune pid=1821682)[0m [303]	train-mlogloss:2.40576	validation-mlogloss:2.42636
[36m(train_xgb_ray_tune pid=1821682)[0m [304]	train-mlogloss:2.40576	validation-mlogloss:2.42636
[36m(train_xgb_ray_tune pid=1821687)[0m [249]	train-mlogloss:2.12292	validation-mlogloss:2.08827
[36m(train_xgb_ray_tune pid=1821687)[0m [250]	train-mlogloss:2.12189	validation-mlogloss:2.08731
[36m(train_xgb_ray_tune pid=1821670)[0m [234]	train-mlogloss:1.98275	validation-mlogloss:1.94260
[36m(train_xgb_ray_tune pid=1821670)[0m [235]	train-mlogloss:1.98146	validation-mlogloss:1.94142
[36m(train_xgb_ray_tune pid=1821684)[0m [240]	train-mlogloss:2.26188	validation-mlogloss:2.24155
[36m(train_xgb_ray_tune pid=1821684)[0m [241]	train-mlogloss:2.26098	validation-mlogloss:2.24076
[36m(train_xgb_ray_tune pid=1821674)[0m [235]	train-mlogloss:2.05589	validation-mlogloss:2.00010
[36m(train_xgb_ray_tune pid=1821674)[0m [236]	train-mlogloss:2.05488	validation-mlogloss:1.99918
[36m(train_xgb_ray_tune pid=1821683)[0m [248]	train-mlogloss:2.29044	validation-mlogloss:2.27913
[36m(train_xgb_ray_tune pid=1821683)[0m [249]	train-mlogloss:2.28983	validation-mlogloss:2.27852
[36m(train_xgb_ray_tune pid=1821683)[0m [250]	train-mlogloss:2.28932	validation-mlogloss:2.27800
[36m(train_xgb_ray_tune pid=1821663)[0m [205]	train-mlogloss:2.12063	validation-mlogloss:2.07811
[36m(train_xgb_ray_tune pid=1821663)[0m [206]	train-mlogloss:2.11922	validation-mlogloss:2.07672
[36m(train_xgb_ray_tune pid=1821691)[0m [224]	train-mlogloss:2.01692	validation-mlogloss:1.97271
[36m(train_xgb_ray_tune pid=1821691)[0m [225]	train-mlogloss:2.01615	validation-mlogloss:1.97203
[36m(train_xgb_ray_tune pid=1821680)[0m [212]	train-mlogloss:1.99228	validation-mlogloss:1.95199
[36m(train_xgb_ray_tune pid=1821680)[0m [213]	train-mlogloss:1.99110	validation-mlogloss:1.95106
[36m(train_xgb_ray_tune pid=1821689)[0m [247]	train-mlogloss:2.15050	validation-mlogloss:2.10315
[36m(train_xgb_ray_tune pid=1821689)[0m [248]	train-mlogloss:2.14936	validation-mlogloss:2.10208
[36m(train_xgb_ray_tune pid=1821672)[0m [206]	train-mlogloss:1.91237	validation-mlogloss:1.88221
[36m(train_xgb_ray_tune pid=1821672)[0m [207]	train-mlogloss:1.91140	validation-mlogloss:1.88129
[36m(train_xgb_ray_tune pid=1821671)[0m [219]	train-mlogloss:2.28294	validation-mlogloss:2.26164
[36m(train_xgb_ray_tune pid=1821669)[0m [223]	train-mlogloss:2.13750	validation-mlogloss:2.10900
[36m(train_xgb_ray_tune pid=1821669)[0m [224]	train-mlogloss:2.13627	validation-mlogloss:2.10771
[36m(train_xgb_ray_tune pid=1821690)[0m [316]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821690)[0m [317]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821686)[0m [242]	train-mlogloss:2.30915	validation-mlogloss:2.29198
[36m(train_xgb_ray_tune pid=1821686)[0m [243]	train-mlogloss:2.30829	validation-mlogloss:2.29103
[36m(train_xgb_ray_tune pid=1821673)[0m [312]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821673)[0m [313]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821682)[0m [305]	train-mlogloss:2.40576	validation-mlogloss:2.42636
[36m(train_xgb_ray_tune pid=1821682)[0m [306]	train-mlogloss:2.40568	validation-mlogloss:2.42626
[36m(train_xgb_ray_tune pid=1821687)[0m [251]	train-mlogloss:2.12102	validation-mlogloss:2.08645
[36m(train_xgb_ray_tune pid=1821687)[0m [252]	train-mlogloss:2.12003	validation-mlogloss:2.08544
[36m(train_xgb_ray_tune pid=1821670)[0m [236]	train-mlogloss:1.98030	validation-mlogloss:1.94054
[36m(train_xgb_ray_tune pid=1821670)[0m [237]	train-mlogloss:1.97905	validation-mlogloss:1.93933
[36m(train_xgb_ray_tune pid=1821684)[0m [242]	train-mlogloss:2.26011	validation-mlogloss:2.23989
[36m(train_xgb_ray_tune pid=1821684)[0m [243]	train-mlogloss:2.25924	validation-mlogloss:2.23906
[36m(train_xgb_ray_tune pid=1821674)[0m [237]	train-mlogloss:2.05385	validation-mlogloss:1.99804
[36m(train_xgb_ray_tune pid=1821674)[0m [238]	train-mlogloss:2.05284	validation-mlogloss:1.99709
[36m(train_xgb_ray_tune pid=1821683)[0m [251]	train-mlogloss:2.28868	validation-mlogloss:2.27744
[36m(train_xgb_ray_tune pid=1821683)[0m [252]	train-mlogloss:2.28807	validation-mlogloss:2.27687
[36m(train_xgb_ray_tune pid=1821669)[0m [225]	train-mlogloss:2.13506	validation-mlogloss:2.10651
[36m(train_xgb_ray_tune pid=1821686)[0m [244]	train-mlogloss:2.30759	validation-mlogloss:2.29035
[36m(train_xgb_ray_tune pid=1821673)[0m [314]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821691)[0m [226]	train-mlogloss:2.01520	validation-mlogloss:1.97143
[36m(train_xgb_ray_tune pid=1821682)[0m [307]	train-mlogloss:2.40568	validation-mlogloss:2.42626
[36m(train_xgb_ray_tune pid=1821684)[0m [244]	train-mlogloss:2.25847	validation-mlogloss:2.23840
[36m(train_xgb_ray_tune pid=1821671)[0m [220]	train-mlogloss:2.28159	validation-mlogloss:2.26027
[36m(train_xgb_ray_tune pid=1821689)[0m [249]	train-mlogloss:2.14822	validation-mlogloss:2.10091
[36m(train_xgb_ray_tune pid=1821672)[0m [208]	train-mlogloss:1.91042	validation-mlogloss:1.88041
[36m(train_xgb_ray_tune pid=1821690)[0m [318]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821683)[0m [253]	train-mlogloss:2.28751	validation-mlogloss:2.27628
[36m(train_xgb_ray_tune pid=1821663)[0m [207]	train-mlogloss:2.11781	validation-mlogloss:2.07530
[36m(train_xgb_ray_tune pid=1821687)[0m [253]	train-mlogloss:2.11911	validation-mlogloss:2.08474
[36m(train_xgb_ray_tune pid=1821674)[0m [239]	train-mlogloss:2.05194	validation-mlogloss:1.99637
[36m(train_xgb_ray_tune pid=1821670)[0m [238]	train-mlogloss:1.97792	validation-mlogloss:1.93805
[36m(train_xgb_ray_tune pid=1821673)[0m [315]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821682)[0m [308]	train-mlogloss:2.40568	validation-mlogloss:2.42626
[36m(train_xgb_ray_tune pid=1821663)[0m [208]	train-mlogloss:2.11642	validation-mlogloss:2.07387
[36m(train_xgb_ray_tune pid=1821691)[0m [227]	train-mlogloss:2.01440	validation-mlogloss:1.97067
[36m(train_xgb_ray_tune pid=1821691)[0m [228]	train-mlogloss:2.01350	validation-mlogloss:1.96996
[36m(train_xgb_ray_tune pid=1821680)[0m [214]	train-mlogloss:1.98986	validation-mlogloss:1.94987
[36m(train_xgb_ray_tune pid=1821680)[0m [215]	train-mlogloss:1.98850	validation-mlogloss:1.94886
[36m(train_xgb_ray_tune pid=1821689)[0m [250]	train-mlogloss:2.14708	validation-mlogloss:2.09971
[36m(train_xgb_ray_tune pid=1821672)[0m [209]	train-mlogloss:1.90953	validation-mlogloss:1.87958
[36m(train_xgb_ray_tune pid=1821671)[0m [221]	train-mlogloss:2.28032	validation-mlogloss:2.25893
[36m(train_xgb_ray_tune pid=1821669)[0m [226]	train-mlogloss:2.13371	validation-mlogloss:2.10499
[36m(train_xgb_ray_tune pid=1821669)[0m [227]	train-mlogloss:2.13237	validation-mlogloss:2.10359
[36m(train_xgb_ray_tune pid=1821690)[0m [319]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821690)[0m [320]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821686)[0m [245]	train-mlogloss:2.30673	validation-mlogloss:2.28955
[36m(train_xgb_ray_tune pid=1821686)[0m [246]	train-mlogloss:2.30590	validation-mlogloss:2.28873
[36m(train_xgb_ray_tune pid=1821686)[0m [247]	train-mlogloss:2.30515	validation-mlogloss:2.28800
[36m(train_xgb_ray_tune pid=1821673)[0m [316]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821673)[0m [317]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821682)[0m [309]	train-mlogloss:2.40568	validation-mlogloss:2.42626
[36m(train_xgb_ray_tune pid=1821682)[0m [310]	train-mlogloss:2.40568	validation-mlogloss:2.42626
[36m(train_xgb_ray_tune pid=1821682)[0m [311]	train-mlogloss:2.40568	validation-mlogloss:2.42626
[36m(train_xgb_ray_tune pid=1821687)[0m [254]	train-mlogloss:2.11811	validation-mlogloss:2.08375
[36m(train_xgb_ray_tune pid=1821670)[0m [239]	train-mlogloss:1.97664	validation-mlogloss:1.93683
[36m(train_xgb_ray_tune pid=1821670)[0m [240]	train-mlogloss:1.97552	validation-mlogloss:1.93575
[36m(train_xgb_ray_tune pid=1821684)[0m [245]	train-mlogloss:2.25767	validation-mlogloss:2.23768
[36m(train_xgb_ray_tune pid=1821684)[0m [246]	train-mlogloss:2.25694	validation-mlogloss:2.23701
[36m(train_xgb_ray_tune pid=1821674)[0m [240]	train-mlogloss:2.05103	validation-mlogloss:1.99552
[36m(train_xgb_ray_tune pid=1821674)[0m [241]	train-mlogloss:2.04994	validation-mlogloss:1.99442
[36m(train_xgb_ray_tune pid=1821683)[0m [254]	train-mlogloss:2.28710	validation-mlogloss:2.27590
[36m(train_xgb_ray_tune pid=1821683)[0m [255]	train-mlogloss:2.28644	validation-mlogloss:2.27514
[36m(train_xgb_ray_tune pid=1821689)[0m [251]	train-mlogloss:2.14596	validation-mlogloss:2.09859
[36m(train_xgb_ray_tune pid=1821672)[0m [210]	train-mlogloss:1.90865	validation-mlogloss:1.87892
[36m(train_xgb_ray_tune pid=1821671)[0m [222]	train-mlogloss:2.27901	validation-mlogloss:2.25752
[36m(train_xgb_ray_tune pid=1821687)[0m [255]	train-mlogloss:2.11716	validation-mlogloss:2.08275
[36m(train_xgb_ray_tune pid=1821663)[0m [209]	train-mlogloss:2.11505	validation-mlogloss:2.07243
[36m(train_xgb_ray_tune pid=1821663)[0m [210]	train-mlogloss:2.11364	validation-mlogloss:2.07095
[36m(train_xgb_ray_tune pid=1821691)[0m [229]	train-mlogloss:2.01284	validation-mlogloss:1.96951
[36m(train_xgb_ray_tune pid=1821691)[0m [230]	train-mlogloss:2.01209	validation-mlogloss:1.96883
[36m(train_xgb_ray_tune pid=1821680)[0m [216]	train-mlogloss:1.98731	validation-mlogloss:1.94781
[36m(train_xgb_ray_tune pid=1821680)[0m [217]	train-mlogloss:1.98619	validation-mlogloss:1.94673
[36m(train_xgb_ray_tune pid=1821689)[0m [252]	train-mlogloss:2.14483	validation-mlogloss:2.09735
[36m(train_xgb_ray_tune pid=1821672)[0m [211]	train-mlogloss:1.90775	validation-mlogloss:1.87811
[36m(train_xgb_ray_tune pid=1821671)[0m [223]	train-mlogloss:2.27768	validation-mlogloss:2.25615
[36m(train_xgb_ray_tune pid=1821669)[0m [228]	train-mlogloss:2.13116	validation-mlogloss:2.10234
[36m(train_xgb_ray_tune pid=1821690)[0m [321]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821690)[0m [322]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821690)[0m [323]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821686)[0m [248]	train-mlogloss:2.30436	validation-mlogloss:2.28711
[36m(train_xgb_ray_tune pid=1821686)[0m [249]	train-mlogloss:2.30358	validation-mlogloss:2.28629
[36m(train_xgb_ray_tune pid=1821673)[0m [318]	train-mlogloss:2.56571	validation-mlogloss:2.58712
[36m(train_xgb_ray_tune pid=1821673)[0m [319]	train-mlogloss:2.56563	validation-mlogloss:2.58705
[36m(train_xgb_ray_tune pid=1821682)[0m [312]	train-mlogloss:2.40568	validation-mlogloss:2.42626
[36m(train_xgb_ray_tune pid=1821682)[0m [313]	train-mlogloss:2.40553	validation-mlogloss:2.42613
[36m(train_xgb_ray_tune pid=1821682)[0m [314]	train-mlogloss:2.40544	validation-mlogloss:2.42601
[36m(train_xgb_ray_tune pid=1821687)[0m [256]	train-mlogloss:2.11635	validation-mlogloss:2.08184
[36m(train_xgb_ray_tune pid=1821670)[0m [241]	train-mlogloss:1.97434	validation-mlogloss:1.93458
[36m(train_xgb_ray_tune pid=1821670)[0m [242]	train-mlogloss:1.97321	validation-mlogloss:1.93353
[36m(train_xgb_ray_tune pid=1821684)[0m [247]	train-mlogloss:2.25613	validation-mlogloss:2.23622
[36m(train_xgb_ray_tune pid=1821684)[0m [248]	train-mlogloss:2.25544	validation-mlogloss:2.23556
[36m(train_xgb_ray_tune pid=1821674)[0m [242]	train-mlogloss:2.04897	validation-mlogloss:1.99347
[36m(train_xgb_ray_tune pid=1821674)[0m [243]	train-mlogloss:2.04808	validation-mlogloss:1.99279
[36m(train_xgb_ray_tune pid=1821683)[0m [256]	train-mlogloss:2.28593	validation-mlogloss:2.27458
[36m(train_xgb_ray_tune pid=1821683)[0m [257]	train-mlogloss:2.28533	validation-mlogloss:2.27400
[36m(train_xgb_ray_tune pid=1821669)[0m [229]	train-mlogloss:2.12999	validation-mlogloss:2.10131
[36m(train_xgb_ray_tune pid=1821673)[0m [320]	train-mlogloss:2.56563	validation-mlogloss:2.58705
[36m(train_xgb_ray_tune pid=1821687)[0m [257]	train-mlogloss:2.11532	validation-mlogloss:2.08070
[36m(train_xgb_ray_tune pid=1821683)[0m [258]	train-mlogloss:2.28469	validation-mlogloss:2.27326
[36m(train_xgb_ray_tune pid=1821689)[0m [253]	train-mlogloss:2.14370	validation-mlogloss:2.09621
[36m(train_xgb_ray_tune pid=1821682)[0m [315]	train-mlogloss:2.40530	validation-mlogloss:2.42589
[36m(train_xgb_ray_tune pid=1821686)[0m [250]	train-mlogloss:2.30282	validation-mlogloss:2.28550
[36m(train_xgb_ray_tune pid=1821672)[0m [212]	train-mlogloss:1.90685	validation-mlogloss:1.87738
[36m(train_xgb_ray_tune pid=1821684)[0m [249]	train-mlogloss:2.25464	validation-mlogloss:2.23479
[36m(train_xgb_ray_tune pid=1821674)[0m [244]	train-mlogloss:2.04710	validation-mlogloss:1.99184
[36m(train_xgb_ray_tune pid=1821691)[0m [231]	train-mlogloss:2.01125	validation-mlogloss:1.96797
[36m(train_xgb_ray_tune pid=1821671)[0m [224]	train-mlogloss:2.27643	validation-mlogloss:2.25481
[36m(train_xgb_ray_tune pid=1821690)[0m [324]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821673)[0m [321]	train-mlogloss:2.56555	validation-mlogloss:2.58699
[36m(train_xgb_ray_tune pid=1821670)[0m [243]	train-mlogloss:1.97200	validation-mlogloss:1.93244
[36m(train_xgb_ray_tune pid=1821663)[0m [211]	train-mlogloss:2.11220	validation-mlogloss:2.06954
[36m(train_xgb_ray_tune pid=1821663)[0m [212]	train-mlogloss:2.11078	validation-mlogloss:2.06824
[36m(train_xgb_ray_tune pid=1821691)[0m [232]	train-mlogloss:2.01043	validation-mlogloss:1.96716
[36m(train_xgb_ray_tune pid=1821680)[0m [218]	train-mlogloss:1.98500	validation-mlogloss:1.94560
[36m(train_xgb_ray_tune pid=1821680)[0m [219]	train-mlogloss:1.98383	validation-mlogloss:1.94441
[36m(train_xgb_ray_tune pid=1821689)[0m [254]	train-mlogloss:2.14261	validation-mlogloss:2.09508
[36m(train_xgb_ray_tune pid=1821689)[0m [255]	train-mlogloss:2.14141	validation-mlogloss:2.09376
[36m(train_xgb_ray_tune pid=1821672)[0m [213]	train-mlogloss:1.90586	validation-mlogloss:1.87667
[36m(train_xgb_ray_tune pid=1821671)[0m [225]	train-mlogloss:2.27513	validation-mlogloss:2.25347
[36m(train_xgb_ray_tune pid=1821669)[0m [230]	train-mlogloss:2.12870	validation-mlogloss:2.09997
[36m(train_xgb_ray_tune pid=1821669)[0m [231]	train-mlogloss:2.12742	validation-mlogloss:2.09862
[36m(train_xgb_ray_tune pid=1821690)[0m [325]	train-mlogloss:2.58765	validation-mlogloss:2.60532
[36m(train_xgb_ray_tune pid=1821686)[0m [251]	train-mlogloss:2.30196	validation-mlogloss:2.28467
[36m(train_xgb_ray_tune pid=1821686)[0m [252]	train-mlogloss:2.30116	validation-mlogloss:2.28385
[36m(train_xgb_ray_tune pid=1821673)[0m [322]	train-mlogloss:2.56540	validation-mlogloss:2.58690
[36m(train_xgb_ray_tune pid=1821673)[0m [323]	train-mlogloss:2.56540	validation-mlogloss:2.58690
[36m(train_xgb_ray_tune pid=1821682)[0m [316]	train-mlogloss:2.40509	validation-mlogloss:2.42575
[36m(train_xgb_ray_tune pid=1821682)[0m [317]	train-mlogloss:2.40493	validation-mlogloss:2.42556
[36m(train_xgb_ray_tune pid=1821687)[0m [258]	train-mlogloss:2.11430	validation-mlogloss:2.07972
[36m(train_xgb_ray_tune pid=1821687)[0m [259]	train-mlogloss:2.11335	validation-mlogloss:2.07870
[36m(train_xgb_ray_tune pid=1821670)[0m [244]	train-mlogloss:1.97085	validation-mlogloss:1.93147
[36m(train_xgb_ray_tune pid=1821684)[0m [250]	train-mlogloss:2.25390	validation-mlogloss:2.23406
[36m(train_xgb_ray_tune pid=1821684)[0m [251]	train-mlogloss:2.25321	validation-mlogloss:2.23338
[36m(train_xgb_ray_tune pid=1821674)[0m [245]	train-mlogloss:2.04635	validation-mlogloss:1.99123
[36m(train_xgb_ray_tune pid=1821674)[0m [246]	train-mlogloss:2.04548	validation-mlogloss:1.99035
[36m(train_xgb_ray_tune pid=1821674)[0m [247]	train-mlogloss:2.04444	validation-mlogloss:1.98934
[36m(train_xgb_ray_tune pid=1821683)[0m [259]	train-mlogloss:2.28414	validation-mlogloss:2.27279
[36m(train_xgb_ray_tune pid=1821683)[0m [260]	train-mlogloss:2.28356	validation-mlogloss:2.27220
[36m(train_xgb_ray_tune pid=1821691)[0m [233]	train-mlogloss:2.00970	validation-mlogloss:1.96659
[36m(train_xgb_ray_tune pid=1821672)[0m [214]	train-mlogloss:1.90519	validation-mlogloss:1.87603
[36m(train_xgb_ray_tune pid=1821682)[0m [318]	train-mlogloss:2.40493	validation-mlogloss:2.42556
[36m(train_xgb_ray_tune pid=1821673)[0m [324]	train-mlogloss:2.56540	validation-mlogloss:2.58690
[36m(train_xgb_ray_tune pid=1821663)[0m [213]	train-mlogloss:2.10941	validation-mlogloss:2.06690
[36m(train_xgb_ray_tune pid=1821691)[0m [234]	train-mlogloss:2.00888	validation-mlogloss:1.96589
[36m(train_xgb_ray_tune pid=1821680)[0m [220]	train-mlogloss:1.98273	validation-mlogloss:1.94359
[36m(train_xgb_ray_tune pid=1821689)[0m [256]	train-mlogloss:2.14033	validation-mlogloss:2.09270
[36m(train_xgb_ray_tune pid=1821672)[0m [215]	train-mlogloss:1.90419	validation-mlogloss:1.87545
[36m(train_xgb_ray_tune pid=1821671)[0m [226]	train-mlogloss:2.27383	validation-mlogloss:2.25216
[36m(train_xgb_ray_tune pid=1821671)[0m [227]	train-mlogloss:2.27251	validation-mlogloss:2.25080
[36m(train_xgb_ray_tune pid=1821669)[0m [232]	train-mlogloss:2.12624	validation-mlogloss:2.09735
[36m(train_xgb_ray_tune pid=1821686)[0m [253]	train-mlogloss:2.30046	validation-mlogloss:2.28312
[36m(train_xgb_ray_tune pid=1821673)[0m [325]	train-mlogloss:2.56540	validation-mlogloss:2.58690
[36m(train_xgb_ray_tune pid=1821673)[0m [326]	train-mlogloss:2.56540	validation-mlogloss:2.58690
[36m(train_xgb_ray_tune pid=1821682)[0m [319]	train-mlogloss:2.40493	validation-mlogloss:2.42556
[36m(train_xgb_ray_tune pid=1821682)[0m [320]	train-mlogloss:2.40493	validation-mlogloss:2.42556
[36m(train_xgb_ray_tune pid=1821687)[0m [260]	train-mlogloss:2.11238	validation-mlogloss:2.07777
[36m(train_xgb_ray_tune pid=1821687)[0m [261]	train-mlogloss:2.11151	validation-mlogloss:2.07686
[36m(train_xgb_ray_tune pid=1821670)[0m [245]	train-mlogloss:1.96974	validation-mlogloss:1.93073
[36m(train_xgb_ray_tune pid=1821670)[0m [246]	train-mlogloss:1.96855	validation-mlogloss:1.92947
[36m(train_xgb_ray_tune pid=1821684)[0m [252]	train-mlogloss:2.25238	validation-mlogloss:2.23264
[36m(train_xgb_ray_tune pid=1821684)[0m [253]	train-mlogloss:2.25153	validation-mlogloss:2.23173
[36m(train_xgb_ray_tune pid=1821674)[0m [248]	train-mlogloss:2.04351	validation-mlogloss:1.98844
[36m(train_xgb_ray_tune pid=1821674)[0m [249]	train-mlogloss:2.04247	validation-mlogloss:1.98737
[36m(train_xgb_ray_tune pid=1821674)[0m [250]	train-mlogloss:2.04162	validation-mlogloss:1.98646
[36m(train_xgb_ray_tune pid=1821683)[0m [261]	train-mlogloss:2.28307	validation-mlogloss:2.27179
[36m(train_xgb_ray_tune pid=1821683)[0m [262]	train-mlogloss:2.28248	validation-mlogloss:2.27120
[36m(train_xgb_ray_tune pid=1821691)[0m [235]	train-mlogloss:2.00804	validation-mlogloss:1.96537
[36m(train_xgb_ray_tune pid=1821689)[0m [257]	train-mlogloss:2.13919	validation-mlogloss:2.09152
[36m(train_xgb_ray_tune pid=1821686)[0m [254]	train-mlogloss:2.29969	validation-mlogloss:2.28233
[36m(train_xgb_ray_tune pid=1821673)[0m [327]	train-mlogloss:2.56533	validation-mlogloss:2.58683
[36m(train_xgb_ray_tune pid=1821680)[0m [221]	train-mlogloss:1.98159	validation-mlogloss:1.94251
[36m(train_xgb_ray_tune pid=1821669)[0m [233]	train-mlogloss:2.12507	validation-mlogloss:2.09612
[36m(train_xgb_ray_tune pid=1821663)[0m [214]	train-mlogloss:2.10804	validation-mlogloss:2.06557
[36m(train_xgb_ray_tune pid=1821683)[0m [263]	train-mlogloss:2.28208	validation-mlogloss:2.27090
[36m(train_xgb_ray_tune pid=1821672)[0m [216]	train-mlogloss:1.90319	validation-mlogloss:1.87464
[36m(train_xgb_ray_tune pid=1821670)[0m [247]	train-mlogloss:1.96735	validation-mlogloss:1.92822
[36m(train_xgb_ray_tune pid=1821673)[0m [328]	train-mlogloss:2.56519	validation-mlogloss:2.58676
[36m(train_xgb_ray_tune pid=1821682)[0m [321]	train-mlogloss:2.40493	validation-mlogloss:2.42556
[36m(train_xgb_ray_tune pid=1821691)[0m [236]	train-mlogloss:2.00730	validation-mlogloss:1.96482
[36m(train_xgb_ray_tune pid=1821687)[0m [262]	train-mlogloss:2.11059	validation-mlogloss:2.07598
[36m(train_xgb_ray_tune pid=1821674)[0m [251]	train-mlogloss:2.04082	validation-mlogloss:1.98581
[36m(train_xgb_ray_tune pid=1821663)[0m [215]	train-mlogloss:2.10662	validation-mlogloss:2.06405
[36m(train_xgb_ray_tune pid=1821691)[0m [237]	train-mlogloss:2.00636	validation-mlogloss:1.96410
[36m(train_xgb_ray_tune pid=1821691)[0m [238]	train-mlogloss:2.00545	validation-mlogloss:1.96323
[36m(train_xgb_ray_tune pid=1821680)[0m [222]	train-mlogloss:1.98052	validation-mlogloss:1.94146
[36m(train_xgb_ray_tune pid=1821689)[0m [258]	train-mlogloss:2.13805	validation-mlogloss:2.09032
[36m(train_xgb_ray_tune pid=1821689)[0m [259]	train-mlogloss:2.13701	validation-mlogloss:2.08934
[36m(train_xgb_ray_tune pid=1821672)[0m [217]	train-mlogloss:1.90223	validation-mlogloss:1.87382
[36m(train_xgb_ray_tune pid=1821672)[0m [218]	train-mlogloss:1.90150	validation-mlogloss:1.87328
[36m(train_xgb_ray_tune pid=1821671)[0m [228]	train-mlogloss:2.27123	validation-mlogloss:2.24944
[36m(train_xgb_ray_tune pid=1821671)[0m [229]	train-mlogloss:2.26997	validation-mlogloss:2.24811
[36m(train_xgb_ray_tune pid=1821669)[0m [234]	train-mlogloss:2.12390	validation-mlogloss:2.09496
[36m(train_xgb_ray_tune pid=1821669)[0m [235]	train-mlogloss:2.12261	validation-mlogloss:2.09363
[36m(train_xgb_ray_tune pid=1821686)[0m [255]	train-mlogloss:2.29888	validation-mlogloss:2.28157
[36m(train_xgb_ray_tune pid=1821686)[0m [256]	train-mlogloss:2.29815	validation-mlogloss:2.28083
[36m(train_xgb_ray_tune pid=1821673)[0m [329]	train-mlogloss:2.56519	validation-mlogloss:2.58676
[36m(train_xgb_ray_tune pid=1821673)[0m [330]	train-mlogloss:2.56503	validation-mlogloss:2.58666
[36m(train_xgb_ray_tune pid=1821682)[0m [322]	train-mlogloss:2.40493	validation-mlogloss:2.42556
[36m(train_xgb_ray_tune pid=1821682)[0m [323]	train-mlogloss:2.40479	validation-mlogloss:2.42541
[36m(train_xgb_ray_tune pid=1821687)[0m [263]	train-mlogloss:2.10968	validation-mlogloss:2.07507
[36m(train_xgb_ray_tune pid=1821670)[0m [248]	train-mlogloss:1.96622	validation-mlogloss:1.92714
[36m(train_xgb_ray_tune pid=1821670)[0m [249]	train-mlogloss:1.96517	validation-mlogloss:1.92624
[36m(train_xgb_ray_tune pid=1821684)[0m [254]	train-mlogloss:2.25081	validation-mlogloss:2.23109
[36m(train_xgb_ray_tune pid=1821684)[0m [255]	train-mlogloss:2.25016	validation-mlogloss:2.23045
[36m(train_xgb_ray_tune pid=1821674)[0m [252]	train-mlogloss:2.03987	validation-mlogloss:1.98485
[36m(train_xgb_ray_tune pid=1821674)[0m [253]	train-mlogloss:2.03892	validation-mlogloss:1.98386
[36m(train_xgb_ray_tune pid=1821683)[0m [264]	train-mlogloss:2.28163	validation-mlogloss:2.27046
[36m(train_xgb_ray_tune pid=1821683)[0m [265]	train-mlogloss:2.28095	validation-mlogloss:2.26962
[36m(train_xgb_ray_tune pid=1821663)[0m [216]	train-mlogloss:2.10515	validation-mlogloss:2.06256
[36m(train_xgb_ray_tune pid=1821680)[0m [223]	train-mlogloss:1.97927	validation-mlogloss:1.94031
[36m(train_xgb_ray_tune pid=1821687)[0m [264]	train-mlogloss:2.10867	validation-mlogloss:2.07414
[36m(train_xgb_ray_tune pid=1821674)[0m [254]	train-mlogloss:2.03792	validation-mlogloss:1.98296
[36m(train_xgb_ray_tune pid=1821686)[0m [257]	train-mlogloss:2.29737	validation-mlogloss:2.28005
[36m(train_xgb_ray_tune pid=1821673)[0m [331]	train-mlogloss:2.56503	validation-mlogloss:2.58666
[36m(train_xgb_ray_tune pid=1821682)[0m [324]	train-mlogloss:2.40470	validation-mlogloss:2.42528
[36m(train_xgb_ray_tune pid=1821684)[0m [256]	train-mlogloss:2.24945	validation-mlogloss:2.22973
[36m(train_xgb_ray_tune pid=1821691)[0m [239]	train-mlogloss:2.00468	validation-mlogloss:1.96243
[36m(train_xgb_ray_tune pid=1821689)[0m [260]	train-mlogloss:2.13596	validation-mlogloss:2.08829
[36m(train_xgb_ray_tune pid=1821683)[0m [266]	train-mlogloss:2.28050	validation-mlogloss:2.26913
[36m(train_xgb_ray_tune pid=1821663)[0m [217]	train-mlogloss:2.10369	validation-mlogloss:2.06105
[36m(train_xgb_ray_tune pid=1821691)[0m [240]	train-mlogloss:2.00400	validation-mlogloss:1.96183
[36m(train_xgb_ray_tune pid=1821691)[0m [241]	train-mlogloss:2.00337	validation-mlogloss:1.96123
[36m(train_xgb_ray_tune pid=1821680)[0m [224]	train-mlogloss:1.97821	validation-mlogloss:1.93934
[36m(train_xgb_ray_tune pid=1821680)[0m [225]	train-mlogloss:1.97712	validation-mlogloss:1.93833
[36m(train_xgb_ray_tune pid=1821689)[0m [261]	train-mlogloss:2.13478	validation-mlogloss:2.08701
[36m(train_xgb_ray_tune pid=1821672)[0m [219]	train-mlogloss:1.90064	validation-mlogloss:1.87259
[36m(train_xgb_ray_tune pid=1821672)[0m [220]	train-mlogloss:1.89990	validation-mlogloss:1.87214
[36m(train_xgb_ray_tune pid=1821671)[0m [230]	train-mlogloss:2.26871	validation-mlogloss:2.24682
[36m(train_xgb_ray_tune pid=1821671)[0m [231]	train-mlogloss:2.26745	validation-mlogloss:2.24554
[36m(train_xgb_ray_tune pid=1821669)[0m [236]	train-mlogloss:2.12133	validation-mlogloss:2.09243
[36m(train_xgb_ray_tune pid=1821669)[0m [237]	train-mlogloss:2.12021	validation-mlogloss:2.09125
[36m(train_xgb_ray_tune pid=1821686)[0m [258]	train-mlogloss:2.29663	validation-mlogloss:2.27928
[36m(train_xgb_ray_tune pid=1821673)[0m [332]	train-mlogloss:2.56503	validation-mlogloss:2.58666
[36m(train_xgb_ray_tune pid=1821673)[0m [333]	train-mlogloss:2.56485	validation-mlogloss:2.58648
[36m(train_xgb_ray_tune pid=1821682)[0m [325]	train-mlogloss:2.40461	validation-mlogloss:2.42516
[36m(train_xgb_ray_tune pid=1821682)[0m [326]	train-mlogloss:2.40454	validation-mlogloss:2.42507
[36m(train_xgb_ray_tune pid=1821687)[0m [265]	train-mlogloss:2.10782	validation-mlogloss:2.07330
[36m(train_xgb_ray_tune pid=1821687)[0m [266]	train-mlogloss:2.10697	validation-mlogloss:2.07245
[36m(train_xgb_ray_tune pid=1821670)[0m [250]	train-mlogloss:1.96410	validation-mlogloss:1.92540
[36m(train_xgb_ray_tune pid=1821670)[0m [251]	train-mlogloss:1.96290	validation-mlogloss:1.92440
[36m(train_xgb_ray_tune pid=1821684)[0m [257]	train-mlogloss:2.24868	validation-mlogloss:2.22898
[36m(train_xgb_ray_tune pid=1821674)[0m [255]	train-mlogloss:2.03721	validation-mlogloss:1.98227
[36m(train_xgb_ray_tune pid=1821674)[0m [256]	train-mlogloss:2.03640	validation-mlogloss:1.98153
[36m(train_xgb_ray_tune pid=1821683)[0m [267]	train-mlogloss:2.28002	validation-mlogloss:2.26870
[36m(train_xgb_ray_tune pid=1821683)[0m [268]	train-mlogloss:2.27964	validation-mlogloss:2.26838
[36m(train_xgb_ray_tune pid=1821686)[0m [259]	train-mlogloss:2.29598	validation-mlogloss:2.27868
[36m(train_xgb_ray_tune pid=1821670)[0m [252]	train-mlogloss:1.96183	validation-mlogloss:1.92331
[36m(train_xgb_ray_tune pid=1821684)[0m [258]	train-mlogloss:2.24801	validation-mlogloss:2.22832
[36m(train_xgb_ray_tune pid=1821689)[0m [262]	train-mlogloss:2.13365	validation-mlogloss:2.08590
[36m(train_xgb_ray_tune pid=1821674)[0m [257]	train-mlogloss:2.03553	validation-mlogloss:1.98088
[36m(train_xgb_ray_tune pid=1821663)[0m [218]	train-mlogloss:2.10242	validation-mlogloss:2.05976
[36m(train_xgb_ray_tune pid=1821673)[0m [334]	train-mlogloss:2.56485	validation-mlogloss:2.58648
[36m(train_xgb_ray_tune pid=1821682)[0m [327]	train-mlogloss:2.40454	validation-mlogloss:2.42507

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:42:58. Total running time: 28s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s              25.243 │
│ time_total_s                  25.243 │
│ training_iteration                 1 │
│ validation_accuracy          0.16577 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:42:58. Total running time: 28s
[36m(train_xgb_ray_tune pid=1821663)[0m [219]	train-mlogloss:2.10109	validation-mlogloss:2.05849
[36m(train_xgb_ray_tune pid=1821691)[0m [242]	train-mlogloss:2.00260	validation-mlogloss:1.96057
[36m(train_xgb_ray_tune pid=1821691)[0m [243]	train-mlogloss:2.00201	validation-mlogloss:1.96009
[36m(train_xgb_ray_tune pid=1821680)[0m [226]	train-mlogloss:1.97600	validation-mlogloss:1.93744
[36m(train_xgb_ray_tune pid=1821689)[0m [263]	train-mlogloss:2.13259	validation-mlogloss:2.08480
[36m(train_xgb_ray_tune pid=1821689)[0m [264]	train-mlogloss:2.13154	validation-mlogloss:2.08378
[36m(train_xgb_ray_tune pid=1821672)[0m [221]	train-mlogloss:1.89903	validation-mlogloss:1.87138
[36m(train_xgb_ray_tune pid=1821672)[0m [222]	train-mlogloss:1.89819	validation-mlogloss:1.87066
[36m(train_xgb_ray_tune pid=1821671)[0m [232]	train-mlogloss:2.26619	validation-mlogloss:2.24411
[36m(train_xgb_ray_tune pid=1821671)[0m [233]	train-mlogloss:2.26496	validation-mlogloss:2.24288
[36m(train_xgb_ray_tune pid=1821669)[0m [238]	train-mlogloss:2.11902	validation-mlogloss:2.09008
[36m(train_xgb_ray_tune pid=1821669)[0m [239]	train-mlogloss:2.11782	validation-mlogloss:2.08873
[36m(train_xgb_ray_tune pid=1821686)[0m [260]	train-mlogloss:2.29523	validation-mlogloss:2.27805
[36m(train_xgb_ray_tune pid=1821686)[0m [261]	train-mlogloss:2.29444	validation-mlogloss:2.27723
[36m(train_xgb_ray_tune pid=1821673)[0m [335]	train-mlogloss:2.56461	validation-mlogloss:2.58628
[36m(train_xgb_ray_tune pid=1821673)[0m [336]	train-mlogloss:2.56461	validation-mlogloss:2.58628
[36m(train_xgb_ray_tune pid=1821682)[0m [328]	train-mlogloss:2.40445	validation-mlogloss:2.42495
[36m(train_xgb_ray_tune pid=1821682)[0m [329]	train-mlogloss:2.40437	validation-mlogloss:2.42485
[36m(train_xgb_ray_tune pid=1821687)[0m [267]	train-mlogloss:2.10612	validation-mlogloss:2.07162
[36m(train_xgb_ray_tune pid=1821687)[0m [268]	train-mlogloss:2.10527	validation-mlogloss:2.07066
[36m(train_xgb_ray_tune pid=1821670)[0m [253]	train-mlogloss:1.96077	validation-mlogloss:1.92225
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[36m(train_xgb_ray_tune pid=1821689)[0m [288]	train-mlogloss:2.10653	validation-mlogloss:2.05828
[36m(train_xgb_ray_tune pid=1821686)[0m [281]	train-mlogloss:2.28085	validation-mlogloss:2.26376
[36m(train_xgb_ray_tune pid=1821673)[0m [361]	train-mlogloss:2.56434	validation-mlogloss:2.58604
[36m(train_xgb_ray_tune pid=1821670)[0m [278]	train-mlogloss:1.93457	validation-mlogloss:1.89904
[36m(train_xgb_ray_tune pid=1821691)[0m [270]	train-mlogloss:1.98593	validation-mlogloss:1.94627
[36m(train_xgb_ray_tune pid=1821671)[0m [250]	train-mlogloss:2.24407	validation-mlogloss:2.22071
[36m(train_xgb_ray_tune pid=1821687)[0m [295]	train-mlogloss:2.08455	validation-mlogloss:2.05056
[36m(train_xgb_ray_tune pid=1821683)[0m [297]	train-mlogloss:2.26678	validation-mlogloss:2.25667
[36m(train_xgb_ray_tune pid=1821663)[0m [237]	train-mlogloss:2.07794	validation-mlogloss:2.03507
[36m(train_xgb_ray_tune pid=1821691)[0m [271]	train-mlogloss:1.98531	validation-mlogloss:1.94554
[36m(train_xgb_ray_tune pid=1821691)[0m [272]	train-mlogloss:1.98467	validation-mlogloss:1.94488
[36m(train_xgb_ray_tune pid=1821680)[0m [246]	train-mlogloss:1.95660	validation-mlogloss:1.92080
[36m(train_xgb_ray_tune pid=1821680)[0m [247]	train-mlogloss:1.95563	validation-mlogloss:1.92006
[36m(train_xgb_ray_tune pid=1821689)[0m [289]	train-mlogloss:2.10554	validation-mlogloss:2.05735
[36m(train_xgb_ray_tune pid=1821689)[0m [290]	train-mlogloss:2.10457	validation-mlogloss:2.05644
[36m(train_xgb_ray_tune pid=1821672)[0m [241]	train-mlogloss:1.88425	validation-mlogloss:1.86047
[36m(train_xgb_ray_tune pid=1821672)[0m [242]	train-mlogloss:1.88365	validation-mlogloss:1.86003
[36m(train_xgb_ray_tune pid=1821671)[0m [251]	train-mlogloss:2.24286	validation-mlogloss:2.21951
[36m(train_xgb_ray_tune pid=1821669)[0m [258]	train-mlogloss:2.09672	validation-mlogloss:2.06678
[36m(train_xgb_ray_tune pid=1821669)[0m [259]	train-mlogloss:2.09564	validation-mlogloss:2.06556
[36m(train_xgb_ray_tune pid=1821686)[0m [282]	train-mlogloss:2.28018	validation-mlogloss:2.26311
[36m(train_xgb_ray_tune pid=1821686)[0m [283]	train-mlogloss:2.27949	validation-mlogloss:2.26255
[36m(train_xgb_ray_tune pid=1821673)[0m [362]	train-mlogloss:2.56434	validation-mlogloss:2.58604
[36m(train_xgb_ray_tune pid=1821673)[0m [363]	train-mlogloss:2.56434	validation-mlogloss:2.58604
[36m(train_xgb_ray_tune pid=1821682)[0m [358]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821682)[0m [359]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821682)[0m [360]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821687)[0m [296]	train-mlogloss:2.08391	validation-mlogloss:2.04980
[36m(train_xgb_ray_tune pid=1821687)[0m [297]	train-mlogloss:2.08311	validation-mlogloss:2.04886
[36m(train_xgb_ray_tune pid=1821670)[0m [279]	train-mlogloss:1.93356	validation-mlogloss:1.89832
[36m(train_xgb_ray_tune pid=1821684)[0m [284]	train-mlogloss:2.23085	validation-mlogloss:2.21128
[36m(train_xgb_ray_tune pid=1821684)[0m [285]	train-mlogloss:2.23022	validation-mlogloss:2.21068
[36m(train_xgb_ray_tune pid=1821674)[0m [280]	train-mlogloss:2.01809	validation-mlogloss:1.96413
[36m(train_xgb_ray_tune pid=1821674)[0m [281]	train-mlogloss:2.01746	validation-mlogloss:1.96372
[36m(train_xgb_ray_tune pid=1821683)[0m [298]	train-mlogloss:2.26636	validation-mlogloss:2.25635
[36m(train_xgb_ray_tune pid=1821683)[0m [299]	train-mlogloss:2.26597	validation-mlogloss:2.25608
[36m(train_xgb_ray_tune pid=1821663)[0m [238]	train-mlogloss:2.07673	validation-mlogloss:2.03401
[36m(train_xgb_ray_tune pid=1821691)[0m [273]	train-mlogloss:1.98408	validation-mlogloss:1.94436
[36m(train_xgb_ray_tune pid=1821689)[0m [291]	train-mlogloss:2.10352	validation-mlogloss:2.05532
[36m(train_xgb_ray_tune pid=1821687)[0m [298]	train-mlogloss:2.08243	validation-mlogloss:2.04823
[36m(train_xgb_ray_tune pid=1821670)[0m [280]	train-mlogloss:1.93248	validation-mlogloss:1.89741
[36m(train_xgb_ray_tune pid=1821684)[0m [286]	train-mlogloss:2.22949	validation-mlogloss:2.20992
[36m(train_xgb_ray_tune pid=1821672)[0m [243]	train-mlogloss:1.88302	validation-mlogloss:1.85947
[36m(train_xgb_ray_tune pid=1821673)[0m [364]	train-mlogloss:2.56434	validation-mlogloss:2.58604
[36m(train_xgb_ray_tune pid=1821682)[0m [361]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821691)[0m [274]	train-mlogloss:1.98380	validation-mlogloss:1.94407
[36m(train_xgb_ray_tune pid=1821689)[0m [292]	train-mlogloss:2.10254	validation-mlogloss:2.05421
[36m(train_xgb_ray_tune pid=1821671)[0m [252]	train-mlogloss:2.24167	validation-mlogloss:2.21827
[36m(train_xgb_ray_tune pid=1821674)[0m [282]	train-mlogloss:2.01677	validation-mlogloss:1.96304
[36m(train_xgb_ray_tune pid=1821680)[0m [248]	train-mlogloss:1.95478	validation-mlogloss:1.91925
[36m(train_xgb_ray_tune pid=1821669)[0m [260]	train-mlogloss:2.09462	validation-mlogloss:2.06443
[36m(train_xgb_ray_tune pid=1821686)[0m [284]	train-mlogloss:2.27889	validation-mlogloss:2.26198
[36m(train_xgb_ray_tune pid=1821687)[0m [299]	train-mlogloss:2.08166	validation-mlogloss:2.04744
[36m(train_xgb_ray_tune pid=1821684)[0m [287]	train-mlogloss:2.22892	validation-mlogloss:2.20935
[36m(train_xgb_ray_tune pid=1821683)[0m [300]	train-mlogloss:2.26562	validation-mlogloss:2.25586
[36m(train_xgb_ray_tune pid=1821663)[0m [239]	train-mlogloss:2.07557	validation-mlogloss:2.03281
[36m(train_xgb_ray_tune pid=1821673)[0m [365]	train-mlogloss:2.56434	validation-mlogloss:2.58604
[36m(train_xgb_ray_tune pid=1821682)[0m [362]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821691)[0m [275]	train-mlogloss:1.98322	validation-mlogloss:1.94369
[36m(train_xgb_ray_tune pid=1821670)[0m [281]	train-mlogloss:1.93154	validation-mlogloss:1.89655
[36m(train_xgb_ray_tune pid=1821689)[0m [293]	train-mlogloss:2.10155	validation-mlogloss:2.05314
[36m(train_xgb_ray_tune pid=1821672)[0m [244]	train-mlogloss:1.88242	validation-mlogloss:1.85894
[36m(train_xgb_ray_tune pid=1821663)[0m [240]	train-mlogloss:2.07438	validation-mlogloss:2.03170
[36m(train_xgb_ray_tune pid=1821691)[0m [276]	train-mlogloss:1.98277	validation-mlogloss:1.94337
[36m(train_xgb_ray_tune pid=1821691)[0m [277]	train-mlogloss:1.98225	validation-mlogloss:1.94300
[36m(train_xgb_ray_tune pid=1821691)[0m [278]	train-mlogloss:1.98175	validation-mlogloss:1.94246
[36m(train_xgb_ray_tune pid=1821680)[0m [249]	train-mlogloss:1.95396	validation-mlogloss:1.91857
[36m(train_xgb_ray_tune pid=1821689)[0m [294]	train-mlogloss:2.10059	validation-mlogloss:2.05224
[36m(train_xgb_ray_tune pid=1821672)[0m [245]	train-mlogloss:1.88168	validation-mlogloss:1.85838
[36m(train_xgb_ray_tune pid=1821671)[0m [253]	train-mlogloss:2.24050	validation-mlogloss:2.21705
[36m(train_xgb_ray_tune pid=1821671)[0m [254]	train-mlogloss:2.23935	validation-mlogloss:2.21583
[36m(train_xgb_ray_tune pid=1821669)[0m [261]	train-mlogloss:2.09355	validation-mlogloss:2.06339
[36m(train_xgb_ray_tune pid=1821669)[0m [262]	train-mlogloss:2.09250	validation-mlogloss:2.06230
[36m(train_xgb_ray_tune pid=1821686)[0m [285]	train-mlogloss:2.27826	validation-mlogloss:2.26140
[36m(train_xgb_ray_tune pid=1821686)[0m [286]	train-mlogloss:2.27770	validation-mlogloss:2.26085
[36m(train_xgb_ray_tune pid=1821673)[0m [366]	train-mlogloss:2.56434	validation-mlogloss:2.58604
[36m(train_xgb_ray_tune pid=1821673)[0m [367]	train-mlogloss:2.56425	validation-mlogloss:2.58598
[36m(train_xgb_ray_tune pid=1821673)[0m [368]	train-mlogloss:2.56410	validation-mlogloss:2.58588
[36m(train_xgb_ray_tune pid=1821682)[0m [363]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821682)[0m [364]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821682)[0m [365]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821687)[0m [300]	train-mlogloss:2.08111	validation-mlogloss:2.04687
[36m(train_xgb_ray_tune pid=1821687)[0m [301]	train-mlogloss:2.08049	validation-mlogloss:2.04636
[36m(train_xgb_ray_tune pid=1821670)[0m [282]	train-mlogloss:1.93051	validation-mlogloss:1.89564
[36m(train_xgb_ray_tune pid=1821670)[0m [283]	train-mlogloss:1.92962	validation-mlogloss:1.89488
[36m(train_xgb_ray_tune pid=1821684)[0m [288]	train-mlogloss:2.22851	validation-mlogloss:2.20905
[36m(train_xgb_ray_tune pid=1821684)[0m [289]	train-mlogloss:2.22797	validation-mlogloss:2.20849
[36m(train_xgb_ray_tune pid=1821674)[0m [283]	train-mlogloss:2.01599	validation-mlogloss:1.96217
[36m(train_xgb_ray_tune pid=1821674)[0m [284]	train-mlogloss:2.01534	validation-mlogloss:1.96160
[36m(train_xgb_ray_tune pid=1821683)[0m [301]	train-mlogloss:2.26515	validation-mlogloss:2.25533
[36m(train_xgb_ray_tune pid=1821683)[0m [302]	train-mlogloss:2.26472	validation-mlogloss:2.25493
[36m(train_xgb_ray_tune pid=1821663)[0m [241]	train-mlogloss:2.07327	validation-mlogloss:2.03053
[36m(train_xgb_ray_tune pid=1821680)[0m [250]	train-mlogloss:1.95316	validation-mlogloss:1.91786
[36m(train_xgb_ray_tune pid=1821673)[0m [369]	train-mlogloss:2.56388	validation-mlogloss:2.58570

Trial status: 15 RUNNING | 5 TERMINATED
Current time: 2025-11-06 21:42:59. Total running time: 30s
Logical resource usage: 15.0/20 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_1cb55    RUNNING                    754             3        0.00708953      0.572333             0.571419   23.2246                    63       1.1888        43.7925              5319                                                     │
│ trial_1cb55    RUNNING                    271             3        0.0190181       0.628713             0.644453    5.39879                  116      50.2256        13.9432              1016                                                     │
│ trial_1cb55    RUNNING                    420             2        0.0114507       0.674775             0.784948   16.1511                   138       1.94599       25.0934              4910                                                     │
│ trial_1cb55    RUNNING                    315             3        0.0185528       0.750404             0.640788   16.2339                   132       5.66557      699.33                4881                                                     │
│ trial_1cb55    RUNNING                    671             3        0.00656652      0.840697             0.632676   20.0238                   175     146.659         14.3622              1766                                                     │
│ trial_1cb55    RUNNING                    261             3        0.0079232       0.695251             0.679307   14.9999                   149       3.29567      351.316                773                                                     │
│ trial_1cb55    RUNNING                    407             3        0.00839124      0.623236             0.585971   14.2771                   141      99.7363        36.3844              8847                                                     │
│ trial_1cb55    RUNNING                    533             2        0.0159374       0.671786             0.754294   17.6281                   107      26.8082       366.449               9665                                                     │
│ trial_1cb55    RUNNING                    595             3        0.012221        0.64406              0.601166   27.5846                   147      21.8054         8.5704              3985                                                     │
│ trial_1cb55    RUNNING                    345             2        0.00624441      0.839356             0.5687     19.6342                   156       8.55672       25.9994              7299                                                     │
│ trial_1cb55    RUNNING                    672             3        0.018443        0.848987             0.786135   16.1061                   189     250.383        109.728               3866                                                     │
│ trial_1cb55    RUNNING                    733             3        0.0143482       0.737584             0.823754   28.6324                   109      71.6413       494.079               1372                                                     │
│ trial_1cb55    RUNNING                    718             3        0.00997422      0.696604             0.679719   29.37                      83       6.04013       21.9013              3622                                                     │
│ trial_1cb55    RUNNING                    386             2        0.0118711       0.536963             0.683892   14.8021                    69     231.759         24.4769              6579                                                     │
│ trial_1cb55    RUNNING                    799             2        0.00999408      0.501305             0.843765   28.8012                   121       6.57783        5.49196             4707                                                     │
│ trial_1cb55    TERMINATED                 448             3        0.015063        0.548208             0.634636   15.8129                   114     413.067          8.48831             9642        1           11.826                 0.12428   │
│ trial_1cb55    TERMINATED                 259             2        0.0162511       0.636471             0.73363    19.5734                    84     200.438        106.568               5001        1           22.1076                0.268017  │
│ trial_1cb55    TERMINATED                 226             2        0.0109774       0.771305             0.792725   22.4585                    91      46.6636        52.4725              1090        1           23.7949                0.460989  │
│ trial_1cb55    TERMINATED                 545             3        0.0194414       0.759991             0.501904    6.50189                   61     860.959        756.382               6475        1            5.32095               0.0639269 │
│ trial_1cb55    TERMINATED                 720             2        0.015517        0.706389             0.597535   28.2665                   146     322.046         42.6044              9545        1           25.243                 0.165773  │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1821663)[0m [242]	train-mlogloss:2.07203	validation-mlogloss:2.02937
[36m(train_xgb_ray_tune pid=1821691)[0m [279]	train-mlogloss:1.98131	validation-mlogloss:1.94199
[36m(train_xgb_ray_tune pid=1821691)[0m [280]	train-mlogloss:1.98076	validation-mlogloss:1.94165
[36m(train_xgb_ray_tune pid=1821680)[0m [251]	train-mlogloss:1.95232	validation-mlogloss:1.91717
[36m(train_xgb_ray_tune pid=1821689)[0m [295]	train-mlogloss:2.09964	validation-mlogloss:2.05133
[36m(train_xgb_ray_tune pid=1821689)[0m [296]	train-mlogloss:2.09872	validation-mlogloss:2.05051
[36m(train_xgb_ray_tune pid=1821672)[0m [246]	train-mlogloss:1.88091	validation-mlogloss:1.85767
[36m(train_xgb_ray_tune pid=1821672)[0m [247]	train-mlogloss:1.88026	validation-mlogloss:1.85720
[36m(train_xgb_ray_tune pid=1821671)[0m [255]	train-mlogloss:2.23816	validation-mlogloss:2.21461
[36m(train_xgb_ray_tune pid=1821669)[0m [263]	train-mlogloss:2.09146	validation-mlogloss:2.06135
[36m(train_xgb_ray_tune pid=1821669)[0m [264]	train-mlogloss:2.09042	validation-mlogloss:2.06021
[36m(train_xgb_ray_tune pid=1821686)[0m [287]	train-mlogloss:2.27707	validation-mlogloss:2.26017
[36m(train_xgb_ray_tune pid=1821686)[0m [288]	train-mlogloss:2.27648	validation-mlogloss:2.25967
[36m(train_xgb_ray_tune pid=1821673)[0m [370]	train-mlogloss:2.56388	validation-mlogloss:2.58570
[36m(train_xgb_ray_tune pid=1821673)[0m [371]	train-mlogloss:2.56388	validation-mlogloss:2.58570
[36m(train_xgb_ray_tune pid=1821673)[0m [372]	train-mlogloss:2.56380	validation-mlogloss:2.58564
[36m(train_xgb_ray_tune pid=1821682)[0m [366]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821682)[0m [367]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821682)[0m [368]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821682)[0m [369]	train-mlogloss:2.40313	validation-mlogloss:2.42366
[36m(train_xgb_ray_tune pid=1821687)[0m [302]	train-mlogloss:2.07985	validation-mlogloss:2.04567
[36m(train_xgb_ray_tune pid=1821687)[0m [303]	train-mlogloss:2.07923	validation-mlogloss:2.04513
[36m(train_xgb_ray_tune pid=1821670)[0m [284]	train-mlogloss:1.92867	validation-mlogloss:1.89425
[36m(train_xgb_ray_tune pid=1821670)[0m [285]	train-mlogloss:1.92776	validation-mlogloss:1.89357
[36m(train_xgb_ray_tune pid=1821684)[0m [290]	train-mlogloss:2.22737	validation-mlogloss:2.20790
[36m(train_xgb_ray_tune pid=1821684)[0m [291]	train-mlogloss:2.22671	validation-mlogloss:2.20728
[36m(train_xgb_ray_tune pid=1821674)[0m [285]	train-mlogloss:2.01470	validation-mlogloss:1.96123
[36m(train_xgb_ray_tune pid=1821674)[0m [286]	train-mlogloss:2.01411	validation-mlogloss:1.96066
[36m(train_xgb_ray_tune pid=1821683)[0m [303]	train-mlogloss:2.26439	validation-mlogloss:2.25461
[36m(train_xgb_ray_tune pid=1821683)[0m [304]	train-mlogloss:2.26400	validation-mlogloss:2.25431
[36m(train_xgb_ray_tune pid=1821680)[0m [252]	train-mlogloss:1.95146	validation-mlogloss:1.91648
[36m(train_xgb_ray_tune pid=1821687)[0m [304]	train-mlogloss:2.07845	validation-mlogloss:2.04433
[36m(train_xgb_ray_tune pid=1821670)[0m [286]	train-mlogloss:1.92680	validation-mlogloss:1.89291
[36m(train_xgb_ray_tune pid=1821663)[0m [243]	train-mlogloss:2.07086	validation-mlogloss:2.02822
[36m(train_xgb_ray_tune pid=1821671)[0m [256]	train-mlogloss:2.23696	validation-mlogloss:2.21340
[36m(train_xgb_ray_tune pid=1821673)[0m [373]	train-mlogloss:2.56380	validation-mlogloss:2.58564
[36m(train_xgb_ray_tune pid=1821684)[0m [292]	train-mlogloss:2.22606	validation-mlogloss:2.20664
[36m(train_xgb_ray_tune pid=1821683)[0m [305]	train-mlogloss:2.26364	validation-mlogloss:2.25394
[36m(train_xgb_ray_tune pid=1821691)[0m [281]	train-mlogloss:1.98032	validation-mlogloss:1.94142
[36m(train_xgb_ray_tune pid=1821672)[0m [248]	train-mlogloss:1.87962	validation-mlogloss:1.85665
[36m(train_xgb_ray_tune pid=1821674)[0m [287]	train-mlogloss:2.01351	validation-mlogloss:1.96016
[36m(train_xgb_ray_tune pid=1821689)[0m [297]	train-mlogloss:2.09775	validation-mlogloss:2.04957
[36m(train_xgb_ray_tune pid=1821663)[0m [244]	train-mlogloss:2.06983	validation-mlogloss:2.02724
[36m(train_xgb_ray_tune pid=1821691)[0m [282]	train-mlogloss:1.97985	validation-mlogloss:1.94099
[36m(train_xgb_ray_tune pid=1821680)[0m [253]	train-mlogloss:1.95066	validation-mlogloss:1.91587
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[36m(train_xgb_ray_tune pid=1821673)[0m   _log_deprecation_warning([32m [repeated 3x across cluster][0m
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[36m(train_xgb_ray_tune pid=1821670)[0m [302]	train-mlogloss:1.91204	validation-mlogloss:1.88048
[36m(train_xgb_ray_tune pid=1821663)[0m [254]	train-mlogloss:2.05783	validation-mlogloss:2.01501
[36m(train_xgb_ray_tune pid=1821691)[0m [292]	train-mlogloss:1.97502	validation-mlogloss:1.93739
[36m(train_xgb_ray_tune pid=1821691)[0m [293]	train-mlogloss:1.97472	validation-mlogloss:1.93711
[36m(train_xgb_ray_tune pid=1821680)[0m [262]	train-mlogloss:1.94336	validation-mlogloss:1.90960
[36m(train_xgb_ray_tune pid=1821689)[0m [307]	train-mlogloss:2.08838	validation-mlogloss:2.04021
[36m(train_xgb_ray_tune pid=1821689)[0m [308]	train-mlogloss:2.08743	validation-mlogloss:2.03923
[36m(train_xgb_ray_tune pid=1821689)[0m [309]	train-mlogloss:2.08656	validation-mlogloss:2.03844
[36m(train_xgb_ray_tune pid=1821672)[0m [264]	train-mlogloss:1.87030	validation-mlogloss:1.85058
[36m(train_xgb_ray_tune pid=1821672)[0m [265]	train-mlogloss:1.86968	validation-mlogloss:1.85023
[36m(train_xgb_ray_tune pid=1821669)[0m [274]	train-mlogloss:2.08046	validation-mlogloss:2.05009
[36m(train_xgb_ray_tune pid=1821669)[0m [275]	train-mlogloss:2.07953	validation-mlogloss:2.04910
[36m(train_xgb_ray_tune pid=1821686)[0m [301]	train-mlogloss:2.26889	validation-mlogloss:2.25238
[36m(train_xgb_ray_tune pid=1821686)[0m [302]	train-mlogloss:2.26847	validation-mlogloss:2.25201
[36m(train_xgb_ray_tune pid=1821682)[0m [383]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821682)[0m [384]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821687)[0m [320]	train-mlogloss:2.06789	validation-mlogloss:2.03426
[36m(train_xgb_ray_tune pid=1821687)[0m [321]	train-mlogloss:2.06727	validation-mlogloss:2.03368
[36m(train_xgb_ray_tune pid=1821687)[0m [322]	train-mlogloss:2.06673	validation-mlogloss:2.03313
[36m(train_xgb_ray_tune pid=1821670)[0m [303]	train-mlogloss:1.91113	validation-mlogloss:1.87974
[36m(train_xgb_ray_tune pid=1821670)[0m [304]	train-mlogloss:1.91023	validation-mlogloss:1.87904
[36m(train_xgb_ray_tune pid=1821684)[0m [303]	train-mlogloss:2.22036	validation-mlogloss:2.20112
[36m(train_xgb_ray_tune pid=1821684)[0m [304]	train-mlogloss:2.21992	validation-mlogloss:2.20067
[36m(train_xgb_ray_tune pid=1821674)[0m [297]	train-mlogloss:2.00700	validation-mlogloss:1.95415
[36m(train_xgb_ray_tune pid=1821674)[0m [298]	train-mlogloss:2.00644	validation-mlogloss:1.95369
[36m(train_xgb_ray_tune pid=1821683)[0m [318]	train-mlogloss:2.25881	validation-mlogloss:2.24970
[36m(train_xgb_ray_tune pid=1821683)[0m [319]	train-mlogloss:2.25848	validation-mlogloss:2.24938
[36m(train_xgb_ray_tune pid=1821663)[0m [255]	train-mlogloss:2.05670	validation-mlogloss:2.01391
[36m(train_xgb_ray_tune pid=1821670)[0m [305]	train-mlogloss:1.90933	validation-mlogloss:1.87830
[36m(train_xgb_ray_tune pid=1821680)[0m [263]	train-mlogloss:1.94257	validation-mlogloss:1.90890
[36m(train_xgb_ray_tune pid=1821687)[0m [323]	train-mlogloss:2.06613	validation-mlogloss:2.03258
[36m(train_xgb_ray_tune pid=1821691)[0m [294]	train-mlogloss:1.97428	validation-mlogloss:1.93661
[36m(train_xgb_ray_tune pid=1821689)[0m [310]	train-mlogloss:2.08565	validation-mlogloss:2.03759
[36m(train_xgb_ray_tune pid=1821674)[0m [299]	train-mlogloss:2.00582	validation-mlogloss:1.95310

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:00. Total running time: 31s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             28.2754 │
│ time_total_s                 28.2754 │
│ training_iteration                 1 │
│ validation_accuracy          0.20071 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=1821683)[0m [320]	train-mlogloss:2.25812	validation-mlogloss:2.24908

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:00. Total running time: 31s
[36m(train_xgb_ray_tune pid=1821663)[0m [256]	train-mlogloss:2.05553	validation-mlogloss:2.01291
[36m(train_xgb_ray_tune pid=1821663)[0m [257]	train-mlogloss:2.05450	validation-mlogloss:2.01184
[36m(train_xgb_ray_tune pid=1821691)[0m [295]	train-mlogloss:1.97382	validation-mlogloss:1.93611
[36m(train_xgb_ray_tune pid=1821691)[0m [296]	train-mlogloss:1.97328	validation-mlogloss:1.93564
[36m(train_xgb_ray_tune pid=1821680)[0m [264]	train-mlogloss:1.94181	validation-mlogloss:1.90832
[36m(train_xgb_ray_tune pid=1821680)[0m [265]	train-mlogloss:1.94098	validation-mlogloss:1.90763
[36m(train_xgb_ray_tune pid=1821689)[0m [311]	train-mlogloss:2.08474	validation-mlogloss:2.03679
[36m(train_xgb_ray_tune pid=1821689)[0m [312]	train-mlogloss:2.08381	validation-mlogloss:2.03576
[36m(train_xgb_ray_tune pid=1821672)[0m [266]	train-mlogloss:1.86927	validation-mlogloss:1.84994
[36m(train_xgb_ray_tune pid=1821672)[0m [267]	train-mlogloss:1.86884	validation-mlogloss:1.84962
[36m(train_xgb_ray_tune pid=1821669)[0m [276]	train-mlogloss:2.07855	validation-mlogloss:2.04805
[36m(train_xgb_ray_tune pid=1821669)[0m [277]	train-mlogloss:2.07763	validation-mlogloss:2.04713
[36m(train_xgb_ray_tune pid=1821686)[0m [303]	train-mlogloss:2.26785	validation-mlogloss:2.25145
[36m(train_xgb_ray_tune pid=1821686)[0m [304]	train-mlogloss:2.26735	validation-mlogloss:2.25106
[36m(train_xgb_ray_tune pid=1821682)[0m [385]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821682)[0m [386]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821687)[0m [324]	train-mlogloss:2.06544	validation-mlogloss:2.03195
[36m(train_xgb_ray_tune pid=1821687)[0m [325]	train-mlogloss:2.06485	validation-mlogloss:2.03142
[36m(train_xgb_ray_tune pid=1821670)[0m [306]	train-mlogloss:1.90842	validation-mlogloss:1.87764
[36m(train_xgb_ray_tune pid=1821670)[0m [307]	train-mlogloss:1.90748	validation-mlogloss:1.87705
[36m(train_xgb_ray_tune pid=1821684)[0m [305]	train-mlogloss:2.21932	validation-mlogloss:2.20007
[36m(train_xgb_ray_tune pid=1821684)[0m [306]	train-mlogloss:2.21889	validation-mlogloss:2.19971
[36m(train_xgb_ray_tune pid=1821684)[0m [307]	train-mlogloss:2.21848	validation-mlogloss:2.19931
[36m(train_xgb_ray_tune pid=1821674)[0m [300]	train-mlogloss:2.00527	validation-mlogloss:1.95264
[36m(train_xgb_ray_tune pid=1821674)[0m [301]	train-mlogloss:2.00467	validation-mlogloss:1.95203
[36m(train_xgb_ray_tune pid=1821683)[0m [321]	train-mlogloss:2.25775	validation-mlogloss:2.24877
[36m(train_xgb_ray_tune pid=1821683)[0m [322]	train-mlogloss:2.25740	validation-mlogloss:2.24848
[36m(train_xgb_ray_tune pid=1821682)[0m [387]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821670)[0m [308]	train-mlogloss:1.90668	validation-mlogloss:1.87633
[36m(train_xgb_ray_tune pid=1821684)[0m [308]	train-mlogloss:2.21799	validation-mlogloss:2.19884
[36m(train_xgb_ray_tune pid=1821680)[0m [266]	train-mlogloss:1.94020	validation-mlogloss:1.90696
[36m(train_xgb_ray_tune pid=1821669)[0m [278]	train-mlogloss:2.07668	validation-mlogloss:2.04612
[36m(train_xgb_ray_tune pid=1821689)[0m [313]	train-mlogloss:2.08286	validation-mlogloss:2.03473
[36m(train_xgb_ray_tune pid=1821672)[0m [268]	train-mlogloss:1.86832	validation-mlogloss:1.84927
[36m(train_xgb_ray_tune pid=1821686)[0m [305]	train-mlogloss:2.26690	validation-mlogloss:2.25063
[36m(train_xgb_ray_tune pid=1821663)[0m [258]	train-mlogloss:2.05341	validation-mlogloss:2.01085
[36m(train_xgb_ray_tune pid=1821663)[0m [259]	train-mlogloss:2.05235	validation-mlogloss:2.00981
[36m(train_xgb_ray_tune pid=1821691)[0m [297]	train-mlogloss:1.97300	validation-mlogloss:1.93550
[36m(train_xgb_ray_tune pid=1821691)[0m [298]	train-mlogloss:1.97264	validation-mlogloss:1.93528
[36m(train_xgb_ray_tune pid=1821680)[0m [267]	train-mlogloss:1.93946	validation-mlogloss:1.90632
[36m(train_xgb_ray_tune pid=1821680)[0m [268]	train-mlogloss:1.93876	validation-mlogloss:1.90562
[36m(train_xgb_ray_tune pid=1821689)[0m [314]	train-mlogloss:2.08193	validation-mlogloss:2.03372
[36m(train_xgb_ray_tune pid=1821689)[0m [315]	train-mlogloss:2.08103	validation-mlogloss:2.03293
[36m(train_xgb_ray_tune pid=1821672)[0m [269]	train-mlogloss:1.86790	validation-mlogloss:1.84900
[36m(train_xgb_ray_tune pid=1821669)[0m [279]	train-mlogloss:2.07575	validation-mlogloss:2.04510
[36m(train_xgb_ray_tune pid=1821669)[0m [280]	train-mlogloss:2.07479	validation-mlogloss:2.04396
[36m(train_xgb_ray_tune pid=1821686)[0m [306]	train-mlogloss:2.26634	validation-mlogloss:2.25017
[36m(train_xgb_ray_tune pid=1821682)[0m [388]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821682)[0m [389]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821687)[0m [326]	train-mlogloss:2.06418	validation-mlogloss:2.03078
[36m(train_xgb_ray_tune pid=1821687)[0m [327]	train-mlogloss:2.06362	validation-mlogloss:2.03030
[36m(train_xgb_ray_tune pid=1821670)[0m [309]	train-mlogloss:1.90572	validation-mlogloss:1.87555
[36m(train_xgb_ray_tune pid=1821670)[0m [310]	train-mlogloss:1.90482	validation-mlogloss:1.87470
[36m(train_xgb_ray_tune pid=1821670)[0m [311]	train-mlogloss:1.90396	validation-mlogloss:1.87388
[36m(train_xgb_ray_tune pid=1821684)[0m [309]	train-mlogloss:2.21749	validation-mlogloss:2.19835
[36m(train_xgb_ray_tune pid=1821684)[0m [310]	train-mlogloss:2.21703	validation-mlogloss:2.19789
[36m(train_xgb_ray_tune pid=1821684)[0m [311]	train-mlogloss:2.21669	validation-mlogloss:2.19761
[36m(train_xgb_ray_tune pid=1821674)[0m [302]	train-mlogloss:2.00411	validation-mlogloss:1.95158
[36m(train_xgb_ray_tune pid=1821674)[0m [303]	train-mlogloss:2.00356	validation-mlogloss:1.95118
[36m(train_xgb_ray_tune pid=1821683)[0m [323]	train-mlogloss:2.25704	validation-mlogloss:2.24816
[36m(train_xgb_ray_tune pid=1821683)[0m [324]	train-mlogloss:2.25671	validation-mlogloss:2.24784
[36m(train_xgb_ray_tune pid=1821683)[0m [325]	train-mlogloss:2.25640	validation-mlogloss:2.24750
[36m(train_xgb_ray_tune pid=1821680)[0m [269]	train-mlogloss:1.93799	validation-mlogloss:1.90505
[36m(train_xgb_ray_tune pid=1821689)[0m [316]	train-mlogloss:2.08007	validation-mlogloss:2.03211
[36m(train_xgb_ray_tune pid=1821669)[0m [281]	train-mlogloss:2.07372	validation-mlogloss:2.04295
[36m(train_xgb_ray_tune pid=1821686)[0m [307]	train-mlogloss:2.26589	validation-mlogloss:2.24978
[36m(train_xgb_ray_tune pid=1821663)[0m [260]	train-mlogloss:2.05124	validation-mlogloss:2.00863
[36m(train_xgb_ray_tune pid=1821682)[0m [390]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821684)[0m [312]	train-mlogloss:2.21619	validation-mlogloss:2.19713
[36m(train_xgb_ray_tune pid=1821691)[0m [299]	train-mlogloss:1.97237	validation-mlogloss:1.93507
[36m(train_xgb_ray_tune pid=1821672)[0m [270]	train-mlogloss:1.86733	validation-mlogloss:1.84855

