2025-10-27 09:33:56.557815: 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`.
2025-10-27 09:33:56.570913: 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 00:00:1761554036.585613  396970 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554036.590153  396970 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554036.601676  396970 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554036.601701  396970 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554036.601705  396970 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554036.601707  396970 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:33:56.605176: 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(
2025-10-27 09:34:14,649	INFO worker.py:1927 -- Started a local Ray instance.
2025-10-27 09:34:15,338	INFO tune.py:253 -- Initializing Ray automatically. For cluster usage or custom Ray initialization, call `ray.init(...)` before `Tuner(...)`.
2025-10-27 09:34:15,409	INFO trial.py:182 -- Creating a new dirname dir_b8b81_5db3 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,413	INFO trial.py:182 -- Creating a new dirname dir_b8b81_a650 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,415	INFO trial.py:182 -- Creating a new dirname dir_b8b81_e396 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,418	INFO trial.py:182 -- Creating a new dirname dir_b8b81_4972 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,420	INFO trial.py:182 -- Creating a new dirname dir_b8b81_239b because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,422	INFO trial.py:182 -- Creating a new dirname dir_b8b81_4e78 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,425	INFO trial.py:182 -- Creating a new dirname dir_b8b81_aaa5 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,427	INFO trial.py:182 -- Creating a new dirname dir_b8b81_ae8b because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,430	INFO trial.py:182 -- Creating a new dirname dir_b8b81_a8a1 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,432	INFO trial.py:182 -- Creating a new dirname dir_b8b81_0e19 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,434	INFO trial.py:182 -- Creating a new dirname dir_b8b81_6654 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,437	INFO trial.py:182 -- Creating a new dirname dir_b8b81_3915 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,439	INFO trial.py:182 -- Creating a new dirname dir_b8b81_90c5 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,443	INFO trial.py:182 -- Creating a new dirname dir_b8b81_95f5 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,446	INFO trial.py:182 -- Creating a new dirname dir_b8b81_f451 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,449	INFO trial.py:182 -- Creating a new dirname dir_b8b81_d939 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,452	INFO trial.py:182 -- Creating a new dirname dir_b8b81_0ffa because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,456	INFO trial.py:182 -- Creating a new dirname dir_b8b81_8749 because trial dirname 'dir_b8b81' already exists.
2025-10-27 09:34:15,460	INFO trial.py:182 -- Creating a new dirname dir_b8b81_c3dc because trial dirname 'dir_b8b81' 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_gyr_17_classes/XGBoost_hyperparameters_tuning
To visualize your results with TensorBoard, run: `tensorboard --logdir /tmp/ray/session_2025-10-27_09-34-12_925023_396970/artifacts/2025-10-27_09-34-15/XGBoost_hyperparameters_tuning/driver_artifacts`

Trial status: 20 PENDING
Current time: 2025-10-27 09:34:15. 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_b8b81    PENDING                  785             2        0.0152561       0.333235             0.509718   5.36058                   59      1.72191        0.791369             8764 │
│ trial_b8b81    PENDING                  436             2        0.0151967       0.687426             0.508211   3.6508                    32      0.236551       2.80111                23 │
│ trial_b8b81    PENDING                  540             2        0.0154571       0.498324             0.399232   7.5555                    57      0.518023       1.37493              3189 │
│ trial_b8b81    PENDING                  353             2        0.00577946      0.588048             0.300442   8.55953                   34      5.80421        0.579503             5130 │
│ trial_b8b81    PENDING                  677             2        0.00718957      0.347983             0.517791   6.43243                   12      0.249615       2.3729               3650 │
│ trial_b8b81    PENDING                  347             2        0.00373864      0.624615             0.491362   7.40223                   33      0.177621      15.6491               4377 │
│ trial_b8b81    PENDING                  749             2        0.00684262      0.511093             0.642296   2.23501                   26      2.59404        5.58484              8397 │
│ trial_b8b81    PENDING                  550             2        0.0146521       0.333218             0.403476   8.58164                   12      8.33367       54.5003               6890 │
│ trial_b8b81    PENDING                  789             2        0.00862436      0.519278             0.453361   7.20008                   21      1.57911        3.85557               985 │
│ trial_b8b81    PENDING                  416             2        0.00418167      0.347849             0.419215   6.11886                   39      1.02586        0.871116             4157 │
│ trial_b8b81    PENDING                  737             2        0.0033156       0.459322             0.608053   3.18821                   28     93.719          1.30518              5776 │
│ trial_b8b81    PENDING                  650             2        0.00313347      0.693701             0.492938   9.79394                   12      1.55806        6.0203               5382 │
│ trial_b8b81    PENDING                  860             2        0.0136591       0.502887             0.62787    4.03237                   37     28.4997        51.4794               8253 │
│ trial_b8b81    PENDING                  500             2        0.0168463       0.316536             0.311578   7.53857                   21     25.6984         1.41457              2854 │
│ trial_b8b81    PENDING                  528             2        0.00285688      0.536565             0.651463   5.278                     25      2.19742        2.87126               507 │
│ trial_b8b81    PENDING                  319             2        0.0172683       0.44677              0.688075   6.64719                   21      1.24884       27.0934               5802 │
│ trial_b8b81    PENDING                  783             2        0.0197427       0.306766             0.67443    7.59557                   58     66.8206        16.8769               7467 │
│ trial_b8b81    PENDING                  725             2        0.0143453       0.659911             0.418968   3.84157                   53      0.163473      19.04                 9244 │
│ trial_b8b81    PENDING                  601             2        0.0132953       0.653242             0.585449   3.87352                   49      4.74374       97.5749               9239 │
│ trial_b8b81    PENDING                  871             2        0.0139431       0.314738             0.444055   8.48731                   42      0.988245      70.352                9194 │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.39923 │
│ gamma                         7.5555 │
│ learning_rate                0.01546 │
│ max_depth                          2 │
│ min_child_weight                  57 │
│ num_boost_round                  540 │
│ random_state                    3189 │
│ reg_alpha                    0.51802 │
│ reg_lambda                   1.37493 │
│ subsample                    0.49832 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.30044 │
│ gamma                        8.55953 │
│ learning_rate                0.00578 │
│ max_depth                          2 │
│ min_child_weight                  34 │
│ num_boost_round                  353 │
│ random_state                    5130 │
│ reg_alpha                    5.80421 │
│ reg_lambda                    0.5795 │
│ subsample                    0.58805 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.41922 │
│ gamma                        6.11886 │
│ learning_rate                0.00418 │
│ max_depth                          2 │
│ min_child_weight                  39 │
│ num_boost_round                  416 │
│ random_state                    4157 │
│ reg_alpha                    1.02586 │
│ reg_lambda                   0.87112 │
│ subsample                    0.34785 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.40348 │
│ gamma                        8.58164 │
│ learning_rate                0.01465 │
│ max_depth                          2 │
│ min_child_weight                  12 │
│ num_boost_round                  550 │
│ random_state                    6890 │
│ reg_alpha                    8.33367 │
│ reg_lambda                   54.5003 │
│ subsample                    0.33322 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.51779 │
│ gamma                        6.43243 │
│ learning_rate                0.00719 │
│ max_depth                          2 │
│ min_child_weight                  12 │
│ num_boost_round                  677 │
│ random_state                    3650 │
│ reg_alpha                    0.24961 │
│ reg_lambda                    2.3729 │
│ subsample                    0.34798 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.62787 │
│ gamma                        4.03237 │
│ learning_rate                0.01366 │
│ max_depth                          2 │
│ min_child_weight                  37 │
│ num_boost_round                  860 │
│ random_state                    8253 │
│ reg_alpha                    28.4997 │
│ reg_lambda                   51.4794 │
│ subsample                    0.50289 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.50972 │
│ gamma                        5.36058 │
│ learning_rate                0.01526 │
│ max_depth                          2 │
│ min_child_weight                  59 │
│ num_boost_round                  785 │
│ random_state                    8764 │
│ reg_alpha                    1.72191 │
│ reg_lambda                   0.79137 │
│ subsample                    0.33324 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.67443 │
│ gamma                        7.59557 │
│ learning_rate                0.01974 │
│ max_depth                          2 │
│ min_child_weight                  58 │
│ num_boost_round                  783 │
│ random_state                    7467 │
│ reg_alpha                    66.8206 │
│ reg_lambda                   16.8769 │
│ subsample                    0.30677 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.58545 │
│ gamma                        3.87352 │
│ learning_rate                 0.0133 │
│ max_depth                          2 │
│ min_child_weight                  49 │
│ num_boost_round                  601 │
│ random_state                    9239 │
│ reg_alpha                    4.74374 │
│ reg_lambda                   97.5749 │
│ subsample                    0.65324 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.49294 │
│ gamma                        9.79394 │
│ learning_rate                0.00313 │
│ max_depth                          2 │
│ min_child_weight                  12 │
│ num_boost_round                  650 │
│ random_state                    5382 │
│ reg_alpha                    1.55806 │
│ reg_lambda                    6.0203 │
│ subsample                     0.6937 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree              0.6423 │
│ gamma                        2.23501 │
│ learning_rate                0.00684 │
│ max_depth                          2 │
│ min_child_weight                  26 │
│ num_boost_round                  749 │
│ random_state                    8397 │
│ reg_alpha                    2.59404 │
│ reg_lambda                   5.58484 │
│ subsample                    0.51109 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.60805 │
│ gamma                        3.18821 │
│ learning_rate                0.00332 │
│ max_depth                          2 │
│ min_child_weight                  28 │
│ num_boost_round                  737 │
│ random_state                    5776 │
│ reg_alpha                     93.719 │
│ reg_lambda                   1.30518 │
│ subsample                    0.45932 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.65146 │
│ gamma                          5.278 │
│ learning_rate                0.00286 │
│ max_depth                          2 │
│ min_child_weight                  25 │
│ num_boost_round                  528 │
│ random_state                     507 │
│ reg_alpha                    2.19742 │
│ reg_lambda                   2.87126 │
│ subsample                    0.53657 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.44405 │
│ gamma                        8.48731 │
│ learning_rate                0.01394 │
│ max_depth                          2 │
│ min_child_weight                  42 │
│ num_boost_round                  871 │
│ random_state                    9194 │
│ reg_alpha                    0.98825 │
│ reg_lambda                    70.352 │
│ subsample                    0.31474 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.50821 │
│ gamma                         3.6508 │
│ learning_rate                 0.0152 │
│ max_depth                          2 │
│ min_child_weight                  32 │
│ num_boost_round                  436 │
│ random_state                      23 │
│ reg_alpha                    0.23655 │
│ reg_lambda                   2.80111 │
│ subsample                    0.68743 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.31158 │
│ gamma                        7.53857 │
│ learning_rate                0.01685 │
│ max_depth                          2 │
│ min_child_weight                  21 │
│ num_boost_round                  500 │
│ random_state                    2854 │
│ reg_alpha                    25.6984 │
│ reg_lambda                   1.41457 │
│ subsample                    0.31654 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.49136 │
│ gamma                        7.40223 │
│ learning_rate                0.00374 │
│ max_depth                          2 │
│ min_child_weight                  33 │
│ num_boost_round                  347 │
│ random_state                    4377 │
│ reg_alpha                    0.17762 │
│ reg_lambda                   15.6491 │
│ subsample                    0.62461 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.68807 │
│ gamma                        6.64719 │
│ learning_rate                0.01727 │
│ max_depth                          2 │
│ min_child_weight                  21 │
│ num_boost_round                  319 │
│ random_state                    5802 │
│ reg_alpha                    1.24884 │
│ reg_lambda                   27.0934 │
│ subsample                    0.44677 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
[36m(train_xgb_ray_tune pid=398880)[0m 2025-10-27 09:34:18.442434: 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=398880)[0m 2025-10-27 09:34:18.467505: 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=398880)[0m WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
[36m(train_xgb_ray_tune pid=398880)[0m E0000 00:00:1761554058.493825  400044 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=398880)[0m E0000 00:00:1761554058.501757  400044 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=398880)[0m W0000 00:00:1761554058.522270  400044 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=398880)[0m W0000 00:00:1761554058.522310  400044 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=398880)[0m W0000 00:00:1761554058.522313  400044 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=398880)[0m W0000 00:00:1761554058.522315  400044 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=398880)[0m 2025-10-27 09:34:18.528325: 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=398880)[0m To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.45336 │
│ gamma                        7.20008 │
│ learning_rate                0.00862 │
│ max_depth                          2 │
│ min_child_weight                  21 │
│ num_boost_round                  789 │
│ random_state                     985 │
│ reg_alpha                    1.57911 │
│ reg_lambda                   3.85557 │
│ subsample                    0.51928 │
╰──────────────────────────────────────╯
Trial trial_b8b81 started with configuration:
╭──────────────────────────────────────╮
│ Trial trial_b8b81 config             │
├──────────────────────────────────────┤
│ colsample_bytree             0.41897 │
│ gamma                        3.84157 │
│ learning_rate                0.01435 │
│ max_depth                          2 │
│ min_child_weight                  53 │
│ num_boost_round                  725 │
│ random_state                    9244 │
│ reg_alpha                    0.16347 │
│ reg_lambda                     19.04 │
│ subsample                    0.65991 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=398880)[0m [0]	train-mlogloss:2.69387	validation-mlogloss:2.69271
[36m(train_xgb_ray_tune pid=398893)[0m [0]	train-mlogloss:2.70240	validation-mlogloss:2.70194
[36m(train_xgb_ray_tune pid=398880)[0m [1]	train-mlogloss:2.67981	validation-mlogloss:2.67777
[36m(train_xgb_ray_tune pid=398915)[0m [0]	train-mlogloss:2.70426	validation-mlogloss:2.70425
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[36m(train_xgb_ray_tune pid=398916)[0m [87]	train-mlogloss:2.56523	validation-mlogloss:2.55932
[36m(train_xgb_ray_tune pid=398893)[0m [98]	train-mlogloss:2.34996	validation-mlogloss:2.31403
[36m(train_xgb_ray_tune pid=398918)[0m [91]	train-mlogloss:2.49435	validation-mlogloss:2.46840
[36m(train_xgb_ray_tune pid=398913)[0m [100]	train-mlogloss:2.28917	validation-mlogloss:2.29811
[36m(train_xgb_ray_tune pid=398914)[0m [84]	train-mlogloss:2.10428	validation-mlogloss:2.07438
[36m(train_xgb_ray_tune pid=398906)[0m [96]	train-mlogloss:2.21176	validation-mlogloss:2.19051
[36m(train_xgb_ray_tune pid=398886)[0m [93]	train-mlogloss:2.09461	validation-mlogloss:2.05687
[36m(train_xgb_ray_tune pid=398903)[0m [99]	train-mlogloss:2.27121	validation-mlogloss:2.23078
[36m(train_xgb_ray_tune pid=398912)[0m [92]	train-mlogloss:2.24890	validation-mlogloss:2.20784
[36m(train_xgb_ray_tune pid=398916)[0m [88]	train-mlogloss:2.56392	validation-mlogloss:2.55799
[36m(train_xgb_ray_tune pid=398904)[0m [89]	train-mlogloss:2.46851	validation-mlogloss:2.44228
[36m(train_xgb_ray_tune pid=398879)[0m [85]	train-mlogloss:2.09492	validation-mlogloss:2.05481
[36m(train_xgb_ray_tune pid=398894)[0m [88]	train-mlogloss:2.32185	validation-mlogloss:2.28182
[36m(train_xgb_ray_tune pid=398880)[0m [100]	train-mlogloss:2.05272	validation-mlogloss:2.01371
[36m(train_xgb_ray_tune pid=398915)[0m [107]	train-mlogloss:2.40079	validation-mlogloss:2.36745
[36m(train_xgb_ray_tune pid=398900)[0m [92]	train-mlogloss:2.48027	validation-mlogloss:2.45555
[36m(train_xgb_ray_tune pid=398905)[0m [90]	train-mlogloss:2.23490	validation-mlogloss:2.21353
[36m(train_xgb_ray_tune pid=398902)[0m [94]	train-mlogloss:2.14360	validation-mlogloss:2.10328
[36m(train_xgb_ray_tune pid=398913)[0m [101]	train-mlogloss:2.28779	validation-mlogloss:2.29711
[36m(train_xgb_ray_tune pid=398901)[0m [88]	train-mlogloss:2.13241	validation-mlogloss:2.09620
[36m(train_xgb_ray_tune pid=398917)[0m [91]	train-mlogloss:2.22563	validation-mlogloss:2.20503
[36m(train_xgb_ray_tune pid=398892)[0m [94]	train-mlogloss:2.24464	validation-mlogloss:2.22557
[36m(train_xgb_ray_tune pid=398893)[0m [99]	train-mlogloss:2.34747	validation-mlogloss:2.31148
[36m(train_xgb_ray_tune pid=398906)[0m [97]	train-mlogloss:2.20868	validation-mlogloss:2.18702
[36m(train_xgb_ray_tune pid=398918)[0m [92]	train-mlogloss:2.49252	validation-mlogloss:2.46647
[36m(train_xgb_ray_tune pid=398914)[0m [85]	train-mlogloss:2.10061	validation-mlogloss:2.07091
[36m(train_xgb_ray_tune pid=398894)[0m [89]	train-mlogloss:2.31892	validation-mlogloss:2.27900
[36m(train_xgb_ray_tune pid=398886)[0m [94]	train-mlogloss:2.09136	validation-mlogloss:2.05385
[36m(train_xgb_ray_tune pid=398903)[0m [100]	train-mlogloss:2.26853	validation-mlogloss:2.22776
[36m(train_xgb_ray_tune pid=398893)[0m [100]	train-mlogloss:2.34506	validation-mlogloss:2.30894
[36m(train_xgb_ray_tune pid=398912)[0m [93]	train-mlogloss:2.24582	validation-mlogloss:2.20487
[36m(train_xgb_ray_tune pid=398916)[0m [89]	train-mlogloss:2.56258	validation-mlogloss:2.55657
[36m(train_xgb_ray_tune pid=398904)[0m [90]	train-mlogloss:2.46644	validation-mlogloss:2.44007
[36m(train_xgb_ray_tune pid=398879)[0m [86]	train-mlogloss:2.09125	validation-mlogloss:2.05134
[36m(train_xgb_ray_tune pid=398880)[0m [101]	train-mlogloss:2.04972	validation-mlogloss:2.01073
[36m(train_xgb_ray_tune pid=398915)[0m [108]	train-mlogloss:2.39881	validation-mlogloss:2.36536
[36m(train_xgb_ray_tune pid=398900)[0m [93]	train-mlogloss:2.47834	validation-mlogloss:2.45341
[36m(train_xgb_ray_tune pid=398905)[0m [91]	train-mlogloss:2.23172	validation-mlogloss:2.21045
[36m(train_xgb_ray_tune pid=398902)[0m [95]	train-mlogloss:2.14049	validation-mlogloss:2.10002
[36m(train_xgb_ray_tune pid=398913)[0m [102]	train-mlogloss:2.28612	validation-mlogloss:2.29574
[36m(train_xgb_ray_tune pid=398917)[0m [92]	train-mlogloss:2.22235	validation-mlogloss:2.20168
[36m(train_xgb_ray_tune pid=398892)[0m [95]	train-mlogloss:2.24143	validation-mlogloss:2.22251
[36m(train_xgb_ray_tune pid=398886)[0m [95]	train-mlogloss:2.08806	validation-mlogloss:2.05071
[36m(train_xgb_ray_tune pid=398906)[0m [98]	train-mlogloss:2.20538	validation-mlogloss:2.18350
[36m(train_xgb_ray_tune pid=398894)[0m [90]	train-mlogloss:2.31602	validation-mlogloss:2.27591
[36m(train_xgb_ray_tune pid=398902)[0m [96]	train-mlogloss:2.13771	validation-mlogloss:2.09734
[36m(train_xgb_ray_tune pid=398918)[0m [93]	train-mlogloss:2.49075	validation-mlogloss:2.46452
[36m(train_xgb_ray_tune pid=398901)[0m [89]	train-mlogloss:2.12892	validation-mlogloss:2.09278
[36m(train_xgb_ray_tune pid=398914)[0m [86]	train-mlogloss:2.09681	validation-mlogloss:2.06756
[36m(train_xgb_ray_tune pid=398903)[0m [101]	train-mlogloss:2.26573	validation-mlogloss:2.22515
[36m(train_xgb_ray_tune pid=398915)[0m [109]	train-mlogloss:2.39693	validation-mlogloss:2.36332
[36m(train_xgb_ray_tune pid=398892)[0m [96]	train-mlogloss:2.23822	validation-mlogloss:2.21900
[36m(train_xgb_ray_tune pid=398893)[0m [101]	train-mlogloss:2.34257	validation-mlogloss:2.30638
[36m(train_xgb_ray_tune pid=398912)[0m [94]	train-mlogloss:2.24279	validation-mlogloss:2.20195
[36m(train_xgb_ray_tune pid=398916)[0m [90]	train-mlogloss:2.56127	validation-mlogloss:2.55528
[36m(train_xgb_ray_tune pid=398904)[0m [91]	train-mlogloss:2.46434	validation-mlogloss:2.43776
[36m(train_xgb_ray_tune pid=398879)[0m [87]	train-mlogloss:2.08779	validation-mlogloss:2.04839
[36m(train_xgb_ray_tune pid=398880)[0m [102]	train-mlogloss:2.04667	validation-mlogloss:2.00770
[36m(train_xgb_ray_tune pid=398900)[0m [94]	train-mlogloss:2.47645	validation-mlogloss:2.45132
[36m(train_xgb_ray_tune pid=398905)[0m [92]	train-mlogloss:2.22856	validation-mlogloss:2.20707
[36m(train_xgb_ray_tune pid=398913)[0m [103]	train-mlogloss:2.28468	validation-mlogloss:2.29424
[36m(train_xgb_ray_tune pid=398917)[0m [93]	train-mlogloss:2.21907	validation-mlogloss:2.19871
[36m(train_xgb_ray_tune pid=398886)[0m [96]	train-mlogloss:2.08452	validation-mlogloss:2.04741
[36m(train_xgb_ray_tune pid=398903)[0m [102]	train-mlogloss:2.26307	validation-mlogloss:2.22247
[36m(train_xgb_ray_tune pid=398906)[0m [99]	train-mlogloss:2.20241	validation-mlogloss:2.18069
[36m(train_xgb_ray_tune pid=398894)[0m [91]	train-mlogloss:2.31320	validation-mlogloss:2.27294
[36m(train_xgb_ray_tune pid=398915)[0m [110]	train-mlogloss:2.39490	validation-mlogloss:2.36112
[36m(train_xgb_ray_tune pid=398902)[0m [97]	train-mlogloss:2.13494	validation-mlogloss:2.09487
[36m(train_xgb_ray_tune pid=398918)[0m [94]	train-mlogloss:2.48900	validation-mlogloss:2.46263
[36m(train_xgb_ray_tune pid=398913)[0m [104]	train-mlogloss:2.28324	validation-mlogloss:2.29302
[36m(train_xgb_ray_tune pid=398901)[0m [90]	train-mlogloss:2.12545	validation-mlogloss:2.08908
[36m(train_xgb_ray_tune pid=398914)[0m [87]	train-mlogloss:2.09335	validation-mlogloss:2.06407
[36m(train_xgb_ray_tune pid=398892)[0m [97]	train-mlogloss:2.23511	validation-mlogloss:2.21584
[36m(train_xgb_ray_tune pid=398893)[0m [102]	train-mlogloss:2.34006	validation-mlogloss:2.30365
[36m(train_xgb_ray_tune pid=398912)[0m [95]	train-mlogloss:2.23985	validation-mlogloss:2.19904
[36m(train_xgb_ray_tune pid=398916)[0m [91]	train-mlogloss:2.55994	validation-mlogloss:2.55394
[36m(train_xgb_ray_tune pid=398904)[0m [92]	train-mlogloss:2.46234	validation-mlogloss:2.43568
[36m(train_xgb_ray_tune pid=398879)[0m [88]	train-mlogloss:2.08437	validation-mlogloss:2.04544
[36m(train_xgb_ray_tune pid=398880)[0m [103]	train-mlogloss:2.04345	validation-mlogloss:2.00423
[36m(train_xgb_ray_tune pid=398900)[0m [95]	train-mlogloss:2.47458	validation-mlogloss:2.44938
[36m(train_xgb_ray_tune pid=398905)[0m [93]	train-mlogloss:2.22554	validation-mlogloss:2.20386
[36m(train_xgb_ray_tune pid=398918)[0m [95]	train-mlogloss:2.48719	validation-mlogloss:2.46057
[36m(train_xgb_ray_tune pid=398917)[0m [94]	train-mlogloss:2.21584	validation-mlogloss:2.19521
[36m(train_xgb_ray_tune pid=398886)[0m [97]	train-mlogloss:2.08110	validation-mlogloss:2.04390
[36m(train_xgb_ray_tune pid=398903)[0m [103]	train-mlogloss:2.26038	validation-mlogloss:2.21973
[36m(train_xgb_ray_tune pid=398906)[0m [100]	train-mlogloss:2.19950	validation-mlogloss:2.17743
[36m(train_xgb_ray_tune pid=398894)[0m [92]	train-mlogloss:2.31048	validation-mlogloss:2.27013
[36m(train_xgb_ray_tune pid=398915)[0m [111]	train-mlogloss:2.39281	validation-mlogloss:2.35892
[36m(train_xgb_ray_tune pid=398900)[0m [96]	train-mlogloss:2.47267	validation-mlogloss:2.44743
[36m(train_xgb_ray_tune pid=398902)[0m [98]	train-mlogloss:2.13229	validation-mlogloss:2.09225
[36m(train_xgb_ray_tune pid=398913)[0m [105]	train-mlogloss:2.28164	validation-mlogloss:2.29140
[36m(train_xgb_ray_tune pid=398901)[0m [91]	train-mlogloss:2.12206	validation-mlogloss:2.08574
[36m(train_xgb_ray_tune pid=398914)[0m [88]	train-mlogloss:2.08982	validation-mlogloss:2.06057
[36m(train_xgb_ray_tune pid=398892)[0m [98]	train-mlogloss:2.23194	validation-mlogloss:2.21279
[36m(train_xgb_ray_tune pid=398912)[0m [96]	train-mlogloss:2.23694	validation-mlogloss:2.19629
[36m(train_xgb_ray_tune pid=398904)[0m [93]	train-mlogloss:2.46033	validation-mlogloss:2.43340
[36m(train_xgb_ray_tune pid=398893)[0m [103]	train-mlogloss:2.33757	validation-mlogloss:2.30110
[36m(train_xgb_ray_tune pid=398880)[0m [104]	train-mlogloss:2.04039	validation-mlogloss:2.00112

Trial status: 20 RUNNING
Current time: 2025-10-27 09:34:45. Total running time: 30s
Logical resource usage: 20.0/20 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_b8b81    RUNNING                  785             2        0.0152561       0.333235             0.509718   5.36058                   59      1.72191        0.791369             8764 │
│ trial_b8b81    RUNNING                  436             2        0.0151967       0.687426             0.508211   3.6508                    32      0.236551       2.80111                23 │
│ trial_b8b81    RUNNING                  540             2        0.0154571       0.498324             0.399232   7.5555                    57      0.518023       1.37493              3189 │
│ trial_b8b81    RUNNING                  353             2        0.00577946      0.588048             0.300442   8.55953                   34      5.80421        0.579503             5130 │
│ trial_b8b81    RUNNING                  677             2        0.00718957      0.347983             0.517791   6.43243                   12      0.249615       2.3729               3650 │
│ trial_b8b81    RUNNING                  347             2        0.00373864      0.624615             0.491362   7.40223                   33      0.177621      15.6491               4377 │
│ trial_b8b81    RUNNING                  749             2        0.00684262      0.511093             0.642296   2.23501                   26      2.59404        5.58484              8397 │
│ trial_b8b81    RUNNING                  550             2        0.0146521       0.333218             0.403476   8.58164                   12      8.33367       54.5003               6890 │
│ trial_b8b81    RUNNING                  789             2        0.00862436      0.519278             0.453361   7.20008                   21      1.57911        3.85557               985 │
│ trial_b8b81    RUNNING                  416             2        0.00418167      0.347849             0.419215   6.11886                   39      1.02586        0.871116             4157 │
│ trial_b8b81    RUNNING                  737             2        0.0033156       0.459322             0.608053   3.18821                   28     93.719          1.30518              5776 │
│ trial_b8b81    RUNNING                  650             2        0.00313347      0.693701             0.492938   9.79394                   12      1.55806        6.0203               5382 │
│ trial_b8b81    RUNNING                  860             2        0.0136591       0.502887             0.62787    4.03237                   37     28.4997        51.4794               8253 │
│ trial_b8b81    RUNNING                  500             2        0.0168463       0.316536             0.311578   7.53857                   21     25.6984         1.41457              2854 │
│ trial_b8b81    RUNNING                  528             2        0.00285688      0.536565             0.651463   5.278                     25      2.19742        2.87126               507 │
│ trial_b8b81    RUNNING                  319             2        0.0172683       0.44677              0.688075   6.64719                   21      1.24884       27.0934               5802 │
│ trial_b8b81    RUNNING                  783             2        0.0197427       0.306766             0.67443    7.59557                   58     66.8206        16.8769               7467 │
│ trial_b8b81    RUNNING                  725             2        0.0143453       0.659911             0.418968   3.84157                   53      0.163473      19.04                 9244 │
│ trial_b8b81    RUNNING                  601             2        0.0132953       0.653242             0.585449   3.87352                   49      4.74374       97.5749               9239 │
│ trial_b8b81    RUNNING                  871             2        0.0139431       0.314738             0.444055   8.48731                   42      0.988245      70.352                9194 │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=398886)[0m [98]	train-mlogloss:2.07792	validation-mlogloss:2.04097
[36m(train_xgb_ray_tune pid=398916)[0m [92]	train-mlogloss:2.55864	validation-mlogloss:2.55268
[36m(train_xgb_ray_tune pid=398879)[0m [89]	train-mlogloss:2.08078	validation-mlogloss:2.04248
[36m(train_xgb_ray_tune pid=398905)[0m [94]	train-mlogloss:2.22258	validation-mlogloss:2.20096
[36m(train_xgb_ray_tune pid=398918)[0m [96]	train-mlogloss:2.48531	validation-mlogloss:2.45845
[36m(train_xgb_ray_tune pid=398913)[0m [106]	train-mlogloss:2.28003	validation-mlogloss:2.28995
[36m(train_xgb_ray_tune pid=398917)[0m [95]	train-mlogloss:2.21258	validation-mlogloss:2.19204
[36m(train_xgb_ray_tune pid=398915)[0m [112]	train-mlogloss:2.39084	validation-mlogloss:2.35694
[36m(train_xgb_ray_tune pid=398903)[0m [104]	train-mlogloss:2.25776	validation-mlogloss:2.21705
[36m(train_xgb_ray_tune pid=398893)[0m [104]	train-mlogloss:2.33517	validation-mlogloss:2.29853
[36m(train_xgb_ray_tune pid=398912)[0m [97]	train-mlogloss:2.23408	validation-mlogloss:2.19346
[36m(train_xgb_ray_tune pid=398906)[0m [101]	train-mlogloss:2.19652	validation-mlogloss:2.17449
[36m(train_xgb_ray_tune pid=398904)[0m [94]	train-mlogloss:2.45831	validation-mlogloss:2.43136
[36m(train_xgb_ray_tune pid=398894)[0m [93]	train-mlogloss:2.30766	validation-mlogloss:2.26728
[36m(train_xgb_ray_tune pid=398880)[0m [105]	train-mlogloss:2.03742	validation-mlogloss:1.99841
[36m(train_xgb_ray_tune pid=398900)[0m [97]	train-mlogloss:2.47081	validation-mlogloss:2.44535
[36m(train_xgb_ray_tune pid=398902)[0m [99]	train-mlogloss:2.12932	validation-mlogloss:2.08928
[36m(train_xgb_ray_tune pid=398901)[0m [92]	train-mlogloss:2.11860	validation-mlogloss:2.08220
[36m(train_xgb_ray_tune pid=398914)[0m [89]	train-mlogloss:2.08628	validation-mlogloss:2.05750
[36m(train_xgb_ray_tune pid=398892)[0m [99]	train-mlogloss:2.22893	validation-mlogloss:2.20979
[36m(train_xgb_ray_tune pid=398886)[0m [99]	train-mlogloss:2.07466	validation-mlogloss:2.03769
[36m(train_xgb_ray_tune pid=398906)[0m [102]	train-mlogloss:2.19362	validation-mlogloss:2.17152
[36m(train_xgb_ray_tune pid=398916)[0m [93]	train-mlogloss:2.55738	validation-mlogloss:2.55137
[36m(train_xgb_ray_tune pid=398879)[0m [90]	train-mlogloss:2.07745	validation-mlogloss:2.03927
[36m(train_xgb_ray_tune pid=398915)[0m [113]	train-mlogloss:2.38884	validation-mlogloss:2.35486
[36m(train_xgb_ray_tune pid=398905)[0m [95]	train-mlogloss:2.21955	validation-mlogloss:2.19780
[36m(train_xgb_ray_tune pid=398918)[0m [97]	train-mlogloss:2.48361	validation-mlogloss:2.45653
[36m(train_xgb_ray_tune pid=398913)[0m [107]	train-mlogloss:2.27852	validation-mlogloss:2.28869
[36m(train_xgb_ray_tune pid=398917)[0m [96]	train-mlogloss:2.20939	validation-mlogloss:2.18876
[36m(train_xgb_ray_tune pid=398892)[0m [100]	train-mlogloss:2.22588	validation-mlogloss:2.20680
[36m(train_xgb_ray_tune pid=398903)[0m [105]	train-mlogloss:2.25512	validation-mlogloss:2.21425
[36m(train_xgb_ray_tune pid=398893)[0m [105]	train-mlogloss:2.33279	validation-mlogloss:2.29583
[36m(train_xgb_ray_tune pid=398912)[0m [98]	train-mlogloss:2.23123	validation-mlogloss:2.19057
[36m(train_xgb_ray_tune pid=398904)[0m [95]	train-mlogloss:2.45628	validation-mlogloss:2.42913
[36m(train_xgb_ray_tune pid=398894)[0m [94]	train-mlogloss:2.30493	validation-mlogloss:2.26446
[36m(train_xgb_ray_tune pid=398880)[0m [106]	train-mlogloss:2.03449	validation-mlogloss:1.99532
[36m(train_xgb_ray_tune pid=398900)[0m [98]	train-mlogloss:2.46888	validation-mlogloss:2.44317
[36m(train_xgb_ray_tune pid=398902)[0m [100]	train-mlogloss:2.12668	validation-mlogloss:2.08686
[36m(train_xgb_ray_tune pid=398918)[0m [98]	train-mlogloss:2.48187	validation-mlogloss:2.45454
[36m(train_xgb_ray_tune pid=398901)[0m [93]	train-mlogloss:2.11514	validation-mlogloss:2.07932
[36m(train_xgb_ray_tune pid=398914)[0m [90]	train-mlogloss:2.08278	validation-mlogloss:2.05396
[36m(train_xgb_ray_tune pid=398886)[0m [100]	train-mlogloss:2.07163	validation-mlogloss:2.03498
[36m(train_xgb_ray_tune pid=398906)[0m [103]	train-mlogloss:2.19085	validation-mlogloss:2.16871
[36m(train_xgb_ray_tune pid=398916)[0m [94]	train-mlogloss:2.55610	validation-mlogloss:2.55002
[36m(train_xgb_ray_tune pid=398879)[0m [91]	train-mlogloss:2.07393	validation-mlogloss:2.03574
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[36m(train_xgb_ray_tune pid=398915)[0m [251]	train-mlogloss:2.17481	validation-mlogloss:2.13198
[36m(train_xgb_ray_tune pid=398900)[0m [221]	train-mlogloss:2.28548	validation-mlogloss:2.24591
[36m(train_xgb_ray_tune pid=398905)[0m [218]	train-mlogloss:1.97168	validation-mlogloss:1.95406
[36m(train_xgb_ray_tune pid=398902)[0m [228]	train-mlogloss:1.93173	validation-mlogloss:1.90019
[36m(train_xgb_ray_tune pid=398901)[0m [217]	train-mlogloss:1.84698	validation-mlogloss:1.84226
[36m(train_xgb_ray_tune pid=398892)[0m [229]	train-mlogloss:1.96322	validation-mlogloss:1.94570
Trial status: 20 RUNNING
Current time: 2025-10-27 09:35:15. Total running time: 1min 0s
Logical resource usage: 20.0/20 CPUs, 0/1 GPUs (0.0/1.0 accelerator_type:G)
[36m(train_xgb_ray_tune pid=398886)[0m [226]	train-mlogloss:1.81431	validation-mlogloss:1.80587
╭─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ Trial name     status       num_boost_round     max_depth     learning_rate     subsample     colsample_bytree     gamma     min_child_weight     reg_alpha     reg_lambda     random_state │
├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ trial_b8b81    RUNNING                  785             2        0.0152561       0.333235             0.509718   5.36058                   59      1.72191        0.791369             8764 │
│ trial_b8b81    RUNNING                  436             2        0.0151967       0.687426             0.508211   3.6508                    32      0.236551       2.80111                23 │
│ trial_b8b81    RUNNING                  540             2        0.0154571       0.498324             0.399232   7.5555                    57      0.518023       1.37493              3189 │
│ trial_b8b81    RUNNING                  353             2        0.00577946      0.588048             0.300442   8.55953                   34      5.80421        0.579503             5130 │
│ trial_b8b81    RUNNING                  677             2        0.00718957      0.347983             0.517791   6.43243                   12      0.249615       2.3729               3650 │
│ trial_b8b81    RUNNING                  347             2        0.00373864      0.624615             0.491362   7.40223                   33      0.177621      15.6491               4377 │
│ trial_b8b81    RUNNING                  749             2        0.00684262      0.511093             0.642296   2.23501                   26      2.59404        5.58484              8397 │
│ trial_b8b81    RUNNING                  550             2        0.0146521       0.333218             0.403476   8.58164                   12      8.33367       54.5003               6890 │
│ trial_b8b81    RUNNING                  789             2        0.00862436      0.519278             0.453361   7.20008                   21      1.57911        3.85557               985 │
│ trial_b8b81    RUNNING                  416             2        0.00418167      0.347849             0.419215   6.11886                   39      1.02586        0.871116             4157 │
│ trial_b8b81    RUNNING                  737             2        0.0033156       0.459322             0.608053   3.18821                   28     93.719          1.30518              5776 │
│ trial_b8b81    RUNNING                  650             2        0.00313347      0.693701             0.492938   9.79394                   12      1.55806        6.0203               5382 │
│ trial_b8b81    RUNNING                  860             2        0.0136591       0.502887             0.62787    4.03237                   37     28.4997        51.4794               8253 │
│ trial_b8b81    RUNNING                  500             2        0.0168463       0.316536             0.311578   7.53857                   21     25.6984         1.41457              2854 │
│ trial_b8b81    RUNNING                  528             2        0.00285688      0.536565             0.651463   5.278                     25      2.19742        2.87126               507 │
│ trial_b8b81    RUNNING                  319             2        0.0172683       0.44677              0.688075   6.64719                   21      1.24884       27.0934               5802 │
│ trial_b8b81    RUNNING                  783             2        0.0197427       0.306766             0.67443    7.59557                   58     66.8206        16.8769               7467 │
│ trial_b8b81    RUNNING                  725             2        0.0143453       0.659911             0.418968   3.84157                   53      0.163473      19.04                 9244 │
│ trial_b8b81    RUNNING                  601             2        0.0132953       0.653242             0.585449   3.87352                   49      4.74374       97.5749               9239 │
│ trial_b8b81    RUNNING                  871             2        0.0139431       0.314738             0.444055   8.48731                   42      0.988245      70.352                9194 │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=398917)[0m [216]	train-mlogloss:1.94897	validation-mlogloss:1.93792
[36m(train_xgb_ray_tune pid=398892)[0m [230]	train-mlogloss:1.96185	validation-mlogloss:1.94431
[36m(train_xgb_ray_tune pid=398906)[0m [229]	train-mlogloss:1.94822	validation-mlogloss:1.92473
[36m(train_xgb_ray_tune pid=398904)[0m [219]	train-mlogloss:2.25612	validation-mlogloss:2.21628
[36m(train_xgb_ray_tune pid=398879)[0m [210]	train-mlogloss:1.80963	validation-mlogloss:1.81783
[36m(train_xgb_ray_tune pid=398894)[0m [216]	train-mlogloss:2.06368	validation-mlogloss:2.02830
[36m(train_xgb_ray_tune pid=398915)[0m [252]	train-mlogloss:2.17355	validation-mlogloss:2.13062
[36m(train_xgb_ray_tune pid=398900)[0m [222]	train-mlogloss:2.28427	validation-mlogloss:2.24457
[36m(train_xgb_ray_tune pid=398905)[0m [219]	train-mlogloss:1.97034	validation-mlogloss:1.95275
[36m(train_xgb_ray_tune pid=398913)[0m [265]	train-mlogloss:2.18045	validation-mlogloss:2.19614
[36m(train_xgb_ray_tune pid=398901)[0m [218]	train-mlogloss:1.84550	validation-mlogloss:1.84114
[36m(train_xgb_ray_tune pid=398886)[0m [227]	train-mlogloss:1.81309	validation-mlogloss:1.80480
[36m(train_xgb_ray_tune pid=398903)[0m [233]	train-mlogloss:2.01380	validation-mlogloss:1.98310
[36m(train_xgb_ray_tune pid=398893)[0m [241]	train-mlogloss:2.09752	validation-mlogloss:2.05513
�G+@z��08`W��}���{��@Y����������\`W��}��`D�W���G+�~��`��W���G+���`M�W��G+����@L�W�P�G+Ё���K�W���G+������W���G+����0Y�W��Y�W��}��~���a��Hb����������k���b����K+~�� ��W�@Y����jW��~��0Y�W��Y�W��}��(~���a��Hb����������k���b����K+P��� ��W�@Y����jW����0Y�W��Y�W��}��@~���a��Hb����������k���b������������K+ ��W�[36m(train_xgb_ray_tune pid=398912)[0m [224]	train-mlogloss:1.97789	validation-mlogloss:1.95030
[36m(train_xgb_ray_tune pid=398916)[0m [219]	train-mlogloss:2.42426	validation-mlogloss:2.41723
[36m(train_xgb_ray_tune pid=398880)[0m [232]	train-mlogloss:1.79243	validation-mlogloss:1.79501
[36m(train_xgb_ray_tune pid=398902)[0m [230]	train-mlogloss:1.93022	validation-mlogloss:1.89909
[36m(train_xgb_ray_tune pid=398918)[0m [226]	train-mlogloss:2.29911	validation-mlogloss:2.25910
[36m(train_xgb_ray_tune pid=398913)[0m [266]	train-mlogloss:2.18045	validation-mlogloss:2.19614
[36m(train_xgb_ray_tune pid=398914)[0m [208]	train-mlogloss:1.81298	validation-mlogloss:1.81645
[36m(train_xgb_ray_tune pid=398917)[0m [217]	train-mlogloss:1.94742	validation-mlogloss:1.93643
[36m(train_xgb_ray_tune pid=398892)[0m [231]	train-mlogloss:1.96042	validation-mlogloss:1.94301
[36m(train_xgb_ray_tune pid=398906)[0m [230]	train-mlogloss:1.94694	validation-mlogloss:1.92375
[36m(train_xgb_ray_tune pid=398904)[0m [220]	train-mlogloss:2.25487	validation-mlogloss:2.21496
[36m(train_xgb_ray_tune pid=398879)[0m [211]	train-mlogloss:1.80827	validation-mlogloss:1.81696
[36m(train_xgb_ray_tune pid=398894)[0m [217]	train-mlogloss:2.06223	validation-mlogloss:2.02693
[36m(train_xgb_ray_tune pid=398915)[0m [253]	train-mlogloss:2.17240	validation-mlogloss:2.12948
[36m(train_xgb_ray_tune pid=398900)[0m [223]	train-mlogloss:2.28308	validation-mlogloss:2.24335
[36m(train_xgb_ray_tune pid=398905)[0m [220]	train-mlogloss:1.96899	validation-mlogloss:1.95152
[36m(train_xgb_ray_tune pid=398901)[0m [219]	train-mlogloss:1.84411	validation-mlogloss:1.84003
[36m(train_xgb_ray_tune pid=398886)[0m [228]	train-mlogloss:1.81181	validation-mlogloss:1.80376
[36m(train_xgb_ray_tune pid=398903)[0m [234]	train-mlogloss:2.01239	validation-mlogloss:1.98185
[36m(train_xgb_ray_tune pid=398893)[0m [242]	train-mlogloss:2.09626	validation-mlogloss:2.05395
[36m(train_xgb_ray_tune pid=398912)[0m [225]	train-mlogloss:1.97642	validation-mlogloss:1.94901
[36m(train_xgb_ray_tune pid=398916)[0m [220]	train-mlogloss:2.42340	validation-mlogloss:2.41638
[36m(train_xgb_ray_tune pid=398880)[0m [233]	train-mlogloss:1.79120	validation-mlogloss:1.79385
[36m(train_xgb_ray_tune pid=398915)[0m [254]	train-mlogloss:2.17120	validation-mlogloss:2.12820
[36m(train_xgb_ray_tune pid=398902)[0m [231]	train-mlogloss:1.92961	validation-mlogloss:1.89863
[36m(train_xgb_ray_tune pid=398918)[0m [227]	train-mlogloss:2.29796	validation-mlogloss:2.25791
[36m(train_xgb_ray_tune pid=398913)[0m [267]	train-mlogloss:2.18023	validation-mlogloss:2.19587
[36m(train_xgb_ray_tune pid=398914)[0m [209]	train-mlogloss:1.81141	validation-mlogloss:1.81511
[36m(train_xgb_ray_tune pid=398917)[0m [218]	train-mlogloss:1.94595	validation-mlogloss:1.93518
[36m(train_xgb_ray_tune pid=398892)[0m [232]	train-mlogloss:1.95915	validation-mlogloss:1.94191
[36m(train_xgb_ray_tune pid=398906)[0m [231]	train-mlogloss:1.94575	validation-mlogloss:1.92256
[36m(train_xgb_ray_tune pid=398904)[0m [221]	train-mlogloss:2.25359	validation-mlogloss:2.21364
[36m(train_xgb_ray_tune pid=398879)[0m [212]	train-mlogloss:1.80693	validation-mlogloss:1.81615
[36m(train_xgb_ray_tune pid=398894)[0m [218]	train-mlogloss:2.06076	validation-mlogloss:2.02560
[36m(train_xgb_ray_tune pid=398900)[0m [224]	train-mlogloss:2.28189	validation-mlogloss:2.24214
[36m(train_xgb_ray_tune pid=398905)[0m [221]	train-mlogloss:1.96765	validation-mlogloss:1.95043
[36m(train_xgb_ray_tune pid=398902)[0m [232]	train-mlogloss:1.92897	validation-mlogloss:1.89823
[36m(train_xgb_ray_tune pid=398913)[0m [268]	train-mlogloss:2.18001	validation-mlogloss:2.19566
[36m(train_xgb_ray_tune pid=398901)[0m [220]	train-mlogloss:1.84262	validation-mlogloss:1.83905
[36m(train_xgb_ray_tune pid=398886)[0m [229]	train-mlogloss:1.81043	validation-mlogloss:1.80286
[36m(train_xgb_ray_tune pid=398918)[0m [228]	train-mlogloss:2.29681	validation-mlogloss:2.25675
[36m(train_xgb_ray_tune pid=398903)[0m [235]	train-mlogloss:2.01104	validation-mlogloss:1.98073
[36m(train_xgb_ray_tune pid=398893)[0m [243]	train-mlogloss:2.09495	validation-mlogloss:2.05268
[36m(train_xgb_ray_tune pid=398912)[0m [226]	train-mlogloss:1.97505	validation-mlogloss:1.94789
[36m(train_xgb_ray_tune pid=398916)[0m [221]	train-mlogloss:2.42256	validation-mlogloss:2.41550
[36m(train_xgb_ray_tune pid=398880)[0m [234]	train-mlogloss:1.78984	validation-mlogloss:1.79274
[36m(train_xgb_ray_tune pid=398915)[0m [255]	train-mlogloss:2.17006	validation-mlogloss:2.12712
[36m(train_xgb_ray_tune pid=398914)[0m [210]	train-mlogloss:1.80988	validation-mlogloss:1.81418
[36m(train_xgb_ray_tune pid=398917)[0m [219]	train-mlogloss:1.94460	validation-mlogloss:1.93400
[36m(train_xgb_ray_tune pid=398892)[0m [233]	train-mlogloss:1.95779	validation-mlogloss:1.94060
[36m(train_xgb_ray_tune pid=398913)[0m [269]	train-mlogloss:2.17971	validation-mlogloss:2.19525
[36m(train_xgb_ray_tune pid=398901)[0m [221]	train-mlogloss:1.84121	validation-mlogloss:1.83764
[36m(train_xgb_ray_tune pid=398906)[0m [232]	train-mlogloss:1.94458	validation-mlogloss:1.92170
[36m(train_xgb_ray_tune pid=398904)[0m [222]	train-mlogloss:2.25230	validation-mlogloss:2.21233
[36m(train_xgb_ray_tune pid=398902)[0m [233]	train-mlogloss:1.92817	validation-mlogloss:1.89760
[36m(train_xgb_ray_tune pid=398886)[0m [230]	train-mlogloss:1.80898	validation-mlogloss:1.80171
[36m(train_xgb_ray_tune pid=398879)[0m [213]	train-mlogloss:1.80536	validation-mlogloss:1.81501
[36m(train_xgb_ray_tune pid=398894)[0m [219]	train-mlogloss:2.05936	validation-mlogloss:2.02432
[36m(train_xgb_ray_tune pid=398900)[0m [225]	train-mlogloss:2.28067	validation-mlogloss:2.24094
[36m(train_xgb_ray_tune pid=398905)[0m [222]	train-mlogloss:1.96634	validation-mlogloss:1.94915
[36m(train_xgb_ray_tune pid=398918)[0m [229]	train-mlogloss:2.29568	validation-mlogloss:2.25556
[36m(train_xgb_ray_tune pid=398917)[0m [220]	train-mlogloss:1.94310	validation-mlogloss:1.93270
[36m(train_xgb_ray_tune pid=398913)[0m [270]	train-mlogloss:2.17971	validation-mlogloss:2.19525
[36m(train_xgb_ray_tune pid=398903)[0m [236]	train-mlogloss:2.00969	validation-mlogloss:1.97942
[36m(train_xgb_ray_tune pid=398893)[0m [244]	train-mlogloss:2.09372	validation-mlogloss:2.05142
[36m(train_xgb_ray_tune pid=398912)[0m [227]	train-mlogloss:1.97357	validation-mlogloss:1.94644
[36m(train_xgb_ray_tune pid=398906)[0m [233]	train-mlogloss:1.94325	validation-mlogloss:1.92052
[36m(train_xgb_ray_tune pid=398916)[0m [222]	train-mlogloss:2.42169	validation-mlogloss:2.41462
[36m(train_xgb_ray_tune pid=398904)[0m [223]	train-mlogloss:2.25103	validation-mlogloss:2.21095
[36m(train_xgb_ray_tune pid=398880)[0m [235]	train-mlogloss:1.78861	validation-mlogloss:1.79210
[36m(train_xgb_ray_tune pid=398915)[0m [256]	train-mlogloss:2.16890	validation-mlogloss:2.12592
[36m(train_xgb_ray_tune pid=398902)[0m [234]	train-mlogloss:1.92746	validation-mlogloss:1.89692
[36m(train_xgb_ray_tune pid=398901)[0m [222]	train-mlogloss:1.83969	validation-mlogloss:1.83659
[36m(train_xgb_ray_tune pid=398914)[0m [211]	train-mlogloss:1.80838	validation-mlogloss:1.81316
[36m(train_xgb_ray_tune pid=398892)[0m [234]	train-mlogloss:1.95646	validation-mlogloss:1.93948
[36m(train_xgb_ray_tune pid=398886)[0m [231]	train-mlogloss:1.80775	validation-mlogloss:1.80098
[36m(train_xgb_ray_tune pid=398879)[0m [214]	train-mlogloss:1.80391	validation-mlogloss:1.81415
[36m(train_xgb_ray_tune pid=398894)[0m [220]	train-mlogloss:2.05783	validation-mlogloss:2.02289
[36m(train_xgb_ray_tune pid=398915)[0m [257]	train-mlogloss:2.16767	validation-mlogloss:2.12469
[36m(train_xgb_ray_tune pid=398900)[0m [226]	train-mlogloss:2.27947	validation-mlogloss:2.23963
[36m(train_xgb_ray_tune pid=398905)[0m [223]	train-mlogloss:1.96498	validation-mlogloss:1.94779
[36m(train_xgb_ray_tune pid=398918)[0m [230]	train-mlogloss:2.29457	validation-mlogloss:2.25442
[36m(train_xgb_ray_tune pid=398913)[0m [271]	train-mlogloss:2.17951	validation-mlogloss:2.19506
[36m(train_xgb_ray_tune pid=398917)[0m [221]	train-mlogloss:1.94163	validation-mlogloss:1.93132
[36m(train_xgb_ray_tune pid=398903)[0m [237]	train-mlogloss:2.00833	validation-mlogloss:1.97810
[36m(train_xgb_ray_tune pid=398893)[0m [245]	train-mlogloss:2.09250	validation-mlogloss:2.05013
[36m(train_xgb_ray_tune pid=398912)[0m [228]	train-mlogloss:1.97214	validation-mlogloss:1.94529
[36m(train_xgb_ray_tune pid=398906)[0m [234]	train-mlogloss:1.94202	validation-mlogloss:1.91947
[36m(train_xgb_ray_tune pid=398904)[0m [224]	train-mlogloss:2.24977	validation-mlogloss:2.20950
[36m(train_xgb_ray_tune pid=398880)[0m [236]	train-mlogloss:1.78739	validation-mlogloss:1.79133
[36m(train_xgb_ray_tune pid=398900)[0m [227]	train-mlogloss:2.27830	validation-mlogloss:2.23836
[36m(train_xgb_ray_tune pid=398902)[0m [235]	train-mlogloss:1.92668	validation-mlogloss:1.89624
[36m(train_xgb_ray_tune pid=398913)[0m [272]	train-mlogloss:2.17897	validation-mlogloss:2.19466
[36m(train_xgb_ray_tune pid=398914)[0m [212]	train-mlogloss:1.80690	validation-mlogloss:1.81230
[36m(train_xgb_ray_tune pid=398892)[0m [235]	train-mlogloss:1.95504	validation-mlogloss:1.93792
[36m(train_xgb_ray_tune pid=398901)[0m [223]	train-mlogloss:1.83824	validation-mlogloss:1.83559
[36m(train_xgb_ray_tune pid=398905)[0m [224]	train-mlogloss:1.96379	validation-mlogloss:1.94676
[36m(train_xgb_ray_tune pid=398886)[0m [232]	train-mlogloss:1.80649	validation-mlogloss:1.79964
[36m(train_xgb_ray_tune pid=398916)[0m [223]	train-mlogloss:2.42081	validation-mlogloss:2.41379
[36m(train_xgb_ray_tune pid=398879)[0m [215]	train-mlogloss:1.80242	validation-mlogloss:1.81294
[36m(train_xgb_ray_tune pid=398894)[0m [221]	train-mlogloss:2.05633	validation-mlogloss:2.02135
[36m(train_xgb_ray_tune pid=398880)[0m [237]	train-mlogloss:1.78616	validation-mlogloss:1.79062
[36m(train_xgb_ray_tune pid=398915)[0m [258]	train-mlogloss:2.16649	validation-mlogloss:2.12358
[36m(train_xgb_ray_tune pid=398902)[0m [236]	train-mlogloss:1.92620	validation-mlogloss:1.89573
[36m(train_xgb_ray_tune pid=398918)[0m [231]	train-mlogloss:2.29342	validation-mlogloss:2.25330
[36m(train_xgb_ray_tune pid=398917)[0m [222]	train-mlogloss:1.94020	validation-mlogloss:1.93025
[36m(train_xgb_ray_tune pid=398892)[0m [236]	train-mlogloss:1.95381	validation-mlogloss:1.93673
[36m(train_xgb_ray_tune pid=398893)[0m [246]	train-mlogloss:2.09119	validation-mlogloss:2.04879
[36m(train_xgb_ray_tune pid=398913)[0m [273]	train-mlogloss:2.17856	validation-mlogloss:2.19433
[36m(train_xgb_ray_tune pid=398886)[0m [233]	train-mlogloss:1.80521	validation-mlogloss:1.79905
[36m(train_xgb_ray_tune pid=398903)[0m [238]	train-mlogloss:2.00691	validation-mlogloss:1.97703
[36m(train_xgb_ray_tune pid=398912)[0m [229]	train-mlogloss:1.97076	validation-mlogloss:1.94398
[36m(train_xgb_ray_tune pid=398906)[0m [235]	train-mlogloss:1.94078	validation-mlogloss:1.91836
[36m(train_xgb_ray_tune pid=398904)[0m [225]	train-mlogloss:2.24851	validation-mlogloss:2.20821
[36m(train_xgb_ray_tune pid=398900)[0m [228]	train-mlogloss:2.27713	validation-mlogloss:2.23716
[36m(train_xgb_ray_tune pid=398905)[0m [225]	train-mlogloss:1.96241	validation-mlogloss:1.94531
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[36m(train_xgb_ray_tune pid=398916)[0m [327]	train-mlogloss:2.34282	validation-mlogloss:2.33703
[36m(train_xgb_ray_tune pid=398894)[0m [321]	train-mlogloss:1.93725	validation-mlogloss:1.91565
[36m(train_xgb_ray_tune pid=398915)[0m [374]	train-mlogloss:2.05078	validation-mlogloss:2.01202
[36m(train_xgb_ray_tune pid=398905)[0m [323]	train-mlogloss:1.85906	validation-mlogloss:1.85230
[36m(train_xgb_ray_tune pid=398902)[0m [371]	train-mlogloss:1.87366	validation-mlogloss:1.85215
[36m(train_xgb_ray_tune pid=398918)[0m [337]	train-mlogloss:2.18791	validation-mlogloss:2.14731
[36m(train_xgb_ray_tune pid=398913)[0m [431]	train-mlogloss:2.16175	validation-mlogloss:2.17645
[36m(train_xgb_ray_tune pid=398914)[0m [313]	train-mlogloss:1.68769	validation-mlogloss:1.73931
[36m(train_xgb_ray_tune pid=398917)[0m [325]	train-mlogloss:1.81788	validation-mlogloss:1.82544
[36m(train_xgb_ray_tune pid=398904)[0m [331]	train-mlogloss:2.13378	validation-mlogloss:2.09391
[36m(train_xgb_ray_tune pid=398886)[0m [334]	train-mlogloss:1.70097	validation-mlogloss:1.73368
[36m(train_xgb_ray_tune pid=398903)[0m [344]	train-mlogloss:1.88745	validation-mlogloss:1.87480
[36m(train_xgb_ray_tune pid=398879)[0m [323]	train-mlogloss:1.67688	validation-mlogloss:1.74080
[36m(train_xgb_ray_tune pid=398880)[0m [347]	train-mlogloss:1.67647	validation-mlogloss:1.72693
[36m(train_xgb_ray_tune pid=398915)[0m [375]	train-mlogloss:2.04991	validation-mlogloss:2.01126
[36m(train_xgb_ray_tune pid=398900)[0m [333]	train-mlogloss:2.16909	validation-mlogloss:2.12869
[36m(train_xgb_ray_tune pid=398902)[0m [372]	train-mlogloss:1.87338	validation-mlogloss:1.85188
[36m(train_xgb_ray_tune pid=398901)[0m [330]	train-mlogloss:1.71987	validation-mlogloss:1.75616
[36m(train_xgb_ray_tune pid=398914)[0m [314]	train-mlogloss:1.68682	validation-mlogloss:1.73875
[36m(train_xgb_ray_tune pid=398892)[0m [347]	train-mlogloss:1.84220	validation-mlogloss:1.83434
[36m(train_xgb_ray_tune pid=398912)[0m [335]	train-mlogloss:1.85013	validation-mlogloss:1.84515
[36m(train_xgb_ray_tune pid=398906)[0m [346]	train-mlogloss:1.84185	validation-mlogloss:1.82862
[36m(train_xgb_ray_tune pid=398905)[0m [324]	train-mlogloss:1.85823	validation-mlogloss:1.85156
[36m(train_xgb_ray_tune pid=398918)[0m [338]	train-mlogloss:2.18703	validation-mlogloss:2.14642
[36m(train_xgb_ray_tune pid=398913)[0m [432]	train-mlogloss:2.16175	validation-mlogloss:2.17645
[36m(train_xgb_ray_tune pid=398886)[0m [335]	train-mlogloss:1.70011	validation-mlogloss:1.73331
[36m(train_xgb_ray_tune pid=398916)[0m [328]	train-mlogloss:2.34218	validation-mlogloss:2.33640
[36m(train_xgb_ray_tune pid=398904)[0m [332]	train-mlogloss:2.13288	validation-mlogloss:2.09313
[36m(train_xgb_ray_tune pid=398894)[0m [322]	train-mlogloss:1.93628	validation-mlogloss:1.91490
[36m(train_xgb_ray_tune pid=398917)[0m [326]	train-mlogloss:1.81692	validation-mlogloss:1.82475
[36m(train_xgb_ray_tune pid=398892)[0m [348]	train-mlogloss:1.84145	validation-mlogloss:1.83363
[36m(train_xgb_ray_tune pid=398903)[0m [345]	train-mlogloss:1.88656	validation-mlogloss:1.87414
[36m(train_xgb_ray_tune pid=398912)[0m [336]	train-mlogloss:1.84921	validation-mlogloss:1.84439
[36m(train_xgb_ray_tune pid=398906)[0m [347]	train-mlogloss:1.84129	validation-mlogloss:1.82811
[36m(train_xgb_ray_tune pid=398879)[0m [324]	train-mlogloss:1.67592	validation-mlogloss:1.74028
[36m(train_xgb_ray_tune pid=398880)[0m [348]	train-mlogloss:1.67559	validation-mlogloss:1.72664
[36m(train_xgb_ray_tune pid=398915)[0m [376]	train-mlogloss:2.04908	validation-mlogloss:2.01054
[36m(train_xgb_ray_tune pid=398900)[0m [334]	train-mlogloss:2.16818	validation-mlogloss:2.12776
[36m(train_xgb_ray_tune pid=398905)[0m [325]	train-mlogloss:1.85737	validation-mlogloss:1.85077
[36m(train_xgb_ray_tune pid=398902)[0m [373]	train-mlogloss:1.87324	validation-mlogloss:1.85172
[36m(train_xgb_ray_tune pid=398918)[0m [339]	train-mlogloss:2.18617	validation-mlogloss:2.14562
[36m(train_xgb_ray_tune pid=398913)[0m [433]	train-mlogloss:2.16175	validation-mlogloss:2.17645
[36m(train_xgb_ray_tune pid=398901)[0m [331]	train-mlogloss:1.71895	validation-mlogloss:1.75565
[36m(train_xgb_ray_tune pid=398914)[0m [315]	train-mlogloss:1.68594	validation-mlogloss:1.73817
[36m(train_xgb_ray_tune pid=398916)[0m [329]	train-mlogloss:2.34155	validation-mlogloss:2.33577
[36m(train_xgb_ray_tune pid=398886)[0m [336]	train-mlogloss:1.69933	validation-mlogloss:1.73310
[36m(train_xgb_ray_tune pid=398904)[0m [333]	train-mlogloss:2.13196	validation-mlogloss:2.09226
[36m(train_xgb_ray_tune pid=398894)[0m [323]	train-mlogloss:1.93523	validation-mlogloss:1.91413
[36m(train_xgb_ray_tune pid=398880)[0m [349]	train-mlogloss:1.67482	validation-mlogloss:1.72617
[36m(train_xgb_ray_tune pid=398902)[0m [374]	train-mlogloss:1.87281	validation-mlogloss:1.85119
[36m(train_xgb_ray_tune pid=398918)[0m [340]	train-mlogloss:2.18528	validation-mlogloss:2.14487
[36m(train_xgb_ray_tune pid=398913)[0m [434]	train-mlogloss:2.16175	validation-mlogloss:2.17645
[36m(train_xgb_ray_tune pid=398917)[0m [327]	train-mlogloss:1.81604	validation-mlogloss:1.82414
[36m(train_xgb_ray_tune pid=398892)[0m [349]	train-mlogloss:1.84066	validation-mlogloss:1.83309
[36m(train_xgb_ray_tune pid=398903)[0m [346]	train-mlogloss:1.88567	validation-mlogloss:1.87329
[36m(train_xgb_ray_tune pid=398912)[0m [337]	train-mlogloss:1.84825	validation-mlogloss:1.84367
[36m(train_xgb_ray_tune pid=398906)[0m [348]	train-mlogloss:1.84066	validation-mlogloss:1.82762
[36m(train_xgb_ray_tune pid=398916)[0m [330]	train-mlogloss:2.34090	validation-mlogloss:2.33518
[36m(train_xgb_ray_tune pid=398904)[0m [334]	train-mlogloss:2.13100	validation-mlogloss:2.09132
[36m(train_xgb_ray_tune pid=398879)[0m [325]	train-mlogloss:1.67495	validation-mlogloss:1.73991
[36m(train_xgb_ray_tune pid=398915)[0m [377]	train-mlogloss:2.04822	validation-mlogloss:2.00974
[36m(train_xgb_ray_tune pid=398900)[0m [335]	train-mlogloss:2.16730	validation-mlogloss:2.12697
[36m(train_xgb_ray_tune pid=398905)[0m [326]	train-mlogloss:1.85655	validation-mlogloss:1.85004
[36m(train_xgb_ray_tune pid=398913)[0m [435]	train-mlogloss:2.16175	validation-mlogloss:2.17645
[36m(train_xgb_ray_tune pid=398901)[0m [332]	train-mlogloss:1.71809	validation-mlogloss:1.75510
[36m(train_xgb_ray_tune pid=398914)[0m [316]	train-mlogloss:1.68495	validation-mlogloss:1.73787
[36m(train_xgb_ray_tune pid=398917)[0m [328]	train-mlogloss:1.81509	validation-mlogloss:1.82342
[36m(train_xgb_ray_tune pid=398892)[0m [350]	train-mlogloss:1.83996	validation-mlogloss:1.83259
[36m(train_xgb_ray_tune pid=398886)[0m [337]	train-mlogloss:1.69851	validation-mlogloss:1.73238
[36m(train_xgb_ray_tune pid=398906)[0m [349]	train-mlogloss:1.83995	validation-mlogloss:1.82711
[36m(train_xgb_ray_tune pid=398894)[0m [324]	train-mlogloss:1.93427	validation-mlogloss:1.91318
[36m(train_xgb_ray_tune pid=398880)[0m [350]	train-mlogloss:1.67402	validation-mlogloss:1.72588
[36m(train_xgb_ray_tune pid=398915)[0m [378]	train-mlogloss:2.04737	validation-mlogloss:2.00893
[36m(train_xgb_ray_tune pid=398902)[0m [375]	train-mlogloss:1.87261	validation-mlogloss:1.85101
[36m(train_xgb_ray_tune pid=398918)[0m [341]	train-mlogloss:2.18445	validation-mlogloss:2.14406
[36m(train_xgb_ray_tune pid=398901)[0m [333]	train-mlogloss:1.71712	validation-mlogloss:1.75466
[36m(train_xgb_ray_tune pid=398886)[0m [338]	train-mlogloss:1.69765	validation-mlogloss:1.73188
[36m(train_xgb_ray_tune pid=398903)[0m [347]	train-mlogloss:1.88473	validation-mlogloss:1.87264
[36m(train_xgb_ray_tune pid=398912)[0m [338]	train-mlogloss:1.84733	validation-mlogloss:1.84299
[36m(train_xgb_ray_tune pid=398916)[0m [331]	train-mlogloss:2.34023	validation-mlogloss:2.33457
[36m(train_xgb_ray_tune pid=398904)[0m [335]	train-mlogloss:2.13007	validation-mlogloss:2.09044
[36m(train_xgb_ray_tune pid=398879)[0m [326]	train-mlogloss:1.67405	validation-mlogloss:1.73966
[36m(train_xgb_ray_tune pid=398900)[0m [336]	train-mlogloss:2.16639	validation-mlogloss:2.12614
[36m(train_xgb_ray_tune pid=398905)[0m [327]	train-mlogloss:1.85565	validation-mlogloss:1.84927
[36m(train_xgb_ray_tune pid=398902)[0m [376]	train-mlogloss:1.87258	validation-mlogloss:1.85105
[36m(train_xgb_ray_tune pid=398918)[0m [342]	train-mlogloss:2.18359	validation-mlogloss:2.14317
[36m(train_xgb_ray_tune pid=398913)[0m [436]	train-mlogloss:2.16170	validation-mlogloss:2.17636
[36m(train_xgb_ray_tune pid=398914)[0m [317]	train-mlogloss:1.68398	validation-mlogloss:1.73725
[36m(train_xgb_ray_tune pid=398917)[0m [329]	train-mlogloss:1.81415	validation-mlogloss:1.82264
[36m(train_xgb_ray_tune pid=398892)[0m [351]	train-mlogloss:1.83914	validation-mlogloss:1.83197
[36m(train_xgb_ray_tune pid=398906)[0m [350]	train-mlogloss:1.83940	validation-mlogloss:1.82681
[36m(train_xgb_ray_tune pid=398894)[0m [325]	train-mlogloss:1.93330	validation-mlogloss:1.91246
[36m(train_xgb_ray_tune pid=398880)[0m [351]	train-mlogloss:1.67329	validation-mlogloss:1.72549
[36m(train_xgb_ray_tune pid=398915)[0m [379]	train-mlogloss:2.04649	validation-mlogloss:2.00810
[36m(train_xgb_ray_tune pid=398900)[0m [337]	train-mlogloss:2.16551	validation-mlogloss:2.12526
[36m(train_xgb_ray_tune pid=398905)[0m [328]	train-mlogloss:1.85487	validation-mlogloss:1.84854
[36m(train_xgb_ray_tune pid=398902)[0m [377]	train-mlogloss:1.87235	validation-mlogloss:1.85084
[36m(train_xgb_ray_tune pid=398913)[0m [437]	train-mlogloss:2.16170	validation-mlogloss:2.17636
[36m(train_xgb_ray_tune pid=398901)[0m [334]	train-mlogloss:1.71627	validation-mlogloss:1.75434
[36m(train_xgb_ray_tune pid=398912)[0m [339]	train-mlogloss:1.84632	validation-mlogloss:1.84226
[36m(train_xgb_ray_tune pid=398886)[0m [339]	train-mlogloss:1.69685	validation-mlogloss:1.73156
[36m(train_xgb_ray_tune pid=398906)[0m [351]	train-mlogloss:1.83891	validation-mlogloss:1.82641
[36m(train_xgb_ray_tune pid=398916)[0m [332]	train-mlogloss:2.33960	validation-mlogloss:2.33402
[36m(train_xgb_ray_tune pid=398904)[0m [336]	train-mlogloss:2.12915	validation-mlogloss:2.08954
[36m(train_xgb_ray_tune pid=398879)[0m [327]	train-mlogloss:1.67312	validation-mlogloss:1.73929
[36m(train_xgb_ray_tune pid=398915)[0m [380]	train-mlogloss:2.04569	validation-mlogloss:2.00742
[36m(train_xgb_ray_tune pid=398902)[0m [378]	train-mlogloss:1.87215	validation-mlogloss:1.85069
[36m(train_xgb_ray_tune pid=398918)[0m [343]	train-mlogloss:2.18274	validation-mlogloss:2.14236
[36m(train_xgb_ray_tune pid=398913)[0m [438]	train-mlogloss:2.16163	validation-mlogloss:2.17634
[36m(train_xgb_ray_tune pid=398914)[0m [318]	train-mlogloss:1.68306	validation-mlogloss:1.73673
[36m(train_xgb_ray_tune pid=398917)[0m [330]	train-mlogloss:1.81321	validation-mlogloss:1.82196
[36m(train_xgb_ray_tune pid=398892)[0m [352]	train-mlogloss:1.83852	validation-mlogloss:1.83134
[36m(train_xgb_ray_tune pid=398893)[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=398893)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=398914)[0m 2025-10-27 09:34:18.901622: 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=398901)[0m 2025-10-27 09:34:18.975248: 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=398901)[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=398901)[0m E0000 00:00:1761554059.002828  400187 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=398901)[0m E0000 00:00:1761554059.011172  400187 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=398914)[0m W0000 00:00:1761554058.987345  400173 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=398914)[0m 2025-10-27 09:34:18.992633: 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=398914)[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=398903)[0m [348]	train-mlogloss:1.88378	validation-mlogloss:1.87185
[36m(train_xgb_ray_tune pid=398894)[0m [326]	train-mlogloss:1.93222	validation-mlogloss:1.91144
[36m(train_xgb_ray_tune pid=398880)[0m [352]	train-mlogloss:1.67252	validation-mlogloss:1.72513
[36m(train_xgb_ray_tune pid=398901)[0m [335]	train-mlogloss:1.71532	validation-mlogloss:1.75381
[36m(train_xgb_ray_tune pid=398912)[0m [340]	train-mlogloss:1.84538	validation-mlogloss:1.84156
[36m(train_xgb_ray_tune pid=398906)[0m [352]	train-mlogloss:1.83834	validation-mlogloss:1.82590
[36m(train_xgb_ray_tune pid=398916)[0m [333]	train-mlogloss:2.33895	validation-mlogloss:2.33338
[36m(train_xgb_ray_tune pid=398904)[0m [337]	train-mlogloss:2.12823	validation-mlogloss:2.08861
[36m(train_xgb_ray_tune pid=398879)[0m [328]	train-mlogloss:1.67231	validation-mlogloss:1.73897
[36m(train_xgb_ray_tune pid=398900)[0m [338]	train-mlogloss:2.16459	validation-mlogloss:2.12444
[36m(train_xgb_ray_tune pid=398905)[0m [329]	train-mlogloss:1.85406	validation-mlogloss:1.84773
[36m(train_xgb_ray_tune pid=398902)[0m [379]	train-mlogloss:1.87197	validation-mlogloss:1.85060
[36m(train_xgb_ray_tune pid=398918)[0m [344]	train-mlogloss:2.18189	validation-mlogloss:2.14153
[36m(train_xgb_ray_tune pid=398913)[0m [439]	train-mlogloss:2.16149	validation-mlogloss:2.17620
[36m(train_xgb_ray_tune pid=398886)[0m [340]	train-mlogloss:1.69595	validation-mlogloss:1.73101
[36m(train_xgb_ray_tune pid=398903)[0m [349]	train-mlogloss:1.88288	validation-mlogloss:1.87121
[36m(train_xgb_ray_tune pid=398894)[0m [327]	train-mlogloss:1.93125	validation-mlogloss:1.91058
[36m(train_xgb_ray_tune pid=398880)[0m [353]	train-mlogloss:1.67175	validation-mlogloss:1.72467
[36m(train_xgb_ray_tune pid=398915)[0m [381]	train-mlogloss:2.04483	validation-mlogloss:2.00670
[36m(train_xgb_ray_tune pid=398902)[0m [380]	train-mlogloss:1.87197	validation-mlogloss:1.85060
[36m(train_xgb_ray_tune pid=398901)[0m [336]	train-mlogloss:1.71447	validation-mlogloss:1.75349
[36m(train_xgb_ray_tune pid=398917)[0m [331]	train-mlogloss:1.81233	validation-mlogloss:1.82130
[36m(train_xgb_ray_tune pid=398892)[0m [353]	train-mlogloss:1.83776	validation-mlogloss:1.83061
[36m(train_xgb_ray_tune pid=398913)[0m [440]	train-mlogloss:2.16134	validation-mlogloss:2.17607
[36m(train_xgb_ray_tune pid=398912)[0m [341]	train-mlogloss:1.84442	validation-mlogloss:1.84068
[36m(train_xgb_ray_tune pid=398906)[0m [353]	train-mlogloss:1.83770	validation-mlogloss:1.82531
[36m(train_xgb_ray_tune pid=398916)[0m [334]	train-mlogloss:2.33830	validation-mlogloss:2.33277
[36m(train_xgb_ray_tune pid=398904)[0m [338]	train-mlogloss:2.12728	validation-mlogloss:2.08767
[36m(train_xgb_ray_tune pid=398879)[0m [329]	train-mlogloss:1.67135	validation-mlogloss:1.73843
[36m(train_xgb_ray_tune pid=398915)[0m [382]	train-mlogloss:2.04405	validation-mlogloss:2.00592
[36m(train_xgb_ray_tune pid=398900)[0m [339]	train-mlogloss:2.16369	validation-mlogloss:2.12352
[36m(train_xgb_ray_tune pid=398905)[0m [330]	train-mlogloss:1.85324	validation-mlogloss:1.84710
[36m(train_xgb_ray_tune pid=398902)[0m [381]	train-mlogloss:1.87177	validation-mlogloss:1.85035
[36m(train_xgb_ray_tune pid=398918)[0m [345]	train-mlogloss:2.18103	validation-mlogloss:2.14067
[36m(train_xgb_ray_tune pid=398917)[0m [332]	train-mlogloss:1.81140	validation-mlogloss:1.82066
[36m(train_xgb_ray_tune pid=398886)[0m [341]	train-mlogloss:1.69513	validation-mlogloss:1.73062
[36m(train_xgb_ray_tune pid=398903)[0m [350]	train-mlogloss:1.88194	validation-mlogloss:1.87039
[36m(train_xgb_ray_tune pid=398906)[0m [354]	train-mlogloss:1.83708	validation-mlogloss:1.82485
[36m(train_xgb_ray_tune pid=398894)[0m [328]	train-mlogloss:1.93028	validation-mlogloss:1.90974
[36m(train_xgb_ray_tune pid=398880)[0m [354]	train-mlogloss:1.67095	validation-mlogloss:1.72434
[36m(train_xgb_ray_tune pid=398915)[0m [383]	train-mlogloss:2.04326	validation-mlogloss:2.00519
[36m(train_xgb_ray_tune pid=398905)[0m [331]	train-mlogloss:1.85245	validation-mlogloss:1.84619
[36m(train_xgb_ray_tune pid=398913)[0m [441]	train-mlogloss:2.16134	validation-mlogloss:2.17607
[36m(train_xgb_ray_tune pid=398901)[0m [337]	train-mlogloss:1.71364	validation-mlogloss:1.75308
[36m(train_xgb_ray_tune pid=398892)[0m [354]	train-mlogloss:1.83697	validation-mlogloss:1.83006
[36m(train_xgb_ray_tune pid=398912)[0m [342]	train-mlogloss:1.84348	validation-mlogloss:1.83989
[36m(train_xgb_ray_tune pid=398900)[0m [340]	train-mlogloss:2.16281	validation-mlogloss:2.12267
[36m(train_xgb_ray_tune pid=398906)[0m [355]	train-mlogloss:1.83636	validation-mlogloss:1.82425
[36m(train_xgb_ray_tune pid=398916)[0m [335]	train-mlogloss:2.33760	validation-mlogloss:2.33206
[36m(train_xgb_ray_tune pid=398904)[0m [339]	train-mlogloss:2.12635	validation-mlogloss:2.08673
[36m(train_xgb_ray_tune pid=398879)[0m [330]	train-mlogloss:1.67045	validation-mlogloss:1.73777
[36m(train_xgb_ray_tune pid=398915)[0m [384]	train-mlogloss:2.04244	validation-mlogloss:2.00454
[36m(train_xgb_ray_tune pid=398902)[0m [382]	train-mlogloss:1.87141	validation-mlogloss:1.85018
[36m(train_xgb_ray_tune pid=398918)[0m [346]	train-mlogloss:2.18019	validation-mlogloss:2.13989
[36m(train_xgb_ray_tune pid=398913)[0m [442]	train-mlogloss:2.16134	validation-mlogloss:2.17607
[36m(train_xgb_ray_tune pid=398917)[0m [333]	train-mlogloss:1.81044	validation-mlogloss:1.81995
[36m(train_xgb_ray_tune pid=398901)[0m [338]	train-mlogloss:1.71278	validation-mlogloss:1.75257
[36m(train_xgb_ray_tune pid=398886)[0m [342]	train-mlogloss:1.69434	validation-mlogloss:1.72998

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:35:44. Total running time: 1min 28s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             85.8844 │
│ time_total_s                 85.8844 │
│ training_iteration                 1 │
│ validation_accuracy          0.50864 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:35:44. Total running time: 1min 28s
[36m(train_xgb_ray_tune pid=398903)[0m [351]	train-mlogloss:1.88107	validation-mlogloss:1.86970
[36m(train_xgb_ray_tune pid=398912)[0m [343]	train-mlogloss:1.84255	validation-mlogloss:1.83910
[36m(train_xgb_ray_tune pid=398916)[0m [336]	train-mlogloss:2.33694	validation-mlogloss:2.33135
[36m(train_xgb_ray_tune pid=398894)[0m [329]	train-mlogloss:1.92936	validation-mlogloss:1.90908
[36m(train_xgb_ray_tune pid=398880)[0m [355]	train-mlogloss:1.67020	validation-mlogloss:1.72418
[36m(train_xgb_ray_tune pid=398900)[0m [341]	train-mlogloss:2.16192	validation-mlogloss:2.12180
[36m(train_xgb_ray_tune pid=398905)[0m [332]	train-mlogloss:1.85162	validation-mlogloss:1.84544
[36m(train_xgb_ray_tune pid=398902)[0m [383]	train-mlogloss:1.87116	validation-mlogloss:1.84980
[36m(train_xgb_ray_tune pid=398918)[0m [347]	train-mlogloss:2.17931	validation-mlogloss:2.13903
[36m(train_xgb_ray_tune pid=398913)[0m [443]	train-mlogloss:2.16128	validation-mlogloss:2.17604
[36m(train_xgb_ray_tune pid=398892)[0m [355]	train-mlogloss:1.83634	validation-mlogloss:1.82949
[36m(train_xgb_ray_tune pid=398906)[0m [356]	train-mlogloss:1.83579	validation-mlogloss:1.82377
[36m(train_xgb_ray_tune pid=398904)[0m [340]	train-mlogloss:2.12542	validation-mlogloss:2.08587
[36m(train_xgb_ray_tune pid=398915)[0m [385]	train-mlogloss:2.04157	validation-mlogloss:2.00369
[36m(train_xgb_ray_tune pid=398886)[0m [343]	train-mlogloss:1.69352	validation-mlogloss:1.72954
[36m(train_xgb_ray_tune pid=398879)[0m [331]	train-mlogloss:1.66956	validation-mlogloss:1.73722
[36m(train_xgb_ray_tune pid=398880)[0m [356]	train-mlogloss:1.66940	validation-mlogloss:1.72394
[36m(train_xgb_ray_tune pid=398902)[0m [384]	train-mlogloss:1.87095	validation-mlogloss:1.84957
[36m(train_xgb_ray_tune pid=398913)[0m [444]	train-mlogloss:2.16119	validation-mlogloss:2.17592
[36m(train_xgb_ray_tune pid=398901)[0m [339]	train-mlogloss:1.71179	validation-mlogloss:1.75200
[36m(train_xgb_ray_tune pid=398917)[0m [334]	train-mlogloss:1.80947	validation-mlogloss:1.81941
[36m(train_xgb_ray_tune pid=398892)[0m [356]	train-mlogloss:1.83555	validation-mlogloss:1.82888
[36m(train_xgb_ray_tune pid=398905)[0m [333]	train-mlogloss:1.85086	validation-mlogloss:1.84482
[36m(train_xgb_ray_tune pid=398913)[0m [445]	train-mlogloss:2.16119	validation-mlogloss:2.17592
[36m(train_xgb_ray_tune pid=398903)[0m [352]	train-mlogloss:1.88022	validation-mlogloss:1.86893
[36m(train_xgb_ray_tune pid=398912)[0m [344]	train-mlogloss:1.84164	validation-mlogloss:1.83834
[36m(train_xgb_ray_tune pid=398906)[0m [357]	train-mlogloss:1.83516	validation-mlogloss:1.82331
[36m(train_xgb_ray_tune pid=398916)[0m [337]	train-mlogloss:2.33626	validation-mlogloss:2.33073
[36m(train_xgb_ray_tune pid=398904)[0m [341]	train-mlogloss:2.12446	validation-mlogloss:2.08494
[36m(train_xgb_ray_tune pid=398879)[0m [332]	train-mlogloss:1.66874	validation-mlogloss:1.73702
[36m(train_xgb_ray_tune pid=398894)[0m [330]	train-mlogloss:1.92842	validation-mlogloss:1.90843
[36m(train_xgb_ray_tune pid=398915)[0m [386]	train-mlogloss:2.04069	validation-mlogloss:2.00279
[36m(train_xgb_ray_tune pid=398900)[0m [342]	train-mlogloss:2.16106	validation-mlogloss:2.12094
[36m(train_xgb_ray_tune pid=398902)[0m [385]	train-mlogloss:1.87095	validation-mlogloss:1.84957
[36m(train_xgb_ray_tune pid=398918)[0m [348]	train-mlogloss:2.17849	validation-mlogloss:2.13830
[36m(train_xgb_ray_tune pid=398913)[0m [446]	train-mlogloss:2.16103	validation-mlogloss:2.17563
[36m(train_xgb_ray_tune pid=398901)[0m [340]	train-mlogloss:1.71088	validation-mlogloss:1.75158
[36m(train_xgb_ray_tune pid=398917)[0m [335]	train-mlogloss:1.80861	validation-mlogloss:1.81876
[36m(train_xgb_ray_tune pid=398886)[0m [344]	train-mlogloss:1.69263	validation-mlogloss:1.72918
[36m(train_xgb_ray_tune pid=398903)[0m [353]	train-mlogloss:1.87940	validation-mlogloss:1.86828
[36m(train_xgb_ray_tune pid=398906)[0m [358]	train-mlogloss:1.83449	validation-mlogloss:1.82287
[36m(train_xgb_ray_tune pid=398916)[0m [338]	train-mlogloss:2.33563	validation-mlogloss:2.33010
[36m(train_xgb_ray_tune pid=398880)[0m [357]	train-mlogloss:1.66865	validation-mlogloss:1.72366
[36m(train_xgb_ray_tune pid=398915)[0m [387]	train-mlogloss:2.03987	validation-mlogloss:2.00197
[36m(train_xgb_ray_tune pid=398900)[0m [343]	train-mlogloss:2.16018	validation-mlogloss:2.12006
[36m(train_xgb_ray_tune pid=398905)[0m [334]	train-mlogloss:1.85007	validation-mlogloss:1.84415
[36m(train_xgb_ray_tune pid=398902)[0m [386]	train-mlogloss:1.87073	validation-mlogloss:1.84942
[36m(train_xgb_ray_tune pid=398918)[0m [349]	train-mlogloss:2.17766	validation-mlogloss:2.13752
[36m(train_xgb_ray_tune pid=398913)[0m [447]	train-mlogloss:2.16103	validation-mlogloss:2.17563
[36m(train_xgb_ray_tune pid=398892)[0m [357]	train-mlogloss:1.83484	validation-mlogloss:1.82828
[36m(train_xgb_ray_tune pid=398912)[0m [345]	train-mlogloss:1.84067	validation-mlogloss:1.83754
[36m(train_xgb_ray_tune pid=398904)[0m [342]	train-mlogloss:2.12351	validation-mlogloss:2.08401
[36m(train_xgb_ray_tune pid=398879)[0m [333]	train-mlogloss:1.66781	validation-mlogloss:1.73646
[36m(train_xgb_ray_tune pid=398894)[0m [331]	train-mlogloss:1.92744	validation-mlogloss:1.90752
[36m(train_xgb_ray_tune pid=398901)[0m [341]	train-mlogloss:1.70999	validation-mlogloss:1.75103
[36m(train_xgb_ray_tune pid=398917)[0m [336]	train-mlogloss:1.80770	validation-mlogloss:1.81828
[36m(train_xgb_ray_tune pid=398892)[0m [358]	train-mlogloss:1.83400	validation-mlogloss:1.82785
[36m(train_xgb_ray_tune pid=398886)[0m [345]	train-mlogloss:1.69175	validation-mlogloss:1.72880
[36m(train_xgb_ray_tune pid=398880)[0m [358]	train-mlogloss:1.66791	validation-mlogloss:1.72312
[36m(train_xgb_ray_tune pid=398903)[0m [354]	train-mlogloss:1.87849	validation-mlogloss:1.86777
[36m(train_xgb_ray_tune pid=398906)[0m [359]	train-mlogloss:1.83391	validation-mlogloss:1.82244
[36m(train_xgb_ray_tune pid=398916)[0m [339]	train-mlogloss:2.33503	validation-mlogloss:2.32952
[36m(train_xgb_ray_tune pid=398915)[0m [388]	train-mlogloss:2.03905	validation-mlogloss:2.00130
[36m(train_xgb_ray_tune pid=398900)[0m [344]	train-mlogloss:2.15925	validation-mlogloss:2.11916
[36m(train_xgb_ray_tune pid=398905)[0m [335]	train-mlogloss:1.84928	validation-mlogloss:1.84350
[36m(train_xgb_ray_tune pid=398902)[0m [387]	train-mlogloss:1.87052	validation-mlogloss:1.84914
[36m(train_xgb_ray_tune pid=398918)[0m [350]	train-mlogloss:2.17688	validation-mlogloss:2.13687
[36m(train_xgb_ray_tune pid=398913)[0m [448]	train-mlogloss:2.16103	validation-mlogloss:2.17563
[36m(train_xgb_ray_tune pid=398912)[0m [346]	train-mlogloss:1.83979	validation-mlogloss:1.83702
[36m(train_xgb_ray_tune pid=398904)[0m [343]	train-mlogloss:2.12262	validation-mlogloss:2.08314
[36m(train_xgb_ray_tune pid=398894)[0m [332]	train-mlogloss:1.92650	validation-mlogloss:1.90670
[36m(train_xgb_ray_tune pid=398886)[0m [346]	train-mlogloss:1.69097	validation-mlogloss:1.72864
[36m(train_xgb_ray_tune pid=398906)[0m [360]	train-mlogloss:1.83338	validation-mlogloss:1.82187
[36m(train_xgb_ray_tune pid=398879)[0m [334]	train-mlogloss:1.66689	validation-mlogloss:1.73575
[36m(train_xgb_ray_tune pid=398880)[0m [359]	train-mlogloss:1.66710	validation-mlogloss:1.72267
[36m(train_xgb_ray_tune pid=398900)[0m [345]	train-mlogloss:2.15841	validation-mlogloss:2.11835
[36m(train_xgb_ray_tune pid=398902)[0m [388]	train-mlogloss:1.87015	validation-mlogloss:1.84883
[36m(train_xgb_ray_tune pid=398913)[0m [449]	train-mlogloss:2.16103	validation-mlogloss:2.17563
[36m(train_xgb_ray_tune pid=398901)[0m [342]	train-mlogloss:1.70909	validation-mlogloss:1.75058
[36m(train_xgb_ray_tune pid=398917)[0m [337]	train-mlogloss:1.80680	validation-mlogloss:1.81771
[36m(train_xgb_ray_tune pid=398892)[0m [359]	train-mlogloss:1.83315	validation-mlogloss:1.82715
[36m(train_xgb_ray_tune pid=398903)[0m [355]	train-mlogloss:1.87762	validation-mlogloss:1.86709
[36m(train_xgb_ray_tune pid=398912)[0m [347]	train-mlogloss:1.83883	validation-mlogloss:1.83630
[36m(train_xgb_ray_tune pid=398916)[0m [340]	train-mlogloss:2.33439	validation-mlogloss:2.32889
[36m(train_xgb_ray_tune pid=398904)[0m [344]	train-mlogloss:2.12170	validation-mlogloss:2.08238
[36m(train_xgb_ray_tune pid=398894)[0m [333]	train-mlogloss:1.92554	validation-mlogloss:1.90593
[36m(train_xgb_ray_tune pid=398915)[0m [389]	train-mlogloss:2.03822	validation-mlogloss:2.00051
[36m(train_xgb_ray_tune pid=398900)[0m [346]	train-mlogloss:2.15757	validation-mlogloss:2.11754
[36m(train_xgb_ray_tune pid=398905)[0m [336]	train-mlogloss:1.84848	validation-mlogloss:1.84282
[36m(train_xgb_ray_tune pid=398902)[0m [389]	train-mlogloss:1.87007	validation-mlogloss:1.84879
[36m(train_xgb_ray_tune pid=398918)[0m [351]	train-mlogloss:2.17604	validation-mlogloss:2.13599
[36m(train_xgb_ray_tune pid=398913)[0m [450]	train-mlogloss:2.16092	validation-mlogloss:2.17549
[36m(train_xgb_ray_tune pid=398901)[0m [343]	train-mlogloss:1.70818	validation-mlogloss:1.74991
[36m(train_xgb_ray_tune pid=398886)[0m [347]	train-mlogloss:1.69020	validation-mlogloss:1.72820
[36m(train_xgb_ray_tune pid=398906)[0m [361]	train-mlogloss:1.83277	validation-mlogloss:1.82138
[36m(train_xgb_ray_tune pid=398879)[0m [335]	train-mlogloss:1.66600	validation-mlogloss:1.73505
[36m(train_xgb_ray_tune pid=398880)[0m [360]	train-mlogloss:1.66638	validation-mlogloss:1.72240
[36m(train_xgb_ray_tune pid=398913)[0m [451]	train-mlogloss:2.16081	validation-mlogloss:2.17538
[36m(train_xgb_ray_tune pid=398892)[0m [360]	train-mlogloss:1.83234	validation-mlogloss:1.82640
[36m(train_xgb_ray_tune pid=398916)[0m [341]	train-mlogloss:2.33375	validation-mlogloss:2.32821
[36m(train_xgb_ray_tune pid=398915)[0m [390]	train-mlogloss:2.03744	validation-mlogloss:1.99973