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:01. Total running time: 31s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             28.3228 │
│ time_total_s                 28.3228 │
│ training_iteration                 1 │
│ validation_accuracy          0.43855 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:01. Total running time: 31s
[36m(train_xgb_ray_tune pid=1821663)[0m [261]	train-mlogloss:2.05004	validation-mlogloss:2.00749
[36m(train_xgb_ray_tune pid=1821663)[0m [262]	train-mlogloss:2.04907	validation-mlogloss:2.00654
[36m(train_xgb_ray_tune pid=1821691)[0m [300]	train-mlogloss:1.97210	validation-mlogloss:1.93483
[36m(train_xgb_ray_tune pid=1821691)[0m [301]	train-mlogloss:1.97177	validation-mlogloss:1.93459
[36m(train_xgb_ray_tune pid=1821680)[0m [270]	train-mlogloss:1.93722	validation-mlogloss:1.90439
[36m(train_xgb_ray_tune pid=1821680)[0m [271]	train-mlogloss:1.93652	validation-mlogloss:1.90379
[36m(train_xgb_ray_tune pid=1821680)[0m [272]	train-mlogloss:1.93579	validation-mlogloss:1.90314
[36m(train_xgb_ray_tune pid=1821689)[0m [317]	train-mlogloss:2.07920	validation-mlogloss:2.03134
[36m(train_xgb_ray_tune pid=1821689)[0m [318]	train-mlogloss:2.07828	validation-mlogloss:2.03047
[36m(train_xgb_ray_tune pid=1821669)[0m [282]	train-mlogloss:2.07288	validation-mlogloss:2.04210
[36m(train_xgb_ray_tune pid=1821669)[0m [283]	train-mlogloss:2.07201	validation-mlogloss:2.04122
[36m(train_xgb_ray_tune pid=1821686)[0m [308]	train-mlogloss:2.26545	validation-mlogloss:2.24941
[36m(train_xgb_ray_tune pid=1821686)[0m [309]	train-mlogloss:2.26493	validation-mlogloss:2.24897
[36m(train_xgb_ray_tune pid=1821682)[0m [391]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821682)[0m [392]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821687)[0m [328]	train-mlogloss:2.06295	validation-mlogloss:2.02956
[36m(train_xgb_ray_tune pid=1821687)[0m [329]	train-mlogloss:2.06237	validation-mlogloss:2.02897
[36m(train_xgb_ray_tune pid=1821670)[0m [312]	train-mlogloss:1.90311	validation-mlogloss:1.87304
[36m(train_xgb_ray_tune pid=1821670)[0m [313]	train-mlogloss:1.90223	validation-mlogloss:1.87217
[36m(train_xgb_ray_tune pid=1821670)[0m [314]	train-mlogloss:1.90140	validation-mlogloss:1.87150
[36m(train_xgb_ray_tune pid=1821684)[0m [313]	train-mlogloss:2.21585	validation-mlogloss:2.19684
[36m(train_xgb_ray_tune pid=1821684)[0m [314]	train-mlogloss:2.21541	validation-mlogloss:2.19642
[36m(train_xgb_ray_tune pid=1821684)[0m [315]	train-mlogloss:2.21492	validation-mlogloss:2.19588
[36m(train_xgb_ray_tune pid=1821674)[0m [304]	train-mlogloss:2.00300	validation-mlogloss:1.95061
[36m(train_xgb_ray_tune pid=1821674)[0m [305]	train-mlogloss:2.00244	validation-mlogloss:1.95021
[36m(train_xgb_ray_tune pid=1821683)[0m [326]	train-mlogloss:2.25608	validation-mlogloss:2.24726
[36m(train_xgb_ray_tune pid=1821683)[0m [327]	train-mlogloss:2.25567	validation-mlogloss:2.24685
[36m(train_xgb_ray_tune pid=1821683)[0m [328]	train-mlogloss:2.25526	validation-mlogloss:2.24655
[36m(train_xgb_ray_tune pid=1821689)[0m [319]	train-mlogloss:2.07737	validation-mlogloss:2.02963
[36m(train_xgb_ray_tune pid=1821669)[0m [284]	train-mlogloss:2.07101	validation-mlogloss:2.04015
[36m(train_xgb_ray_tune pid=1821683)[0m [329]	train-mlogloss:2.25491	validation-mlogloss:2.24618
[36m(train_xgb_ray_tune pid=1821663)[0m [263]	train-mlogloss:2.04801	validation-mlogloss:2.00554
[36m(train_xgb_ray_tune pid=1821663)[0m [264]	train-mlogloss:2.04694	validation-mlogloss:2.00458
[36m(train_xgb_ray_tune pid=1821663)[0m [265]	train-mlogloss:2.04593	validation-mlogloss:2.00363
[36m(train_xgb_ray_tune pid=1821691)[0m [302]	train-mlogloss:1.97121	validation-mlogloss:1.93388
[36m(train_xgb_ray_tune pid=1821691)[0m [303]	train-mlogloss:1.97068	validation-mlogloss:1.93350
[36m(train_xgb_ray_tune pid=1821680)[0m [273]	train-mlogloss:1.93515	validation-mlogloss:1.90270
[36m(train_xgb_ray_tune pid=1821689)[0m [320]	train-mlogloss:2.07647	validation-mlogloss:2.02873
[36m(train_xgb_ray_tune pid=1821689)[0m [321]	train-mlogloss:2.07548	validation-mlogloss:2.02773
[36m(train_xgb_ray_tune pid=1821689)[0m [322]	train-mlogloss:2.07460	validation-mlogloss:2.02692
[36m(train_xgb_ray_tune pid=1821669)[0m [285]	train-mlogloss:2.07006	validation-mlogloss:2.03913
[36m(train_xgb_ray_tune pid=1821669)[0m [286]	train-mlogloss:2.06919	validation-mlogloss:2.03821
[36m(train_xgb_ray_tune pid=1821686)[0m [310]	train-mlogloss:2.26434	validation-mlogloss:2.24831
[36m(train_xgb_ray_tune pid=1821686)[0m [311]	train-mlogloss:2.26382	validation-mlogloss:2.24786
[36m(train_xgb_ray_tune pid=1821682)[0m [393]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821682)[0m [394]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821687)[0m [330]	train-mlogloss:2.06179	validation-mlogloss:2.02836
[36m(train_xgb_ray_tune pid=1821687)[0m [331]	train-mlogloss:2.06106	validation-mlogloss:2.02763
[36m(train_xgb_ray_tune pid=1821670)[0m [315]	train-mlogloss:1.90067	validation-mlogloss:1.87084
[36m(train_xgb_ray_tune pid=1821670)[0m [316]	train-mlogloss:1.89987	validation-mlogloss:1.87024
[36m(train_xgb_ray_tune pid=1821670)[0m [317]	train-mlogloss:1.89900	validation-mlogloss:1.86959
[36m(train_xgb_ray_tune pid=1821684)[0m [316]	train-mlogloss:2.21444	validation-mlogloss:2.19546
[36m(train_xgb_ray_tune pid=1821684)[0m [317]	train-mlogloss:2.21387	validation-mlogloss:2.19484
[36m(train_xgb_ray_tune pid=1821684)[0m [318]	train-mlogloss:2.21345	validation-mlogloss:2.19439
[36m(train_xgb_ray_tune pid=1821674)[0m [306]	train-mlogloss:2.00185	validation-mlogloss:1.94949
[36m(train_xgb_ray_tune pid=1821674)[0m [307]	train-mlogloss:2.00130	validation-mlogloss:1.94906
[36m(train_xgb_ray_tune pid=1821683)[0m [330]	train-mlogloss:2.25468	validation-mlogloss:2.24600
[36m(train_xgb_ray_tune pid=1821683)[0m [331]	train-mlogloss:2.25432	validation-mlogloss:2.24564
[36m(train_xgb_ray_tune pid=1821683)[0m [332]	train-mlogloss:2.25396	validation-mlogloss:2.24527
[36m(train_xgb_ray_tune pid=1821680)[0m [274]	train-mlogloss:1.93430	validation-mlogloss:1.90195
[36m(train_xgb_ray_tune pid=1821691)[0m [304]	train-mlogloss:1.97027	validation-mlogloss:1.93329
[36m(train_xgb_ray_tune pid=1821669)[0m [287]	train-mlogloss:2.06829	validation-mlogloss:2.03721
[36m(train_xgb_ray_tune pid=1821682)[0m [395]	train-mlogloss:2.40275	validation-mlogloss:2.42319
[36m(train_xgb_ray_tune pid=1821684)[0m [319]	train-mlogloss:2.21310	validation-mlogloss:2.19408
[36m(train_xgb_ray_tune pid=1821683)[0m [333]	train-mlogloss:2.25344	validation-mlogloss:2.24472
[36m(train_xgb_ray_tune pid=1821663)[0m [266]	train-mlogloss:2.04484	validation-mlogloss:2.00253
[36m(train_xgb_ray_tune pid=1821663)[0m [267]	train-mlogloss:2.04381	validation-mlogloss:2.00151
[36m(train_xgb_ray_tune pid=1821663)[0m [268]	train-mlogloss:2.04278	validation-mlogloss:2.00067
[36m(train_xgb_ray_tune pid=1821691)[0m [305]	train-mlogloss:1.96990	validation-mlogloss:1.93302
[36m(train_xgb_ray_tune pid=1821691)[0m [306]	train-mlogloss:1.96968	validation-mlogloss:1.93283
[36m(train_xgb_ray_tune pid=1821680)[0m [275]	train-mlogloss:1.93359	validation-mlogloss:1.90124
[36m(train_xgb_ray_tune pid=1821680)[0m [276]	train-mlogloss:1.93287	validation-mlogloss:1.90060
[36m(train_xgb_ray_tune pid=1821689)[0m [323]	train-mlogloss:2.07371	validation-mlogloss:2.02604
[36m(train_xgb_ray_tune pid=1821669)[0m [288]	train-mlogloss:2.06727	validation-mlogloss:2.03632
[36m(train_xgb_ray_tune pid=1821669)[0m [289]	train-mlogloss:2.06632	validation-mlogloss:2.03521
[36m(train_xgb_ray_tune pid=1821686)[0m [312]	train-mlogloss:2.26326	validation-mlogloss:2.24733
[36m(train_xgb_ray_tune pid=1821686)[0m [313]	train-mlogloss:2.26279	validation-mlogloss:2.24694
[36m(train_xgb_ray_tune pid=1821682)[0m [396]	train-mlogloss:2.40266	validation-mlogloss:2.42308
[36m(train_xgb_ray_tune pid=1821682)[0m [397]	train-mlogloss:2.40266	validation-mlogloss:2.42308
[36m(train_xgb_ray_tune pid=1821682)[0m [398]	train-mlogloss:2.40252	validation-mlogloss:2.42295
[36m(train_xgb_ray_tune pid=1821682)[0m [399]	train-mlogloss:2.40245	validation-mlogloss:2.42290
[36m(train_xgb_ray_tune pid=1821687)[0m [332]	train-mlogloss:2.06052	validation-mlogloss:2.02713
[36m(train_xgb_ray_tune pid=1821687)[0m [333]	train-mlogloss:2.06008	validation-mlogloss:2.02669
[36m(train_xgb_ray_tune pid=1821670)[0m [318]	train-mlogloss:1.89812	validation-mlogloss:1.86886
[36m(train_xgb_ray_tune pid=1821670)[0m [319]	train-mlogloss:1.89734	validation-mlogloss:1.86835
[36m(train_xgb_ray_tune pid=1821684)[0m [320]	train-mlogloss:2.21268	validation-mlogloss:2.19359
[36m(train_xgb_ray_tune pid=1821684)[0m [321]	train-mlogloss:2.21225	validation-mlogloss:2.19323
[36m(train_xgb_ray_tune pid=1821684)[0m [322]	train-mlogloss:2.21188	validation-mlogloss:2.19291
[36m(train_xgb_ray_tune pid=1821674)[0m [308]	train-mlogloss:2.00082	validation-mlogloss:1.94874
[36m(train_xgb_ray_tune pid=1821674)[0m [309]	train-mlogloss:2.00009	validation-mlogloss:1.94813
[36m(train_xgb_ray_tune pid=1821683)[0m [334]	train-mlogloss:2.25304	validation-mlogloss:2.24429
[36m(train_xgb_ray_tune pid=1821683)[0m [335]	train-mlogloss:2.25268	validation-mlogloss:2.24397
[36m(train_xgb_ray_tune pid=1821683)[0m [336]	train-mlogloss:2.25237	validation-mlogloss:2.24372
[36m(train_xgb_ray_tune pid=1821689)[0m [324]	train-mlogloss:2.07286	validation-mlogloss:2.02527
[36m(train_xgb_ray_tune pid=1821670)[0m [320]	train-mlogloss:1.89652	validation-mlogloss:1.86761
[36m(train_xgb_ray_tune pid=1821680)[0m [277]	train-mlogloss:1.93219	validation-mlogloss:1.90007
[36m(train_xgb_ray_tune pid=1821683)[0m [337]	train-mlogloss:2.25207	validation-mlogloss:2.24343
[36m(train_xgb_ray_tune pid=1821663)[0m [269]	train-mlogloss:2.04176	validation-mlogloss:1.99974
[36m(train_xgb_ray_tune pid=1821663)[0m [270]	train-mlogloss:2.04065	validation-mlogloss:1.99873
[36m(train_xgb_ray_tune pid=1821663)[0m [271]	train-mlogloss:2.03963	validation-mlogloss:1.99761
[36m(train_xgb_ray_tune pid=1821691)[0m [307]	train-mlogloss:1.96931	validation-mlogloss:1.93249
[36m(train_xgb_ray_tune pid=1821691)[0m [308]	train-mlogloss:1.96886	validation-mlogloss:1.93210
[36m(train_xgb_ray_tune pid=1821680)[0m [278]	train-mlogloss:1.93145	validation-mlogloss:1.89948
[36m(train_xgb_ray_tune pid=1821680)[0m [279]	train-mlogloss:1.93077	validation-mlogloss:1.89891
[36m(train_xgb_ray_tune pid=1821689)[0m [325]	train-mlogloss:2.07194	validation-mlogloss:2.02445
[36m(train_xgb_ray_tune pid=1821669)[0m [290]	train-mlogloss:2.06532	validation-mlogloss:2.03427
[36m(train_xgb_ray_tune pid=1821669)[0m [291]	train-mlogloss:2.06430	validation-mlogloss:2.03328
[36m(train_xgb_ray_tune pid=1821686)[0m [314]	train-mlogloss:2.26223	validation-mlogloss:2.24638
[36m(train_xgb_ray_tune pid=1821682)[0m [400]	train-mlogloss:2.40245	validation-mlogloss:2.42290
[36m(train_xgb_ray_tune pid=1821682)[0m [401]	train-mlogloss:2.40245	validation-mlogloss:2.42290
[36m(train_xgb_ray_tune pid=1821682)[0m [402]	train-mlogloss:2.40245	validation-mlogloss:2.42290
[36m(train_xgb_ray_tune pid=1821682)[0m [403]	train-mlogloss:2.40245	validation-mlogloss:2.42290
[36m(train_xgb_ray_tune pid=1821687)[0m [334]	train-mlogloss:2.05940	validation-mlogloss:2.02608
[36m(train_xgb_ray_tune pid=1821687)[0m [335]	train-mlogloss:2.05890	validation-mlogloss:2.02559
[36m(train_xgb_ray_tune pid=1821670)[0m [321]	train-mlogloss:1.89567	validation-mlogloss:1.86689
[36m(train_xgb_ray_tune pid=1821670)[0m [322]	train-mlogloss:1.89486	validation-mlogloss:1.86615
[36m(train_xgb_ray_tune pid=1821670)[0m [323]	train-mlogloss:1.89402	validation-mlogloss:1.86537
[36m(train_xgb_ray_tune pid=1821684)[0m [323]	train-mlogloss:2.21153	validation-mlogloss:2.19259
[36m(train_xgb_ray_tune pid=1821684)[0m [324]	train-mlogloss:2.21120	validation-mlogloss:2.19231
[36m(train_xgb_ray_tune pid=1821684)[0m [325]	train-mlogloss:2.21087	validation-mlogloss:2.19202
[36m(train_xgb_ray_tune pid=1821674)[0m [310]	train-mlogloss:1.99965	validation-mlogloss:1.94775
[36m(train_xgb_ray_tune pid=1821674)[0m [311]	train-mlogloss:1.99912	validation-mlogloss:1.94733
[36m(train_xgb_ray_tune pid=1821683)[0m [338]	train-mlogloss:2.25180	validation-mlogloss:2.24314
[36m(train_xgb_ray_tune pid=1821683)[0m [339]	train-mlogloss:2.25149	validation-mlogloss:2.24283
[36m(train_xgb_ray_tune pid=1821683)[0m [340]	train-mlogloss:2.25123	validation-mlogloss:2.24258
[36m(train_xgb_ray_tune pid=1821686)[0m [315]	train-mlogloss:2.26169	validation-mlogloss:2.24588
[36m(train_xgb_ray_tune pid=1821669)[0m [292]	train-mlogloss:2.06341	validation-mlogloss:2.03231
[36m(train_xgb_ray_tune pid=1821684)[0m [326]	train-mlogloss:2.21053	validation-mlogloss:2.19170
[36m(train_xgb_ray_tune pid=1821691)[0m [309]	train-mlogloss:1.96849	validation-mlogloss:1.93179
[36m(train_xgb_ray_tune pid=1821689)[0m [326]	train-mlogloss:2.07104	validation-mlogloss:2.02363
[36m(train_xgb_ray_tune pid=1821682)[0m [404]	train-mlogloss:2.40245	validation-mlogloss:2.42290
[36m(train_xgb_ray_tune pid=1821687)[0m [336]	train-mlogloss:2.05835	validation-mlogloss:2.02500
[36m(train_xgb_ray_tune pid=1821680)[0m [280]	train-mlogloss:1.93007	validation-mlogloss:1.89828
[36m(train_xgb_ray_tune pid=1821663)[0m [272]	train-mlogloss:2.03856	validation-mlogloss:1.99661
[36m(train_xgb_ray_tune pid=1821663)[0m [273]	train-mlogloss:2.03756	validation-mlogloss:1.99558
[36m(train_xgb_ray_tune pid=1821691)[0m [310]	train-mlogloss:1.96821	validation-mlogloss:1.93158
[36m(train_xgb_ray_tune pid=1821691)[0m [311]	train-mlogloss:1.96784	validation-mlogloss:1.93129
[36m(train_xgb_ray_tune pid=1821680)[0m [281]	train-mlogloss:1.92927	validation-mlogloss:1.89762
[36m(train_xgb_ray_tune pid=1821680)[0m [282]	train-mlogloss:1.92864	validation-mlogloss:1.89714
[36m(train_xgb_ray_tune pid=1821689)[0m [327]	train-mlogloss:2.07019	validation-mlogloss:2.02279
[36m(train_xgb_ray_tune pid=1821669)[0m [293]	train-mlogloss:2.06253	validation-mlogloss:2.03154
[36m(train_xgb_ray_tune pid=1821686)[0m [316]	train-mlogloss:2.26121	validation-mlogloss:2.24542
[36m(train_xgb_ray_tune pid=1821686)[0m [317]	train-mlogloss:2.26079	validation-mlogloss:2.24504
[36m(train_xgb_ray_tune pid=1821682)[0m [405]	train-mlogloss:2.40245	validation-mlogloss:2.42290
[36m(train_xgb_ray_tune pid=1821682)[0m [406]	train-mlogloss:2.40245	validation-mlogloss:2.42290
[36m(train_xgb_ray_tune pid=1821682)[0m [407]	train-mlogloss:2.40238	validation-mlogloss:2.42286
[36m(train_xgb_ray_tune pid=1821682)[0m [408]	train-mlogloss:2.40238	validation-mlogloss:2.42286
[36m(train_xgb_ray_tune pid=1821687)[0m [337]	train-mlogloss:2.05775	validation-mlogloss:2.02432
[36m(train_xgb_ray_tune pid=1821687)[0m [338]	train-mlogloss:2.05722	validation-mlogloss:2.02389
[36m(train_xgb_ray_tune pid=1821687)[0m [339]	train-mlogloss:2.05663	validation-mlogloss:2.02337
[36m(train_xgb_ray_tune pid=1821670)[0m [324]	train-mlogloss:1.89319	validation-mlogloss:1.86482
[36m(train_xgb_ray_tune pid=1821670)[0m [325]	train-mlogloss:1.89239	validation-mlogloss:1.86434
[36m(train_xgb_ray_tune pid=1821670)[0m [326]	train-mlogloss:1.89157	validation-mlogloss:1.86388
[36m(train_xgb_ray_tune pid=1821684)[0m [327]	train-mlogloss:2.21014	validation-mlogloss:2.19131
[36m(train_xgb_ray_tune pid=1821684)[0m [328]	train-mlogloss:2.20983	validation-mlogloss:2.19105
[36m(train_xgb_ray_tune pid=1821684)[0m [329]	train-mlogloss:2.20938	validation-mlogloss:2.19060
[36m(train_xgb_ray_tune pid=1821674)[0m [312]	train-mlogloss:1.99857	validation-mlogloss:1.94681
[36m(train_xgb_ray_tune pid=1821674)[0m [313]	train-mlogloss:1.99804	validation-mlogloss:1.94633
[36m(train_xgb_ray_tune pid=1821683)[0m [341]	train-mlogloss:2.25101	validation-mlogloss:2.24242
[36m(train_xgb_ray_tune pid=1821683)[0m [342]	train-mlogloss:2.25066	validation-mlogloss:2.24212
[36m(train_xgb_ray_tune pid=1821663)[0m [274]	train-mlogloss:2.03650	validation-mlogloss:1.99457
[36m(train_xgb_ray_tune pid=1821669)[0m [294]	train-mlogloss:2.06178	validation-mlogloss:2.03086
[36m(train_xgb_ray_tune pid=1821663)[0m [275]	train-mlogloss:2.03547	validation-mlogloss:1.99376
[36m(train_xgb_ray_tune pid=1821663)[0m [276]	train-mlogloss:2.03440	validation-mlogloss:1.99281
[36m(train_xgb_ray_tune pid=1821691)[0m [312]	train-mlogloss:1.96752	validation-mlogloss:1.93093
[36m(train_xgb_ray_tune pid=1821691)[0m [313]	train-mlogloss:1.96699	validation-mlogloss:1.93034
[36m(train_xgb_ray_tune pid=1821680)[0m [283]	train-mlogloss:1.92799	validation-mlogloss:1.89667
[36m(train_xgb_ray_tune pid=1821680)[0m [284]	train-mlogloss:1.92738	validation-mlogloss:1.89613
[36m(train_xgb_ray_tune pid=1821680)[0m [285]	train-mlogloss:1.92682	validation-mlogloss:1.89572
[36m(train_xgb_ray_tune pid=1821689)[0m [328]	train-mlogloss:2.06937	validation-mlogloss:2.02206
[36m(train_xgb_ray_tune pid=1821689)[0m [329]	train-mlogloss:2.06850	validation-mlogloss:2.02123
[36m(train_xgb_ray_tune pid=1821669)[0m [295]	train-mlogloss:2.06092	validation-mlogloss:2.02997
[36m(train_xgb_ray_tune pid=1821686)[0m [318]	train-mlogloss:2.26029	validation-mlogloss:2.24462
[36m(train_xgb_ray_tune pid=1821686)[0m [319]	train-mlogloss:2.25995	validation-mlogloss:2.24433
[36m(train_xgb_ray_tune pid=1821682)[0m [409]	train-mlogloss:2.40238	validation-mlogloss:2.42286
[36m(train_xgb_ray_tune pid=1821682)[0m [410]	train-mlogloss:2.40238	validation-mlogloss:2.42286
[36m(train_xgb_ray_tune pid=1821682)[0m [411]	train-mlogloss:2.40238	validation-mlogloss:2.42286
[36m(train_xgb_ray_tune pid=1821682)[0m [412]	train-mlogloss:2.40231	validation-mlogloss:2.42281
[36m(train_xgb_ray_tune pid=1821687)[0m [340]	train-mlogloss:2.05612	validation-mlogloss:2.02293
[36m(train_xgb_ray_tune pid=1821687)[0m [341]	train-mlogloss:2.05548	validation-mlogloss:2.02230
[36m(train_xgb_ray_tune pid=1821687)[0m [342]	train-mlogloss:2.05493	validation-mlogloss:2.02180
[36m(train_xgb_ray_tune pid=1821670)[0m [327]	train-mlogloss:1.89082	validation-mlogloss:1.86322
[36m(train_xgb_ray_tune pid=1821670)[0m [328]	train-mlogloss:1.88993	validation-mlogloss:1.86254
[36m(train_xgb_ray_tune pid=1821670)[0m [329]	train-mlogloss:1.88908	validation-mlogloss:1.86169
[36m(train_xgb_ray_tune pid=1821684)[0m [330]	train-mlogloss:2.20889	validation-mlogloss:2.19015
[36m(train_xgb_ray_tune pid=1821684)[0m [331]	train-mlogloss:2.20852	validation-mlogloss:2.18981
[36m(train_xgb_ray_tune pid=1821684)[0m [332]	train-mlogloss:2.20810	validation-mlogloss:2.18936
[36m(train_xgb_ray_tune pid=1821684)[0m [333]	train-mlogloss:2.20776	validation-mlogloss:2.18907
[36m(train_xgb_ray_tune pid=1821674)[0m [314]	train-mlogloss:1.99750	validation-mlogloss:1.94579
[36m(train_xgb_ray_tune pid=1821674)[0m [315]	train-mlogloss:1.99700	validation-mlogloss:1.94542
[36m(train_xgb_ray_tune pid=1821683)[0m [343]	train-mlogloss:2.25035	validation-mlogloss:2.24180
[36m(train_xgb_ray_tune pid=1821683)[0m [344]	train-mlogloss:2.25002	validation-mlogloss:2.24148

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:02. Total running time: 32s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             29.3636 │
│ time_total_s                 29.3636 │
│ training_iteration                 1 │
│ validation_accuracy          0.49891 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:02. Total running time: 32s
[36m(train_xgb_ray_tune pid=1821663)[0m [277]	train-mlogloss:2.03330	validation-mlogloss:1.99180
[36m(train_xgb_ray_tune pid=1821663)[0m [278]	train-mlogloss:2.03230	validation-mlogloss:1.99092
[36m(train_xgb_ray_tune pid=1821691)[0m [314]	train-mlogloss:1.96668	validation-mlogloss:1.93006
[36m(train_xgb_ray_tune pid=1821691)[0m [315]	train-mlogloss:1.96632	validation-mlogloss:1.92972
[36m(train_xgb_ray_tune pid=1821691)[0m [316]	train-mlogloss:1.96601	validation-mlogloss:1.92954
[36m(train_xgb_ray_tune pid=1821680)[0m [286]	train-mlogloss:1.92619	validation-mlogloss:1.89523
[36m(train_xgb_ray_tune pid=1821680)[0m [287]	train-mlogloss:1.92555	validation-mlogloss:1.89479
[36m(train_xgb_ray_tune pid=1821680)[0m [288]	train-mlogloss:1.92488	validation-mlogloss:1.89424
[36m(train_xgb_ray_tune pid=1821689)[0m [330]	train-mlogloss:2.06765	validation-mlogloss:2.02030
[36m(train_xgb_ray_tune pid=1821689)[0m [331]	train-mlogloss:2.06676	validation-mlogloss:2.01945
[36m(train_xgb_ray_tune pid=1821689)[0m [332]	train-mlogloss:2.06590	validation-mlogloss:2.01862
[36m(train_xgb_ray_tune pid=1821669)[0m [296]	train-mlogloss:2.06004	validation-mlogloss:2.02904
[36m(train_xgb_ray_tune pid=1821669)[0m [297]	train-mlogloss:2.05921	validation-mlogloss:2.02820
[36m(train_xgb_ray_tune pid=1821686)[0m [320]	train-mlogloss:2.25948	validation-mlogloss:2.24387
[36m(train_xgb_ray_tune pid=1821686)[0m [321]	train-mlogloss:2.25906	validation-mlogloss:2.24350
[36m(train_xgb_ray_tune pid=1821682)[0m [413]	train-mlogloss:2.40231	validation-mlogloss:2.42281
[36m(train_xgb_ray_tune pid=1821682)[0m [414]	train-mlogloss:2.40231	validation-mlogloss:2.42281
[36m(train_xgb_ray_tune pid=1821687)[0m [343]	train-mlogloss:2.05439	validation-mlogloss:2.02121
[36m(train_xgb_ray_tune pid=1821687)[0m [344]	train-mlogloss:2.05385	validation-mlogloss:2.02068
[36m(train_xgb_ray_tune pid=1821687)[0m [345]	train-mlogloss:2.05338	validation-mlogloss:2.02032
[36m(train_xgb_ray_tune pid=1821670)[0m [330]	train-mlogloss:1.88829	validation-mlogloss:1.86135
[36m(train_xgb_ray_tune pid=1821670)[0m [331]	train-mlogloss:1.88760	validation-mlogloss:1.86066
[36m(train_xgb_ray_tune pid=1821670)[0m [332]	train-mlogloss:1.88689	validation-mlogloss:1.86033
[36m(train_xgb_ray_tune pid=1821684)[0m [334]	train-mlogloss:2.20743	validation-mlogloss:2.18878
[36m(train_xgb_ray_tune pid=1821684)[0m [335]	train-mlogloss:2.20715	validation-mlogloss:2.18855
[36m(train_xgb_ray_tune pid=1821684)[0m [336]	train-mlogloss:2.20680	validation-mlogloss:2.18822
[36m(train_xgb_ray_tune pid=1821674)[0m [316]	train-mlogloss:1.99645	validation-mlogloss:1.94484
[36m(train_xgb_ray_tune pid=1821683)[0m [345]	train-mlogloss:2.24967	validation-mlogloss:2.24120
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[36m(train_xgb_ray_tune pid=1821684)[0m [354]	train-mlogloss:2.20032	validation-mlogloss:2.18236
[36m(train_xgb_ray_tune pid=1821663)[0m [293]	train-mlogloss:2.01749	validation-mlogloss:1.97726
[36m(train_xgb_ray_tune pid=1821663)[0m [294]	train-mlogloss:2.01650	validation-mlogloss:1.97646
[36m(train_xgb_ray_tune pid=1821663)[0m [295]	train-mlogloss:2.01560	validation-mlogloss:1.97563
[36m(train_xgb_ray_tune pid=1821691)[0m [335]	train-mlogloss:1.96046	validation-mlogloss:1.92534
[36m(train_xgb_ray_tune pid=1821691)[0m [336]	train-mlogloss:1.96018	validation-mlogloss:1.92507
[36m(train_xgb_ray_tune pid=1821691)[0m [337]	train-mlogloss:1.95994	validation-mlogloss:1.92493
[36m(train_xgb_ray_tune pid=1821691)[0m [338]	train-mlogloss:1.95967	validation-mlogloss:1.92476
[36m(train_xgb_ray_tune pid=1821680)[0m [304]	train-mlogloss:1.91458	validation-mlogloss:1.88604
[36m(train_xgb_ray_tune pid=1821680)[0m [305]	train-mlogloss:1.91389	validation-mlogloss:1.88551
[36m(train_xgb_ray_tune pid=1821680)[0m [306]	train-mlogloss:1.91327	validation-mlogloss:1.88509
[36m(train_xgb_ray_tune pid=1821669)[0m [308]	train-mlogloss:2.04987	validation-mlogloss:2.01904
[36m(train_xgb_ray_tune pid=1821669)[0m [309]	train-mlogloss:2.04917	validation-mlogloss:2.01834
[36m(train_xgb_ray_tune pid=1821686)[0m [332]	train-mlogloss:2.25454	validation-mlogloss:2.23938
[36m(train_xgb_ray_tune pid=1821686)[0m [333]	train-mlogloss:2.25420	validation-mlogloss:2.23906
[36m(train_xgb_ray_tune pid=1821682)[0m [428]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821682)[0m [429]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821687)[0m [364]	train-mlogloss:2.04383	validation-mlogloss:2.01167
[36m(train_xgb_ray_tune pid=1821687)[0m [365]	train-mlogloss:2.04334	validation-mlogloss:2.01118
[36m(train_xgb_ray_tune pid=1821687)[0m [366]	train-mlogloss:2.04294	validation-mlogloss:2.01092
[36m(train_xgb_ray_tune pid=1821670)[0m [349]	train-mlogloss:1.87444	validation-mlogloss:1.85021
[36m(train_xgb_ray_tune pid=1821670)[0m [350]	train-mlogloss:1.87375	validation-mlogloss:1.84980
[36m(train_xgb_ray_tune pid=1821670)[0m [351]	train-mlogloss:1.87308	validation-mlogloss:1.84932
[36m(train_xgb_ray_tune pid=1821684)[0m [355]	train-mlogloss:2.20009	validation-mlogloss:2.18216
[36m(train_xgb_ray_tune pid=1821684)[0m [356]	train-mlogloss:2.19976	validation-mlogloss:2.18188
[36m(train_xgb_ray_tune pid=1821684)[0m [357]	train-mlogloss:2.19953	validation-mlogloss:2.18168
[36m(train_xgb_ray_tune pid=1821674)[0m [328]	train-mlogloss:1.99039	validation-mlogloss:1.93971
[36m(train_xgb_ray_tune pid=1821674)[0m [329]	train-mlogloss:1.98989	validation-mlogloss:1.93932
[36m(train_xgb_ray_tune pid=1821683)[0m [358]	train-mlogloss:2.24615	validation-mlogloss:2.23803
[36m(train_xgb_ray_tune pid=1821683)[0m [359]	train-mlogloss:2.24587	validation-mlogloss:2.23780
[36m(train_xgb_ray_tune pid=1821663)[0m [296]	train-mlogloss:2.01460	validation-mlogloss:1.97475
[36m(train_xgb_ray_tune pid=1821663)[0m [297]	train-mlogloss:2.01361	validation-mlogloss:1.97386
[36m(train_xgb_ray_tune pid=1821691)[0m [339]	train-mlogloss:1.95948	validation-mlogloss:1.92461
[36m(train_xgb_ray_tune pid=1821691)[0m [340]	train-mlogloss:1.95929	validation-mlogloss:1.92446
[36m(train_xgb_ray_tune pid=1821691)[0m [341]	train-mlogloss:1.95914	validation-mlogloss:1.92437
[36m(train_xgb_ray_tune pid=1821680)[0m [307]	train-mlogloss:1.91272	validation-mlogloss:1.88464
[36m(train_xgb_ray_tune pid=1821680)[0m [308]	train-mlogloss:1.91207	validation-mlogloss:1.88409
[36m(train_xgb_ray_tune pid=1821680)[0m [309]	train-mlogloss:1.91156	validation-mlogloss:1.88378
[36m(train_xgb_ray_tune pid=1821669)[0m [310]	train-mlogloss:2.04832	validation-mlogloss:2.01741
[36m(train_xgb_ray_tune pid=1821669)[0m [311]	train-mlogloss:2.04754	validation-mlogloss:2.01682
[36m(train_xgb_ray_tune pid=1821686)[0m [334]	train-mlogloss:2.25371	validation-mlogloss:2.23856
[36m(train_xgb_ray_tune pid=1821686)[0m [335]	train-mlogloss:2.25326	validation-mlogloss:2.23811
[36m(train_xgb_ray_tune pid=1821682)[0m [430]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821682)[0m [431]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821687)[0m [367]	train-mlogloss:2.04255	validation-mlogloss:2.01044
[36m(train_xgb_ray_tune pid=1821687)[0m [368]	train-mlogloss:2.04209	validation-mlogloss:2.01009
[36m(train_xgb_ray_tune pid=1821687)[0m [369]	train-mlogloss:2.04168	validation-mlogloss:2.00966
[36m(train_xgb_ray_tune pid=1821687)[0m [370]	train-mlogloss:2.04128	validation-mlogloss:2.00919
[36m(train_xgb_ray_tune pid=1821670)[0m [352]	train-mlogloss:1.87230	validation-mlogloss:1.84873
[36m(train_xgb_ray_tune pid=1821670)[0m [353]	train-mlogloss:1.87150	validation-mlogloss:1.84824
[36m(train_xgb_ray_tune pid=1821684)[0m [358]	train-mlogloss:2.19921	validation-mlogloss:2.18138
[36m(train_xgb_ray_tune pid=1821684)[0m [359]	train-mlogloss:2.19889	validation-mlogloss:2.18111
[36m(train_xgb_ray_tune pid=1821684)[0m [360]	train-mlogloss:2.19863	validation-mlogloss:2.18088
[36m(train_xgb_ray_tune pid=1821684)[0m [361]	train-mlogloss:2.19816	validation-mlogloss:2.18044
[36m(train_xgb_ray_tune pid=1821674)[0m [330]	train-mlogloss:1.98943	validation-mlogloss:1.93893
[36m(train_xgb_ray_tune pid=1821683)[0m [360]	train-mlogloss:2.24563	validation-mlogloss:2.23762
[36m(train_xgb_ray_tune pid=1821683)[0m [361]	train-mlogloss:2.24527	validation-mlogloss:2.23731
[36m(train_xgb_ray_tune pid=1821663)[0m [298]	train-mlogloss:2.01266	validation-mlogloss:1.97291
[36m(train_xgb_ray_tune pid=1821670)[0m [354]	train-mlogloss:1.87077	validation-mlogloss:1.84771
[36m(train_xgb_ray_tune pid=1821674)[0m [331]	train-mlogloss:1.98889	validation-mlogloss:1.93859
[36m(train_xgb_ray_tune pid=1821663)[0m [299]	train-mlogloss:2.01170	validation-mlogloss:1.97207
[36m(train_xgb_ray_tune pid=1821663)[0m [300]	train-mlogloss:2.01084	validation-mlogloss:1.97122
[36m(train_xgb_ray_tune pid=1821691)[0m [342]	train-mlogloss:1.95882	validation-mlogloss:1.92405
[36m(train_xgb_ray_tune pid=1821691)[0m [343]	train-mlogloss:1.95861	validation-mlogloss:1.92383
[36m(train_xgb_ray_tune pid=1821691)[0m [344]	train-mlogloss:1.95842	validation-mlogloss:1.92365
[36m(train_xgb_ray_tune pid=1821691)[0m [345]	train-mlogloss:1.95814	validation-mlogloss:1.92343
[36m(train_xgb_ray_tune pid=1821680)[0m [310]	train-mlogloss:1.91102	validation-mlogloss:1.88337
[36m(train_xgb_ray_tune pid=1821680)[0m [311]	train-mlogloss:1.91039	validation-mlogloss:1.88297
[36m(train_xgb_ray_tune pid=1821680)[0m [312]	train-mlogloss:1.90984	validation-mlogloss:1.88252
[36m(train_xgb_ray_tune pid=1821669)[0m [312]	train-mlogloss:2.04674	validation-mlogloss:2.01598
[36m(train_xgb_ray_tune pid=1821669)[0m [313]	train-mlogloss:2.04590	validation-mlogloss:2.01513
[36m(train_xgb_ray_tune pid=1821686)[0m [336]	train-mlogloss:2.25290	validation-mlogloss:2.23785
[36m(train_xgb_ray_tune pid=1821686)[0m [337]	train-mlogloss:2.25248	validation-mlogloss:2.23743
[36m(train_xgb_ray_tune pid=1821682)[0m [432]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821682)[0m [433]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821687)[0m [371]	train-mlogloss:2.04085	validation-mlogloss:2.00882
[36m(train_xgb_ray_tune pid=1821687)[0m [372]	train-mlogloss:2.04048	validation-mlogloss:2.00846
[36m(train_xgb_ray_tune pid=1821687)[0m [373]	train-mlogloss:2.03999	validation-mlogloss:2.00811
[36m(train_xgb_ray_tune pid=1821670)[0m [355]	train-mlogloss:1.87005	validation-mlogloss:1.84729
[36m(train_xgb_ray_tune pid=1821670)[0m [356]	train-mlogloss:1.86939	validation-mlogloss:1.84675
[36m(train_xgb_ray_tune pid=1821670)[0m [357]	train-mlogloss:1.86877	validation-mlogloss:1.84634
[36m(train_xgb_ray_tune pid=1821684)[0m [362]	train-mlogloss:2.19778	validation-mlogloss:2.18005
[36m(train_xgb_ray_tune pid=1821684)[0m [363]	train-mlogloss:2.19752	validation-mlogloss:2.17978
[36m(train_xgb_ray_tune pid=1821684)[0m [364]	train-mlogloss:2.19719	validation-mlogloss:2.17944
[36m(train_xgb_ray_tune pid=1821674)[0m [332]	train-mlogloss:1.98843	validation-mlogloss:1.93821
[36m(train_xgb_ray_tune pid=1821683)[0m [362]	train-mlogloss:2.24498	validation-mlogloss:2.23703
[36m(train_xgb_ray_tune pid=1821683)[0m [363]	train-mlogloss:2.24469	validation-mlogloss:2.23674
[36m(train_xgb_ray_tune pid=1821682)[0m [434]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821674)[0m [333]	train-mlogloss:1.98799	validation-mlogloss:1.93788

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:03. Total running time: 33s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             30.3986 │
│ time_total_s                 30.3986 │
│ training_iteration                 1 │
│ validation_accuracy           0.4864 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:03. Total running time: 33s
[36m(train_xgb_ray_tune pid=1821663)[0m [301]	train-mlogloss:2.00999	validation-mlogloss:1.97034
[36m(train_xgb_ray_tune pid=1821663)[0m [302]	train-mlogloss:2.00910	validation-mlogloss:1.96946
[36m(train_xgb_ray_tune pid=1821663)[0m [303]	train-mlogloss:2.00816	validation-mlogloss:1.96844
[36m(train_xgb_ray_tune pid=1821691)[0m [346]	train-mlogloss:1.95797	validation-mlogloss:1.92328
[36m(train_xgb_ray_tune pid=1821691)[0m [347]	train-mlogloss:1.95764	validation-mlogloss:1.92303
[36m(train_xgb_ray_tune pid=1821691)[0m [348]	train-mlogloss:1.95749	validation-mlogloss:1.92298
[36m(train_xgb_ray_tune pid=1821691)[0m [349]	train-mlogloss:1.95721	validation-mlogloss:1.92270
[36m(train_xgb_ray_tune pid=1821680)[0m [313]	train-mlogloss:1.90931	validation-mlogloss:1.88213
[36m(train_xgb_ray_tune pid=1821680)[0m [314]	train-mlogloss:1.90885	validation-mlogloss:1.88189
[36m(train_xgb_ray_tune pid=1821680)[0m [315]	train-mlogloss:1.90842	validation-mlogloss:1.88155
[36m(train_xgb_ray_tune pid=1821669)[0m [314]	train-mlogloss:2.04510	validation-mlogloss:2.01425
[36m(train_xgb_ray_tune pid=1821686)[0m [338]	train-mlogloss:2.25211	validation-mlogloss:2.23707
[36m(train_xgb_ray_tune pid=1821686)[0m [339]	train-mlogloss:2.25171	validation-mlogloss:2.23669
[36m(train_xgb_ray_tune pid=1821682)[0m [435]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821682)[0m [436]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821687)[0m [374]	train-mlogloss:2.03951	validation-mlogloss:2.00770
[36m(train_xgb_ray_tune pid=1821687)[0m [375]	train-mlogloss:2.03909	validation-mlogloss:2.00728
[36m(train_xgb_ray_tune pid=1821687)[0m [376]	train-mlogloss:2.03872	validation-mlogloss:2.00693
[36m(train_xgb_ray_tune pid=1821670)[0m [358]	train-mlogloss:1.86807	validation-mlogloss:1.84571
[36m(train_xgb_ray_tune pid=1821670)[0m [359]	train-mlogloss:1.86740	validation-mlogloss:1.84532
[36m(train_xgb_ray_tune pid=1821670)[0m [360]	train-mlogloss:1.86673	validation-mlogloss:1.84484
[36m(train_xgb_ray_tune pid=1821684)[0m [365]	train-mlogloss:2.19697	validation-mlogloss:2.17926
[36m(train_xgb_ray_tune pid=1821684)[0m [366]	train-mlogloss:2.19662	validation-mlogloss:2.17896
[36m(train_xgb_ray_tune pid=1821684)[0m [367]	train-mlogloss:2.19640	validation-mlogloss:2.17877
[36m(train_xgb_ray_tune pid=1821684)[0m [368]	train-mlogloss:2.19605	validation-mlogloss:2.17847
[36m(train_xgb_ray_tune pid=1821674)[0m [334]	train-mlogloss:1.98757	validation-mlogloss:1.93755
[36m(train_xgb_ray_tune pid=1821674)[0m [335]	train-mlogloss:1.98714	validation-mlogloss:1.93723
[36m(train_xgb_ray_tune pid=1821683)[0m [364]	train-mlogloss:2.24441	validation-mlogloss:2.23649
[36m(train_xgb_ray_tune pid=1821683)[0m [365]	train-mlogloss:2.24413	validation-mlogloss:2.23627
[36m(train_xgb_ray_tune pid=1821683)[0m [366]	train-mlogloss:2.24390	validation-mlogloss:2.23604
[36m(train_xgb_ray_tune pid=1821680)[0m [316]	train-mlogloss:1.90795	validation-mlogloss:1.88124
[36m(train_xgb_ray_tune pid=1821687)[0m [377]	train-mlogloss:2.03838	validation-mlogloss:2.00678
[36m(train_xgb_ray_tune pid=1821663)[0m [304]	train-mlogloss:2.00734	validation-mlogloss:1.96766
[36m(train_xgb_ray_tune pid=1821663)[0m [305]	train-mlogloss:2.00641	validation-mlogloss:1.96685
[36m(train_xgb_ray_tune pid=1821691)[0m [350]	train-mlogloss:1.95701	validation-mlogloss:1.92260
[36m(train_xgb_ray_tune pid=1821691)[0m [351]	train-mlogloss:1.95687	validation-mlogloss:1.92251
[36m(train_xgb_ray_tune pid=1821691)[0m [352]	train-mlogloss:1.95661	validation-mlogloss:1.92225
[36m(train_xgb_ray_tune pid=1821680)[0m [317]	train-mlogloss:1.90751	validation-mlogloss:1.88096
[36m(train_xgb_ray_tune pid=1821680)[0m [318]	train-mlogloss:1.90711	validation-mlogloss:1.88063
[36m(train_xgb_ray_tune pid=1821680)[0m [319]	train-mlogloss:1.90642	validation-mlogloss:1.88023
[36m(train_xgb_ray_tune pid=1821686)[0m [340]	train-mlogloss:2.25124	validation-mlogloss:2.23624
[36m(train_xgb_ray_tune pid=1821686)[0m [341]	train-mlogloss:2.25085	validation-mlogloss:2.23583
[36m(train_xgb_ray_tune pid=1821682)[0m [437]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821682)[0m [438]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821687)[0m [378]	train-mlogloss:2.03789	validation-mlogloss:2.00629
[36m(train_xgb_ray_tune pid=1821687)[0m [379]	train-mlogloss:2.03747	validation-mlogloss:2.00599
[36m(train_xgb_ray_tune pid=1821687)[0m [380]	train-mlogloss:2.03697	validation-mlogloss:2.00555
[36m(train_xgb_ray_tune pid=1821670)[0m [361]	train-mlogloss:1.86611	validation-mlogloss:1.84434
[36m(train_xgb_ray_tune pid=1821670)[0m [362]	train-mlogloss:1.86542	validation-mlogloss:1.84372
[36m(train_xgb_ray_tune pid=1821684)[0m [369]	train-mlogloss:2.19577	validation-mlogloss:2.17821
[36m(train_xgb_ray_tune pid=1821684)[0m [370]	train-mlogloss:2.19536	validation-mlogloss:2.17784
[36m(train_xgb_ray_tune pid=1821684)[0m [371]	train-mlogloss:2.19513	validation-mlogloss:2.17761
[36m(train_xgb_ray_tune pid=1821684)[0m [372]	train-mlogloss:2.19488	validation-mlogloss:2.17738
[36m(train_xgb_ray_tune pid=1821674)[0m [336]	train-mlogloss:1.98678	validation-mlogloss:1.93702
[36m(train_xgb_ray_tune pid=1821674)[0m [337]	train-mlogloss:1.98633	validation-mlogloss:1.93666
[36m(train_xgb_ray_tune pid=1821674)[0m [338]	train-mlogloss:1.98590	validation-mlogloss:1.93626
[36m(train_xgb_ray_tune pid=1821674)[0m [339]	train-mlogloss:1.98530	validation-mlogloss:1.93570
[36m(train_xgb_ray_tune pid=1821683)[0m [367]	train-mlogloss:2.24362	validation-mlogloss:2.23576
[36m(train_xgb_ray_tune pid=1821683)[0m [368]	train-mlogloss:2.24320	validation-mlogloss:2.23537
[36m(train_xgb_ray_tune pid=1821683)[0m [369]	train-mlogloss:2.24288	validation-mlogloss:2.23505
[36m(train_xgb_ray_tune pid=1821683)[0m [370]	train-mlogloss:2.24260	validation-mlogloss:2.23481
[36m(train_xgb_ray_tune pid=1821663)[0m [306]	train-mlogloss:2.00563	validation-mlogloss:1.96613
[36m(train_xgb_ray_tune pid=1821670)[0m [363]	train-mlogloss:1.86474	validation-mlogloss:1.84320
[36m(train_xgb_ray_tune pid=1821663)[0m [307]	train-mlogloss:2.00468	validation-mlogloss:1.96515
[36m(train_xgb_ray_tune pid=1821663)[0m [308]	train-mlogloss:2.00384	validation-mlogloss:1.96445
[36m(train_xgb_ray_tune pid=1821691)[0m [353]	train-mlogloss:1.95636	validation-mlogloss:1.92193
[36m(train_xgb_ray_tune pid=1821691)[0m [354]	train-mlogloss:1.95616	validation-mlogloss:1.92182
[36m(train_xgb_ray_tune pid=1821691)[0m [355]	train-mlogloss:1.95586	validation-mlogloss:1.92155
[36m(train_xgb_ray_tune pid=1821691)[0m [356]	train-mlogloss:1.95551	validation-mlogloss:1.92119
[36m(train_xgb_ray_tune pid=1821680)[0m [320]	train-mlogloss:1.90594	validation-mlogloss:1.87983
[36m(train_xgb_ray_tune pid=1821680)[0m [321]	train-mlogloss:1.90541	validation-mlogloss:1.87958
[36m(train_xgb_ray_tune pid=1821680)[0m [322]	train-mlogloss:1.90488	validation-mlogloss:1.87921
[36m(train_xgb_ray_tune pid=1821686)[0m [342]	train-mlogloss:2.25046	validation-mlogloss:2.23551
[36m(train_xgb_ray_tune pid=1821686)[0m [343]	train-mlogloss:2.25012	validation-mlogloss:2.23520
[36m(train_xgb_ray_tune pid=1821682)[0m [439]	train-mlogloss:2.40210	validation-mlogloss:2.42266
[36m(train_xgb_ray_tune pid=1821687)[0m [381]	train-mlogloss:2.03652	validation-mlogloss:2.00516
[36m(train_xgb_ray_tune pid=1821687)[0m [382]	train-mlogloss:2.03613	validation-mlogloss:2.00487
[36m(train_xgb_ray_tune pid=1821687)[0m [383]	train-mlogloss:2.03579	validation-mlogloss:2.00462
[36m(train_xgb_ray_tune pid=1821670)[0m [364]	train-mlogloss:1.86409	validation-mlogloss:1.84280
[36m(train_xgb_ray_tune pid=1821670)[0m [365]	train-mlogloss:1.86345	validation-mlogloss:1.84233
[36m(train_xgb_ray_tune pid=1821670)[0m [366]	train-mlogloss:1.86272	validation-mlogloss:1.84167
[36m(train_xgb_ray_tune pid=1821684)[0m [373]	train-mlogloss:2.19459	validation-mlogloss:2.17708
[36m(train_xgb_ray_tune pid=1821684)[0m [374]	train-mlogloss:2.19421	validation-mlogloss:2.17669
[36m(train_xgb_ray_tune pid=1821684)[0m [375]	train-mlogloss:2.19387	validation-mlogloss:2.17634
[36m(train_xgb_ray_tune pid=1821674)[0m [340]	train-mlogloss:1.98463	validation-mlogloss:1.93513
[36m(train_xgb_ray_tune pid=1821674)[0m [341]	train-mlogloss:1.98415	validation-mlogloss:1.93473
[36m(train_xgb_ray_tune pid=1821674)[0m [342]	train-mlogloss:1.98377	validation-mlogloss:1.93438
[36m(train_xgb_ray_tune pid=1821683)[0m [371]	train-mlogloss:2.24233	validation-mlogloss:2.23453
[36m(train_xgb_ray_tune pid=1821683)[0m [372]	train-mlogloss:2.24208	validation-mlogloss:2.23430
[36m(train_xgb_ray_tune pid=1821683)[0m [373]	train-mlogloss:2.24181	validation-mlogloss:2.23405
[36m(train_xgb_ray_tune pid=1821683)[0m [374]	train-mlogloss:2.24152	validation-mlogloss:2.23377
[36m(train_xgb_ray_tune pid=1821663)[0m [309]	train-mlogloss:2.00301	validation-mlogloss:1.96377
[36m(train_xgb_ray_tune pid=1821686)[0m [344]	train-mlogloss:2.24980	validation-mlogloss:2.23494
[36m(train_xgb_ray_tune pid=1821687)[0m [384]	train-mlogloss:2.03542	validation-mlogloss:2.00421
[36m(train_xgb_ray_tune pid=1821684)[0m [376]	train-mlogloss:2.19355	validation-mlogloss:2.17603
[36m(train_xgb_ray_tune pid=1821663)[0m [310]	train-mlogloss:2.00220	validation-mlogloss:1.96310
[36m(train_xgb_ray_tune pid=1821663)[0m [311]	train-mlogloss:2.00135	validation-mlogloss:1.96237
[36m(train_xgb_ray_tune pid=1821691)[0m [357]	train-mlogloss:1.95530	validation-mlogloss:1.92096
[36m(train_xgb_ray_tune pid=1821691)[0m [358]	train-mlogloss:1.95510	validation-mlogloss:1.92086
[36m(train_xgb_ray_tune pid=1821691)[0m [359]	train-mlogloss:1.95496	validation-mlogloss:1.92072
[36m(train_xgb_ray_tune pid=1821691)[0m [360]	train-mlogloss:1.95477	validation-mlogloss:1.92053
[36m(train_xgb_ray_tune pid=1821680)[0m [323]	train-mlogloss:1.90428	validation-mlogloss:1.87865
[36m(train_xgb_ray_tune pid=1821680)[0m [324]	train-mlogloss:1.90366	validation-mlogloss:1.87825
[36m(train_xgb_ray_tune pid=1821680)[0m [325]	train-mlogloss:1.90324	validation-mlogloss:1.87803
[36m(train_xgb_ray_tune pid=1821686)[0m [345]	train-mlogloss:2.24951	validation-mlogloss:2.23469
[36m(train_xgb_ray_tune pid=1821686)[0m [346]	train-mlogloss:2.24905	validation-mlogloss:2.23427
[36m(train_xgb_ray_tune pid=1821687)[0m [385]	train-mlogloss:2.03498	validation-mlogloss:2.00379
[36m(train_xgb_ray_tune pid=1821687)[0m [386]	train-mlogloss:2.03462	validation-mlogloss:2.00340
[36m(train_xgb_ray_tune pid=1821687)[0m [387]	train-mlogloss:2.03430	validation-mlogloss:2.00311
[36m(train_xgb_ray_tune pid=1821670)[0m [367]	train-mlogloss:1.86197	validation-mlogloss:1.84118
[36m(train_xgb_ray_tune pid=1821670)[0m [368]	train-mlogloss:1.86134	validation-mlogloss:1.84072
[36m(train_xgb_ray_tune pid=1821670)[0m [369]	train-mlogloss:1.86066	validation-mlogloss:1.84015
[36m(train_xgb_ray_tune pid=1821684)[0m [377]	train-mlogloss:2.19334	validation-mlogloss:2.17581
[36m(train_xgb_ray_tune pid=1821684)[0m [378]	train-mlogloss:2.19304	validation-mlogloss:2.17557
[36m(train_xgb_ray_tune pid=1821684)[0m [379]	train-mlogloss:2.19283	validation-mlogloss:2.17543
[36m(train_xgb_ray_tune pid=1821674)[0m [343]	train-mlogloss:1.98338	validation-mlogloss:1.93395
[36m(train_xgb_ray_tune pid=1821674)[0m [344]	train-mlogloss:1.98295	validation-mlogloss:1.93353
[36m(train_xgb_ray_tune pid=1821674)[0m [345]	train-mlogloss:1.98243	validation-mlogloss:1.93304
[36m(train_xgb_ray_tune pid=1821674)[0m [346]	train-mlogloss:1.98198	validation-mlogloss:1.93255
[36m(train_xgb_ray_tune pid=1821683)[0m [375]	train-mlogloss:2.24128	validation-mlogloss:2.23353
[36m(train_xgb_ray_tune pid=1821683)[0m [376]	train-mlogloss:2.24110	validation-mlogloss:2.23334
[36m(train_xgb_ray_tune pid=1821683)[0m [377]	train-mlogloss:2.24069	validation-mlogloss:2.23303
[36m(train_xgb_ray_tune pid=1821683)[0m [378]	train-mlogloss:2.24051	validation-mlogloss:2.23286
[36m(train_xgb_ray_tune pid=1821663)[0m [312]	train-mlogloss:2.00057	validation-mlogloss:1.96158
[36m(train_xgb_ray_tune pid=1821663)[0m [313]	train-mlogloss:1.99979	validation-mlogloss:1.96093
[36m(train_xgb_ray_tune pid=1821663)[0m [314]	train-mlogloss:1.99885	validation-mlogloss:1.96000
[36m(train_xgb_ray_tune pid=1821691)[0m [361]	train-mlogloss:1.95462	validation-mlogloss:1.92042
[36m(train_xgb_ray_tune pid=1821691)[0m [362]	train-mlogloss:1.95451	validation-mlogloss:1.92030
[36m(train_xgb_ray_tune pid=1821691)[0m [363]	train-mlogloss:1.95431	validation-mlogloss:1.92019
[36m(train_xgb_ray_tune pid=1821691)[0m [364]	train-mlogloss:1.95427	validation-mlogloss:1.92016
[36m(train_xgb_ray_tune pid=1821680)[0m [326]	train-mlogloss:1.90273	validation-mlogloss:1.87755
[36m(train_xgb_ray_tune pid=1821680)[0m [327]	train-mlogloss:1.90220	validation-mlogloss:1.87707
[36m(train_xgb_ray_tune pid=1821680)[0m [328]	train-mlogloss:1.90170	validation-mlogloss:1.87672
[36m(train_xgb_ray_tune pid=1821686)[0m [347]	train-mlogloss:2.24866	validation-mlogloss:2.23389
[36m(train_xgb_ray_tune pid=1821686)[0m [348]	train-mlogloss:2.24836	validation-mlogloss:2.23363
[36m(train_xgb_ray_tune pid=1821687)[0m [388]	train-mlogloss:2.03395	validation-mlogloss:2.00287
[36m(train_xgb_ray_tune pid=1821687)[0m [389]	train-mlogloss:2.03362	validation-mlogloss:2.00251
[36m(train_xgb_ray_tune pid=1821687)[0m [390]	train-mlogloss:2.03324	validation-mlogloss:2.00227
[36m(train_xgb_ray_tune pid=1821687)[0m [391]	train-mlogloss:2.03293	validation-mlogloss:2.00212
[36m(train_xgb_ray_tune pid=1821670)[0m [370]	train-mlogloss:1.85994	validation-mlogloss:1.83958
[36m(train_xgb_ray_tune pid=1821670)[0m [371]	train-mlogloss:1.85935	validation-mlogloss:1.83923
[36m(train_xgb_ray_tune pid=1821670)[0m [372]	train-mlogloss:1.85870	validation-mlogloss:1.83877
[36m(train_xgb_ray_tune pid=1821684)[0m [380]	train-mlogloss:2.19245	validation-mlogloss:2.17504
[36m(train_xgb_ray_tune pid=1821684)[0m [381]	train-mlogloss:2.19208	validation-mlogloss:2.17466
[36m(train_xgb_ray_tune pid=1821684)[0m [382]	train-mlogloss:2.19183	validation-mlogloss:2.17447
[36m(train_xgb_ray_tune pid=1821684)[0m [383]	train-mlogloss:2.19152	validation-mlogloss:2.17418
[36m(train_xgb_ray_tune pid=1821674)[0m [347]	train-mlogloss:1.98160	validation-mlogloss:1.93222
[36m(train_xgb_ray_tune pid=1821674)[0m [348]	train-mlogloss:1.98117	validation-mlogloss:1.93188
[36m(train_xgb_ray_tune pid=1821674)[0m [349]	train-mlogloss:1.98077	validation-mlogloss:1.93146
[36m(train_xgb_ray_tune pid=1821683)[0m [379]	train-mlogloss:2.24017	validation-mlogloss:2.23261
[36m(train_xgb_ray_tune pid=1821683)[0m [380]	train-mlogloss:2.23998	validation-mlogloss:2.23252
[36m(train_xgb_ray_tune pid=1821683)[0m [381]	train-mlogloss:2.23980	validation-mlogloss:2.23244
[36m(train_xgb_ray_tune pid=1821683)[0m [382]	train-mlogloss:2.23954	validation-mlogloss:2.23224
[36m(train_xgb_ray_tune pid=1821663)[0m [315]	train-mlogloss:1.99800	validation-mlogloss:1.95929
[36m(train_xgb_ray_tune pid=1821663)[0m [316]	train-mlogloss:1.99714	validation-mlogloss:1.95853
[36m(train_xgb_ray_tune pid=1821663)[0m [317]	train-mlogloss:1.99633	validation-mlogloss:1.95786
[36m(train_xgb_ray_tune pid=1821691)[0m [365]	train-mlogloss:1.95420	validation-mlogloss:1.92011
[36m(train_xgb_ray_tune pid=1821691)[0m [366]	train-mlogloss:1.95405	validation-mlogloss:1.91998
[36m(train_xgb_ray_tune pid=1821691)[0m [367]	train-mlogloss:1.95385	validation-mlogloss:1.91976
[36m(train_xgb_ray_tune pid=1821691)[0m [368]	train-mlogloss:1.95377	validation-mlogloss:1.91971
[36m(train_xgb_ray_tune pid=1821680)[0m [329]	train-mlogloss:1.90132	validation-mlogloss:1.87650
[36m(train_xgb_ray_tune pid=1821680)[0m [330]	train-mlogloss:1.90076	validation-mlogloss:1.87584
[36m(train_xgb_ray_tune pid=1821680)[0m [331]	train-mlogloss:1.90033	validation-mlogloss:1.87559
[36m(train_xgb_ray_tune pid=1821680)[0m [332]	train-mlogloss:1.89998	validation-mlogloss:1.87542
[36m(train_xgb_ray_tune pid=1821686)[0m [349]	train-mlogloss:2.24797	validation-mlogloss:2.23324
[36m(train_xgb_ray_tune pid=1821686)[0m [350]	train-mlogloss:2.24765	validation-mlogloss:2.23295
[36m(train_xgb_ray_tune pid=1821687)[0m [392]	train-mlogloss:2.03251	validation-mlogloss:2.00168
[36m(train_xgb_ray_tune pid=1821687)[0m [393]	train-mlogloss:2.03207	validation-mlogloss:2.00121
[36m(train_xgb_ray_tune pid=1821687)[0m [394]	train-mlogloss:2.03177	validation-mlogloss:2.00100
[36m(train_xgb_ray_tune pid=1821670)[0m [373]	train-mlogloss:1.85804	validation-mlogloss:1.83828
[36m(train_xgb_ray_tune pid=1821670)[0m [374]	train-mlogloss:1.85742	validation-mlogloss:1.83778
[36m(train_xgb_ray_tune pid=1821670)[0m [375]	train-mlogloss:1.85679	validation-mlogloss:1.83740
[36m(train_xgb_ray_tune pid=1821670)[0m [376]	train-mlogloss:1.85621	validation-mlogloss:1.83704
[36m(train_xgb_ray_tune pid=1821684)[0m [384]	train-mlogloss:2.19122	validation-mlogloss:2.17388
[36m(train_xgb_ray_tune pid=1821684)[0m [385]	train-mlogloss:2.19098	validation-mlogloss:2.17364
[36m(train_xgb_ray_tune pid=1821684)[0m [386]	train-mlogloss:2.19065	validation-mlogloss:2.17335
[36m(train_xgb_ray_tune pid=1821684)[0m [387]	train-mlogloss:2.19020	validation-mlogloss:2.17282
[36m(train_xgb_ray_tune pid=1821674)[0m [350]	train-mlogloss:1.98048	validation-mlogloss:1.93128
[36m(train_xgb_ray_tune pid=1821674)[0m [351]	train-mlogloss:1.98020	validation-mlogloss:1.93105
[36m(train_xgb_ray_tune pid=1821674)[0m [352]	train-mlogloss:1.97998	validation-mlogloss:1.93089
[36m(train_xgb_ray_tune pid=1821674)[0m [353]	train-mlogloss:1.97954	validation-mlogloss:1.93058
[36m(train_xgb_ray_tune pid=1821683)[0m [383]	train-mlogloss:2.23923	validation-mlogloss:2.23188
[36m(train_xgb_ray_tune pid=1821683)[0m [384]	train-mlogloss:2.23900	validation-mlogloss:2.23164
[36m(train_xgb_ray_tune pid=1821683)[0m [385]	train-mlogloss:2.23873	validation-mlogloss:2.23141
[36m(train_xgb_ray_tune pid=1821686)[0m [351]	train-mlogloss:2.24733	validation-mlogloss:2.23270
[36m(train_xgb_ray_tune pid=1821683)[0m [386]	train-mlogloss:2.23849	validation-mlogloss:2.23124
[36m(train_xgb_ray_tune pid=1821691)[0m [369]	train-mlogloss:1.95358	validation-mlogloss:1.91961
[36m(train_xgb_ray_tune pid=1821687)[0m [395]	train-mlogloss:2.03142	validation-mlogloss:2.00078

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:03. Total running time: 34s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             31.0931 │
│ time_total_s                 31.0931 │
│ training_iteration                 1 │
│ validation_accuracy          0.47012 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:03. Total running time: 34s
[36m(train_xgb_ray_tune pid=1821663)[0m [318]	train-mlogloss:1.99550	validation-mlogloss:1.95710
[36m(train_xgb_ray_tune pid=1821663)[0m [319]	train-mlogloss:1.99458	validation-mlogloss:1.95630
[36m(train_xgb_ray_tune pid=1821691)[0m [370]	train-mlogloss:1.95333	validation-mlogloss:1.91935
[36m(train_xgb_ray_tune pid=1821691)[0m [371]	train-mlogloss:1.95303	validation-mlogloss:1.91905
[36m(train_xgb_ray_tune pid=1821691)[0m [372]	train-mlogloss:1.95286	validation-mlogloss:1.91894
[36m(train_xgb_ray_tune pid=1821680)[0m [333]	train-mlogloss:1.89936	validation-mlogloss:1.87501
[36m(train_xgb_ray_tune pid=1821680)[0m [334]	train-mlogloss:1.89892	validation-mlogloss:1.87470
[36m(train_xgb_ray_tune pid=1821680)[0m [335]	train-mlogloss:1.89839	validation-mlogloss:1.87438
[36m(train_xgb_ray_tune pid=1821686)[0m [352]	train-mlogloss:2.24696	validation-mlogloss:2.23240
[36m(train_xgb_ray_tune pid=1821686)[0m [353]	train-mlogloss:2.24664	validation-mlogloss:2.23209
[36m(train_xgb_ray_tune pid=1821687)[0m [396]	train-mlogloss:2.03102	validation-mlogloss:2.00049
[36m(train_xgb_ray_tune pid=1821687)[0m [397]	train-mlogloss:2.03063	validation-mlogloss:2.00012
[36m(train_xgb_ray_tune pid=1821687)[0m [398]	train-mlogloss:2.03020	validation-mlogloss:1.99968
[36m(train_xgb_ray_tune pid=1821670)[0m [377]	train-mlogloss:1.85559	validation-mlogloss:1.83667
[36m(train_xgb_ray_tune pid=1821670)[0m [378]	train-mlogloss:1.85494	validation-mlogloss:1.83617
[36m(train_xgb_ray_tune pid=1821670)[0m [379]	train-mlogloss:1.85434	validation-mlogloss:1.83568
[36m(train_xgb_ray_tune pid=1821684)[0m [388]	train-mlogloss:2.18996	validation-mlogloss:2.17261
[36m(train_xgb_ray_tune pid=1821684)[0m [389]	train-mlogloss:2.18965	validation-mlogloss:2.17231
[36m(train_xgb_ray_tune pid=1821684)[0m [390]	train-mlogloss:2.18945	validation-mlogloss:2.17215
[36m(train_xgb_ray_tune pid=1821684)[0m [391]	train-mlogloss:2.18920	validation-mlogloss:2.17188
[36m(train_xgb_ray_tune pid=1821674)[0m [354]	train-mlogloss:1.97920	validation-mlogloss:1.93036
[36m(train_xgb_ray_tune pid=1821674)[0m [355]	train-mlogloss:1.97868	validation-mlogloss:1.93010
[36m(train_xgb_ray_tune pid=1821674)[0m [356]	train-mlogloss:1.97829	validation-mlogloss:1.92976
[36m(train_xgb_ray_tune pid=1821674)[0m [357]	train-mlogloss:1.97787	validation-mlogloss:1.92940
[36m(train_xgb_ray_tune pid=1821683)[0m [387]	train-mlogloss:2.23828	validation-mlogloss:2.23112
[36m(train_xgb_ray_tune pid=1821683)[0m [388]	train-mlogloss:2.23796	validation-mlogloss:2.23086
[36m(train_xgb_ray_tune pid=1821683)[0m [389]	train-mlogloss:2.23774	validation-mlogloss:2.23073
[36m(train_xgb_ray_tune pid=1821691)[0m [373]	train-mlogloss:1.95267	validation-mlogloss:1.91879
[36m(train_xgb_ray_tune pid=1821683)[0m [390]	train-mlogloss:2.23753	validation-mlogloss:2.23052
[36m(train_xgb_ray_tune pid=1821663)[0m [320]	train-mlogloss:1.99375	validation-mlogloss:1.95554
[36m(train_xgb_ray_tune pid=1821686)[0m [354]	train-mlogloss:2.24634	validation-mlogloss:2.23178
[36m(train_xgb_ray_tune pid=1821687)[0m [399]	train-mlogloss:2.02988	validation-mlogloss:1.99950
[36m(train_xgb_ray_tune pid=1821680)[0m [336]	train-mlogloss:1.89794	validation-mlogloss:1.87402
[36m(train_xgb_ray_tune pid=1821670)[0m [380]	train-mlogloss:1.85372	validation-mlogloss:1.83525
[36m(train_xgb_ray_tune pid=1821663)[0m [321]	train-mlogloss:1.99296	validation-mlogloss:1.95480
[36m(train_xgb_ray_tune pid=1821663)[0m [322]	train-mlogloss:1.99206	validation-mlogloss:1.95388
[36m(train_xgb_ray_tune pid=1821691)[0m [374]	train-mlogloss:1.95256	validation-mlogloss:1.91876
[36m(train_xgb_ray_tune pid=1821691)[0m [375]	train-mlogloss:1.95241	validation-mlogloss:1.91865
[36m(train_xgb_ray_tune pid=1821691)[0m [376]	train-mlogloss:1.95238	validation-mlogloss:1.91863
[36m(train_xgb_ray_tune pid=1821691)[0m [377]	train-mlogloss:1.95227	validation-mlogloss:1.91862
[36m(train_xgb_ray_tune pid=1821680)[0m [337]	train-mlogloss:1.89740	validation-mlogloss:1.87366
[36m(train_xgb_ray_tune pid=1821680)[0m [338]	train-mlogloss:1.89693	validation-mlogloss:1.87335
[36m(train_xgb_ray_tune pid=1821680)[0m [339]	train-mlogloss:1.89649	validation-mlogloss:1.87307
[36m(train_xgb_ray_tune pid=1821686)[0m [355]	train-mlogloss:2.24600	validation-mlogloss:2.23146
[36m(train_xgb_ray_tune pid=1821686)[0m [356]	train-mlogloss:2.24567	validation-mlogloss:2.23116
[36m(train_xgb_ray_tune pid=1821687)[0m [400]	train-mlogloss:2.02958	validation-mlogloss:1.99919
[36m(train_xgb_ray_tune pid=1821687)[0m [401]	train-mlogloss:2.02922	validation-mlogloss:1.99882
[36m(train_xgb_ray_tune pid=1821687)[0m [402]	train-mlogloss:2.02896	validation-mlogloss:1.99856
[36m(train_xgb_ray_tune pid=1821670)[0m [381]	train-mlogloss:1.85308	validation-mlogloss:1.83480
[36m(train_xgb_ray_tune pid=1821670)[0m [382]	train-mlogloss:1.85254	validation-mlogloss:1.83438
[36m(train_xgb_ray_tune pid=1821670)[0m [383]	train-mlogloss:1.85199	validation-mlogloss:1.83407
[36m(train_xgb_ray_tune pid=1821684)[0m [392]	train-mlogloss:2.18896	validation-mlogloss:2.17165
[36m(train_xgb_ray_tune pid=1821684)[0m [393]	train-mlogloss:2.18868	validation-mlogloss:2.17141
[36m(train_xgb_ray_tune pid=1821684)[0m [394]	train-mlogloss:2.18847	validation-mlogloss:2.17124
[36m(train_xgb_ray_tune pid=1821684)[0m [395]	train-mlogloss:2.18827	validation-mlogloss:2.17112
[36m(train_xgb_ray_tune pid=1821674)[0m [358]	train-mlogloss:1.97746	validation-mlogloss:1.92892
[36m(train_xgb_ray_tune pid=1821674)[0m [359]	train-mlogloss:1.97704	validation-mlogloss:1.92857
[36m(train_xgb_ray_tune pid=1821674)[0m [360]	train-mlogloss:1.97670	validation-mlogloss:1.92829
[36m(train_xgb_ray_tune pid=1821674)[0m [361]	train-mlogloss:1.97629	validation-mlogloss:1.92793
[36m(train_xgb_ray_tune pid=1821683)[0m [391]	train-mlogloss:2.23708	validation-mlogloss:2.23006
[36m(train_xgb_ray_tune pid=1821683)[0m [392]	train-mlogloss:2.23682	validation-mlogloss:2.22981
[36m(train_xgb_ray_tune pid=1821683)[0m [393]	train-mlogloss:2.23659	validation-mlogloss:2.22960
[36m(train_xgb_ray_tune pid=1821683)[0m [394]	train-mlogloss:2.23636	validation-mlogloss:2.22940
[36m(train_xgb_ray_tune pid=1821687)[0m [403]	train-mlogloss:2.02862	validation-mlogloss:1.99835
[36m(train_xgb_ray_tune pid=1821663)[0m [323]	train-mlogloss:1.99124	validation-mlogloss:1.95330
[36m(train_xgb_ray_tune pid=1821691)[0m [378]	train-mlogloss:1.95213	validation-mlogloss:1.91853
[36m(train_xgb_ray_tune pid=1821686)[0m [357]	train-mlogloss:2.24544	validation-mlogloss:2.23096
[36m(train_xgb_ray_tune pid=1821684)[0m [396]	train-mlogloss:2.18804	validation-mlogloss:2.17091

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:04. Total running time: 34s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             31.5358 │
│ time_total_s                 31.5358 │
│ training_iteration                 1 │
│ validation_accuracy          0.30792 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:04. Total running time: 34s
[36m(train_xgb_ray_tune pid=1821663)[0m [324]	train-mlogloss:1.99037	validation-mlogloss:1.95247
[36m(train_xgb_ray_tune pid=1821663)[0m [325]	train-mlogloss:1.98959	validation-mlogloss:1.95163
[36m(train_xgb_ray_tune pid=1821691)[0m [379]	train-mlogloss:1.95197	validation-mlogloss:1.91847
[36m(train_xgb_ray_tune pid=1821691)[0m [380]	train-mlogloss:1.95179	validation-mlogloss:1.91836
[36m(train_xgb_ray_tune pid=1821691)[0m [381]	train-mlogloss:1.95156	validation-mlogloss:1.91807
[36m(train_xgb_ray_tune pid=1821680)[0m [340]	train-mlogloss:1.89605	validation-mlogloss:1.87270
[36m(train_xgb_ray_tune pid=1821680)[0m [341]	train-mlogloss:1.89564	validation-mlogloss:1.87250
[36m(train_xgb_ray_tune pid=1821680)[0m [342]	train-mlogloss:1.89509	validation-mlogloss:1.87197
[36m(train_xgb_ray_tune pid=1821686)[0m [358]	train-mlogloss:2.24504	validation-mlogloss:2.23058
[36m(train_xgb_ray_tune pid=1821686)[0m [359]	train-mlogloss:2.24475	validation-mlogloss:2.23030
[36m(train_xgb_ray_tune pid=1821687)[0m [404]	train-mlogloss:2.02819	validation-mlogloss:1.99790
[36m(train_xgb_ray_tune pid=1821687)[0m [405]	train-mlogloss:2.02779	validation-mlogloss:1.99759
[36m(train_xgb_ray_tune pid=1821687)[0m [406]	train-mlogloss:2.02753	validation-mlogloss:1.99737
[36m(train_xgb_ray_tune pid=1821670)[0m [384]	train-mlogloss:1.85132	validation-mlogloss:1.83346
[36m(train_xgb_ray_tune pid=1821670)[0m [385]	train-mlogloss:1.85072	validation-mlogloss:1.83307
[36m(train_xgb_ray_tune pid=1821670)[0m [386]	train-mlogloss:1.85014	validation-mlogloss:1.83272
[36m(train_xgb_ray_tune pid=1821684)[0m [397]	train-mlogloss:2.18779	validation-mlogloss:2.17070
[36m(train_xgb_ray_tune pid=1821684)[0m [398]	train-mlogloss:2.18757	validation-mlogloss:2.17048
[36m(train_xgb_ray_tune pid=1821684)[0m [399]	train-mlogloss:2.18722	validation-mlogloss:2.17009
[36m(train_xgb_ray_tune pid=1821674)[0m [362]	train-mlogloss:1.97599	validation-mlogloss:1.92769
[36m(train_xgb_ray_tune pid=1821674)[0m [363]	train-mlogloss:1.97568	validation-mlogloss:1.92754
[36m(train_xgb_ray_tune pid=1821674)[0m [364]	train-mlogloss:1.97522	validation-mlogloss:1.92727
[36m(train_xgb_ray_tune pid=1821674)[0m [365]	train-mlogloss:1.97485	validation-mlogloss:1.92703
[36m(train_xgb_ray_tune pid=1821683)[0m [395]	train-mlogloss:2.23611	validation-mlogloss:2.22925
[36m(train_xgb_ray_tune pid=1821683)[0m [396]	train-mlogloss:2.23593	validation-mlogloss:2.22909
[36m(train_xgb_ray_tune pid=1821683)[0m [397]	train-mlogloss:2.23571	validation-mlogloss:2.22890
[36m(train_xgb_ray_tune pid=1821683)[0m [398]	train-mlogloss:2.23545	validation-mlogloss:2.22866
[36m(train_xgb_ray_tune pid=1821663)[0m [326]	train-mlogloss:1.98876	validation-mlogloss:1.95095
[36m(train_xgb_ray_tune pid=1821691)[0m [382]	train-mlogloss:1.95134	validation-mlogloss:1.91786
[36m(train_xgb_ray_tune pid=1821680)[0m [343]	train-mlogloss:1.89476	validation-mlogloss:1.87185
[36m(train_xgb_ray_tune pid=1821686)[0m [360]	train-mlogloss:2.24441	validation-mlogloss:2.22999
[36m(train_xgb_ray_tune pid=1821687)[0m [407]	train-mlogloss:2.02711	validation-mlogloss:1.99715
[36m(train_xgb_ray_tune pid=1821684)[0m [400]	train-mlogloss:2.18706	validation-mlogloss:2.16997
[36m(train_xgb_ray_tune pid=1821683)[0m [399]	train-mlogloss:2.23519	validation-mlogloss:2.22847
[36m(train_xgb_ray_tune pid=1821663)[0m [327]	train-mlogloss:1.98801	validation-mlogloss:1.95032
[36m(train_xgb_ray_tune pid=1821663)[0m [328]	train-mlogloss:1.98719	validation-mlogloss:1.94958
[36m(train_xgb_ray_tune pid=1821663)[0m [329]	train-mlogloss:1.98638	validation-mlogloss:1.94889
[36m(train_xgb_ray_tune pid=1821691)[0m [383]	train-mlogloss:1.95124	validation-mlogloss:1.91777
[36m(train_xgb_ray_tune pid=1821691)[0m [384]	train-mlogloss:1.95105	validation-mlogloss:1.91762
[36m(train_xgb_ray_tune pid=1821691)[0m [385]	train-mlogloss:1.95098	validation-mlogloss:1.91753
[36m(train_xgb_ray_tune pid=1821691)[0m [386]	train-mlogloss:1.95090	validation-mlogloss:1.91752
[36m(train_xgb_ray_tune pid=1821680)[0m [344]	train-mlogloss:1.89445	validation-mlogloss:1.87156
[36m(train_xgb_ray_tune pid=1821680)[0m [345]	train-mlogloss:1.89408	validation-mlogloss:1.87119
[36m(train_xgb_ray_tune pid=1821680)[0m [346]	train-mlogloss:1.89369	validation-mlogloss:1.87087
[36m(train_xgb_ray_tune pid=1821686)[0m [361]	train-mlogloss:2.24412	validation-mlogloss:2.22972
[36m(train_xgb_ray_tune pid=1821686)[0m [362]	train-mlogloss:2.24368	validation-mlogloss:2.22928
[36m(train_xgb_ray_tune pid=1821686)[0m [363]	train-mlogloss:2.24332	validation-mlogloss:2.22895
[36m(train_xgb_ray_tune pid=1821687)[0m [408]	train-mlogloss:2.02677	validation-mlogloss:1.99687
[36m(train_xgb_ray_tune pid=1821687)[0m [409]	train-mlogloss:2.02635	validation-mlogloss:1.99653
[36m(train_xgb_ray_tune pid=1821687)[0m [410]	train-mlogloss:2.02606	validation-mlogloss:1.99626
[36m(train_xgb_ray_tune pid=1821670)[0m [387]	train-mlogloss:1.84952	validation-mlogloss:1.83222
[36m(train_xgb_ray_tune pid=1821670)[0m [388]	train-mlogloss:1.84891	validation-mlogloss:1.83189
[36m(train_xgb_ray_tune pid=1821670)[0m [389]	train-mlogloss:1.84825	validation-mlogloss:1.83145
[36m(train_xgb_ray_tune pid=1821684)[0m [401]	train-mlogloss:2.18684	validation-mlogloss:2.16984
[36m(train_xgb_ray_tune pid=1821684)[0m [402]	train-mlogloss:2.18648	validation-mlogloss:2.16947
[36m(train_xgb_ray_tune pid=1821684)[0m [403]	train-mlogloss:2.18627	validation-mlogloss:2.16935
[36m(train_xgb_ray_tune pid=1821674)[0m [366]	train-mlogloss:1.97461	validation-mlogloss:1.92682
[36m(train_xgb_ray_tune pid=1821674)[0m [367]	train-mlogloss:1.97420	validation-mlogloss:1.92654
[36m(train_xgb_ray_tune pid=1821674)[0m [368]	train-mlogloss:1.97393	validation-mlogloss:1.92637
[36m(train_xgb_ray_tune pid=1821674)[0m [369]	train-mlogloss:1.97367	validation-mlogloss:1.92620
[36m(train_xgb_ray_tune pid=1821683)[0m [400]	train-mlogloss:2.23497	validation-mlogloss:2.22833
[36m(train_xgb_ray_tune pid=1821683)[0m [401]	train-mlogloss:2.23470	validation-mlogloss:2.22806
[36m(train_xgb_ray_tune pid=1821683)[0m [402]	train-mlogloss:2.23444	validation-mlogloss:2.22783
[36m(train_xgb_ray_tune pid=1821663)[0m [330]	train-mlogloss:1.98564	validation-mlogloss:1.94824
[36m(train_xgb_ray_tune pid=1821663)[0m [331]	train-mlogloss:1.98484	validation-mlogloss:1.94753
[36m(train_xgb_ray_tune pid=1821663)[0m [332]	train-mlogloss:1.98416	validation-mlogloss:1.94682
[36m(train_xgb_ray_tune pid=1821691)[0m [387]	train-mlogloss:1.95086	validation-mlogloss:1.91755
[36m(train_xgb_ray_tune pid=1821691)[0m [388]	train-mlogloss:1.95069	validation-mlogloss:1.91737
[36m(train_xgb_ray_tune pid=1821691)[0m [389]	train-mlogloss:1.95057	validation-mlogloss:1.91733
[36m(train_xgb_ray_tune pid=1821691)[0m [390]	train-mlogloss:1.95046	validation-mlogloss:1.91719
[36m(train_xgb_ray_tune pid=1821680)[0m [347]	train-mlogloss:1.89312	validation-mlogloss:1.87045
[36m(train_xgb_ray_tune pid=1821680)[0m [348]	train-mlogloss:1.89267	validation-mlogloss:1.87015
[36m(train_xgb_ray_tune pid=1821680)[0m [349]	train-mlogloss:1.89223	validation-mlogloss:1.86987
[36m(train_xgb_ray_tune pid=1821680)[0m [350]	train-mlogloss:1.89191	validation-mlogloss:1.86959
[36m(train_xgb_ray_tune pid=1821686)[0m [364]	train-mlogloss:2.24307	validation-mlogloss:2.22870
[36m(train_xgb_ray_tune pid=1821686)[0m [365]	train-mlogloss:2.24271	validation-mlogloss:2.22837
[36m(train_xgb_ray_tune pid=1821686)[0m [366]	train-mlogloss:2.24226	validation-mlogloss:2.22794
[36m(train_xgb_ray_tune pid=1821686)[0m [367]	train-mlogloss:2.24190	validation-mlogloss:2.22759
[36m(train_xgb_ray_tune pid=1821687)[0m [411]	train-mlogloss:2.02578	validation-mlogloss:1.99604
[36m(train_xgb_ray_tune pid=1821687)[0m [412]	train-mlogloss:2.02550	validation-mlogloss:1.99583
[36m(train_xgb_ray_tune pid=1821687)[0m [413]	train-mlogloss:2.02526	validation-mlogloss:1.99559
[36m(train_xgb_ray_tune pid=1821687)[0m [414]	train-mlogloss:2.02497	validation-mlogloss:1.99540
[36m(train_xgb_ray_tune pid=1821670)[0m [390]	train-mlogloss:1.84775	validation-mlogloss:1.83120
[36m(train_xgb_ray_tune pid=1821670)[0m [391]	train-mlogloss:1.84717	validation-mlogloss:1.83076
[36m(train_xgb_ray_tune pid=1821670)[0m [392]	train-mlogloss:1.84665	validation-mlogloss:1.83045
[36m(train_xgb_ray_tune pid=1821670)[0m [393]	train-mlogloss:1.84605	validation-mlogloss:1.83008
[36m(train_xgb_ray_tune pid=1821684)[0m [404]	train-mlogloss:2.18598	validation-mlogloss:2.16912
[36m(train_xgb_ray_tune pid=1821684)[0m [405]	train-mlogloss:2.18577	validation-mlogloss:2.16895
[36m(train_xgb_ray_tune pid=1821684)[0m [406]	train-mlogloss:2.18548	validation-mlogloss:2.16873
[36m(train_xgb_ray_tune pid=1821674)[0m [370]	train-mlogloss:1.97330	validation-mlogloss:1.92582
[36m(train_xgb_ray_tune pid=1821674)[0m [371]	train-mlogloss:1.97302	validation-mlogloss:1.92554
[36m(train_xgb_ray_tune pid=1821674)[0m [372]	train-mlogloss:1.97271	validation-mlogloss:1.92532
[36m(train_xgb_ray_tune pid=1821683)[0m [403]	train-mlogloss:2.23419	validation-mlogloss:2.22758
[36m(train_xgb_ray_tune pid=1821683)[0m [404]	train-mlogloss:2.23402	validation-mlogloss:2.22743
[36m(train_xgb_ray_tune pid=1821683)[0m [405]	train-mlogloss:2.23380	validation-mlogloss:2.22724
[36m(train_xgb_ray_tune pid=1821683)[0m [406]	train-mlogloss:2.23359	validation-mlogloss:2.22711
[36m(train_xgb_ray_tune pid=1821663)[0m [333]	train-mlogloss:1.98327	validation-mlogloss:1.94598
[36m(train_xgb_ray_tune pid=1821663)[0m [334]	train-mlogloss:1.98260	validation-mlogloss:1.94529
[36m(train_xgb_ray_tune pid=1821663)[0m [335]	train-mlogloss:1.98181	validation-mlogloss:1.94461
[36m(train_xgb_ray_tune pid=1821691)[0m [391]	train-mlogloss:1.95039	validation-mlogloss:1.91716
[36m(train_xgb_ray_tune pid=1821691)[0m [392]	train-mlogloss:1.95029	validation-mlogloss:1.91709
[36m(train_xgb_ray_tune pid=1821691)[0m [393]	train-mlogloss:1.95022	validation-mlogloss:1.91703
[36m(train_xgb_ray_tune pid=1821691)[0m [394]	train-mlogloss:1.94991	validation-mlogloss:1.91677
[36m(train_xgb_ray_tune pid=1821680)[0m [351]	train-mlogloss:1.89148	validation-mlogloss:1.86927
[36m(train_xgb_ray_tune pid=1821680)[0m [352]	train-mlogloss:1.89121	validation-mlogloss:1.86906
[36m(train_xgb_ray_tune pid=1821680)[0m [353]	train-mlogloss:1.89085	validation-mlogloss:1.86882
[36m(train_xgb_ray_tune pid=1821686)[0m [368]	train-mlogloss:2.24150	validation-mlogloss:2.22716
[36m(train_xgb_ray_tune pid=1821686)[0m [369]	train-mlogloss:2.24121	validation-mlogloss:2.22687
[36m(train_xgb_ray_tune pid=1821686)[0m [370]	train-mlogloss:2.24084	validation-mlogloss:2.22649
[36m(train_xgb_ray_tune pid=1821686)[0m [371]	train-mlogloss:2.24052	validation-mlogloss:2.22619
[36m(train_xgb_ray_tune pid=1821687)[0m [415]	train-mlogloss:2.02480	validation-mlogloss:1.99532
[36m(train_xgb_ray_tune pid=1821687)[0m [416]	train-mlogloss:2.02458	validation-mlogloss:1.99511
[36m(train_xgb_ray_tune pid=1821687)[0m [417]	train-mlogloss:2.02426	validation-mlogloss:1.99484
[36m(train_xgb_ray_tune pid=1821687)[0m [418]	train-mlogloss:2.02394	validation-mlogloss:1.99458
[36m(train_xgb_ray_tune pid=1821670)[0m [394]	train-mlogloss:1.84550	validation-mlogloss:1.82980
[36m(train_xgb_ray_tune pid=1821670)[0m [395]	train-mlogloss:1.84488	validation-mlogloss:1.82934
[36m(train_xgb_ray_tune pid=1821670)[0m [396]	train-mlogloss:1.84426	validation-mlogloss:1.82875
[36m(train_xgb_ray_tune pid=1821674)[0m [373]	train-mlogloss:1.97243	validation-mlogloss:1.92498
[36m(train_xgb_ray_tune pid=1821674)[0m [374]	train-mlogloss:1.97190	validation-mlogloss:1.92455
[36m(train_xgb_ray_tune pid=1821674)[0m [375]	train-mlogloss:1.97156	validation-mlogloss:1.92426
[36m(train_xgb_ray_tune pid=1821674)[0m [376]	train-mlogloss:1.97126	validation-mlogloss:1.92397
[36m(train_xgb_ray_tune pid=1821683)[0m [407]	train-mlogloss:2.23337	validation-mlogloss:2.22690
[36m(train_xgb_ray_tune pid=1821683)[0m [408]	train-mlogloss:2.23316	validation-mlogloss:2.22674
[36m(train_xgb_ray_tune pid=1821683)[0m [409]	train-mlogloss:2.23295	validation-mlogloss:2.22664
[36m(train_xgb_ray_tune pid=1821683)[0m [410]	train-mlogloss:2.23273	validation-mlogloss:2.22648
[36m(train_xgb_ray_tune pid=1821683)[0m [411]	train-mlogloss:2.23257	validation-mlogloss:2.22634
[36m(train_xgb_ray_tune pid=1821691)[0m [395]	train-mlogloss:1.94968	validation-mlogloss:1.91668
[36m(train_xgb_ray_tune pid=1821663)[0m [336]	train-mlogloss:1.98107	validation-mlogloss:1.94405
[36m(train_xgb_ray_tune pid=1821663)[0m [337]	train-mlogloss:1.98029	validation-mlogloss:1.94329
[36m(train_xgb_ray_tune pid=1821663)[0m [338]	train-mlogloss:1.97948	validation-mlogloss:1.94260
[36m(train_xgb_ray_tune pid=1821691)[0m [396]	train-mlogloss:1.94941	validation-mlogloss:1.91643
[36m(train_xgb_ray_tune pid=1821691)[0m [397]	train-mlogloss:1.94934	validation-mlogloss:1.91635
[36m(train_xgb_ray_tune pid=1821691)[0m [398]	train-mlogloss:1.94920	validation-mlogloss:1.91626
[36m(train_xgb_ray_tune pid=1821691)[0m [399]	train-mlogloss:1.94920	validation-mlogloss:1.91626
[36m(train_xgb_ray_tune pid=1821680)[0m [354]	train-mlogloss:1.89037	validation-mlogloss:1.86846
[36m(train_xgb_ray_tune pid=1821680)[0m [355]	train-mlogloss:1.89000	validation-mlogloss:1.86818
[36m(train_xgb_ray_tune pid=1821680)[0m [356]	train-mlogloss:1.88964	validation-mlogloss:1.86790
[36m(train_xgb_ray_tune pid=1821680)[0m [357]	train-mlogloss:1.88916	validation-mlogloss:1.86755
[36m(train_xgb_ray_tune pid=1821686)[0m [372]	train-mlogloss:2.24023	validation-mlogloss:2.22587
[36m(train_xgb_ray_tune pid=1821686)[0m [373]	train-mlogloss:2.23998	validation-mlogloss:2.22565
[36m(train_xgb_ray_tune pid=1821686)[0m [374]	train-mlogloss:2.23969	validation-mlogloss:2.22538
[36m(train_xgb_ray_tune pid=1821686)[0m [375]	train-mlogloss:2.23941	validation-mlogloss:2.22509
[36m(train_xgb_ray_tune pid=1821687)[0m [419]	train-mlogloss:2.02362	validation-mlogloss:1.99423
[36m(train_xgb_ray_tune pid=1821687)[0m [420]	train-mlogloss:2.02324	validation-mlogloss:1.99387
[36m(train_xgb_ray_tune pid=1821687)[0m [421]	train-mlogloss:2.02294	validation-mlogloss:1.99359
[36m(train_xgb_ray_tune pid=1821687)[0m [422]	train-mlogloss:2.02258	validation-mlogloss:1.99334
[36m(train_xgb_ray_tune pid=1821670)[0m [397]	train-mlogloss:1.84365	validation-mlogloss:1.82825
[36m(train_xgb_ray_tune pid=1821670)[0m [398]	train-mlogloss:1.84312	validation-mlogloss:1.82793
[36m(train_xgb_ray_tune pid=1821670)[0m [399]	train-mlogloss:1.84260	validation-mlogloss:1.82763
[36m(train_xgb_ray_tune pid=1821670)[0m [400]	train-mlogloss:1.84210	validation-mlogloss:1.82713
[36m(train_xgb_ray_tune pid=1821674)[0m [377]	train-mlogloss:1.97094	validation-mlogloss:1.92380
[36m(train_xgb_ray_tune pid=1821674)[0m [378]	train-mlogloss:1.97075	validation-mlogloss:1.92366
[36m(train_xgb_ray_tune pid=1821674)[0m [379]	train-mlogloss:1.97047	validation-mlogloss:1.92336
[36m(train_xgb_ray_tune pid=1821674)[0m [380]	train-mlogloss:1.97016	validation-mlogloss:1.92312
[36m(train_xgb_ray_tune pid=1821683)[0m [412]	train-mlogloss:2.23235	validation-mlogloss:2.22613
[36m(train_xgb_ray_tune pid=1821683)[0m [413]	train-mlogloss:2.23219	validation-mlogloss:2.22595
[36m(train_xgb_ray_tune pid=1821683)[0m [414]	train-mlogloss:2.23198	validation-mlogloss:2.22575
[36m(train_xgb_ray_tune pid=1821683)[0m [415]	train-mlogloss:2.23182	validation-mlogloss:2.22562
[36m(train_xgb_ray_tune pid=1821686)[0m [376]	train-mlogloss:2.23914	validation-mlogloss:2.22486
[36m(train_xgb_ray_tune pid=1821663)[0m [339]	train-mlogloss:1.97871	validation-mlogloss:1.94190
[36m(train_xgb_ray_tune pid=1821663)[0m [340]	train-mlogloss:1.97802	validation-mlogloss:1.94129
[36m(train_xgb_ray_tune pid=1821663)[0m [341]	train-mlogloss:1.97720	validation-mlogloss:1.94059
[36m(train_xgb_ray_tune pid=1821691)[0m [400]	train-mlogloss:1.94902	validation-mlogloss:1.91607
[36m(train_xgb_ray_tune pid=1821691)[0m [401]	train-mlogloss:1.94869	validation-mlogloss:1.91584
[36m(train_xgb_ray_tune pid=1821691)[0m [402]	train-mlogloss:1.94856	validation-mlogloss:1.91573
[36m(train_xgb_ray_tune pid=1821691)[0m [403]	train-mlogloss:1.94835	validation-mlogloss:1.91553
[36m(train_xgb_ray_tune pid=1821680)[0m [358]	train-mlogloss:1.88881	validation-mlogloss:1.86724
[36m(train_xgb_ray_tune pid=1821680)[0m [359]	train-mlogloss:1.88846	validation-mlogloss:1.86701
[36m(train_xgb_ray_tune pid=1821680)[0m [360]	train-mlogloss:1.88811	validation-mlogloss:1.86681
[36m(train_xgb_ray_tune pid=1821680)[0m [361]	train-mlogloss:1.88778	validation-mlogloss:1.86669
[36m(train_xgb_ray_tune pid=1821686)[0m [377]	train-mlogloss:2.23886	validation-mlogloss:2.22461
[36m(train_xgb_ray_tune pid=1821686)[0m [378]	train-mlogloss:2.23857	validation-mlogloss:2.22437
[36m(train_xgb_ray_tune pid=1821686)[0m [379]	train-mlogloss:2.23832	validation-mlogloss:2.22414
[36m(train_xgb_ray_tune pid=1821686)[0m [380]	train-mlogloss:2.23805	validation-mlogloss:2.22387
[36m(train_xgb_ray_tune pid=1821687)[0m [423]	train-mlogloss:2.02226	validation-mlogloss:1.99312
[36m(train_xgb_ray_tune pid=1821687)[0m [424]	train-mlogloss:2.02194	validation-mlogloss:1.99280
[36m(train_xgb_ray_tune pid=1821687)[0m [425]	train-mlogloss:2.02171	validation-mlogloss:1.99252
[36m(train_xgb_ray_tune pid=1821687)[0m [426]	train-mlogloss:2.02147	validation-mlogloss:1.99229
[36m(train_xgb_ray_tune pid=1821670)[0m [401]	train-mlogloss:1.84157	validation-mlogloss:1.82683
[36m(train_xgb_ray_tune pid=1821670)[0m [402]	train-mlogloss:1.84104	validation-mlogloss:1.82639
[36m(train_xgb_ray_tune pid=1821670)[0m [403]	train-mlogloss:1.84054	validation-mlogloss:1.82611
[36m(train_xgb_ray_tune pid=1821670)[0m [404]	train-mlogloss:1.83997	validation-mlogloss:1.82573
[36m(train_xgb_ray_tune pid=1821674)[0m [381]	train-mlogloss:1.96990	validation-mlogloss:1.92292
[36m(train_xgb_ray_tune pid=1821674)[0m [382]	train-mlogloss:1.96958	validation-mlogloss:1.92272
[36m(train_xgb_ray_tune pid=1821674)[0m [383]	train-mlogloss:1.96916	validation-mlogloss:1.92249
[36m(train_xgb_ray_tune pid=1821674)[0m [384]	train-mlogloss:1.96878	validation-mlogloss:1.92230
[36m(train_xgb_ray_tune pid=1821683)[0m [416]	train-mlogloss:2.23162	validation-mlogloss:2.22542
[36m(train_xgb_ray_tune pid=1821683)[0m [417]	train-mlogloss:2.23150	validation-mlogloss:2.22533
[36m(train_xgb_ray_tune pid=1821683)[0m [418]	train-mlogloss:2.23128	validation-mlogloss:2.22512
[36m(train_xgb_ray_tune pid=1821683)[0m [419]	train-mlogloss:2.23112	validation-mlogloss:2.22497
[36m(train_xgb_ray_tune pid=1821683)[0m [420]	train-mlogloss:2.23088	validation-mlogloss:2.22477

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:04. Total running time: 35s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             31.9777 │
│ time_total_s                 31.9777 │
│ training_iteration                 1 │
│ validation_accuracy          0.37522 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:04. Total running time: 35s
[36m(train_xgb_ray_tune pid=1821663)[0m [342]	train-mlogloss:1.97638	validation-mlogloss:1.93970
[36m(train_xgb_ray_tune pid=1821663)[0m [343]	train-mlogloss:1.97563	validation-mlogloss:1.93903
[36m(train_xgb_ray_tune pid=1821663)[0m [344]	train-mlogloss:1.97480	validation-mlogloss:1.93822
[36m(train_xgb_ray_tune pid=1821691)[0m [404]	train-mlogloss:1.94820	validation-mlogloss:1.91544
[36m(train_xgb_ray_tune pid=1821691)[0m [405]	train-mlogloss:1.94810	validation-mlogloss:1.91535
[36m(train_xgb_ray_tune pid=1821691)[0m [406]	train-mlogloss:1.94799	validation-mlogloss:1.91535
[36m(train_xgb_ray_tune pid=1821691)[0m [407]	train-mlogloss:1.94789	validation-mlogloss:1.91521
[36m(train_xgb_ray_tune pid=1821691)[0m [408]	train-mlogloss:1.94775	validation-mlogloss:1.91507
[36m(train_xgb_ray_tune pid=1821680)[0m [362]	train-mlogloss:1.88740	validation-mlogloss:1.86652
[36m(train_xgb_ray_tune pid=1821680)[0m [363]	train-mlogloss:1.88706	validation-mlogloss:1.86629
[36m(train_xgb_ray_tune pid=1821680)[0m [364]	train-mlogloss:1.88660	validation-mlogloss:1.86601
[36m(train_xgb_ray_tune pid=1821686)[0m [381]	train-mlogloss:2.23775	validation-mlogloss:2.22359
[36m(train_xgb_ray_tune pid=1821686)[0m [382]	train-mlogloss:2.23737	validation-mlogloss:2.22326
[36m(train_xgb_ray_tune pid=1821686)[0m [383]	train-mlogloss:2.23709	validation-mlogloss:2.22299
[36m(train_xgb_ray_tune pid=1821686)[0m [384]	train-mlogloss:2.23688	validation-mlogloss:2.22279
[36m(train_xgb_ray_tune pid=1821687)[0m [427]	train-mlogloss:2.02121	validation-mlogloss:1.99214
[36m(train_xgb_ray_tune pid=1821687)[0m [428]	train-mlogloss:2.02098	validation-mlogloss:1.99189
[36m(train_xgb_ray_tune pid=1821687)[0m [429]	train-mlogloss:2.02066	validation-mlogloss:1.99169
[36m(train_xgb_ray_tune pid=1821687)[0m [430]	train-mlogloss:2.02034	validation-mlogloss:1.99145
[36m(train_xgb_ray_tune pid=1821670)[0m [405]	train-mlogloss:1.83941	validation-mlogloss:1.82532
[36m(train_xgb_ray_tune pid=1821670)[0m [406]	train-mlogloss:1.83881	validation-mlogloss:1.82492
[36m(train_xgb_ray_tune pid=1821670)[0m [407]	train-mlogloss:1.83821	validation-mlogloss:1.82456
[36m(train_xgb_ray_tune pid=1821674)[0m [385]	train-mlogloss:1.96842	validation-mlogloss:1.92199
[36m(train_xgb_ray_tune pid=1821674)[0m [386]	train-mlogloss:1.96823	validation-mlogloss:1.92184
[36m(train_xgb_ray_tune pid=1821674)[0m [387]	train-mlogloss:1.96801	validation-mlogloss:1.92157
[36m(train_xgb_ray_tune pid=1821674)[0m [388]	train-mlogloss:1.96751	validation-mlogloss:1.92112
[36m(train_xgb_ray_tune pid=1821683)[0m [421]	train-mlogloss:2.23076	validation-mlogloss:2.22474
[36m(train_xgb_ray_tune pid=1821683)[0m [422]	train-mlogloss:2.23057	validation-mlogloss:2.22464
[36m(train_xgb_ray_tune pid=1821683)[0m [423]	train-mlogloss:2.23040	validation-mlogloss:2.22452
[36m(train_xgb_ray_tune pid=1821683)[0m [424]	train-mlogloss:2.23021	validation-mlogloss:2.22442
[36m(train_xgb_ray_tune pid=1821663)[0m [345]	train-mlogloss:1.97409	validation-mlogloss:1.93763
[36m(train_xgb_ray_tune pid=1821663)[0m [346]	train-mlogloss:1.97340	validation-mlogloss:1.93709
[36m(train_xgb_ray_tune pid=1821663)[0m [347]	train-mlogloss:1.97267	validation-mlogloss:1.93637
[36m(train_xgb_ray_tune pid=1821691)[0m [409]	train-mlogloss:1.94762	validation-mlogloss:1.91494
[36m(train_xgb_ray_tune pid=1821691)[0m [410]	train-mlogloss:1.94753	validation-mlogloss:1.91478
[36m(train_xgb_ray_tune pid=1821691)[0m [411]	train-mlogloss:1.94736	validation-mlogloss:1.91459
[36m(train_xgb_ray_tune pid=1821691)[0m [412]	train-mlogloss:1.94733	validation-mlogloss:1.91457
[36m(train_xgb_ray_tune pid=1821680)[0m [365]	train-mlogloss:1.88617	validation-mlogloss:1.86577
[36m(train_xgb_ray_tune pid=1821680)[0m [366]	train-mlogloss:1.88591	validation-mlogloss:1.86559
[36m(train_xgb_ray_tune pid=1821680)[0m [367]	train-mlogloss:1.88558	validation-mlogloss:1.86527
[36m(train_xgb_ray_tune pid=1821680)[0m [368]	train-mlogloss:1.88524	validation-mlogloss:1.86493
[36m(train_xgb_ray_tune pid=1821686)[0m [385]	train-mlogloss:2.23662	validation-mlogloss:2.22258
[36m(train_xgb_ray_tune pid=1821686)[0m [386]	train-mlogloss:2.23626	validation-mlogloss:2.22221
[36m(train_xgb_ray_tune pid=1821686)[0m [387]	train-mlogloss:2.23591	validation-mlogloss:2.22187
[36m(train_xgb_ray_tune pid=1821686)[0m [388]	train-mlogloss:2.23568	validation-mlogloss:2.22166
[36m(train_xgb_ray_tune pid=1821687)[0m [431]	train-mlogloss:2.02008	validation-mlogloss:1.99124
[36m(train_xgb_ray_tune pid=1821687)[0m [432]	train-mlogloss:2.01975	validation-mlogloss:1.99088
[36m(train_xgb_ray_tune pid=1821687)[0m [433]	train-mlogloss:2.01955	validation-mlogloss:1.99072
[36m(train_xgb_ray_tune pid=1821687)[0m [434]	train-mlogloss:2.01931	validation-mlogloss:1.99053
[36m(train_xgb_ray_tune pid=1821670)[0m [408]	train-mlogloss:1.83772	validation-mlogloss:1.82437
[36m(train_xgb_ray_tune pid=1821670)[0m [409]	train-mlogloss:1.83724	validation-mlogloss:1.82413
[36m(train_xgb_ray_tune pid=1821670)[0m [410]	train-mlogloss:1.83678	validation-mlogloss:1.82384
[36m(train_xgb_ray_tune pid=1821670)[0m [411]	train-mlogloss:1.83628	validation-mlogloss:1.82354
[36m(train_xgb_ray_tune pid=1821674)[0m [389]	train-mlogloss:1.96727	validation-mlogloss:1.92092
[36m(train_xgb_ray_tune pid=1821674)[0m [390]	train-mlogloss:1.96689	validation-mlogloss:1.92061
[36m(train_xgb_ray_tune pid=1821674)[0m [391]	train-mlogloss:1.96653	validation-mlogloss:1.92043
[36m(train_xgb_ray_tune pid=1821674)[0m [392]	train-mlogloss:1.96625	validation-mlogloss:1.92029
[36m(train_xgb_ray_tune pid=1821683)[0m [425]	train-mlogloss:2.22991	validation-mlogloss:2.22407
[36m(train_xgb_ray_tune pid=1821683)[0m [426]	train-mlogloss:2.22980	validation-mlogloss:2.22405
[36m(train_xgb_ray_tune pid=1821683)[0m [427]	train-mlogloss:2.22960	validation-mlogloss:2.22385
[36m(train_xgb_ray_tune pid=1821683)[0m [428]	train-mlogloss:2.22936	validation-mlogloss:2.22362
[36m(train_xgb_ray_tune pid=1821663)[0m [348]	train-mlogloss:1.97194	validation-mlogloss:1.93568
[36m(train_xgb_ray_tune pid=1821663)[0m [349]	train-mlogloss:1.97128	validation-mlogloss:1.93518
[36m(train_xgb_ray_tune pid=1821663)[0m [350]	train-mlogloss:1.97064	validation-mlogloss:1.93452
[36m(train_xgb_ray_tune pid=1821691)[0m [413]	train-mlogloss:1.94726	validation-mlogloss:1.91458
[36m(train_xgb_ray_tune pid=1821691)[0m [414]	train-mlogloss:1.94716	validation-mlogloss:1.91446
[36m(train_xgb_ray_tune pid=1821691)[0m [415]	train-mlogloss:1.94702	validation-mlogloss:1.91441
[36m(train_xgb_ray_tune pid=1821691)[0m [416]	train-mlogloss:1.94702	validation-mlogloss:1.91441
[36m(train_xgb_ray_tune pid=1821680)[0m [369]	train-mlogloss:1.88477	validation-mlogloss:1.86462
[36m(train_xgb_ray_tune pid=1821680)[0m [370]	train-mlogloss:1.88444	validation-mlogloss:1.86446
[36m(train_xgb_ray_tune pid=1821680)[0m [371]	train-mlogloss:1.88410	validation-mlogloss:1.86433
[36m(train_xgb_ray_tune pid=1821680)[0m [372]	train-mlogloss:1.88376	validation-mlogloss:1.86412
[36m(train_xgb_ray_tune pid=1821686)[0m [389]	train-mlogloss:2.23542	validation-mlogloss:2.22143
[36m(train_xgb_ray_tune pid=1821686)[0m [390]	train-mlogloss:2.23512	validation-mlogloss:2.22111
[36m(train_xgb_ray_tune pid=1821686)[0m [391]	train-mlogloss:2.23484	validation-mlogloss:2.22085
[36m(train_xgb_ray_tune pid=1821686)[0m [392]	train-mlogloss:2.23453	validation-mlogloss:2.22053
[36m(train_xgb_ray_tune pid=1821687)[0m [435]	train-mlogloss:2.01916	validation-mlogloss:1.99046
[36m(train_xgb_ray_tune pid=1821687)[0m [436]	train-mlogloss:2.01889	validation-mlogloss:1.99026
[36m(train_xgb_ray_tune pid=1821687)[0m [437]	train-mlogloss:2.01862	validation-mlogloss:1.99010
[36m(train_xgb_ray_tune pid=1821687)[0m [438]	train-mlogloss:2.01837	validation-mlogloss:1.98996
[36m(train_xgb_ray_tune pid=1821670)[0m [412]	train-mlogloss:1.83586	validation-mlogloss:1.82324
[36m(train_xgb_ray_tune pid=1821670)[0m [413]	train-mlogloss:1.83537	validation-mlogloss:1.82291
[36m(train_xgb_ray_tune pid=1821670)[0m [414]	train-mlogloss:1.83477	validation-mlogloss:1.82236
[36m(train_xgb_ray_tune pid=1821674)[0m [393]	train-mlogloss:1.96596	validation-mlogloss:1.92021
[36m(train_xgb_ray_tune pid=1821674)[0m [394]	train-mlogloss:1.96580	validation-mlogloss:1.92013
[36m(train_xgb_ray_tune pid=1821674)[0m [395]	train-mlogloss:1.96552	validation-mlogloss:1.91999
[36m(train_xgb_ray_tune pid=1821674)[0m [396]	train-mlogloss:1.96531	validation-mlogloss:1.91983
[36m(train_xgb_ray_tune pid=1821683)[0m [429]	train-mlogloss:2.22916	validation-mlogloss:2.22343
[36m(train_xgb_ray_tune pid=1821683)[0m [430]	train-mlogloss:2.22900	validation-mlogloss:2.22327
[36m(train_xgb_ray_tune pid=1821683)[0m [431]	train-mlogloss:2.22889	validation-mlogloss:2.22317
[36m(train_xgb_ray_tune pid=1821683)[0m [432]	train-mlogloss:2.22874	validation-mlogloss:2.22304
[36m(train_xgb_ray_tune pid=1821663)[0m [351]	train-mlogloss:1.96991	validation-mlogloss:1.93394
[36m(train_xgb_ray_tune pid=1821663)[0m [352]	train-mlogloss:1.96916	validation-mlogloss:1.93326
[36m(train_xgb_ray_tune pid=1821663)[0m [353]	train-mlogloss:1.96843	validation-mlogloss:1.93252
[36m(train_xgb_ray_tune pid=1821691)[0m [417]	train-mlogloss:1.94692	validation-mlogloss:1.91437
[36m(train_xgb_ray_tune pid=1821691)[0m [418]	train-mlogloss:1.94678	validation-mlogloss:1.91420
[36m(train_xgb_ray_tune pid=1821691)[0m [419]	train-mlogloss:1.94672	validation-mlogloss:1.91416
[36m(train_xgb_ray_tune pid=1821691)[0m [420]	train-mlogloss:1.94656	validation-mlogloss:1.91406
[36m(train_xgb_ray_tune pid=1821680)[0m [373]	train-mlogloss:1.88350	validation-mlogloss:1.86399
[36m(train_xgb_ray_tune pid=1821680)[0m [374]	train-mlogloss:1.88319	validation-mlogloss:1.86380
[36m(train_xgb_ray_tune pid=1821680)[0m [375]	train-mlogloss:1.88290	validation-mlogloss:1.86362
[36m(train_xgb_ray_tune pid=1821680)[0m [376]	train-mlogloss:1.88250	validation-mlogloss:1.86342
[36m(train_xgb_ray_tune pid=1821686)[0m [393]	train-mlogloss:2.23433	validation-mlogloss:2.22036
[36m(train_xgb_ray_tune pid=1821686)[0m [394]	train-mlogloss:2.23411	validation-mlogloss:2.22018
[36m(train_xgb_ray_tune pid=1821686)[0m [395]	train-mlogloss:2.23387	validation-mlogloss:2.21992
[36m(train_xgb_ray_tune pid=1821686)[0m [396]	train-mlogloss:2.23358	validation-mlogloss:2.21963
[36m(train_xgb_ray_tune pid=1821687)[0m [439]	train-mlogloss:2.01809	validation-mlogloss:1.98980
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[36m(train_xgb_ray_tune pid=1821687)[0m [441]	train-mlogloss:2.01765	validation-mlogloss:1.98943
[36m(train_xgb_ray_tune pid=1821687)[0m [442]	train-mlogloss:2.01735	validation-mlogloss:1.98916
[36m(train_xgb_ray_tune pid=1821670)[0m [415]	train-mlogloss:1.83431	validation-mlogloss:1.82214
[36m(train_xgb_ray_tune pid=1821670)[0m [416]	train-mlogloss:1.83369	validation-mlogloss:1.82177
[36m(train_xgb_ray_tune pid=1821670)[0m [417]	train-mlogloss:1.83326	validation-mlogloss:1.82161
[36m(train_xgb_ray_tune pid=1821670)[0m [418]	train-mlogloss:1.83274	validation-mlogloss:1.82129
[36m(train_xgb_ray_tune pid=1821674)[0m [397]	train-mlogloss:1.96508	validation-mlogloss:1.91975
[36m(train_xgb_ray_tune pid=1821674)[0m [398]	train-mlogloss:1.96485	validation-mlogloss:1.91957
[36m(train_xgb_ray_tune pid=1821674)[0m [399]	train-mlogloss:1.96464	validation-mlogloss:1.91943
[36m(train_xgb_ray_tune pid=1821674)[0m [400]	train-mlogloss:1.96439	validation-mlogloss:1.91930
[36m(train_xgb_ray_tune pid=1821683)[0m [433]	train-mlogloss:2.22858	validation-mlogloss:2.22288
[36m(train_xgb_ray_tune pid=1821683)[0m [434]	train-mlogloss:2.22834	validation-mlogloss:2.22266
[36m(train_xgb_ray_tune pid=1821683)[0m [435]	train-mlogloss:2.22815	validation-mlogloss:2.22250
[36m(train_xgb_ray_tune pid=1821683)[0m [436]	train-mlogloss:2.22799	validation-mlogloss:2.22234
[36m(train_xgb_ray_tune pid=1821691)[0m [421]	train-mlogloss:1.94649	validation-mlogloss:1.91405
[36m(train_xgb_ray_tune pid=1821683)[0m [437]	train-mlogloss:2.22780	validation-mlogloss:2.22217
[36m(train_xgb_ray_tune pid=1821686)[0m [397]	train-mlogloss:2.23336	validation-mlogloss:2.21945
[36m(train_xgb_ray_tune pid=1821663)[0m [354]	train-mlogloss:1.96764	validation-mlogloss:1.93174
[36m(train_xgb_ray_tune pid=1821663)[0m [355]	train-mlogloss:1.96686	validation-mlogloss:1.93116
[36m(train_xgb_ray_tune pid=1821663)[0m [356]	train-mlogloss:1.96612	validation-mlogloss:1.93050
[36m(train_xgb_ray_tune pid=1821691)[0m [422]	train-mlogloss:1.94640	validation-mlogloss:1.91400
[36m(train_xgb_ray_tune pid=1821691)[0m [423]	train-mlogloss:1.94636	validation-mlogloss:1.91395
[36m(train_xgb_ray_tune pid=1821691)[0m [424]	train-mlogloss:1.94636	validation-mlogloss:1.91394
[36m(train_xgb_ray_tune pid=1821691)[0m [425]	train-mlogloss:1.94629	validation-mlogloss:1.91393
[36m(train_xgb_ray_tune pid=1821680)[0m [377]	train-mlogloss:1.88224	validation-mlogloss:1.86329
[36m(train_xgb_ray_tune pid=1821680)[0m [378]	train-mlogloss:1.88179	validation-mlogloss:1.86289
[36m(train_xgb_ray_tune pid=1821680)[0m [379]	train-mlogloss:1.88134	validation-mlogloss:1.86248
[36m(train_xgb_ray_tune pid=1821680)[0m [380]	train-mlogloss:1.88108	validation-mlogloss:1.86234
[36m(train_xgb_ray_tune pid=1821686)[0m [398]	train-mlogloss:2.23310	validation-mlogloss:2.21918
[36m(train_xgb_ray_tune pid=1821686)[0m [399]	train-mlogloss:2.23280	validation-mlogloss:2.21893
[36m(train_xgb_ray_tune pid=1821686)[0m [400]	train-mlogloss:2.23261	validation-mlogloss:2.21877
[36m(train_xgb_ray_tune pid=1821686)[0m [401]	train-mlogloss:2.23244	validation-mlogloss:2.21863
[36m(train_xgb_ray_tune pid=1821687)[0m [443]	train-mlogloss:2.01711	validation-mlogloss:1.98897
[36m(train_xgb_ray_tune pid=1821687)[0m [444]	train-mlogloss:2.01684	validation-mlogloss:1.98877
[36m(train_xgb_ray_tune pid=1821687)[0m [445]	train-mlogloss:2.01662	validation-mlogloss:1.98856
[36m(train_xgb_ray_tune pid=1821687)[0m [446]	train-mlogloss:2.01637	validation-mlogloss:1.98833
[36m(train_xgb_ray_tune pid=1821670)[0m [419]	train-mlogloss:1.83215	validation-mlogloss:1.82083
[36m(train_xgb_ray_tune pid=1821674)[0m [401]	train-mlogloss:1.96418	validation-mlogloss:1.91915
[36m(train_xgb_ray_tune pid=1821674)[0m [402]	train-mlogloss:1.96388	validation-mlogloss:1.91887
[36m(train_xgb_ray_tune pid=1821674)[0m [403]	train-mlogloss:1.96366	validation-mlogloss:1.91855
[36m(train_xgb_ray_tune pid=1821674)[0m [404]	train-mlogloss:1.96327	validation-mlogloss:1.91821
[36m(train_xgb_ray_tune pid=1821683)[0m [438]	train-mlogloss:2.22766	validation-mlogloss:2.22204
[36m(train_xgb_ray_tune pid=1821683)[0m [439]	train-mlogloss:2.22752	validation-mlogloss:2.22194
[36m(train_xgb_ray_tune pid=1821683)[0m [440]	train-mlogloss:2.22740	validation-mlogloss:2.22181
[36m(train_xgb_ray_tune pid=1821683)[0m [441]	train-mlogloss:2.22725	validation-mlogloss:2.22165
[36m(train_xgb_ray_tune pid=1821663)[0m [357]	train-mlogloss:1.96545	validation-mlogloss:1.92999
[36m(train_xgb_ray_tune pid=1821691)[0m [426]	train-mlogloss:1.94619	validation-mlogloss:1.91380
[36m(train_xgb_ray_tune pid=1821663)[0m [358]	train-mlogloss:1.96472	validation-mlogloss:1.92934
[36m(train_xgb_ray_tune pid=1821663)[0m [359]	train-mlogloss:1.96399	validation-mlogloss:1.92876
[36m(train_xgb_ray_tune pid=1821663)[0m [360]	train-mlogloss:1.96331	validation-mlogloss:1.92813
[36m(train_xgb_ray_tune pid=1821691)[0m [427]	train-mlogloss:1.94609	validation-mlogloss:1.91367
[36m(train_xgb_ray_tune pid=1821691)[0m [428]	train-mlogloss:1.94606	validation-mlogloss:1.91365
[36m(train_xgb_ray_tune pid=1821691)[0m [429]	train-mlogloss:1.94606	validation-mlogloss:1.91365
[36m(train_xgb_ray_tune pid=1821691)[0m [430]	train-mlogloss:1.94603	validation-mlogloss:1.91365
[36m(train_xgb_ray_tune pid=1821680)[0m [381]	train-mlogloss:1.88076	validation-mlogloss:1.86213
[36m(train_xgb_ray_tune pid=1821680)[0m [382]	train-mlogloss:1.88053	validation-mlogloss:1.86191
[36m(train_xgb_ray_tune pid=1821680)[0m [383]	train-mlogloss:1.88023	validation-mlogloss:1.86173
[36m(train_xgb_ray_tune pid=1821680)[0m [384]	train-mlogloss:1.87993	validation-mlogloss:1.86149
[36m(train_xgb_ray_tune pid=1821686)[0m [402]	train-mlogloss:2.23218	validation-mlogloss:2.21839
[36m(train_xgb_ray_tune pid=1821686)[0m [403]	train-mlogloss:2.23182	validation-mlogloss:2.21803
[36m(train_xgb_ray_tune pid=1821686)[0m [404]	train-mlogloss:2.23158	validation-mlogloss:2.21783
[36m(train_xgb_ray_tune pid=1821686)[0m [405]	train-mlogloss:2.23130	validation-mlogloss:2.21758
[36m(train_xgb_ray_tune pid=1821687)[0m [447]	train-mlogloss:2.01611	validation-mlogloss:1.98815
[36m(train_xgb_ray_tune pid=1821687)[0m [448]	train-mlogloss:2.01588	validation-mlogloss:1.98797
[36m(train_xgb_ray_tune pid=1821687)[0m [449]	train-mlogloss:2.01564	validation-mlogloss:1.98773
[36m(train_xgb_ray_tune pid=1821687)[0m [450]	train-mlogloss:2.01535	validation-mlogloss:1.98739
[36m(train_xgb_ray_tune pid=1821687)[0m [451]	train-mlogloss:2.01504	validation-mlogloss:1.98708
[36m(train_xgb_ray_tune pid=1821674)[0m [405]	train-mlogloss:1.96298	validation-mlogloss:1.91797
[36m(train_xgb_ray_tune pid=1821674)[0m [406]	train-mlogloss:1.96277	validation-mlogloss:1.91785
[36m(train_xgb_ray_tune pid=1821674)[0m [407]	train-mlogloss:1.96259	validation-mlogloss:1.91767
[36m(train_xgb_ray_tune pid=1821674)[0m [408]	train-mlogloss:1.96245	validation-mlogloss:1.91758
[36m(train_xgb_ray_tune pid=1821674)[0m [409]	train-mlogloss:1.96228	validation-mlogloss:1.91737
[36m(train_xgb_ray_tune pid=1821683)[0m [442]	train-mlogloss:2.22710	validation-mlogloss:2.22153
[36m(train_xgb_ray_tune pid=1821683)[0m [443]	train-mlogloss:2.22690	validation-mlogloss:2.22135
[36m(train_xgb_ray_tune pid=1821683)[0m [444]	train-mlogloss:2.22680	validation-mlogloss:2.22126
[36m(train_xgb_ray_tune pid=1821683)[0m [445]	train-mlogloss:2.22674	validation-mlogloss:2.22121
[36m(train_xgb_ray_tune pid=1821683)[0m [446]	train-mlogloss:2.22663	validation-mlogloss:2.22111
[36m(train_xgb_ray_tune pid=1821663)[0m [361]	train-mlogloss:1.96261	validation-mlogloss:1.92751
[36m(train_xgb_ray_tune pid=1821663)[0m [362]	train-mlogloss:1.96199	validation-mlogloss:1.92700
[36m(train_xgb_ray_tune pid=1821663)[0m [363]	train-mlogloss:1.96132	validation-mlogloss:1.92655
[36m(train_xgb_ray_tune pid=1821691)[0m [431]	train-mlogloss:1.94592	validation-mlogloss:1.91358
[36m(train_xgb_ray_tune pid=1821691)[0m [432]	train-mlogloss:1.94586	validation-mlogloss:1.91346
[36m(train_xgb_ray_tune pid=1821691)[0m [433]	train-mlogloss:1.94580	validation-mlogloss:1.91340
[36m(train_xgb_ray_tune pid=1821691)[0m [434]	train-mlogloss:1.94576	validation-mlogloss:1.91335
[36m(train_xgb_ray_tune pid=1821691)[0m [435]	train-mlogloss:1.94568	validation-mlogloss:1.91327
[36m(train_xgb_ray_tune pid=1821680)[0m [385]	train-mlogloss:1.87967	validation-mlogloss:1.86129
[36m(train_xgb_ray_tune pid=1821680)[0m [386]	train-mlogloss:1.87924	validation-mlogloss:1.86092
[36m(train_xgb_ray_tune pid=1821680)[0m [387]	train-mlogloss:1.87909	validation-mlogloss:1.86085
[36m(train_xgb_ray_tune pid=1821680)[0m [388]	train-mlogloss:1.87883	validation-mlogloss:1.86070
[36m(train_xgb_ray_tune pid=1821686)[0m [406]	train-mlogloss:2.23108	validation-mlogloss:2.21737
[36m(train_xgb_ray_tune pid=1821686)[0m [407]	train-mlogloss:2.23087	validation-mlogloss:2.21719
[36m(train_xgb_ray_tune pid=1821686)[0m [408]	train-mlogloss:2.23064	validation-mlogloss:2.21694
[36m(train_xgb_ray_tune pid=1821686)[0m [409]	train-mlogloss:2.23038	validation-mlogloss:2.21669
[36m(train_xgb_ray_tune pid=1821686)[0m [410]	train-mlogloss:2.23018	validation-mlogloss:2.21652
[36m(train_xgb_ray_tune pid=1821687)[0m [452]	train-mlogloss:2.01478	validation-mlogloss:1.98692
[36m(train_xgb_ray_tune pid=1821687)[0m [453]	train-mlogloss:2.01455	validation-mlogloss:1.98669
[36m(train_xgb_ray_tune pid=1821687)[0m [454]	train-mlogloss:2.01430	validation-mlogloss:1.98641
[36m(train_xgb_ray_tune pid=1821687)[0m [455]	train-mlogloss:2.01406	validation-mlogloss:1.98626
[36m(train_xgb_ray_tune pid=1821674)[0m [410]	train-mlogloss:1.96209	validation-mlogloss:1.91716
[36m(train_xgb_ray_tune pid=1821674)[0m [411]	train-mlogloss:1.96195	validation-mlogloss:1.91707
[36m(train_xgb_ray_tune pid=1821674)[0m [412]	train-mlogloss:1.96162	validation-mlogloss:1.91665
[36m(train_xgb_ray_tune pid=1821674)[0m [413]	train-mlogloss:1.96119	validation-mlogloss:1.91631
[36m(train_xgb_ray_tune pid=1821683)[0m [447]	train-mlogloss:2.22639	validation-mlogloss:2.22092
[36m(train_xgb_ray_tune pid=1821683)[0m [448]	train-mlogloss:2.22629	validation-mlogloss:2.22084
[36m(train_xgb_ray_tune pid=1821683)[0m [449]	train-mlogloss:2.22614	validation-mlogloss:2.22072
[36m(train_xgb_ray_tune pid=1821683)[0m [450]	train-mlogloss:2.22603	validation-mlogloss:2.22064
[36m(train_xgb_ray_tune pid=1821663)[0m [364]	train-mlogloss:1.96067	validation-mlogloss:1.92605
[36m(train_xgb_ray_tune pid=1821663)[0m [365]	train-mlogloss:1.95988	validation-mlogloss:1.92522
[36m(train_xgb_ray_tune pid=1821663)[0m [366]	train-mlogloss:1.95915	validation-mlogloss:1.92458
[36m(train_xgb_ray_tune pid=1821691)[0m [436]	train-mlogloss:1.94553	validation-mlogloss:1.91315
[36m(train_xgb_ray_tune pid=1821691)[0m [437]	train-mlogloss:1.94550	validation-mlogloss:1.91312
[36m(train_xgb_ray_tune pid=1821691)[0m [438]	train-mlogloss:1.94547	validation-mlogloss:1.91308
[36m(train_xgb_ray_tune pid=1821691)[0m [439]	train-mlogloss:1.94547	validation-mlogloss:1.91308
[36m(train_xgb_ray_tune pid=1821680)[0m [389]	train-mlogloss:1.87860	validation-mlogloss:1.86060
[36m(train_xgb_ray_tune pid=1821680)[0m [390]	train-mlogloss:1.87831	validation-mlogloss:1.86032
[36m(train_xgb_ray_tune pid=1821680)[0m [391]	train-mlogloss:1.87804	validation-mlogloss:1.86015
[36m(train_xgb_ray_tune pid=1821680)[0m [392]	train-mlogloss:1.87784	validation-mlogloss:1.86004
[36m(train_xgb_ray_tune pid=1821686)[0m [411]	train-mlogloss:2.23001	validation-mlogloss:2.21637
[36m(train_xgb_ray_tune pid=1821686)[0m [412]	train-mlogloss:2.22975	validation-mlogloss:2.21616
[36m(train_xgb_ray_tune pid=1821686)[0m [413]	train-mlogloss:2.22950	validation-mlogloss:2.21594
[36m(train_xgb_ray_tune pid=1821686)[0m [414]	train-mlogloss:2.22924	validation-mlogloss:2.21571
[36m(train_xgb_ray_tune pid=1821687)[0m [456]	train-mlogloss:2.01386	validation-mlogloss:1.98618
[36m(train_xgb_ray_tune pid=1821687)[0m [457]	train-mlogloss:2.01360	validation-mlogloss:1.98599
[36m(train_xgb_ray_tune pid=1821687)[0m [458]	train-mlogloss:2.01335	validation-mlogloss:1.98586
[36m(train_xgb_ray_tune pid=1821687)[0m [459]	train-mlogloss:2.01310	validation-mlogloss:1.98566
[36m(train_xgb_ray_tune pid=1821674)[0m [414]	train-mlogloss:1.96092	validation-mlogloss:1.91619
[36m(train_xgb_ray_tune pid=1821674)[0m [415]	train-mlogloss:1.96062	validation-mlogloss:1.91592
[36m(train_xgb_ray_tune pid=1821674)[0m [416]	train-mlogloss:1.96040	validation-mlogloss:1.91580
[36m(train_xgb_ray_tune pid=1821674)[0m [417]	train-mlogloss:1.96018	validation-mlogloss:1.91556
[36m(train_xgb_ray_tune pid=1821683)[0m [451]	train-mlogloss:2.22593	validation-mlogloss:2.22060
[36m(train_xgb_ray_tune pid=1821683)[0m [452]	train-mlogloss:2.22583	validation-mlogloss:2.22052
[36m(train_xgb_ray_tune pid=1821683)[0m [453]	train-mlogloss:2.22563	validation-mlogloss:2.22035
[36m(train_xgb_ray_tune pid=1821683)[0m [454]	train-mlogloss:2.22557	validation-mlogloss:2.22034
[36m(train_xgb_ray_tune pid=1821683)[0m [455]	train-mlogloss:2.22547	validation-mlogloss:2.22030
[36m(train_xgb_ray_tune pid=1821663)[0m [367]	train-mlogloss:1.95857	validation-mlogloss:1.92405
[36m(train_xgb_ray_tune pid=1821691)[0m [440]	train-mlogloss:1.94537	validation-mlogloss:1.91299

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:05. Total running time: 35s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             33.0308 │
│ time_total_s                 33.0308 │
│ training_iteration                 1 │
│ validation_accuracy          0.50427 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:05. Total running time: 35s
[36m(train_xgb_ray_tune pid=1821663)[0m [368]	train-mlogloss:1.95786	validation-mlogloss:1.92344
[36m(train_xgb_ray_tune pid=1821663)[0m [369]	train-mlogloss:1.95726	validation-mlogloss:1.92300
[36m(train_xgb_ray_tune pid=1821663)[0m [370]	train-mlogloss:1.95658	validation-mlogloss:1.92243
[36m(train_xgb_ray_tune pid=1821691)[0m [441]	train-mlogloss:1.94534	validation-mlogloss:1.91296
[36m(train_xgb_ray_tune pid=1821691)[0m [442]	train-mlogloss:1.94531	validation-mlogloss:1.91295
[36m(train_xgb_ray_tune pid=1821691)[0m [443]	train-mlogloss:1.94520	validation-mlogloss:1.91292
[36m(train_xgb_ray_tune pid=1821691)[0m [444]	train-mlogloss:1.94513	validation-mlogloss:1.91292
[36m(train_xgb_ray_tune pid=1821680)[0m [393]	train-mlogloss:1.87764	validation-mlogloss:1.85989
[36m(train_xgb_ray_tune pid=1821680)[0m [394]	train-mlogloss:1.87719	validation-mlogloss:1.85962
[36m(train_xgb_ray_tune pid=1821680)[0m [395]	train-mlogloss:1.87705	validation-mlogloss:1.85953
[36m(train_xgb_ray_tune pid=1821680)[0m [396]	train-mlogloss:1.87682	validation-mlogloss:1.85932
[36m(train_xgb_ray_tune pid=1821686)[0m [415]	train-mlogloss:2.22898	validation-mlogloss:2.21550
[36m(train_xgb_ray_tune pid=1821686)[0m [416]	train-mlogloss:2.22877	validation-mlogloss:2.21530
[36m(train_xgb_ray_tune pid=1821686)[0m [417]	train-mlogloss:2.22856	validation-mlogloss:2.21510
[36m(train_xgb_ray_tune pid=1821686)[0m [418]	train-mlogloss:2.22834	validation-mlogloss:2.21489
[36m(train_xgb_ray_tune pid=1821687)[0m [460]	train-mlogloss:2.01283	validation-mlogloss:1.98549
[36m(train_xgb_ray_tune pid=1821687)[0m [461]	train-mlogloss:2.01263	validation-mlogloss:1.98535
[36m(train_xgb_ray_tune pid=1821687)[0m [462]	train-mlogloss:2.01240	validation-mlogloss:1.98520
[36m(train_xgb_ray_tune pid=1821687)[0m [463]	train-mlogloss:2.01204	validation-mlogloss:1.98485
[36m(train_xgb_ray_tune pid=1821674)[0m [418]	train-mlogloss:1.95992	validation-mlogloss:1.91542
[36m(train_xgb_ray_tune pid=1821674)[0m [419]	train-mlogloss:1.95975	validation-mlogloss:1.91531
[36m(train_xgb_ray_tune pid=1821674)[0m [420]	train-mlogloss:1.95953	validation-mlogloss:1.91512
[36m(train_xgb_ray_tune pid=1821674)[0m [421]	train-mlogloss:1.95935	validation-mlogloss:1.91504
[36m(train_xgb_ray_tune pid=1821683)[0m [456]	train-mlogloss:2.22536	validation-mlogloss:2.22021
[36m(train_xgb_ray_tune pid=1821683)[0m [457]	train-mlogloss:2.22518	validation-mlogloss:2.22004
[36m(train_xgb_ray_tune pid=1821683)[0m [458]	train-mlogloss:2.22512	validation-mlogloss:2.22003
[36m(train_xgb_ray_tune pid=1821683)[0m [459]	train-mlogloss:2.22498	validation-mlogloss:2.21995
[36m(train_xgb_ray_tune pid=1821663)[0m [371]	train-mlogloss:1.95585	validation-mlogloss:1.92181
[36m(train_xgb_ray_tune pid=1821663)[0m [372]	train-mlogloss:1.95524	validation-mlogloss:1.92127
[36m(train_xgb_ray_tune pid=1821663)[0m [373]	train-mlogloss:1.95462	validation-mlogloss:1.92078
[36m(train_xgb_ray_tune pid=1821691)[0m [445]	train-mlogloss:1.94502	validation-mlogloss:1.91287
[36m(train_xgb_ray_tune pid=1821691)[0m [446]	train-mlogloss:1.94502	validation-mlogloss:1.91287
[36m(train_xgb_ray_tune pid=1821691)[0m [447]	train-mlogloss:1.94495	validation-mlogloss:1.91282
[36m(train_xgb_ray_tune pid=1821691)[0m [448]	train-mlogloss:1.94495	validation-mlogloss:1.91282
[36m(train_xgb_ray_tune pid=1821691)[0m [449]	train-mlogloss:1.94489	validation-mlogloss:1.91280
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[36m(train_xgb_ray_tune pid=1821691)[0m [529]	train-mlogloss:1.94205	validation-mlogloss:1.91043
[36m(train_xgb_ray_tune pid=1821680)[0m [467]	train-mlogloss:1.86281	validation-mlogloss:1.84954
[36m(train_xgb_ray_tune pid=1821680)[0m [468]	train-mlogloss:1.86273	validation-mlogloss:1.84949
[36m(train_xgb_ray_tune pid=1821680)[0m [469]	train-mlogloss:1.86260	validation-mlogloss:1.84946
[36m(train_xgb_ray_tune pid=1821680)[0m [470]	train-mlogloss:1.86230	validation-mlogloss:1.84918
[36m(train_xgb_ray_tune pid=1821686)[0m [495]	train-mlogloss:2.21405	validation-mlogloss:2.20218
[36m(train_xgb_ray_tune pid=1821686)[0m [496]	train-mlogloss:2.21392	validation-mlogloss:2.20209
[36m(train_xgb_ray_tune pid=1821686)[0m [497]	train-mlogloss:2.21381	validation-mlogloss:2.20200
[36m(train_xgb_ray_tune pid=1821686)[0m [498]	train-mlogloss:2.21367	validation-mlogloss:2.20189
[36m(train_xgb_ray_tune pid=1821674)[0m [495]	train-mlogloss:1.94733	validation-mlogloss:1.90646
[36m(train_xgb_ray_tune pid=1821674)[0m [496]	train-mlogloss:1.94726	validation-mlogloss:1.90643
[36m(train_xgb_ray_tune pid=1821674)[0m [497]	train-mlogloss:1.94723	validation-mlogloss:1.90641
[36m(train_xgb_ray_tune pid=1821674)[0m [498]	train-mlogloss:1.94711	validation-mlogloss:1.90627
[36m(train_xgb_ray_tune pid=1821674)[0m [499]	train-mlogloss:1.94711	validation-mlogloss:1.90627
[36m(train_xgb_ray_tune pid=1821683)[0m [538]	train-mlogloss:2.21770	validation-mlogloss:2.21424
[36m(train_xgb_ray_tune pid=1821683)[0m [539]	train-mlogloss:2.21770	validation-mlogloss:2.21424
[36m(train_xgb_ray_tune pid=1821683)[0m [540]	train-mlogloss:2.21756	validation-mlogloss:2.21411
[36m(train_xgb_ray_tune pid=1821683)[0m [541]	train-mlogloss:2.21747	validation-mlogloss:2.21402
[36m(train_xgb_ray_tune pid=1821680)[0m [471]	train-mlogloss:1.86225	validation-mlogloss:1.84914
[36m(train_xgb_ray_tune pid=1821686)[0m [499]	train-mlogloss:2.21356	validation-mlogloss:2.20181
[36m(train_xgb_ray_tune pid=1821683)[0m [542]	train-mlogloss:2.21738	validation-mlogloss:2.21400
[36m(train_xgb_ray_tune pid=1821663)[0m [432]	train-mlogloss:1.92187	validation-mlogloss:1.89239
[36m(train_xgb_ray_tune pid=1821663)[0m [433]	train-mlogloss:1.92131	validation-mlogloss:1.89195
[36m(train_xgb_ray_tune pid=1821663)[0m [434]	train-mlogloss:1.92077	validation-mlogloss:1.89153
[36m(train_xgb_ray_tune pid=1821663)[0m [435]	train-mlogloss:1.92019	validation-mlogloss:1.89104
[36m(train_xgb_ray_tune pid=1821691)[0m [530]	train-mlogloss:1.94192	validation-mlogloss:1.91030
[36m(train_xgb_ray_tune pid=1821691)[0m [531]	train-mlogloss:1.94192	validation-mlogloss:1.91030
[36m(train_xgb_ray_tune pid=1821691)[0m [532]	train-mlogloss:1.94186	validation-mlogloss:1.91026
[36m(train_xgb_ray_tune pid=1821691)[0m [533]	train-mlogloss:1.94186	validation-mlogloss:1.91026
[36m(train_xgb_ray_tune pid=1821691)[0m [534]	train-mlogloss:1.94179	validation-mlogloss:1.91021
[36m(train_xgb_ray_tune pid=1821680)[0m [472]	train-mlogloss:1.86208	validation-mlogloss:1.84900
[36m(train_xgb_ray_tune pid=1821680)[0m [473]	train-mlogloss:1.86201	validation-mlogloss:1.84892
[36m(train_xgb_ray_tune pid=1821680)[0m [474]	train-mlogloss:1.86193	validation-mlogloss:1.84888
[36m(train_xgb_ray_tune pid=1821680)[0m [475]	train-mlogloss:1.86186	validation-mlogloss:1.84890
[36m(train_xgb_ray_tune pid=1821686)[0m [500]	train-mlogloss:2.21346	validation-mlogloss:2.20174
[36m(train_xgb_ray_tune pid=1821686)[0m [501]	train-mlogloss:2.21327	validation-mlogloss:2.20158
[36m(train_xgb_ray_tune pid=1821686)[0m [502]	train-mlogloss:2.21309	validation-mlogloss:2.20143
[36m(train_xgb_ray_tune pid=1821686)[0m [503]	train-mlogloss:2.21291	validation-mlogloss:2.20128
[36m(train_xgb_ray_tune pid=1821674)[0m [500]	train-mlogloss:1.94711	validation-mlogloss:1.90627
[36m(train_xgb_ray_tune pid=1821674)[0m [501]	train-mlogloss:1.94711	validation-mlogloss:1.90626
[36m(train_xgb_ray_tune pid=1821674)[0m [502]	train-mlogloss:1.94705	validation-mlogloss:1.90622
[36m(train_xgb_ray_tune pid=1821674)[0m [503]	train-mlogloss:1.94703	validation-mlogloss:1.90618
[36m(train_xgb_ray_tune pid=1821683)[0m [543]	train-mlogloss:2.21738	validation-mlogloss:2.21400
[36m(train_xgb_ray_tune pid=1821683)[0m [544]	train-mlogloss:2.21738	validation-mlogloss:2.21400
[36m(train_xgb_ray_tune pid=1821683)[0m [545]	train-mlogloss:2.21738	validation-mlogloss:2.21400
[36m(train_xgb_ray_tune pid=1821683)[0m [546]	train-mlogloss:2.21738	validation-mlogloss:2.21400
[36m(train_xgb_ray_tune pid=1821674)[0m [504]	train-mlogloss:1.94691	validation-mlogloss:1.90609
[36m(train_xgb_ray_tune pid=1821663)[0m [436]	train-mlogloss:1.91959	validation-mlogloss:1.89049
[36m(train_xgb_ray_tune pid=1821663)[0m [437]	train-mlogloss:1.91915	validation-mlogloss:1.89006
[36m(train_xgb_ray_tune pid=1821663)[0m [438]	train-mlogloss:1.91870	validation-mlogloss:1.88979
[36m(train_xgb_ray_tune pid=1821691)[0m [535]	train-mlogloss:1.94165	validation-mlogloss:1.90999
[36m(train_xgb_ray_tune pid=1821691)[0m [536]	train-mlogloss:1.94162	validation-mlogloss:1.90994
[36m(train_xgb_ray_tune pid=1821691)[0m [537]	train-mlogloss:1.94159	validation-mlogloss:1.90993
[36m(train_xgb_ray_tune pid=1821691)[0m [538]	train-mlogloss:1.94156	validation-mlogloss:1.90987
[36m(train_xgb_ray_tune pid=1821691)[0m [539]	train-mlogloss:1.94156	validation-mlogloss:1.90987
[36m(train_xgb_ray_tune pid=1821680)[0m [476]	train-mlogloss:1.86178	validation-mlogloss:1.84885
[36m(train_xgb_ray_tune pid=1821680)[0m [477]	train-mlogloss:1.86164	validation-mlogloss:1.84881
[36m(train_xgb_ray_tune pid=1821680)[0m [478]	train-mlogloss:1.86154	validation-mlogloss:1.84880
[36m(train_xgb_ray_tune pid=1821680)[0m [479]	train-mlogloss:1.86129	validation-mlogloss:1.84866
[36m(train_xgb_ray_tune pid=1821687)[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 8x across cluster][0m
[36m(train_xgb_ray_tune pid=1821687)[0m   _log_deprecation_warning([32m [repeated 8x across cluster][0m
[36m(train_xgb_ray_tune pid=1821680)[0m [480]	train-mlogloss:1.86117	validation-mlogloss:1.84857
[36m(train_xgb_ray_tune pid=1821686)[0m [504]	train-mlogloss:2.21273	validation-mlogloss:2.20114
[36m(train_xgb_ray_tune pid=1821686)[0m [505]	train-mlogloss:2.21260	validation-mlogloss:2.20103
[36m(train_xgb_ray_tune pid=1821686)[0m [506]	train-mlogloss:2.21247	validation-mlogloss:2.20094
[36m(train_xgb_ray_tune pid=1821686)[0m [507]	train-mlogloss:2.21235	validation-mlogloss:2.20083
[36m(train_xgb_ray_tune pid=1821686)[0m [508]	train-mlogloss:2.21220	validation-mlogloss:2.20072
[36m(train_xgb_ray_tune pid=1821674)[0m [505]	train-mlogloss:1.94678	validation-mlogloss:1.90600
[36m(train_xgb_ray_tune pid=1821674)[0m [506]	train-mlogloss:1.94678	validation-mlogloss:1.90600
[36m(train_xgb_ray_tune pid=1821674)[0m [507]	train-mlogloss:1.94655	validation-mlogloss:1.90582
[36m(train_xgb_ray_tune pid=1821674)[0m [508]	train-mlogloss:1.94642	validation-mlogloss:1.90574
[36m(train_xgb_ray_tune pid=1821683)[0m [547]	train-mlogloss:2.21738	validation-mlogloss:2.21400
[36m(train_xgb_ray_tune pid=1821683)[0m [548]	train-mlogloss:2.21734	validation-mlogloss:2.21394
[36m(train_xgb_ray_tune pid=1821683)[0m [549]	train-mlogloss:2.21729	validation-mlogloss:2.21390
[36m(train_xgb_ray_tune pid=1821683)[0m [550]	train-mlogloss:2.21729	validation-mlogloss:2.21390
[36m(train_xgb_ray_tune pid=1821683)[0m [551]	train-mlogloss:2.21729	validation-mlogloss:2.21390
[36m(train_xgb_ray_tune pid=1821663)[0m [439]	train-mlogloss:1.91821	validation-mlogloss:1.88936

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:07. Total running time: 38s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             35.2506 │
│ time_total_s                 35.2506 │
│ training_iteration                 1 │
│ validation_accuracy           0.4588 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:07. Total running time: 38s
[36m(train_xgb_ray_tune pid=1821663)[0m [440]	train-mlogloss:1.91768	validation-mlogloss:1.88893
[36m(train_xgb_ray_tune pid=1821663)[0m [441]	train-mlogloss:1.91721	validation-mlogloss:1.88846
[36m(train_xgb_ray_tune pid=1821663)[0m [442]	train-mlogloss:1.91678	validation-mlogloss:1.88805
[36m(train_xgb_ray_tune pid=1821691)[0m [540]	train-mlogloss:1.94146	validation-mlogloss:1.90983
[36m(train_xgb_ray_tune pid=1821691)[0m [541]	train-mlogloss:1.94143	validation-mlogloss:1.90978
[36m(train_xgb_ray_tune pid=1821691)[0m [542]	train-mlogloss:1.94137	validation-mlogloss:1.90975
[36m(train_xgb_ray_tune pid=1821691)[0m [543]	train-mlogloss:1.94130	validation-mlogloss:1.90972
[36m(train_xgb_ray_tune pid=1821680)[0m [481]	train-mlogloss:1.86105	validation-mlogloss:1.84856
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[36m(train_xgb_ray_tune pid=1821686)[0m [509]	train-mlogloss:2.21207	validation-mlogloss:2.20060
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[36m(train_xgb_ray_tune pid=1821674)[0m [509]	train-mlogloss:1.94633	validation-mlogloss:1.90567
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[36m(train_xgb_ray_tune pid=1821683)[0m [552]	train-mlogloss:2.21725	validation-mlogloss:2.21385
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[36m(train_xgb_ray_tune pid=1821691)[0m [544]	train-mlogloss:1.94126	validation-mlogloss:1.90970
[36m(train_xgb_ray_tune pid=1821663)[0m [443]	train-mlogloss:1.91634	validation-mlogloss:1.88763
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[36m(train_xgb_ray_tune pid=1821663)[0m [446]	train-mlogloss:1.91496	validation-mlogloss:1.88650
[36m(train_xgb_ray_tune pid=1821691)[0m [545]	train-mlogloss:1.94123	validation-mlogloss:1.90965
[36m(train_xgb_ray_tune pid=1821691)[0m [546]	train-mlogloss:1.94123	validation-mlogloss:1.90965
[36m(train_xgb_ray_tune pid=1821691)[0m [547]	train-mlogloss:1.94116	validation-mlogloss:1.90959
[36m(train_xgb_ray_tune pid=1821691)[0m [548]	train-mlogloss:1.94116	validation-mlogloss:1.90959
[36m(train_xgb_ray_tune pid=1821680)[0m [485]	train-mlogloss:1.86061	validation-mlogloss:1.84831
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[36m(train_xgb_ray_tune pid=1821686)[0m [514]	train-mlogloss:2.21135	validation-mlogloss:2.20005
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[36m(train_xgb_ray_tune pid=1821674)[0m [514]	train-mlogloss:1.94600	validation-mlogloss:1.90539
[36m(train_xgb_ray_tune pid=1821674)[0m [515]	train-mlogloss:1.94591	validation-mlogloss:1.90527
[36m(train_xgb_ray_tune pid=1821674)[0m [516]	train-mlogloss:1.94585	validation-mlogloss:1.90527
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[36m(train_xgb_ray_tune pid=1821683)[0m [557]	train-mlogloss:2.21695	validation-mlogloss:2.21353
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[36m(train_xgb_ray_tune pid=1821663)[0m [447]	train-mlogloss:1.91455	validation-mlogloss:1.88615
[36m(train_xgb_ray_tune pid=1821663)[0m [448]	train-mlogloss:1.91412	validation-mlogloss:1.88579
[36m(train_xgb_ray_tune pid=1821663)[0m [449]	train-mlogloss:1.91371	validation-mlogloss:1.88548
[36m(train_xgb_ray_tune pid=1821663)[0m [450]	train-mlogloss:1.91322	validation-mlogloss:1.88504
[36m(train_xgb_ray_tune pid=1821691)[0m [549]	train-mlogloss:1.94113	validation-mlogloss:1.90957
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[36m(train_xgb_ray_tune pid=1821680)[0m [490]	train-mlogloss:1.86019	validation-mlogloss:1.84831
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[36m(train_xgb_ray_tune pid=1821686)[0m [518]	train-mlogloss:2.21080	validation-mlogloss:2.19961
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[36m(train_xgb_ray_tune pid=1821674)[0m [519]	train-mlogloss:1.94563	validation-mlogloss:1.90510
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[36m(train_xgb_ray_tune pid=1821683)[0m [562]	train-mlogloss:2.21685	validation-mlogloss:2.21350
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[36m(train_xgb_ray_tune pid=1821674)[0m [582]	train-mlogloss:1.94151	validation-mlogloss:1.90140
[36m(train_xgb_ray_tune pid=1821674)[0m [583]	train-mlogloss:1.94139	validation-mlogloss:1.90130
[36m(train_xgb_ray_tune pid=1821674)[0m [584]	train-mlogloss:1.94126	validation-mlogloss:1.90121
[36m(train_xgb_ray_tune pid=1821674)[0m [585]	train-mlogloss:1.94119	validation-mlogloss:1.90118
[36m(train_xgb_ray_tune pid=1821683)[0m [627]	train-mlogloss:2.21431	validation-mlogloss:2.21106
[36m(train_xgb_ray_tune pid=1821683)[0m [628]	train-mlogloss:2.21427	validation-mlogloss:2.21106
[36m(train_xgb_ray_tune pid=1821683)[0m [629]	train-mlogloss:2.21427	validation-mlogloss:2.21106
[36m(train_xgb_ray_tune pid=1821683)[0m [630]	train-mlogloss:2.21427	validation-mlogloss:2.21106
[36m(train_xgb_ray_tune pid=1821683)[0m [631]	train-mlogloss:2.21427	validation-mlogloss:2.21106
[36m(train_xgb_ray_tune pid=1821663)[0m [501]	train-mlogloss:1.89332	validation-mlogloss:1.86873
[36m(train_xgb_ray_tune pid=1821674)[0m [586]	train-mlogloss:1.94119	validation-mlogloss:1.90118
[36m(train_xgb_ray_tune pid=1821683)[0m [632]	train-mlogloss:2.21427	validation-mlogloss:2.21106
[36m(train_xgb_ray_tune pid=1821680)[0m [557]	train-mlogloss:1.85588	validation-mlogloss:1.84559

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:09. Total running time: 39s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             36.7657 │
│ time_total_s                 36.7657 │
│ training_iteration                 1 │
│ validation_accuracy          0.48303 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:09. Total running time: 39s
[36m(train_xgb_ray_tune pid=1821663)[0m [502]	train-mlogloss:1.89296	validation-mlogloss:1.86849
[36m(train_xgb_ray_tune pid=1821663)[0m [503]	train-mlogloss:1.89250	validation-mlogloss:1.86806
[36m(train_xgb_ray_tune pid=1821663)[0m [504]	train-mlogloss:1.89218	validation-mlogloss:1.86782
[36m(train_xgb_ray_tune pid=1821663)[0m [505]	train-mlogloss:1.89182	validation-mlogloss:1.86754
[36m(train_xgb_ray_tune pid=1821680)[0m [558]	train-mlogloss:1.85581	validation-mlogloss:1.84554
[36m(train_xgb_ray_tune pid=1821680)[0m [559]	train-mlogloss:1.85579	validation-mlogloss:1.84554
[36m(train_xgb_ray_tune pid=1821680)[0m [560]	train-mlogloss:1.85579	validation-mlogloss:1.84554
[36m(train_xgb_ray_tune pid=1821680)[0m [561]	train-mlogloss:1.85574	validation-mlogloss:1.84548
[36m(train_xgb_ray_tune pid=1821680)[0m [562]	train-mlogloss:1.85574	validation-mlogloss:1.84549
[36m(train_xgb_ray_tune pid=1821686)[0m [587]	train-mlogloss:2.20251	validation-mlogloss:2.19291
[36m(train_xgb_ray_tune pid=1821686)[0m [588]	train-mlogloss:2.20238	validation-mlogloss:2.19278
[36m(train_xgb_ray_tune pid=1821686)[0m [589]	train-mlogloss:2.20227	validation-mlogloss:2.19273
[36m(train_xgb_ray_tune pid=1821686)[0m [590]	train-mlogloss:2.20221	validation-mlogloss:2.19269
[36m(train_xgb_ray_tune pid=1821686)[0m [591]	train-mlogloss:2.20214	validation-mlogloss:2.19262
[36m(train_xgb_ray_tune pid=1821674)[0m [587]	train-mlogloss:1.94114	validation-mlogloss:1.90116
[36m(train_xgb_ray_tune pid=1821674)[0m [588]	train-mlogloss:1.94114	validation-mlogloss:1.90116
[36m(train_xgb_ray_tune pid=1821674)[0m [589]	train-mlogloss:1.94107	validation-mlogloss:1.90108
[36m(train_xgb_ray_tune pid=1821674)[0m [590]	train-mlogloss:1.94107	validation-mlogloss:1.90107
[36m(train_xgb_ray_tune pid=1821674)[0m [591]	train-mlogloss:1.94104	validation-mlogloss:1.90108
[36m(train_xgb_ray_tune pid=1821683)[0m [633]	train-mlogloss:2.21427	validation-mlogloss:2.21106
[36m(train_xgb_ray_tune pid=1821683)[0m [634]	train-mlogloss:2.21422	validation-mlogloss:2.21105
[36m(train_xgb_ray_tune pid=1821683)[0m [635]	train-mlogloss:2.21418	validation-mlogloss:2.21105
[36m(train_xgb_ray_tune pid=1821683)[0m [636]	train-mlogloss:2.21413	validation-mlogloss:2.21102
[36m(train_xgb_ray_tune pid=1821683)[0m [637]	train-mlogloss:2.21409	validation-mlogloss:2.21100
[36m(train_xgb_ray_tune pid=1821663)[0m [506]	train-mlogloss:1.89146	validation-mlogloss:1.86722
[36m(train_xgb_ray_tune pid=1821663)[0m [507]	train-mlogloss:1.89120	validation-mlogloss:1.86704
[36m(train_xgb_ray_tune pid=1821663)[0m [508]	train-mlogloss:1.89084	validation-mlogloss:1.86688
[36m(train_xgb_ray_tune pid=1821663)[0m [509]	train-mlogloss:1.89048	validation-mlogloss:1.86647
[36m(train_xgb_ray_tune pid=1821680)[0m [563]	train-mlogloss:1.85572	validation-mlogloss:1.84548
[36m(train_xgb_ray_tune pid=1821680)[0m [564]	train-mlogloss:1.85548	validation-mlogloss:1.84526
[36m(train_xgb_ray_tune pid=1821680)[0m [565]	train-mlogloss:1.85548	validation-mlogloss:1.84525
[36m(train_xgb_ray_tune pid=1821680)[0m [566]	train-mlogloss:1.85545	validation-mlogloss:1.84523
[36m(train_xgb_ray_tune pid=1821680)[0m [567]	train-mlogloss:1.85534	validation-mlogloss:1.84518
[36m(train_xgb_ray_tune pid=1821686)[0m [592]	train-mlogloss:2.20203	validation-mlogloss:2.19252
[36m(train_xgb_ray_tune pid=1821686)[0m [593]	train-mlogloss:2.20198	validation-mlogloss:2.19247
[36m(train_xgb_ray_tune pid=1821686)[0m [594]	train-mlogloss:2.20193	validation-mlogloss:2.19243
[36m(train_xgb_ray_tune pid=1821686)[0m [595]	train-mlogloss:2.20183	validation-mlogloss:2.19237
[36m(train_xgb_ray_tune pid=1821686)[0m [596]	train-mlogloss:2.20175	validation-mlogloss:2.19232
[36m(train_xgb_ray_tune pid=1821674)[0m [592]	train-mlogloss:1.94095	validation-mlogloss:1.90099
[36m(train_xgb_ray_tune pid=1821674)[0m [593]	train-mlogloss:1.94090	validation-mlogloss:1.90094
[36m(train_xgb_ray_tune pid=1821674)[0m [594]	train-mlogloss:1.94087	validation-mlogloss:1.90096
[36m(train_xgb_ray_tune pid=1821674)[0m [595]	train-mlogloss:1.94066	validation-mlogloss:1.90089
[36m(train_xgb_ray_tune pid=1821674)[0m [596]	train-mlogloss:1.94066	validation-mlogloss:1.90088
[36m(train_xgb_ray_tune pid=1821683)[0m [638]	train-mlogloss:2.21405	validation-mlogloss:2.21094
[36m(train_xgb_ray_tune pid=1821683)[0m [639]	train-mlogloss:2.21405	validation-mlogloss:2.21094
[36m(train_xgb_ray_tune pid=1821683)[0m [640]	train-mlogloss:2.21405	validation-mlogloss:2.21094
[36m(train_xgb_ray_tune pid=1821683)[0m [641]	train-mlogloss:2.21405	validation-mlogloss:2.21094
[36m(train_xgb_ray_tune pid=1821683)[0m [642]	train-mlogloss:2.21405	validation-mlogloss:2.21094
[36m(train_xgb_ray_tune pid=1821663)[0m [510]	train-mlogloss:1.89014	validation-mlogloss:1.86622
[36m(train_xgb_ray_tune pid=1821663)[0m [511]	train-mlogloss:1.88978	validation-mlogloss:1.86597
[36m(train_xgb_ray_tune pid=1821663)[0m [512]	train-mlogloss:1.88938	validation-mlogloss:1.86571
[36m(train_xgb_ray_tune pid=1821663)[0m [513]	train-mlogloss:1.88904	validation-mlogloss:1.86537
[36m(train_xgb_ray_tune pid=1821680)[0m [568]	train-mlogloss:1.85527	validation-mlogloss:1.84506
[36m(train_xgb_ray_tune pid=1821680)[0m [569]	train-mlogloss:1.85527	validation-mlogloss:1.84506
[36m(train_xgb_ray_tune pid=1821680)[0m [570]	train-mlogloss:1.85525	validation-mlogloss:1.84505
[36m(train_xgb_ray_tune pid=1821680)[0m [571]	train-mlogloss:1.85525	validation-mlogloss:1.84505
[36m(train_xgb_ray_tune pid=1821680)[0m [572]	train-mlogloss:1.85522	validation-mlogloss:1.84504
[36m(train_xgb_ray_tune pid=1821686)[0m [597]	train-mlogloss:2.20166	validation-mlogloss:2.19223
[36m(train_xgb_ray_tune pid=1821686)[0m [598]	train-mlogloss:2.20158	validation-mlogloss:2.19218
[36m(train_xgb_ray_tune pid=1821686)[0m [599]	train-mlogloss:2.20145	validation-mlogloss:2.19205
[36m(train_xgb_ray_tune pid=1821686)[0m [600]	train-mlogloss:2.20141	validation-mlogloss:2.19201
[36m(train_xgb_ray_tune pid=1821686)[0m [601]	train-mlogloss:2.20132	validation-mlogloss:2.19194
[36m(train_xgb_ray_tune pid=1821674)[0m [597]	train-mlogloss:1.94061	validation-mlogloss:1.90083
[36m(train_xgb_ray_tune pid=1821674)[0m [598]	train-mlogloss:1.94061	validation-mlogloss:1.90083
[36m(train_xgb_ray_tune pid=1821674)[0m [599]	train-mlogloss:1.94058	validation-mlogloss:1.90081
[36m(train_xgb_ray_tune pid=1821674)[0m [600]	train-mlogloss:1.94048	validation-mlogloss:1.90075
[36m(train_xgb_ray_tune pid=1821674)[0m [601]	train-mlogloss:1.94042	validation-mlogloss:1.90072
[36m(train_xgb_ray_tune pid=1821683)[0m [643]	train-mlogloss:2.21396	validation-mlogloss:2.21085
[36m(train_xgb_ray_tune pid=1821683)[0m [644]	train-mlogloss:2.21392	validation-mlogloss:2.21083
[36m(train_xgb_ray_tune pid=1821683)[0m [645]	train-mlogloss:2.21392	validation-mlogloss:2.21083
[36m(train_xgb_ray_tune pid=1821683)[0m [646]	train-mlogloss:2.21392	validation-mlogloss:2.21083
[36m(train_xgb_ray_tune pid=1821683)[0m [647]	train-mlogloss:2.21387	validation-mlogloss:2.21076
[36m(train_xgb_ray_tune pid=1821686)[0m [602]	train-mlogloss:2.20125	validation-mlogloss:2.19188
[36m(train_xgb_ray_tune pid=1821683)[0m [648]	train-mlogloss:2.21383	validation-mlogloss:2.21075
[36m(train_xgb_ray_tune pid=1821663)[0m [514]	train-mlogloss:1.88874	validation-mlogloss:1.86515
[36m(train_xgb_ray_tune pid=1821663)[0m [515]	train-mlogloss:1.88844	validation-mlogloss:1.86495
[36m(train_xgb_ray_tune pid=1821663)[0m [516]	train-mlogloss:1.88814	validation-mlogloss:1.86469
[36m(train_xgb_ray_tune pid=1821663)[0m [517]	train-mlogloss:1.88781	validation-mlogloss:1.86444
[36m(train_xgb_ray_tune pid=1821680)[0m [573]	train-mlogloss:1.85518	validation-mlogloss:1.84500
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[36m(train_xgb_ray_tune pid=1821680)[0m [575]	train-mlogloss:1.85511	validation-mlogloss:1.84493
[36m(train_xgb_ray_tune pid=1821680)[0m [576]	train-mlogloss:1.85507	validation-mlogloss:1.84486
[36m(train_xgb_ray_tune pid=1821680)[0m [577]	train-mlogloss:1.85498	validation-mlogloss:1.84484
[36m(train_xgb_ray_tune pid=1821686)[0m [603]	train-mlogloss:2.20110	validation-mlogloss:2.19177
[36m(train_xgb_ray_tune pid=1821686)[0m [604]	train-mlogloss:2.20108	validation-mlogloss:2.19176
[36m(train_xgb_ray_tune pid=1821686)[0m [605]	train-mlogloss:2.20103	validation-mlogloss:2.19173
[36m(train_xgb_ray_tune pid=1821686)[0m [606]	train-mlogloss:2.20096	validation-mlogloss:2.19169
[36m(train_xgb_ray_tune pid=1821686)[0m [607]	train-mlogloss:2.20091	validation-mlogloss:2.19164
[36m(train_xgb_ray_tune pid=1821674)[0m [602]	train-mlogloss:1.94034	validation-mlogloss:1.90061
[36m(train_xgb_ray_tune pid=1821674)[0m [603]	train-mlogloss:1.94034	validation-mlogloss:1.90061
[36m(train_xgb_ray_tune pid=1821674)[0m [604]	train-mlogloss:1.94034	validation-mlogloss:1.90061
[36m(train_xgb_ray_tune pid=1821674)[0m [605]	train-mlogloss:1.94034	validation-mlogloss:1.90061
[36m(train_xgb_ray_tune pid=1821674)[0m [606]	train-mlogloss:1.94028	validation-mlogloss:1.90053
[36m(train_xgb_ray_tune pid=1821683)[0m [649]	train-mlogloss:2.21378	validation-mlogloss:2.21071
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[36m(train_xgb_ray_tune pid=1821683)[0m [651]	train-mlogloss:2.21374	validation-mlogloss:2.21065
[36m(train_xgb_ray_tune pid=1821683)[0m [652]	train-mlogloss:2.21374	validation-mlogloss:2.21065
[36m(train_xgb_ray_tune pid=1821683)[0m [653]	train-mlogloss:2.21374	validation-mlogloss:2.21065
[36m(train_xgb_ray_tune pid=1821663)[0m [518]	train-mlogloss:1.88748	validation-mlogloss:1.86416
[36m(train_xgb_ray_tune pid=1821663)[0m [519]	train-mlogloss:1.88715	validation-mlogloss:1.86394
[36m(train_xgb_ray_tune pid=1821663)[0m [520]	train-mlogloss:1.88679	validation-mlogloss:1.86359
[36m(train_xgb_ray_tune pid=1821663)[0m [521]	train-mlogloss:1.88645	validation-mlogloss:1.86341
[36m(train_xgb_ray_tune pid=1821680)[0m [578]	train-mlogloss:1.85486	validation-mlogloss:1.84473
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[36m(train_xgb_ray_tune pid=1821680)[0m [580]	train-mlogloss:1.85474	validation-mlogloss:1.84465
[36m(train_xgb_ray_tune pid=1821680)[0m [581]	train-mlogloss:1.85472	validation-mlogloss:1.84462
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[36m(train_xgb_ray_tune pid=1821686)[0m [608]	train-mlogloss:2.20082	validation-mlogloss:2.19157
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[36m(train_xgb_ray_tune pid=1821674)[0m [607]	train-mlogloss:1.94025	validation-mlogloss:1.90046
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[36m(train_xgb_ray_tune pid=1821686)[0m [613]	train-mlogloss:2.20047	validation-mlogloss:2.19130
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[36m(train_xgb_ray_tune pid=1821674)[0m [612]	train-mlogloss:1.94019	validation-mlogloss:1.90040
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[36m(train_xgb_ray_tune pid=1821683)[0m [659]	train-mlogloss:2.21365	validation-mlogloss:2.21057
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[36m(train_xgb_ray_tune pid=1821680)[0m [588]	train-mlogloss:1.85436	validation-mlogloss:1.84425
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[36m(train_xgb_ray_tune pid=1821674)[0m [688]	train-mlogloss:1.93689	validation-mlogloss:1.89778
[36m(train_xgb_ray_tune pid=1821674)[0m [689]	train-mlogloss:1.93689	validation-mlogloss:1.89779
[36m(train_xgb_ray_tune pid=1821674)[0m [690]	train-mlogloss:1.93686	validation-mlogloss:1.89775
[36m(train_xgb_ray_tune pid=1821674)[0m [691]	train-mlogloss:1.93677	validation-mlogloss:1.89771
[36m(train_xgb_ray_tune pid=1821674)[0m [692]	train-mlogloss:1.93675	validation-mlogloss:1.89766