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:35:45. Total running time: 1min 29s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             86.7446 │
│ time_total_s                 86.7446 │
│ training_iteration                 1 │
│ validation_accuracy          0.51261 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=398903)[0m [356]	train-mlogloss:1.87674	validation-mlogloss:1.86637
[36m(train_xgb_ray_tune pid=398912)[0m [348]	train-mlogloss:1.83786	validation-mlogloss:1.83557
[36m(train_xgb_ray_tune pid=398904)[0m [345]	train-mlogloss:2.12079	validation-mlogloss:2.08153
[36m(train_xgb_ray_tune pid=398879)[0m [336]	train-mlogloss:1.66512	validation-mlogloss:1.73448
[36m(train_xgb_ray_tune pid=398894)[0m [334]	train-mlogloss:1.92455	validation-mlogloss:1.90504
[36m(train_xgb_ray_tune pid=398880)[0m [361]	train-mlogloss:1.66566	validation-mlogloss:1.72204

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:35:45. Total running time: 1min 29s
[36m(train_xgb_ray_tune pid=398900)[0m [347]	train-mlogloss:2.15670	validation-mlogloss:2.11666
[36m(train_xgb_ray_tune pid=398905)[0m [337]	train-mlogloss:1.84766	validation-mlogloss:1.84227
[36m(train_xgb_ray_tune pid=398902)[0m [390]	train-mlogloss:1.86975	validation-mlogloss:1.84842
[36m(train_xgb_ray_tune pid=398918)[0m [352]	train-mlogloss:2.17520	validation-mlogloss:2.13522
[36m(train_xgb_ray_tune pid=398913)[0m [452]	train-mlogloss:2.16081	validation-mlogloss:2.17538
[36m(train_xgb_ray_tune pid=398913)[0m [453]	train-mlogloss:2.16081	validation-mlogloss:2.17538
[36m(train_xgb_ray_tune pid=398901)[0m [344]	train-mlogloss:1.70728	validation-mlogloss:1.74952
[36m(train_xgb_ray_tune pid=398917)[0m [338]	train-mlogloss:1.80586	validation-mlogloss:1.81687
[36m(train_xgb_ray_tune pid=398892)[0m [361]	train-mlogloss:1.83162	validation-mlogloss:1.82571
[36m(train_xgb_ray_tune pid=398886)[0m [348]	train-mlogloss:1.68952	validation-mlogloss:1.72788
[36m(train_xgb_ray_tune pid=398903)[0m [357]	train-mlogloss:1.87578	validation-mlogloss:1.86541
[36m(train_xgb_ray_tune pid=398906)[0m [362]	train-mlogloss:1.83215	validation-mlogloss:1.82085
[36m(train_xgb_ray_tune pid=398916)[0m [342]	train-mlogloss:2.33311	validation-mlogloss:2.32757
[36m(train_xgb_ray_tune pid=398915)[0m [391]	train-mlogloss:2.03656	validation-mlogloss:1.99888
[36m(train_xgb_ray_tune pid=398900)[0m [348]	train-mlogloss:2.15584	validation-mlogloss:2.11578
[36m(train_xgb_ray_tune pid=398902)[0m [391]	train-mlogloss:1.86963	validation-mlogloss:1.84833
[36m(train_xgb_ray_tune pid=398918)[0m [353]	train-mlogloss:2.17437	validation-mlogloss:2.13444
[36m(train_xgb_ray_tune pid=398913)[0m [454]	train-mlogloss:2.16075	validation-mlogloss:2.17534
[36m(train_xgb_ray_tune pid=398917)[0m [339]	train-mlogloss:1.80491	validation-mlogloss:1.81615
[36m(train_xgb_ray_tune pid=398912)[0m [349]	train-mlogloss:1.83694	validation-mlogloss:1.83496
[36m(train_xgb_ray_tune pid=398904)[0m [346]	train-mlogloss:2.11991	validation-mlogloss:2.08069
[36m(train_xgb_ray_tune pid=398894)[0m [335]	train-mlogloss:1.92354	validation-mlogloss:1.90409
[36m(train_xgb_ray_tune pid=398901)[0m [345]	train-mlogloss:1.70638	validation-mlogloss:1.74904
[36m(train_xgb_ray_tune pid=398886)[0m [349]	train-mlogloss:1.68871	validation-mlogloss:1.72757
[36m(train_xgb_ray_tune pid=398906)[0m [363]	train-mlogloss:1.83160	validation-mlogloss:1.82042
[36m(train_xgb_ray_tune pid=398879)[0m [337]	train-mlogloss:1.66422	validation-mlogloss:1.73411
[36m(train_xgb_ray_tune pid=398880)[0m [362]	train-mlogloss:1.66478	validation-mlogloss:1.72167
[36m(train_xgb_ray_tune pid=398915)[0m [392]	train-mlogloss:2.03582	validation-mlogloss:1.99826
[36m(train_xgb_ray_tune pid=398905)[0m [338]	train-mlogloss:1.84686	validation-mlogloss:1.84162
[36m(train_xgb_ray_tune pid=398902)[0m [392]	train-mlogloss:1.86946	validation-mlogloss:1.84822
[36m(train_xgb_ray_tune pid=398913)[0m [455]	train-mlogloss:2.16075	validation-mlogloss:2.17534
[36m(train_xgb_ray_tune pid=398892)[0m [362]	train-mlogloss:1.83082	validation-mlogloss:1.82504
[36m(train_xgb_ray_tune pid=398916)[0m [343]	train-mlogloss:2.33244	validation-mlogloss:2.32687
[36m(train_xgb_ray_tune pid=398903)[0m [358]	train-mlogloss:1.87487	validation-mlogloss:1.86474
[36m(train_xgb_ray_tune pid=398912)[0m [350]	train-mlogloss:1.83610	validation-mlogloss:1.83440
[36m(train_xgb_ray_tune pid=398894)[0m [336]	train-mlogloss:1.92260	validation-mlogloss:1.90327
[36m(train_xgb_ray_tune pid=398880)[0m [363]	train-mlogloss:1.66399	validation-mlogloss:1.72142
[36m(train_xgb_ray_tune pid=398900)[0m [349]	train-mlogloss:2.15492	validation-mlogloss:2.11486
[36m(train_xgb_ray_tune pid=398905)[0m [339]	train-mlogloss:1.84607	validation-mlogloss:1.84091
[36m(train_xgb_ray_tune pid=398902)[0m [393]	train-mlogloss:1.86936	validation-mlogloss:1.84814
[36m(train_xgb_ray_tune pid=398918)[0m [354]	train-mlogloss:2.17353	validation-mlogloss:2.13364
[36m(train_xgb_ray_tune pid=398913)[0m [456]	train-mlogloss:2.16069	validation-mlogloss:2.17530
[36m(train_xgb_ray_tune pid=398901)[0m [346]	train-mlogloss:1.70554	validation-mlogloss:1.74846
[36m(train_xgb_ray_tune pid=398917)[0m [340]	train-mlogloss:1.80399	validation-mlogloss:1.81541
[36m(train_xgb_ray_tune pid=398892)[0m [363]	train-mlogloss:1.83014	validation-mlogloss:1.82437
[36m(train_xgb_ray_tune pid=398906)[0m [364]	train-mlogloss:1.83092	validation-mlogloss:1.82001
[36m(train_xgb_ray_tune pid=398879)[0m [338]	train-mlogloss:1.66342	validation-mlogloss:1.73384
[36m(train_xgb_ray_tune pid=398886)[0m [350]	train-mlogloss:1.68788	validation-mlogloss:1.72727

Trial status: 18 RUNNING | 2 TERMINATED
Current time: 2025-10-27 09:35:45. Total running time: 1min 30s
Logical resource usage: 18.0/20 CPUs, 0/1 GPUs (0.0/1.0 accelerator_type:G)
╭───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ Trial name     status         num_boost_round     max_depth     learning_rate     subsample     colsample_bytree     gamma     min_child_weight     reg_alpha     reg_lambda     random_state     iter     total time (s)     validation_accuracy │
├───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ trial_b8b81    RUNNING                    785             2        0.0152561       0.333235             0.509718   5.36058                   59      1.72191        0.791369             8764                                                     │
│ trial_b8b81    RUNNING                    436             2        0.0151967       0.687426             0.508211   3.6508                    32      0.236551       2.80111                23                                                     │
│ trial_b8b81    RUNNING                    540             2        0.0154571       0.498324             0.399232   7.5555                    57      0.518023       1.37493              3189                                                     │
│ trial_b8b81    RUNNING                    677             2        0.00718957      0.347983             0.517791   6.43243                   12      0.249615       2.3729               3650                                                     │
│ trial_b8b81    RUNNING                    347             2        0.00373864      0.624615             0.491362   7.40223                   33      0.177621      15.6491               4377                                                     │
│ trial_b8b81    RUNNING                    749             2        0.00684262      0.511093             0.642296   2.23501                   26      2.59404        5.58484              8397                                                     │
│ trial_b8b81    RUNNING                    550             2        0.0146521       0.333218             0.403476   8.58164                   12      8.33367       54.5003               6890                                                     │
│ trial_b8b81    RUNNING                    789             2        0.00862436      0.519278             0.453361   7.20008                   21      1.57911        3.85557               985                                                     │
│ trial_b8b81    RUNNING                    416             2        0.00418167      0.347849             0.419215   6.11886                   39      1.02586        0.871116             4157                                                     │
│ trial_b8b81    RUNNING                    737             2        0.0033156       0.459322             0.608053   3.18821                   28     93.719          1.30518              5776                                                     │
│ trial_b8b81    RUNNING                    650             2        0.00313347      0.693701             0.492938   9.79394                   12      1.55806        6.0203               5382                                                     │
│ trial_b8b81    RUNNING                    860             2        0.0136591       0.502887             0.62787    4.03237                   37     28.4997        51.4794               8253                                                     │
│ trial_b8b81    RUNNING                    500             2        0.0168463       0.316536             0.311578   7.53857                   21     25.6984         1.41457              2854                                                     │
│ trial_b8b81    RUNNING                    528             2        0.00285688      0.536565             0.651463   5.278                     25      2.19742        2.87126               507                                                     │
│ trial_b8b81    RUNNING                    783             2        0.0197427       0.306766             0.67443    7.59557                   58     66.8206        16.8769               7467                                                     │
│ trial_b8b81    RUNNING                    725             2        0.0143453       0.659911             0.418968   3.84157                   53      0.163473      19.04                 9244                                                     │
│ trial_b8b81    RUNNING                    601             2        0.0132953       0.653242             0.585449   3.87352                   49      4.74374       97.5749               9239                                                     │
│ trial_b8b81    RUNNING                    871             2        0.0139431       0.314738             0.444055   8.48731                   42      0.988245      70.352                9194                                                     │
│ trial_b8b81    TERMINATED                 353             2        0.00577946      0.588048             0.300442   8.55953                   34      5.80421        0.579503             5130        1            85.8844                0.508636 │
│ trial_b8b81    TERMINATED                 319             2        0.0172683       0.44677              0.688075   6.64719                   21      1.24884       27.0934               5802        1            86.7446                0.512607 │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=398915)[0m [393]	train-mlogloss:2.03502	validation-mlogloss:1.99755
[36m(train_xgb_ray_tune pid=398900)[0m [350]	train-mlogloss:2.15405	validation-mlogloss:2.11398
[36m(train_xgb_ray_tune pid=398913)[0m [457]	train-mlogloss:2.16058	validation-mlogloss:2.17517
[36m(train_xgb_ray_tune pid=398901)[0m [347]	train-mlogloss:1.70474	validation-mlogloss:1.74797
����P���p����p��k��Vq*�	@X�W�0��� ���pq�������������0���pq��p��������hq��[36m(train_xgb_ray_tune pid=398917)[0m [341]	train-mlogloss:1.80304	validation-mlogloss:1.81473
[36m(train_xgb_ray_tune pid=398902)[0m [394]	train-mlogloss:1.86921	validation-mlogloss:1.84789
[36m(train_xgb_ray_tune pid=398886)[0m [351]	train-mlogloss:1.68716	validation-mlogloss:1.72724
[36m(train_xgb_ray_tune pid=398912)[0m [351]	train-mlogloss:1.83525	validation-mlogloss:1.83381
[36m(train_xgb_ray_tune pid=398906)[0m [365]	train-mlogloss:1.83035	validation-mlogloss:1.81947
[36m(train_xgb_ray_tune pid=398879)[0m [339]	train-mlogloss:1.66258	validation-mlogloss:1.73342
[36m(train_xgb_ray_tune pid=398894)[0m [337]	train-mlogloss:1.92164	validation-mlogloss:1.90251
[36m(train_xgb_ray_tune pid=398915)[0m [394]	train-mlogloss:2.03423	validation-mlogloss:1.99683
[36m(train_xgb_ray_tune pid=398905)[0m [340]	train-mlogloss:1.84526	validation-mlogloss:1.84025
[36m(train_xgb_ray_tune pid=398902)[0m [395]	train-mlogloss:1.86898	validation-mlogloss:1.84777
[36m(train_xgb_ray_tune pid=398918)[0m [355]	train-mlogloss:2.17270	validation-mlogloss:2.13282
[36m(train_xgb_ray_tune pid=398913)[0m [458]	train-mlogloss:2.16047	validation-mlogloss:2.17501
[36m(train_xgb_ray_tune pid=398892)[0m [364]	train-mlogloss:1.82938	validation-mlogloss:1.82377
[36m(train_xgb_ray_tune pid=398916)[0m [345]	train-mlogloss:2.33123	validation-mlogloss:2.32571
[36m(train_xgb_ray_tune pid=398880)[0m [365]	train-mlogloss:1.66249	validation-mlogloss:1.72086
[36m(train_xgb_ray_tune pid=398903)[0m [360]	train-mlogloss:1.87306	validation-mlogloss:1.86342
[36m(train_xgb_ray_tune pid=398906)[0m [366]	train-mlogloss:1.82976	validation-mlogloss:1.81911
[36m(train_xgb_ray_tune pid=398879)[0m [340]	train-mlogloss:1.66163	validation-mlogloss:1.73325
[36m(train_xgb_ray_tune pid=398894)[0m [338]	train-mlogloss:1.92075	validation-mlogloss:1.90179
[36m(train_xgb_ray_tune pid=398915)[0m [395]	train-mlogloss:2.03344	validation-mlogloss:1.99615
[36m(train_xgb_ray_tune pid=398900)[0m [351]	train-mlogloss:2.15321	validation-mlogloss:2.11314
[36m(train_xgb_ray_tune pid=398902)[0m [396]	train-mlogloss:1.86891	validation-mlogloss:1.84766
[36m(train_xgb_ray_tune pid=398918)[0m [356]	train-mlogloss:2.17185	validation-mlogloss:2.13200
[36m(train_xgb_ray_tune pid=398913)[0m [459]	train-mlogloss:2.16047	validation-mlogloss:2.17501
[36m(train_xgb_ray_tune pid=398901)[0m [348]	train-mlogloss:1.70383	validation-mlogloss:1.74753
[36m(train_xgb_ray_tune pid=398917)[0m [342]	train-mlogloss:1.80216	validation-mlogloss:1.81420
[36m(train_xgb_ray_tune pid=398892)[0m [365]	train-mlogloss:1.82855	validation-mlogloss:1.82341
[36m(train_xgb_ray_tune pid=398886)[0m [352]	train-mlogloss:1.68635	validation-mlogloss:1.72698
[36m(train_xgb_ray_tune pid=398912)[0m [352]	train-mlogloss:1.83436	validation-mlogloss:1.83325
[36m(train_xgb_ray_tune pid=398880)[0m [366]	train-mlogloss:1.66180	validation-mlogloss:1.72036
[36m(train_xgb_ray_tune pid=398905)[0m [341]	train-mlogloss:1.84452	validation-mlogloss:1.83942
[36m(train_xgb_ray_tune pid=398913)[0m [460]	train-mlogloss:2.16040	validation-mlogloss:2.17498
[36m(train_xgb_ray_tune pid=398903)[0m [361]	train-mlogloss:1.87212	validation-mlogloss:1.86271
[36m(train_xgb_ray_tune pid=398906)[0m [367]	train-mlogloss:1.82926	validation-mlogloss:1.81872
[36m(train_xgb_ray_tune pid=398916)[0m [346]	train-mlogloss:2.33061	validation-mlogloss:2.32509
[36m(train_xgb_ray_tune pid=398894)[0m [339]	train-mlogloss:1.91977	validation-mlogloss:1.90096
[36m(train_xgb_ray_tune pid=398900)[0m [352]	train-mlogloss:2.15238	validation-mlogloss:2.11232
[36m(train_xgb_ray_tune pid=398901)[0m [349]	train-mlogloss:1.70311	validation-mlogloss:1.74715
[36m(train_xgb_ray_tune pid=398917)[0m [343]	train-mlogloss:1.80127	validation-mlogloss:1.81357
[36m(train_xgb_ray_tune pid=398892)[0m [366]	train-mlogloss:1.82783	validation-mlogloss:1.82291
[36m(train_xgb_ray_tune pid=398880)[0m [367]	train-mlogloss:1.66115	validation-mlogloss:1.72007
[36m(train_xgb_ray_tune pid=398915)[0m [396]	train-mlogloss:2.03263	validation-mlogloss:1.99545
[36m(train_xgb_ray_tune pid=398902)[0m [397]	train-mlogloss:1.86867	validation-mlogloss:1.84740
[36m(train_xgb_ray_tune pid=398913)[0m [461]	train-mlogloss:2.16040	validation-mlogloss:2.17498
[36m(train_xgb_ray_tune pid=398886)[0m [353]	train-mlogloss:1.68559	validation-mlogloss:1.72628
[36m(train_xgb_ray_tune pid=398912)[0m [353]	train-mlogloss:1.83346	validation-mlogloss:1.83269
[36m(train_xgb_ray_tune pid=398906)[0m [368]	train-mlogloss:1.82869	validation-mlogloss:1.81826
[36m(train_xgb_ray_tune pid=398916)[0m [347]	train-mlogloss:2.32998	validation-mlogloss:2.32447
[36m(train_xgb_ray_tune pid=398879)[0m [341]	train-mlogloss:1.66081	validation-mlogloss:1.73299
[36m(train_xgb_ray_tune pid=398905)[0m [342]	train-mlogloss:1.84376	validation-mlogloss:1.83877
[36m(train_xgb_ray_tune pid=398918)[0m [357]	train-mlogloss:2.17102	validation-mlogloss:2.13121
[36m(train_xgb_ray_tune pid=398913)[0m [462]	train-mlogloss:2.16040	validation-mlogloss:2.17498
[36m(train_xgb_ray_tune pid=398901)[0m [350]	train-mlogloss:1.70235	validation-mlogloss:1.74657
[36m(train_xgb_ray_tune pid=398903)[0m [362]	train-mlogloss:1.87125	validation-mlogloss:1.86190
[36m(train_xgb_ray_tune pid=398902)[0m [398]	train-mlogloss:1.86854	validation-mlogloss:1.84721
[36m(train_xgb_ray_tune pid=398917)[0m [344]	train-mlogloss:1.80036	validation-mlogloss:1.81298
[36m(train_xgb_ray_tune pid=398894)[0m [340]	train-mlogloss:1.91877	validation-mlogloss:1.90011
[36m(train_xgb_ray_tune pid=398880)[0m [368]	train-mlogloss:1.66043	validation-mlogloss:1.71978
[36m(train_xgb_ray_tune pid=398915)[0m [397]	train-mlogloss:2.03182	validation-mlogloss:1.99472
[36m(train_xgb_ray_tune pid=398886)[0m [354]	train-mlogloss:1.68485	validation-mlogloss:1.72622
[36m(train_xgb_ray_tune pid=398912)[0m [354]	train-mlogloss:1.83255	validation-mlogloss:1.83193
[36m(train_xgb_ray_tune pid=398906)[0m [369]	train-mlogloss:1.82830	validation-mlogloss:1.81796
[36m(train_xgb_ray_tune pid=398916)[0m [348]	train-mlogloss:2.32937	validation-mlogloss:2.32391
[36m(train_xgb_ray_tune pid=398879)[0m [342]	train-mlogloss:1.65998	validation-mlogloss:1.73265
[36m(train_xgb_ray_tune pid=398900)[0m [353]	train-mlogloss:2.15152	validation-mlogloss:2.11150
[36m(train_xgb_ray_tune pid=398905)[0m [343]	train-mlogloss:1.84291	validation-mlogloss:1.83815
[36m(train_xgb_ray_tune pid=398902)[0m [399]	train-mlogloss:1.86842	validation-mlogloss:1.84708
[36m(train_xgb_ray_tune pid=398918)[0m [358]	train-mlogloss:2.17018	validation-mlogloss:2.13039
[36m(train_xgb_ray_tune pid=398913)[0m [463]	train-mlogloss:2.16040	validation-mlogloss:2.17498
[36m(train_xgb_ray_tune pid=398901)[0m [351]	train-mlogloss:1.70159	validation-mlogloss:1.74602
[36m(train_xgb_ray_tune pid=398892)[0m [367]	train-mlogloss:1.82716	validation-mlogloss:1.82241
[36m(train_xgb_ray_tune pid=398903)[0m [363]	train-mlogloss:1.87037	validation-mlogloss:1.86127
[36m(train_xgb_ray_tune pid=398906)[0m [370]	train-mlogloss:1.82792	validation-mlogloss:1.81765
[36m(train_xgb_ray_tune pid=398916)[0m [349]	train-mlogloss:2.32875	validation-mlogloss:2.32329
[36m(train_xgb_ray_tune pid=398894)[0m [341]	train-mlogloss:1.91785	validation-mlogloss:1.89928
[36m(train_xgb_ray_tune pid=398880)[0m [369]	train-mlogloss:1.65964	validation-mlogloss:1.71930
[36m(train_xgb_ray_tune pid=398915)[0m [398]	train-mlogloss:2.03104	validation-mlogloss:1.99407
[36m(train_xgb_ray_tune pid=398900)[0m [354]	train-mlogloss:2.15065	validation-mlogloss:2.11062
[36m(train_xgb_ray_tune pid=398913)[0m [464]	train-mlogloss:2.16025	validation-mlogloss:2.17470
[36m(train_xgb_ray_tune pid=398917)[0m [345]	train-mlogloss:1.79955	validation-mlogloss:1.81246
[36m(train_xgb_ray_tune pid=398892)[0m [368]	train-mlogloss:1.82655	validation-mlogloss:1.82193
[36m(train_xgb_ray_tune pid=398886)[0m [355]	train-mlogloss:1.68413	validation-mlogloss:1.72581
[36m(train_xgb_ray_tune pid=398902)[0m [400]	train-mlogloss:1.86833	validation-mlogloss:1.84697
[36m(train_xgb_ray_tune pid=398901)[0m [352]	train-mlogloss:1.70083	validation-mlogloss:1.74558
[36m(train_xgb_ray_tune pid=398903)[0m [364]	train-mlogloss:1.86949	validation-mlogloss:1.86053
[36m(train_xgb_ray_tune pid=398912)[0m [355]	train-mlogloss:1.83168	validation-mlogloss:1.83134
[36m(train_xgb_ray_tune pid=398879)[0m [343]	train-mlogloss:1.65913	validation-mlogloss:1.73244
[36m(train_xgb_ray_tune pid=398880)[0m [370]	train-mlogloss:1.65880	validation-mlogloss:1.71907
[36m(train_xgb_ray_tune pid=398915)[0m [399]	train-mlogloss:2.03018	validation-mlogloss:1.99331
[36m(train_xgb_ray_tune pid=398905)[0m [344]	train-mlogloss:1.84215	validation-mlogloss:1.83761
[36m(train_xgb_ray_tune pid=398918)[0m [359]	train-mlogloss:2.16937	validation-mlogloss:2.12949
[36m(train_xgb_ray_tune pid=398913)[0m [465]	train-mlogloss:2.16018	validation-mlogloss:2.17465
[36m(train_xgb_ray_tune pid=398892)[0m [369]	train-mlogloss:1.82587	validation-mlogloss:1.82141
[36m(train_xgb_ray_tune pid=398886)[0m [356]	train-mlogloss:1.68345	validation-mlogloss:1.72540
[36m(train_xgb_ray_tune pid=398906)[0m [371]	train-mlogloss:1.82740	validation-mlogloss:1.81709
[36m(train_xgb_ray_tune pid=398916)[0m [350]	train-mlogloss:2.32814	validation-mlogloss:2.32270
[36m(train_xgb_ray_tune pid=398879)[0m [344]	train-mlogloss:1.65831	validation-mlogloss:1.73245
[36m(train_xgb_ray_tune pid=398894)[0m [342]	train-mlogloss:1.91691	validation-mlogloss:1.89848
[36m(train_xgb_ray_tune pid=398880)[0m [371]	train-mlogloss:1.65801	validation-mlogloss:1.71882
[36m(train_xgb_ray_tune pid=398900)[0m [355]	train-mlogloss:2.14981	validation-mlogloss:2.10987
[36m(train_xgb_ray_tune pid=398902)[0m [401]	train-mlogloss:1.86811	validation-mlogloss:1.84673
[36m(train_xgb_ray_tune pid=398918)[0m [360]	train-mlogloss:2.16855	validation-mlogloss:2.12871
[36m(train_xgb_ray_tune pid=398913)[0m [466]	train-mlogloss:2.16006	validation-mlogloss:2.17453
[36m(train_xgb_ray_tune pid=398901)[0m [353]	train-mlogloss:1.69992	validation-mlogloss:1.74522
[36m(train_xgb_ray_tune pid=398917)[0m [346]	train-mlogloss:1.79860	validation-mlogloss:1.81175
[36m(train_xgb_ray_tune pid=398903)[0m [365]	train-mlogloss:1.86864	validation-mlogloss:1.85992
[36m(train_xgb_ray_tune pid=398912)[0m [356]	train-mlogloss:1.83084	validation-mlogloss:1.83086
[36m(train_xgb_ray_tune pid=398906)[0m [372]	train-mlogloss:1.82682	validation-mlogloss:1.81656
[36m(train_xgb_ray_tune pid=398916)[0m [351]	train-mlogloss:2.32754	validation-mlogloss:2.32205
[36m(train_xgb_ray_tune pid=398894)[0m [343]	train-mlogloss:1.91598	validation-mlogloss:1.89759
[36m(train_xgb_ray_tune pid=398915)[0m [400]	train-mlogloss:2.02941	validation-mlogloss:1.99250
[36m(train_xgb_ray_tune pid=398905)[0m [345]	train-mlogloss:1.84141	validation-mlogloss:1.83694
[36m(train_xgb_ray_tune pid=398902)[0m [402]	train-mlogloss:1.86795	validation-mlogloss:1.84655
[36m(train_xgb_ray_tune pid=398913)[0m [467]	train-mlogloss:2.16006	validation-mlogloss:2.17453
[36m(train_xgb_ray_tune pid=398917)[0m [347]	train-mlogloss:1.79772	validation-mlogloss:1.81122
[36m(train_xgb_ray_tune pid=398892)[0m [370]	train-mlogloss:1.82521	validation-mlogloss:1.82088
[36m(train_xgb_ray_tune pid=398886)[0m [357]	train-mlogloss:1.68270	validation-mlogloss:1.72499
[36m(train_xgb_ray_tune pid=398918)[0m [361]	train-mlogloss:2.16773	validation-mlogloss:2.12792
[36m(train_xgb_ray_tune pid=398901)[0m [354]	train-mlogloss:1.69896	validation-mlogloss:1.74475

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:35:47. Total running time: 1min 31s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             88.6951 │
│ time_total_s                 88.6951 │
│ training_iteration                 1 │
│ validation_accuracy          0.49037 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:35:47. Total running time: 1min 31s
[36m(train_xgb_ray_tune pid=398879)[0m [345]	train-mlogloss:1.65746	validation-mlogloss:1.73218
[36m(train_xgb_ray_tune pid=398880)[0m [372]	train-mlogloss:1.65722	validation-mlogloss:1.71826
[36m(train_xgb_ray_tune pid=398915)[0m [401]	train-mlogloss:2.02858	validation-mlogloss:1.99177
[36m(train_xgb_ray_tune pid=398900)[0m [356]	train-mlogloss:2.14897	validation-mlogloss:2.10910
[36m(train_xgb_ray_tune pid=398902)[0m [403]	train-mlogloss:1.86792	validation-mlogloss:1.84649
[36m(train_xgb_ray_tune pid=398913)[0m [468]	train-mlogloss:2.16000	validation-mlogloss:2.17450
[36m(train_xgb_ray_tune pid=398892)[0m [371]	train-mlogloss:1.82458	validation-mlogloss:1.82043
[36m(train_xgb_ray_tune pid=398903)[0m [366]	train-mlogloss:1.86777	validation-mlogloss:1.85935
[36m(train_xgb_ray_tune pid=398912)[0m [357]	train-mlogloss:1.82994	validation-mlogloss:1.83015
[36m(train_xgb_ray_tune pid=398906)[0m [373]	train-mlogloss:1.82631	validation-mlogloss:1.81610
[36m(train_xgb_ray_tune pid=398886)[0m [358]	train-mlogloss:1.68196	validation-mlogloss:1.72423
[36m(train_xgb_ray_tune pid=398916)[0m [352]	train-mlogloss:2.32693	validation-mlogloss:2.32150
[36m(train_xgb_ray_tune pid=398879)[0m [346]	train-mlogloss:1.65658	validation-mlogloss:1.73190
[36m(train_xgb_ray_tune pid=398894)[0m [344]	train-mlogloss:1.91500	validation-mlogloss:1.89672
[36m(train_xgb_ray_tune pid=398880)[0m [373]	train-mlogloss:1.65650	validation-mlogloss:1.71790
[36m(train_xgb_ray_tune pid=398915)[0m [402]	train-mlogloss:2.02779	validation-mlogloss:1.99118
[36m(train_xgb_ray_tune pid=398900)[0m [357]	train-mlogloss:2.14811	validation-mlogloss:2.10827
[36m(train_xgb_ray_tune pid=398905)[0m [346]	train-mlogloss:1.84065	validation-mlogloss:1.83632
[36m(train_xgb_ray_tune pid=398902)[0m [404]	train-mlogloss:1.86766	validation-mlogloss:1.84621
[36m(train_xgb_ray_tune pid=398918)[0m [362]	train-mlogloss:2.16693	validation-mlogloss:2.12717
[36m(train_xgb_ray_tune pid=398913)[0m [469]	train-mlogloss:2.16000	validation-mlogloss:2.17450
[36m(train_xgb_ray_tune pid=398901)[0m [355]	train-mlogloss:1.69810	validation-mlogloss:1.74437
[36m(train_xgb_ray_tune pid=398917)[0m [348]	train-mlogloss:1.79684	validation-mlogloss:1.81047
[36m(train_xgb_ray_tune pid=398903)[0m [367]	train-mlogloss:1.86693	validation-mlogloss:1.85880
[36m(train_xgb_ray_tune pid=398912)[0m [358]	train-mlogloss:1.82911	validation-mlogloss:1.82956
[36m(train_xgb_ray_tune pid=398906)[0m [374]	train-mlogloss:1.82578	validation-mlogloss:1.81581
[36m(train_xgb_ray_tune pid=398916)[0m [353]	train-mlogloss:2.32632	validation-mlogloss:2.32093
[36m(train_xgb_ray_tune pid=398894)[0m [345]	train-mlogloss:1.91405	validation-mlogloss:1.89586
[36m(train_xgb_ray_tune pid=398880)[0m [374]	train-mlogloss:1.65578	validation-mlogloss:1.71773
[36m(train_xgb_ray_tune pid=398915)[0m [403]	train-mlogloss:2.02702	validation-mlogloss:1.99048
[36m(train_xgb_ray_tune pid=398900)[0m [358]	train-mlogloss:2.14727	validation-mlogloss:2.10748
[36m(train_xgb_ray_tune pid=398905)[0m [347]	train-mlogloss:1.83986	validation-mlogloss:1.83572
[36m(train_xgb_ray_tune pid=398902)[0m [405]	train-mlogloss:1.86731	validation-mlogloss:1.84592
[36m(train_xgb_ray_tune pid=398918)[0m [363]	train-mlogloss:2.16611	validation-mlogloss:2.12634
[36m(train_xgb_ray_tune pid=398913)[0m [470]	train-mlogloss:2.15994	validation-mlogloss:2.17442
[36m(train_xgb_ray_tune pid=398901)[0m [356]	train-mlogloss:1.69726	validation-mlogloss:1.74405
[36m(train_xgb_ray_tune pid=398917)[0m [349]	train-mlogloss:1.79597	validation-mlogloss:1.80990
[36m(train_xgb_ray_tune pid=398892)[0m [372]	train-mlogloss:1.82385	validation-mlogloss:1.81960
[36m(train_xgb_ray_tune pid=398886)[0m [359]	train-mlogloss:1.68108	validation-mlogloss:1.72374
[36m(train_xgb_ray_tune pid=398906)[0m [375]	train-mlogloss:1.82530	validation-mlogloss:1.81557
[36m(train_xgb_ray_tune pid=398879)[0m [347]	train-mlogloss:1.65573	validation-mlogloss:1.73135
[36m(train_xgb_ray_tune pid=398905)[0m [348]	train-mlogloss:1.83902	validation-mlogloss:1.83516
[36m(train_xgb_ray_tune pid=398913)[0m [471]	train-mlogloss:2.15969	validation-mlogloss:2.17420
[36m(train_xgb_ray_tune pid=398892)[0m [373]	train-mlogloss:1.82323	validation-mlogloss:1.81920
[36m(train_xgb_ray_tune pid=398912)[0m [359]	train-mlogloss:1.82831	validation-mlogloss:1.82878
[36m(train_xgb_ray_tune pid=398915)[0m [404]	train-mlogloss:2.02631	validation-mlogloss:1.98999
[36m(train_xgb_ray_tune pid=398900)[0m [359]	train-mlogloss:2.14643	validation-mlogloss:2.10674
[36m(train_xgb_ray_tune pid=398902)[0m [406]	train-mlogloss:1.86714	validation-mlogloss:1.84583
[36m(train_xgb_ray_tune pid=398903)[0m [368]	train-mlogloss:1.86605	validation-mlogloss:1.85821
[36m(train_xgb_ray_tune pid=398886)[0m [360]	train-mlogloss:1.68036	validation-mlogloss:1.72339
[36m(train_xgb_ray_tune pid=398916)[0m [354]	train-mlogloss:2.32568	validation-mlogloss:2.32030
[36m(train_xgb_ray_tune pid=398879)[0m [348]	train-mlogloss:1.65484	validation-mlogloss:1.73109
[36m(train_xgb_ray_tune pid=398894)[0m [346]	train-mlogloss:1.91301	validation-mlogloss:1.89514
[36m(train_xgb_ray_tune pid=398880)[0m [375]	train-mlogloss:1.65502	validation-mlogloss:1.71741
[36m(train_xgb_ray_tune pid=398902)[0m [407]	train-mlogloss:1.86711	validation-mlogloss:1.84583
[36m(train_xgb_ray_tune pid=398918)[0m [364]	train-mlogloss:2.16530	validation-mlogloss:2.12562
[36m(train_xgb_ray_tune pid=398913)[0m [472]	train-mlogloss:2.15969	validation-mlogloss:2.17420
[36m(train_xgb_ray_tune pid=398901)[0m [357]	train-mlogloss:1.69640	validation-mlogloss:1.74358
[36m(train_xgb_ray_tune pid=398917)[0m [350]	train-mlogloss:1.79506	validation-mlogloss:1.80924
[36m(train_xgb_ray_tune pid=398892)[0m [374]	train-mlogloss:1.82246	validation-mlogloss:1.81850
[36m(train_xgb_ray_tune pid=398906)[0m [376]	train-mlogloss:1.82484	validation-mlogloss:1.81507
[36m(train_xgb_ray_tune pid=398915)[0m [405]	train-mlogloss:2.02555	validation-mlogloss:1.98937
[36m(train_xgb_ray_tune pid=398886)[0m [361]	train-mlogloss:1.67962	validation-mlogloss:1.72292
[36m(train_xgb_ray_tune pid=398903)[0m [369]	train-mlogloss:1.86520	validation-mlogloss:1.85760
[36m(train_xgb_ray_tune pid=398912)[0m [360]	train-mlogloss:1.82739	validation-mlogloss:1.82811
[36m(train_xgb_ray_tune pid=398916)[0m [355]	train-mlogloss:2.32508	validation-mlogloss:2.31970
[36m(train_xgb_ray_tune pid=398879)[0m [349]	train-mlogloss:1.65389	validation-mlogloss:1.73065
[36m(train_xgb_ray_tune pid=398880)[0m [376]	train-mlogloss:1.65428	validation-mlogloss:1.71732
[36m(train_xgb_ray_tune pid=398900)[0m [360]	train-mlogloss:2.14558	validation-mlogloss:2.10592
[36m(train_xgb_ray_tune pid=398905)[0m [349]	train-mlogloss:1.83828	validation-mlogloss:1.83447
[36m(train_xgb_ray_tune pid=398918)[0m [365]	train-mlogloss:2.16453	validation-mlogloss:2.12490
[36m(train_xgb_ray_tune pid=398913)[0m [473]	train-mlogloss:2.15969	validation-mlogloss:2.17420
[36m(train_xgb_ray_tune pid=398901)[0m [358]	train-mlogloss:1.69564	validation-mlogloss:1.74322
[36m(train_xgb_ray_tune pid=398917)[0m [351]	train-mlogloss:1.79418	validation-mlogloss:1.80877
[36m(train_xgb_ray_tune pid=398892)[0m [375]	train-mlogloss:1.82184	validation-mlogloss:1.81815
[36m(train_xgb_ray_tune pid=398902)[0m [408]	train-mlogloss:1.86707	validation-mlogloss:1.84578
[36m(train_xgb_ray_tune pid=398906)[0m [377]	train-mlogloss:1.82425	validation-mlogloss:1.81460
[36m(train_xgb_ray_tune pid=398894)[0m [347]	train-mlogloss:1.91206	validation-mlogloss:1.89439
[36m(train_xgb_ray_tune pid=398915)[0m [406]	train-mlogloss:2.02481	validation-mlogloss:1.98870
[36m(train_xgb_ray_tune pid=398900)[0m [361]	train-mlogloss:2.14472	validation-mlogloss:2.10516
[36m(train_xgb_ray_tune pid=398913)[0m [474]	train-mlogloss:2.15969	validation-mlogloss:2.17420
[36m(train_xgb_ray_tune pid=398892)[0m [376]	train-mlogloss:1.82125	validation-mlogloss:1.81753
[36m(train_xgb_ray_tune pid=398886)[0m [362]	train-mlogloss:1.67883	validation-mlogloss:1.72254
[36m(train_xgb_ray_tune pid=398912)[0m [361]	train-mlogloss:1.82655	validation-mlogloss:1.82763
[36m(train_xgb_ray_tune pid=398905)[0m [350]	train-mlogloss:1.83757	validation-mlogloss:1.83398
[36m(train_xgb_ray_tune pid=398902)[0m [409]	train-mlogloss:1.86701	validation-mlogloss:1.84573
[36m(train_xgb_ray_tune pid=398901)[0m [359]	train-mlogloss:1.69482	validation-mlogloss:1.74266
[36m(train_xgb_ray_tune pid=398916)[0m [356]	train-mlogloss:2.32448	validation-mlogloss:2.31913
[36m(train_xgb_ray_tune pid=398915)[0m [407]	train-mlogloss:2.02400	validation-mlogloss:1.98796
[36m(train_xgb_ray_tune pid=398918)[0m [366]	train-mlogloss:2.16370	validation-mlogloss:2.12415
[36m(train_xgb_ray_tune pid=398886)[0m [363]	train-mlogloss:1.67810	validation-mlogloss:1.72219
[36m(train_xgb_ray_tune pid=398903)[0m [370]	train-mlogloss:1.86441	validation-mlogloss:1.85716
[36m(train_xgb_ray_tune pid=398906)[0m [378]	train-mlogloss:1.82369	validation-mlogloss:1.81410
[36m(train_xgb_ray_tune pid=398879)[0m [350]	train-mlogloss:1.65303	validation-mlogloss:1.73028
[36m(train_xgb_ray_tune pid=398894)[0m [348]	train-mlogloss:1.91115	validation-mlogloss:1.89369
[36m(train_xgb_ray_tune pid=398880)[0m [377]	train-mlogloss:1.65360	validation-mlogloss:1.71702
[36m(train_xgb_ray_tune pid=398902)[0m [410]	train-mlogloss:1.86696	validation-mlogloss:1.84571
[36m(train_xgb_ray_tune pid=398913)[0m [475]	train-mlogloss:2.15969	validation-mlogloss:2.17420
[36m(train_xgb_ray_tune pid=398917)[0m [352]	train-mlogloss:1.79335	validation-mlogloss:1.80826
[36m(train_xgb_ray_tune pid=398903)[0m [371]	train-mlogloss:1.86362	validation-mlogloss:1.85661
[36m(train_xgb_ray_tune pid=398912)[0m [362]	train-mlogloss:1.82563	validation-mlogloss:1.82689
[36m(train_xgb_ray_tune pid=398916)[0m [357]	train-mlogloss:2.32382	validation-mlogloss:2.31852
[36m(train_xgb_ray_tune pid=398879)[0m [351]	train-mlogloss:1.65218	validation-mlogloss:1.72980
[36m(train_xgb_ray_tune pid=398880)[0m [378]	train-mlogloss:1.65287	validation-mlogloss:1.71667
[36m(train_xgb_ray_tune pid=398915)[0m [408]	train-mlogloss:2.02319	validation-mlogloss:1.98729
[36m(train_xgb_ray_tune pid=398900)[0m [362]	train-mlogloss:2.14385	validation-mlogloss:2.10431
[36m(train_xgb_ray_tune pid=398905)[0m [351]	train-mlogloss:1.83684	validation-mlogloss:1.83346
[36m(train_xgb_ray_tune pid=398902)[0m [411]	train-mlogloss:1.86675	validation-mlogloss:1.84562
[36m(train_xgb_ray_tune pid=398918)[0m [367]	train-mlogloss:2.16291	validation-mlogloss:2.12343
[36m(train_xgb_ray_tune pid=398913)[0m [476]	train-mlogloss:2.15969	validation-mlogloss:2.17420
[36m(train_xgb_ray_tune pid=398901)[0m [360]	train-mlogloss:1.69407	validation-mlogloss:1.74218
[36m(train_xgb_ray_tune pid=398917)[0m [353]	train-mlogloss:1.79250	validation-mlogloss:1.80774
[36m(train_xgb_ray_tune pid=398892)[0m [377]	train-mlogloss:1.82065	validation-mlogloss:1.81713
[36m(train_xgb_ray_tune pid=398886)[0m [364]	train-mlogloss:1.67731	validation-mlogloss:1.72171
[36m(train_xgb_ray_tune pid=398906)[0m [379]	train-mlogloss:1.82316	validation-mlogloss:1.81361
[36m(train_xgb_ray_tune pid=398913)[0m [477]	train-mlogloss:2.15969	validation-mlogloss:2.17420
[36m(train_xgb_ray_tune pid=398918)[0m [368]	train-mlogloss:2.16213	validation-mlogloss:2.12266
[36m(train_xgb_ray_tune pid=398912)[0m [363]	train-mlogloss:1.82476	validation-mlogloss:1.82628
[36m(train_xgb_ray_tune pid=398916)[0m [358]	train-mlogloss:2.32322	validation-mlogloss:2.31793
[36m(train_xgb_ray_tune pid=398879)[0m [352]	train-mlogloss:1.65136	validation-mlogloss:1.72931
[36m(train_xgb_ray_tune pid=398894)[0m [349]	train-mlogloss:1.91018	validation-mlogloss:1.89282
[36m(train_xgb_ray_tune pid=398880)[0m [379]	train-mlogloss:1.65218	validation-mlogloss:1.71628
[36m(train_xgb_ray_tune pid=398915)[0m [409]	train-mlogloss:2.02241	validation-mlogloss:1.98656
[36m(train_xgb_ray_tune pid=398900)[0m [363]	train-mlogloss:2.14303	validation-mlogloss:2.10349
[36m(train_xgb_ray_tune pid=398905)[0m [352]	train-mlogloss:1.83606	validation-mlogloss:1.83274
[36m(train_xgb_ray_tune pid=398902)[0m [412]	train-mlogloss:1.86655	validation-mlogloss:1.84549
[36m(train_xgb_ray_tune pid=398913)[0m [478]	train-mlogloss:2.15969	validation-mlogloss:2.17420
[36m(train_xgb_ray_tune pid=398901)[0m [361]	train-mlogloss:1.69318	validation-mlogloss:1.74193
[36m(train_xgb_ray_tune pid=398892)[0m [378]	train-mlogloss:1.81991	validation-mlogloss:1.81665
[36m(train_xgb_ray_tune pid=398903)[0m [372]	train-mlogloss:1.86280	validation-mlogloss:1.85593
[36m(train_xgb_ray_tune pid=398906)[0m [380]	train-mlogloss:1.82260	validation-mlogloss:1.81318
[36m(train_xgb_ray_tune pid=398886)[0m [365]	train-mlogloss:1.67666	validation-mlogloss:1.72136
[36m(train_xgb_ray_tune pid=398912)[0m [364]	train-mlogloss:1.82387	validation-mlogloss:1.82570
[36m(train_xgb_ray_tune pid=398894)[0m [350]	train-mlogloss:1.90931	validation-mlogloss:1.89207
[36m(train_xgb_ray_tune pid=398915)[0m [410]	train-mlogloss:2.02167	validation-mlogloss:1.98593
[36m(train_xgb_ray_tune pid=398902)[0m [413]	train-mlogloss:1.86637	validation-mlogloss:1.84536
[36m(train_xgb_ray_tune pid=398918)[0m [369]	train-mlogloss:2.16130	validation-mlogloss:2.12189
[36m(train_xgb_ray_tune pid=398913)[0m [479]	train-mlogloss:2.15969	validation-mlogloss:2.17420
[36m(train_xgb_ray_tune pid=398917)[0m [354]	train-mlogloss:1.79161	validation-mlogloss:1.80730
[36m(train_xgb_ray_tune pid=398892)[0m [379]	train-mlogloss:1.81923	validation-mlogloss:1.81593
[36m(train_xgb_ray_tune pid=398900)[0m [364]	train-mlogloss:2.14219	validation-mlogloss:2.10274
[36m(train_xgb_ray_tune pid=398886)[0m [366]	train-mlogloss:1.67580	validation-mlogloss:1.72104
[36m(train_xgb_ray_tune pid=398903)[0m [373]	train-mlogloss:1.86181	validation-mlogloss:1.85502
[36m(train_xgb_ray_tune pid=398912)[0m [365]	train-mlogloss:1.82308	validation-mlogloss:1.82519
[36m(train_xgb_ray_tune pid=398906)[0m [381]	train-mlogloss:1.82213	validation-mlogloss:1.81278
[36m(train_xgb_ray_tune pid=398916)[0m [359]	train-mlogloss:2.32263	validation-mlogloss:2.31740
[36m(train_xgb_ray_tune pid=398879)[0m [353]	train-mlogloss:1.65051	validation-mlogloss:1.72879
[36m(train_xgb_ray_tune pid=398880)[0m [380]	train-mlogloss:1.65152	validation-mlogloss:1.71591
[36m(train_xgb_ray_tune pid=398905)[0m [353]	train-mlogloss:1.83532	validation-mlogloss:1.83216
[36m(train_xgb_ray_tune pid=398902)[0m [414]	train-mlogloss:1.86627	validation-mlogloss:1.84522
[36m(train_xgb_ray_tune pid=398918)[0m [370]	train-mlogloss:2.16049	validation-mlogloss:2.12105
[36m(train_xgb_ray_tune pid=398913)[0m [480]	train-mlogloss:2.15956	validation-mlogloss:2.17400
[36m(train_xgb_ray_tune pid=398901)[0m [362]	train-mlogloss:1.69235	validation-mlogloss:1.74159
[36m(train_xgb_ray_tune pid=398917)[0m [355]	train-mlogloss:1.79071	validation-mlogloss:1.80668
[36m(train_xgb_ray_tune pid=398892)[0m [380]	train-mlogloss:1.81857	validation-mlogloss:1.81533
[36m(train_xgb_ray_tune pid=398886)[0m [367]	train-mlogloss:1.67515	validation-mlogloss:1.72071
[36m(train_xgb_ray_tune pid=398906)[0m [382]	train-mlogloss:1.82165	validation-mlogloss:1.81239
[36m(train_xgb_ray_tune pid=398916)[0m [360]	train-mlogloss:2.32202	validation-mlogloss:2.31688
[36m(train_xgb_ray_tune pid=398879)[0m [354]	train-mlogloss:1.64975	validation-mlogloss:1.72845
[36m(train_xgb_ray_tune pid=398894)[0m [351]	train-mlogloss:1.90836	validation-mlogloss:1.89112
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[36m(train_xgb_ray_tune pid=398886)[0m [378]	train-mlogloss:1.66687	validation-mlogloss:1.71668
[36m(train_xgb_ray_tune pid=398903)[0m [383]	train-mlogloss:1.85324	validation-mlogloss:1.84817
[36m(train_xgb_ray_tune pid=398912)[0m [375]	train-mlogloss:1.81446	validation-mlogloss:1.81928
[36m(train_xgb_ray_tune pid=398906)[0m [394]	train-mlogloss:1.81602	validation-mlogloss:1.80777
[36m(train_xgb_ray_tune pid=398916)[0m [370]	train-mlogloss:2.31598	validation-mlogloss:2.31097
[36m(train_xgb_ray_tune pid=398894)[0m [360]	train-mlogloss:1.90027	validation-mlogloss:1.88392
[36m(train_xgb_ray_tune pid=398880)[0m [391]	train-mlogloss:1.64352	validation-mlogloss:1.71300
[36m(train_xgb_ray_tune pid=398900)[0m [374]	train-mlogloss:2.13393	validation-mlogloss:2.09468
[36m(train_xgb_ray_tune pid=398905)[0m [364]	train-mlogloss:1.82730	validation-mlogloss:1.82615
[36m(train_xgb_ray_tune pid=398902)[0m [430]	train-mlogloss:1.86447	validation-mlogloss:1.84366
[36m(train_xgb_ray_tune pid=398918)[0m [381]	train-mlogloss:2.15180	validation-mlogloss:2.11257
[36m(train_xgb_ray_tune pid=398913)[0m [495]	train-mlogloss:2.15855	validation-mlogloss:2.17292
[36m(train_xgb_ray_tune pid=398901)[0m [373]	train-mlogloss:1.68339	validation-mlogloss:1.73691
[36m(train_xgb_ray_tune pid=398917)[0m [366]	train-mlogloss:1.78132	validation-mlogloss:1.79967
[36m(train_xgb_ray_tune pid=398892)[0m [391]	train-mlogloss:1.81163	validation-mlogloss:1.80980
[36m(train_xgb_ray_tune pid=398913)[0m [496]	train-mlogloss:2.15855	validation-mlogloss:2.17292
[36m(train_xgb_ray_tune pid=398916)[0m [371]	train-mlogloss:2.31543	validation-mlogloss:2.31045
[36m(train_xgb_ray_tune pid=398903)[0m [384]	train-mlogloss:1.85241	validation-mlogloss:1.84758
[36m(train_xgb_ray_tune pid=398886)[0m [379]	train-mlogloss:1.66604	validation-mlogloss:1.71619
[36m(train_xgb_ray_tune pid=398912)[0m [376]	train-mlogloss:1.81362	validation-mlogloss:1.81873
[36m(train_xgb_ray_tune pid=398906)[0m [395]	train-mlogloss:1.81551	validation-mlogloss:1.80736
[36m(train_xgb_ray_tune pid=398879)[0m [366]	train-mlogloss:1.63995	validation-mlogloss:1.72471
[36m(train_xgb_ray_tune pid=398894)[0m [361]	train-mlogloss:1.89935	validation-mlogloss:1.88309
[36m(train_xgb_ray_tune pid=398880)[0m [392]	train-mlogloss:1.64277	validation-mlogloss:1.71269
[36m(train_xgb_ray_tune pid=398900)[0m [375]	train-mlogloss:2.13313	validation-mlogloss:2.09394
[36m(train_xgb_ray_tune pid=398902)[0m [431]	train-mlogloss:1.86441	validation-mlogloss:1.84363
[36m(train_xgb_ray_tune pid=398918)[0m [382]	train-mlogloss:2.15101	validation-mlogloss:2.11189
[36m(train_xgb_ray_tune pid=398913)[0m [497]	train-mlogloss:2.15855	validation-mlogloss:2.17292
[36m(train_xgb_ray_tune pid=398901)[0m [374]	train-mlogloss:1.68261	validation-mlogloss:1.73669
[36m(train_xgb_ray_tune pid=398917)[0m [367]	train-mlogloss:1.78044	validation-mlogloss:1.79910
[36m(train_xgb_ray_tune pid=398886)[0m [380]	train-mlogloss:1.66530	validation-mlogloss:1.71603
[36m(train_xgb_ray_tune pid=398903)[0m [385]	train-mlogloss:1.85150	validation-mlogloss:1.84683
[36m(train_xgb_ray_tune pid=398906)[0m [396]	train-mlogloss:1.81505	validation-mlogloss:1.80701
[36m(train_xgb_ray_tune pid=398916)[0m [372]	train-mlogloss:2.31484	validation-mlogloss:2.30987
[36m(train_xgb_ray_tune pid=398879)[0m [367]	train-mlogloss:1.63906	validation-mlogloss:1.72447
[36m(train_xgb_ray_tune pid=398894)[0m [362]	train-mlogloss:1.89848	validation-mlogloss:1.88246
[36m(train_xgb_ray_tune pid=398900)[0m [376]	train-mlogloss:2.13232	validation-mlogloss:2.09313
[36m(train_xgb_ray_tune pid=398905)[0m [365]	train-mlogloss:1.82656	validation-mlogloss:1.82552
[36m(train_xgb_ray_tune pid=398902)[0m [432]	train-mlogloss:1.86429	validation-mlogloss:1.84355
[36m(train_xgb_ray_tune pid=398913)[0m [498]	train-mlogloss:2.15842	validation-mlogloss:2.17279
[36m(train_xgb_ray_tune pid=398901)[0m [375]	train-mlogloss:1.68182	validation-mlogloss:1.73627
[36m(train_xgb_ray_tune pid=398915)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=398915)[0m   _log_deprecation_warning([32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=398892)[0m [392]	train-mlogloss:1.81100	validation-mlogloss:1.80921
[36m(train_xgb_ray_tune pid=398912)[0m [377]	train-mlogloss:1.81273	validation-mlogloss:1.81820
[36m(train_xgb_ray_tune pid=398916)[0m [373]	train-mlogloss:2.31423	validation-mlogloss:2.30926
[36m(train_xgb_ray_tune pid=398918)[0m [383]	train-mlogloss:2.15019	validation-mlogloss:2.11106
[36m(train_xgb_ray_tune pid=398902)[0m [433]	train-mlogloss:1.86429	validation-mlogloss:1.84355
[36m(train_xgb_ray_tune pid=398903)[0m [386]	train-mlogloss:1.85069	validation-mlogloss:1.84612
[36m(train_xgb_ray_tune pid=398917)[0m [368]	train-mlogloss:1.77969	validation-mlogloss:1.79851
[36m(train_xgb_ray_tune pid=398880)[0m [393]	train-mlogloss:1.64215	validation-mlogloss:1.71239
[36m(train_xgb_ray_tune pid=398886)[0m [381]	train-mlogloss:1.66457	validation-mlogloss:1.71577
[36m(train_xgb_ray_tune pid=398906)[0m [397]	train-mlogloss:1.81456	validation-mlogloss:1.80660
[36m(train_xgb_ray_tune pid=398894)[0m [363]	train-mlogloss:1.89757	validation-mlogloss:1.88172
[36m(train_xgb_ray_tune pid=398900)[0m [377]	train-mlogloss:2.13149	validation-mlogloss:2.09235
[36m(train_xgb_ray_tune pid=398905)[0m [366]	train-mlogloss:1.82587	validation-mlogloss:1.82495
[36m(train_xgb_ray_tune pid=398913)[0m [499]	train-mlogloss:2.15842	validation-mlogloss:2.17279
[36m(train_xgb_ray_tune pid=398901)[0m [376]	train-mlogloss:1.68091	validation-mlogloss:1.73569
[36m(train_xgb_ray_tune pid=398892)[0m [393]	train-mlogloss:1.81041	validation-mlogloss:1.80859
[36m(train_xgb_ray_tune pid=398879)[0m [368]	train-mlogloss:1.63829	validation-mlogloss:1.72398
[36m(train_xgb_ray_tune pid=398902)[0m [434]	train-mlogloss:1.86419	validation-mlogloss:1.84345
[36m(train_xgb_ray_tune pid=398886)[0m [382]	train-mlogloss:1.66378	validation-mlogloss:1.71561
[36m(train_xgb_ray_tune pid=398903)[0m [387]	train-mlogloss:1.84988	validation-mlogloss:1.84550
[36m(train_xgb_ray_tune pid=398912)[0m [378]	train-mlogloss:1.81188	validation-mlogloss:1.81763
[36m(train_xgb_ray_tune pid=398906)[0m [398]	train-mlogloss:1.81402	validation-mlogloss:1.80612
[36m(train_xgb_ray_tune pid=398916)[0m [374]	train-mlogloss:2.31362	validation-mlogloss:2.30861
[36m(train_xgb_ray_tune pid=398894)[0m [364]	train-mlogloss:1.89667	validation-mlogloss:1.88100
[36m(train_xgb_ray_tune pid=398880)[0m [394]	train-mlogloss:1.64144	validation-mlogloss:1.71210
[36m(train_xgb_ray_tune pid=398900)[0m [378]	train-mlogloss:2.13064	validation-mlogloss:2.09149
[36m(train_xgb_ray_tune pid=398905)[0m [367]	train-mlogloss:1.82515	validation-mlogloss:1.82435
[36m(train_xgb_ray_tune pid=398918)[0m [384]	train-mlogloss:2.14940	validation-mlogloss:2.11038
[36m(train_xgb_ray_tune pid=398913)[0m [500]	train-mlogloss:2.15821	validation-mlogloss:2.17245
[36m(train_xgb_ray_tune pid=398917)[0m [369]	train-mlogloss:1.77879	validation-mlogloss:1.79784
[36m(train_xgb_ray_tune pid=398892)[0m [394]	train-mlogloss:1.80983	validation-mlogloss:1.80810

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:35:51. Total running time: 1min 36s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             93.3898 │
│ time_total_s                 93.3898 │
│ training_iteration                 1 │
│ validation_accuracy           0.5001 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:35:51. Total running time: 1min 36s
[36m(train_xgb_ray_tune pid=398903)[0m [388]	train-mlogloss:1.84906	validation-mlogloss:1.84481
[36m(train_xgb_ray_tune pid=398912)[0m [379]	train-mlogloss:1.81107	validation-mlogloss:1.81706
[36m(train_xgb_ray_tune pid=398916)[0m [375]	train-mlogloss:2.31305	validation-mlogloss:2.30810
[36m(train_xgb_ray_tune pid=398879)[0m [369]	train-mlogloss:1.63749	validation-mlogloss:1.72357
[36m(train_xgb_ray_tune pid=398894)[0m [365]	train-mlogloss:1.89577	validation-mlogloss:1.88029
[36m(train_xgb_ray_tune pid=398880)[0m [395]	train-mlogloss:1.64076	validation-mlogloss:1.71178
[36m(train_xgb_ray_tune pid=398905)[0m [368]	train-mlogloss:1.82441	validation-mlogloss:1.82375
[36m(train_xgb_ray_tune pid=398902)[0m [435]	train-mlogloss:1.86398	validation-mlogloss:1.84329
[36m(train_xgb_ray_tune pid=398918)[0m [385]	train-mlogloss:2.14861	validation-mlogloss:2.10962
[36m(train_xgb_ray_tune pid=398913)[0m [501]	train-mlogloss:2.15821	validation-mlogloss:2.17245
[36m(train_xgb_ray_tune pid=398901)[0m [377]	train-mlogloss:1.68014	validation-mlogloss:1.73557
[36m(train_xgb_ray_tune pid=398892)[0m [395]	train-mlogloss:1.80908	validation-mlogloss:1.80755
[36m(train_xgb_ray_tune pid=398886)[0m [383]	train-mlogloss:1.66311	validation-mlogloss:1.71528
[36m(train_xgb_ray_tune pid=398902)[0m [436]	train-mlogloss:1.86381	validation-mlogloss:1.84320
[36m(train_xgb_ray_tune pid=398903)[0m [389]	train-mlogloss:1.84821	validation-mlogloss:1.84421
[36m(train_xgb_ray_tune pid=398906)[0m [399]	train-mlogloss:1.81355	validation-mlogloss:1.80564
[36m(train_xgb_ray_tune pid=398879)[0m [370]	train-mlogloss:1.63669	validation-mlogloss:1.72320
[36m(train_xgb_ray_tune pid=398894)[0m [366]	train-mlogloss:1.89492	validation-mlogloss:1.87952
[36m(train_xgb_ray_tune pid=398900)[0m [379]	train-mlogloss:2.12987	validation-mlogloss:2.09079
[36m(train_xgb_ray_tune pid=398905)[0m [369]	train-mlogloss:1.82373	validation-mlogloss:1.82331
[36m(train_xgb_ray_tune pid=398913)[0m [502]	train-mlogloss:2.15799	validation-mlogloss:2.17221
[36m(train_xgb_ray_tune pid=398901)[0m [378]	train-mlogloss:1.67936	validation-mlogloss:1.73492
[36m(train_xgb_ray_tune pid=398917)[0m [370]	train-mlogloss:1.77797	validation-mlogloss:1.79731
[36m(train_xgb_ray_tune pid=398892)[0m [396]	train-mlogloss:1.80841	validation-mlogloss:1.80694
[36m(train_xgb_ray_tune pid=398912)[0m [380]	train-mlogloss:1.81033	validation-mlogloss:1.81643
[36m(train_xgb_ray_tune pid=398902)[0m [437]	train-mlogloss:1.86360	validation-mlogloss:1.84291
[36m(train_xgb_ray_tune pid=398886)[0m [384]	train-mlogloss:1.66241	validation-mlogloss:1.71495
[36m(train_xgb_ray_tune pid=398906)[0m [400]	train-mlogloss:1.81309	validation-mlogloss:1.80525
[36m(train_xgb_ray_tune pid=398916)[0m [376]	train-mlogloss:2.31249	validation-mlogloss:2.30761
[36m(train_xgb_ray_tune pid=398894)[0m [367]	train-mlogloss:1.89404	validation-mlogloss:1.87886
[36m(train_xgb_ray_tune pid=398880)[0m [396]	train-mlogloss:1.64008	validation-mlogloss:1.71155
[36m(train_xgb_ray_tune pid=398900)[0m [380]	train-mlogloss:2.12906	validation-mlogloss:2.09011
[36m(train_xgb_ray_tune pid=398905)[0m [370]	train-mlogloss:1.82302	validation-mlogloss:1.82283
[36m(train_xgb_ray_tune pid=398902)[0m [438]	train-mlogloss:1.86360	validation-mlogloss:1.84291
[36m(train_xgb_ray_tune pid=398918)[0m [386]	train-mlogloss:2.14781	validation-mlogloss:2.10880
[36m(train_xgb_ray_tune pid=398913)[0m [503]	train-mlogloss:2.15799	validation-mlogloss:2.17221
[36m(train_xgb_ray_tune pid=398901)[0m [379]	train-mlogloss:1.67864	validation-mlogloss:1.73452
[36m(train_xgb_ray_tune pid=398917)[0m [371]	train-mlogloss:1.77712	validation-mlogloss:1.79678
[36m(train_xgb_ray_tune pid=398892)[0m [397]	train-mlogloss:1.80778	validation-mlogloss:1.80630
[36m(train_xgb_ray_tune pid=398903)[0m [390]	train-mlogloss:1.84739	validation-mlogloss:1.84357
[36m(train_xgb_ray_tune pid=398879)[0m [371]	train-mlogloss:1.63583	validation-mlogloss:1.72288
[36m(train_xgb_ray_tune pid=398886)[0m [385]	train-mlogloss:1.66180	validation-mlogloss:1.71465
[36m(train_xgb_ray_tune pid=398912)[0m [381]	train-mlogloss:1.80956	validation-mlogloss:1.81587
[36m(train_xgb_ray_tune pid=398906)[0m [401]	train-mlogloss:1.81268	validation-mlogloss:1.80491
[36m(train_xgb_ray_tune pid=398916)[0m [377]	train-mlogloss:2.31186	validation-mlogloss:2.30697
[36m(train_xgb_ray_tune pid=398894)[0m [368]	train-mlogloss:1.89319	validation-mlogloss:1.87814
[36m(train_xgb_ray_tune pid=398880)[0m [397]	train-mlogloss:1.63936	validation-mlogloss:1.71126
[36m(train_xgb_ray_tune pid=398905)[0m [371]	train-mlogloss:1.82236	validation-mlogloss:1.82227
[36m(train_xgb_ray_tune pid=398902)[0m [439]	train-mlogloss:1.86338	validation-mlogloss:1.84261
[36m(train_xgb_ray_tune pid=398918)[0m [387]	train-mlogloss:2.14700	validation-mlogloss:2.10795
[36m(train_xgb_ray_tune pid=398913)[0m [504]	train-mlogloss:2.15799	validation-mlogloss:2.17221
[36m(train_xgb_ray_tune pid=398901)[0m [380]	train-mlogloss:1.67789	validation-mlogloss:1.73405
[36m(train_xgb_ray_tune pid=398892)[0m [398]	train-mlogloss:1.80721	validation-mlogloss:1.80580
[36m(train_xgb_ray_tune pid=398903)[0m [391]	train-mlogloss:1.84653	validation-mlogloss:1.84297
[36m(train_xgb_ray_tune pid=398906)[0m [402]	train-mlogloss:1.81227	validation-mlogloss:1.80469
[36m(train_xgb_ray_tune pid=398916)[0m [378]	train-mlogloss:2.31127	validation-mlogloss:2.30641
[36m(train_xgb_ray_tune pid=398879)[0m [372]	train-mlogloss:1.63505	validation-mlogloss:1.72241
[36m(train_xgb_ray_tune pid=398900)[0m [381]	train-mlogloss:2.12826	validation-mlogloss:2.08940
[36m(train_xgb_ray_tune pid=398913)[0m [505]	train-mlogloss:2.15799	validation-mlogloss:2.17221
[36m(train_xgb_ray_tune pid=398901)[0m [381]	train-mlogloss:1.67713	validation-mlogloss:1.73367
[36m(train_xgb_ray_tune pid=398917)[0m [372]	train-mlogloss:1.77628	validation-mlogloss:1.79628
[36m(train_xgb_ray_tune pid=398892)[0m [399]	train-mlogloss:1.80661	validation-mlogloss:1.80550
[36m(train_xgb_ray_tune pid=398912)[0m [382]	train-mlogloss:1.80868	validation-mlogloss:1.81533
[36m(train_xgb_ray_tune pid=398902)[0m [440]	train-mlogloss:1.86311	validation-mlogloss:1.84239
[36m(train_xgb_ray_tune pid=398886)[0m [386]	train-mlogloss:1.66113	validation-mlogloss:1.71439
[36m(train_xgb_ray_tune pid=398880)[0m [398]	train-mlogloss:1.63869	validation-mlogloss:1.71102
[36m(train_xgb_ray_tune pid=398905)[0m [372]	train-mlogloss:1.82166	validation-mlogloss:1.82173
[36m(train_xgb_ray_tune pid=398913)[0m [506]	train-mlogloss:2.15799	validation-mlogloss:2.17221
[36m(train_xgb_ray_tune pid=398903)[0m [392]	train-mlogloss:1.84577	validation-mlogloss:1.84245
[36m(train_xgb_ray_tune pid=398916)[0m [379]	train-mlogloss:2.31071	validation-mlogloss:2.30588
[36m(train_xgb_ray_tune pid=398879)[0m [373]	train-mlogloss:1.63428	validation-mlogloss:1.72217
[36m(train_xgb_ray_tune pid=398894)[0m [369]	train-mlogloss:1.89240	validation-mlogloss:1.87747
[36m(train_xgb_ray_tune pid=398900)[0m [382]	train-mlogloss:2.12746	validation-mlogloss:2.08868
[36m(train_xgb_ray_tune pid=398918)[0m [388]	train-mlogloss:2.14622	validation-mlogloss:2.10718
[36m(train_xgb_ray_tune pid=398913)[0m [507]	train-mlogloss:2.15799	validation-mlogloss:2.17221
[36m(train_xgb_ray_tune pid=398901)[0m [382]	train-mlogloss:1.67640	validation-mlogloss:1.73335
[36m(train_xgb_ray_tune pid=398917)[0m [373]	train-mlogloss:1.77546	validation-mlogloss:1.79575
[36m(train_xgb_ray_tune pid=398892)[0m [400]	train-mlogloss:1.80597	validation-mlogloss:1.80496
[36m(train_xgb_ray_tune pid=398886)[0m [387]	train-mlogloss:1.66048	validation-mlogloss:1.71411
[36m(train_xgb_ray_tune pid=398912)[0m [383]	train-mlogloss:1.80780	validation-mlogloss:1.81485
[36m(train_xgb_ray_tune pid=398906)[0m [403]	train-mlogloss:1.81180	validation-mlogloss:1.80448
[36m(train_xgb_ray_tune pid=398916)[0m [380]	train-mlogloss:2.31014	validation-mlogloss:2.30537
[36m(train_xgb_ray_tune pid=398894)[0m [370]	train-mlogloss:1.89151	validation-mlogloss:1.87683
[36m(train_xgb_ray_tune pid=398880)[0m [399]	train-mlogloss:1.63795	validation-mlogloss:1.71084
[36m(train_xgb_ray_tune pid=398900)[0m [383]	train-mlogloss:2.12668	validation-mlogloss:2.08791
[36m(train_xgb_ray_tune pid=398905)[0m [373]	train-mlogloss:1.82095	validation-mlogloss:1.82117
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[36m(train_xgb_ray_tune pid=398892)[0m [453]	train-mlogloss:1.77778	validation-mlogloss:1.78242
[36m(train_xgb_ray_tune pid=398912)[0m [435]	train-mlogloss:1.76862	validation-mlogloss:1.78787
[36m(train_xgb_ray_tune pid=398886)[0m [440]	train-mlogloss:1.62587	validation-mlogloss:1.70035
[36m(train_xgb_ray_tune pid=398903)[0m [440]	train-mlogloss:1.80882	validation-mlogloss:1.81473
[36m(train_xgb_ray_tune pid=398906)[0m [463]	train-mlogloss:1.78955	validation-mlogloss:1.78725
[36m(train_xgb_ray_tune pid=398916)[0m [428]	train-mlogloss:2.28401	validation-mlogloss:2.28012
[36m(train_xgb_ray_tune pid=398894)[0m [415]	train-mlogloss:1.85503	validation-mlogloss:1.84849
[36m(train_xgb_ray_tune pid=398880)[0m [451]	train-mlogloss:1.60440	validation-mlogloss:1.69827
[36m(train_xgb_ray_tune pid=398900)[0m [437]	train-mlogloss:2.08622	validation-mlogloss:2.05043
[36m(train_xgb_ray_tune pid=398905)[0m [422]	train-mlogloss:1.78973	validation-mlogloss:1.79755
[36m(train_xgb_ray_tune pid=398918)[0m [440]	train-mlogloss:2.10803	validation-mlogloss:2.07076
[36m(train_xgb_ray_tune pid=398913)[0m [582]	train-mlogloss:2.15402	validation-mlogloss:2.16749
[36m(train_xgb_ray_tune pid=398901)[0m [435]	train-mlogloss:1.63916	validation-mlogloss:1.71636
[36m(train_xgb_ray_tune pid=398917)[0m [422]	train-mlogloss:1.73836	validation-mlogloss:1.77198
[36m(train_xgb_ray_tune pid=398892)[0m [454]	train-mlogloss:1.77739	validation-mlogloss:1.78220
[36m(train_xgb_ray_tune pid=398886)[0m [441]	train-mlogloss:1.62528	validation-mlogloss:1.70018
[36m(train_xgb_ray_tune pid=398903)[0m [441]	train-mlogloss:1.80814	validation-mlogloss:1.81427
[36m(train_xgb_ray_tune pid=398912)[0m [436]	train-mlogloss:1.76792	validation-mlogloss:1.78733
[36m(train_xgb_ray_tune pid=398906)[0m [464]	train-mlogloss:1.78933	validation-mlogloss:1.78707
[36m(train_xgb_ray_tune pid=398916)[0m [429]	train-mlogloss:2.28349	validation-mlogloss:2.27962
[36m(train_xgb_ray_tune pid=398879)[0m [427]	train-mlogloss:1.59374	validation-mlogloss:1.70899
[36m(train_xgb_ray_tune pid=398894)[0m [416]	train-mlogloss:1.85429	validation-mlogloss:1.84796
[36m(train_xgb_ray_tune pid=398880)[0m [452]	train-mlogloss:1.60382	validation-mlogloss:1.69795
[36m(train_xgb_ray_tune pid=398905)[0m [423]	train-mlogloss:1.78908	validation-mlogloss:1.79710
[36m(train_xgb_ray_tune pid=398918)[0m [441]	train-mlogloss:2.10733	validation-mlogloss:2.07010
[36m(train_xgb_ray_tune pid=398913)[0m [583]	train-mlogloss:2.15402	validation-mlogloss:2.16749
[36m(train_xgb_ray_tune pid=398892)[0m [455]	train-mlogloss:1.77692	validation-mlogloss:1.78202
[36m(train_xgb_ray_tune pid=398903)[0m [442]	train-mlogloss:1.80743	validation-mlogloss:1.81380
[36m(train_xgb_ray_tune pid=398912)[0m [437]	train-mlogloss:1.76719	validation-mlogloss:1.78696
[36m(train_xgb_ray_tune pid=398906)[0m [465]	train-mlogloss:1.78907	validation-mlogloss:1.78705
[36m(train_xgb_ray_tune pid=398902)[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=398902)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=398916)[0m [430]	train-mlogloss:2.28295	validation-mlogloss:2.27903
[36m(train_xgb_ray_tune pid=398880)[0m [453]	train-mlogloss:1.60316	validation-mlogloss:1.69760
[36m(train_xgb_ray_tune pid=398900)[0m [438]	train-mlogloss:2.08548	validation-mlogloss:2.04972
[36m(train_xgb_ray_tune pid=398918)[0m [442]	train-mlogloss:2.10663	validation-mlogloss:2.06945
[36m(train_xgb_ray_tune pid=398913)[0m [584]	train-mlogloss:2.15402	validation-mlogloss:2.16749
[36m(train_xgb_ray_tune pid=398901)[0m [436]	train-mlogloss:1.63846	validation-mlogloss:1.71605
[36m(train_xgb_ray_tune pid=398917)[0m [423]	train-mlogloss:1.73762	validation-mlogloss:1.77148
[36m(train_xgb_ray_tune pid=398892)[0m [456]	train-mlogloss:1.77652	validation-mlogloss:1.78169
[36m(train_xgb_ray_tune pid=398879)[0m [428]	train-mlogloss:1.59303	validation-mlogloss:1.70870
[36m(train_xgb_ray_tune pid=398886)[0m [442]	train-mlogloss:1.62460	validation-mlogloss:1.69983
[36m(train_xgb_ray_tune pid=398916)[0m [431]	train-mlogloss:2.28247	validation-mlogloss:2.27858
[36m(train_xgb_ray_tune pid=398894)[0m [417]	train-mlogloss:1.85347	validation-mlogloss:1.84740
[36m(train_xgb_ray_tune pid=398880)[0m [454]	train-mlogloss:1.60267	validation-mlogloss:1.69742
[36m(train_xgb_ray_tune pid=398900)[0m [439]	train-mlogloss:2.08479	validation-mlogloss:2.04910
[36m(train_xgb_ray_tune pid=398905)[0m [424]	train-mlogloss:1.78854	validation-mlogloss:1.79658
[36m(train_xgb_ray_tune pid=398913)[0m [585]	train-mlogloss:2.15402	validation-mlogloss:2.16749
[36m(train_xgb_ray_tune pid=398901)[0m [437]	train-mlogloss:1.63781	validation-mlogloss:1.71560
[36m(train_xgb_ray_tune pid=398917)[0m [424]	train-mlogloss:1.73690	validation-mlogloss:1.77107
[36m(train_xgb_ray_tune pid=398892)[0m [457]	train-mlogloss:1.77609	validation-mlogloss:1.78130
[36m(train_xgb_ray_tune pid=398886)[0m [443]	train-mlogloss:1.62402	validation-mlogloss:1.69993
[36m(train_xgb_ray_tune pid=398903)[0m [443]	train-mlogloss:1.80673	validation-mlogloss:1.81342
[36m(train_xgb_ray_tune pid=398912)[0m [438]	train-mlogloss:1.76638	validation-mlogloss:1.78644
[36m(train_xgb_ray_tune pid=398906)[0m [466]	train-mlogloss:1.78870	validation-mlogloss:1.78681
[36m(train_xgb_ray_tune pid=398916)[0m [432]	train-mlogloss:2.28196	validation-mlogloss:2.27807
[36m(train_xgb_ray_tune pid=398879)[0m [429]	train-mlogloss:1.59225	validation-mlogloss:1.70866
[36m(train_xgb_ray_tune pid=398880)[0m [455]	train-mlogloss:1.60213	validation-mlogloss:1.69723
[36m(train_xgb_ray_tune pid=398900)[0m [440]	train-mlogloss:2.08408	validation-mlogloss:2.04842
[36m(train_xgb_ray_tune pid=398905)[0m [425]	train-mlogloss:1.78796	validation-mlogloss:1.79609
[36m(train_xgb_ray_tune pid=398918)[0m [443]	train-mlogloss:2.10594	validation-mlogloss:2.06879
[36m(train_xgb_ray_tune pid=398913)[0m [586]	train-mlogloss:2.15402	validation-mlogloss:2.16749
[36m(train_xgb_ray_tune pid=398917)[0m [425]	train-mlogloss:1.73620	validation-mlogloss:1.77065
[36m(train_xgb_ray_tune pid=398892)[0m [458]	train-mlogloss:1.77568	validation-mlogloss:1.78118
[36m(train_xgb_ray_tune pid=398901)[0m [438]	train-mlogloss:1.63721	validation-mlogloss:1.71532
[36m(train_xgb_ray_tune pid=398886)[0m [444]	train-mlogloss:1.62347	validation-mlogloss:1.69984
[36m(train_xgb_ray_tune pid=398903)[0m [444]	train-mlogloss:1.80607	validation-mlogloss:1.81312
[36m(train_xgb_ray_tune pid=398912)[0m [439]	train-mlogloss:1.76562	validation-mlogloss:1.78576
[36m(train_xgb_ray_tune pid=398906)[0m [467]	train-mlogloss:1.78848	validation-mlogloss:1.78663
[36m(train_xgb_ray_tune pid=398916)[0m [433]	train-mlogloss:2.28148	validation-mlogloss:2.27763
[36m(train_xgb_ray_tune pid=398879)[0m [430]	train-mlogloss:1.59158	validation-mlogloss:1.70892
[36m(train_xgb_ray_tune pid=398894)[0m [418]	train-mlogloss:1.85271	validation-mlogloss:1.84673
[36m(train_xgb_ray_tune pid=398880)[0m [456]	train-mlogloss:1.60150	validation-mlogloss:1.69695
[36m(train_xgb_ray_tune pid=398900)[0m [441]	train-mlogloss:2.08335	validation-mlogloss:2.04766
[36m(train_xgb_ray_tune pid=398918)[0m [444]	train-mlogloss:2.10525	validation-mlogloss:2.06813
[36m(train_xgb_ray_tune pid=398913)[0m [587]	train-mlogloss:2.15402	validation-mlogloss:2.16749
[36m(train_xgb_ray_tune pid=398901)[0m [439]	train-mlogloss:1.63660	validation-mlogloss:1.71502
[36m(train_xgb_ray_tune pid=398892)[0m [459]	train-mlogloss:1.77522	validation-mlogloss:1.78093
[36m(train_xgb_ray_tune pid=398905)[0m [426]	train-mlogloss:1.78744	validation-mlogloss:1.79569

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:01. Total running time: 1min 46s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             103.427 │
│ time_total_s                 103.427 │
│ training_iteration                 1 │
│ validation_accuracy           0.5001 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:01. Total running time: 1min 46s
[36m(train_xgb_ray_tune pid=398886)[0m [445]	train-mlogloss:1.62283	validation-mlogloss:1.69953
[36m(train_xgb_ray_tune pid=398912)[0m [440]	train-mlogloss:1.76491	validation-mlogloss:1.78518
[36m(train_xgb_ray_tune pid=398906)[0m [468]	train-mlogloss:1.78809	validation-mlogloss:1.78641
[36m(train_xgb_ray_tune pid=398879)[0m [431]	train-mlogloss:1.59087	validation-mlogloss:1.70878
[36m(train_xgb_ray_tune pid=398894)[0m [419]	train-mlogloss:1.85193	validation-mlogloss:1.84610
[36m(train_xgb_ray_tune pid=398913)[0m [588]	train-mlogloss:2.15402	validation-mlogloss:2.16749
[36m(train_xgb_ray_tune pid=398917)[0m [426]	train-mlogloss:1.73548	validation-mlogloss:1.77007
[36m(train_xgb_ray_tune pid=398917)[0m [427]	train-mlogloss:1.73479	validation-mlogloss:1.76974
[36m(train_xgb_ray_tune pid=398892)[0m [460]	train-mlogloss:1.77474	validation-mlogloss:1.78061
[36m(train_xgb_ray_tune pid=398903)[0m [445]	train-mlogloss:1.80534	validation-mlogloss:1.81249
[36m(train_xgb_ray_tune pid=398916)[0m [434]	train-mlogloss:2.28098	validation-mlogloss:2.27714
[36m(train_xgb_ray_tune pid=398903)[0m [446]	train-mlogloss:1.80462	validation-mlogloss:1.81190
[36m(train_xgb_ray_tune pid=398912)[0m [441]	train-mlogloss:1.76422	validation-mlogloss:1.78456
[36m(train_xgb_ray_tune pid=398906)[0m [469]	train-mlogloss:1.78780	validation-mlogloss:1.78623
[36m(train_xgb_ray_tune pid=398880)[0m [457]	train-mlogloss:1.60096	validation-mlogloss:1.69679
[36m(train_xgb_ray_tune pid=398900)[0m [442]	train-mlogloss:2.08263	validation-mlogloss:2.04690
[36m(train_xgb_ray_tune pid=398905)[0m [427]	train-mlogloss:1.78680	validation-mlogloss:1.79523
[36m(train_xgb_ray_tune pid=398918)[0m [445]	train-mlogloss:2.10455	validation-mlogloss:2.06743
[36m(train_xgb_ray_tune pid=398913)[0m [589]	train-mlogloss:2.15402	validation-mlogloss:2.16749
[36m(train_xgb_ray_tune pid=398901)[0m [440]	train-mlogloss:1.63602	validation-mlogloss:1.71500
[36m(train_xgb_ray_tune pid=398886)[0m [446]	train-mlogloss:1.62220	validation-mlogloss:1.69930
[36m(train_xgb_ray_tune pid=398879)[0m [432]	train-mlogloss:1.59020	validation-mlogloss:1.70850
[36m(train_xgb_ray_tune pid=398917)[0m [428]	train-mlogloss:1.73412	validation-mlogloss:1.76938
[36m(train_xgb_ray_tune pid=398903)[0m [447]	train-mlogloss:1.80393	validation-mlogloss:1.81145
[36m(train_xgb_ray_tune pid=398912)[0m [442]	train-mlogloss:1.76354	validation-mlogloss:1.78418
[36m(train_xgb_ray_tune pid=398906)[0m [470]	train-mlogloss:1.78759	validation-mlogloss:1.78615
[36m(train_xgb_ray_tune pid=398916)[0m [435]	train-mlogloss:2.28048	validation-mlogloss:2.27667
[36m(train_xgb_ray_tune pid=398894)[0m [420]	train-mlogloss:1.85114	validation-mlogloss:1.84545
[36m(train_xgb_ray_tune pid=398880)[0m [458]	train-mlogloss:1.60033	validation-mlogloss:1.69643
[36m(train_xgb_ray_tune pid=398900)[0m [443]	train-mlogloss:2.08195	validation-mlogloss:2.04617
[36m(train_xgb_ray_tune pid=398905)[0m [428]	train-mlogloss:1.78632	validation-mlogloss:1.79491
[36m(train_xgb_ray_tune pid=398918)[0m [446]	train-mlogloss:2.10385	validation-mlogloss:2.06671
[36m(train_xgb_ray_tune pid=398913)[0m [590]	train-mlogloss:2.15402	validation-mlogloss:2.16749
[36m(train_xgb_ray_tune pid=398901)[0m [441]	train-mlogloss:1.63541	validation-mlogloss:1.71467
[36m(train_xgb_ray_tune pid=398892)[0m [461]	train-mlogloss:1.77435	validation-mlogloss:1.78034
[36m(train_xgb_ray_tune pid=398901)[0m [442]	train-mlogloss:1.63476	validation-mlogloss:1.71461
[36m(train_xgb_ray_tune pid=398886)[0m [447]	train-mlogloss:1.62164	validation-mlogloss:1.69909
[36m(train_xgb_ray_tune pid=398903)[0m [448]	train-mlogloss:1.80322	validation-mlogloss:1.81091
[36m(train_xgb_ray_tune pid=398912)[0m [443]	train-mlogloss:1.76283	validation-mlogloss:1.78377
[36m(train_xgb_ray_tune pid=398916)[0m [436]	train-mlogloss:2.27997	validation-mlogloss:2.27621
[36m(train_xgb_ray_tune pid=398879)[0m [433]	train-mlogloss:1.58954	validation-mlogloss:1.70830
[36m(train_xgb_ray_tune pid=398894)[0m [421]	train-mlogloss:1.85041	validation-mlogloss:1.84490
[36m(train_xgb_ray_tune pid=398900)[0m [444]	train-mlogloss:2.08121	validation-mlogloss:2.04550
[36m(train_xgb_ray_tune pid=398905)[0m [429]	train-mlogloss:1.78570	validation-mlogloss:1.79447
[36m(train_xgb_ray_tune pid=398913)[0m [591]	train-mlogloss:2.15379	validation-mlogloss:2.16713
[36m(train_xgb_ray_tune pid=398901)[0m [443]	train-mlogloss:1.63408	validation-mlogloss:1.71441
[36m(train_xgb_ray_tune pid=398917)[0m [429]	train-mlogloss:1.73343	validation-mlogloss:1.76901
[36m(train_xgb_ray_tune pid=398892)[0m [462]	train-mlogloss:1.77384	validation-mlogloss:1.78003
[36m(train_xgb_ray_tune pid=398918)[0m [447]	train-mlogloss:2.10316	validation-mlogloss:2.06606
[36m(train_xgb_ray_tune pid=398886)[0m [448]	train-mlogloss:1.62107	validation-mlogloss:1.69904
[36m(train_xgb_ray_tune pid=398903)[0m [449]	train-mlogloss:1.80250	validation-mlogloss:1.81037
[36m(train_xgb_ray_tune pid=398912)[0m [444]	train-mlogloss:1.76212	validation-mlogloss:1.78337
[36m(train_xgb_ray_tune pid=398906)[0m [471]	train-mlogloss:1.78727	validation-mlogloss:1.78597
[36m(train_xgb_ray_tune pid=398916)[0m [437]	train-mlogloss:2.27951	validation-mlogloss:2.27578
[36m(train_xgb_ray_tune pid=398879)[0m [434]	train-mlogloss:1.58886	validation-mlogloss:1.70811
[36m(train_xgb_ray_tune pid=398880)[0m [459]	train-mlogloss:1.59979	validation-mlogloss:1.69627
[36m(train_xgb_ray_tune pid=398900)[0m [445]	train-mlogloss:2.08049	validation-mlogloss:2.04473
[36m(train_xgb_ray_tune pid=398905)[0m [430]	train-mlogloss:1.78513	validation-mlogloss:1.79406
[36m(train_xgb_ray_tune pid=398913)[0m [592]	train-mlogloss:2.15379	validation-mlogloss:2.16713
[36m(train_xgb_ray_tune pid=398901)[0m [444]	train-mlogloss:1.63345	validation-mlogloss:1.71422
[36m(train_xgb_ray_tune pid=398917)[0m [430]	train-mlogloss:1.73273	validation-mlogloss:1.76872
[36m(train_xgb_ray_tune pid=398892)[0m [463]	train-mlogloss:1.77331	validation-mlogloss:1.77963
[36m(train_xgb_ray_tune pid=398903)[0m [450]	train-mlogloss:1.80180	validation-mlogloss:1.80989
[36m(train_xgb_ray_tune pid=398912)[0m [445]	train-mlogloss:1.76139	validation-mlogloss:1.78294
[36m(train_xgb_ray_tune pid=398906)[0m [472]	train-mlogloss:1.78697	validation-mlogloss:1.78593
[36m(train_xgb_ray_tune pid=398916)[0m [438]	train-mlogloss:2.27899	validation-mlogloss:2.27526
[36m(train_xgb_ray_tune pid=398879)[0m [435]	train-mlogloss:1.58822	validation-mlogloss:1.70805
[36m(train_xgb_ray_tune pid=398894)[0m [422]	train-mlogloss:1.84967	validation-mlogloss:1.84433
[36m(train_xgb_ray_tune pid=398880)[0m [460]	train-mlogloss:1.59924	validation-mlogloss:1.69601
[36m(train_xgb_ray_tune pid=398900)[0m [446]	train-mlogloss:2.07982	validation-mlogloss:2.04410
[36m(train_xgb_ray_tune pid=398918)[0m [448]	train-mlogloss:2.10246	validation-mlogloss:2.06545
[36m(train_xgb_ray_tune pid=398913)[0m [593]	train-mlogloss:2.15379	validation-mlogloss:2.16713
[36m(train_xgb_ray_tune pid=398901)[0m [445]	train-mlogloss:1.63285	validation-mlogloss:1.71371
[36m(train_xgb_ray_tune pid=398905)[0m [431]	train-mlogloss:1.78453	validation-mlogloss:1.79364
[36m(train_xgb_ray_tune pid=398886)[0m [449]	train-mlogloss:1.62049	validation-mlogloss:1.69868
[36m(train_xgb_ray_tune pid=398903)[0m [451]	train-mlogloss:1.80110	validation-mlogloss:1.80946
[36m(train_xgb_ray_tune pid=398912)[0m [446]	train-mlogloss:1.76067	validation-mlogloss:1.78254
[36m(train_xgb_ray_tune pid=398906)[0m [473]	train-mlogloss:1.78674	validation-mlogloss:1.78569
[36m(train_xgb_ray_tune pid=398916)[0m [439]	train-mlogloss:2.27845	validation-mlogloss:2.27476
[36m(train_xgb_ray_tune pid=398894)[0m [423]	train-mlogloss:1.84892	validation-mlogloss:1.84369
[36m(train_xgb_ray_tune pid=398880)[0m [461]	train-mlogloss:1.59875	validation-mlogloss:1.69576
[36m(train_xgb_ray_tune pid=398918)[0m [449]	train-mlogloss:2.10176	validation-mlogloss:2.06481
[36m(train_xgb_ray_tune pid=398913)[0m [594]	train-mlogloss:2.15379	validation-mlogloss:2.16713
[36m(train_xgb_ray_tune pid=398901)[0m [446]	train-mlogloss:1.63221	validation-mlogloss:1.71340
[36m(train_xgb_ray_tune pid=398917)[0m [431]	train-mlogloss:1.73204	validation-mlogloss:1.76837
[36m(train_xgb_ray_tune pid=398892)[0m [464]	train-mlogloss:1.77282	validation-mlogloss:1.77913
[36m(train_xgb_ray_tune pid=398886)[0m [450]	train-mlogloss:1.61991	validation-mlogloss:1.69857
[36m(train_xgb_ray_tune pid=398903)[0m [452]	train-mlogloss:1.80037	validation-mlogloss:1.80891
[36m(train_xgb_ray_tune pid=398912)[0m [447]	train-mlogloss:1.75999	validation-mlogloss:1.78212
[36m(train_xgb_ray_tune pid=398906)[0m [474]	train-mlogloss:1.78649	validation-mlogloss:1.78557
[36m(train_xgb_ray_tune pid=398916)[0m [440]	train-mlogloss:2.27794	validation-mlogloss:2.27425
[36m(train_xgb_ray_tune pid=398900)[0m [447]	train-mlogloss:2.07911	validation-mlogloss:2.04345
[36m(train_xgb_ray_tune pid=398905)[0m [432]	train-mlogloss:1.78397	validation-mlogloss:1.79328
[36m(train_xgb_ray_tune pid=398913)[0m [595]	train-mlogloss:2.15379	validation-mlogloss:2.16713
[36m(train_xgb_ray_tune pid=398901)[0m [447]	train-mlogloss:1.63157	validation-mlogloss:1.71301
[36m(train_xgb_ray_tune pid=398917)[0m [432]	train-mlogloss:1.73133	validation-mlogloss:1.76790
[36m(train_xgb_ray_tune pid=398892)[0m [465]	train-mlogloss:1.77236	validation-mlogloss:1.77882
[36m(train_xgb_ray_tune pid=398903)[0m [453]	train-mlogloss:1.79964	validation-mlogloss:1.80845
[36m(train_xgb_ray_tune pid=398912)[0m [448]	train-mlogloss:1.75937	validation-mlogloss:1.78180
[36m(train_xgb_ray_tune pid=398906)[0m [475]	train-mlogloss:1.78610	validation-mlogloss:1.78526
[36m(train_xgb_ray_tune pid=398916)[0m [441]	train-mlogloss:2.27745	validation-mlogloss:2.27381
[36m(train_xgb_ray_tune pid=398894)[0m [424]	train-mlogloss:1.84820	validation-mlogloss:1.84312
[36m(train_xgb_ray_tune pid=398880)[0m [462]	train-mlogloss:1.59822	validation-mlogloss:1.69569
[36m(train_xgb_ray_tune pid=398900)[0m [448]	train-mlogloss:2.07844	validation-mlogloss:2.04286
[36m(train_xgb_ray_tune pid=398905)[0m [433]	train-mlogloss:1.78350	validation-mlogloss:1.79286
[36m(train_xgb_ray_tune pid=398918)[0m [450]	train-mlogloss:2.10107	validation-mlogloss:2.06417
[36m(train_xgb_ray_tune pid=398913)[0m [596]	train-mlogloss:2.15369	validation-mlogloss:2.16710
[36m(train_xgb_ray_tune pid=398901)[0m [448]	train-mlogloss:1.63097	validation-mlogloss:1.71273
[36m(train_xgb_ray_tune pid=398917)[0m [433]	train-mlogloss:1.73064	validation-mlogloss:1.76754
[36m(train_xgb_ray_tune pid=398892)[0m [466]	train-mlogloss:1.77192	validation-mlogloss:1.77860
[36m(train_xgb_ray_tune pid=398886)[0m [451]	train-mlogloss:1.61939	validation-mlogloss:1.69838
[36m(train_xgb_ray_tune pid=398879)[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=398879)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=398903)[0m [454]	train-mlogloss:1.79898	validation-mlogloss:1.80794
[36m(train_xgb_ray_tune pid=398916)[0m [442]	train-mlogloss:2.27691	validation-mlogloss:2.27329
[36m(train_xgb_ray_tune pid=398880)[0m [463]	train-mlogloss:1.59771	validation-mlogloss:1.69553
[36m(train_xgb_ray_tune pid=398900)[0m [449]	train-mlogloss:2.07779	validation-mlogloss:2.04222
[36m(train_xgb_ray_tune pid=398905)[0m [434]	train-mlogloss:1.78295	validation-mlogloss:1.79246
[36m(train_xgb_ray_tune pid=398913)[0m [597]	train-mlogloss:2.15361	validation-mlogloss:2.16707
[36m(train_xgb_ray_tune pid=398901)[0m [449]	train-mlogloss:1.63037	validation-mlogloss:1.71261
[36m(train_xgb_ray_tune pid=398912)[0m [449]	train-mlogloss:1.75869	validation-mlogloss:1.78147
[36m(train_xgb_ray_tune pid=398894)[0m [425]	train-mlogloss:1.84746	validation-mlogloss:1.84249
[36m(train_xgb_ray_tune pid=398918)[0m [451]	train-mlogloss:2.10038	validation-mlogloss:2.06343
[36m(train_xgb_ray_tune pid=398901)[0m [450]	train-mlogloss:1.62977	validation-mlogloss:1.71219
[36m(train_xgb_ray_tune pid=398886)[0m [452]	train-mlogloss:1.61878	validation-mlogloss:1.69812
[36m(train_xgb_ray_tune pid=398903)[0m [455]	train-mlogloss:1.79829	validation-mlogloss:1.80748
[36m(train_xgb_ray_tune pid=398906)[0m [476]	train-mlogloss:1.78581	validation-mlogloss:1.78511
[36m(train_xgb_ray_tune pid=398916)[0m [443]	train-mlogloss:2.27640	validation-mlogloss:2.27283
[36m(train_xgb_ray_tune pid=398880)[0m [464]	train-mlogloss:1.59727	validation-mlogloss:1.69543
[36m(train_xgb_ray_tune pid=398900)[0m [450]	train-mlogloss:2.07711	validation-mlogloss:2.04163
[36m(train_xgb_ray_tune pid=398905)[0m [435]	train-mlogloss:1.78243	validation-mlogloss:1.79219
[36m(train_xgb_ray_tune pid=398913)[0m [598]	train-mlogloss:2.15361	validation-mlogloss:2.16707
[36m(train_xgb_ray_tune pid=398901)[0m [451]	train-mlogloss:1.62911	validation-mlogloss:1.71185
[36m(train_xgb_ray_tune pid=398917)[0m [434]	train-mlogloss:1.73000	validation-mlogloss:1.76711
[36m(train_xgb_ray_tune pid=398892)[0m [467]	train-mlogloss:1.77144	validation-mlogloss:1.77820
[36m(train_xgb_ray_tune pid=398886)[0m [453]	train-mlogloss:1.61817	validation-mlogloss:1.69779
[36m(train_xgb_ray_tune pid=398912)[0m [450]	train-mlogloss:1.75789	validation-mlogloss:1.78112
[36m(train_xgb_ray_tune pid=398906)[0m [477]	train-mlogloss:1.78550	validation-mlogloss:1.78496
[36m(train_xgb_ray_tune pid=398916)[0m [444]	train-mlogloss:2.27590	validation-mlogloss:2.27235
[36m(train_xgb_ray_tune pid=398894)[0m [426]	train-mlogloss:1.84671	validation-mlogloss:1.84191
[36m(train_xgb_ray_tune pid=398900)[0m [451]	train-mlogloss:2.07642	validation-mlogloss:2.04100
[36m(train_xgb_ray_tune pid=398905)[0m [436]	train-mlogloss:1.78189	validation-mlogloss:1.79188
[36m(train_xgb_ray_tune pid=398918)[0m [452]	train-mlogloss:2.09969	validation-mlogloss:2.06279
[36m(train_xgb_ray_tune pid=398913)[0m [599]	train-mlogloss:2.15349	validation-mlogloss:2.16697
[36m(train_xgb_ray_tune pid=398901)[0m [452]	train-mlogloss:1.62839	validation-mlogloss:1.71166
[36m(train_xgb_ray_tune pid=398917)[0m [435]	train-mlogloss:1.72933	validation-mlogloss:1.76679
[36m(train_xgb_ray_tune pid=398892)[0m [468]	train-mlogloss:1.77092	validation-mlogloss:1.77794
[36m(train_xgb_ray_tune pid=398916)[0m [445]	train-mlogloss:2.27541	validation-mlogloss:2.27191
[36m(train_xgb_ray_tune pid=398903)[0m [456]	train-mlogloss:1.79766	validation-mlogloss:1.80700
[36m(train_xgb_ray_tune pid=398912)[0m [451]	train-mlogloss:1.75724	validation-mlogloss:1.78075
[36m(train_xgb_ray_tune pid=398906)[0m [478]	train-mlogloss:1.78507	validation-mlogloss:1.78457
[36m(train_xgb_ray_tune pid=398916)[0m [446]	train-mlogloss:2.27493	validation-mlogloss:2.27145
[36m(train_xgb_ray_tune pid=398880)[0m [465]	train-mlogloss:1.59672	validation-mlogloss:1.69524
[36m(train_xgb_ray_tune pid=398900)[0m [452]	train-mlogloss:2.07573	validation-mlogloss:2.04036
[36m(train_xgb_ray_tune pid=398905)[0m [437]	train-mlogloss:1.78137	validation-mlogloss:1.79158
[36m(train_xgb_ray_tune pid=398913)[0m [600]	train-mlogloss:2.15344	validation-mlogloss:2.16685
[36m(train_xgb_ray_tune pid=398901)[0m [453]	train-mlogloss:1.62775	validation-mlogloss:1.71153
[36m(train_xgb_ray_tune pid=398886)[0m [454]	train-mlogloss:1.61762	validation-mlogloss:1.69737
[36m(train_xgb_ray_tune pid=398912)[0m [452]	train-mlogloss:1.75654	validation-mlogloss:1.78037
[36m(train_xgb_ray_tune pid=398906)[0m [479]	train-mlogloss:1.78468	validation-mlogloss:1.78435
[36m(train_xgb_ray_tune pid=398916)[0m [447]	train-mlogloss:2.27445	validation-mlogloss:2.27100
[36m(train_xgb_ray_tune pid=398894)[0m [427]	train-mlogloss:1.84594	validation-mlogloss:1.84135
[36m(train_xgb_ray_tune pid=398880)[0m [466]	train-mlogloss:1.59623	validation-mlogloss:1.69512
[36m(train_xgb_ray_tune pid=398900)[0m [453]	train-mlogloss:2.07506	validation-mlogloss:2.03975
[36m(train_xgb_ray_tune pid=398905)[0m [438]	train-mlogloss:1.78077	validation-mlogloss:1.79109
[36m(train_xgb_ray_tune pid=398918)[0m [453]	train-mlogloss:2.09899	validation-mlogloss:2.06212
[36m(train_xgb_ray_tune pid=398913)[0m [601]	train-mlogloss:2.15344	validation-mlogloss:2.16685
[36m(train_xgb_ray_tune pid=398901)[0m [454]	train-mlogloss:1.62708	validation-mlogloss:1.71110
[36m(train_xgb_ray_tune pid=398917)[0m [436]	train-mlogloss:1.72864	validation-mlogloss:1.76642
[36m(train_xgb_ray_tune pid=398892)[0m [469]	train-mlogloss:1.77044	validation-mlogloss:1.77758
[36m(train_xgb_ray_tune pid=398903)[0m [457]	train-mlogloss:1.79700	validation-mlogloss:1.80639
[36m(train_xgb_ray_tune pid=398917)[0m [437]	train-mlogloss:1.72802	validation-mlogloss:1.76592

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:03. Total running time: 1min 48s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s              105.27 │
│ time_total_s                  105.27 │
│ training_iteration                 1 │
│ validation_accuracy          0.51777 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=398886)[0m [455]	train-mlogloss:1.61711	validation-mlogloss:1.69728
[36m(train_xgb_ray_tune pid=398912)[0m [453]	train-mlogloss:1.75586	validation-mlogloss:1.78006
[36m(train_xgb_ray_tune pid=398916)[0m [448]	train-mlogloss:2.27397	validation-mlogloss:2.27054
[36m(train_xgb_ray_tune pid=398894)[0m [428]	train-mlogloss:1.84518	validation-mlogloss:1.84071
[36m(train_xgb_ray_tune pid=398880)[0m [467]	train-mlogloss:1.59572	validation-mlogloss:1.69486
[36m(train_xgb_ray_tune pid=398918)[0m [454]	train-mlogloss:2.09831	validation-mlogloss:2.06141
[36m(train_xgb_ray_tune pid=398913)[0m [602]	train-mlogloss:2.15344	validation-mlogloss:2.16685
[36m(train_xgb_ray_tune pid=398901)[0m [455]	train-mlogloss:1.62644	validation-mlogloss:1.71078
[36m(train_xgb_ray_tune pid=398917)[0m [438]	train-mlogloss:1.72735	validation-mlogloss:1.76554
[36m(train_xgb_ray_tune pid=398892)[0m [470]	train-mlogloss:1.76999	validation-mlogloss:1.77734
[36m(train_xgb_ray_tune pid=398906)[0m [480]	train-mlogloss:1.78439	validation-mlogloss:1.78419

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:03. Total running time: 1min 48s
[36m(train_xgb_ray_tune pid=398903)[0m [458]	train-mlogloss:1.79635	validation-mlogloss:1.80589
[36m(train_xgb_ray_tune pid=398912)[0m [454]	train-mlogloss:1.75524	validation-mlogloss:1.77977
[36m(train_xgb_ray_tune pid=398906)[0m [481]	train-mlogloss:1.78418	validation-mlogloss:1.78407
[36m(train_xgb_ray_tune pid=398916)[0m [449]	train-mlogloss:2.27352	validation-mlogloss:2.27012
[36m(train_xgb_ray_tune pid=398894)[0m [429]	train-mlogloss:1.84444	validation-mlogloss:1.84010
[36m(train_xgb_ray_tune pid=398900)[0m [454]	train-mlogloss:2.07436	validation-mlogloss:2.03918
[36m(train_xgb_ray_tune pid=398905)[0m [439]	train-mlogloss:1.78025	validation-mlogloss:1.79066
[36m(train_xgb_ray_tune pid=398918)[0m [455]	train-mlogloss:2.09767	validation-mlogloss:2.06077
[36m(train_xgb_ray_tune pid=398913)[0m [603]	train-mlogloss:2.15333	validation-mlogloss:2.16676
[36m(train_xgb_ray_tune pid=398901)[0m [456]	train-mlogloss:1.62587	validation-mlogloss:1.71059
[36m(train_xgb_ray_tune pid=398917)[0m [439]	train-mlogloss:1.72667	validation-mlogloss:1.76515
[36m(train_xgb_ray_tune pid=398892)[0m [471]	train-mlogloss:1.76955	validation-mlogloss:1.77699
[36m(train_xgb_ray_tune pid=398886)[0m [456]	train-mlogloss:1.61652	validation-mlogloss:1.69721
[36m(train_xgb_ray_tune pid=398903)[0m [459]	train-mlogloss:1.79565	validation-mlogloss:1.80545
[36m(train_xgb_ray_tune pid=398912)[0m [455]	train-mlogloss:1.75450	validation-mlogloss:1.77919
[36m(train_xgb_ray_tune pid=398906)[0m [482]	train-mlogloss:1.78388	validation-mlogloss:1.78381
[36m(train_xgb_ray_tune pid=398916)[0m [450]	train-mlogloss:2.27302	validation-mlogloss:2.26964
[36m(train_xgb_ray_tune pid=398880)[0m [468]	train-mlogloss:1.59514	validation-mlogloss:1.69488
[36m(train_xgb_ray_tune pid=398900)[0m [455]	train-mlogloss:2.07369	validation-mlogloss:2.03856
[36m(train_xgb_ray_tune pid=398905)[0m [440]	train-mlogloss:1.77975	validation-mlogloss:1.79040
[36m(train_xgb_ray_tune pid=398918)[0m [456]	train-mlogloss:2.09697	validation-mlogloss:2.06012
[36m(train_xgb_ray_tune pid=398913)[0m [604]	train-mlogloss:2.15333	validation-mlogloss:2.16676
[36m(train_xgb_ray_tune pid=398901)[0m [457]	train-mlogloss:1.62529	validation-mlogloss:1.71037
[36m(train_xgb_ray_tune pid=398917)[0m [440]	train-mlogloss:1.72594	validation-mlogloss:1.76458
[36m(train_xgb_ray_tune pid=398892)[0m [472]	train-mlogloss:1.76912	validation-mlogloss:1.77650
[36m(train_xgb_ray_tune pid=398912)[0m [456]	train-mlogloss:1.75381	validation-mlogloss:1.77883
[36m(train_xgb_ray_tune pid=398886)[0m [457]	train-mlogloss:1.61599	validation-mlogloss:1.69690
[36m(train_xgb_ray_tune pid=398906)[0m [483]	train-mlogloss:1.78355	validation-mlogloss:1.78350
[36m(train_xgb_ray_tune pid=398894)[0m [430]	train-mlogloss:1.84365	validation-mlogloss:1.83948
[36m(train_xgb_ray_tune pid=398880)[0m [469]	train-mlogloss:1.59463	validation-mlogloss:1.69468
[36m(train_xgb_ray_tune pid=398900)[0m [456]	train-mlogloss:2.07301	validation-mlogloss:2.03790
[36m(train_xgb_ray_tune pid=398913)[0m [605]	train-mlogloss:2.15320	validation-mlogloss:2.16664
[36m(train_xgb_ray_tune pid=398913)[0m [606]	train-mlogloss:2.15320	validation-mlogloss:2.16664
[36m(train_xgb_ray_tune pid=398901)[0m [458]	train-mlogloss:1.62472	validation-mlogloss:1.71008
[36m(train_xgb_ray_tune pid=398917)[0m [441]	train-mlogloss:1.72525	validation-mlogloss:1.76418
[36m(train_xgb_ray_tune pid=398892)[0m [473]	train-mlogloss:1.76869	validation-mlogloss:1.77628
[36m(train_xgb_ray_tune pid=398912)[0m [457]	train-mlogloss:1.75312	validation-mlogloss:1.77850
[36m(train_xgb_ray_tune pid=398906)[0m [484]	train-mlogloss:1.78324	validation-mlogloss:1.78326
[36m(train_xgb_ray_tune pid=398905)[0m [441]	train-mlogloss:1.77923	validation-mlogloss:1.79000
[36m(train_xgb_ray_tune pid=398901)[0m [459]	train-mlogloss:1.62412	validation-mlogloss:1.70999
[36m(train_xgb_ray_tune pid=398892)[0m [474]	train-mlogloss:1.76830	validation-mlogloss:1.77599
[36m(train_xgb_ray_tune pid=398886)[0m [458]	train-mlogloss:1.61535	validation-mlogloss:1.69656
[36m(train_xgb_ray_tune pid=398903)[0m [460]	train-mlogloss:1.79495	validation-mlogloss:1.80501
[36m(train_xgb_ray_tune pid=398912)[0m [458]	train-mlogloss:1.75247	validation-mlogloss:1.77812
[36m(train_xgb_ray_tune pid=398916)[0m [451]	train-mlogloss:2.27251	validation-mlogloss:2.26911
[36m(train_xgb_ray_tune pid=398894)[0m [431]	train-mlogloss:1.84289	validation-mlogloss:1.83887
[36m(train_xgb_ray_tune pid=398880)[0m [470]	train-mlogloss:1.59406	validation-mlogloss:1.69465
[36m(train_xgb_ray_tune pid=398918)[0m [457]	train-mlogloss:2.09629	validation-mlogloss:2.05953
[36m(train_xgb_ray_tune pid=398913)[0m [607]	train-mlogloss:2.15320	validation-mlogloss:2.16664
[36m(train_xgb_ray_tune pid=398913)[0m [608]	train-mlogloss:2.15313	validation-mlogloss:2.16661
[36m(train_xgb_ray_tune pid=398901)[0m [460]	train-mlogloss:1.62345	validation-mlogloss:1.70970
[36m(train_xgb_ray_tune pid=398917)[0m [442]	train-mlogloss:1.72453	validation-mlogloss:1.76365
[36m(train_xgb_ray_tune pid=398892)[0m [475]	train-mlogloss:1.76786	validation-mlogloss:1.77571
[36m(train_xgb_ray_tune pid=398903)[0m [461]	train-mlogloss:1.79426	validation-mlogloss:1.80448
[36m(train_xgb_ray_tune pid=398912)[0m [459]	train-mlogloss:1.75181	validation-mlogloss:1.77775
[36m(train_xgb_ray_tune pid=398906)[0m [485]	train-mlogloss:1.78298	validation-mlogloss:1.78291
[36m(train_xgb_ray_tune pid=398916)[0m [452]	train-mlogloss:2.27196	validation-mlogloss:2.26851
[36m(train_xgb_ray_tune pid=398880)[0m [471]	train-mlogloss:1.59349	validation-mlogloss:1.69459
[36m(train_xgb_ray_tune pid=398900)[0m [457]	train-mlogloss:2.07233	validation-mlogloss:2.03732
[36m(train_xgb_ray_tune pid=398905)[0m [442]	train-mlogloss:1.77867	validation-mlogloss:1.78968
[36m(train_xgb_ray_tune pid=398918)[0m [458]	train-mlogloss:2.09561	validation-mlogloss:2.05886
[36m(train_xgb_ray_tune pid=398913)[0m [609]	train-mlogloss:2.15307	validation-mlogloss:2.16654
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[36m(train_xgb_ray_tune pid=398917)[0m [443]	train-mlogloss:1.72386	validation-mlogloss:1.76334
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[36m(train_xgb_ray_tune pid=398916)[0m [490]	train-mlogloss:2.25410	validation-mlogloss:2.25122
[36m(train_xgb_ray_tune pid=398894)[0m [467]	train-mlogloss:1.81738	validation-mlogloss:1.82018
[36m(train_xgb_ray_tune pid=398880)[0m [512]	train-mlogloss:1.57229	validation-mlogloss:1.68769
[36m(train_xgb_ray_tune pid=398900)[0m [494]	train-mlogloss:2.04784	validation-mlogloss:2.01499
[36m(train_xgb_ray_tune pid=398905)[0m [495]	train-mlogloss:1.75431	validation-mlogloss:1.77375
[36m(train_xgb_ray_tune pid=398905)[0m [496]	train-mlogloss:1.75396	validation-mlogloss:1.77349
[36m(train_xgb_ray_tune pid=398918)[0m [508]	train-mlogloss:2.06362	validation-mlogloss:2.02995
[36m(train_xgb_ray_tune pid=398913)[0m [690]	train-mlogloss:2.14930	validation-mlogloss:2.16190
[36m(train_xgb_ray_tune pid=398917)[0m [493]	train-mlogloss:1.69275	validation-mlogloss:1.74619
[36m(train_xgb_ray_tune pid=398892)[0m [541]	train-mlogloss:1.74419	validation-mlogloss:1.75997
[36m(train_xgb_ray_tune pid=398886)[0m [506]	train-mlogloss:1.58990	validation-mlogloss:1.68777
[36m(train_xgb_ray_tune pid=398912)[0m [501]	train-mlogloss:1.72525	validation-mlogloss:1.76280
[36m(train_xgb_ray_tune pid=398894)[0m [468]	train-mlogloss:1.81673	validation-mlogloss:1.81976
[36m(train_xgb_ray_tune pid=398880)[0m [513]	train-mlogloss:1.57181	validation-mlogloss:1.68755
[36m(train_xgb_ray_tune pid=398905)[0m [497]	train-mlogloss:1.75349	validation-mlogloss:1.77326
[36m(train_xgb_ray_tune pid=398918)[0m [509]	train-mlogloss:2.06302	validation-mlogloss:2.02943
[36m(train_xgb_ray_tune pid=398913)[0m [691]	train-mlogloss:2.14930	validation-mlogloss:2.16190
[36m(train_xgb_ray_tune pid=398913)[0m [692]	train-mlogloss:2.14913	validation-mlogloss:2.16175
[36m(train_xgb_ray_tune pid=398901)[0m [501]	train-mlogloss:1.59953	validation-mlogloss:1.70190
[36m(train_xgb_ray_tune pid=398917)[0m [494]	train-mlogloss:1.69214	validation-mlogloss:1.74601
[36m(train_xgb_ray_tune pid=398892)[0m [542]	train-mlogloss:1.74384	validation-mlogloss:1.75975
[36m(train_xgb_ray_tune pid=398892)[0m [543]	train-mlogloss:1.74355	validation-mlogloss:1.75949
[36m(train_xgb_ray_tune pid=398903)[0m [499]	train-mlogloss:1.76932	validation-mlogloss:1.78755
[36m(train_xgb_ray_tune pid=398912)[0m [502]	train-mlogloss:1.72466	validation-mlogloss:1.76253
[36m(train_xgb_ray_tune pid=398916)[0m [491]	train-mlogloss:2.25367	validation-mlogloss:2.25081
[36m(train_xgb_ray_tune pid=398880)[0m [514]	train-mlogloss:1.57129	validation-mlogloss:1.68728
[36m(train_xgb_ray_tune pid=398900)[0m [495]	train-mlogloss:2.04722	validation-mlogloss:2.01443
[36m(train_xgb_ray_tune pid=398905)[0m [498]	train-mlogloss:1.75307	validation-mlogloss:1.77310
[36m(train_xgb_ray_tune pid=398918)[0m [510]	train-mlogloss:2.06239	validation-mlogloss:2.02890
[36m(train_xgb_ray_tune pid=398918)[0m [511]	train-mlogloss:2.06178	validation-mlogloss:2.02841
[36m(train_xgb_ray_tune pid=398913)[0m [693]	train-mlogloss:2.14913	validation-mlogloss:2.16175
[36m(train_xgb_ray_tune pid=398901)[0m [502]	train-mlogloss:1.59894	validation-mlogloss:1.70178
[36m(train_xgb_ray_tune pid=398917)[0m [495]	train-mlogloss:1.69154	validation-mlogloss:1.74562
[36m(train_xgb_ray_tune pid=398892)[0m [544]	train-mlogloss:1.74314	validation-mlogloss:1.75921
[36m(train_xgb_ray_tune pid=398886)[0m [507]	train-mlogloss:1.58942	validation-mlogloss:1.68753
[36m(train_xgb_ray_tune pid=398903)[0m [500]	train-mlogloss:1.76873	validation-mlogloss:1.78704
[36m(train_xgb_ray_tune pid=398916)[0m [492]	train-mlogloss:2.25324	validation-mlogloss:2.25042
[36m(train_xgb_ray_tune pid=398894)[0m [469]	train-mlogloss:1.81606	validation-mlogloss:1.81930
[36m(train_xgb_ray_tune pid=398900)[0m [496]	train-mlogloss:2.04657	validation-mlogloss:2.01382
[36m(train_xgb_ray_tune pid=398905)[0m [499]	train-mlogloss:1.75278	validation-mlogloss:1.77306
[36m(train_xgb_ray_tune pid=398918)[0m [512]	train-mlogloss:2.06118	validation-mlogloss:2.02783
[36m(train_xgb_ray_tune pid=398913)[0m [694]	train-mlogloss:2.14907	validation-mlogloss:2.16173
[36m(train_xgb_ray_tune pid=398913)[0m [695]	train-mlogloss:2.14907	validation-mlogloss:2.16173
[36m(train_xgb_ray_tune pid=398917)[0m [496]	train-mlogloss:1.69097	validation-mlogloss:1.74525
[36m(train_xgb_ray_tune pid=398892)[0m [545]	train-mlogloss:1.74281	validation-mlogloss:1.75910
[36m(train_xgb_ray_tune pid=398886)[0m [508]	train-mlogloss:1.58885	validation-mlogloss:1.68727
[36m(train_xgb_ray_tune pid=398912)[0m [503]	train-mlogloss:1.72407	validation-mlogloss:1.76210
[36m(train_xgb_ray_tune pid=398880)[0m [515]	train-mlogloss:1.57084	validation-mlogloss:1.68682
[36m(train_xgb_ray_tune pid=398905)[0m [500]	train-mlogloss:1.75238	validation-mlogloss:1.77290
[36m(train_xgb_ray_tune pid=398918)[0m [513]	train-mlogloss:2.06057	validation-mlogloss:2.02725
[36m(train_xgb_ray_tune pid=398913)[0m [696]	train-mlogloss:2.14901	validation-mlogloss:2.16166
[36m(train_xgb_ray_tune pid=398901)[0m [503]	train-mlogloss:1.59838	validation-mlogloss:1.70168
[36m(train_xgb_ray_tune pid=398917)[0m [497]	train-mlogloss:1.69042	validation-mlogloss:1.74499
[36m(train_xgb_ray_tune pid=398892)[0m [546]	train-mlogloss:1.74252	validation-mlogloss:1.75894
[36m(train_xgb_ray_tune pid=398916)[0m [493]	train-mlogloss:2.25279	validation-mlogloss:2.25004
[36m(train_xgb_ray_tune pid=398894)[0m [470]	train-mlogloss:1.81543	validation-mlogloss:1.81893
[36m(train_xgb_ray_tune pid=398913)[0m [697]	train-mlogloss:2.14894	validation-mlogloss:2.16154
[36m(train_xgb_ray_tune pid=398886)[0m [509]	train-mlogloss:1.58835	validation-mlogloss:1.68714
[36m(train_xgb_ray_tune pid=398903)[0m [501]	train-mlogloss:1.76806	validation-mlogloss:1.78654
[36m(train_xgb_ray_tune pid=398912)[0m [504]	train-mlogloss:1.72348	validation-mlogloss:1.76180
[36m(train_xgb_ray_tune pid=398880)[0m [516]	train-mlogloss:1.57037	validation-mlogloss:1.68648
[36m(train_xgb_ray_tune pid=398900)[0m [497]	train-mlogloss:2.04594	validation-mlogloss:2.01332
[36m(train_xgb_ray_tune pid=398905)[0m [501]	train-mlogloss:1.75195	validation-mlogloss:1.77261
[36m(train_xgb_ray_tune pid=398918)[0m [514]	train-mlogloss:2.05998	validation-mlogloss:2.02671
[36m(train_xgb_ray_tune pid=398913)[0m [698]	train-mlogloss:2.14894	validation-mlogloss:2.16154
[36m(train_xgb_ray_tune pid=398901)[0m [504]	train-mlogloss:1.59778	validation-mlogloss:1.70152
[36m(train_xgb_ray_tune pid=398917)[0m [498]	train-mlogloss:1.68988	validation-mlogloss:1.74466
[36m(train_xgb_ray_tune pid=398892)[0m [547]	train-mlogloss:1.74225	validation-mlogloss:1.75885
[36m(train_xgb_ray_tune pid=398892)[0m [548]	train-mlogloss:1.74189	validation-mlogloss:1.75861
[36m(train_xgb_ray_tune pid=398905)[0m [502]	train-mlogloss:1.75162	validation-mlogloss:1.77244
[36m(train_xgb_ray_tune pid=398917)[0m [499]	train-mlogloss:1.68934	validation-mlogloss:1.74437
[36m(train_xgb_ray_tune pid=398903)[0m [502]	train-mlogloss:1.76743	validation-mlogloss:1.78630
[36m(train_xgb_ray_tune pid=398912)[0m [505]	train-mlogloss:1.72288	validation-mlogloss:1.76156
[36m(train_xgb_ray_tune pid=398916)[0m [494]	train-mlogloss:2.25232	validation-mlogloss:2.24962
[36m(train_xgb_ray_tune pid=398894)[0m [471]	train-mlogloss:1.81475	validation-mlogloss:1.81850
[36m(train_xgb_ray_tune pid=398880)[0m [517]	train-mlogloss:1.56986	validation-mlogloss:1.68632
[36m(train_xgb_ray_tune pid=398900)[0m [498]	train-mlogloss:2.04528	validation-mlogloss:2.01274
[36m(train_xgb_ray_tune pid=398905)[0m [503]	train-mlogloss:1.75121	validation-mlogloss:1.77222
[36m(train_xgb_ray_tune pid=398918)[0m [515]	train-mlogloss:2.05938	validation-mlogloss:2.02615
[36m(train_xgb_ray_tune pid=398913)[0m [699]	train-mlogloss:2.14887	validation-mlogloss:2.16154
[36m(train_xgb_ray_tune pid=398913)[0m [700]	train-mlogloss:2.14887	validation-mlogloss:2.16154
[36m(train_xgb_ray_tune pid=398901)[0m [505]	train-mlogloss:1.59723	validation-mlogloss:1.70136
[36m(train_xgb_ray_tune pid=398917)[0m [500]	train-mlogloss:1.68880	validation-mlogloss:1.74422
[36m(train_xgb_ray_tune pid=398892)[0m [549]	train-mlogloss:1.74161	validation-mlogloss:1.75846
[36m(train_xgb_ray_tune pid=398886)[0m [510]	train-mlogloss:1.58784	validation-mlogloss:1.68685
[36m(train_xgb_ray_tune pid=398903)[0m [503]	train-mlogloss:1.76676	validation-mlogloss:1.78580
[36m(train_xgb_ray_tune pid=398916)[0m [495]	train-mlogloss:2.25188	validation-mlogloss:2.24921
[36m(train_xgb_ray_tune pid=398880)[0m [518]	train-mlogloss:1.56939	validation-mlogloss:1.68614
[36m(train_xgb_ray_tune pid=398905)[0m [504]	train-mlogloss:1.75084	validation-mlogloss:1.77203
[36m(train_xgb_ray_tune pid=398918)[0m [516]	train-mlogloss:2.05877	validation-mlogloss:2.02563
[36m(train_xgb_ray_tune pid=398913)[0m [701]	train-mlogloss:2.14872	validation-mlogloss:2.16133
[36m(train_xgb_ray_tune pid=398901)[0m [506]	train-mlogloss:1.59668	validation-mlogloss:1.70141
[36m(train_xgb_ray_tune pid=398917)[0m [501]	train-mlogloss:1.68824	validation-mlogloss:1.74388
[36m(train_xgb_ray_tune pid=398892)[0m [550]	train-mlogloss:1.74133	validation-mlogloss:1.75838
[36m(train_xgb_ray_tune pid=398894)[0m [472]	train-mlogloss:1.81405	validation-mlogloss:1.81806
[36m(train_xgb_ray_tune pid=398913)[0m [702]	train-mlogloss:2.14872	validation-mlogloss:2.16133

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:11. Total running time: 1min 56s
[36m(train_xgb_ray_tune pid=398906)[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=398906)[0m   _log_deprecation_warning(
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             113.767 │
│ time_total_s                 113.767 │
│ training_iteration                 1 │
│ validation_accuracy          0.51201 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=398886)[0m [511]	train-mlogloss:1.58738	validation-mlogloss:1.68660
[36m(train_xgb_ray_tune pid=398912)[0m [506]	train-mlogloss:1.72226	validation-mlogloss:1.76129
[36m(train_xgb_ray_tune pid=398900)[0m [499]	train-mlogloss:2.04467	validation-mlogloss:2.01225
[36m(train_xgb_ray_tune pid=398905)[0m [505]	train-mlogloss:1.75045	validation-mlogloss:1.77179
[36m(train_xgb_ray_tune pid=398918)[0m [517]	train-mlogloss:2.05817	validation-mlogloss:2.02508
[36m(train_xgb_ray_tune pid=398913)[0m [703]	train-mlogloss:2.14866	validation-mlogloss:2.16126
[36m(train_xgb_ray_tune pid=398917)[0m [502]	train-mlogloss:1.68765	validation-mlogloss:1.74345
[36m(train_xgb_ray_tune pid=398892)[0m [551]	train-mlogloss:1.74094	validation-mlogloss:1.75804
[36m(train_xgb_ray_tune pid=398892)[0m [552]	train-mlogloss:1.74074	validation-mlogloss:1.75784

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:12. Total running time: 1min 56s
[36m(train_xgb_ray_tune pid=398886)[0m [512]	train-mlogloss:1.58692	validation-mlogloss:1.68646
[36m(train_xgb_ray_tune pid=398903)[0m [504]	train-mlogloss:1.76608	validation-mlogloss:1.78551
[36m(train_xgb_ray_tune pid=398912)[0m [507]	train-mlogloss:1.72165	validation-mlogloss:1.76095
[36m(train_xgb_ray_tune pid=398916)[0m [496]	train-mlogloss:2.25141	validation-mlogloss:2.24873
[36m(train_xgb_ray_tune pid=398894)[0m [473]	train-mlogloss:1.81332	validation-mlogloss:1.81755
[36m(train_xgb_ray_tune pid=398880)[0m [519]	train-mlogloss:1.56894	validation-mlogloss:1.68584
[36m(train_xgb_ray_tune pid=398900)[0m [500]	train-mlogloss:2.04405	validation-mlogloss:2.01166
[36m(train_xgb_ray_tune pid=398905)[0m [506]	train-mlogloss:1.75006	validation-mlogloss:1.77160
[36m(train_xgb_ray_tune pid=398918)[0m [518]	train-mlogloss:2.05757	validation-mlogloss:2.02453
[36m(train_xgb_ray_tune pid=398913)[0m [704]	train-mlogloss:2.14866	validation-mlogloss:2.16126
[36m(train_xgb_ray_tune pid=398913)[0m [705]	train-mlogloss:2.14866	validation-mlogloss:2.16126
[36m(train_xgb_ray_tune pid=398901)[0m [507]	train-mlogloss:1.59616	validation-mlogloss:1.70133
[36m(train_xgb_ray_tune pid=398917)[0m [503]	train-mlogloss:1.68708	validation-mlogloss:1.74310
[36m(train_xgb_ray_tune pid=398892)[0m [553]	train-mlogloss:1.74039	validation-mlogloss:1.75780
[36m(train_xgb_ray_tune pid=398901)[0m [508]	train-mlogloss:1.59564	validation-mlogloss:1.70116
[36m(train_xgb_ray_tune pid=398903)[0m [505]	train-mlogloss:1.76537	validation-mlogloss:1.78498
[36m(train_xgb_ray_tune pid=398916)[0m [497]	train-mlogloss:2.25100	validation-mlogloss:2.24837
[36m(train_xgb_ray_tune pid=398894)[0m [474]	train-mlogloss:1.81261	validation-mlogloss:1.81707
[36m(train_xgb_ray_tune pid=398880)[0m [520]	train-mlogloss:1.56849	validation-mlogloss:1.68570
[36m(train_xgb_ray_tune pid=398900)[0m [501]	train-mlogloss:2.04345	validation-mlogloss:2.01116
[36m(train_xgb_ray_tune pid=398905)[0m [507]	train-mlogloss:1.74971	validation-mlogloss:1.77144
[36m(train_xgb_ray_tune pid=398918)[0m [519]	train-mlogloss:2.05696	validation-mlogloss:2.02393
[36m(train_xgb_ray_tune pid=398913)[0m [706]	train-mlogloss:2.14866	validation-mlogloss:2.16126
[36m(train_xgb_ray_tune pid=398901)[0m [509]	train-mlogloss:1.59502	validation-mlogloss:1.70112
[36m(train_xgb_ray_tune pid=398917)[0m [504]	train-mlogloss:1.68648	validation-mlogloss:1.74282
[36m(train_xgb_ray_tune pid=398892)[0m [554]	train-mlogloss:1.74003	validation-mlogloss:1.75765
[36m(train_xgb_ray_tune pid=398886)[0m [513]	train-mlogloss:1.58637	validation-mlogloss:1.68628
[36m(train_xgb_ray_tune pid=398912)[0m [508]	train-mlogloss:1.72106	validation-mlogloss:1.76055
[36m(train_xgb_ray_tune pid=398880)[0m [521]	train-mlogloss:1.56795	validation-mlogloss:1.68558
[36m(train_xgb_ray_tune pid=398900)[0m [502]	train-mlogloss:2.04284	validation-mlogloss:2.01059
[36m(train_xgb_ray_tune pid=398905)[0m [508]	train-mlogloss:1.74929	validation-mlogloss:1.77128
[36m(train_xgb_ray_tune pid=398918)[0m [520]	train-mlogloss:2.05637	validation-mlogloss:2.02335
[36m(train_xgb_ray_tune pid=398913)[0m [707]	train-mlogloss:2.14857	validation-mlogloss:2.16107
[36m(train_xgb_ray_tune pid=398913)[0m [708]	train-mlogloss:2.14857	validation-mlogloss:2.16107
[36m(train_xgb_ray_tune pid=398901)[0m [510]	train-mlogloss:1.59459	validation-mlogloss:1.70097
[36m(train_xgb_ray_tune pid=398917)[0m [505]	train-mlogloss:1.68590	validation-mlogloss:1.74246
[36m(train_xgb_ray_tune pid=398892)[0m [555]	train-mlogloss:1.73972	validation-mlogloss:1.75750
[36m(train_xgb_ray_tune pid=398916)[0m [498]	train-mlogloss:2.25059	validation-mlogloss:2.24795
[36m(train_xgb_ray_tune pid=398886)[0m [514]	train-mlogloss:1.58592	validation-mlogloss:1.68608
[36m(train_xgb_ray_tune pid=398903)[0m [506]	train-mlogloss:1.76472	validation-mlogloss:1.78459
[36m(train_xgb_ray_tune pid=398912)[0m [509]	train-mlogloss:1.72050	validation-mlogloss:1.76020
[36m(train_xgb_ray_tune pid=398894)[0m [475]	train-mlogloss:1.81196	validation-mlogloss:1.81674
[36m(train_xgb_ray_tune pid=398900)[0m [503]	train-mlogloss:2.04224	validation-mlogloss:2.01008
[36m(train_xgb_ray_tune pid=398905)[0m [509]	train-mlogloss:1.74895	validation-mlogloss:1.77112
[36m(train_xgb_ray_tune pid=398905)[0m [510]	train-mlogloss:1.74856	validation-mlogloss:1.77086
[36m(train_xgb_ray_tune pid=398918)[0m [521]	train-mlogloss:2.05576	validation-mlogloss:2.02278
[36m(train_xgb_ray_tune pid=398913)[0m [709]	train-mlogloss:2.14857	validation-mlogloss:2.16107
[36m(train_xgb_ray_tune pid=398901)[0m [511]	train-mlogloss:1.59407	validation-mlogloss:1.70078
[36m(train_xgb_ray_tune pid=398917)[0m [506]	train-mlogloss:1.68537	validation-mlogloss:1.74229
[36m(train_xgb_ray_tune pid=398917)[0m [507]	train-mlogloss:1.68480	validation-mlogloss:1.74209
[36m(train_xgb_ray_tune pid=398892)[0m [556]	train-mlogloss:1.73955	validation-mlogloss:1.75740
[36m(train_xgb_ray_tune pid=398903)[0m [507]	train-mlogloss:1.76409	validation-mlogloss:1.78426
[36m(train_xgb_ray_tune pid=398912)[0m [510]	train-mlogloss:1.71988	validation-mlogloss:1.75979
[36m(train_xgb_ray_tune pid=398916)[0m [499]	train-mlogloss:2.25014	validation-mlogloss:2.24750
[36m(train_xgb_ray_tune pid=398880)[0m [522]	train-mlogloss:1.56742	validation-mlogloss:1.68532
[36m(train_xgb_ray_tune pid=398900)[0m [504]	train-mlogloss:2.04160	validation-mlogloss:2.00950
[36m(train_xgb_ray_tune pid=398900)[0m [505]	train-mlogloss:2.04098	validation-mlogloss:2.00900
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[36m(train_xgb_ray_tune pid=398905)[0m [527]	train-mlogloss:1.74263	validation-mlogloss:1.76698
[36m(train_xgb_ray_tune pid=398913)[0m [732]	train-mlogloss:2.14768	validation-mlogloss:2.15992
[36m(train_xgb_ray_tune pid=398913)[0m [733]	train-mlogloss:2.14761	validation-mlogloss:2.15989
[36m(train_xgb_ray_tune pid=398901)[0m [528]	train-mlogloss:1.58468	validation-mlogloss:1.69775
[36m(train_xgb_ray_tune pid=398903)[0m [522]	train-mlogloss:1.75459	validation-mlogloss:1.77841
[36m(train_xgb_ray_tune pid=398886)[0m [525]	train-mlogloss:1.58050	validation-mlogloss:1.68459
[36m(train_xgb_ray_tune pid=398903)[0m [523]	train-mlogloss:1.75402	validation-mlogloss:1.77801
[36m(train_xgb_ray_tune pid=398912)[0m [520]	train-mlogloss:1.71423	validation-mlogloss:1.75647
[36m(train_xgb_ray_tune pid=398916)[0m [509]	train-mlogloss:2.24575	validation-mlogloss:2.24336
[36m(train_xgb_ray_tune pid=398880)[0m [539]	train-mlogloss:1.55942	validation-mlogloss:1.68377
[36m(train_xgb_ray_tune pid=398918)[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=398918)[0m   _log_deprecation_warning(
[36m(train_xgb_ray_tune pid=398900)[0m [521]	train-mlogloss:2.03107	validation-mlogloss:2.00025
[36m(train_xgb_ray_tune pid=398905)[0m [528]	train-mlogloss:1.74224	validation-mlogloss:1.76673
[36m(train_xgb_ray_tune pid=398913)[0m [734]	train-mlogloss:2.14761	validation-mlogloss:2.15989
[36m(train_xgb_ray_tune pid=398901)[0m [529]	train-mlogloss:1.58413	validation-mlogloss:1.69783
[36m(train_xgb_ray_tune pid=398901)[0m [530]	train-mlogloss:1.58363	validation-mlogloss:1.69777
[36m(train_xgb_ray_tune pid=398917)[0m [518]	train-mlogloss:1.67853	validation-mlogloss:1.73903
[36m(train_xgb_ray_tune pid=398892)[0m [570]	train-mlogloss:1.73549	validation-mlogloss:1.75497

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:14. Total running time: 1min 58s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             115.912 │
│ time_total_s                 115.912 │
│ training_iteration                 1 │
│ validation_accuracy          0.48839 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:14. Total running time: 1min 58s
[36m(train_xgb_ray_tune pid=398886)[0m [526]	train-mlogloss:1.57998	validation-mlogloss:1.68444
[36m(train_xgb_ray_tune pid=398903)[0m [524]	train-mlogloss:1.75342	validation-mlogloss:1.77765
[36m(train_xgb_ray_tune pid=398916)[0m [510]	train-mlogloss:2.24535	validation-mlogloss:2.24297
[36m(train_xgb_ray_tune pid=398894)[0m [486]	train-mlogloss:1.80474	validation-mlogloss:1.81208
[36m(train_xgb_ray_tune pid=398900)[0m [522]	train-mlogloss:2.03047	validation-mlogloss:1.99972
[36m(train_xgb_ray_tune pid=398905)[0m [529]	train-mlogloss:1.74189	validation-mlogloss:1.76645
[36m(train_xgb_ray_tune pid=398905)[0m [530]	train-mlogloss:1.74149	validation-mlogloss:1.76624
[36m(train_xgb_ray_tune pid=398913)[0m [735]	train-mlogloss:2.14761	validation-mlogloss:2.15989
[36m(train_xgb_ray_tune pid=398913)[0m [736]	train-mlogloss:2.14752	validation-mlogloss:2.15980
[36m(train_xgb_ray_tune pid=398901)[0m [531]	train-mlogloss:1.58308	validation-mlogloss:1.69757
[36m(train_xgb_ray_tune pid=398917)[0m [519]	train-mlogloss:1.67795	validation-mlogloss:1.73870
[36m(train_xgb_ray_tune pid=398892)[0m [571]	train-mlogloss:1.73527	validation-mlogloss:1.75480
[36m(train_xgb_ray_tune pid=398903)[0m [525]	train-mlogloss:1.75279	validation-mlogloss:1.77720
[36m(train_xgb_ray_tune pid=398912)[0m [521]	train-mlogloss:1.71359	validation-mlogloss:1.75621
[36m(train_xgb_ray_tune pid=398916)[0m [511]	train-mlogloss:2.24489	validation-mlogloss:2.24249
[36m(train_xgb_ray_tune pid=398894)[0m [487]	train-mlogloss:1.80405	validation-mlogloss:1.81164
[36m(train_xgb_ray_tune pid=398900)[0m [523]	train-mlogloss:2.02992	validation-mlogloss:1.99922
[36m(train_xgb_ray_tune pid=398905)[0m [531]	train-mlogloss:1.74106	validation-mlogloss:1.76606
[36m(train_xgb_ray_tune pid=398913)[0m [737]	train-mlogloss:2.14752	validation-mlogloss:2.15980
[36m(train_xgb_ray_tune pid=398901)[0m [532]	train-mlogloss:1.58252	validation-mlogloss:1.69734
[36m(train_xgb_ray_tune pid=398892)[0m [572]	train-mlogloss:1.73496	validation-mlogloss:1.75453
[36m(train_xgb_ray_tune pid=398886)[0m [527]	train-mlogloss:1.57950	validation-mlogloss:1.68439
[36m(train_xgb_ray_tune pid=398903)[0m [526]	train-mlogloss:1.75217	validation-mlogloss:1.77675
[36m(train_xgb_ray_tune pid=398912)[0m [522]	train-mlogloss:1.71309	validation-mlogloss:1.75594
[36m(train_xgb_ray_tune pid=398916)[0m [512]	train-mlogloss:2.24440	validation-mlogloss:2.24198
[36m(train_xgb_ray_tune pid=398894)[0m [488]	train-mlogloss:1.80339	validation-mlogloss:1.81113
[36m(train_xgb_ray_tune pid=398900)[0m [524]	train-mlogloss:2.02932	validation-mlogloss:1.99867
[36m(train_xgb_ray_tune pid=398905)[0m [532]	train-mlogloss:1.74074	validation-mlogloss:1.76580
[36m(train_xgb_ray_tune pid=398913)[0m [738]	train-mlogloss:2.14752	validation-mlogloss:2.15980
[36m(train_xgb_ray_tune pid=398913)[0m [739]	train-mlogloss:2.14752	validation-mlogloss:2.15980
[36m(train_xgb_ray_tune pid=398901)[0m [533]	train-mlogloss:1.58198	validation-mlogloss:1.69711
[36m(train_xgb_ray_tune pid=398917)[0m [520]	train-mlogloss:1.67739	validation-mlogloss:1.73855
[36m(train_xgb_ray_tune pid=398892)[0m [573]	train-mlogloss:1.73468	validation-mlogloss:1.75426
[36m(train_xgb_ray_tune pid=398916)[0m [513]	train-mlogloss:2.24396	validation-mlogloss:2.24154
[36m(train_xgb_ray_tune pid=398886)[0m [528]	train-mlogloss:1.57898	validation-mlogloss:1.68409
[36m(train_xgb_ray_tune pid=398900)[0m [525]	train-mlogloss:2.02874	validation-mlogloss:1.99818
[36m(train_xgb_ray_tune pid=398886)[0m [529]	train-mlogloss:1.57852	validation-mlogloss:1.68395
[36m(train_xgb_ray_tune pid=398903)[0m [527]	train-mlogloss:1.75160	validation-mlogloss:1.77637
[36m(train_xgb_ray_tune pid=398912)[0m [523]	train-mlogloss:1.71248	validation-mlogloss:1.75547
[36m(train_xgb_ray_tune pid=398916)[0m [514]	train-mlogloss:2.24351	validation-mlogloss:2.24111
[36m(train_xgb_ray_tune pid=398894)[0m [489]	train-mlogloss:1.80279	validation-mlogloss:1.81065
[36m(train_xgb_ray_tune pid=398900)[0m [526]	train-mlogloss:2.02814	validation-mlogloss:1.99762
[36m(train_xgb_ray_tune pid=398905)[0m [533]	train-mlogloss:1.74039	validation-mlogloss:1.76557
[36m(train_xgb_ray_tune pid=398905)[0m [534]	train-mlogloss:1.74012	validation-mlogloss:1.76537
[36m(train_xgb_ray_tune pid=398913)[0m [740]	train-mlogloss:2.14752	validation-mlogloss:2.15980
[36m(train_xgb_ray_tune pid=398913)[0m [741]	train-mlogloss:2.14739	validation-mlogloss:2.15967
[36m(train_xgb_ray_tune pid=398901)[0m [534]	train-mlogloss:1.58140	validation-mlogloss:1.69693
[36m(train_xgb_ray_tune pid=398917)[0m [521]	train-mlogloss:1.67686	validation-mlogloss:1.73828
[36m(train_xgb_ray_tune pid=398892)[0m [574]	train-mlogloss:1.73445	validation-mlogloss:1.75420
[36m(train_xgb_ray_tune pid=398903)[0m [528]	train-mlogloss:1.75096	validation-mlogloss:1.77594
[36m(train_xgb_ray_tune pid=398912)[0m [524]	train-mlogloss:1.71188	validation-mlogloss:1.75518
[36m(train_xgb_ray_tune pid=398886)[0m [530]	train-mlogloss:1.57803	validation-mlogloss:1.68387
[36m(train_xgb_ray_tune pid=398903)[0m [529]	train-mlogloss:1.75036	validation-mlogloss:1.77561
[36m(train_xgb_ray_tune pid=398912)[0m [525]	train-mlogloss:1.71127	validation-mlogloss:1.75476
[36m(train_xgb_ray_tune pid=398916)[0m [515]	train-mlogloss:2.24310	validation-mlogloss:2.24073
[36m(train_xgb_ray_tune pid=398894)[0m [490]	train-mlogloss:1.80217	validation-mlogloss:1.81034
[36m(train_xgb_ray_tune pid=398900)[0m [527]	train-mlogloss:2.02756	validation-mlogloss:1.99715
[36m(train_xgb_ray_tune pid=398905)[0m [535]	train-mlogloss:1.73980	validation-mlogloss:1.76509
[36m(train_xgb_ray_tune pid=398913)[0m [742]	train-mlogloss:2.14725	validation-mlogloss:2.15958
[36m(train_xgb_ray_tune pid=398913)[0m [743]	train-mlogloss:2.14725	validation-mlogloss:2.15958
[36m(train_xgb_ray_tune pid=398901)[0m [535]	train-mlogloss:1.58086	validation-mlogloss:1.69669
[36m(train_xgb_ray_tune pid=398917)[0m [522]	train-mlogloss:1.67634	validation-mlogloss:1.73795
[36m(train_xgb_ray_tune pid=398892)[0m [575]	train-mlogloss:1.73428	validation-mlogloss:1.75413
[36m(train_xgb_ray_tune pid=398886)[0m [531]	train-mlogloss:1.57758	validation-mlogloss:1.68389
[36m(train_xgb_ray_tune pid=398903)[0m [530]	train-mlogloss:1.74980	validation-mlogloss:1.77528
[36m(train_xgb_ray_tune pid=398912)[0m [526]	train-mlogloss:1.71065	validation-mlogloss:1.75458
[36m(train_xgb_ray_tune pid=398916)[0m [516]	train-mlogloss:2.24268	validation-mlogloss:2.24035
[36m(train_xgb_ray_tune pid=398900)[0m [528]	train-mlogloss:2.02697	validation-mlogloss:1.99658
[36m(train_xgb_ray_tune pid=398905)[0m [536]	train-mlogloss:1.73952	validation-mlogloss:1.76485
[36m(train_xgb_ray_tune pid=398913)[0m [744]	train-mlogloss:2.14715	validation-mlogloss:2.15950
[36m(train_xgb_ray_tune pid=398913)[0m [745]	train-mlogloss:2.14715	validation-mlogloss:2.15950
[36m(train_xgb_ray_tune pid=398892)[0m [576]	train-mlogloss:1.73405	validation-mlogloss:1.75393
[36m(train_xgb_ray_tune pid=398886)[0m [532]	train-mlogloss:1.57713	validation-mlogloss:1.68360
[36m(train_xgb_ray_tune pid=398901)[0m [536]	train-mlogloss:1.58034	validation-mlogloss:1.69670
[36m(train_xgb_ray_tune pid=398886)[0m [533]	train-mlogloss:1.57668	validation-mlogloss:1.68348
[36m(train_xgb_ray_tune pid=398903)[0m [531]	train-mlogloss:1.74920	validation-mlogloss:1.77494
[36m(train_xgb_ray_tune pid=398912)[0m [527]	train-mlogloss:1.71011	validation-mlogloss:1.75423
[36m(train_xgb_ray_tune pid=398916)[0m [517]	train-mlogloss:2.24228	validation-mlogloss:2.24002
[36m(train_xgb_ray_tune pid=398916)[0m [518]	train-mlogloss:2.24185	validation-mlogloss:2.23959
[36m(train_xgb_ray_tune pid=398894)[0m [491]	train-mlogloss:1.80152	validation-mlogloss:1.80998
[36m(train_xgb_ray_tune pid=398900)[0m [529]	train-mlogloss:2.02638	validation-mlogloss:1.99604
[36m(train_xgb_ray_tune pid=398905)[0m [537]	train-mlogloss:1.73913	validation-mlogloss:1.76461
[36m(train_xgb_ray_tune pid=398905)[0m [538]	train-mlogloss:1.73885	validation-mlogloss:1.76445
[36m(train_xgb_ray_tune pid=398913)[0m [746]	train-mlogloss:2.14715	validation-mlogloss:2.15950
[36m(train_xgb_ray_tune pid=398917)[0m [523]	train-mlogloss:1.67581	validation-mlogloss:1.73778
[36m(train_xgb_ray_tune pid=398892)[0m [577]	train-mlogloss:1.73368	validation-mlogloss:1.75352
[36m(train_xgb_ray_tune pid=398913)[0m [747]	train-mlogloss:2.14708	validation-mlogloss:2.15943
[36m(train_xgb_ray_tune pid=398912)[0m [528]	train-mlogloss:1.70954	validation-mlogloss:1.75381
[36m(train_xgb_ray_tune pid=398900)[0m [530]	train-mlogloss:2.02582	validation-mlogloss:1.99550
[36m(train_xgb_ray_tune pid=398903)[0m [532]	train-mlogloss:1.74859	validation-mlogloss:1.77442
[36m(train_xgb_ray_tune pid=398886)[0m [534]	train-mlogloss:1.57623	validation-mlogloss:1.68341
[36m(train_xgb_ray_tune pid=398903)[0m [533]	train-mlogloss:1.74800	validation-mlogloss:1.77419
[36m(train_xgb_ray_tune pid=398912)[0m [529]	train-mlogloss:1.70900	validation-mlogloss:1.75361
[36m(train_xgb_ray_tune pid=398916)[0m [519]	train-mlogloss:2.24144	validation-mlogloss:2.23923
[36m(train_xgb_ray_tune pid=398894)[0m [492]	train-mlogloss:1.80092	validation-mlogloss:1.80957
[36m(train_xgb_ray_tune pid=398900)[0m [531]	train-mlogloss:2.02522	validation-mlogloss:1.99494
[36m(train_xgb_ray_tune pid=398905)[0m [539]	train-mlogloss:1.73854	validation-mlogloss:1.76432
[36m(train_xgb_ray_tune pid=398913)[0m [748]	train-mlogloss:2.14708	validation-mlogloss:2.15943
[36m(train_xgb_ray_tune pid=398901)[0m [537]	train-mlogloss:1.57982	validation-mlogloss:1.69685
[36m(train_xgb_ray_tune pid=398917)[0m [524]	train-mlogloss:1.67525	validation-mlogloss:1.73748
[36m(train_xgb_ray_tune pid=398892)[0m [578]	train-mlogloss:1.73349	validation-mlogloss:1.75346
[36m(train_xgb_ray_tune pid=398913)[0m [749]	train-mlogloss:2.14708	validation-mlogloss:2.15943
[36m(train_xgb_ray_tune pid=398886)[0m [535]	train-mlogloss:1.57573	validation-mlogloss:1.68304
[36m(train_xgb_ray_tune pid=398886)[0m [536]	train-mlogloss:1.57525	validation-mlogloss:1.68295
[36m(train_xgb_ray_tune pid=398903)[0m [534]	train-mlogloss:1.74738	validation-mlogloss:1.77373
[36m(train_xgb_ray_tune pid=398912)[0m [530]	train-mlogloss:1.70848	validation-mlogloss:1.75342
[36m(train_xgb_ray_tune pid=398916)[0m [520]	train-mlogloss:2.24104	validation-mlogloss:2.23886
[36m(train_xgb_ray_tune pid=398894)[0m [493]	train-mlogloss:1.80029	validation-mlogloss:1.80908
[36m(train_xgb_ray_tune pid=398900)[0m [532]	train-mlogloss:2.02464	validation-mlogloss:1.99442
[36m(train_xgb_ray_tune pid=398905)[0m [540]	train-mlogloss:1.73823	validation-mlogloss:1.76419
[36m(train_xgb_ray_tune pid=398905)[0m [541]	train-mlogloss:1.73789	validation-mlogloss:1.76394
[36m(train_xgb_ray_tune pid=398913)[0m [750]	train-mlogloss:2.14708	validation-mlogloss:2.15943
[36m(train_xgb_ray_tune pid=398901)[0m [538]	train-mlogloss:1.57925	validation-mlogloss:1.69658
[36m(train_xgb_ray_tune pid=398917)[0m [525]	train-mlogloss:1.67468	validation-mlogloss:1.73707
[36m(train_xgb_ray_tune pid=398892)[0m [579]	train-mlogloss:1.73312	validation-mlogloss:1.75326

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:15. Total running time: 2min 0s
╭─────────────────────────────────────╮
│ Trial trial_b8b81 result            │
├─────────────────────────────────────┤
│ checkpoint_dir_name                 │
│ time_this_iter_s             117.34 │
│ time_total_s                 117.34 │
│ training_iteration                1 │
│ validation_accuracy          0.5271 │
╰─────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:15. Total running time: 2min 0s
[36m(train_xgb_ray_tune pid=398886)[0m [537]	train-mlogloss:1.57481	validation-mlogloss:1.68300
[36m(train_xgb_ray_tune pid=398903)[0m [535]	train-mlogloss:1.74678	validation-mlogloss:1.77338
[36m(train_xgb_ray_tune pid=398912)[0m [531]	train-mlogloss:1.70791	validation-mlogloss:1.75326
[36m(train_xgb_ray_tune pid=398916)[0m [521]	train-mlogloss:2.24067	validation-mlogloss:2.23853
[36m(train_xgb_ray_tune pid=398916)[0m [522]	train-mlogloss:2.24025	validation-mlogloss:2.23816
[36m(train_xgb_ray_tune pid=398900)[0m [533]	train-mlogloss:2.02406	validation-mlogloss:1.99395
[36m(train_xgb_ray_tune pid=398905)[0m [542]	train-mlogloss:1.73753	validation-mlogloss:1.76374
[36m(train_xgb_ray_tune pid=398913)[0m [751]	train-mlogloss:2.14708	validation-mlogloss:2.15943
[36m(train_xgb_ray_tune pid=398913)[0m [752]	train-mlogloss:2.14708	validation-mlogloss:2.15943
[36m(train_xgb_ray_tune pid=398901)[0m [539]	train-mlogloss:1.57870	validation-mlogloss:1.69638
[36m(train_xgb_ray_tune pid=398912)[0m [532]	train-mlogloss:1.70735	validation-mlogloss:1.75296
[36m(train_xgb_ray_tune pid=398892)[0m [580]	train-mlogloss:1.73283	validation-mlogloss:1.75308
[36m(train_xgb_ray_tune pid=398886)[0m [538]	train-mlogloss:1.57439	validation-mlogloss:1.68293
[36m(train_xgb_ray_tune pid=398903)[0m [536]	train-mlogloss:1.74619	validation-mlogloss:1.77294
[36m(train_xgb_ray_tune pid=398903)[0m [537]	train-mlogloss:1.74564	validation-mlogloss:1.77254
[36m(train_xgb_ray_tune pid=398912)[0m [533]	train-mlogloss:1.70677	validation-mlogloss:1.75263
[36m(train_xgb_ray_tune pid=398916)[0m [523]	train-mlogloss:2.23982	validation-mlogloss:2.23774
[36m(train_xgb_ray_tune pid=398894)[0m [494]	train-mlogloss:1.79965	validation-mlogloss:1.80860
[36m(train_xgb_ray_tune pid=398894)[0m [495]	train-mlogloss:1.79907	validation-mlogloss:1.80810
[36m(train_xgb_ray_tune pid=398900)[0m [534]	train-mlogloss:2.02348	validation-mlogloss:1.99341
[36m(train_xgb_ray_tune pid=398905)[0m [543]	train-mlogloss:1.73719	validation-mlogloss:1.76361
[36m(train_xgb_ray_tune pid=398913)[0m [753]	train-mlogloss:2.14702	validation-mlogloss:2.15930
[36m(train_xgb_ray_tune pid=398901)[0m [540]	train-mlogloss:1.57816	validation-mlogloss:1.69629
[36m(train_xgb_ray_tune pid=398917)[0m [526]	train-mlogloss:1.67412	validation-mlogloss:1.73684
[36m(train_xgb_ray_tune pid=398900)[0m [535]	train-mlogloss:2.02287	validation-mlogloss:1.99286
[36m(train_xgb_ray_tune pid=398913)[0m [754]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398892)[0m [581]	train-mlogloss:1.73261	validation-mlogloss:1.75299
[36m(train_xgb_ray_tune pid=398901)[0m [541]	train-mlogloss:1.57767	validation-mlogloss:1.69615
[36m(train_xgb_ray_tune pid=398886)[0m [539]	train-mlogloss:1.57393	validation-mlogloss:1.68304
[36m(train_xgb_ray_tune pid=398886)[0m [540]	train-mlogloss:1.57341	validation-mlogloss:1.68286
[36m(train_xgb_ray_tune pid=398903)[0m [538]	train-mlogloss:1.74505	validation-mlogloss:1.77224
[36m(train_xgb_ray_tune pid=398912)[0m [534]	train-mlogloss:1.70613	validation-mlogloss:1.75236
[36m(train_xgb_ray_tune pid=398916)[0m [524]	train-mlogloss:2.23941	validation-mlogloss:2.23737
[36m(train_xgb_ray_tune pid=398894)[0m [496]	train-mlogloss:1.79841	validation-mlogloss:1.80764
[36m(train_xgb_ray_tune pid=398900)[0m [536]	train-mlogloss:2.02227	validation-mlogloss:1.99228
[36m(train_xgb_ray_tune pid=398905)[0m [544]	train-mlogloss:1.73691	validation-mlogloss:1.76337
[36m(train_xgb_ray_tune pid=398905)[0m [545]	train-mlogloss:1.73663	validation-mlogloss:1.76334
[36m(train_xgb_ray_tune pid=398913)[0m [755]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398901)[0m [542]	train-mlogloss:1.57714	validation-mlogloss:1.69604
[36m(train_xgb_ray_tune pid=398917)[0m [527]	train-mlogloss:1.67358	validation-mlogloss:1.73668
[36m(train_xgb_ray_tune pid=398892)[0m [582]	train-mlogloss:1.73237	validation-mlogloss:1.75277
[36m(train_xgb_ray_tune pid=398913)[0m [756]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398886)[0m [541]	train-mlogloss:1.57298	validation-mlogloss:1.68263
[36m(train_xgb_ray_tune pid=398903)[0m [539]	train-mlogloss:1.74447	validation-mlogloss:1.77204
[36m(train_xgb_ray_tune pid=398912)[0m [535]	train-mlogloss:1.70557	validation-mlogloss:1.75218
[36m(train_xgb_ray_tune pid=398916)[0m [525]	train-mlogloss:2.23895	validation-mlogloss:2.23694
[36m(train_xgb_ray_tune pid=398916)[0m [526]	train-mlogloss:2.23850	validation-mlogloss:2.23652
[36m(train_xgb_ray_tune pid=398894)[0m [497]	train-mlogloss:1.79780	validation-mlogloss:1.80729
[36m(train_xgb_ray_tune pid=398900)[0m [537]	train-mlogloss:2.02168	validation-mlogloss:1.99175
[36m(train_xgb_ray_tune pid=398905)[0m [546]	train-mlogloss:1.73644	validation-mlogloss:1.76317
[36m(train_xgb_ray_tune pid=398913)[0m [757]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398901)[0m [543]	train-mlogloss:1.57665	validation-mlogloss:1.69581
[36m(train_xgb_ray_tune pid=398917)[0m [528]	train-mlogloss:1.67302	validation-mlogloss:1.73648

Trial status: 11 RUNNING | 9 TERMINATED
Current time: 2025-10-27 09:36:15. Total running time: 2min 0s
Logical resource usage: 11.0/20 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_b8b81    RUNNING                    785             2        0.0152561       0.333235             0.509718   5.36058                   59      1.72191        0.791369             8764                                                     │
│ trial_b8b81    RUNNING                    677             2        0.00718957      0.347983             0.517791   6.43243                   12      0.249615       2.3729               3650                                                     │
│ trial_b8b81    RUNNING                    749             2        0.00684262      0.511093             0.642296   2.23501                   26      2.59404        5.58484              8397                                                     │
│ trial_b8b81    RUNNING                    789             2        0.00862436      0.519278             0.453361   7.20008                   21      1.57911        3.85557               985                                                     │
│ trial_b8b81    RUNNING                    737             2        0.0033156       0.459322             0.608053   3.18821                   28     93.719          1.30518              5776                                                     │
│ trial_b8b81    RUNNING                    650             2        0.00313347      0.693701             0.492938   9.79394                   12      1.55806        6.0203               5382                                                     │
│ trial_b8b81    RUNNING                    860             2        0.0136591       0.502887             0.62787    4.03237                   37     28.4997        51.4794               8253                                                     │
│ trial_b8b81    RUNNING                    783             2        0.0197427       0.306766             0.67443    7.59557                   58     66.8206        16.8769               7467                                                     │
│ trial_b8b81    RUNNING                    725             2        0.0143453       0.659911             0.418968   3.84157                   53      0.163473      19.04                 9244                                                     │
│ trial_b8b81    RUNNING                    601             2        0.0132953       0.653242             0.585449   3.87352                   49      4.74374       97.5749               9239                                                     │
│ trial_b8b81    RUNNING                    871             2        0.0139431       0.314738             0.444055   8.48731                   42      0.988245      70.352                9194                                                     │
│ trial_b8b81    TERMINATED                 436             2        0.0151967       0.687426             0.508211   3.6508                    32      0.236551       2.80111                23        1           105.27                  0.517769 │
│ trial_b8b81    TERMINATED                 540             2        0.0154571       0.498324             0.399232   7.5555                    57      0.518023       1.37493              3189        1           117.34                  0.527099 │
│ trial_b8b81    TERMINATED                 353             2        0.00577946      0.588048             0.300442   8.55953                   34      5.80421        0.579503             5130        1            85.8844                0.508636 │
│ trial_b8b81    TERMINATED                 347             2        0.00373864      0.624615             0.491362   7.40223                   33      0.177621      15.6491               4377        1            88.6951                0.490371 │
│ trial_b8b81    TERMINATED                 550             2        0.0146521       0.333218             0.403476   8.58164                   12      8.33367       54.5003               6890        1           113.767                 0.512011 │
│ trial_b8b81    TERMINATED                 416             2        0.00418167      0.347849             0.419215   6.11886                   39      1.02586        0.871116             4157        1            93.3898                0.500099 │
│ trial_b8b81    TERMINATED                 500             2        0.0168463       0.316536             0.311578   7.53857                   21     25.6984         1.41457              2854        1           103.427                 0.500099 │
│ trial_b8b81    TERMINATED                 528             2        0.00285688      0.536565             0.651463   5.278                     25      2.19742        2.87126               507        1           115.912                 0.488386 │
│ trial_b8b81    TERMINATED                 319             2        0.0172683       0.44677              0.688075   6.64719                   21      1.24884       27.0934               5802        1            86.7446                0.512607 │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=398886)[0m [542]	train-mlogloss:1.57249	validation-mlogloss:1.68241
[36m(train_xgb_ray_tune pid=398903)[0m [540]	train-mlogloss:1.74390	validation-mlogloss:1.77175
[36m(train_xgb_ray_tune pid=398903)[0m [541]	train-mlogloss:1.74332	validation-mlogloss:1.77154
[36m(train_xgb_ray_tune pid=398912)[0m [536]	train-mlogloss:1.70499	validation-mlogloss:1.75182
[36m(train_xgb_ray_tune pid=398912)[0m [537]	train-mlogloss:1.70443	validation-mlogloss:1.75150
[36m(train_xgb_ray_tune pid=398916)[0m [527]	train-mlogloss:2.23807	validation-mlogloss:2.23608
[36m(train_xgb_ray_tune pid=398894)[0m [498]	train-mlogloss:1.79714	validation-mlogloss:1.80682
[36m(train_xgb_ray_tune pid=398900)[0m [538]	train-mlogloss:2.02111	validation-mlogloss:1.99118
[36m(train_xgb_ray_tune pid=398905)[0m [547]	train-mlogloss:1.73616	validation-mlogloss:1.76294
[36m(train_xgb_ray_tune pid=398913)[0m [758]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398913)[0m [759]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398901)[0m [544]	train-mlogloss:1.57618	validation-mlogloss:1.69557
[36m(train_xgb_ray_tune pid=398892)[0m [583]	train-mlogloss:1.73207	validation-mlogloss:1.75248
[36m(train_xgb_ray_tune pid=398886)[0m [543]	train-mlogloss:1.57208	validation-mlogloss:1.68221
[36m(train_xgb_ray_tune pid=398886)[0m [544]	train-mlogloss:1.57167	validation-mlogloss:1.68212
[36m(train_xgb_ray_tune pid=398903)[0m [542]	train-mlogloss:1.74276	validation-mlogloss:1.77124
[36m(train_xgb_ray_tune pid=398912)[0m [538]	train-mlogloss:1.70384	validation-mlogloss:1.75118
[36m(train_xgb_ray_tune pid=398916)[0m [528]	train-mlogloss:2.23766	validation-mlogloss:2.23569
[36m(train_xgb_ray_tune pid=398894)[0m [499]	train-mlogloss:1.79652	validation-mlogloss:1.80646
[36m(train_xgb_ray_tune pid=398900)[0m [539]	train-mlogloss:2.02053	validation-mlogloss:1.99066
[36m(train_xgb_ray_tune pid=398905)[0m [548]	train-mlogloss:1.73590	validation-mlogloss:1.76287
[36m(train_xgb_ray_tune pid=398905)[0m [549]	train-mlogloss:1.73556	validation-mlogloss:1.76259
[36m(train_xgb_ray_tune pid=398913)[0m [760]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398913)[0m [761]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398901)[0m [545]	train-mlogloss:1.57563	validation-mlogloss:1.69540
[36m(train_xgb_ray_tune pid=398917)[0m [529]	train-mlogloss:1.67246	validation-mlogloss:1.73603
[36m(train_xgb_ray_tune pid=398892)[0m [584]	train-mlogloss:1.73184	validation-mlogloss:1.75243
[36m(train_xgb_ray_tune pid=398894)[0m [500]	train-mlogloss:1.79580	validation-mlogloss:1.80596
[36m(train_xgb_ray_tune pid=398901)[0m [546]	train-mlogloss:1.57513	validation-mlogloss:1.69525
[36m(train_xgb_ray_tune pid=398886)[0m [545]	train-mlogloss:1.57127	validation-mlogloss:1.68202
[36m(train_xgb_ray_tune pid=398903)[0m [543]	train-mlogloss:1.74223	validation-mlogloss:1.77091
[36m(train_xgb_ray_tune pid=398912)[0m [539]	train-mlogloss:1.70335	validation-mlogloss:1.75092
[36m(train_xgb_ray_tune pid=398916)[0m [529]	train-mlogloss:2.23722	validation-mlogloss:2.23523
[36m(train_xgb_ray_tune pid=398894)[0m [501]	train-mlogloss:1.79516	validation-mlogloss:1.80571
[36m(train_xgb_ray_tune pid=398900)[0m [540]	train-mlogloss:2.01997	validation-mlogloss:1.99015
[36m(train_xgb_ray_tune pid=398900)[0m [541]	train-mlogloss:2.01939	validation-mlogloss:1.98957
[36m(train_xgb_ray_tune pid=398905)[0m [550]	train-mlogloss:1.73518	validation-mlogloss:1.76236
[36m(train_xgb_ray_tune pid=398913)[0m [762]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398901)[0m [547]	train-mlogloss:1.57458	validation-mlogloss:1.69505
[36m(train_xgb_ray_tune pid=398917)[0m [530]	train-mlogloss:1.67190	validation-mlogloss:1.73568
[36m(train_xgb_ray_tune pid=398892)[0m [585]	train-mlogloss:1.73159	validation-mlogloss:1.75243
[36m(train_xgb_ray_tune pid=398913)[0m [763]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398886)[0m [546]	train-mlogloss:1.57083	validation-mlogloss:1.68195
[36m(train_xgb_ray_tune pid=398903)[0m [544]	train-mlogloss:1.74166	validation-mlogloss:1.77056
[36m(train_xgb_ray_tune pid=398912)[0m [540]	train-mlogloss:1.70281	validation-mlogloss:1.75063
[36m(train_xgb_ray_tune pid=398916)[0m [530]	train-mlogloss:2.23681	validation-mlogloss:2.23483
[36m(train_xgb_ray_tune pid=398894)[0m [502]	train-mlogloss:1.79451	validation-mlogloss:1.80524
[36m(train_xgb_ray_tune pid=398900)[0m [542]	train-mlogloss:2.01883	validation-mlogloss:1.98906
[36m(train_xgb_ray_tune pid=398905)[0m [551]	train-mlogloss:1.73492	validation-mlogloss:1.76222
[36m(train_xgb_ray_tune pid=398913)[0m [764]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398901)[0m [548]	train-mlogloss:1.57408	validation-mlogloss:1.69493
[36m(train_xgb_ray_tune pid=398892)[0m [586]	train-mlogloss:1.73146	validation-mlogloss:1.75240
[36m(train_xgb_ray_tune pid=398903)[0m [545]	train-mlogloss:1.74113	validation-mlogloss:1.77031
[36m(train_xgb_ray_tune pid=398912)[0m [541]	train-mlogloss:1.70221	validation-mlogloss:1.75030
[36m(train_xgb_ray_tune pid=398913)[0m [765]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398886)[0m [547]	train-mlogloss:1.57043	validation-mlogloss:1.68181
[36m(train_xgb_ray_tune pid=398886)[0m [548]	train-mlogloss:1.56995	validation-mlogloss:1.68179
[36m(train_xgb_ray_tune pid=398903)[0m [546]	train-mlogloss:1.74059	validation-mlogloss:1.76998
[36m(train_xgb_ray_tune pid=398912)[0m [542]	train-mlogloss:1.70157	validation-mlogloss:1.75006
[36m(train_xgb_ray_tune pid=398916)[0m [531]	train-mlogloss:2.23642	validation-mlogloss:2.23448
[36m(train_xgb_ray_tune pid=398916)[0m [532]	train-mlogloss:2.23597	validation-mlogloss:2.23406
[36m(train_xgb_ray_tune pid=398894)[0m [503]	train-mlogloss:1.79383	validation-mlogloss:1.80466
[36m(train_xgb_ray_tune pid=398900)[0m [543]	train-mlogloss:2.01827	validation-mlogloss:1.98857
[36m(train_xgb_ray_tune pid=398905)[0m [552]	train-mlogloss:1.73464	validation-mlogloss:1.76201
[36m(train_xgb_ray_tune pid=398905)[0m [553]	train-mlogloss:1.73433	validation-mlogloss:1.76183
[36m(train_xgb_ray_tune pid=398913)[0m [766]	train-mlogloss:2.14682	validation-mlogloss:2.15911
[36m(train_xgb_ray_tune pid=398901)[0m [549]	train-mlogloss:1.57362	validation-mlogloss:1.69484
[36m(train_xgb_ray_tune pid=398901)[0m [550]	train-mlogloss:1.57313	validation-mlogloss:1.69486
[36m(train_xgb_ray_tune pid=398917)[0m [531]	train-mlogloss:1.67138	validation-mlogloss:1.73546
[36m(train_xgb_ray_tune pid=398892)[0m [587]	train-mlogloss:1.73116	validation-mlogloss:1.75219
[36m(train_xgb_ray_tune pid=398886)[0m [549]	train-mlogloss:1.56953	validation-mlogloss:1.68180
[36m(train_xgb_ray_tune pid=398903)[0m [547]	train-mlogloss:1.73998	validation-mlogloss:1.76962
[36m(train_xgb_ray_tune pid=398912)[0m [543]	train-mlogloss:1.70104	validation-mlogloss:1.74978
[36m(train_xgb_ray_tune pid=398916)[0m [533]	train-mlogloss:2.23557	validation-mlogloss:2.23368
[36m(train_xgb_ray_tune pid=398894)[0m [504]	train-mlogloss:1.79318	validation-mlogloss:1.80432
[36m(train_xgb_ray_tune pid=398900)[0m [544]	train-mlogloss:2.01769	validation-mlogloss:1.98806
[36m(train_xgb_ray_tune pid=398905)[0m [554]	train-mlogloss:1.73397	validation-mlogloss:1.76160
[36m(train_xgb_ray_tune pid=398913)[0m [767]	train-mlogloss:2.14674	validation-mlogloss:2.15899
[36m(train_xgb_ray_tune pid=398913)[0m [768]	train-mlogloss:2.14650	validation-mlogloss:2.15870
[36m(train_xgb_ray_tune pid=398901)[0m [551]	train-mlogloss:1.57267	validation-mlogloss:1.69475
[36m(train_xgb_ray_tune pid=398917)[0m [532]	train-mlogloss:1.67086	validation-mlogloss:1.73511
[36m(train_xgb_ray_tune pid=398892)[0m [588]	train-mlogloss:1.73091	validation-mlogloss:1.75204
[36m(train_xgb_ray_tune pid=398886)[0m [550]	train-mlogloss:1.56908	validation-mlogloss:1.68154
[36m(train_xgb_ray_tune pid=398903)[0m [548]	train-mlogloss:1.73944	validation-mlogloss:1.76929
[36m(train_xgb_ray_tune pid=398912)[0m [544]	train-mlogloss:1.70044	validation-mlogloss:1.74944
[36m(train_xgb_ray_tune pid=398916)[0m [534]	train-mlogloss:2.23517	validation-mlogloss:2.23333
[36m(train_xgb_ray_tune pid=398894)[0m [505]	train-mlogloss:1.79258	validation-mlogloss:1.80386
[36m(train_xgb_ray_tune pid=398894)[0m [506]	train-mlogloss:1.79190	validation-mlogloss:1.80342
[36m(train_xgb_ray_tune pid=398900)[0m [545]	train-mlogloss:2.01709	validation-mlogloss:1.98750
[36m(train_xgb_ray_tune pid=398900)[0m [546]	train-mlogloss:2.01651	validation-mlogloss:1.98694
[36m(train_xgb_ray_tune pid=398905)[0m [555]	train-mlogloss:1.73370	validation-mlogloss:1.76136
[36m(train_xgb_ray_tune pid=398913)[0m [769]	train-mlogloss:2.14639	validation-mlogloss:2.15857
[36m(train_xgb_ray_tune pid=398913)[0m [770]	train-mlogloss:2.14639	validation-mlogloss:2.15857
[36m(train_xgb_ray_tune pid=398901)[0m [552]	train-mlogloss:1.57219	validation-mlogloss:1.69460
[36m(train_xgb_ray_tune pid=398892)[0m [589]	train-mlogloss:1.73069	validation-mlogloss:1.75189
[36m(train_xgb_ray_tune pid=398886)[0m [551]	train-mlogloss:1.56863	validation-mlogloss:1.68131
[36m(train_xgb_ray_tune pid=398917)[0m [533]	train-mlogloss:1.67032	validation-mlogloss:1.73483
[36m(train_xgb_ray_tune pid=398903)[0m [549]	train-mlogloss:1.73888	validation-mlogloss:1.76889
[36m(train_xgb_ray_tune pid=398886)[0m [552]	train-mlogloss:1.56815	validation-mlogloss:1.68126
[36m(train_xgb_ray_tune pid=398903)[0m [550]	train-mlogloss:1.73832	validation-mlogloss:1.76857
[36m(train_xgb_ray_tune pid=398912)[0m [545]	train-mlogloss:1.69991	validation-mlogloss:1.74917
[36m(train_xgb_ray_tune pid=398912)[0m [546]	train-mlogloss:1.69933	validation-mlogloss:1.74895
[36m(train_xgb_ray_tune pid=398916)[0m [535]	train-mlogloss:2.23470	validation-mlogloss:2.23285
[36m(train_xgb_ray_tune pid=398894)[0m [507]	train-mlogloss:1.79126	validation-mlogloss:1.80309
[36m(train_xgb_ray_tune pid=398900)[0m [547]	train-mlogloss:2.01594	validation-mlogloss:1.98645
[36m(train_xgb_ray_tune pid=398905)[0m [556]	train-mlogloss:1.73337	validation-mlogloss:1.76121
[36m(train_xgb_ray_tune pid=398905)[0m [557]	train-mlogloss:1.73298	validation-mlogloss:1.76102
[36m(train_xgb_ray_tune pid=398913)[0m [771]	train-mlogloss:2.14639	validation-mlogloss:2.15857
[36m(train_xgb_ray_tune pid=398913)[0m [772]	train-mlogloss:2.14639	validation-mlogloss:2.15857
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[36m(train_xgb_ray_tune pid=398901)[0m [571]	train-mlogloss:1.56261	validation-mlogloss:1.69147
[36m(train_xgb_ray_tune pid=398901)[0m [572]	train-mlogloss:1.56214	validation-mlogloss:1.69107
[36m(train_xgb_ray_tune pid=398917)[0m [543]	train-mlogloss:1.66506	validation-mlogloss:1.73224
[36m(train_xgb_ray_tune pid=398892)[0m [602]	train-mlogloss:1.72758	validation-mlogloss:1.75011
[36m(train_xgb_ray_tune pid=398886)[0m [571]	train-mlogloss:1.56001	validation-mlogloss:1.67920
[36m(train_xgb_ray_tune pid=398903)[0m [568]	train-mlogloss:1.72832	validation-mlogloss:1.76317
[36m(train_xgb_ray_tune pid=398912)[0m [564]	train-mlogloss:1.68983	validation-mlogloss:1.74359
[36m(train_xgb_ray_tune pid=398916)[0m [553]	train-mlogloss:2.22740	validation-mlogloss:2.22582
[36m(train_xgb_ray_tune pid=398894)[0m [524]	train-mlogloss:1.78080	validation-mlogloss:1.79603
[36m(train_xgb_ray_tune pid=398900)[0m [564]	train-mlogloss:2.00626	validation-mlogloss:1.97774
[36m(train_xgb_ray_tune pid=398905)[0m [576]	train-mlogloss:1.72714	validation-mlogloss:1.75740
[36m(train_xgb_ray_tune pid=398901)[0m [573]	train-mlogloss:1.56159	validation-mlogloss:1.69103
[36m(train_xgb_ray_tune pid=398892)[0m [603]	train-mlogloss:1.72731	validation-mlogloss:1.75000
[36m(train_xgb_ray_tune pid=398900)[0m [565]	train-mlogloss:2.00571	validation-mlogloss:1.97729
[36m(train_xgb_ray_tune pid=398917)[0m [544]	train-mlogloss:1.66456	validation-mlogloss:1.73191
[36m(train_xgb_ray_tune pid=398894)[0m [525]	train-mlogloss:1.78020	validation-mlogloss:1.79559
[36m(train_xgb_ray_tune pid=398886)[0m [572]	train-mlogloss:1.55964	validation-mlogloss:1.67919
[36m(train_xgb_ray_tune pid=398903)[0m [569]	train-mlogloss:1.72776	validation-mlogloss:1.76282
[36m(train_xgb_ray_tune pid=398912)[0m [565]	train-mlogloss:1.68927	validation-mlogloss:1.74325
[36m(train_xgb_ray_tune pid=398912)[0m [566]	train-mlogloss:1.68877	validation-mlogloss:1.74301
[36m(train_xgb_ray_tune pid=398916)[0m [554]	train-mlogloss:2.22700	validation-mlogloss:2.22543
[36m(train_xgb_ray_tune pid=398916)[0m [555]	train-mlogloss:2.22659	validation-mlogloss:2.22501
[36m(train_xgb_ray_tune pid=398894)[0m [526]	train-mlogloss:1.77962	validation-mlogloss:1.79518
[36m(train_xgb_ray_tune pid=398900)[0m [566]	train-mlogloss:2.00516	validation-mlogloss:1.97681
[36m(train_xgb_ray_tune pid=398905)[0m [577]	train-mlogloss:1.72684	validation-mlogloss:1.75731
[36m(train_xgb_ray_tune pid=398901)[0m [574]	train-mlogloss:1.56108	validation-mlogloss:1.69073
[36m(train_xgb_ray_tune pid=398892)[0m [604]	train-mlogloss:1.72695	validation-mlogloss:1.74965
[36m(train_xgb_ray_tune pid=398886)[0m [573]	train-mlogloss:1.55916	validation-mlogloss:1.67908
[36m(train_xgb_ray_tune pid=398886)[0m [574]	train-mlogloss:1.55877	validation-mlogloss:1.67886
[36m(train_xgb_ray_tune pid=398903)[0m [570]	train-mlogloss:1.72724	validation-mlogloss:1.76254
[36m(train_xgb_ray_tune pid=398903)[0m [571]	train-mlogloss:1.72665	validation-mlogloss:1.76223
[36m(train_xgb_ray_tune pid=398912)[0m [567]	train-mlogloss:1.68826	validation-mlogloss:1.74275
[36m(train_xgb_ray_tune pid=398916)[0m [556]	train-mlogloss:2.22621	validation-mlogloss:2.22464
[36m(train_xgb_ray_tune pid=398894)[0m [527]	train-mlogloss:1.77899	validation-mlogloss:1.79485
[36m(train_xgb_ray_tune pid=398900)[0m [567]	train-mlogloss:2.00461	validation-mlogloss:1.97629
[36m(train_xgb_ray_tune pid=398905)[0m [578]	train-mlogloss:1.72654	validation-mlogloss:1.75706
[36m(train_xgb_ray_tune pid=398905)[0m [579]	train-mlogloss:1.72632	validation-mlogloss:1.75695
[36m(train_xgb_ray_tune pid=398901)[0m [575]	train-mlogloss:1.56065	validation-mlogloss:1.69071
[36m(train_xgb_ray_tune pid=398901)[0m [576]	train-mlogloss:1.56011	validation-mlogloss:1.69049
[36m(train_xgb_ray_tune pid=398917)[0m [545]	train-mlogloss:1.66401	validation-mlogloss:1.73163
[36m(train_xgb_ray_tune pid=398892)[0m [605]	train-mlogloss:1.72679	validation-mlogloss:1.74958