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:11. Total running time: 42s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s              39.063 │
│ time_total_s                  39.063 │
│ training_iteration                 1 │
│ validation_accuracy          0.36966 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:11. Total running time: 42s
[36m(train_xgb_ray_tune pid=1821663)[0m [592]	train-mlogloss:1.86725	validation-mlogloss:1.85001
[36m(train_xgb_ray_tune pid=1821663)[0m [593]	train-mlogloss:1.86699	validation-mlogloss:1.84986
[36m(train_xgb_ray_tune pid=1821663)[0m [594]	train-mlogloss:1.86670	validation-mlogloss:1.84968
[36m(train_xgb_ray_tune pid=1821663)[0m [595]	train-mlogloss:1.86650	validation-mlogloss:1.84950
[36m(train_xgb_ray_tune pid=1821680)[0m [666]	train-mlogloss:1.85182	validation-mlogloss:1.84244
[36m(train_xgb_ray_tune pid=1821680)[0m [667]	train-mlogloss:1.85175	validation-mlogloss:1.84239
[36m(train_xgb_ray_tune pid=1821680)[0m [668]	train-mlogloss:1.85167	validation-mlogloss:1.84233
[36m(train_xgb_ray_tune pid=1821680)[0m [669]	train-mlogloss:1.85167	validation-mlogloss:1.84233
[36m(train_xgb_ray_tune pid=1821680)[0m [670]	train-mlogloss:1.85162	validation-mlogloss:1.84234
[36m(train_xgb_ray_tune pid=1821674)[0m [693]	train-mlogloss:1.93675	validation-mlogloss:1.89767
[36m(train_xgb_ray_tune pid=1821674)[0m [694]	train-mlogloss:1.93675	validation-mlogloss:1.89766
[36m(train_xgb_ray_tune pid=1821674)[0m [695]	train-mlogloss:1.93668	validation-mlogloss:1.89757
[36m(train_xgb_ray_tune pid=1821674)[0m [696]	train-mlogloss:1.93668	validation-mlogloss:1.89758
[36m(train_xgb_ray_tune pid=1821674)[0m [697]	train-mlogloss:1.93665	validation-mlogloss:1.89752
[36m(train_xgb_ray_tune pid=1821663)[0m [596]	train-mlogloss:1.86631	validation-mlogloss:1.84937
[36m(train_xgb_ray_tune pid=1821663)[0m [597]	train-mlogloss:1.86608	validation-mlogloss:1.84923
[36m(train_xgb_ray_tune pid=1821663)[0m [598]	train-mlogloss:1.86586	validation-mlogloss:1.84911
[36m(train_xgb_ray_tune pid=1821663)[0m [599]	train-mlogloss:1.86569	validation-mlogloss:1.84906
[36m(train_xgb_ray_tune pid=1821663)[0m [600]	train-mlogloss:1.86544	validation-mlogloss:1.84892
[36m(train_xgb_ray_tune pid=1821680)[0m [671]	train-mlogloss:1.85158	validation-mlogloss:1.84229
[36m(train_xgb_ray_tune pid=1821680)[0m [672]	train-mlogloss:1.85158	validation-mlogloss:1.84230
[36m(train_xgb_ray_tune pid=1821680)[0m [673]	train-mlogloss:1.85158	validation-mlogloss:1.84229
[36m(train_xgb_ray_tune pid=1821680)[0m [674]	train-mlogloss:1.85155	validation-mlogloss:1.84226
[36m(train_xgb_ray_tune pid=1821680)[0m [675]	train-mlogloss:1.85153	validation-mlogloss:1.84225
[36m(train_xgb_ray_tune pid=1821674)[0m [698]	train-mlogloss:1.93663	validation-mlogloss:1.89751
[36m(train_xgb_ray_tune pid=1821674)[0m [699]	train-mlogloss:1.93660	validation-mlogloss:1.89750
[36m(train_xgb_ray_tune pid=1821674)[0m [700]	train-mlogloss:1.93657	validation-mlogloss:1.89748
[36m(train_xgb_ray_tune pid=1821674)[0m [701]	train-mlogloss:1.93651	validation-mlogloss:1.89745
[36m(train_xgb_ray_tune pid=1821674)[0m [702]	train-mlogloss:1.93651	validation-mlogloss:1.89745
[36m(train_xgb_ray_tune pid=1821680)[0m [676]	train-mlogloss:1.85151	validation-mlogloss:1.84228

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:12. Total running time: 42s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             39.3348 │
│ time_total_s                 39.3348 │
│ training_iteration                 1 │
│ validation_accuracy          0.36252 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:12. Total running time: 42s
[36m(train_xgb_ray_tune pid=1821663)[0m [601]	train-mlogloss:1.86522	validation-mlogloss:1.84882
[36m(train_xgb_ray_tune pid=1821663)[0m [602]	train-mlogloss:1.86500	validation-mlogloss:1.84864
[36m(train_xgb_ray_tune pid=1821663)[0m [603]	train-mlogloss:1.86483	validation-mlogloss:1.84854
[36m(train_xgb_ray_tune pid=1821663)[0m [604]	train-mlogloss:1.86463	validation-mlogloss:1.84842
[36m(train_xgb_ray_tune pid=1821680)[0m [677]	train-mlogloss:1.85149	validation-mlogloss:1.84224
[36m(train_xgb_ray_tune pid=1821680)[0m [678]	train-mlogloss:1.85149	validation-mlogloss:1.84224
[36m(train_xgb_ray_tune pid=1821680)[0m [679]	train-mlogloss:1.85149	validation-mlogloss:1.84224
[36m(train_xgb_ray_tune pid=1821680)[0m [680]	train-mlogloss:1.85144	validation-mlogloss:1.84221
[36m(train_xgb_ray_tune pid=1821680)[0m [681]	train-mlogloss:1.85142	validation-mlogloss:1.84220
[36m(train_xgb_ray_tune pid=1821674)[0m [703]	train-mlogloss:1.93643	validation-mlogloss:1.89734
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[36m(train_xgb_ray_tune pid=1821663)[0m [605]	train-mlogloss:1.86442	validation-mlogloss:1.84831
[36m(train_xgb_ray_tune pid=1821674)[0m [708]	train-mlogloss:1.93637	validation-mlogloss:1.89735
[36m(train_xgb_ray_tune pid=1821663)[0m [606]	train-mlogloss:1.86421	validation-mlogloss:1.84814
[36m(train_xgb_ray_tune pid=1821663)[0m [607]	train-mlogloss:1.86404	validation-mlogloss:1.84802
[36m(train_xgb_ray_tune pid=1821663)[0m [608]	train-mlogloss:1.86380	validation-mlogloss:1.84789
[36m(train_xgb_ray_tune pid=1821663)[0m [609]	train-mlogloss:1.86359	validation-mlogloss:1.84778
[36m(train_xgb_ray_tune pid=1821680)[0m [682]	train-mlogloss:1.85142	validation-mlogloss:1.84220
[36m(train_xgb_ray_tune pid=1821680)[0m [683]	train-mlogloss:1.85142	validation-mlogloss:1.84220
[36m(train_xgb_ray_tune pid=1821680)[0m [684]	train-mlogloss:1.85140	validation-mlogloss:1.84217
[36m(train_xgb_ray_tune pid=1821680)[0m [685]	train-mlogloss:1.85138	validation-mlogloss:1.84215
[36m(train_xgb_ray_tune pid=1821680)[0m [686]	train-mlogloss:1.85134	validation-mlogloss:1.84212
[36m(train_xgb_ray_tune pid=1821674)[0m [709]	train-mlogloss:1.93625	validation-mlogloss:1.89720
[36m(train_xgb_ray_tune pid=1821674)[0m [710]	train-mlogloss:1.93615	validation-mlogloss:1.89716
[36m(train_xgb_ray_tune pid=1821674)[0m [711]	train-mlogloss:1.93612	validation-mlogloss:1.89715
[36m(train_xgb_ray_tune pid=1821674)[0m [712]	train-mlogloss:1.93612	validation-mlogloss:1.89715
[36m(train_xgb_ray_tune pid=1821674)[0m [713]	train-mlogloss:1.93609	validation-mlogloss:1.89712
[36m(train_xgb_ray_tune pid=1821663)[0m [610]	train-mlogloss:1.86345	validation-mlogloss:1.84772
[36m(train_xgb_ray_tune pid=1821663)[0m [611]	train-mlogloss:1.86324	validation-mlogloss:1.84759
[36m(train_xgb_ray_tune pid=1821663)[0m [612]	train-mlogloss:1.86305	validation-mlogloss:1.84746
[36m(train_xgb_ray_tune pid=1821663)[0m [613]	train-mlogloss:1.86286	validation-mlogloss:1.84734
[36m(train_xgb_ray_tune pid=1821663)[0m [614]	train-mlogloss:1.86267	validation-mlogloss:1.84720
[36m(train_xgb_ray_tune pid=1821680)[0m [687]	train-mlogloss:1.85132	validation-mlogloss:1.84206
[36m(train_xgb_ray_tune pid=1821680)[0m [688]	train-mlogloss:1.85128	validation-mlogloss:1.84205
[36m(train_xgb_ray_tune pid=1821680)[0m [689]	train-mlogloss:1.85121	validation-mlogloss:1.84200
[36m(train_xgb_ray_tune pid=1821680)[0m [690]	train-mlogloss:1.85119	validation-mlogloss:1.84200
[36m(train_xgb_ray_tune pid=1821680)[0m [691]	train-mlogloss:1.85119	validation-mlogloss:1.84200
[36m(train_xgb_ray_tune pid=1821674)[0m [714]	train-mlogloss:1.93589	validation-mlogloss:1.89697
[36m(train_xgb_ray_tune pid=1821674)[0m [715]	train-mlogloss:1.93589	validation-mlogloss:1.89697
[36m(train_xgb_ray_tune pid=1821674)[0m [716]	train-mlogloss:1.93586	validation-mlogloss:1.89695
[36m(train_xgb_ray_tune pid=1821674)[0m [717]	train-mlogloss:1.93586	validation-mlogloss:1.89695
[36m(train_xgb_ray_tune pid=1821674)[0m [718]	train-mlogloss:1.93583	validation-mlogloss:1.89690
[36m(train_xgb_ray_tune pid=1821680)[0m [692]	train-mlogloss:1.85117	validation-mlogloss:1.84198
[36m(train_xgb_ray_tune pid=1821663)[0m [615]	train-mlogloss:1.86240	validation-mlogloss:1.84706
[36m(train_xgb_ray_tune pid=1821663)[0m [616]	train-mlogloss:1.86224	validation-mlogloss:1.84690
[36m(train_xgb_ray_tune pid=1821663)[0m [617]	train-mlogloss:1.86203	validation-mlogloss:1.84674
[36m(train_xgb_ray_tune pid=1821663)[0m [618]	train-mlogloss:1.86180	validation-mlogloss:1.84667
[36m(train_xgb_ray_tune pid=1821680)[0m [693]	train-mlogloss:1.85110	validation-mlogloss:1.84186
[36m(train_xgb_ray_tune pid=1821680)[0m [694]	train-mlogloss:1.85106	validation-mlogloss:1.84184
[36m(train_xgb_ray_tune pid=1821680)[0m [695]	train-mlogloss:1.85106	validation-mlogloss:1.84184
[36m(train_xgb_ray_tune pid=1821680)[0m [696]	train-mlogloss:1.85104	validation-mlogloss:1.84179
[36m(train_xgb_ray_tune pid=1821680)[0m [697]	train-mlogloss:1.85102	validation-mlogloss:1.84175
[36m(train_xgb_ray_tune pid=1821674)[0m [719]	train-mlogloss:1.93580	validation-mlogloss:1.89686
[36m(train_xgb_ray_tune pid=1821674)[0m [720]	train-mlogloss:1.93571	validation-mlogloss:1.89675
[36m(train_xgb_ray_tune pid=1821674)[0m [721]	train-mlogloss:1.93571	validation-mlogloss:1.89675
[36m(train_xgb_ray_tune pid=1821674)[0m [722]	train-mlogloss:1.93546	validation-mlogloss:1.89646
[36m(train_xgb_ray_tune pid=1821674)[0m [723]	train-mlogloss:1.93546	validation-mlogloss:1.89646
[36m(train_xgb_ray_tune pid=1821663)[0m [619]	train-mlogloss:1.86165	validation-mlogloss:1.84661
[36m(train_xgb_ray_tune pid=1821663)[0m [620]	train-mlogloss:1.86143	validation-mlogloss:1.84646
[36m(train_xgb_ray_tune pid=1821663)[0m [621]	train-mlogloss:1.86125	validation-mlogloss:1.84629
[36m(train_xgb_ray_tune pid=1821663)[0m [622]	train-mlogloss:1.86107	validation-mlogloss:1.84620
[36m(train_xgb_ray_tune pid=1821663)[0m [623]	train-mlogloss:1.86084	validation-mlogloss:1.84612
[36m(train_xgb_ray_tune pid=1821680)[0m [698]	train-mlogloss:1.85100	validation-mlogloss:1.84172
[36m(train_xgb_ray_tune pid=1821680)[0m [699]	train-mlogloss:1.85089	validation-mlogloss:1.84166
[36m(train_xgb_ray_tune pid=1821680)[0m [700]	train-mlogloss:1.85089	validation-mlogloss:1.84166
[36m(train_xgb_ray_tune pid=1821680)[0m [701]	train-mlogloss:1.85087	validation-mlogloss:1.84166
[36m(train_xgb_ray_tune pid=1821680)[0m [702]	train-mlogloss:1.85085	validation-mlogloss:1.84164
[36m(train_xgb_ray_tune pid=1821674)[0m [724]	train-mlogloss:1.93541	validation-mlogloss:1.89642
[36m(train_xgb_ray_tune pid=1821674)[0m [725]	train-mlogloss:1.93541	validation-mlogloss:1.89642
[36m(train_xgb_ray_tune pid=1821674)[0m [726]	train-mlogloss:1.93535	validation-mlogloss:1.89639
[36m(train_xgb_ray_tune pid=1821674)[0m [727]	train-mlogloss:1.93523	validation-mlogloss:1.89637
[36m(train_xgb_ray_tune pid=1821674)[0m [728]	train-mlogloss:1.93520	validation-mlogloss:1.89628
[36m(train_xgb_ray_tune pid=1821663)[0m [624]	train-mlogloss:1.86063	validation-mlogloss:1.84600
[36m(train_xgb_ray_tune pid=1821663)[0m [625]	train-mlogloss:1.86039	validation-mlogloss:1.84578
[36m(train_xgb_ray_tune pid=1821663)[0m [626]	train-mlogloss:1.86020	validation-mlogloss:1.84567
[36m(train_xgb_ray_tune pid=1821663)[0m [627]	train-mlogloss:1.86006	validation-mlogloss:1.84561
[36m(train_xgb_ray_tune pid=1821680)[0m [703]	train-mlogloss:1.85083	validation-mlogloss:1.84163
[36m(train_xgb_ray_tune pid=1821680)[0m [704]	train-mlogloss:1.85083	validation-mlogloss:1.84163
[36m(train_xgb_ray_tune pid=1821680)[0m [705]	train-mlogloss:1.85079	validation-mlogloss:1.84154
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[36m(train_xgb_ray_tune pid=1821680)[0m [707]	train-mlogloss:1.85076	validation-mlogloss:1.84153
[36m(train_xgb_ray_tune pid=1821674)[0m [729]	train-mlogloss:1.93513	validation-mlogloss:1.89623
[36m(train_xgb_ray_tune pid=1821674)[0m [730]	train-mlogloss:1.93513	validation-mlogloss:1.89623
[36m(train_xgb_ray_tune pid=1821674)[0m [731]	train-mlogloss:1.93504	validation-mlogloss:1.89615
[36m(train_xgb_ray_tune pid=1821674)[0m [732]	train-mlogloss:1.93504	validation-mlogloss:1.89616
[36m(train_xgb_ray_tune pid=1821674)[0m [733]	train-mlogloss:1.93498	validation-mlogloss:1.89611
[36m(train_xgb_ray_tune pid=1821663)[0m [628]	train-mlogloss:1.85989	validation-mlogloss:1.84556
[36m(train_xgb_ray_tune pid=1821663)[0m [629]	train-mlogloss:1.85967	validation-mlogloss:1.84546
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[36m(train_xgb_ray_tune pid=1821680)[0m [708]	train-mlogloss:1.85074	validation-mlogloss:1.84153
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[36m(train_xgb_ray_tune pid=1821674)[0m [734]	train-mlogloss:1.93492	validation-mlogloss:1.89612
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[36m(train_xgb_ray_tune pid=1821663)[0m [633]	train-mlogloss:1.85896	validation-mlogloss:1.84495
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[36m(train_xgb_ray_tune pid=1821680)[0m [714]	train-mlogloss:1.85063	validation-mlogloss:1.84146
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[36m(train_xgb_ray_tune pid=1821680)[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=1821680)[0m   _log_deprecation_warning([32m [repeated 4x across cluster][0m
[36m(train_xgb_ray_tune pid=1821663)[0m [653]	train-mlogloss:1.85554	validation-mlogloss:1.84269
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[36m(train_xgb_ray_tune pid=1821674)[0m [770]	train-mlogloss:1.93377	validation-mlogloss:1.89521

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:13. Total running time: 43s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             40.9008 │
│ time_total_s                 40.9008 │
│ training_iteration                 1 │
│ validation_accuracy          0.50069 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:13. Total running time: 43s
[36m(train_xgb_ray_tune pid=1821663)[0m [662]	train-mlogloss:1.85420	validation-mlogloss:1.84189
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2025-11-06 21:43:16,162	INFO tune.py:1009 -- Wrote the latest version of all result files and experiment state to '/mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_M/case_M_XGB_acc_17_classes/XGBoost_hyperparameters_tuning' in 0.0083s.
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[36m(train_xgb_ray_tune pid=1821663)[0m [710]	train-mlogloss:1.84770	validation-mlogloss:1.83779

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:14. Total running time: 44s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             41.7507 │
│ time_total_s                 41.7507 │
│ training_iteration                 1 │
│ validation_accuracy          0.48739 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:14. Total running time: 44s
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[36m(train_xgb_ray_tune pid=1821663)[0m [736]	train-mlogloss:1.84492	validation-mlogloss:1.83619
[36m(train_xgb_ray_tune pid=1821663)[0m [737]	train-mlogloss:1.84484	validation-mlogloss:1.83616
[36m(train_xgb_ray_tune pid=1821663)[0m [738]	train-mlogloss:1.84464	validation-mlogloss:1.83597
[36m(train_xgb_ray_tune pid=1821663)[0m [739]	train-mlogloss:1.84456	validation-mlogloss:1.83590
[36m(train_xgb_ray_tune pid=1821663)[0m [740]	train-mlogloss:1.84446	validation-mlogloss:1.83584
[36m(train_xgb_ray_tune pid=1821663)[0m [741]	train-mlogloss:1.84439	validation-mlogloss:1.83585
[36m(train_xgb_ray_tune pid=1821663)[0m [742]	train-mlogloss:1.84422	validation-mlogloss:1.83573
[36m(train_xgb_ray_tune pid=1821663)[0m [743]	train-mlogloss:1.84415	validation-mlogloss:1.83565
[36m(train_xgb_ray_tune pid=1821663)[0m [744]	train-mlogloss:1.84408	validation-mlogloss:1.83564
[36m(train_xgb_ray_tune pid=1821663)[0m [745]	train-mlogloss:1.84398	validation-mlogloss:1.83555
[36m(train_xgb_ray_tune pid=1821663)[0m [746]	train-mlogloss:1.84388	validation-mlogloss:1.83550
[36m(train_xgb_ray_tune pid=1821663)[0m [747]	train-mlogloss:1.84384	validation-mlogloss:1.83545
[36m(train_xgb_ray_tune pid=1821663)[0m [748]	train-mlogloss:1.84368	validation-mlogloss:1.83535
[36m(train_xgb_ray_tune pid=1821663)[0m [749]	train-mlogloss:1.84362	validation-mlogloss:1.83534
[36m(train_xgb_ray_tune pid=1821663)[0m [750]	train-mlogloss:1.84354	validation-mlogloss:1.83527
[36m(train_xgb_ray_tune pid=1821663)[0m [751]	train-mlogloss:1.84350	validation-mlogloss:1.83520
[36m(train_xgb_ray_tune pid=1821663)[0m [752]	train-mlogloss:1.84341	validation-mlogloss:1.83512
[36m(train_xgb_ray_tune pid=1821663)[0m [753]	train-mlogloss:1.84325	validation-mlogloss:1.83499

Trial trial_1cb55 finished iteration 1 at 2025-11-06 21:43:16. Total running time: 46s
╭──────────────────────────────────────╮
│ Trial trial_1cb55 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             43.3743 │
│ time_total_s                 43.3743 │
│ training_iteration                 1 │
│ validation_accuracy          0.50208 │
╰──────────────────────────────────────╯

Trial trial_1cb55 completed after 1 iterations at 2025-11-06 21:43:16. Total running time: 46s

Trial status: 20 TERMINATED
Current time: 2025-11-06 21:43:16. Total running time: 46s
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_1cb55    TERMINATED                 754             3        0.00708953      0.572333             0.571419   23.2246                    63       1.1888        43.7925              5319        1           43.3743                0.502085  │
│ trial_1cb55    TERMINATED                 271             3        0.0190181       0.628713             0.644453    5.39879                  116      50.2256        13.9432              1016        1           29.3636                0.498908  │
│ trial_1cb55    TERMINATED                 420             2        0.0114507       0.674775             0.784948   16.1511                   138       1.94599       25.0934              4910        1           33.0308                0.504268  │
│ trial_1cb55    TERMINATED                 315             3        0.0185528       0.750404             0.640788   16.2339                   132       5.66557      699.33                4881        1           31.0931                0.470121  │
│ trial_1cb55    TERMINATED                 671             3        0.00656652      0.840697             0.632676   20.0238                   175     146.659         14.3622              1766        1           39.063                 0.369664  │
│ trial_1cb55    TERMINATED                 261             3        0.0079232       0.695251             0.679307   14.9999                   149       3.29567      351.316                773        1           28.3228                0.438555  │
│ trial_1cb55    TERMINATED                 448             3        0.015063        0.548208             0.634636   15.8129                   114     413.067          8.48831             9642        1           11.826                 0.12428   │
│ trial_1cb55    TERMINATED                 407             3        0.00839124      0.623236             0.585971   14.2771                   141      99.7363        36.3844              8847        1           31.9777                0.375223  │
│ trial_1cb55    TERMINATED                 533             2        0.0159374       0.671786             0.754294   17.6281                   107      26.8082       366.449               9665        1           35.2506                0.458805  │
│ trial_1cb55    TERMINATED                 595             3        0.012221        0.64406              0.601166   27.5846                   147      21.8054         8.5704              3985        1           36.7657                0.483026  │
│ trial_1cb55    TERMINATED                 259             2        0.0162511       0.636471             0.73363    19.5734                    84     200.438        106.568               5001        1           22.1076                0.268017  │
│ trial_1cb55    TERMINATED                 226             2        0.0109774       0.771305             0.792725   22.4585                    91      46.6636        52.4725              1090        1           23.7949                0.460989  │
│ trial_1cb55    TERMINATED                 345             2        0.00624441      0.839356             0.5687     19.6342                   156       8.55672       25.9994              7299        1           30.3986                0.486401  │
│ trial_1cb55    TERMINATED                 545             3        0.0194414       0.759991             0.501904    6.50189                   61     860.959        756.382               6475        1            5.32095               0.0639269 │
│ trial_1cb55    TERMINATED                 672             3        0.018443        0.848987             0.786135   16.1061                   189     250.383        109.728               3866        1           31.5358                0.307921  │
│ trial_1cb55    TERMINATED                 733             3        0.0143482       0.737584             0.823754   28.6324                   109      71.6413       494.079               1372        1           39.3348                0.362517  │
│ trial_1cb55    TERMINATED                 720             2        0.015517        0.706389             0.597535   28.2665                   146     322.046         42.6044              9545        1           25.243                 0.165773  │
│ trial_1cb55    TERMINATED                 718             3        0.00997422      0.696604             0.679719   29.37                      83       6.04013       21.9013              3622        1           40.9008                0.500695  │
│ trial_1cb55    TERMINATED                 386             2        0.0118711       0.536963             0.683892   14.8021                    69     231.759         24.4769              6579        1           28.2754                0.200715  │
│ trial_1cb55    TERMINATED                 799             2        0.00999408      0.501305             0.843765   28.8012                   121       6.57783        5.49196             4707        1           41.7507                0.487393  │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Mejores hiperparámetros XGBoost: {'num_boost_round': 420, 'max_depth': 2, 'learning_rate': 0.011450661425445114, 'subsample': 0.6747751033782248, 'colsample_bytree': 0.7849481342435494, 'gamma': 16.15110900148842, 'min_child_weight': 138, 'reg_alpha': 1.9459863194560743, 'reg_lambda': 25.093438623126175, 'random_state': 4910}
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[413]	train-mlogloss:1.83535	validation-mlogloss:1.82350
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[415]	train-mlogloss:1.83440	validation-mlogloss:1.82288
[416]	train-mlogloss:1.83394	validation-mlogloss:1.82255
[417]	train-mlogloss:1.83347	validation-mlogloss:1.82214
[418]	train-mlogloss:1.83301	validation-mlogloss:1.82188
[419]	train-mlogloss:1.83252	validation-mlogloss:1.82159
Saved model to disk.
[36m(train_xgb_ray_tune pid=1821663)[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=1821663)[0m   _log_deprecation_warning([32m [repeated 2x across cluster][0m
2025-11-06 21:43:34.680119: 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 21:43:34.691345: 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 00:00:1762461814.704278 1823822 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762461814.708321 1823822 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762461814.718023 1823822 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461814.718041 1823822 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461814.718043 1823822 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461814.718045 1823822 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:43:34.721280: 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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[343]	train-mlogloss:1.87854	validation-mlogloss:1.85350
[344]	train-mlogloss:1.87779	validation-mlogloss:1.85296
[345]	train-mlogloss:1.87698	validation-mlogloss:1.85244
[346]	train-mlogloss:1.87616	validation-mlogloss:1.85183
[347]	train-mlogloss:1.87552	validation-mlogloss:1.85145
[348]	train-mlogloss:1.87477	validation-mlogloss:1.85084
[349]	train-mlogloss:1.87411	validation-mlogloss:1.85021
[350]	train-mlogloss:1.87341	validation-mlogloss:1.84976
[351]	train-mlogloss:1.87268	validation-mlogloss:1.84916
[352]	train-mlogloss:1.87200	validation-mlogloss:1.84871
[353]	train-mlogloss:1.87124	validation-mlogloss:1.84832
[354]	train-mlogloss:1.87050	validation-mlogloss:1.84802
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[357]	train-mlogloss:1.86853	validation-mlogloss:1.84661
[358]	train-mlogloss:1.86788	validation-mlogloss:1.84617
[359]	train-mlogloss:1.86725	validation-mlogloss:1.84566
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[370]	train-mlogloss:1.86002	validation-mlogloss:1.84041
[371]	train-mlogloss:1.85934	validation-mlogloss:1.83980
[372]	train-mlogloss:1.85878	validation-mlogloss:1.83937
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[385]	train-mlogloss:1.85065	validation-mlogloss:1.83385
[386]	train-mlogloss:1.85008	validation-mlogloss:1.83333
[387]	train-mlogloss:1.84957	validation-mlogloss:1.83302
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[389]	train-mlogloss:1.84847	validation-mlogloss:1.83235
[390]	train-mlogloss:1.84792	validation-mlogloss:1.83207
[391]	train-mlogloss:1.84740	validation-mlogloss:1.83172
[392]	train-mlogloss:1.84686	validation-mlogloss:1.83123
[393]	train-mlogloss:1.84635	validation-mlogloss:1.83094
[394]	train-mlogloss:1.84581	validation-mlogloss:1.83065
[395]	train-mlogloss:1.84519	validation-mlogloss:1.83033
[396]	train-mlogloss:1.84453	validation-mlogloss:1.82987
[397]	train-mlogloss:1.84399	validation-mlogloss:1.82951
[398]	train-mlogloss:1.84354	validation-mlogloss:1.82913
[399]	train-mlogloss:1.84296	validation-mlogloss:1.82873
[400]	train-mlogloss:1.84240	validation-mlogloss:1.82851
[401]	train-mlogloss:1.84186	validation-mlogloss:1.82825
[402]	train-mlogloss:1.84125	validation-mlogloss:1.82777
[403]	train-mlogloss:1.84071	validation-mlogloss:1.82740
[404]	train-mlogloss:1.84015	validation-mlogloss:1.82699
[405]	train-mlogloss:1.83967	validation-mlogloss:1.82667
[406]	train-mlogloss:1.83914	validation-mlogloss:1.82633
[407]	train-mlogloss:1.83858	validation-mlogloss:1.82603
[408]	train-mlogloss:1.83799	validation-mlogloss:1.82573
[409]	train-mlogloss:1.83747	validation-mlogloss:1.82531
[410]	train-mlogloss:1.83696	validation-mlogloss:1.82505
[411]	train-mlogloss:1.83646	validation-mlogloss:1.82468
[412]	train-mlogloss:1.83593	validation-mlogloss:1.82429
[413]	train-mlogloss:1.83540	validation-mlogloss:1.82406
[414]	train-mlogloss:1.83489	validation-mlogloss:1.82377
[415]	train-mlogloss:1.83438	validation-mlogloss:1.82340
[416]	train-mlogloss:1.83386	validation-mlogloss:1.82318
[417]	train-mlogloss:1.83343	validation-mlogloss:1.82292
[418]	train-mlogloss:1.83294	validation-mlogloss:1.82249
[419]	train-mlogloss:1.83254	validation-mlogloss:1.82219
Saved model to disk.
2025-11-06 21:43:56.876142: 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 21:43:56.887202: 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 00:00:1762461836.900366 1824210 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762461836.904584 1824210 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762461836.914884 1824210 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461836.914903 1824210 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461836.914913 1824210 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461836.914915 1824210 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:43:56.917933: 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:2.68543	validation-mlogloss:2.68406
[3]	train-mlogloss:2.67804	validation-mlogloss:2.67625
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[6]	train-mlogloss:2.65595	validation-mlogloss:2.65198
[7]	train-mlogloss:2.64906	validation-mlogloss:2.64469
[8]	train-mlogloss:2.64232	validation-mlogloss:2.63742
[9]	train-mlogloss:2.63560	validation-mlogloss:2.63004
[10]	train-mlogloss:2.62845	validation-mlogloss:2.62215
[11]	train-mlogloss:2.62168	validation-mlogloss:2.61447
[12]	train-mlogloss:2.61463	validation-mlogloss:2.60680
[13]	train-mlogloss:2.60807	validation-mlogloss:2.59949
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[16]	train-mlogloss:2.58833	validation-mlogloss:2.57772
[17]	train-mlogloss:2.58202	validation-mlogloss:2.57100
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[19]	train-mlogloss:2.56962	validation-mlogloss:2.55765
[20]	train-mlogloss:2.56373	validation-mlogloss:2.55150
[21]	train-mlogloss:2.55764	validation-mlogloss:2.54458
[22]	train-mlogloss:2.55178	validation-mlogloss:2.53846
[23]	train-mlogloss:2.54606	validation-mlogloss:2.53245
[24]	train-mlogloss:2.54025	validation-mlogloss:2.52629
[25]	train-mlogloss:2.53442	validation-mlogloss:2.51986
[26]	train-mlogloss:2.52892	validation-mlogloss:2.51399
[27]	train-mlogloss:2.52342	validation-mlogloss:2.50815
[28]	train-mlogloss:2.51791	validation-mlogloss:2.50217
[29]	train-mlogloss:2.51247	validation-mlogloss:2.49614
[30]	train-mlogloss:2.50724	validation-mlogloss:2.49040
[31]	train-mlogloss:2.50177	validation-mlogloss:2.48452
[32]	train-mlogloss:2.49618	validation-mlogloss:2.47814
[33]	train-mlogloss:2.49089	validation-mlogloss:2.47228
[34]	train-mlogloss:2.48580	validation-mlogloss:2.46653
[35]	train-mlogloss:2.48079	validation-mlogloss:2.46111
[36]	train-mlogloss:2.47583	validation-mlogloss:2.45562
[37]	train-mlogloss:2.47099	validation-mlogloss:2.45042
[38]	train-mlogloss:2.46558	validation-mlogloss:2.44385
[39]	train-mlogloss:2.46069	validation-mlogloss:2.43866
[40]	train-mlogloss:2.45570	validation-mlogloss:2.43329
[41]	train-mlogloss:2.45117	validation-mlogloss:2.42839
[42]	train-mlogloss:2.44627	validation-mlogloss:2.42305
[43]	train-mlogloss:2.44158	validation-mlogloss:2.41797
[44]	train-mlogloss:2.43693	validation-mlogloss:2.41301
[45]	train-mlogloss:2.43230	validation-mlogloss:2.40798
[46]	train-mlogloss:2.42772	validation-mlogloss:2.40288
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[48]	train-mlogloss:2.41914	validation-mlogloss:2.39374
[49]	train-mlogloss:2.41475	validation-mlogloss:2.38874
[50]	train-mlogloss:2.41048	validation-mlogloss:2.38434
[51]	train-mlogloss:2.40574	validation-mlogloss:2.37927
[52]	train-mlogloss:2.40134	validation-mlogloss:2.37422
[53]	train-mlogloss:2.39696	validation-mlogloss:2.36932
[54]	train-mlogloss:2.39255	validation-mlogloss:2.36455
[55]	train-mlogloss:2.38860	validation-mlogloss:2.36020
[56]	train-mlogloss:2.38434	validation-mlogloss:2.35554
[57]	train-mlogloss:2.38000	validation-mlogloss:2.35071
[58]	train-mlogloss:2.37577	validation-mlogloss:2.34558
[59]	train-mlogloss:2.37148	validation-mlogloss:2.34072
[60]	train-mlogloss:2.36719	validation-mlogloss:2.33585
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[62]	train-mlogloss:2.35930	validation-mlogloss:2.32743
[63]	train-mlogloss:2.35541	validation-mlogloss:2.32346
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[65]	train-mlogloss:2.34757	validation-mlogloss:2.31497
[66]	train-mlogloss:2.34349	validation-mlogloss:2.31055
[67]	train-mlogloss:2.33975	validation-mlogloss:2.30660
[68]	train-mlogloss:2.33602	validation-mlogloss:2.30260
[69]	train-mlogloss:2.33223	validation-mlogloss:2.29835
[70]	train-mlogloss:2.32842	validation-mlogloss:2.29417
[71]	train-mlogloss:2.32473	validation-mlogloss:2.29031
[72]	train-mlogloss:2.32125	validation-mlogloss:2.28651
[73]	train-mlogloss:2.31759	validation-mlogloss:2.28264
[74]	train-mlogloss:2.31371	validation-mlogloss:2.27814
[75]	train-mlogloss:2.31000	validation-mlogloss:2.27401
[76]	train-mlogloss:2.30628	validation-mlogloss:2.26991
[77]	train-mlogloss:2.30277	validation-mlogloss:2.26603
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[83]	train-mlogloss:2.28202	validation-mlogloss:2.24337
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[104]	train-mlogloss:2.21886	validation-mlogloss:2.17519
[105]	train-mlogloss:2.21633	validation-mlogloss:2.17283
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[109]	train-mlogloss:2.20556	validation-mlogloss:2.16144
[110]	train-mlogloss:2.20298	validation-mlogloss:2.15858
[111]	train-mlogloss:2.20036	validation-mlogloss:2.15596
[112]	train-mlogloss:2.19773	validation-mlogloss:2.15327
[113]	train-mlogloss:2.19526	validation-mlogloss:2.15082
[114]	train-mlogloss:2.19262	validation-mlogloss:2.14802
[115]	train-mlogloss:2.19021	validation-mlogloss:2.14564
[116]	train-mlogloss:2.18767	validation-mlogloss:2.14273
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[132]	train-mlogloss:2.14978	validation-mlogloss:2.10328
[133]	train-mlogloss:2.14755	validation-mlogloss:2.10117
[134]	train-mlogloss:2.14530	validation-mlogloss:2.09891
[135]	train-mlogloss:2.14323	validation-mlogloss:2.09699
[136]	train-mlogloss:2.14104	validation-mlogloss:2.09459
[137]	train-mlogloss:2.13906	validation-mlogloss:2.09258
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[139]	train-mlogloss:2.13498	validation-mlogloss:2.08850
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[144]	train-mlogloss:2.12475	validation-mlogloss:2.07874
[145]	train-mlogloss:2.12288	validation-mlogloss:2.07698
[146]	train-mlogloss:2.12072	validation-mlogloss:2.07496
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[149]	train-mlogloss:2.11473	validation-mlogloss:2.06881
[150]	train-mlogloss:2.11266	validation-mlogloss:2.06680
[151]	train-mlogloss:2.11073	validation-mlogloss:2.06488
[152]	train-mlogloss:2.10888	validation-mlogloss:2.06301
[153]	train-mlogloss:2.10688	validation-mlogloss:2.06117
[154]	train-mlogloss:2.10498	validation-mlogloss:2.05923
[155]	train-mlogloss:2.10308	validation-mlogloss:2.05743
[156]	train-mlogloss:2.10130	validation-mlogloss:2.05570
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[160]	train-mlogloss:2.09367	validation-mlogloss:2.04776
[161]	train-mlogloss:2.09187	validation-mlogloss:2.04581
[162]	train-mlogloss:2.09011	validation-mlogloss:2.04408
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[164]	train-mlogloss:2.08642	validation-mlogloss:2.04065
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[173]	train-mlogloss:2.07079	validation-mlogloss:2.02527
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[191]	train-mlogloss:2.04140	validation-mlogloss:1.99631
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[193]	train-mlogloss:2.03826	validation-mlogloss:1.99345
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[195]	train-mlogloss:2.03517	validation-mlogloss:1.99087
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[197]	train-mlogloss:2.03228	validation-mlogloss:1.98811
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[271]	train-mlogloss:1.94123	validation-mlogloss:1.90521
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[370]	train-mlogloss:1.85920	validation-mlogloss:1.84145
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[373]	train-mlogloss:1.85723	validation-mlogloss:1.84003
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[385]	train-mlogloss:1.84990	validation-mlogloss:1.83491
[386]	train-mlogloss:1.84928	validation-mlogloss:1.83433
[387]	train-mlogloss:1.84861	validation-mlogloss:1.83378
[388]	train-mlogloss:1.84799	validation-mlogloss:1.83341
[389]	train-mlogloss:1.84739	validation-mlogloss:1.83288
[390]	train-mlogloss:1.84685	validation-mlogloss:1.83260
[391]	train-mlogloss:1.84637	validation-mlogloss:1.83233
[392]	train-mlogloss:1.84579	validation-mlogloss:1.83188
[393]	train-mlogloss:1.84513	validation-mlogloss:1.83126
[394]	train-mlogloss:1.84453	validation-mlogloss:1.83081
[395]	train-mlogloss:1.84397	validation-mlogloss:1.83045
[396]	train-mlogloss:1.84344	validation-mlogloss:1.83005
[397]	train-mlogloss:1.84292	validation-mlogloss:1.82974
[398]	train-mlogloss:1.84236	validation-mlogloss:1.82930
[399]	train-mlogloss:1.84181	validation-mlogloss:1.82887
[400]	train-mlogloss:1.84123	validation-mlogloss:1.82846
[401]	train-mlogloss:1.84076	validation-mlogloss:1.82825
[402]	train-mlogloss:1.84021	validation-mlogloss:1.82773
[403]	train-mlogloss:1.83960	validation-mlogloss:1.82731
[404]	train-mlogloss:1.83911	validation-mlogloss:1.82699
[405]	train-mlogloss:1.83859	validation-mlogloss:1.82673
[406]	train-mlogloss:1.83814	validation-mlogloss:1.82644
[407]	train-mlogloss:1.83756	validation-mlogloss:1.82609
[408]	train-mlogloss:1.83701	validation-mlogloss:1.82578
[409]	train-mlogloss:1.83641	validation-mlogloss:1.82546
[410]	train-mlogloss:1.83586	validation-mlogloss:1.82505
[411]	train-mlogloss:1.83537	validation-mlogloss:1.82474
[412]	train-mlogloss:1.83490	validation-mlogloss:1.82440
[413]	train-mlogloss:1.83446	validation-mlogloss:1.82402
[414]	train-mlogloss:1.83396	validation-mlogloss:1.82356
[415]	train-mlogloss:1.83351	validation-mlogloss:1.82306
[416]	train-mlogloss:1.83302	validation-mlogloss:1.82265
[417]	train-mlogloss:1.83251	validation-mlogloss:1.82236
[418]	train-mlogloss:1.83195	validation-mlogloss:1.82185
[419]	train-mlogloss:1.83142	validation-mlogloss:1.82154
Saved model to disk.
2025-11-06 21:44:19.017913: 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 21:44:19.029115: 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 00:00:1762461859.042403 1824595 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762461859.046463 1824595 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762461859.056559 1824595 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461859.056579 1824595 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461859.056581 1824595 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461859.056584 1824595 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:44:19.059590: 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:2.69311	validation-mlogloss:2.69230
[2]	train-mlogloss:2.68575	validation-mlogloss:2.68465
[3]	train-mlogloss:2.67837	validation-mlogloss:2.67672
[4]	train-mlogloss:2.67086	validation-mlogloss:2.66859
[5]	train-mlogloss:2.66363	validation-mlogloss:2.66069
[6]	train-mlogloss:2.65680	validation-mlogloss:2.65344
[7]	train-mlogloss:2.64971	validation-mlogloss:2.64554
[8]	train-mlogloss:2.64240	validation-mlogloss:2.63758
[9]	train-mlogloss:2.63503	validation-mlogloss:2.62937
[10]	train-mlogloss:2.62846	validation-mlogloss:2.62231
[11]	train-mlogloss:2.62142	validation-mlogloss:2.61462
[12]	train-mlogloss:2.61463	validation-mlogloss:2.60735
[13]	train-mlogloss:2.60787	validation-mlogloss:2.60006
[14]	train-mlogloss:2.60139	validation-mlogloss:2.59321
[15]	train-mlogloss:2.59502	validation-mlogloss:2.58628
[16]	train-mlogloss:2.58850	validation-mlogloss:2.57923
[17]	train-mlogloss:2.58213	validation-mlogloss:2.57199
[18]	train-mlogloss:2.57604	validation-mlogloss:2.56552
[19]	train-mlogloss:2.57012	validation-mlogloss:2.55953
[20]	train-mlogloss:2.56420	validation-mlogloss:2.55325
[21]	train-mlogloss:2.55830	validation-mlogloss:2.54712
[22]	train-mlogloss:2.55238	validation-mlogloss:2.54072
[23]	train-mlogloss:2.54644	validation-mlogloss:2.53402
[24]	train-mlogloss:2.54036	validation-mlogloss:2.52702
[25]	train-mlogloss:2.53428	validation-mlogloss:2.52015
[26]	train-mlogloss:2.52856	validation-mlogloss:2.51377
[27]	train-mlogloss:2.52295	validation-mlogloss:2.50761
[28]	train-mlogloss:2.51723	validation-mlogloss:2.50111
[29]	train-mlogloss:2.51178	validation-mlogloss:2.49523
[30]	train-mlogloss:2.50640	validation-mlogloss:2.48941
[31]	train-mlogloss:2.50095	validation-mlogloss:2.48352
[32]	train-mlogloss:2.49533	validation-mlogloss:2.47721
[33]	train-mlogloss:2.49008	validation-mlogloss:2.47129
[34]	train-mlogloss:2.48490	validation-mlogloss:2.46527
[35]	train-mlogloss:2.47968	validation-mlogloss:2.45968
[36]	train-mlogloss:2.47458	validation-mlogloss:2.45379
[37]	train-mlogloss:2.46965	validation-mlogloss:2.44837
[38]	train-mlogloss:2.46491	validation-mlogloss:2.44361
[39]	train-mlogloss:2.45983	validation-mlogloss:2.43791
[40]	train-mlogloss:2.45521	validation-mlogloss:2.43292
[41]	train-mlogloss:2.45043	validation-mlogloss:2.42772
[42]	train-mlogloss:2.44545	validation-mlogloss:2.42204
[43]	train-mlogloss:2.44075	validation-mlogloss:2.41710
[44]	train-mlogloss:2.43625	validation-mlogloss:2.41247
[45]	train-mlogloss:2.43127	validation-mlogloss:2.40655
[46]	train-mlogloss:2.42673	validation-mlogloss:2.40151
[47]	train-mlogloss:2.42200	validation-mlogloss:2.39628
[48]	train-mlogloss:2.41766	validation-mlogloss:2.39177
[49]	train-mlogloss:2.41327	validation-mlogloss:2.38706
[50]	train-mlogloss:2.40873	validation-mlogloss:2.38216
[51]	train-mlogloss:2.40425	validation-mlogloss:2.37694
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[352]	train-mlogloss:1.87126	validation-mlogloss:1.84867
[353]	train-mlogloss:1.87044	validation-mlogloss:1.84803
[354]	train-mlogloss:1.86980	validation-mlogloss:1.84765
[355]	train-mlogloss:1.86907	validation-mlogloss:1.84700
[356]	train-mlogloss:1.86837	validation-mlogloss:1.84651
[357]	train-mlogloss:1.86769	validation-mlogloss:1.84596
[358]	train-mlogloss:1.86697	validation-mlogloss:1.84539
[359]	train-mlogloss:1.86624	validation-mlogloss:1.84508
[360]	train-mlogloss:1.86560	validation-mlogloss:1.84450
[361]	train-mlogloss:1.86501	validation-mlogloss:1.84401
[362]	train-mlogloss:1.86429	validation-mlogloss:1.84350
[363]	train-mlogloss:1.86359	validation-mlogloss:1.84289
[364]	train-mlogloss:1.86287	validation-mlogloss:1.84233
[365]	train-mlogloss:1.86224	validation-mlogloss:1.84188
[366]	train-mlogloss:1.86150	validation-mlogloss:1.84142
[367]	train-mlogloss:1.86085	validation-mlogloss:1.84108
[368]	train-mlogloss:1.86020	validation-mlogloss:1.84062
[369]	train-mlogloss:1.85954	validation-mlogloss:1.84020
[370]	train-mlogloss:1.85883	validation-mlogloss:1.83973
[371]	train-mlogloss:1.85825	validation-mlogloss:1.83929
[372]	train-mlogloss:1.85753	validation-mlogloss:1.83881
[373]	train-mlogloss:1.85694	validation-mlogloss:1.83841
[374]	train-mlogloss:1.85629	validation-mlogloss:1.83802
[375]	train-mlogloss:1.85581	validation-mlogloss:1.83766
[376]	train-mlogloss:1.85509	validation-mlogloss:1.83718
[377]	train-mlogloss:1.85442	validation-mlogloss:1.83665
[378]	train-mlogloss:1.85375	validation-mlogloss:1.83622
[379]	train-mlogloss:1.85321	validation-mlogloss:1.83589
[380]	train-mlogloss:1.85265	validation-mlogloss:1.83537
[381]	train-mlogloss:1.85205	validation-mlogloss:1.83494
[382]	train-mlogloss:1.85148	validation-mlogloss:1.83461
[383]	train-mlogloss:1.85095	validation-mlogloss:1.83441
[384]	train-mlogloss:1.85038	validation-mlogloss:1.83397
[385]	train-mlogloss:1.84977	validation-mlogloss:1.83360
[386]	train-mlogloss:1.84911	validation-mlogloss:1.83331
[387]	train-mlogloss:1.84848	validation-mlogloss:1.83282
[388]	train-mlogloss:1.84786	validation-mlogloss:1.83240
[389]	train-mlogloss:1.84732	validation-mlogloss:1.83200
[390]	train-mlogloss:1.84679	validation-mlogloss:1.83159
[391]	train-mlogloss:1.84626	validation-mlogloss:1.83140
[392]	train-mlogloss:1.84560	validation-mlogloss:1.83092
[393]	train-mlogloss:1.84502	validation-mlogloss:1.83049
[394]	train-mlogloss:1.84443	validation-mlogloss:1.83011
[395]	train-mlogloss:1.84382	validation-mlogloss:1.82970
[396]	train-mlogloss:1.84316	validation-mlogloss:1.82918
[397]	train-mlogloss:1.84267	validation-mlogloss:1.82886
[398]	train-mlogloss:1.84201	validation-mlogloss:1.82862
[399]	train-mlogloss:1.84141	validation-mlogloss:1.82812
[400]	train-mlogloss:1.84095	validation-mlogloss:1.82785
[401]	train-mlogloss:1.84041	validation-mlogloss:1.82746
[402]	train-mlogloss:1.83994	validation-mlogloss:1.82715
[403]	train-mlogloss:1.83936	validation-mlogloss:1.82675
[404]	train-mlogloss:1.83877	validation-mlogloss:1.82647
[405]	train-mlogloss:1.83821	validation-mlogloss:1.82612
[406]	train-mlogloss:1.83759	validation-mlogloss:1.82576
[407]	train-mlogloss:1.83707	validation-mlogloss:1.82537
[408]	train-mlogloss:1.83658	validation-mlogloss:1.82510
[409]	train-mlogloss:1.83601	validation-mlogloss:1.82471
[410]	train-mlogloss:1.83552	validation-mlogloss:1.82435
[411]	train-mlogloss:1.83503	validation-mlogloss:1.82412
[412]	train-mlogloss:1.83453	validation-mlogloss:1.82365
[413]	train-mlogloss:1.83400	validation-mlogloss:1.82334
[414]	train-mlogloss:1.83350	validation-mlogloss:1.82308
[415]	train-mlogloss:1.83297	validation-mlogloss:1.82287
[416]	train-mlogloss:1.83247	validation-mlogloss:1.82253
[417]	train-mlogloss:1.83199	validation-mlogloss:1.82207
[418]	train-mlogloss:1.83157	validation-mlogloss:1.82166
[419]	train-mlogloss:1.83106	validation-mlogloss:1.82129
Saved model to disk.

=== EJECUCIÓN 1 ===

--- TRAIN (ejecución 1) ---

--- TEST (ejecución 1) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.23 [%]
Global accuracy score (test) = 44.14 [%]
Global F1 score (train) = 43.75 [%]
Global F1 score (test) = 43.28 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.46      0.45       184
       CAMINAR USUAL SPEED       0.30      0.14      0.19       184
            CAMINAR ZIGZAG       0.31      0.56      0.40       184
          DE PIE BARRIENDO       0.71      0.40      0.51       184
   DE PIE DOBLANDO TOALLAS       0.44      0.44      0.44       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.39       184
          DE PIE USANDO PC       0.21      0.33      0.26       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.58      0.61       184
           SENTADO LEYENDO       0.47      0.39      0.42       184
         SENTADO USANDO PC       0.27      0.14      0.19       184
      SENTADO VIENDO LA TV       0.24      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.64      0.56      0.60       184
                    TROTAR       0.68      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 1: 44.14 [%]
F1-score capturado en la ejecución 1: 43.28 [%]

=== EJECUCIÓN 2 ===

--- TRAIN (ejecución 2) ---

--- TEST (ejecución 2) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.21 [%]
Global accuracy score (test) = 44.25 [%]
Global F1 score (train) = 43.77 [%]
Global F1 score (test) = 43.38 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.49      0.72      0.59       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.46      0.45       184
       CAMINAR USUAL SPEED       0.32      0.16      0.21       184
            CAMINAR ZIGZAG       0.32      0.55      0.40       184
          DE PIE BARRIENDO       0.69      0.40      0.50       184
   DE PIE DOBLANDO TOALLAS       0.45      0.44      0.44       184
    DE PIE MOVIENDO LIBROS       0.37      0.39      0.38       184
          DE PIE USANDO PC       0.21      0.32      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.64      0.58      0.61       184
           SENTADO LEYENDO       0.46      0.38      0.42       184
         SENTADO USANDO PC       0.29      0.15      0.19       184
      SENTADO VIENDO LA TV       0.26      0.17      0.20       184
   SUBIR Y BAJAR ESCALERAS       0.61      0.56      0.59       184
                    TROTAR       0.65      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 2: 44.25 [%]
F1-score capturado en la ejecución 2: 43.38 [%]

=== EJECUCIÓN 3 ===

--- TRAIN (ejecución 3) ---

--- TEST (ejecución 3) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.37 [%]
Global accuracy score (test) = 44.06 [%]
Global F1 score (train) = 43.93 [%]
Global F1 score (test) = 43.39 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.71      0.56       184
 CAMINAR CON MÓVIL O LIBRO       0.41      0.46      0.44       184
       CAMINAR USUAL SPEED       0.36      0.18      0.24       184
            CAMINAR ZIGZAG       0.31      0.53      0.39       184
          DE PIE BARRIENDO       0.71      0.39      0.51       184
   DE PIE DOBLANDO TOALLAS       0.44      0.43      0.44       184
    DE PIE MOVIENDO LIBROS       0.37      0.39      0.38       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.57      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.57      0.61       184
           SENTADO LEYENDO       0.46      0.40      0.43       184
         SENTADO USANDO PC       0.27      0.12      0.17       184
      SENTADO VIENDO LA TV       0.27      0.18      0.21       184
   SUBIR Y BAJAR ESCALERAS       0.66      0.56      0.61       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.46      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 3: 44.06 [%]
F1-score capturado en la ejecución 3: 43.39 [%]

=== EJECUCIÓN 4 ===

--- TRAIN (ejecución 4) ---

--- TEST (ejecución 4) ---
2025-11-06 21:44:41.467946: 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 21:44:41.479117: 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 00:00:1762461881.492324 1824967 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762461881.496427 1824967 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762461881.506483 1824967 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461881.506514 1824967 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461881.506516 1824967 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461881.506517 1824967 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:44:41.509646: 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:2.70063	validation-mlogloss:2.70021
[1]	train-mlogloss:2.69307	validation-mlogloss:2.69217
[2]	train-mlogloss:2.68545	validation-mlogloss:2.68393
[3]	train-mlogloss:2.67803	validation-mlogloss:2.67593
[4]	train-mlogloss:2.67068	validation-mlogloss:2.66822
[5]	train-mlogloss:2.66340	validation-mlogloss:2.66021
[6]	train-mlogloss:2.65668	validation-mlogloss:2.65308
[7]	train-mlogloss:2.64924	validation-mlogloss:2.64515
[8]	train-mlogloss:2.64205	validation-mlogloss:2.63730
[9]	train-mlogloss:2.63495	validation-mlogloss:2.62974
[10]	train-mlogloss:2.62828	validation-mlogloss:2.62251
[11]	train-mlogloss:2.62120	validation-mlogloss:2.61445
[12]	train-mlogloss:2.61440	validation-mlogloss:2.60698
[13]	train-mlogloss:2.60766	validation-mlogloss:2.59955
[14]	train-mlogloss:2.60092	validation-mlogloss:2.59191
[15]	train-mlogloss:2.59435	validation-mlogloss:2.58449
[16]	train-mlogloss:2.58796	validation-mlogloss:2.57738
[17]	train-mlogloss:2.58183	validation-mlogloss:2.57091
[18]	train-mlogloss:2.57551	validation-mlogloss:2.56406
[19]	train-mlogloss:2.56929	validation-mlogloss:2.55729
[20]	train-mlogloss:2.56323	validation-mlogloss:2.55063
[21]	train-mlogloss:2.55727	validation-mlogloss:2.54425
[22]	train-mlogloss:2.55135	validation-mlogloss:2.53791
[23]	train-mlogloss:2.54537	validation-mlogloss:2.53127
[24]	train-mlogloss:2.53979	validation-mlogloss:2.52551
[25]	train-mlogloss:2.53366	validation-mlogloss:2.51863
[26]	train-mlogloss:2.52797	validation-mlogloss:2.51264
[27]	train-mlogloss:2.52241	validation-mlogloss:2.50692
[28]	train-mlogloss:2.51687	validation-mlogloss:2.50103
[29]	train-mlogloss:2.51155	validation-mlogloss:2.49544
[30]	train-mlogloss:2.50602	validation-mlogloss:2.48932
[31]	train-mlogloss:2.50080	validation-mlogloss:2.48378
[32]	train-mlogloss:2.49529	validation-mlogloss:2.47752
[33]	train-mlogloss:2.49003	validation-mlogloss:2.47177
[34]	train-mlogloss:2.48484	validation-mlogloss:2.46605
[35]	train-mlogloss:2.47971	validation-mlogloss:2.46037
[36]	train-mlogloss:2.47485	validation-mlogloss:2.45507
[37]	train-mlogloss:2.46990	validation-mlogloss:2.44970
[38]	train-mlogloss:2.46458	validation-mlogloss:2.44357
[39]	train-mlogloss:2.45944	validation-mlogloss:2.43773
[40]	train-mlogloss:2.45450	validation-mlogloss:2.43241
[41]	train-mlogloss:2.44967	validation-mlogloss:2.42705
[42]	train-mlogloss:2.44489	validation-mlogloss:2.42203
[43]	train-mlogloss:2.44012	validation-mlogloss:2.41673
[44]	train-mlogloss:2.43552	validation-mlogloss:2.41175
[45]	train-mlogloss:2.43107	validation-mlogloss:2.40689
[46]	train-mlogloss:2.42644	validation-mlogloss:2.40193
[47]	train-mlogloss:2.42164	validation-mlogloss:2.39637
[48]	train-mlogloss:2.41716	validation-mlogloss:2.39140
[49]	train-mlogloss:2.41271	validation-mlogloss:2.38652
[50]	train-mlogloss:2.40824	validation-mlogloss:2.38151
[51]	train-mlogloss:2.40389	validation-mlogloss:2.37678
[52]	train-mlogloss:2.39952	validation-mlogloss:2.37200
[53]	train-mlogloss:2.39517	validation-mlogloss:2.36726
[54]	train-mlogloss:2.39086	validation-mlogloss:2.36252
[55]	train-mlogloss:2.38666	validation-mlogloss:2.35799
[56]	train-mlogloss:2.38220	validation-mlogloss:2.35288
[57]	train-mlogloss:2.37790	validation-mlogloss:2.34799
[58]	train-mlogloss:2.37368	validation-mlogloss:2.34335
[59]	train-mlogloss:2.36966	validation-mlogloss:2.33917
[60]	train-mlogloss:2.36566	validation-mlogloss:2.33486
[61]	train-mlogloss:2.36156	validation-mlogloss:2.33064
[62]	train-mlogloss:2.35766	validation-mlogloss:2.32647
[63]	train-mlogloss:2.35361	validation-mlogloss:2.32199
[64]	train-mlogloss:2.34969	validation-mlogloss:2.31768
[65]	train-mlogloss:2.34605	validation-mlogloss:2.31400
[66]	train-mlogloss:2.34222	validation-mlogloss:2.30981
[67]	train-mlogloss:2.33836	validation-mlogloss:2.30555
[68]	train-mlogloss:2.33482	validation-mlogloss:2.30189
[69]	train-mlogloss:2.33104	validation-mlogloss:2.29766
[70]	train-mlogloss:2.32729	validation-mlogloss:2.29331
[71]	train-mlogloss:2.32351	validation-mlogloss:2.28922
[72]	train-mlogloss:2.31973	validation-mlogloss:2.28496
[73]	train-mlogloss:2.31598	validation-mlogloss:2.28090
[74]	train-mlogloss:2.31245	validation-mlogloss:2.27697
[75]	train-mlogloss:2.30882	validation-mlogloss:2.27300
[76]	train-mlogloss:2.30543	validation-mlogloss:2.26931
[77]	train-mlogloss:2.30221	validation-mlogloss:2.26594
[78]	train-mlogloss:2.29881	validation-mlogloss:2.26233
[79]	train-mlogloss:2.29536	validation-mlogloss:2.25852
[80]	train-mlogloss:2.29180	validation-mlogloss:2.25462
[81]	train-mlogloss:2.28855	validation-mlogloss:2.25113
[82]	train-mlogloss:2.28513	validation-mlogloss:2.24736
[83]	train-mlogloss:2.28166	validation-mlogloss:2.24373
[84]	train-mlogloss:2.27843	validation-mlogloss:2.24040
[85]	train-mlogloss:2.27528	validation-mlogloss:2.23730
[86]	train-mlogloss:2.27211	validation-mlogloss:2.23392
[87]	train-mlogloss:2.26894	validation-mlogloss:2.23067
[88]	train-mlogloss:2.26568	validation-mlogloss:2.22722
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[388]	train-mlogloss:1.84871	validation-mlogloss:1.83325
[389]	train-mlogloss:1.84812	validation-mlogloss:1.83285
[390]	train-mlogloss:1.84755	validation-mlogloss:1.83234
[391]	train-mlogloss:1.84701	validation-mlogloss:1.83198
[392]	train-mlogloss:1.84645	validation-mlogloss:1.83152
[393]	train-mlogloss:1.84594	validation-mlogloss:1.83124
[394]	train-mlogloss:1.84537	validation-mlogloss:1.83089
[395]	train-mlogloss:1.84481	validation-mlogloss:1.83048
[396]	train-mlogloss:1.84420	validation-mlogloss:1.83018
[397]	train-mlogloss:1.84362	validation-mlogloss:1.82984
[398]	train-mlogloss:1.84306	validation-mlogloss:1.82940
[399]	train-mlogloss:1.84260	validation-mlogloss:1.82916
[400]	train-mlogloss:1.84204	validation-mlogloss:1.82877
[401]	train-mlogloss:1.84138	validation-mlogloss:1.82821
[402]	train-mlogloss:1.84085	validation-mlogloss:1.82780
[403]	train-mlogloss:1.84026	validation-mlogloss:1.82742
[404]	train-mlogloss:1.83989	validation-mlogloss:1.82724
[405]	train-mlogloss:1.83930	validation-mlogloss:1.82699
[406]	train-mlogloss:1.83876	validation-mlogloss:1.82656
[407]	train-mlogloss:1.83819	validation-mlogloss:1.82614
[408]	train-mlogloss:1.83757	validation-mlogloss:1.82570
[409]	train-mlogloss:1.83704	validation-mlogloss:1.82543
[410]	train-mlogloss:1.83658	validation-mlogloss:1.82507
[411]	train-mlogloss:1.83611	validation-mlogloss:1.82479
[412]	train-mlogloss:1.83559	validation-mlogloss:1.82451
[413]	train-mlogloss:1.83503	validation-mlogloss:1.82421
[414]	train-mlogloss:1.83454	validation-mlogloss:1.82392
[415]	train-mlogloss:1.83406	validation-mlogloss:1.82356
[416]	train-mlogloss:1.83359	validation-mlogloss:1.82328
[417]	train-mlogloss:1.83308	validation-mlogloss:1.82291
[418]	train-mlogloss:1.83267	validation-mlogloss:1.82261
[419]	train-mlogloss:1.83223	validation-mlogloss:1.82237
Saved model to disk.
2025-11-06 21:45:03.448146: 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 21:45:03.459572: 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 00:00:1762461903.472704 1825371 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762461903.476791 1825371 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762461903.486479 1825371 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461903.486523 1825371 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461903.486525 1825371 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461903.486526 1825371 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:45:03.489718: 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:2.70055	validation-mlogloss:2.70022
[1]	train-mlogloss:2.69260	validation-mlogloss:2.69153
[2]	train-mlogloss:2.68537	validation-mlogloss:2.68398
[3]	train-mlogloss:2.67769	validation-mlogloss:2.67556
[4]	train-mlogloss:2.67009	validation-mlogloss:2.66713
[5]	train-mlogloss:2.66315	validation-mlogloss:2.65979
[6]	train-mlogloss:2.65596	validation-mlogloss:2.65243
[7]	train-mlogloss:2.64896	validation-mlogloss:2.64490
[8]	train-mlogloss:2.64223	validation-mlogloss:2.63788
[9]	train-mlogloss:2.63512	validation-mlogloss:2.63008
[10]	train-mlogloss:2.62873	validation-mlogloss:2.62339
[11]	train-mlogloss:2.62210	validation-mlogloss:2.61596
[12]	train-mlogloss:2.61531	validation-mlogloss:2.60859
[13]	train-mlogloss:2.60841	validation-mlogloss:2.60064
[14]	train-mlogloss:2.60180	validation-mlogloss:2.59372
[15]	train-mlogloss:2.59542	validation-mlogloss:2.58681
[16]	train-mlogloss:2.58895	validation-mlogloss:2.57965
[17]	train-mlogloss:2.58278	validation-mlogloss:2.57273
[18]	train-mlogloss:2.57680	validation-mlogloss:2.56632
[19]	train-mlogloss:2.57065	validation-mlogloss:2.56000
[20]	train-mlogloss:2.56471	validation-mlogloss:2.55331
[21]	train-mlogloss:2.55893	validation-mlogloss:2.54704
[22]	train-mlogloss:2.55266	validation-mlogloss:2.53980
[23]	train-mlogloss:2.54671	validation-mlogloss:2.53308
[24]	train-mlogloss:2.54076	validation-mlogloss:2.52683
[25]	train-mlogloss:2.53510	validation-mlogloss:2.52057
[26]	train-mlogloss:2.52943	validation-mlogloss:2.51460
[27]	train-mlogloss:2.52373	validation-mlogloss:2.50819
[28]	train-mlogloss:2.51832	validation-mlogloss:2.50232
[29]	train-mlogloss:2.51288	validation-mlogloss:2.49648
[30]	train-mlogloss:2.50747	validation-mlogloss:2.49024
[31]	train-mlogloss:2.50208	validation-mlogloss:2.48428
[32]	train-mlogloss:2.49679	validation-mlogloss:2.47839
[33]	train-mlogloss:2.49138	validation-mlogloss:2.47236
[34]	train-mlogloss:2.48608	validation-mlogloss:2.46648
[35]	train-mlogloss:2.48096	validation-mlogloss:2.46088
[36]	train-mlogloss:2.47569	validation-mlogloss:2.45515
[37]	train-mlogloss:2.47056	validation-mlogloss:2.44944
[38]	train-mlogloss:2.46556	validation-mlogloss:2.44399
[39]	train-mlogloss:2.46046	validation-mlogloss:2.43851
[40]	train-mlogloss:2.45533	validation-mlogloss:2.43274
[41]	train-mlogloss:2.45075	validation-mlogloss:2.42797
[42]	train-mlogloss:2.44604	validation-mlogloss:2.42282
[43]	train-mlogloss:2.44124	validation-mlogloss:2.41753
[44]	train-mlogloss:2.43658	validation-mlogloss:2.41239
[45]	train-mlogloss:2.43199	validation-mlogloss:2.40753
[46]	train-mlogloss:2.42743	validation-mlogloss:2.40249
[47]	train-mlogloss:2.42265	validation-mlogloss:2.39702
[48]	train-mlogloss:2.41836	validation-mlogloss:2.39220
[49]	train-mlogloss:2.41396	validation-mlogloss:2.38733
[50]	train-mlogloss:2.40957	validation-mlogloss:2.38259
[51]	train-mlogloss:2.40506	validation-mlogloss:2.37739
[52]	train-mlogloss:2.40061	validation-mlogloss:2.37267
[53]	train-mlogloss:2.39632	validation-mlogloss:2.36775
[54]	train-mlogloss:2.39228	validation-mlogloss:2.36356
[55]	train-mlogloss:2.38809	validation-mlogloss:2.35884
[56]	train-mlogloss:2.38373	validation-mlogloss:2.35396
[57]	train-mlogloss:2.37924	validation-mlogloss:2.34888
[58]	train-mlogloss:2.37481	validation-mlogloss:2.34391
[59]	train-mlogloss:2.37072	validation-mlogloss:2.33958
[60]	train-mlogloss:2.36664	validation-mlogloss:2.33511
[61]	train-mlogloss:2.36239	validation-mlogloss:2.33008
[62]	train-mlogloss:2.35840	validation-mlogloss:2.32580
[63]	train-mlogloss:2.35420	validation-mlogloss:2.32107
[64]	train-mlogloss:2.35033	validation-mlogloss:2.31677
[65]	train-mlogloss:2.34625	validation-mlogloss:2.31239
[66]	train-mlogloss:2.34232	validation-mlogloss:2.30830
[67]	train-mlogloss:2.33833	validation-mlogloss:2.30360
[68]	train-mlogloss:2.33460	validation-mlogloss:2.29968
[69]	train-mlogloss:2.33083	validation-mlogloss:2.29559
[70]	train-mlogloss:2.32697	validation-mlogloss:2.29132
[71]	train-mlogloss:2.32349	validation-mlogloss:2.28787
[72]	train-mlogloss:2.31994	validation-mlogloss:2.28389
[73]	train-mlogloss:2.31610	validation-mlogloss:2.27975
[74]	train-mlogloss:2.31244	validation-mlogloss:2.27558
[75]	train-mlogloss:2.30891	validation-mlogloss:2.27156
[76]	train-mlogloss:2.30525	validation-mlogloss:2.26738
[77]	train-mlogloss:2.30171	validation-mlogloss:2.26369
[78]	train-mlogloss:2.29810	validation-mlogloss:2.25951
[79]	train-mlogloss:2.29453	validation-mlogloss:2.25537
[80]	train-mlogloss:2.29110	validation-mlogloss:2.25181
[81]	train-mlogloss:2.28797	validation-mlogloss:2.24879
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[84]	train-mlogloss:2.27810	validation-mlogloss:2.23853
[85]	train-mlogloss:2.27493	validation-mlogloss:2.23518
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[87]	train-mlogloss:2.26896	validation-mlogloss:2.22905
[88]	train-mlogloss:2.26578	validation-mlogloss:2.22552
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[90]	train-mlogloss:2.25952	validation-mlogloss:2.21882
[91]	train-mlogloss:2.25640	validation-mlogloss:2.21531
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[93]	train-mlogloss:2.25028	validation-mlogloss:2.20883
[94]	train-mlogloss:2.24745	validation-mlogloss:2.20588
[95]	train-mlogloss:2.24452	validation-mlogloss:2.20277
[96]	train-mlogloss:2.24148	validation-mlogloss:2.19955
[97]	train-mlogloss:2.23858	validation-mlogloss:2.19627
[98]	train-mlogloss:2.23567	validation-mlogloss:2.19297
[99]	train-mlogloss:2.23292	validation-mlogloss:2.18995
[100]	train-mlogloss:2.23004	validation-mlogloss:2.18674
[101]	train-mlogloss:2.22724	validation-mlogloss:2.18399
[102]	train-mlogloss:2.22445	validation-mlogloss:2.18098
[103]	train-mlogloss:2.22160	validation-mlogloss:2.17769
[104]	train-mlogloss:2.21885	validation-mlogloss:2.17459
[105]	train-mlogloss:2.21614	validation-mlogloss:2.17159
[106]	train-mlogloss:2.21352	validation-mlogloss:2.16896
[107]	train-mlogloss:2.21101	validation-mlogloss:2.16650
[108]	train-mlogloss:2.20831	validation-mlogloss:2.16351
[109]	train-mlogloss:2.20555	validation-mlogloss:2.16054
[110]	train-mlogloss:2.20277	validation-mlogloss:2.15747
[111]	train-mlogloss:2.20022	validation-mlogloss:2.15473
[112]	train-mlogloss:2.19767	validation-mlogloss:2.15220
[113]	train-mlogloss:2.19519	validation-mlogloss:2.14979
[114]	train-mlogloss:2.19271	validation-mlogloss:2.14750
[115]	train-mlogloss:2.19017	validation-mlogloss:2.14500
[116]	train-mlogloss:2.18765	validation-mlogloss:2.14253
[117]	train-mlogloss:2.18510	validation-mlogloss:2.13999
[118]	train-mlogloss:2.18249	validation-mlogloss:2.13730
[119]	train-mlogloss:2.18010	validation-mlogloss:2.13491
[120]	train-mlogloss:2.17776	validation-mlogloss:2.13224
[121]	train-mlogloss:2.17529	validation-mlogloss:2.12959
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[123]	train-mlogloss:2.17061	validation-mlogloss:2.12485
[124]	train-mlogloss:2.16825	validation-mlogloss:2.12234
[125]	train-mlogloss:2.16597	validation-mlogloss:2.11992
[126]	train-mlogloss:2.16362	validation-mlogloss:2.11744
[127]	train-mlogloss:2.16142	validation-mlogloss:2.11536
[128]	train-mlogloss:2.15923	validation-mlogloss:2.11310
[129]	train-mlogloss:2.15701	validation-mlogloss:2.11065
[130]	train-mlogloss:2.15482	validation-mlogloss:2.10853
[131]	train-mlogloss:2.15258	validation-mlogloss:2.10651
[132]	train-mlogloss:2.15033	validation-mlogloss:2.10409
[133]	train-mlogloss:2.14825	validation-mlogloss:2.10216
[134]	train-mlogloss:2.14595	validation-mlogloss:2.09977
[135]	train-mlogloss:2.14373	validation-mlogloss:2.09752
[136]	train-mlogloss:2.14160	validation-mlogloss:2.09540
[137]	train-mlogloss:2.13946	validation-mlogloss:2.09327
[138]	train-mlogloss:2.13718	validation-mlogloss:2.09078
[139]	train-mlogloss:2.13497	validation-mlogloss:2.08852
[140]	train-mlogloss:2.13291	validation-mlogloss:2.08642
[141]	train-mlogloss:2.13074	validation-mlogloss:2.08412
[142]	train-mlogloss:2.12857	validation-mlogloss:2.08194
[143]	train-mlogloss:2.12652	validation-mlogloss:2.07980
[144]	train-mlogloss:2.12435	validation-mlogloss:2.07765
[145]	train-mlogloss:2.12248	validation-mlogloss:2.07604
[146]	train-mlogloss:2.12038	validation-mlogloss:2.07371
[147]	train-mlogloss:2.11845	validation-mlogloss:2.07184
[148]	train-mlogloss:2.11635	validation-mlogloss:2.06983
[149]	train-mlogloss:2.11439	validation-mlogloss:2.06811
[150]	train-mlogloss:2.11244	validation-mlogloss:2.06609
[151]	train-mlogloss:2.11041	validation-mlogloss:2.06376
[152]	train-mlogloss:2.10847	validation-mlogloss:2.06200
[153]	train-mlogloss:2.10655	validation-mlogloss:2.06026
[154]	train-mlogloss:2.10459	validation-mlogloss:2.05827
[155]	train-mlogloss:2.10270	validation-mlogloss:2.05642
[156]	train-mlogloss:2.10077	validation-mlogloss:2.05432
[157]	train-mlogloss:2.09892	validation-mlogloss:2.05248
[158]	train-mlogloss:2.09697	validation-mlogloss:2.05063
[159]	train-mlogloss:2.09514	validation-mlogloss:2.04880
[160]	train-mlogloss:2.09332	validation-mlogloss:2.04687
[161]	train-mlogloss:2.09144	validation-mlogloss:2.04507
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[164]	train-mlogloss:2.08601	validation-mlogloss:2.03995
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[189]	train-mlogloss:2.04467	validation-mlogloss:1.99925
[190]	train-mlogloss:2.04311	validation-mlogloss:1.99795
[191]	train-mlogloss:2.04155	validation-mlogloss:1.99642
[192]	train-mlogloss:2.04006	validation-mlogloss:1.99533
[193]	train-mlogloss:2.03865	validation-mlogloss:1.99391
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[200]	train-mlogloss:2.02815	validation-mlogloss:1.98352
[201]	train-mlogloss:2.02662	validation-mlogloss:1.98204
[202]	train-mlogloss:2.02516	validation-mlogloss:1.98062
[203]	train-mlogloss:2.02370	validation-mlogloss:1.97938
[204]	train-mlogloss:2.02229	validation-mlogloss:1.97826
[205]	train-mlogloss:2.02088	validation-mlogloss:1.97676
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[210]	train-mlogloss:2.01379	validation-mlogloss:1.97017
[211]	train-mlogloss:2.01247	validation-mlogloss:1.96923
[212]	train-mlogloss:2.01115	validation-mlogloss:1.96787
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[221]	train-mlogloss:1.99913	validation-mlogloss:1.95713
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[389]	train-mlogloss:1.84824	validation-mlogloss:1.83311
[390]	train-mlogloss:1.84769	validation-mlogloss:1.83270
[391]	train-mlogloss:1.84717	validation-mlogloss:1.83231
[392]	train-mlogloss:1.84657	validation-mlogloss:1.83175
[393]	train-mlogloss:1.84606	validation-mlogloss:1.83149
[394]	train-mlogloss:1.84549	validation-mlogloss:1.83122
[395]	train-mlogloss:1.84489	validation-mlogloss:1.83072
[396]	train-mlogloss:1.84433	validation-mlogloss:1.83027
[397]	train-mlogloss:1.84378	validation-mlogloss:1.82987
[398]	train-mlogloss:1.84315	validation-mlogloss:1.82953
[399]	train-mlogloss:1.84261	validation-mlogloss:1.82918
[400]	train-mlogloss:1.84210	validation-mlogloss:1.82884
[401]	train-mlogloss:1.84156	validation-mlogloss:1.82840
[402]	train-mlogloss:1.84105	validation-mlogloss:1.82809
[403]	train-mlogloss:1.84049	validation-mlogloss:1.82783
[404]	train-mlogloss:1.83991	validation-mlogloss:1.82756
[405]	train-mlogloss:1.83933	validation-mlogloss:1.82707
[406]	train-mlogloss:1.83874	validation-mlogloss:1.82667
[407]	train-mlogloss:1.83824	validation-mlogloss:1.82625
[408]	train-mlogloss:1.83769	validation-mlogloss:1.82578
[409]	train-mlogloss:1.83720	validation-mlogloss:1.82548
[410]	train-mlogloss:1.83667	validation-mlogloss:1.82505
[411]	train-mlogloss:1.83623	validation-mlogloss:1.82476
[412]	train-mlogloss:1.83565	validation-mlogloss:1.82437
[413]	train-mlogloss:1.83506	validation-mlogloss:1.82397
[414]	train-mlogloss:1.83448	validation-mlogloss:1.82357
[415]	train-mlogloss:1.83401	validation-mlogloss:1.82323
[416]	train-mlogloss:1.83351	validation-mlogloss:1.82283
[417]	train-mlogloss:1.83295	validation-mlogloss:1.82249
[418]	train-mlogloss:1.83248	validation-mlogloss:1.82232
[419]	train-mlogloss:1.83192	validation-mlogloss:1.82193
Saved model to disk.
2025-11-06 21:45:25.418916: 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 21:45:25.430158: 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 00:00:1762461925.443425 1825738 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762461925.447532 1825738 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762461925.457391 1825738 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461925.457407 1825738 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461925.457408 1825738 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461925.457409 1825738 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:45:25.460548: 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:2.69284	validation-mlogloss:2.69142
[2]	train-mlogloss:2.68535	validation-mlogloss:2.68325
[3]	train-mlogloss:2.67809	validation-mlogloss:2.67590
[4]	train-mlogloss:2.67078	validation-mlogloss:2.66793
[5]	train-mlogloss:2.66334	validation-mlogloss:2.65992
[6]	train-mlogloss:2.65562	validation-mlogloss:2.65168
[7]	train-mlogloss:2.64815	validation-mlogloss:2.64364
[8]	train-mlogloss:2.64085	validation-mlogloss:2.63535
[9]	train-mlogloss:2.63399	validation-mlogloss:2.62788
[10]	train-mlogloss:2.62706	validation-mlogloss:2.62028
[11]	train-mlogloss:2.62052	validation-mlogloss:2.61320
[12]	train-mlogloss:2.61422	validation-mlogloss:2.60636
[13]	train-mlogloss:2.60742	validation-mlogloss:2.59892
[14]	train-mlogloss:2.60066	validation-mlogloss:2.59167
[15]	train-mlogloss:2.59423	validation-mlogloss:2.58449
[16]	train-mlogloss:2.58766	validation-mlogloss:2.57729
[17]	train-mlogloss:2.58130	validation-mlogloss:2.57048
[18]	train-mlogloss:2.57501	validation-mlogloss:2.56352
[19]	train-mlogloss:2.56895	validation-mlogloss:2.55695
[20]	train-mlogloss:2.56288	validation-mlogloss:2.55034
[21]	train-mlogloss:2.55700	validation-mlogloss:2.54396
[22]	train-mlogloss:2.55097	validation-mlogloss:2.53740
[23]	train-mlogloss:2.54513	validation-mlogloss:2.53126
[24]	train-mlogloss:2.53939	validation-mlogloss:2.52522
[25]	train-mlogloss:2.53370	validation-mlogloss:2.51929
[26]	train-mlogloss:2.52813	validation-mlogloss:2.51319
[27]	train-mlogloss:2.52256	validation-mlogloss:2.50701
[28]	train-mlogloss:2.51693	validation-mlogloss:2.50067
[29]	train-mlogloss:2.51139	validation-mlogloss:2.49469
[30]	train-mlogloss:2.50587	validation-mlogloss:2.48864
[31]	train-mlogloss:2.50047	validation-mlogloss:2.48267
[32]	train-mlogloss:2.49537	validation-mlogloss:2.47718
[33]	train-mlogloss:2.49021	validation-mlogloss:2.47173
[34]	train-mlogloss:2.48512	validation-mlogloss:2.46615
[35]	train-mlogloss:2.47998	validation-mlogloss:2.46058
[36]	train-mlogloss:2.47481	validation-mlogloss:2.45467
[37]	train-mlogloss:2.46982	validation-mlogloss:2.44907
[38]	train-mlogloss:2.46495	validation-mlogloss:2.44395
[39]	train-mlogloss:2.46012	validation-mlogloss:2.43874
[40]	train-mlogloss:2.45539	validation-mlogloss:2.43357
[41]	train-mlogloss:2.45059	validation-mlogloss:2.42828
[42]	train-mlogloss:2.44565	validation-mlogloss:2.42268
[43]	train-mlogloss:2.44118	validation-mlogloss:2.41788
[44]	train-mlogloss:2.43654	validation-mlogloss:2.41295
[45]	train-mlogloss:2.43152	validation-mlogloss:2.40747
[46]	train-mlogloss:2.42685	validation-mlogloss:2.40237
[47]	train-mlogloss:2.42234	validation-mlogloss:2.39743
[48]	train-mlogloss:2.41783	validation-mlogloss:2.39244
[49]	train-mlogloss:2.41344	validation-mlogloss:2.38751
[50]	train-mlogloss:2.40899	validation-mlogloss:2.38259
[51]	train-mlogloss:2.40479	validation-mlogloss:2.37803
[52]	train-mlogloss:2.40040	validation-mlogloss:2.37305
[53]	train-mlogloss:2.39624	validation-mlogloss:2.36856
[54]	train-mlogloss:2.39198	validation-mlogloss:2.36384
[55]	train-mlogloss:2.38801	validation-mlogloss:2.35961
[56]	train-mlogloss:2.38358	validation-mlogloss:2.35449
[57]	train-mlogloss:2.37975	validation-mlogloss:2.35052
[58]	train-mlogloss:2.37566	validation-mlogloss:2.34621
[59]	train-mlogloss:2.37125	validation-mlogloss:2.34106
[60]	train-mlogloss:2.36697	validation-mlogloss:2.33636
[61]	train-mlogloss:2.36311	validation-mlogloss:2.33207
[62]	train-mlogloss:2.35908	validation-mlogloss:2.32783
[63]	train-mlogloss:2.35503	validation-mlogloss:2.32318
[64]	train-mlogloss:2.35081	validation-mlogloss:2.31848
[65]	train-mlogloss:2.34678	validation-mlogloss:2.31385
[66]	train-mlogloss:2.34309	validation-mlogloss:2.31007
[67]	train-mlogloss:2.33935	validation-mlogloss:2.30621
[68]	train-mlogloss:2.33573	validation-mlogloss:2.30241
[69]	train-mlogloss:2.33176	validation-mlogloss:2.29791
[70]	train-mlogloss:2.32818	validation-mlogloss:2.29400
[71]	train-mlogloss:2.32471	validation-mlogloss:2.29016
[72]	train-mlogloss:2.32099	validation-mlogloss:2.28593
[73]	train-mlogloss:2.31733	validation-mlogloss:2.28193
[74]	train-mlogloss:2.31373	validation-mlogloss:2.27816
[75]	train-mlogloss:2.31033	validation-mlogloss:2.27453
[76]	train-mlogloss:2.30684	validation-mlogloss:2.27096
[77]	train-mlogloss:2.30330	validation-mlogloss:2.26683
[78]	train-mlogloss:2.29999	validation-mlogloss:2.26335
[79]	train-mlogloss:2.29661	validation-mlogloss:2.25976
[80]	train-mlogloss:2.29309	validation-mlogloss:2.25578
[81]	train-mlogloss:2.28992	validation-mlogloss:2.25246
[82]	train-mlogloss:2.28665	validation-mlogloss:2.24905
[83]	train-mlogloss:2.28320	validation-mlogloss:2.24536
[84]	train-mlogloss:2.28012	validation-mlogloss:2.24213
[85]	train-mlogloss:2.27683	validation-mlogloss:2.23868
[86]	train-mlogloss:2.27381	validation-mlogloss:2.23558
[87]	train-mlogloss:2.27055	validation-mlogloss:2.23218
[88]	train-mlogloss:2.26738	validation-mlogloss:2.22860
[89]	train-mlogloss:2.26405	validation-mlogloss:2.22501
[90]	train-mlogloss:2.26108	validation-mlogloss:2.22194
[91]	train-mlogloss:2.25800	validation-mlogloss:2.21876
[92]	train-mlogloss:2.25478	validation-mlogloss:2.21518
[93]	train-mlogloss:2.25165	validation-mlogloss:2.21187
[94]	train-mlogloss:2.24874	validation-mlogloss:2.20887
[95]	train-mlogloss:2.24577	validation-mlogloss:2.20579
[96]	train-mlogloss:2.24285	validation-mlogloss:2.20270
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[396]	train-mlogloss:1.84397	validation-mlogloss:1.82950
[397]	train-mlogloss:1.84343	validation-mlogloss:1.82889
[398]	train-mlogloss:1.84288	validation-mlogloss:1.82864
[399]	train-mlogloss:1.84236	validation-mlogloss:1.82825
[400]	train-mlogloss:1.84187	validation-mlogloss:1.82792
[401]	train-mlogloss:1.84135	validation-mlogloss:1.82763
[402]	train-mlogloss:1.84073	validation-mlogloss:1.82704
[403]	train-mlogloss:1.84019	validation-mlogloss:1.82669
[404]	train-mlogloss:1.83973	validation-mlogloss:1.82643
[405]	train-mlogloss:1.83917	validation-mlogloss:1.82611
[406]	train-mlogloss:1.83870	validation-mlogloss:1.82572
[407]	train-mlogloss:1.83815	validation-mlogloss:1.82540
[408]	train-mlogloss:1.83765	validation-mlogloss:1.82498
[409]	train-mlogloss:1.83708	validation-mlogloss:1.82451
[410]	train-mlogloss:1.83651	validation-mlogloss:1.82404
[411]	train-mlogloss:1.83599	validation-mlogloss:1.82378
[412]	train-mlogloss:1.83550	validation-mlogloss:1.82351
[413]	train-mlogloss:1.83498	validation-mlogloss:1.82329
[414]	train-mlogloss:1.83445	validation-mlogloss:1.82280
[415]	train-mlogloss:1.83400	validation-mlogloss:1.82264
[416]	train-mlogloss:1.83348	validation-mlogloss:1.82223
[417]	train-mlogloss:1.83297	validation-mlogloss:1.82187
[418]	train-mlogloss:1.83243	validation-mlogloss:1.82143
[419]	train-mlogloss:1.83196	validation-mlogloss:1.82118
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.24 [%]
Global accuracy score (test) = 44.43 [%]
Global F1 score (train) = 43.75 [%]
Global F1 score (test) = 43.77 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.49      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.47      0.46       184
       CAMINAR USUAL SPEED       0.34      0.19      0.24       184
            CAMINAR ZIGZAG       0.31      0.52      0.39       184
          DE PIE BARRIENDO       0.70      0.41      0.52       184
   DE PIE DOBLANDO TOALLAS       0.45      0.44      0.45       184
    DE PIE MOVIENDO LIBROS       0.37      0.39      0.38       184
          DE PIE USANDO PC       0.21      0.33      0.26       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.64      0.57      0.61       184
           SENTADO LEYENDO       0.48      0.40      0.44       184
         SENTADO USANDO PC       0.27      0.14      0.19       184
      SENTADO VIENDO LA TV       0.25      0.16      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.65      0.55      0.60       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.46      0.45      0.44      2737
              weighted avg       0.45      0.44      0.44      2737


Accuracy capturado en la ejecución 4: 44.43 [%]
F1-score capturado en la ejecución 4: 43.77 [%]

=== EJECUCIÓN 5 ===

--- TRAIN (ejecución 5) ---

--- TEST (ejecución 5) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.17 [%]
Global accuracy score (test) = 44.36 [%]
Global F1 score (train) = 43.67 [%]
Global F1 score (test) = 43.55 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.72      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.46      0.44       184
       CAMINAR USUAL SPEED       0.33      0.16      0.21       184
            CAMINAR ZIGZAG       0.32      0.54      0.40       184
          DE PIE BARRIENDO       0.71      0.40      0.51       184
   DE PIE DOBLANDO TOALLAS       0.47      0.43      0.45       184
    DE PIE MOVIENDO LIBROS       0.38      0.40      0.39       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.58      0.61       184
           SENTADO LEYENDO       0.47      0.41      0.44       184
         SENTADO USANDO PC       0.28      0.13      0.18       184
      SENTADO VIENDO LA TV       0.27      0.17      0.21       184
   SUBIR Y BAJAR ESCALERAS       0.65      0.56      0.60       184
                    TROTAR       0.66      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.46      0.44      0.44      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 5: 44.36 [%]
F1-score capturado en la ejecución 5: 43.55 [%]

=== EJECUCIÓN 6 ===

--- TRAIN (ejecución 6) ---

--- TEST (ejecución 6) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.26 [%]
Global accuracy score (test) = 44.5 [%]
Global F1 score (train) = 43.82 [%]
Global F1 score (test) = 43.76 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.49      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.42      0.46      0.44       184
       CAMINAR USUAL SPEED       0.36      0.18      0.24       184
            CAMINAR ZIGZAG       0.32      0.54      0.40       184
          DE PIE BARRIENDO       0.71      0.40      0.51       184
   DE PIE DOBLANDO TOALLAS       0.44      0.44      0.44       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.38       184
          DE PIE USANDO PC       0.21      0.32      0.26       184
        FASE REPOSO CON K5       0.55      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.58      0.61       184
           SENTADO LEYENDO       0.47      0.39      0.43       184
         SENTADO USANDO PC       0.31      0.17      0.22       184
      SENTADO VIENDO LA TV       0.23      0.14      0.17       184
   SUBIR Y BAJAR ESCALERAS       0.64      0.58      0.61       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.45      2737
                 macro avg       0.46      0.45      0.44      2737
              weighted avg       0.46      0.45      0.44      2737


Accuracy capturado en la ejecución 6: 44.5 [%]
F1-score capturado en la ejecución 6: 43.76 [%]

=== EJECUCIÓN 7 ===

--- TRAIN (ejecución 7) ---

--- TEST (ejecución 7) ---
2025-11-06 21:45:47.655959: 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 21:45:47.667229: 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 00:00:1762461947.680307 1826107 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762461947.684400 1826107 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762461947.694386 1826107 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461947.694404 1826107 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461947.694406 1826107 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461947.694407 1826107 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:45:47.697532: 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:2.70043	validation-mlogloss:2.69959
[1]	train-mlogloss:2.69288	validation-mlogloss:2.69154
[2]	train-mlogloss:2.68549	validation-mlogloss:2.68358
[3]	train-mlogloss:2.67830	validation-mlogloss:2.67595
[4]	train-mlogloss:2.67102	validation-mlogloss:2.66819
[5]	train-mlogloss:2.66327	validation-mlogloss:2.65985
[6]	train-mlogloss:2.65612	validation-mlogloss:2.65222
[7]	train-mlogloss:2.64907	validation-mlogloss:2.64481
[8]	train-mlogloss:2.64213	validation-mlogloss:2.63734
[9]	train-mlogloss:2.63506	validation-mlogloss:2.63003
[10]	train-mlogloss:2.62864	validation-mlogloss:2.62318
[11]	train-mlogloss:2.62158	validation-mlogloss:2.61548
[12]	train-mlogloss:2.61498	validation-mlogloss:2.60825
[13]	train-mlogloss:2.60847	validation-mlogloss:2.60116
[14]	train-mlogloss:2.60186	validation-mlogloss:2.59404
[15]	train-mlogloss:2.59514	validation-mlogloss:2.58648
[16]	train-mlogloss:2.58880	validation-mlogloss:2.57984
[17]	train-mlogloss:2.58222	validation-mlogloss:2.57246
[18]	train-mlogloss:2.57595	validation-mlogloss:2.56556
[19]	train-mlogloss:2.56960	validation-mlogloss:2.55835
[20]	train-mlogloss:2.56352	validation-mlogloss:2.55154
[21]	train-mlogloss:2.55746	validation-mlogloss:2.54509
[22]	train-mlogloss:2.55133	validation-mlogloss:2.53834
[23]	train-mlogloss:2.54562	validation-mlogloss:2.53217
[24]	train-mlogloss:2.53973	validation-mlogloss:2.52572
[25]	train-mlogloss:2.53397	validation-mlogloss:2.51911
[26]	train-mlogloss:2.52831	validation-mlogloss:2.51299
[27]	train-mlogloss:2.52269	validation-mlogloss:2.50673
[28]	train-mlogloss:2.51725	validation-mlogloss:2.50060
[29]	train-mlogloss:2.51189	validation-mlogloss:2.49481
[30]	train-mlogloss:2.50684	validation-mlogloss:2.48947
[31]	train-mlogloss:2.50140	validation-mlogloss:2.48309
[32]	train-mlogloss:2.49622	validation-mlogloss:2.47745
[33]	train-mlogloss:2.49113	validation-mlogloss:2.47196
[34]	train-mlogloss:2.48602	validation-mlogloss:2.46603
[35]	train-mlogloss:2.48102	validation-mlogloss:2.46055
[36]	train-mlogloss:2.47613	validation-mlogloss:2.45499
[37]	train-mlogloss:2.47116	validation-mlogloss:2.44946
[38]	train-mlogloss:2.46619	validation-mlogloss:2.44405
[39]	train-mlogloss:2.46128	validation-mlogloss:2.43879
[40]	train-mlogloss:2.45637	validation-mlogloss:2.43317
[41]	train-mlogloss:2.45163	validation-mlogloss:2.42798
[42]	train-mlogloss:2.44688	validation-mlogloss:2.42283
[43]	train-mlogloss:2.44215	validation-mlogloss:2.41801
[44]	train-mlogloss:2.43766	validation-mlogloss:2.41342
[45]	train-mlogloss:2.43316	validation-mlogloss:2.40854
[46]	train-mlogloss:2.42827	validation-mlogloss:2.40303
[47]	train-mlogloss:2.42364	validation-mlogloss:2.39779
[48]	train-mlogloss:2.41900	validation-mlogloss:2.39270
[49]	train-mlogloss:2.41450	validation-mlogloss:2.38782
[50]	train-mlogloss:2.41001	validation-mlogloss:2.38278
[51]	train-mlogloss:2.40539	validation-mlogloss:2.37772
[52]	train-mlogloss:2.40097	validation-mlogloss:2.37283
[53]	train-mlogloss:2.39629	validation-mlogloss:2.36746
[54]	train-mlogloss:2.39212	validation-mlogloss:2.36294
[55]	train-mlogloss:2.38779	validation-mlogloss:2.35801
[56]	train-mlogloss:2.38372	validation-mlogloss:2.35363
[57]	train-mlogloss:2.37969	validation-mlogloss:2.34921
[58]	train-mlogloss:2.37562	validation-mlogloss:2.34466
[59]	train-mlogloss:2.37161	validation-mlogloss:2.34019
[60]	train-mlogloss:2.36728	validation-mlogloss:2.33516
[61]	train-mlogloss:2.36313	validation-mlogloss:2.33071
[62]	train-mlogloss:2.35885	validation-mlogloss:2.32577
[63]	train-mlogloss:2.35478	validation-mlogloss:2.32116
[64]	train-mlogloss:2.35094	validation-mlogloss:2.31703
[65]	train-mlogloss:2.34704	validation-mlogloss:2.31256
[66]	train-mlogloss:2.34323	validation-mlogloss:2.30859
[67]	train-mlogloss:2.33955	validation-mlogloss:2.30464
[68]	train-mlogloss:2.33578	validation-mlogloss:2.30059
[69]	train-mlogloss:2.33203	validation-mlogloss:2.29639
[70]	train-mlogloss:2.32818	validation-mlogloss:2.29199
[71]	train-mlogloss:2.32460	validation-mlogloss:2.28810
[72]	train-mlogloss:2.32084	validation-mlogloss:2.28392
[73]	train-mlogloss:2.31730	validation-mlogloss:2.28002
[74]	train-mlogloss:2.31377	validation-mlogloss:2.27623
[75]	train-mlogloss:2.31017	validation-mlogloss:2.27230
[76]	train-mlogloss:2.30675	validation-mlogloss:2.26870
[77]	train-mlogloss:2.30351	validation-mlogloss:2.26529
[78]	train-mlogloss:2.30025	validation-mlogloss:2.26210
[79]	train-mlogloss:2.29654	validation-mlogloss:2.25782
[80]	train-mlogloss:2.29321	validation-mlogloss:2.25444
[81]	train-mlogloss:2.28998	validation-mlogloss:2.25124
[82]	train-mlogloss:2.28647	validation-mlogloss:2.24734
[83]	train-mlogloss:2.28304	validation-mlogloss:2.24363
[84]	train-mlogloss:2.27973	validation-mlogloss:2.23996
[85]	train-mlogloss:2.27631	validation-mlogloss:2.23614
[86]	train-mlogloss:2.27297	validation-mlogloss:2.23230
[87]	train-mlogloss:2.26954	validation-mlogloss:2.22841
[88]	train-mlogloss:2.26660	validation-mlogloss:2.22533
[89]	train-mlogloss:2.26346	validation-mlogloss:2.22197
[90]	train-mlogloss:2.26033	validation-mlogloss:2.21891
[91]	train-mlogloss:2.25701	validation-mlogloss:2.21512
[92]	train-mlogloss:2.25413	validation-mlogloss:2.21197
[93]	train-mlogloss:2.25107	validation-mlogloss:2.20858
[94]	train-mlogloss:2.24807	validation-mlogloss:2.20542
[95]	train-mlogloss:2.24518	validation-mlogloss:2.20258
[96]	train-mlogloss:2.24206	validation-mlogloss:2.19895
[97]	train-mlogloss:2.23931	validation-mlogloss:2.19611
[98]	train-mlogloss:2.23647	validation-mlogloss:2.19309
[99]	train-mlogloss:2.23379	validation-mlogloss:2.19044
[100]	train-mlogloss:2.23099	validation-mlogloss:2.18767
[101]	train-mlogloss:2.22824	validation-mlogloss:2.18475
[102]	train-mlogloss:2.22537	validation-mlogloss:2.18159
[103]	train-mlogloss:2.22252	validation-mlogloss:2.17851
[104]	train-mlogloss:2.21994	validation-mlogloss:2.17599
[105]	train-mlogloss:2.21728	validation-mlogloss:2.17311
[106]	train-mlogloss:2.21458	validation-mlogloss:2.17029
[107]	train-mlogloss:2.21189	validation-mlogloss:2.16735
[108]	train-mlogloss:2.20912	validation-mlogloss:2.16406
[109]	train-mlogloss:2.20659	validation-mlogloss:2.16158
[110]	train-mlogloss:2.20404	validation-mlogloss:2.15907
[111]	train-mlogloss:2.20150	validation-mlogloss:2.15655
[112]	train-mlogloss:2.19879	validation-mlogloss:2.15360
[113]	train-mlogloss:2.19625	validation-mlogloss:2.15097
[114]	train-mlogloss:2.19370	validation-mlogloss:2.14837
[115]	train-mlogloss:2.19107	validation-mlogloss:2.14562
[116]	train-mlogloss:2.18847	validation-mlogloss:2.14268
[117]	train-mlogloss:2.18608	validation-mlogloss:2.14010
[118]	train-mlogloss:2.18359	validation-mlogloss:2.13747
[119]	train-mlogloss:2.18106	validation-mlogloss:2.13487
[120]	train-mlogloss:2.17874	validation-mlogloss:2.13247
[121]	train-mlogloss:2.17638	validation-mlogloss:2.13014
[122]	train-mlogloss:2.17400	validation-mlogloss:2.12765
[123]	train-mlogloss:2.17163	validation-mlogloss:2.12550
[124]	train-mlogloss:2.16904	validation-mlogloss:2.12290
[125]	train-mlogloss:2.16669	validation-mlogloss:2.12032
[126]	train-mlogloss:2.16442	validation-mlogloss:2.11782
[127]	train-mlogloss:2.16209	validation-mlogloss:2.11535
[128]	train-mlogloss:2.15992	validation-mlogloss:2.11330
[129]	train-mlogloss:2.15754	validation-mlogloss:2.11081
[130]	train-mlogloss:2.15531	validation-mlogloss:2.10830
[131]	train-mlogloss:2.15309	validation-mlogloss:2.10612
[132]	train-mlogloss:2.15083	validation-mlogloss:2.10371
[133]	train-mlogloss:2.14856	validation-mlogloss:2.10129
[134]	train-mlogloss:2.14639	validation-mlogloss:2.09904
[135]	train-mlogloss:2.14427	validation-mlogloss:2.09664
[136]	train-mlogloss:2.14205	validation-mlogloss:2.09412
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Saved model to disk.
2025-11-06 21:46:09.542511: 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 21:46:09.553950: 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 00:00:1762461969.566927 1826497 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762461969.571141 1826497 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762461969.581146 1826497 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461969.581164 1826497 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461969.581166 1826497 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461969.581168 1826497 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:46:09.584356: 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:2.70024	validation-mlogloss:2.69958
[1]	train-mlogloss:2.69218	validation-mlogloss:2.69067
[2]	train-mlogloss:2.68473	validation-mlogloss:2.68274
[3]	train-mlogloss:2.67762	validation-mlogloss:2.67517
[4]	train-mlogloss:2.67045	validation-mlogloss:2.66726
[5]	train-mlogloss:2.66246	validation-mlogloss:2.65824
[6]	train-mlogloss:2.65550	validation-mlogloss:2.65099
[7]	train-mlogloss:2.64827	validation-mlogloss:2.64350
[8]	train-mlogloss:2.64116	validation-mlogloss:2.63587
[9]	train-mlogloss:2.63425	validation-mlogloss:2.62823
[10]	train-mlogloss:2.62719	validation-mlogloss:2.62048
[11]	train-mlogloss:2.62014	validation-mlogloss:2.61246
[12]	train-mlogloss:2.61322	validation-mlogloss:2.60500
[13]	train-mlogloss:2.60687	validation-mlogloss:2.59812
[14]	train-mlogloss:2.60023	validation-mlogloss:2.59080
[15]	train-mlogloss:2.59376	validation-mlogloss:2.58344
[16]	train-mlogloss:2.58721	validation-mlogloss:2.57598
[17]	train-mlogloss:2.58084	validation-mlogloss:2.56905
[18]	train-mlogloss:2.57456	validation-mlogloss:2.56244
[19]	train-mlogloss:2.56819	validation-mlogloss:2.55540
[20]	train-mlogloss:2.56205	validation-mlogloss:2.54857
[21]	train-mlogloss:2.55600	validation-mlogloss:2.54190
[22]	train-mlogloss:2.55001	validation-mlogloss:2.53510
[23]	train-mlogloss:2.54421	validation-mlogloss:2.52886
[24]	train-mlogloss:2.53841	validation-mlogloss:2.52264
[25]	train-mlogloss:2.53259	validation-mlogloss:2.51600
[26]	train-mlogloss:2.52709	validation-mlogloss:2.51023
[27]	train-mlogloss:2.52147	validation-mlogloss:2.50384
[28]	train-mlogloss:2.51598	validation-mlogloss:2.49805
[29]	train-mlogloss:2.51048	validation-mlogloss:2.49185
[30]	train-mlogloss:2.50513	validation-mlogloss:2.48620
[31]	train-mlogloss:2.49972	validation-mlogloss:2.48014
[32]	train-mlogloss:2.49441	validation-mlogloss:2.47457
[33]	train-mlogloss:2.48931	validation-mlogloss:2.46922
[34]	train-mlogloss:2.48425	validation-mlogloss:2.46387
[35]	train-mlogloss:2.47912	validation-mlogloss:2.45792
[36]	train-mlogloss:2.47370	validation-mlogloss:2.45158
[37]	train-mlogloss:2.46879	validation-mlogloss:2.44652
[38]	train-mlogloss:2.46389	validation-mlogloss:2.44101
[39]	train-mlogloss:2.45931	validation-mlogloss:2.43618
[40]	train-mlogloss:2.45450	validation-mlogloss:2.43083
[41]	train-mlogloss:2.44978	validation-mlogloss:2.42564
[42]	train-mlogloss:2.44502	validation-mlogloss:2.42056
[43]	train-mlogloss:2.44029	validation-mlogloss:2.41557
[44]	train-mlogloss:2.43559	validation-mlogloss:2.41035
[45]	train-mlogloss:2.43087	validation-mlogloss:2.40527
[46]	train-mlogloss:2.42640	validation-mlogloss:2.40064
[47]	train-mlogloss:2.42162	validation-mlogloss:2.39538
[48]	train-mlogloss:2.41696	validation-mlogloss:2.38987
[49]	train-mlogloss:2.41223	validation-mlogloss:2.38447
[50]	train-mlogloss:2.40765	validation-mlogloss:2.37904
[51]	train-mlogloss:2.40335	validation-mlogloss:2.37433
[52]	train-mlogloss:2.39889	validation-mlogloss:2.36975
[53]	train-mlogloss:2.39435	validation-mlogloss:2.36454
[54]	train-mlogloss:2.39025	validation-mlogloss:2.36028
[55]	train-mlogloss:2.38596	validation-mlogloss:2.35569
[56]	train-mlogloss:2.38176	validation-mlogloss:2.35104
[57]	train-mlogloss:2.37739	validation-mlogloss:2.34625
[58]	train-mlogloss:2.37350	validation-mlogloss:2.34229
[59]	train-mlogloss:2.36930	validation-mlogloss:2.33738
[60]	train-mlogloss:2.36545	validation-mlogloss:2.33342
[61]	train-mlogloss:2.36136	validation-mlogloss:2.32877
[62]	train-mlogloss:2.35755	validation-mlogloss:2.32480
[63]	train-mlogloss:2.35373	validation-mlogloss:2.32071
[64]	train-mlogloss:2.34958	validation-mlogloss:2.31590
[65]	train-mlogloss:2.34559	validation-mlogloss:2.31148
[66]	train-mlogloss:2.34177	validation-mlogloss:2.30747
[67]	train-mlogloss:2.33787	validation-mlogloss:2.30323
[68]	train-mlogloss:2.33382	validation-mlogloss:2.29860
[69]	train-mlogloss:2.33016	validation-mlogloss:2.29463
[70]	train-mlogloss:2.32662	validation-mlogloss:2.29090
[71]	train-mlogloss:2.32282	validation-mlogloss:2.28676
[72]	train-mlogloss:2.31903	validation-mlogloss:2.28244
[73]	train-mlogloss:2.31544	validation-mlogloss:2.27858
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[75]	train-mlogloss:2.30849	validation-mlogloss:2.27103
[76]	train-mlogloss:2.30514	validation-mlogloss:2.26750
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[78]	train-mlogloss:2.29840	validation-mlogloss:2.26016
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[85]	train-mlogloss:2.27522	validation-mlogloss:2.23523
[86]	train-mlogloss:2.27176	validation-mlogloss:2.23135
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[88]	train-mlogloss:2.26544	validation-mlogloss:2.22487
[89]	train-mlogloss:2.26225	validation-mlogloss:2.22124
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[91]	train-mlogloss:2.25636	validation-mlogloss:2.21526
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[93]	train-mlogloss:2.25025	validation-mlogloss:2.20873
[94]	train-mlogloss:2.24737	validation-mlogloss:2.20576
[95]	train-mlogloss:2.24447	validation-mlogloss:2.20279
[96]	train-mlogloss:2.24155	validation-mlogloss:2.19956
[97]	train-mlogloss:2.23857	validation-mlogloss:2.19627
[98]	train-mlogloss:2.23588	validation-mlogloss:2.19360
[99]	train-mlogloss:2.23318	validation-mlogloss:2.19103
[100]	train-mlogloss:2.23031	validation-mlogloss:2.18784
[101]	train-mlogloss:2.22753	validation-mlogloss:2.18482
[102]	train-mlogloss:2.22458	validation-mlogloss:2.18174
[103]	train-mlogloss:2.22186	validation-mlogloss:2.17875
[104]	train-mlogloss:2.21903	validation-mlogloss:2.17570
[105]	train-mlogloss:2.21627	validation-mlogloss:2.17265
[106]	train-mlogloss:2.21348	validation-mlogloss:2.16981
[107]	train-mlogloss:2.21075	validation-mlogloss:2.16720
[108]	train-mlogloss:2.20810	validation-mlogloss:2.16450
[109]	train-mlogloss:2.20540	validation-mlogloss:2.16137
[110]	train-mlogloss:2.20279	validation-mlogloss:2.15840
[111]	train-mlogloss:2.20020	validation-mlogloss:2.15566
[112]	train-mlogloss:2.19763	validation-mlogloss:2.15304
[113]	train-mlogloss:2.19496	validation-mlogloss:2.15019
[114]	train-mlogloss:2.19254	validation-mlogloss:2.14780
[115]	train-mlogloss:2.18992	validation-mlogloss:2.14508
[116]	train-mlogloss:2.18748	validation-mlogloss:2.14251
[117]	train-mlogloss:2.18511	validation-mlogloss:2.14014
[118]	train-mlogloss:2.18267	validation-mlogloss:2.13758
[119]	train-mlogloss:2.18004	validation-mlogloss:2.13476
[120]	train-mlogloss:2.17747	validation-mlogloss:2.13221
[121]	train-mlogloss:2.17493	validation-mlogloss:2.12953
[122]	train-mlogloss:2.17241	validation-mlogloss:2.12668
[123]	train-mlogloss:2.17006	validation-mlogloss:2.12433
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[125]	train-mlogloss:2.16541	validation-mlogloss:2.11938
[126]	train-mlogloss:2.16307	validation-mlogloss:2.11673
[127]	train-mlogloss:2.16086	validation-mlogloss:2.11445
[128]	train-mlogloss:2.15851	validation-mlogloss:2.11209
[129]	train-mlogloss:2.15612	validation-mlogloss:2.10955
[130]	train-mlogloss:2.15401	validation-mlogloss:2.10749
[131]	train-mlogloss:2.15186	validation-mlogloss:2.10556
[132]	train-mlogloss:2.14966	validation-mlogloss:2.10335
[133]	train-mlogloss:2.14759	validation-mlogloss:2.10140
[134]	train-mlogloss:2.14544	validation-mlogloss:2.09939
[135]	train-mlogloss:2.14340	validation-mlogloss:2.09726
[136]	train-mlogloss:2.14123	validation-mlogloss:2.09494
[137]	train-mlogloss:2.13891	validation-mlogloss:2.09257
[138]	train-mlogloss:2.13660	validation-mlogloss:2.08995
[139]	train-mlogloss:2.13456	validation-mlogloss:2.08771
[140]	train-mlogloss:2.13244	validation-mlogloss:2.08555
[141]	train-mlogloss:2.13048	validation-mlogloss:2.08363
[142]	train-mlogloss:2.12833	validation-mlogloss:2.08135
[143]	train-mlogloss:2.12611	validation-mlogloss:2.07886
[144]	train-mlogloss:2.12399	validation-mlogloss:2.07685
[145]	train-mlogloss:2.12195	validation-mlogloss:2.07491
[146]	train-mlogloss:2.11981	validation-mlogloss:2.07264
[147]	train-mlogloss:2.11790	validation-mlogloss:2.07096
[148]	train-mlogloss:2.11592	validation-mlogloss:2.06879
[149]	train-mlogloss:2.11401	validation-mlogloss:2.06678
[150]	train-mlogloss:2.11201	validation-mlogloss:2.06468
[151]	train-mlogloss:2.11005	validation-mlogloss:2.06269
[152]	train-mlogloss:2.10812	validation-mlogloss:2.06073
[153]	train-mlogloss:2.10611	validation-mlogloss:2.05860
[154]	train-mlogloss:2.10419	validation-mlogloss:2.05682
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[402]	train-mlogloss:1.84102	validation-mlogloss:1.82632
[403]	train-mlogloss:1.84050	validation-mlogloss:1.82593
[404]	train-mlogloss:1.83987	validation-mlogloss:1.82536
[405]	train-mlogloss:1.83928	validation-mlogloss:1.82508
[406]	train-mlogloss:1.83869	validation-mlogloss:1.82471
[407]	train-mlogloss:1.83820	validation-mlogloss:1.82429
[408]	train-mlogloss:1.83774	validation-mlogloss:1.82395
[409]	train-mlogloss:1.83724	validation-mlogloss:1.82358
[410]	train-mlogloss:1.83674	validation-mlogloss:1.82316
[411]	train-mlogloss:1.83623	validation-mlogloss:1.82283
[412]	train-mlogloss:1.83563	validation-mlogloss:1.82241
[413]	train-mlogloss:1.83511	validation-mlogloss:1.82213
[414]	train-mlogloss:1.83460	validation-mlogloss:1.82173
[415]	train-mlogloss:1.83392	validation-mlogloss:1.82142
[416]	train-mlogloss:1.83340	validation-mlogloss:1.82100
[417]	train-mlogloss:1.83287	validation-mlogloss:1.82069
[418]	train-mlogloss:1.83241	validation-mlogloss:1.82048
[419]	train-mlogloss:1.83195	validation-mlogloss:1.82024
Saved model to disk.
2025-11-06 21:46:31.271258: 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 21:46:31.282913: 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 00:00:1762461991.295995 1826862 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762461991.300150 1826862 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762461991.310062 1826862 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461991.310082 1826862 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461991.310083 1826862 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762461991.310085 1826862 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:46:31.313243: 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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[21]	train-mlogloss:2.55741	validation-mlogloss:2.54450
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[25]	train-mlogloss:2.53423	validation-mlogloss:2.51890
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[34]	train-mlogloss:2.48597	validation-mlogloss:2.46665
[35]	train-mlogloss:2.48080	validation-mlogloss:2.46094
[36]	train-mlogloss:2.47576	validation-mlogloss:2.45531
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[39]	train-mlogloss:2.46052	validation-mlogloss:2.43846
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[42]	train-mlogloss:2.44589	validation-mlogloss:2.42219
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[55]	train-mlogloss:2.38742	validation-mlogloss:2.35857
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[72]	train-mlogloss:2.32023	validation-mlogloss:2.28478
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[75]	train-mlogloss:2.30935	validation-mlogloss:2.27303
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[132]	train-mlogloss:2.15007	validation-mlogloss:2.10252
[133]	train-mlogloss:2.14789	validation-mlogloss:2.10037
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[136]	train-mlogloss:2.14153	validation-mlogloss:2.09421
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[139]	train-mlogloss:2.13510	validation-mlogloss:2.08768
[140]	train-mlogloss:2.13302	validation-mlogloss:2.08568
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[398]	train-mlogloss:1.84353	validation-mlogloss:1.83056
[399]	train-mlogloss:1.84298	validation-mlogloss:1.83029
[400]	train-mlogloss:1.84245	validation-mlogloss:1.82992
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[402]	train-mlogloss:1.84129	validation-mlogloss:1.82906
[403]	train-mlogloss:1.84082	validation-mlogloss:1.82876
[404]	train-mlogloss:1.84022	validation-mlogloss:1.82839
[405]	train-mlogloss:1.83978	validation-mlogloss:1.82802
[406]	train-mlogloss:1.83920	validation-mlogloss:1.82770
[407]	train-mlogloss:1.83861	validation-mlogloss:1.82715
[408]	train-mlogloss:1.83810	validation-mlogloss:1.82683
[409]	train-mlogloss:1.83757	validation-mlogloss:1.82658
[410]	train-mlogloss:1.83710	validation-mlogloss:1.82624
[411]	train-mlogloss:1.83660	validation-mlogloss:1.82571
[412]	train-mlogloss:1.83613	validation-mlogloss:1.82544
[413]	train-mlogloss:1.83559	validation-mlogloss:1.82492
[414]	train-mlogloss:1.83505	validation-mlogloss:1.82454
[415]	train-mlogloss:1.83456	validation-mlogloss:1.82411
[416]	train-mlogloss:1.83412	validation-mlogloss:1.82390
[417]	train-mlogloss:1.83359	validation-mlogloss:1.82371
[418]	train-mlogloss:1.83316	validation-mlogloss:1.82345
[419]	train-mlogloss:1.83271	validation-mlogloss:1.82312
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.33 [%]
Global accuracy score (test) = 44.06 [%]
Global F1 score (train) = 43.86 [%]
Global F1 score (test) = 43.26 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.46      0.45       184
       CAMINAR USUAL SPEED       0.33      0.16      0.21       184
            CAMINAR ZIGZAG       0.31      0.53      0.39       184
          DE PIE BARRIENDO       0.73      0.41      0.52       184
   DE PIE DOBLANDO TOALLAS       0.46      0.45      0.45       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.39       184
          DE PIE USANDO PC       0.20      0.33      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.57      0.61       184
           SENTADO LEYENDO       0.44      0.39      0.41       184
         SENTADO USANDO PC       0.23      0.11      0.15       184
      SENTADO VIENDO LA TV       0.28      0.16      0.20       184
   SUBIR Y BAJAR ESCALERAS       0.66      0.56      0.61       184
                    TROTAR       0.65      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 7: 44.06 [%]
F1-score capturado en la ejecución 7: 43.26 [%]

=== EJECUCIÓN 8 ===

--- TRAIN (ejecución 8) ---

--- TEST (ejecución 8) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.13 [%]
Global accuracy score (test) = 44.14 [%]
Global F1 score (train) = 43.63 [%]
Global F1 score (test) = 43.34 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.49      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.46      0.44       184
       CAMINAR USUAL SPEED       0.34      0.16      0.22       184
            CAMINAR ZIGZAG       0.31      0.53      0.39       184
          DE PIE BARRIENDO       0.72      0.40      0.51       184
   DE PIE DOBLANDO TOALLAS       0.44      0.45      0.44       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.39       184
          DE PIE USANDO PC       0.20      0.32      0.24       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.59      0.62       184
           SENTADO LEYENDO       0.49      0.41      0.45       184
         SENTADO USANDO PC       0.23      0.11      0.15       184
      SENTADO VIENDO LA TV       0.24      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.65      0.56      0.60       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 8: 44.14 [%]
F1-score capturado en la ejecución 8: 43.34 [%]

=== EJECUCIÓN 9 ===

--- TRAIN (ejecución 9) ---

--- TEST (ejecución 9) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.2 [%]
Global accuracy score (test) = 44.36 [%]
Global F1 score (train) = 43.71 [%]
Global F1 score (test) = 43.6 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.46      0.45       184
       CAMINAR USUAL SPEED       0.34      0.18      0.23       184
            CAMINAR ZIGZAG       0.32      0.54      0.40       184
          DE PIE BARRIENDO       0.72      0.41      0.53       184
   DE PIE DOBLANDO TOALLAS       0.47      0.45      0.46       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.38       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.58      0.61       184
           SENTADO LEYENDO       0.45      0.40      0.42       184
         SENTADO USANDO PC       0.27      0.13      0.18       184
      SENTADO VIENDO LA TV       0.25      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.64      0.56      0.60       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.46      0.44      0.44      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 9: 44.36 [%]
F1-score capturado en la ejecución 9: 43.6 [%]

=== EJECUCIÓN 10 ===

--- TRAIN (ejecución 10) ---

--- TEST (ejecución 10) ---
2025-11-06 21:46:53.019427: 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 21:46:53.030626: 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 00:00:1762462013.043905 1827232 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462013.047891 1827232 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462013.057841 1827232 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462013.057857 1827232 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462013.057858 1827232 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462013.057860 1827232 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:46:53.060933: 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:2.70029	validation-mlogloss:2.69951
[1]	train-mlogloss:2.69271	validation-mlogloss:2.69140
[2]	train-mlogloss:2.68513	validation-mlogloss:2.68341
[3]	train-mlogloss:2.67784	validation-mlogloss:2.67535
[4]	train-mlogloss:2.67065	validation-mlogloss:2.66744
[5]	train-mlogloss:2.66351	validation-mlogloss:2.65952
[6]	train-mlogloss:2.65645	validation-mlogloss:2.65189
[7]	train-mlogloss:2.64943	validation-mlogloss:2.64455
[8]	train-mlogloss:2.64232	validation-mlogloss:2.63670
[9]	train-mlogloss:2.63576	validation-mlogloss:2.62968
[10]	train-mlogloss:2.62859	validation-mlogloss:2.62188
[11]	train-mlogloss:2.62161	validation-mlogloss:2.61412
[12]	train-mlogloss:2.61491	validation-mlogloss:2.60690
[13]	train-mlogloss:2.60808	validation-mlogloss:2.59919
[14]	train-mlogloss:2.60151	validation-mlogloss:2.59181
[15]	train-mlogloss:2.59506	validation-mlogloss:2.58462
[16]	train-mlogloss:2.58897	validation-mlogloss:2.57807
[17]	train-mlogloss:2.58278	validation-mlogloss:2.57127
[18]	train-mlogloss:2.57649	validation-mlogloss:2.56464
[19]	train-mlogloss:2.57030	validation-mlogloss:2.55764
[20]	train-mlogloss:2.56410	validation-mlogloss:2.55081
[21]	train-mlogloss:2.55825	validation-mlogloss:2.54465
[22]	train-mlogloss:2.55232	validation-mlogloss:2.53866
[23]	train-mlogloss:2.54648	validation-mlogloss:2.53229
[24]	train-mlogloss:2.54054	validation-mlogloss:2.52547
[25]	train-mlogloss:2.53479	validation-mlogloss:2.51921
[26]	train-mlogloss:2.52914	validation-mlogloss:2.51307
[27]	train-mlogloss:2.52350	validation-mlogloss:2.50695
[28]	train-mlogloss:2.51790	validation-mlogloss:2.50072
[29]	train-mlogloss:2.51260	validation-mlogloss:2.49494
[30]	train-mlogloss:2.50730	validation-mlogloss:2.48903
[31]	train-mlogloss:2.50174	validation-mlogloss:2.48276
[32]	train-mlogloss:2.49614	validation-mlogloss:2.47636
[33]	train-mlogloss:2.49081	validation-mlogloss:2.47028
[34]	train-mlogloss:2.48556	validation-mlogloss:2.46420
[35]	train-mlogloss:2.48039	validation-mlogloss:2.45857
[36]	train-mlogloss:2.47520	validation-mlogloss:2.45278
[37]	train-mlogloss:2.47023	validation-mlogloss:2.44722
[38]	train-mlogloss:2.46549	validation-mlogloss:2.44229
[39]	train-mlogloss:2.46054	validation-mlogloss:2.43690
[40]	train-mlogloss:2.45544	validation-mlogloss:2.43136
[41]	train-mlogloss:2.45017	validation-mlogloss:2.42534
[42]	train-mlogloss:2.44537	validation-mlogloss:2.42016
[43]	train-mlogloss:2.44079	validation-mlogloss:2.41521
[44]	train-mlogloss:2.43616	validation-mlogloss:2.41008
[45]	train-mlogloss:2.43142	validation-mlogloss:2.40483
[46]	train-mlogloss:2.42690	validation-mlogloss:2.39972
[47]	train-mlogloss:2.42229	validation-mlogloss:2.39472
[48]	train-mlogloss:2.41788	validation-mlogloss:2.39042
[49]	train-mlogloss:2.41340	validation-mlogloss:2.38548
[50]	train-mlogloss:2.40897	validation-mlogloss:2.38037
[51]	train-mlogloss:2.40456	validation-mlogloss:2.37576
[52]	train-mlogloss:2.39996	validation-mlogloss:2.37056
[53]	train-mlogloss:2.39565	validation-mlogloss:2.36588
[54]	train-mlogloss:2.39144	validation-mlogloss:2.36125
[55]	train-mlogloss:2.38741	validation-mlogloss:2.35704
[56]	train-mlogloss:2.38331	validation-mlogloss:2.35227
[57]	train-mlogloss:2.37898	validation-mlogloss:2.34729
[58]	train-mlogloss:2.37487	validation-mlogloss:2.34284
[59]	train-mlogloss:2.37071	validation-mlogloss:2.33840
[60]	train-mlogloss:2.36662	validation-mlogloss:2.33404
[61]	train-mlogloss:2.36260	validation-mlogloss:2.32974
[62]	train-mlogloss:2.35844	validation-mlogloss:2.32481
[63]	train-mlogloss:2.35456	validation-mlogloss:2.32070
[64]	train-mlogloss:2.35049	validation-mlogloss:2.31639
[65]	train-mlogloss:2.34642	validation-mlogloss:2.31220
[66]	train-mlogloss:2.34266	validation-mlogloss:2.30807
[67]	train-mlogloss:2.33886	validation-mlogloss:2.30378
[68]	train-mlogloss:2.33488	validation-mlogloss:2.29956
[69]	train-mlogloss:2.33097	validation-mlogloss:2.29541
[70]	train-mlogloss:2.32722	validation-mlogloss:2.29122
[71]	train-mlogloss:2.32348	validation-mlogloss:2.28698
[72]	train-mlogloss:2.31995	validation-mlogloss:2.28317
[73]	train-mlogloss:2.31619	validation-mlogloss:2.27887
[74]	train-mlogloss:2.31263	validation-mlogloss:2.27490
[75]	train-mlogloss:2.30915	validation-mlogloss:2.27125
[76]	train-mlogloss:2.30548	validation-mlogloss:2.26705
[77]	train-mlogloss:2.30181	validation-mlogloss:2.26284
[78]	train-mlogloss:2.29851	validation-mlogloss:2.25952
[79]	train-mlogloss:2.29492	validation-mlogloss:2.25563
[80]	train-mlogloss:2.29158	validation-mlogloss:2.25214
[81]	train-mlogloss:2.28836	validation-mlogloss:2.24887
[82]	train-mlogloss:2.28489	validation-mlogloss:2.24504
[83]	train-mlogloss:2.28160	validation-mlogloss:2.24136
[84]	train-mlogloss:2.27847	validation-mlogloss:2.23811
[85]	train-mlogloss:2.27544	validation-mlogloss:2.23522
[86]	train-mlogloss:2.27243	validation-mlogloss:2.23223
[87]	train-mlogloss:2.26913	validation-mlogloss:2.22869
[88]	train-mlogloss:2.26608	validation-mlogloss:2.22569
[89]	train-mlogloss:2.26281	validation-mlogloss:2.22209
[90]	train-mlogloss:2.25994	validation-mlogloss:2.21914
[91]	train-mlogloss:2.25679	validation-mlogloss:2.21565
[92]	train-mlogloss:2.25365	validation-mlogloss:2.21236
[93]	train-mlogloss:2.25053	validation-mlogloss:2.20882
[94]	train-mlogloss:2.24753	validation-mlogloss:2.20552
[95]	train-mlogloss:2.24448	validation-mlogloss:2.20248
[96]	train-mlogloss:2.24169	validation-mlogloss:2.19935
[97]	train-mlogloss:2.23885	validation-mlogloss:2.19638
[98]	train-mlogloss:2.23579	validation-mlogloss:2.19307
[99]	train-mlogloss:2.23280	validation-mlogloss:2.18986
[100]	train-mlogloss:2.22994	validation-mlogloss:2.18665
[101]	train-mlogloss:2.22700	validation-mlogloss:2.18340
[102]	train-mlogloss:2.22425	validation-mlogloss:2.18047
[103]	train-mlogloss:2.22127	validation-mlogloss:2.17734
[104]	train-mlogloss:2.21866	validation-mlogloss:2.17447
[105]	train-mlogloss:2.21599	validation-mlogloss:2.17152
[106]	train-mlogloss:2.21327	validation-mlogloss:2.16865
[107]	train-mlogloss:2.21037	validation-mlogloss:2.16535
[108]	train-mlogloss:2.20768	validation-mlogloss:2.16238
[109]	train-mlogloss:2.20496	validation-mlogloss:2.15943
[110]	train-mlogloss:2.20227	validation-mlogloss:2.15658
[111]	train-mlogloss:2.19956	validation-mlogloss:2.15364
[112]	train-mlogloss:2.19699	validation-mlogloss:2.15077
[113]	train-mlogloss:2.19449	validation-mlogloss:2.14837
[114]	train-mlogloss:2.19192	validation-mlogloss:2.14552
[115]	train-mlogloss:2.18942	validation-mlogloss:2.14278
[116]	train-mlogloss:2.18693	validation-mlogloss:2.14027
[117]	train-mlogloss:2.18458	validation-mlogloss:2.13782
[118]	train-mlogloss:2.18215	validation-mlogloss:2.13545
[119]	train-mlogloss:2.17975	validation-mlogloss:2.13296
[120]	train-mlogloss:2.17738	validation-mlogloss:2.13064
[121]	train-mlogloss:2.17511	validation-mlogloss:2.12813
[122]	train-mlogloss:2.17273	validation-mlogloss:2.12560
[123]	train-mlogloss:2.17044	validation-mlogloss:2.12318
[124]	train-mlogloss:2.16803	validation-mlogloss:2.12078
[125]	train-mlogloss:2.16576	validation-mlogloss:2.11846
[126]	train-mlogloss:2.16356	validation-mlogloss:2.11639
[127]	train-mlogloss:2.16124	validation-mlogloss:2.11409
[128]	train-mlogloss:2.15897	validation-mlogloss:2.11181
[129]	train-mlogloss:2.15663	validation-mlogloss:2.10918
[130]	train-mlogloss:2.15454	validation-mlogloss:2.10708
[131]	train-mlogloss:2.15221	validation-mlogloss:2.10455
[132]	train-mlogloss:2.14988	validation-mlogloss:2.10199
[133]	train-mlogloss:2.14762	validation-mlogloss:2.09966
[134]	train-mlogloss:2.14531	validation-mlogloss:2.09713
[135]	train-mlogloss:2.14306	validation-mlogloss:2.09500
[136]	train-mlogloss:2.14096	validation-mlogloss:2.09300
[137]	train-mlogloss:2.13887	validation-mlogloss:2.09071
[138]	train-mlogloss:2.13682	validation-mlogloss:2.08866
[139]	train-mlogloss:2.13473	validation-mlogloss:2.08645
[140]	train-mlogloss:2.13261	validation-mlogloss:2.08437
[141]	train-mlogloss:2.13047	validation-mlogloss:2.08228
[142]	train-mlogloss:2.12838	validation-mlogloss:2.08027
[143]	train-mlogloss:2.12631	validation-mlogloss:2.07830
[144]	train-mlogloss:2.12428	validation-mlogloss:2.07638
[145]	train-mlogloss:2.12227	validation-mlogloss:2.07439
[146]	train-mlogloss:2.12032	validation-mlogloss:2.07258
[147]	train-mlogloss:2.11828	validation-mlogloss:2.07021
[148]	train-mlogloss:2.11634	validation-mlogloss:2.06829
[149]	train-mlogloss:2.11428	validation-mlogloss:2.06623
[150]	train-mlogloss:2.11230	validation-mlogloss:2.06432
[151]	train-mlogloss:2.11042	validation-mlogloss:2.06256
[152]	train-mlogloss:2.10847	validation-mlogloss:2.06061
[153]	train-mlogloss:2.10658	validation-mlogloss:2.05890
[154]	train-mlogloss:2.10476	validation-mlogloss:2.05719
[155]	train-mlogloss:2.10281	validation-mlogloss:2.05500
[156]	train-mlogloss:2.10087	validation-mlogloss:2.05304
[157]	train-mlogloss:2.09881	validation-mlogloss:2.05099
[158]	train-mlogloss:2.09697	validation-mlogloss:2.04906
[159]	train-mlogloss:2.09518	validation-mlogloss:2.04734
[160]	train-mlogloss:2.09332	validation-mlogloss:2.04553
[161]	train-mlogloss:2.09147	validation-mlogloss:2.04368
[162]	train-mlogloss:2.08958	validation-mlogloss:2.04214
[163]	train-mlogloss:2.08779	validation-mlogloss:2.04027
[164]	train-mlogloss:2.08601	validation-mlogloss:2.03870
[165]	train-mlogloss:2.08409	validation-mlogloss:2.03679
[166]	train-mlogloss:2.08240	validation-mlogloss:2.03531
[167]	train-mlogloss:2.08062	validation-mlogloss:2.03364
[168]	train-mlogloss:2.07895	validation-mlogloss:2.03221
[169]	train-mlogloss:2.07724	validation-mlogloss:2.03043
[170]	train-mlogloss:2.07543	validation-mlogloss:2.02877
[171]	train-mlogloss:2.07365	validation-mlogloss:2.02678
[172]	train-mlogloss:2.07188	validation-mlogloss:2.02504
[173]	train-mlogloss:2.07017	validation-mlogloss:2.02326
[174]	train-mlogloss:2.06850	validation-mlogloss:2.02168
[175]	train-mlogloss:2.06680	validation-mlogloss:2.01989
[176]	train-mlogloss:2.06513	validation-mlogloss:2.01819
[177]	train-mlogloss:2.06338	validation-mlogloss:2.01640
[178]	train-mlogloss:2.06172	validation-mlogloss:2.01487
[179]	train-mlogloss:2.06014	validation-mlogloss:2.01348
[180]	train-mlogloss:2.05851	validation-mlogloss:2.01185
[181]	train-mlogloss:2.05689	validation-mlogloss:2.01038
[182]	train-mlogloss:2.05529	validation-mlogloss:2.00896
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[389]	train-mlogloss:1.84746	validation-mlogloss:1.83161
[390]	train-mlogloss:1.84682	validation-mlogloss:1.83105
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[393]	train-mlogloss:1.84510	validation-mlogloss:1.82995
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[395]	train-mlogloss:1.84402	validation-mlogloss:1.82915
[396]	train-mlogloss:1.84354	validation-mlogloss:1.82888
[397]	train-mlogloss:1.84297	validation-mlogloss:1.82842
[398]	train-mlogloss:1.84237	validation-mlogloss:1.82791
[399]	train-mlogloss:1.84174	validation-mlogloss:1.82748
[400]	train-mlogloss:1.84118	validation-mlogloss:1.82705
[401]	train-mlogloss:1.84067	validation-mlogloss:1.82668
[402]	train-mlogloss:1.84008	validation-mlogloss:1.82627
[403]	train-mlogloss:1.83947	validation-mlogloss:1.82585
[404]	train-mlogloss:1.83891	validation-mlogloss:1.82544
[405]	train-mlogloss:1.83825	validation-mlogloss:1.82508
[406]	train-mlogloss:1.83773	validation-mlogloss:1.82472
[407]	train-mlogloss:1.83715	validation-mlogloss:1.82426
[408]	train-mlogloss:1.83669	validation-mlogloss:1.82391
[409]	train-mlogloss:1.83623	validation-mlogloss:1.82357
[410]	train-mlogloss:1.83565	validation-mlogloss:1.82308
[411]	train-mlogloss:1.83513	validation-mlogloss:1.82269
[412]	train-mlogloss:1.83462	validation-mlogloss:1.82240
[413]	train-mlogloss:1.83412	validation-mlogloss:1.82218
[414]	train-mlogloss:1.83359	validation-mlogloss:1.82174
[415]	train-mlogloss:1.83312	validation-mlogloss:1.82136
[416]	train-mlogloss:1.83270	validation-mlogloss:1.82114
[417]	train-mlogloss:1.83213	validation-mlogloss:1.82081
[418]	train-mlogloss:1.83168	validation-mlogloss:1.82053
[419]	train-mlogloss:1.83120	validation-mlogloss:1.82006
Saved model to disk.
2025-11-06 21:47:14.843177: 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 21:47:14.854496: 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 00:00:1762462034.867417 1827623 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462034.871494 1827623 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462034.881198 1827623 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462034.881215 1827623 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462034.881217 1827623 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462034.881218 1827623 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:47:14.884362: 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:2.68561	validation-mlogloss:2.68382
[3]	train-mlogloss:2.67822	validation-mlogloss:2.67614
[4]	train-mlogloss:2.67110	validation-mlogloss:2.66835
[5]	train-mlogloss:2.66427	validation-mlogloss:2.66137
[6]	train-mlogloss:2.65698	validation-mlogloss:2.65375
[7]	train-mlogloss:2.64984	validation-mlogloss:2.64596
[8]	train-mlogloss:2.64257	validation-mlogloss:2.63826
[9]	train-mlogloss:2.63554	validation-mlogloss:2.63072
[10]	train-mlogloss:2.62872	validation-mlogloss:2.62306
[11]	train-mlogloss:2.62185	validation-mlogloss:2.61546
[12]	train-mlogloss:2.61490	validation-mlogloss:2.60781
[13]	train-mlogloss:2.60791	validation-mlogloss:2.60011
[14]	train-mlogloss:2.60113	validation-mlogloss:2.59223
[15]	train-mlogloss:2.59454	validation-mlogloss:2.58487
[16]	train-mlogloss:2.58803	validation-mlogloss:2.57752
[17]	train-mlogloss:2.58183	validation-mlogloss:2.57104
[18]	train-mlogloss:2.57535	validation-mlogloss:2.56423
[19]	train-mlogloss:2.56908	validation-mlogloss:2.55739
[20]	train-mlogloss:2.56316	validation-mlogloss:2.55076
[21]	train-mlogloss:2.55682	validation-mlogloss:2.54383
[22]	train-mlogloss:2.55069	validation-mlogloss:2.53706
[23]	train-mlogloss:2.54458	validation-mlogloss:2.53038
[24]	train-mlogloss:2.53888	validation-mlogloss:2.52403
[25]	train-mlogloss:2.53320	validation-mlogloss:2.51786
[26]	train-mlogloss:2.52761	validation-mlogloss:2.51183
[27]	train-mlogloss:2.52197	validation-mlogloss:2.50553
[28]	train-mlogloss:2.51658	validation-mlogloss:2.49952
[29]	train-mlogloss:2.51078	validation-mlogloss:2.49304
[30]	train-mlogloss:2.50533	validation-mlogloss:2.48715
[31]	train-mlogloss:2.50010	validation-mlogloss:2.48119
[32]	train-mlogloss:2.49500	validation-mlogloss:2.47566
[33]	train-mlogloss:2.48979	validation-mlogloss:2.46989
[34]	train-mlogloss:2.48469	validation-mlogloss:2.46430
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[335]	train-mlogloss:1.88455	validation-mlogloss:1.85917
[336]	train-mlogloss:1.88378	validation-mlogloss:1.85856
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[339]	train-mlogloss:1.88162	validation-mlogloss:1.85683
[340]	train-mlogloss:1.88078	validation-mlogloss:1.85628
[341]	train-mlogloss:1.88005	validation-mlogloss:1.85574
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[343]	train-mlogloss:1.87857	validation-mlogloss:1.85459
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[346]	train-mlogloss:1.87626	validation-mlogloss:1.85287
[347]	train-mlogloss:1.87549	validation-mlogloss:1.85226
[348]	train-mlogloss:1.87478	validation-mlogloss:1.85168
[349]	train-mlogloss:1.87401	validation-mlogloss:1.85120
[350]	train-mlogloss:1.87337	validation-mlogloss:1.85078
[351]	train-mlogloss:1.87267	validation-mlogloss:1.85029
[352]	train-mlogloss:1.87193	validation-mlogloss:1.84961
[353]	train-mlogloss:1.87126	validation-mlogloss:1.84929
[354]	train-mlogloss:1.87061	validation-mlogloss:1.84886
[355]	train-mlogloss:1.86991	validation-mlogloss:1.84837
[356]	train-mlogloss:1.86925	validation-mlogloss:1.84786
[357]	train-mlogloss:1.86858	validation-mlogloss:1.84726
[358]	train-mlogloss:1.86785	validation-mlogloss:1.84670
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[367]	train-mlogloss:1.86207	validation-mlogloss:1.84253
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[370]	train-mlogloss:1.86015	validation-mlogloss:1.84079
[371]	train-mlogloss:1.85946	validation-mlogloss:1.84042
[372]	train-mlogloss:1.85880	validation-mlogloss:1.83992
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[374]	train-mlogloss:1.85750	validation-mlogloss:1.83884
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[386]	train-mlogloss:1.85025	validation-mlogloss:1.83348
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[388]	train-mlogloss:1.84924	validation-mlogloss:1.83298
[389]	train-mlogloss:1.84868	validation-mlogloss:1.83265
[390]	train-mlogloss:1.84805	validation-mlogloss:1.83214
[391]	train-mlogloss:1.84749	validation-mlogloss:1.83168
[392]	train-mlogloss:1.84687	validation-mlogloss:1.83129
[393]	train-mlogloss:1.84626	validation-mlogloss:1.83100
[394]	train-mlogloss:1.84568	validation-mlogloss:1.83066
[395]	train-mlogloss:1.84515	validation-mlogloss:1.83044
[396]	train-mlogloss:1.84446	validation-mlogloss:1.82990
[397]	train-mlogloss:1.84392	validation-mlogloss:1.82973
[398]	train-mlogloss:1.84340	validation-mlogloss:1.82945
[399]	train-mlogloss:1.84286	validation-mlogloss:1.82906
[400]	train-mlogloss:1.84229	validation-mlogloss:1.82866
[401]	train-mlogloss:1.84172	validation-mlogloss:1.82822
[402]	train-mlogloss:1.84109	validation-mlogloss:1.82778
[403]	train-mlogloss:1.84052	validation-mlogloss:1.82731
[404]	train-mlogloss:1.83998	validation-mlogloss:1.82684
[405]	train-mlogloss:1.83942	validation-mlogloss:1.82644
[406]	train-mlogloss:1.83886	validation-mlogloss:1.82607
[407]	train-mlogloss:1.83838	validation-mlogloss:1.82577
[408]	train-mlogloss:1.83780	validation-mlogloss:1.82539
[409]	train-mlogloss:1.83721	validation-mlogloss:1.82495
[410]	train-mlogloss:1.83668	validation-mlogloss:1.82464
[411]	train-mlogloss:1.83610	validation-mlogloss:1.82435
[412]	train-mlogloss:1.83551	validation-mlogloss:1.82387
[413]	train-mlogloss:1.83506	validation-mlogloss:1.82360
[414]	train-mlogloss:1.83460	validation-mlogloss:1.82322
[415]	train-mlogloss:1.83410	validation-mlogloss:1.82285
[416]	train-mlogloss:1.83350	validation-mlogloss:1.82239
[417]	train-mlogloss:1.83294	validation-mlogloss:1.82203
[418]	train-mlogloss:1.83246	validation-mlogloss:1.82163
[419]	train-mlogloss:1.83197	validation-mlogloss:1.82137
Saved model to disk.
2025-11-06 21:47:37.162810: 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 21:47:37.174164: 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 00:00:1762462057.187783 1827993 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462057.191808 1827993 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462057.202174 1827993 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462057.202195 1827993 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462057.202205 1827993 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462057.202206 1827993 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:47:37.205505: 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:2.69294	validation-mlogloss:2.69204
[2]	train-mlogloss:2.68576	validation-mlogloss:2.68491
[3]	train-mlogloss:2.67860	validation-mlogloss:2.67714
[4]	train-mlogloss:2.67165	validation-mlogloss:2.66992
[5]	train-mlogloss:2.66449	validation-mlogloss:2.66222
[6]	train-mlogloss:2.65743	validation-mlogloss:2.65440
[7]	train-mlogloss:2.65030	validation-mlogloss:2.64710
[8]	train-mlogloss:2.64321	validation-mlogloss:2.63956
[9]	train-mlogloss:2.63640	validation-mlogloss:2.63221
[10]	train-mlogloss:2.62926	validation-mlogloss:2.62425
[11]	train-mlogloss:2.62277	validation-mlogloss:2.61716
[12]	train-mlogloss:2.61589	validation-mlogloss:2.60936
[13]	train-mlogloss:2.60912	validation-mlogloss:2.60191
[14]	train-mlogloss:2.60238	validation-mlogloss:2.59426
[15]	train-mlogloss:2.59577	validation-mlogloss:2.58693
[16]	train-mlogloss:2.58906	validation-mlogloss:2.57948
[17]	train-mlogloss:2.58238	validation-mlogloss:2.57180
[18]	train-mlogloss:2.57604	validation-mlogloss:2.56475
[19]	train-mlogloss:2.56975	validation-mlogloss:2.55788
[20]	train-mlogloss:2.56394	validation-mlogloss:2.55161
[21]	train-mlogloss:2.55776	validation-mlogloss:2.54455
[22]	train-mlogloss:2.55192	validation-mlogloss:2.53834
[23]	train-mlogloss:2.54595	validation-mlogloss:2.53163
[24]	train-mlogloss:2.54032	validation-mlogloss:2.52591
[25]	train-mlogloss:2.53447	validation-mlogloss:2.51963
[26]	train-mlogloss:2.52899	validation-mlogloss:2.51355
[27]	train-mlogloss:2.52337	validation-mlogloss:2.50731
[28]	train-mlogloss:2.51763	validation-mlogloss:2.50075
[29]	train-mlogloss:2.51228	validation-mlogloss:2.49501
[30]	train-mlogloss:2.50679	validation-mlogloss:2.48882
[31]	train-mlogloss:2.50133	validation-mlogloss:2.48277
[32]	train-mlogloss:2.49604	validation-mlogloss:2.47715
[33]	train-mlogloss:2.49093	validation-mlogloss:2.47160
[34]	train-mlogloss:2.48568	validation-mlogloss:2.46601
[35]	train-mlogloss:2.48050	validation-mlogloss:2.46030
[36]	train-mlogloss:2.47520	validation-mlogloss:2.45460
[37]	train-mlogloss:2.47008	validation-mlogloss:2.44896
[38]	train-mlogloss:2.46499	validation-mlogloss:2.44318
[39]	train-mlogloss:2.45975	validation-mlogloss:2.43722
[40]	train-mlogloss:2.45479	validation-mlogloss:2.43192
[41]	train-mlogloss:2.45001	validation-mlogloss:2.42674
[42]	train-mlogloss:2.44514	validation-mlogloss:2.42120
[43]	train-mlogloss:2.44046	validation-mlogloss:2.41633
[44]	train-mlogloss:2.43606	validation-mlogloss:2.41191
[45]	train-mlogloss:2.43151	validation-mlogloss:2.40683
[46]	train-mlogloss:2.42703	validation-mlogloss:2.40218
[47]	train-mlogloss:2.42253	validation-mlogloss:2.39744
[48]	train-mlogloss:2.41814	validation-mlogloss:2.39274
[49]	train-mlogloss:2.41366	validation-mlogloss:2.38772
[50]	train-mlogloss:2.40933	validation-mlogloss:2.38324
[51]	train-mlogloss:2.40468	validation-mlogloss:2.37804
[52]	train-mlogloss:2.40023	validation-mlogloss:2.37308
[53]	train-mlogloss:2.39600	validation-mlogloss:2.36855
[54]	train-mlogloss:2.39133	validation-mlogloss:2.36319
[55]	train-mlogloss:2.38705	validation-mlogloss:2.35834
[56]	train-mlogloss:2.38294	validation-mlogloss:2.35410
[57]	train-mlogloss:2.37859	validation-mlogloss:2.34927
[58]	train-mlogloss:2.37416	validation-mlogloss:2.34435
[59]	train-mlogloss:2.37013	validation-mlogloss:2.33998
[60]	train-mlogloss:2.36585	validation-mlogloss:2.33518
[61]	train-mlogloss:2.36167	validation-mlogloss:2.33040
[62]	train-mlogloss:2.35794	validation-mlogloss:2.32651
[63]	train-mlogloss:2.35383	validation-mlogloss:2.32209
[64]	train-mlogloss:2.34993	validation-mlogloss:2.31777
[65]	train-mlogloss:2.34587	validation-mlogloss:2.31315
[66]	train-mlogloss:2.34215	validation-mlogloss:2.30926
[67]	train-mlogloss:2.33848	validation-mlogloss:2.30538
[68]	train-mlogloss:2.33444	validation-mlogloss:2.30073
[69]	train-mlogloss:2.33085	validation-mlogloss:2.29671
[70]	train-mlogloss:2.32691	validation-mlogloss:2.29237
[71]	train-mlogloss:2.32313	validation-mlogloss:2.28814
[72]	train-mlogloss:2.31940	validation-mlogloss:2.28389
[73]	train-mlogloss:2.31581	validation-mlogloss:2.28003
[74]	train-mlogloss:2.31237	validation-mlogloss:2.27641
[75]	train-mlogloss:2.30898	validation-mlogloss:2.27279
[76]	train-mlogloss:2.30553	validation-mlogloss:2.26912
[77]	train-mlogloss:2.30215	validation-mlogloss:2.26541
[78]	train-mlogloss:2.29860	validation-mlogloss:2.26148
[79]	train-mlogloss:2.29505	validation-mlogloss:2.25738
[80]	train-mlogloss:2.29183	validation-mlogloss:2.25403
[81]	train-mlogloss:2.28878	validation-mlogloss:2.25101
[82]	train-mlogloss:2.28545	validation-mlogloss:2.24729
[83]	train-mlogloss:2.28220	validation-mlogloss:2.24372
[84]	train-mlogloss:2.27874	validation-mlogloss:2.23986
[85]	train-mlogloss:2.27562	validation-mlogloss:2.23659
[86]	train-mlogloss:2.27242	validation-mlogloss:2.23307
[87]	train-mlogloss:2.26939	validation-mlogloss:2.23002
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[89]	train-mlogloss:2.26293	validation-mlogloss:2.22301
[90]	train-mlogloss:2.25971	validation-mlogloss:2.21956
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[94]	train-mlogloss:2.24749	validation-mlogloss:2.20631
[95]	train-mlogloss:2.24463	validation-mlogloss:2.20307
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[97]	train-mlogloss:2.23891	validation-mlogloss:2.19744
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[99]	train-mlogloss:2.23300	validation-mlogloss:2.19101
[100]	train-mlogloss:2.23001	validation-mlogloss:2.18800
[101]	train-mlogloss:2.22723	validation-mlogloss:2.18517
[102]	train-mlogloss:2.22434	validation-mlogloss:2.18182
[103]	train-mlogloss:2.22165	validation-mlogloss:2.17916
[104]	train-mlogloss:2.21906	validation-mlogloss:2.17652
[105]	train-mlogloss:2.21644	validation-mlogloss:2.17386
[106]	train-mlogloss:2.21360	validation-mlogloss:2.17086
[107]	train-mlogloss:2.21106	validation-mlogloss:2.16831
[108]	train-mlogloss:2.20840	validation-mlogloss:2.16547
[109]	train-mlogloss:2.20580	validation-mlogloss:2.16291
[110]	train-mlogloss:2.20313	validation-mlogloss:2.16006
[111]	train-mlogloss:2.20064	validation-mlogloss:2.15755
[112]	train-mlogloss:2.19797	validation-mlogloss:2.15465
[113]	train-mlogloss:2.19542	validation-mlogloss:2.15206
[114]	train-mlogloss:2.19274	validation-mlogloss:2.14903
[115]	train-mlogloss:2.19021	validation-mlogloss:2.14658
[116]	train-mlogloss:2.18783	validation-mlogloss:2.14439
[117]	train-mlogloss:2.18531	validation-mlogloss:2.14170
[118]	train-mlogloss:2.18293	validation-mlogloss:2.13928
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[120]	train-mlogloss:2.17798	validation-mlogloss:2.13395
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[123]	train-mlogloss:2.17067	validation-mlogloss:2.12623
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[126]	train-mlogloss:2.16384	validation-mlogloss:2.11938
[127]	train-mlogloss:2.16140	validation-mlogloss:2.11643
[128]	train-mlogloss:2.15894	validation-mlogloss:2.11370
[129]	train-mlogloss:2.15674	validation-mlogloss:2.11171
[130]	train-mlogloss:2.15450	validation-mlogloss:2.10926
[131]	train-mlogloss:2.15219	validation-mlogloss:2.10693
[132]	train-mlogloss:2.14987	validation-mlogloss:2.10460
[133]	train-mlogloss:2.14767	validation-mlogloss:2.10223
[134]	train-mlogloss:2.14542	validation-mlogloss:2.09996
[135]	train-mlogloss:2.14333	validation-mlogloss:2.09775
[136]	train-mlogloss:2.14115	validation-mlogloss:2.09552
[137]	train-mlogloss:2.13910	validation-mlogloss:2.09329
[138]	train-mlogloss:2.13704	validation-mlogloss:2.09123
[139]	train-mlogloss:2.13486	validation-mlogloss:2.08895
[140]	train-mlogloss:2.13286	validation-mlogloss:2.08709
[141]	train-mlogloss:2.13076	validation-mlogloss:2.08491
[142]	train-mlogloss:2.12873	validation-mlogloss:2.08304
[143]	train-mlogloss:2.12667	validation-mlogloss:2.08073
[144]	train-mlogloss:2.12466	validation-mlogloss:2.07842
[145]	train-mlogloss:2.12268	validation-mlogloss:2.07634
[146]	train-mlogloss:2.12051	validation-mlogloss:2.07396
[147]	train-mlogloss:2.11861	validation-mlogloss:2.07199
[148]	train-mlogloss:2.11651	validation-mlogloss:2.07007
[149]	train-mlogloss:2.11458	validation-mlogloss:2.06826
[150]	train-mlogloss:2.11253	validation-mlogloss:2.06586
[151]	train-mlogloss:2.11052	validation-mlogloss:2.06374
[152]	train-mlogloss:2.10855	validation-mlogloss:2.06185
[153]	train-mlogloss:2.10640	validation-mlogloss:2.05942
[154]	train-mlogloss:2.10452	validation-mlogloss:2.05765
[155]	train-mlogloss:2.10261	validation-mlogloss:2.05580
[156]	train-mlogloss:2.10073	validation-mlogloss:2.05407
[157]	train-mlogloss:2.09892	validation-mlogloss:2.05252
[158]	train-mlogloss:2.09725	validation-mlogloss:2.05094
[159]	train-mlogloss:2.09543	validation-mlogloss:2.04919
[160]	train-mlogloss:2.09358	validation-mlogloss:2.04721
[161]	train-mlogloss:2.09180	validation-mlogloss:2.04542
[162]	train-mlogloss:2.08997	validation-mlogloss:2.04364
[163]	train-mlogloss:2.08819	validation-mlogloss:2.04212
[164]	train-mlogloss:2.08641	validation-mlogloss:2.04038
[165]	train-mlogloss:2.08463	validation-mlogloss:2.03879
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[171]	train-mlogloss:2.07424	validation-mlogloss:2.02825
[172]	train-mlogloss:2.07257	validation-mlogloss:2.02666
[173]	train-mlogloss:2.07079	validation-mlogloss:2.02506
[174]	train-mlogloss:2.06897	validation-mlogloss:2.02332
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[187]	train-mlogloss:2.04752	validation-mlogloss:2.00259
[188]	train-mlogloss:2.04595	validation-mlogloss:2.00100
[189]	train-mlogloss:2.04430	validation-mlogloss:1.99933
[190]	train-mlogloss:2.04274	validation-mlogloss:1.99768
[191]	train-mlogloss:2.04112	validation-mlogloss:1.99604
[192]	train-mlogloss:2.03950	validation-mlogloss:1.99446
[193]	train-mlogloss:2.03794	validation-mlogloss:1.99268
[194]	train-mlogloss:2.03650	validation-mlogloss:1.99120
[195]	train-mlogloss:2.03502	validation-mlogloss:1.98994
[196]	train-mlogloss:2.03354	validation-mlogloss:1.98854
[197]	train-mlogloss:2.03205	validation-mlogloss:1.98721
[198]	train-mlogloss:2.03061	validation-mlogloss:1.98559
[199]	train-mlogloss:2.02921	validation-mlogloss:1.98425
[200]	train-mlogloss:2.02777	validation-mlogloss:1.98304
[201]	train-mlogloss:2.02634	validation-mlogloss:1.98171
[202]	train-mlogloss:2.02489	validation-mlogloss:1.98039
[203]	train-mlogloss:2.02338	validation-mlogloss:1.97882
[204]	train-mlogloss:2.02194	validation-mlogloss:1.97754
[205]	train-mlogloss:2.02059	validation-mlogloss:1.97624
[206]	train-mlogloss:2.01913	validation-mlogloss:1.97479
[207]	train-mlogloss:2.01781	validation-mlogloss:1.97353
[208]	train-mlogloss:2.01635	validation-mlogloss:1.97222
[209]	train-mlogloss:2.01503	validation-mlogloss:1.97101
[210]	train-mlogloss:2.01364	validation-mlogloss:1.96958
[211]	train-mlogloss:2.01238	validation-mlogloss:1.96840
[212]	train-mlogloss:2.01106	validation-mlogloss:1.96680
[213]	train-mlogloss:2.00973	validation-mlogloss:1.96564
[214]	train-mlogloss:2.00834	validation-mlogloss:1.96441
[215]	train-mlogloss:2.00701	validation-mlogloss:1.96298
[216]	train-mlogloss:2.00570	validation-mlogloss:1.96169
[217]	train-mlogloss:2.00440	validation-mlogloss:1.96066
[218]	train-mlogloss:2.00306	validation-mlogloss:1.95929
[219]	train-mlogloss:2.00177	validation-mlogloss:1.95828
[220]	train-mlogloss:2.00051	validation-mlogloss:1.95705
[221]	train-mlogloss:1.99928	validation-mlogloss:1.95584
[222]	train-mlogloss:1.99803	validation-mlogloss:1.95467
[223]	train-mlogloss:1.99675	validation-mlogloss:1.95348
[224]	train-mlogloss:1.99542	validation-mlogloss:1.95241
[225]	train-mlogloss:1.99411	validation-mlogloss:1.95121
[226]	train-mlogloss:1.99286	validation-mlogloss:1.94983
[227]	train-mlogloss:1.99156	validation-mlogloss:1.94876
[228]	train-mlogloss:1.99024	validation-mlogloss:1.94762
[229]	train-mlogloss:1.98906	validation-mlogloss:1.94651
[230]	train-mlogloss:1.98783	validation-mlogloss:1.94543
[231]	train-mlogloss:1.98659	validation-mlogloss:1.94432
[232]	train-mlogloss:1.98540	validation-mlogloss:1.94323
[233]	train-mlogloss:1.98416	validation-mlogloss:1.94222
[234]	train-mlogloss:1.98288	validation-mlogloss:1.94117
[235]	train-mlogloss:1.98169	validation-mlogloss:1.94023
[236]	train-mlogloss:1.98041	validation-mlogloss:1.93915
[237]	train-mlogloss:1.97931	validation-mlogloss:1.93827
[238]	train-mlogloss:1.97805	validation-mlogloss:1.93714
[239]	train-mlogloss:1.97683	validation-mlogloss:1.93592
[240]	train-mlogloss:1.97554	validation-mlogloss:1.93460
[241]	train-mlogloss:1.97425	validation-mlogloss:1.93342
[242]	train-mlogloss:1.97310	validation-mlogloss:1.93236
[243]	train-mlogloss:1.97189	validation-mlogloss:1.93115
[244]	train-mlogloss:1.97066	validation-mlogloss:1.92989
[245]	train-mlogloss:1.96951	validation-mlogloss:1.92886
[246]	train-mlogloss:1.96834	validation-mlogloss:1.92798
[247]	train-mlogloss:1.96717	validation-mlogloss:1.92692
[248]	train-mlogloss:1.96607	validation-mlogloss:1.92591
[249]	train-mlogloss:1.96494	validation-mlogloss:1.92479
[250]	train-mlogloss:1.96372	validation-mlogloss:1.92371
[251]	train-mlogloss:1.96259	validation-mlogloss:1.92254
[252]	train-mlogloss:1.96145	validation-mlogloss:1.92140
[253]	train-mlogloss:1.96040	validation-mlogloss:1.92065
[254]	train-mlogloss:1.95927	validation-mlogloss:1.91959
[255]	train-mlogloss:1.95814	validation-mlogloss:1.91881
[256]	train-mlogloss:1.95700	validation-mlogloss:1.91757
[257]	train-mlogloss:1.95586	validation-mlogloss:1.91659
[258]	train-mlogloss:1.95473	validation-mlogloss:1.91569
[259]	train-mlogloss:1.95364	validation-mlogloss:1.91458
[260]	train-mlogloss:1.95247	validation-mlogloss:1.91343
[261]	train-mlogloss:1.95148	validation-mlogloss:1.91251
[262]	train-mlogloss:1.95040	validation-mlogloss:1.91161
[263]	train-mlogloss:1.94936	validation-mlogloss:1.91073
[264]	train-mlogloss:1.94830	validation-mlogloss:1.90981
[265]	train-mlogloss:1.94735	validation-mlogloss:1.90894
[266]	train-mlogloss:1.94628	validation-mlogloss:1.90799
[267]	train-mlogloss:1.94530	validation-mlogloss:1.90730
[268]	train-mlogloss:1.94432	validation-mlogloss:1.90648
[269]	train-mlogloss:1.94327	validation-mlogloss:1.90565
[270]	train-mlogloss:1.94232	validation-mlogloss:1.90474
[271]	train-mlogloss:1.94126	validation-mlogloss:1.90394
[272]	train-mlogloss:1.94028	validation-mlogloss:1.90309
[273]	train-mlogloss:1.93931	validation-mlogloss:1.90222
[274]	train-mlogloss:1.93823	validation-mlogloss:1.90128
[275]	train-mlogloss:1.93725	validation-mlogloss:1.90026
[276]	train-mlogloss:1.93621	validation-mlogloss:1.89948
[277]	train-mlogloss:1.93525	validation-mlogloss:1.89873
[278]	train-mlogloss:1.93423	validation-mlogloss:1.89801
[279]	train-mlogloss:1.93324	validation-mlogloss:1.89703
[280]	train-mlogloss:1.93226	validation-mlogloss:1.89639
[281]	train-mlogloss:1.93139	validation-mlogloss:1.89581
[282]	train-mlogloss:1.93045	validation-mlogloss:1.89504
[283]	train-mlogloss:1.92946	validation-mlogloss:1.89413
[284]	train-mlogloss:1.92846	validation-mlogloss:1.89307
[285]	train-mlogloss:1.92762	validation-mlogloss:1.89249
[286]	train-mlogloss:1.92667	validation-mlogloss:1.89151
[287]	train-mlogloss:1.92569	validation-mlogloss:1.89070
[288]	train-mlogloss:1.92475	validation-mlogloss:1.88996
[289]	train-mlogloss:1.92381	validation-mlogloss:1.88913
[290]	train-mlogloss:1.92285	validation-mlogloss:1.88836
[291]	train-mlogloss:1.92197	validation-mlogloss:1.88759
[292]	train-mlogloss:1.92112	validation-mlogloss:1.88700
[293]	train-mlogloss:1.92027	validation-mlogloss:1.88617
[294]	train-mlogloss:1.91931	validation-mlogloss:1.88540
[295]	train-mlogloss:1.91825	validation-mlogloss:1.88448
[296]	train-mlogloss:1.91731	validation-mlogloss:1.88381
[297]	train-mlogloss:1.91638	validation-mlogloss:1.88293
[298]	train-mlogloss:1.91547	validation-mlogloss:1.88218
[299]	train-mlogloss:1.91457	validation-mlogloss:1.88154
[300]	train-mlogloss:1.91363	validation-mlogloss:1.88070
[301]	train-mlogloss:1.91270	validation-mlogloss:1.87985
[302]	train-mlogloss:1.91182	validation-mlogloss:1.87927
[303]	train-mlogloss:1.91088	validation-mlogloss:1.87861
[304]	train-mlogloss:1.90998	validation-mlogloss:1.87795
[305]	train-mlogloss:1.90905	validation-mlogloss:1.87719
[306]	train-mlogloss:1.90814	validation-mlogloss:1.87628
[307]	train-mlogloss:1.90730	validation-mlogloss:1.87566
[308]	train-mlogloss:1.90643	validation-mlogloss:1.87506
[309]	train-mlogloss:1.90559	validation-mlogloss:1.87438
[310]	train-mlogloss:1.90473	validation-mlogloss:1.87368
[311]	train-mlogloss:1.90390	validation-mlogloss:1.87304
[312]	train-mlogloss:1.90290	validation-mlogloss:1.87226
[313]	train-mlogloss:1.90203	validation-mlogloss:1.87168
[314]	train-mlogloss:1.90123	validation-mlogloss:1.87107
[315]	train-mlogloss:1.90032	validation-mlogloss:1.87030
[316]	train-mlogloss:1.89944	validation-mlogloss:1.86958
[317]	train-mlogloss:1.89867	validation-mlogloss:1.86918
[318]	train-mlogloss:1.89796	validation-mlogloss:1.86871
[319]	train-mlogloss:1.89716	validation-mlogloss:1.86808
[320]	train-mlogloss:1.89632	validation-mlogloss:1.86746
[321]	train-mlogloss:1.89546	validation-mlogloss:1.86668
[322]	train-mlogloss:1.89460	validation-mlogloss:1.86592
[323]	train-mlogloss:1.89382	validation-mlogloss:1.86534
[324]	train-mlogloss:1.89296	validation-mlogloss:1.86452
[325]	train-mlogloss:1.89216	validation-mlogloss:1.86404
[326]	train-mlogloss:1.89135	validation-mlogloss:1.86335
[327]	train-mlogloss:1.89059	validation-mlogloss:1.86303
[328]	train-mlogloss:1.88990	validation-mlogloss:1.86257
[329]	train-mlogloss:1.88916	validation-mlogloss:1.86185
[330]	train-mlogloss:1.88846	validation-mlogloss:1.86128
[331]	train-mlogloss:1.88769	validation-mlogloss:1.86076
[332]	train-mlogloss:1.88692	validation-mlogloss:1.86037
[333]	train-mlogloss:1.88618	validation-mlogloss:1.85983
[334]	train-mlogloss:1.88546	validation-mlogloss:1.85929
[335]	train-mlogloss:1.88473	validation-mlogloss:1.85864
[336]	train-mlogloss:1.88400	validation-mlogloss:1.85799
[337]	train-mlogloss:1.88326	validation-mlogloss:1.85743
[338]	train-mlogloss:1.88261	validation-mlogloss:1.85698
[339]	train-mlogloss:1.88184	validation-mlogloss:1.85633
[340]	train-mlogloss:1.88114	validation-mlogloss:1.85579
[341]	train-mlogloss:1.88025	validation-mlogloss:1.85519
[342]	train-mlogloss:1.87949	validation-mlogloss:1.85443
[343]	train-mlogloss:1.87875	validation-mlogloss:1.85392
[344]	train-mlogloss:1.87800	validation-mlogloss:1.85337
[345]	train-mlogloss:1.87728	validation-mlogloss:1.85291
[346]	train-mlogloss:1.87653	validation-mlogloss:1.85231
[347]	train-mlogloss:1.87583	validation-mlogloss:1.85173
[348]	train-mlogloss:1.87514	validation-mlogloss:1.85117
[349]	train-mlogloss:1.87441	validation-mlogloss:1.85047
[350]	train-mlogloss:1.87360	validation-mlogloss:1.84972
[351]	train-mlogloss:1.87290	validation-mlogloss:1.84925
[352]	train-mlogloss:1.87214	validation-mlogloss:1.84868
[353]	train-mlogloss:1.87147	validation-mlogloss:1.84811
[354]	train-mlogloss:1.87083	validation-mlogloss:1.84753
[355]	train-mlogloss:1.87010	validation-mlogloss:1.84708
[356]	train-mlogloss:1.86941	validation-mlogloss:1.84647
[357]	train-mlogloss:1.86869	validation-mlogloss:1.84581
[358]	train-mlogloss:1.86800	validation-mlogloss:1.84541
[359]	train-mlogloss:1.86729	validation-mlogloss:1.84480
[360]	train-mlogloss:1.86659	validation-mlogloss:1.84430
[361]	train-mlogloss:1.86589	validation-mlogloss:1.84378
[362]	train-mlogloss:1.86516	validation-mlogloss:1.84328
[363]	train-mlogloss:1.86441	validation-mlogloss:1.84273
[364]	train-mlogloss:1.86370	validation-mlogloss:1.84234
[365]	train-mlogloss:1.86311	validation-mlogloss:1.84191
[366]	train-mlogloss:1.86241	validation-mlogloss:1.84134
[367]	train-mlogloss:1.86173	validation-mlogloss:1.84086
[368]	train-mlogloss:1.86106	validation-mlogloss:1.84025
[369]	train-mlogloss:1.86037	validation-mlogloss:1.83982
[370]	train-mlogloss:1.85966	validation-mlogloss:1.83938
[371]	train-mlogloss:1.85901	validation-mlogloss:1.83898
[372]	train-mlogloss:1.85841	validation-mlogloss:1.83842
[373]	train-mlogloss:1.85779	validation-mlogloss:1.83794
[374]	train-mlogloss:1.85719	validation-mlogloss:1.83757
[375]	train-mlogloss:1.85650	validation-mlogloss:1.83727
[376]	train-mlogloss:1.85587	validation-mlogloss:1.83683
[377]	train-mlogloss:1.85530	validation-mlogloss:1.83648
[378]	train-mlogloss:1.85461	validation-mlogloss:1.83611
[379]	train-mlogloss:1.85394	validation-mlogloss:1.83571
[380]	train-mlogloss:1.85320	validation-mlogloss:1.83521
[381]	train-mlogloss:1.85252	validation-mlogloss:1.83471
[382]	train-mlogloss:1.85191	validation-mlogloss:1.83432
[383]	train-mlogloss:1.85131	validation-mlogloss:1.83380
[384]	train-mlogloss:1.85073	validation-mlogloss:1.83328
[385]	train-mlogloss:1.85011	validation-mlogloss:1.83273
[386]	train-mlogloss:1.84952	validation-mlogloss:1.83234
[387]	train-mlogloss:1.84898	validation-mlogloss:1.83199
[388]	train-mlogloss:1.84841	validation-mlogloss:1.83153
[389]	train-mlogloss:1.84774	validation-mlogloss:1.83099
[390]	train-mlogloss:1.84724	validation-mlogloss:1.83058
[391]	train-mlogloss:1.84658	validation-mlogloss:1.83006
[392]	train-mlogloss:1.84603	validation-mlogloss:1.82962
[393]	train-mlogloss:1.84544	validation-mlogloss:1.82930
[394]	train-mlogloss:1.84489	validation-mlogloss:1.82897
[395]	train-mlogloss:1.84430	validation-mlogloss:1.82866
[396]	train-mlogloss:1.84370	validation-mlogloss:1.82828
[397]	train-mlogloss:1.84310	validation-mlogloss:1.82801
[398]	train-mlogloss:1.84253	validation-mlogloss:1.82765
[399]	train-mlogloss:1.84206	validation-mlogloss:1.82728
[400]	train-mlogloss:1.84140	validation-mlogloss:1.82699
[401]	train-mlogloss:1.84086	validation-mlogloss:1.82661
[402]	train-mlogloss:1.84043	validation-mlogloss:1.82625
[403]	train-mlogloss:1.83992	validation-mlogloss:1.82590
[404]	train-mlogloss:1.83946	validation-mlogloss:1.82549
[405]	train-mlogloss:1.83898	validation-mlogloss:1.82507
[406]	train-mlogloss:1.83843	validation-mlogloss:1.82474
[407]	train-mlogloss:1.83796	validation-mlogloss:1.82434
[408]	train-mlogloss:1.83745	validation-mlogloss:1.82403
[409]	train-mlogloss:1.83699	validation-mlogloss:1.82380
[410]	train-mlogloss:1.83648	validation-mlogloss:1.82348
[411]	train-mlogloss:1.83594	validation-mlogloss:1.82305
[412]	train-mlogloss:1.83543	validation-mlogloss:1.82279
[413]	train-mlogloss:1.83503	validation-mlogloss:1.82251
[414]	train-mlogloss:1.83455	validation-mlogloss:1.82213
[415]	train-mlogloss:1.83406	validation-mlogloss:1.82191
[416]	train-mlogloss:1.83351	validation-mlogloss:1.82154
[417]	train-mlogloss:1.83300	validation-mlogloss:1.82125
[418]	train-mlogloss:1.83259	validation-mlogloss:1.82103
[419]	train-mlogloss:1.83219	validation-mlogloss:1.82075
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.32 [%]
Global accuracy score (test) = 43.92 [%]
Global F1 score (train) = 43.82 [%]
Global F1 score (test) = 43.04 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.49      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.46      0.44       184
       CAMINAR USUAL SPEED       0.34      0.16      0.21       184
            CAMINAR ZIGZAG       0.31      0.54      0.40       184
          DE PIE BARRIENDO       0.69      0.39      0.50       184
   DE PIE DOBLANDO TOALLAS       0.45      0.45      0.45       184
    DE PIE MOVIENDO LIBROS       0.37      0.39      0.38       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.58      0.61       184
           SENTADO LEYENDO       0.46      0.39      0.42       184
         SENTADO USANDO PC       0.26      0.12      0.17       184
      SENTADO VIENDO LA TV       0.24      0.16      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.62      0.56      0.59       184
                    TROTAR       0.65      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 10: 43.92 [%]
F1-score capturado en la ejecución 10: 43.04 [%]