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:18. Total running time: 2min 3s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             120.375 │
│ time_total_s                 120.375 │
│ training_iteration                 1 │
│ validation_accuracy          0.37602 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:18. Total running time: 2min 3s
[36m(train_xgb_ray_tune pid=398886)[0m [575]	train-mlogloss:1.55831	validation-mlogloss:1.67851
[36m(train_xgb_ray_tune pid=398903)[0m [572]	train-mlogloss:1.72604	validation-mlogloss:1.76201
[36m(train_xgb_ray_tune pid=398912)[0m [568]	train-mlogloss:1.68774	validation-mlogloss:1.74245
[36m(train_xgb_ray_tune pid=398916)[0m [557]	train-mlogloss:2.22578	validation-mlogloss:2.22420
[36m(train_xgb_ray_tune pid=398894)[0m [528]	train-mlogloss:1.77844	validation-mlogloss:1.79451
[36m(train_xgb_ray_tune pid=398900)[0m [568]	train-mlogloss:2.00404	validation-mlogloss:1.97576
[36m(train_xgb_ray_tune pid=398905)[0m [580]	train-mlogloss:1.72602	validation-mlogloss:1.75681
[36m(train_xgb_ray_tune pid=398901)[0m [577]	train-mlogloss:1.55963	validation-mlogloss:1.69037
[36m(train_xgb_ray_tune pid=398917)[0m [546]	train-mlogloss:1.66348	validation-mlogloss:1.73142
[36m(train_xgb_ray_tune pid=398892)[0m [606]	train-mlogloss:1.72657	validation-mlogloss:1.74945
[36m(train_xgb_ray_tune pid=398886)[0m [576]	train-mlogloss:1.55787	validation-mlogloss:1.67857
[36m(train_xgb_ray_tune pid=398886)[0m [577]	train-mlogloss:1.55751	validation-mlogloss:1.67858
[36m(train_xgb_ray_tune pid=398903)[0m [573]	train-mlogloss:1.72557	validation-mlogloss:1.76174
[36m(train_xgb_ray_tune pid=398912)[0m [569]	train-mlogloss:1.68722	validation-mlogloss:1.74218
[36m(train_xgb_ray_tune pid=398912)[0m [570]	train-mlogloss:1.68668	validation-mlogloss:1.74198
[36m(train_xgb_ray_tune pid=398916)[0m [558]	train-mlogloss:2.22540	validation-mlogloss:2.22388
[36m(train_xgb_ray_tune pid=398916)[0m [559]	train-mlogloss:2.22494	validation-mlogloss:2.22342
[36m(train_xgb_ray_tune pid=398894)[0m [529]	train-mlogloss:1.77784	validation-mlogloss:1.79416
[36m(train_xgb_ray_tune pid=398900)[0m [569]	train-mlogloss:2.00350	validation-mlogloss:1.97527
[36m(train_xgb_ray_tune pid=398905)[0m [581]	train-mlogloss:1.72573	validation-mlogloss:1.75668
[36m(train_xgb_ray_tune pid=398901)[0m [578]	train-mlogloss:1.55913	validation-mlogloss:1.69013
[36m(train_xgb_ray_tune pid=398917)[0m [547]	train-mlogloss:1.66294	validation-mlogloss:1.73105
[36m(train_xgb_ray_tune pid=398892)[0m [607]	train-mlogloss:1.72631	validation-mlogloss:1.74930
[36m(train_xgb_ray_tune pid=398894)[0m [530]	train-mlogloss:1.77729	validation-mlogloss:1.79373
[36m(train_xgb_ray_tune pid=398905)[0m [582]	train-mlogloss:1.72548	validation-mlogloss:1.75654
[36m(train_xgb_ray_tune pid=398892)[0m [608]	train-mlogloss:1.72609	validation-mlogloss:1.74927
[36m(train_xgb_ray_tune pid=398886)[0m [578]	train-mlogloss:1.55712	validation-mlogloss:1.67844
[36m(train_xgb_ray_tune pid=398903)[0m [574]	train-mlogloss:1.72502	validation-mlogloss:1.76134
[36m(train_xgb_ray_tune pid=398903)[0m [575]	train-mlogloss:1.72449	validation-mlogloss:1.76108
[36m(train_xgb_ray_tune pid=398912)[0m [571]	train-mlogloss:1.68621	validation-mlogloss:1.74166
[36m(train_xgb_ray_tune pid=398916)[0m [560]	train-mlogloss:2.22458	validation-mlogloss:2.22309
[36m(train_xgb_ray_tune pid=398894)[0m [531]	train-mlogloss:1.77669	validation-mlogloss:1.79329
[36m(train_xgb_ray_tune pid=398900)[0m [570]	train-mlogloss:2.00296	validation-mlogloss:1.97481
[36m(train_xgb_ray_tune pid=398905)[0m [583]	train-mlogloss:1.72527	validation-mlogloss:1.75638
[36m(train_xgb_ray_tune pid=398901)[0m [579]	train-mlogloss:1.55859	validation-mlogloss:1.69002
[36m(train_xgb_ray_tune pid=398901)[0m [580]	train-mlogloss:1.55812	validation-mlogloss:1.68982
[36m(train_xgb_ray_tune pid=398917)[0m [548]	train-mlogloss:1.66244	validation-mlogloss:1.73075
[36m(train_xgb_ray_tune pid=398917)[0m [549]	train-mlogloss:1.66198	validation-mlogloss:1.73055
[36m(train_xgb_ray_tune pid=398892)[0m [609]	train-mlogloss:1.72581	validation-mlogloss:1.74909
[36m(train_xgb_ray_tune pid=398900)[0m [571]	train-mlogloss:2.00242	validation-mlogloss:1.97434
[36m(train_xgb_ray_tune pid=398886)[0m [579]	train-mlogloss:1.55665	validation-mlogloss:1.67834
[36m(train_xgb_ray_tune pid=398903)[0m [576]	train-mlogloss:1.72394	validation-mlogloss:1.76081
[36m(train_xgb_ray_tune pid=398912)[0m [572]	train-mlogloss:1.68564	validation-mlogloss:1.74139
[36m(train_xgb_ray_tune pid=398916)[0m [561]	train-mlogloss:2.22413	validation-mlogloss:2.22260
[36m(train_xgb_ray_tune pid=398894)[0m [532]	train-mlogloss:1.77603	validation-mlogloss:1.79293
[36m(train_xgb_ray_tune pid=398900)[0m [572]	train-mlogloss:2.00186	validation-mlogloss:1.97388
[36m(train_xgb_ray_tune pid=398905)[0m [584]	train-mlogloss:1.72494	validation-mlogloss:1.75616
[36m(train_xgb_ray_tune pid=398901)[0m [581]	train-mlogloss:1.55766	validation-mlogloss:1.68975
[36m(train_xgb_ray_tune pid=398917)[0m [550]	train-mlogloss:1.66149	validation-mlogloss:1.73047
[36m(train_xgb_ray_tune pid=398892)[0m [610]	train-mlogloss:1.72561	validation-mlogloss:1.74896
[36m(train_xgb_ray_tune pid=398892)[0m [611]	train-mlogloss:1.72534	validation-mlogloss:1.74888
[36m(train_xgb_ray_tune pid=398886)[0m [580]	train-mlogloss:1.55619	validation-mlogloss:1.67831
[36m(train_xgb_ray_tune pid=398886)[0m [581]	train-mlogloss:1.55580	validation-mlogloss:1.67809
[36m(train_xgb_ray_tune pid=398903)[0m [577]	train-mlogloss:1.72341	validation-mlogloss:1.76058
[36m(train_xgb_ray_tune pid=398912)[0m [573]	train-mlogloss:1.68513	validation-mlogloss:1.74111
[36m(train_xgb_ray_tune pid=398912)[0m [574]	train-mlogloss:1.68459	validation-mlogloss:1.74079
[36m(train_xgb_ray_tune pid=398916)[0m [562]	train-mlogloss:2.22373	validation-mlogloss:2.22223
[36m(train_xgb_ray_tune pid=398894)[0m [533]	train-mlogloss:1.77546	validation-mlogloss:1.79254
[36m(train_xgb_ray_tune pid=398900)[0m [573]	train-mlogloss:2.00129	validation-mlogloss:1.97335
[36m(train_xgb_ray_tune pid=398905)[0m [585]	train-mlogloss:1.72476	validation-mlogloss:1.75604
[36m(train_xgb_ray_tune pid=398905)[0m [586]	train-mlogloss:1.72453	validation-mlogloss:1.75596
[36m(train_xgb_ray_tune pid=398901)[0m [582]	train-mlogloss:1.55713	validation-mlogloss:1.68962
[36m(train_xgb_ray_tune pid=398917)[0m [551]	train-mlogloss:1.66100	validation-mlogloss:1.73024
[36m(train_xgb_ray_tune pid=398892)[0m [612]	train-mlogloss:1.72504	validation-mlogloss:1.74867
[36m(train_xgb_ray_tune pid=398916)[0m [563]	train-mlogloss:2.22333	validation-mlogloss:2.22187
[36m(train_xgb_ray_tune pid=398901)[0m [583]	train-mlogloss:1.55661	validation-mlogloss:1.68941
[36m(train_xgb_ray_tune pid=398886)[0m [582]	train-mlogloss:1.55535	validation-mlogloss:1.67795
[36m(train_xgb_ray_tune pid=398903)[0m [578]	train-mlogloss:1.72287	validation-mlogloss:1.76028
[36m(train_xgb_ray_tune pid=398903)[0m [579]	train-mlogloss:1.72234	validation-mlogloss:1.76000
[36m(train_xgb_ray_tune pid=398912)[0m [575]	train-mlogloss:1.68408	validation-mlogloss:1.74057
[36m(train_xgb_ray_tune pid=398916)[0m [564]	train-mlogloss:2.22291	validation-mlogloss:2.22145
[36m(train_xgb_ray_tune pid=398894)[0m [534]	train-mlogloss:1.77482	validation-mlogloss:1.79216
[36m(train_xgb_ray_tune pid=398894)[0m [535]	train-mlogloss:1.77422	validation-mlogloss:1.79191
[36m(train_xgb_ray_tune pid=398900)[0m [574]	train-mlogloss:2.00072	validation-mlogloss:1.97276
[36m(train_xgb_ray_tune pid=398905)[0m [587]	train-mlogloss:1.72436	validation-mlogloss:1.75588
[36m(train_xgb_ray_tune pid=398901)[0m [584]	train-mlogloss:1.55610	validation-mlogloss:1.68922
[36m(train_xgb_ray_tune pid=398917)[0m [552]	train-mlogloss:1.66050	validation-mlogloss:1.73000
[36m(train_xgb_ray_tune pid=398917)[0m [553]	train-mlogloss:1.65999	validation-mlogloss:1.72973
[36m(train_xgb_ray_tune pid=398892)[0m [613]	train-mlogloss:1.72480	validation-mlogloss:1.74850
[36m(train_xgb_ray_tune pid=398892)[0m [614]	train-mlogloss:1.72464	validation-mlogloss:1.74832
[36m(train_xgb_ray_tune pid=398886)[0m [583]	train-mlogloss:1.55489	validation-mlogloss:1.67776
[36m(train_xgb_ray_tune pid=398886)[0m [584]	train-mlogloss:1.55451	validation-mlogloss:1.67753
[36m(train_xgb_ray_tune pid=398903)[0m [580]	train-mlogloss:1.72182	validation-mlogloss:1.75968
[36m(train_xgb_ray_tune pid=398912)[0m [576]	train-mlogloss:1.68350	validation-mlogloss:1.74030
[36m(train_xgb_ray_tune pid=398916)[0m [565]	train-mlogloss:2.22254	validation-mlogloss:2.22109
[36m(train_xgb_ray_tune pid=398894)[0m [536]	train-mlogloss:1.77363	validation-mlogloss:1.79152
[36m(train_xgb_ray_tune pid=398900)[0m [575]	train-mlogloss:2.00016	validation-mlogloss:1.97231
[36m(train_xgb_ray_tune pid=398900)[0m [576]	train-mlogloss:1.99962	validation-mlogloss:1.97186
[36m(train_xgb_ray_tune pid=398905)[0m [588]	train-mlogloss:1.72401	validation-mlogloss:1.75567
[36m(train_xgb_ray_tune pid=398905)[0m [589]	train-mlogloss:1.72370	validation-mlogloss:1.75552
[36m(train_xgb_ray_tune pid=398901)[0m [585]	train-mlogloss:1.55563	validation-mlogloss:1.68905
[36m(train_xgb_ray_tune pid=398917)[0m [554]	train-mlogloss:1.65946	validation-mlogloss:1.72952
[36m(train_xgb_ray_tune pid=398892)[0m [615]	train-mlogloss:1.72440	validation-mlogloss:1.74810
[36m(train_xgb_ray_tune pid=398886)[0m [585]	train-mlogloss:1.55404	validation-mlogloss:1.67731
[36m(train_xgb_ray_tune pid=398903)[0m [581]	train-mlogloss:1.72128	validation-mlogloss:1.75934
[36m(train_xgb_ray_tune pid=398912)[0m [577]	train-mlogloss:1.68294	validation-mlogloss:1.74000
[36m(train_xgb_ray_tune pid=398912)[0m [578]	train-mlogloss:1.68245	validation-mlogloss:1.73970
[36m(train_xgb_ray_tune pid=398916)[0m [566]	train-mlogloss:2.22214	validation-mlogloss:2.22070
[36m(train_xgb_ray_tune pid=398894)[0m [537]	train-mlogloss:1.77307	validation-mlogloss:1.79115
[36m(train_xgb_ray_tune pid=398900)[0m [577]	train-mlogloss:1.99908	validation-mlogloss:1.97139
[36m(train_xgb_ray_tune pid=398905)[0m [590]	train-mlogloss:1.72346	validation-mlogloss:1.75538
[36m(train_xgb_ray_tune pid=398901)[0m [586]	train-mlogloss:1.55510	validation-mlogloss:1.68886
[36m(train_xgb_ray_tune pid=398901)[0m [587]	train-mlogloss:1.55462	validation-mlogloss:1.68881
[36m(train_xgb_ray_tune pid=398917)[0m [555]	train-mlogloss:1.65893	validation-mlogloss:1.72934
[36m(train_xgb_ray_tune pid=398892)[0m [616]	train-mlogloss:1.72419	validation-mlogloss:1.74803
[36m(train_xgb_ray_tune pid=398892)[0m [617]	train-mlogloss:1.72403	validation-mlogloss:1.74789
[36m(train_xgb_ray_tune pid=398886)[0m [586]	train-mlogloss:1.55359	validation-mlogloss:1.67750
[36m(train_xgb_ray_tune pid=398903)[0m [582]	train-mlogloss:1.72073	validation-mlogloss:1.75893
[36m(train_xgb_ray_tune pid=398912)[0m [579]	train-mlogloss:1.68191	validation-mlogloss:1.73940
[36m(train_xgb_ray_tune pid=398916)[0m [567]	train-mlogloss:2.22175	validation-mlogloss:2.22032
[36m(train_xgb_ray_tune pid=398916)[0m [568]	train-mlogloss:2.22138	validation-mlogloss:2.21995
[36m(train_xgb_ray_tune pid=398894)[0m [538]	train-mlogloss:1.77249	validation-mlogloss:1.79081
[36m(train_xgb_ray_tune pid=398900)[0m [578]	train-mlogloss:1.99851	validation-mlogloss:1.97094
[36m(train_xgb_ray_tune pid=398905)[0m [591]	train-mlogloss:1.72321	validation-mlogloss:1.75521
[36m(train_xgb_ray_tune pid=398901)[0m [588]	train-mlogloss:1.55412	validation-mlogloss:1.68863
[36m(train_xgb_ray_tune pid=398917)[0m [556]	train-mlogloss:1.65837	validation-mlogloss:1.72903
[36m(train_xgb_ray_tune pid=398892)[0m [618]	train-mlogloss:1.72383	validation-mlogloss:1.74772
[36m(train_xgb_ray_tune pid=398903)[0m [583]	train-mlogloss:1.72024	validation-mlogloss:1.75886
[36m(train_xgb_ray_tune pid=398886)[0m [587]	train-mlogloss:1.55320	validation-mlogloss:1.67768
[36m(train_xgb_ray_tune pid=398886)[0m [588]	train-mlogloss:1.55284	validation-mlogloss:1.67761
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[36m(train_xgb_ray_tune pid=398886)[0m [640]	train-mlogloss:1.53368	validation-mlogloss:1.67276
[36m(train_xgb_ray_tune pid=398903)[0m [633]	train-mlogloss:1.69462	validation-mlogloss:1.74549
[36m(train_xgb_ray_tune pid=398912)[0m [630]	train-mlogloss:1.65703	validation-mlogloss:1.72779
[36m(train_xgb_ray_tune pid=398912)[0m [631]	train-mlogloss:1.65653	validation-mlogloss:1.72761
[36m(train_xgb_ray_tune pid=398916)[0m [618]	train-mlogloss:2.20321	validation-mlogloss:2.20269
[36m(train_xgb_ray_tune pid=398894)[0m [587]	train-mlogloss:1.74558	validation-mlogloss:1.77462
[36m(train_xgb_ray_tune pid=398900)[0m [627]	train-mlogloss:1.97265	validation-mlogloss:1.94819
[36m(train_xgb_ray_tune pid=398905)[0m [646]	train-mlogloss:1.71109	validation-mlogloss:1.74837
[36m(train_xgb_ray_tune pid=398905)[0m [647]	train-mlogloss:1.71086	validation-mlogloss:1.74822
[36m(train_xgb_ray_tune pid=398901)[0m [641]	train-mlogloss:1.52977	validation-mlogloss:1.68118
[36m(train_xgb_ray_tune pid=398901)[0m [642]	train-mlogloss:1.52936	validation-mlogloss:1.68105
[36m(train_xgb_ray_tune pid=398892)[0m [678]	train-mlogloss:1.71200	validation-mlogloss:1.74066
[36m(train_xgb_ray_tune pid=398903)[0m [634]	train-mlogloss:1.69414	validation-mlogloss:1.74528
[36m(train_xgb_ray_tune pid=398900)[0m [628]	train-mlogloss:1.97212	validation-mlogloss:1.94768
[36m(train_xgb_ray_tune pid=398886)[0m [641]	train-mlogloss:1.53330	validation-mlogloss:1.67258
[36m(train_xgb_ray_tune pid=398886)[0m [642]	train-mlogloss:1.53301	validation-mlogloss:1.67244
[36m(train_xgb_ray_tune pid=398903)[0m [635]	train-mlogloss:1.69363	validation-mlogloss:1.74496
[36m(train_xgb_ray_tune pid=398912)[0m [632]	train-mlogloss:1.65600	validation-mlogloss:1.72744
[36m(train_xgb_ray_tune pid=398916)[0m [619]	train-mlogloss:2.20287	validation-mlogloss:2.20232
[36m(train_xgb_ray_tune pid=398916)[0m [620]	train-mlogloss:2.20250	validation-mlogloss:2.20195
[36m(train_xgb_ray_tune pid=398894)[0m [588]	train-mlogloss:1.74507	validation-mlogloss:1.77436
[36m(train_xgb_ray_tune pid=398900)[0m [629]	train-mlogloss:1.97164	validation-mlogloss:1.94729
[36m(train_xgb_ray_tune pid=398905)[0m [648]	train-mlogloss:1.71073	validation-mlogloss:1.74817
[36m(train_xgb_ray_tune pid=398901)[0m [643]	train-mlogloss:1.52891	validation-mlogloss:1.68099
[36m(train_xgb_ray_tune pid=398892)[0m [679]	train-mlogloss:1.71190	validation-mlogloss:1.74061
[36m(train_xgb_ray_tune pid=398892)[0m [680]	train-mlogloss:1.71168	validation-mlogloss:1.74051
[36m(train_xgb_ray_tune pid=398886)[0m [643]	train-mlogloss:1.53266	validation-mlogloss:1.67237
[36m(train_xgb_ray_tune pid=398903)[0m [636]	train-mlogloss:1.69317	validation-mlogloss:1.74471
[36m(train_xgb_ray_tune pid=398912)[0m [633]	train-mlogloss:1.65549	validation-mlogloss:1.72707
[36m(train_xgb_ray_tune pid=398912)[0m [634]	train-mlogloss:1.65503	validation-mlogloss:1.72690
[36m(train_xgb_ray_tune pid=398916)[0m [621]	train-mlogloss:2.20217	validation-mlogloss:2.20163
[36m(train_xgb_ray_tune pid=398894)[0m [589]	train-mlogloss:1.74453	validation-mlogloss:1.77406
[36m(train_xgb_ray_tune pid=398894)[0m [590]	train-mlogloss:1.74399	validation-mlogloss:1.77369
[36m(train_xgb_ray_tune pid=398900)[0m [630]	train-mlogloss:1.97112	validation-mlogloss:1.94687
[36m(train_xgb_ray_tune pid=398905)[0m [649]	train-mlogloss:1.71054	validation-mlogloss:1.74799
[36m(train_xgb_ray_tune pid=398905)[0m [650]	train-mlogloss:1.71040	validation-mlogloss:1.74793
[36m(train_xgb_ray_tune pid=398901)[0m [644]	train-mlogloss:1.52852	validation-mlogloss:1.68106
[36m(train_xgb_ray_tune pid=398901)[0m [645]	train-mlogloss:1.52811	validation-mlogloss:1.68107
[36m(train_xgb_ray_tune pid=398892)[0m [681]	train-mlogloss:1.71150	validation-mlogloss:1.74038
[36m(train_xgb_ray_tune pid=398892)[0m [682]	train-mlogloss:1.71138	validation-mlogloss:1.74031
[36m(train_xgb_ray_tune pid=398886)[0m [644]	train-mlogloss:1.53231	validation-mlogloss:1.67219
[36m(train_xgb_ray_tune pid=398886)[0m [645]	train-mlogloss:1.53188	validation-mlogloss:1.67197
[36m(train_xgb_ray_tune pid=398903)[0m [637]	train-mlogloss:1.69268	validation-mlogloss:1.74451
[36m(train_xgb_ray_tune pid=398903)[0m [638]	train-mlogloss:1.69220	validation-mlogloss:1.74425
[36m(train_xgb_ray_tune pid=398912)[0m [635]	train-mlogloss:1.65455	validation-mlogloss:1.72664
[36m(train_xgb_ray_tune pid=398916)[0m [622]	train-mlogloss:2.20179	validation-mlogloss:2.20125
[36m(train_xgb_ray_tune pid=398894)[0m [591]	train-mlogloss:1.74345	validation-mlogloss:1.77337
[36m(train_xgb_ray_tune pid=398900)[0m [631]	train-mlogloss:1.97058	validation-mlogloss:1.94638
[36m(train_xgb_ray_tune pid=398900)[0m [632]	train-mlogloss:1.97008	validation-mlogloss:1.94590
[36m(train_xgb_ray_tune pid=398905)[0m [651]	train-mlogloss:1.71022	validation-mlogloss:1.74787
[36m(train_xgb_ray_tune pid=398901)[0m [646]	train-mlogloss:1.52773	validation-mlogloss:1.68095
[36m(train_xgb_ray_tune pid=398892)[0m [683]	train-mlogloss:1.71115	validation-mlogloss:1.74020
[36m(train_xgb_ray_tune pid=398886)[0m [646]	train-mlogloss:1.53159	validation-mlogloss:1.67193
[36m(train_xgb_ray_tune pid=398917)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=398917)[0m   _log_deprecation_warning([32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=398903)[0m [639]	train-mlogloss:1.69178	validation-mlogloss:1.74412
[36m(train_xgb_ray_tune pid=398912)[0m [636]	train-mlogloss:1.65410	validation-mlogloss:1.72640
[36m(train_xgb_ray_tune pid=398916)[0m [623]	train-mlogloss:2.20138	validation-mlogloss:2.20082
[36m(train_xgb_ray_tune pid=398916)[0m [624]	train-mlogloss:2.20105	validation-mlogloss:2.20054
[36m(train_xgb_ray_tune pid=398894)[0m [592]	train-mlogloss:1.74291	validation-mlogloss:1.77303
[36m(train_xgb_ray_tune pid=398900)[0m [633]	train-mlogloss:1.96957	validation-mlogloss:1.94548
[36m(train_xgb_ray_tune pid=398905)[0m [652]	train-mlogloss:1.70998	validation-mlogloss:1.74773
[36m(train_xgb_ray_tune pid=398905)[0m [653]	train-mlogloss:1.70985	validation-mlogloss:1.74769
[36m(train_xgb_ray_tune pid=398901)[0m [647]	train-mlogloss:1.52731	validation-mlogloss:1.68082
[36m(train_xgb_ray_tune pid=398892)[0m [684]	train-mlogloss:1.71110	validation-mlogloss:1.74020
[36m(train_xgb_ray_tune pid=398892)[0m [685]	train-mlogloss:1.71091	validation-mlogloss:1.73995
[36m(train_xgb_ray_tune pid=398886)[0m [647]	train-mlogloss:1.53130	validation-mlogloss:1.67196
[36m(train_xgb_ray_tune pid=398903)[0m [640]	train-mlogloss:1.69126	validation-mlogloss:1.74398
[36m(train_xgb_ray_tune pid=398912)[0m [637]	train-mlogloss:1.65363	validation-mlogloss:1.72622
[36m(train_xgb_ray_tune pid=398912)[0m [638]	train-mlogloss:1.65319	validation-mlogloss:1.72592
[36m(train_xgb_ray_tune pid=398916)[0m [625]	train-mlogloss:2.20069	validation-mlogloss:2.20019
[36m(train_xgb_ray_tune pid=398894)[0m [593]	train-mlogloss:1.74243	validation-mlogloss:1.77278
[36m(train_xgb_ray_tune pid=398894)[0m [594]	train-mlogloss:1.74193	validation-mlogloss:1.77245
[36m(train_xgb_ray_tune pid=398900)[0m [634]	train-mlogloss:1.96907	validation-mlogloss:1.94509
[36m(train_xgb_ray_tune pid=398905)[0m [654]	train-mlogloss:1.70970	validation-mlogloss:1.74766
[36m(train_xgb_ray_tune pid=398905)[0m [655]	train-mlogloss:1.70949	validation-mlogloss:1.74741
[36m(train_xgb_ray_tune pid=398901)[0m [648]	train-mlogloss:1.52685	validation-mlogloss:1.68080
[36m(train_xgb_ray_tune pid=398901)[0m [649]	train-mlogloss:1.52649	validation-mlogloss:1.68052
[36m(train_xgb_ray_tune pid=398892)[0m [686]	train-mlogloss:1.71072	validation-mlogloss:1.73973
[36m(train_xgb_ray_tune pid=398892)[0m [687]	train-mlogloss:1.71058	validation-mlogloss:1.73960
[36m(train_xgb_ray_tune pid=398886)[0m [648]	train-mlogloss:1.53092	validation-mlogloss:1.67186
[36m(train_xgb_ray_tune pid=398903)[0m [641]	train-mlogloss:1.69081	validation-mlogloss:1.74376
[36m(train_xgb_ray_tune pid=398886)[0m [649]	train-mlogloss:1.53065	validation-mlogloss:1.67199
[36m(train_xgb_ray_tune pid=398903)[0m [642]	train-mlogloss:1.69033	validation-mlogloss:1.74362
[36m(train_xgb_ray_tune pid=398912)[0m [639]	train-mlogloss:1.65273	validation-mlogloss:1.72566
[36m(train_xgb_ray_tune pid=398916)[0m [626]	train-mlogloss:2.20034	validation-mlogloss:2.19983
[36m(train_xgb_ray_tune pid=398894)[0m [595]	train-mlogloss:1.74139	validation-mlogloss:1.77193
[36m(train_xgb_ray_tune pid=398900)[0m [635]	train-mlogloss:1.96855	validation-mlogloss:1.94460
[36m(train_xgb_ray_tune pid=398905)[0m [656]	train-mlogloss:1.70938	validation-mlogloss:1.74734
[36m(train_xgb_ray_tune pid=398901)[0m [650]	train-mlogloss:1.52602	validation-mlogloss:1.68033
[36m(train_xgb_ray_tune pid=398892)[0m [688]	train-mlogloss:1.71046	validation-mlogloss:1.73957
[36m(train_xgb_ray_tune pid=398916)[0m [627]	train-mlogloss:2.19999	validation-mlogloss:2.19948
[36m(train_xgb_ray_tune pid=398900)[0m [636]	train-mlogloss:1.96802	validation-mlogloss:1.94414
[36m(train_xgb_ray_tune pid=398886)[0m [650]	train-mlogloss:1.53023	validation-mlogloss:1.67178
[36m(train_xgb_ray_tune pid=398886)[0m [651]	train-mlogloss:1.52990	validation-mlogloss:1.67176
[36m(train_xgb_ray_tune pid=398903)[0m [643]	train-mlogloss:1.68981	validation-mlogloss:1.74343
[36m(train_xgb_ray_tune pid=398912)[0m [640]	train-mlogloss:1.65229	validation-mlogloss:1.72544
[36m(train_xgb_ray_tune pid=398912)[0m [641]	train-mlogloss:1.65177	validation-mlogloss:1.72523
[36m(train_xgb_ray_tune pid=398916)[0m [628]	train-mlogloss:2.19962	validation-mlogloss:2.19909
[36m(train_xgb_ray_tune pid=398894)[0m [596]	train-mlogloss:1.74091	validation-mlogloss:1.77161
[36m(train_xgb_ray_tune pid=398900)[0m [637]	train-mlogloss:1.96754	validation-mlogloss:1.94371
[36m(train_xgb_ray_tune pid=398905)[0m [657]	train-mlogloss:1.70924	validation-mlogloss:1.74720
[36m(train_xgb_ray_tune pid=398905)[0m [658]	train-mlogloss:1.70908	validation-mlogloss:1.74720
[36m(train_xgb_ray_tune pid=398901)[0m [651]	train-mlogloss:1.52563	validation-mlogloss:1.68030
[36m(train_xgb_ray_tune pid=398901)[0m [652]	train-mlogloss:1.52515	validation-mlogloss:1.68017
[36m(train_xgb_ray_tune pid=398892)[0m [689]	train-mlogloss:1.71025	validation-mlogloss:1.73939
[36m(train_xgb_ray_tune pid=398892)[0m [690]	train-mlogloss:1.71008	validation-mlogloss:1.73926

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:25. Total running time: 2min 9s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             126.697 │
│ time_total_s                 126.697 │
│ training_iteration                 1 │
│ validation_accuracy          0.51678 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:25. Total running time: 2min 9s
[36m(train_xgb_ray_tune pid=398886)[0m [652]	train-mlogloss:1.52964	validation-mlogloss:1.67175
[36m(train_xgb_ray_tune pid=398903)[0m [644]	train-mlogloss:1.68937	validation-mlogloss:1.74326
[36m(train_xgb_ray_tune pid=398903)[0m [645]	train-mlogloss:1.68885	validation-mlogloss:1.74299
[36m(train_xgb_ray_tune pid=398912)[0m [642]	train-mlogloss:1.65133	validation-mlogloss:1.72502
[36m(train_xgb_ray_tune pid=398916)[0m [629]	train-mlogloss:2.19929	validation-mlogloss:2.19880
[36m(train_xgb_ray_tune pid=398894)[0m [597]	train-mlogloss:1.74036	validation-mlogloss:1.77118
[36m(train_xgb_ray_tune pid=398894)[0m [598]	train-mlogloss:1.73984	validation-mlogloss:1.77085
[36m(train_xgb_ray_tune pid=398900)[0m [638]	train-mlogloss:1.96706	validation-mlogloss:1.94328
[36m(train_xgb_ray_tune pid=398905)[0m [659]	train-mlogloss:1.70889	validation-mlogloss:1.74713
[36m(train_xgb_ray_tune pid=398905)[0m [660]	train-mlogloss:1.70872	validation-mlogloss:1.74707
[36m(train_xgb_ray_tune pid=398901)[0m [653]	train-mlogloss:1.52475	validation-mlogloss:1.68009
[36m(train_xgb_ray_tune pid=398892)[0m [691]	train-mlogloss:1.70996	validation-mlogloss:1.73923
[36m(train_xgb_ray_tune pid=398892)[0m [692]	train-mlogloss:1.70978	validation-mlogloss:1.73918
[36m(train_xgb_ray_tune pid=398886)[0m [653]	train-mlogloss:1.52928	validation-mlogloss:1.67162
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[36m(train_xgb_ray_tune pid=398903)[0m [646]	train-mlogloss:1.68837	validation-mlogloss:1.74276
[36m(train_xgb_ray_tune pid=398912)[0m [643]	train-mlogloss:1.65082	validation-mlogloss:1.72492
[36m(train_xgb_ray_tune pid=398912)[0m [644]	train-mlogloss:1.65039	validation-mlogloss:1.72481
[36m(train_xgb_ray_tune pid=398916)[0m [630]	train-mlogloss:2.19898	validation-mlogloss:2.19852
[36m(train_xgb_ray_tune pid=398916)[0m [631]	train-mlogloss:2.19868	validation-mlogloss:2.19826
[36m(train_xgb_ray_tune pid=398894)[0m [599]	train-mlogloss:1.73933	validation-mlogloss:1.77051
[36m(train_xgb_ray_tune pid=398900)[0m [639]	train-mlogloss:1.96657	validation-mlogloss:1.94289
[36m(train_xgb_ray_tune pid=398900)[0m [640]	train-mlogloss:1.96605	validation-mlogloss:1.94254
[36m(train_xgb_ray_tune pid=398905)[0m [661]	train-mlogloss:1.70858	validation-mlogloss:1.74700
[36m(train_xgb_ray_tune pid=398901)[0m [654]	train-mlogloss:1.52432	validation-mlogloss:1.67997
[36m(train_xgb_ray_tune pid=398901)[0m [655]	train-mlogloss:1.52390	validation-mlogloss:1.67994
[36m(train_xgb_ray_tune pid=398892)[0m [693]	train-mlogloss:1.70968	validation-mlogloss:1.73906
[36m(train_xgb_ray_tune pid=398892)[0m [694]	train-mlogloss:1.70949	validation-mlogloss:1.73901
[36m(train_xgb_ray_tune pid=398886)[0m [655]	train-mlogloss:1.52861	validation-mlogloss:1.67193
[36m(train_xgb_ray_tune pid=398903)[0m [647]	train-mlogloss:1.68794	validation-mlogloss:1.74249
[36m(train_xgb_ray_tune pid=398903)[0m [648]	train-mlogloss:1.68751	validation-mlogloss:1.74231
[36m(train_xgb_ray_tune pid=398912)[0m [645]	train-mlogloss:1.64991	validation-mlogloss:1.72459
[36m(train_xgb_ray_tune pid=398916)[0m [632]	train-mlogloss:2.19833	validation-mlogloss:2.19790
[36m(train_xgb_ray_tune pid=398894)[0m [600]	train-mlogloss:1.73882	validation-mlogloss:1.77026
[36m(train_xgb_ray_tune pid=398900)[0m [641]	train-mlogloss:1.96556	validation-mlogloss:1.94212
[36m(train_xgb_ray_tune pid=398905)[0m [662]	train-mlogloss:1.70830	validation-mlogloss:1.74684
[36m(train_xgb_ray_tune pid=398905)[0m [663]	train-mlogloss:1.70806	validation-mlogloss:1.74674
[36m(train_xgb_ray_tune pid=398901)[0m [656]	train-mlogloss:1.52349	validation-mlogloss:1.67987
[36m(train_xgb_ray_tune pid=398892)[0m [695]	train-mlogloss:1.70929	validation-mlogloss:1.73880
[36m(train_xgb_ray_tune pid=398894)[0m [601]	train-mlogloss:1.73832	validation-mlogloss:1.76993
[36m(train_xgb_ray_tune pid=398886)[0m [656]	train-mlogloss:1.52823	validation-mlogloss:1.67180
[36m(train_xgb_ray_tune pid=398886)[0m [657]	train-mlogloss:1.52796	validation-mlogloss:1.67159
[36m(train_xgb_ray_tune pid=398903)[0m [649]	train-mlogloss:1.68703	validation-mlogloss:1.74213
[36m(train_xgb_ray_tune pid=398912)[0m [646]	train-mlogloss:1.64944	validation-mlogloss:1.72445
[36m(train_xgb_ray_tune pid=398912)[0m [647]	train-mlogloss:1.64895	validation-mlogloss:1.72428
[36m(train_xgb_ray_tune pid=398916)[0m [633]	train-mlogloss:2.19802	validation-mlogloss:2.19763
[36m(train_xgb_ray_tune pid=398916)[0m [634]	train-mlogloss:2.19769	validation-mlogloss:2.19729
[36m(train_xgb_ray_tune pid=398894)[0m [602]	train-mlogloss:1.73779	validation-mlogloss:1.76963
[36m(train_xgb_ray_tune pid=398900)[0m [642]	train-mlogloss:1.96509	validation-mlogloss:1.94177
[36m(train_xgb_ray_tune pid=398905)[0m [664]	train-mlogloss:1.70790	validation-mlogloss:1.74661
[36m(train_xgb_ray_tune pid=398901)[0m [657]	train-mlogloss:1.52305	validation-mlogloss:1.67976
[36m(train_xgb_ray_tune pid=398901)[0m [658]	train-mlogloss:1.52269	validation-mlogloss:1.67973
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[36m(train_xgb_ray_tune pid=398894)[0m [621]	train-mlogloss:1.72831	validation-mlogloss:1.76439
[36m(train_xgb_ray_tune pid=398905)[0m [686]	train-mlogloss:1.70420	validation-mlogloss:1.74474
[36m(train_xgb_ray_tune pid=398901)[0m [678]	train-mlogloss:1.51423	validation-mlogloss:1.67756
[36m(train_xgb_ray_tune pid=398901)[0m [679]	train-mlogloss:1.51386	validation-mlogloss:1.67750
[36m(train_xgb_ray_tune pid=398892)[0m [720]	train-mlogloss:1.70556	validation-mlogloss:1.73660
[36m(train_xgb_ray_tune pid=398892)[0m [721]	train-mlogloss:1.70550	validation-mlogloss:1.73657
[36m(train_xgb_ray_tune pid=398886)[0m [679]	train-mlogloss:1.52100	validation-mlogloss:1.67002
[36m(train_xgb_ray_tune pid=398886)[0m [680]	train-mlogloss:1.52070	validation-mlogloss:1.67008
[36m(train_xgb_ray_tune pid=398903)[0m [670]	train-mlogloss:1.67715	validation-mlogloss:1.73713
[36m(train_xgb_ray_tune pid=398903)[0m [671]	train-mlogloss:1.67672	validation-mlogloss:1.73699
[36m(train_xgb_ray_tune pid=398912)[0m [668]	train-mlogloss:1.63969	validation-mlogloss:1.71967
[36m(train_xgb_ray_tune pid=398916)[0m [654]	train-mlogloss:2.19108	validation-mlogloss:2.19097
[36m(train_xgb_ray_tune pid=398916)[0m [655]	train-mlogloss:2.19075	validation-mlogloss:2.19068
[36m(train_xgb_ray_tune pid=398894)[0m [622]	train-mlogloss:1.72781	validation-mlogloss:1.76422
[36m(train_xgb_ray_tune pid=398905)[0m [687]	train-mlogloss:1.70404	validation-mlogloss:1.74473
[36m(train_xgb_ray_tune pid=398905)[0m [688]	train-mlogloss:1.70390	validation-mlogloss:1.74466
[36m(train_xgb_ray_tune pid=398901)[0m [680]	train-mlogloss:1.51343	validation-mlogloss:1.67755
[36m(train_xgb_ray_tune pid=398901)[0m [681]	train-mlogloss:1.51299	validation-mlogloss:1.67744
[36m(train_xgb_ray_tune pid=398892)[0m [722]	train-mlogloss:1.70539	validation-mlogloss:1.73655
[36m(train_xgb_ray_tune pid=398892)[0m [723]	train-mlogloss:1.70526	validation-mlogloss:1.73642

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:27. Total running time: 2min 11s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             128.769 │
│ time_total_s                 128.769 │
│ training_iteration                 1 │
│ validation_accuracy           0.5003 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:27. Total running time: 2min 11s
[36m(train_xgb_ray_tune pid=398886)[0m [681]	train-mlogloss:1.52028	validation-mlogloss:1.67009
[36m(train_xgb_ray_tune pid=398886)[0m [682]	train-mlogloss:1.51988	validation-mlogloss:1.66998
[36m(train_xgb_ray_tune pid=398903)[0m [672]	train-mlogloss:1.67629	validation-mlogloss:1.73680
[36m(train_xgb_ray_tune pid=398912)[0m [669]	train-mlogloss:1.63928	validation-mlogloss:1.71945
[36m(train_xgb_ray_tune pid=398912)[0m [670]	train-mlogloss:1.63885	validation-mlogloss:1.71928
[36m(train_xgb_ray_tune pid=398916)[0m [656]	train-mlogloss:2.19045	validation-mlogloss:2.19039
[36m(train_xgb_ray_tune pid=398916)[0m [657]	train-mlogloss:2.19014	validation-mlogloss:2.19007
[36m(train_xgb_ray_tune pid=398894)[0m [623]	train-mlogloss:1.72729	validation-mlogloss:1.76404
[36m(train_xgb_ray_tune pid=398894)[0m [624]	train-mlogloss:1.72678	validation-mlogloss:1.76370
[36m(train_xgb_ray_tune pid=398905)[0m [689]	train-mlogloss:1.70373	validation-mlogloss:1.74447
[36m(train_xgb_ray_tune pid=398905)[0m [690]	train-mlogloss:1.70365	validation-mlogloss:1.74446
[36m(train_xgb_ray_tune pid=398901)[0m [682]	train-mlogloss:1.51264	validation-mlogloss:1.67743
[36m(train_xgb_ray_tune pid=398892)[0m [724]	train-mlogloss:1.70518	validation-mlogloss:1.73640
[36m(train_xgb_ray_tune pid=398892)[0m [725]	train-mlogloss:1.70511	validation-mlogloss:1.73642
[36m(train_xgb_ray_tune pid=398886)[0m [683]	train-mlogloss:1.51954	validation-mlogloss:1.66995
[36m(train_xgb_ray_tune pid=398903)[0m [673]	train-mlogloss:1.67586	validation-mlogloss:1.73662
[36m(train_xgb_ray_tune pid=398903)[0m [674]	train-mlogloss:1.67540	validation-mlogloss:1.73634
[36m(train_xgb_ray_tune pid=398912)[0m [671]	train-mlogloss:1.63848	validation-mlogloss:1.71909
[36m(train_xgb_ray_tune pid=398916)[0m [658]	train-mlogloss:2.18978	validation-mlogloss:2.18969
[36m(train_xgb_ray_tune pid=398894)[0m [625]	train-mlogloss:1.72628	validation-mlogloss:1.76347
[36m(train_xgb_ray_tune pid=398894)[0m [626]	train-mlogloss:1.72580	validation-mlogloss:1.76320
[36m(train_xgb_ray_tune pid=398905)[0m [691]	train-mlogloss:1.70356	validation-mlogloss:1.74445
[36m(train_xgb_ray_tune pid=398905)[0m [692]	train-mlogloss:1.70336	validation-mlogloss:1.74432
[36m(train_xgb_ray_tune pid=398901)[0m [683]	train-mlogloss:1.51220	validation-mlogloss:1.67722
[36m(train_xgb_ray_tune pid=398901)[0m [684]	train-mlogloss:1.51177	validation-mlogloss:1.67711
[36m(train_xgb_ray_tune pid=398892)[0m [726]	train-mlogloss:1.70501	validation-mlogloss:1.73636
[36m(train_xgb_ray_tune pid=398892)[0m [727]	train-mlogloss:1.70482	validation-mlogloss:1.73624
[36m(train_xgb_ray_tune pid=398912)[0m [672]	train-mlogloss:1.63803	validation-mlogloss:1.71897
[36m(train_xgb_ray_tune pid=398886)[0m [684]	train-mlogloss:1.51927	validation-mlogloss:1.67000
[36m(train_xgb_ray_tune pid=398886)[0m [685]	train-mlogloss:1.51887	validation-mlogloss:1.66993
[36m(train_xgb_ray_tune pid=398903)[0m [675]	train-mlogloss:1.67500	validation-mlogloss:1.73622
[36m(train_xgb_ray_tune pid=398903)[0m [676]	train-mlogloss:1.67457	validation-mlogloss:1.73618
[36m(train_xgb_ray_tune pid=398912)[0m [673]	train-mlogloss:1.63759	validation-mlogloss:1.71868
[36m(train_xgb_ray_tune pid=398916)[0m [659]	train-mlogloss:2.18946	validation-mlogloss:2.18938
[36m(train_xgb_ray_tune pid=398916)[0m [660]	train-mlogloss:2.18915	validation-mlogloss:2.18911
[36m(train_xgb_ray_tune pid=398894)[0m [627]	train-mlogloss:1.72533	validation-mlogloss:1.76283
[36m(train_xgb_ray_tune pid=398905)[0m [693]	train-mlogloss:1.70327	validation-mlogloss:1.74431
[36m(train_xgb_ray_tune pid=398905)[0m [694]	train-mlogloss:1.70309	validation-mlogloss:1.74410
[36m(train_xgb_ray_tune pid=398901)[0m [685]	train-mlogloss:1.51136	validation-mlogloss:1.67695
[36m(train_xgb_ray_tune pid=398901)[0m [686]	train-mlogloss:1.51101	validation-mlogloss:1.67682
[36m(train_xgb_ray_tune pid=398892)[0m [728]	train-mlogloss:1.70461	validation-mlogloss:1.73613
[36m(train_xgb_ray_tune pid=398892)[0m [729]	train-mlogloss:1.70443	validation-mlogloss:1.73594
[36m(train_xgb_ray_tune pid=398886)[0m [686]	train-mlogloss:1.51848	validation-mlogloss:1.66990
[36m(train_xgb_ray_tune pid=398886)[0m [687]	train-mlogloss:1.51810	validation-mlogloss:1.66999
[36m(train_xgb_ray_tune pid=398912)[0m [674]	train-mlogloss:1.63715	validation-mlogloss:1.71843
[36m(train_xgb_ray_tune pid=398912)[0m [675]	train-mlogloss:1.63670	validation-mlogloss:1.71833
[36m(train_xgb_ray_tune pid=398916)[0m [661]	train-mlogloss:2.18883	validation-mlogloss:2.18878
[36m(train_xgb_ray_tune pid=398916)[0m [662]	train-mlogloss:2.18853	validation-mlogloss:2.18848
[36m(train_xgb_ray_tune pid=398894)[0m [628]	train-mlogloss:1.72485	validation-mlogloss:1.76255
[36m(train_xgb_ray_tune pid=398894)[0m [629]	train-mlogloss:1.72435	validation-mlogloss:1.76231
[36m(train_xgb_ray_tune pid=398905)[0m [695]	train-mlogloss:1.70292	validation-mlogloss:1.74395
[36m(train_xgb_ray_tune pid=398905)[0m [696]	train-mlogloss:1.70268	validation-mlogloss:1.74378
[36m(train_xgb_ray_tune pid=398901)[0m [687]	train-mlogloss:1.51052	validation-mlogloss:1.67659
[36m(train_xgb_ray_tune pid=398901)[0m [688]	train-mlogloss:1.51013	validation-mlogloss:1.67648
[36m(train_xgb_ray_tune pid=398892)[0m [730]	train-mlogloss:1.70430	validation-mlogloss:1.73593
[36m(train_xgb_ray_tune pid=398892)[0m [731]	train-mlogloss:1.70422	validation-mlogloss:1.73587
[36m(train_xgb_ray_tune pid=398886)[0m [688]	train-mlogloss:1.51776	validation-mlogloss:1.66994
[36m(train_xgb_ray_tune pid=398886)[0m [689]	train-mlogloss:1.51755	validation-mlogloss:1.66994
[36m(train_xgb_ray_tune pid=398912)[0m [676]	train-mlogloss:1.63622	validation-mlogloss:1.71825
[36m(train_xgb_ray_tune pid=398912)[0m [677]	train-mlogloss:1.63575	validation-mlogloss:1.71809
[36m(train_xgb_ray_tune pid=398916)[0m [663]	train-mlogloss:2.18823	validation-mlogloss:2.18823
[36m(train_xgb_ray_tune pid=398894)[0m [630]	train-mlogloss:1.72386	validation-mlogloss:1.76206
[36m(train_xgb_ray_tune pid=398905)[0m [697]	train-mlogloss:1.70256	validation-mlogloss:1.74374
[36m(train_xgb_ray_tune pid=398901)[0m [689]	train-mlogloss:1.50968	validation-mlogloss:1.67644
[36m(train_xgb_ray_tune pid=398892)[0m [732]	train-mlogloss:1.70407	validation-mlogloss:1.73585
[36m(train_xgb_ray_tune pid=398892)[0m [733]	train-mlogloss:1.70380	validation-mlogloss:1.73570
[36m(train_xgb_ray_tune pid=398886)[0m [690]	train-mlogloss:1.51725	validation-mlogloss:1.66998
[36m(train_xgb_ray_tune pid=398886)[0m [691]	train-mlogloss:1.51697	validation-mlogloss:1.66982
[36m(train_xgb_ray_tune pid=398912)[0m [678]	train-mlogloss:1.63530	validation-mlogloss:1.71796
[36m(train_xgb_ray_tune pid=398916)[0m [664]	train-mlogloss:2.18791	validation-mlogloss:2.18791
[36m(train_xgb_ray_tune pid=398916)[0m [665]	train-mlogloss:2.18758	validation-mlogloss:2.18759
[36m(train_xgb_ray_tune pid=398894)[0m [631]	train-mlogloss:1.72342	validation-mlogloss:1.76177
[36m(train_xgb_ray_tune pid=398894)[0m [632]	train-mlogloss:1.72296	validation-mlogloss:1.76162
[36m(train_xgb_ray_tune pid=398905)[0m [698]	train-mlogloss:1.70236	validation-mlogloss:1.74367
[36m(train_xgb_ray_tune pid=398905)[0m [699]	train-mlogloss:1.70228	validation-mlogloss:1.74365
[36m(train_xgb_ray_tune pid=398901)[0m [690]	train-mlogloss:1.50925	validation-mlogloss:1.67635
[36m(train_xgb_ray_tune pid=398901)[0m [691]	train-mlogloss:1.50885	validation-mlogloss:1.67632
[36m(train_xgb_ray_tune pid=398892)[0m [734]	train-mlogloss:1.70371	validation-mlogloss:1.73561
[36m(train_xgb_ray_tune pid=398892)[0m [735]	train-mlogloss:1.70354	validation-mlogloss:1.73547
[36m(train_xgb_ray_tune pid=398912)[0m [679]	train-mlogloss:1.63489	validation-mlogloss:1.71782
[36m(train_xgb_ray_tune pid=398905)[0m [700]	train-mlogloss:1.70217	validation-mlogloss:1.74358
[36m(train_xgb_ray_tune pid=398886)[0m [692]	train-mlogloss:1.51654	validation-mlogloss:1.66982
[36m(train_xgb_ray_tune pid=398886)[0m [693]	train-mlogloss:1.51629	validation-mlogloss:1.66970
[36m(train_xgb_ray_tune pid=398912)[0m [680]	train-mlogloss:1.63444	validation-mlogloss:1.71772
[36m(train_xgb_ray_tune pid=398916)[0m [666]	train-mlogloss:2.18729	validation-mlogloss:2.18732
[36m(train_xgb_ray_tune pid=398916)[0m [667]	train-mlogloss:2.18699	validation-mlogloss:2.18704
[36m(train_xgb_ray_tune pid=398894)[0m [633]	train-mlogloss:1.72248	validation-mlogloss:1.76134
[36m(train_xgb_ray_tune pid=398894)[0m [634]	train-mlogloss:1.72200	validation-mlogloss:1.76104
[36m(train_xgb_ray_tune pid=398905)[0m [701]	train-mlogloss:1.70201	validation-mlogloss:1.74352
[36m(train_xgb_ray_tune pid=398905)[0m [702]	train-mlogloss:1.70195	validation-mlogloss:1.74345
[36m(train_xgb_ray_tune pid=398901)[0m [692]	train-mlogloss:1.50845	validation-mlogloss:1.67617
[36m(train_xgb_ray_tune pid=398901)[0m [693]	train-mlogloss:1.50804	validation-mlogloss:1.67613
[36m(train_xgb_ray_tune pid=398892)[0m [736]	train-mlogloss:1.70337	validation-mlogloss:1.73545
[36m(train_xgb_ray_tune pid=398892)[0m [737]	train-mlogloss:1.70321	validation-mlogloss:1.73536
[36m(train_xgb_ray_tune pid=398892)[0m [738]	train-mlogloss:1.70307	validation-mlogloss:1.73525
[36m(train_xgb_ray_tune pid=398886)[0m [694]	train-mlogloss:1.51602	validation-mlogloss:1.66955
[36m(train_xgb_ray_tune pid=398886)[0m [695]	train-mlogloss:1.51569	validation-mlogloss:1.66953
[36m(train_xgb_ray_tune pid=398912)[0m [681]	train-mlogloss:1.63403	validation-mlogloss:1.71753
[36m(train_xgb_ray_tune pid=398912)[0m [682]	train-mlogloss:1.63361	validation-mlogloss:1.71737
[36m(train_xgb_ray_tune pid=398916)[0m [668]	train-mlogloss:2.18669	validation-mlogloss:2.18678
[36m(train_xgb_ray_tune pid=398916)[0m [669]	train-mlogloss:2.18635	validation-mlogloss:2.18645
[36m(train_xgb_ray_tune pid=398894)[0m [635]	train-mlogloss:1.72152	validation-mlogloss:1.76092
[36m(train_xgb_ray_tune pid=398894)[0m [636]	train-mlogloss:1.72105	validation-mlogloss:1.76070
[36m(train_xgb_ray_tune pid=398905)[0m [703]	train-mlogloss:1.70182	validation-mlogloss:1.74339
[36m(train_xgb_ray_tune pid=398905)[0m [704]	train-mlogloss:1.70168	validation-mlogloss:1.74341
[36m(train_xgb_ray_tune pid=398901)[0m [694]	train-mlogloss:1.50766	validation-mlogloss:1.67614
[36m(train_xgb_ray_tune pid=398901)[0m [695]	train-mlogloss:1.50725	validation-mlogloss:1.67613
[36m(train_xgb_ray_tune pid=398892)[0m [739]	train-mlogloss:1.70297	validation-mlogloss:1.73524
[36m(train_xgb_ray_tune pid=398892)[0m [740]	train-mlogloss:1.70290	validation-mlogloss:1.73516
[36m(train_xgb_ray_tune pid=398886)[0m [696]	train-mlogloss:1.51541	validation-mlogloss:1.66954
[36m(train_xgb_ray_tune pid=398912)[0m [683]	train-mlogloss:1.63318	validation-mlogloss:1.71716
[36m(train_xgb_ray_tune pid=398912)[0m [684]	train-mlogloss:1.63273	validation-mlogloss:1.71700
[36m(train_xgb_ray_tune pid=398916)[0m [670]	train-mlogloss:2.18605	validation-mlogloss:2.18618
[36m(train_xgb_ray_tune pid=398894)[0m [637]	train-mlogloss:1.72059	validation-mlogloss:1.76038
[36m(train_xgb_ray_tune pid=398905)[0m [705]	train-mlogloss:1.70158	validation-mlogloss:1.74330
[36m(train_xgb_ray_tune pid=398905)[0m [706]	train-mlogloss:1.70152	validation-mlogloss:1.74332
[36m(train_xgb_ray_tune pid=398901)[0m [696]	train-mlogloss:1.50683	validation-mlogloss:1.67618
[36m(train_xgb_ray_tune pid=398901)[0m [697]	train-mlogloss:1.50642	validation-mlogloss:1.67598
[36m(train_xgb_ray_tune pid=398892)[0m [741]	train-mlogloss:1.70284	validation-mlogloss:1.73506
[36m(train_xgb_ray_tune pid=398892)[0m [742]	train-mlogloss:1.70264	validation-mlogloss:1.73497
[36m(train_xgb_ray_tune pid=398886)[0m [697]	train-mlogloss:1.51512	validation-mlogloss:1.66961
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[36m(train_xgb_ray_tune pid=398912)[0m [685]	train-mlogloss:1.63227	validation-mlogloss:1.71683
[36m(train_xgb_ray_tune pid=398912)[0m [686]	train-mlogloss:1.63186	validation-mlogloss:1.71675
[36m(train_xgb_ray_tune pid=398916)[0m [671]	train-mlogloss:2.18572	validation-mlogloss:2.18586
[36m(train_xgb_ray_tune pid=398916)[0m [672]	train-mlogloss:2.18540	validation-mlogloss:2.18555
[36m(train_xgb_ray_tune pid=398894)[0m [638]	train-mlogloss:1.72009	validation-mlogloss:1.76025
[36m(train_xgb_ray_tune pid=398894)[0m [639]	train-mlogloss:1.71964	validation-mlogloss:1.75997
[36m(train_xgb_ray_tune pid=398905)[0m [707]	train-mlogloss:1.70146	validation-mlogloss:1.74329
[36m(train_xgb_ray_tune pid=398905)[0m [708]	train-mlogloss:1.70139	validation-mlogloss:1.74323
[36m(train_xgb_ray_tune pid=398901)[0m [698]	train-mlogloss:1.50603	validation-mlogloss:1.67593
[36m(train_xgb_ray_tune pid=398892)[0m [743]	train-mlogloss:1.70253	validation-mlogloss:1.73496
[36m(train_xgb_ray_tune pid=398892)[0m [744]	train-mlogloss:1.70238	validation-mlogloss:1.73482
[36m(train_xgb_ray_tune pid=398886)[0m [699]	train-mlogloss:1.51455	validation-mlogloss:1.66953
[36m(train_xgb_ray_tune pid=398901)[0m [699]	train-mlogloss:1.50562	validation-mlogloss:1.67589
[36m(train_xgb_ray_tune pid=398886)[0m [700]	train-mlogloss:1.51419	validation-mlogloss:1.66934
[36m(train_xgb_ray_tune pid=398912)[0m [687]	train-mlogloss:1.63143	validation-mlogloss:1.71661
[36m(train_xgb_ray_tune pid=398916)[0m [673]	train-mlogloss:2.18509	validation-mlogloss:2.18530
[36m(train_xgb_ray_tune pid=398916)[0m [674]	train-mlogloss:2.18476	validation-mlogloss:2.18495
[36m(train_xgb_ray_tune pid=398894)[0m [640]	train-mlogloss:1.71913	validation-mlogloss:1.75957
[36m(train_xgb_ray_tune pid=398905)[0m [709]	train-mlogloss:1.70126	validation-mlogloss:1.74321
[36m(train_xgb_ray_tune pid=398905)[0m [710]	train-mlogloss:1.70115	validation-mlogloss:1.74315
[36m(train_xgb_ray_tune pid=398901)[0m [700]	train-mlogloss:1.50522	validation-mlogloss:1.67568
[36m(train_xgb_ray_tune pid=398892)[0m [745]	train-mlogloss:1.70223	validation-mlogloss:1.73480
[36m(train_xgb_ray_tune pid=398892)[0m [746]	train-mlogloss:1.70212	validation-mlogloss:1.73478
[36m(train_xgb_ray_tune pid=398886)[0m [701]	train-mlogloss:1.51396	validation-mlogloss:1.66930
[36m(train_xgb_ray_tune pid=398912)[0m [688]	train-mlogloss:1.63105	validation-mlogloss:1.71650
[36m(train_xgb_ray_tune pid=398894)[0m [641]	train-mlogloss:1.71865	validation-mlogloss:1.75931
[36m(train_xgb_ray_tune pid=398886)[0m [702]	train-mlogloss:1.51375	validation-mlogloss:1.66932
[36m(train_xgb_ray_tune pid=398912)[0m [689]	train-mlogloss:1.63060	validation-mlogloss:1.71631
[36m(train_xgb_ray_tune pid=398916)[0m [675]	train-mlogloss:2.18443	validation-mlogloss:2.18462
[36m(train_xgb_ray_tune pid=398916)[0m [676]	train-mlogloss:2.18412	validation-mlogloss:2.18432
[36m(train_xgb_ray_tune pid=398894)[0m [642]	train-mlogloss:1.71812	validation-mlogloss:1.75907
[36m(train_xgb_ray_tune pid=398905)[0m [711]	train-mlogloss:1.70101	validation-mlogloss:1.74311
[36m(train_xgb_ray_tune pid=398905)[0m [712]	train-mlogloss:1.70096	validation-mlogloss:1.74308
[36m(train_xgb_ray_tune pid=398901)[0m [701]	train-mlogloss:1.50479	validation-mlogloss:1.67562
[36m(train_xgb_ray_tune pid=398901)[0m [702]	train-mlogloss:1.50437	validation-mlogloss:1.67546
[36m(train_xgb_ray_tune pid=398892)[0m [747]	train-mlogloss:1.70198	validation-mlogloss:1.73468
[36m(train_xgb_ray_tune pid=398892)[0m [748]	train-mlogloss:1.70184	validation-mlogloss:1.73463
[36m(train_xgb_ray_tune pid=398886)[0m [703]	train-mlogloss:1.51338	validation-mlogloss:1.66935
[36m(train_xgb_ray_tune pid=398892)[0m [749]	train-mlogloss:1.70175	validation-mlogloss:1.73461

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:28. Total running time: 2min 13s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             130.233 │
│ time_total_s                 130.233 │
│ training_iteration                 1 │
│ validation_accuracy          0.51697 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:28. Total running time: 2min 13s
[36m(train_xgb_ray_tune pid=398886)[0m [704]	train-mlogloss:1.51311	validation-mlogloss:1.66933
[36m(train_xgb_ray_tune pid=398886)[0m [705]	train-mlogloss:1.51289	validation-mlogloss:1.66914
[36m(train_xgb_ray_tune pid=398912)[0m [690]	train-mlogloss:1.63019	validation-mlogloss:1.71618
[36m(train_xgb_ray_tune pid=398912)[0m [691]	train-mlogloss:1.62976	validation-mlogloss:1.71603
[36m(train_xgb_ray_tune pid=398916)[0m [677]	train-mlogloss:2.18382	validation-mlogloss:2.18405
[36m(train_xgb_ray_tune pid=398894)[0m [643]	train-mlogloss:1.71763	validation-mlogloss:1.75893
[36m(train_xgb_ray_tune pid=398894)[0m [644]	train-mlogloss:1.71715	validation-mlogloss:1.75872
[36m(train_xgb_ray_tune pid=398905)[0m [713]	train-mlogloss:1.70081	validation-mlogloss:1.74303
[36m(train_xgb_ray_tune pid=398905)[0m [714]	train-mlogloss:1.70070	validation-mlogloss:1.74301
[36m(train_xgb_ray_tune pid=398901)[0m [703]	train-mlogloss:1.50399	validation-mlogloss:1.67546
[36m(train_xgb_ray_tune pid=398901)[0m [704]	train-mlogloss:1.50363	validation-mlogloss:1.67529
[36m(train_xgb_ray_tune pid=398892)[0m [750]	train-mlogloss:1.70167	validation-mlogloss:1.73460
[36m(train_xgb_ray_tune pid=398892)[0m [751]	train-mlogloss:1.70147	validation-mlogloss:1.73448
[36m(train_xgb_ray_tune pid=398886)[0m [706]	train-mlogloss:1.51261	validation-mlogloss:1.66914
[36m(train_xgb_ray_tune pid=398886)[0m [707]	train-mlogloss:1.51236	validation-mlogloss:1.66909
[36m(train_xgb_ray_tune pid=398912)[0m [692]	train-mlogloss:1.62934	validation-mlogloss:1.71595
[36m(train_xgb_ray_tune pid=398912)[0m [693]	train-mlogloss:1.62890	validation-mlogloss:1.71576
[36m(train_xgb_ray_tune pid=398916)[0m [678]	train-mlogloss:2.18353	validation-mlogloss:2.18381
[36m(train_xgb_ray_tune pid=398916)[0m [679]	train-mlogloss:2.18322	validation-mlogloss:2.18349
[36m(train_xgb_ray_tune pid=398894)[0m [645]	train-mlogloss:1.71663	validation-mlogloss:1.75838
[36m(train_xgb_ray_tune pid=398894)[0m [646]	train-mlogloss:1.71617	validation-mlogloss:1.75820
[36m(train_xgb_ray_tune pid=398905)[0m [715]	train-mlogloss:1.70058	validation-mlogloss:1.74294
[36m(train_xgb_ray_tune pid=398905)[0m [716]	train-mlogloss:1.70054	validation-mlogloss:1.74293
[36m(train_xgb_ray_tune pid=398901)[0m [705]	train-mlogloss:1.50325	validation-mlogloss:1.67521
[36m(train_xgb_ray_tune pid=398901)[0m [706]	train-mlogloss:1.50288	validation-mlogloss:1.67493
[36m(train_xgb_ray_tune pid=398892)[0m [752]	train-mlogloss:1.70136	validation-mlogloss:1.73437
[36m(train_xgb_ray_tune pid=398892)[0m [753]	train-mlogloss:1.70127	validation-mlogloss:1.73434
[36m(train_xgb_ray_tune pid=398886)[0m [708]	train-mlogloss:1.51212	validation-mlogloss:1.66913
[36m(train_xgb_ray_tune pid=398912)[0m [694]	train-mlogloss:1.62851	validation-mlogloss:1.71556
[36m(train_xgb_ray_tune pid=398912)[0m [695]	train-mlogloss:1.62809	validation-mlogloss:1.71531
[36m(train_xgb_ray_tune pid=398916)[0m [680]	train-mlogloss:2.18291	validation-mlogloss:2.18318
[36m(train_xgb_ray_tune pid=398916)[0m [681]	train-mlogloss:2.18256	validation-mlogloss:2.18279
[36m(train_xgb_ray_tune pid=398894)[0m [647]	train-mlogloss:1.71569	validation-mlogloss:1.75794
[36m(train_xgb_ray_tune pid=398905)[0m [717]	train-mlogloss:1.70046	validation-mlogloss:1.74293
[36m(train_xgb_ray_tune pid=398905)[0m [718]	train-mlogloss:1.70029	validation-mlogloss:1.74285
[36m(train_xgb_ray_tune pid=398901)[0m [707]	train-mlogloss:1.50251	validation-mlogloss:1.67470
[36m(train_xgb_ray_tune pid=398901)[0m [708]	train-mlogloss:1.50209	validation-mlogloss:1.67466
[36m(train_xgb_ray_tune pid=398892)[0m [754]	train-mlogloss:1.70124	validation-mlogloss:1.73434
[36m(train_xgb_ray_tune pid=398892)[0m [755]	train-mlogloss:1.70110	validation-mlogloss:1.73421
[36m(train_xgb_ray_tune pid=398886)[0m [709]	train-mlogloss:1.51180	validation-mlogloss:1.66909
[36m(train_xgb_ray_tune pid=398905)[0m [719]	train-mlogloss:1.70018	validation-mlogloss:1.74282
[36m(train_xgb_ray_tune pid=398886)[0m [710]	train-mlogloss:1.51149	validation-mlogloss:1.66898
[36m(train_xgb_ray_tune pid=398912)[0m [696]	train-mlogloss:1.62768	validation-mlogloss:1.71522
[36m(train_xgb_ray_tune pid=398916)[0m [682]	train-mlogloss:2.18223	validation-mlogloss:2.18245
[36m(train_xgb_ray_tune pid=398916)[0m [683]	train-mlogloss:2.18190	validation-mlogloss:2.18213
[36m(train_xgb_ray_tune pid=398894)[0m [648]	train-mlogloss:1.71521	validation-mlogloss:1.75763
[36m(train_xgb_ray_tune pid=398894)[0m [649]	train-mlogloss:1.71472	validation-mlogloss:1.75738
[36m(train_xgb_ray_tune pid=398905)[0m [720]	train-mlogloss:1.70007	validation-mlogloss:1.74267
[36m(train_xgb_ray_tune pid=398905)[0m [721]	train-mlogloss:1.69994	validation-mlogloss:1.74262
[36m(train_xgb_ray_tune pid=398901)[0m [709]	train-mlogloss:1.50169	validation-mlogloss:1.67469
[36m(train_xgb_ray_tune pid=398901)[0m [710]	train-mlogloss:1.50128	validation-mlogloss:1.67451
[36m(train_xgb_ray_tune pid=398892)[0m [756]	train-mlogloss:1.70100	validation-mlogloss:1.73422
[36m(train_xgb_ray_tune pid=398892)[0m [757]	train-mlogloss:1.70089	validation-mlogloss:1.73413
[36m(train_xgb_ray_tune pid=398892)[0m [758]	train-mlogloss:1.70074	validation-mlogloss:1.73411
[36m(train_xgb_ray_tune pid=398886)[0m [711]	train-mlogloss:1.51116	validation-mlogloss:1.66885
[36m(train_xgb_ray_tune pid=398886)[0m [712]	train-mlogloss:1.51093	validation-mlogloss:1.66865
[36m(train_xgb_ray_tune pid=398912)[0m [697]	train-mlogloss:1.62730	validation-mlogloss:1.71500
[36m(train_xgb_ray_tune pid=398912)[0m [698]	train-mlogloss:1.62689	validation-mlogloss:1.71489
[36m(train_xgb_ray_tune pid=398916)[0m [684]	train-mlogloss:2.18158	validation-mlogloss:2.18180
[36m(train_xgb_ray_tune pid=398894)[0m [650]	train-mlogloss:1.71422	validation-mlogloss:1.75708
[36m(train_xgb_ray_tune pid=398894)[0m [651]	train-mlogloss:1.71377	validation-mlogloss:1.75686
[36m(train_xgb_ray_tune pid=398905)[0m [722]	train-mlogloss:1.69985	validation-mlogloss:1.74260
[36m(train_xgb_ray_tune pid=398905)[0m [723]	train-mlogloss:1.69959	validation-mlogloss:1.74239
[36m(train_xgb_ray_tune pid=398901)[0m [711]	train-mlogloss:1.50090	validation-mlogloss:1.67453
[36m(train_xgb_ray_tune pid=398901)[0m [712]	train-mlogloss:1.50047	validation-mlogloss:1.67433
[36m(train_xgb_ray_tune pid=398892)[0m [759]	train-mlogloss:1.70063	validation-mlogloss:1.73409
[36m(train_xgb_ray_tune pid=398892)[0m [760]	train-mlogloss:1.70049	validation-mlogloss:1.73406
[36m(train_xgb_ray_tune pid=398916)[0m [685]	train-mlogloss:2.18129	validation-mlogloss:2.18151
[36m(train_xgb_ray_tune pid=398886)[0m [713]	train-mlogloss:1.51064	validation-mlogloss:1.66867
[36m(train_xgb_ray_tune pid=398886)[0m [714]	train-mlogloss:1.51051	validation-mlogloss:1.66868
[36m(train_xgb_ray_tune pid=398886)[0m [715]	train-mlogloss:1.51023	validation-mlogloss:1.66877
[36m(train_xgb_ray_tune pid=398912)[0m [699]	train-mlogloss:1.62651	validation-mlogloss:1.71471
[36m(train_xgb_ray_tune pid=398912)[0m [700]	train-mlogloss:1.62614	validation-mlogloss:1.71460
[36m(train_xgb_ray_tune pid=398916)[0m [686]	train-mlogloss:2.18100	validation-mlogloss:2.18121
[36m(train_xgb_ray_tune pid=398894)[0m [652]	train-mlogloss:1.71330	validation-mlogloss:1.75656
[36m(train_xgb_ray_tune pid=398894)[0m [653]	train-mlogloss:1.71281	validation-mlogloss:1.75636
[36m(train_xgb_ray_tune pid=398905)[0m [724]	train-mlogloss:1.69945	validation-mlogloss:1.74234
[36m(train_xgb_ray_tune pid=398905)[0m [725]	train-mlogloss:1.69938	validation-mlogloss:1.74230
[36m(train_xgb_ray_tune pid=398901)[0m [713]	train-mlogloss:1.50007	validation-mlogloss:1.67418
[36m(train_xgb_ray_tune pid=398901)[0m [714]	train-mlogloss:1.49969	validation-mlogloss:1.67409
[36m(train_xgb_ray_tune pid=398892)[0m [761]	train-mlogloss:1.70037	validation-mlogloss:1.73406
[36m(train_xgb_ray_tune pid=398892)[0m [762]	train-mlogloss:1.70018	validation-mlogloss:1.73396
[36m(train_xgb_ray_tune pid=398886)[0m [716]	train-mlogloss:1.50994	validation-mlogloss:1.66873
[36m(train_xgb_ray_tune pid=398886)[0m [717]	train-mlogloss:1.50964	validation-mlogloss:1.66869
[36m(train_xgb_ray_tune pid=398912)[0m [701]	train-mlogloss:1.62571	validation-mlogloss:1.71444
[36m(train_xgb_ray_tune pid=398912)[0m [702]	train-mlogloss:1.62528	validation-mlogloss:1.71415
[36m(train_xgb_ray_tune pid=398916)[0m [687]	train-mlogloss:2.18070	validation-mlogloss:2.18089
[36m(train_xgb_ray_tune pid=398916)[0m [688]	train-mlogloss:2.18040	validation-mlogloss:2.18065
[36m(train_xgb_ray_tune pid=398894)[0m [654]	train-mlogloss:1.71235	validation-mlogloss:1.75612
[36m(train_xgb_ray_tune pid=398905)[0m [726]	train-mlogloss:1.69922	validation-mlogloss:1.74215
[36m(train_xgb_ray_tune pid=398905)[0m [727]	train-mlogloss:1.69908	validation-mlogloss:1.74204
[36m(train_xgb_ray_tune pid=398901)[0m [715]	train-mlogloss:1.49926	validation-mlogloss:1.67405
[36m(train_xgb_ray_tune pid=398901)[0m [716]	train-mlogloss:1.49885	validation-mlogloss:1.67393
[36m(train_xgb_ray_tune pid=398892)[0m [763]	train-mlogloss:1.70009	validation-mlogloss:1.73392
[36m(train_xgb_ray_tune pid=398892)[0m [764]	train-mlogloss:1.69997	validation-mlogloss:1.73386
[36m(train_xgb_ray_tune pid=398894)[0m [655]	train-mlogloss:1.71188	validation-mlogloss:1.75577
[36m(train_xgb_ray_tune pid=398892)[0m [765]	train-mlogloss:1.69987	validation-mlogloss:1.73384
[36m(train_xgb_ray_tune pid=398886)[0m [718]	train-mlogloss:1.50942	validation-mlogloss:1.66872
[36m(train_xgb_ray_tune pid=398886)[0m [719]	train-mlogloss:1.50908	validation-mlogloss:1.66876
[36m(train_xgb_ray_tune pid=398912)[0m [703]	train-mlogloss:1.62489	validation-mlogloss:1.71399
[36m(train_xgb_ray_tune pid=398912)[0m [704]	train-mlogloss:1.62448	validation-mlogloss:1.71394
[36m(train_xgb_ray_tune pid=398916)[0m [689]	train-mlogloss:2.18012	validation-mlogloss:2.18039
[36m(train_xgb_ray_tune pid=398916)[0m [690]	train-mlogloss:2.17982	validation-mlogloss:2.18009
[36m(train_xgb_ray_tune pid=398894)[0m [656]	train-mlogloss:1.71140	validation-mlogloss:1.75562
[36m(train_xgb_ray_tune pid=398905)[0m [728]	train-mlogloss:1.69896	validation-mlogloss:1.74200
[36m(train_xgb_ray_tune pid=398905)[0m [729]	train-mlogloss:1.69890	validation-mlogloss:1.74203
[36m(train_xgb_ray_tune pid=398901)[0m [717]	train-mlogloss:1.49843	validation-mlogloss:1.67400
[36m(train_xgb_ray_tune pid=398901)[0m [718]	train-mlogloss:1.49797	validation-mlogloss:1.67394
[36m(train_xgb_ray_tune pid=398892)[0m [766]	train-mlogloss:1.69974	validation-mlogloss:1.73373
[36m(train_xgb_ray_tune pid=398892)[0m [767]	train-mlogloss:1.69955	validation-mlogloss:1.73363
[36m(train_xgb_ray_tune pid=398886)[0m [720]	train-mlogloss:1.50876	validation-mlogloss:1.66876
[36m(train_xgb_ray_tune pid=398886)[0m [721]	train-mlogloss:1.50853	validation-mlogloss:1.66872
[36m(train_xgb_ray_tune pid=398912)[0m [705]	train-mlogloss:1.62407	validation-mlogloss:1.71376
[36m(train_xgb_ray_tune pid=398912)[0m [706]	train-mlogloss:1.62363	validation-mlogloss:1.71363
[36m(train_xgb_ray_tune pid=398916)[0m [691]	train-mlogloss:2.17952	validation-mlogloss:2.17980
[36m(train_xgb_ray_tune pid=398916)[0m [692]	train-mlogloss:2.17921	validation-mlogloss:2.17952
[36m(train_xgb_ray_tune pid=398894)[0m [657]	train-mlogloss:1.71094	validation-mlogloss:1.75539
[36m(train_xgb_ray_tune pid=398894)[0m [658]	train-mlogloss:1.71048	validation-mlogloss:1.75511
[36m(train_xgb_ray_tune pid=398905)[0m [730]	train-mlogloss:1.69876	validation-mlogloss:1.74185
[36m(train_xgb_ray_tune pid=398905)[0m [731]	train-mlogloss:1.69862	validation-mlogloss:1.74176
[36m(train_xgb_ray_tune pid=398901)[0m [719]	train-mlogloss:1.49751	validation-mlogloss:1.67389
[36m(train_xgb_ray_tune pid=398901)[0m [720]	train-mlogloss:1.49709	validation-mlogloss:1.67390
[36m(train_xgb_ray_tune pid=398892)[0m [768]	train-mlogloss:1.69943	validation-mlogloss:1.73362
[36m(train_xgb_ray_tune pid=398892)[0m [769]	train-mlogloss:1.69931	validation-mlogloss:1.73353
[36m(train_xgb_ray_tune pid=398886)[0m [722]	train-mlogloss:1.50827	validation-mlogloss:1.66862
[36m(train_xgb_ray_tune pid=398886)[0m [723]	train-mlogloss:1.50797	validation-mlogloss:1.66873
[36m(train_xgb_ray_tune pid=398912)[0m [707]	train-mlogloss:1.62322	validation-mlogloss:1.71345
[36m(train_xgb_ray_tune pid=398912)[0m [708]	train-mlogloss:1.62279	validation-mlogloss:1.71338
[36m(train_xgb_ray_tune pid=398916)[0m [693]	train-mlogloss:2.17891	validation-mlogloss:2.17920
[36m(train_xgb_ray_tune pid=398916)[0m [694]	train-mlogloss:2.17861	validation-mlogloss:2.17894
[36m(train_xgb_ray_tune pid=398894)[0m [659]	train-mlogloss:1.71000	validation-mlogloss:1.75486
[36m(train_xgb_ray_tune pid=398894)[0m [660]	train-mlogloss:1.70950	validation-mlogloss:1.75461
[36m(train_xgb_ray_tune pid=398905)[0m [732]	train-mlogloss:1.69843	validation-mlogloss:1.74168
[36m(train_xgb_ray_tune pid=398905)[0m [733]	train-mlogloss:1.69826	validation-mlogloss:1.74157
[36m(train_xgb_ray_tune pid=398901)[0m [721]	train-mlogloss:1.49670	validation-mlogloss:1.67378
[36m(train_xgb_ray_tune pid=398901)[0m [722]	train-mlogloss:1.49627	validation-mlogloss:1.67377
[36m(train_xgb_ray_tune pid=398892)[0m [770]	train-mlogloss:1.69922	validation-mlogloss:1.73345
[36m(train_xgb_ray_tune pid=398892)[0m [771]	train-mlogloss:1.69917	validation-mlogloss:1.73346
[36m(train_xgb_ray_tune pid=398892)[0m [772]	train-mlogloss:1.69906	validation-mlogloss:1.73337
[36m(train_xgb_ray_tune pid=398905)[0m [734]	train-mlogloss:1.69813	validation-mlogloss:1.74148
[36m(train_xgb_ray_tune pid=398886)[0m [724]	train-mlogloss:1.50769	validation-mlogloss:1.66879
[36m(train_xgb_ray_tune pid=398886)[0m [725]	train-mlogloss:1.50745	validation-mlogloss:1.66871
[36m(train_xgb_ray_tune pid=398912)[0m [709]	train-mlogloss:1.62237	validation-mlogloss:1.71311
[36m(train_xgb_ray_tune pid=398912)[0m [710]	train-mlogloss:1.62195	validation-mlogloss:1.71318
[36m(train_xgb_ray_tune pid=398916)[0m [695]	train-mlogloss:2.17831	validation-mlogloss:2.17869
[36m(train_xgb_ray_tune pid=398916)[0m [696]	train-mlogloss:2.17799	validation-mlogloss:2.17837
[36m(train_xgb_ray_tune pid=398894)[0m [661]	train-mlogloss:1.70905	validation-mlogloss:1.75436
[36m(train_xgb_ray_tune pid=398894)[0m [662]	train-mlogloss:1.70856	validation-mlogloss:1.75408
[36m(train_xgb_ray_tune pid=398905)[0m [735]	train-mlogloss:1.69807	validation-mlogloss:1.74141
[36m(train_xgb_ray_tune pid=398905)[0m [736]	train-mlogloss:1.69795	validation-mlogloss:1.74130
[36m(train_xgb_ray_tune pid=398901)[0m [723]	train-mlogloss:1.49591	validation-mlogloss:1.67359
[36m(train_xgb_ray_tune pid=398901)[0m [724]	train-mlogloss:1.49551	validation-mlogloss:1.67338
[36m(train_xgb_ray_tune pid=398892)[0m [773]	train-mlogloss:1.69900	validation-mlogloss:1.73336
[36m(train_xgb_ray_tune pid=398892)[0m [774]	train-mlogloss:1.69886	validation-mlogloss:1.73328
[36m(train_xgb_ray_tune pid=398886)[0m [726]	train-mlogloss:1.50719	validation-mlogloss:1.66863
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[36m(train_xgb_ray_tune pid=398912)[0m [711]	train-mlogloss:1.62156	validation-mlogloss:1.71303
[36m(train_xgb_ray_tune pid=398912)[0m [712]	train-mlogloss:1.62115	validation-mlogloss:1.71293
[36m(train_xgb_ray_tune pid=398916)[0m [697]	train-mlogloss:2.17766	validation-mlogloss:2.17801
[36m(train_xgb_ray_tune pid=398916)[0m [698]	train-mlogloss:2.17739	validation-mlogloss:2.17775
[36m(train_xgb_ray_tune pid=398894)[0m [663]	train-mlogloss:1.70808	validation-mlogloss:1.75387
[36m(train_xgb_ray_tune pid=398894)[0m [664]	train-mlogloss:1.70766	validation-mlogloss:1.75371
[36m(train_xgb_ray_tune pid=398905)[0m [737]	train-mlogloss:1.69789	validation-mlogloss:1.74127
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[36m(train_xgb_ray_tune pid=398892)[0m [775]	train-mlogloss:1.69879	validation-mlogloss:1.73321
[36m(train_xgb_ray_tune pid=398892)[0m [776]	train-mlogloss:1.69866	validation-mlogloss:1.73314
[36m(train_xgb_ray_tune pid=398892)[0m [777]	train-mlogloss:1.69857	validation-mlogloss:1.73306
[36m(train_xgb_ray_tune pid=398886)[0m [728]	train-mlogloss:1.50663	validation-mlogloss:1.66838
[36m(train_xgb_ray_tune pid=398886)[0m [729]	train-mlogloss:1.50641	validation-mlogloss:1.66840
[36m(train_xgb_ray_tune pid=398912)[0m [713]	train-mlogloss:1.62078	validation-mlogloss:1.71292
[36m(train_xgb_ray_tune pid=398912)[0m [714]	train-mlogloss:1.62034	validation-mlogloss:1.71280
[36m(train_xgb_ray_tune pid=398916)[0m [699]	train-mlogloss:2.17707	validation-mlogloss:2.17743
[36m(train_xgb_ray_tune pid=398894)[0m [665]	train-mlogloss:1.70716	validation-mlogloss:1.75350
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[36m(train_xgb_ray_tune pid=398905)[0m [740]	train-mlogloss:1.69756	validation-mlogloss:1.74101
[36m(train_xgb_ray_tune pid=398892)[0m [778]	train-mlogloss:1.69850	validation-mlogloss:1.73301
[36m(train_xgb_ray_tune pid=398892)[0m [779]	train-mlogloss:1.69838	validation-mlogloss:1.73292
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[36m(train_xgb_ray_tune pid=398912)[0m [715]	train-mlogloss:1.61993	validation-mlogloss:1.71269
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[36m(train_xgb_ray_tune pid=398916)[0m [700]	train-mlogloss:2.17678	validation-mlogloss:2.17719
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[36m(train_xgb_ray_tune pid=398894)[0m [666]	train-mlogloss:1.70671	validation-mlogloss:1.75339
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[36m(train_xgb_ray_tune pid=398905)[0m [741]	train-mlogloss:1.69747	validation-mlogloss:1.74099
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[36m(train_xgb_ray_tune pid=398892)[0m [780]	train-mlogloss:1.69828	validation-mlogloss:1.73285
[36m(train_xgb_ray_tune pid=398892)[0m [781]	train-mlogloss:1.69815	validation-mlogloss:1.73279
[36m(train_xgb_ray_tune pid=398892)[0m [782]	train-mlogloss:1.69801	validation-mlogloss:1.73267
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[36m(train_xgb_ray_tune pid=398912)[0m [717]	train-mlogloss:1.61910	validation-mlogloss:1.71245
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[36m(train_xgb_ray_tune pid=398916)[0m [702]	train-mlogloss:2.17615	validation-mlogloss:2.17652
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[36m(train_xgb_ray_tune pid=398894)[0m [668]	train-mlogloss:1.70578	validation-mlogloss:1.75301
[36m(train_xgb_ray_tune pid=398894)[0m [669]	train-mlogloss:1.70531	validation-mlogloss:1.75288
[36m(train_xgb_ray_tune pid=398905)[0m [744]	train-mlogloss:1.69711	validation-mlogloss:1.74080
[36m(train_xgb_ray_tune pid=398905)[0m [745]	train-mlogloss:1.69703	validation-mlogloss:1.74082
[36m(train_xgb_ray_tune pid=398892)[0m [783]	train-mlogloss:1.69790	validation-mlogloss:1.73252
[36m(train_xgb_ray_tune pid=398892)[0m [784]	train-mlogloss:1.69777	validation-mlogloss:1.73250
[36m(train_xgb_ray_tune pid=398886)[0m [735]	train-mlogloss:1.50504	validation-mlogloss:1.66797
[36m(train_xgb_ray_tune pid=398886)[0m [736]	train-mlogloss:1.50482	validation-mlogloss:1.66792
[36m(train_xgb_ray_tune pid=398912)[0m [719]	train-mlogloss:1.61827	validation-mlogloss:1.71209
[36m(train_xgb_ray_tune pid=398912)[0m [720]	train-mlogloss:1.61784	validation-mlogloss:1.71193
[36m(train_xgb_ray_tune pid=398916)[0m [704]	train-mlogloss:2.17555	validation-mlogloss:2.17588
[36m(train_xgb_ray_tune pid=398916)[0m [705]	train-mlogloss:2.17521	validation-mlogloss:2.17552
[36m(train_xgb_ray_tune pid=398894)[0m [670]	train-mlogloss:1.70487	validation-mlogloss:1.75264
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[36m(train_xgb_ray_tune pid=398905)[0m [747]	train-mlogloss:1.69687	validation-mlogloss:1.74076
[36m(train_xgb_ray_tune pid=398892)[0m [785]	train-mlogloss:1.69772	validation-mlogloss:1.73249
[36m(train_xgb_ray_tune pid=398892)[0m [786]	train-mlogloss:1.69764	validation-mlogloss:1.73248
[36m(train_xgb_ray_tune pid=398892)[0m [787]	train-mlogloss:1.69748	validation-mlogloss:1.73229
[36m(train_xgb_ray_tune pid=398886)[0m [737]	train-mlogloss:1.50454	validation-mlogloss:1.66802
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[36m(train_xgb_ray_tune pid=398912)[0m [721]	train-mlogloss:1.61745	validation-mlogloss:1.71170
[36m(train_xgb_ray_tune pid=398912)[0m [722]	train-mlogloss:1.61702	validation-mlogloss:1.71148
[36m(train_xgb_ray_tune pid=398916)[0m [706]	train-mlogloss:2.17495	validation-mlogloss:2.17531
[36m(train_xgb_ray_tune pid=398916)[0m [707]	train-mlogloss:2.17466	validation-mlogloss:2.17505
[36m(train_xgb_ray_tune pid=398894)[0m [672]	train-mlogloss:1.70395	validation-mlogloss:1.75220
[36m(train_xgb_ray_tune pid=398894)[0m [673]	train-mlogloss:1.70348	validation-mlogloss:1.75197
[36m(train_xgb_ray_tune pid=398905)[0m [748]	train-mlogloss:1.69674	validation-mlogloss:1.74069
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[36m(train_xgb_ray_tune pid=398905)[0m [750]	train-mlogloss:1.69662	validation-mlogloss:1.74060
[36m(train_xgb_ray_tune pid=398892)[0m [788]	train-mlogloss:1.69737	validation-mlogloss:1.73230
[36m(train_xgb_ray_tune pid=398892)[0m [789]	train-mlogloss:1.69728	validation-mlogloss:1.73223
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[36m(train_xgb_ray_tune pid=398912)[0m [723]	train-mlogloss:1.61663	validation-mlogloss:1.71147
[36m(train_xgb_ray_tune pid=398912)[0m [724]	train-mlogloss:1.61622	validation-mlogloss:1.71143
[36m(train_xgb_ray_tune pid=398916)[0m [708]	train-mlogloss:2.17435	validation-mlogloss:2.17476
[36m(train_xgb_ray_tune pid=398916)[0m [709]	train-mlogloss:2.17407	validation-mlogloss:2.17449
[36m(train_xgb_ray_tune pid=398894)[0m [674]	train-mlogloss:1.70306	validation-mlogloss:1.75171
[36m(train_xgb_ray_tune pid=398894)[0m [675]	train-mlogloss:1.70262	validation-mlogloss:1.75142
[36m(train_xgb_ray_tune pid=398905)[0m [751]	train-mlogloss:1.69654	validation-mlogloss:1.74060
[36m(train_xgb_ray_tune pid=398905)[0m [752]	train-mlogloss:1.69650	validation-mlogloss:1.74055
[36m(train_xgb_ray_tune pid=398892)[0m [790]	train-mlogloss:1.69712	validation-mlogloss:1.73213
[36m(train_xgb_ray_tune pid=398892)[0m [791]	train-mlogloss:1.69697	validation-mlogloss:1.73206
[36m(train_xgb_ray_tune pid=398892)[0m [792]	train-mlogloss:1.69683	validation-mlogloss:1.73201
[36m(train_xgb_ray_tune pid=398886)[0m [741]	train-mlogloss:1.50346	validation-mlogloss:1.66779
[36m(train_xgb_ray_tune pid=398886)[0m [742]	train-mlogloss:1.50319	validation-mlogloss:1.66767
[36m(train_xgb_ray_tune pid=398886)[0m [743]	train-mlogloss:1.50299	validation-mlogloss:1.66774
[36m(train_xgb_ray_tune pid=398912)[0m [725]	train-mlogloss:1.61582	validation-mlogloss:1.71130
[36m(train_xgb_ray_tune pid=398912)[0m [726]	train-mlogloss:1.61544	validation-mlogloss:1.71117
[36m(train_xgb_ray_tune pid=398916)[0m [710]	train-mlogloss:2.17383	validation-mlogloss:2.17427
[36m(train_xgb_ray_tune pid=398916)[0m [711]	train-mlogloss:2.17355	validation-mlogloss:2.17404
[36m(train_xgb_ray_tune pid=398894)[0m [676]	train-mlogloss:1.70216	validation-mlogloss:1.75122
[36m(train_xgb_ray_tune pid=398894)[0m [677]	train-mlogloss:1.70170	validation-mlogloss:1.75092
[36m(train_xgb_ray_tune pid=398905)[0m [753]	train-mlogloss:1.69643	validation-mlogloss:1.74052
[36m(train_xgb_ray_tune pid=398905)[0m [754]	train-mlogloss:1.69634	validation-mlogloss:1.74052
[36m(train_xgb_ray_tune pid=398905)[0m [755]	train-mlogloss:1.69619	validation-mlogloss:1.74042
[36m(train_xgb_ray_tune pid=398892)[0m [793]	train-mlogloss:1.69669	validation-mlogloss:1.73202
[36m(train_xgb_ray_tune pid=398892)[0m [794]	train-mlogloss:1.69667	validation-mlogloss:1.73199