=== EJECUCIÓN 11 ===

--- TRAIN (ejecución 11) ---

--- TEST (ejecución 11) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.32 [%]
Global accuracy score (test) = 44.14 [%]
Global F1 score (train) = 43.83 [%]
Global F1 score (test) = 43.42 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.47      0.46       184
       CAMINAR USUAL SPEED       0.35      0.20      0.25       184
            CAMINAR ZIGZAG       0.32      0.51      0.39       184
          DE PIE BARRIENDO       0.69      0.41      0.51       184
   DE PIE DOBLANDO TOALLAS       0.45      0.43      0.44       184
    DE PIE MOVIENDO LIBROS       0.37      0.39      0.38       184
          DE PIE USANDO PC       0.21      0.33      0.26       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.58      0.61       184
           SENTADO LEYENDO       0.46      0.39      0.42       184
         SENTADO USANDO PC       0.25      0.12      0.17       184
      SENTADO VIENDO LA TV       0.24      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.64      0.55      0.59       184
                    TROTAR       0.66      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 11: 44.14 [%]
F1-score capturado en la ejecución 11: 43.42 [%]

=== EJECUCIÓN 12 ===

--- TRAIN (ejecución 12) ---

--- TEST (ejecución 12) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.16 [%]
Global accuracy score (test) = 44.28 [%]
Global F1 score (train) = 43.67 [%]
Global F1 score (test) = 43.5 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.46      0.45       184
       CAMINAR USUAL SPEED       0.34      0.18      0.23       184
            CAMINAR ZIGZAG       0.31      0.52      0.39       184
          DE PIE BARRIENDO       0.71      0.42      0.53       184
   DE PIE DOBLANDO TOALLAS       0.46      0.46      0.46       184
    DE PIE MOVIENDO LIBROS       0.40      0.41      0.40       184
          DE PIE USANDO PC       0.20      0.30      0.24       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.64      0.57      0.61       184
           SENTADO LEYENDO       0.45      0.38      0.41       184
         SENTADO USANDO PC       0.27      0.14      0.18       184
      SENTADO VIENDO LA TV       0.24      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.60      0.55      0.57       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 12: 44.28 [%]
F1-score capturado en la ejecución 12: 43.5 [%]

=== EJECUCIÓN 13 ===

--- TRAIN (ejecución 13) ---

--- TEST (ejecución 13) ---
2025-11-06 21:47:58.825573: 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 21:47:58.836793: 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 00:00:1762462078.850143 1828355 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462078.854433 1828355 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462078.864320 1828355 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462078.864335 1828355 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462078.864336 1828355 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462078.864337 1828355 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:47:58.867446: 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:2.70039	validation-mlogloss:2.69988
[1]	train-mlogloss:2.69286	validation-mlogloss:2.69217
[2]	train-mlogloss:2.68556	validation-mlogloss:2.68461
[3]	train-mlogloss:2.67838	validation-mlogloss:2.67686
[4]	train-mlogloss:2.67116	validation-mlogloss:2.66931
[5]	train-mlogloss:2.66379	validation-mlogloss:2.66150
[6]	train-mlogloss:2.65623	validation-mlogloss:2.65342
[7]	train-mlogloss:2.64935	validation-mlogloss:2.64599
[8]	train-mlogloss:2.64256	validation-mlogloss:2.63849
[9]	train-mlogloss:2.63552	validation-mlogloss:2.63104
[10]	train-mlogloss:2.62859	validation-mlogloss:2.62357
[11]	train-mlogloss:2.62185	validation-mlogloss:2.61618
[12]	train-mlogloss:2.61513	validation-mlogloss:2.60882
[13]	train-mlogloss:2.60845	validation-mlogloss:2.60169
[14]	train-mlogloss:2.60149	validation-mlogloss:2.59388
[15]	train-mlogloss:2.59494	validation-mlogloss:2.58667
[16]	train-mlogloss:2.58852	validation-mlogloss:2.57951
[17]	train-mlogloss:2.58206	validation-mlogloss:2.57228
[18]	train-mlogloss:2.57587	validation-mlogloss:2.56575
[19]	train-mlogloss:2.56983	validation-mlogloss:2.55911
[20]	train-mlogloss:2.56365	validation-mlogloss:2.55242
[21]	train-mlogloss:2.55747	validation-mlogloss:2.54562
[22]	train-mlogloss:2.55160	validation-mlogloss:2.53901
[23]	train-mlogloss:2.54561	validation-mlogloss:2.53238
[24]	train-mlogloss:2.53961	validation-mlogloss:2.52565
[25]	train-mlogloss:2.53395	validation-mlogloss:2.51956
[26]	train-mlogloss:2.52824	validation-mlogloss:2.51325
[27]	train-mlogloss:2.52259	validation-mlogloss:2.50660
[28]	train-mlogloss:2.51695	validation-mlogloss:2.50049
[29]	train-mlogloss:2.51136	validation-mlogloss:2.49434
[30]	train-mlogloss:2.50603	validation-mlogloss:2.48870
[31]	train-mlogloss:2.50056	validation-mlogloss:2.48259
[32]	train-mlogloss:2.49526	validation-mlogloss:2.47671
[33]	train-mlogloss:2.49012	validation-mlogloss:2.47121
[34]	train-mlogloss:2.48487	validation-mlogloss:2.46540
[35]	train-mlogloss:2.47958	validation-mlogloss:2.45964
[36]	train-mlogloss:2.47450	validation-mlogloss:2.45397
[37]	train-mlogloss:2.46952	validation-mlogloss:2.44854
[38]	train-mlogloss:2.46459	validation-mlogloss:2.44330
[39]	train-mlogloss:2.45973	validation-mlogloss:2.43788
[40]	train-mlogloss:2.45503	validation-mlogloss:2.43279
[41]	train-mlogloss:2.45026	validation-mlogloss:2.42767
[42]	train-mlogloss:2.44559	validation-mlogloss:2.42231
[43]	train-mlogloss:2.44086	validation-mlogloss:2.41733
[44]	train-mlogloss:2.43620	validation-mlogloss:2.41219
[45]	train-mlogloss:2.43169	validation-mlogloss:2.40734
[46]	train-mlogloss:2.42684	validation-mlogloss:2.40181
[47]	train-mlogloss:2.42226	validation-mlogloss:2.39698
[48]	train-mlogloss:2.41776	validation-mlogloss:2.39197
[49]	train-mlogloss:2.41325	validation-mlogloss:2.38689
[50]	train-mlogloss:2.40895	validation-mlogloss:2.38220
[51]	train-mlogloss:2.40434	validation-mlogloss:2.37706
[52]	train-mlogloss:2.39980	validation-mlogloss:2.37215
[53]	train-mlogloss:2.39526	validation-mlogloss:2.36701
[54]	train-mlogloss:2.39115	validation-mlogloss:2.36249
[55]	train-mlogloss:2.38692	validation-mlogloss:2.35796
[56]	train-mlogloss:2.38262	validation-mlogloss:2.35312
[57]	train-mlogloss:2.37854	validation-mlogloss:2.34856
[58]	train-mlogloss:2.37448	validation-mlogloss:2.34430
[59]	train-mlogloss:2.37052	validation-mlogloss:2.34015
[60]	train-mlogloss:2.36636	validation-mlogloss:2.33559
[61]	train-mlogloss:2.36215	validation-mlogloss:2.33082
[62]	train-mlogloss:2.35822	validation-mlogloss:2.32659
[63]	train-mlogloss:2.35414	validation-mlogloss:2.32227
[64]	train-mlogloss:2.35022	validation-mlogloss:2.31769
[65]	train-mlogloss:2.34621	validation-mlogloss:2.31313
[66]	train-mlogloss:2.34209	validation-mlogloss:2.30839
[67]	train-mlogloss:2.33837	validation-mlogloss:2.30452
[68]	train-mlogloss:2.33476	validation-mlogloss:2.30072
[69]	train-mlogloss:2.33109	validation-mlogloss:2.29707
[70]	train-mlogloss:2.32739	validation-mlogloss:2.29288
[71]	train-mlogloss:2.32359	validation-mlogloss:2.28869
[72]	train-mlogloss:2.31979	validation-mlogloss:2.28438
[73]	train-mlogloss:2.31635	validation-mlogloss:2.28056
[74]	train-mlogloss:2.31282	validation-mlogloss:2.27687
[75]	train-mlogloss:2.30930	validation-mlogloss:2.27306
[76]	train-mlogloss:2.30568	validation-mlogloss:2.26899
[77]	train-mlogloss:2.30214	validation-mlogloss:2.26525
[78]	train-mlogloss:2.29875	validation-mlogloss:2.26163
[79]	train-mlogloss:2.29522	validation-mlogloss:2.25790
[80]	train-mlogloss:2.29165	validation-mlogloss:2.25390
[81]	train-mlogloss:2.28838	validation-mlogloss:2.25055
[82]	train-mlogloss:2.28503	validation-mlogloss:2.24719
[83]	train-mlogloss:2.28182	validation-mlogloss:2.24376
[84]	train-mlogloss:2.27861	validation-mlogloss:2.24032
[85]	train-mlogloss:2.27521	validation-mlogloss:2.23620
[86]	train-mlogloss:2.27189	validation-mlogloss:2.23264
[87]	train-mlogloss:2.26864	validation-mlogloss:2.22908
[88]	train-mlogloss:2.26542	validation-mlogloss:2.22565
[89]	train-mlogloss:2.26228	validation-mlogloss:2.22218
[90]	train-mlogloss:2.25920	validation-mlogloss:2.21893
[91]	train-mlogloss:2.25619	validation-mlogloss:2.21582
[92]	train-mlogloss:2.25302	validation-mlogloss:2.21241
[93]	train-mlogloss:2.24991	validation-mlogloss:2.20886
[94]	train-mlogloss:2.24712	validation-mlogloss:2.20577
[95]	train-mlogloss:2.24418	validation-mlogloss:2.20254
[96]	train-mlogloss:2.24114	validation-mlogloss:2.19928
[97]	train-mlogloss:2.23831	validation-mlogloss:2.19612
[98]	train-mlogloss:2.23552	validation-mlogloss:2.19292
[99]	train-mlogloss:2.23265	validation-mlogloss:2.18979
[100]	train-mlogloss:2.22984	validation-mlogloss:2.18690
[101]	train-mlogloss:2.22700	validation-mlogloss:2.18386
[102]	train-mlogloss:2.22419	validation-mlogloss:2.18097
[103]	train-mlogloss:2.22143	validation-mlogloss:2.17805
[104]	train-mlogloss:2.21863	validation-mlogloss:2.17508
[105]	train-mlogloss:2.21595	validation-mlogloss:2.17225
[106]	train-mlogloss:2.21325	validation-mlogloss:2.16939
[107]	train-mlogloss:2.21066	validation-mlogloss:2.16668
[108]	train-mlogloss:2.20800	validation-mlogloss:2.16380
[109]	train-mlogloss:2.20550	validation-mlogloss:2.16132
[110]	train-mlogloss:2.20282	validation-mlogloss:2.15841
[111]	train-mlogloss:2.20027	validation-mlogloss:2.15569
[112]	train-mlogloss:2.19767	validation-mlogloss:2.15305
[113]	train-mlogloss:2.19499	validation-mlogloss:2.15019
[114]	train-mlogloss:2.19249	validation-mlogloss:2.14739
[115]	train-mlogloss:2.18996	validation-mlogloss:2.14472
[116]	train-mlogloss:2.18752	validation-mlogloss:2.14205
[117]	train-mlogloss:2.18493	validation-mlogloss:2.13928
[118]	train-mlogloss:2.18246	validation-mlogloss:2.13667
[119]	train-mlogloss:2.17989	validation-mlogloss:2.13391
[120]	train-mlogloss:2.17753	validation-mlogloss:2.13130
[121]	train-mlogloss:2.17503	validation-mlogloss:2.12859
[122]	train-mlogloss:2.17266	validation-mlogloss:2.12616
[123]	train-mlogloss:2.17040	validation-mlogloss:2.12378
[124]	train-mlogloss:2.16790	validation-mlogloss:2.12096
[125]	train-mlogloss:2.16552	validation-mlogloss:2.11844
[126]	train-mlogloss:2.16339	validation-mlogloss:2.11628
[127]	train-mlogloss:2.16099	validation-mlogloss:2.11379
[128]	train-mlogloss:2.15875	validation-mlogloss:2.11157
[129]	train-mlogloss:2.15640	validation-mlogloss:2.10903
[130]	train-mlogloss:2.15427	validation-mlogloss:2.10707
[131]	train-mlogloss:2.15194	validation-mlogloss:2.10462
[132]	train-mlogloss:2.14956	validation-mlogloss:2.10200
[133]	train-mlogloss:2.14738	validation-mlogloss:2.09966
[134]	train-mlogloss:2.14516	validation-mlogloss:2.09728
[135]	train-mlogloss:2.14302	validation-mlogloss:2.09488
[136]	train-mlogloss:2.14076	validation-mlogloss:2.09261
[137]	train-mlogloss:2.13849	validation-mlogloss:2.09013
[138]	train-mlogloss:2.13630	validation-mlogloss:2.08788
[139]	train-mlogloss:2.13430	validation-mlogloss:2.08594
[140]	train-mlogloss:2.13232	validation-mlogloss:2.08394
[141]	train-mlogloss:2.13038	validation-mlogloss:2.08218
[142]	train-mlogloss:2.12832	validation-mlogloss:2.08019
[143]	train-mlogloss:2.12628	validation-mlogloss:2.07833
[144]	train-mlogloss:2.12434	validation-mlogloss:2.07634
[145]	train-mlogloss:2.12232	validation-mlogloss:2.07436
[146]	train-mlogloss:2.12042	validation-mlogloss:2.07250
[147]	train-mlogloss:2.11825	validation-mlogloss:2.07031
[148]	train-mlogloss:2.11615	validation-mlogloss:2.06845
[149]	train-mlogloss:2.11411	validation-mlogloss:2.06627
[150]	train-mlogloss:2.11219	validation-mlogloss:2.06438
[151]	train-mlogloss:2.11031	validation-mlogloss:2.06253
[152]	train-mlogloss:2.10837	validation-mlogloss:2.06070
[153]	train-mlogloss:2.10636	validation-mlogloss:2.05860
[154]	train-mlogloss:2.10434	validation-mlogloss:2.05647
[155]	train-mlogloss:2.10250	validation-mlogloss:2.05480
[156]	train-mlogloss:2.10056	validation-mlogloss:2.05292
[157]	train-mlogloss:2.09856	validation-mlogloss:2.05096
[158]	train-mlogloss:2.09668	validation-mlogloss:2.04895
[159]	train-mlogloss:2.09490	validation-mlogloss:2.04741
[160]	train-mlogloss:2.09280	validation-mlogloss:2.04536
[161]	train-mlogloss:2.09093	validation-mlogloss:2.04343
[162]	train-mlogloss:2.08905	validation-mlogloss:2.04143
[163]	train-mlogloss:2.08721	validation-mlogloss:2.03964
[164]	train-mlogloss:2.08535	validation-mlogloss:2.03774
[165]	train-mlogloss:2.08360	validation-mlogloss:2.03604
[166]	train-mlogloss:2.08183	validation-mlogloss:2.03444
[167]	train-mlogloss:2.08009	validation-mlogloss:2.03278
[168]	train-mlogloss:2.07830	validation-mlogloss:2.03087
[169]	train-mlogloss:2.07664	validation-mlogloss:2.02925
[170]	train-mlogloss:2.07499	validation-mlogloss:2.02784
[171]	train-mlogloss:2.07332	validation-mlogloss:2.02625
[172]	train-mlogloss:2.07154	validation-mlogloss:2.02443
[173]	train-mlogloss:2.06982	validation-mlogloss:2.02258
[174]	train-mlogloss:2.06813	validation-mlogloss:2.02099
[175]	train-mlogloss:2.06644	validation-mlogloss:2.01944
[176]	train-mlogloss:2.06475	validation-mlogloss:2.01771
[177]	train-mlogloss:2.06312	validation-mlogloss:2.01606
[178]	train-mlogloss:2.06155	validation-mlogloss:2.01469
[179]	train-mlogloss:2.05984	validation-mlogloss:2.01290
[180]	train-mlogloss:2.05817	validation-mlogloss:2.01130
[181]	train-mlogloss:2.05656	validation-mlogloss:2.00978
[182]	train-mlogloss:2.05496	validation-mlogloss:2.00841
[183]	train-mlogloss:2.05336	validation-mlogloss:2.00686
[184]	train-mlogloss:2.05173	validation-mlogloss:2.00523
[185]	train-mlogloss:2.05015	validation-mlogloss:2.00366
[186]	train-mlogloss:2.04858	validation-mlogloss:2.00231
[187]	train-mlogloss:2.04699	validation-mlogloss:2.00084
[188]	train-mlogloss:2.04552	validation-mlogloss:1.99963
[189]	train-mlogloss:2.04393	validation-mlogloss:1.99807
[190]	train-mlogloss:2.04242	validation-mlogloss:1.99664
[191]	train-mlogloss:2.04091	validation-mlogloss:1.99509
[192]	train-mlogloss:2.03946	validation-mlogloss:1.99381
[193]	train-mlogloss:2.03792	validation-mlogloss:1.99250
[194]	train-mlogloss:2.03642	validation-mlogloss:1.99101
[195]	train-mlogloss:2.03502	validation-mlogloss:1.98960
[196]	train-mlogloss:2.03359	validation-mlogloss:1.98838
[197]	train-mlogloss:2.03209	validation-mlogloss:1.98720
[198]	train-mlogloss:2.03053	validation-mlogloss:1.98577
[199]	train-mlogloss:2.02915	validation-mlogloss:1.98449
[200]	train-mlogloss:2.02771	validation-mlogloss:1.98304
[201]	train-mlogloss:2.02629	validation-mlogloss:1.98177
[202]	train-mlogloss:2.02486	validation-mlogloss:1.98055
[203]	train-mlogloss:2.02332	validation-mlogloss:1.97896
[204]	train-mlogloss:2.02197	validation-mlogloss:1.97770
[205]	train-mlogloss:2.02045	validation-mlogloss:1.97621
[206]	train-mlogloss:2.01904	validation-mlogloss:1.97479
[207]	train-mlogloss:2.01762	validation-mlogloss:1.97350
[208]	train-mlogloss:2.01629	validation-mlogloss:1.97224
[209]	train-mlogloss:2.01499	validation-mlogloss:1.97092
[210]	train-mlogloss:2.01347	validation-mlogloss:1.96940
[211]	train-mlogloss:2.01205	validation-mlogloss:1.96819
[212]	train-mlogloss:2.01077	validation-mlogloss:1.96689
[213]	train-mlogloss:2.00941	validation-mlogloss:1.96576
[214]	train-mlogloss:2.00820	validation-mlogloss:1.96475
[215]	train-mlogloss:2.00685	validation-mlogloss:1.96338
[216]	train-mlogloss:2.00554	validation-mlogloss:1.96243
[217]	train-mlogloss:2.00422	validation-mlogloss:1.96125
[218]	train-mlogloss:2.00281	validation-mlogloss:1.95992
[219]	train-mlogloss:2.00151	validation-mlogloss:1.95864
[220]	train-mlogloss:2.00023	validation-mlogloss:1.95759
[221]	train-mlogloss:1.99893	validation-mlogloss:1.95614
[222]	train-mlogloss:1.99759	validation-mlogloss:1.95488
[223]	train-mlogloss:1.99630	validation-mlogloss:1.95375
[224]	train-mlogloss:1.99506	validation-mlogloss:1.95264
[225]	train-mlogloss:1.99383	validation-mlogloss:1.95156
[226]	train-mlogloss:1.99270	validation-mlogloss:1.95077
[227]	train-mlogloss:1.99138	validation-mlogloss:1.94940
[228]	train-mlogloss:1.99017	validation-mlogloss:1.94822
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[391]	train-mlogloss:1.84690	validation-mlogloss:1.83054
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[393]	train-mlogloss:1.84576	validation-mlogloss:1.82962
[394]	train-mlogloss:1.84516	validation-mlogloss:1.82910
[395]	train-mlogloss:1.84459	validation-mlogloss:1.82892
[396]	train-mlogloss:1.84408	validation-mlogloss:1.82847
[397]	train-mlogloss:1.84358	validation-mlogloss:1.82823
[398]	train-mlogloss:1.84295	validation-mlogloss:1.82781
[399]	train-mlogloss:1.84239	validation-mlogloss:1.82752
[400]	train-mlogloss:1.84174	validation-mlogloss:1.82714
[401]	train-mlogloss:1.84124	validation-mlogloss:1.82674
[402]	train-mlogloss:1.84074	validation-mlogloss:1.82649
[403]	train-mlogloss:1.84026	validation-mlogloss:1.82607
[404]	train-mlogloss:1.83971	validation-mlogloss:1.82571
[405]	train-mlogloss:1.83908	validation-mlogloss:1.82513
[406]	train-mlogloss:1.83853	validation-mlogloss:1.82482
[407]	train-mlogloss:1.83793	validation-mlogloss:1.82437
[408]	train-mlogloss:1.83741	validation-mlogloss:1.82403
[409]	train-mlogloss:1.83686	validation-mlogloss:1.82354
[410]	train-mlogloss:1.83638	validation-mlogloss:1.82317
[411]	train-mlogloss:1.83588	validation-mlogloss:1.82294
[412]	train-mlogloss:1.83533	validation-mlogloss:1.82263
[413]	train-mlogloss:1.83479	validation-mlogloss:1.82223
[414]	train-mlogloss:1.83426	validation-mlogloss:1.82180
[415]	train-mlogloss:1.83379	validation-mlogloss:1.82157
[416]	train-mlogloss:1.83318	validation-mlogloss:1.82125
[417]	train-mlogloss:1.83270	validation-mlogloss:1.82096
[418]	train-mlogloss:1.83220	validation-mlogloss:1.82069
[419]	train-mlogloss:1.83175	validation-mlogloss:1.82035
Saved model to disk.
2025-11-06 21:48:20.625962: 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 21:48:20.637225: 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 00:00:1762462100.650395 1828745 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462100.654682 1828745 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462100.664476 1828745 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462100.664498 1828745 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462100.664500 1828745 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462100.664502 1828745 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:48:20.667631: 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:2.68558	validation-mlogloss:2.68438
[3]	train-mlogloss:2.67848	validation-mlogloss:2.67715
[4]	train-mlogloss:2.67095	validation-mlogloss:2.66885
[5]	train-mlogloss:2.66405	validation-mlogloss:2.66167
[6]	train-mlogloss:2.65718	validation-mlogloss:2.65392
[7]	train-mlogloss:2.64978	validation-mlogloss:2.64611
[8]	train-mlogloss:2.64251	validation-mlogloss:2.63816
[9]	train-mlogloss:2.63600	validation-mlogloss:2.63142
[10]	train-mlogloss:2.62902	validation-mlogloss:2.62369
[11]	train-mlogloss:2.62245	validation-mlogloss:2.61667
[12]	train-mlogloss:2.61569	validation-mlogloss:2.60902
[13]	train-mlogloss:2.60910	validation-mlogloss:2.60189
[14]	train-mlogloss:2.60217	validation-mlogloss:2.59393
[15]	train-mlogloss:2.59555	validation-mlogloss:2.58651
[16]	train-mlogloss:2.58881	validation-mlogloss:2.57906
[17]	train-mlogloss:2.58230	validation-mlogloss:2.57180
[18]	train-mlogloss:2.57599	validation-mlogloss:2.56490
[19]	train-mlogloss:2.56992	validation-mlogloss:2.55854
[20]	train-mlogloss:2.56376	validation-mlogloss:2.55151
[21]	train-mlogloss:2.55768	validation-mlogloss:2.54506
[22]	train-mlogloss:2.55164	validation-mlogloss:2.53834
[23]	train-mlogloss:2.54581	validation-mlogloss:2.53188
[24]	train-mlogloss:2.53995	validation-mlogloss:2.52559
[25]	train-mlogloss:2.53410	validation-mlogloss:2.51941
[26]	train-mlogloss:2.52829	validation-mlogloss:2.51295
[27]	train-mlogloss:2.52289	validation-mlogloss:2.50712
[28]	train-mlogloss:2.51742	validation-mlogloss:2.50102
[29]	train-mlogloss:2.51215	validation-mlogloss:2.49541
[30]	train-mlogloss:2.50691	validation-mlogloss:2.48954
[31]	train-mlogloss:2.50151	validation-mlogloss:2.48353
[32]	train-mlogloss:2.49624	validation-mlogloss:2.47788
[33]	train-mlogloss:2.49099	validation-mlogloss:2.47184
[34]	train-mlogloss:2.48585	validation-mlogloss:2.46640
[35]	train-mlogloss:2.48077	validation-mlogloss:2.46090
[36]	train-mlogloss:2.47565	validation-mlogloss:2.45504
[37]	train-mlogloss:2.47077	validation-mlogloss:2.44988
[38]	train-mlogloss:2.46568	validation-mlogloss:2.44460
[39]	train-mlogloss:2.46076	validation-mlogloss:2.43930
[40]	train-mlogloss:2.45604	validation-mlogloss:2.43424
[41]	train-mlogloss:2.45107	validation-mlogloss:2.42865
[42]	train-mlogloss:2.44619	validation-mlogloss:2.42338
[43]	train-mlogloss:2.44130	validation-mlogloss:2.41781
[44]	train-mlogloss:2.43655	validation-mlogloss:2.41243
[45]	train-mlogloss:2.43203	validation-mlogloss:2.40757
[46]	train-mlogloss:2.42716	validation-mlogloss:2.40217
[47]	train-mlogloss:2.42271	validation-mlogloss:2.39750
[48]	train-mlogloss:2.41826	validation-mlogloss:2.39281
[49]	train-mlogloss:2.41373	validation-mlogloss:2.38790
[50]	train-mlogloss:2.40928	validation-mlogloss:2.38306
[51]	train-mlogloss:2.40469	validation-mlogloss:2.37793
[52]	train-mlogloss:2.40043	validation-mlogloss:2.37308
[53]	train-mlogloss:2.39576	validation-mlogloss:2.36793
[54]	train-mlogloss:2.39143	validation-mlogloss:2.36316
[55]	train-mlogloss:2.38730	validation-mlogloss:2.35881
[56]	train-mlogloss:2.38315	validation-mlogloss:2.35447
[57]	train-mlogloss:2.37878	validation-mlogloss:2.34938
[58]	train-mlogloss:2.37458	validation-mlogloss:2.34488
[59]	train-mlogloss:2.37032	validation-mlogloss:2.34028
[60]	train-mlogloss:2.36625	validation-mlogloss:2.33581
[61]	train-mlogloss:2.36192	validation-mlogloss:2.33087
[62]	train-mlogloss:2.35777	validation-mlogloss:2.32634
[63]	train-mlogloss:2.35384	validation-mlogloss:2.32208
[64]	train-mlogloss:2.35002	validation-mlogloss:2.31804
[65]	train-mlogloss:2.34624	validation-mlogloss:2.31377
[66]	train-mlogloss:2.34259	validation-mlogloss:2.30997
[67]	train-mlogloss:2.33879	validation-mlogloss:2.30593
[68]	train-mlogloss:2.33485	validation-mlogloss:2.30157
[69]	train-mlogloss:2.33094	validation-mlogloss:2.29706
[70]	train-mlogloss:2.32746	validation-mlogloss:2.29356
[71]	train-mlogloss:2.32379	validation-mlogloss:2.28951
[72]	train-mlogloss:2.32023	validation-mlogloss:2.28576
[73]	train-mlogloss:2.31653	validation-mlogloss:2.28159
[74]	train-mlogloss:2.31305	validation-mlogloss:2.27772
[75]	train-mlogloss:2.30943	validation-mlogloss:2.27395
[76]	train-mlogloss:2.30587	validation-mlogloss:2.27004
[77]	train-mlogloss:2.30214	validation-mlogloss:2.26604
[78]	train-mlogloss:2.29871	validation-mlogloss:2.26232
[79]	train-mlogloss:2.29553	validation-mlogloss:2.25881
[80]	train-mlogloss:2.29211	validation-mlogloss:2.25527
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[380]	train-mlogloss:1.85373	validation-mlogloss:1.83632
[381]	train-mlogloss:1.85329	validation-mlogloss:1.83604
[382]	train-mlogloss:1.85258	validation-mlogloss:1.83548
[383]	train-mlogloss:1.85185	validation-mlogloss:1.83502
[384]	train-mlogloss:1.85122	validation-mlogloss:1.83460
[385]	train-mlogloss:1.85064	validation-mlogloss:1.83425
[386]	train-mlogloss:1.84994	validation-mlogloss:1.83381
[387]	train-mlogloss:1.84943	validation-mlogloss:1.83350
[388]	train-mlogloss:1.84874	validation-mlogloss:1.83300
[389]	train-mlogloss:1.84813	validation-mlogloss:1.83248
[390]	train-mlogloss:1.84756	validation-mlogloss:1.83219
[391]	train-mlogloss:1.84703	validation-mlogloss:1.83169
[392]	train-mlogloss:1.84649	validation-mlogloss:1.83119
[393]	train-mlogloss:1.84589	validation-mlogloss:1.83089
[394]	train-mlogloss:1.84530	validation-mlogloss:1.83032
[395]	train-mlogloss:1.84476	validation-mlogloss:1.83006
[396]	train-mlogloss:1.84416	validation-mlogloss:1.82960
[397]	train-mlogloss:1.84358	validation-mlogloss:1.82921
[398]	train-mlogloss:1.84298	validation-mlogloss:1.82886
[399]	train-mlogloss:1.84244	validation-mlogloss:1.82856
[400]	train-mlogloss:1.84184	validation-mlogloss:1.82828
[401]	train-mlogloss:1.84126	validation-mlogloss:1.82790
[402]	train-mlogloss:1.84072	validation-mlogloss:1.82750
[403]	train-mlogloss:1.84021	validation-mlogloss:1.82723
[404]	train-mlogloss:1.83966	validation-mlogloss:1.82690
[405]	train-mlogloss:1.83915	validation-mlogloss:1.82660
[406]	train-mlogloss:1.83864	validation-mlogloss:1.82619
[407]	train-mlogloss:1.83807	validation-mlogloss:1.82583
[408]	train-mlogloss:1.83757	validation-mlogloss:1.82542
[409]	train-mlogloss:1.83710	validation-mlogloss:1.82515
[410]	train-mlogloss:1.83653	validation-mlogloss:1.82470
[411]	train-mlogloss:1.83607	validation-mlogloss:1.82432
[412]	train-mlogloss:1.83557	validation-mlogloss:1.82412
[413]	train-mlogloss:1.83513	validation-mlogloss:1.82380
[414]	train-mlogloss:1.83465	validation-mlogloss:1.82337
[415]	train-mlogloss:1.83418	validation-mlogloss:1.82299
[416]	train-mlogloss:1.83373	validation-mlogloss:1.82275
[417]	train-mlogloss:1.83311	validation-mlogloss:1.82241
[418]	train-mlogloss:1.83259	validation-mlogloss:1.82205
[419]	train-mlogloss:1.83214	validation-mlogloss:1.82188
Saved model to disk.
2025-11-06 21:48:42.511467: 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 21:48:42.522908: 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 00:00:1762462122.537050 1829113 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462122.541541 1829113 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462122.552236 1829113 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462122.552259 1829113 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462122.552261 1829113 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462122.552263 1829113 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:48:42.555679: 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:2.69280	validation-mlogloss:2.69166
[2]	train-mlogloss:2.68570	validation-mlogloss:2.68379
[3]	train-mlogloss:2.67808	validation-mlogloss:2.67581
[4]	train-mlogloss:2.67093	validation-mlogloss:2.66829
[5]	train-mlogloss:2.66384	validation-mlogloss:2.66081
[6]	train-mlogloss:2.65694	validation-mlogloss:2.65311
[7]	train-mlogloss:2.64935	validation-mlogloss:2.64506
[8]	train-mlogloss:2.64263	validation-mlogloss:2.63792
[9]	train-mlogloss:2.63551	validation-mlogloss:2.62999
[10]	train-mlogloss:2.62857	validation-mlogloss:2.62249
[11]	train-mlogloss:2.62186	validation-mlogloss:2.61523
[12]	train-mlogloss:2.61517	validation-mlogloss:2.60811
[13]	train-mlogloss:2.60878	validation-mlogloss:2.60136
[14]	train-mlogloss:2.60196	validation-mlogloss:2.59394
[15]	train-mlogloss:2.59530	validation-mlogloss:2.58658
[16]	train-mlogloss:2.58899	validation-mlogloss:2.57948
[17]	train-mlogloss:2.58236	validation-mlogloss:2.57210
[18]	train-mlogloss:2.57609	validation-mlogloss:2.56536
[19]	train-mlogloss:2.56980	validation-mlogloss:2.55858
[20]	train-mlogloss:2.56346	validation-mlogloss:2.55167
[21]	train-mlogloss:2.55735	validation-mlogloss:2.54477
[22]	train-mlogloss:2.55166	validation-mlogloss:2.53844
[23]	train-mlogloss:2.54575	validation-mlogloss:2.53192
[24]	train-mlogloss:2.54016	validation-mlogloss:2.52601
[25]	train-mlogloss:2.53421	validation-mlogloss:2.51933
[26]	train-mlogloss:2.52844	validation-mlogloss:2.51282
[27]	train-mlogloss:2.52285	validation-mlogloss:2.50675
[28]	train-mlogloss:2.51744	validation-mlogloss:2.50089
[29]	train-mlogloss:2.51208	validation-mlogloss:2.49532
[30]	train-mlogloss:2.50675	validation-mlogloss:2.48961
[31]	train-mlogloss:2.50130	validation-mlogloss:2.48360
[32]	train-mlogloss:2.49598	validation-mlogloss:2.47760
[33]	train-mlogloss:2.49087	validation-mlogloss:2.47211
[34]	train-mlogloss:2.48584	validation-mlogloss:2.46660
[35]	train-mlogloss:2.48055	validation-mlogloss:2.46065
[36]	train-mlogloss:2.47562	validation-mlogloss:2.45534
[37]	train-mlogloss:2.47044	validation-mlogloss:2.44966
[38]	train-mlogloss:2.46557	validation-mlogloss:2.44422
[39]	train-mlogloss:2.46061	validation-mlogloss:2.43894
[40]	train-mlogloss:2.45572	validation-mlogloss:2.43389
[41]	train-mlogloss:2.45108	validation-mlogloss:2.42897
[42]	train-mlogloss:2.44628	validation-mlogloss:2.42373
[43]	train-mlogloss:2.44139	validation-mlogloss:2.41822
[44]	train-mlogloss:2.43677	validation-mlogloss:2.41316
[45]	train-mlogloss:2.43176	validation-mlogloss:2.40752
[46]	train-mlogloss:2.42727	validation-mlogloss:2.40267
[47]	train-mlogloss:2.42256	validation-mlogloss:2.39758
[48]	train-mlogloss:2.41803	validation-mlogloss:2.39251
[49]	train-mlogloss:2.41368	validation-mlogloss:2.38786
[50]	train-mlogloss:2.40914	validation-mlogloss:2.38301
[51]	train-mlogloss:2.40454	validation-mlogloss:2.37788
[52]	train-mlogloss:2.39994	validation-mlogloss:2.37259
[53]	train-mlogloss:2.39563	validation-mlogloss:2.36818
[54]	train-mlogloss:2.39130	validation-mlogloss:2.36334
[55]	train-mlogloss:2.38729	validation-mlogloss:2.35921
[56]	train-mlogloss:2.38295	validation-mlogloss:2.35435
[57]	train-mlogloss:2.37873	validation-mlogloss:2.34935
[58]	train-mlogloss:2.37456	validation-mlogloss:2.34472
[59]	train-mlogloss:2.37052	validation-mlogloss:2.34004
[60]	train-mlogloss:2.36643	validation-mlogloss:2.33576
[61]	train-mlogloss:2.36231	validation-mlogloss:2.33089
[62]	train-mlogloss:2.35836	validation-mlogloss:2.32640
[63]	train-mlogloss:2.35445	validation-mlogloss:2.32227
[64]	train-mlogloss:2.35053	validation-mlogloss:2.31774
[65]	train-mlogloss:2.34668	validation-mlogloss:2.31358
[66]	train-mlogloss:2.34275	validation-mlogloss:2.30951
[67]	train-mlogloss:2.33895	validation-mlogloss:2.30520
[68]	train-mlogloss:2.33532	validation-mlogloss:2.30142
[69]	train-mlogloss:2.33155	validation-mlogloss:2.29729
[70]	train-mlogloss:2.32769	validation-mlogloss:2.29291
[71]	train-mlogloss:2.32393	validation-mlogloss:2.28864
[72]	train-mlogloss:2.32062	validation-mlogloss:2.28545
[73]	train-mlogloss:2.31721	validation-mlogloss:2.28183
[74]	train-mlogloss:2.31374	validation-mlogloss:2.27825
[75]	train-mlogloss:2.30996	validation-mlogloss:2.27395
[76]	train-mlogloss:2.30651	validation-mlogloss:2.27024
[77]	train-mlogloss:2.30303	validation-mlogloss:2.26635
[78]	train-mlogloss:2.29970	validation-mlogloss:2.26285
[79]	train-mlogloss:2.29628	validation-mlogloss:2.25904
[80]	train-mlogloss:2.29275	validation-mlogloss:2.25490
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[95]	train-mlogloss:2.24553	validation-mlogloss:2.20389
[96]	train-mlogloss:2.24256	validation-mlogloss:2.20067
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[98]	train-mlogloss:2.23694	validation-mlogloss:2.19505
[99]	train-mlogloss:2.23392	validation-mlogloss:2.19153
[100]	train-mlogloss:2.23111	validation-mlogloss:2.18847
[101]	train-mlogloss:2.22839	validation-mlogloss:2.18559
[102]	train-mlogloss:2.22547	validation-mlogloss:2.18236
[103]	train-mlogloss:2.22268	validation-mlogloss:2.17924
[104]	train-mlogloss:2.21989	validation-mlogloss:2.17651
[105]	train-mlogloss:2.21700	validation-mlogloss:2.17340
[106]	train-mlogloss:2.21430	validation-mlogloss:2.17040
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[108]	train-mlogloss:2.20908	validation-mlogloss:2.16522
[109]	train-mlogloss:2.20629	validation-mlogloss:2.16202
[110]	train-mlogloss:2.20363	validation-mlogloss:2.15911
[111]	train-mlogloss:2.20099	validation-mlogloss:2.15648
[112]	train-mlogloss:2.19838	validation-mlogloss:2.15382
[113]	train-mlogloss:2.19595	validation-mlogloss:2.15113
[114]	train-mlogloss:2.19339	validation-mlogloss:2.14839
[115]	train-mlogloss:2.19082	validation-mlogloss:2.14571
[116]	train-mlogloss:2.18836	validation-mlogloss:2.14312
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[126]	train-mlogloss:2.16472	validation-mlogloss:2.11828
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[130]	train-mlogloss:2.15530	validation-mlogloss:2.10863
[131]	train-mlogloss:2.15303	validation-mlogloss:2.10612
[132]	train-mlogloss:2.15088	validation-mlogloss:2.10410
[133]	train-mlogloss:2.14874	validation-mlogloss:2.10203
[134]	train-mlogloss:2.14650	validation-mlogloss:2.09975
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[136]	train-mlogloss:2.14219	validation-mlogloss:2.09522
[137]	train-mlogloss:2.13999	validation-mlogloss:2.09296
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[139]	train-mlogloss:2.13564	validation-mlogloss:2.08871
[140]	train-mlogloss:2.13356	validation-mlogloss:2.08646
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[145]	train-mlogloss:2.12343	validation-mlogloss:2.07630
[146]	train-mlogloss:2.12145	validation-mlogloss:2.07425
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[150]	train-mlogloss:2.11345	validation-mlogloss:2.06626
[151]	train-mlogloss:2.11152	validation-mlogloss:2.06423
[152]	train-mlogloss:2.10945	validation-mlogloss:2.06205
[153]	train-mlogloss:2.10747	validation-mlogloss:2.05995
[154]	train-mlogloss:2.10554	validation-mlogloss:2.05818
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[164]	train-mlogloss:2.08664	validation-mlogloss:2.03949
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[193]	train-mlogloss:2.03874	validation-mlogloss:1.99349
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[202]	train-mlogloss:2.02553	validation-mlogloss:1.98136
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[211]	train-mlogloss:2.01276	validation-mlogloss:1.96953
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[235]	train-mlogloss:1.98136	validation-mlogloss:1.94030
[236]	train-mlogloss:1.98024	validation-mlogloss:1.93911
[237]	train-mlogloss:1.97907	validation-mlogloss:1.93810
[238]	train-mlogloss:1.97788	validation-mlogloss:1.93700
[239]	train-mlogloss:1.97670	validation-mlogloss:1.93590
[240]	train-mlogloss:1.97557	validation-mlogloss:1.93510
[241]	train-mlogloss:1.97444	validation-mlogloss:1.93408
[242]	train-mlogloss:1.97328	validation-mlogloss:1.93285
[243]	train-mlogloss:1.97216	validation-mlogloss:1.93173
[244]	train-mlogloss:1.97096	validation-mlogloss:1.93073
[245]	train-mlogloss:1.96977	validation-mlogloss:1.92974
[246]	train-mlogloss:1.96861	validation-mlogloss:1.92844
[247]	train-mlogloss:1.96748	validation-mlogloss:1.92757
[248]	train-mlogloss:1.96631	validation-mlogloss:1.92670
[249]	train-mlogloss:1.96517	validation-mlogloss:1.92574
[250]	train-mlogloss:1.96400	validation-mlogloss:1.92478
[251]	train-mlogloss:1.96280	validation-mlogloss:1.92376
[252]	train-mlogloss:1.96161	validation-mlogloss:1.92245
[253]	train-mlogloss:1.96057	validation-mlogloss:1.92170
[254]	train-mlogloss:1.95943	validation-mlogloss:1.92064
[255]	train-mlogloss:1.95833	validation-mlogloss:1.91980
[256]	train-mlogloss:1.95722	validation-mlogloss:1.91878
[257]	train-mlogloss:1.95619	validation-mlogloss:1.91798
[258]	train-mlogloss:1.95510	validation-mlogloss:1.91708
[259]	train-mlogloss:1.95399	validation-mlogloss:1.91606
[260]	train-mlogloss:1.95289	validation-mlogloss:1.91512
[261]	train-mlogloss:1.95179	validation-mlogloss:1.91431
[262]	train-mlogloss:1.95068	validation-mlogloss:1.91361
[263]	train-mlogloss:1.94967	validation-mlogloss:1.91281
[264]	train-mlogloss:1.94857	validation-mlogloss:1.91187
[265]	train-mlogloss:1.94748	validation-mlogloss:1.91083
[266]	train-mlogloss:1.94649	validation-mlogloss:1.90991
[267]	train-mlogloss:1.94553	validation-mlogloss:1.90903
[268]	train-mlogloss:1.94441	validation-mlogloss:1.90796
[269]	train-mlogloss:1.94336	validation-mlogloss:1.90692
[270]	train-mlogloss:1.94241	validation-mlogloss:1.90612
[271]	train-mlogloss:1.94134	validation-mlogloss:1.90507
[272]	train-mlogloss:1.94032	validation-mlogloss:1.90412
[273]	train-mlogloss:1.93934	validation-mlogloss:1.90341
[274]	train-mlogloss:1.93835	validation-mlogloss:1.90255
[275]	train-mlogloss:1.93733	validation-mlogloss:1.90146
[276]	train-mlogloss:1.93633	validation-mlogloss:1.90056
[277]	train-mlogloss:1.93535	validation-mlogloss:1.89979
[278]	train-mlogloss:1.93432	validation-mlogloss:1.89895
[279]	train-mlogloss:1.93325	validation-mlogloss:1.89809
[280]	train-mlogloss:1.93224	validation-mlogloss:1.89719
[281]	train-mlogloss:1.93121	validation-mlogloss:1.89629
[282]	train-mlogloss:1.93021	validation-mlogloss:1.89531
[283]	train-mlogloss:1.92923	validation-mlogloss:1.89446
[284]	train-mlogloss:1.92827	validation-mlogloss:1.89360
[285]	train-mlogloss:1.92729	validation-mlogloss:1.89275
[286]	train-mlogloss:1.92629	validation-mlogloss:1.89190
[287]	train-mlogloss:1.92524	validation-mlogloss:1.89094
[288]	train-mlogloss:1.92429	validation-mlogloss:1.89011
[289]	train-mlogloss:1.92331	validation-mlogloss:1.88921
[290]	train-mlogloss:1.92233	validation-mlogloss:1.88843
[291]	train-mlogloss:1.92142	validation-mlogloss:1.88755
[292]	train-mlogloss:1.92049	validation-mlogloss:1.88699
[293]	train-mlogloss:1.91959	validation-mlogloss:1.88610
[294]	train-mlogloss:1.91873	validation-mlogloss:1.88533
[295]	train-mlogloss:1.91787	validation-mlogloss:1.88463
[296]	train-mlogloss:1.91697	validation-mlogloss:1.88381
[297]	train-mlogloss:1.91604	validation-mlogloss:1.88314
[298]	train-mlogloss:1.91516	validation-mlogloss:1.88244
[299]	train-mlogloss:1.91423	validation-mlogloss:1.88171
[300]	train-mlogloss:1.91328	validation-mlogloss:1.88087
[301]	train-mlogloss:1.91238	validation-mlogloss:1.88001
[302]	train-mlogloss:1.91149	validation-mlogloss:1.87931
[303]	train-mlogloss:1.91063	validation-mlogloss:1.87856
[304]	train-mlogloss:1.90973	validation-mlogloss:1.87783
[305]	train-mlogloss:1.90882	validation-mlogloss:1.87692
[306]	train-mlogloss:1.90795	validation-mlogloss:1.87630
[307]	train-mlogloss:1.90711	validation-mlogloss:1.87577
[308]	train-mlogloss:1.90624	validation-mlogloss:1.87492
[309]	train-mlogloss:1.90523	validation-mlogloss:1.87427
[310]	train-mlogloss:1.90439	validation-mlogloss:1.87351
[311]	train-mlogloss:1.90351	validation-mlogloss:1.87291
[312]	train-mlogloss:1.90279	validation-mlogloss:1.87233
[313]	train-mlogloss:1.90199	validation-mlogloss:1.87167
[314]	train-mlogloss:1.90115	validation-mlogloss:1.87108
[315]	train-mlogloss:1.90035	validation-mlogloss:1.87056
[316]	train-mlogloss:1.89960	validation-mlogloss:1.87005
[317]	train-mlogloss:1.89879	validation-mlogloss:1.86947
[318]	train-mlogloss:1.89797	validation-mlogloss:1.86874
[319]	train-mlogloss:1.89715	validation-mlogloss:1.86824
[320]	train-mlogloss:1.89637	validation-mlogloss:1.86763
[321]	train-mlogloss:1.89542	validation-mlogloss:1.86677
[322]	train-mlogloss:1.89449	validation-mlogloss:1.86597
[323]	train-mlogloss:1.89370	validation-mlogloss:1.86540
[324]	train-mlogloss:1.89289	validation-mlogloss:1.86479
[325]	train-mlogloss:1.89217	validation-mlogloss:1.86428
[326]	train-mlogloss:1.89137	validation-mlogloss:1.86360
[327]	train-mlogloss:1.89059	validation-mlogloss:1.86288
[328]	train-mlogloss:1.88977	validation-mlogloss:1.86226
[329]	train-mlogloss:1.88894	validation-mlogloss:1.86168
[330]	train-mlogloss:1.88808	validation-mlogloss:1.86086
[331]	train-mlogloss:1.88731	validation-mlogloss:1.86014
[332]	train-mlogloss:1.88654	validation-mlogloss:1.85957
[333]	train-mlogloss:1.88569	validation-mlogloss:1.85902
[334]	train-mlogloss:1.88497	validation-mlogloss:1.85855
[335]	train-mlogloss:1.88426	validation-mlogloss:1.85795
[336]	train-mlogloss:1.88359	validation-mlogloss:1.85756
[337]	train-mlogloss:1.88276	validation-mlogloss:1.85685
[338]	train-mlogloss:1.88195	validation-mlogloss:1.85614
[339]	train-mlogloss:1.88113	validation-mlogloss:1.85568
[340]	train-mlogloss:1.88039	validation-mlogloss:1.85524
[341]	train-mlogloss:1.87963	validation-mlogloss:1.85455
[342]	train-mlogloss:1.87880	validation-mlogloss:1.85388
[343]	train-mlogloss:1.87813	validation-mlogloss:1.85341
[344]	train-mlogloss:1.87750	validation-mlogloss:1.85292
[345]	train-mlogloss:1.87678	validation-mlogloss:1.85248
[346]	train-mlogloss:1.87601	validation-mlogloss:1.85200
[347]	train-mlogloss:1.87532	validation-mlogloss:1.85154
[348]	train-mlogloss:1.87448	validation-mlogloss:1.85110
[349]	train-mlogloss:1.87377	validation-mlogloss:1.85052
[350]	train-mlogloss:1.87308	validation-mlogloss:1.85005
[351]	train-mlogloss:1.87240	validation-mlogloss:1.84956
[352]	train-mlogloss:1.87171	validation-mlogloss:1.84902
[353]	train-mlogloss:1.87099	validation-mlogloss:1.84857
[354]	train-mlogloss:1.87025	validation-mlogloss:1.84806
[355]	train-mlogloss:1.86952	validation-mlogloss:1.84763
[356]	train-mlogloss:1.86877	validation-mlogloss:1.84721
[357]	train-mlogloss:1.86808	validation-mlogloss:1.84665
[358]	train-mlogloss:1.86739	validation-mlogloss:1.84613
[359]	train-mlogloss:1.86673	validation-mlogloss:1.84571
[360]	train-mlogloss:1.86604	validation-mlogloss:1.84517
[361]	train-mlogloss:1.86536	validation-mlogloss:1.84465
[362]	train-mlogloss:1.86477	validation-mlogloss:1.84424
[363]	train-mlogloss:1.86410	validation-mlogloss:1.84362
[364]	train-mlogloss:1.86344	validation-mlogloss:1.84316
[365]	train-mlogloss:1.86283	validation-mlogloss:1.84252
[366]	train-mlogloss:1.86214	validation-mlogloss:1.84222
[367]	train-mlogloss:1.86147	validation-mlogloss:1.84161
[368]	train-mlogloss:1.86079	validation-mlogloss:1.84121
[369]	train-mlogloss:1.86015	validation-mlogloss:1.84051
[370]	train-mlogloss:1.85953	validation-mlogloss:1.83996
[371]	train-mlogloss:1.85885	validation-mlogloss:1.83950
[372]	train-mlogloss:1.85826	validation-mlogloss:1.83926
[373]	train-mlogloss:1.85760	validation-mlogloss:1.83900
[374]	train-mlogloss:1.85699	validation-mlogloss:1.83859
[375]	train-mlogloss:1.85640	validation-mlogloss:1.83838
[376]	train-mlogloss:1.85579	validation-mlogloss:1.83812
[377]	train-mlogloss:1.85519	validation-mlogloss:1.83763
[378]	train-mlogloss:1.85458	validation-mlogloss:1.83720
[379]	train-mlogloss:1.85402	validation-mlogloss:1.83683
[380]	train-mlogloss:1.85334	validation-mlogloss:1.83627
[381]	train-mlogloss:1.85268	validation-mlogloss:1.83566
[382]	train-mlogloss:1.85208	validation-mlogloss:1.83524
[383]	train-mlogloss:1.85151	validation-mlogloss:1.83482
[384]	train-mlogloss:1.85083	validation-mlogloss:1.83426
[385]	train-mlogloss:1.85026	validation-mlogloss:1.83392
[386]	train-mlogloss:1.84967	validation-mlogloss:1.83367
[387]	train-mlogloss:1.84909	validation-mlogloss:1.83335
[388]	train-mlogloss:1.84859	validation-mlogloss:1.83303
[389]	train-mlogloss:1.84803	validation-mlogloss:1.83275
[390]	train-mlogloss:1.84744	validation-mlogloss:1.83218
[391]	train-mlogloss:1.84683	validation-mlogloss:1.83175
[392]	train-mlogloss:1.84626	validation-mlogloss:1.83142
[393]	train-mlogloss:1.84571	validation-mlogloss:1.83102
[394]	train-mlogloss:1.84520	validation-mlogloss:1.83083
[395]	train-mlogloss:1.84473	validation-mlogloss:1.83056
[396]	train-mlogloss:1.84416	validation-mlogloss:1.83024
[397]	train-mlogloss:1.84363	validation-mlogloss:1.82981
[398]	train-mlogloss:1.84308	validation-mlogloss:1.82932
[399]	train-mlogloss:1.84252	validation-mlogloss:1.82884
[400]	train-mlogloss:1.84200	validation-mlogloss:1.82851
[401]	train-mlogloss:1.84140	validation-mlogloss:1.82819
[402]	train-mlogloss:1.84087	validation-mlogloss:1.82788
[403]	train-mlogloss:1.84036	validation-mlogloss:1.82764
[404]	train-mlogloss:1.83981	validation-mlogloss:1.82718
[405]	train-mlogloss:1.83932	validation-mlogloss:1.82690
[406]	train-mlogloss:1.83888	validation-mlogloss:1.82664
[407]	train-mlogloss:1.83834	validation-mlogloss:1.82619
[408]	train-mlogloss:1.83795	validation-mlogloss:1.82591
[409]	train-mlogloss:1.83740	validation-mlogloss:1.82553
[410]	train-mlogloss:1.83692	validation-mlogloss:1.82509
[411]	train-mlogloss:1.83638	validation-mlogloss:1.82476
[412]	train-mlogloss:1.83586	validation-mlogloss:1.82438
[413]	train-mlogloss:1.83531	validation-mlogloss:1.82396
[414]	train-mlogloss:1.83483	validation-mlogloss:1.82376
[415]	train-mlogloss:1.83439	validation-mlogloss:1.82344
[416]	train-mlogloss:1.83392	validation-mlogloss:1.82306
[417]	train-mlogloss:1.83344	validation-mlogloss:1.82285
[418]	train-mlogloss:1.83301	validation-mlogloss:1.82257
[419]	train-mlogloss:1.83255	validation-mlogloss:1.82222
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.17 [%]
Global accuracy score (test) = 44.36 [%]
Global F1 score (train) = 43.71 [%]
Global F1 score (test) = 43.5 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.72      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.45      0.44       184
       CAMINAR USUAL SPEED       0.31      0.15      0.21       184
            CAMINAR ZIGZAG       0.32      0.55      0.40       184
          DE PIE BARRIENDO       0.74      0.42      0.53       184
   DE PIE DOBLANDO TOALLAS       0.45      0.44      0.44       184
    DE PIE MOVIENDO LIBROS       0.38      0.40      0.39       184
          DE PIE USANDO PC       0.22      0.33      0.26       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.64      0.58      0.61       184
           SENTADO LEYENDO       0.47      0.40      0.43       184
         SENTADO USANDO PC       0.26      0.13      0.17       184
      SENTADO VIENDO LA TV       0.24      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.65      0.56      0.60       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 13: 44.36 [%]
F1-score capturado en la ejecución 13: 43.5 [%]

=== EJECUCIÓN 14 ===

--- TRAIN (ejecución 14) ---

--- TEST (ejecución 14) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.37 [%]
Global accuracy score (test) = 44.14 [%]
Global F1 score (train) = 43.88 [%]
Global F1 score (test) = 43.38 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.44      0.44       184
       CAMINAR USUAL SPEED       0.37      0.18      0.25       184
            CAMINAR ZIGZAG       0.31      0.53      0.39       184
          DE PIE BARRIENDO       0.71      0.43      0.53       184
   DE PIE DOBLANDO TOALLAS       0.45      0.43      0.44       184
    DE PIE MOVIENDO LIBROS       0.37      0.39      0.38       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.58      0.61       184
           SENTADO LEYENDO       0.46      0.39      0.42       184
         SENTADO USANDO PC       0.24      0.12      0.16       184
      SENTADO VIENDO LA TV       0.23      0.15      0.18       184
   SUBIR Y BAJAR ESCALERAS       0.63      0.56      0.59       184
                    TROTAR       0.66      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 14: 44.14 [%]
F1-score capturado en la ejecución 14: 43.38 [%]

=== EJECUCIÓN 15 ===

--- TRAIN (ejecución 15) ---

--- TEST (ejecución 15) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.24 [%]
Global accuracy score (test) = 43.55 [%]
Global F1 score (train) = 43.73 [%]
Global F1 score (test) = 42.61 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.42      0.45      0.44       184
       CAMINAR USUAL SPEED       0.29      0.15      0.20       184
            CAMINAR ZIGZAG       0.32      0.55      0.40       184
          DE PIE BARRIENDO       0.68      0.39      0.50       184
   DE PIE DOBLANDO TOALLAS       0.46      0.43      0.45       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.38       184
          DE PIE USANDO PC       0.20      0.31      0.24       184
        FASE REPOSO CON K5       0.55      0.83      0.66       184
INCREMENTAL CICLOERGOMETRO       0.65      0.57      0.61       184
           SENTADO LEYENDO       0.46      0.39      0.42       184
         SENTADO USANDO PC       0.21      0.10      0.13       184
      SENTADO VIENDO LA TV       0.23      0.15      0.18       184
   SUBIR Y BAJAR ESCALERAS       0.65      0.56      0.60       184
                    TROTAR       0.66      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.44      0.44      0.43      2737
              weighted avg       0.44      0.44      0.42      2737


Accuracy capturado en la ejecución 15: 43.55 [%]
F1-score capturado en la ejecución 15: 42.61 [%]