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:30. Total running time: 2min 15s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             132.021 │
│ time_total_s                 132.021 │
│ training_iteration                 1 │
│ validation_accuracy          0.52511 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:30. Total running time: 2min 15s
[36m(train_xgb_ray_tune pid=398886)[0m [744]	train-mlogloss:1.50276	validation-mlogloss:1.66774
[36m(train_xgb_ray_tune pid=398886)[0m [745]	train-mlogloss:1.50241	validation-mlogloss:1.66760
[36m(train_xgb_ray_tune pid=398912)[0m [727]	train-mlogloss:1.61509	validation-mlogloss:1.71112
[36m(train_xgb_ray_tune pid=398912)[0m [728]	train-mlogloss:1.61466	validation-mlogloss:1.71091
[36m(train_xgb_ray_tune pid=398901)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=398901)[0m   _log_deprecation_warning([32m [repeated 3x across cluster][0m
[36m(train_xgb_ray_tune pid=398916)[0m [712]	train-mlogloss:2.17323	validation-mlogloss:2.17371
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[36m(train_xgb_ray_tune pid=398912)[0m [729]	train-mlogloss:1.61427	validation-mlogloss:1.71077
[36m(train_xgb_ray_tune pid=398912)[0m [730]	train-mlogloss:1.61388	validation-mlogloss:1.71076
[36m(train_xgb_ray_tune pid=398916)[0m [714]	train-mlogloss:2.17265	validation-mlogloss:2.17314
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[36m(train_xgb_ray_tune pid=398894)[0m [680]	train-mlogloss:1.70029	validation-mlogloss:1.75049
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[36m(train_xgb_ray_tune pid=398905)[0m [758]	train-mlogloss:1.69596	validation-mlogloss:1.74032
[36m(train_xgb_ray_tune pid=398905)[0m [759]	train-mlogloss:1.69582	validation-mlogloss:1.74022
[36m(train_xgb_ray_tune pid=398892)[0m [798]	train-mlogloss:1.69628	validation-mlogloss:1.73162
[36m(train_xgb_ray_tune pid=398892)[0m [799]	train-mlogloss:1.69618	validation-mlogloss:1.73152
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[36m(train_xgb_ray_tune pid=398912)[0m [731]	train-mlogloss:1.61349	validation-mlogloss:1.71064
[36m(train_xgb_ray_tune pid=398912)[0m [732]	train-mlogloss:1.61311	validation-mlogloss:1.71058
[36m(train_xgb_ray_tune pid=398916)[0m [716]	train-mlogloss:2.17213	validation-mlogloss:2.17271
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[36m(train_xgb_ray_tune pid=398905)[0m [760]	train-mlogloss:1.69570	validation-mlogloss:1.74017
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[36m(train_xgb_ray_tune pid=398905)[0m [762]	train-mlogloss:1.69555	validation-mlogloss:1.74003
[36m(train_xgb_ray_tune pid=398892)[0m [800]	train-mlogloss:1.69610	validation-mlogloss:1.73146
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[36m(train_xgb_ray_tune pid=398892)[0m [802]	train-mlogloss:1.69589	validation-mlogloss:1.73131
[36m(train_xgb_ray_tune pid=398886)[0m [750]	train-mlogloss:1.50113	validation-mlogloss:1.66758
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[36m(train_xgb_ray_tune pid=398912)[0m [733]	train-mlogloss:1.61272	validation-mlogloss:1.71053
[36m(train_xgb_ray_tune pid=398912)[0m [734]	train-mlogloss:1.61234	validation-mlogloss:1.71059
[36m(train_xgb_ray_tune pid=398916)[0m [718]	train-mlogloss:2.17156	validation-mlogloss:2.17219
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[36m(train_xgb_ray_tune pid=398886)[0m [783]	train-mlogloss:1.49344	validation-mlogloss:1.66654
[36m(train_xgb_ray_tune pid=398912)[0m [760]	train-mlogloss:1.60236	validation-mlogloss:1.70717
[36m(train_xgb_ray_tune pid=398912)[0m [761]	train-mlogloss:1.60199	validation-mlogloss:1.70708
[36m(train_xgb_ray_tune pid=398912)[0m [762]	train-mlogloss:1.60163	validation-mlogloss:1.70697
[36m(train_xgb_ray_tune pid=398894)[0m [710]	train-mlogloss:1.68722	validation-mlogloss:1.74382
[36m(train_xgb_ray_tune pid=398894)[0m [711]	train-mlogloss:1.68678	validation-mlogloss:1.74365
[36m(train_xgb_ray_tune pid=398905)[0m [796]	train-mlogloss:1.69234	validation-mlogloss:1.73845
[36m(train_xgb_ray_tune pid=398905)[0m [797]	train-mlogloss:1.69224	validation-mlogloss:1.73841
[36m(train_xgb_ray_tune pid=398892)[0m [838]	train-mlogloss:1.69255	validation-mlogloss:1.72970
[36m(train_xgb_ray_tune pid=398892)[0m [839]	train-mlogloss:1.69254	validation-mlogloss:1.72969
[36m(train_xgb_ray_tune pid=398892)[0m [840]	train-mlogloss:1.69239	validation-mlogloss:1.72968
[36m(train_xgb_ray_tune pid=398886)[0m [784]	train-mlogloss:1.49319	validation-mlogloss:1.66645
[36m(train_xgb_ray_tune pid=398912)[0m [763]	train-mlogloss:1.60125	validation-mlogloss:1.70689
[36m(train_xgb_ray_tune pid=398912)[0m [764]	train-mlogloss:1.60089	validation-mlogloss:1.70674
[36m(train_xgb_ray_tune pid=398894)[0m [712]	train-mlogloss:1.68636	validation-mlogloss:1.74349
[36m(train_xgb_ray_tune pid=398894)[0m [713]	train-mlogloss:1.68593	validation-mlogloss:1.74330
[36m(train_xgb_ray_tune pid=398905)[0m [798]	train-mlogloss:1.69209	validation-mlogloss:1.73828
[36m(train_xgb_ray_tune pid=398905)[0m [799]	train-mlogloss:1.69205	validation-mlogloss:1.73826
[36m(train_xgb_ray_tune pid=398905)[0m [800]	train-mlogloss:1.69199	validation-mlogloss:1.73825
[36m(train_xgb_ray_tune pid=398892)[0m [841]	train-mlogloss:1.69230	validation-mlogloss:1.72964
[36m(train_xgb_ray_tune pid=398892)[0m [842]	train-mlogloss:1.69215	validation-mlogloss:1.72956
[36m(train_xgb_ray_tune pid=398892)[0m [843]	train-mlogloss:1.69209	validation-mlogloss:1.72957
[36m(train_xgb_ray_tune pid=398912)[0m [765]	train-mlogloss:1.60055	validation-mlogloss:1.70663
[36m(train_xgb_ray_tune pid=398912)[0m [766]	train-mlogloss:1.60019	validation-mlogloss:1.70641
[36m(train_xgb_ray_tune pid=398894)[0m [714]	train-mlogloss:1.68547	validation-mlogloss:1.74301
[36m(train_xgb_ray_tune pid=398894)[0m [715]	train-mlogloss:1.68504	validation-mlogloss:1.74277
[36m(train_xgb_ray_tune pid=398905)[0m [801]	train-mlogloss:1.69199	validation-mlogloss:1.73825
[36m(train_xgb_ray_tune pid=398905)[0m [802]	train-mlogloss:1.69193	validation-mlogloss:1.73821
[36m(train_xgb_ray_tune pid=398905)[0m [803]	train-mlogloss:1.69188	validation-mlogloss:1.73818
[36m(train_xgb_ray_tune pid=398892)[0m [844]	train-mlogloss:1.69201	validation-mlogloss:1.72963
[36m(train_xgb_ray_tune pid=398892)[0m [845]	train-mlogloss:1.69186	validation-mlogloss:1.72951

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:32. Total running time: 2min 17s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             134.282 │
│ time_total_s                 134.282 │
│ training_iteration                 1 │
│ validation_accuracy          0.40937 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:32. Total running time: 2min 17s
[36m(train_xgb_ray_tune pid=398912)[0m [767]	train-mlogloss:1.59978	validation-mlogloss:1.70634
[36m(train_xgb_ray_tune pid=398912)[0m [768]	train-mlogloss:1.59941	validation-mlogloss:1.70611
[36m(train_xgb_ray_tune pid=398894)[0m [716]	train-mlogloss:1.68459	validation-mlogloss:1.74249
[36m(train_xgb_ray_tune pid=398894)[0m [717]	train-mlogloss:1.68418	validation-mlogloss:1.74226
[36m(train_xgb_ray_tune pid=398905)[0m [804]	train-mlogloss:1.69180	validation-mlogloss:1.73813
[36m(train_xgb_ray_tune pid=398905)[0m [805]	train-mlogloss:1.69166	validation-mlogloss:1.73804
[36m(train_xgb_ray_tune pid=398892)[0m [846]	train-mlogloss:1.69168	validation-mlogloss:1.72941
[36m(train_xgb_ray_tune pid=398892)[0m [847]	train-mlogloss:1.69167	validation-mlogloss:1.72941
[36m(train_xgb_ray_tune pid=398892)[0m [848]	train-mlogloss:1.69159	validation-mlogloss:1.72935
[36m(train_xgb_ray_tune pid=398912)[0m [769]	train-mlogloss:1.59904	validation-mlogloss:1.70626
[36m(train_xgb_ray_tune pid=398912)[0m [770]	train-mlogloss:1.59866	validation-mlogloss:1.70607
[36m(train_xgb_ray_tune pid=398894)[0m [718]	train-mlogloss:1.68375	validation-mlogloss:1.74205
[36m(train_xgb_ray_tune pid=398894)[0m [719]	train-mlogloss:1.68330	validation-mlogloss:1.74190
[36m(train_xgb_ray_tune pid=398905)[0m [806]	train-mlogloss:1.69155	validation-mlogloss:1.73797
[36m(train_xgb_ray_tune pid=398905)[0m [807]	train-mlogloss:1.69150	validation-mlogloss:1.73792
[36m(train_xgb_ray_tune pid=398905)[0m [808]	train-mlogloss:1.69135	validation-mlogloss:1.73787
[36m(train_xgb_ray_tune pid=398892)[0m [849]	train-mlogloss:1.69157	validation-mlogloss:1.72932
[36m(train_xgb_ray_tune pid=398892)[0m [850]	train-mlogloss:1.69151	validation-mlogloss:1.72926
[36m(train_xgb_ray_tune pid=398892)[0m [851]	train-mlogloss:1.69143	validation-mlogloss:1.72925
[36m(train_xgb_ray_tune pid=398912)[0m [771]	train-mlogloss:1.59826	validation-mlogloss:1.70576
[36m(train_xgb_ray_tune pid=398912)[0m [772]	train-mlogloss:1.59792	validation-mlogloss:1.70583
[36m(train_xgb_ray_tune pid=398912)[0m [773]	train-mlogloss:1.59756	validation-mlogloss:1.70576
[36m(train_xgb_ray_tune pid=398894)[0m [720]	train-mlogloss:1.68287	validation-mlogloss:1.74168
[36m(train_xgb_ray_tune pid=398894)[0m [721]	train-mlogloss:1.68247	validation-mlogloss:1.74153
[36m(train_xgb_ray_tune pid=398905)[0m [809]	train-mlogloss:1.69127	validation-mlogloss:1.73783
[36m(train_xgb_ray_tune pid=398905)[0m [810]	train-mlogloss:1.69123	validation-mlogloss:1.73782
[36m(train_xgb_ray_tune pid=398905)[0m [811]	train-mlogloss:1.69115	validation-mlogloss:1.73775
[36m(train_xgb_ray_tune pid=398892)[0m [852]	train-mlogloss:1.69134	validation-mlogloss:1.72923
[36m(train_xgb_ray_tune pid=398892)[0m [853]	train-mlogloss:1.69126	validation-mlogloss:1.72913
[36m(train_xgb_ray_tune pid=398892)[0m [854]	train-mlogloss:1.69114	validation-mlogloss:1.72910
[36m(train_xgb_ray_tune pid=398912)[0m [774]	train-mlogloss:1.59719	validation-mlogloss:1.70562
[36m(train_xgb_ray_tune pid=398912)[0m [775]	train-mlogloss:1.59684	validation-mlogloss:1.70554
[36m(train_xgb_ray_tune pid=398894)[0m [722]	train-mlogloss:1.68206	validation-mlogloss:1.74136
[36m(train_xgb_ray_tune pid=398894)[0m [723]	train-mlogloss:1.68163	validation-mlogloss:1.74124
[36m(train_xgb_ray_tune pid=398905)[0m [812]	train-mlogloss:1.69105	validation-mlogloss:1.73772
[36m(train_xgb_ray_tune pid=398905)[0m [813]	train-mlogloss:1.69099	validation-mlogloss:1.73769
[36m(train_xgb_ray_tune pid=398892)[0m [855]	train-mlogloss:1.69104	validation-mlogloss:1.72909
[36m(train_xgb_ray_tune pid=398892)[0m [856]	train-mlogloss:1.69092	validation-mlogloss:1.72899
[36m(train_xgb_ray_tune pid=398892)[0m [857]	train-mlogloss:1.69078	validation-mlogloss:1.72881
[36m(train_xgb_ray_tune pid=398894)[0m [724]	train-mlogloss:1.68116	validation-mlogloss:1.74100
[36m(train_xgb_ray_tune pid=398905)[0m [814]	train-mlogloss:1.69092	validation-mlogloss:1.73764
[36m(train_xgb_ray_tune pid=398912)[0m [776]	train-mlogloss:1.59649	validation-mlogloss:1.70558
[36m(train_xgb_ray_tune pid=398912)[0m [777]	train-mlogloss:1.59616	validation-mlogloss:1.70546
[36m(train_xgb_ray_tune pid=398894)[0m [725]	train-mlogloss:1.68074	validation-mlogloss:1.74066
[36m(train_xgb_ray_tune pid=398894)[0m [726]	train-mlogloss:1.68032	validation-mlogloss:1.74048
[36m(train_xgb_ray_tune pid=398905)[0m [815]	train-mlogloss:1.69087	validation-mlogloss:1.73760
[36m(train_xgb_ray_tune pid=398905)[0m [816]	train-mlogloss:1.69081	validation-mlogloss:1.73757
[36m(train_xgb_ray_tune pid=398892)[0m [858]	train-mlogloss:1.69065	validation-mlogloss:1.72872
[36m(train_xgb_ray_tune pid=398892)[0m [859]	train-mlogloss:1.69058	validation-mlogloss:1.72866
[36m(train_xgb_ray_tune pid=398892)[0m [860]	train-mlogloss:1.69051	validation-mlogloss:1.72862
[36m(train_xgb_ray_tune pid=398905)[0m [817]	train-mlogloss:1.69068	validation-mlogloss:1.73750
[36m(train_xgb_ray_tune pid=398912)[0m [778]	train-mlogloss:1.59575	validation-mlogloss:1.70529
[36m(train_xgb_ray_tune pid=398912)[0m [779]	train-mlogloss:1.59538	validation-mlogloss:1.70518
[36m(train_xgb_ray_tune pid=398912)[0m [780]	train-mlogloss:1.59500	validation-mlogloss:1.70513
[36m(train_xgb_ray_tune pid=398894)[0m [727]	train-mlogloss:1.67989	validation-mlogloss:1.74026
[36m(train_xgb_ray_tune pid=398894)[0m [728]	train-mlogloss:1.67952	validation-mlogloss:1.74015
[36m(train_xgb_ray_tune pid=398905)[0m [818]	train-mlogloss:1.69061	validation-mlogloss:1.73746
[36m(train_xgb_ray_tune pid=398905)[0m [819]	train-mlogloss:1.69053	validation-mlogloss:1.73736
[36m(train_xgb_ray_tune pid=398892)[0m [861]	train-mlogloss:1.69035	validation-mlogloss:1.72863
[36m(train_xgb_ray_tune pid=398892)[0m [862]	train-mlogloss:1.69025	validation-mlogloss:1.72862
[36m(train_xgb_ray_tune pid=398892)[0m [863]	train-mlogloss:1.69017	validation-mlogloss:1.72862
[36m(train_xgb_ray_tune pid=398905)[0m [820]	train-mlogloss:1.69051	validation-mlogloss:1.73734

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:33. Total running time: 2min 17s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             135.023 │
│ time_total_s                 135.023 │
│ training_iteration                 1 │
│ validation_accuracy          0.51658 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:33. Total running time: 2min 17s
[36m(train_xgb_ray_tune pid=398912)[0m [781]	train-mlogloss:1.59463	validation-mlogloss:1.70492
[36m(train_xgb_ray_tune pid=398912)[0m [782]	train-mlogloss:1.59425	validation-mlogloss:1.70483
[36m(train_xgb_ray_tune pid=398894)[0m [729]	train-mlogloss:1.67912	validation-mlogloss:1.73990
[36m(train_xgb_ray_tune pid=398894)[0m [730]	train-mlogloss:1.67875	validation-mlogloss:1.73966
[36m(train_xgb_ray_tune pid=398905)[0m [821]	train-mlogloss:1.69046	validation-mlogloss:1.73730
[36m(train_xgb_ray_tune pid=398905)[0m [822]	train-mlogloss:1.69045	validation-mlogloss:1.73732
[36m(train_xgb_ray_tune pid=398892)[0m [864]	train-mlogloss:1.69009	validation-mlogloss:1.72856
[36m(train_xgb_ray_tune pid=398892)[0m [865]	train-mlogloss:1.68993	validation-mlogloss:1.72849
[36m(train_xgb_ray_tune pid=398892)[0m [866]	train-mlogloss:1.68985	validation-mlogloss:1.72840
[36m(train_xgb_ray_tune pid=398912)[0m [783]	train-mlogloss:1.59383	validation-mlogloss:1.70467
[36m(train_xgb_ray_tune pid=398912)[0m [784]	train-mlogloss:1.59344	validation-mlogloss:1.70476
[36m(train_xgb_ray_tune pid=398894)[0m [731]	train-mlogloss:1.67830	validation-mlogloss:1.73940
[36m(train_xgb_ray_tune pid=398894)[0m [732]	train-mlogloss:1.67786	validation-mlogloss:1.73914
[36m(train_xgb_ray_tune pid=398905)[0m [823]	train-mlogloss:1.69039	validation-mlogloss:1.73728
[36m(train_xgb_ray_tune pid=398905)[0m [824]	train-mlogloss:1.69031	validation-mlogloss:1.73727
[36m(train_xgb_ray_tune pid=398905)[0m [825]	train-mlogloss:1.69022	validation-mlogloss:1.73725
[36m(train_xgb_ray_tune pid=398892)[0m [867]	train-mlogloss:1.68977	validation-mlogloss:1.72836
[36m(train_xgb_ray_tune pid=398892)[0m [868]	train-mlogloss:1.68955	validation-mlogloss:1.72836
[36m(train_xgb_ray_tune pid=398892)[0m [869]	train-mlogloss:1.68948	validation-mlogloss:1.72838
[36m(train_xgb_ray_tune pid=398894)[0m [733]	train-mlogloss:1.67745	validation-mlogloss:1.73898
[36m(train_xgb_ray_tune pid=398905)[0m [826]	train-mlogloss:1.69019	validation-mlogloss:1.73722
[36m(train_xgb_ray_tune pid=398912)[0m [785]	train-mlogloss:1.59308	validation-mlogloss:1.70464
[36m(train_xgb_ray_tune pid=398912)[0m [786]	train-mlogloss:1.59274	validation-mlogloss:1.70452
[36m(train_xgb_ray_tune pid=398912)[0m [787]	train-mlogloss:1.59238	validation-mlogloss:1.70441
[36m(train_xgb_ray_tune pid=398894)[0m [734]	train-mlogloss:1.67705	validation-mlogloss:1.73884
[36m(train_xgb_ray_tune pid=398894)[0m [735]	train-mlogloss:1.67667	validation-mlogloss:1.73869
[36m(train_xgb_ray_tune pid=398905)[0m [827]	train-mlogloss:1.69013	validation-mlogloss:1.73721
[36m(train_xgb_ray_tune pid=398905)[0m [828]	train-mlogloss:1.69000	validation-mlogloss:1.73713
[36m(train_xgb_ray_tune pid=398892)[0m [870]	train-mlogloss:1.68942	validation-mlogloss:1.72835
[36m(train_xgb_ray_tune pid=398912)[0m [788]	train-mlogloss:1.59201	validation-mlogloss:1.70417
[36m(train_xgb_ray_tune pid=398894)[0m [736]	train-mlogloss:1.67624	validation-mlogloss:1.73850
[36m(train_xgb_ray_tune pid=398894)[0m [737]	train-mlogloss:1.67584	validation-mlogloss:1.73835
[36m(train_xgb_ray_tune pid=398905)[0m [829]	train-mlogloss:1.68990	validation-mlogloss:1.73713
[36m(train_xgb_ray_tune pid=398905)[0m [830]	train-mlogloss:1.68988	validation-mlogloss:1.73710
[36m(train_xgb_ray_tune pid=398905)[0m [831]	train-mlogloss:1.68979	validation-mlogloss:1.73702
[36m(train_xgb_ray_tune pid=398894)[0m [738]	train-mlogloss:1.67539	validation-mlogloss:1.73806
[36m(train_xgb_ray_tune pid=398894)[0m [739]	train-mlogloss:1.67496	validation-mlogloss:1.73788
[36m(train_xgb_ray_tune pid=398905)[0m [832]	train-mlogloss:1.68967	validation-mlogloss:1.73697
[36m(train_xgb_ray_tune pid=398905)[0m [833]	train-mlogloss:1.68963	validation-mlogloss:1.73700
[36m(train_xgb_ray_tune pid=398905)[0m [834]	train-mlogloss:1.68963	validation-mlogloss:1.73700
[36m(train_xgb_ray_tune pid=398894)[0m [740]	train-mlogloss:1.67458	validation-mlogloss:1.73766
[36m(train_xgb_ray_tune pid=398894)[0m [741]	train-mlogloss:1.67418	validation-mlogloss:1.73744
[36m(train_xgb_ray_tune pid=398894)[0m [742]	train-mlogloss:1.67378	validation-mlogloss:1.73719
[36m(train_xgb_ray_tune pid=398905)[0m [835]	train-mlogloss:1.68960	validation-mlogloss:1.73702
[36m(train_xgb_ray_tune pid=398905)[0m [836]	train-mlogloss:1.68959	validation-mlogloss:1.73703
[36m(train_xgb_ray_tune pid=398905)[0m [837]	train-mlogloss:1.68946	validation-mlogloss:1.73698
[36m(train_xgb_ray_tune pid=398894)[0m [743]	train-mlogloss:1.67337	validation-mlogloss:1.73693
[36m(train_xgb_ray_tune pid=398894)[0m [744]	train-mlogloss:1.67294	validation-mlogloss:1.73673
[36m(train_xgb_ray_tune pid=398905)[0m [838]	train-mlogloss:1.68937	validation-mlogloss:1.73695
[36m(train_xgb_ray_tune pid=398905)[0m [839]	train-mlogloss:1.68928	validation-mlogloss:1.73690
[36m(train_xgb_ray_tune pid=398905)[0m [840]	train-mlogloss:1.68919	validation-mlogloss:1.73687
[36m(train_xgb_ray_tune pid=398894)[0m [745]	train-mlogloss:1.67253	validation-mlogloss:1.73663
[36m(train_xgb_ray_tune pid=398894)[0m [746]	train-mlogloss:1.67214	validation-mlogloss:1.73642
[36m(train_xgb_ray_tune pid=398905)[0m [841]	train-mlogloss:1.68907	validation-mlogloss:1.73686
[36m(train_xgb_ray_tune pid=398905)[0m [842]	train-mlogloss:1.68900	validation-mlogloss:1.73688
[36m(train_xgb_ray_tune pid=398905)[0m [843]	train-mlogloss:1.68893	validation-mlogloss:1.73688
[36m(train_xgb_ray_tune pid=398894)[0m [747]	train-mlogloss:1.67172	validation-mlogloss:1.73617
[36m(train_xgb_ray_tune pid=398894)[0m [748]	train-mlogloss:1.67133	validation-mlogloss:1.73600
[36m(train_xgb_ray_tune pid=398905)[0m [844]	train-mlogloss:1.68890	validation-mlogloss:1.73683
[36m(train_xgb_ray_tune pid=398905)[0m [845]	train-mlogloss:1.68888	validation-mlogloss:1.73682
[36m(train_xgb_ray_tune pid=398905)[0m [846]	train-mlogloss:1.68878	validation-mlogloss:1.73681
[36m(train_xgb_ray_tune pid=398905)[0m [847]	train-mlogloss:1.68871	validation-mlogloss:1.73671
[36m(train_xgb_ray_tune pid=398905)[0m [848]	train-mlogloss:1.68861	validation-mlogloss:1.73669

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:34. Total running time: 2min 18s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             135.932 │
│ time_total_s                 135.932 │
│ training_iteration                 1 │
│ validation_accuracy          0.51638 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:34. Total running time: 2min 18s
[36m(train_xgb_ray_tune pid=398905)[0m [849]	train-mlogloss:1.68847	validation-mlogloss:1.73661
[36m(train_xgb_ray_tune pid=398905)[0m [850]	train-mlogloss:1.68840	validation-mlogloss:1.73664
[36m(train_xgb_ray_tune pid=398905)[0m [851]	train-mlogloss:1.68833	validation-mlogloss:1.73654

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:34. Total running time: 2min 19s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             135.913 │
│ time_total_s                 135.913 │
│ training_iteration                 1 │
│ validation_accuracy          0.51956 │
╰──────────────────────────────────────╯
[36m(train_xgb_ray_tune pid=398905)[0m [852]	train-mlogloss:1.68827	validation-mlogloss:1.73650

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:34. Total running time: 2min 19s
[36m(train_xgb_ray_tune pid=398905)[0m [853]	train-mlogloss:1.68822	validation-mlogloss:1.73649
[36m(train_xgb_ray_tune pid=398905)[0m [854]	train-mlogloss:1.68813	validation-mlogloss:1.73645
[36m(train_xgb_ray_tune pid=398905)[0m [855]	train-mlogloss:1.68807	validation-mlogloss:1.73641
[36m(train_xgb_ray_tune pid=398905)[0m [856]	train-mlogloss:1.68806	validation-mlogloss:1.73639
[36m(train_xgb_ray_tune pid=398905)[0m [857]	train-mlogloss:1.68806	validation-mlogloss:1.73639
[36m(train_xgb_ray_tune pid=398905)[0m [858]	train-mlogloss:1.68802	validation-mlogloss:1.73639
[36m(train_xgb_ray_tune pid=398905)[0m [859]	train-mlogloss:1.68797	validation-mlogloss:1.73638

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:34. Total running time: 2min 19s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             136.514 │
│ time_total_s                 136.514 │
│ training_iteration                 1 │
│ validation_accuracy          0.51856 │
╰──────────────────────────────────────╯

2025-10-27 09:36:35,490	INFO tune.py:1009 -- Wrote the latest version of all result files and experiment state to '/mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_M/case_M_XGB_acc_gyr_17_classes/XGBoost_hyperparameters_tuning' in 0.0116s.
Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:34. Total running time: 2min 19s

Trial trial_b8b81 finished iteration 1 at 2025-10-27 09:36:35. Total running time: 2min 20s
╭──────────────────────────────────────╮
│ Trial trial_b8b81 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             137.195 │
│ time_total_s                 137.195 │
│ training_iteration                 1 │
│ validation_accuracy          0.51281 │
╰──────────────────────────────────────╯

Trial trial_b8b81 completed after 1 iterations at 2025-10-27 09:36:35. Total running time: 2min 20s

Trial status: 20 TERMINATED
Current time: 2025-10-27 09:36:35. Total running time: 2min 20s
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_b8b81    TERMINATED                 785             2        0.0152561       0.333235             0.509718   5.36058                   59      1.72191        0.791369             8764        1           135.023                 0.516577 │
│ trial_b8b81    TERMINATED                 436             2        0.0151967       0.687426             0.508211   3.6508                    32      0.236551       2.80111                23        1           105.27                  0.517769 │
│ trial_b8b81    TERMINATED                 540             2        0.0154571       0.498324             0.399232   7.5555                    57      0.518023       1.37493              3189        1           117.34                  0.527099 │
│ trial_b8b81    TERMINATED                 353             2        0.00577946      0.588048             0.300442   8.55953                   34      5.80421        0.579503             5130        1            85.8844                0.508636 │
│ trial_b8b81    TERMINATED                 677             2        0.00718957      0.347983             0.517791   6.43243                   12      0.249615       2.3729               3650        1           130.233                 0.516974 │
│ trial_b8b81    TERMINATED                 347             2        0.00373864      0.624615             0.491362   7.40223                   33      0.177621      15.6491               4377        1            88.6951                0.490371 │
│ trial_b8b81    TERMINATED                 749             2        0.00684262      0.511093             0.642296   2.23501                   26      2.59404        5.58484              8397        1           136.514                 0.518563 │
│ trial_b8b81    TERMINATED                 550             2        0.0146521       0.333218             0.403476   8.58164                   12      8.33367       54.5003               6890        1           113.767                 0.512011 │
│ trial_b8b81    TERMINATED                 789             2        0.00862436      0.519278             0.453361   7.20008                   21      1.57911        3.85557               985        1           135.913                 0.519555 │
│ trial_b8b81    TERMINATED                 416             2        0.00418167      0.347849             0.419215   6.11886                   39      1.02586        0.871116             4157        1            93.3898                0.500099 │
│ trial_b8b81    TERMINATED                 737             2        0.0033156       0.459322             0.608053   3.18821                   28     93.719          1.30518              5776        1           134.282                 0.409371 │
│ trial_b8b81    TERMINATED                 650             2        0.00313347      0.693701             0.492938   9.79394                   12      1.55806        6.0203               5382        1           128.769                 0.500298 │
│ trial_b8b81    TERMINATED                 860             2        0.0136591       0.502887             0.62787    4.03237                   37     28.4997        51.4794               8253        1           137.195                 0.512805 │
│ trial_b8b81    TERMINATED                 500             2        0.0168463       0.316536             0.311578   7.53857                   21     25.6984         1.41457              2854        1           103.427                 0.500099 │
│ trial_b8b81    TERMINATED                 528             2        0.00285688      0.536565             0.651463   5.278                     25      2.19742        2.87126               507        1           115.912                 0.488386 │
│ trial_b8b81    TERMINATED                 319             2        0.0172683       0.44677              0.688075   6.64719                   21      1.24884       27.0934               5802        1            86.7446                0.512607 │
│ trial_b8b81    TERMINATED                 783             2        0.0197427       0.306766             0.67443    7.59557                   58     66.8206        16.8769               7467        1           120.375                 0.376017 │
│ trial_b8b81    TERMINATED                 725             2        0.0143453       0.659911             0.418968   3.84157                   53      0.163473      19.04                 9244        1           132.021                 0.525114 │
│ trial_b8b81    TERMINATED                 601             2        0.0132953       0.653242             0.585449   3.87352                   49      4.74374       97.5749               9239        1           126.697                 0.516776 │
│ trial_b8b81    TERMINATED                 871             2        0.0139431       0.314738             0.444055   8.48731                   42      0.988245      70.352                9194        1           135.932                 0.516379 │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Mejores hiperparámetros XGBoost: {'num_boost_round': 540, 'max_depth': 2, 'learning_rate': 0.015457148776475776, 'subsample': 0.4983238434881435, 'colsample_bytree': 0.3992316676316109, 'gamma': 7.555500034847491, 'min_child_weight': 57, 'reg_alpha': 0.5180233416407111, 'reg_lambda': 1.3749290932337588, 'random_state': 3189}
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[537]	train-mlogloss:1.56068	validation-mlogloss:1.68533
[538]	train-mlogloss:1.56029	validation-mlogloss:1.68520
[539]	train-mlogloss:1.55983	validation-mlogloss:1.68516
Saved model to disk.
[36m(train_xgb_ray_tune pid=398905)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 6x across cluster][0m
[36m(train_xgb_ray_tune pid=398905)[0m   _log_deprecation_warning([32m [repeated 6x across cluster][0m
2025-10-27 09:37:07.084522: 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`.
2025-10-27 09:37:07.096989: 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 00:00:1761554227.111014  403200 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554227.115414  403200 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554227.126567  403200 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554227.126603  403200 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554227.126606  403200 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554227.126609  403200 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:37:07.130077: 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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[516]	train-mlogloss:1.56943	validation-mlogloss:1.68618
[517]	train-mlogloss:1.56891	validation-mlogloss:1.68606
[518]	train-mlogloss:1.56838	validation-mlogloss:1.68597
[519]	train-mlogloss:1.56784	validation-mlogloss:1.68578
[520]	train-mlogloss:1.56736	validation-mlogloss:1.68574
[521]	train-mlogloss:1.56686	validation-mlogloss:1.68564
[522]	train-mlogloss:1.56639	validation-mlogloss:1.68554
[523]	train-mlogloss:1.56592	validation-mlogloss:1.68543
[524]	train-mlogloss:1.56544	validation-mlogloss:1.68524
[525]	train-mlogloss:1.56488	validation-mlogloss:1.68514
[526]	train-mlogloss:1.56434	validation-mlogloss:1.68511
[527]	train-mlogloss:1.56388	validation-mlogloss:1.68509
[528]	train-mlogloss:1.56343	validation-mlogloss:1.68497
[529]	train-mlogloss:1.56300	validation-mlogloss:1.68490
[530]	train-mlogloss:1.56247	validation-mlogloss:1.68479
[531]	train-mlogloss:1.56207	validation-mlogloss:1.68451
[532]	train-mlogloss:1.56162	validation-mlogloss:1.68453
[533]	train-mlogloss:1.56110	validation-mlogloss:1.68434
[534]	train-mlogloss:1.56061	validation-mlogloss:1.68420
[535]	train-mlogloss:1.56016	validation-mlogloss:1.68404
[536]	train-mlogloss:1.55972	validation-mlogloss:1.68385
[537]	train-mlogloss:1.55931	validation-mlogloss:1.68390
[538]	train-mlogloss:1.55894	validation-mlogloss:1.68370
[539]	train-mlogloss:1.55849	validation-mlogloss:1.68374
Saved model to disk.
2025-10-27 09:37:52.133276: 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`.
2025-10-27 09:37:52.145706: 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 00:00:1761554272.159055  404088 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554272.163183  404088 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554272.174087  404088 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554272.174111  404088 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554272.174123  404088 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554272.174125  404088 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:37:52.177399: 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:2.69408	validation-mlogloss:2.69287
[1]	train-mlogloss:2.68130	validation-mlogloss:2.67844
[2]	train-mlogloss:2.66727	validation-mlogloss:2.66395
[3]	train-mlogloss:2.65389	validation-mlogloss:2.64938
[4]	train-mlogloss:2.63981	validation-mlogloss:2.63322
[5]	train-mlogloss:2.62737	validation-mlogloss:2.61945
[6]	train-mlogloss:2.61510	validation-mlogloss:2.60533
[7]	train-mlogloss:2.60264	validation-mlogloss:2.59144
[8]	train-mlogloss:2.59012	validation-mlogloss:2.57730
[9]	train-mlogloss:2.57823	validation-mlogloss:2.56422
[10]	train-mlogloss:2.56672	validation-mlogloss:2.55129
[11]	train-mlogloss:2.55541	validation-mlogloss:2.53845
[12]	train-mlogloss:2.54554	validation-mlogloss:2.52684
[13]	train-mlogloss:2.53508	validation-mlogloss:2.51485
[14]	train-mlogloss:2.52489	validation-mlogloss:2.50399
[15]	train-mlogloss:2.51475	validation-mlogloss:2.49369
[16]	train-mlogloss:2.50482	validation-mlogloss:2.48286
[17]	train-mlogloss:2.49543	validation-mlogloss:2.47253
[18]	train-mlogloss:2.48619	validation-mlogloss:2.46201
[19]	train-mlogloss:2.47726	validation-mlogloss:2.45210
[20]	train-mlogloss:2.46808	validation-mlogloss:2.44213
[21]	train-mlogloss:2.45926	validation-mlogloss:2.43245
[22]	train-mlogloss:2.45099	validation-mlogloss:2.42245
[23]	train-mlogloss:2.44245	validation-mlogloss:2.41260
[24]	train-mlogloss:2.43424	validation-mlogloss:2.40387
[25]	train-mlogloss:2.42655	validation-mlogloss:2.39595
[26]	train-mlogloss:2.41834	validation-mlogloss:2.38697
[27]	train-mlogloss:2.41057	validation-mlogloss:2.37768
[28]	train-mlogloss:2.40275	validation-mlogloss:2.36968
[29]	train-mlogloss:2.39529	validation-mlogloss:2.36153
[30]	train-mlogloss:2.38770	validation-mlogloss:2.35340
[31]	train-mlogloss:2.38044	validation-mlogloss:2.34551
[32]	train-mlogloss:2.37277	validation-mlogloss:2.33716
[33]	train-mlogloss:2.36554	validation-mlogloss:2.32898
[34]	train-mlogloss:2.35851	validation-mlogloss:2.32187
[35]	train-mlogloss:2.35204	validation-mlogloss:2.31486
[36]	train-mlogloss:2.34511	validation-mlogloss:2.30693
[37]	train-mlogloss:2.33847	validation-mlogloss:2.29975
[38]	train-mlogloss:2.33220	validation-mlogloss:2.29315
[39]	train-mlogloss:2.32561	validation-mlogloss:2.28650
[40]	train-mlogloss:2.31946	validation-mlogloss:2.28066
[41]	train-mlogloss:2.31302	validation-mlogloss:2.27347
[42]	train-mlogloss:2.30679	validation-mlogloss:2.26653
[43]	train-mlogloss:2.30067	validation-mlogloss:2.25995
[44]	train-mlogloss:2.29446	validation-mlogloss:2.25325
[45]	train-mlogloss:2.28859	validation-mlogloss:2.24698
[46]	train-mlogloss:2.28290	validation-mlogloss:2.24071
[47]	train-mlogloss:2.27723	validation-mlogloss:2.23507
[48]	train-mlogloss:2.27120	validation-mlogloss:2.22876
[49]	train-mlogloss:2.26572	validation-mlogloss:2.22363
[50]	train-mlogloss:2.26005	validation-mlogloss:2.21818
[51]	train-mlogloss:2.25461	validation-mlogloss:2.21273
[52]	train-mlogloss:2.24926	validation-mlogloss:2.20728
[53]	train-mlogloss:2.24406	validation-mlogloss:2.20178
[54]	train-mlogloss:2.23882	validation-mlogloss:2.19625
[55]	train-mlogloss:2.23345	validation-mlogloss:2.19054
[56]	train-mlogloss:2.22845	validation-mlogloss:2.18558
[57]	train-mlogloss:2.22325	validation-mlogloss:2.18030
[58]	train-mlogloss:2.21815	validation-mlogloss:2.17550
[59]	train-mlogloss:2.21313	validation-mlogloss:2.17063
[60]	train-mlogloss:2.20812	validation-mlogloss:2.16542
[61]	train-mlogloss:2.20329	validation-mlogloss:2.16053
[62]	train-mlogloss:2.19869	validation-mlogloss:2.15570
[63]	train-mlogloss:2.19394	validation-mlogloss:2.15132
[64]	train-mlogloss:2.18918	validation-mlogloss:2.14627
[65]	train-mlogloss:2.18456	validation-mlogloss:2.14138
[66]	train-mlogloss:2.18029	validation-mlogloss:2.13738
[67]	train-mlogloss:2.17585	validation-mlogloss:2.13264
[68]	train-mlogloss:2.17122	validation-mlogloss:2.12795
[69]	train-mlogloss:2.16645	validation-mlogloss:2.12320
[70]	train-mlogloss:2.16231	validation-mlogloss:2.11915
[71]	train-mlogloss:2.15802	validation-mlogloss:2.11504
[72]	train-mlogloss:2.15393	validation-mlogloss:2.11103
[73]	train-mlogloss:2.14981	validation-mlogloss:2.10701
[74]	train-mlogloss:2.14557	validation-mlogloss:2.10272
[75]	train-mlogloss:2.14166	validation-mlogloss:2.09930
[76]	train-mlogloss:2.13749	validation-mlogloss:2.09491
[77]	train-mlogloss:2.13369	validation-mlogloss:2.09139
[78]	train-mlogloss:2.12966	validation-mlogloss:2.08740
[79]	train-mlogloss:2.12562	validation-mlogloss:2.08342
[80]	train-mlogloss:2.12169	validation-mlogloss:2.07972
[81]	train-mlogloss:2.11802	validation-mlogloss:2.07602
[82]	train-mlogloss:2.11404	validation-mlogloss:2.07176
[83]	train-mlogloss:2.11045	validation-mlogloss:2.06843
[84]	train-mlogloss:2.10694	validation-mlogloss:2.06476
[85]	train-mlogloss:2.10324	validation-mlogloss:2.06128
[86]	train-mlogloss:2.09982	validation-mlogloss:2.05770
[87]	train-mlogloss:2.09618	validation-mlogloss:2.05426
[88]	train-mlogloss:2.09275	validation-mlogloss:2.05124
[89]	train-mlogloss:2.08923	validation-mlogloss:2.04822
[90]	train-mlogloss:2.08563	validation-mlogloss:2.04482
[91]	train-mlogloss:2.08206	validation-mlogloss:2.04162
[92]	train-mlogloss:2.07868	validation-mlogloss:2.03810
[93]	train-mlogloss:2.07545	validation-mlogloss:2.03511
[94]	train-mlogloss:2.07215	validation-mlogloss:2.03191
[95]	train-mlogloss:2.06900	validation-mlogloss:2.02834
[96]	train-mlogloss:2.06570	validation-mlogloss:2.02495
[97]	train-mlogloss:2.06239	validation-mlogloss:2.02198
[98]	train-mlogloss:2.05920	validation-mlogloss:2.01929
[99]	train-mlogloss:2.05590	validation-mlogloss:2.01592
[100]	train-mlogloss:2.05280	validation-mlogloss:2.01281
[101]	train-mlogloss:2.04956	validation-mlogloss:2.00926
[102]	train-mlogloss:2.04642	validation-mlogloss:2.00654
[103]	train-mlogloss:2.04336	validation-mlogloss:2.00391
[104]	train-mlogloss:2.04018	validation-mlogloss:2.00090
[105]	train-mlogloss:2.03736	validation-mlogloss:1.99839
[106]	train-mlogloss:2.03435	validation-mlogloss:1.99533
[107]	train-mlogloss:2.03156	validation-mlogloss:1.99283
[108]	train-mlogloss:2.02865	validation-mlogloss:1.99037
[109]	train-mlogloss:2.02557	validation-mlogloss:1.98752
[110]	train-mlogloss:2.02272	validation-mlogloss:1.98467
[111]	train-mlogloss:2.01968	validation-mlogloss:1.98193
[112]	train-mlogloss:2.01690	validation-mlogloss:1.97906
[113]	train-mlogloss:2.01425	validation-mlogloss:1.97694
[114]	train-mlogloss:2.01154	validation-mlogloss:1.97458
[115]	train-mlogloss:2.00873	validation-mlogloss:1.97223
[116]	train-mlogloss:2.00612	validation-mlogloss:1.96983
[117]	train-mlogloss:2.00344	validation-mlogloss:1.96752
[118]	train-mlogloss:2.00078	validation-mlogloss:1.96510
[119]	train-mlogloss:1.99816	validation-mlogloss:1.96305
[120]	train-mlogloss:1.99552	validation-mlogloss:1.96052
[121]	train-mlogloss:1.99303	validation-mlogloss:1.95807
[122]	train-mlogloss:1.99064	validation-mlogloss:1.95591
[123]	train-mlogloss:1.98802	validation-mlogloss:1.95341
[124]	train-mlogloss:1.98563	validation-mlogloss:1.95119
[125]	train-mlogloss:1.98313	validation-mlogloss:1.94865
[126]	train-mlogloss:1.98054	validation-mlogloss:1.94633
[127]	train-mlogloss:1.97806	validation-mlogloss:1.94422
[128]	train-mlogloss:1.97571	validation-mlogloss:1.94208
[129]	train-mlogloss:1.97333	validation-mlogloss:1.94011
[130]	train-mlogloss:1.97069	validation-mlogloss:1.93760
[131]	train-mlogloss:1.96841	validation-mlogloss:1.93567
[132]	train-mlogloss:1.96574	validation-mlogloss:1.93299
[133]	train-mlogloss:1.96336	validation-mlogloss:1.93071
[134]	train-mlogloss:1.96098	validation-mlogloss:1.92864
[135]	train-mlogloss:1.95861	validation-mlogloss:1.92650
[136]	train-mlogloss:1.95643	validation-mlogloss:1.92484
[137]	train-mlogloss:1.95395	validation-mlogloss:1.92230
[138]	train-mlogloss:1.95160	validation-mlogloss:1.92034
[139]	train-mlogloss:1.94925	validation-mlogloss:1.91859
[140]	train-mlogloss:1.94691	validation-mlogloss:1.91654
[141]	train-mlogloss:1.94461	validation-mlogloss:1.91450
[142]	train-mlogloss:1.94258	validation-mlogloss:1.91276
[143]	train-mlogloss:1.94030	validation-mlogloss:1.91055
[144]	train-mlogloss:1.93825	validation-mlogloss:1.90911
[145]	train-mlogloss:1.93587	validation-mlogloss:1.90702
[146]	train-mlogloss:1.93376	validation-mlogloss:1.90532
[147]	train-mlogloss:1.93156	validation-mlogloss:1.90359
[148]	train-mlogloss:1.92933	validation-mlogloss:1.90181
[149]	train-mlogloss:1.92721	validation-mlogloss:1.90013
[150]	train-mlogloss:1.92518	validation-mlogloss:1.89872
[151]	train-mlogloss:1.92303	validation-mlogloss:1.89675
[152]	train-mlogloss:1.92092	validation-mlogloss:1.89492
[153]	train-mlogloss:1.91891	validation-mlogloss:1.89364
[154]	train-mlogloss:1.91700	validation-mlogloss:1.89209
[155]	train-mlogloss:1.91493	validation-mlogloss:1.89001
[156]	train-mlogloss:1.91295	validation-mlogloss:1.88862
[157]	train-mlogloss:1.91108	validation-mlogloss:1.88714
[158]	train-mlogloss:1.90898	validation-mlogloss:1.88560
[159]	train-mlogloss:1.90703	validation-mlogloss:1.88416
[160]	train-mlogloss:1.90513	validation-mlogloss:1.88239
[161]	train-mlogloss:1.90326	validation-mlogloss:1.88082
[162]	train-mlogloss:1.90143	validation-mlogloss:1.87927
[163]	train-mlogloss:1.89944	validation-mlogloss:1.87744
[164]	train-mlogloss:1.89756	validation-mlogloss:1.87598
[165]	train-mlogloss:1.89572	validation-mlogloss:1.87456
[166]	train-mlogloss:1.89393	validation-mlogloss:1.87340
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[168]	train-mlogloss:1.89015	validation-mlogloss:1.87033
[169]	train-mlogloss:1.88836	validation-mlogloss:1.86911
[170]	train-mlogloss:1.88650	validation-mlogloss:1.86753
[171]	train-mlogloss:1.88467	validation-mlogloss:1.86596
[172]	train-mlogloss:1.88299	validation-mlogloss:1.86449
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[174]	train-mlogloss:1.87938	validation-mlogloss:1.86129
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[181]	train-mlogloss:1.86724	validation-mlogloss:1.85140
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[188]	train-mlogloss:1.85548	validation-mlogloss:1.84244
[189]	train-mlogloss:1.85388	validation-mlogloss:1.84129
[190]	train-mlogloss:1.85222	validation-mlogloss:1.83992
[191]	train-mlogloss:1.85057	validation-mlogloss:1.83863
[192]	train-mlogloss:1.84889	validation-mlogloss:1.83761
[193]	train-mlogloss:1.84730	validation-mlogloss:1.83643
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[195]	train-mlogloss:1.84428	validation-mlogloss:1.83419
[196]	train-mlogloss:1.84275	validation-mlogloss:1.83319
[197]	train-mlogloss:1.84114	validation-mlogloss:1.83194
[198]	train-mlogloss:1.83975	validation-mlogloss:1.83093
[199]	train-mlogloss:1.83818	validation-mlogloss:1.82991
[200]	train-mlogloss:1.83668	validation-mlogloss:1.82897
[201]	train-mlogloss:1.83525	validation-mlogloss:1.82756
[202]	train-mlogloss:1.83370	validation-mlogloss:1.82643
[203]	train-mlogloss:1.83227	validation-mlogloss:1.82551
[204]	train-mlogloss:1.83076	validation-mlogloss:1.82434
[205]	train-mlogloss:1.82952	validation-mlogloss:1.82324
[206]	train-mlogloss:1.82808	validation-mlogloss:1.82228
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[208]	train-mlogloss:1.82503	validation-mlogloss:1.82037
[209]	train-mlogloss:1.82358	validation-mlogloss:1.81911
[210]	train-mlogloss:1.82209	validation-mlogloss:1.81818
[211]	train-mlogloss:1.82056	validation-mlogloss:1.81702
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Saved model to disk.
2025-10-27 09:38:37.552640: 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`.
2025-10-27 09:38:37.565154: 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 00:00:1761554317.578806  404982 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554317.583120  404982 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554317.593984  404982 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554317.594009  404982 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554317.594019  404982 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554317.594022  404982 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:38:37.597327: 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:2.69296	validation-mlogloss:2.69072
[1]	train-mlogloss:2.67910	validation-mlogloss:2.67514
[2]	train-mlogloss:2.66476	validation-mlogloss:2.65899
[3]	train-mlogloss:2.65045	validation-mlogloss:2.64235
[4]	train-mlogloss:2.63654	validation-mlogloss:2.62699
[5]	train-mlogloss:2.62393	validation-mlogloss:2.61313
[6]	train-mlogloss:2.61241	validation-mlogloss:2.60096
[7]	train-mlogloss:2.60157	validation-mlogloss:2.58829
[8]	train-mlogloss:2.58925	validation-mlogloss:2.57448
[9]	train-mlogloss:2.57787	validation-mlogloss:2.56232
[10]	train-mlogloss:2.56617	validation-mlogloss:2.54944
[11]	train-mlogloss:2.55466	validation-mlogloss:2.53715
[12]	train-mlogloss:2.54361	validation-mlogloss:2.52436
[13]	train-mlogloss:2.53325	validation-mlogloss:2.51328
[14]	train-mlogloss:2.52426	validation-mlogloss:2.50367
[15]	train-mlogloss:2.51438	validation-mlogloss:2.49321
[16]	train-mlogloss:2.50452	validation-mlogloss:2.48289
[17]	train-mlogloss:2.49497	validation-mlogloss:2.47234
[18]	train-mlogloss:2.48490	validation-mlogloss:2.46111
[19]	train-mlogloss:2.47549	validation-mlogloss:2.45060
[20]	train-mlogloss:2.46684	validation-mlogloss:2.44183
[21]	train-mlogloss:2.45772	validation-mlogloss:2.43177
[22]	train-mlogloss:2.44967	validation-mlogloss:2.42394
[23]	train-mlogloss:2.44083	validation-mlogloss:2.41381
[24]	train-mlogloss:2.43251	validation-mlogloss:2.40511
[25]	train-mlogloss:2.42446	validation-mlogloss:2.39682
[26]	train-mlogloss:2.41668	validation-mlogloss:2.38862
[27]	train-mlogloss:2.40909	validation-mlogloss:2.38016
[28]	train-mlogloss:2.40130	validation-mlogloss:2.37158
[29]	train-mlogloss:2.39383	validation-mlogloss:2.36353
[30]	train-mlogloss:2.38643	validation-mlogloss:2.35520
[31]	train-mlogloss:2.37893	validation-mlogloss:2.34718
[32]	train-mlogloss:2.37173	validation-mlogloss:2.33950
[33]	train-mlogloss:2.36432	validation-mlogloss:2.33089
[34]	train-mlogloss:2.35736	validation-mlogloss:2.32328
[35]	train-mlogloss:2.35027	validation-mlogloss:2.31511
[36]	train-mlogloss:2.34315	validation-mlogloss:2.30726
[37]	train-mlogloss:2.33605	validation-mlogloss:2.29946
[38]	train-mlogloss:2.32973	validation-mlogloss:2.29288
[39]	train-mlogloss:2.32312	validation-mlogloss:2.28601
[40]	train-mlogloss:2.31689	validation-mlogloss:2.27900
[41]	train-mlogloss:2.31084	validation-mlogloss:2.27295
[42]	train-mlogloss:2.30455	validation-mlogloss:2.26630
[43]	train-mlogloss:2.29867	validation-mlogloss:2.25972
[44]	train-mlogloss:2.29278	validation-mlogloss:2.25353
[45]	train-mlogloss:2.28703	validation-mlogloss:2.24813
[46]	train-mlogloss:2.28120	validation-mlogloss:2.24226
[47]	train-mlogloss:2.27581	validation-mlogloss:2.23673
[48]	train-mlogloss:2.26990	validation-mlogloss:2.23049
[49]	train-mlogloss:2.26454	validation-mlogloss:2.22491
[50]	train-mlogloss:2.25899	validation-mlogloss:2.21934
[51]	train-mlogloss:2.25339	validation-mlogloss:2.21359
[52]	train-mlogloss:2.24790	validation-mlogloss:2.20773
[53]	train-mlogloss:2.24254	validation-mlogloss:2.20203
[54]	train-mlogloss:2.23729	validation-mlogloss:2.19606
[55]	train-mlogloss:2.23194	validation-mlogloss:2.19041
[56]	train-mlogloss:2.22690	validation-mlogloss:2.18504
[57]	train-mlogloss:2.22192	validation-mlogloss:2.17999
[58]	train-mlogloss:2.21711	validation-mlogloss:2.17544
[59]	train-mlogloss:2.21221	validation-mlogloss:2.17037
[60]	train-mlogloss:2.20723	validation-mlogloss:2.16518
[61]	train-mlogloss:2.20232	validation-mlogloss:2.16038
[62]	train-mlogloss:2.19776	validation-mlogloss:2.15665
[63]	train-mlogloss:2.19288	validation-mlogloss:2.15147
[64]	train-mlogloss:2.18821	validation-mlogloss:2.14667
[65]	train-mlogloss:2.18378	validation-mlogloss:2.14240
[66]	train-mlogloss:2.17931	validation-mlogloss:2.13805
[67]	train-mlogloss:2.17503	validation-mlogloss:2.13393
[68]	train-mlogloss:2.17054	validation-mlogloss:2.12929
[69]	train-mlogloss:2.16636	validation-mlogloss:2.12541
[70]	train-mlogloss:2.16215	validation-mlogloss:2.12117
[71]	train-mlogloss:2.15774	validation-mlogloss:2.11659
[72]	train-mlogloss:2.15346	validation-mlogloss:2.11258
[73]	train-mlogloss:2.14928	validation-mlogloss:2.10822
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[75]	train-mlogloss:2.14116	validation-mlogloss:2.10023
[76]	train-mlogloss:2.13708	validation-mlogloss:2.09613
[77]	train-mlogloss:2.13321	validation-mlogloss:2.09252
[78]	train-mlogloss:2.12901	validation-mlogloss:2.08827
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[81]	train-mlogloss:2.11703	validation-mlogloss:2.07684
[82]	train-mlogloss:2.11339	validation-mlogloss:2.07333
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[84]	train-mlogloss:2.10609	validation-mlogloss:2.06608
[85]	train-mlogloss:2.10250	validation-mlogloss:2.06282
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[91]	train-mlogloss:2.08201	validation-mlogloss:2.04367
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[93]	train-mlogloss:2.07539	validation-mlogloss:2.03716
[94]	train-mlogloss:2.07203	validation-mlogloss:2.03428
[95]	train-mlogloss:2.06854	validation-mlogloss:2.03093
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[97]	train-mlogloss:2.06198	validation-mlogloss:2.02474
[98]	train-mlogloss:2.05890	validation-mlogloss:2.02189
[99]	train-mlogloss:2.05581	validation-mlogloss:2.01941
[100]	train-mlogloss:2.05262	validation-mlogloss:2.01640
[101]	train-mlogloss:2.04950	validation-mlogloss:2.01335
[102]	train-mlogloss:2.04646	validation-mlogloss:2.01034
[103]	train-mlogloss:2.04350	validation-mlogloss:2.00757
[104]	train-mlogloss:2.04007	validation-mlogloss:2.00417
[105]	train-mlogloss:2.03695	validation-mlogloss:2.00102
[106]	train-mlogloss:2.03397	validation-mlogloss:1.99831
[107]	train-mlogloss:2.03086	validation-mlogloss:1.99539
[108]	train-mlogloss:2.02783	validation-mlogloss:1.99267
[109]	train-mlogloss:2.02489	validation-mlogloss:1.99032
[110]	train-mlogloss:2.02209	validation-mlogloss:1.98778
[111]	train-mlogloss:2.01920	validation-mlogloss:1.98500
[112]	train-mlogloss:2.01635	validation-mlogloss:1.98277
[113]	train-mlogloss:2.01366	validation-mlogloss:1.98010
[114]	train-mlogloss:2.01092	validation-mlogloss:1.97757
[115]	train-mlogloss:2.00817	validation-mlogloss:1.97539
[116]	train-mlogloss:2.00558	validation-mlogloss:1.97254
[117]	train-mlogloss:2.00287	validation-mlogloss:1.96982
[118]	train-mlogloss:2.00018	validation-mlogloss:1.96744
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[120]	train-mlogloss:1.99473	validation-mlogloss:1.96203
[121]	train-mlogloss:1.99216	validation-mlogloss:1.95958
[122]	train-mlogloss:1.98971	validation-mlogloss:1.95735
[123]	train-mlogloss:1.98699	validation-mlogloss:1.95473
[124]	train-mlogloss:1.98457	validation-mlogloss:1.95256
[125]	train-mlogloss:1.98219	validation-mlogloss:1.95061
[126]	train-mlogloss:1.97980	validation-mlogloss:1.94858
[127]	train-mlogloss:1.97722	validation-mlogloss:1.94617
[128]	train-mlogloss:1.97479	validation-mlogloss:1.94413
[129]	train-mlogloss:1.97233	validation-mlogloss:1.94200
[130]	train-mlogloss:1.96994	validation-mlogloss:1.94019
[131]	train-mlogloss:1.96727	validation-mlogloss:1.93762
[132]	train-mlogloss:1.96504	validation-mlogloss:1.93534
[133]	train-mlogloss:1.96258	validation-mlogloss:1.93295
[134]	train-mlogloss:1.96025	validation-mlogloss:1.93100
[135]	train-mlogloss:1.95774	validation-mlogloss:1.92885
[136]	train-mlogloss:1.95542	validation-mlogloss:1.92695
[137]	train-mlogloss:1.95321	validation-mlogloss:1.92509
[138]	train-mlogloss:1.95099	validation-mlogloss:1.92284
[139]	train-mlogloss:1.94845	validation-mlogloss:1.92046
[140]	train-mlogloss:1.94613	validation-mlogloss:1.91853
[141]	train-mlogloss:1.94379	validation-mlogloss:1.91619
[142]	train-mlogloss:1.94170	validation-mlogloss:1.91443
[143]	train-mlogloss:1.93946	validation-mlogloss:1.91245
[144]	train-mlogloss:1.93735	validation-mlogloss:1.91058
[145]	train-mlogloss:1.93517	validation-mlogloss:1.90892
[146]	train-mlogloss:1.93308	validation-mlogloss:1.90727
[147]	train-mlogloss:1.93100	validation-mlogloss:1.90554
[148]	train-mlogloss:1.92895	validation-mlogloss:1.90376
[149]	train-mlogloss:1.92671	validation-mlogloss:1.90193
[150]	train-mlogloss:1.92455	validation-mlogloss:1.89991
[151]	train-mlogloss:1.92255	validation-mlogloss:1.89822
[152]	train-mlogloss:1.92049	validation-mlogloss:1.89693
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[523]	train-mlogloss:1.56597	validation-mlogloss:1.68755
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[525]	train-mlogloss:1.56488	validation-mlogloss:1.68697
[526]	train-mlogloss:1.56443	validation-mlogloss:1.68684
[527]	train-mlogloss:1.56395	validation-mlogloss:1.68649
[528]	train-mlogloss:1.56346	validation-mlogloss:1.68656
[529]	train-mlogloss:1.56301	validation-mlogloss:1.68656
[530]	train-mlogloss:1.56248	validation-mlogloss:1.68641
[531]	train-mlogloss:1.56200	validation-mlogloss:1.68619
[532]	train-mlogloss:1.56154	validation-mlogloss:1.68612
[533]	train-mlogloss:1.56109	validation-mlogloss:1.68592
[534]	train-mlogloss:1.56068	validation-mlogloss:1.68592
[535]	train-mlogloss:1.56026	validation-mlogloss:1.68571
[536]	train-mlogloss:1.55984	validation-mlogloss:1.68571
[537]	train-mlogloss:1.55932	validation-mlogloss:1.68571
[538]	train-mlogloss:1.55877	validation-mlogloss:1.68553
[539]	train-mlogloss:1.55836	validation-mlogloss:1.68550
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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.06 [%]
Global accuracy score (test) = 44.57 [%]
Global F1 score (train) = 51.19 [%]
Global F1 score (test) = 44.03 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.71      0.56       184
 CAMINAR CON MÓVIL O LIBRO       0.39      0.46      0.42       184
       CAMINAR USUAL SPEED       0.32      0.26      0.29       184
            CAMINAR ZIGZAG       0.38      0.54      0.45       184
          DE PIE BARRIENDO       0.78      0.33      0.46       184
   DE PIE DOBLANDO TOALLAS       0.49      0.40      0.44       184
    DE PIE MOVIENDO LIBROS       0.37      0.36      0.36       184
          DE PIE USANDO PC       0.21      0.31      0.25       184
        FASE REPOSO CON K5       0.56      0.86      0.68       184
INCREMENTAL CICLOERGOMETRO       0.75      0.69      0.72       184
           SENTADO LEYENDO       0.45      0.32      0.37       184
         SENTADO USANDO PC       0.26      0.16      0.20       184
      SENTADO VIENDO LA TV       0.29      0.25      0.27       184
   SUBIR Y BAJAR ESCALERAS       0.57      0.49      0.53       184
                    TROTAR       0.65      0.58      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 1: 44.57 [%]
F1-score capturado en la ejecución 1: 44.03 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.19 [%]
Global accuracy score (test) = 45.34 [%]
Global F1 score (train) = 51.33 [%]
Global F1 score (test) = 44.84 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.76      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.36      0.46      0.41       184
       CAMINAR USUAL SPEED       0.36      0.28      0.32       184
            CAMINAR ZIGZAG       0.41      0.54      0.46       184
          DE PIE BARRIENDO       0.77      0.29      0.42       184
   DE PIE DOBLANDO TOALLAS       0.52      0.43      0.47       184
    DE PIE MOVIENDO LIBROS       0.37      0.34      0.35       184
          DE PIE USANDO PC       0.19      0.31      0.23       184
        FASE REPOSO CON K5       0.58      0.85      0.69       184
INCREMENTAL CICLOERGOMETRO       0.76      0.69      0.72       184
           SENTADO LEYENDO       0.52      0.35      0.42       184
         SENTADO USANDO PC       0.20      0.12      0.15       184
      SENTADO VIENDO LA TV       0.34      0.28      0.31       184
   SUBIR Y BAJAR ESCALERAS       0.63      0.54      0.58       184
                    TROTAR       0.66      0.57      0.61       161

                  accuracy                           0.45      2737
                 macro avg       0.48      0.45      0.45      2737
              weighted avg       0.47      0.45      0.45      2737


Accuracy capturado en la ejecución 2: 45.34 [%]
F1-score capturado en la ejecución 2: 44.84 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.43 [%]
Global accuracy score (test) = 45.01 [%]
Global F1 score (train) = 51.55 [%]
Global F1 score (test) = 44.43 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.73      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.37      0.46      0.41       184
       CAMINAR USUAL SPEED       0.33      0.27      0.30       184
            CAMINAR ZIGZAG       0.39      0.53      0.45       184
          DE PIE BARRIENDO       0.74      0.30      0.43       184
   DE PIE DOBLANDO TOALLAS       0.51      0.41      0.46       184
    DE PIE MOVIENDO LIBROS       0.39      0.35      0.37       184
          DE PIE USANDO PC       0.20      0.30      0.24       184
        FASE REPOSO CON K5       0.57      0.86      0.68       184
INCREMENTAL CICLOERGOMETRO       0.74      0.70      0.72       184
           SENTADO LEYENDO       0.49      0.39      0.43       184
         SENTADO USANDO PC       0.23      0.14      0.18       184
      SENTADO VIENDO LA TV       0.28      0.23      0.25       184
   SUBIR Y BAJAR ESCALERAS       0.64      0.51      0.57       184
                    TROTAR       0.65      0.57      0.61       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.45      0.44      2737
              weighted avg       0.46      0.45      0.44      2737


Accuracy capturado en la ejecución 3: 45.01 [%]
F1-score capturado en la ejecución 3: 44.43 [%]

=== EJECUCIÓN 4 ===

--- TRAIN (ejecución 4) ---

--- TEST (ejecución 4) ---
2025-10-27 09:39:24.065864: 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`.
2025-10-27 09:39:24.078567: 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 00:00:1761554364.092303  405908 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554364.096686  405908 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554364.107718  405908 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554364.107744  405908 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554364.107747  405908 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554364.107749  405908 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:39:24.111164: 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:2.69364	validation-mlogloss:2.69244
[1]	train-mlogloss:2.67894	validation-mlogloss:2.67639
[2]	train-mlogloss:2.66775	validation-mlogloss:2.66367
[3]	train-mlogloss:2.65524	validation-mlogloss:2.64994
[4]	train-mlogloss:2.64259	validation-mlogloss:2.63559
[5]	train-mlogloss:2.62878	validation-mlogloss:2.62058
[6]	train-mlogloss:2.61570	validation-mlogloss:2.60616
[7]	train-mlogloss:2.60321	validation-mlogloss:2.59253
[8]	train-mlogloss:2.59122	validation-mlogloss:2.57980
[9]	train-mlogloss:2.57943	validation-mlogloss:2.56699
[10]	train-mlogloss:2.56798	validation-mlogloss:2.55390
[11]	train-mlogloss:2.55669	validation-mlogloss:2.54155
[12]	train-mlogloss:2.54618	validation-mlogloss:2.52949
[13]	train-mlogloss:2.53580	validation-mlogloss:2.51823
[14]	train-mlogloss:2.52565	validation-mlogloss:2.50708
[15]	train-mlogloss:2.51579	validation-mlogloss:2.49638
[16]	train-mlogloss:2.50662	validation-mlogloss:2.48674
[17]	train-mlogloss:2.49687	validation-mlogloss:2.47566
[18]	train-mlogloss:2.48766	validation-mlogloss:2.46633
[19]	train-mlogloss:2.47840	validation-mlogloss:2.45552
[20]	train-mlogloss:2.46912	validation-mlogloss:2.44498
[21]	train-mlogloss:2.46046	validation-mlogloss:2.43555
[22]	train-mlogloss:2.45221	validation-mlogloss:2.42615
[23]	train-mlogloss:2.44370	validation-mlogloss:2.41740
[24]	train-mlogloss:2.43558	validation-mlogloss:2.40843
[25]	train-mlogloss:2.42759	validation-mlogloss:2.39978
[26]	train-mlogloss:2.41972	validation-mlogloss:2.39058
[27]	train-mlogloss:2.41173	validation-mlogloss:2.38211
[28]	train-mlogloss:2.40368	validation-mlogloss:2.37340
[29]	train-mlogloss:2.39628	validation-mlogloss:2.36558
[30]	train-mlogloss:2.38797	validation-mlogloss:2.35666
[31]	train-mlogloss:2.38110	validation-mlogloss:2.34947
[32]	train-mlogloss:2.37416	validation-mlogloss:2.34177
[33]	train-mlogloss:2.36722	validation-mlogloss:2.33485
[34]	train-mlogloss:2.36001	validation-mlogloss:2.32705
[35]	train-mlogloss:2.35315	validation-mlogloss:2.31945
[36]	train-mlogloss:2.34639	validation-mlogloss:2.31225
[37]	train-mlogloss:2.33943	validation-mlogloss:2.30444
[38]	train-mlogloss:2.33331	validation-mlogloss:2.29717
[39]	train-mlogloss:2.32697	validation-mlogloss:2.29059
[40]	train-mlogloss:2.32067	validation-mlogloss:2.28373
[41]	train-mlogloss:2.31428	validation-mlogloss:2.27653
[42]	train-mlogloss:2.30804	validation-mlogloss:2.26984
[43]	train-mlogloss:2.30186	validation-mlogloss:2.26301
[44]	train-mlogloss:2.29561	validation-mlogloss:2.25630
[45]	train-mlogloss:2.28990	validation-mlogloss:2.25026
[46]	train-mlogloss:2.28384	validation-mlogloss:2.24377
[47]	train-mlogloss:2.27773	validation-mlogloss:2.23789
[48]	train-mlogloss:2.27196	validation-mlogloss:2.23188
[49]	train-mlogloss:2.26649	validation-mlogloss:2.22664
[50]	train-mlogloss:2.26082	validation-mlogloss:2.22058
[51]	train-mlogloss:2.25540	validation-mlogloss:2.21452
[52]	train-mlogloss:2.25014	validation-mlogloss:2.20878
[53]	train-mlogloss:2.24476	validation-mlogloss:2.20333
[54]	train-mlogloss:2.23944	validation-mlogloss:2.19766
[55]	train-mlogloss:2.23426	validation-mlogloss:2.19269
[56]	train-mlogloss:2.22896	validation-mlogloss:2.18713
[57]	train-mlogloss:2.22424	validation-mlogloss:2.18252
[58]	train-mlogloss:2.21919	validation-mlogloss:2.17719
[59]	train-mlogloss:2.21390	validation-mlogloss:2.17173
[60]	train-mlogloss:2.20915	validation-mlogloss:2.16734
[61]	train-mlogloss:2.20410	validation-mlogloss:2.16199
[62]	train-mlogloss:2.19922	validation-mlogloss:2.15693
[63]	train-mlogloss:2.19439	validation-mlogloss:2.15196
[64]	train-mlogloss:2.18980	validation-mlogloss:2.14726
[65]	train-mlogloss:2.18507	validation-mlogloss:2.14225
[66]	train-mlogloss:2.18069	validation-mlogloss:2.13844
[67]	train-mlogloss:2.17606	validation-mlogloss:2.13383
[68]	train-mlogloss:2.17177	validation-mlogloss:2.12941
[69]	train-mlogloss:2.16732	validation-mlogloss:2.12481
[70]	train-mlogloss:2.16290	validation-mlogloss:2.12024
[71]	train-mlogloss:2.15865	validation-mlogloss:2.11635
[72]	train-mlogloss:2.15460	validation-mlogloss:2.11209
[73]	train-mlogloss:2.15021	validation-mlogloss:2.10794
[74]	train-mlogloss:2.14598	validation-mlogloss:2.10375
[75]	train-mlogloss:2.14169	validation-mlogloss:2.09971
[76]	train-mlogloss:2.13775	validation-mlogloss:2.09576
[77]	train-mlogloss:2.13348	validation-mlogloss:2.09110
[78]	train-mlogloss:2.12957	validation-mlogloss:2.08729
[79]	train-mlogloss:2.12583	validation-mlogloss:2.08342
[80]	train-mlogloss:2.12216	validation-mlogloss:2.07968
[81]	train-mlogloss:2.11841	validation-mlogloss:2.07617
[82]	train-mlogloss:2.11462	validation-mlogloss:2.07257
[83]	train-mlogloss:2.11084	validation-mlogloss:2.06886
[84]	train-mlogloss:2.10714	validation-mlogloss:2.06549
[85]	train-mlogloss:2.10351	validation-mlogloss:2.06157
[86]	train-mlogloss:2.09969	validation-mlogloss:2.05765
[87]	train-mlogloss:2.09615	validation-mlogloss:2.05432
[88]	train-mlogloss:2.09274	validation-mlogloss:2.05083
[89]	train-mlogloss:2.08925	validation-mlogloss:2.04748
[90]	train-mlogloss:2.08561	validation-mlogloss:2.04388
[91]	train-mlogloss:2.08237	validation-mlogloss:2.04109
[92]	train-mlogloss:2.07913	validation-mlogloss:2.03801
[93]	train-mlogloss:2.07560	validation-mlogloss:2.03500
[94]	train-mlogloss:2.07228	validation-mlogloss:2.03187
[95]	train-mlogloss:2.06914	validation-mlogloss:2.02854
[96]	train-mlogloss:2.06597	validation-mlogloss:2.02564
[97]	train-mlogloss:2.06268	validation-mlogloss:2.02288
[98]	train-mlogloss:2.05949	validation-mlogloss:2.02008
[99]	train-mlogloss:2.05638	validation-mlogloss:2.01720
[100]	train-mlogloss:2.05339	validation-mlogloss:2.01420
[101]	train-mlogloss:2.05030	validation-mlogloss:2.01136
[102]	train-mlogloss:2.04729	validation-mlogloss:2.00838
[103]	train-mlogloss:2.04419	validation-mlogloss:2.00538
[104]	train-mlogloss:2.04113	validation-mlogloss:2.00228
[105]	train-mlogloss:2.03806	validation-mlogloss:1.99947
[106]	train-mlogloss:2.03519	validation-mlogloss:1.99710
[107]	train-mlogloss:2.03215	validation-mlogloss:1.99439
[108]	train-mlogloss:2.02935	validation-mlogloss:1.99185
[109]	train-mlogloss:2.02633	validation-mlogloss:1.98898
[110]	train-mlogloss:2.02327	validation-mlogloss:1.98591
[111]	train-mlogloss:2.02039	validation-mlogloss:1.98330
[112]	train-mlogloss:2.01731	validation-mlogloss:1.98050
[113]	train-mlogloss:2.01440	validation-mlogloss:1.97797
[114]	train-mlogloss:2.01160	validation-mlogloss:1.97540
[115]	train-mlogloss:2.00898	validation-mlogloss:1.97310
[116]	train-mlogloss:2.00627	validation-mlogloss:1.97102
[117]	train-mlogloss:2.00351	validation-mlogloss:1.96845
[118]	train-mlogloss:2.00087	validation-mlogloss:1.96597
[119]	train-mlogloss:1.99828	validation-mlogloss:1.96390
[120]	train-mlogloss:1.99582	validation-mlogloss:1.96164
[121]	train-mlogloss:1.99316	validation-mlogloss:1.95919
[122]	train-mlogloss:1.99050	validation-mlogloss:1.95690
[123]	train-mlogloss:1.98815	validation-mlogloss:1.95482
[124]	train-mlogloss:1.98572	validation-mlogloss:1.95245
[125]	train-mlogloss:1.98317	validation-mlogloss:1.95025
[126]	train-mlogloss:1.98058	validation-mlogloss:1.94787
[127]	train-mlogloss:1.97817	validation-mlogloss:1.94600
[128]	train-mlogloss:1.97569	validation-mlogloss:1.94396
[129]	train-mlogloss:1.97316	validation-mlogloss:1.94180
[130]	train-mlogloss:1.97071	validation-mlogloss:1.93971
[131]	train-mlogloss:1.96809	validation-mlogloss:1.93699
[132]	train-mlogloss:1.96577	validation-mlogloss:1.93460
[133]	train-mlogloss:1.96342	validation-mlogloss:1.93253
[134]	train-mlogloss:1.96111	validation-mlogloss:1.93069
[135]	train-mlogloss:1.95854	validation-mlogloss:1.92845
[136]	train-mlogloss:1.95634	validation-mlogloss:1.92656
[137]	train-mlogloss:1.95395	validation-mlogloss:1.92451
[138]	train-mlogloss:1.95172	validation-mlogloss:1.92277
[139]	train-mlogloss:1.94952	validation-mlogloss:1.92085
[140]	train-mlogloss:1.94737	validation-mlogloss:1.91922
[141]	train-mlogloss:1.94525	validation-mlogloss:1.91733
[142]	train-mlogloss:1.94302	validation-mlogloss:1.91526
[143]	train-mlogloss:1.94080	validation-mlogloss:1.91289
[144]	train-mlogloss:1.93879	validation-mlogloss:1.91087
[145]	train-mlogloss:1.93673	validation-mlogloss:1.90894
[146]	train-mlogloss:1.93469	validation-mlogloss:1.90751
[147]	train-mlogloss:1.93248	validation-mlogloss:1.90550
[148]	train-mlogloss:1.93027	validation-mlogloss:1.90402
[149]	train-mlogloss:1.92834	validation-mlogloss:1.90249
[150]	train-mlogloss:1.92617	validation-mlogloss:1.90073
[151]	train-mlogloss:1.92390	validation-mlogloss:1.89887
[152]	train-mlogloss:1.92181	validation-mlogloss:1.89703
[153]	train-mlogloss:1.91974	validation-mlogloss:1.89506
[154]	train-mlogloss:1.91768	validation-mlogloss:1.89315
[155]	train-mlogloss:1.91567	validation-mlogloss:1.89133
[156]	train-mlogloss:1.91343	validation-mlogloss:1.88922
[157]	train-mlogloss:1.91164	validation-mlogloss:1.88776
[158]	train-mlogloss:1.90960	validation-mlogloss:1.88605
[159]	train-mlogloss:1.90774	validation-mlogloss:1.88422
[160]	train-mlogloss:1.90592	validation-mlogloss:1.88288
[161]	train-mlogloss:1.90381	validation-mlogloss:1.88108
[162]	train-mlogloss:1.90191	validation-mlogloss:1.87936
[163]	train-mlogloss:1.89997	validation-mlogloss:1.87812
[164]	train-mlogloss:1.89807	validation-mlogloss:1.87619
[165]	train-mlogloss:1.89616	validation-mlogloss:1.87447
[166]	train-mlogloss:1.89412	validation-mlogloss:1.87258
[167]	train-mlogloss:1.89209	validation-mlogloss:1.87081
[168]	train-mlogloss:1.89017	validation-mlogloss:1.86935
[169]	train-mlogloss:1.88844	validation-mlogloss:1.86803
[170]	train-mlogloss:1.88661	validation-mlogloss:1.86620
[171]	train-mlogloss:1.88484	validation-mlogloss:1.86444
[172]	train-mlogloss:1.88314	validation-mlogloss:1.86317
[173]	train-mlogloss:1.88136	validation-mlogloss:1.86167
[174]	train-mlogloss:1.87957	validation-mlogloss:1.86039
[175]	train-mlogloss:1.87774	validation-mlogloss:1.85891
[176]	train-mlogloss:1.87584	validation-mlogloss:1.85737
[177]	train-mlogloss:1.87402	validation-mlogloss:1.85594
[178]	train-mlogloss:1.87230	validation-mlogloss:1.85477
[179]	train-mlogloss:1.87067	validation-mlogloss:1.85313
[180]	train-mlogloss:1.86889	validation-mlogloss:1.85153
[181]	train-mlogloss:1.86719	validation-mlogloss:1.84991
[182]	train-mlogloss:1.86557	validation-mlogloss:1.84846
[183]	train-mlogloss:1.86380	validation-mlogloss:1.84695
[184]	train-mlogloss:1.86225	validation-mlogloss:1.84554
[185]	train-mlogloss:1.86061	validation-mlogloss:1.84430
[186]	train-mlogloss:1.85901	validation-mlogloss:1.84315
[187]	train-mlogloss:1.85750	validation-mlogloss:1.84170
[188]	train-mlogloss:1.85592	validation-mlogloss:1.84078
[189]	train-mlogloss:1.85424	validation-mlogloss:1.83894
[190]	train-mlogloss:1.85272	validation-mlogloss:1.83750
[191]	train-mlogloss:1.85124	validation-mlogloss:1.83638
[192]	train-mlogloss:1.84967	validation-mlogloss:1.83519
[193]	train-mlogloss:1.84812	validation-mlogloss:1.83403
[194]	train-mlogloss:1.84662	validation-mlogloss:1.83285
[195]	train-mlogloss:1.84512	validation-mlogloss:1.83159
[196]	train-mlogloss:1.84365	validation-mlogloss:1.83070
[197]	train-mlogloss:1.84215	validation-mlogloss:1.82941
[198]	train-mlogloss:1.84054	validation-mlogloss:1.82837
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[499]	train-mlogloss:1.57799	validation-mlogloss:1.68766
[500]	train-mlogloss:1.57743	validation-mlogloss:1.68754
[501]	train-mlogloss:1.57687	validation-mlogloss:1.68740
[502]	train-mlogloss:1.57634	validation-mlogloss:1.68718
[503]	train-mlogloss:1.57583	validation-mlogloss:1.68694
[504]	train-mlogloss:1.57537	validation-mlogloss:1.68681
[505]	train-mlogloss:1.57480	validation-mlogloss:1.68666
[506]	train-mlogloss:1.57429	validation-mlogloss:1.68656
[507]	train-mlogloss:1.57380	validation-mlogloss:1.68637
[508]	train-mlogloss:1.57331	validation-mlogloss:1.68620
[509]	train-mlogloss:1.57281	validation-mlogloss:1.68611
[510]	train-mlogloss:1.57229	validation-mlogloss:1.68611
[511]	train-mlogloss:1.57178	validation-mlogloss:1.68582
[512]	train-mlogloss:1.57123	validation-mlogloss:1.68555
[513]	train-mlogloss:1.57080	validation-mlogloss:1.68548
[514]	train-mlogloss:1.57025	validation-mlogloss:1.68535
[515]	train-mlogloss:1.56985	validation-mlogloss:1.68529
[516]	train-mlogloss:1.56938	validation-mlogloss:1.68521
[517]	train-mlogloss:1.56889	validation-mlogloss:1.68510
[518]	train-mlogloss:1.56851	validation-mlogloss:1.68497
[519]	train-mlogloss:1.56807	validation-mlogloss:1.68475
[520]	train-mlogloss:1.56760	validation-mlogloss:1.68467
[521]	train-mlogloss:1.56712	validation-mlogloss:1.68467
[522]	train-mlogloss:1.56665	validation-mlogloss:1.68461
[523]	train-mlogloss:1.56616	validation-mlogloss:1.68450
[524]	train-mlogloss:1.56557	validation-mlogloss:1.68411
[525]	train-mlogloss:1.56510	validation-mlogloss:1.68424
[526]	train-mlogloss:1.56470	validation-mlogloss:1.68415
[527]	train-mlogloss:1.56425	validation-mlogloss:1.68396
[528]	train-mlogloss:1.56378	validation-mlogloss:1.68390
[529]	train-mlogloss:1.56331	validation-mlogloss:1.68389
[530]	train-mlogloss:1.56280	validation-mlogloss:1.68399
[531]	train-mlogloss:1.56239	validation-mlogloss:1.68385
[532]	train-mlogloss:1.56197	validation-mlogloss:1.68389
[533]	train-mlogloss:1.56148	validation-mlogloss:1.68374
[534]	train-mlogloss:1.56102	validation-mlogloss:1.68373
[535]	train-mlogloss:1.56054	validation-mlogloss:1.68347
[536]	train-mlogloss:1.56015	validation-mlogloss:1.68342
[537]	train-mlogloss:1.55971	validation-mlogloss:1.68333
[538]	train-mlogloss:1.55927	validation-mlogloss:1.68309
[539]	train-mlogloss:1.55886	validation-mlogloss:1.68292
Saved model to disk.
2025-10-27 09:40:09.660510: 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`.
2025-10-27 09:40:09.673339: 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 00:00:1761554409.687629  406818 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554409.692104  406818 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554409.703446  406818 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554409.703469  406818 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554409.703473  406818 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554409.703476  406818 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:40:09.706829: 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:2.69285	validation-mlogloss:2.69112
[1]	train-mlogloss:2.68066	validation-mlogloss:2.67670
[2]	train-mlogloss:2.66752	validation-mlogloss:2.66226
[3]	train-mlogloss:2.65369	validation-mlogloss:2.64581
[4]	train-mlogloss:2.64172	validation-mlogloss:2.63174
[5]	train-mlogloss:2.62962	validation-mlogloss:2.61825
[6]	train-mlogloss:2.61709	validation-mlogloss:2.60474
[7]	train-mlogloss:2.60546	validation-mlogloss:2.59277
[8]	train-mlogloss:2.59326	validation-mlogloss:2.57904
[9]	train-mlogloss:2.58152	validation-mlogloss:2.56598
[10]	train-mlogloss:2.57097	validation-mlogloss:2.55428
[11]	train-mlogloss:2.56004	validation-mlogloss:2.54178
[12]	train-mlogloss:2.54925	validation-mlogloss:2.52955
[13]	train-mlogloss:2.53898	validation-mlogloss:2.51804
[14]	train-mlogloss:2.52958	validation-mlogloss:2.50775
[15]	train-mlogloss:2.51955	validation-mlogloss:2.49676
[16]	train-mlogloss:2.50976	validation-mlogloss:2.48600
[17]	train-mlogloss:2.50056	validation-mlogloss:2.47625
[18]	train-mlogloss:2.49103	validation-mlogloss:2.46573
[19]	train-mlogloss:2.48206	validation-mlogloss:2.45550
[20]	train-mlogloss:2.47321	validation-mlogloss:2.44602
[21]	train-mlogloss:2.46409	validation-mlogloss:2.43658
[22]	train-mlogloss:2.45525	validation-mlogloss:2.42707
[23]	train-mlogloss:2.44668	validation-mlogloss:2.41788
[24]	train-mlogloss:2.43848	validation-mlogloss:2.40900
[25]	train-mlogloss:2.43069	validation-mlogloss:2.40062
[26]	train-mlogloss:2.42288	validation-mlogloss:2.39224
[27]	train-mlogloss:2.41497	validation-mlogloss:2.38341
[28]	train-mlogloss:2.40660	validation-mlogloss:2.37454
[29]	train-mlogloss:2.39898	validation-mlogloss:2.36614
[30]	train-mlogloss:2.39155	validation-mlogloss:2.35812
[31]	train-mlogloss:2.38385	validation-mlogloss:2.34934
[32]	train-mlogloss:2.37680	validation-mlogloss:2.34202
[33]	train-mlogloss:2.36986	validation-mlogloss:2.33484
[34]	train-mlogloss:2.36320	validation-mlogloss:2.32753
[35]	train-mlogloss:2.35599	validation-mlogloss:2.31961
[36]	train-mlogloss:2.34861	validation-mlogloss:2.31229
[37]	train-mlogloss:2.34212	validation-mlogloss:2.30540
[38]	train-mlogloss:2.33561	validation-mlogloss:2.29864
[39]	train-mlogloss:2.32896	validation-mlogloss:2.29154
[40]	train-mlogloss:2.32242	validation-mlogloss:2.28471
[41]	train-mlogloss:2.31611	validation-mlogloss:2.27831
[42]	train-mlogloss:2.31014	validation-mlogloss:2.27170
[43]	train-mlogloss:2.30397	validation-mlogloss:2.26602
[44]	train-mlogloss:2.29798	validation-mlogloss:2.25927
[45]	train-mlogloss:2.29174	validation-mlogloss:2.25240
[46]	train-mlogloss:2.28585	validation-mlogloss:2.24591
[47]	train-mlogloss:2.28016	validation-mlogloss:2.23989
[48]	train-mlogloss:2.27442	validation-mlogloss:2.23410
[49]	train-mlogloss:2.26890	validation-mlogloss:2.22838
[50]	train-mlogloss:2.26343	validation-mlogloss:2.22316
[51]	train-mlogloss:2.25813	validation-mlogloss:2.21776
[52]	train-mlogloss:2.25271	validation-mlogloss:2.21224
[53]	train-mlogloss:2.24729	validation-mlogloss:2.20605
[54]	train-mlogloss:2.24175	validation-mlogloss:2.20020
[55]	train-mlogloss:2.23662	validation-mlogloss:2.19507
[56]	train-mlogloss:2.23118	validation-mlogloss:2.18923
[57]	train-mlogloss:2.22624	validation-mlogloss:2.18412
[58]	train-mlogloss:2.22126	validation-mlogloss:2.17883
[59]	train-mlogloss:2.21629	validation-mlogloss:2.17419
[60]	train-mlogloss:2.21141	validation-mlogloss:2.16890
[61]	train-mlogloss:2.20666	validation-mlogloss:2.16446
[62]	train-mlogloss:2.20180	validation-mlogloss:2.15989
[63]	train-mlogloss:2.19711	validation-mlogloss:2.15530
[64]	train-mlogloss:2.19260	validation-mlogloss:2.15064
[65]	train-mlogloss:2.18799	validation-mlogloss:2.14620
[66]	train-mlogloss:2.18339	validation-mlogloss:2.14140
[67]	train-mlogloss:2.17881	validation-mlogloss:2.13703
[68]	train-mlogloss:2.17447	validation-mlogloss:2.13254
[69]	train-mlogloss:2.17011	validation-mlogloss:2.12789
[70]	train-mlogloss:2.16574	validation-mlogloss:2.12316
[71]	train-mlogloss:2.16138	validation-mlogloss:2.11839
[72]	train-mlogloss:2.15713	validation-mlogloss:2.11418
[73]	train-mlogloss:2.15278	validation-mlogloss:2.10996
[74]	train-mlogloss:2.14843	validation-mlogloss:2.10547
[75]	train-mlogloss:2.14428	validation-mlogloss:2.10144
[76]	train-mlogloss:2.14024	validation-mlogloss:2.09716
[77]	train-mlogloss:2.13590	validation-mlogloss:2.09290
[78]	train-mlogloss:2.13182	validation-mlogloss:2.08895
[79]	train-mlogloss:2.12797	validation-mlogloss:2.08538
[80]	train-mlogloss:2.12412	validation-mlogloss:2.08175
[81]	train-mlogloss:2.12025	validation-mlogloss:2.07806
[82]	train-mlogloss:2.11633	validation-mlogloss:2.07417
[83]	train-mlogloss:2.11260	validation-mlogloss:2.07019
[84]	train-mlogloss:2.10872	validation-mlogloss:2.06604
[85]	train-mlogloss:2.10494	validation-mlogloss:2.06253
[86]	train-mlogloss:2.10137	validation-mlogloss:2.05882
[87]	train-mlogloss:2.09775	validation-mlogloss:2.05533
[88]	train-mlogloss:2.09433	validation-mlogloss:2.05215
[89]	train-mlogloss:2.09084	validation-mlogloss:2.04868
[90]	train-mlogloss:2.08742	validation-mlogloss:2.04558
[91]	train-mlogloss:2.08396	validation-mlogloss:2.04226
[92]	train-mlogloss:2.08071	validation-mlogloss:2.03934
[93]	train-mlogloss:2.07727	validation-mlogloss:2.03609
[94]	train-mlogloss:2.07399	validation-mlogloss:2.03287
[95]	train-mlogloss:2.07061	validation-mlogloss:2.03003
[96]	train-mlogloss:2.06740	validation-mlogloss:2.02674
[97]	train-mlogloss:2.06398	validation-mlogloss:2.02329
[98]	train-mlogloss:2.06092	validation-mlogloss:2.02052
[99]	train-mlogloss:2.05777	validation-mlogloss:2.01752
[100]	train-mlogloss:2.05463	validation-mlogloss:2.01474
[101]	train-mlogloss:2.05158	validation-mlogloss:2.01188
[102]	train-mlogloss:2.04865	validation-mlogloss:2.00920
[103]	train-mlogloss:2.04551	validation-mlogloss:2.00609
[104]	train-mlogloss:2.04254	validation-mlogloss:2.00341
[105]	train-mlogloss:2.03948	validation-mlogloss:2.00061
[106]	train-mlogloss:2.03636	validation-mlogloss:1.99778
[107]	train-mlogloss:2.03345	validation-mlogloss:1.99515
[108]	train-mlogloss:2.03053	validation-mlogloss:1.99244
[109]	train-mlogloss:2.02769	validation-mlogloss:1.99005
[110]	train-mlogloss:2.02488	validation-mlogloss:1.98734
[111]	train-mlogloss:2.02178	validation-mlogloss:1.98454
[112]	train-mlogloss:2.01884	validation-mlogloss:1.98197
[113]	train-mlogloss:2.01603	validation-mlogloss:1.97951
[114]	train-mlogloss:2.01318	validation-mlogloss:1.97717
[115]	train-mlogloss:2.01034	validation-mlogloss:1.97431
[116]	train-mlogloss:2.00745	validation-mlogloss:1.97153
[117]	train-mlogloss:2.00481	validation-mlogloss:1.96917
[118]	train-mlogloss:2.00223	validation-mlogloss:1.96699
[119]	train-mlogloss:1.99956	validation-mlogloss:1.96445
[120]	train-mlogloss:1.99661	validation-mlogloss:1.96152
[121]	train-mlogloss:1.99407	validation-mlogloss:1.95911
[122]	train-mlogloss:1.99149	validation-mlogloss:1.95691
[123]	train-mlogloss:1.98890	validation-mlogloss:1.95447
[124]	train-mlogloss:1.98612	validation-mlogloss:1.95168
[125]	train-mlogloss:1.98371	validation-mlogloss:1.94964
[126]	train-mlogloss:1.98110	validation-mlogloss:1.94751
[127]	train-mlogloss:1.97864	validation-mlogloss:1.94541
[128]	train-mlogloss:1.97612	validation-mlogloss:1.94273
[129]	train-mlogloss:1.97379	validation-mlogloss:1.94099
[130]	train-mlogloss:1.97143	validation-mlogloss:1.93903
[131]	train-mlogloss:1.96914	validation-mlogloss:1.93691
[132]	train-mlogloss:1.96677	validation-mlogloss:1.93513
[133]	train-mlogloss:1.96455	validation-mlogloss:1.93316
[134]	train-mlogloss:1.96218	validation-mlogloss:1.93114
[135]	train-mlogloss:1.95970	validation-mlogloss:1.92961
[136]	train-mlogloss:1.95738	validation-mlogloss:1.92738
[137]	train-mlogloss:1.95513	validation-mlogloss:1.92550
[138]	train-mlogloss:1.95278	validation-mlogloss:1.92340
[139]	train-mlogloss:1.95052	validation-mlogloss:1.92139
[140]	train-mlogloss:1.94822	validation-mlogloss:1.91940
[141]	train-mlogloss:1.94582	validation-mlogloss:1.91691
[142]	train-mlogloss:1.94357	validation-mlogloss:1.91484
[143]	train-mlogloss:1.94143	validation-mlogloss:1.91270
[144]	train-mlogloss:1.93915	validation-mlogloss:1.91065
[145]	train-mlogloss:1.93690	validation-mlogloss:1.90855
[146]	train-mlogloss:1.93478	validation-mlogloss:1.90625
[147]	train-mlogloss:1.93273	validation-mlogloss:1.90452
[148]	train-mlogloss:1.93073	validation-mlogloss:1.90257
[149]	train-mlogloss:1.92862	validation-mlogloss:1.90071
[150]	train-mlogloss:1.92657	validation-mlogloss:1.89877
[151]	train-mlogloss:1.92457	validation-mlogloss:1.89725
[152]	train-mlogloss:1.92248	validation-mlogloss:1.89521
[153]	train-mlogloss:1.92046	validation-mlogloss:1.89339
[154]	train-mlogloss:1.91840	validation-mlogloss:1.89159
[155]	train-mlogloss:1.91650	validation-mlogloss:1.88998
[156]	train-mlogloss:1.91454	validation-mlogloss:1.88876
[157]	train-mlogloss:1.91245	validation-mlogloss:1.88698
[158]	train-mlogloss:1.91057	validation-mlogloss:1.88539
[159]	train-mlogloss:1.90854	validation-mlogloss:1.88361
[160]	train-mlogloss:1.90677	validation-mlogloss:1.88222
[161]	train-mlogloss:1.90498	validation-mlogloss:1.88070
[162]	train-mlogloss:1.90305	validation-mlogloss:1.87921
[163]	train-mlogloss:1.90118	validation-mlogloss:1.87766
[164]	train-mlogloss:1.89916	validation-mlogloss:1.87599
[165]	train-mlogloss:1.89715	validation-mlogloss:1.87486
[166]	train-mlogloss:1.89511	validation-mlogloss:1.87322
[167]	train-mlogloss:1.89315	validation-mlogloss:1.87149
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[169]	train-mlogloss:1.88963	validation-mlogloss:1.86856
[170]	train-mlogloss:1.88783	validation-mlogloss:1.86685
[171]	train-mlogloss:1.88603	validation-mlogloss:1.86505
[172]	train-mlogloss:1.88402	validation-mlogloss:1.86335
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[181]	train-mlogloss:1.86853	validation-mlogloss:1.85120
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[185]	train-mlogloss:1.86208	validation-mlogloss:1.84617
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[189]	train-mlogloss:1.85534	validation-mlogloss:1.84061
[190]	train-mlogloss:1.85375	validation-mlogloss:1.83939
[191]	train-mlogloss:1.85203	validation-mlogloss:1.83780
[192]	train-mlogloss:1.85044	validation-mlogloss:1.83656
[193]	train-mlogloss:1.84899	validation-mlogloss:1.83535
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[195]	train-mlogloss:1.84604	validation-mlogloss:1.83351
[196]	train-mlogloss:1.84467	validation-mlogloss:1.83238
[197]	train-mlogloss:1.84318	validation-mlogloss:1.83107
[198]	train-mlogloss:1.84174	validation-mlogloss:1.83020
[199]	train-mlogloss:1.84003	validation-mlogloss:1.82918
[200]	train-mlogloss:1.83841	validation-mlogloss:1.82803
[201]	train-mlogloss:1.83693	validation-mlogloss:1.82680
[202]	train-mlogloss:1.83540	validation-mlogloss:1.82562
[203]	train-mlogloss:1.83388	validation-mlogloss:1.82447
[204]	train-mlogloss:1.83242	validation-mlogloss:1.82327
[205]	train-mlogloss:1.83084	validation-mlogloss:1.82227
[206]	train-mlogloss:1.82944	validation-mlogloss:1.82140
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[208]	train-mlogloss:1.82638	validation-mlogloss:1.81907
[209]	train-mlogloss:1.82490	validation-mlogloss:1.81786
[210]	train-mlogloss:1.82338	validation-mlogloss:1.81687
[211]	train-mlogloss:1.82199	validation-mlogloss:1.81552
[212]	train-mlogloss:1.82044	validation-mlogloss:1.81440
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[214]	train-mlogloss:1.81764	validation-mlogloss:1.81239
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[222]	train-mlogloss:1.80661	validation-mlogloss:1.80432
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[534]	train-mlogloss:1.56210	validation-mlogloss:1.67932
[535]	train-mlogloss:1.56173	validation-mlogloss:1.67919
[536]	train-mlogloss:1.56122	validation-mlogloss:1.67936
[537]	train-mlogloss:1.56067	validation-mlogloss:1.67924
[538]	train-mlogloss:1.56017	validation-mlogloss:1.67919
[539]	train-mlogloss:1.55972	validation-mlogloss:1.67923
Saved model to disk.
2025-10-27 09:40:55.004078: 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`.
2025-10-27 09:40:55.016890: 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 00:00:1761554455.030538  407709 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554455.034686  407709 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554455.045727  407709 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554455.045750  407709 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554455.045753  407709 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554455.045756  407709 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:40:55.049061: 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:2.69583	validation-mlogloss:2.69377
[1]	train-mlogloss:2.68085	validation-mlogloss:2.67662
[2]	train-mlogloss:2.66781	validation-mlogloss:2.66185
[3]	train-mlogloss:2.65466	validation-mlogloss:2.64719
[4]	train-mlogloss:2.64187	validation-mlogloss:2.63304
[5]	train-mlogloss:2.62804	validation-mlogloss:2.61746
[6]	train-mlogloss:2.61512	validation-mlogloss:2.60272
[7]	train-mlogloss:2.60298	validation-mlogloss:2.58929
[8]	train-mlogloss:2.59104	validation-mlogloss:2.57660
[9]	train-mlogloss:2.58028	validation-mlogloss:2.56454
[10]	train-mlogloss:2.56926	validation-mlogloss:2.55182
[11]	train-mlogloss:2.55869	validation-mlogloss:2.54051
[12]	train-mlogloss:2.54890	validation-mlogloss:2.52906
[13]	train-mlogloss:2.53840	validation-mlogloss:2.51669
[14]	train-mlogloss:2.52715	validation-mlogloss:2.50439
[15]	train-mlogloss:2.51696	validation-mlogloss:2.49344
[16]	train-mlogloss:2.50751	validation-mlogloss:2.48308
[17]	train-mlogloss:2.49709	validation-mlogloss:2.47166
[18]	train-mlogloss:2.48771	validation-mlogloss:2.46188
[19]	train-mlogloss:2.47835	validation-mlogloss:2.45180
[20]	train-mlogloss:2.46952	validation-mlogloss:2.44243
[21]	train-mlogloss:2.46129	validation-mlogloss:2.43338
[22]	train-mlogloss:2.45217	validation-mlogloss:2.42347
[23]	train-mlogloss:2.44387	validation-mlogloss:2.41432
[24]	train-mlogloss:2.43536	validation-mlogloss:2.40474
[25]	train-mlogloss:2.42767	validation-mlogloss:2.39651
[26]	train-mlogloss:2.41933	validation-mlogloss:2.38758
[27]	train-mlogloss:2.41125	validation-mlogloss:2.37891
[28]	train-mlogloss:2.40309	validation-mlogloss:2.37028
[29]	train-mlogloss:2.39560	validation-mlogloss:2.36180
[30]	train-mlogloss:2.38770	validation-mlogloss:2.35326
[31]	train-mlogloss:2.38040	validation-mlogloss:2.34475
[32]	train-mlogloss:2.37323	validation-mlogloss:2.33667
[33]	train-mlogloss:2.36603	validation-mlogloss:2.32835
[34]	train-mlogloss:2.35889	validation-mlogloss:2.32020
[35]	train-mlogloss:2.35159	validation-mlogloss:2.31226
[36]	train-mlogloss:2.34490	validation-mlogloss:2.30520
[37]	train-mlogloss:2.33823	validation-mlogloss:2.29794
[38]	train-mlogloss:2.33186	validation-mlogloss:2.29164
[39]	train-mlogloss:2.32532	validation-mlogloss:2.28447
[40]	train-mlogloss:2.31925	validation-mlogloss:2.27764
[41]	train-mlogloss:2.31272	validation-mlogloss:2.27058
[42]	train-mlogloss:2.30666	validation-mlogloss:2.26462
[43]	train-mlogloss:2.30067	validation-mlogloss:2.25844
[44]	train-mlogloss:2.29422	validation-mlogloss:2.25160
[45]	train-mlogloss:2.28817	validation-mlogloss:2.24512
[46]	train-mlogloss:2.28211	validation-mlogloss:2.23859
[47]	train-mlogloss:2.27629	validation-mlogloss:2.23250
[48]	train-mlogloss:2.27035	validation-mlogloss:2.22625
[49]	train-mlogloss:2.26466	validation-mlogloss:2.22066
[50]	train-mlogloss:2.25936	validation-mlogloss:2.21560
[51]	train-mlogloss:2.25361	validation-mlogloss:2.21025
[52]	train-mlogloss:2.24806	validation-mlogloss:2.20437
[53]	train-mlogloss:2.24267	validation-mlogloss:2.19874
[54]	train-mlogloss:2.23732	validation-mlogloss:2.19316
[55]	train-mlogloss:2.23203	validation-mlogloss:2.18811
[56]	train-mlogloss:2.22688	validation-mlogloss:2.18294
[57]	train-mlogloss:2.22176	validation-mlogloss:2.17798
[58]	train-mlogloss:2.21685	validation-mlogloss:2.17293
[59]	train-mlogloss:2.21196	validation-mlogloss:2.16853
[60]	train-mlogloss:2.20728	validation-mlogloss:2.16413
[61]	train-mlogloss:2.20257	validation-mlogloss:2.15914
[62]	train-mlogloss:2.19764	validation-mlogloss:2.15391
[63]	train-mlogloss:2.19314	validation-mlogloss:2.14954
[64]	train-mlogloss:2.18863	validation-mlogloss:2.14497
[65]	train-mlogloss:2.18413	validation-mlogloss:2.14046
[66]	train-mlogloss:2.17981	validation-mlogloss:2.13641
[67]	train-mlogloss:2.17521	validation-mlogloss:2.13178
[68]	train-mlogloss:2.17075	validation-mlogloss:2.12776
[69]	train-mlogloss:2.16603	validation-mlogloss:2.12274
[70]	train-mlogloss:2.16175	validation-mlogloss:2.11872
[71]	train-mlogloss:2.15747	validation-mlogloss:2.11450
[72]	train-mlogloss:2.15328	validation-mlogloss:2.11019
[73]	train-mlogloss:2.14927	validation-mlogloss:2.10622
[74]	train-mlogloss:2.14512	validation-mlogloss:2.10209
[75]	train-mlogloss:2.14096	validation-mlogloss:2.09805
[76]	train-mlogloss:2.13693	validation-mlogloss:2.09394
[77]	train-mlogloss:2.13290	validation-mlogloss:2.09034
[78]	train-mlogloss:2.12884	validation-mlogloss:2.08615
[79]	train-mlogloss:2.12483	validation-mlogloss:2.08206
[80]	train-mlogloss:2.12087	validation-mlogloss:2.07835
[81]	train-mlogloss:2.11717	validation-mlogloss:2.07489
[82]	train-mlogloss:2.11342	validation-mlogloss:2.07114
[83]	train-mlogloss:2.10980	validation-mlogloss:2.06759
[84]	train-mlogloss:2.10613	validation-mlogloss:2.06434
[85]	train-mlogloss:2.10262	validation-mlogloss:2.06081
[86]	train-mlogloss:2.09882	validation-mlogloss:2.05743
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[88]	train-mlogloss:2.09147	validation-mlogloss:2.05085
[89]	train-mlogloss:2.08799	validation-mlogloss:2.04788
[90]	train-mlogloss:2.08449	validation-mlogloss:2.04460
[91]	train-mlogloss:2.08115	validation-mlogloss:2.04148
[92]	train-mlogloss:2.07789	validation-mlogloss:2.03846
[93]	train-mlogloss:2.07462	validation-mlogloss:2.03543
[94]	train-mlogloss:2.07132	validation-mlogloss:2.03221
[95]	train-mlogloss:2.06812	validation-mlogloss:2.02931
[96]	train-mlogloss:2.06490	validation-mlogloss:2.02635
[97]	train-mlogloss:2.06143	validation-mlogloss:2.02320
[98]	train-mlogloss:2.05833	validation-mlogloss:2.02027
[99]	train-mlogloss:2.05515	validation-mlogloss:2.01714
[100]	train-mlogloss:2.05207	validation-mlogloss:2.01468
[101]	train-mlogloss:2.04908	validation-mlogloss:2.01216
[102]	train-mlogloss:2.04580	validation-mlogloss:2.00907
[103]	train-mlogloss:2.04283	validation-mlogloss:2.00640
[104]	train-mlogloss:2.03982	validation-mlogloss:2.00317
[105]	train-mlogloss:2.03679	validation-mlogloss:2.00075
[106]	train-mlogloss:2.03372	validation-mlogloss:1.99810
[107]	train-mlogloss:2.03061	validation-mlogloss:1.99517
[108]	train-mlogloss:2.02768	validation-mlogloss:1.99217
[109]	train-mlogloss:2.02479	validation-mlogloss:1.98948
[110]	train-mlogloss:2.02193	validation-mlogloss:1.98662
[111]	train-mlogloss:2.01890	validation-mlogloss:1.98397
[112]	train-mlogloss:2.01591	validation-mlogloss:1.98125
[113]	train-mlogloss:2.01316	validation-mlogloss:1.97859
[114]	train-mlogloss:2.01036	validation-mlogloss:1.97577
[115]	train-mlogloss:2.00765	validation-mlogloss:1.97319
[116]	train-mlogloss:2.00476	validation-mlogloss:1.97076
[117]	train-mlogloss:2.00200	validation-mlogloss:1.96805
[118]	train-mlogloss:1.99939	validation-mlogloss:1.96548
[119]	train-mlogloss:1.99683	validation-mlogloss:1.96355
[120]	train-mlogloss:1.99433	validation-mlogloss:1.96132
[121]	train-mlogloss:1.99177	validation-mlogloss:1.95902
[122]	train-mlogloss:1.98933	validation-mlogloss:1.95660
[123]	train-mlogloss:1.98699	validation-mlogloss:1.95446
[124]	train-mlogloss:1.98444	validation-mlogloss:1.95181
[125]	train-mlogloss:1.98200	validation-mlogloss:1.94952
[126]	train-mlogloss:1.97966	validation-mlogloss:1.94746
[127]	train-mlogloss:1.97713	validation-mlogloss:1.94530
[128]	train-mlogloss:1.97479	validation-mlogloss:1.94269
[129]	train-mlogloss:1.97247	validation-mlogloss:1.94078
[130]	train-mlogloss:1.96996	validation-mlogloss:1.93836
[131]	train-mlogloss:1.96766	validation-mlogloss:1.93630
[132]	train-mlogloss:1.96530	validation-mlogloss:1.93449
[133]	train-mlogloss:1.96289	validation-mlogloss:1.93220
[134]	train-mlogloss:1.96043	validation-mlogloss:1.92962
[135]	train-mlogloss:1.95811	validation-mlogloss:1.92794
[136]	train-mlogloss:1.95573	validation-mlogloss:1.92561
[137]	train-mlogloss:1.95351	validation-mlogloss:1.92332
[138]	train-mlogloss:1.95125	validation-mlogloss:1.92111
[139]	train-mlogloss:1.94911	validation-mlogloss:1.91939
[140]	train-mlogloss:1.94681	validation-mlogloss:1.91750
[141]	train-mlogloss:1.94457	validation-mlogloss:1.91547
[142]	train-mlogloss:1.94246	validation-mlogloss:1.91374
[143]	train-mlogloss:1.94032	validation-mlogloss:1.91162
[144]	train-mlogloss:1.93814	validation-mlogloss:1.90964
[145]	train-mlogloss:1.93605	validation-mlogloss:1.90806
[146]	train-mlogloss:1.93396	validation-mlogloss:1.90639
[147]	train-mlogloss:1.93181	validation-mlogloss:1.90464
[148]	train-mlogloss:1.92981	validation-mlogloss:1.90307
[149]	train-mlogloss:1.92797	validation-mlogloss:1.90150
[150]	train-mlogloss:1.92580	validation-mlogloss:1.89938
[151]	train-mlogloss:1.92373	validation-mlogloss:1.89776
[152]	train-mlogloss:1.92167	validation-mlogloss:1.89587
[153]	train-mlogloss:1.91959	validation-mlogloss:1.89401
[154]	train-mlogloss:1.91768	validation-mlogloss:1.89203
[155]	train-mlogloss:1.91571	validation-mlogloss:1.89022
[156]	train-mlogloss:1.91377	validation-mlogloss:1.88839
[157]	train-mlogloss:1.91186	validation-mlogloss:1.88663
[158]	train-mlogloss:1.90990	validation-mlogloss:1.88495
[159]	train-mlogloss:1.90797	validation-mlogloss:1.88344
[160]	train-mlogloss:1.90605	validation-mlogloss:1.88167
[161]	train-mlogloss:1.90415	validation-mlogloss:1.87974
[162]	train-mlogloss:1.90221	validation-mlogloss:1.87826
[163]	train-mlogloss:1.90036	validation-mlogloss:1.87668
[164]	train-mlogloss:1.89853	validation-mlogloss:1.87526
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[190]	train-mlogloss:1.85331	validation-mlogloss:1.84019
[191]	train-mlogloss:1.85174	validation-mlogloss:1.83902
[192]	train-mlogloss:1.85018	validation-mlogloss:1.83809
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[196]	train-mlogloss:1.84365	validation-mlogloss:1.83301
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[199]	train-mlogloss:1.83902	validation-mlogloss:1.82945
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[201]	train-mlogloss:1.83594	validation-mlogloss:1.82697
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[516]	train-mlogloss:1.56863	validation-mlogloss:1.68373
[517]	train-mlogloss:1.56812	validation-mlogloss:1.68378
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[519]	train-mlogloss:1.56719	validation-mlogloss:1.68361
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[522]	train-mlogloss:1.56571	validation-mlogloss:1.68298
[523]	train-mlogloss:1.56524	validation-mlogloss:1.68274
[524]	train-mlogloss:1.56480	validation-mlogloss:1.68259
[525]	train-mlogloss:1.56439	validation-mlogloss:1.68251
[526]	train-mlogloss:1.56392	validation-mlogloss:1.68250
[527]	train-mlogloss:1.56343	validation-mlogloss:1.68225
[528]	train-mlogloss:1.56298	validation-mlogloss:1.68229
[529]	train-mlogloss:1.56254	validation-mlogloss:1.68242
[530]	train-mlogloss:1.56204	validation-mlogloss:1.68243
[531]	train-mlogloss:1.56152	validation-mlogloss:1.68221
[532]	train-mlogloss:1.56104	validation-mlogloss:1.68215
[533]	train-mlogloss:1.56061	validation-mlogloss:1.68204
[534]	train-mlogloss:1.56018	validation-mlogloss:1.68192
[535]	train-mlogloss:1.55974	validation-mlogloss:1.68183
[536]	train-mlogloss:1.55925	validation-mlogloss:1.68185
[537]	train-mlogloss:1.55869	validation-mlogloss:1.68180
[538]	train-mlogloss:1.55824	validation-mlogloss:1.68164
[539]	train-mlogloss:1.55782	validation-mlogloss:1.68160
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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.4 [%]
Global accuracy score (test) = 44.68 [%]
Global F1 score (train) = 51.55 [%]
Global F1 score (test) = 44.15 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.73      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.36      0.46      0.40       184
       CAMINAR USUAL SPEED       0.35      0.28      0.31       184
            CAMINAR ZIGZAG       0.38      0.52      0.44       184
          DE PIE BARRIENDO       0.74      0.32      0.44       184
   DE PIE DOBLANDO TOALLAS       0.51      0.42      0.46       184
    DE PIE MOVIENDO LIBROS       0.36      0.32      0.34       184
          DE PIE USANDO PC       0.20      0.31      0.24       184
        FASE REPOSO CON K5       0.56      0.85      0.68       184
INCREMENTAL CICLOERGOMETRO       0.75      0.68      0.71       184
           SENTADO LEYENDO       0.48      0.37      0.42       184
         SENTADO USANDO PC       0.21      0.12      0.16       184
      SENTADO VIENDO LA TV       0.30      0.25      0.27       184
   SUBIR Y BAJAR ESCALERAS       0.60      0.52      0.56       184
                    TROTAR       0.67      0.57      0.62       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 4: 44.68 [%]
F1-score capturado en la ejecución 4: 44.15 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.39 [%]
Global accuracy score (test) = 45.2 [%]
Global F1 score (train) = 51.5 [%]
Global F1 score (test) = 44.7 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.73      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.37      0.47      0.41       184
       CAMINAR USUAL SPEED       0.34      0.30      0.32       184
            CAMINAR ZIGZAG       0.39      0.51      0.44       184
          DE PIE BARRIENDO       0.75      0.30      0.43       184
   DE PIE DOBLANDO TOALLAS       0.51      0.43      0.47       184
    DE PIE MOVIENDO LIBROS       0.37      0.34      0.35       184
          DE PIE USANDO PC       0.22      0.33      0.26       184
        FASE REPOSO CON K5       0.57      0.85      0.68       184
INCREMENTAL CICLOERGOMETRO       0.72      0.68      0.70       184
           SENTADO LEYENDO       0.52      0.37      0.43       184
         SENTADO USANDO PC       0.22      0.13      0.16       184
      SENTADO VIENDO LA TV       0.32      0.28      0.30       184
   SUBIR Y BAJAR ESCALERAS       0.64      0.50      0.56       184
                    TROTAR       0.66      0.57      0.61       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.45      0.45      2737
              weighted avg       0.47      0.45      0.45      2737


Accuracy capturado en la ejecución 5: 45.2 [%]
F1-score capturado en la ejecución 5: 44.7 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.44 [%]
Global accuracy score (test) = 45.05 [%]
Global F1 score (train) = 51.55 [%]
Global F1 score (test) = 44.56 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.75      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.36      0.47      0.41       184
       CAMINAR USUAL SPEED       0.37      0.31      0.34       184
            CAMINAR ZIGZAG       0.38      0.52      0.44       184
          DE PIE BARRIENDO       0.76      0.31      0.44       184
   DE PIE DOBLANDO TOALLAS       0.50      0.42      0.46       184
    DE PIE MOVIENDO LIBROS       0.34      0.31      0.33       184
          DE PIE USANDO PC       0.21      0.33      0.26       184
        FASE REPOSO CON K5       0.56      0.85      0.67       184
INCREMENTAL CICLOERGOMETRO       0.75      0.68      0.72       184
           SENTADO LEYENDO       0.46      0.30      0.36       184
         SENTADO USANDO PC       0.25      0.15      0.18       184
      SENTADO VIENDO LA TV       0.31      0.27      0.29       184
   SUBIR Y BAJAR ESCALERAS       0.68      0.54      0.60       184
                    TROTAR       0.67      0.57      0.62       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.45      0.45      2737
              weighted avg       0.47      0.45      0.44      2737


Accuracy capturado en la ejecución 6: 45.05 [%]
F1-score capturado en la ejecución 6: 44.56 [%]

=== EJECUCIÓN 7 ===

--- TRAIN (ejecución 7) ---

--- TEST (ejecución 7) ---
2025-10-27 09:41:41.116603: 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`.
2025-10-27 09:41:41.129896: 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 00:00:1761554501.143779  408611 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554501.148084  408611 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554501.159643  408611 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554501.159674  408611 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554501.159677  408611 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554501.159680  408611 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:41:41.163123: 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:2.69410	validation-mlogloss:2.69271
[1]	train-mlogloss:2.68145	validation-mlogloss:2.67890
[2]	train-mlogloss:2.66872	validation-mlogloss:2.66394
[3]	train-mlogloss:2.65609	validation-mlogloss:2.64899
[4]	train-mlogloss:2.64317	validation-mlogloss:2.63476
[5]	train-mlogloss:2.62979	validation-mlogloss:2.61966
[6]	train-mlogloss:2.61875	validation-mlogloss:2.60703
[7]	train-mlogloss:2.60614	validation-mlogloss:2.59339
[8]	train-mlogloss:2.59418	validation-mlogloss:2.58034
[9]	train-mlogloss:2.58218	validation-mlogloss:2.56696
[10]	train-mlogloss:2.57076	validation-mlogloss:2.55448
[11]	train-mlogloss:2.55938	validation-mlogloss:2.54178
[12]	train-mlogloss:2.54852	validation-mlogloss:2.53006
[13]	train-mlogloss:2.53804	validation-mlogloss:2.51833
[14]	train-mlogloss:2.52785	validation-mlogloss:2.50664
[15]	train-mlogloss:2.51771	validation-mlogloss:2.49557
[16]	train-mlogloss:2.50791	validation-mlogloss:2.48518
[17]	train-mlogloss:2.49860	validation-mlogloss:2.47504
[18]	train-mlogloss:2.48937	validation-mlogloss:2.46512
[19]	train-mlogloss:2.48035	validation-mlogloss:2.45565
[20]	train-mlogloss:2.47108	validation-mlogloss:2.44548
[21]	train-mlogloss:2.46196	validation-mlogloss:2.43562
[22]	train-mlogloss:2.45294	validation-mlogloss:2.42524
[23]	train-mlogloss:2.44430	validation-mlogloss:2.41629
[24]	train-mlogloss:2.43584	validation-mlogloss:2.40710
[25]	train-mlogloss:2.42764	validation-mlogloss:2.39825
[26]	train-mlogloss:2.41949	validation-mlogloss:2.38916
[27]	train-mlogloss:2.41173	validation-mlogloss:2.38106
[28]	train-mlogloss:2.40430	validation-mlogloss:2.37310
[29]	train-mlogloss:2.39675	validation-mlogloss:2.36522
[30]	train-mlogloss:2.38974	validation-mlogloss:2.35740
[31]	train-mlogloss:2.38236	validation-mlogloss:2.34960
[32]	train-mlogloss:2.37524	validation-mlogloss:2.34240
[33]	train-mlogloss:2.36771	validation-mlogloss:2.33363
[34]	train-mlogloss:2.36057	validation-mlogloss:2.32584
[35]	train-mlogloss:2.35338	validation-mlogloss:2.31768
[36]	train-mlogloss:2.34668	validation-mlogloss:2.31031
[37]	train-mlogloss:2.34006	validation-mlogloss:2.30284
[38]	train-mlogloss:2.33366	validation-mlogloss:2.29574
[39]	train-mlogloss:2.32686	validation-mlogloss:2.28765
[40]	train-mlogloss:2.32077	validation-mlogloss:2.28091
[41]	train-mlogloss:2.31427	validation-mlogloss:2.27419
[42]	train-mlogloss:2.30807	validation-mlogloss:2.26750
[43]	train-mlogloss:2.30180	validation-mlogloss:2.26082
[44]	train-mlogloss:2.29581	validation-mlogloss:2.25414
[45]	train-mlogloss:2.28976	validation-mlogloss:2.24814
[46]	train-mlogloss:2.28399	validation-mlogloss:2.24216
[47]	train-mlogloss:2.27834	validation-mlogloss:2.23547
[48]	train-mlogloss:2.27261	validation-mlogloss:2.22971
[49]	train-mlogloss:2.26702	validation-mlogloss:2.22367
[50]	train-mlogloss:2.26156	validation-mlogloss:2.21781
[51]	train-mlogloss:2.25616	validation-mlogloss:2.21258
[52]	train-mlogloss:2.25098	validation-mlogloss:2.20675
[53]	train-mlogloss:2.24577	validation-mlogloss:2.20165
[54]	train-mlogloss:2.24050	validation-mlogloss:2.19628
[55]	train-mlogloss:2.23503	validation-mlogloss:2.19063
[56]	train-mlogloss:2.22975	validation-mlogloss:2.18553
[57]	train-mlogloss:2.22498	validation-mlogloss:2.18020
[58]	train-mlogloss:2.22000	validation-mlogloss:2.17521
[59]	train-mlogloss:2.21538	validation-mlogloss:2.17066
[60]	train-mlogloss:2.21038	validation-mlogloss:2.16614
[61]	train-mlogloss:2.20566	validation-mlogloss:2.16139
[62]	train-mlogloss:2.20103	validation-mlogloss:2.15672
[63]	train-mlogloss:2.19606	validation-mlogloss:2.15156
[64]	train-mlogloss:2.19111	validation-mlogloss:2.14662
[65]	train-mlogloss:2.18669	validation-mlogloss:2.14231
[66]	train-mlogloss:2.18228	validation-mlogloss:2.13800
[67]	train-mlogloss:2.17757	validation-mlogloss:2.13315
[68]	train-mlogloss:2.17302	validation-mlogloss:2.12838
[69]	train-mlogloss:2.16861	validation-mlogloss:2.12377
[70]	train-mlogloss:2.16448	validation-mlogloss:2.11987
[71]	train-mlogloss:2.16018	validation-mlogloss:2.11532
[72]	train-mlogloss:2.15599	validation-mlogloss:2.11125
[73]	train-mlogloss:2.15179	validation-mlogloss:2.10683
[74]	train-mlogloss:2.14766	validation-mlogloss:2.10289
[75]	train-mlogloss:2.14361	validation-mlogloss:2.09892
[76]	train-mlogloss:2.13946	validation-mlogloss:2.09481
[77]	train-mlogloss:2.13557	validation-mlogloss:2.09114
[78]	train-mlogloss:2.13145	validation-mlogloss:2.08688
[79]	train-mlogloss:2.12750	validation-mlogloss:2.08281
[80]	train-mlogloss:2.12365	validation-mlogloss:2.07948
[81]	train-mlogloss:2.11991	validation-mlogloss:2.07603
[82]	train-mlogloss:2.11617	validation-mlogloss:2.07255
[83]	train-mlogloss:2.11237	validation-mlogloss:2.06873
[84]	train-mlogloss:2.10876	validation-mlogloss:2.06540
[85]	train-mlogloss:2.10502	validation-mlogloss:2.06179
[86]	train-mlogloss:2.10136	validation-mlogloss:2.05869
[87]	train-mlogloss:2.09769	validation-mlogloss:2.05564
[88]	train-mlogloss:2.09404	validation-mlogloss:2.05172
[89]	train-mlogloss:2.09060	validation-mlogloss:2.04820
[90]	train-mlogloss:2.08706	validation-mlogloss:2.04485
[91]	train-mlogloss:2.08378	validation-mlogloss:2.04147
[92]	train-mlogloss:2.08033	validation-mlogloss:2.03850
[93]	train-mlogloss:2.07695	validation-mlogloss:2.03556
[94]	train-mlogloss:2.07363	validation-mlogloss:2.03222
[95]	train-mlogloss:2.07001	validation-mlogloss:2.02837
[96]	train-mlogloss:2.06681	validation-mlogloss:2.02550
[97]	train-mlogloss:2.06357	validation-mlogloss:2.02237
[98]	train-mlogloss:2.06038	validation-mlogloss:2.01922
[99]	train-mlogloss:2.05733	validation-mlogloss:2.01658
[100]	train-mlogloss:2.05418	validation-mlogloss:2.01381
[101]	train-mlogloss:2.05094	validation-mlogloss:2.01106
[102]	train-mlogloss:2.04767	validation-mlogloss:2.00777
[103]	train-mlogloss:2.04447	validation-mlogloss:2.00492
[104]	train-mlogloss:2.04151	validation-mlogloss:2.00244
[105]	train-mlogloss:2.03839	validation-mlogloss:1.99950
[106]	train-mlogloss:2.03543	validation-mlogloss:1.99646
[107]	train-mlogloss:2.03259	validation-mlogloss:1.99394
[108]	train-mlogloss:2.02980	validation-mlogloss:1.99183
[109]	train-mlogloss:2.02693	validation-mlogloss:1.98923
[110]	train-mlogloss:2.02419	validation-mlogloss:1.98640
[111]	train-mlogloss:2.02142	validation-mlogloss:1.98389
[112]	train-mlogloss:2.01878	validation-mlogloss:1.98110
[113]	train-mlogloss:2.01615	validation-mlogloss:1.97873
[114]	train-mlogloss:2.01346	validation-mlogloss:1.97621
[115]	train-mlogloss:2.01092	validation-mlogloss:1.97418
[116]	train-mlogloss:2.00838	validation-mlogloss:1.97183
[117]	train-mlogloss:2.00569	validation-mlogloss:1.96942
[118]	train-mlogloss:2.00310	validation-mlogloss:1.96705
[119]	train-mlogloss:2.00050	validation-mlogloss:1.96475
[120]	train-mlogloss:1.99785	validation-mlogloss:1.96244
[121]	train-mlogloss:1.99531	validation-mlogloss:1.96000
[122]	train-mlogloss:1.99270	validation-mlogloss:1.95800
[123]	train-mlogloss:1.98998	validation-mlogloss:1.95572
[124]	train-mlogloss:1.98749	validation-mlogloss:1.95337
[125]	train-mlogloss:1.98500	validation-mlogloss:1.95146
[126]	train-mlogloss:1.98252	validation-mlogloss:1.94921
[127]	train-mlogloss:1.98011	validation-mlogloss:1.94691
[128]	train-mlogloss:1.97761	validation-mlogloss:1.94481
[129]	train-mlogloss:1.97520	validation-mlogloss:1.94270
[130]	train-mlogloss:1.97265	validation-mlogloss:1.94012
[131]	train-mlogloss:1.97012	validation-mlogloss:1.93802
[132]	train-mlogloss:1.96767	validation-mlogloss:1.93578
[133]	train-mlogloss:1.96534	validation-mlogloss:1.93396
[134]	train-mlogloss:1.96303	validation-mlogloss:1.93208
[135]	train-mlogloss:1.96076	validation-mlogloss:1.93069
[136]	train-mlogloss:1.95835	validation-mlogloss:1.92832
[137]	train-mlogloss:1.95598	validation-mlogloss:1.92603
[138]	train-mlogloss:1.95382	validation-mlogloss:1.92439
[139]	train-mlogloss:1.95161	validation-mlogloss:1.92246
[140]	train-mlogloss:1.94931	validation-mlogloss:1.92049
[141]	train-mlogloss:1.94717	validation-mlogloss:1.91878
[142]	train-mlogloss:1.94493	validation-mlogloss:1.91666
[143]	train-mlogloss:1.94264	validation-mlogloss:1.91436
[144]	train-mlogloss:1.94055	validation-mlogloss:1.91268
[145]	train-mlogloss:1.93837	validation-mlogloss:1.91085
[146]	train-mlogloss:1.93610	validation-mlogloss:1.90890
[147]	train-mlogloss:1.93394	validation-mlogloss:1.90710
[148]	train-mlogloss:1.93182	validation-mlogloss:1.90539
[149]	train-mlogloss:1.92969	validation-mlogloss:1.90357
[150]	train-mlogloss:1.92761	validation-mlogloss:1.90212
[151]	train-mlogloss:1.92557	validation-mlogloss:1.90009
[152]	train-mlogloss:1.92358	validation-mlogloss:1.89838
[153]	train-mlogloss:1.92149	validation-mlogloss:1.89702
[154]	train-mlogloss:1.91934	validation-mlogloss:1.89519
[155]	train-mlogloss:1.91734	validation-mlogloss:1.89388
[156]	train-mlogloss:1.91523	validation-mlogloss:1.89227
[157]	train-mlogloss:1.91329	validation-mlogloss:1.89081
[158]	train-mlogloss:1.91125	validation-mlogloss:1.88903
[159]	train-mlogloss:1.90924	validation-mlogloss:1.88720
[160]	train-mlogloss:1.90731	validation-mlogloss:1.88536
[161]	train-mlogloss:1.90533	validation-mlogloss:1.88353
[162]	train-mlogloss:1.90356	validation-mlogloss:1.88199
[163]	train-mlogloss:1.90164	validation-mlogloss:1.88058
[164]	train-mlogloss:1.89962	validation-mlogloss:1.87872
[165]	train-mlogloss:1.89770	validation-mlogloss:1.87736
[166]	train-mlogloss:1.89579	validation-mlogloss:1.87560
[167]	train-mlogloss:1.89391	validation-mlogloss:1.87435
[168]	train-mlogloss:1.89215	validation-mlogloss:1.87250
[169]	train-mlogloss:1.89032	validation-mlogloss:1.87086
[170]	train-mlogloss:1.88845	validation-mlogloss:1.86939
[171]	train-mlogloss:1.88670	validation-mlogloss:1.86800
[172]	train-mlogloss:1.88498	validation-mlogloss:1.86633
[173]	train-mlogloss:1.88318	validation-mlogloss:1.86501
[174]	train-mlogloss:1.88127	validation-mlogloss:1.86324
[175]	train-mlogloss:1.87958	validation-mlogloss:1.86201
[176]	train-mlogloss:1.87780	validation-mlogloss:1.86057
[177]	train-mlogloss:1.87603	validation-mlogloss:1.85915
[178]	train-mlogloss:1.87432	validation-mlogloss:1.85790
[179]	train-mlogloss:1.87246	validation-mlogloss:1.85620
[180]	train-mlogloss:1.87073	validation-mlogloss:1.85493
[181]	train-mlogloss:1.86910	validation-mlogloss:1.85365
[182]	train-mlogloss:1.86747	validation-mlogloss:1.85225
[183]	train-mlogloss:1.86578	validation-mlogloss:1.85065
[184]	train-mlogloss:1.86411	validation-mlogloss:1.84900
[185]	train-mlogloss:1.86236	validation-mlogloss:1.84793
[186]	train-mlogloss:1.86071	validation-mlogloss:1.84642
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[487]	train-mlogloss:1.58574	validation-mlogloss:1.69106
[488]	train-mlogloss:1.58517	validation-mlogloss:1.69096
[489]	train-mlogloss:1.58462	validation-mlogloss:1.69085
[490]	train-mlogloss:1.58411	validation-mlogloss:1.69061
[491]	train-mlogloss:1.58367	validation-mlogloss:1.69061
[492]	train-mlogloss:1.58317	validation-mlogloss:1.69065
[493]	train-mlogloss:1.58268	validation-mlogloss:1.69032
[494]	train-mlogloss:1.58216	validation-mlogloss:1.68997
[495]	train-mlogloss:1.58167	validation-mlogloss:1.68962
[496]	train-mlogloss:1.58112	validation-mlogloss:1.68949
[497]	train-mlogloss:1.58065	validation-mlogloss:1.68950
[498]	train-mlogloss:1.58020	validation-mlogloss:1.68932
[499]	train-mlogloss:1.57977	validation-mlogloss:1.68910
[500]	train-mlogloss:1.57930	validation-mlogloss:1.68896
[501]	train-mlogloss:1.57882	validation-mlogloss:1.68863
[502]	train-mlogloss:1.57843	validation-mlogloss:1.68850
[503]	train-mlogloss:1.57791	validation-mlogloss:1.68826
[504]	train-mlogloss:1.57742	validation-mlogloss:1.68786
[505]	train-mlogloss:1.57700	validation-mlogloss:1.68774
[506]	train-mlogloss:1.57650	validation-mlogloss:1.68741
[507]	train-mlogloss:1.57599	validation-mlogloss:1.68718
[508]	train-mlogloss:1.57543	validation-mlogloss:1.68700
[509]	train-mlogloss:1.57494	validation-mlogloss:1.68693
[510]	train-mlogloss:1.57444	validation-mlogloss:1.68681
[511]	train-mlogloss:1.57402	validation-mlogloss:1.68675
[512]	train-mlogloss:1.57347	validation-mlogloss:1.68645
[513]	train-mlogloss:1.57304	validation-mlogloss:1.68636
[514]	train-mlogloss:1.57251	validation-mlogloss:1.68628
[515]	train-mlogloss:1.57193	validation-mlogloss:1.68593
[516]	train-mlogloss:1.57148	validation-mlogloss:1.68585
[517]	train-mlogloss:1.57094	validation-mlogloss:1.68567
[518]	train-mlogloss:1.57048	validation-mlogloss:1.68547
[519]	train-mlogloss:1.57005	validation-mlogloss:1.68517
[520]	train-mlogloss:1.56954	validation-mlogloss:1.68493
[521]	train-mlogloss:1.56903	validation-mlogloss:1.68490
[522]	train-mlogloss:1.56852	validation-mlogloss:1.68470
[523]	train-mlogloss:1.56796	validation-mlogloss:1.68452
[524]	train-mlogloss:1.56747	validation-mlogloss:1.68448
[525]	train-mlogloss:1.56704	validation-mlogloss:1.68435
[526]	train-mlogloss:1.56657	validation-mlogloss:1.68425
[527]	train-mlogloss:1.56599	validation-mlogloss:1.68417
[528]	train-mlogloss:1.56547	validation-mlogloss:1.68397
[529]	train-mlogloss:1.56497	validation-mlogloss:1.68391
[530]	train-mlogloss:1.56450	validation-mlogloss:1.68378
[531]	train-mlogloss:1.56400	validation-mlogloss:1.68366
[532]	train-mlogloss:1.56348	validation-mlogloss:1.68343
[533]	train-mlogloss:1.56306	validation-mlogloss:1.68328
[534]	train-mlogloss:1.56259	validation-mlogloss:1.68313
[535]	train-mlogloss:1.56215	validation-mlogloss:1.68292
[536]	train-mlogloss:1.56166	validation-mlogloss:1.68286
[537]	train-mlogloss:1.56122	validation-mlogloss:1.68275
[538]	train-mlogloss:1.56078	validation-mlogloss:1.68280
[539]	train-mlogloss:1.56033	validation-mlogloss:1.68277
Saved model to disk.
2025-10-27 09:42:26.721479: 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`.
2025-10-27 09:42:26.734232: 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 00:00:1761554546.748196  409507 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554546.752569  409507 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554546.763554  409507 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554546.763578  409507 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554546.763581  409507 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554546.763584  409507 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:42:26.766992: 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:2.69389	validation-mlogloss:2.69244
[1]	train-mlogloss:2.67922	validation-mlogloss:2.67539
[2]	train-mlogloss:2.66634	validation-mlogloss:2.66266
[3]	train-mlogloss:2.65260	validation-mlogloss:2.64763
[4]	train-mlogloss:2.64089	validation-mlogloss:2.63379
[5]	train-mlogloss:2.62905	validation-mlogloss:2.62061
[6]	train-mlogloss:2.61722	validation-mlogloss:2.60728
[7]	train-mlogloss:2.60423	validation-mlogloss:2.59276
[8]	train-mlogloss:2.59217	validation-mlogloss:2.57988
[9]	train-mlogloss:2.58033	validation-mlogloss:2.56651
[10]	train-mlogloss:2.56927	validation-mlogloss:2.55468
[11]	train-mlogloss:2.55840	validation-mlogloss:2.54239
[12]	train-mlogloss:2.54818	validation-mlogloss:2.53108
[13]	train-mlogloss:2.53765	validation-mlogloss:2.51927
[14]	train-mlogloss:2.52747	validation-mlogloss:2.50780
[15]	train-mlogloss:2.51727	validation-mlogloss:2.49650
[16]	train-mlogloss:2.50776	validation-mlogloss:2.48552
[17]	train-mlogloss:2.49828	validation-mlogloss:2.47501
[18]	train-mlogloss:2.48953	validation-mlogloss:2.46524
[19]	train-mlogloss:2.48003	validation-mlogloss:2.45475
[20]	train-mlogloss:2.47079	validation-mlogloss:2.44456
[21]	train-mlogloss:2.46236	validation-mlogloss:2.43485
[22]	train-mlogloss:2.45387	validation-mlogloss:2.42562
[23]	train-mlogloss:2.44529	validation-mlogloss:2.41687
[24]	train-mlogloss:2.43676	validation-mlogloss:2.40686
[25]	train-mlogloss:2.42827	validation-mlogloss:2.39698
[26]	train-mlogloss:2.42038	validation-mlogloss:2.38829
[27]	train-mlogloss:2.41242	validation-mlogloss:2.38025
[28]	train-mlogloss:2.40448	validation-mlogloss:2.37132
[29]	train-mlogloss:2.39642	validation-mlogloss:2.36302
[30]	train-mlogloss:2.38936	validation-mlogloss:2.35496
[31]	train-mlogloss:2.38142	validation-mlogloss:2.34640
[32]	train-mlogloss:2.37389	validation-mlogloss:2.33856
[33]	train-mlogloss:2.36663	validation-mlogloss:2.33056
[34]	train-mlogloss:2.35935	validation-mlogloss:2.32266
[35]	train-mlogloss:2.35235	validation-mlogloss:2.31549
[36]	train-mlogloss:2.34583	validation-mlogloss:2.30795
[37]	train-mlogloss:2.33907	validation-mlogloss:2.30001
[38]	train-mlogloss:2.33209	validation-mlogloss:2.29202
[39]	train-mlogloss:2.32586	validation-mlogloss:2.28523
[40]	train-mlogloss:2.31941	validation-mlogloss:2.27838
[41]	train-mlogloss:2.31328	validation-mlogloss:2.27181
[42]	train-mlogloss:2.30703	validation-mlogloss:2.26557
[43]	train-mlogloss:2.30082	validation-mlogloss:2.25905
[44]	train-mlogloss:2.29463	validation-mlogloss:2.25276
[45]	train-mlogloss:2.28883	validation-mlogloss:2.24640
[46]	train-mlogloss:2.28294	validation-mlogloss:2.24021
[47]	train-mlogloss:2.27729	validation-mlogloss:2.23424
[48]	train-mlogloss:2.27142	validation-mlogloss:2.22807
[49]	train-mlogloss:2.26575	validation-mlogloss:2.22216
[50]	train-mlogloss:2.26036	validation-mlogloss:2.21693
[51]	train-mlogloss:2.25499	validation-mlogloss:2.21091
[52]	train-mlogloss:2.24956	validation-mlogloss:2.20527
[53]	train-mlogloss:2.24400	validation-mlogloss:2.19956
[54]	train-mlogloss:2.23877	validation-mlogloss:2.19434
[55]	train-mlogloss:2.23371	validation-mlogloss:2.18916
[56]	train-mlogloss:2.22870	validation-mlogloss:2.18431
[57]	train-mlogloss:2.22350	validation-mlogloss:2.17934
[58]	train-mlogloss:2.21854	validation-mlogloss:2.17400
[59]	train-mlogloss:2.21349	validation-mlogloss:2.16874
[60]	train-mlogloss:2.20867	validation-mlogloss:2.16409
[61]	train-mlogloss:2.20405	validation-mlogloss:2.15964
[62]	train-mlogloss:2.19945	validation-mlogloss:2.15482
[63]	train-mlogloss:2.19461	validation-mlogloss:2.14983
[64]	train-mlogloss:2.19016	validation-mlogloss:2.14562
[65]	train-mlogloss:2.18570	validation-mlogloss:2.14121
[66]	train-mlogloss:2.18119	validation-mlogloss:2.13647
[67]	train-mlogloss:2.17680	validation-mlogloss:2.13242
[68]	train-mlogloss:2.17251	validation-mlogloss:2.12783
[69]	train-mlogloss:2.16821	validation-mlogloss:2.12366
[70]	train-mlogloss:2.16409	validation-mlogloss:2.11954
[71]	train-mlogloss:2.15969	validation-mlogloss:2.11530
[72]	train-mlogloss:2.15526	validation-mlogloss:2.11115
[73]	train-mlogloss:2.15098	validation-mlogloss:2.10620
[74]	train-mlogloss:2.14673	validation-mlogloss:2.10198
[75]	train-mlogloss:2.14271	validation-mlogloss:2.09793
[76]	train-mlogloss:2.13874	validation-mlogloss:2.09394
[77]	train-mlogloss:2.13492	validation-mlogloss:2.09031
[78]	train-mlogloss:2.13063	validation-mlogloss:2.08600
[79]	train-mlogloss:2.12666	validation-mlogloss:2.08224
[80]	train-mlogloss:2.12257	validation-mlogloss:2.07817
[81]	train-mlogloss:2.11879	validation-mlogloss:2.07468
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[83]	train-mlogloss:2.11123	validation-mlogloss:2.06683
[84]	train-mlogloss:2.10771	validation-mlogloss:2.06353
[85]	train-mlogloss:2.10426	validation-mlogloss:2.06038
[86]	train-mlogloss:2.10058	validation-mlogloss:2.05697
[87]	train-mlogloss:2.09706	validation-mlogloss:2.05336
[88]	train-mlogloss:2.09345	validation-mlogloss:2.04989
[89]	train-mlogloss:2.08991	validation-mlogloss:2.04644
[90]	train-mlogloss:2.08649	validation-mlogloss:2.04275
[91]	train-mlogloss:2.08300	validation-mlogloss:2.03914
[92]	train-mlogloss:2.07979	validation-mlogloss:2.03613
[93]	train-mlogloss:2.07617	validation-mlogloss:2.03268
[94]	train-mlogloss:2.07288	validation-mlogloss:2.02906
[95]	train-mlogloss:2.06935	validation-mlogloss:2.02585
[96]	train-mlogloss:2.06623	validation-mlogloss:2.02282
[97]	train-mlogloss:2.06299	validation-mlogloss:2.02014
[98]	train-mlogloss:2.05991	validation-mlogloss:2.01688
[99]	train-mlogloss:2.05670	validation-mlogloss:2.01382
[100]	train-mlogloss:2.05343	validation-mlogloss:2.01114
[101]	train-mlogloss:2.05029	validation-mlogloss:2.00837
[102]	train-mlogloss:2.04728	validation-mlogloss:2.00536
[103]	train-mlogloss:2.04423	validation-mlogloss:2.00256
[104]	train-mlogloss:2.04108	validation-mlogloss:1.99932
[105]	train-mlogloss:2.03797	validation-mlogloss:1.99638
[106]	train-mlogloss:2.03514	validation-mlogloss:1.99392
[107]	train-mlogloss:2.03219	validation-mlogloss:1.99136
[108]	train-mlogloss:2.02946	validation-mlogloss:1.98900
[109]	train-mlogloss:2.02623	validation-mlogloss:1.98606
[110]	train-mlogloss:2.02351	validation-mlogloss:1.98344
[111]	train-mlogloss:2.02079	validation-mlogloss:1.98076
[112]	train-mlogloss:2.01794	validation-mlogloss:1.97825
[113]	train-mlogloss:2.01516	validation-mlogloss:1.97573
[114]	train-mlogloss:2.01246	validation-mlogloss:1.97343
[115]	train-mlogloss:2.00984	validation-mlogloss:1.97101
[116]	train-mlogloss:2.00702	validation-mlogloss:1.96847
[117]	train-mlogloss:2.00423	validation-mlogloss:1.96609
[118]	train-mlogloss:2.00149	validation-mlogloss:1.96393
[119]	train-mlogloss:1.99869	validation-mlogloss:1.96133
[120]	train-mlogloss:1.99590	validation-mlogloss:1.95894
[121]	train-mlogloss:1.99325	validation-mlogloss:1.95650
[122]	train-mlogloss:1.99056	validation-mlogloss:1.95398
[123]	train-mlogloss:1.98796	validation-mlogloss:1.95178
[124]	train-mlogloss:1.98537	validation-mlogloss:1.94924
[125]	train-mlogloss:1.98292	validation-mlogloss:1.94689
[126]	train-mlogloss:1.98048	validation-mlogloss:1.94489
[127]	train-mlogloss:1.97789	validation-mlogloss:1.94264
[128]	train-mlogloss:1.97529	validation-mlogloss:1.94038
[129]	train-mlogloss:1.97279	validation-mlogloss:1.93803
[130]	train-mlogloss:1.97057	validation-mlogloss:1.93580
[131]	train-mlogloss:1.96835	validation-mlogloss:1.93371
[132]	train-mlogloss:1.96602	validation-mlogloss:1.93141
[133]	train-mlogloss:1.96362	validation-mlogloss:1.92905
[134]	train-mlogloss:1.96133	validation-mlogloss:1.92715
[135]	train-mlogloss:1.95896	validation-mlogloss:1.92496
[136]	train-mlogloss:1.95672	validation-mlogloss:1.92270
[137]	train-mlogloss:1.95443	validation-mlogloss:1.92076
[138]	train-mlogloss:1.95210	validation-mlogloss:1.91873
[139]	train-mlogloss:1.94978	validation-mlogloss:1.91701
[140]	train-mlogloss:1.94756	validation-mlogloss:1.91513
[141]	train-mlogloss:1.94528	validation-mlogloss:1.91322
[142]	train-mlogloss:1.94301	validation-mlogloss:1.91138
[143]	train-mlogloss:1.94091	validation-mlogloss:1.90982
[144]	train-mlogloss:1.93869	validation-mlogloss:1.90806
[145]	train-mlogloss:1.93668	validation-mlogloss:1.90633
[146]	train-mlogloss:1.93449	validation-mlogloss:1.90478
[147]	train-mlogloss:1.93245	validation-mlogloss:1.90310
[148]	train-mlogloss:1.93017	validation-mlogloss:1.90100
[149]	train-mlogloss:1.92805	validation-mlogloss:1.89920
[150]	train-mlogloss:1.92583	validation-mlogloss:1.89745
[151]	train-mlogloss:1.92359	validation-mlogloss:1.89546
[152]	train-mlogloss:1.92161	validation-mlogloss:1.89372
[153]	train-mlogloss:1.91956	validation-mlogloss:1.89190
[154]	train-mlogloss:1.91760	validation-mlogloss:1.89059
[155]	train-mlogloss:1.91559	validation-mlogloss:1.88884
[156]	train-mlogloss:1.91352	validation-mlogloss:1.88719
[157]	train-mlogloss:1.91160	validation-mlogloss:1.88557
[158]	train-mlogloss:1.90967	validation-mlogloss:1.88369
[159]	train-mlogloss:1.90774	validation-mlogloss:1.88191
[160]	train-mlogloss:1.90575	validation-mlogloss:1.88063
[161]	train-mlogloss:1.90382	validation-mlogloss:1.87930
[162]	train-mlogloss:1.90188	validation-mlogloss:1.87783
[163]	train-mlogloss:1.89988	validation-mlogloss:1.87600
[164]	train-mlogloss:1.89805	validation-mlogloss:1.87423
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[168]	train-mlogloss:1.89051	validation-mlogloss:1.86756
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[170]	train-mlogloss:1.88686	validation-mlogloss:1.86500
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[172]	train-mlogloss:1.88327	validation-mlogloss:1.86193
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[190]	train-mlogloss:1.85229	validation-mlogloss:1.83806
[191]	train-mlogloss:1.85065	validation-mlogloss:1.83674
[192]	train-mlogloss:1.84903	validation-mlogloss:1.83563
[193]	train-mlogloss:1.84748	validation-mlogloss:1.83433
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[195]	train-mlogloss:1.84448	validation-mlogloss:1.83231
[196]	train-mlogloss:1.84291	validation-mlogloss:1.83114
[197]	train-mlogloss:1.84141	validation-mlogloss:1.83023
[198]	train-mlogloss:1.83982	validation-mlogloss:1.82917
[199]	train-mlogloss:1.83824	validation-mlogloss:1.82812
[200]	train-mlogloss:1.83671	validation-mlogloss:1.82693
[201]	train-mlogloss:1.83524	validation-mlogloss:1.82570
[202]	train-mlogloss:1.83373	validation-mlogloss:1.82461
[203]	train-mlogloss:1.83223	validation-mlogloss:1.82354
[204]	train-mlogloss:1.83069	validation-mlogloss:1.82231
[205]	train-mlogloss:1.82923	validation-mlogloss:1.82135
[206]	train-mlogloss:1.82778	validation-mlogloss:1.82040
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[208]	train-mlogloss:1.82493	validation-mlogloss:1.81845
[209]	train-mlogloss:1.82354	validation-mlogloss:1.81769
[210]	train-mlogloss:1.82206	validation-mlogloss:1.81689
[211]	train-mlogloss:1.82069	validation-mlogloss:1.81611
[212]	train-mlogloss:1.81920	validation-mlogloss:1.81497
[213]	train-mlogloss:1.81770	validation-mlogloss:1.81377
[214]	train-mlogloss:1.81641	validation-mlogloss:1.81303
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[217]	train-mlogloss:1.81241	validation-mlogloss:1.80987
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[521]	train-mlogloss:1.56814	validation-mlogloss:1.68510
[522]	train-mlogloss:1.56761	validation-mlogloss:1.68490
[523]	train-mlogloss:1.56716	validation-mlogloss:1.68497
[524]	train-mlogloss:1.56665	validation-mlogloss:1.68483
[525]	train-mlogloss:1.56607	validation-mlogloss:1.68461
[526]	train-mlogloss:1.56561	validation-mlogloss:1.68441
[527]	train-mlogloss:1.56523	validation-mlogloss:1.68445
[528]	train-mlogloss:1.56466	validation-mlogloss:1.68420
[529]	train-mlogloss:1.56419	validation-mlogloss:1.68390
[530]	train-mlogloss:1.56371	validation-mlogloss:1.68390
[531]	train-mlogloss:1.56315	validation-mlogloss:1.68371
[532]	train-mlogloss:1.56272	validation-mlogloss:1.68370
[533]	train-mlogloss:1.56223	validation-mlogloss:1.68342
[534]	train-mlogloss:1.56167	validation-mlogloss:1.68312
[535]	train-mlogloss:1.56114	validation-mlogloss:1.68319
[536]	train-mlogloss:1.56069	validation-mlogloss:1.68321
[537]	train-mlogloss:1.56019	validation-mlogloss:1.68312
[538]	train-mlogloss:1.55975	validation-mlogloss:1.68297
[539]	train-mlogloss:1.55943	validation-mlogloss:1.68298
Saved model to disk.
2025-10-27 09:43:13.011213: 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`.
2025-10-27 09:43:13.024019: 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 00:00:1761554593.038097  410407 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554593.042412  410407 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554593.053437  410407 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554593.053463  410407 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554593.053467  410407 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554593.053469  410407 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:43:13.056851: 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:2.69600	validation-mlogloss:2.69477
[1]	train-mlogloss:2.68197	validation-mlogloss:2.67960
[2]	train-mlogloss:2.66925	validation-mlogloss:2.66592
[3]	train-mlogloss:2.65548	validation-mlogloss:2.65136
[4]	train-mlogloss:2.64274	validation-mlogloss:2.63621
[5]	train-mlogloss:2.62964	validation-mlogloss:2.62200
[6]	train-mlogloss:2.61700	validation-mlogloss:2.60734
[7]	train-mlogloss:2.60508	validation-mlogloss:2.59395
[8]	train-mlogloss:2.59323	validation-mlogloss:2.58050
[9]	train-mlogloss:2.58152	validation-mlogloss:2.56798
[10]	train-mlogloss:2.57021	validation-mlogloss:2.55470
[11]	train-mlogloss:2.55866	validation-mlogloss:2.54236
[12]	train-mlogloss:2.54854	validation-mlogloss:2.53144
[13]	train-mlogloss:2.53761	validation-mlogloss:2.51854
[14]	train-mlogloss:2.52731	validation-mlogloss:2.50750
[15]	train-mlogloss:2.51758	validation-mlogloss:2.49729
[16]	train-mlogloss:2.50814	validation-mlogloss:2.48664
[17]	train-mlogloss:2.49893	validation-mlogloss:2.47655
[18]	train-mlogloss:2.48944	validation-mlogloss:2.46601
[19]	train-mlogloss:2.48103	validation-mlogloss:2.45682
[20]	train-mlogloss:2.47186	validation-mlogloss:2.44640
[21]	train-mlogloss:2.46312	validation-mlogloss:2.43719
[22]	train-mlogloss:2.45409	validation-mlogloss:2.42735
[23]	train-mlogloss:2.44572	validation-mlogloss:2.41822
[24]	train-mlogloss:2.43682	validation-mlogloss:2.40834
[25]	train-mlogloss:2.42829	validation-mlogloss:2.39893
[26]	train-mlogloss:2.41992	validation-mlogloss:2.38974
[27]	train-mlogloss:2.41211	validation-mlogloss:2.38082
[28]	train-mlogloss:2.40455	validation-mlogloss:2.37285
[29]	train-mlogloss:2.39711	validation-mlogloss:2.36482
[30]	train-mlogloss:2.38939	validation-mlogloss:2.35667
[31]	train-mlogloss:2.38176	validation-mlogloss:2.34859
[32]	train-mlogloss:2.37406	validation-mlogloss:2.34022
[33]	train-mlogloss:2.36660	validation-mlogloss:2.33257
[34]	train-mlogloss:2.35993	validation-mlogloss:2.32477
[35]	train-mlogloss:2.35295	validation-mlogloss:2.31720
[36]	train-mlogloss:2.34599	validation-mlogloss:2.31022
[37]	train-mlogloss:2.33907	validation-mlogloss:2.30252
[38]	train-mlogloss:2.33268	validation-mlogloss:2.29526
[39]	train-mlogloss:2.32597	validation-mlogloss:2.28856
[40]	train-mlogloss:2.31940	validation-mlogloss:2.28121
[41]	train-mlogloss:2.31300	validation-mlogloss:2.27449
[42]	train-mlogloss:2.30660	validation-mlogloss:2.26783
[43]	train-mlogloss:2.30042	validation-mlogloss:2.26143
[44]	train-mlogloss:2.29396	validation-mlogloss:2.25521
[45]	train-mlogloss:2.28841	validation-mlogloss:2.24942
[46]	train-mlogloss:2.28267	validation-mlogloss:2.24317
[47]	train-mlogloss:2.27684	validation-mlogloss:2.23689
[48]	train-mlogloss:2.27120	validation-mlogloss:2.23052
[49]	train-mlogloss:2.26525	validation-mlogloss:2.22442
[50]	train-mlogloss:2.25962	validation-mlogloss:2.21856
[51]	train-mlogloss:2.25386	validation-mlogloss:2.21270
[52]	train-mlogloss:2.24855	validation-mlogloss:2.20738
[53]	train-mlogloss:2.24330	validation-mlogloss:2.20239
[54]	train-mlogloss:2.23793	validation-mlogloss:2.19699
[55]	train-mlogloss:2.23290	validation-mlogloss:2.19222
[56]	train-mlogloss:2.22754	validation-mlogloss:2.18671
[57]	train-mlogloss:2.22264	validation-mlogloss:2.18198
[58]	train-mlogloss:2.21760	validation-mlogloss:2.17699
[59]	train-mlogloss:2.21281	validation-mlogloss:2.17177
[60]	train-mlogloss:2.20801	validation-mlogloss:2.16718
[61]	train-mlogloss:2.20318	validation-mlogloss:2.16254
[62]	train-mlogloss:2.19836	validation-mlogloss:2.15758
[63]	train-mlogloss:2.19366	validation-mlogloss:2.15307
[64]	train-mlogloss:2.18879	validation-mlogloss:2.14802
[65]	train-mlogloss:2.18405	validation-mlogloss:2.14368
[66]	train-mlogloss:2.17968	validation-mlogloss:2.13977
[67]	train-mlogloss:2.17519	validation-mlogloss:2.13523
[68]	train-mlogloss:2.17093	validation-mlogloss:2.13049
[69]	train-mlogloss:2.16651	validation-mlogloss:2.12620
[70]	train-mlogloss:2.16233	validation-mlogloss:2.12230
[71]	train-mlogloss:2.15814	validation-mlogloss:2.11825
[72]	train-mlogloss:2.15412	validation-mlogloss:2.11441
[73]	train-mlogloss:2.15001	validation-mlogloss:2.11035
[74]	train-mlogloss:2.14580	validation-mlogloss:2.10609
[75]	train-mlogloss:2.14170	validation-mlogloss:2.10184
[76]	train-mlogloss:2.13782	validation-mlogloss:2.09800
[77]	train-mlogloss:2.13373	validation-mlogloss:2.09425
[78]	train-mlogloss:2.12991	validation-mlogloss:2.09069
[79]	train-mlogloss:2.12594	validation-mlogloss:2.08676
[80]	train-mlogloss:2.12214	validation-mlogloss:2.08288
[81]	train-mlogloss:2.11839	validation-mlogloss:2.07919
[82]	train-mlogloss:2.11484	validation-mlogloss:2.07574
[83]	train-mlogloss:2.11127	validation-mlogloss:2.07244
[84]	train-mlogloss:2.10763	validation-mlogloss:2.06887
[85]	train-mlogloss:2.10397	validation-mlogloss:2.06503
[86]	train-mlogloss:2.10036	validation-mlogloss:2.06158
[87]	train-mlogloss:2.09678	validation-mlogloss:2.05832
[88]	train-mlogloss:2.09340	validation-mlogloss:2.05513
[89]	train-mlogloss:2.08994	validation-mlogloss:2.05185
[90]	train-mlogloss:2.08645	validation-mlogloss:2.04861
[91]	train-mlogloss:2.08295	validation-mlogloss:2.04525
[92]	train-mlogloss:2.07961	validation-mlogloss:2.04166
[93]	train-mlogloss:2.07620	validation-mlogloss:2.03853
[94]	train-mlogloss:2.07286	validation-mlogloss:2.03571
[95]	train-mlogloss:2.06953	validation-mlogloss:2.03256
[96]	train-mlogloss:2.06632	validation-mlogloss:2.02987
[97]	train-mlogloss:2.06317	validation-mlogloss:2.02712
[98]	train-mlogloss:2.06000	validation-mlogloss:2.02440
[99]	train-mlogloss:2.05694	validation-mlogloss:2.02143
[100]	train-mlogloss:2.05388	validation-mlogloss:2.01871
[101]	train-mlogloss:2.05063	validation-mlogloss:2.01584
[102]	train-mlogloss:2.04760	validation-mlogloss:2.01293
[103]	train-mlogloss:2.04455	validation-mlogloss:2.01003
[104]	train-mlogloss:2.04150	validation-mlogloss:2.00700
[105]	train-mlogloss:2.03856	validation-mlogloss:2.00450
[106]	train-mlogloss:2.03565	validation-mlogloss:2.00218
[107]	train-mlogloss:2.03280	validation-mlogloss:1.99989
[108]	train-mlogloss:2.02979	validation-mlogloss:1.99690
[109]	train-mlogloss:2.02680	validation-mlogloss:1.99378
[110]	train-mlogloss:2.02411	validation-mlogloss:1.99129
[111]	train-mlogloss:2.02146	validation-mlogloss:1.98891
[112]	train-mlogloss:2.01853	validation-mlogloss:1.98631
[113]	train-mlogloss:2.01557	validation-mlogloss:1.98313
[114]	train-mlogloss:2.01273	validation-mlogloss:1.98035
[115]	train-mlogloss:2.00990	validation-mlogloss:1.97759
[116]	train-mlogloss:2.00723	validation-mlogloss:1.97517
[117]	train-mlogloss:2.00431	validation-mlogloss:1.97214
[118]	train-mlogloss:2.00164	validation-mlogloss:1.96973
[119]	train-mlogloss:1.99911	validation-mlogloss:1.96748
[120]	train-mlogloss:1.99649	validation-mlogloss:1.96506
[121]	train-mlogloss:1.99397	validation-mlogloss:1.96295
[122]	train-mlogloss:1.99148	validation-mlogloss:1.96068
[123]	train-mlogloss:1.98890	validation-mlogloss:1.95869
[124]	train-mlogloss:1.98639	validation-mlogloss:1.95656
[125]	train-mlogloss:1.98398	validation-mlogloss:1.95430
[126]	train-mlogloss:1.98145	validation-mlogloss:1.95152
[127]	train-mlogloss:1.97892	validation-mlogloss:1.94905
[128]	train-mlogloss:1.97651	validation-mlogloss:1.94666
[129]	train-mlogloss:1.97404	validation-mlogloss:1.94441
[130]	train-mlogloss:1.97152	validation-mlogloss:1.94240
[131]	train-mlogloss:1.96912	validation-mlogloss:1.94043
[132]	train-mlogloss:1.96667	validation-mlogloss:1.93845
[133]	train-mlogloss:1.96441	validation-mlogloss:1.93675
[134]	train-mlogloss:1.96202	validation-mlogloss:1.93417
[135]	train-mlogloss:1.95966	validation-mlogloss:1.93184
[136]	train-mlogloss:1.95736	validation-mlogloss:1.92932
[137]	train-mlogloss:1.95498	validation-mlogloss:1.92721
[138]	train-mlogloss:1.95272	validation-mlogloss:1.92506
[139]	train-mlogloss:1.95047	validation-mlogloss:1.92338
[140]	train-mlogloss:1.94817	validation-mlogloss:1.92129
[141]	train-mlogloss:1.94597	validation-mlogloss:1.91930
[142]	train-mlogloss:1.94369	validation-mlogloss:1.91726
[143]	train-mlogloss:1.94144	validation-mlogloss:1.91551
[144]	train-mlogloss:1.93920	validation-mlogloss:1.91362
[145]	train-mlogloss:1.93708	validation-mlogloss:1.91175
[146]	train-mlogloss:1.93504	validation-mlogloss:1.91047
[147]	train-mlogloss:1.93286	validation-mlogloss:1.90835
[148]	train-mlogloss:1.93081	validation-mlogloss:1.90665
[149]	train-mlogloss:1.92882	validation-mlogloss:1.90514
[150]	train-mlogloss:1.92662	validation-mlogloss:1.90312
[151]	train-mlogloss:1.92462	validation-mlogloss:1.90140
[152]	train-mlogloss:1.92248	validation-mlogloss:1.89941
[153]	train-mlogloss:1.92021	validation-mlogloss:1.89785
[154]	train-mlogloss:1.91824	validation-mlogloss:1.89643
[155]	train-mlogloss:1.91622	validation-mlogloss:1.89532
[156]	train-mlogloss:1.91426	validation-mlogloss:1.89366
[157]	train-mlogloss:1.91240	validation-mlogloss:1.89209
[158]	train-mlogloss:1.91047	validation-mlogloss:1.89052
[159]	train-mlogloss:1.90853	validation-mlogloss:1.88879
[160]	train-mlogloss:1.90672	validation-mlogloss:1.88724
[161]	train-mlogloss:1.90470	validation-mlogloss:1.88568
[162]	train-mlogloss:1.90284	validation-mlogloss:1.88408
[163]	train-mlogloss:1.90079	validation-mlogloss:1.88236
[164]	train-mlogloss:1.89886	validation-mlogloss:1.88067
[165]	train-mlogloss:1.89693	validation-mlogloss:1.87906
[166]	train-mlogloss:1.89509	validation-mlogloss:1.87790
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[169]	train-mlogloss:1.88947	validation-mlogloss:1.87300
[170]	train-mlogloss:1.88767	validation-mlogloss:1.87162
[171]	train-mlogloss:1.88591	validation-mlogloss:1.86996
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[173]	train-mlogloss:1.88221	validation-mlogloss:1.86677
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[189]	train-mlogloss:1.85484	validation-mlogloss:1.84596
[190]	train-mlogloss:1.85328	validation-mlogloss:1.84489
[191]	train-mlogloss:1.85161	validation-mlogloss:1.84343
[192]	train-mlogloss:1.85004	validation-mlogloss:1.84227
[193]	train-mlogloss:1.84831	validation-mlogloss:1.84038
[194]	train-mlogloss:1.84669	validation-mlogloss:1.83894
[195]	train-mlogloss:1.84502	validation-mlogloss:1.83764
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[198]	train-mlogloss:1.84023	validation-mlogloss:1.83431
[199]	train-mlogloss:1.83862	validation-mlogloss:1.83318
[200]	train-mlogloss:1.83719	validation-mlogloss:1.83201
[201]	train-mlogloss:1.83568	validation-mlogloss:1.83082
[202]	train-mlogloss:1.83418	validation-mlogloss:1.82957
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[205]	train-mlogloss:1.82971	validation-mlogloss:1.82592
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[208]	train-mlogloss:1.82526	validation-mlogloss:1.82252
[209]	train-mlogloss:1.82375	validation-mlogloss:1.82157
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[211]	train-mlogloss:1.82094	validation-mlogloss:1.81931
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[522]	train-mlogloss:1.56629	validation-mlogloss:1.68761
[523]	train-mlogloss:1.56577	validation-mlogloss:1.68741
[524]	train-mlogloss:1.56530	validation-mlogloss:1.68742
[525]	train-mlogloss:1.56475	validation-mlogloss:1.68707
[526]	train-mlogloss:1.56421	validation-mlogloss:1.68688
[527]	train-mlogloss:1.56376	validation-mlogloss:1.68680
[528]	train-mlogloss:1.56337	validation-mlogloss:1.68663
[529]	train-mlogloss:1.56293	validation-mlogloss:1.68639
[530]	train-mlogloss:1.56256	validation-mlogloss:1.68653
[531]	train-mlogloss:1.56210	validation-mlogloss:1.68644
[532]	train-mlogloss:1.56161	validation-mlogloss:1.68651
[533]	train-mlogloss:1.56112	validation-mlogloss:1.68632
[534]	train-mlogloss:1.56062	validation-mlogloss:1.68611
[535]	train-mlogloss:1.56022	validation-mlogloss:1.68602
[536]	train-mlogloss:1.55976	validation-mlogloss:1.68603
[537]	train-mlogloss:1.55933	validation-mlogloss:1.68570
[538]	train-mlogloss:1.55883	validation-mlogloss:1.68544
[539]	train-mlogloss:1.55831	validation-mlogloss:1.68528
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, 91)
(18469, 91)
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 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.51 [%]
Global accuracy score (test) = 45.56 [%]
Global F1 score (train) = 51.65 [%]
Global F1 score (test) = 44.89 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.77      0.59       184
 CAMINAR CON MÓVIL O LIBRO       0.37      0.46      0.41       184
       CAMINAR USUAL SPEED       0.35      0.27      0.30       184
            CAMINAR ZIGZAG       0.40      0.55      0.46       184
          DE PIE BARRIENDO       0.75      0.29      0.42       184
   DE PIE DOBLANDO TOALLAS       0.50      0.42      0.46       184
    DE PIE MOVIENDO LIBROS       0.37      0.32      0.34       184
          DE PIE USANDO PC       0.23      0.35      0.28       184
        FASE REPOSO CON K5       0.57      0.86      0.69       184
INCREMENTAL CICLOERGOMETRO       0.75      0.68      0.72       184
           SENTADO LEYENDO       0.52      0.39      0.45       184
         SENTADO USANDO PC       0.26      0.16      0.20       184
      SENTADO VIENDO LA TV       0.29      0.24      0.27       184
   SUBIR Y BAJAR ESCALERAS       0.63      0.51      0.56       184
                    TROTAR       0.64      0.57      0.61       161

                  accuracy                           0.46      2737
                 macro avg       0.47      0.46      0.45      2737
              weighted avg       0.47      0.46      0.45      2737


Accuracy capturado en la ejecución 7: 45.56 [%]
F1-score capturado en la ejecución 7: 44.89 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.19 [%]
Global accuracy score (test) = 45.12 [%]
Global F1 score (train) = 51.31 [%]
Global F1 score (test) = 44.54 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.74      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.38      0.46      0.41       184
       CAMINAR USUAL SPEED       0.36      0.28      0.32       184
            CAMINAR ZIGZAG       0.38      0.55      0.45       184
          DE PIE BARRIENDO       0.71      0.30      0.42       184
   DE PIE DOBLANDO TOALLAS       0.52      0.43      0.47       184
    DE PIE MOVIENDO LIBROS       0.38      0.33      0.35       184
          DE PIE USANDO PC       0.21      0.33      0.26       184
        FASE REPOSO CON K5       0.58      0.85      0.69       184
INCREMENTAL CICLOERGOMETRO       0.75      0.67      0.71       184
           SENTADO LEYENDO       0.53      0.39      0.45       184
         SENTADO USANDO PC       0.18      0.10      0.13       184
      SENTADO VIENDO LA TV       0.30      0.27      0.28       184
   SUBIR Y BAJAR ESCALERAS       0.63      0.50      0.56       184
                    TROTAR       0.65      0.57      0.61       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.45      0.45      2737
              weighted avg       0.47      0.45      0.44      2737


Accuracy capturado en la ejecución 8: 45.12 [%]
F1-score capturado en la ejecución 8: 44.54 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.31 [%]
Global accuracy score (test) = 44.9 [%]
Global F1 score (train) = 51.43 [%]
Global F1 score (test) = 44.29 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.74      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.36      0.48      0.41       184
       CAMINAR USUAL SPEED       0.33      0.27      0.30       184
            CAMINAR ZIGZAG       0.39      0.52      0.44       184
          DE PIE BARRIENDO       0.73      0.31      0.44       184
   DE PIE DOBLANDO TOALLAS       0.52      0.43      0.47       184
    DE PIE MOVIENDO LIBROS       0.36      0.33      0.34       184
          DE PIE USANDO PC       0.22      0.34      0.27       184
        FASE REPOSO CON K5       0.57      0.86      0.69       184
INCREMENTAL CICLOERGOMETRO       0.75      0.70      0.72       184
           SENTADO LEYENDO       0.49      0.35      0.41       184
         SENTADO USANDO PC       0.22      0.12      0.16       184
      SENTADO VIENDO LA TV       0.30      0.26      0.28       184
   SUBIR Y BAJAR ESCALERAS       0.61      0.48      0.54       184
                    TROTAR       0.65      0.57      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 9: 44.9 [%]
F1-score capturado en la ejecución 9: 44.29 [%]