=== EJECUCIÓN 16 ===

--- TRAIN (ejecución 16) ---

--- TEST (ejecución 16) ---
2025-11-06 21:49:04.452926: 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 21:49:04.464307: 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 00:00:1762462144.477787 1829476 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462144.481838 1829476 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462144.492078 1829476 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462144.492096 1829476 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462144.492097 1829476 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462144.492099 1829476 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:49:04.495381: 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:2.70023	validation-mlogloss:2.70005
[1]	train-mlogloss:2.69248	validation-mlogloss:2.69190
[2]	train-mlogloss:2.68501	validation-mlogloss:2.68391
[3]	train-mlogloss:2.67781	validation-mlogloss:2.67637
[4]	train-mlogloss:2.67055	validation-mlogloss:2.66856
[5]	train-mlogloss:2.66308	validation-mlogloss:2.66043
[6]	train-mlogloss:2.65644	validation-mlogloss:2.65356
[7]	train-mlogloss:2.64963	validation-mlogloss:2.64615
[8]	train-mlogloss:2.64219	validation-mlogloss:2.63813
[9]	train-mlogloss:2.63507	validation-mlogloss:2.63041
[10]	train-mlogloss:2.62802	validation-mlogloss:2.62259
[11]	train-mlogloss:2.62075	validation-mlogloss:2.61469
[12]	train-mlogloss:2.61443	validation-mlogloss:2.60801
[13]	train-mlogloss:2.60748	validation-mlogloss:2.60061
[14]	train-mlogloss:2.60118	validation-mlogloss:2.59363
[15]	train-mlogloss:2.59455	validation-mlogloss:2.58646
[16]	train-mlogloss:2.58788	validation-mlogloss:2.57931
[17]	train-mlogloss:2.58151	validation-mlogloss:2.57222
[18]	train-mlogloss:2.57507	validation-mlogloss:2.56515
[19]	train-mlogloss:2.56883	validation-mlogloss:2.55829
[20]	train-mlogloss:2.56280	validation-mlogloss:2.55169
[21]	train-mlogloss:2.55671	validation-mlogloss:2.54491
[22]	train-mlogloss:2.55081	validation-mlogloss:2.53833
[23]	train-mlogloss:2.54481	validation-mlogloss:2.53175
[24]	train-mlogloss:2.53899	validation-mlogloss:2.52524
[25]	train-mlogloss:2.53311	validation-mlogloss:2.51875
[26]	train-mlogloss:2.52710	validation-mlogloss:2.51185
[27]	train-mlogloss:2.52119	validation-mlogloss:2.50511
[28]	train-mlogloss:2.51575	validation-mlogloss:2.49916
[29]	train-mlogloss:2.51026	validation-mlogloss:2.49300
[30]	train-mlogloss:2.50491	validation-mlogloss:2.48717
[31]	train-mlogloss:2.49975	validation-mlogloss:2.48184
[32]	train-mlogloss:2.49449	validation-mlogloss:2.47590
[33]	train-mlogloss:2.48938	validation-mlogloss:2.47043
[34]	train-mlogloss:2.48426	validation-mlogloss:2.46492
[35]	train-mlogloss:2.47920	validation-mlogloss:2.45930
[36]	train-mlogloss:2.47405	validation-mlogloss:2.45360
[37]	train-mlogloss:2.46917	validation-mlogloss:2.44804
[38]	train-mlogloss:2.46440	validation-mlogloss:2.44295
[39]	train-mlogloss:2.45944	validation-mlogloss:2.43756
[40]	train-mlogloss:2.45482	validation-mlogloss:2.43253
[41]	train-mlogloss:2.45007	validation-mlogloss:2.42737
[42]	train-mlogloss:2.44506	validation-mlogloss:2.42173
[43]	train-mlogloss:2.44048	validation-mlogloss:2.41691
[44]	train-mlogloss:2.43584	validation-mlogloss:2.41167
[45]	train-mlogloss:2.43129	validation-mlogloss:2.40679
[46]	train-mlogloss:2.42683	validation-mlogloss:2.40180
[47]	train-mlogloss:2.42236	validation-mlogloss:2.39686
[48]	train-mlogloss:2.41776	validation-mlogloss:2.39144
[49]	train-mlogloss:2.41331	validation-mlogloss:2.38653
[50]	train-mlogloss:2.40901	validation-mlogloss:2.38189
[51]	train-mlogloss:2.40459	validation-mlogloss:2.37701
[52]	train-mlogloss:2.40034	validation-mlogloss:2.37230
[53]	train-mlogloss:2.39622	validation-mlogloss:2.36794
[54]	train-mlogloss:2.39183	validation-mlogloss:2.36322
[55]	train-mlogloss:2.38758	validation-mlogloss:2.35863
[56]	train-mlogloss:2.38313	validation-mlogloss:2.35339
[57]	train-mlogloss:2.37892	validation-mlogloss:2.34883
[58]	train-mlogloss:2.37468	validation-mlogloss:2.34423
[59]	train-mlogloss:2.37037	validation-mlogloss:2.33942
[60]	train-mlogloss:2.36636	validation-mlogloss:2.33511
[61]	train-mlogloss:2.36227	validation-mlogloss:2.33052
[62]	train-mlogloss:2.35833	validation-mlogloss:2.32634
[63]	train-mlogloss:2.35422	validation-mlogloss:2.32188
[64]	train-mlogloss:2.35051	validation-mlogloss:2.31797
[65]	train-mlogloss:2.34663	validation-mlogloss:2.31386
[66]	train-mlogloss:2.34268	validation-mlogloss:2.30966
[67]	train-mlogloss:2.33879	validation-mlogloss:2.30518
[68]	train-mlogloss:2.33490	validation-mlogloss:2.30077
[69]	train-mlogloss:2.33103	validation-mlogloss:2.29647
[70]	train-mlogloss:2.32722	validation-mlogloss:2.29231
[71]	train-mlogloss:2.32370	validation-mlogloss:2.28848
[72]	train-mlogloss:2.31987	validation-mlogloss:2.28438
[73]	train-mlogloss:2.31642	validation-mlogloss:2.28099
[74]	train-mlogloss:2.31267	validation-mlogloss:2.27705
[75]	train-mlogloss:2.30942	validation-mlogloss:2.27352
[76]	train-mlogloss:2.30591	validation-mlogloss:2.26955
[77]	train-mlogloss:2.30250	validation-mlogloss:2.26603
[78]	train-mlogloss:2.29871	validation-mlogloss:2.26194
[79]	train-mlogloss:2.29540	validation-mlogloss:2.25852
[80]	train-mlogloss:2.29193	validation-mlogloss:2.25469
[81]	train-mlogloss:2.28863	validation-mlogloss:2.25085
[82]	train-mlogloss:2.28537	validation-mlogloss:2.24742
[83]	train-mlogloss:2.28208	validation-mlogloss:2.24404
[84]	train-mlogloss:2.27902	validation-mlogloss:2.24085
[85]	train-mlogloss:2.27572	validation-mlogloss:2.23699
[86]	train-mlogloss:2.27264	validation-mlogloss:2.23396
[87]	train-mlogloss:2.26934	validation-mlogloss:2.23025
[88]	train-mlogloss:2.26605	validation-mlogloss:2.22679
[89]	train-mlogloss:2.26283	validation-mlogloss:2.22307
[90]	train-mlogloss:2.25979	validation-mlogloss:2.21988
[91]	train-mlogloss:2.25686	validation-mlogloss:2.21672
[92]	train-mlogloss:2.25389	validation-mlogloss:2.21373
[93]	train-mlogloss:2.25098	validation-mlogloss:2.21055
[94]	train-mlogloss:2.24801	validation-mlogloss:2.20736
[95]	train-mlogloss:2.24519	validation-mlogloss:2.20452
[96]	train-mlogloss:2.24235	validation-mlogloss:2.20159
[97]	train-mlogloss:2.23941	validation-mlogloss:2.19841
[98]	train-mlogloss:2.23635	validation-mlogloss:2.19509
[99]	train-mlogloss:2.23363	validation-mlogloss:2.19239
[100]	train-mlogloss:2.23093	validation-mlogloss:2.18960
[101]	train-mlogloss:2.22819	validation-mlogloss:2.18684
[102]	train-mlogloss:2.22550	validation-mlogloss:2.18392
[103]	train-mlogloss:2.22257	validation-mlogloss:2.18069
[104]	train-mlogloss:2.21982	validation-mlogloss:2.17762
[105]	train-mlogloss:2.21693	validation-mlogloss:2.17455
[106]	train-mlogloss:2.21420	validation-mlogloss:2.17170
[107]	train-mlogloss:2.21136	validation-mlogloss:2.16852
[108]	train-mlogloss:2.20863	validation-mlogloss:2.16567
[109]	train-mlogloss:2.20605	validation-mlogloss:2.16291
[110]	train-mlogloss:2.20367	validation-mlogloss:2.16061
[111]	train-mlogloss:2.20116	validation-mlogloss:2.15810
[112]	train-mlogloss:2.19864	validation-mlogloss:2.15543
[113]	train-mlogloss:2.19615	validation-mlogloss:2.15291
[114]	train-mlogloss:2.19354	validation-mlogloss:2.15010
[115]	train-mlogloss:2.19113	validation-mlogloss:2.14762
[116]	train-mlogloss:2.18853	validation-mlogloss:2.14481
[117]	train-mlogloss:2.18610	validation-mlogloss:2.14207
[118]	train-mlogloss:2.18362	validation-mlogloss:2.13952
[119]	train-mlogloss:2.18118	validation-mlogloss:2.13697
[120]	train-mlogloss:2.17881	validation-mlogloss:2.13455
[121]	train-mlogloss:2.17652	validation-mlogloss:2.13206
[122]	train-mlogloss:2.17432	validation-mlogloss:2.12983
[123]	train-mlogloss:2.17206	validation-mlogloss:2.12756
[124]	train-mlogloss:2.16964	validation-mlogloss:2.12490
[125]	train-mlogloss:2.16715	validation-mlogloss:2.12203
[126]	train-mlogloss:2.16477	validation-mlogloss:2.11965
[127]	train-mlogloss:2.16239	validation-mlogloss:2.11717
[128]	train-mlogloss:2.16007	validation-mlogloss:2.11454
[129]	train-mlogloss:2.15774	validation-mlogloss:2.11206
[130]	train-mlogloss:2.15523	validation-mlogloss:2.10942
[131]	train-mlogloss:2.15295	validation-mlogloss:2.10710
[132]	train-mlogloss:2.15074	validation-mlogloss:2.10455
[133]	train-mlogloss:2.14848	validation-mlogloss:2.10236
[134]	train-mlogloss:2.14635	validation-mlogloss:2.10013
[135]	train-mlogloss:2.14410	validation-mlogloss:2.09783
[136]	train-mlogloss:2.14193	validation-mlogloss:2.09567
[137]	train-mlogloss:2.13969	validation-mlogloss:2.09325
[138]	train-mlogloss:2.13742	validation-mlogloss:2.09094
[139]	train-mlogloss:2.13525	validation-mlogloss:2.08860
[140]	train-mlogloss:2.13323	validation-mlogloss:2.08666
[141]	train-mlogloss:2.13110	validation-mlogloss:2.08454
[142]	train-mlogloss:2.12906	validation-mlogloss:2.08257
[143]	train-mlogloss:2.12698	validation-mlogloss:2.08057
[144]	train-mlogloss:2.12492	validation-mlogloss:2.07850
[145]	train-mlogloss:2.12289	validation-mlogloss:2.07631
[146]	train-mlogloss:2.12070	validation-mlogloss:2.07370
[147]	train-mlogloss:2.11867	validation-mlogloss:2.07154
[148]	train-mlogloss:2.11667	validation-mlogloss:2.06972
[149]	train-mlogloss:2.11474	validation-mlogloss:2.06791
[150]	train-mlogloss:2.11288	validation-mlogloss:2.06610
[151]	train-mlogloss:2.11092	validation-mlogloss:2.06414
[152]	train-mlogloss:2.10886	validation-mlogloss:2.06199
[153]	train-mlogloss:2.10683	validation-mlogloss:2.05992
[154]	train-mlogloss:2.10484	validation-mlogloss:2.05781
[155]	train-mlogloss:2.10280	validation-mlogloss:2.05572
[156]	train-mlogloss:2.10083	validation-mlogloss:2.05372
[157]	train-mlogloss:2.09895	validation-mlogloss:2.05181
[158]	train-mlogloss:2.09701	validation-mlogloss:2.04982
[159]	train-mlogloss:2.09518	validation-mlogloss:2.04803
[160]	train-mlogloss:2.09336	validation-mlogloss:2.04613
[161]	train-mlogloss:2.09168	validation-mlogloss:2.04462
[162]	train-mlogloss:2.08991	validation-mlogloss:2.04302
[163]	train-mlogloss:2.08819	validation-mlogloss:2.04135
[164]	train-mlogloss:2.08643	validation-mlogloss:2.03973
[165]	train-mlogloss:2.08461	validation-mlogloss:2.03791
[166]	train-mlogloss:2.08280	validation-mlogloss:2.03608
[167]	train-mlogloss:2.08108	validation-mlogloss:2.03451
[168]	train-mlogloss:2.07921	validation-mlogloss:2.03280
[169]	train-mlogloss:2.07753	validation-mlogloss:2.03132
[170]	train-mlogloss:2.07584	validation-mlogloss:2.02949
[171]	train-mlogloss:2.07411	validation-mlogloss:2.02763
[172]	train-mlogloss:2.07231	validation-mlogloss:2.02587
[173]	train-mlogloss:2.07053	validation-mlogloss:2.02421
[174]	train-mlogloss:2.06885	validation-mlogloss:2.02249
[175]	train-mlogloss:2.06718	validation-mlogloss:2.02108
[176]	train-mlogloss:2.06540	validation-mlogloss:2.01936
[177]	train-mlogloss:2.06391	validation-mlogloss:2.01801
[178]	train-mlogloss:2.06232	validation-mlogloss:2.01655
[179]	train-mlogloss:2.06065	validation-mlogloss:2.01491
[180]	train-mlogloss:2.05907	validation-mlogloss:2.01329
[181]	train-mlogloss:2.05739	validation-mlogloss:2.01182
[182]	train-mlogloss:2.05585	validation-mlogloss:2.01068
[183]	train-mlogloss:2.05419	validation-mlogloss:2.00923
[184]	train-mlogloss:2.05260	validation-mlogloss:2.00746
[185]	train-mlogloss:2.05088	validation-mlogloss:2.00550
[186]	train-mlogloss:2.04932	validation-mlogloss:2.00393
[187]	train-mlogloss:2.04773	validation-mlogloss:2.00248
[188]	train-mlogloss:2.04615	validation-mlogloss:2.00079
[189]	train-mlogloss:2.04464	validation-mlogloss:1.99953
[190]	train-mlogloss:2.04314	validation-mlogloss:1.99795
[191]	train-mlogloss:2.04155	validation-mlogloss:1.99660
[192]	train-mlogloss:2.03995	validation-mlogloss:1.99508
[193]	train-mlogloss:2.03843	validation-mlogloss:1.99376
[194]	train-mlogloss:2.03692	validation-mlogloss:1.99237
[195]	train-mlogloss:2.03531	validation-mlogloss:1.99080
[196]	train-mlogloss:2.03365	validation-mlogloss:1.98911
[197]	train-mlogloss:2.03209	validation-mlogloss:1.98762
[198]	train-mlogloss:2.03057	validation-mlogloss:1.98637
[199]	train-mlogloss:2.02915	validation-mlogloss:1.98516
[200]	train-mlogloss:2.02769	validation-mlogloss:1.98375
[201]	train-mlogloss:2.02618	validation-mlogloss:1.98218
[202]	train-mlogloss:2.02472	validation-mlogloss:1.98084
[203]	train-mlogloss:2.02331	validation-mlogloss:1.97953
[204]	train-mlogloss:2.02194	validation-mlogloss:1.97827
[205]	train-mlogloss:2.02046	validation-mlogloss:1.97671
[206]	train-mlogloss:2.01897	validation-mlogloss:1.97520
[207]	train-mlogloss:2.01765	validation-mlogloss:1.97391
[208]	train-mlogloss:2.01636	validation-mlogloss:1.97280
[209]	train-mlogloss:2.01502	validation-mlogloss:1.97147
[210]	train-mlogloss:2.01367	validation-mlogloss:1.97036
[211]	train-mlogloss:2.01237	validation-mlogloss:1.96923
[212]	train-mlogloss:2.01108	validation-mlogloss:1.96802
[213]	train-mlogloss:2.00972	validation-mlogloss:1.96686
[214]	train-mlogloss:2.00831	validation-mlogloss:1.96546
[215]	train-mlogloss:2.00701	validation-mlogloss:1.96435
[216]	train-mlogloss:2.00564	validation-mlogloss:1.96303
[217]	train-mlogloss:2.00438	validation-mlogloss:1.96185
[218]	train-mlogloss:2.00308	validation-mlogloss:1.96049
[219]	train-mlogloss:2.00179	validation-mlogloss:1.95930
[220]	train-mlogloss:2.00046	validation-mlogloss:1.95818
[221]	train-mlogloss:1.99910	validation-mlogloss:1.95700
[222]	train-mlogloss:1.99773	validation-mlogloss:1.95551
[223]	train-mlogloss:1.99654	validation-mlogloss:1.95437
[224]	train-mlogloss:1.99522	validation-mlogloss:1.95320
[225]	train-mlogloss:1.99401	validation-mlogloss:1.95218
[226]	train-mlogloss:1.99278	validation-mlogloss:1.95082
[227]	train-mlogloss:1.99153	validation-mlogloss:1.94951
[228]	train-mlogloss:1.99031	validation-mlogloss:1.94848
[229]	train-mlogloss:1.98907	validation-mlogloss:1.94728
[230]	train-mlogloss:1.98774	validation-mlogloss:1.94620
[231]	train-mlogloss:1.98652	validation-mlogloss:1.94505
[232]	train-mlogloss:1.98526	validation-mlogloss:1.94402
[233]	train-mlogloss:1.98408	validation-mlogloss:1.94295
[234]	train-mlogloss:1.98292	validation-mlogloss:1.94176
[235]	train-mlogloss:1.98168	validation-mlogloss:1.94063
[236]	train-mlogloss:1.98050	validation-mlogloss:1.93958
[237]	train-mlogloss:1.97933	validation-mlogloss:1.93867
[238]	train-mlogloss:1.97808	validation-mlogloss:1.93752
[239]	train-mlogloss:1.97690	validation-mlogloss:1.93645
[240]	train-mlogloss:1.97576	validation-mlogloss:1.93542
[241]	train-mlogloss:1.97470	validation-mlogloss:1.93445
[242]	train-mlogloss:1.97343	validation-mlogloss:1.93333
[243]	train-mlogloss:1.97228	validation-mlogloss:1.93220
[244]	train-mlogloss:1.97122	validation-mlogloss:1.93128
[245]	train-mlogloss:1.96994	validation-mlogloss:1.93004
[246]	train-mlogloss:1.96876	validation-mlogloss:1.92911
[247]	train-mlogloss:1.96756	validation-mlogloss:1.92797
[248]	train-mlogloss:1.96647	validation-mlogloss:1.92709
[249]	train-mlogloss:1.96532	validation-mlogloss:1.92599
[250]	train-mlogloss:1.96420	validation-mlogloss:1.92495
[251]	train-mlogloss:1.96314	validation-mlogloss:1.92400
[252]	train-mlogloss:1.96199	validation-mlogloss:1.92291
[253]	train-mlogloss:1.96091	validation-mlogloss:1.92187
[254]	train-mlogloss:1.95983	validation-mlogloss:1.92101
[255]	train-mlogloss:1.95878	validation-mlogloss:1.92012
[256]	train-mlogloss:1.95760	validation-mlogloss:1.91930
[257]	train-mlogloss:1.95656	validation-mlogloss:1.91855
[258]	train-mlogloss:1.95559	validation-mlogloss:1.91782
[259]	train-mlogloss:1.95447	validation-mlogloss:1.91684
[260]	train-mlogloss:1.95343	validation-mlogloss:1.91600
[261]	train-mlogloss:1.95242	validation-mlogloss:1.91521
[262]	train-mlogloss:1.95135	validation-mlogloss:1.91415
[263]	train-mlogloss:1.95032	validation-mlogloss:1.91308
[264]	train-mlogloss:1.94925	validation-mlogloss:1.91230
[265]	train-mlogloss:1.94825	validation-mlogloss:1.91147
[266]	train-mlogloss:1.94716	validation-mlogloss:1.91056
[267]	train-mlogloss:1.94612	validation-mlogloss:1.90967
[268]	train-mlogloss:1.94516	validation-mlogloss:1.90871
[269]	train-mlogloss:1.94410	validation-mlogloss:1.90779
[270]	train-mlogloss:1.94303	validation-mlogloss:1.90679
[271]	train-mlogloss:1.94200	validation-mlogloss:1.90588
[272]	train-mlogloss:1.94100	validation-mlogloss:1.90502
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[274]	train-mlogloss:1.93889	validation-mlogloss:1.90333
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[398]	train-mlogloss:1.84365	validation-mlogloss:1.83017
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[403]	train-mlogloss:1.84098	validation-mlogloss:1.82838
[404]	train-mlogloss:1.84043	validation-mlogloss:1.82814
[405]	train-mlogloss:1.83983	validation-mlogloss:1.82784
[406]	train-mlogloss:1.83930	validation-mlogloss:1.82741
[407]	train-mlogloss:1.83868	validation-mlogloss:1.82712
[408]	train-mlogloss:1.83827	validation-mlogloss:1.82690
[409]	train-mlogloss:1.83772	validation-mlogloss:1.82659
[410]	train-mlogloss:1.83724	validation-mlogloss:1.82632
[411]	train-mlogloss:1.83670	validation-mlogloss:1.82607
[412]	train-mlogloss:1.83612	validation-mlogloss:1.82570
[413]	train-mlogloss:1.83555	validation-mlogloss:1.82515
[414]	train-mlogloss:1.83512	validation-mlogloss:1.82498
[415]	train-mlogloss:1.83449	validation-mlogloss:1.82446
[416]	train-mlogloss:1.83401	validation-mlogloss:1.82406
[417]	train-mlogloss:1.83352	validation-mlogloss:1.82373
[418]	train-mlogloss:1.83301	validation-mlogloss:1.82339
[419]	train-mlogloss:1.83250	validation-mlogloss:1.82311
Saved model to disk.
2025-11-06 21:49:26.297159: 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 21:49:26.308582: 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 00:00:1762462166.322232 1829882 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462166.326555 1829882 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462166.336417 1829882 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462166.336432 1829882 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462166.336434 1829882 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462166.336436 1829882 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:49:26.339535: 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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[24]	train-mlogloss:2.53951	validation-mlogloss:2.52462
[25]	train-mlogloss:2.53392	validation-mlogloss:2.51836
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[34]	train-mlogloss:2.48544	validation-mlogloss:2.46460
[35]	train-mlogloss:2.48049	validation-mlogloss:2.45935
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[75]	train-mlogloss:2.30893	validation-mlogloss:2.27009
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Saved model to disk.
2025-11-06 21:49:48.303980: 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 21:49:48.315398: 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 00:00:1762462188.328610 1830251 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462188.332840 1830251 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462188.342678 1830251 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462188.342697 1830251 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462188.342698 1830251 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462188.342700 1830251 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:49:48.345860: 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:2.70036	validation-mlogloss:2.69972
[1]	train-mlogloss:2.69263	validation-mlogloss:2.69184
[2]	train-mlogloss:2.68523	validation-mlogloss:2.68418
[3]	train-mlogloss:2.67742	validation-mlogloss:2.67565
[4]	train-mlogloss:2.67022	validation-mlogloss:2.66796
[5]	train-mlogloss:2.66302	validation-mlogloss:2.66028
[6]	train-mlogloss:2.65552	validation-mlogloss:2.65193
[7]	train-mlogloss:2.64858	validation-mlogloss:2.64415
[8]	train-mlogloss:2.64169	validation-mlogloss:2.63650
[9]	train-mlogloss:2.63472	validation-mlogloss:2.62924
[10]	train-mlogloss:2.62820	validation-mlogloss:2.62239
[11]	train-mlogloss:2.62146	validation-mlogloss:2.61524
[12]	train-mlogloss:2.61511	validation-mlogloss:2.60864
[13]	train-mlogloss:2.60822	validation-mlogloss:2.60097
[14]	train-mlogloss:2.60138	validation-mlogloss:2.59342
[15]	train-mlogloss:2.59509	validation-mlogloss:2.58656
[16]	train-mlogloss:2.58841	validation-mlogloss:2.57916
[17]	train-mlogloss:2.58201	validation-mlogloss:2.57195
[18]	train-mlogloss:2.57564	validation-mlogloss:2.56469
[19]	train-mlogloss:2.56950	validation-mlogloss:2.55777
[20]	train-mlogloss:2.56343	validation-mlogloss:2.55113
[21]	train-mlogloss:2.55727	validation-mlogloss:2.54438
[22]	train-mlogloss:2.55137	validation-mlogloss:2.53830
[23]	train-mlogloss:2.54543	validation-mlogloss:2.53176
[24]	train-mlogloss:2.53979	validation-mlogloss:2.52566
[25]	train-mlogloss:2.53407	validation-mlogloss:2.51956
[26]	train-mlogloss:2.52843	validation-mlogloss:2.51333
[27]	train-mlogloss:2.52292	validation-mlogloss:2.50727
[28]	train-mlogloss:2.51745	validation-mlogloss:2.50133
[29]	train-mlogloss:2.51193	validation-mlogloss:2.49508
[30]	train-mlogloss:2.50666	validation-mlogloss:2.48938
[31]	train-mlogloss:2.50125	validation-mlogloss:2.48363
[32]	train-mlogloss:2.49571	validation-mlogloss:2.47719
[33]	train-mlogloss:2.49045	validation-mlogloss:2.47138
[34]	train-mlogloss:2.48502	validation-mlogloss:2.46537
[35]	train-mlogloss:2.47990	validation-mlogloss:2.45982
[36]	train-mlogloss:2.47501	validation-mlogloss:2.45463
[37]	train-mlogloss:2.46998	validation-mlogloss:2.44888
[38]	train-mlogloss:2.46504	validation-mlogloss:2.44343
[39]	train-mlogloss:2.45998	validation-mlogloss:2.43768
[40]	train-mlogloss:2.45480	validation-mlogloss:2.43173
[41]	train-mlogloss:2.45011	validation-mlogloss:2.42669
[42]	train-mlogloss:2.44525	validation-mlogloss:2.42128
[43]	train-mlogloss:2.44032	validation-mlogloss:2.41576
[44]	train-mlogloss:2.43574	validation-mlogloss:2.41096
[45]	train-mlogloss:2.43101	validation-mlogloss:2.40563
[46]	train-mlogloss:2.42623	validation-mlogloss:2.40025
[47]	train-mlogloss:2.42130	validation-mlogloss:2.39479
[48]	train-mlogloss:2.41678	validation-mlogloss:2.39008
[49]	train-mlogloss:2.41245	validation-mlogloss:2.38552
[50]	train-mlogloss:2.40767	validation-mlogloss:2.37996
[51]	train-mlogloss:2.40348	validation-mlogloss:2.37545
[52]	train-mlogloss:2.39896	validation-mlogloss:2.37014
[53]	train-mlogloss:2.39477	validation-mlogloss:2.36555
[54]	train-mlogloss:2.39043	validation-mlogloss:2.36069
[55]	train-mlogloss:2.38618	validation-mlogloss:2.35630
[56]	train-mlogloss:2.38216	validation-mlogloss:2.35208
[57]	train-mlogloss:2.37807	validation-mlogloss:2.34774
[58]	train-mlogloss:2.37411	validation-mlogloss:2.34346
[59]	train-mlogloss:2.36976	validation-mlogloss:2.33852
[60]	train-mlogloss:2.36547	validation-mlogloss:2.33343
[61]	train-mlogloss:2.36143	validation-mlogloss:2.32916
[62]	train-mlogloss:2.35763	validation-mlogloss:2.32533
[63]	train-mlogloss:2.35363	validation-mlogloss:2.32074
[64]	train-mlogloss:2.34958	validation-mlogloss:2.31604
[65]	train-mlogloss:2.34590	validation-mlogloss:2.31218
[66]	train-mlogloss:2.34200	validation-mlogloss:2.30799
[67]	train-mlogloss:2.33817	validation-mlogloss:2.30384
[68]	train-mlogloss:2.33462	validation-mlogloss:2.30022
[69]	train-mlogloss:2.33098	validation-mlogloss:2.29618
[70]	train-mlogloss:2.32741	validation-mlogloss:2.29252
[71]	train-mlogloss:2.32385	validation-mlogloss:2.28874
[72]	train-mlogloss:2.32020	validation-mlogloss:2.28471
[73]	train-mlogloss:2.31676	validation-mlogloss:2.28107
[74]	train-mlogloss:2.31304	validation-mlogloss:2.27682
[75]	train-mlogloss:2.30950	validation-mlogloss:2.27302
[76]	train-mlogloss:2.30593	validation-mlogloss:2.26891
[77]	train-mlogloss:2.30233	validation-mlogloss:2.26482
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[92]	train-mlogloss:2.25358	validation-mlogloss:2.21230
[93]	train-mlogloss:2.25071	validation-mlogloss:2.20925
[94]	train-mlogloss:2.24762	validation-mlogloss:2.20584
[95]	train-mlogloss:2.24463	validation-mlogloss:2.20249
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[98]	train-mlogloss:2.23566	validation-mlogloss:2.19252
[99]	train-mlogloss:2.23293	validation-mlogloss:2.18996
[100]	train-mlogloss:2.23010	validation-mlogloss:2.18698
[101]	train-mlogloss:2.22727	validation-mlogloss:2.18391
[102]	train-mlogloss:2.22420	validation-mlogloss:2.18034
[103]	train-mlogloss:2.22153	validation-mlogloss:2.17757
[104]	train-mlogloss:2.21875	validation-mlogloss:2.17469
[105]	train-mlogloss:2.21623	validation-mlogloss:2.17221
[106]	train-mlogloss:2.21354	validation-mlogloss:2.16926
[107]	train-mlogloss:2.21103	validation-mlogloss:2.16684
[108]	train-mlogloss:2.20840	validation-mlogloss:2.16400
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[110]	train-mlogloss:2.20310	validation-mlogloss:2.15844
[111]	train-mlogloss:2.20055	validation-mlogloss:2.15582
[112]	train-mlogloss:2.19818	validation-mlogloss:2.15339
[113]	train-mlogloss:2.19559	validation-mlogloss:2.15048
[114]	train-mlogloss:2.19308	validation-mlogloss:2.14782
[115]	train-mlogloss:2.19046	validation-mlogloss:2.14493
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[131]	train-mlogloss:2.15293	validation-mlogloss:2.10620
[132]	train-mlogloss:2.15065	validation-mlogloss:2.10391
[133]	train-mlogloss:2.14843	validation-mlogloss:2.10144
[134]	train-mlogloss:2.14631	validation-mlogloss:2.09910
[135]	train-mlogloss:2.14413	validation-mlogloss:2.09688
[136]	train-mlogloss:2.14204	validation-mlogloss:2.09484
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[145]	train-mlogloss:2.12318	validation-mlogloss:2.07633
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[277]	train-mlogloss:1.93542	validation-mlogloss:1.90019
[278]	train-mlogloss:1.93441	validation-mlogloss:1.89915
[279]	train-mlogloss:1.93346	validation-mlogloss:1.89840
[280]	train-mlogloss:1.93251	validation-mlogloss:1.89745
[281]	train-mlogloss:1.93156	validation-mlogloss:1.89650
[282]	train-mlogloss:1.93058	validation-mlogloss:1.89565
[283]	train-mlogloss:1.92968	validation-mlogloss:1.89499
[284]	train-mlogloss:1.92873	validation-mlogloss:1.89392
[285]	train-mlogloss:1.92783	validation-mlogloss:1.89310
[286]	train-mlogloss:1.92682	validation-mlogloss:1.89214
[287]	train-mlogloss:1.92590	validation-mlogloss:1.89127
[288]	train-mlogloss:1.92490	validation-mlogloss:1.89030
[289]	train-mlogloss:1.92393	validation-mlogloss:1.88932
[290]	train-mlogloss:1.92307	validation-mlogloss:1.88854
[291]	train-mlogloss:1.92207	validation-mlogloss:1.88778
[292]	train-mlogloss:1.92113	validation-mlogloss:1.88704
[293]	train-mlogloss:1.92017	validation-mlogloss:1.88633
[294]	train-mlogloss:1.91919	validation-mlogloss:1.88564
[295]	train-mlogloss:1.91823	validation-mlogloss:1.88471
[296]	train-mlogloss:1.91734	validation-mlogloss:1.88404
[297]	train-mlogloss:1.91646	validation-mlogloss:1.88333
[298]	train-mlogloss:1.91551	validation-mlogloss:1.88259
[299]	train-mlogloss:1.91452	validation-mlogloss:1.88182
[300]	train-mlogloss:1.91362	validation-mlogloss:1.88108
[301]	train-mlogloss:1.91271	validation-mlogloss:1.88024
[302]	train-mlogloss:1.91180	validation-mlogloss:1.87956
[303]	train-mlogloss:1.91094	validation-mlogloss:1.87876
[304]	train-mlogloss:1.91014	validation-mlogloss:1.87806
[305]	train-mlogloss:1.90925	validation-mlogloss:1.87744
[306]	train-mlogloss:1.90833	validation-mlogloss:1.87667
[307]	train-mlogloss:1.90734	validation-mlogloss:1.87591
[308]	train-mlogloss:1.90650	validation-mlogloss:1.87518
[309]	train-mlogloss:1.90565	validation-mlogloss:1.87459
[310]	train-mlogloss:1.90473	validation-mlogloss:1.87403
[311]	train-mlogloss:1.90400	validation-mlogloss:1.87329
[312]	train-mlogloss:1.90311	validation-mlogloss:1.87263
[313]	train-mlogloss:1.90226	validation-mlogloss:1.87189
[314]	train-mlogloss:1.90141	validation-mlogloss:1.87118
[315]	train-mlogloss:1.90063	validation-mlogloss:1.87068
[316]	train-mlogloss:1.89982	validation-mlogloss:1.87007
[317]	train-mlogloss:1.89890	validation-mlogloss:1.86935
[318]	train-mlogloss:1.89801	validation-mlogloss:1.86856
[319]	train-mlogloss:1.89724	validation-mlogloss:1.86781
[320]	train-mlogloss:1.89644	validation-mlogloss:1.86719
[321]	train-mlogloss:1.89565	validation-mlogloss:1.86651
[322]	train-mlogloss:1.89489	validation-mlogloss:1.86591
[323]	train-mlogloss:1.89411	validation-mlogloss:1.86525
[324]	train-mlogloss:1.89336	validation-mlogloss:1.86471
[325]	train-mlogloss:1.89251	validation-mlogloss:1.86401
[326]	train-mlogloss:1.89167	validation-mlogloss:1.86324
[327]	train-mlogloss:1.89090	validation-mlogloss:1.86265
[328]	train-mlogloss:1.89015	validation-mlogloss:1.86205
[329]	train-mlogloss:1.88937	validation-mlogloss:1.86161
[330]	train-mlogloss:1.88854	validation-mlogloss:1.86089
[331]	train-mlogloss:1.88767	validation-mlogloss:1.86031
[332]	train-mlogloss:1.88686	validation-mlogloss:1.85964
[333]	train-mlogloss:1.88605	validation-mlogloss:1.85901
[334]	train-mlogloss:1.88526	validation-mlogloss:1.85848
[335]	train-mlogloss:1.88447	validation-mlogloss:1.85791
[336]	train-mlogloss:1.88372	validation-mlogloss:1.85736
[337]	train-mlogloss:1.88297	validation-mlogloss:1.85670
[338]	train-mlogloss:1.88221	validation-mlogloss:1.85599
[339]	train-mlogloss:1.88140	validation-mlogloss:1.85521
[340]	train-mlogloss:1.88069	validation-mlogloss:1.85473
[341]	train-mlogloss:1.87999	validation-mlogloss:1.85408
[342]	train-mlogloss:1.87922	validation-mlogloss:1.85357
[343]	train-mlogloss:1.87842	validation-mlogloss:1.85313
[344]	train-mlogloss:1.87772	validation-mlogloss:1.85270
[345]	train-mlogloss:1.87701	validation-mlogloss:1.85220
[346]	train-mlogloss:1.87631	validation-mlogloss:1.85174
[347]	train-mlogloss:1.87569	validation-mlogloss:1.85123
[348]	train-mlogloss:1.87494	validation-mlogloss:1.85065
[349]	train-mlogloss:1.87426	validation-mlogloss:1.85011
[350]	train-mlogloss:1.87358	validation-mlogloss:1.84967
[351]	train-mlogloss:1.87285	validation-mlogloss:1.84906
[352]	train-mlogloss:1.87218	validation-mlogloss:1.84870
[353]	train-mlogloss:1.87148	validation-mlogloss:1.84823
[354]	train-mlogloss:1.87077	validation-mlogloss:1.84773
[355]	train-mlogloss:1.87010	validation-mlogloss:1.84724
[356]	train-mlogloss:1.86947	validation-mlogloss:1.84672
[357]	train-mlogloss:1.86876	validation-mlogloss:1.84618
[358]	train-mlogloss:1.86805	validation-mlogloss:1.84556
[359]	train-mlogloss:1.86735	validation-mlogloss:1.84520
[360]	train-mlogloss:1.86665	validation-mlogloss:1.84468
[361]	train-mlogloss:1.86595	validation-mlogloss:1.84426
[362]	train-mlogloss:1.86526	validation-mlogloss:1.84381
[363]	train-mlogloss:1.86460	validation-mlogloss:1.84333
[364]	train-mlogloss:1.86393	validation-mlogloss:1.84300
[365]	train-mlogloss:1.86325	validation-mlogloss:1.84252
[366]	train-mlogloss:1.86256	validation-mlogloss:1.84194
[367]	train-mlogloss:1.86196	validation-mlogloss:1.84163
[368]	train-mlogloss:1.86138	validation-mlogloss:1.84119
[369]	train-mlogloss:1.86071	validation-mlogloss:1.84077
[370]	train-mlogloss:1.86004	validation-mlogloss:1.84019
[371]	train-mlogloss:1.85947	validation-mlogloss:1.83970
[372]	train-mlogloss:1.85887	validation-mlogloss:1.83937
[373]	train-mlogloss:1.85824	validation-mlogloss:1.83885
[374]	train-mlogloss:1.85763	validation-mlogloss:1.83858
[375]	train-mlogloss:1.85704	validation-mlogloss:1.83817
[376]	train-mlogloss:1.85643	validation-mlogloss:1.83757
[377]	train-mlogloss:1.85588	validation-mlogloss:1.83715
[378]	train-mlogloss:1.85532	validation-mlogloss:1.83677
[379]	train-mlogloss:1.85466	validation-mlogloss:1.83633
[380]	train-mlogloss:1.85407	validation-mlogloss:1.83586
[381]	train-mlogloss:1.85345	validation-mlogloss:1.83551
[382]	train-mlogloss:1.85280	validation-mlogloss:1.83504
[383]	train-mlogloss:1.85224	validation-mlogloss:1.83465
[384]	train-mlogloss:1.85165	validation-mlogloss:1.83420
[385]	train-mlogloss:1.85106	validation-mlogloss:1.83353
[386]	train-mlogloss:1.85041	validation-mlogloss:1.83330
[387]	train-mlogloss:1.84980	validation-mlogloss:1.83293
[388]	train-mlogloss:1.84916	validation-mlogloss:1.83244
[389]	train-mlogloss:1.84857	validation-mlogloss:1.83209
[390]	train-mlogloss:1.84795	validation-mlogloss:1.83170
[391]	train-mlogloss:1.84735	validation-mlogloss:1.83138
[392]	train-mlogloss:1.84683	validation-mlogloss:1.83081
[393]	train-mlogloss:1.84624	validation-mlogloss:1.83050
[394]	train-mlogloss:1.84565	validation-mlogloss:1.83007
[395]	train-mlogloss:1.84508	validation-mlogloss:1.82968
[396]	train-mlogloss:1.84441	validation-mlogloss:1.82924
[397]	train-mlogloss:1.84393	validation-mlogloss:1.82872
[398]	train-mlogloss:1.84335	validation-mlogloss:1.82829
[399]	train-mlogloss:1.84284	validation-mlogloss:1.82797
[400]	train-mlogloss:1.84227	validation-mlogloss:1.82747
[401]	train-mlogloss:1.84165	validation-mlogloss:1.82707
[402]	train-mlogloss:1.84116	validation-mlogloss:1.82679
[403]	train-mlogloss:1.84070	validation-mlogloss:1.82639
[404]	train-mlogloss:1.84016	validation-mlogloss:1.82611
[405]	train-mlogloss:1.83950	validation-mlogloss:1.82572
[406]	train-mlogloss:1.83894	validation-mlogloss:1.82531
[407]	train-mlogloss:1.83846	validation-mlogloss:1.82488
[408]	train-mlogloss:1.83795	validation-mlogloss:1.82453
[409]	train-mlogloss:1.83743	validation-mlogloss:1.82414
[410]	train-mlogloss:1.83687	validation-mlogloss:1.82388
[411]	train-mlogloss:1.83646	validation-mlogloss:1.82357
[412]	train-mlogloss:1.83590	validation-mlogloss:1.82328
[413]	train-mlogloss:1.83535	validation-mlogloss:1.82285
[414]	train-mlogloss:1.83480	validation-mlogloss:1.82243
[415]	train-mlogloss:1.83436	validation-mlogloss:1.82209
[416]	train-mlogloss:1.83392	validation-mlogloss:1.82197
[417]	train-mlogloss:1.83341	validation-mlogloss:1.82170
[418]	train-mlogloss:1.83292	validation-mlogloss:1.82153
[419]	train-mlogloss:1.83237	validation-mlogloss:1.82113
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.4 [%]
Global accuracy score (test) = 44.36 [%]
Global F1 score (train) = 43.92 [%]
Global F1 score (test) = 43.59 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.47      0.46       184
       CAMINAR USUAL SPEED       0.35      0.18      0.24       184
            CAMINAR ZIGZAG       0.32      0.54      0.40       184
          DE PIE BARRIENDO       0.69      0.41      0.51       184
   DE PIE DOBLANDO TOALLAS       0.45      0.44      0.45       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.38       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.64      0.58      0.61       184
           SENTADO LEYENDO       0.46      0.38      0.42       184
         SENTADO USANDO PC       0.26      0.12      0.17       184
      SENTADO VIENDO LA TV       0.26      0.18      0.21       184
   SUBIR Y BAJAR ESCALERAS       0.63      0.56      0.59       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.44      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 16: 44.36 [%]
F1-score capturado en la ejecución 16: 43.59 [%]

=== EJECUCIÓN 17 ===

--- TRAIN (ejecución 17) ---

--- TEST (ejecución 17) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.23 [%]
Global accuracy score (test) = 44.39 [%]
Global F1 score (train) = 43.78 [%]
Global F1 score (test) = 43.67 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.73      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.47      0.45       184
       CAMINAR USUAL SPEED       0.37      0.19      0.25       184
            CAMINAR ZIGZAG       0.31      0.54      0.40       184
          DE PIE BARRIENDO       0.72      0.41      0.52       184
   DE PIE DOBLANDO TOALLAS       0.45      0.43      0.44       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.39       184
          DE PIE USANDO PC       0.20      0.31      0.24       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.66      0.58      0.62       184
           SENTADO LEYENDO       0.45      0.38      0.41       184
         SENTADO USANDO PC       0.29      0.15      0.20       184
      SENTADO VIENDO LA TV       0.24      0.15      0.18       184
   SUBIR Y BAJAR ESCALERAS       0.66      0.56      0.61       184
                    TROTAR       0.66      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.46      0.44      0.44      2737
              weighted avg       0.46      0.44      0.44      2737


Accuracy capturado en la ejecución 17: 44.39 [%]
F1-score capturado en la ejecución 17: 43.67 [%]

=== EJECUCIÓN 18 ===

--- TRAIN (ejecución 18) ---

--- TEST (ejecución 18) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.3 [%]
Global accuracy score (test) = 44.43 [%]
Global F1 score (train) = 43.82 [%]
Global F1 score (test) = 43.74 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.71      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.46      0.45       184
       CAMINAR USUAL SPEED       0.34      0.17      0.23       184
            CAMINAR ZIGZAG       0.31      0.53      0.39       184
          DE PIE BARRIENDO       0.72      0.42      0.53       184
   DE PIE DOBLANDO TOALLAS       0.46      0.45      0.46       184
    DE PIE MOVIENDO LIBROS       0.38      0.40      0.39       184
          DE PIE USANDO PC       0.21      0.33      0.26       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.64      0.57      0.61       184
           SENTADO LEYENDO       0.46      0.39      0.42       184
         SENTADO USANDO PC       0.27      0.14      0.19       184
      SENTADO VIENDO LA TV       0.26      0.16      0.20       184
   SUBIR Y BAJAR ESCALERAS       0.63      0.55      0.59       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.46      0.45      0.44      2737
              weighted avg       0.46      0.44      0.44      2737


Accuracy capturado en la ejecución 18: 44.43 [%]
F1-score capturado en la ejecución 18: 43.74 [%]

=== EJECUCIÓN 19 ===

--- TRAIN (ejecución 19) ---

--- TEST (ejecución 19) ---
2025-11-06 21:50:10.179237: 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 21:50:10.190468: 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 00:00:1762462210.204134 1830624 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462210.208433 1830624 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462210.218417 1830624 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462210.218435 1830624 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462210.218436 1830624 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462210.218445 1830624 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:50:10.221578: 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:2.70033	validation-mlogloss:2.69976
[1]	train-mlogloss:2.69307	validation-mlogloss:2.69208
[2]	train-mlogloss:2.68557	validation-mlogloss:2.68392
[3]	train-mlogloss:2.67797	validation-mlogloss:2.67599
[4]	train-mlogloss:2.67077	validation-mlogloss:2.66846
[5]	train-mlogloss:2.66365	validation-mlogloss:2.66084
[6]	train-mlogloss:2.65653	validation-mlogloss:2.65302
[7]	train-mlogloss:2.64914	validation-mlogloss:2.64462
[8]	train-mlogloss:2.64255	validation-mlogloss:2.63810
[9]	train-mlogloss:2.63585	validation-mlogloss:2.63079
[10]	train-mlogloss:2.62937	validation-mlogloss:2.62410
[11]	train-mlogloss:2.62224	validation-mlogloss:2.61650
[12]	train-mlogloss:2.61576	validation-mlogloss:2.60950
[13]	train-mlogloss:2.60908	validation-mlogloss:2.60207
[14]	train-mlogloss:2.60247	validation-mlogloss:2.59477
[15]	train-mlogloss:2.59592	validation-mlogloss:2.58781
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[389]	train-mlogloss:1.84817	validation-mlogloss:1.83238
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[393]	train-mlogloss:1.84603	validation-mlogloss:1.83112
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[395]	train-mlogloss:1.84490	validation-mlogloss:1.83032
[396]	train-mlogloss:1.84431	validation-mlogloss:1.83007
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[398]	train-mlogloss:1.84320	validation-mlogloss:1.82941
[399]	train-mlogloss:1.84254	validation-mlogloss:1.82903
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[401]	train-mlogloss:1.84149	validation-mlogloss:1.82838
[402]	train-mlogloss:1.84086	validation-mlogloss:1.82801
[403]	train-mlogloss:1.84027	validation-mlogloss:1.82766
[404]	train-mlogloss:1.83955	validation-mlogloss:1.82727
[405]	train-mlogloss:1.83902	validation-mlogloss:1.82687
[406]	train-mlogloss:1.83843	validation-mlogloss:1.82646
[407]	train-mlogloss:1.83793	validation-mlogloss:1.82609
[408]	train-mlogloss:1.83738	validation-mlogloss:1.82569
[409]	train-mlogloss:1.83691	validation-mlogloss:1.82531
[410]	train-mlogloss:1.83634	validation-mlogloss:1.82484
[411]	train-mlogloss:1.83584	validation-mlogloss:1.82438
[412]	train-mlogloss:1.83527	validation-mlogloss:1.82394
[413]	train-mlogloss:1.83471	validation-mlogloss:1.82354
[414]	train-mlogloss:1.83428	validation-mlogloss:1.82326
[415]	train-mlogloss:1.83377	validation-mlogloss:1.82288
[416]	train-mlogloss:1.83321	validation-mlogloss:1.82253
[417]	train-mlogloss:1.83266	validation-mlogloss:1.82204
[418]	train-mlogloss:1.83222	validation-mlogloss:1.82167
[419]	train-mlogloss:1.83170	validation-mlogloss:1.82133
Saved model to disk.
2025-11-06 21:50:32.342511: 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 21:50:32.353892: 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 00:00:1762462232.367181 1831019 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462232.371103 1831019 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462232.380986 1831019 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462232.381004 1831019 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462232.381006 1831019 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462232.381008 1831019 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:50:32.383953: 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:2.68542	validation-mlogloss:2.68407
[3]	train-mlogloss:2.67792	validation-mlogloss:2.67622
[4]	train-mlogloss:2.67089	validation-mlogloss:2.66864
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[6]	train-mlogloss:2.65683	validation-mlogloss:2.65351
[7]	train-mlogloss:2.64980	validation-mlogloss:2.64592
[8]	train-mlogloss:2.64255	validation-mlogloss:2.63795
[9]	train-mlogloss:2.63557	validation-mlogloss:2.63056
[10]	train-mlogloss:2.62861	validation-mlogloss:2.62278
[11]	train-mlogloss:2.62185	validation-mlogloss:2.61523
[12]	train-mlogloss:2.61478	validation-mlogloss:2.60756
[13]	train-mlogloss:2.60806	validation-mlogloss:2.60027
[14]	train-mlogloss:2.60151	validation-mlogloss:2.59314
[15]	train-mlogloss:2.59486	validation-mlogloss:2.58581
[16]	train-mlogloss:2.58855	validation-mlogloss:2.57898
[17]	train-mlogloss:2.58233	validation-mlogloss:2.57249
[18]	train-mlogloss:2.57618	validation-mlogloss:2.56553
[19]	train-mlogloss:2.57008	validation-mlogloss:2.55889
[20]	train-mlogloss:2.56385	validation-mlogloss:2.55191
[21]	train-mlogloss:2.55774	validation-mlogloss:2.54510
[22]	train-mlogloss:2.55183	validation-mlogloss:2.53861
[23]	train-mlogloss:2.54614	validation-mlogloss:2.53253
[24]	train-mlogloss:2.54036	validation-mlogloss:2.52638
[25]	train-mlogloss:2.53443	validation-mlogloss:2.51960
[26]	train-mlogloss:2.52844	validation-mlogloss:2.51292
[27]	train-mlogloss:2.52254	validation-mlogloss:2.50608
[28]	train-mlogloss:2.51694	validation-mlogloss:2.50022
[29]	train-mlogloss:2.51148	validation-mlogloss:2.49410
[30]	train-mlogloss:2.50594	validation-mlogloss:2.48803
[31]	train-mlogloss:2.50040	validation-mlogloss:2.48175
[32]	train-mlogloss:2.49523	validation-mlogloss:2.47618
[33]	train-mlogloss:2.49005	validation-mlogloss:2.47046
[34]	train-mlogloss:2.48492	validation-mlogloss:2.46486
[35]	train-mlogloss:2.47989	validation-mlogloss:2.45926
[36]	train-mlogloss:2.47487	validation-mlogloss:2.45388
[37]	train-mlogloss:2.47005	validation-mlogloss:2.44869
[38]	train-mlogloss:2.46496	validation-mlogloss:2.44307
[39]	train-mlogloss:2.45965	validation-mlogloss:2.43684
[40]	train-mlogloss:2.45470	validation-mlogloss:2.43126
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[42]	train-mlogloss:2.44535	validation-mlogloss:2.42141
[43]	train-mlogloss:2.44064	validation-mlogloss:2.41618
[44]	train-mlogloss:2.43593	validation-mlogloss:2.41089
[45]	train-mlogloss:2.43115	validation-mlogloss:2.40585
[46]	train-mlogloss:2.42670	validation-mlogloss:2.40090
[47]	train-mlogloss:2.42212	validation-mlogloss:2.39581
[48]	train-mlogloss:2.41754	validation-mlogloss:2.39065
[49]	train-mlogloss:2.41278	validation-mlogloss:2.38521
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[51]	train-mlogloss:2.40404	validation-mlogloss:2.37551
[52]	train-mlogloss:2.39967	validation-mlogloss:2.37072
[53]	train-mlogloss:2.39538	validation-mlogloss:2.36591
[54]	train-mlogloss:2.39113	validation-mlogloss:2.36138
[55]	train-mlogloss:2.38688	validation-mlogloss:2.35679
[56]	train-mlogloss:2.38254	validation-mlogloss:2.35195
[57]	train-mlogloss:2.37830	validation-mlogloss:2.34722
[58]	train-mlogloss:2.37390	validation-mlogloss:2.34220
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[60]	train-mlogloss:2.36599	validation-mlogloss:2.33355
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[62]	train-mlogloss:2.35805	validation-mlogloss:2.32485
[63]	train-mlogloss:2.35385	validation-mlogloss:2.32042
[64]	train-mlogloss:2.34992	validation-mlogloss:2.31607
[65]	train-mlogloss:2.34614	validation-mlogloss:2.31199
[66]	train-mlogloss:2.34228	validation-mlogloss:2.30787
[67]	train-mlogloss:2.33835	validation-mlogloss:2.30364
[68]	train-mlogloss:2.33447	validation-mlogloss:2.29934
[69]	train-mlogloss:2.33082	validation-mlogloss:2.29553
[70]	train-mlogloss:2.32745	validation-mlogloss:2.29193
[71]	train-mlogloss:2.32394	validation-mlogloss:2.28809
[72]	train-mlogloss:2.32013	validation-mlogloss:2.28371
[73]	train-mlogloss:2.31647	validation-mlogloss:2.27961
[74]	train-mlogloss:2.31283	validation-mlogloss:2.27557
[75]	train-mlogloss:2.30929	validation-mlogloss:2.27170
[76]	train-mlogloss:2.30584	validation-mlogloss:2.26807
[77]	train-mlogloss:2.30215	validation-mlogloss:2.26375
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[104]	train-mlogloss:2.21929	validation-mlogloss:2.17585
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[111]	train-mlogloss:2.20057	validation-mlogloss:2.15581
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[113]	train-mlogloss:2.19552	validation-mlogloss:2.15021
[114]	train-mlogloss:2.19287	validation-mlogloss:2.14705
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[133]	train-mlogloss:2.14777	validation-mlogloss:2.10011
[134]	train-mlogloss:2.14562	validation-mlogloss:2.09797
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[136]	train-mlogloss:2.14134	validation-mlogloss:2.09356
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[149]	train-mlogloss:2.11471	validation-mlogloss:2.06714
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[152]	train-mlogloss:2.10867	validation-mlogloss:2.06094
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[155]	train-mlogloss:2.10293	validation-mlogloss:2.05515
[156]	train-mlogloss:2.10096	validation-mlogloss:2.05321
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[158]	train-mlogloss:2.09703	validation-mlogloss:2.04898
[159]	train-mlogloss:2.09523	validation-mlogloss:2.04710
[160]	train-mlogloss:2.09341	validation-mlogloss:2.04525
[161]	train-mlogloss:2.09151	validation-mlogloss:2.04340
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[164]	train-mlogloss:2.08600	validation-mlogloss:2.03786
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[272]	train-mlogloss:1.94085	validation-mlogloss:1.90369
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[372]	train-mlogloss:1.85864	validation-mlogloss:1.83888
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[389]	train-mlogloss:1.84838	validation-mlogloss:1.83201
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[391]	train-mlogloss:1.84723	validation-mlogloss:1.83102
[392]	train-mlogloss:1.84668	validation-mlogloss:1.83074
[393]	train-mlogloss:1.84606	validation-mlogloss:1.83034
[394]	train-mlogloss:1.84552	validation-mlogloss:1.82995
[395]	train-mlogloss:1.84498	validation-mlogloss:1.82947
[396]	train-mlogloss:1.84438	validation-mlogloss:1.82921
[397]	train-mlogloss:1.84378	validation-mlogloss:1.82875
[398]	train-mlogloss:1.84323	validation-mlogloss:1.82835
[399]	train-mlogloss:1.84268	validation-mlogloss:1.82805
[400]	train-mlogloss:1.84219	validation-mlogloss:1.82775
[401]	train-mlogloss:1.84169	validation-mlogloss:1.82754
[402]	train-mlogloss:1.84119	validation-mlogloss:1.82723
[403]	train-mlogloss:1.84059	validation-mlogloss:1.82674
[404]	train-mlogloss:1.83994	validation-mlogloss:1.82635
[405]	train-mlogloss:1.83942	validation-mlogloss:1.82610
[406]	train-mlogloss:1.83895	validation-mlogloss:1.82575
[407]	train-mlogloss:1.83845	validation-mlogloss:1.82540
[408]	train-mlogloss:1.83790	validation-mlogloss:1.82523
[409]	train-mlogloss:1.83735	validation-mlogloss:1.82476
[410]	train-mlogloss:1.83690	validation-mlogloss:1.82445
[411]	train-mlogloss:1.83639	validation-mlogloss:1.82414
[412]	train-mlogloss:1.83585	validation-mlogloss:1.82371
[413]	train-mlogloss:1.83532	validation-mlogloss:1.82349
[414]	train-mlogloss:1.83488	validation-mlogloss:1.82324
[415]	train-mlogloss:1.83445	validation-mlogloss:1.82304
[416]	train-mlogloss:1.83391	validation-mlogloss:1.82261
[417]	train-mlogloss:1.83342	validation-mlogloss:1.82225
[418]	train-mlogloss:1.83294	validation-mlogloss:1.82215
[419]	train-mlogloss:1.83255	validation-mlogloss:1.82194
Saved model to disk.
2025-11-06 21:50:54.150253: 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 21:50:54.161403: 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 00:00:1762462254.174342 1831382 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462254.178432 1831382 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462254.188163 1831382 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462254.188180 1831382 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462254.188182 1831382 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462254.188183 1831382 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:50:54.191284: 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:2.70049	validation-mlogloss:2.70025
[1]	train-mlogloss:2.69315	validation-mlogloss:2.69242
[2]	train-mlogloss:2.68568	validation-mlogloss:2.68412
[3]	train-mlogloss:2.67836	validation-mlogloss:2.67627
[4]	train-mlogloss:2.67119	validation-mlogloss:2.66867
[5]	train-mlogloss:2.66406	validation-mlogloss:2.66103
[6]	train-mlogloss:2.65687	validation-mlogloss:2.65327
[7]	train-mlogloss:2.64988	validation-mlogloss:2.64559
[8]	train-mlogloss:2.64314	validation-mlogloss:2.63859
[9]	train-mlogloss:2.63621	validation-mlogloss:2.63125
[10]	train-mlogloss:2.62913	validation-mlogloss:2.62351
[11]	train-mlogloss:2.62244	validation-mlogloss:2.61610
[12]	train-mlogloss:2.61550	validation-mlogloss:2.60841
[13]	train-mlogloss:2.60865	validation-mlogloss:2.60088
[14]	train-mlogloss:2.60203	validation-mlogloss:2.59359
[15]	train-mlogloss:2.59538	validation-mlogloss:2.58596
[16]	train-mlogloss:2.58897	validation-mlogloss:2.57874
[17]	train-mlogloss:2.58277	validation-mlogloss:2.57242
[18]	train-mlogloss:2.57641	validation-mlogloss:2.56538
[19]	train-mlogloss:2.57015	validation-mlogloss:2.55838
[20]	train-mlogloss:2.56428	validation-mlogloss:2.55205
[21]	train-mlogloss:2.55827	validation-mlogloss:2.54544
[22]	train-mlogloss:2.55196	validation-mlogloss:2.53814
[23]	train-mlogloss:2.54613	validation-mlogloss:2.53159
[24]	train-mlogloss:2.54025	validation-mlogloss:2.52507
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[325]	train-mlogloss:1.89284	validation-mlogloss:1.86533
[326]	train-mlogloss:1.89194	validation-mlogloss:1.86452
[327]	train-mlogloss:1.89110	validation-mlogloss:1.86396
[328]	train-mlogloss:1.89038	validation-mlogloss:1.86333
[329]	train-mlogloss:1.88954	validation-mlogloss:1.86257
[330]	train-mlogloss:1.88874	validation-mlogloss:1.86191
[331]	train-mlogloss:1.88800	validation-mlogloss:1.86139
[332]	train-mlogloss:1.88720	validation-mlogloss:1.86074
[333]	train-mlogloss:1.88643	validation-mlogloss:1.86006
[334]	train-mlogloss:1.88567	validation-mlogloss:1.85953
[335]	train-mlogloss:1.88484	validation-mlogloss:1.85892
[336]	train-mlogloss:1.88409	validation-mlogloss:1.85837
[337]	train-mlogloss:1.88330	validation-mlogloss:1.85791
[338]	train-mlogloss:1.88248	validation-mlogloss:1.85737
[339]	train-mlogloss:1.88176	validation-mlogloss:1.85692
[340]	train-mlogloss:1.88102	validation-mlogloss:1.85650
[341]	train-mlogloss:1.88028	validation-mlogloss:1.85584
[342]	train-mlogloss:1.87954	validation-mlogloss:1.85524
[343]	train-mlogloss:1.87882	validation-mlogloss:1.85483
[344]	train-mlogloss:1.87810	validation-mlogloss:1.85418
[345]	train-mlogloss:1.87741	validation-mlogloss:1.85377
[346]	train-mlogloss:1.87669	validation-mlogloss:1.85332
[347]	train-mlogloss:1.87598	validation-mlogloss:1.85267
[348]	train-mlogloss:1.87518	validation-mlogloss:1.85202
[349]	train-mlogloss:1.87449	validation-mlogloss:1.85149
[350]	train-mlogloss:1.87381	validation-mlogloss:1.85097
[351]	train-mlogloss:1.87314	validation-mlogloss:1.85048
[352]	train-mlogloss:1.87237	validation-mlogloss:1.84995
[353]	train-mlogloss:1.87166	validation-mlogloss:1.84939
[354]	train-mlogloss:1.87092	validation-mlogloss:1.84895
[355]	train-mlogloss:1.87025	validation-mlogloss:1.84852
[356]	train-mlogloss:1.86946	validation-mlogloss:1.84795
[357]	train-mlogloss:1.86882	validation-mlogloss:1.84752
[358]	train-mlogloss:1.86815	validation-mlogloss:1.84706
[359]	train-mlogloss:1.86753	validation-mlogloss:1.84667
[360]	train-mlogloss:1.86678	validation-mlogloss:1.84604
[361]	train-mlogloss:1.86611	validation-mlogloss:1.84550
[362]	train-mlogloss:1.86554	validation-mlogloss:1.84493
[363]	train-mlogloss:1.86492	validation-mlogloss:1.84446
[364]	train-mlogloss:1.86425	validation-mlogloss:1.84396
[365]	train-mlogloss:1.86358	validation-mlogloss:1.84343
[366]	train-mlogloss:1.86292	validation-mlogloss:1.84290
[367]	train-mlogloss:1.86232	validation-mlogloss:1.84247
[368]	train-mlogloss:1.86173	validation-mlogloss:1.84208
[369]	train-mlogloss:1.86114	validation-mlogloss:1.84163
[370]	train-mlogloss:1.86046	validation-mlogloss:1.84113
[371]	train-mlogloss:1.85984	validation-mlogloss:1.84087
[372]	train-mlogloss:1.85919	validation-mlogloss:1.84042
[373]	train-mlogloss:1.85853	validation-mlogloss:1.84003
[374]	train-mlogloss:1.85792	validation-mlogloss:1.83950
[375]	train-mlogloss:1.85723	validation-mlogloss:1.83886
[376]	train-mlogloss:1.85659	validation-mlogloss:1.83850
[377]	train-mlogloss:1.85600	validation-mlogloss:1.83797
[378]	train-mlogloss:1.85529	validation-mlogloss:1.83747
[379]	train-mlogloss:1.85464	validation-mlogloss:1.83709
[380]	train-mlogloss:1.85408	validation-mlogloss:1.83666
[381]	train-mlogloss:1.85337	validation-mlogloss:1.83613
[382]	train-mlogloss:1.85274	validation-mlogloss:1.83570
[383]	train-mlogloss:1.85207	validation-mlogloss:1.83518
[384]	train-mlogloss:1.85144	validation-mlogloss:1.83474
[385]	train-mlogloss:1.85095	validation-mlogloss:1.83457
[386]	train-mlogloss:1.85027	validation-mlogloss:1.83407
[387]	train-mlogloss:1.84975	validation-mlogloss:1.83367
[388]	train-mlogloss:1.84909	validation-mlogloss:1.83329
[389]	train-mlogloss:1.84846	validation-mlogloss:1.83282
[390]	train-mlogloss:1.84786	validation-mlogloss:1.83243
[391]	train-mlogloss:1.84733	validation-mlogloss:1.83202
[392]	train-mlogloss:1.84679	validation-mlogloss:1.83154
[393]	train-mlogloss:1.84621	validation-mlogloss:1.83112
[394]	train-mlogloss:1.84561	validation-mlogloss:1.83084
[395]	train-mlogloss:1.84501	validation-mlogloss:1.83034
[396]	train-mlogloss:1.84447	validation-mlogloss:1.83005
[397]	train-mlogloss:1.84397	validation-mlogloss:1.82984
[398]	train-mlogloss:1.84350	validation-mlogloss:1.82968
[399]	train-mlogloss:1.84298	validation-mlogloss:1.82935
[400]	train-mlogloss:1.84242	validation-mlogloss:1.82891
[401]	train-mlogloss:1.84187	validation-mlogloss:1.82838
[402]	train-mlogloss:1.84129	validation-mlogloss:1.82783
[403]	train-mlogloss:1.84077	validation-mlogloss:1.82744
[404]	train-mlogloss:1.84013	validation-mlogloss:1.82701
[405]	train-mlogloss:1.83963	validation-mlogloss:1.82671
[406]	train-mlogloss:1.83905	validation-mlogloss:1.82625
[407]	train-mlogloss:1.83860	validation-mlogloss:1.82597
[408]	train-mlogloss:1.83812	validation-mlogloss:1.82556
[409]	train-mlogloss:1.83754	validation-mlogloss:1.82512
[410]	train-mlogloss:1.83699	validation-mlogloss:1.82465
[411]	train-mlogloss:1.83647	validation-mlogloss:1.82436
[412]	train-mlogloss:1.83602	validation-mlogloss:1.82408
[413]	train-mlogloss:1.83555	validation-mlogloss:1.82369
[414]	train-mlogloss:1.83508	validation-mlogloss:1.82341
[415]	train-mlogloss:1.83456	validation-mlogloss:1.82297
[416]	train-mlogloss:1.83397	validation-mlogloss:1.82253
[417]	train-mlogloss:1.83336	validation-mlogloss:1.82212
[418]	train-mlogloss:1.83292	validation-mlogloss:1.82171
[419]	train-mlogloss:1.83236	validation-mlogloss:1.82134
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.25 [%]
Global accuracy score (test) = 44.14 [%]
Global F1 score (train) = 43.75 [%]
Global F1 score (test) = 43.32 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.49      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.42      0.45      0.43       184
       CAMINAR USUAL SPEED       0.33      0.16      0.22       184
            CAMINAR ZIGZAG       0.32      0.54      0.40       184
          DE PIE BARRIENDO       0.71      0.40      0.51       184
   DE PIE DOBLANDO TOALLAS       0.45      0.45      0.45       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.38       184
          DE PIE USANDO PC       0.20      0.31      0.24       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.66      0.58      0.62       184
           SENTADO LEYENDO       0.47      0.41      0.44       184
         SENTADO USANDO PC       0.29      0.14      0.19       184
      SENTADO VIENDO LA TV       0.25      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.61      0.56      0.58       184
                    TROTAR       0.66      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 19: 44.14 [%]
F1-score capturado en la ejecución 19: 43.32 [%]

=== EJECUCIÓN 20 ===

--- TRAIN (ejecución 20) ---

--- TEST (ejecución 20) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.28 [%]
Global accuracy score (test) = 44.5 [%]
Global F1 score (train) = 43.83 [%]
Global F1 score (test) = 43.77 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.71      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.47      0.45       184
       CAMINAR USUAL SPEED       0.34      0.18      0.23       184
            CAMINAR ZIGZAG       0.32      0.53      0.40       184
          DE PIE BARRIENDO       0.71      0.40      0.51       184
   DE PIE DOBLANDO TOALLAS       0.45      0.43      0.44       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.39       184
          DE PIE USANDO PC       0.21      0.33      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.57      0.61       184
           SENTADO LEYENDO       0.48      0.41      0.45       184
         SENTADO USANDO PC       0.29      0.15      0.20       184
      SENTADO VIENDO LA TV       0.27      0.17      0.21       184
   SUBIR Y BAJAR ESCALERAS       0.62      0.56      0.59       184
                    TROTAR       0.65      0.55      0.60       161

                  accuracy                           0.45      2737
                 macro avg       0.46      0.45      0.44      2737
              weighted avg       0.46      0.45      0.44      2737


Accuracy capturado en la ejecución 20: 44.5 [%]
F1-score capturado en la ejecución 20: 43.77 [%]

=== EJECUCIÓN 21 ===

--- TRAIN (ejecución 21) ---

--- TEST (ejecución 21) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.31 [%]
Global accuracy score (test) = 44.25 [%]
Global F1 score (train) = 43.8 [%]
Global F1 score (test) = 43.44 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.49      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.46      0.45       184
       CAMINAR USUAL SPEED       0.33      0.16      0.22       184
            CAMINAR ZIGZAG       0.31      0.53      0.39       184
          DE PIE BARRIENDO       0.74      0.40      0.52       184
   DE PIE DOBLANDO TOALLAS       0.44      0.45      0.45       184
    DE PIE MOVIENDO LIBROS       0.40      0.40      0.40       184
          DE PIE USANDO PC       0.20      0.33      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.58      0.61       184
           SENTADO LEYENDO       0.47      0.40      0.43       184
         SENTADO USANDO PC       0.25      0.12      0.17       184
      SENTADO VIENDO LA TV       0.25      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.63      0.56      0.59       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 21: 44.25 [%]
F1-score capturado en la ejecución 21: 43.44 [%]