=== EJECUCIÓN 10 ===

--- TRAIN (ejecución 10) ---

--- TEST (ejecución 10) ---
2025-10-27 09:43:58.693935: 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`.
2025-10-27 09:43:58.706743: 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 00:00:1761554638.720738  411301 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554638.724899  411301 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554638.735798  411301 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554638.735821  411301 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554638.735824  411301 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554638.735826  411301 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:43:58.739043: 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:2.69455	validation-mlogloss:2.69474
[1]	train-mlogloss:2.68080	validation-mlogloss:2.68061
[2]	train-mlogloss:2.66652	validation-mlogloss:2.66506
[3]	train-mlogloss:2.65350	validation-mlogloss:2.65156
[4]	train-mlogloss:2.64207	validation-mlogloss:2.63802
[5]	train-mlogloss:2.62946	validation-mlogloss:2.62410
[6]	train-mlogloss:2.61723	validation-mlogloss:2.61080
[7]	train-mlogloss:2.60504	validation-mlogloss:2.59689
[8]	train-mlogloss:2.59251	validation-mlogloss:2.58273
[9]	train-mlogloss:2.58169	validation-mlogloss:2.57135
[10]	train-mlogloss:2.57040	validation-mlogloss:2.55787
[11]	train-mlogloss:2.55906	validation-mlogloss:2.54534
[12]	train-mlogloss:2.54861	validation-mlogloss:2.53333
[13]	train-mlogloss:2.53806	validation-mlogloss:2.52120
[14]	train-mlogloss:2.52759	validation-mlogloss:2.50947
[15]	train-mlogloss:2.51801	validation-mlogloss:2.49848
[16]	train-mlogloss:2.50841	validation-mlogloss:2.48754
[17]	train-mlogloss:2.49855	validation-mlogloss:2.47660
[18]	train-mlogloss:2.48885	validation-mlogloss:2.46581
[19]	train-mlogloss:2.47957	validation-mlogloss:2.45454
[20]	train-mlogloss:2.47118	validation-mlogloss:2.44506
[21]	train-mlogloss:2.46273	validation-mlogloss:2.43511
[22]	train-mlogloss:2.45505	validation-mlogloss:2.42600
[23]	train-mlogloss:2.44659	validation-mlogloss:2.41649
[24]	train-mlogloss:2.43798	validation-mlogloss:2.40687
[25]	train-mlogloss:2.42991	validation-mlogloss:2.39772
[26]	train-mlogloss:2.42144	validation-mlogloss:2.38785
[27]	train-mlogloss:2.41279	validation-mlogloss:2.37868
[28]	train-mlogloss:2.40435	validation-mlogloss:2.36964
[29]	train-mlogloss:2.39676	validation-mlogloss:2.36164
[30]	train-mlogloss:2.38959	validation-mlogloss:2.35349
[31]	train-mlogloss:2.38230	validation-mlogloss:2.34551
[32]	train-mlogloss:2.37493	validation-mlogloss:2.33724
[33]	train-mlogloss:2.36800	validation-mlogloss:2.32931
[34]	train-mlogloss:2.36087	validation-mlogloss:2.32116
[35]	train-mlogloss:2.35383	validation-mlogloss:2.31339
[36]	train-mlogloss:2.34698	validation-mlogloss:2.30610
[37]	train-mlogloss:2.34009	validation-mlogloss:2.29886
[38]	train-mlogloss:2.33305	validation-mlogloss:2.29084
[39]	train-mlogloss:2.32644	validation-mlogloss:2.28376
[40]	train-mlogloss:2.31994	validation-mlogloss:2.27700
[41]	train-mlogloss:2.31361	validation-mlogloss:2.26989
[42]	train-mlogloss:2.30711	validation-mlogloss:2.26304
[43]	train-mlogloss:2.30095	validation-mlogloss:2.25616
[44]	train-mlogloss:2.29496	validation-mlogloss:2.25042
[45]	train-mlogloss:2.28903	validation-mlogloss:2.24437
[46]	train-mlogloss:2.28320	validation-mlogloss:2.23860
[47]	train-mlogloss:2.27752	validation-mlogloss:2.23219
[48]	train-mlogloss:2.27159	validation-mlogloss:2.22593
[49]	train-mlogloss:2.26609	validation-mlogloss:2.22056
[50]	train-mlogloss:2.26054	validation-mlogloss:2.21467
[51]	train-mlogloss:2.25493	validation-mlogloss:2.20898
[52]	train-mlogloss:2.24967	validation-mlogloss:2.20345
[53]	train-mlogloss:2.24444	validation-mlogloss:2.19850
[54]	train-mlogloss:2.23886	validation-mlogloss:2.19296
[55]	train-mlogloss:2.23382	validation-mlogloss:2.18777
[56]	train-mlogloss:2.22859	validation-mlogloss:2.18253
[57]	train-mlogloss:2.22376	validation-mlogloss:2.17789
[58]	train-mlogloss:2.21885	validation-mlogloss:2.17291
[59]	train-mlogloss:2.21395	validation-mlogloss:2.16750
[60]	train-mlogloss:2.20938	validation-mlogloss:2.16295
[61]	train-mlogloss:2.20434	validation-mlogloss:2.15772
[62]	train-mlogloss:2.19938	validation-mlogloss:2.15257
[63]	train-mlogloss:2.19468	validation-mlogloss:2.14728
[64]	train-mlogloss:2.19022	validation-mlogloss:2.14317
[65]	train-mlogloss:2.18597	validation-mlogloss:2.13872
[66]	train-mlogloss:2.18133	validation-mlogloss:2.13390
[67]	train-mlogloss:2.17693	validation-mlogloss:2.12920
[68]	train-mlogloss:2.17271	validation-mlogloss:2.12509
[69]	train-mlogloss:2.16819	validation-mlogloss:2.12088
[70]	train-mlogloss:2.16397	validation-mlogloss:2.11710
[71]	train-mlogloss:2.15982	validation-mlogloss:2.11279
[72]	train-mlogloss:2.15556	validation-mlogloss:2.10863
[73]	train-mlogloss:2.15130	validation-mlogloss:2.10476
[74]	train-mlogloss:2.14717	validation-mlogloss:2.10055
[75]	train-mlogloss:2.14330	validation-mlogloss:2.09663
[76]	train-mlogloss:2.13929	validation-mlogloss:2.09273
[77]	train-mlogloss:2.13547	validation-mlogloss:2.08884
[78]	train-mlogloss:2.13159	validation-mlogloss:2.08494
[79]	train-mlogloss:2.12784	validation-mlogloss:2.08146
[80]	train-mlogloss:2.12406	validation-mlogloss:2.07805
[81]	train-mlogloss:2.12038	validation-mlogloss:2.07425
[82]	train-mlogloss:2.11639	validation-mlogloss:2.07064
[83]	train-mlogloss:2.11254	validation-mlogloss:2.06672
[84]	train-mlogloss:2.10861	validation-mlogloss:2.06313
[85]	train-mlogloss:2.10489	validation-mlogloss:2.05977
[86]	train-mlogloss:2.10124	validation-mlogloss:2.05629
[87]	train-mlogloss:2.09734	validation-mlogloss:2.05276
[88]	train-mlogloss:2.09380	validation-mlogloss:2.04960
[89]	train-mlogloss:2.09037	validation-mlogloss:2.04620
[90]	train-mlogloss:2.08687	validation-mlogloss:2.04280
[91]	train-mlogloss:2.08351	validation-mlogloss:2.03949
[92]	train-mlogloss:2.08017	validation-mlogloss:2.03630
[93]	train-mlogloss:2.07687	validation-mlogloss:2.03350
[94]	train-mlogloss:2.07363	validation-mlogloss:2.03060
[95]	train-mlogloss:2.07020	validation-mlogloss:2.02738
[96]	train-mlogloss:2.06692	validation-mlogloss:2.02448
[97]	train-mlogloss:2.06370	validation-mlogloss:2.02135
[98]	train-mlogloss:2.06047	validation-mlogloss:2.01820
[99]	train-mlogloss:2.05703	validation-mlogloss:2.01488
[100]	train-mlogloss:2.05395	validation-mlogloss:2.01167
[101]	train-mlogloss:2.05090	validation-mlogloss:2.00875
[102]	train-mlogloss:2.04789	validation-mlogloss:2.00584
[103]	train-mlogloss:2.04475	validation-mlogloss:2.00335
[104]	train-mlogloss:2.04180	validation-mlogloss:2.00098
[105]	train-mlogloss:2.03883	validation-mlogloss:1.99778
[106]	train-mlogloss:2.03591	validation-mlogloss:1.99507
[107]	train-mlogloss:2.03277	validation-mlogloss:1.99240
[108]	train-mlogloss:2.02992	validation-mlogloss:1.98961
[109]	train-mlogloss:2.02711	validation-mlogloss:1.98698
[110]	train-mlogloss:2.02417	validation-mlogloss:1.98420
[111]	train-mlogloss:2.02140	validation-mlogloss:1.98192
[112]	train-mlogloss:2.01866	validation-mlogloss:1.97915
[113]	train-mlogloss:2.01592	validation-mlogloss:1.97655
[114]	train-mlogloss:2.01332	validation-mlogloss:1.97442
[115]	train-mlogloss:2.01069	validation-mlogloss:1.97205
[116]	train-mlogloss:2.00793	validation-mlogloss:1.96950
[117]	train-mlogloss:2.00523	validation-mlogloss:1.96719
[118]	train-mlogloss:2.00233	validation-mlogloss:1.96419
[119]	train-mlogloss:1.99985	validation-mlogloss:1.96201
[120]	train-mlogloss:1.99733	validation-mlogloss:1.95997
[121]	train-mlogloss:1.99485	validation-mlogloss:1.95786
[122]	train-mlogloss:1.99242	validation-mlogloss:1.95580
[123]	train-mlogloss:1.98995	validation-mlogloss:1.95405
[124]	train-mlogloss:1.98748	validation-mlogloss:1.95167
[125]	train-mlogloss:1.98507	validation-mlogloss:1.94955
[126]	train-mlogloss:1.98267	validation-mlogloss:1.94748
[127]	train-mlogloss:1.97995	validation-mlogloss:1.94473
[128]	train-mlogloss:1.97744	validation-mlogloss:1.94253
[129]	train-mlogloss:1.97490	validation-mlogloss:1.93991
[130]	train-mlogloss:1.97245	validation-mlogloss:1.93743
[131]	train-mlogloss:1.96992	validation-mlogloss:1.93480
[132]	train-mlogloss:1.96748	validation-mlogloss:1.93257
[133]	train-mlogloss:1.96483	validation-mlogloss:1.93016
[134]	train-mlogloss:1.96236	validation-mlogloss:1.92794
[135]	train-mlogloss:1.95998	validation-mlogloss:1.92579
[136]	train-mlogloss:1.95779	validation-mlogloss:1.92364
[137]	train-mlogloss:1.95531	validation-mlogloss:1.92157
[138]	train-mlogloss:1.95297	validation-mlogloss:1.91944
[139]	train-mlogloss:1.95063	validation-mlogloss:1.91747
[140]	train-mlogloss:1.94833	validation-mlogloss:1.91536
[141]	train-mlogloss:1.94615	validation-mlogloss:1.91328
[142]	train-mlogloss:1.94395	validation-mlogloss:1.91159
[143]	train-mlogloss:1.94177	validation-mlogloss:1.90985
[144]	train-mlogloss:1.93973	validation-mlogloss:1.90791
[145]	train-mlogloss:1.93755	validation-mlogloss:1.90591
[146]	train-mlogloss:1.93526	validation-mlogloss:1.90419
[147]	train-mlogloss:1.93318	validation-mlogloss:1.90237
[148]	train-mlogloss:1.93106	validation-mlogloss:1.90067
[149]	train-mlogloss:1.92907	validation-mlogloss:1.89915
[150]	train-mlogloss:1.92686	validation-mlogloss:1.89714
[151]	train-mlogloss:1.92479	validation-mlogloss:1.89562
[152]	train-mlogloss:1.92264	validation-mlogloss:1.89378
[153]	train-mlogloss:1.92078	validation-mlogloss:1.89234
[154]	train-mlogloss:1.91858	validation-mlogloss:1.89020
[155]	train-mlogloss:1.91640	validation-mlogloss:1.88824
[156]	train-mlogloss:1.91438	validation-mlogloss:1.88670
[157]	train-mlogloss:1.91233	validation-mlogloss:1.88523
[158]	train-mlogloss:1.91013	validation-mlogloss:1.88355
[159]	train-mlogloss:1.90812	validation-mlogloss:1.88161
[160]	train-mlogloss:1.90624	validation-mlogloss:1.87996
[161]	train-mlogloss:1.90428	validation-mlogloss:1.87860
[162]	train-mlogloss:1.90247	validation-mlogloss:1.87698
[163]	train-mlogloss:1.90061	validation-mlogloss:1.87563
[164]	train-mlogloss:1.89861	validation-mlogloss:1.87428
[165]	train-mlogloss:1.89680	validation-mlogloss:1.87292
[166]	train-mlogloss:1.89499	validation-mlogloss:1.87118
[167]	train-mlogloss:1.89323	validation-mlogloss:1.86997
[168]	train-mlogloss:1.89108	validation-mlogloss:1.86816
[169]	train-mlogloss:1.88911	validation-mlogloss:1.86685
[170]	train-mlogloss:1.88727	validation-mlogloss:1.86524
[171]	train-mlogloss:1.88553	validation-mlogloss:1.86372
[172]	train-mlogloss:1.88380	validation-mlogloss:1.86246
[173]	train-mlogloss:1.88196	validation-mlogloss:1.86062
[174]	train-mlogloss:1.88014	validation-mlogloss:1.85952
[175]	train-mlogloss:1.87834	validation-mlogloss:1.85827
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[476]	train-mlogloss:1.58984	validation-mlogloss:1.69312
[477]	train-mlogloss:1.58930	validation-mlogloss:1.69292
[478]	train-mlogloss:1.58876	validation-mlogloss:1.69290
[479]	train-mlogloss:1.58825	validation-mlogloss:1.69287
[480]	train-mlogloss:1.58775	validation-mlogloss:1.69258
[481]	train-mlogloss:1.58718	validation-mlogloss:1.69240
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[483]	train-mlogloss:1.58616	validation-mlogloss:1.69194
[484]	train-mlogloss:1.58561	validation-mlogloss:1.69166
[485]	train-mlogloss:1.58501	validation-mlogloss:1.69139
[486]	train-mlogloss:1.58442	validation-mlogloss:1.69138
[487]	train-mlogloss:1.58392	validation-mlogloss:1.69125
[488]	train-mlogloss:1.58346	validation-mlogloss:1.69102
[489]	train-mlogloss:1.58288	validation-mlogloss:1.69070
[490]	train-mlogloss:1.58231	validation-mlogloss:1.69035
[491]	train-mlogloss:1.58172	validation-mlogloss:1.69003
[492]	train-mlogloss:1.58119	validation-mlogloss:1.68994
[493]	train-mlogloss:1.58069	validation-mlogloss:1.68972
[494]	train-mlogloss:1.58018	validation-mlogloss:1.68960
[495]	train-mlogloss:1.57964	validation-mlogloss:1.68927
[496]	train-mlogloss:1.57899	validation-mlogloss:1.68929
[497]	train-mlogloss:1.57855	validation-mlogloss:1.68897
[498]	train-mlogloss:1.57795	validation-mlogloss:1.68877
[499]	train-mlogloss:1.57749	validation-mlogloss:1.68869
[500]	train-mlogloss:1.57688	validation-mlogloss:1.68855
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[502]	train-mlogloss:1.57583	validation-mlogloss:1.68821
[503]	train-mlogloss:1.57531	validation-mlogloss:1.68812
[504]	train-mlogloss:1.57485	validation-mlogloss:1.68798
[505]	train-mlogloss:1.57440	validation-mlogloss:1.68798
[506]	train-mlogloss:1.57382	validation-mlogloss:1.68758
[507]	train-mlogloss:1.57329	validation-mlogloss:1.68751
[508]	train-mlogloss:1.57278	validation-mlogloss:1.68727
[509]	train-mlogloss:1.57227	validation-mlogloss:1.68715
[510]	train-mlogloss:1.57178	validation-mlogloss:1.68711
[511]	train-mlogloss:1.57131	validation-mlogloss:1.68692
[512]	train-mlogloss:1.57077	validation-mlogloss:1.68672
[513]	train-mlogloss:1.57029	validation-mlogloss:1.68661
[514]	train-mlogloss:1.56974	validation-mlogloss:1.68647
[515]	train-mlogloss:1.56921	validation-mlogloss:1.68653
[516]	train-mlogloss:1.56865	validation-mlogloss:1.68620
[517]	train-mlogloss:1.56811	validation-mlogloss:1.68616
[518]	train-mlogloss:1.56762	validation-mlogloss:1.68595
[519]	train-mlogloss:1.56713	validation-mlogloss:1.68590
[520]	train-mlogloss:1.56656	validation-mlogloss:1.68566
[521]	train-mlogloss:1.56605	validation-mlogloss:1.68567
[522]	train-mlogloss:1.56560	validation-mlogloss:1.68564
[523]	train-mlogloss:1.56517	validation-mlogloss:1.68537
[524]	train-mlogloss:1.56470	validation-mlogloss:1.68514
[525]	train-mlogloss:1.56421	validation-mlogloss:1.68497
[526]	train-mlogloss:1.56367	validation-mlogloss:1.68496
[527]	train-mlogloss:1.56329	validation-mlogloss:1.68484
[528]	train-mlogloss:1.56277	validation-mlogloss:1.68467
[529]	train-mlogloss:1.56232	validation-mlogloss:1.68449
[530]	train-mlogloss:1.56186	validation-mlogloss:1.68434
[531]	train-mlogloss:1.56139	validation-mlogloss:1.68425
[532]	train-mlogloss:1.56094	validation-mlogloss:1.68411
[533]	train-mlogloss:1.56046	validation-mlogloss:1.68381
[534]	train-mlogloss:1.56000	validation-mlogloss:1.68364
[535]	train-mlogloss:1.55961	validation-mlogloss:1.68350
[536]	train-mlogloss:1.55926	validation-mlogloss:1.68359
[537]	train-mlogloss:1.55885	validation-mlogloss:1.68357
[538]	train-mlogloss:1.55844	validation-mlogloss:1.68342
[539]	train-mlogloss:1.55807	validation-mlogloss:1.68339
Saved model to disk.
2025-10-27 09:44:44.655112: 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`.
2025-10-27 09:44:44.667794: 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 00:00:1761554684.681232  412193 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554684.685504  412193 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554684.696441  412193 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554684.696465  412193 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554684.696469  412193 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554684.696471  412193 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:44:44.699846: 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:2.67971	validation-mlogloss:2.67659
[2]	train-mlogloss:2.66740	validation-mlogloss:2.66244
[3]	train-mlogloss:2.65386	validation-mlogloss:2.64768
[4]	train-mlogloss:2.64053	validation-mlogloss:2.63214
[5]	train-mlogloss:2.62778	validation-mlogloss:2.61815
[6]	train-mlogloss:2.61424	validation-mlogloss:2.60268
[7]	train-mlogloss:2.60231	validation-mlogloss:2.58955
[8]	train-mlogloss:2.59039	validation-mlogloss:2.57566
[9]	train-mlogloss:2.57926	validation-mlogloss:2.56235
[10]	train-mlogloss:2.56758	validation-mlogloss:2.54900
[11]	train-mlogloss:2.55685	validation-mlogloss:2.53672
[12]	train-mlogloss:2.54596	validation-mlogloss:2.52426
[13]	train-mlogloss:2.53492	validation-mlogloss:2.51186
[14]	train-mlogloss:2.52453	validation-mlogloss:2.50028
[15]	train-mlogloss:2.51544	validation-mlogloss:2.48988
[16]	train-mlogloss:2.50596	validation-mlogloss:2.47889
[17]	train-mlogloss:2.49600	validation-mlogloss:2.46812
[18]	train-mlogloss:2.48656	validation-mlogloss:2.45760
[19]	train-mlogloss:2.47770	validation-mlogloss:2.44800
[20]	train-mlogloss:2.46854	validation-mlogloss:2.43766
[21]	train-mlogloss:2.45931	validation-mlogloss:2.42763
[22]	train-mlogloss:2.45011	validation-mlogloss:2.41765
[23]	train-mlogloss:2.44180	validation-mlogloss:2.40872
[24]	train-mlogloss:2.43407	validation-mlogloss:2.40013
[25]	train-mlogloss:2.42581	validation-mlogloss:2.39079
[26]	train-mlogloss:2.41772	validation-mlogloss:2.38233
[27]	train-mlogloss:2.41007	validation-mlogloss:2.37408
[28]	train-mlogloss:2.40228	validation-mlogloss:2.36516
[29]	train-mlogloss:2.39466	validation-mlogloss:2.35735
[30]	train-mlogloss:2.38722	validation-mlogloss:2.34903
[31]	train-mlogloss:2.37994	validation-mlogloss:2.34109
[32]	train-mlogloss:2.37262	validation-mlogloss:2.33296
[33]	train-mlogloss:2.36544	validation-mlogloss:2.32541
[34]	train-mlogloss:2.35853	validation-mlogloss:2.31850
[35]	train-mlogloss:2.35117	validation-mlogloss:2.31054
[36]	train-mlogloss:2.34461	validation-mlogloss:2.30388
[37]	train-mlogloss:2.33788	validation-mlogloss:2.29633
[38]	train-mlogloss:2.33114	validation-mlogloss:2.28889
[39]	train-mlogloss:2.32449	validation-mlogloss:2.28165
[40]	train-mlogloss:2.31821	validation-mlogloss:2.27476
[41]	train-mlogloss:2.31200	validation-mlogloss:2.26887
[42]	train-mlogloss:2.30593	validation-mlogloss:2.26252
[43]	train-mlogloss:2.29974	validation-mlogloss:2.25611
[44]	train-mlogloss:2.29358	validation-mlogloss:2.24938
[45]	train-mlogloss:2.28743	validation-mlogloss:2.24258
[46]	train-mlogloss:2.28174	validation-mlogloss:2.23739
[47]	train-mlogloss:2.27579	validation-mlogloss:2.23073
[48]	train-mlogloss:2.27034	validation-mlogloss:2.22527
[49]	train-mlogloss:2.26482	validation-mlogloss:2.21912
[50]	train-mlogloss:2.25941	validation-mlogloss:2.21356
[51]	train-mlogloss:2.25426	validation-mlogloss:2.20846
[52]	train-mlogloss:2.24881	validation-mlogloss:2.20288
[53]	train-mlogloss:2.24320	validation-mlogloss:2.19696
[54]	train-mlogloss:2.23775	validation-mlogloss:2.19191
[55]	train-mlogloss:2.23266	validation-mlogloss:2.18699
[56]	train-mlogloss:2.22755	validation-mlogloss:2.18174
[57]	train-mlogloss:2.22276	validation-mlogloss:2.17657
[58]	train-mlogloss:2.21771	validation-mlogloss:2.17156
[59]	train-mlogloss:2.21278	validation-mlogloss:2.16649
[60]	train-mlogloss:2.20758	validation-mlogloss:2.16106
[61]	train-mlogloss:2.20286	validation-mlogloss:2.15656
[62]	train-mlogloss:2.19810	validation-mlogloss:2.15150
[63]	train-mlogloss:2.19345	validation-mlogloss:2.14677
[64]	train-mlogloss:2.18886	validation-mlogloss:2.14165
[65]	train-mlogloss:2.18431	validation-mlogloss:2.13704
[66]	train-mlogloss:2.18019	validation-mlogloss:2.13272
[67]	train-mlogloss:2.17558	validation-mlogloss:2.12849
[68]	train-mlogloss:2.17109	validation-mlogloss:2.12386
[69]	train-mlogloss:2.16656	validation-mlogloss:2.11948
[70]	train-mlogloss:2.16201	validation-mlogloss:2.11493
[71]	train-mlogloss:2.15804	validation-mlogloss:2.11130
[72]	train-mlogloss:2.15377	validation-mlogloss:2.10701
[73]	train-mlogloss:2.14983	validation-mlogloss:2.10284
[74]	train-mlogloss:2.14568	validation-mlogloss:2.09852
[75]	train-mlogloss:2.14179	validation-mlogloss:2.09481
[76]	train-mlogloss:2.13764	validation-mlogloss:2.09099
[77]	train-mlogloss:2.13373	validation-mlogloss:2.08675
[78]	train-mlogloss:2.12984	validation-mlogloss:2.08338
[79]	train-mlogloss:2.12597	validation-mlogloss:2.07934
[80]	train-mlogloss:2.12209	validation-mlogloss:2.07562
[81]	train-mlogloss:2.11820	validation-mlogloss:2.07212
[82]	train-mlogloss:2.11432	validation-mlogloss:2.06822
[83]	train-mlogloss:2.11058	validation-mlogloss:2.06478
[84]	train-mlogloss:2.10669	validation-mlogloss:2.06077
[85]	train-mlogloss:2.10297	validation-mlogloss:2.05721
[86]	train-mlogloss:2.09938	validation-mlogloss:2.05374
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[88]	train-mlogloss:2.09253	validation-mlogloss:2.04761
[89]	train-mlogloss:2.08925	validation-mlogloss:2.04484
[90]	train-mlogloss:2.08580	validation-mlogloss:2.04185
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[92]	train-mlogloss:2.07878	validation-mlogloss:2.03490
[93]	train-mlogloss:2.07535	validation-mlogloss:2.03133
[94]	train-mlogloss:2.07206	validation-mlogloss:2.02823
[95]	train-mlogloss:2.06881	validation-mlogloss:2.02531
[96]	train-mlogloss:2.06558	validation-mlogloss:2.02220
[97]	train-mlogloss:2.06237	validation-mlogloss:2.01951
[98]	train-mlogloss:2.05922	validation-mlogloss:2.01662
[99]	train-mlogloss:2.05616	validation-mlogloss:2.01395
[100]	train-mlogloss:2.05321	validation-mlogloss:2.01142
[101]	train-mlogloss:2.05015	validation-mlogloss:2.00851
[102]	train-mlogloss:2.04704	validation-mlogloss:2.00543
[103]	train-mlogloss:2.04389	validation-mlogloss:2.00256
[104]	train-mlogloss:2.04090	validation-mlogloss:1.99987
[105]	train-mlogloss:2.03788	validation-mlogloss:1.99704
[106]	train-mlogloss:2.03476	validation-mlogloss:1.99455
[107]	train-mlogloss:2.03193	validation-mlogloss:1.99187
[108]	train-mlogloss:2.02888	validation-mlogloss:1.98886
[109]	train-mlogloss:2.02602	validation-mlogloss:1.98653
[110]	train-mlogloss:2.02298	validation-mlogloss:1.98360
[111]	train-mlogloss:2.02027	validation-mlogloss:1.98138
[112]	train-mlogloss:2.01707	validation-mlogloss:1.97810
[113]	train-mlogloss:2.01422	validation-mlogloss:1.97526
[114]	train-mlogloss:2.01146	validation-mlogloss:1.97297
[115]	train-mlogloss:2.00871	validation-mlogloss:1.97018
[116]	train-mlogloss:2.00599	validation-mlogloss:1.96782
[117]	train-mlogloss:2.00326	validation-mlogloss:1.96547
[118]	train-mlogloss:2.00059	validation-mlogloss:1.96306
[119]	train-mlogloss:1.99794	validation-mlogloss:1.96029
[120]	train-mlogloss:1.99525	validation-mlogloss:1.95780
[121]	train-mlogloss:1.99268	validation-mlogloss:1.95559
[122]	train-mlogloss:1.99018	validation-mlogloss:1.95361
[123]	train-mlogloss:1.98757	validation-mlogloss:1.95113
[124]	train-mlogloss:1.98481	validation-mlogloss:1.94863
[125]	train-mlogloss:1.98234	validation-mlogloss:1.94639
[126]	train-mlogloss:1.98001	validation-mlogloss:1.94446
[127]	train-mlogloss:1.97753	validation-mlogloss:1.94193
[128]	train-mlogloss:1.97510	validation-mlogloss:1.93940
[129]	train-mlogloss:1.97261	validation-mlogloss:1.93745
[130]	train-mlogloss:1.97025	validation-mlogloss:1.93580
[131]	train-mlogloss:1.96772	validation-mlogloss:1.93347
[132]	train-mlogloss:1.96529	validation-mlogloss:1.93127
[133]	train-mlogloss:1.96283	validation-mlogloss:1.92883
[134]	train-mlogloss:1.96055	validation-mlogloss:1.92663
[135]	train-mlogloss:1.95832	validation-mlogloss:1.92485
[136]	train-mlogloss:1.95597	validation-mlogloss:1.92282
[137]	train-mlogloss:1.95372	validation-mlogloss:1.92096
[138]	train-mlogloss:1.95149	validation-mlogloss:1.91941
[139]	train-mlogloss:1.94907	validation-mlogloss:1.91716
[140]	train-mlogloss:1.94686	validation-mlogloss:1.91529
[141]	train-mlogloss:1.94471	validation-mlogloss:1.91378
[142]	train-mlogloss:1.94244	validation-mlogloss:1.91204
[143]	train-mlogloss:1.94020	validation-mlogloss:1.91031
[144]	train-mlogloss:1.93801	validation-mlogloss:1.90851
[145]	train-mlogloss:1.93588	validation-mlogloss:1.90656
[146]	train-mlogloss:1.93384	validation-mlogloss:1.90473
[147]	train-mlogloss:1.93167	validation-mlogloss:1.90292
[148]	train-mlogloss:1.92958	validation-mlogloss:1.90123
[149]	train-mlogloss:1.92760	validation-mlogloss:1.89975
[150]	train-mlogloss:1.92550	validation-mlogloss:1.89803
[151]	train-mlogloss:1.92327	validation-mlogloss:1.89592
[152]	train-mlogloss:1.92115	validation-mlogloss:1.89380
[153]	train-mlogloss:1.91915	validation-mlogloss:1.89206
[154]	train-mlogloss:1.91721	validation-mlogloss:1.89037
[155]	train-mlogloss:1.91518	validation-mlogloss:1.88894
[156]	train-mlogloss:1.91319	validation-mlogloss:1.88696
[157]	train-mlogloss:1.91117	validation-mlogloss:1.88535
[158]	train-mlogloss:1.90924	validation-mlogloss:1.88376
[159]	train-mlogloss:1.90737	validation-mlogloss:1.88197
[160]	train-mlogloss:1.90548	validation-mlogloss:1.88046
[161]	train-mlogloss:1.90346	validation-mlogloss:1.87856
[162]	train-mlogloss:1.90161	validation-mlogloss:1.87725
[163]	train-mlogloss:1.89973	validation-mlogloss:1.87577
[164]	train-mlogloss:1.89790	validation-mlogloss:1.87412
[165]	train-mlogloss:1.89603	validation-mlogloss:1.87284
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[169]	train-mlogloss:1.88876	validation-mlogloss:1.86685
[170]	train-mlogloss:1.88707	validation-mlogloss:1.86529
[171]	train-mlogloss:1.88515	validation-mlogloss:1.86346
[172]	train-mlogloss:1.88328	validation-mlogloss:1.86232
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[189]	train-mlogloss:1.85369	validation-mlogloss:1.83866
[190]	train-mlogloss:1.85208	validation-mlogloss:1.83765
[191]	train-mlogloss:1.85064	validation-mlogloss:1.83662
[192]	train-mlogloss:1.84907	validation-mlogloss:1.83563
[193]	train-mlogloss:1.84754	validation-mlogloss:1.83457
[194]	train-mlogloss:1.84601	validation-mlogloss:1.83321
[195]	train-mlogloss:1.84439	validation-mlogloss:1.83230
[196]	train-mlogloss:1.84282	validation-mlogloss:1.83124
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[198]	train-mlogloss:1.83974	validation-mlogloss:1.82866
[199]	train-mlogloss:1.83819	validation-mlogloss:1.82752
[200]	train-mlogloss:1.83670	validation-mlogloss:1.82639
[201]	train-mlogloss:1.83525	validation-mlogloss:1.82505
[202]	train-mlogloss:1.83365	validation-mlogloss:1.82394
[203]	train-mlogloss:1.83205	validation-mlogloss:1.82263
[204]	train-mlogloss:1.83042	validation-mlogloss:1.82152
[205]	train-mlogloss:1.82893	validation-mlogloss:1.82033
[206]	train-mlogloss:1.82749	validation-mlogloss:1.81928
[207]	train-mlogloss:1.82613	validation-mlogloss:1.81825
[208]	train-mlogloss:1.82486	validation-mlogloss:1.81747
[209]	train-mlogloss:1.82342	validation-mlogloss:1.81644
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[511]	train-mlogloss:1.57174	validation-mlogloss:1.68645
[512]	train-mlogloss:1.57127	validation-mlogloss:1.68634
[513]	train-mlogloss:1.57075	validation-mlogloss:1.68611
[514]	train-mlogloss:1.57027	validation-mlogloss:1.68591
[515]	train-mlogloss:1.56986	validation-mlogloss:1.68556
[516]	train-mlogloss:1.56936	validation-mlogloss:1.68554
[517]	train-mlogloss:1.56887	validation-mlogloss:1.68531
[518]	train-mlogloss:1.56831	validation-mlogloss:1.68501
[519]	train-mlogloss:1.56788	validation-mlogloss:1.68490
[520]	train-mlogloss:1.56740	validation-mlogloss:1.68470
[521]	train-mlogloss:1.56692	validation-mlogloss:1.68444
[522]	train-mlogloss:1.56645	validation-mlogloss:1.68422
[523]	train-mlogloss:1.56603	validation-mlogloss:1.68413
[524]	train-mlogloss:1.56556	validation-mlogloss:1.68401
[525]	train-mlogloss:1.56502	validation-mlogloss:1.68396
[526]	train-mlogloss:1.56458	validation-mlogloss:1.68387
[527]	train-mlogloss:1.56409	validation-mlogloss:1.68379
[528]	train-mlogloss:1.56359	validation-mlogloss:1.68369
[529]	train-mlogloss:1.56318	validation-mlogloss:1.68357
[530]	train-mlogloss:1.56274	validation-mlogloss:1.68343
[531]	train-mlogloss:1.56219	validation-mlogloss:1.68339
[532]	train-mlogloss:1.56176	validation-mlogloss:1.68329
[533]	train-mlogloss:1.56130	validation-mlogloss:1.68316
[534]	train-mlogloss:1.56089	validation-mlogloss:1.68301
[535]	train-mlogloss:1.56046	validation-mlogloss:1.68285
[536]	train-mlogloss:1.56003	validation-mlogloss:1.68272
[537]	train-mlogloss:1.55957	validation-mlogloss:1.68252
[538]	train-mlogloss:1.55906	validation-mlogloss:1.68257
[539]	train-mlogloss:1.55855	validation-mlogloss:1.68236
Saved model to disk.
2025-10-27 09:45:30.296423: 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`.
2025-10-27 09:45:30.309066: 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 00:00:1761554730.322708  413121 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554730.327025  413121 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554730.337889  413121 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554730.337911  413121 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554730.337915  413121 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554730.337917  413121 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:45:30.341229: 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:2.69391	validation-mlogloss:2.69252
[1]	train-mlogloss:2.67897	validation-mlogloss:2.67619
[2]	train-mlogloss:2.66596	validation-mlogloss:2.66237
[3]	train-mlogloss:2.65292	validation-mlogloss:2.64800
[4]	train-mlogloss:2.64088	validation-mlogloss:2.63473
[5]	train-mlogloss:2.62850	validation-mlogloss:2.62136
[6]	train-mlogloss:2.61549	validation-mlogloss:2.60709
[7]	train-mlogloss:2.60309	validation-mlogloss:2.59294
[8]	train-mlogloss:2.59089	validation-mlogloss:2.57942
[9]	train-mlogloss:2.57887	validation-mlogloss:2.56635
[10]	train-mlogloss:2.56706	validation-mlogloss:2.55300
[11]	train-mlogloss:2.55604	validation-mlogloss:2.54053
[12]	train-mlogloss:2.54558	validation-mlogloss:2.52851
[13]	train-mlogloss:2.53511	validation-mlogloss:2.51679
[14]	train-mlogloss:2.52463	validation-mlogloss:2.50430
[15]	train-mlogloss:2.51456	validation-mlogloss:2.49263
[16]	train-mlogloss:2.50513	validation-mlogloss:2.48174
[17]	train-mlogloss:2.49568	validation-mlogloss:2.47111
[18]	train-mlogloss:2.48591	validation-mlogloss:2.46023
[19]	train-mlogloss:2.47678	validation-mlogloss:2.45063
[20]	train-mlogloss:2.46785	validation-mlogloss:2.44085
[21]	train-mlogloss:2.45868	validation-mlogloss:2.43112
[22]	train-mlogloss:2.45023	validation-mlogloss:2.42166
[23]	train-mlogloss:2.44156	validation-mlogloss:2.41212
[24]	train-mlogloss:2.43342	validation-mlogloss:2.40293
[25]	train-mlogloss:2.42505	validation-mlogloss:2.39373
[26]	train-mlogloss:2.41721	validation-mlogloss:2.38515
[27]	train-mlogloss:2.40929	validation-mlogloss:2.37637
[28]	train-mlogloss:2.40115	validation-mlogloss:2.36766
[29]	train-mlogloss:2.39361	validation-mlogloss:2.35980
[30]	train-mlogloss:2.38601	validation-mlogloss:2.35130
[31]	train-mlogloss:2.37851	validation-mlogloss:2.34285
[32]	train-mlogloss:2.37106	validation-mlogloss:2.33500
[33]	train-mlogloss:2.36382	validation-mlogloss:2.32703
[34]	train-mlogloss:2.35712	validation-mlogloss:2.32006
[35]	train-mlogloss:2.34982	validation-mlogloss:2.31182
[36]	train-mlogloss:2.34331	validation-mlogloss:2.30487
[37]	train-mlogloss:2.33671	validation-mlogloss:2.29868
[38]	train-mlogloss:2.33032	validation-mlogloss:2.29184
[39]	train-mlogloss:2.32372	validation-mlogloss:2.28467
[40]	train-mlogloss:2.31721	validation-mlogloss:2.27757
[41]	train-mlogloss:2.31123	validation-mlogloss:2.27102
[42]	train-mlogloss:2.30504	validation-mlogloss:2.26433
[43]	train-mlogloss:2.29901	validation-mlogloss:2.25835
[44]	train-mlogloss:2.29282	validation-mlogloss:2.25167
[45]	train-mlogloss:2.28684	validation-mlogloss:2.24557
[46]	train-mlogloss:2.28095	validation-mlogloss:2.23930
[47]	train-mlogloss:2.27522	validation-mlogloss:2.23374
[48]	train-mlogloss:2.27008	validation-mlogloss:2.22841
[49]	train-mlogloss:2.26438	validation-mlogloss:2.22289
[50]	train-mlogloss:2.25890	validation-mlogloss:2.21700
[51]	train-mlogloss:2.25351	validation-mlogloss:2.21095
[52]	train-mlogloss:2.24806	validation-mlogloss:2.20547
[53]	train-mlogloss:2.24285	validation-mlogloss:2.19973
[54]	train-mlogloss:2.23759	validation-mlogloss:2.19469
[55]	train-mlogloss:2.23232	validation-mlogloss:2.18970
[56]	train-mlogloss:2.22700	validation-mlogloss:2.18425
[57]	train-mlogloss:2.22198	validation-mlogloss:2.17911
[58]	train-mlogloss:2.21697	validation-mlogloss:2.17401
[59]	train-mlogloss:2.21223	validation-mlogloss:2.16927
[60]	train-mlogloss:2.20756	validation-mlogloss:2.16437
[61]	train-mlogloss:2.20268	validation-mlogloss:2.15908
[62]	train-mlogloss:2.19798	validation-mlogloss:2.15441
[63]	train-mlogloss:2.19317	validation-mlogloss:2.14962
[64]	train-mlogloss:2.18873	validation-mlogloss:2.14489
[65]	train-mlogloss:2.18434	validation-mlogloss:2.14069
[66]	train-mlogloss:2.17996	validation-mlogloss:2.13634
[67]	train-mlogloss:2.17575	validation-mlogloss:2.13210
[68]	train-mlogloss:2.17132	validation-mlogloss:2.12755
[69]	train-mlogloss:2.16703	validation-mlogloss:2.12363
[70]	train-mlogloss:2.16270	validation-mlogloss:2.11935
[71]	train-mlogloss:2.15845	validation-mlogloss:2.11545
[72]	train-mlogloss:2.15424	validation-mlogloss:2.11147
[73]	train-mlogloss:2.15013	validation-mlogloss:2.10757
[74]	train-mlogloss:2.14601	validation-mlogloss:2.10364
[75]	train-mlogloss:2.14204	validation-mlogloss:2.09986
[76]	train-mlogloss:2.13797	validation-mlogloss:2.09600
[77]	train-mlogloss:2.13393	validation-mlogloss:2.09203
[78]	train-mlogloss:2.12986	validation-mlogloss:2.08775
[79]	train-mlogloss:2.12600	validation-mlogloss:2.08391
[80]	train-mlogloss:2.12215	validation-mlogloss:2.08044
[81]	train-mlogloss:2.11835	validation-mlogloss:2.07647
[82]	train-mlogloss:2.11472	validation-mlogloss:2.07333
[83]	train-mlogloss:2.11109	validation-mlogloss:2.06935
[84]	train-mlogloss:2.10743	validation-mlogloss:2.06592
[85]	train-mlogloss:2.10357	validation-mlogloss:2.06213
[86]	train-mlogloss:2.10014	validation-mlogloss:2.05860
[87]	train-mlogloss:2.09657	validation-mlogloss:2.05527
[88]	train-mlogloss:2.09308	validation-mlogloss:2.05185
[89]	train-mlogloss:2.08956	validation-mlogloss:2.04831
[90]	train-mlogloss:2.08609	validation-mlogloss:2.04493
[91]	train-mlogloss:2.08276	validation-mlogloss:2.04213
[92]	train-mlogloss:2.07935	validation-mlogloss:2.03860
[93]	train-mlogloss:2.07591	validation-mlogloss:2.03528
[94]	train-mlogloss:2.07248	validation-mlogloss:2.03252
[95]	train-mlogloss:2.06922	validation-mlogloss:2.02954
[96]	train-mlogloss:2.06620	validation-mlogloss:2.02637
[97]	train-mlogloss:2.06290	validation-mlogloss:2.02322
[98]	train-mlogloss:2.05971	validation-mlogloss:2.02036
[99]	train-mlogloss:2.05666	validation-mlogloss:2.01756
[100]	train-mlogloss:2.05358	validation-mlogloss:2.01501
[101]	train-mlogloss:2.05040	validation-mlogloss:2.01205
[102]	train-mlogloss:2.04721	validation-mlogloss:2.00903
[103]	train-mlogloss:2.04421	validation-mlogloss:2.00656
[104]	train-mlogloss:2.04109	validation-mlogloss:2.00357
[105]	train-mlogloss:2.03798	validation-mlogloss:2.00060
[106]	train-mlogloss:2.03499	validation-mlogloss:1.99807
[107]	train-mlogloss:2.03203	validation-mlogloss:1.99512
[108]	train-mlogloss:2.02904	validation-mlogloss:1.99218
[109]	train-mlogloss:2.02621	validation-mlogloss:1.98962
[110]	train-mlogloss:2.02330	validation-mlogloss:1.98676
[111]	train-mlogloss:2.02054	validation-mlogloss:1.98404
[112]	train-mlogloss:2.01772	validation-mlogloss:1.98166
[113]	train-mlogloss:2.01487	validation-mlogloss:1.97893
[114]	train-mlogloss:2.01199	validation-mlogloss:1.97653
[115]	train-mlogloss:2.00924	validation-mlogloss:1.97414
[116]	train-mlogloss:2.00630	validation-mlogloss:1.97142
[117]	train-mlogloss:2.00350	validation-mlogloss:1.96900
[118]	train-mlogloss:2.00072	validation-mlogloss:1.96650
[119]	train-mlogloss:1.99818	validation-mlogloss:1.96451
[120]	train-mlogloss:1.99567	validation-mlogloss:1.96230
[121]	train-mlogloss:1.99324	validation-mlogloss:1.96007
[122]	train-mlogloss:1.99075	validation-mlogloss:1.95778
[123]	train-mlogloss:1.98817	validation-mlogloss:1.95555
[124]	train-mlogloss:1.98574	validation-mlogloss:1.95314
[125]	train-mlogloss:1.98340	validation-mlogloss:1.95126
[126]	train-mlogloss:1.98083	validation-mlogloss:1.94875
[127]	train-mlogloss:1.97839	validation-mlogloss:1.94640
[128]	train-mlogloss:1.97585	validation-mlogloss:1.94404
[129]	train-mlogloss:1.97324	validation-mlogloss:1.94190
[130]	train-mlogloss:1.97067	validation-mlogloss:1.93978
[131]	train-mlogloss:1.96819	validation-mlogloss:1.93766
[132]	train-mlogloss:1.96585	validation-mlogloss:1.93561
[133]	train-mlogloss:1.96347	validation-mlogloss:1.93348
[134]	train-mlogloss:1.96114	validation-mlogloss:1.93133
[135]	train-mlogloss:1.95884	validation-mlogloss:1.92952
[136]	train-mlogloss:1.95663	validation-mlogloss:1.92799
[137]	train-mlogloss:1.95446	validation-mlogloss:1.92619
[138]	train-mlogloss:1.95229	validation-mlogloss:1.92408
[139]	train-mlogloss:1.94996	validation-mlogloss:1.92179
[140]	train-mlogloss:1.94771	validation-mlogloss:1.91989
[141]	train-mlogloss:1.94544	validation-mlogloss:1.91807
[142]	train-mlogloss:1.94332	validation-mlogloss:1.91628
[143]	train-mlogloss:1.94107	validation-mlogloss:1.91429
[144]	train-mlogloss:1.93892	validation-mlogloss:1.91234
[145]	train-mlogloss:1.93673	validation-mlogloss:1.91017
[146]	train-mlogloss:1.93471	validation-mlogloss:1.90864
[147]	train-mlogloss:1.93260	validation-mlogloss:1.90688
[148]	train-mlogloss:1.93058	validation-mlogloss:1.90524
[149]	train-mlogloss:1.92837	validation-mlogloss:1.90312
[150]	train-mlogloss:1.92637	validation-mlogloss:1.90159
[151]	train-mlogloss:1.92436	validation-mlogloss:1.89976
[152]	train-mlogloss:1.92226	validation-mlogloss:1.89789
[153]	train-mlogloss:1.92022	validation-mlogloss:1.89616
[154]	train-mlogloss:1.91826	validation-mlogloss:1.89451
[155]	train-mlogloss:1.91616	validation-mlogloss:1.89276
[156]	train-mlogloss:1.91430	validation-mlogloss:1.89137
[157]	train-mlogloss:1.91222	validation-mlogloss:1.88944
[158]	train-mlogloss:1.91023	validation-mlogloss:1.88767
[159]	train-mlogloss:1.90827	validation-mlogloss:1.88641
[160]	train-mlogloss:1.90603	validation-mlogloss:1.88463
[161]	train-mlogloss:1.90408	validation-mlogloss:1.88328
[162]	train-mlogloss:1.90222	validation-mlogloss:1.88177
[163]	train-mlogloss:1.90038	validation-mlogloss:1.88013
[164]	train-mlogloss:1.89859	validation-mlogloss:1.87886
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[171]	train-mlogloss:1.88558	validation-mlogloss:1.86793
[172]	train-mlogloss:1.88367	validation-mlogloss:1.86623
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[189]	train-mlogloss:1.85445	validation-mlogloss:1.84264
[190]	train-mlogloss:1.85272	validation-mlogloss:1.84149
[191]	train-mlogloss:1.85111	validation-mlogloss:1.84030
[192]	train-mlogloss:1.84959	validation-mlogloss:1.83917
[193]	train-mlogloss:1.84804	validation-mlogloss:1.83827
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[195]	train-mlogloss:1.84494	validation-mlogloss:1.83567
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[199]	train-mlogloss:1.83856	validation-mlogloss:1.83070
[200]	train-mlogloss:1.83714	validation-mlogloss:1.82963
[201]	train-mlogloss:1.83558	validation-mlogloss:1.82864
[202]	train-mlogloss:1.83404	validation-mlogloss:1.82736
[203]	train-mlogloss:1.83262	validation-mlogloss:1.82617
[204]	train-mlogloss:1.83130	validation-mlogloss:1.82508
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[209]	train-mlogloss:1.82395	validation-mlogloss:1.81979
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[211]	train-mlogloss:1.82135	validation-mlogloss:1.81766
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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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.15 [%]
Global accuracy score (test) = 46.04 [%]
Global F1 score (train) = 51.3 [%]
Global F1 score (test) = 45.44 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.49      0.74      0.59       184
 CAMINAR CON MÓVIL O LIBRO       0.37      0.47      0.41       184
       CAMINAR USUAL SPEED       0.35      0.31      0.33       184
            CAMINAR ZIGZAG       0.41      0.54      0.47       184
          DE PIE BARRIENDO       0.77      0.33      0.46       184
   DE PIE DOBLANDO TOALLAS       0.49      0.42      0.45       184
    DE PIE MOVIENDO LIBROS       0.38      0.33      0.35       184
          DE PIE USANDO PC       0.22      0.34      0.27       184
        FASE REPOSO CON K5       0.58      0.86      0.69       184
INCREMENTAL CICLOERGOMETRO       0.74      0.70      0.72       184
           SENTADO LEYENDO       0.49      0.38      0.43       184
         SENTADO USANDO PC       0.22      0.13      0.16       184
      SENTADO VIENDO LA TV       0.30      0.23      0.26       184
   SUBIR Y BAJAR ESCALERAS       0.66      0.57      0.61       184
                    TROTAR       0.65      0.57      0.61       161

                  accuracy                           0.46      2737
                 macro avg       0.47      0.46      0.45      2737
              weighted avg       0.47      0.46      0.45      2737


Accuracy capturado en la ejecución 10: 46.04 [%]
F1-score capturado en la ejecución 10: 45.44 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.43 [%]
Global accuracy score (test) = 45.2 [%]
Global F1 score (train) = 51.57 [%]
Global F1 score (test) = 44.71 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.74      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.38      0.47      0.42       184
       CAMINAR USUAL SPEED       0.35      0.28      0.31       184
            CAMINAR ZIGZAG       0.38      0.54      0.45       184
          DE PIE BARRIENDO       0.76      0.31      0.44       184
   DE PIE DOBLANDO TOALLAS       0.50      0.41      0.45       184
    DE PIE MOVIENDO LIBROS       0.37      0.35      0.36       184
          DE PIE USANDO PC       0.22      0.33      0.26       184
        FASE REPOSO CON K5       0.58      0.86      0.69       184
INCREMENTAL CICLOERGOMETRO       0.74      0.69      0.71       184
           SENTADO LEYENDO       0.47      0.34      0.40       184
         SENTADO USANDO PC       0.28      0.17      0.21       184
      SENTADO VIENDO LA TV       0.28      0.24      0.26       184
   SUBIR Y BAJAR ESCALERAS       0.65      0.50      0.57       184
                    TROTAR       0.66      0.57      0.61       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.45      0.45      2737
              weighted avg       0.47      0.45      0.45      2737


Accuracy capturado en la ejecución 11: 45.2 [%]
F1-score capturado en la ejecución 11: 44.71 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.38 [%]
Global accuracy score (test) = 45.41 [%]
Global F1 score (train) = 51.52 [%]
Global F1 score (test) = 44.89 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.74      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.36      0.47      0.41       184
       CAMINAR USUAL SPEED       0.35      0.28      0.31       184
            CAMINAR ZIGZAG       0.40      0.55      0.46       184
          DE PIE BARRIENDO       0.75      0.31      0.44       184
   DE PIE DOBLANDO TOALLAS       0.51      0.43      0.47       184
    DE PIE MOVIENDO LIBROS       0.37      0.30      0.33       184
          DE PIE USANDO PC       0.22      0.33      0.26       184
        FASE REPOSO CON K5       0.57      0.85      0.68       184
INCREMENTAL CICLOERGOMETRO       0.75      0.70      0.73       184
           SENTADO LEYENDO       0.50      0.36      0.42       184
         SENTADO USANDO PC       0.26      0.16      0.20       184
      SENTADO VIENDO LA TV       0.29      0.25      0.27       184
   SUBIR Y BAJAR ESCALERAS       0.64      0.51      0.56       184
                    TROTAR       0.67      0.57      0.62       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.46      0.45      2737
              weighted avg       0.47      0.45      0.45      2737


Accuracy capturado en la ejecución 12: 45.41 [%]
F1-score capturado en la ejecución 12: 44.89 [%]

=== EJECUCIÓN 13 ===

--- TRAIN (ejecución 13) ---

--- TEST (ejecución 13) ---
2025-10-27 09:46:16.317560: 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`.
2025-10-27 09:46:16.330193: 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 00:00:1761554776.343798  414048 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554776.348261  414048 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554776.359345  414048 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554776.359369  414048 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554776.359373  414048 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554776.359377  414048 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:46:16.362682: 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:2.69227	validation-mlogloss:2.69156
[1]	train-mlogloss:2.67879	validation-mlogloss:2.67632
[2]	train-mlogloss:2.66514	validation-mlogloss:2.66180
[3]	train-mlogloss:2.65304	validation-mlogloss:2.64848
[4]	train-mlogloss:2.63962	validation-mlogloss:2.63292
[5]	train-mlogloss:2.62710	validation-mlogloss:2.61863
[6]	train-mlogloss:2.61468	validation-mlogloss:2.60571
[7]	train-mlogloss:2.60268	validation-mlogloss:2.59262
[8]	train-mlogloss:2.59070	validation-mlogloss:2.57978
[9]	train-mlogloss:2.57997	validation-mlogloss:2.56800
[10]	train-mlogloss:2.56942	validation-mlogloss:2.55591
[11]	train-mlogloss:2.55827	validation-mlogloss:2.54391
[12]	train-mlogloss:2.54755	validation-mlogloss:2.53175
[13]	train-mlogloss:2.53733	validation-mlogloss:2.52051
[14]	train-mlogloss:2.52704	validation-mlogloss:2.50933
[15]	train-mlogloss:2.51694	validation-mlogloss:2.49812
[16]	train-mlogloss:2.50720	validation-mlogloss:2.48748
[17]	train-mlogloss:2.49753	validation-mlogloss:2.47677
[18]	train-mlogloss:2.48780	validation-mlogloss:2.46559
[19]	train-mlogloss:2.47882	validation-mlogloss:2.45573
[20]	train-mlogloss:2.46976	validation-mlogloss:2.44570
[21]	train-mlogloss:2.46089	validation-mlogloss:2.43604
[22]	train-mlogloss:2.45234	validation-mlogloss:2.42637
[23]	train-mlogloss:2.44405	validation-mlogloss:2.41761
[24]	train-mlogloss:2.43558	validation-mlogloss:2.40790
[25]	train-mlogloss:2.42719	validation-mlogloss:2.39864
[26]	train-mlogloss:2.41917	validation-mlogloss:2.39030
[27]	train-mlogloss:2.41160	validation-mlogloss:2.38155
[28]	train-mlogloss:2.40350	validation-mlogloss:2.37308
[29]	train-mlogloss:2.39620	validation-mlogloss:2.36529
[30]	train-mlogloss:2.38858	validation-mlogloss:2.35782
[31]	train-mlogloss:2.38120	validation-mlogloss:2.34957
[32]	train-mlogloss:2.37382	validation-mlogloss:2.34140
[33]	train-mlogloss:2.36655	validation-mlogloss:2.33273
[34]	train-mlogloss:2.35970	validation-mlogloss:2.32550
[35]	train-mlogloss:2.35289	validation-mlogloss:2.31832
[36]	train-mlogloss:2.34586	validation-mlogloss:2.31086
[37]	train-mlogloss:2.33935	validation-mlogloss:2.30441
[38]	train-mlogloss:2.33253	validation-mlogloss:2.29701
[39]	train-mlogloss:2.32591	validation-mlogloss:2.28972
[40]	train-mlogloss:2.31959	validation-mlogloss:2.28283
[41]	train-mlogloss:2.31346	validation-mlogloss:2.27628
[42]	train-mlogloss:2.30725	validation-mlogloss:2.27011
[43]	train-mlogloss:2.30103	validation-mlogloss:2.26389
[44]	train-mlogloss:2.29500	validation-mlogloss:2.25758
[45]	train-mlogloss:2.28896	validation-mlogloss:2.25117
[46]	train-mlogloss:2.28275	validation-mlogloss:2.24476
[47]	train-mlogloss:2.27668	validation-mlogloss:2.23846
[48]	train-mlogloss:2.27076	validation-mlogloss:2.23247
[49]	train-mlogloss:2.26524	validation-mlogloss:2.22705
[50]	train-mlogloss:2.25983	validation-mlogloss:2.22149
[51]	train-mlogloss:2.25459	validation-mlogloss:2.21604
[52]	train-mlogloss:2.24901	validation-mlogloss:2.21048
[53]	train-mlogloss:2.24397	validation-mlogloss:2.20497
[54]	train-mlogloss:2.23872	validation-mlogloss:2.19944
[55]	train-mlogloss:2.23354	validation-mlogloss:2.19440
[56]	train-mlogloss:2.22849	validation-mlogloss:2.18925
[57]	train-mlogloss:2.22338	validation-mlogloss:2.18417
[58]	train-mlogloss:2.21846	validation-mlogloss:2.17925
[59]	train-mlogloss:2.21346	validation-mlogloss:2.17405
[60]	train-mlogloss:2.20873	validation-mlogloss:2.16916
[61]	train-mlogloss:2.20382	validation-mlogloss:2.16396
[62]	train-mlogloss:2.19874	validation-mlogloss:2.15849
[63]	train-mlogloss:2.19415	validation-mlogloss:2.15365
[64]	train-mlogloss:2.18967	validation-mlogloss:2.14919
[65]	train-mlogloss:2.18506	validation-mlogloss:2.14442
[66]	train-mlogloss:2.18079	validation-mlogloss:2.13991
[67]	train-mlogloss:2.17620	validation-mlogloss:2.13486
[68]	train-mlogloss:2.17158	validation-mlogloss:2.13043
[69]	train-mlogloss:2.16723	validation-mlogloss:2.12612
[70]	train-mlogloss:2.16271	validation-mlogloss:2.12112
[71]	train-mlogloss:2.15827	validation-mlogloss:2.11657
[72]	train-mlogloss:2.15403	validation-mlogloss:2.11258
[73]	train-mlogloss:2.14978	validation-mlogloss:2.10781
[74]	train-mlogloss:2.14543	validation-mlogloss:2.10339
[75]	train-mlogloss:2.14131	validation-mlogloss:2.09911
[76]	train-mlogloss:2.13737	validation-mlogloss:2.09514
[77]	train-mlogloss:2.13341	validation-mlogloss:2.09109
[78]	train-mlogloss:2.12952	validation-mlogloss:2.08710
[79]	train-mlogloss:2.12542	validation-mlogloss:2.08349
[80]	train-mlogloss:2.12155	validation-mlogloss:2.07961
[81]	train-mlogloss:2.11777	validation-mlogloss:2.07614
[82]	train-mlogloss:2.11403	validation-mlogloss:2.07188
[83]	train-mlogloss:2.11038	validation-mlogloss:2.06847
[84]	train-mlogloss:2.10656	validation-mlogloss:2.06472
[85]	train-mlogloss:2.10301	validation-mlogloss:2.06115
[86]	train-mlogloss:2.09936	validation-mlogloss:2.05802
[87]	train-mlogloss:2.09584	validation-mlogloss:2.05494
[88]	train-mlogloss:2.09232	validation-mlogloss:2.05176
[89]	train-mlogloss:2.08872	validation-mlogloss:2.04849
[90]	train-mlogloss:2.08525	validation-mlogloss:2.04485
[91]	train-mlogloss:2.08200	validation-mlogloss:2.04174
[92]	train-mlogloss:2.07875	validation-mlogloss:2.03832
[93]	train-mlogloss:2.07556	validation-mlogloss:2.03535
[94]	train-mlogloss:2.07234	validation-mlogloss:2.03204
[95]	train-mlogloss:2.06901	validation-mlogloss:2.02885
[96]	train-mlogloss:2.06588	validation-mlogloss:2.02593
[97]	train-mlogloss:2.06267	validation-mlogloss:2.02299
[98]	train-mlogloss:2.05954	validation-mlogloss:2.01975
[99]	train-mlogloss:2.05632	validation-mlogloss:2.01687
[100]	train-mlogloss:2.05319	validation-mlogloss:2.01399
[101]	train-mlogloss:2.05022	validation-mlogloss:2.01116
[102]	train-mlogloss:2.04725	validation-mlogloss:2.00837
[103]	train-mlogloss:2.04405	validation-mlogloss:2.00562
[104]	train-mlogloss:2.04104	validation-mlogloss:2.00240
[105]	train-mlogloss:2.03805	validation-mlogloss:2.00002
[106]	train-mlogloss:2.03508	validation-mlogloss:1.99749
[107]	train-mlogloss:2.03215	validation-mlogloss:1.99462
[108]	train-mlogloss:2.02922	validation-mlogloss:1.99191
[109]	train-mlogloss:2.02646	validation-mlogloss:1.98976
[110]	train-mlogloss:2.02364	validation-mlogloss:1.98716
[111]	train-mlogloss:2.02055	validation-mlogloss:1.98416
[112]	train-mlogloss:2.01788	validation-mlogloss:1.98174
[113]	train-mlogloss:2.01514	validation-mlogloss:1.97908
[114]	train-mlogloss:2.01244	validation-mlogloss:1.97654
[115]	train-mlogloss:2.00971	validation-mlogloss:1.97401
[116]	train-mlogloss:2.00714	validation-mlogloss:1.97173
[117]	train-mlogloss:2.00457	validation-mlogloss:1.96955
[118]	train-mlogloss:2.00178	validation-mlogloss:1.96685
[119]	train-mlogloss:1.99923	validation-mlogloss:1.96454
[120]	train-mlogloss:1.99674	validation-mlogloss:1.96202
[121]	train-mlogloss:1.99417	validation-mlogloss:1.95956
[122]	train-mlogloss:1.99155	validation-mlogloss:1.95707
[123]	train-mlogloss:1.98913	validation-mlogloss:1.95488
[124]	train-mlogloss:1.98658	validation-mlogloss:1.95276
[125]	train-mlogloss:1.98410	validation-mlogloss:1.95041
[126]	train-mlogloss:1.98171	validation-mlogloss:1.94838
[127]	train-mlogloss:1.97916	validation-mlogloss:1.94608
[128]	train-mlogloss:1.97671	validation-mlogloss:1.94407
[129]	train-mlogloss:1.97440	validation-mlogloss:1.94210
[130]	train-mlogloss:1.97212	validation-mlogloss:1.93997
[131]	train-mlogloss:1.96968	validation-mlogloss:1.93787
[132]	train-mlogloss:1.96725	validation-mlogloss:1.93544
[133]	train-mlogloss:1.96482	validation-mlogloss:1.93333
[134]	train-mlogloss:1.96253	validation-mlogloss:1.93133
[135]	train-mlogloss:1.96023	validation-mlogloss:1.92928
[136]	train-mlogloss:1.95798	validation-mlogloss:1.92730
[137]	train-mlogloss:1.95577	validation-mlogloss:1.92547
[138]	train-mlogloss:1.95351	validation-mlogloss:1.92366
[139]	train-mlogloss:1.95124	validation-mlogloss:1.92206
[140]	train-mlogloss:1.94915	validation-mlogloss:1.92017
[141]	train-mlogloss:1.94695	validation-mlogloss:1.91773
[142]	train-mlogloss:1.94471	validation-mlogloss:1.91583
[143]	train-mlogloss:1.94256	validation-mlogloss:1.91423
[144]	train-mlogloss:1.94022	validation-mlogloss:1.91209
[145]	train-mlogloss:1.93807	validation-mlogloss:1.91019
[146]	train-mlogloss:1.93605	validation-mlogloss:1.90874
[147]	train-mlogloss:1.93388	validation-mlogloss:1.90711
[148]	train-mlogloss:1.93177	validation-mlogloss:1.90532
[149]	train-mlogloss:1.92978	validation-mlogloss:1.90389
[150]	train-mlogloss:1.92764	validation-mlogloss:1.90216
[151]	train-mlogloss:1.92548	validation-mlogloss:1.90016
[152]	train-mlogloss:1.92330	validation-mlogloss:1.89835
[153]	train-mlogloss:1.92123	validation-mlogloss:1.89677
[154]	train-mlogloss:1.91923	validation-mlogloss:1.89502
[155]	train-mlogloss:1.91735	validation-mlogloss:1.89344
[156]	train-mlogloss:1.91536	validation-mlogloss:1.89192
[157]	train-mlogloss:1.91326	validation-mlogloss:1.88996
[158]	train-mlogloss:1.91133	validation-mlogloss:1.88859
[159]	train-mlogloss:1.90929	validation-mlogloss:1.88708
[160]	train-mlogloss:1.90733	validation-mlogloss:1.88536
[161]	train-mlogloss:1.90535	validation-mlogloss:1.88400
[162]	train-mlogloss:1.90349	validation-mlogloss:1.88240
[163]	train-mlogloss:1.90154	validation-mlogloss:1.88065
[164]	train-mlogloss:1.89976	validation-mlogloss:1.87923
[165]	train-mlogloss:1.89783	validation-mlogloss:1.87752
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[466]	train-mlogloss:1.59600	validation-mlogloss:1.69701
[467]	train-mlogloss:1.59542	validation-mlogloss:1.69696
[468]	train-mlogloss:1.59489	validation-mlogloss:1.69696
[469]	train-mlogloss:1.59443	validation-mlogloss:1.69676
[470]	train-mlogloss:1.59384	validation-mlogloss:1.69649
[471]	train-mlogloss:1.59333	validation-mlogloss:1.69614
[472]	train-mlogloss:1.59290	validation-mlogloss:1.69590
[473]	train-mlogloss:1.59240	validation-mlogloss:1.69565
[474]	train-mlogloss:1.59189	validation-mlogloss:1.69553
[475]	train-mlogloss:1.59133	validation-mlogloss:1.69543
[476]	train-mlogloss:1.59077	validation-mlogloss:1.69522
[477]	train-mlogloss:1.59019	validation-mlogloss:1.69512
[478]	train-mlogloss:1.58969	validation-mlogloss:1.69500
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[481]	train-mlogloss:1.58814	validation-mlogloss:1.69474
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[485]	train-mlogloss:1.58597	validation-mlogloss:1.69389
[486]	train-mlogloss:1.58534	validation-mlogloss:1.69354
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[489]	train-mlogloss:1.58371	validation-mlogloss:1.69291
[490]	train-mlogloss:1.58321	validation-mlogloss:1.69275
[491]	train-mlogloss:1.58263	validation-mlogloss:1.69245
[492]	train-mlogloss:1.58204	validation-mlogloss:1.69240
[493]	train-mlogloss:1.58164	validation-mlogloss:1.69223
[494]	train-mlogloss:1.58120	validation-mlogloss:1.69209
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[496]	train-mlogloss:1.58015	validation-mlogloss:1.69185
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[498]	train-mlogloss:1.57891	validation-mlogloss:1.69153
[499]	train-mlogloss:1.57838	validation-mlogloss:1.69130
[500]	train-mlogloss:1.57779	validation-mlogloss:1.69123
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[502]	train-mlogloss:1.57674	validation-mlogloss:1.69108
[503]	train-mlogloss:1.57625	validation-mlogloss:1.69074
[504]	train-mlogloss:1.57582	validation-mlogloss:1.69050
[505]	train-mlogloss:1.57539	validation-mlogloss:1.69047
[506]	train-mlogloss:1.57478	validation-mlogloss:1.69026
[507]	train-mlogloss:1.57429	validation-mlogloss:1.69030
[508]	train-mlogloss:1.57376	validation-mlogloss:1.69019
[509]	train-mlogloss:1.57323	validation-mlogloss:1.69002
[510]	train-mlogloss:1.57273	validation-mlogloss:1.68995
[511]	train-mlogloss:1.57226	validation-mlogloss:1.68971
[512]	train-mlogloss:1.57166	validation-mlogloss:1.68959
[513]	train-mlogloss:1.57111	validation-mlogloss:1.68918
[514]	train-mlogloss:1.57056	validation-mlogloss:1.68891
[515]	train-mlogloss:1.57013	validation-mlogloss:1.68877
[516]	train-mlogloss:1.56969	validation-mlogloss:1.68855
[517]	train-mlogloss:1.56923	validation-mlogloss:1.68843
[518]	train-mlogloss:1.56870	validation-mlogloss:1.68848
[519]	train-mlogloss:1.56813	validation-mlogloss:1.68829
[520]	train-mlogloss:1.56771	validation-mlogloss:1.68829
[521]	train-mlogloss:1.56726	validation-mlogloss:1.68820
[522]	train-mlogloss:1.56675	validation-mlogloss:1.68821
[523]	train-mlogloss:1.56630	validation-mlogloss:1.68799
[524]	train-mlogloss:1.56581	validation-mlogloss:1.68796
[525]	train-mlogloss:1.56537	validation-mlogloss:1.68781
[526]	train-mlogloss:1.56501	validation-mlogloss:1.68783
[527]	train-mlogloss:1.56453	validation-mlogloss:1.68775
[528]	train-mlogloss:1.56397	validation-mlogloss:1.68754
[529]	train-mlogloss:1.56354	validation-mlogloss:1.68742
[530]	train-mlogloss:1.56307	validation-mlogloss:1.68720
[531]	train-mlogloss:1.56260	validation-mlogloss:1.68704
[532]	train-mlogloss:1.56209	validation-mlogloss:1.68704
[533]	train-mlogloss:1.56164	validation-mlogloss:1.68702
[534]	train-mlogloss:1.56109	validation-mlogloss:1.68688
[535]	train-mlogloss:1.56071	validation-mlogloss:1.68674
[536]	train-mlogloss:1.56028	validation-mlogloss:1.68666
[537]	train-mlogloss:1.55988	validation-mlogloss:1.68651
[538]	train-mlogloss:1.55939	validation-mlogloss:1.68639
[539]	train-mlogloss:1.55895	validation-mlogloss:1.68650
Saved model to disk.
2025-10-27 09:47:01.926768: 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`.
2025-10-27 09:47:01.939324: 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 00:00:1761554821.952823  414924 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554821.958431  414924 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554821.969277  414924 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554821.969298  414924 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554821.969302  414924 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554821.969304  414924 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:47:01.972570: 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:2.67983	validation-mlogloss:2.67744
[2]	train-mlogloss:2.66553	validation-mlogloss:2.66127
[3]	train-mlogloss:2.65355	validation-mlogloss:2.64750
[4]	train-mlogloss:2.64098	validation-mlogloss:2.63358
[5]	train-mlogloss:2.62876	validation-mlogloss:2.61977
[6]	train-mlogloss:2.61659	validation-mlogloss:2.60610
[7]	train-mlogloss:2.60496	validation-mlogloss:2.59360
[8]	train-mlogloss:2.59367	validation-mlogloss:2.58203
[9]	train-mlogloss:2.58155	validation-mlogloss:2.56943
[10]	train-mlogloss:2.57063	validation-mlogloss:2.55719
[11]	train-mlogloss:2.55987	validation-mlogloss:2.54475
[12]	train-mlogloss:2.54900	validation-mlogloss:2.53294
[13]	train-mlogloss:2.53817	validation-mlogloss:2.52016
[14]	train-mlogloss:2.52775	validation-mlogloss:2.50837
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[16]	train-mlogloss:2.50677	validation-mlogloss:2.48533
[17]	train-mlogloss:2.49737	validation-mlogloss:2.47510
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[19]	train-mlogloss:2.47870	validation-mlogloss:2.45486
[20]	train-mlogloss:2.46905	validation-mlogloss:2.44478
[21]	train-mlogloss:2.46031	validation-mlogloss:2.43479
[22]	train-mlogloss:2.45199	validation-mlogloss:2.42487
[23]	train-mlogloss:2.44269	validation-mlogloss:2.41487
[24]	train-mlogloss:2.43442	validation-mlogloss:2.40563
[25]	train-mlogloss:2.42658	validation-mlogloss:2.39754
[26]	train-mlogloss:2.41832	validation-mlogloss:2.38826
[27]	train-mlogloss:2.41063	validation-mlogloss:2.37985
[28]	train-mlogloss:2.40254	validation-mlogloss:2.37096
[29]	train-mlogloss:2.39473	validation-mlogloss:2.36228
[30]	train-mlogloss:2.38679	validation-mlogloss:2.35361
[31]	train-mlogloss:2.37922	validation-mlogloss:2.34523
[32]	train-mlogloss:2.37201	validation-mlogloss:2.33766
[33]	train-mlogloss:2.36429	validation-mlogloss:2.32918
[34]	train-mlogloss:2.35697	validation-mlogloss:2.32158
[35]	train-mlogloss:2.35003	validation-mlogloss:2.31429
[36]	train-mlogloss:2.34308	validation-mlogloss:2.30652
[37]	train-mlogloss:2.33649	validation-mlogloss:2.29960
[38]	train-mlogloss:2.32989	validation-mlogloss:2.29233
[39]	train-mlogloss:2.32347	validation-mlogloss:2.28592
[40]	train-mlogloss:2.31693	validation-mlogloss:2.27897
[41]	train-mlogloss:2.31089	validation-mlogloss:2.27265
[42]	train-mlogloss:2.30467	validation-mlogloss:2.26596
[43]	train-mlogloss:2.29882	validation-mlogloss:2.26008
[44]	train-mlogloss:2.29230	validation-mlogloss:2.25351
[45]	train-mlogloss:2.28633	validation-mlogloss:2.24747
[46]	train-mlogloss:2.28058	validation-mlogloss:2.24192
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[48]	train-mlogloss:2.26916	validation-mlogloss:2.23062
[49]	train-mlogloss:2.26360	validation-mlogloss:2.22471
[50]	train-mlogloss:2.25833	validation-mlogloss:2.21925
[51]	train-mlogloss:2.25291	validation-mlogloss:2.21439
[52]	train-mlogloss:2.24738	validation-mlogloss:2.20871
[53]	train-mlogloss:2.24205	validation-mlogloss:2.20334
[54]	train-mlogloss:2.23699	validation-mlogloss:2.19831
[55]	train-mlogloss:2.23208	validation-mlogloss:2.19298
[56]	train-mlogloss:2.22690	validation-mlogloss:2.18762
[57]	train-mlogloss:2.22212	validation-mlogloss:2.18282
[58]	train-mlogloss:2.21717	validation-mlogloss:2.17763
[59]	train-mlogloss:2.21222	validation-mlogloss:2.17287
[60]	train-mlogloss:2.20714	validation-mlogloss:2.16758
[61]	train-mlogloss:2.20243	validation-mlogloss:2.16303
[62]	train-mlogloss:2.19781	validation-mlogloss:2.15863
[63]	train-mlogloss:2.19308	validation-mlogloss:2.15384
[64]	train-mlogloss:2.18851	validation-mlogloss:2.14907
[65]	train-mlogloss:2.18400	validation-mlogloss:2.14481
[66]	train-mlogloss:2.17950	validation-mlogloss:2.14033
[67]	train-mlogloss:2.17506	validation-mlogloss:2.13562
[68]	train-mlogloss:2.17060	validation-mlogloss:2.13111
[69]	train-mlogloss:2.16636	validation-mlogloss:2.12705
[70]	train-mlogloss:2.16197	validation-mlogloss:2.12276
[71]	train-mlogloss:2.15760	validation-mlogloss:2.11833
[72]	train-mlogloss:2.15313	validation-mlogloss:2.11418
[73]	train-mlogloss:2.14899	validation-mlogloss:2.11015
[74]	train-mlogloss:2.14469	validation-mlogloss:2.10586
[75]	train-mlogloss:2.14085	validation-mlogloss:2.10201
[76]	train-mlogloss:2.13693	validation-mlogloss:2.09795
[77]	train-mlogloss:2.13300	validation-mlogloss:2.09388
[78]	train-mlogloss:2.12916	validation-mlogloss:2.08962
[79]	train-mlogloss:2.12523	validation-mlogloss:2.08588
[80]	train-mlogloss:2.12156	validation-mlogloss:2.08196
[81]	train-mlogloss:2.11810	validation-mlogloss:2.07858
[82]	train-mlogloss:2.11431	validation-mlogloss:2.07468
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[84]	train-mlogloss:2.10662	validation-mlogloss:2.06753
[85]	train-mlogloss:2.10288	validation-mlogloss:2.06437
[86]	train-mlogloss:2.09938	validation-mlogloss:2.06081
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[89]	train-mlogloss:2.08884	validation-mlogloss:2.05043
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[91]	train-mlogloss:2.08192	validation-mlogloss:2.04302
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[94]	train-mlogloss:2.07138	validation-mlogloss:2.03257
[95]	train-mlogloss:2.06798	validation-mlogloss:2.02951
[96]	train-mlogloss:2.06453	validation-mlogloss:2.02628
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[99]	train-mlogloss:2.05492	validation-mlogloss:2.01733
[100]	train-mlogloss:2.05186	validation-mlogloss:2.01446
[101]	train-mlogloss:2.04872	validation-mlogloss:2.01105
[102]	train-mlogloss:2.04586	validation-mlogloss:2.00844
[103]	train-mlogloss:2.04298	validation-mlogloss:2.00584
[104]	train-mlogloss:2.03987	validation-mlogloss:2.00251
[105]	train-mlogloss:2.03687	validation-mlogloss:1.99995
[106]	train-mlogloss:2.03386	validation-mlogloss:1.99718
[107]	train-mlogloss:2.03112	validation-mlogloss:1.99461
[108]	train-mlogloss:2.02821	validation-mlogloss:1.99215
[109]	train-mlogloss:2.02517	validation-mlogloss:1.98904
[110]	train-mlogloss:2.02253	validation-mlogloss:1.98688
[111]	train-mlogloss:2.01987	validation-mlogloss:1.98443
[112]	train-mlogloss:2.01712	validation-mlogloss:1.98182
[113]	train-mlogloss:2.01439	validation-mlogloss:1.97948
[114]	train-mlogloss:2.01159	validation-mlogloss:1.97700
[115]	train-mlogloss:2.00870	validation-mlogloss:1.97376
[116]	train-mlogloss:2.00598	validation-mlogloss:1.97177
[117]	train-mlogloss:2.00332	validation-mlogloss:1.96957
[118]	train-mlogloss:2.00074	validation-mlogloss:1.96730
[119]	train-mlogloss:1.99806	validation-mlogloss:1.96489
[120]	train-mlogloss:1.99538	validation-mlogloss:1.96262
[121]	train-mlogloss:1.99281	validation-mlogloss:1.96013
[122]	train-mlogloss:1.99024	validation-mlogloss:1.95800
[123]	train-mlogloss:1.98770	validation-mlogloss:1.95539
[124]	train-mlogloss:1.98524	validation-mlogloss:1.95280
[125]	train-mlogloss:1.98272	validation-mlogloss:1.95050
[126]	train-mlogloss:1.98018	validation-mlogloss:1.94814
[127]	train-mlogloss:1.97761	validation-mlogloss:1.94569
[128]	train-mlogloss:1.97506	validation-mlogloss:1.94333
[129]	train-mlogloss:1.97263	validation-mlogloss:1.94125
[130]	train-mlogloss:1.97032	validation-mlogloss:1.93915
[131]	train-mlogloss:1.96792	validation-mlogloss:1.93717
[132]	train-mlogloss:1.96556	validation-mlogloss:1.93515
[133]	train-mlogloss:1.96318	validation-mlogloss:1.93296
[134]	train-mlogloss:1.96085	validation-mlogloss:1.93129
[135]	train-mlogloss:1.95860	validation-mlogloss:1.92950
[136]	train-mlogloss:1.95631	validation-mlogloss:1.92746
[137]	train-mlogloss:1.95389	validation-mlogloss:1.92536
[138]	train-mlogloss:1.95153	validation-mlogloss:1.92339
[139]	train-mlogloss:1.94937	validation-mlogloss:1.92128
[140]	train-mlogloss:1.94720	validation-mlogloss:1.91966
[141]	train-mlogloss:1.94501	validation-mlogloss:1.91793
[142]	train-mlogloss:1.94296	validation-mlogloss:1.91605
[143]	train-mlogloss:1.94067	validation-mlogloss:1.91424
[144]	train-mlogloss:1.93847	validation-mlogloss:1.91241
[145]	train-mlogloss:1.93636	validation-mlogloss:1.91090
[146]	train-mlogloss:1.93408	validation-mlogloss:1.90903
[147]	train-mlogloss:1.93178	validation-mlogloss:1.90683
[148]	train-mlogloss:1.92969	validation-mlogloss:1.90499
[149]	train-mlogloss:1.92760	validation-mlogloss:1.90324
[150]	train-mlogloss:1.92555	validation-mlogloss:1.90159
[151]	train-mlogloss:1.92353	validation-mlogloss:1.90023
[152]	train-mlogloss:1.92149	validation-mlogloss:1.89823
[153]	train-mlogloss:1.91942	validation-mlogloss:1.89594
[154]	train-mlogloss:1.91750	validation-mlogloss:1.89438
[155]	train-mlogloss:1.91549	validation-mlogloss:1.89241
[156]	train-mlogloss:1.91338	validation-mlogloss:1.89086
[157]	train-mlogloss:1.91133	validation-mlogloss:1.88894
[158]	train-mlogloss:1.90943	validation-mlogloss:1.88727
[159]	train-mlogloss:1.90738	validation-mlogloss:1.88585
[160]	train-mlogloss:1.90537	validation-mlogloss:1.88411
[161]	train-mlogloss:1.90341	validation-mlogloss:1.88257
[162]	train-mlogloss:1.90141	validation-mlogloss:1.88063
[163]	train-mlogloss:1.89947	validation-mlogloss:1.87886
[164]	train-mlogloss:1.89767	validation-mlogloss:1.87697
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[170]	train-mlogloss:1.88678	validation-mlogloss:1.86757
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[172]	train-mlogloss:1.88319	validation-mlogloss:1.86458
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[189]	train-mlogloss:1.85467	validation-mlogloss:1.84221
[190]	train-mlogloss:1.85299	validation-mlogloss:1.84093
[191]	train-mlogloss:1.85141	validation-mlogloss:1.83965
[192]	train-mlogloss:1.84981	validation-mlogloss:1.83870
[193]	train-mlogloss:1.84823	validation-mlogloss:1.83777
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[195]	train-mlogloss:1.84511	validation-mlogloss:1.83498
[196]	train-mlogloss:1.84352	validation-mlogloss:1.83369
[197]	train-mlogloss:1.84203	validation-mlogloss:1.83268
[198]	train-mlogloss:1.84049	validation-mlogloss:1.83144
[199]	train-mlogloss:1.83900	validation-mlogloss:1.83032
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[500]	train-mlogloss:1.57868	validation-mlogloss:1.69075
[501]	train-mlogloss:1.57816	validation-mlogloss:1.69042
[502]	train-mlogloss:1.57766	validation-mlogloss:1.69031
[503]	train-mlogloss:1.57724	validation-mlogloss:1.69026
[504]	train-mlogloss:1.57677	validation-mlogloss:1.69013
[505]	train-mlogloss:1.57626	validation-mlogloss:1.68996
[506]	train-mlogloss:1.57578	validation-mlogloss:1.68956
[507]	train-mlogloss:1.57522	validation-mlogloss:1.68926
[508]	train-mlogloss:1.57466	validation-mlogloss:1.68896
[509]	train-mlogloss:1.57423	validation-mlogloss:1.68878
[510]	train-mlogloss:1.57370	validation-mlogloss:1.68862
[511]	train-mlogloss:1.57330	validation-mlogloss:1.68843
[512]	train-mlogloss:1.57274	validation-mlogloss:1.68822
[513]	train-mlogloss:1.57229	validation-mlogloss:1.68811
[514]	train-mlogloss:1.57179	validation-mlogloss:1.68784
[515]	train-mlogloss:1.57136	validation-mlogloss:1.68766
[516]	train-mlogloss:1.57085	validation-mlogloss:1.68754
[517]	train-mlogloss:1.57036	validation-mlogloss:1.68728
[518]	train-mlogloss:1.56996	validation-mlogloss:1.68701
[519]	train-mlogloss:1.56956	validation-mlogloss:1.68677
[520]	train-mlogloss:1.56908	validation-mlogloss:1.68663
[521]	train-mlogloss:1.56861	validation-mlogloss:1.68649
[522]	train-mlogloss:1.56812	validation-mlogloss:1.68640
[523]	train-mlogloss:1.56766	validation-mlogloss:1.68617
[524]	train-mlogloss:1.56714	validation-mlogloss:1.68595
[525]	train-mlogloss:1.56660	validation-mlogloss:1.68578
[526]	train-mlogloss:1.56610	validation-mlogloss:1.68568
[527]	train-mlogloss:1.56559	validation-mlogloss:1.68569
[528]	train-mlogloss:1.56509	validation-mlogloss:1.68555
[529]	train-mlogloss:1.56462	validation-mlogloss:1.68520
[530]	train-mlogloss:1.56423	validation-mlogloss:1.68511
[531]	train-mlogloss:1.56376	validation-mlogloss:1.68506
[532]	train-mlogloss:1.56321	validation-mlogloss:1.68481
[533]	train-mlogloss:1.56278	validation-mlogloss:1.68472
[534]	train-mlogloss:1.56230	validation-mlogloss:1.68465
[535]	train-mlogloss:1.56184	validation-mlogloss:1.68468
[536]	train-mlogloss:1.56134	validation-mlogloss:1.68441
[537]	train-mlogloss:1.56086	validation-mlogloss:1.68434
[538]	train-mlogloss:1.56044	validation-mlogloss:1.68427
[539]	train-mlogloss:1.56000	validation-mlogloss:1.68395
Saved model to disk.
2025-10-27 09:47:47.559609: 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`.
2025-10-27 09:47:47.579269: 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 00:00:1761554867.592877  415831 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554867.597031  415831 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554867.608193  415831 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554867.608215  415831 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554867.608219  415831 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554867.608221  415831 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:47:47.611456: 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:2.69434	validation-mlogloss:2.69246
[1]	train-mlogloss:2.68012	validation-mlogloss:2.67729
[2]	train-mlogloss:2.66589	validation-mlogloss:2.66140
[3]	train-mlogloss:2.65266	validation-mlogloss:2.64613
[4]	train-mlogloss:2.64137	validation-mlogloss:2.63239
[5]	train-mlogloss:2.62837	validation-mlogloss:2.61774
[6]	train-mlogloss:2.61592	validation-mlogloss:2.60389
[7]	train-mlogloss:2.60407	validation-mlogloss:2.59111
[8]	train-mlogloss:2.59219	validation-mlogloss:2.57863
[9]	train-mlogloss:2.58170	validation-mlogloss:2.56676
[10]	train-mlogloss:2.56972	validation-mlogloss:2.55343
[11]	train-mlogloss:2.55865	validation-mlogloss:2.54148
[12]	train-mlogloss:2.54790	validation-mlogloss:2.52959
[13]	train-mlogloss:2.53733	validation-mlogloss:2.51846
[14]	train-mlogloss:2.52721	validation-mlogloss:2.50750
[15]	train-mlogloss:2.51659	validation-mlogloss:2.49503
[16]	train-mlogloss:2.50672	validation-mlogloss:2.48400
[17]	train-mlogloss:2.49682	validation-mlogloss:2.47303
[18]	train-mlogloss:2.48735	validation-mlogloss:2.46265
[19]	train-mlogloss:2.47789	validation-mlogloss:2.45209
[20]	train-mlogloss:2.46921	validation-mlogloss:2.44169
[21]	train-mlogloss:2.45994	validation-mlogloss:2.43090
[22]	train-mlogloss:2.45088	validation-mlogloss:2.42095
[23]	train-mlogloss:2.44221	validation-mlogloss:2.41162
[24]	train-mlogloss:2.43376	validation-mlogloss:2.40260
[25]	train-mlogloss:2.42477	validation-mlogloss:2.39286
[26]	train-mlogloss:2.41643	validation-mlogloss:2.38386
[27]	train-mlogloss:2.40838	validation-mlogloss:2.37490
[28]	train-mlogloss:2.40045	validation-mlogloss:2.36663
[29]	train-mlogloss:2.39267	validation-mlogloss:2.35778
[30]	train-mlogloss:2.38483	validation-mlogloss:2.34886
[31]	train-mlogloss:2.37736	validation-mlogloss:2.34107
[32]	train-mlogloss:2.37059	validation-mlogloss:2.33438
[33]	train-mlogloss:2.36352	validation-mlogloss:2.32696
[34]	train-mlogloss:2.35658	validation-mlogloss:2.31944
[35]	train-mlogloss:2.34978	validation-mlogloss:2.31212
[36]	train-mlogloss:2.34293	validation-mlogloss:2.30530
[37]	train-mlogloss:2.33632	validation-mlogloss:2.29807
[38]	train-mlogloss:2.32989	validation-mlogloss:2.29106
[39]	train-mlogloss:2.32341	validation-mlogloss:2.28446
[40]	train-mlogloss:2.31738	validation-mlogloss:2.27848
[41]	train-mlogloss:2.31136	validation-mlogloss:2.27176
[42]	train-mlogloss:2.30528	validation-mlogloss:2.26556
[43]	train-mlogloss:2.29902	validation-mlogloss:2.25859
[44]	train-mlogloss:2.29273	validation-mlogloss:2.25140
[45]	train-mlogloss:2.28650	validation-mlogloss:2.24536
[46]	train-mlogloss:2.28084	validation-mlogloss:2.23942
[47]	train-mlogloss:2.27510	validation-mlogloss:2.23343
[48]	train-mlogloss:2.26968	validation-mlogloss:2.22789
[49]	train-mlogloss:2.26404	validation-mlogloss:2.22205
[50]	train-mlogloss:2.25831	validation-mlogloss:2.21595
[51]	train-mlogloss:2.25311	validation-mlogloss:2.21085
[52]	train-mlogloss:2.24792	validation-mlogloss:2.20548
[53]	train-mlogloss:2.24258	validation-mlogloss:2.20048
[54]	train-mlogloss:2.23736	validation-mlogloss:2.19519
[55]	train-mlogloss:2.23244	validation-mlogloss:2.18977
[56]	train-mlogloss:2.22747	validation-mlogloss:2.18480
[57]	train-mlogloss:2.22237	validation-mlogloss:2.18006
[58]	train-mlogloss:2.21734	validation-mlogloss:2.17506
[59]	train-mlogloss:2.21272	validation-mlogloss:2.17014
[60]	train-mlogloss:2.20792	validation-mlogloss:2.16510
[61]	train-mlogloss:2.20332	validation-mlogloss:2.16104
[62]	train-mlogloss:2.19852	validation-mlogloss:2.15642
[63]	train-mlogloss:2.19375	validation-mlogloss:2.15136
[64]	train-mlogloss:2.18925	validation-mlogloss:2.14659
[65]	train-mlogloss:2.18472	validation-mlogloss:2.14201
[66]	train-mlogloss:2.18010	validation-mlogloss:2.13746
[67]	train-mlogloss:2.17598	validation-mlogloss:2.13321
[68]	train-mlogloss:2.17155	validation-mlogloss:2.12898
[69]	train-mlogloss:2.16727	validation-mlogloss:2.12480
[70]	train-mlogloss:2.16308	validation-mlogloss:2.12104
[71]	train-mlogloss:2.15886	validation-mlogloss:2.11699
[72]	train-mlogloss:2.15450	validation-mlogloss:2.11276
[73]	train-mlogloss:2.15053	validation-mlogloss:2.10851
[74]	train-mlogloss:2.14652	validation-mlogloss:2.10439
[75]	train-mlogloss:2.14223	validation-mlogloss:2.10021
[76]	train-mlogloss:2.13826	validation-mlogloss:2.09652
[77]	train-mlogloss:2.13446	validation-mlogloss:2.09294
[78]	train-mlogloss:2.13064	validation-mlogloss:2.08936
[79]	train-mlogloss:2.12678	validation-mlogloss:2.08601
[80]	train-mlogloss:2.12281	validation-mlogloss:2.08208
[81]	train-mlogloss:2.11902	validation-mlogloss:2.07842
[82]	train-mlogloss:2.11525	validation-mlogloss:2.07483
[83]	train-mlogloss:2.11153	validation-mlogloss:2.07121
[84]	train-mlogloss:2.10787	validation-mlogloss:2.06772
[85]	train-mlogloss:2.10430	validation-mlogloss:2.06445
[86]	train-mlogloss:2.10057	validation-mlogloss:2.06111
[87]	train-mlogloss:2.09691	validation-mlogloss:2.05744
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[89]	train-mlogloss:2.08989	validation-mlogloss:2.05050
[90]	train-mlogloss:2.08650	validation-mlogloss:2.04749
[91]	train-mlogloss:2.08306	validation-mlogloss:2.04383
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[93]	train-mlogloss:2.07628	validation-mlogloss:2.03746
[94]	train-mlogloss:2.07307	validation-mlogloss:2.03483
[95]	train-mlogloss:2.06970	validation-mlogloss:2.03147
[96]	train-mlogloss:2.06612	validation-mlogloss:2.02788
[97]	train-mlogloss:2.06277	validation-mlogloss:2.02463
[98]	train-mlogloss:2.05963	validation-mlogloss:2.02133
[99]	train-mlogloss:2.05657	validation-mlogloss:2.01854
[100]	train-mlogloss:2.05354	validation-mlogloss:2.01593
[101]	train-mlogloss:2.05039	validation-mlogloss:2.01280
[102]	train-mlogloss:2.04727	validation-mlogloss:2.00978
[103]	train-mlogloss:2.04421	validation-mlogloss:2.00701
[104]	train-mlogloss:2.04118	validation-mlogloss:2.00399
[105]	train-mlogloss:2.03819	validation-mlogloss:2.00116
[106]	train-mlogloss:2.03523	validation-mlogloss:1.99815
[107]	train-mlogloss:2.03237	validation-mlogloss:1.99544
[108]	train-mlogloss:2.02953	validation-mlogloss:1.99271
[109]	train-mlogloss:2.02667	validation-mlogloss:1.99028
[110]	train-mlogloss:2.02367	validation-mlogloss:1.98764
[111]	train-mlogloss:2.02080	validation-mlogloss:1.98497
[112]	train-mlogloss:2.01803	validation-mlogloss:1.98230
[113]	train-mlogloss:2.01525	validation-mlogloss:1.97985
[114]	train-mlogloss:2.01230	validation-mlogloss:1.97708
[115]	train-mlogloss:2.00955	validation-mlogloss:1.97447
[116]	train-mlogloss:2.00685	validation-mlogloss:1.97194
[117]	train-mlogloss:2.00429	validation-mlogloss:1.96973
[118]	train-mlogloss:2.00157	validation-mlogloss:1.96734
[119]	train-mlogloss:1.99898	validation-mlogloss:1.96495
[120]	train-mlogloss:1.99634	validation-mlogloss:1.96291
[121]	train-mlogloss:1.99371	validation-mlogloss:1.96060
[122]	train-mlogloss:1.99124	validation-mlogloss:1.95821
[123]	train-mlogloss:1.98873	validation-mlogloss:1.95614
[124]	train-mlogloss:1.98629	validation-mlogloss:1.95411
[125]	train-mlogloss:1.98354	validation-mlogloss:1.95147
[126]	train-mlogloss:1.98106	validation-mlogloss:1.94899
[127]	train-mlogloss:1.97855	validation-mlogloss:1.94688
[128]	train-mlogloss:1.97600	validation-mlogloss:1.94413
[129]	train-mlogloss:1.97352	validation-mlogloss:1.94210
[130]	train-mlogloss:1.97111	validation-mlogloss:1.94025
[131]	train-mlogloss:1.96882	validation-mlogloss:1.93834
[132]	train-mlogloss:1.96625	validation-mlogloss:1.93581
[133]	train-mlogloss:1.96400	validation-mlogloss:1.93338
[134]	train-mlogloss:1.96170	validation-mlogloss:1.93155
[135]	train-mlogloss:1.95940	validation-mlogloss:1.92970
[136]	train-mlogloss:1.95711	validation-mlogloss:1.92760
[137]	train-mlogloss:1.95482	validation-mlogloss:1.92584
[138]	train-mlogloss:1.95258	validation-mlogloss:1.92406
[139]	train-mlogloss:1.95034	validation-mlogloss:1.92205
[140]	train-mlogloss:1.94816	validation-mlogloss:1.92025
[141]	train-mlogloss:1.94591	validation-mlogloss:1.91816
[142]	train-mlogloss:1.94380	validation-mlogloss:1.91613
[143]	train-mlogloss:1.94149	validation-mlogloss:1.91404
[144]	train-mlogloss:1.93942	validation-mlogloss:1.91234
[145]	train-mlogloss:1.93728	validation-mlogloss:1.91080
[146]	train-mlogloss:1.93526	validation-mlogloss:1.90925
[147]	train-mlogloss:1.93326	validation-mlogloss:1.90727
[148]	train-mlogloss:1.93101	validation-mlogloss:1.90541
[149]	train-mlogloss:1.92900	validation-mlogloss:1.90397
[150]	train-mlogloss:1.92685	validation-mlogloss:1.90211
[151]	train-mlogloss:1.92495	validation-mlogloss:1.90052
[152]	train-mlogloss:1.92292	validation-mlogloss:1.89926
[153]	train-mlogloss:1.92075	validation-mlogloss:1.89752
[154]	train-mlogloss:1.91880	validation-mlogloss:1.89581
[155]	train-mlogloss:1.91673	validation-mlogloss:1.89368
[156]	train-mlogloss:1.91474	validation-mlogloss:1.89195
[157]	train-mlogloss:1.91262	validation-mlogloss:1.89004
[158]	train-mlogloss:1.91053	validation-mlogloss:1.88803
[159]	train-mlogloss:1.90872	validation-mlogloss:1.88631
[160]	train-mlogloss:1.90658	validation-mlogloss:1.88467
[161]	train-mlogloss:1.90465	validation-mlogloss:1.88288
[162]	train-mlogloss:1.90280	validation-mlogloss:1.88136
[163]	train-mlogloss:1.90092	validation-mlogloss:1.87967
[164]	train-mlogloss:1.89886	validation-mlogloss:1.87774
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[195]	train-mlogloss:1.84534	validation-mlogloss:1.83359
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[200]	train-mlogloss:1.83776	validation-mlogloss:1.82755
[201]	train-mlogloss:1.83628	validation-mlogloss:1.82651
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[535]	train-mlogloss:1.56032	validation-mlogloss:1.68463
[536]	train-mlogloss:1.55981	validation-mlogloss:1.68453
[537]	train-mlogloss:1.55940	validation-mlogloss:1.68444
[538]	train-mlogloss:1.55902	validation-mlogloss:1.68443
[539]	train-mlogloss:1.55851	validation-mlogloss:1.68437
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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.28 [%]
Global accuracy score (test) = 45.74 [%]
Global F1 score (train) = 51.44 [%]
Global F1 score (test) = 45.15 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.45      0.74      0.56       184
 CAMINAR CON MÓVIL O LIBRO       0.38      0.48      0.43       184
       CAMINAR USUAL SPEED       0.37      0.29      0.33       184
            CAMINAR ZIGZAG       0.40      0.54      0.46       184
          DE PIE BARRIENDO       0.75      0.29      0.42       184
   DE PIE DOBLANDO TOALLAS       0.48      0.43      0.46       184
    DE PIE MOVIENDO LIBROS       0.39      0.35      0.37       184
          DE PIE USANDO PC       0.22      0.33      0.26       184
        FASE REPOSO CON K5       0.58      0.86      0.69       184
INCREMENTAL CICLOERGOMETRO       0.75      0.68      0.71       184
           SENTADO LEYENDO       0.53      0.38      0.44       184
         SENTADO USANDO PC       0.22      0.12      0.16       184
      SENTADO VIENDO LA TV       0.32      0.28      0.30       184
   SUBIR Y BAJAR ESCALERAS       0.65      0.51      0.57       184
                    TROTAR       0.65      0.57      0.61       161

                  accuracy                           0.46      2737
                 macro avg       0.48      0.46      0.45      2737
              weighted avg       0.47      0.46      0.45      2737


Accuracy capturado en la ejecución 13: 45.74 [%]
F1-score capturado en la ejecución 13: 45.15 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.34 [%]
Global accuracy score (test) = 44.9 [%]
Global F1 score (train) = 51.5 [%]
Global F1 score (test) = 44.21 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.77      0.59       184
 CAMINAR CON MÓVIL O LIBRO       0.38      0.51      0.44       184
       CAMINAR USUAL SPEED       0.36      0.30      0.33       184
            CAMINAR ZIGZAG       0.40      0.52      0.45       184
          DE PIE BARRIENDO       0.80      0.30      0.43       184
   DE PIE DOBLANDO TOALLAS       0.52      0.42      0.47       184
    DE PIE MOVIENDO LIBROS       0.34      0.32      0.33       184
          DE PIE USANDO PC       0.22      0.33      0.26       184
        FASE REPOSO CON K5       0.57      0.85      0.68       184
INCREMENTAL CICLOERGOMETRO       0.75      0.68      0.72       184
           SENTADO LEYENDO       0.44      0.35      0.39       184
         SENTADO USANDO PC       0.26      0.16      0.20       184
      SENTADO VIENDO LA TV       0.27      0.22      0.24       184
   SUBIR Y BAJAR ESCALERAS       0.60      0.45      0.52       184
                    TROTAR       0.63      0.57      0.60       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.45      0.44      2737
              weighted avg       0.47      0.45      0.44      2737


Accuracy capturado en la ejecución 14: 44.9 [%]
F1-score capturado en la ejecución 14: 44.21 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.37 [%]
Global accuracy score (test) = 45.41 [%]
Global F1 score (train) = 51.5 [%]
Global F1 score (test) = 44.78 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.77      0.59       184
 CAMINAR CON MÓVIL O LIBRO       0.35      0.45      0.39       184
       CAMINAR USUAL SPEED       0.34      0.28      0.31       184
            CAMINAR ZIGZAG       0.38      0.52      0.44       184
          DE PIE BARRIENDO       0.77      0.30      0.44       184
   DE PIE DOBLANDO TOALLAS       0.52      0.42      0.46       184
    DE PIE MOVIENDO LIBROS       0.41      0.35      0.38       184
          DE PIE USANDO PC       0.22      0.34      0.27       184
        FASE REPOSO CON K5       0.57      0.85      0.69       184
INCREMENTAL CICLOERGOMETRO       0.74      0.70      0.72       184
           SENTADO LEYENDO       0.48      0.38      0.42       184
         SENTADO USANDO PC       0.19      0.10      0.13       184
      SENTADO VIENDO LA TV       0.32      0.28      0.30       184
   SUBIR Y BAJAR ESCALERAS       0.64      0.52      0.57       184
                    TROTAR       0.68      0.57      0.62       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.46      0.45      2737
              weighted avg       0.47      0.45      0.45      2737


Accuracy capturado en la ejecución 15: 45.41 [%]
F1-score capturado en la ejecución 15: 44.78 [%]