=== EJECUCIÓN 22 ===

--- TRAIN (ejecución 22) ---

--- TEST (ejecución 22) ---
2025-11-06 21:51:16.060061: 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 21:51:16.071482: 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 00:00:1762462276.084635 1831750 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462276.088551 1831750 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462276.098736 1831750 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462276.098756 1831750 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462276.098757 1831750 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462276.098758 1831750 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:51:16.101863: 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:2.70060	validation-mlogloss:2.70034
[1]	train-mlogloss:2.69332	validation-mlogloss:2.69274
[2]	train-mlogloss:2.68564	validation-mlogloss:2.68473
[3]	train-mlogloss:2.67812	validation-mlogloss:2.67678
[4]	train-mlogloss:2.67067	validation-mlogloss:2.66856
[5]	train-mlogloss:2.66346	validation-mlogloss:2.66085
[6]	train-mlogloss:2.65595	validation-mlogloss:2.65251
[7]	train-mlogloss:2.64894	validation-mlogloss:2.64499
[8]	train-mlogloss:2.64168	validation-mlogloss:2.63706
[9]	train-mlogloss:2.63483	validation-mlogloss:2.62963
[10]	train-mlogloss:2.62816	validation-mlogloss:2.62209
[11]	train-mlogloss:2.62135	validation-mlogloss:2.61483
[12]	train-mlogloss:2.61453	validation-mlogloss:2.60726
[13]	train-mlogloss:2.60778	validation-mlogloss:2.60016
[14]	train-mlogloss:2.60149	validation-mlogloss:2.59335
[15]	train-mlogloss:2.59481	validation-mlogloss:2.58575
[16]	train-mlogloss:2.58826	validation-mlogloss:2.57834
[17]	train-mlogloss:2.58205	validation-mlogloss:2.57177
[18]	train-mlogloss:2.57573	validation-mlogloss:2.56450
[19]	train-mlogloss:2.56931	validation-mlogloss:2.55744
[20]	train-mlogloss:2.56337	validation-mlogloss:2.55103
[21]	train-mlogloss:2.55718	validation-mlogloss:2.54421
[22]	train-mlogloss:2.55136	validation-mlogloss:2.53795
[23]	train-mlogloss:2.54559	validation-mlogloss:2.53178
[24]	train-mlogloss:2.53976	validation-mlogloss:2.52552
[25]	train-mlogloss:2.53398	validation-mlogloss:2.51912
[26]	train-mlogloss:2.52807	validation-mlogloss:2.51250
[27]	train-mlogloss:2.52209	validation-mlogloss:2.50586
[28]	train-mlogloss:2.51629	validation-mlogloss:2.49932
[29]	train-mlogloss:2.51092	validation-mlogloss:2.49358
[30]	train-mlogloss:2.50518	validation-mlogloss:2.48718
[31]	train-mlogloss:2.49998	validation-mlogloss:2.48167
[32]	train-mlogloss:2.49467	validation-mlogloss:2.47600
[33]	train-mlogloss:2.48952	validation-mlogloss:2.47022
[34]	train-mlogloss:2.48463	validation-mlogloss:2.46495
[35]	train-mlogloss:2.47945	validation-mlogloss:2.45922
[36]	train-mlogloss:2.47435	validation-mlogloss:2.45354
[37]	train-mlogloss:2.46924	validation-mlogloss:2.44814
[38]	train-mlogloss:2.46424	validation-mlogloss:2.44259
[39]	train-mlogloss:2.45939	validation-mlogloss:2.43725
[40]	train-mlogloss:2.45455	validation-mlogloss:2.43192
[41]	train-mlogloss:2.44956	validation-mlogloss:2.42667
[42]	train-mlogloss:2.44481	validation-mlogloss:2.42154
[43]	train-mlogloss:2.44013	validation-mlogloss:2.41661
[44]	train-mlogloss:2.43556	validation-mlogloss:2.41155
[45]	train-mlogloss:2.43093	validation-mlogloss:2.40657
[46]	train-mlogloss:2.42631	validation-mlogloss:2.40150
[47]	train-mlogloss:2.42184	validation-mlogloss:2.39672
[48]	train-mlogloss:2.41741	validation-mlogloss:2.39178
[49]	train-mlogloss:2.41279	validation-mlogloss:2.38643
[50]	train-mlogloss:2.40838	validation-mlogloss:2.38181
[51]	train-mlogloss:2.40396	validation-mlogloss:2.37699
[52]	train-mlogloss:2.39961	validation-mlogloss:2.37214
[53]	train-mlogloss:2.39517	validation-mlogloss:2.36724
[54]	train-mlogloss:2.39121	validation-mlogloss:2.36322
[55]	train-mlogloss:2.38687	validation-mlogloss:2.35817
[56]	train-mlogloss:2.38263	validation-mlogloss:2.35336
[57]	train-mlogloss:2.37843	validation-mlogloss:2.34868
[58]	train-mlogloss:2.37429	validation-mlogloss:2.34409
[59]	train-mlogloss:2.37002	validation-mlogloss:2.33927
[60]	train-mlogloss:2.36613	validation-mlogloss:2.33509
[61]	train-mlogloss:2.36215	validation-mlogloss:2.33080
[62]	train-mlogloss:2.35827	validation-mlogloss:2.32679
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[363]	train-mlogloss:1.86375	validation-mlogloss:1.84301
[364]	train-mlogloss:1.86307	validation-mlogloss:1.84249
[365]	train-mlogloss:1.86237	validation-mlogloss:1.84202
[366]	train-mlogloss:1.86171	validation-mlogloss:1.84158
[367]	train-mlogloss:1.86105	validation-mlogloss:1.84116
[368]	train-mlogloss:1.86040	validation-mlogloss:1.84074
[369]	train-mlogloss:1.85969	validation-mlogloss:1.84014
[370]	train-mlogloss:1.85903	validation-mlogloss:1.83995
[371]	train-mlogloss:1.85834	validation-mlogloss:1.83961
[372]	train-mlogloss:1.85770	validation-mlogloss:1.83917
[373]	train-mlogloss:1.85714	validation-mlogloss:1.83884
[374]	train-mlogloss:1.85651	validation-mlogloss:1.83840
[375]	train-mlogloss:1.85585	validation-mlogloss:1.83799
[376]	train-mlogloss:1.85516	validation-mlogloss:1.83738
[377]	train-mlogloss:1.85451	validation-mlogloss:1.83704
[378]	train-mlogloss:1.85382	validation-mlogloss:1.83662
[379]	train-mlogloss:1.85319	validation-mlogloss:1.83631
[380]	train-mlogloss:1.85258	validation-mlogloss:1.83588
[381]	train-mlogloss:1.85194	validation-mlogloss:1.83552
[382]	train-mlogloss:1.85123	validation-mlogloss:1.83494
[383]	train-mlogloss:1.85063	validation-mlogloss:1.83459
[384]	train-mlogloss:1.84998	validation-mlogloss:1.83426
[385]	train-mlogloss:1.84940	validation-mlogloss:1.83388
[386]	train-mlogloss:1.84883	validation-mlogloss:1.83354
[387]	train-mlogloss:1.84823	validation-mlogloss:1.83314
[388]	train-mlogloss:1.84771	validation-mlogloss:1.83289
[389]	train-mlogloss:1.84707	validation-mlogloss:1.83244
[390]	train-mlogloss:1.84642	validation-mlogloss:1.83216
[391]	train-mlogloss:1.84574	validation-mlogloss:1.83172
[392]	train-mlogloss:1.84523	validation-mlogloss:1.83129
[393]	train-mlogloss:1.84464	validation-mlogloss:1.83092
[394]	train-mlogloss:1.84408	validation-mlogloss:1.83063
[395]	train-mlogloss:1.84363	validation-mlogloss:1.83037
[396]	train-mlogloss:1.84308	validation-mlogloss:1.82987
[397]	train-mlogloss:1.84246	validation-mlogloss:1.82952
[398]	train-mlogloss:1.84189	validation-mlogloss:1.82910
[399]	train-mlogloss:1.84136	validation-mlogloss:1.82877
[400]	train-mlogloss:1.84078	validation-mlogloss:1.82823
[401]	train-mlogloss:1.84032	validation-mlogloss:1.82794
[402]	train-mlogloss:1.83984	validation-mlogloss:1.82764
[403]	train-mlogloss:1.83928	validation-mlogloss:1.82719
[404]	train-mlogloss:1.83873	validation-mlogloss:1.82686
[405]	train-mlogloss:1.83818	validation-mlogloss:1.82641
[406]	train-mlogloss:1.83764	validation-mlogloss:1.82610
[407]	train-mlogloss:1.83715	validation-mlogloss:1.82582
[408]	train-mlogloss:1.83653	validation-mlogloss:1.82543
[409]	train-mlogloss:1.83601	validation-mlogloss:1.82502
[410]	train-mlogloss:1.83544	validation-mlogloss:1.82468
[411]	train-mlogloss:1.83493	validation-mlogloss:1.82437
[412]	train-mlogloss:1.83443	validation-mlogloss:1.82398
[413]	train-mlogloss:1.83390	validation-mlogloss:1.82365
[414]	train-mlogloss:1.83333	validation-mlogloss:1.82326
[415]	train-mlogloss:1.83280	validation-mlogloss:1.82284
[416]	train-mlogloss:1.83222	validation-mlogloss:1.82238
[417]	train-mlogloss:1.83166	validation-mlogloss:1.82196
[418]	train-mlogloss:1.83123	validation-mlogloss:1.82174
[419]	train-mlogloss:1.83065	validation-mlogloss:1.82122
Saved model to disk.
2025-11-06 21:51:38.455716: 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 21:51:38.467041: 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 00:00:1762462298.480182 1832141 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462298.484295 1832141 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462298.494119 1832141 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462298.494134 1832141 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462298.494136 1832141 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462298.494137 1832141 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:51:38.497333: 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:2.69401	validation-mlogloss:2.69254
[2]	train-mlogloss:2.68681	validation-mlogloss:2.68495
[3]	train-mlogloss:2.67958	validation-mlogloss:2.67742
[4]	train-mlogloss:2.67235	validation-mlogloss:2.66976
[5]	train-mlogloss:2.66523	validation-mlogloss:2.66216
[6]	train-mlogloss:2.65819	validation-mlogloss:2.65451
[7]	train-mlogloss:2.65119	validation-mlogloss:2.64707
[8]	train-mlogloss:2.64390	validation-mlogloss:2.63897
[9]	train-mlogloss:2.63702	validation-mlogloss:2.63184
[10]	train-mlogloss:2.62981	validation-mlogloss:2.62390
[11]	train-mlogloss:2.62267	validation-mlogloss:2.61607
[12]	train-mlogloss:2.61589	validation-mlogloss:2.60861
[13]	train-mlogloss:2.60932	validation-mlogloss:2.60155
[14]	train-mlogloss:2.60258	validation-mlogloss:2.59397
[15]	train-mlogloss:2.59607	validation-mlogloss:2.58683
[16]	train-mlogloss:2.58959	validation-mlogloss:2.57979
[17]	train-mlogloss:2.58330	validation-mlogloss:2.57293
[18]	train-mlogloss:2.57705	validation-mlogloss:2.56621
[19]	train-mlogloss:2.57084	validation-mlogloss:2.55928
[20]	train-mlogloss:2.56475	validation-mlogloss:2.55264
[21]	train-mlogloss:2.55893	validation-mlogloss:2.54660
[22]	train-mlogloss:2.55308	validation-mlogloss:2.54041
[23]	train-mlogloss:2.54724	validation-mlogloss:2.53409
[24]	train-mlogloss:2.54127	validation-mlogloss:2.52761
[25]	train-mlogloss:2.53576	validation-mlogloss:2.52142
[26]	train-mlogloss:2.53007	validation-mlogloss:2.51517
[27]	train-mlogloss:2.52448	validation-mlogloss:2.50910
[28]	train-mlogloss:2.51871	validation-mlogloss:2.50255
[29]	train-mlogloss:2.51340	validation-mlogloss:2.49685
[30]	train-mlogloss:2.50772	validation-mlogloss:2.49054
[31]	train-mlogloss:2.50234	validation-mlogloss:2.48471
[32]	train-mlogloss:2.49693	validation-mlogloss:2.47877
[33]	train-mlogloss:2.49159	validation-mlogloss:2.47294
[34]	train-mlogloss:2.48646	validation-mlogloss:2.46743
[35]	train-mlogloss:2.48136	validation-mlogloss:2.46189
[36]	train-mlogloss:2.47644	validation-mlogloss:2.45675
[37]	train-mlogloss:2.47158	validation-mlogloss:2.45150
[38]	train-mlogloss:2.46657	validation-mlogloss:2.44615
[39]	train-mlogloss:2.46168	validation-mlogloss:2.44051
[40]	train-mlogloss:2.45676	validation-mlogloss:2.43489
[41]	train-mlogloss:2.45215	validation-mlogloss:2.43000
[42]	train-mlogloss:2.44725	validation-mlogloss:2.42466
[43]	train-mlogloss:2.44272	validation-mlogloss:2.41988
[44]	train-mlogloss:2.43779	validation-mlogloss:2.41422
[45]	train-mlogloss:2.43314	validation-mlogloss:2.40913
[46]	train-mlogloss:2.42862	validation-mlogloss:2.40428
[47]	train-mlogloss:2.42386	validation-mlogloss:2.39891
[48]	train-mlogloss:2.41932	validation-mlogloss:2.39392
[49]	train-mlogloss:2.41489	validation-mlogloss:2.38922
[50]	train-mlogloss:2.41055	validation-mlogloss:2.38480
[51]	train-mlogloss:2.40615	validation-mlogloss:2.38004
[52]	train-mlogloss:2.40183	validation-mlogloss:2.37515
[53]	train-mlogloss:2.39743	validation-mlogloss:2.37065
[54]	train-mlogloss:2.39328	validation-mlogloss:2.36618
[55]	train-mlogloss:2.38925	validation-mlogloss:2.36195
[56]	train-mlogloss:2.38493	validation-mlogloss:2.35725
[57]	train-mlogloss:2.38069	validation-mlogloss:2.35214
[58]	train-mlogloss:2.37670	validation-mlogloss:2.34799
[59]	train-mlogloss:2.37250	validation-mlogloss:2.34359
[60]	train-mlogloss:2.36840	validation-mlogloss:2.33897
[61]	train-mlogloss:2.36433	validation-mlogloss:2.33465
[62]	train-mlogloss:2.36041	validation-mlogloss:2.33063
[63]	train-mlogloss:2.35630	validation-mlogloss:2.32618
[64]	train-mlogloss:2.35253	validation-mlogloss:2.32213
[65]	train-mlogloss:2.34839	validation-mlogloss:2.31728
[66]	train-mlogloss:2.34450	validation-mlogloss:2.31319
[67]	train-mlogloss:2.34068	validation-mlogloss:2.30909
[68]	train-mlogloss:2.33676	validation-mlogloss:2.30464
[69]	train-mlogloss:2.33303	validation-mlogloss:2.30074
[70]	train-mlogloss:2.32929	validation-mlogloss:2.29677
[71]	train-mlogloss:2.32551	validation-mlogloss:2.29268
[72]	train-mlogloss:2.32170	validation-mlogloss:2.28839
[73]	train-mlogloss:2.31803	validation-mlogloss:2.28445
[74]	train-mlogloss:2.31461	validation-mlogloss:2.28090
[75]	train-mlogloss:2.31109	validation-mlogloss:2.27693
[76]	train-mlogloss:2.30756	validation-mlogloss:2.27292
[77]	train-mlogloss:2.30425	validation-mlogloss:2.26956
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[79]	train-mlogloss:2.29724	validation-mlogloss:2.26159
[80]	train-mlogloss:2.29403	validation-mlogloss:2.25821
[81]	train-mlogloss:2.29067	validation-mlogloss:2.25458
[82]	train-mlogloss:2.28731	validation-mlogloss:2.25069
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[84]	train-mlogloss:2.28074	validation-mlogloss:2.24365
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[87]	train-mlogloss:2.27096	validation-mlogloss:2.23335
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[89]	train-mlogloss:2.26464	validation-mlogloss:2.22613
[90]	train-mlogloss:2.26146	validation-mlogloss:2.22273
[91]	train-mlogloss:2.25839	validation-mlogloss:2.21930
[92]	train-mlogloss:2.25527	validation-mlogloss:2.21564
[93]	train-mlogloss:2.25220	validation-mlogloss:2.21240
[94]	train-mlogloss:2.24907	validation-mlogloss:2.20883
[95]	train-mlogloss:2.24614	validation-mlogloss:2.20591
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[99]	train-mlogloss:2.23482	validation-mlogloss:2.19395
[100]	train-mlogloss:2.23184	validation-mlogloss:2.19050
[101]	train-mlogloss:2.22909	validation-mlogloss:2.18758
[102]	train-mlogloss:2.22633	validation-mlogloss:2.18464
[103]	train-mlogloss:2.22335	validation-mlogloss:2.18125
[104]	train-mlogloss:2.22048	validation-mlogloss:2.17820
[105]	train-mlogloss:2.21765	validation-mlogloss:2.17508
[106]	train-mlogloss:2.21486	validation-mlogloss:2.17206
[107]	train-mlogloss:2.21219	validation-mlogloss:2.16923
[108]	train-mlogloss:2.20963	validation-mlogloss:2.16637
[109]	train-mlogloss:2.20684	validation-mlogloss:2.16342
[110]	train-mlogloss:2.20443	validation-mlogloss:2.16087
[111]	train-mlogloss:2.20175	validation-mlogloss:2.15786
[112]	train-mlogloss:2.19910	validation-mlogloss:2.15511
[113]	train-mlogloss:2.19664	validation-mlogloss:2.15262
[114]	train-mlogloss:2.19402	validation-mlogloss:2.14997
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[116]	train-mlogloss:2.18856	validation-mlogloss:2.14381
[117]	train-mlogloss:2.18606	validation-mlogloss:2.14130
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[119]	train-mlogloss:2.18114	validation-mlogloss:2.13640
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[122]	train-mlogloss:2.17395	validation-mlogloss:2.12902
[123]	train-mlogloss:2.17159	validation-mlogloss:2.12640
[124]	train-mlogloss:2.16919	validation-mlogloss:2.12384
[125]	train-mlogloss:2.16690	validation-mlogloss:2.12151
[126]	train-mlogloss:2.16444	validation-mlogloss:2.11909
[127]	train-mlogloss:2.16204	validation-mlogloss:2.11646
[128]	train-mlogloss:2.15977	validation-mlogloss:2.11413
[129]	train-mlogloss:2.15767	validation-mlogloss:2.11206
[130]	train-mlogloss:2.15540	validation-mlogloss:2.10954
[131]	train-mlogloss:2.15324	validation-mlogloss:2.10751
[132]	train-mlogloss:2.15108	validation-mlogloss:2.10521
[133]	train-mlogloss:2.14877	validation-mlogloss:2.10268
[134]	train-mlogloss:2.14647	validation-mlogloss:2.10017
[135]	train-mlogloss:2.14422	validation-mlogloss:2.09791
[136]	train-mlogloss:2.14201	validation-mlogloss:2.09562
[137]	train-mlogloss:2.13996	validation-mlogloss:2.09361
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[139]	train-mlogloss:2.13553	validation-mlogloss:2.08888
[140]	train-mlogloss:2.13344	validation-mlogloss:2.08652
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[143]	train-mlogloss:2.12743	validation-mlogloss:2.08042
[144]	train-mlogloss:2.12549	validation-mlogloss:2.07856
[145]	train-mlogloss:2.12350	validation-mlogloss:2.07672
[146]	train-mlogloss:2.12124	validation-mlogloss:2.07431
[147]	train-mlogloss:2.11910	validation-mlogloss:2.07192
[148]	train-mlogloss:2.11718	validation-mlogloss:2.06994
[149]	train-mlogloss:2.11504	validation-mlogloss:2.06761
[150]	train-mlogloss:2.11298	validation-mlogloss:2.06576
[151]	train-mlogloss:2.11093	validation-mlogloss:2.06370
[152]	train-mlogloss:2.10900	validation-mlogloss:2.06170
[153]	train-mlogloss:2.10705	validation-mlogloss:2.05975
[154]	train-mlogloss:2.10501	validation-mlogloss:2.05758
[155]	train-mlogloss:2.10321	validation-mlogloss:2.05587
[156]	train-mlogloss:2.10136	validation-mlogloss:2.05387
[157]	train-mlogloss:2.09956	validation-mlogloss:2.05220
[158]	train-mlogloss:2.09764	validation-mlogloss:2.05027
[159]	train-mlogloss:2.09563	validation-mlogloss:2.04826
[160]	train-mlogloss:2.09377	validation-mlogloss:2.04633
[161]	train-mlogloss:2.09180	validation-mlogloss:2.04426
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[163]	train-mlogloss:2.08817	validation-mlogloss:2.04048
[164]	train-mlogloss:2.08633	validation-mlogloss:2.03880
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[187]	train-mlogloss:2.04766	validation-mlogloss:2.00111
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[189]	train-mlogloss:2.04443	validation-mlogloss:1.99788
[190]	train-mlogloss:2.04278	validation-mlogloss:1.99620
[191]	train-mlogloss:2.04117	validation-mlogloss:1.99442
[192]	train-mlogloss:2.03964	validation-mlogloss:1.99301
[193]	train-mlogloss:2.03823	validation-mlogloss:1.99182
[194]	train-mlogloss:2.03671	validation-mlogloss:1.99040
[195]	train-mlogloss:2.03517	validation-mlogloss:1.98884
[196]	train-mlogloss:2.03365	validation-mlogloss:1.98737
[197]	train-mlogloss:2.03219	validation-mlogloss:1.98599
[198]	train-mlogloss:2.03066	validation-mlogloss:1.98452
[199]	train-mlogloss:2.02920	validation-mlogloss:1.98320
[200]	train-mlogloss:2.02788	validation-mlogloss:1.98202
[201]	train-mlogloss:2.02642	validation-mlogloss:1.98052
[202]	train-mlogloss:2.02490	validation-mlogloss:1.97911
[203]	train-mlogloss:2.02348	validation-mlogloss:1.97789
[204]	train-mlogloss:2.02196	validation-mlogloss:1.97657
[205]	train-mlogloss:2.02060	validation-mlogloss:1.97499
[206]	train-mlogloss:2.01919	validation-mlogloss:1.97361
[207]	train-mlogloss:2.01785	validation-mlogloss:1.97233
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[209]	train-mlogloss:2.01509	validation-mlogloss:1.96971
[210]	train-mlogloss:2.01360	validation-mlogloss:1.96851
[211]	train-mlogloss:2.01219	validation-mlogloss:1.96705
[212]	train-mlogloss:2.01093	validation-mlogloss:1.96577
[213]	train-mlogloss:2.00958	validation-mlogloss:1.96453
[214]	train-mlogloss:2.00825	validation-mlogloss:1.96326
[215]	train-mlogloss:2.00689	validation-mlogloss:1.96199
[216]	train-mlogloss:2.00560	validation-mlogloss:1.96085
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[371]	train-mlogloss:1.85923	validation-mlogloss:1.83863
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[384]	train-mlogloss:1.85111	validation-mlogloss:1.83280
[385]	train-mlogloss:1.85056	validation-mlogloss:1.83239
[386]	train-mlogloss:1.84995	validation-mlogloss:1.83210
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[389]	train-mlogloss:1.84835	validation-mlogloss:1.83124
[390]	train-mlogloss:1.84778	validation-mlogloss:1.83076
[391]	train-mlogloss:1.84725	validation-mlogloss:1.83041
[392]	train-mlogloss:1.84663	validation-mlogloss:1.82990
[393]	train-mlogloss:1.84602	validation-mlogloss:1.82953
[394]	train-mlogloss:1.84540	validation-mlogloss:1.82905
[395]	train-mlogloss:1.84494	validation-mlogloss:1.82891
[396]	train-mlogloss:1.84436	validation-mlogloss:1.82838
[397]	train-mlogloss:1.84378	validation-mlogloss:1.82788
[398]	train-mlogloss:1.84317	validation-mlogloss:1.82743
[399]	train-mlogloss:1.84267	validation-mlogloss:1.82716
[400]	train-mlogloss:1.84210	validation-mlogloss:1.82682
[401]	train-mlogloss:1.84157	validation-mlogloss:1.82649
[402]	train-mlogloss:1.84096	validation-mlogloss:1.82614
[403]	train-mlogloss:1.84035	validation-mlogloss:1.82578
[404]	train-mlogloss:1.83984	validation-mlogloss:1.82529
[405]	train-mlogloss:1.83932	validation-mlogloss:1.82498
[406]	train-mlogloss:1.83881	validation-mlogloss:1.82465
[407]	train-mlogloss:1.83824	validation-mlogloss:1.82425
[408]	train-mlogloss:1.83769	validation-mlogloss:1.82389
[409]	train-mlogloss:1.83711	validation-mlogloss:1.82344
[410]	train-mlogloss:1.83652	validation-mlogloss:1.82298
[411]	train-mlogloss:1.83588	validation-mlogloss:1.82254
[412]	train-mlogloss:1.83539	validation-mlogloss:1.82217
[413]	train-mlogloss:1.83493	validation-mlogloss:1.82176
[414]	train-mlogloss:1.83441	validation-mlogloss:1.82144
[415]	train-mlogloss:1.83393	validation-mlogloss:1.82116
[416]	train-mlogloss:1.83339	validation-mlogloss:1.82096
[417]	train-mlogloss:1.83273	validation-mlogloss:1.82053
[418]	train-mlogloss:1.83227	validation-mlogloss:1.82021
[419]	train-mlogloss:1.83178	validation-mlogloss:1.81992
Saved model to disk.
2025-11-06 21:52:00.231838: 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 21:52:00.243188: 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 00:00:1762462320.256341 1832510 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462320.260423 1832510 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462320.270191 1832510 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462320.270208 1832510 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462320.270210 1832510 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462320.270211 1832510 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:52:00.273299: 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:2.68551	validation-mlogloss:2.68432
[3]	train-mlogloss:2.67819	validation-mlogloss:2.67675
[4]	train-mlogloss:2.67099	validation-mlogloss:2.66892
[5]	train-mlogloss:2.66324	validation-mlogloss:2.66035
[6]	train-mlogloss:2.65625	validation-mlogloss:2.65263
[7]	train-mlogloss:2.64920	validation-mlogloss:2.64489
[8]	train-mlogloss:2.64209	validation-mlogloss:2.63750
[9]	train-mlogloss:2.63483	validation-mlogloss:2.62955
[10]	train-mlogloss:2.62793	validation-mlogloss:2.62238
[11]	train-mlogloss:2.62141	validation-mlogloss:2.61533
[12]	train-mlogloss:2.61456	validation-mlogloss:2.60761
[13]	train-mlogloss:2.60769	validation-mlogloss:2.59976
[14]	train-mlogloss:2.60102	validation-mlogloss:2.59251
[15]	train-mlogloss:2.59451	validation-mlogloss:2.58564
[16]	train-mlogloss:2.58864	validation-mlogloss:2.57934
[17]	train-mlogloss:2.58216	validation-mlogloss:2.57261
[18]	train-mlogloss:2.57576	validation-mlogloss:2.56535
[19]	train-mlogloss:2.56950	validation-mlogloss:2.55842
[20]	train-mlogloss:2.56324	validation-mlogloss:2.55150
[21]	train-mlogloss:2.55733	validation-mlogloss:2.54512
[22]	train-mlogloss:2.55128	validation-mlogloss:2.53847
[23]	train-mlogloss:2.54560	validation-mlogloss:2.53231
[24]	train-mlogloss:2.53962	validation-mlogloss:2.52569
[25]	train-mlogloss:2.53384	validation-mlogloss:2.51927
[26]	train-mlogloss:2.52810	validation-mlogloss:2.51291
[27]	train-mlogloss:2.52250	validation-mlogloss:2.50650
[28]	train-mlogloss:2.51695	validation-mlogloss:2.50036
[29]	train-mlogloss:2.51153	validation-mlogloss:2.49435
[30]	train-mlogloss:2.50602	validation-mlogloss:2.48840
[31]	train-mlogloss:2.50058	validation-mlogloss:2.48230
[32]	train-mlogloss:2.49524	validation-mlogloss:2.47634
[33]	train-mlogloss:2.49015	validation-mlogloss:2.47076
[34]	train-mlogloss:2.48493	validation-mlogloss:2.46505
[35]	train-mlogloss:2.47937	validation-mlogloss:2.45883
[36]	train-mlogloss:2.47424	validation-mlogloss:2.45299
[37]	train-mlogloss:2.46910	validation-mlogloss:2.44729
[38]	train-mlogloss:2.46424	validation-mlogloss:2.44207
[39]	train-mlogloss:2.45967	validation-mlogloss:2.43740
[40]	train-mlogloss:2.45461	validation-mlogloss:2.43150
[41]	train-mlogloss:2.44962	validation-mlogloss:2.42621
[42]	train-mlogloss:2.44510	validation-mlogloss:2.42126
[43]	train-mlogloss:2.44021	validation-mlogloss:2.41550
[44]	train-mlogloss:2.43554	validation-mlogloss:2.41048
[45]	train-mlogloss:2.43063	validation-mlogloss:2.40506
[46]	train-mlogloss:2.42610	validation-mlogloss:2.40023
[47]	train-mlogloss:2.42172	validation-mlogloss:2.39536
[48]	train-mlogloss:2.41725	validation-mlogloss:2.39048
[49]	train-mlogloss:2.41302	validation-mlogloss:2.38612
[50]	train-mlogloss:2.40896	validation-mlogloss:2.38218
[51]	train-mlogloss:2.40459	validation-mlogloss:2.37775
[52]	train-mlogloss:2.40020	validation-mlogloss:2.37273
[53]	train-mlogloss:2.39587	validation-mlogloss:2.36795
[54]	train-mlogloss:2.39129	validation-mlogloss:2.36282
[55]	train-mlogloss:2.38707	validation-mlogloss:2.35848
[56]	train-mlogloss:2.38296	validation-mlogloss:2.35407
[57]	train-mlogloss:2.37900	validation-mlogloss:2.34984
[58]	train-mlogloss:2.37476	validation-mlogloss:2.34500
[59]	train-mlogloss:2.37060	validation-mlogloss:2.34045
[60]	train-mlogloss:2.36666	validation-mlogloss:2.33614
[61]	train-mlogloss:2.36263	validation-mlogloss:2.33184
[62]	train-mlogloss:2.35865	validation-mlogloss:2.32763
[63]	train-mlogloss:2.35463	validation-mlogloss:2.32321
[64]	train-mlogloss:2.35073	validation-mlogloss:2.31890
[65]	train-mlogloss:2.34679	validation-mlogloss:2.31457
[66]	train-mlogloss:2.34298	validation-mlogloss:2.31045
[67]	train-mlogloss:2.33917	validation-mlogloss:2.30607
[68]	train-mlogloss:2.33540	validation-mlogloss:2.30211
[69]	train-mlogloss:2.33166	validation-mlogloss:2.29779
[70]	train-mlogloss:2.32793	validation-mlogloss:2.29370
[71]	train-mlogloss:2.32425	validation-mlogloss:2.28959
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[372]	train-mlogloss:1.85933	validation-mlogloss:1.84046
[373]	train-mlogloss:1.85869	validation-mlogloss:1.84007
[374]	train-mlogloss:1.85807	validation-mlogloss:1.83954
[375]	train-mlogloss:1.85737	validation-mlogloss:1.83900
[376]	train-mlogloss:1.85671	validation-mlogloss:1.83862
[377]	train-mlogloss:1.85606	validation-mlogloss:1.83820
[378]	train-mlogloss:1.85547	validation-mlogloss:1.83798
[379]	train-mlogloss:1.85485	validation-mlogloss:1.83758
[380]	train-mlogloss:1.85424	validation-mlogloss:1.83718
[381]	train-mlogloss:1.85367	validation-mlogloss:1.83677
[382]	train-mlogloss:1.85305	validation-mlogloss:1.83629
[383]	train-mlogloss:1.85251	validation-mlogloss:1.83593
[384]	train-mlogloss:1.85189	validation-mlogloss:1.83553
[385]	train-mlogloss:1.85132	validation-mlogloss:1.83510
[386]	train-mlogloss:1.85068	validation-mlogloss:1.83460
[387]	train-mlogloss:1.85007	validation-mlogloss:1.83415
[388]	train-mlogloss:1.84956	validation-mlogloss:1.83384
[389]	train-mlogloss:1.84899	validation-mlogloss:1.83356
[390]	train-mlogloss:1.84842	validation-mlogloss:1.83300
[391]	train-mlogloss:1.84780	validation-mlogloss:1.83259
[392]	train-mlogloss:1.84727	validation-mlogloss:1.83208
[393]	train-mlogloss:1.84665	validation-mlogloss:1.83157
[394]	train-mlogloss:1.84608	validation-mlogloss:1.83112
[395]	train-mlogloss:1.84557	validation-mlogloss:1.83059
[396]	train-mlogloss:1.84497	validation-mlogloss:1.83021
[397]	train-mlogloss:1.84434	validation-mlogloss:1.82960
[398]	train-mlogloss:1.84370	validation-mlogloss:1.82912
[399]	train-mlogloss:1.84314	validation-mlogloss:1.82868
[400]	train-mlogloss:1.84251	validation-mlogloss:1.82827
[401]	train-mlogloss:1.84198	validation-mlogloss:1.82794
[402]	train-mlogloss:1.84154	validation-mlogloss:1.82749
[403]	train-mlogloss:1.84099	validation-mlogloss:1.82699
[404]	train-mlogloss:1.84037	validation-mlogloss:1.82644
[405]	train-mlogloss:1.83982	validation-mlogloss:1.82591
[406]	train-mlogloss:1.83922	validation-mlogloss:1.82554
[407]	train-mlogloss:1.83871	validation-mlogloss:1.82507
[408]	train-mlogloss:1.83821	validation-mlogloss:1.82463
[409]	train-mlogloss:1.83768	validation-mlogloss:1.82436
[410]	train-mlogloss:1.83719	validation-mlogloss:1.82400
[411]	train-mlogloss:1.83667	validation-mlogloss:1.82360
[412]	train-mlogloss:1.83617	validation-mlogloss:1.82320
[413]	train-mlogloss:1.83564	validation-mlogloss:1.82268
[414]	train-mlogloss:1.83509	validation-mlogloss:1.82240
[415]	train-mlogloss:1.83463	validation-mlogloss:1.82205
[416]	train-mlogloss:1.83417	validation-mlogloss:1.82177
[417]	train-mlogloss:1.83375	validation-mlogloss:1.82141
[418]	train-mlogloss:1.83320	validation-mlogloss:1.82117
[419]	train-mlogloss:1.83269	validation-mlogloss:1.82087
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.38 [%]
Global accuracy score (test) = 43.73 [%]
Global F1 score (train) = 43.92 [%]
Global F1 score (test) = 42.84 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.49      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.42      0.43      0.43       184
       CAMINAR USUAL SPEED       0.35      0.18      0.24       184
            CAMINAR ZIGZAG       0.32      0.52      0.40       184
          DE PIE BARRIENDO       0.69      0.40      0.50       184
   DE PIE DOBLANDO TOALLAS       0.46      0.45      0.45       184
    DE PIE MOVIENDO LIBROS       0.37      0.39      0.38       184
          DE PIE USANDO PC       0.20      0.33      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.57      0.61       184
           SENTADO LEYENDO       0.46      0.39      0.42       184
         SENTADO USANDO PC       0.23      0.11      0.15       184
      SENTADO VIENDO LA TV       0.24      0.15      0.18       184
   SUBIR Y BAJAR ESCALERAS       0.57      0.56      0.56       184
                    TROTAR       0.65      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.44      0.44      0.43      2737
              weighted avg       0.44      0.44      0.43      2737


Accuracy capturado en la ejecución 22: 43.73 [%]
F1-score capturado en la ejecución 22: 42.84 [%]

=== EJECUCIÓN 23 ===

--- TRAIN (ejecución 23) ---

--- TEST (ejecución 23) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.19 [%]
Global accuracy score (test) = 44.06 [%]
Global F1 score (train) = 43.69 [%]
Global F1 score (test) = 43.28 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.72      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.42      0.45      0.43       184
       CAMINAR USUAL SPEED       0.32      0.16      0.22       184
            CAMINAR ZIGZAG       0.31      0.53      0.39       184
          DE PIE BARRIENDO       0.71      0.40      0.51       184
   DE PIE DOBLANDO TOALLAS       0.46      0.44      0.45       184
    DE PIE MOVIENDO LIBROS       0.39      0.40      0.39       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.64      0.57      0.61       184
           SENTADO LEYENDO       0.46      0.40      0.43       184
         SENTADO USANDO PC       0.27      0.12      0.17       184
      SENTADO VIENDO LA TV       0.25      0.16      0.20       184
   SUBIR Y BAJAR ESCALERAS       0.66      0.56      0.61       184
                    TROTAR       0.66      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 23: 44.06 [%]
F1-score capturado en la ejecución 23: 43.28 [%]

=== EJECUCIÓN 24 ===

--- TRAIN (ejecución 24) ---

--- TEST (ejecución 24) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.17 [%]
Global accuracy score (test) = 44.21 [%]
Global F1 score (train) = 43.66 [%]
Global F1 score (test) = 43.42 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.45      0.44       184
       CAMINAR USUAL SPEED       0.35      0.19      0.25       184
            CAMINAR ZIGZAG       0.32      0.54      0.40       184
          DE PIE BARRIENDO       0.70      0.41      0.52       184
   DE PIE DOBLANDO TOALLAS       0.46      0.46      0.46       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.38       184
          DE PIE USANDO PC       0.20      0.31      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.58      0.61       184
           SENTADO LEYENDO       0.47      0.39      0.43       184
         SENTADO USANDO PC       0.21      0.11      0.14       184
      SENTADO VIENDO LA TV       0.24      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.64      0.56      0.60       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 24: 44.21 [%]
F1-score capturado en la ejecución 24: 43.42 [%]

=== EJECUCIÓN 25 ===

--- TRAIN (ejecución 25) ---

--- TEST (ejecución 25) ---
2025-11-06 21:52:22.068366: 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 21:52:22.079803: 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 00:00:1762462342.093616 1832880 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462342.097845 1832880 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462342.108134 1832880 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462342.108155 1832880 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462342.108156 1832880 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462342.108158 1832880 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:52:22.111249: 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:2.70023	validation-mlogloss:2.69976
[1]	train-mlogloss:2.69284	validation-mlogloss:2.69219
[2]	train-mlogloss:2.68564	validation-mlogloss:2.68456
[3]	train-mlogloss:2.67832	validation-mlogloss:2.67667
[4]	train-mlogloss:2.67122	validation-mlogloss:2.66904
[5]	train-mlogloss:2.66405	validation-mlogloss:2.66122
[6]	train-mlogloss:2.65697	validation-mlogloss:2.65341
[7]	train-mlogloss:2.64974	validation-mlogloss:2.64573
[8]	train-mlogloss:2.64242	validation-mlogloss:2.63765
[9]	train-mlogloss:2.63559	validation-mlogloss:2.63043
[10]	train-mlogloss:2.62889	validation-mlogloss:2.62303
[11]	train-mlogloss:2.62185	validation-mlogloss:2.61535
[12]	train-mlogloss:2.61501	validation-mlogloss:2.60791
[13]	train-mlogloss:2.60831	validation-mlogloss:2.60067
[14]	train-mlogloss:2.60155	validation-mlogloss:2.59337
[15]	train-mlogloss:2.59508	validation-mlogloss:2.58619
[16]	train-mlogloss:2.58849	validation-mlogloss:2.57893
[17]	train-mlogloss:2.58237	validation-mlogloss:2.57270
[18]	train-mlogloss:2.57617	validation-mlogloss:2.56602
[19]	train-mlogloss:2.57015	validation-mlogloss:2.55957
[20]	train-mlogloss:2.56433	validation-mlogloss:2.55335
[21]	train-mlogloss:2.55820	validation-mlogloss:2.54634
[22]	train-mlogloss:2.55246	validation-mlogloss:2.54018
[23]	train-mlogloss:2.54659	validation-mlogloss:2.53388
[24]	train-mlogloss:2.54075	validation-mlogloss:2.52744
[25]	train-mlogloss:2.53491	validation-mlogloss:2.52115
[26]	train-mlogloss:2.52917	validation-mlogloss:2.51484
[27]	train-mlogloss:2.52360	validation-mlogloss:2.50890
[28]	train-mlogloss:2.51809	validation-mlogloss:2.50300
[29]	train-mlogloss:2.51280	validation-mlogloss:2.49745
[30]	train-mlogloss:2.50744	validation-mlogloss:2.49162
[31]	train-mlogloss:2.50194	validation-mlogloss:2.48559
[32]	train-mlogloss:2.49653	validation-mlogloss:2.47940
[33]	train-mlogloss:2.49138	validation-mlogloss:2.47383
[34]	train-mlogloss:2.48631	validation-mlogloss:2.46817
[35]	train-mlogloss:2.48109	validation-mlogloss:2.46239
[36]	train-mlogloss:2.47604	validation-mlogloss:2.45680
[37]	train-mlogloss:2.47075	validation-mlogloss:2.45093
[38]	train-mlogloss:2.46549	validation-mlogloss:2.44496
[39]	train-mlogloss:2.46052	validation-mlogloss:2.43910
[40]	train-mlogloss:2.45563	validation-mlogloss:2.43337
[41]	train-mlogloss:2.45077	validation-mlogloss:2.42778
[42]	train-mlogloss:2.44619	validation-mlogloss:2.42283
[43]	train-mlogloss:2.44150	validation-mlogloss:2.41773
[44]	train-mlogloss:2.43674	validation-mlogloss:2.41268
[45]	train-mlogloss:2.43237	validation-mlogloss:2.40805
[46]	train-mlogloss:2.42767	validation-mlogloss:2.40307
[47]	train-mlogloss:2.42326	validation-mlogloss:2.39817
[48]	train-mlogloss:2.41839	validation-mlogloss:2.39265
[49]	train-mlogloss:2.41370	validation-mlogloss:2.38736
[50]	train-mlogloss:2.40920	validation-mlogloss:2.38232
[51]	train-mlogloss:2.40469	validation-mlogloss:2.37750
[52]	train-mlogloss:2.40054	validation-mlogloss:2.37317
[53]	train-mlogloss:2.39632	validation-mlogloss:2.36856
[54]	train-mlogloss:2.39208	validation-mlogloss:2.36399
[55]	train-mlogloss:2.38766	validation-mlogloss:2.35899
[56]	train-mlogloss:2.38321	validation-mlogloss:2.35397
[57]	train-mlogloss:2.37903	validation-mlogloss:2.34916
[58]	train-mlogloss:2.37526	validation-mlogloss:2.34547
[59]	train-mlogloss:2.37111	validation-mlogloss:2.34076
[60]	train-mlogloss:2.36719	validation-mlogloss:2.33666
[61]	train-mlogloss:2.36309	validation-mlogloss:2.33208
[62]	train-mlogloss:2.35896	validation-mlogloss:2.32748
[63]	train-mlogloss:2.35506	validation-mlogloss:2.32314
[64]	train-mlogloss:2.35108	validation-mlogloss:2.31861
[65]	train-mlogloss:2.34710	validation-mlogloss:2.31435
[66]	train-mlogloss:2.34322	validation-mlogloss:2.31015
[67]	train-mlogloss:2.33958	validation-mlogloss:2.30625
[68]	train-mlogloss:2.33582	validation-mlogloss:2.30241
[69]	train-mlogloss:2.33213	validation-mlogloss:2.29834
[70]	train-mlogloss:2.32834	validation-mlogloss:2.29413
[71]	train-mlogloss:2.32437	validation-mlogloss:2.28950
[72]	train-mlogloss:2.32065	validation-mlogloss:2.28524
[73]	train-mlogloss:2.31726	validation-mlogloss:2.28182
[74]	train-mlogloss:2.31394	validation-mlogloss:2.27833
[75]	train-mlogloss:2.31043	validation-mlogloss:2.27452
[76]	train-mlogloss:2.30714	validation-mlogloss:2.27101
[77]	train-mlogloss:2.30372	validation-mlogloss:2.26733
[78]	train-mlogloss:2.30021	validation-mlogloss:2.26369
[79]	train-mlogloss:2.29702	validation-mlogloss:2.26049
[80]	train-mlogloss:2.29385	validation-mlogloss:2.25732
[81]	train-mlogloss:2.29046	validation-mlogloss:2.25372
[82]	train-mlogloss:2.28714	validation-mlogloss:2.25033
[83]	train-mlogloss:2.28374	validation-mlogloss:2.24662
[84]	train-mlogloss:2.28036	validation-mlogloss:2.24307
[85]	train-mlogloss:2.27697	validation-mlogloss:2.23912
[86]	train-mlogloss:2.27385	validation-mlogloss:2.23569
[87]	train-mlogloss:2.27087	validation-mlogloss:2.23266
[88]	train-mlogloss:2.26754	validation-mlogloss:2.22909
[89]	train-mlogloss:2.26443	validation-mlogloss:2.22581
[90]	train-mlogloss:2.26127	validation-mlogloss:2.22231
[91]	train-mlogloss:2.25821	validation-mlogloss:2.21889
[92]	train-mlogloss:2.25534	validation-mlogloss:2.21601
[93]	train-mlogloss:2.25225	validation-mlogloss:2.21260
[94]	train-mlogloss:2.24907	validation-mlogloss:2.20897
[95]	train-mlogloss:2.24629	validation-mlogloss:2.20626
[96]	train-mlogloss:2.24323	validation-mlogloss:2.20294
[97]	train-mlogloss:2.24025	validation-mlogloss:2.19978
[98]	train-mlogloss:2.23729	validation-mlogloss:2.19662
[99]	train-mlogloss:2.23436	validation-mlogloss:2.19348
[100]	train-mlogloss:2.23153	validation-mlogloss:2.19036
[101]	train-mlogloss:2.22861	validation-mlogloss:2.18702
[102]	train-mlogloss:2.22581	validation-mlogloss:2.18399
[103]	train-mlogloss:2.22301	validation-mlogloss:2.18098
[104]	train-mlogloss:2.22019	validation-mlogloss:2.17767
[105]	train-mlogloss:2.21743	validation-mlogloss:2.17475
[106]	train-mlogloss:2.21487	validation-mlogloss:2.17239
[107]	train-mlogloss:2.21222	validation-mlogloss:2.16962
[108]	train-mlogloss:2.20947	validation-mlogloss:2.16676
[109]	train-mlogloss:2.20671	validation-mlogloss:2.16368
[110]	train-mlogloss:2.20415	validation-mlogloss:2.16110
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[410]	train-mlogloss:1.83667	validation-mlogloss:1.82438
[411]	train-mlogloss:1.83610	validation-mlogloss:1.82409
[412]	train-mlogloss:1.83559	validation-mlogloss:1.82365
[413]	train-mlogloss:1.83519	validation-mlogloss:1.82333
[414]	train-mlogloss:1.83462	validation-mlogloss:1.82299
[415]	train-mlogloss:1.83413	validation-mlogloss:1.82268
[416]	train-mlogloss:1.83358	validation-mlogloss:1.82238
[417]	train-mlogloss:1.83305	validation-mlogloss:1.82196
[418]	train-mlogloss:1.83258	validation-mlogloss:1.82184
[419]	train-mlogloss:1.83210	validation-mlogloss:1.82137
Saved model to disk.
2025-11-06 21:52:43.872709: 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 21:52:43.883973: 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 00:00:1762462363.896991 1833262 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462363.901091 1833262 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462363.910746 1833262 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462363.910769 1833262 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462363.910771 1833262 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462363.910772 1833262 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:52:43.913905: 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:2.70055	validation-mlogloss:2.70014
[1]	train-mlogloss:2.69300	validation-mlogloss:2.69226
[2]	train-mlogloss:2.68570	validation-mlogloss:2.68480
[3]	train-mlogloss:2.67840	validation-mlogloss:2.67697
[4]	train-mlogloss:2.67138	validation-mlogloss:2.66961
[5]	train-mlogloss:2.66413	validation-mlogloss:2.66196
[6]	train-mlogloss:2.65652	validation-mlogloss:2.65373
[7]	train-mlogloss:2.64913	validation-mlogloss:2.64557
[8]	train-mlogloss:2.64179	validation-mlogloss:2.63757
[9]	train-mlogloss:2.63505	validation-mlogloss:2.63030
[10]	train-mlogloss:2.62846	validation-mlogloss:2.62296
[11]	train-mlogloss:2.62136	validation-mlogloss:2.61507
[12]	train-mlogloss:2.61449	validation-mlogloss:2.60759
[13]	train-mlogloss:2.60761	validation-mlogloss:2.59994
[14]	train-mlogloss:2.60079	validation-mlogloss:2.59237
[15]	train-mlogloss:2.59415	validation-mlogloss:2.58518
[16]	train-mlogloss:2.58777	validation-mlogloss:2.57833
[17]	train-mlogloss:2.58145	validation-mlogloss:2.57143
[18]	train-mlogloss:2.57517	validation-mlogloss:2.56446
[19]	train-mlogloss:2.56882	validation-mlogloss:2.55722
[20]	train-mlogloss:2.56255	validation-mlogloss:2.54999
[21]	train-mlogloss:2.55658	validation-mlogloss:2.54344
[22]	train-mlogloss:2.55073	validation-mlogloss:2.53714
[23]	train-mlogloss:2.54488	validation-mlogloss:2.53073
[24]	train-mlogloss:2.53884	validation-mlogloss:2.52394
[25]	train-mlogloss:2.53304	validation-mlogloss:2.51765
[26]	train-mlogloss:2.52719	validation-mlogloss:2.51124
[27]	train-mlogloss:2.52149	validation-mlogloss:2.50494
[28]	train-mlogloss:2.51601	validation-mlogloss:2.49901
[29]	train-mlogloss:2.51049	validation-mlogloss:2.49292
[30]	train-mlogloss:2.50492	validation-mlogloss:2.48672
[31]	train-mlogloss:2.49951	validation-mlogloss:2.48072
[32]	train-mlogloss:2.49416	validation-mlogloss:2.47468
[33]	train-mlogloss:2.48894	validation-mlogloss:2.46875
[34]	train-mlogloss:2.48375	validation-mlogloss:2.46292
[35]	train-mlogloss:2.47857	validation-mlogloss:2.45722
[36]	train-mlogloss:2.47346	validation-mlogloss:2.45150
[37]	train-mlogloss:2.46866	validation-mlogloss:2.44641
[38]	train-mlogloss:2.46367	validation-mlogloss:2.44088
[39]	train-mlogloss:2.45868	validation-mlogloss:2.43524
[40]	train-mlogloss:2.45384	validation-mlogloss:2.42985
[41]	train-mlogloss:2.44902	validation-mlogloss:2.42458
[42]	train-mlogloss:2.44440	validation-mlogloss:2.41954
[43]	train-mlogloss:2.43975	validation-mlogloss:2.41422
[44]	train-mlogloss:2.43521	validation-mlogloss:2.40938
[45]	train-mlogloss:2.43076	validation-mlogloss:2.40476
[46]	train-mlogloss:2.42613	validation-mlogloss:2.39970
[47]	train-mlogloss:2.42135	validation-mlogloss:2.39400
[48]	train-mlogloss:2.41699	validation-mlogloss:2.38932
[49]	train-mlogloss:2.41263	validation-mlogloss:2.38455
[50]	train-mlogloss:2.40825	validation-mlogloss:2.37992
[51]	train-mlogloss:2.40363	validation-mlogloss:2.37464
[52]	train-mlogloss:2.39914	validation-mlogloss:2.36955
[53]	train-mlogloss:2.39477	validation-mlogloss:2.36514
[54]	train-mlogloss:2.39062	validation-mlogloss:2.36087
[55]	train-mlogloss:2.38651	validation-mlogloss:2.35628
[56]	train-mlogloss:2.38219	validation-mlogloss:2.35162
[57]	train-mlogloss:2.37813	validation-mlogloss:2.34754
[58]	train-mlogloss:2.37384	validation-mlogloss:2.34307
[59]	train-mlogloss:2.36979	validation-mlogloss:2.33873
[60]	train-mlogloss:2.36579	validation-mlogloss:2.33467
[61]	train-mlogloss:2.36163	validation-mlogloss:2.33001
[62]	train-mlogloss:2.35738	validation-mlogloss:2.32524
[63]	train-mlogloss:2.35353	validation-mlogloss:2.32099
[64]	train-mlogloss:2.34947	validation-mlogloss:2.31635
[65]	train-mlogloss:2.34560	validation-mlogloss:2.31190
[66]	train-mlogloss:2.34146	validation-mlogloss:2.30725
[67]	train-mlogloss:2.33756	validation-mlogloss:2.30286
[68]	train-mlogloss:2.33386	validation-mlogloss:2.29890
[69]	train-mlogloss:2.33018	validation-mlogloss:2.29477
[70]	train-mlogloss:2.32628	validation-mlogloss:2.29007
[71]	train-mlogloss:2.32289	validation-mlogloss:2.28671
[72]	train-mlogloss:2.31935	validation-mlogloss:2.28288
[73]	train-mlogloss:2.31566	validation-mlogloss:2.27863
[74]	train-mlogloss:2.31231	validation-mlogloss:2.27515
[75]	train-mlogloss:2.30872	validation-mlogloss:2.27135
[76]	train-mlogloss:2.30526	validation-mlogloss:2.26772
[77]	train-mlogloss:2.30185	validation-mlogloss:2.26430
[78]	train-mlogloss:2.29849	validation-mlogloss:2.26057
[79]	train-mlogloss:2.29516	validation-mlogloss:2.25687
[80]	train-mlogloss:2.29172	validation-mlogloss:2.25327
[81]	train-mlogloss:2.28830	validation-mlogloss:2.24979
[82]	train-mlogloss:2.28499	validation-mlogloss:2.24630
[83]	train-mlogloss:2.28185	validation-mlogloss:2.24313
[84]	train-mlogloss:2.27848	validation-mlogloss:2.23942
[85]	train-mlogloss:2.27545	validation-mlogloss:2.23629
[86]	train-mlogloss:2.27224	validation-mlogloss:2.23270
[87]	train-mlogloss:2.26929	validation-mlogloss:2.22967
[88]	train-mlogloss:2.26604	validation-mlogloss:2.22601
[89]	train-mlogloss:2.26284	validation-mlogloss:2.22244
[90]	train-mlogloss:2.25971	validation-mlogloss:2.21908
[91]	train-mlogloss:2.25679	validation-mlogloss:2.21612
[92]	train-mlogloss:2.25381	validation-mlogloss:2.21291
[93]	train-mlogloss:2.25078	validation-mlogloss:2.20954
[94]	train-mlogloss:2.24772	validation-mlogloss:2.20627
[95]	train-mlogloss:2.24480	validation-mlogloss:2.20314
[96]	train-mlogloss:2.24188	validation-mlogloss:2.20001
[97]	train-mlogloss:2.23883	validation-mlogloss:2.19682
[98]	train-mlogloss:2.23617	validation-mlogloss:2.19392
[99]	train-mlogloss:2.23311	validation-mlogloss:2.19069
[100]	train-mlogloss:2.23025	validation-mlogloss:2.18758
[101]	train-mlogloss:2.22733	validation-mlogloss:2.18463
[102]	train-mlogloss:2.22439	validation-mlogloss:2.18136
[103]	train-mlogloss:2.22160	validation-mlogloss:2.17835
[104]	train-mlogloss:2.21881	validation-mlogloss:2.17533
[105]	train-mlogloss:2.21605	validation-mlogloss:2.17260
[106]	train-mlogloss:2.21322	validation-mlogloss:2.16958
[107]	train-mlogloss:2.21057	validation-mlogloss:2.16666
[108]	train-mlogloss:2.20806	validation-mlogloss:2.16395
[109]	train-mlogloss:2.20547	validation-mlogloss:2.16102
[110]	train-mlogloss:2.20281	validation-mlogloss:2.15787
[111]	train-mlogloss:2.20016	validation-mlogloss:2.15496
[112]	train-mlogloss:2.19754	validation-mlogloss:2.15240
[113]	train-mlogloss:2.19499	validation-mlogloss:2.14949
[114]	train-mlogloss:2.19256	validation-mlogloss:2.14706
[115]	train-mlogloss:2.19000	validation-mlogloss:2.14430
[116]	train-mlogloss:2.18743	validation-mlogloss:2.14147
[117]	train-mlogloss:2.18492	validation-mlogloss:2.13902
[118]	train-mlogloss:2.18260	validation-mlogloss:2.13659
[119]	train-mlogloss:2.18025	validation-mlogloss:2.13423
[120]	train-mlogloss:2.17786	validation-mlogloss:2.13154
[121]	train-mlogloss:2.17555	validation-mlogloss:2.12930
[122]	train-mlogloss:2.17320	validation-mlogloss:2.12690
[123]	train-mlogloss:2.17079	validation-mlogloss:2.12443
[124]	train-mlogloss:2.16838	validation-mlogloss:2.12202
[125]	train-mlogloss:2.16622	validation-mlogloss:2.12002
[126]	train-mlogloss:2.16390	validation-mlogloss:2.11747
[127]	train-mlogloss:2.16151	validation-mlogloss:2.11492
[128]	train-mlogloss:2.15911	validation-mlogloss:2.11241
[129]	train-mlogloss:2.15696	validation-mlogloss:2.11047
[130]	train-mlogloss:2.15464	validation-mlogloss:2.10797
[131]	train-mlogloss:2.15257	validation-mlogloss:2.10604
[132]	train-mlogloss:2.15031	validation-mlogloss:2.10363
[133]	train-mlogloss:2.14820	validation-mlogloss:2.10140
[134]	train-mlogloss:2.14604	validation-mlogloss:2.09949
[135]	train-mlogloss:2.14384	validation-mlogloss:2.09734
[136]	train-mlogloss:2.14165	validation-mlogloss:2.09514
[137]	train-mlogloss:2.13950	validation-mlogloss:2.09298
[138]	train-mlogloss:2.13719	validation-mlogloss:2.09040
[139]	train-mlogloss:2.13510	validation-mlogloss:2.08828
[140]	train-mlogloss:2.13308	validation-mlogloss:2.08633
[141]	train-mlogloss:2.13093	validation-mlogloss:2.08415
[142]	train-mlogloss:2.12893	validation-mlogloss:2.08217
[143]	train-mlogloss:2.12693	validation-mlogloss:2.08023
[144]	train-mlogloss:2.12482	validation-mlogloss:2.07820
[145]	train-mlogloss:2.12278	validation-mlogloss:2.07624
[146]	train-mlogloss:2.12073	validation-mlogloss:2.07423
[147]	train-mlogloss:2.11860	validation-mlogloss:2.07197
[148]	train-mlogloss:2.11652	validation-mlogloss:2.06985
[149]	train-mlogloss:2.11450	validation-mlogloss:2.06794
[150]	train-mlogloss:2.11243	validation-mlogloss:2.06610
[151]	train-mlogloss:2.11044	validation-mlogloss:2.06404
[152]	train-mlogloss:2.10842	validation-mlogloss:2.06184
[153]	train-mlogloss:2.10648	validation-mlogloss:2.05987
[154]	train-mlogloss:2.10457	validation-mlogloss:2.05786
[155]	train-mlogloss:2.10261	validation-mlogloss:2.05579
[156]	train-mlogloss:2.10078	validation-mlogloss:2.05392
[157]	train-mlogloss:2.09899	validation-mlogloss:2.05214
[158]	train-mlogloss:2.09701	validation-mlogloss:2.05006
[159]	train-mlogloss:2.09520	validation-mlogloss:2.04814
[160]	train-mlogloss:2.09340	validation-mlogloss:2.04649
[161]	train-mlogloss:2.09166	validation-mlogloss:2.04499
[162]	train-mlogloss:2.08989	validation-mlogloss:2.04334
[163]	train-mlogloss:2.08799	validation-mlogloss:2.04144
[164]	train-mlogloss:2.08617	validation-mlogloss:2.03963
[165]	train-mlogloss:2.08427	validation-mlogloss:2.03774
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[172]	train-mlogloss:2.07171	validation-mlogloss:2.02502
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[189]	train-mlogloss:2.04424	validation-mlogloss:1.99895
[190]	train-mlogloss:2.04278	validation-mlogloss:1.99759
[191]	train-mlogloss:2.04132	validation-mlogloss:1.99651
[192]	train-mlogloss:2.03982	validation-mlogloss:1.99499
[193]	train-mlogloss:2.03830	validation-mlogloss:1.99361
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[195]	train-mlogloss:2.03536	validation-mlogloss:1.99090
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[198]	train-mlogloss:2.03078	validation-mlogloss:1.98654
[199]	train-mlogloss:2.02926	validation-mlogloss:1.98509
[200]	train-mlogloss:2.02787	validation-mlogloss:1.98395
[201]	train-mlogloss:2.02637	validation-mlogloss:1.98235
[202]	train-mlogloss:2.02483	validation-mlogloss:1.98089
[203]	train-mlogloss:2.02347	validation-mlogloss:1.97969
[204]	train-mlogloss:2.02200	validation-mlogloss:1.97814
[205]	train-mlogloss:2.02062	validation-mlogloss:1.97681
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[210]	train-mlogloss:2.01355	validation-mlogloss:1.96984
[211]	train-mlogloss:2.01218	validation-mlogloss:1.96844
[212]	train-mlogloss:2.01085	validation-mlogloss:1.96731
[213]	train-mlogloss:2.00957	validation-mlogloss:1.96609
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[220]	train-mlogloss:2.00014	validation-mlogloss:1.95730
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[396]	train-mlogloss:1.84353	validation-mlogloss:1.82791
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[402]	train-mlogloss:1.84046	validation-mlogloss:1.82596
[403]	train-mlogloss:1.83997	validation-mlogloss:1.82560
[404]	train-mlogloss:1.83948	validation-mlogloss:1.82530
[405]	train-mlogloss:1.83891	validation-mlogloss:1.82503
[406]	train-mlogloss:1.83829	validation-mlogloss:1.82471
[407]	train-mlogloss:1.83771	validation-mlogloss:1.82436
[408]	train-mlogloss:1.83727	validation-mlogloss:1.82407
[409]	train-mlogloss:1.83679	validation-mlogloss:1.82366
[410]	train-mlogloss:1.83632	validation-mlogloss:1.82330
[411]	train-mlogloss:1.83586	validation-mlogloss:1.82276
[412]	train-mlogloss:1.83539	validation-mlogloss:1.82238
[413]	train-mlogloss:1.83492	validation-mlogloss:1.82198
[414]	train-mlogloss:1.83434	validation-mlogloss:1.82151
[415]	train-mlogloss:1.83383	validation-mlogloss:1.82112
[416]	train-mlogloss:1.83329	validation-mlogloss:1.82080
[417]	train-mlogloss:1.83276	validation-mlogloss:1.82038
[418]	train-mlogloss:1.83232	validation-mlogloss:1.82002
[419]	train-mlogloss:1.83188	validation-mlogloss:1.81968
Saved model to disk.
2025-11-06 21:53:05.666432: 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 21:53:05.677914: 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 00:00:1762462385.691582 1833629 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462385.695622 1833629 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462385.705732 1833629 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462385.705749 1833629 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462385.705751 1833629 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462385.705752 1833629 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:53:05.708915: 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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[10]	train-mlogloss:2.62841	validation-mlogloss:2.62328
[11]	train-mlogloss:2.62205	validation-mlogloss:2.61670
[12]	train-mlogloss:2.61506	validation-mlogloss:2.60886
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[23]	train-mlogloss:2.54652	validation-mlogloss:2.53365
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[25]	train-mlogloss:2.53517	validation-mlogloss:2.52133
[26]	train-mlogloss:2.52957	validation-mlogloss:2.51519
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[35]	train-mlogloss:2.48062	validation-mlogloss:2.46085
[36]	train-mlogloss:2.47531	validation-mlogloss:2.45481
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[72]	train-mlogloss:2.32012	validation-mlogloss:2.28334
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[75]	train-mlogloss:2.30948	validation-mlogloss:2.27174
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[104]	train-mlogloss:2.22020	validation-mlogloss:2.17669
[105]	train-mlogloss:2.21740	validation-mlogloss:2.17369
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[113]	train-mlogloss:2.19571	validation-mlogloss:2.15026
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[418]	train-mlogloss:1.83269	validation-mlogloss:1.82063
[419]	train-mlogloss:1.83227	validation-mlogloss:1.82047
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.07 [%]
Global accuracy score (test) = 44.28 [%]
Global F1 score (train) = 43.62 [%]
Global F1 score (test) = 43.61 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.46      0.44       184
       CAMINAR USUAL SPEED       0.34      0.18      0.24       184
            CAMINAR ZIGZAG       0.31      0.52      0.39       184
          DE PIE BARRIENDO       0.70      0.40      0.51       184
   DE PIE DOBLANDO TOALLAS       0.46      0.45      0.45       184
    DE PIE MOVIENDO LIBROS       0.38      0.40      0.39       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.58      0.61       184
           SENTADO LEYENDO       0.46      0.39      0.42       184
         SENTADO USANDO PC       0.27      0.15      0.20       184
      SENTADO VIENDO LA TV       0.25      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.66      0.56      0.60       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.46      0.44      0.44      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 25: 44.28 [%]
F1-score capturado en la ejecución 25: 43.61 [%]

=== EJECUCIÓN 26 ===

--- TRAIN (ejecución 26) ---

--- TEST (ejecución 26) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.26 [%]
Global accuracy score (test) = 44.28 [%]
Global F1 score (train) = 43.77 [%]
Global F1 score (test) = 43.64 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.73      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.46      0.45       184
       CAMINAR USUAL SPEED       0.32      0.18      0.23       184
            CAMINAR ZIGZAG       0.31      0.51      0.38       184
          DE PIE BARRIENDO       0.68      0.41      0.51       184
   DE PIE DOBLANDO TOALLAS       0.47      0.44      0.45       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.38       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.66      0.58      0.62       184
           SENTADO LEYENDO       0.46      0.39      0.42       184
         SENTADO USANDO PC       0.29      0.15      0.20       184
      SENTADO VIENDO LA TV       0.25      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.66      0.56      0.61       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.46      0.44      0.44      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 26: 44.28 [%]
F1-score capturado en la ejecución 26: 43.64 [%]

=== EJECUCIÓN 27 ===

--- TRAIN (ejecución 27) ---

--- TEST (ejecución 27) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.13 [%]
Global accuracy score (test) = 44.46 [%]
Global F1 score (train) = 43.67 [%]
Global F1 score (test) = 43.65 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.43      0.44      0.43       184
       CAMINAR USUAL SPEED       0.35      0.18      0.24       184
            CAMINAR ZIGZAG       0.32      0.54      0.40       184
          DE PIE BARRIENDO       0.70      0.43      0.54       184
   DE PIE DOBLANDO TOALLAS       0.47      0.46      0.47       184
    DE PIE MOVIENDO LIBROS       0.37      0.38      0.37       184
          DE PIE USANDO PC       0.21      0.32      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.66      0.58      0.62       184
           SENTADO LEYENDO       0.46      0.40      0.43       184
         SENTADO USANDO PC       0.25      0.12      0.16       184
      SENTADO VIENDO LA TV       0.24      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.63      0.56      0.59       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.45      0.44      2737
              weighted avg       0.45      0.44      0.44      2737


Accuracy capturado en la ejecución 27: 44.46 [%]
F1-score capturado en la ejecución 27: 43.65 [%]

=== EJECUCIÓN 28 ===

--- TRAIN (ejecución 28) ---

--- TEST (ejecución 28) ---
2025-11-06 21:53:27.462727: 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 21:53:27.474423: 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 00:00:1762462407.487955 1833997 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462407.492044 1833997 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462407.502271 1833997 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462407.502291 1833997 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462407.502292 1833997 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462407.502293 1833997 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:53:27.505538: 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:2.70023	validation-mlogloss:2.69955
[1]	train-mlogloss:2.69261	validation-mlogloss:2.69142
[2]	train-mlogloss:2.68505	validation-mlogloss:2.68338
[3]	train-mlogloss:2.67689	validation-mlogloss:2.67473
[4]	train-mlogloss:2.66975	validation-mlogloss:2.66675
[5]	train-mlogloss:2.66261	validation-mlogloss:2.65904
[6]	train-mlogloss:2.65572	validation-mlogloss:2.65139
[7]	train-mlogloss:2.64867	validation-mlogloss:2.64367
[8]	train-mlogloss:2.64207	validation-mlogloss:2.63665
[9]	train-mlogloss:2.63495	validation-mlogloss:2.62871
[10]	train-mlogloss:2.62825	validation-mlogloss:2.62096
[11]	train-mlogloss:2.62123	validation-mlogloss:2.61340
[12]	train-mlogloss:2.61420	validation-mlogloss:2.60577
[13]	train-mlogloss:2.60747	validation-mlogloss:2.59840
[14]	train-mlogloss:2.60098	validation-mlogloss:2.59130
[15]	train-mlogloss:2.59453	validation-mlogloss:2.58445
[16]	train-mlogloss:2.58803	validation-mlogloss:2.57746
[17]	train-mlogloss:2.58160	validation-mlogloss:2.57050
[18]	train-mlogloss:2.57543	validation-mlogloss:2.56350
[19]	train-mlogloss:2.56912	validation-mlogloss:2.55670
[20]	train-mlogloss:2.56334	validation-mlogloss:2.55054
[21]	train-mlogloss:2.55711	validation-mlogloss:2.54365
[22]	train-mlogloss:2.55109	validation-mlogloss:2.53683
[23]	train-mlogloss:2.54554	validation-mlogloss:2.53096
[24]	train-mlogloss:2.53992	validation-mlogloss:2.52511
[25]	train-mlogloss:2.53408	validation-mlogloss:2.51879
[26]	train-mlogloss:2.52836	validation-mlogloss:2.51245
[27]	train-mlogloss:2.52276	validation-mlogloss:2.50639
[28]	train-mlogloss:2.51728	validation-mlogloss:2.50030
[29]	train-mlogloss:2.51187	validation-mlogloss:2.49415
[30]	train-mlogloss:2.50650	validation-mlogloss:2.48819
[31]	train-mlogloss:2.50118	validation-mlogloss:2.48249
[32]	train-mlogloss:2.49578	validation-mlogloss:2.47657
[33]	train-mlogloss:2.49061	validation-mlogloss:2.47087
[34]	train-mlogloss:2.48578	validation-mlogloss:2.46560
[35]	train-mlogloss:2.48061	validation-mlogloss:2.46008
[36]	train-mlogloss:2.47538	validation-mlogloss:2.45421
[37]	train-mlogloss:2.47038	validation-mlogloss:2.44860
[38]	train-mlogloss:2.46530	validation-mlogloss:2.44321
[39]	train-mlogloss:2.46060	validation-mlogloss:2.43828
[40]	train-mlogloss:2.45590	validation-mlogloss:2.43332
[41]	train-mlogloss:2.45109	validation-mlogloss:2.42806
[42]	train-mlogloss:2.44636	validation-mlogloss:2.42293
[43]	train-mlogloss:2.44130	validation-mlogloss:2.41715
[44]	train-mlogloss:2.43672	validation-mlogloss:2.41224
[45]	train-mlogloss:2.43212	validation-mlogloss:2.40728
[46]	train-mlogloss:2.42757	validation-mlogloss:2.40218
[47]	train-mlogloss:2.42284	validation-mlogloss:2.39687
[48]	train-mlogloss:2.41827	validation-mlogloss:2.39172
[49]	train-mlogloss:2.41374	validation-mlogloss:2.38670
[50]	train-mlogloss:2.40951	validation-mlogloss:2.38194
[51]	train-mlogloss:2.40513	validation-mlogloss:2.37717
[52]	train-mlogloss:2.40077	validation-mlogloss:2.37227
[53]	train-mlogloss:2.39634	validation-mlogloss:2.36743
[54]	train-mlogloss:2.39198	validation-mlogloss:2.36260
[55]	train-mlogloss:2.38787	validation-mlogloss:2.35824
[56]	train-mlogloss:2.38370	validation-mlogloss:2.35340
[57]	train-mlogloss:2.37952	validation-mlogloss:2.34891
[58]	train-mlogloss:2.37531	validation-mlogloss:2.34442
[59]	train-mlogloss:2.37102	validation-mlogloss:2.33977
[60]	train-mlogloss:2.36698	validation-mlogloss:2.33529
[61]	train-mlogloss:2.36283	validation-mlogloss:2.33051
[62]	train-mlogloss:2.35862	validation-mlogloss:2.32569
[63]	train-mlogloss:2.35464	validation-mlogloss:2.32141
[64]	train-mlogloss:2.35090	validation-mlogloss:2.31747
[65]	train-mlogloss:2.34711	validation-mlogloss:2.31338
[66]	train-mlogloss:2.34309	validation-mlogloss:2.30912
[67]	train-mlogloss:2.33920	validation-mlogloss:2.30482
[68]	train-mlogloss:2.33529	validation-mlogloss:2.30036
[69]	train-mlogloss:2.33134	validation-mlogloss:2.29604
[70]	train-mlogloss:2.32764	validation-mlogloss:2.29184
[71]	train-mlogloss:2.32383	validation-mlogloss:2.28791
[72]	train-mlogloss:2.32006	validation-mlogloss:2.28360
[73]	train-mlogloss:2.31643	validation-mlogloss:2.27945
[74]	train-mlogloss:2.31253	validation-mlogloss:2.27511
[75]	train-mlogloss:2.30901	validation-mlogloss:2.27136
[76]	train-mlogloss:2.30525	validation-mlogloss:2.26707
[77]	train-mlogloss:2.30185	validation-mlogloss:2.26343
[78]	train-mlogloss:2.29840	validation-mlogloss:2.25976
[79]	train-mlogloss:2.29490	validation-mlogloss:2.25570
[80]	train-mlogloss:2.29162	validation-mlogloss:2.25211
[81]	train-mlogloss:2.28821	validation-mlogloss:2.24851
[82]	train-mlogloss:2.28502	validation-mlogloss:2.24541
[83]	train-mlogloss:2.28188	validation-mlogloss:2.24208
[84]	train-mlogloss:2.27879	validation-mlogloss:2.23890
[85]	train-mlogloss:2.27552	validation-mlogloss:2.23532
[86]	train-mlogloss:2.27250	validation-mlogloss:2.23230
[87]	train-mlogloss:2.26928	validation-mlogloss:2.22900
[88]	train-mlogloss:2.26598	validation-mlogloss:2.22537
[89]	train-mlogloss:2.26290	validation-mlogloss:2.22187
[90]	train-mlogloss:2.25970	validation-mlogloss:2.21839
[91]	train-mlogloss:2.25656	validation-mlogloss:2.21524
[92]	train-mlogloss:2.25353	validation-mlogloss:2.21202
[93]	train-mlogloss:2.25066	validation-mlogloss:2.20903
[94]	train-mlogloss:2.24753	validation-mlogloss:2.20542
[95]	train-mlogloss:2.24442	validation-mlogloss:2.20186
[96]	train-mlogloss:2.24153	validation-mlogloss:2.19876
[97]	train-mlogloss:2.23849	validation-mlogloss:2.19530
[98]	train-mlogloss:2.23557	validation-mlogloss:2.19236
[99]	train-mlogloss:2.23257	validation-mlogloss:2.18917
[100]	train-mlogloss:2.22969	validation-mlogloss:2.18625
[101]	train-mlogloss:2.22701	validation-mlogloss:2.18348
[102]	train-mlogloss:2.22432	validation-mlogloss:2.18064
[103]	train-mlogloss:2.22166	validation-mlogloss:2.17796
[104]	train-mlogloss:2.21894	validation-mlogloss:2.17513
[105]	train-mlogloss:2.21612	validation-mlogloss:2.17184
[106]	train-mlogloss:2.21331	validation-mlogloss:2.16875
[107]	train-mlogloss:2.21068	validation-mlogloss:2.16585
[108]	train-mlogloss:2.20798	validation-mlogloss:2.16298
[109]	train-mlogloss:2.20525	validation-mlogloss:2.16018
[110]	train-mlogloss:2.20257	validation-mlogloss:2.15749
[111]	train-mlogloss:2.19987	validation-mlogloss:2.15468
[112]	train-mlogloss:2.19736	validation-mlogloss:2.15230
[113]	train-mlogloss:2.19472	validation-mlogloss:2.14957
[114]	train-mlogloss:2.19231	validation-mlogloss:2.14724
[115]	train-mlogloss:2.18982	validation-mlogloss:2.14452
[116]	train-mlogloss:2.18733	validation-mlogloss:2.14210
[117]	train-mlogloss:2.18496	validation-mlogloss:2.13979
[118]	train-mlogloss:2.18248	validation-mlogloss:2.13729
[119]	train-mlogloss:2.18017	validation-mlogloss:2.13494
[120]	train-mlogloss:2.17782	validation-mlogloss:2.13246
[121]	train-mlogloss:2.17558	validation-mlogloss:2.13017
[122]	train-mlogloss:2.17335	validation-mlogloss:2.12794
[123]	train-mlogloss:2.17089	validation-mlogloss:2.12541
[124]	train-mlogloss:2.16870	validation-mlogloss:2.12334
[125]	train-mlogloss:2.16634	validation-mlogloss:2.12091
[126]	train-mlogloss:2.16393	validation-mlogloss:2.11847
[127]	train-mlogloss:2.16159	validation-mlogloss:2.11606
[128]	train-mlogloss:2.15943	validation-mlogloss:2.11405
[129]	train-mlogloss:2.15706	validation-mlogloss:2.11146
[130]	train-mlogloss:2.15496	validation-mlogloss:2.10958
[131]	train-mlogloss:2.15259	validation-mlogloss:2.10685
[132]	train-mlogloss:2.15046	validation-mlogloss:2.10475
[133]	train-mlogloss:2.14824	validation-mlogloss:2.10243
[134]	train-mlogloss:2.14595	validation-mlogloss:2.10021
[135]	train-mlogloss:2.14365	validation-mlogloss:2.09783
[136]	train-mlogloss:2.14159	validation-mlogloss:2.09568
[137]	train-mlogloss:2.13946	validation-mlogloss:2.09342
[138]	train-mlogloss:2.13730	validation-mlogloss:2.09123
[139]	train-mlogloss:2.13530	validation-mlogloss:2.08919
[140]	train-mlogloss:2.13319	validation-mlogloss:2.08689
[141]	train-mlogloss:2.13108	validation-mlogloss:2.08473
[142]	train-mlogloss:2.12893	validation-mlogloss:2.08236
[143]	train-mlogloss:2.12669	validation-mlogloss:2.08000
[144]	train-mlogloss:2.12447	validation-mlogloss:2.07787
[145]	train-mlogloss:2.12248	validation-mlogloss:2.07597
[146]	train-mlogloss:2.12060	validation-mlogloss:2.07407
[147]	train-mlogloss:2.11865	validation-mlogloss:2.07205
[148]	train-mlogloss:2.11671	validation-mlogloss:2.07001
[149]	train-mlogloss:2.11462	validation-mlogloss:2.06785
[150]	train-mlogloss:2.11258	validation-mlogloss:2.06560
[151]	train-mlogloss:2.11055	validation-mlogloss:2.06362
[152]	train-mlogloss:2.10858	validation-mlogloss:2.06149
[153]	train-mlogloss:2.10659	validation-mlogloss:2.05966
[154]	train-mlogloss:2.10464	validation-mlogloss:2.05765
[155]	train-mlogloss:2.10266	validation-mlogloss:2.05558
[156]	train-mlogloss:2.10066	validation-mlogloss:2.05362
[157]	train-mlogloss:2.09884	validation-mlogloss:2.05195
[158]	train-mlogloss:2.09695	validation-mlogloss:2.04990
[159]	train-mlogloss:2.09500	validation-mlogloss:2.04806
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[270]	train-mlogloss:1.94297	validation-mlogloss:1.90645
[271]	train-mlogloss:1.94201	validation-mlogloss:1.90547
[272]	train-mlogloss:1.94098	validation-mlogloss:1.90457
[273]	train-mlogloss:1.93994	validation-mlogloss:1.90374
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[293]	train-mlogloss:1.92029	validation-mlogloss:1.88672
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[389]	train-mlogloss:1.84791	validation-mlogloss:1.83277
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[391]	train-mlogloss:1.84672	validation-mlogloss:1.83196
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[393]	train-mlogloss:1.84555	validation-mlogloss:1.83129
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[395]	train-mlogloss:1.84439	validation-mlogloss:1.83060
[396]	train-mlogloss:1.84387	validation-mlogloss:1.83024
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[398]	train-mlogloss:1.84274	validation-mlogloss:1.82957
[399]	train-mlogloss:1.84214	validation-mlogloss:1.82911
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[401]	train-mlogloss:1.84113	validation-mlogloss:1.82857
[402]	train-mlogloss:1.84068	validation-mlogloss:1.82822
[403]	train-mlogloss:1.84011	validation-mlogloss:1.82791
[404]	train-mlogloss:1.83957	validation-mlogloss:1.82764
[405]	train-mlogloss:1.83905	validation-mlogloss:1.82722
[406]	train-mlogloss:1.83854	validation-mlogloss:1.82679
[407]	train-mlogloss:1.83793	validation-mlogloss:1.82637
[408]	train-mlogloss:1.83749	validation-mlogloss:1.82597
[409]	train-mlogloss:1.83692	validation-mlogloss:1.82565
[410]	train-mlogloss:1.83633	validation-mlogloss:1.82519
[411]	train-mlogloss:1.83573	validation-mlogloss:1.82459
[412]	train-mlogloss:1.83519	validation-mlogloss:1.82426
[413]	train-mlogloss:1.83464	validation-mlogloss:1.82387
[414]	train-mlogloss:1.83421	validation-mlogloss:1.82354
[415]	train-mlogloss:1.83380	validation-mlogloss:1.82315
[416]	train-mlogloss:1.83337	validation-mlogloss:1.82295
[417]	train-mlogloss:1.83291	validation-mlogloss:1.82265
[418]	train-mlogloss:1.83240	validation-mlogloss:1.82226
[419]	train-mlogloss:1.83186	validation-mlogloss:1.82182
Saved model to disk.
2025-11-06 21:53:49.575746: 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 21:53:49.587144: 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 00:00:1762462429.601133 1834388 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762462429.605364 1834388 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762462429.616056 1834388 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462429.616074 1834388 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462429.616076 1834388 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762462429.616085 1834388 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 21:53:49.619414: 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:2.70048	validation-mlogloss:2.69965
[1]	train-mlogloss:2.69285	validation-mlogloss:2.69155
[2]	train-mlogloss:2.68540	validation-mlogloss:2.68354
[3]	train-mlogloss:2.67802	validation-mlogloss:2.67575
[4]	train-mlogloss:2.67030	validation-mlogloss:2.66746
[5]	train-mlogloss:2.66271	validation-mlogloss:2.65921
[6]	train-mlogloss:2.65579	validation-mlogloss:2.65168
[7]	train-mlogloss:2.64857	validation-mlogloss:2.64402
[8]	train-mlogloss:2.64165	validation-mlogloss:2.63648
[9]	train-mlogloss:2.63517	validation-mlogloss:2.62958
[10]	train-mlogloss:2.62806	validation-mlogloss:2.62162
[11]	train-mlogloss:2.62151	validation-mlogloss:2.61450
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[312]	train-mlogloss:1.90245	validation-mlogloss:1.87297
[313]	train-mlogloss:1.90160	validation-mlogloss:1.87219
[314]	train-mlogloss:1.90082	validation-mlogloss:1.87159
[315]	train-mlogloss:1.89990	validation-mlogloss:1.87072
[316]	train-mlogloss:1.89905	validation-mlogloss:1.87017
[317]	train-mlogloss:1.89828	validation-mlogloss:1.86941
[318]	train-mlogloss:1.89750	validation-mlogloss:1.86872
[319]	train-mlogloss:1.89661	validation-mlogloss:1.86794
[320]	train-mlogloss:1.89574	validation-mlogloss:1.86720
[321]	train-mlogloss:1.89492	validation-mlogloss:1.86676
[322]	train-mlogloss:1.89413	validation-mlogloss:1.86614
[323]	train-mlogloss:1.89325	validation-mlogloss:1.86530
[324]	train-mlogloss:1.89241	validation-mlogloss:1.86460
[325]	train-mlogloss:1.89149	validation-mlogloss:1.86394
[326]	train-mlogloss:1.89066	validation-mlogloss:1.86345
[327]	train-mlogloss:1.88988	validation-mlogloss:1.86296
[328]	train-mlogloss:1.88915	validation-mlogloss:1.86246
[329]	train-mlogloss:1.88839	validation-mlogloss:1.86176
[330]	train-mlogloss:1.88758	validation-mlogloss:1.86109
[331]	train-mlogloss:1.88684	validation-mlogloss:1.86066
[332]	train-mlogloss:1.88611	validation-mlogloss:1.86007
[333]	train-mlogloss:1.88538	validation-mlogloss:1.85964
[334]	train-mlogloss:1.88463	validation-mlogloss:1.85923
[335]	train-mlogloss:1.88383	validation-mlogloss:1.85871
[336]	train-mlogloss:1.88303	validation-mlogloss:1.85812
[337]	train-mlogloss:1.88223	validation-mlogloss:1.85746
[338]	train-mlogloss:1.88151	validation-mlogloss:1.85694
[339]	train-mlogloss:1.88073	validation-mlogloss:1.85622
[340]	train-mlogloss:1.87999	validation-mlogloss:1.85563
[341]	train-mlogloss:1.87918	validation-mlogloss:1.85500
[342]	train-mlogloss:1.87849	validation-mlogloss:1.85432
[343]	train-mlogloss:1.87776	validation-mlogloss:1.85393
[344]	train-mlogloss:1.87704	validation-mlogloss:1.85334
[345]	train-mlogloss:1.87634	validation-mlogloss:1.85285
[346]	train-mlogloss:1.87564	validation-mlogloss:1.85233
[347]	train-mlogloss:1.87491	validation-mlogloss:1.85177
[348]	train-mlogloss:1.87422	validation-mlogloss:1.85119
[349]	train-mlogloss:1.87356	validation-mlogloss:1.85086
[350]	train-mlogloss:1.87285	validation-mlogloss:1.85040
[351]	train-mlogloss:1.87208	validation-mlogloss:1.84984
[352]	train-mlogloss:1.87140	validation-mlogloss:1.84930
[353]	train-mlogloss:1.87066	validation-mlogloss:1.84864
[354]	train-mlogloss:1.86997	validation-mlogloss:1.84799
[355]	train-mlogloss:1.86923	validation-mlogloss:1.84747
[356]	train-mlogloss:1.86848	validation-mlogloss:1.84696
[357]	train-mlogloss:1.86791	validation-mlogloss:1.84648
[358]	train-mlogloss:1.86730	validation-mlogloss:1.84617
[359]	train-mlogloss:1.86665	validation-mlogloss:1.84578
[360]	train-mlogloss:1.86600	validation-mlogloss:1.84533
[361]	train-mlogloss:1.86541	validation-mlogloss:1.84489
[362]	train-mlogloss:1.86475	validation-mlogloss:1.84434
[363]	train-mlogloss:1.86404	validation-mlogloss:1.84378
[364]	train-mlogloss:1.86344	validation-mlogloss:1.84329
[365]	train-mlogloss:1.86274	validation-mlogloss:1.84277
[366]	train-mlogloss:1.86214	validation-mlogloss:1.84238
[367]	train-mlogloss:1.86149	validation-mlogloss:1.84186
[368]	train-mlogloss:1.86090	validation-mlogloss:1.84145
[369]	train-mlogloss:1.86024	validation-mlogloss:1.84095
[370]	train-mlogloss:1.85960	validation-mlogloss:1.84053
[371]	train-mlogloss:1.85887	validation-mlogloss:1.84002
[372]	train-mlogloss:1.85819	validation-mlogloss:1.83952
[373]	train-mlogloss:1.85759	validation-mlogloss:1.83896
[374]	train-mlogloss:1.85693	validation-mlogloss:1.83833
[375]	train-mlogloss:1.85628	validation-mlogloss:1.83798
[376]	train-mlogloss:1.85568	validation-mlogloss:1.83748
[377]	train-mlogloss:1.85511	validation-mlogloss:1.83703
[378]	train-mlogloss:1.85448	validation-mlogloss:1.83639
[379]	train-mlogloss:1.85380	validation-mlogloss:1.83594
[380]	train-mlogloss:1.85316	validation-mlogloss:1.83553
[381]	train-mlogloss:1.85253	validation-mlogloss:1.83513
[382]	train-mlogloss:1.85189	validation-mlogloss:1.83475
[383]	train-mlogloss:1.85133	validation-mlogloss:1.83431
[384]	train-mlogloss:1.85075	validation-mlogloss:1.83399
[385]	train-mlogloss:1.85016	validation-mlogloss:1.83352
[386]	train-mlogloss:1.84960	validation-mlogloss:1.83311
[387]	train-mlogloss:1.84898	validation-mlogloss:1.83259
[388]	train-mlogloss:1.84839	validation-mlogloss:1.83211
[389]	train-mlogloss:1.84783	validation-mlogloss:1.83180
[390]	train-mlogloss:1.84715	validation-mlogloss:1.83133
[391]	train-mlogloss:1.84665	validation-mlogloss:1.83093
[392]	train-mlogloss:1.84606	validation-mlogloss:1.83036
[393]	train-mlogloss:1.84548	validation-mlogloss:1.82995
[394]	train-mlogloss:1.84490	validation-mlogloss:1.82964
[395]	train-mlogloss:1.84430	validation-mlogloss:1.82941
[396]	train-mlogloss:1.84375	validation-mlogloss:1.82922
[397]	train-mlogloss:1.84309	validation-mlogloss:1.82874
[398]	train-mlogloss:1.84253	validation-mlogloss:1.82840
[399]	train-mlogloss:1.84192	validation-mlogloss:1.82809
[400]	train-mlogloss:1.84134	validation-mlogloss:1.82774
[401]	train-mlogloss:1.84077	validation-mlogloss:1.82740
[402]	train-mlogloss:1.84026	validation-mlogloss:1.82713
[403]	train-mlogloss:1.83968	validation-mlogloss:1.82687
[404]	train-mlogloss:1.83910	validation-mlogloss:1.82666
[405]	train-mlogloss:1.83856	validation-mlogloss:1.82630
[406]	train-mlogloss:1.83810	validation-mlogloss:1.82587
[407]	train-mlogloss:1.83760	validation-mlogloss:1.82545
[408]	train-mlogloss:1.83699	validation-mlogloss:1.82500
[409]	train-mlogloss:1.83642	validation-mlogloss:1.82446
[410]	train-mlogloss:1.83589	validation-mlogloss:1.82414
[411]	train-mlogloss:1.83532	validation-mlogloss:1.82371
[412]	train-mlogloss:1.83483	validation-mlogloss:1.82329
[413]	train-mlogloss:1.83429	validation-mlogloss:1.82282
[414]	train-mlogloss:1.83374	validation-mlogloss:1.82237
[415]	train-mlogloss:1.83319	validation-mlogloss:1.82199
[416]	train-mlogloss:1.83259	validation-mlogloss:1.82156
[417]	train-mlogloss:1.83213	validation-mlogloss:1.82120
[418]	train-mlogloss:1.83158	validation-mlogloss:1.82077
[419]	train-mlogloss:1.83103	validation-mlogloss:1.82037
Saved model to disk.
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.24 [%]
Global accuracy score (test) = 44.32 [%]
Global F1 score (train) = 43.77 [%]
Global F1 score (test) = 43.56 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.49      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.46      0.45       184
       CAMINAR USUAL SPEED       0.36      0.19      0.25       184
            CAMINAR ZIGZAG       0.32      0.55      0.40       184
          DE PIE BARRIENDO       0.70      0.41      0.52       184
   DE PIE DOBLANDO TOALLAS       0.44      0.43      0.44       184
    DE PIE MOVIENDO LIBROS       0.38      0.39      0.39       184
          DE PIE USANDO PC       0.20      0.31      0.24       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.65      0.58      0.61       184
           SENTADO LEYENDO       0.45      0.39      0.42       184
         SENTADO USANDO PC       0.26      0.13      0.17       184
      SENTADO VIENDO LA TV       0.24      0.15      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.62      0.56      0.59       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.44      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 28: 44.32 [%]
F1-score capturado en la ejecución 28: 43.56 [%]

=== EJECUCIÓN 29 ===

--- TRAIN (ejecución 29) ---

--- TEST (ejecución 29) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.01 [%]
Global accuracy score (test) = 44.06 [%]
Global F1 score (train) = 43.57 [%]
Global F1 score (test) = 43.22 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.72      0.56       184
 CAMINAR CON MÓVIL O LIBRO       0.44      0.46      0.45       184
       CAMINAR USUAL SPEED       0.36      0.17      0.23       184
            CAMINAR ZIGZAG       0.31      0.53      0.39       184
          DE PIE BARRIENDO       0.69      0.41      0.51       184
   DE PIE DOBLANDO TOALLAS       0.45      0.45      0.45       184
    DE PIE MOVIENDO LIBROS       0.38      0.40      0.39       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.56      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.64      0.58      0.61       184
           SENTADO LEYENDO       0.46      0.39      0.42       184
         SENTADO USANDO PC       0.20      0.10      0.13       184
      SENTADO VIENDO LA TV       0.25      0.16      0.20       184
   SUBIR Y BAJAR ESCALERAS       0.67      0.55      0.61       184
                    TROTAR       0.65      0.55      0.60       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 29: 44.06 [%]
F1-score capturado en la ejecución 29: 43.22 [%]

=== EJECUCIÓN 30 ===

--- TRAIN (ejecución 30) ---

--- TEST (ejecución 30) ---
['CAMINAR CON LA COMPRA' 'CAMINAR CON MÓVIL O LIBRO' 'CAMINAR USUAL SPEED'
 'CAMINAR ZIGZAG' 'DE PIE BARRIENDO' 'DE PIE DOBLANDO TOALLAS'
 'DE PIE MOVIENDO LIBROS' 'DE PIE USANDO PC' 'FASE REPOSO CON K5'
 'INCREMENTAL CICLOERGOMETRO' 'SENTADO LEYENDO' 'SENTADO USANDO PC'
 'SENTADO VIENDO LA TV' 'SUBIR Y BAJAR ESCALERAS' 'TROTAR']
15
Mapeo de etiquetas: {'CAMINAR CON LA COMPRA': 0, 'CAMINAR CON MÓVIL O LIBRO': 1, 'CAMINAR USUAL SPEED': 2, 'CAMINAR ZIGZAG': 3, 'DE PIE BARRIENDO': 4, 'DE PIE DOBLANDO TOALLAS': 5, 'DE PIE MOVIENDO LIBROS': 6, 'DE PIE USANDO PC': 7, 'FASE REPOSO CON K5': 8, 'INCREMENTAL CICLOERGOMETRO': 9, 'SENTADO LEYENDO': 10, 'SENTADO USANDO PC': 11, 'SENTADO VIENDO LA TV': 12, 'SUBIR Y BAJAR ESCALERAS': 13, 'TROTAR': 14}
Training a non-convolutional model.
Loaded model from disk.
(2737, 42)
(18469, 42)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 44.22 [%]
Global accuracy score (test) = 44.17 [%]
Global F1 score (train) = 43.76 [%]
Global F1 score (test) = 43.36 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.73      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.45      0.46      0.45       184
       CAMINAR USUAL SPEED       0.34      0.16      0.22       184
            CAMINAR ZIGZAG       0.31      0.53      0.39       184
          DE PIE BARRIENDO       0.69      0.41      0.52       184
   DE PIE DOBLANDO TOALLAS       0.45      0.44      0.45       184
    DE PIE MOVIENDO LIBROS       0.37      0.39      0.38       184
          DE PIE USANDO PC       0.20      0.30      0.24       184
        FASE REPOSO CON K5       0.57      0.83      0.67       184
INCREMENTAL CICLOERGOMETRO       0.64      0.57      0.61       184
           SENTADO LEYENDO       0.45      0.39      0.42       184
         SENTADO USANDO PC       0.28      0.15      0.19       184
      SENTADO VIENDO LA TV       0.25      0.16      0.19       184
   SUBIR Y BAJAR ESCALERAS       0.61      0.56      0.59       184
                    TROTAR       0.67      0.55      0.61       161

                  accuracy                           0.44      2737
                 macro avg       0.45      0.44      0.43      2737
              weighted avg       0.45      0.44      0.43      2737


Accuracy capturado en la ejecución 30: 44.17 [%]
F1-score capturado en la ejecución 30: 43.36 [%]

=== RESUMEN FINAL ===
Accuracies: [44.14, 44.25, 44.06, 44.43, 44.36, 44.5, 44.06, 44.14, 44.36, 43.92, 44.14, 44.28, 44.36, 44.14, 43.55, 44.36, 44.39, 44.43, 44.14, 44.5, 44.25, 43.73, 44.06, 44.21, 44.28, 44.28, 44.46, 44.32, 44.06, 44.17]
F1-scores: [43.28, 43.38, 43.39, 43.77, 43.55, 43.76, 43.26, 43.34, 43.6, 43.04, 43.42, 43.5, 43.5, 43.38, 42.61, 43.59, 43.67, 43.74, 43.32, 43.77, 43.44, 42.84, 43.28, 43.42, 43.61, 43.64, 43.65, 43.56, 43.22, 43.36]
Accuracy mean: 44.2110 | std: 0.2118
F1 mean: 43.4297 | std: 0.2606

Resultados guardados en /mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_M/case_M_XGB_acc_17_classes/metrics_test.npz