=== EJECUCIÓN 16 ===

--- TRAIN (ejecución 16) ---

--- TEST (ejecución 16) ---
2025-10-27 09:48:33.324293: 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`.
2025-10-27 09:48:33.337773: 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 00:00:1761554913.352615  416713 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554913.357038  416713 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554913.368836  416713 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554913.368865  416713 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554913.368869  416713 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554913.368872  416713 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:48:33.372351: 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:2.69439	validation-mlogloss:2.69346
[1]	train-mlogloss:2.68088	validation-mlogloss:2.67743
[2]	train-mlogloss:2.66641	validation-mlogloss:2.66191
[3]	train-mlogloss:2.65317	validation-mlogloss:2.64682
[4]	train-mlogloss:2.64059	validation-mlogloss:2.63240
[5]	train-mlogloss:2.62811	validation-mlogloss:2.61858
[6]	train-mlogloss:2.61606	validation-mlogloss:2.60573
[7]	train-mlogloss:2.60365	validation-mlogloss:2.59145
[8]	train-mlogloss:2.59170	validation-mlogloss:2.57797
[9]	train-mlogloss:2.58085	validation-mlogloss:2.56552
[10]	train-mlogloss:2.56959	validation-mlogloss:2.55337
[11]	train-mlogloss:2.55833	validation-mlogloss:2.54031
[12]	train-mlogloss:2.54707	validation-mlogloss:2.52801
[13]	train-mlogloss:2.53646	validation-mlogloss:2.51623
[14]	train-mlogloss:2.52599	validation-mlogloss:2.50542
[15]	train-mlogloss:2.51674	validation-mlogloss:2.49473
[16]	train-mlogloss:2.50728	validation-mlogloss:2.48454
[17]	train-mlogloss:2.49748	validation-mlogloss:2.47374
[18]	train-mlogloss:2.48747	validation-mlogloss:2.46253
[19]	train-mlogloss:2.47812	validation-mlogloss:2.45227
[20]	train-mlogloss:2.46956	validation-mlogloss:2.44239
[21]	train-mlogloss:2.46051	validation-mlogloss:2.43226
[22]	train-mlogloss:2.45174	validation-mlogloss:2.42213
[23]	train-mlogloss:2.44261	validation-mlogloss:2.41158
[24]	train-mlogloss:2.43396	validation-mlogloss:2.40218
[25]	train-mlogloss:2.42674	validation-mlogloss:2.39374
[26]	train-mlogloss:2.41884	validation-mlogloss:2.38449
[27]	train-mlogloss:2.41080	validation-mlogloss:2.37529
[28]	train-mlogloss:2.40284	validation-mlogloss:2.36646
[29]	train-mlogloss:2.39566	validation-mlogloss:2.35874
[30]	train-mlogloss:2.38795	validation-mlogloss:2.35069
[31]	train-mlogloss:2.38039	validation-mlogloss:2.34332
[32]	train-mlogloss:2.37313	validation-mlogloss:2.33506
[33]	train-mlogloss:2.36613	validation-mlogloss:2.32755
[34]	train-mlogloss:2.35875	validation-mlogloss:2.31955
[35]	train-mlogloss:2.35208	validation-mlogloss:2.31271
[36]	train-mlogloss:2.34536	validation-mlogloss:2.30535
[37]	train-mlogloss:2.33895	validation-mlogloss:2.29897
[38]	train-mlogloss:2.33222	validation-mlogloss:2.29196
[39]	train-mlogloss:2.32579	validation-mlogloss:2.28516
[40]	train-mlogloss:2.31957	validation-mlogloss:2.27900
[41]	train-mlogloss:2.31300	validation-mlogloss:2.27190
[42]	train-mlogloss:2.30695	validation-mlogloss:2.26540
[43]	train-mlogloss:2.30107	validation-mlogloss:2.25886
[44]	train-mlogloss:2.29497	validation-mlogloss:2.25204
[45]	train-mlogloss:2.28894	validation-mlogloss:2.24597
[46]	train-mlogloss:2.28331	validation-mlogloss:2.23953
[47]	train-mlogloss:2.27756	validation-mlogloss:2.23373
[48]	train-mlogloss:2.27203	validation-mlogloss:2.22771
[49]	train-mlogloss:2.26630	validation-mlogloss:2.22195
[50]	train-mlogloss:2.26096	validation-mlogloss:2.21661
[51]	train-mlogloss:2.25533	validation-mlogloss:2.21053
[52]	train-mlogloss:2.24977	validation-mlogloss:2.20500
[53]	train-mlogloss:2.24427	validation-mlogloss:2.19986
[54]	train-mlogloss:2.23906	validation-mlogloss:2.19449
[55]	train-mlogloss:2.23347	validation-mlogloss:2.18905
[56]	train-mlogloss:2.22835	validation-mlogloss:2.18368
[57]	train-mlogloss:2.22324	validation-mlogloss:2.17868
[58]	train-mlogloss:2.21815	validation-mlogloss:2.17334
[59]	train-mlogloss:2.21303	validation-mlogloss:2.16844
[60]	train-mlogloss:2.20818	validation-mlogloss:2.16397
[61]	train-mlogloss:2.20340	validation-mlogloss:2.15838
[62]	train-mlogloss:2.19870	validation-mlogloss:2.15411
[63]	train-mlogloss:2.19411	validation-mlogloss:2.14956
[64]	train-mlogloss:2.18941	validation-mlogloss:2.14471
[65]	train-mlogloss:2.18458	validation-mlogloss:2.13991
[66]	train-mlogloss:2.18013	validation-mlogloss:2.13551
[67]	train-mlogloss:2.17578	validation-mlogloss:2.13126
[68]	train-mlogloss:2.17167	validation-mlogloss:2.12736
[69]	train-mlogloss:2.16736	validation-mlogloss:2.12321
[70]	train-mlogloss:2.16307	validation-mlogloss:2.11898
[71]	train-mlogloss:2.15900	validation-mlogloss:2.11483
[72]	train-mlogloss:2.15466	validation-mlogloss:2.11056
[73]	train-mlogloss:2.15009	validation-mlogloss:2.10625
[74]	train-mlogloss:2.14584	validation-mlogloss:2.10202
[75]	train-mlogloss:2.14161	validation-mlogloss:2.09776
[76]	train-mlogloss:2.13779	validation-mlogloss:2.09374
[77]	train-mlogloss:2.13347	validation-mlogloss:2.08949
[78]	train-mlogloss:2.12953	validation-mlogloss:2.08572
[79]	train-mlogloss:2.12563	validation-mlogloss:2.08178
[80]	train-mlogloss:2.12175	validation-mlogloss:2.07805
[81]	train-mlogloss:2.11802	validation-mlogloss:2.07430
[82]	train-mlogloss:2.11423	validation-mlogloss:2.07043
[83]	train-mlogloss:2.11065	validation-mlogloss:2.06736
[84]	train-mlogloss:2.10701	validation-mlogloss:2.06347
[85]	train-mlogloss:2.10312	validation-mlogloss:2.05946
[86]	train-mlogloss:2.09976	validation-mlogloss:2.05644
[87]	train-mlogloss:2.09623	validation-mlogloss:2.05329
[88]	train-mlogloss:2.09286	validation-mlogloss:2.04973
[89]	train-mlogloss:2.08927	validation-mlogloss:2.04647
[90]	train-mlogloss:2.08583	validation-mlogloss:2.04343
[91]	train-mlogloss:2.08237	validation-mlogloss:2.03992
[92]	train-mlogloss:2.07889	validation-mlogloss:2.03628
[93]	train-mlogloss:2.07536	validation-mlogloss:2.03269
[94]	train-mlogloss:2.07193	validation-mlogloss:2.02981
[95]	train-mlogloss:2.06869	validation-mlogloss:2.02682
[96]	train-mlogloss:2.06573	validation-mlogloss:2.02413
[97]	train-mlogloss:2.06256	validation-mlogloss:2.02087
[98]	train-mlogloss:2.05929	validation-mlogloss:2.01787
[99]	train-mlogloss:2.05630	validation-mlogloss:2.01474
[100]	train-mlogloss:2.05317	validation-mlogloss:2.01172
[101]	train-mlogloss:2.05010	validation-mlogloss:2.00880
[102]	train-mlogloss:2.04713	validation-mlogloss:2.00614
[103]	train-mlogloss:2.04422	validation-mlogloss:2.00353
[104]	train-mlogloss:2.04120	validation-mlogloss:2.00062
[105]	train-mlogloss:2.03816	validation-mlogloss:1.99780
[106]	train-mlogloss:2.03514	validation-mlogloss:1.99543
[107]	train-mlogloss:2.03227	validation-mlogloss:1.99268
[108]	train-mlogloss:2.02923	validation-mlogloss:1.99025
[109]	train-mlogloss:2.02639	validation-mlogloss:1.98757
[110]	train-mlogloss:2.02354	validation-mlogloss:1.98521
[111]	train-mlogloss:2.02061	validation-mlogloss:1.98255
[112]	train-mlogloss:2.01773	validation-mlogloss:1.98005
[113]	train-mlogloss:2.01494	validation-mlogloss:1.97727
[114]	train-mlogloss:2.01210	validation-mlogloss:1.97479
[115]	train-mlogloss:2.00950	validation-mlogloss:1.97257
[116]	train-mlogloss:2.00689	validation-mlogloss:1.97015
[117]	train-mlogloss:2.00422	validation-mlogloss:1.96820
[118]	train-mlogloss:2.00166	validation-mlogloss:1.96567
[119]	train-mlogloss:1.99906	validation-mlogloss:1.96312
[120]	train-mlogloss:1.99652	validation-mlogloss:1.96079
[121]	train-mlogloss:1.99389	validation-mlogloss:1.95850
[122]	train-mlogloss:1.99131	validation-mlogloss:1.95638
[123]	train-mlogloss:1.98878	validation-mlogloss:1.95422
[124]	train-mlogloss:1.98627	validation-mlogloss:1.95191
[125]	train-mlogloss:1.98382	validation-mlogloss:1.94974
[126]	train-mlogloss:1.98140	validation-mlogloss:1.94746
[127]	train-mlogloss:1.97895	validation-mlogloss:1.94505
[128]	train-mlogloss:1.97620	validation-mlogloss:1.94252
[129]	train-mlogloss:1.97373	validation-mlogloss:1.94030
[130]	train-mlogloss:1.97128	validation-mlogloss:1.93795
[131]	train-mlogloss:1.96875	validation-mlogloss:1.93572
[132]	train-mlogloss:1.96639	validation-mlogloss:1.93365
[133]	train-mlogloss:1.96385	validation-mlogloss:1.93129
[134]	train-mlogloss:1.96152	validation-mlogloss:1.92938
[135]	train-mlogloss:1.95926	validation-mlogloss:1.92742
[136]	train-mlogloss:1.95699	validation-mlogloss:1.92535
[137]	train-mlogloss:1.95464	validation-mlogloss:1.92321
[138]	train-mlogloss:1.95235	validation-mlogloss:1.92131
[139]	train-mlogloss:1.95006	validation-mlogloss:1.91928
[140]	train-mlogloss:1.94794	validation-mlogloss:1.91754
[141]	train-mlogloss:1.94569	validation-mlogloss:1.91590
[142]	train-mlogloss:1.94350	validation-mlogloss:1.91397
[143]	train-mlogloss:1.94130	validation-mlogloss:1.91184
[144]	train-mlogloss:1.93920	validation-mlogloss:1.90958
[145]	train-mlogloss:1.93713	validation-mlogloss:1.90790
[146]	train-mlogloss:1.93506	validation-mlogloss:1.90623
[147]	train-mlogloss:1.93274	validation-mlogloss:1.90412
[148]	train-mlogloss:1.93061	validation-mlogloss:1.90241
[149]	train-mlogloss:1.92863	validation-mlogloss:1.90099
[150]	train-mlogloss:1.92654	validation-mlogloss:1.89959
[151]	train-mlogloss:1.92457	validation-mlogloss:1.89782
[152]	train-mlogloss:1.92250	validation-mlogloss:1.89590
[153]	train-mlogloss:1.92053	validation-mlogloss:1.89396
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[453]	train-mlogloss:1.60443	validation-mlogloss:1.69621
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[458]	train-mlogloss:1.60186	validation-mlogloss:1.69532
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[462]	train-mlogloss:1.59937	validation-mlogloss:1.69444
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[467]	train-mlogloss:1.59653	validation-mlogloss:1.69350
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[471]	train-mlogloss:1.59425	validation-mlogloss:1.69257
[472]	train-mlogloss:1.59371	validation-mlogloss:1.69226
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[476]	train-mlogloss:1.59148	validation-mlogloss:1.69168
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[499]	train-mlogloss:1.57918	validation-mlogloss:1.68772
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[503]	train-mlogloss:1.57708	validation-mlogloss:1.68728
[504]	train-mlogloss:1.57657	validation-mlogloss:1.68703
[505]	train-mlogloss:1.57602	validation-mlogloss:1.68690
[506]	train-mlogloss:1.57551	validation-mlogloss:1.68682
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[508]	train-mlogloss:1.57459	validation-mlogloss:1.68653
[509]	train-mlogloss:1.57394	validation-mlogloss:1.68622
[510]	train-mlogloss:1.57336	validation-mlogloss:1.68616
[511]	train-mlogloss:1.57281	validation-mlogloss:1.68601
[512]	train-mlogloss:1.57229	validation-mlogloss:1.68581
[513]	train-mlogloss:1.57172	validation-mlogloss:1.68569
[514]	train-mlogloss:1.57120	validation-mlogloss:1.68577
[515]	train-mlogloss:1.57071	validation-mlogloss:1.68571
[516]	train-mlogloss:1.57027	validation-mlogloss:1.68557
[517]	train-mlogloss:1.56975	validation-mlogloss:1.68549
[518]	train-mlogloss:1.56919	validation-mlogloss:1.68545
[519]	train-mlogloss:1.56876	validation-mlogloss:1.68529
[520]	train-mlogloss:1.56827	validation-mlogloss:1.68514
[521]	train-mlogloss:1.56771	validation-mlogloss:1.68499
[522]	train-mlogloss:1.56724	validation-mlogloss:1.68454
[523]	train-mlogloss:1.56672	validation-mlogloss:1.68426
[524]	train-mlogloss:1.56622	validation-mlogloss:1.68403
[525]	train-mlogloss:1.56577	validation-mlogloss:1.68383
[526]	train-mlogloss:1.56532	validation-mlogloss:1.68389
[527]	train-mlogloss:1.56482	validation-mlogloss:1.68362
[528]	train-mlogloss:1.56445	validation-mlogloss:1.68332
[529]	train-mlogloss:1.56400	validation-mlogloss:1.68313
[530]	train-mlogloss:1.56341	validation-mlogloss:1.68296
[531]	train-mlogloss:1.56296	validation-mlogloss:1.68291
[532]	train-mlogloss:1.56255	validation-mlogloss:1.68273
[533]	train-mlogloss:1.56197	validation-mlogloss:1.68259
[534]	train-mlogloss:1.56149	validation-mlogloss:1.68225
[535]	train-mlogloss:1.56104	validation-mlogloss:1.68227
[536]	train-mlogloss:1.56065	validation-mlogloss:1.68231
[537]	train-mlogloss:1.56024	validation-mlogloss:1.68231
[538]	train-mlogloss:1.55976	validation-mlogloss:1.68235
[539]	train-mlogloss:1.55928	validation-mlogloss:1.68228
Saved model to disk.
2025-10-27 09:49:20.089795: 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`.
2025-10-27 09:49:20.102301: 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 00:00:1761554960.115940  417654 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761554960.120394  417654 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761554960.131566  417654 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554960.131593  417654 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554960.131597  417654 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761554960.131600  417654 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:49:20.135026: 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:2.67969	validation-mlogloss:2.67655
[2]	train-mlogloss:2.66659	validation-mlogloss:2.66240
[3]	train-mlogloss:2.65286	validation-mlogloss:2.64681
[4]	train-mlogloss:2.64020	validation-mlogloss:2.63347
[5]	train-mlogloss:2.62736	validation-mlogloss:2.61937
[6]	train-mlogloss:2.61500	validation-mlogloss:2.60638
[7]	train-mlogloss:2.60256	validation-mlogloss:2.59219
[8]	train-mlogloss:2.59057	validation-mlogloss:2.57888
[9]	train-mlogloss:2.57938	validation-mlogloss:2.56688
[10]	train-mlogloss:2.56760	validation-mlogloss:2.55336
[11]	train-mlogloss:2.55745	validation-mlogloss:2.54162
[12]	train-mlogloss:2.54644	validation-mlogloss:2.52933
[13]	train-mlogloss:2.53558	validation-mlogloss:2.51735
[14]	train-mlogloss:2.52486	validation-mlogloss:2.50592
[15]	train-mlogloss:2.51453	validation-mlogloss:2.49375
[16]	train-mlogloss:2.50570	validation-mlogloss:2.48330
[17]	train-mlogloss:2.49608	validation-mlogloss:2.47224
[18]	train-mlogloss:2.48675	validation-mlogloss:2.46208
[19]	train-mlogloss:2.47744	validation-mlogloss:2.45186
[20]	train-mlogloss:2.46841	validation-mlogloss:2.44226
[21]	train-mlogloss:2.45948	validation-mlogloss:2.43198
[22]	train-mlogloss:2.45073	validation-mlogloss:2.42241
[23]	train-mlogloss:2.44194	validation-mlogloss:2.41265
[24]	train-mlogloss:2.43341	validation-mlogloss:2.40336
[25]	train-mlogloss:2.42573	validation-mlogloss:2.39456
[26]	train-mlogloss:2.41735	validation-mlogloss:2.38534
[27]	train-mlogloss:2.40940	validation-mlogloss:2.37690
[28]	train-mlogloss:2.40184	validation-mlogloss:2.36850
[29]	train-mlogloss:2.39407	validation-mlogloss:2.36053
[30]	train-mlogloss:2.38661	validation-mlogloss:2.35266
[31]	train-mlogloss:2.37907	validation-mlogloss:2.34458
[32]	train-mlogloss:2.37213	validation-mlogloss:2.33715
[33]	train-mlogloss:2.36498	validation-mlogloss:2.32929
[34]	train-mlogloss:2.35789	validation-mlogloss:2.32175
[35]	train-mlogloss:2.35104	validation-mlogloss:2.31448
[36]	train-mlogloss:2.34430	validation-mlogloss:2.30708
[37]	train-mlogloss:2.33738	validation-mlogloss:2.30007
[38]	train-mlogloss:2.33086	validation-mlogloss:2.29296
[39]	train-mlogloss:2.32460	validation-mlogloss:2.28639
[40]	train-mlogloss:2.31846	validation-mlogloss:2.27925
[41]	train-mlogloss:2.31239	validation-mlogloss:2.27288
[42]	train-mlogloss:2.30623	validation-mlogloss:2.26608
[43]	train-mlogloss:2.30030	validation-mlogloss:2.25978
[44]	train-mlogloss:2.29387	validation-mlogloss:2.25260
[45]	train-mlogloss:2.28787	validation-mlogloss:2.24588
[46]	train-mlogloss:2.28224	validation-mlogloss:2.24008
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[48]	train-mlogloss:2.27071	validation-mlogloss:2.22871
[49]	train-mlogloss:2.26503	validation-mlogloss:2.22254
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[51]	train-mlogloss:2.25431	validation-mlogloss:2.21137
[52]	train-mlogloss:2.24870	validation-mlogloss:2.20520
[53]	train-mlogloss:2.24349	validation-mlogloss:2.19984
[54]	train-mlogloss:2.23818	validation-mlogloss:2.19484
[55]	train-mlogloss:2.23286	validation-mlogloss:2.18945
[56]	train-mlogloss:2.22770	validation-mlogloss:2.18409
[57]	train-mlogloss:2.22304	validation-mlogloss:2.17931
[58]	train-mlogloss:2.21800	validation-mlogloss:2.17406
[59]	train-mlogloss:2.21337	validation-mlogloss:2.16943
[60]	train-mlogloss:2.20845	validation-mlogloss:2.16451
[61]	train-mlogloss:2.20369	validation-mlogloss:2.15990
[62]	train-mlogloss:2.19880	validation-mlogloss:2.15486
[63]	train-mlogloss:2.19387	validation-mlogloss:2.14962
[64]	train-mlogloss:2.18907	validation-mlogloss:2.14498
[65]	train-mlogloss:2.18438	validation-mlogloss:2.14002
[66]	train-mlogloss:2.17993	validation-mlogloss:2.13551
[67]	train-mlogloss:2.17550	validation-mlogloss:2.13111
[68]	train-mlogloss:2.17080	validation-mlogloss:2.12656
[69]	train-mlogloss:2.16651	validation-mlogloss:2.12266
[70]	train-mlogloss:2.16236	validation-mlogloss:2.11834
[71]	train-mlogloss:2.15810	validation-mlogloss:2.11410
[72]	train-mlogloss:2.15384	validation-mlogloss:2.11020
[73]	train-mlogloss:2.14969	validation-mlogloss:2.10594
[74]	train-mlogloss:2.14565	validation-mlogloss:2.10182
[75]	train-mlogloss:2.14154	validation-mlogloss:2.09770
[76]	train-mlogloss:2.13767	validation-mlogloss:2.09403
[77]	train-mlogloss:2.13363	validation-mlogloss:2.09009
[78]	train-mlogloss:2.12975	validation-mlogloss:2.08636
[79]	train-mlogloss:2.12607	validation-mlogloss:2.08268
[80]	train-mlogloss:2.12225	validation-mlogloss:2.07886
[81]	train-mlogloss:2.11842	validation-mlogloss:2.07494
[82]	train-mlogloss:2.11470	validation-mlogloss:2.07113
[83]	train-mlogloss:2.11080	validation-mlogloss:2.06743
[84]	train-mlogloss:2.10713	validation-mlogloss:2.06423
[85]	train-mlogloss:2.10361	validation-mlogloss:2.06092
[86]	train-mlogloss:2.10020	validation-mlogloss:2.05757
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[95]	train-mlogloss:2.06959	validation-mlogloss:2.02894
[96]	train-mlogloss:2.06643	validation-mlogloss:2.02594
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[98]	train-mlogloss:2.05999	validation-mlogloss:2.01937
[99]	train-mlogloss:2.05673	validation-mlogloss:2.01634
[100]	train-mlogloss:2.05351	validation-mlogloss:2.01313
[101]	train-mlogloss:2.05030	validation-mlogloss:2.01011
[102]	train-mlogloss:2.04716	validation-mlogloss:2.00686
[103]	train-mlogloss:2.04402	validation-mlogloss:2.00408
[104]	train-mlogloss:2.04102	validation-mlogloss:2.00154
[105]	train-mlogloss:2.03804	validation-mlogloss:1.99882
[106]	train-mlogloss:2.03500	validation-mlogloss:1.99603
[107]	train-mlogloss:2.03216	validation-mlogloss:1.99329
[108]	train-mlogloss:2.02911	validation-mlogloss:1.99043
[109]	train-mlogloss:2.02637	validation-mlogloss:1.98811
[110]	train-mlogloss:2.02354	validation-mlogloss:1.98539
[111]	train-mlogloss:2.02057	validation-mlogloss:1.98269
[112]	train-mlogloss:2.01776	validation-mlogloss:1.98009
[113]	train-mlogloss:2.01509	validation-mlogloss:1.97759
[114]	train-mlogloss:2.01245	validation-mlogloss:1.97557
[115]	train-mlogloss:2.00977	validation-mlogloss:1.97295
[116]	train-mlogloss:2.00710	validation-mlogloss:1.97059
[117]	train-mlogloss:2.00436	validation-mlogloss:1.96835
[118]	train-mlogloss:2.00167	validation-mlogloss:1.96580
[119]	train-mlogloss:1.99894	validation-mlogloss:1.96346
[120]	train-mlogloss:1.99607	validation-mlogloss:1.96072
[121]	train-mlogloss:1.99349	validation-mlogloss:1.95833
[122]	train-mlogloss:1.99099	validation-mlogloss:1.95607
[123]	train-mlogloss:1.98821	validation-mlogloss:1.95350
[124]	train-mlogloss:1.98571	validation-mlogloss:1.95119
[125]	train-mlogloss:1.98300	validation-mlogloss:1.94871
[126]	train-mlogloss:1.98051	validation-mlogloss:1.94676
[127]	train-mlogloss:1.97799	validation-mlogloss:1.94435
[128]	train-mlogloss:1.97557	validation-mlogloss:1.94237
[129]	train-mlogloss:1.97316	validation-mlogloss:1.94057
[130]	train-mlogloss:1.97055	validation-mlogloss:1.93841
[131]	train-mlogloss:1.96808	validation-mlogloss:1.93635
[132]	train-mlogloss:1.96580	validation-mlogloss:1.93449
[133]	train-mlogloss:1.96332	validation-mlogloss:1.93239
[134]	train-mlogloss:1.96104	validation-mlogloss:1.93070
[135]	train-mlogloss:1.95863	validation-mlogloss:1.92842
[136]	train-mlogloss:1.95632	validation-mlogloss:1.92626
[137]	train-mlogloss:1.95408	validation-mlogloss:1.92435
[138]	train-mlogloss:1.95192	validation-mlogloss:1.92223
[139]	train-mlogloss:1.94965	validation-mlogloss:1.92056
[140]	train-mlogloss:1.94738	validation-mlogloss:1.91851
[141]	train-mlogloss:1.94515	validation-mlogloss:1.91636
[142]	train-mlogloss:1.94286	validation-mlogloss:1.91413
[143]	train-mlogloss:1.94062	validation-mlogloss:1.91215
[144]	train-mlogloss:1.93827	validation-mlogloss:1.91036
[145]	train-mlogloss:1.93608	validation-mlogloss:1.90851
[146]	train-mlogloss:1.93402	validation-mlogloss:1.90694
[147]	train-mlogloss:1.93195	validation-mlogloss:1.90502
[148]	train-mlogloss:1.92995	validation-mlogloss:1.90345
[149]	train-mlogloss:1.92803	validation-mlogloss:1.90188
[150]	train-mlogloss:1.92583	validation-mlogloss:1.89990
[151]	train-mlogloss:1.92386	validation-mlogloss:1.89854
[152]	train-mlogloss:1.92182	validation-mlogloss:1.89675
[153]	train-mlogloss:1.91974	validation-mlogloss:1.89489
[154]	train-mlogloss:1.91764	validation-mlogloss:1.89341
[155]	train-mlogloss:1.91568	validation-mlogloss:1.89190
[156]	train-mlogloss:1.91371	validation-mlogloss:1.89040
[157]	train-mlogloss:1.91166	validation-mlogloss:1.88833
[158]	train-mlogloss:1.90957	validation-mlogloss:1.88633
[159]	train-mlogloss:1.90766	validation-mlogloss:1.88466
[160]	train-mlogloss:1.90569	validation-mlogloss:1.88287
[161]	train-mlogloss:1.90375	validation-mlogloss:1.88116
[162]	train-mlogloss:1.90185	validation-mlogloss:1.87961
[163]	train-mlogloss:1.89997	validation-mlogloss:1.87795
[164]	train-mlogloss:1.89817	validation-mlogloss:1.87668
[165]	train-mlogloss:1.89633	validation-mlogloss:1.87517
[166]	train-mlogloss:1.89458	validation-mlogloss:1.87351
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[169]	train-mlogloss:1.88893	validation-mlogloss:1.86840
[170]	train-mlogloss:1.88722	validation-mlogloss:1.86690
[171]	train-mlogloss:1.88537	validation-mlogloss:1.86537
[172]	train-mlogloss:1.88346	validation-mlogloss:1.86364
[173]	train-mlogloss:1.88171	validation-mlogloss:1.86229
[174]	train-mlogloss:1.87994	validation-mlogloss:1.86063
[175]	train-mlogloss:1.87819	validation-mlogloss:1.85888
[176]	train-mlogloss:1.87643	validation-mlogloss:1.85730
[177]	train-mlogloss:1.87462	validation-mlogloss:1.85570
[178]	train-mlogloss:1.87280	validation-mlogloss:1.85411
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[180]	train-mlogloss:1.86923	validation-mlogloss:1.85129
[181]	train-mlogloss:1.86759	validation-mlogloss:1.84992
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[186]	train-mlogloss:1.85941	validation-mlogloss:1.84382
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[488]	train-mlogloss:1.58403	validation-mlogloss:1.68889
[489]	train-mlogloss:1.58362	validation-mlogloss:1.68879
[490]	train-mlogloss:1.58306	validation-mlogloss:1.68846
[491]	train-mlogloss:1.58243	validation-mlogloss:1.68838
[492]	train-mlogloss:1.58187	validation-mlogloss:1.68818
[493]	train-mlogloss:1.58145	validation-mlogloss:1.68821
[494]	train-mlogloss:1.58100	validation-mlogloss:1.68820
[495]	train-mlogloss:1.58053	validation-mlogloss:1.68794
[496]	train-mlogloss:1.57998	validation-mlogloss:1.68772
[497]	train-mlogloss:1.57942	validation-mlogloss:1.68751
[498]	train-mlogloss:1.57891	validation-mlogloss:1.68748
[499]	train-mlogloss:1.57840	validation-mlogloss:1.68730
[500]	train-mlogloss:1.57791	validation-mlogloss:1.68710
[501]	train-mlogloss:1.57736	validation-mlogloss:1.68709
[502]	train-mlogloss:1.57683	validation-mlogloss:1.68718
[503]	train-mlogloss:1.57631	validation-mlogloss:1.68691
[504]	train-mlogloss:1.57570	validation-mlogloss:1.68683
[505]	train-mlogloss:1.57518	validation-mlogloss:1.68669
[506]	train-mlogloss:1.57464	validation-mlogloss:1.68651
[507]	train-mlogloss:1.57424	validation-mlogloss:1.68633
[508]	train-mlogloss:1.57370	validation-mlogloss:1.68611
[509]	train-mlogloss:1.57324	validation-mlogloss:1.68603
[510]	train-mlogloss:1.57271	validation-mlogloss:1.68590
[511]	train-mlogloss:1.57220	validation-mlogloss:1.68568
[512]	train-mlogloss:1.57167	validation-mlogloss:1.68539
[513]	train-mlogloss:1.57116	validation-mlogloss:1.68551
[514]	train-mlogloss:1.57071	validation-mlogloss:1.68517
[515]	train-mlogloss:1.57018	validation-mlogloss:1.68513
[516]	train-mlogloss:1.56969	validation-mlogloss:1.68498
[517]	train-mlogloss:1.56914	validation-mlogloss:1.68484
[518]	train-mlogloss:1.56871	validation-mlogloss:1.68471
[519]	train-mlogloss:1.56814	validation-mlogloss:1.68428
[520]	train-mlogloss:1.56764	validation-mlogloss:1.68412
[521]	train-mlogloss:1.56714	validation-mlogloss:1.68409
[522]	train-mlogloss:1.56657	validation-mlogloss:1.68389
[523]	train-mlogloss:1.56601	validation-mlogloss:1.68363
[524]	train-mlogloss:1.56557	validation-mlogloss:1.68349
[525]	train-mlogloss:1.56506	validation-mlogloss:1.68342
[526]	train-mlogloss:1.56443	validation-mlogloss:1.68325
[527]	train-mlogloss:1.56403	validation-mlogloss:1.68315
[528]	train-mlogloss:1.56353	validation-mlogloss:1.68295
[529]	train-mlogloss:1.56306	validation-mlogloss:1.68275
[530]	train-mlogloss:1.56259	validation-mlogloss:1.68269
[531]	train-mlogloss:1.56210	validation-mlogloss:1.68267
[532]	train-mlogloss:1.56173	validation-mlogloss:1.68258
[533]	train-mlogloss:1.56118	validation-mlogloss:1.68237
[534]	train-mlogloss:1.56067	validation-mlogloss:1.68217
[535]	train-mlogloss:1.56021	validation-mlogloss:1.68213
[536]	train-mlogloss:1.55973	validation-mlogloss:1.68195
[537]	train-mlogloss:1.55931	validation-mlogloss:1.68186
[538]	train-mlogloss:1.55884	validation-mlogloss:1.68178
[539]	train-mlogloss:1.55842	validation-mlogloss:1.68182
Saved model to disk.
2025-10-27 09:50:05.711201: 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`.
2025-10-27 09:50:05.723698: 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 00:00:1761555005.737285  418578 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555005.741466  418578 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555005.752469  418578 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555005.752493  418578 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555005.752496  418578 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555005.752499  418578 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:50:05.755862: 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:2.69397	validation-mlogloss:2.69278
[1]	train-mlogloss:2.67942	validation-mlogloss:2.67691
[2]	train-mlogloss:2.66677	validation-mlogloss:2.66234
[3]	train-mlogloss:2.65286	validation-mlogloss:2.64702
[4]	train-mlogloss:2.63972	validation-mlogloss:2.63302
[5]	train-mlogloss:2.62663	validation-mlogloss:2.61809
[6]	train-mlogloss:2.61382	validation-mlogloss:2.60331
[7]	train-mlogloss:2.60184	validation-mlogloss:2.59014
[8]	train-mlogloss:2.58985	validation-mlogloss:2.57680
[9]	train-mlogloss:2.57885	validation-mlogloss:2.56481
[10]	train-mlogloss:2.56722	validation-mlogloss:2.55165
[11]	train-mlogloss:2.55647	validation-mlogloss:2.54007
[12]	train-mlogloss:2.54549	validation-mlogloss:2.52777
[13]	train-mlogloss:2.53528	validation-mlogloss:2.51653
[14]	train-mlogloss:2.52484	validation-mlogloss:2.50515
[15]	train-mlogloss:2.51493	validation-mlogloss:2.49464
[16]	train-mlogloss:2.50476	validation-mlogloss:2.48309
[17]	train-mlogloss:2.49498	validation-mlogloss:2.47231
[18]	train-mlogloss:2.48532	validation-mlogloss:2.46142
[19]	train-mlogloss:2.47690	validation-mlogloss:2.45188
[20]	train-mlogloss:2.46820	validation-mlogloss:2.44166
[21]	train-mlogloss:2.45917	validation-mlogloss:2.43172
[22]	train-mlogloss:2.45060	validation-mlogloss:2.42234
[23]	train-mlogloss:2.44205	validation-mlogloss:2.41318
[24]	train-mlogloss:2.43412	validation-mlogloss:2.40447
[25]	train-mlogloss:2.42624	validation-mlogloss:2.39554
[26]	train-mlogloss:2.41794	validation-mlogloss:2.38691
[27]	train-mlogloss:2.41002	validation-mlogloss:2.37806
[28]	train-mlogloss:2.40222	validation-mlogloss:2.36977
[29]	train-mlogloss:2.39415	validation-mlogloss:2.36091
[30]	train-mlogloss:2.38660	validation-mlogloss:2.35235
[31]	train-mlogloss:2.37944	validation-mlogloss:2.34484
[32]	train-mlogloss:2.37224	validation-mlogloss:2.33764
[33]	train-mlogloss:2.36521	validation-mlogloss:2.32944
[34]	train-mlogloss:2.35826	validation-mlogloss:2.32233
[35]	train-mlogloss:2.35130	validation-mlogloss:2.31467
[36]	train-mlogloss:2.34488	validation-mlogloss:2.30793
[37]	train-mlogloss:2.33815	validation-mlogloss:2.30110
[38]	train-mlogloss:2.33185	validation-mlogloss:2.29498
[39]	train-mlogloss:2.32524	validation-mlogloss:2.28770
[40]	train-mlogloss:2.31909	validation-mlogloss:2.28112
[41]	train-mlogloss:2.31247	validation-mlogloss:2.27390
[42]	train-mlogloss:2.30627	validation-mlogloss:2.26669
[43]	train-mlogloss:2.30017	validation-mlogloss:2.26050
[44]	train-mlogloss:2.29392	validation-mlogloss:2.25375
[45]	train-mlogloss:2.28783	validation-mlogloss:2.24730
[46]	train-mlogloss:2.28212	validation-mlogloss:2.24112
[47]	train-mlogloss:2.27636	validation-mlogloss:2.23488
[48]	train-mlogloss:2.27091	validation-mlogloss:2.22929
[49]	train-mlogloss:2.26545	validation-mlogloss:2.22350
[50]	train-mlogloss:2.25992	validation-mlogloss:2.21788
[51]	train-mlogloss:2.25429	validation-mlogloss:2.21212
[52]	train-mlogloss:2.24887	validation-mlogloss:2.20628
[53]	train-mlogloss:2.24411	validation-mlogloss:2.20142
[54]	train-mlogloss:2.23925	validation-mlogloss:2.19638
[55]	train-mlogloss:2.23413	validation-mlogloss:2.19138
[56]	train-mlogloss:2.22914	validation-mlogloss:2.18624
[57]	train-mlogloss:2.22378	validation-mlogloss:2.18067
[58]	train-mlogloss:2.21889	validation-mlogloss:2.17586
[59]	train-mlogloss:2.21407	validation-mlogloss:2.17117
[60]	train-mlogloss:2.20913	validation-mlogloss:2.16621
[61]	train-mlogloss:2.20419	validation-mlogloss:2.16112
[62]	train-mlogloss:2.19937	validation-mlogloss:2.15617
[63]	train-mlogloss:2.19481	validation-mlogloss:2.15184
[64]	train-mlogloss:2.19036	validation-mlogloss:2.14774
[65]	train-mlogloss:2.18587	validation-mlogloss:2.14331
[66]	train-mlogloss:2.18129	validation-mlogloss:2.13857
[67]	train-mlogloss:2.17672	validation-mlogloss:2.13451
[68]	train-mlogloss:2.17238	validation-mlogloss:2.12995
[69]	train-mlogloss:2.16816	validation-mlogloss:2.12569
[70]	train-mlogloss:2.16373	validation-mlogloss:2.12135
[71]	train-mlogloss:2.15935	validation-mlogloss:2.11734
[72]	train-mlogloss:2.15516	validation-mlogloss:2.11304
[73]	train-mlogloss:2.15081	validation-mlogloss:2.10895
[74]	train-mlogloss:2.14697	validation-mlogloss:2.10520
[75]	train-mlogloss:2.14289	validation-mlogloss:2.10138
[76]	train-mlogloss:2.13890	validation-mlogloss:2.09771
[77]	train-mlogloss:2.13511	validation-mlogloss:2.09378
[78]	train-mlogloss:2.13153	validation-mlogloss:2.09041
[79]	train-mlogloss:2.12771	validation-mlogloss:2.08682
[80]	train-mlogloss:2.12376	validation-mlogloss:2.08312
[81]	train-mlogloss:2.12001	validation-mlogloss:2.07928
[82]	train-mlogloss:2.11637	validation-mlogloss:2.07594
[83]	train-mlogloss:2.11255	validation-mlogloss:2.07243
[84]	train-mlogloss:2.10889	validation-mlogloss:2.06883
[85]	train-mlogloss:2.10530	validation-mlogloss:2.06509
[86]	train-mlogloss:2.10116	validation-mlogloss:2.06073
[87]	train-mlogloss:2.09772	validation-mlogloss:2.05731
[88]	train-mlogloss:2.09420	validation-mlogloss:2.05363
[89]	train-mlogloss:2.09072	validation-mlogloss:2.05010
[90]	train-mlogloss:2.08717	validation-mlogloss:2.04638
[91]	train-mlogloss:2.08367	validation-mlogloss:2.04342
[92]	train-mlogloss:2.08039	validation-mlogloss:2.04053
[93]	train-mlogloss:2.07708	validation-mlogloss:2.03753
[94]	train-mlogloss:2.07379	validation-mlogloss:2.03429
[95]	train-mlogloss:2.07027	validation-mlogloss:2.03060
[96]	train-mlogloss:2.06683	validation-mlogloss:2.02749
[97]	train-mlogloss:2.06367	validation-mlogloss:2.02424
[98]	train-mlogloss:2.06037	validation-mlogloss:2.02126
[99]	train-mlogloss:2.05735	validation-mlogloss:2.01824
[100]	train-mlogloss:2.05397	validation-mlogloss:2.01519
[101]	train-mlogloss:2.05096	validation-mlogloss:2.01238
[102]	train-mlogloss:2.04797	validation-mlogloss:2.00958
[103]	train-mlogloss:2.04481	validation-mlogloss:2.00651
[104]	train-mlogloss:2.04148	validation-mlogloss:2.00328
[105]	train-mlogloss:2.03841	validation-mlogloss:2.00039
[106]	train-mlogloss:2.03539	validation-mlogloss:1.99721
[107]	train-mlogloss:2.03249	validation-mlogloss:1.99451
[108]	train-mlogloss:2.02953	validation-mlogloss:1.99194
[109]	train-mlogloss:2.02682	validation-mlogloss:1.98948
[110]	train-mlogloss:2.02398	validation-mlogloss:1.98697
[111]	train-mlogloss:2.02121	validation-mlogloss:1.98463
[112]	train-mlogloss:2.01852	validation-mlogloss:1.98219
[113]	train-mlogloss:2.01569	validation-mlogloss:1.97948
[114]	train-mlogloss:2.01291	validation-mlogloss:1.97693
[115]	train-mlogloss:2.01010	validation-mlogloss:1.97453
[116]	train-mlogloss:2.00738	validation-mlogloss:1.97199
[117]	train-mlogloss:2.00471	validation-mlogloss:1.96952
[118]	train-mlogloss:2.00198	validation-mlogloss:1.96696
[119]	train-mlogloss:1.99918	validation-mlogloss:1.96435
[120]	train-mlogloss:1.99661	validation-mlogloss:1.96224
[121]	train-mlogloss:1.99417	validation-mlogloss:1.96015
[122]	train-mlogloss:1.99158	validation-mlogloss:1.95787
[123]	train-mlogloss:1.98909	validation-mlogloss:1.95586
[124]	train-mlogloss:1.98649	validation-mlogloss:1.95358
[125]	train-mlogloss:1.98389	validation-mlogloss:1.95106
[126]	train-mlogloss:1.98138	validation-mlogloss:1.94879
[127]	train-mlogloss:1.97895	validation-mlogloss:1.94664
[128]	train-mlogloss:1.97658	validation-mlogloss:1.94417
[129]	train-mlogloss:1.97431	validation-mlogloss:1.94199
[130]	train-mlogloss:1.97183	validation-mlogloss:1.93968
[131]	train-mlogloss:1.96955	validation-mlogloss:1.93765
[132]	train-mlogloss:1.96715	validation-mlogloss:1.93558
[133]	train-mlogloss:1.96471	validation-mlogloss:1.93316
[134]	train-mlogloss:1.96231	validation-mlogloss:1.93070
[135]	train-mlogloss:1.95982	validation-mlogloss:1.92849
[136]	train-mlogloss:1.95734	validation-mlogloss:1.92609
[137]	train-mlogloss:1.95521	validation-mlogloss:1.92441
[138]	train-mlogloss:1.95294	validation-mlogloss:1.92234
[139]	train-mlogloss:1.95069	validation-mlogloss:1.92050
[140]	train-mlogloss:1.94867	validation-mlogloss:1.91891
[141]	train-mlogloss:1.94635	validation-mlogloss:1.91725
[142]	train-mlogloss:1.94406	validation-mlogloss:1.91558
[143]	train-mlogloss:1.94199	validation-mlogloss:1.91380
[144]	train-mlogloss:1.93978	validation-mlogloss:1.91189
[145]	train-mlogloss:1.93751	validation-mlogloss:1.90955
[146]	train-mlogloss:1.93534	validation-mlogloss:1.90772
[147]	train-mlogloss:1.93325	validation-mlogloss:1.90614
[148]	train-mlogloss:1.93100	validation-mlogloss:1.90402
[149]	train-mlogloss:1.92891	validation-mlogloss:1.90218
[150]	train-mlogloss:1.92667	validation-mlogloss:1.90035
[151]	train-mlogloss:1.92450	validation-mlogloss:1.89834
[152]	train-mlogloss:1.92228	validation-mlogloss:1.89639
[153]	train-mlogloss:1.92015	validation-mlogloss:1.89445
[154]	train-mlogloss:1.91809	validation-mlogloss:1.89262
[155]	train-mlogloss:1.91613	validation-mlogloss:1.89129
[156]	train-mlogloss:1.91410	validation-mlogloss:1.88957
[157]	train-mlogloss:1.91212	validation-mlogloss:1.88802
[158]	train-mlogloss:1.91014	validation-mlogloss:1.88638
[159]	train-mlogloss:1.90821	validation-mlogloss:1.88444
[160]	train-mlogloss:1.90619	validation-mlogloss:1.88253
[161]	train-mlogloss:1.90418	validation-mlogloss:1.88062
[162]	train-mlogloss:1.90226	validation-mlogloss:1.87884
[163]	train-mlogloss:1.90026	validation-mlogloss:1.87697
[164]	train-mlogloss:1.89823	validation-mlogloss:1.87512
[165]	train-mlogloss:1.89641	validation-mlogloss:1.87360
[166]	train-mlogloss:1.89471	validation-mlogloss:1.87238
[167]	train-mlogloss:1.89281	validation-mlogloss:1.87084
[168]	train-mlogloss:1.89095	validation-mlogloss:1.86971
[169]	train-mlogloss:1.88922	validation-mlogloss:1.86823
[170]	train-mlogloss:1.88739	validation-mlogloss:1.86694
[171]	train-mlogloss:1.88566	validation-mlogloss:1.86574
[172]	train-mlogloss:1.88385	validation-mlogloss:1.86402
[173]	train-mlogloss:1.88216	validation-mlogloss:1.86288
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[176]	train-mlogloss:1.87681	validation-mlogloss:1.85888
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[179]	train-mlogloss:1.87146	validation-mlogloss:1.85435
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[187]	train-mlogloss:1.85787	validation-mlogloss:1.84406
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[189]	train-mlogloss:1.85466	validation-mlogloss:1.84135
[190]	train-mlogloss:1.85304	validation-mlogloss:1.83998
[191]	train-mlogloss:1.85139	validation-mlogloss:1.83857
[192]	train-mlogloss:1.84972	validation-mlogloss:1.83741
[193]	train-mlogloss:1.84816	validation-mlogloss:1.83630
[194]	train-mlogloss:1.84652	validation-mlogloss:1.83482
[195]	train-mlogloss:1.84491	validation-mlogloss:1.83360
[196]	train-mlogloss:1.84340	validation-mlogloss:1.83240
[197]	train-mlogloss:1.84205	validation-mlogloss:1.83129
[198]	train-mlogloss:1.84041	validation-mlogloss:1.82990
[199]	train-mlogloss:1.83889	validation-mlogloss:1.82885
[200]	train-mlogloss:1.83733	validation-mlogloss:1.82747
[201]	train-mlogloss:1.83578	validation-mlogloss:1.82628
[202]	train-mlogloss:1.83423	validation-mlogloss:1.82523
[203]	train-mlogloss:1.83267	validation-mlogloss:1.82413
[204]	train-mlogloss:1.83122	validation-mlogloss:1.82289
[205]	train-mlogloss:1.82983	validation-mlogloss:1.82201
[206]	train-mlogloss:1.82833	validation-mlogloss:1.82116
[207]	train-mlogloss:1.82664	validation-mlogloss:1.81967
[208]	train-mlogloss:1.82523	validation-mlogloss:1.81868
[209]	train-mlogloss:1.82381	validation-mlogloss:1.81772
[210]	train-mlogloss:1.82238	validation-mlogloss:1.81671
[211]	train-mlogloss:1.82098	validation-mlogloss:1.81592
[212]	train-mlogloss:1.81943	validation-mlogloss:1.81506
[213]	train-mlogloss:1.81794	validation-mlogloss:1.81398
[214]	train-mlogloss:1.81638	validation-mlogloss:1.81290
[215]	train-mlogloss:1.81491	validation-mlogloss:1.81188
[216]	train-mlogloss:1.81337	validation-mlogloss:1.81065
[217]	train-mlogloss:1.81196	validation-mlogloss:1.80973
[218]	train-mlogloss:1.81063	validation-mlogloss:1.80864
[219]	train-mlogloss:1.80934	validation-mlogloss:1.80788
[220]	train-mlogloss:1.80802	validation-mlogloss:1.80670
[221]	train-mlogloss:1.80651	validation-mlogloss:1.80561
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[523]	train-mlogloss:1.56468	validation-mlogloss:1.68449
[524]	train-mlogloss:1.56418	validation-mlogloss:1.68448
[525]	train-mlogloss:1.56373	validation-mlogloss:1.68452
[526]	train-mlogloss:1.56325	validation-mlogloss:1.68432
[527]	train-mlogloss:1.56275	validation-mlogloss:1.68416
[528]	train-mlogloss:1.56232	validation-mlogloss:1.68399
[529]	train-mlogloss:1.56187	validation-mlogloss:1.68396
[530]	train-mlogloss:1.56136	validation-mlogloss:1.68394
[531]	train-mlogloss:1.56085	validation-mlogloss:1.68386
[532]	train-mlogloss:1.56033	validation-mlogloss:1.68378
[533]	train-mlogloss:1.55986	validation-mlogloss:1.68359
[534]	train-mlogloss:1.55938	validation-mlogloss:1.68361
[535]	train-mlogloss:1.55886	validation-mlogloss:1.68365
[536]	train-mlogloss:1.55829	validation-mlogloss:1.68367
[537]	train-mlogloss:1.55790	validation-mlogloss:1.68342
[538]	train-mlogloss:1.55747	validation-mlogloss:1.68329
[539]	train-mlogloss:1.55702	validation-mlogloss:1.68310
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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.49 [%]
Global accuracy score (test) = 44.46 [%]
Global F1 score (train) = 51.64 [%]
Global F1 score (test) = 43.69 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.77      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.38      0.46      0.41       184
       CAMINAR USUAL SPEED       0.36      0.27      0.31       184
            CAMINAR ZIGZAG       0.38      0.54      0.44       184
          DE PIE BARRIENDO       0.75      0.28      0.40       184
   DE PIE DOBLANDO TOALLAS       0.49      0.43      0.46       184
    DE PIE MOVIENDO LIBROS       0.35      0.32      0.33       184
          DE PIE USANDO PC       0.20      0.31      0.24       184
        FASE REPOSO CON K5       0.56      0.85      0.68       184
INCREMENTAL CICLOERGOMETRO       0.75      0.69      0.72       184
           SENTADO LEYENDO       0.49      0.36      0.42       184
         SENTADO USANDO PC       0.21      0.12      0.15       184
      SENTADO VIENDO LA TV       0.26      0.22      0.24       184
   SUBIR Y BAJAR ESCALERAS       0.62      0.50      0.55       184
                    TROTAR       0.64      0.57      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 16: 44.46 [%]
F1-score capturado en la ejecución 16: 43.69 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.2 [%]
Global accuracy score (test) = 45.05 [%]
Global F1 score (train) = 51.32 [%]
Global F1 score (test) = 44.37 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.76      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.38      0.46      0.42       184
       CAMINAR USUAL SPEED       0.36      0.28      0.31       184
            CAMINAR ZIGZAG       0.38      0.55      0.45       184
          DE PIE BARRIENDO       0.73      0.29      0.42       184
   DE PIE DOBLANDO TOALLAS       0.49      0.43      0.46       184
    DE PIE MOVIENDO LIBROS       0.34      0.29      0.32       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.57      0.86      0.69       184
INCREMENTAL CICLOERGOMETRO       0.75      0.70      0.72       184
           SENTADO LEYENDO       0.44      0.34      0.38       184
         SENTADO USANDO PC       0.25      0.14      0.18       184
      SENTADO VIENDO LA TV       0.31      0.25      0.28       184
   SUBIR Y BAJAR ESCALERAS       0.68      0.53      0.60       184
                    TROTAR       0.68      0.57      0.62       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.45      0.44      2737
              weighted avg       0.47      0.45      0.44      2737


Accuracy capturado en la ejecución 17: 45.05 [%]
F1-score capturado en la ejecución 17: 44.37 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.39 [%]
Global accuracy score (test) = 45.34 [%]
Global F1 score (train) = 51.52 [%]
Global F1 score (test) = 44.84 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.74      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.37      0.46      0.41       184
       CAMINAR USUAL SPEED       0.38      0.30      0.34       184
            CAMINAR ZIGZAG       0.39      0.55      0.46       184
          DE PIE BARRIENDO       0.76      0.30      0.43       184
   DE PIE DOBLANDO TOALLAS       0.51      0.43      0.47       184
    DE PIE MOVIENDO LIBROS       0.40      0.35      0.37       184
          DE PIE USANDO PC       0.21      0.33      0.26       184
        FASE REPOSO CON K5       0.58      0.85      0.69       184
INCREMENTAL CICLOERGOMETRO       0.76      0.69      0.72       184
           SENTADO LEYENDO       0.51      0.39      0.44       184
         SENTADO USANDO PC       0.24      0.14      0.18       184
      SENTADO VIENDO LA TV       0.27      0.23      0.25       184
   SUBIR Y BAJAR ESCALERAS       0.61      0.47      0.53       184
                    TROTAR       0.66      0.57      0.61       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.45      0.45      2737
              weighted avg       0.47      0.45      0.45      2737


Accuracy capturado en la ejecución 18: 45.34 [%]
F1-score capturado en la ejecución 18: 44.84 [%]

=== EJECUCIÓN 19 ===

--- TRAIN (ejecución 19) ---

--- TEST (ejecución 19) ---
2025-10-27 09:50:51.771680: 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`.
2025-10-27 09:50:51.784333: 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 00:00:1761555051.797966  419474 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555051.802290  419474 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555051.813233  419474 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555051.813256  419474 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555051.813259  419474 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555051.813262  419474 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:50:51.816608: 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:2.69389	validation-mlogloss:2.69299
[1]	train-mlogloss:2.67960	validation-mlogloss:2.67743
[2]	train-mlogloss:2.66684	validation-mlogloss:2.66372
[3]	train-mlogloss:2.65309	validation-mlogloss:2.64886
[4]	train-mlogloss:2.64078	validation-mlogloss:2.63604
[5]	train-mlogloss:2.62735	validation-mlogloss:2.62024
[6]	train-mlogloss:2.61449	validation-mlogloss:2.60653
[7]	train-mlogloss:2.60200	validation-mlogloss:2.59285
[8]	train-mlogloss:2.58991	validation-mlogloss:2.58004
[9]	train-mlogloss:2.57911	validation-mlogloss:2.56855
[10]	train-mlogloss:2.56862	validation-mlogloss:2.55676
[11]	train-mlogloss:2.55739	validation-mlogloss:2.54416
[12]	train-mlogloss:2.54659	validation-mlogloss:2.53278
[13]	train-mlogloss:2.53690	validation-mlogloss:2.52123
[14]	train-mlogloss:2.52709	validation-mlogloss:2.51077
[15]	train-mlogloss:2.51647	validation-mlogloss:2.49865
[16]	train-mlogloss:2.50693	validation-mlogloss:2.48816
[17]	train-mlogloss:2.49698	validation-mlogloss:2.47692
[18]	train-mlogloss:2.48758	validation-mlogloss:2.46677
[19]	train-mlogloss:2.47798	validation-mlogloss:2.45634
[20]	train-mlogloss:2.46880	validation-mlogloss:2.44578
[21]	train-mlogloss:2.45973	validation-mlogloss:2.43542
[22]	train-mlogloss:2.45110	validation-mlogloss:2.42533
[23]	train-mlogloss:2.44253	validation-mlogloss:2.41592
[24]	train-mlogloss:2.43437	validation-mlogloss:2.40742
[25]	train-mlogloss:2.42597	validation-mlogloss:2.39767
[26]	train-mlogloss:2.41839	validation-mlogloss:2.38959
[27]	train-mlogloss:2.41032	validation-mlogloss:2.38081
[28]	train-mlogloss:2.40239	validation-mlogloss:2.37222
[29]	train-mlogloss:2.39507	validation-mlogloss:2.36413
[30]	train-mlogloss:2.38762	validation-mlogloss:2.35561
[31]	train-mlogloss:2.38002	validation-mlogloss:2.34724
[32]	train-mlogloss:2.37278	validation-mlogloss:2.33951
[33]	train-mlogloss:2.36599	validation-mlogloss:2.33265
[34]	train-mlogloss:2.35893	validation-mlogloss:2.32528
[35]	train-mlogloss:2.35206	validation-mlogloss:2.31762
[36]	train-mlogloss:2.34533	validation-mlogloss:2.31027
[37]	train-mlogloss:2.33854	validation-mlogloss:2.30336
[38]	train-mlogloss:2.33192	validation-mlogloss:2.29638
[39]	train-mlogloss:2.32575	validation-mlogloss:2.29035
[40]	train-mlogloss:2.31903	validation-mlogloss:2.28298
[41]	train-mlogloss:2.31261	validation-mlogloss:2.27624
[42]	train-mlogloss:2.30629	validation-mlogloss:2.26929
[43]	train-mlogloss:2.30018	validation-mlogloss:2.26262
[44]	train-mlogloss:2.29419	validation-mlogloss:2.25604
[45]	train-mlogloss:2.28808	validation-mlogloss:2.24939
[46]	train-mlogloss:2.28212	validation-mlogloss:2.24375
[47]	train-mlogloss:2.27614	validation-mlogloss:2.23739
[48]	train-mlogloss:2.27003	validation-mlogloss:2.23089
[49]	train-mlogloss:2.26445	validation-mlogloss:2.22479
[50]	train-mlogloss:2.25884	validation-mlogloss:2.21845
[51]	train-mlogloss:2.25342	validation-mlogloss:2.21279
[52]	train-mlogloss:2.24802	validation-mlogloss:2.20705
[53]	train-mlogloss:2.24252	validation-mlogloss:2.20140
[54]	train-mlogloss:2.23726	validation-mlogloss:2.19602
[55]	train-mlogloss:2.23192	validation-mlogloss:2.19011
[56]	train-mlogloss:2.22696	validation-mlogloss:2.18520
[57]	train-mlogloss:2.22202	validation-mlogloss:2.18039
[58]	train-mlogloss:2.21710	validation-mlogloss:2.17457
[59]	train-mlogloss:2.21220	validation-mlogloss:2.16968
[60]	train-mlogloss:2.20756	validation-mlogloss:2.16510
[61]	train-mlogloss:2.20289	validation-mlogloss:2.16089
[62]	train-mlogloss:2.19806	validation-mlogloss:2.15617
[63]	train-mlogloss:2.19336	validation-mlogloss:2.15203
[64]	train-mlogloss:2.18900	validation-mlogloss:2.14762
[65]	train-mlogloss:2.18443	validation-mlogloss:2.14320
[66]	train-mlogloss:2.17993	validation-mlogloss:2.13876
[67]	train-mlogloss:2.17540	validation-mlogloss:2.13396
[68]	train-mlogloss:2.17083	validation-mlogloss:2.12904
[69]	train-mlogloss:2.16672	validation-mlogloss:2.12463
[70]	train-mlogloss:2.16214	validation-mlogloss:2.12051
[71]	train-mlogloss:2.15772	validation-mlogloss:2.11607
[72]	train-mlogloss:2.15351	validation-mlogloss:2.11215
[73]	train-mlogloss:2.14952	validation-mlogloss:2.10814
[74]	train-mlogloss:2.14543	validation-mlogloss:2.10393
[75]	train-mlogloss:2.14147	validation-mlogloss:2.10016
[76]	train-mlogloss:2.13759	validation-mlogloss:2.09635
[77]	train-mlogloss:2.13375	validation-mlogloss:2.09260
[78]	train-mlogloss:2.12973	validation-mlogloss:2.08858
[79]	train-mlogloss:2.12567	validation-mlogloss:2.08459
[80]	train-mlogloss:2.12191	validation-mlogloss:2.08121
[81]	train-mlogloss:2.11809	validation-mlogloss:2.07773
[82]	train-mlogloss:2.11439	validation-mlogloss:2.07398
[83]	train-mlogloss:2.11074	validation-mlogloss:2.07011
[84]	train-mlogloss:2.10712	validation-mlogloss:2.06683
[85]	train-mlogloss:2.10329	validation-mlogloss:2.06323
[86]	train-mlogloss:2.09963	validation-mlogloss:2.05986
[87]	train-mlogloss:2.09616	validation-mlogloss:2.05630
[88]	train-mlogloss:2.09253	validation-mlogloss:2.05256
[89]	train-mlogloss:2.08926	validation-mlogloss:2.04961
[90]	train-mlogloss:2.08594	validation-mlogloss:2.04638
[91]	train-mlogloss:2.08254	validation-mlogloss:2.04274
[92]	train-mlogloss:2.07928	validation-mlogloss:2.03965
[93]	train-mlogloss:2.07594	validation-mlogloss:2.03662
[94]	train-mlogloss:2.07256	validation-mlogloss:2.03354
[95]	train-mlogloss:2.06922	validation-mlogloss:2.03041
[96]	train-mlogloss:2.06597	validation-mlogloss:2.02741
[97]	train-mlogloss:2.06291	validation-mlogloss:2.02442
[98]	train-mlogloss:2.05977	validation-mlogloss:2.02167
[99]	train-mlogloss:2.05679	validation-mlogloss:2.01875
[100]	train-mlogloss:2.05367	validation-mlogloss:2.01600
[101]	train-mlogloss:2.05062	validation-mlogloss:2.01328
[102]	train-mlogloss:2.04752	validation-mlogloss:2.01024
[103]	train-mlogloss:2.04441	validation-mlogloss:2.00712
[104]	train-mlogloss:2.04118	validation-mlogloss:2.00415
[105]	train-mlogloss:2.03806	validation-mlogloss:2.00114
[106]	train-mlogloss:2.03511	validation-mlogloss:1.99825
[107]	train-mlogloss:2.03219	validation-mlogloss:1.99515
[108]	train-mlogloss:2.02934	validation-mlogloss:1.99260
[109]	train-mlogloss:2.02632	validation-mlogloss:1.98985
[110]	train-mlogloss:2.02334	validation-mlogloss:1.98690
[111]	train-mlogloss:2.02036	validation-mlogloss:1.98447
[112]	train-mlogloss:2.01764	validation-mlogloss:1.98199
[113]	train-mlogloss:2.01490	validation-mlogloss:1.97963
[114]	train-mlogloss:2.01196	validation-mlogloss:1.97688
[115]	train-mlogloss:2.00929	validation-mlogloss:1.97464
[116]	train-mlogloss:2.00670	validation-mlogloss:1.97247
[117]	train-mlogloss:2.00388	validation-mlogloss:1.96960
[118]	train-mlogloss:2.00134	validation-mlogloss:1.96715
[119]	train-mlogloss:1.99875	validation-mlogloss:1.96481
[120]	train-mlogloss:1.99620	validation-mlogloss:1.96249
[121]	train-mlogloss:1.99369	validation-mlogloss:1.96002
[122]	train-mlogloss:1.99117	validation-mlogloss:1.95762
[123]	train-mlogloss:1.98857	validation-mlogloss:1.95493
[124]	train-mlogloss:1.98595	validation-mlogloss:1.95233
[125]	train-mlogloss:1.98346	validation-mlogloss:1.95001
[126]	train-mlogloss:1.98109	validation-mlogloss:1.94781
[127]	train-mlogloss:1.97853	validation-mlogloss:1.94541
[128]	train-mlogloss:1.97604	validation-mlogloss:1.94332
[129]	train-mlogloss:1.97362	validation-mlogloss:1.94117
[130]	train-mlogloss:1.97099	validation-mlogloss:1.93883
[131]	train-mlogloss:1.96851	validation-mlogloss:1.93643
[132]	train-mlogloss:1.96612	validation-mlogloss:1.93428
[133]	train-mlogloss:1.96377	validation-mlogloss:1.93204
[134]	train-mlogloss:1.96130	validation-mlogloss:1.92990
[135]	train-mlogloss:1.95917	validation-mlogloss:1.92821
[136]	train-mlogloss:1.95692	validation-mlogloss:1.92672
[137]	train-mlogloss:1.95465	validation-mlogloss:1.92473
[138]	train-mlogloss:1.95243	validation-mlogloss:1.92284
[139]	train-mlogloss:1.95015	validation-mlogloss:1.92078
[140]	train-mlogloss:1.94781	validation-mlogloss:1.91873
[141]	train-mlogloss:1.94561	validation-mlogloss:1.91692
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[447]	train-mlogloss:1.60817	validation-mlogloss:1.70000
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[449]	train-mlogloss:1.60692	validation-mlogloss:1.69982
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[466]	train-mlogloss:1.59707	validation-mlogloss:1.69642
[467]	train-mlogloss:1.59661	validation-mlogloss:1.69622
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[470]	train-mlogloss:1.59488	validation-mlogloss:1.69536
[471]	train-mlogloss:1.59427	validation-mlogloss:1.69517
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[476]	train-mlogloss:1.59136	validation-mlogloss:1.69411
[477]	train-mlogloss:1.59087	validation-mlogloss:1.69406
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[490]	train-mlogloss:1.58393	validation-mlogloss:1.69237
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[499]	train-mlogloss:1.57909	validation-mlogloss:1.69104
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[503]	train-mlogloss:1.57703	validation-mlogloss:1.69014
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[505]	train-mlogloss:1.57603	validation-mlogloss:1.68964
[506]	train-mlogloss:1.57558	validation-mlogloss:1.68938
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[508]	train-mlogloss:1.57450	validation-mlogloss:1.68904
[509]	train-mlogloss:1.57404	validation-mlogloss:1.68877
[510]	train-mlogloss:1.57357	validation-mlogloss:1.68876
[511]	train-mlogloss:1.57304	validation-mlogloss:1.68857
[512]	train-mlogloss:1.57264	validation-mlogloss:1.68842
[513]	train-mlogloss:1.57221	validation-mlogloss:1.68843
[514]	train-mlogloss:1.57176	validation-mlogloss:1.68845
[515]	train-mlogloss:1.57126	validation-mlogloss:1.68833
[516]	train-mlogloss:1.57081	validation-mlogloss:1.68835
[517]	train-mlogloss:1.57028	validation-mlogloss:1.68834
[518]	train-mlogloss:1.56973	validation-mlogloss:1.68823
[519]	train-mlogloss:1.56931	validation-mlogloss:1.68815
[520]	train-mlogloss:1.56873	validation-mlogloss:1.68810
[521]	train-mlogloss:1.56825	validation-mlogloss:1.68780
[522]	train-mlogloss:1.56781	validation-mlogloss:1.68778
[523]	train-mlogloss:1.56736	validation-mlogloss:1.68762
[524]	train-mlogloss:1.56685	validation-mlogloss:1.68743
[525]	train-mlogloss:1.56635	validation-mlogloss:1.68744
[526]	train-mlogloss:1.56588	validation-mlogloss:1.68711
[527]	train-mlogloss:1.56548	validation-mlogloss:1.68692
[528]	train-mlogloss:1.56492	validation-mlogloss:1.68669
[529]	train-mlogloss:1.56441	validation-mlogloss:1.68640
[530]	train-mlogloss:1.56405	validation-mlogloss:1.68630
[531]	train-mlogloss:1.56357	validation-mlogloss:1.68640
[532]	train-mlogloss:1.56312	validation-mlogloss:1.68641
[533]	train-mlogloss:1.56261	validation-mlogloss:1.68623
[534]	train-mlogloss:1.56217	validation-mlogloss:1.68603
[535]	train-mlogloss:1.56166	validation-mlogloss:1.68594
[536]	train-mlogloss:1.56127	validation-mlogloss:1.68584
[537]	train-mlogloss:1.56084	validation-mlogloss:1.68586
[538]	train-mlogloss:1.56042	validation-mlogloss:1.68576
[539]	train-mlogloss:1.55995	validation-mlogloss:1.68556
Saved model to disk.
2025-10-27 09:51:37.443450: 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`.
2025-10-27 09:51:37.456046: 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 00:00:1761555097.469713  420370 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555097.474235  420370 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555097.485277  420370 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555097.485302  420370 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555097.485307  420370 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555097.485311  420370 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:51:37.488725: 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:2.67907	validation-mlogloss:2.67638
[2]	train-mlogloss:2.66521	validation-mlogloss:2.66165
[3]	train-mlogloss:2.65234	validation-mlogloss:2.64706
[4]	train-mlogloss:2.64029	validation-mlogloss:2.63345
[5]	train-mlogloss:2.62654	validation-mlogloss:2.61740
[6]	train-mlogloss:2.61452	validation-mlogloss:2.60329
[7]	train-mlogloss:2.60253	validation-mlogloss:2.58992
[8]	train-mlogloss:2.59088	validation-mlogloss:2.57729
[9]	train-mlogloss:2.57874	validation-mlogloss:2.56342
[10]	train-mlogloss:2.56766	validation-mlogloss:2.55144
[11]	train-mlogloss:2.55690	validation-mlogloss:2.53995
[12]	train-mlogloss:2.54605	validation-mlogloss:2.52772
[13]	train-mlogloss:2.53543	validation-mlogloss:2.51656
[14]	train-mlogloss:2.52527	validation-mlogloss:2.50572
[15]	train-mlogloss:2.51538	validation-mlogloss:2.49497
[16]	train-mlogloss:2.50523	validation-mlogloss:2.48396
[17]	train-mlogloss:2.49541	validation-mlogloss:2.47300
[18]	train-mlogloss:2.48660	validation-mlogloss:2.46298
[19]	train-mlogloss:2.47752	validation-mlogloss:2.45261
[20]	train-mlogloss:2.46868	validation-mlogloss:2.44246
[21]	train-mlogloss:2.45957	validation-mlogloss:2.43244
[22]	train-mlogloss:2.45083	validation-mlogloss:2.42260
[23]	train-mlogloss:2.44233	validation-mlogloss:2.41325
[24]	train-mlogloss:2.43373	validation-mlogloss:2.40334
[25]	train-mlogloss:2.42507	validation-mlogloss:2.39365
[26]	train-mlogloss:2.41706	validation-mlogloss:2.38513
[27]	train-mlogloss:2.40944	validation-mlogloss:2.37688
[28]	train-mlogloss:2.40150	validation-mlogloss:2.36808
[29]	train-mlogloss:2.39419	validation-mlogloss:2.35968
[30]	train-mlogloss:2.38657	validation-mlogloss:2.35168
[31]	train-mlogloss:2.37932	validation-mlogloss:2.34414
[32]	train-mlogloss:2.37223	validation-mlogloss:2.33671
[33]	train-mlogloss:2.36501	validation-mlogloss:2.32889
[34]	train-mlogloss:2.35782	validation-mlogloss:2.32159
[35]	train-mlogloss:2.35079	validation-mlogloss:2.31374
[36]	train-mlogloss:2.34444	validation-mlogloss:2.30714
[37]	train-mlogloss:2.33729	validation-mlogloss:2.29951
[38]	train-mlogloss:2.33069	validation-mlogloss:2.29254
[39]	train-mlogloss:2.32422	validation-mlogloss:2.28580
[40]	train-mlogloss:2.31812	validation-mlogloss:2.27871
[41]	train-mlogloss:2.31218	validation-mlogloss:2.27274
[42]	train-mlogloss:2.30631	validation-mlogloss:2.26678
[43]	train-mlogloss:2.29988	validation-mlogloss:2.26025
[44]	train-mlogloss:2.29377	validation-mlogloss:2.25436
[45]	train-mlogloss:2.28792	validation-mlogloss:2.24842
[46]	train-mlogloss:2.28196	validation-mlogloss:2.24243
[47]	train-mlogloss:2.27593	validation-mlogloss:2.23640
[48]	train-mlogloss:2.27030	validation-mlogloss:2.23059
[49]	train-mlogloss:2.26459	validation-mlogloss:2.22469
[50]	train-mlogloss:2.25918	validation-mlogloss:2.21943
[51]	train-mlogloss:2.25387	validation-mlogloss:2.21371
[52]	train-mlogloss:2.24854	validation-mlogloss:2.20840
[53]	train-mlogloss:2.24315	validation-mlogloss:2.20296
[54]	train-mlogloss:2.23776	validation-mlogloss:2.19755
[55]	train-mlogloss:2.23231	validation-mlogloss:2.19215
[56]	train-mlogloss:2.22712	validation-mlogloss:2.18642
[57]	train-mlogloss:2.22216	validation-mlogloss:2.18139
[58]	train-mlogloss:2.21710	validation-mlogloss:2.17614
[59]	train-mlogloss:2.21236	validation-mlogloss:2.17104
[60]	train-mlogloss:2.20757	validation-mlogloss:2.16621
[61]	train-mlogloss:2.20292	validation-mlogloss:2.16168
[62]	train-mlogloss:2.19832	validation-mlogloss:2.15663
[63]	train-mlogloss:2.19345	validation-mlogloss:2.15180
[64]	train-mlogloss:2.18897	validation-mlogloss:2.14718
[65]	train-mlogloss:2.18422	validation-mlogloss:2.14243
[66]	train-mlogloss:2.17938	validation-mlogloss:2.13720
[67]	train-mlogloss:2.17499	validation-mlogloss:2.13301
[68]	train-mlogloss:2.17045	validation-mlogloss:2.12851
[69]	train-mlogloss:2.16611	validation-mlogloss:2.12405
[70]	train-mlogloss:2.16166	validation-mlogloss:2.11969
[71]	train-mlogloss:2.15750	validation-mlogloss:2.11554
[72]	train-mlogloss:2.15327	validation-mlogloss:2.11173
[73]	train-mlogloss:2.14914	validation-mlogloss:2.10745
[74]	train-mlogloss:2.14499	validation-mlogloss:2.10339
[75]	train-mlogloss:2.14068	validation-mlogloss:2.09911
[76]	train-mlogloss:2.13659	validation-mlogloss:2.09517
[77]	train-mlogloss:2.13281	validation-mlogloss:2.09159
[78]	train-mlogloss:2.12864	validation-mlogloss:2.08775
[79]	train-mlogloss:2.12486	validation-mlogloss:2.08426
[80]	train-mlogloss:2.12093	validation-mlogloss:2.08061
[81]	train-mlogloss:2.11706	validation-mlogloss:2.07710
[82]	train-mlogloss:2.11338	validation-mlogloss:2.07339
[83]	train-mlogloss:2.10980	validation-mlogloss:2.06999
[84]	train-mlogloss:2.10589	validation-mlogloss:2.06628
[85]	train-mlogloss:2.10215	validation-mlogloss:2.06241
[86]	train-mlogloss:2.09866	validation-mlogloss:2.05927
[87]	train-mlogloss:2.09532	validation-mlogloss:2.05615
[88]	train-mlogloss:2.09169	validation-mlogloss:2.05282
[89]	train-mlogloss:2.08817	validation-mlogloss:2.04936
[90]	train-mlogloss:2.08492	validation-mlogloss:2.04625
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[92]	train-mlogloss:2.07810	validation-mlogloss:2.04012
[93]	train-mlogloss:2.07479	validation-mlogloss:2.03709
[94]	train-mlogloss:2.07126	validation-mlogloss:2.03371
[95]	train-mlogloss:2.06800	validation-mlogloss:2.03047
[96]	train-mlogloss:2.06453	validation-mlogloss:2.02691
[97]	train-mlogloss:2.06121	validation-mlogloss:2.02350
[98]	train-mlogloss:2.05802	validation-mlogloss:2.02044
[99]	train-mlogloss:2.05467	validation-mlogloss:2.01713
[100]	train-mlogloss:2.05155	validation-mlogloss:2.01421
[101]	train-mlogloss:2.04845	validation-mlogloss:2.01131
[102]	train-mlogloss:2.04526	validation-mlogloss:2.00795
[103]	train-mlogloss:2.04202	validation-mlogloss:2.00517
[104]	train-mlogloss:2.03882	validation-mlogloss:2.00195
[105]	train-mlogloss:2.03546	validation-mlogloss:1.99877
[106]	train-mlogloss:2.03245	validation-mlogloss:1.99633
[107]	train-mlogloss:2.02951	validation-mlogloss:1.99361
[108]	train-mlogloss:2.02665	validation-mlogloss:1.99083
[109]	train-mlogloss:2.02381	validation-mlogloss:1.98829
[110]	train-mlogloss:2.02106	validation-mlogloss:1.98588
[111]	train-mlogloss:2.01818	validation-mlogloss:1.98351
[112]	train-mlogloss:2.01547	validation-mlogloss:1.98099
[113]	train-mlogloss:2.01272	validation-mlogloss:1.97826
[114]	train-mlogloss:2.00998	validation-mlogloss:1.97572
[115]	train-mlogloss:2.00715	validation-mlogloss:1.97308
[116]	train-mlogloss:2.00449	validation-mlogloss:1.97083
[117]	train-mlogloss:2.00174	validation-mlogloss:1.96831
[118]	train-mlogloss:1.99919	validation-mlogloss:1.96581
[119]	train-mlogloss:1.99652	validation-mlogloss:1.96326
[120]	train-mlogloss:1.99395	validation-mlogloss:1.96069
[121]	train-mlogloss:1.99138	validation-mlogloss:1.95827
[122]	train-mlogloss:1.98894	validation-mlogloss:1.95645
[123]	train-mlogloss:1.98627	validation-mlogloss:1.95384
[124]	train-mlogloss:1.98370	validation-mlogloss:1.95160
[125]	train-mlogloss:1.98130	validation-mlogloss:1.94953
[126]	train-mlogloss:1.97898	validation-mlogloss:1.94733
[127]	train-mlogloss:1.97662	validation-mlogloss:1.94561
[128]	train-mlogloss:1.97415	validation-mlogloss:1.94314
[129]	train-mlogloss:1.97163	validation-mlogloss:1.94068
[130]	train-mlogloss:1.96931	validation-mlogloss:1.93876
[131]	train-mlogloss:1.96676	validation-mlogloss:1.93655
[132]	train-mlogloss:1.96441	validation-mlogloss:1.93461
[133]	train-mlogloss:1.96206	validation-mlogloss:1.93280
[134]	train-mlogloss:1.95971	validation-mlogloss:1.93101
[135]	train-mlogloss:1.95747	validation-mlogloss:1.92910
[136]	train-mlogloss:1.95521	validation-mlogloss:1.92691
[137]	train-mlogloss:1.95308	validation-mlogloss:1.92503
[138]	train-mlogloss:1.95072	validation-mlogloss:1.92265
[139]	train-mlogloss:1.94857	validation-mlogloss:1.92082
[140]	train-mlogloss:1.94644	validation-mlogloss:1.91879
[141]	train-mlogloss:1.94439	validation-mlogloss:1.91714
[142]	train-mlogloss:1.94222	validation-mlogloss:1.91502
[143]	train-mlogloss:1.94019	validation-mlogloss:1.91310
[144]	train-mlogloss:1.93796	validation-mlogloss:1.91117
[145]	train-mlogloss:1.93581	validation-mlogloss:1.90949
[146]	train-mlogloss:1.93374	validation-mlogloss:1.90767
[147]	train-mlogloss:1.93172	validation-mlogloss:1.90605
[148]	train-mlogloss:1.92958	validation-mlogloss:1.90391
[149]	train-mlogloss:1.92746	validation-mlogloss:1.90230
[150]	train-mlogloss:1.92552	validation-mlogloss:1.90054
[151]	train-mlogloss:1.92349	validation-mlogloss:1.89913
[152]	train-mlogloss:1.92156	validation-mlogloss:1.89740
[153]	train-mlogloss:1.91951	validation-mlogloss:1.89544
[154]	train-mlogloss:1.91731	validation-mlogloss:1.89367
[155]	train-mlogloss:1.91542	validation-mlogloss:1.89195
[156]	train-mlogloss:1.91351	validation-mlogloss:1.89038
[157]	train-mlogloss:1.91154	validation-mlogloss:1.88887
[158]	train-mlogloss:1.90966	validation-mlogloss:1.88721
[159]	train-mlogloss:1.90768	validation-mlogloss:1.88542
[160]	train-mlogloss:1.90580	validation-mlogloss:1.88390
[161]	train-mlogloss:1.90393	validation-mlogloss:1.88237
[162]	train-mlogloss:1.90190	validation-mlogloss:1.88072
[163]	train-mlogloss:1.90005	validation-mlogloss:1.87920
[164]	train-mlogloss:1.89828	validation-mlogloss:1.87754
[165]	train-mlogloss:1.89633	validation-mlogloss:1.87601
[166]	train-mlogloss:1.89444	validation-mlogloss:1.87442
[167]	train-mlogloss:1.89242	validation-mlogloss:1.87276
[168]	train-mlogloss:1.89051	validation-mlogloss:1.87123
[169]	train-mlogloss:1.88863	validation-mlogloss:1.86971
[170]	train-mlogloss:1.88682	validation-mlogloss:1.86817
[171]	train-mlogloss:1.88487	validation-mlogloss:1.86641
[172]	train-mlogloss:1.88298	validation-mlogloss:1.86484
[173]	train-mlogloss:1.88119	validation-mlogloss:1.86308
[174]	train-mlogloss:1.87931	validation-mlogloss:1.86155
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[476]	train-mlogloss:1.58974	validation-mlogloss:1.69479
[477]	train-mlogloss:1.58909	validation-mlogloss:1.69455
[478]	train-mlogloss:1.58852	validation-mlogloss:1.69403
[479]	train-mlogloss:1.58792	validation-mlogloss:1.69387
[480]	train-mlogloss:1.58737	validation-mlogloss:1.69367
[481]	train-mlogloss:1.58691	validation-mlogloss:1.69338
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[483]	train-mlogloss:1.58588	validation-mlogloss:1.69308
[484]	train-mlogloss:1.58525	validation-mlogloss:1.69269
[485]	train-mlogloss:1.58476	validation-mlogloss:1.69250
[486]	train-mlogloss:1.58426	validation-mlogloss:1.69232
[487]	train-mlogloss:1.58387	validation-mlogloss:1.69216
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[489]	train-mlogloss:1.58290	validation-mlogloss:1.69177
[490]	train-mlogloss:1.58235	validation-mlogloss:1.69171
[491]	train-mlogloss:1.58172	validation-mlogloss:1.69159
[492]	train-mlogloss:1.58123	validation-mlogloss:1.69129
[493]	train-mlogloss:1.58074	validation-mlogloss:1.69101
[494]	train-mlogloss:1.58030	validation-mlogloss:1.69080
[495]	train-mlogloss:1.57975	validation-mlogloss:1.69049
[496]	train-mlogloss:1.57922	validation-mlogloss:1.69025
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[498]	train-mlogloss:1.57823	validation-mlogloss:1.69019
[499]	train-mlogloss:1.57778	validation-mlogloss:1.68992
[500]	train-mlogloss:1.57725	validation-mlogloss:1.68981
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[503]	train-mlogloss:1.57576	validation-mlogloss:1.68968
[504]	train-mlogloss:1.57525	validation-mlogloss:1.68963
[505]	train-mlogloss:1.57463	validation-mlogloss:1.68953
[506]	train-mlogloss:1.57417	validation-mlogloss:1.68955
[507]	train-mlogloss:1.57369	validation-mlogloss:1.68939
[508]	train-mlogloss:1.57321	validation-mlogloss:1.68918
[509]	train-mlogloss:1.57276	validation-mlogloss:1.68894
[510]	train-mlogloss:1.57231	validation-mlogloss:1.68897
[511]	train-mlogloss:1.57185	validation-mlogloss:1.68899
[512]	train-mlogloss:1.57135	validation-mlogloss:1.68881
[513]	train-mlogloss:1.57089	validation-mlogloss:1.68869
[514]	train-mlogloss:1.57036	validation-mlogloss:1.68842
[515]	train-mlogloss:1.56980	validation-mlogloss:1.68842
[516]	train-mlogloss:1.56925	validation-mlogloss:1.68841
[517]	train-mlogloss:1.56876	validation-mlogloss:1.68843
[518]	train-mlogloss:1.56822	validation-mlogloss:1.68824
[519]	train-mlogloss:1.56773	validation-mlogloss:1.68815
[520]	train-mlogloss:1.56728	validation-mlogloss:1.68819
[521]	train-mlogloss:1.56679	validation-mlogloss:1.68812
[522]	train-mlogloss:1.56631	validation-mlogloss:1.68793
[523]	train-mlogloss:1.56584	validation-mlogloss:1.68777
[524]	train-mlogloss:1.56537	validation-mlogloss:1.68752
[525]	train-mlogloss:1.56482	validation-mlogloss:1.68740
[526]	train-mlogloss:1.56435	validation-mlogloss:1.68738
[527]	train-mlogloss:1.56388	validation-mlogloss:1.68725
[528]	train-mlogloss:1.56338	validation-mlogloss:1.68714
[529]	train-mlogloss:1.56296	validation-mlogloss:1.68712
[530]	train-mlogloss:1.56253	validation-mlogloss:1.68685
[531]	train-mlogloss:1.56201	validation-mlogloss:1.68679
[532]	train-mlogloss:1.56151	validation-mlogloss:1.68678
[533]	train-mlogloss:1.56110	validation-mlogloss:1.68648
[534]	train-mlogloss:1.56063	validation-mlogloss:1.68617
[535]	train-mlogloss:1.56020	validation-mlogloss:1.68598
[536]	train-mlogloss:1.55978	validation-mlogloss:1.68581
[537]	train-mlogloss:1.55931	validation-mlogloss:1.68570
[538]	train-mlogloss:1.55898	validation-mlogloss:1.68570
[539]	train-mlogloss:1.55853	validation-mlogloss:1.68566
Saved model to disk.
2025-10-27 09:52:23.447503: 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`.
2025-10-27 09:52:23.460047: 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 00:00:1761555143.473452  421278 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555143.477731  421278 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555143.488693  421278 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555143.488716  421278 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555143.488719  421278 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555143.488722  421278 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:52:23.492002: 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:2.68036	validation-mlogloss:2.67746
[2]	train-mlogloss:2.66646	validation-mlogloss:2.66163
[3]	train-mlogloss:2.65393	validation-mlogloss:2.64790
[4]	train-mlogloss:2.64108	validation-mlogloss:2.63316
[5]	train-mlogloss:2.62948	validation-mlogloss:2.61929
[6]	train-mlogloss:2.61686	validation-mlogloss:2.60638
[7]	train-mlogloss:2.60402	validation-mlogloss:2.59137
[8]	train-mlogloss:2.59167	validation-mlogloss:2.57690
[9]	train-mlogloss:2.58055	validation-mlogloss:2.56483
[10]	train-mlogloss:2.56859	validation-mlogloss:2.55097
[11]	train-mlogloss:2.55796	validation-mlogloss:2.53901
[12]	train-mlogloss:2.54711	validation-mlogloss:2.52688
[13]	train-mlogloss:2.53706	validation-mlogloss:2.51633
[14]	train-mlogloss:2.52739	validation-mlogloss:2.50450
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[16]	train-mlogloss:2.50724	validation-mlogloss:2.48210
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[19]	train-mlogloss:2.47944	validation-mlogloss:2.45189
[20]	train-mlogloss:2.46983	validation-mlogloss:2.44141
[21]	train-mlogloss:2.46059	validation-mlogloss:2.43116
[22]	train-mlogloss:2.45170	validation-mlogloss:2.42136
[23]	train-mlogloss:2.44308	validation-mlogloss:2.41224
[24]	train-mlogloss:2.43489	validation-mlogloss:2.40372
[25]	train-mlogloss:2.42705	validation-mlogloss:2.39471
[26]	train-mlogloss:2.41933	validation-mlogloss:2.38658
[27]	train-mlogloss:2.41132	validation-mlogloss:2.37862
[28]	train-mlogloss:2.40370	validation-mlogloss:2.36979
[29]	train-mlogloss:2.39600	validation-mlogloss:2.36109
[30]	train-mlogloss:2.38844	validation-mlogloss:2.35324
[31]	train-mlogloss:2.38096	validation-mlogloss:2.34524
[32]	train-mlogloss:2.37419	validation-mlogloss:2.33737
[33]	train-mlogloss:2.36695	validation-mlogloss:2.32965
[34]	train-mlogloss:2.35967	validation-mlogloss:2.32164
[35]	train-mlogloss:2.35297	validation-mlogloss:2.31427
[36]	train-mlogloss:2.34650	validation-mlogloss:2.30754
[37]	train-mlogloss:2.33994	validation-mlogloss:2.30067
[38]	train-mlogloss:2.33314	validation-mlogloss:2.29316
[39]	train-mlogloss:2.32689	validation-mlogloss:2.28640
[40]	train-mlogloss:2.32048	validation-mlogloss:2.27946
[41]	train-mlogloss:2.31404	validation-mlogloss:2.27211
[42]	train-mlogloss:2.30808	validation-mlogloss:2.26556
[43]	train-mlogloss:2.30231	validation-mlogloss:2.25904
[44]	train-mlogloss:2.29608	validation-mlogloss:2.25224
[45]	train-mlogloss:2.29039	validation-mlogloss:2.24595
[46]	train-mlogloss:2.28441	validation-mlogloss:2.23989
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[48]	train-mlogloss:2.27316	validation-mlogloss:2.22882
[49]	train-mlogloss:2.26752	validation-mlogloss:2.22296
[50]	train-mlogloss:2.26204	validation-mlogloss:2.21749
[51]	train-mlogloss:2.25636	validation-mlogloss:2.21147
[52]	train-mlogloss:2.25073	validation-mlogloss:2.20580
[53]	train-mlogloss:2.24552	validation-mlogloss:2.20037
[54]	train-mlogloss:2.24019	validation-mlogloss:2.19511
[55]	train-mlogloss:2.23505	validation-mlogloss:2.19004
[56]	train-mlogloss:2.22948	validation-mlogloss:2.18444
[57]	train-mlogloss:2.22460	validation-mlogloss:2.17916
[58]	train-mlogloss:2.21968	validation-mlogloss:2.17447
[59]	train-mlogloss:2.21504	validation-mlogloss:2.16923
[60]	train-mlogloss:2.20981	validation-mlogloss:2.16374
[61]	train-mlogloss:2.20491	validation-mlogloss:2.15805
[62]	train-mlogloss:2.20025	validation-mlogloss:2.15403
[63]	train-mlogloss:2.19556	validation-mlogloss:2.14967
[64]	train-mlogloss:2.19100	validation-mlogloss:2.14526
[65]	train-mlogloss:2.18635	validation-mlogloss:2.14070
[66]	train-mlogloss:2.18171	validation-mlogloss:2.13584
[67]	train-mlogloss:2.17738	validation-mlogloss:2.13180
[68]	train-mlogloss:2.17307	validation-mlogloss:2.12771
[69]	train-mlogloss:2.16874	validation-mlogloss:2.12314
[70]	train-mlogloss:2.16438	validation-mlogloss:2.11876
[71]	train-mlogloss:2.15990	validation-mlogloss:2.11452
[72]	train-mlogloss:2.15574	validation-mlogloss:2.11031
[73]	train-mlogloss:2.15122	validation-mlogloss:2.10587
[74]	train-mlogloss:2.14714	validation-mlogloss:2.10144
[75]	train-mlogloss:2.14317	validation-mlogloss:2.09753
[76]	train-mlogloss:2.13888	validation-mlogloss:2.09340
[77]	train-mlogloss:2.13473	validation-mlogloss:2.08926
[78]	train-mlogloss:2.13076	validation-mlogloss:2.08500
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[83]	train-mlogloss:2.11126	validation-mlogloss:2.06600
[84]	train-mlogloss:2.10750	validation-mlogloss:2.06253
[85]	train-mlogloss:2.10375	validation-mlogloss:2.05916
[86]	train-mlogloss:2.10011	validation-mlogloss:2.05521
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[95]	train-mlogloss:2.06925	validation-mlogloss:2.02533
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[99]	train-mlogloss:2.05620	validation-mlogloss:2.01321
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[101]	train-mlogloss:2.04999	validation-mlogloss:2.00729
[102]	train-mlogloss:2.04679	validation-mlogloss:2.00407
[103]	train-mlogloss:2.04377	validation-mlogloss:2.00140
[104]	train-mlogloss:2.04076	validation-mlogloss:1.99840
[105]	train-mlogloss:2.03779	validation-mlogloss:1.99559
[106]	train-mlogloss:2.03471	validation-mlogloss:1.99281
[107]	train-mlogloss:2.03179	validation-mlogloss:1.99011
[108]	train-mlogloss:2.02900	validation-mlogloss:1.98752
[109]	train-mlogloss:2.02607	validation-mlogloss:1.98471
[110]	train-mlogloss:2.02320	validation-mlogloss:1.98217
[111]	train-mlogloss:2.02026	validation-mlogloss:1.97916
[112]	train-mlogloss:2.01735	validation-mlogloss:1.97648
[113]	train-mlogloss:2.01468	validation-mlogloss:1.97384
[114]	train-mlogloss:2.01192	validation-mlogloss:1.97169
[115]	train-mlogloss:2.00929	validation-mlogloss:1.96961
[116]	train-mlogloss:2.00676	validation-mlogloss:1.96754
[117]	train-mlogloss:2.00408	validation-mlogloss:1.96493
[118]	train-mlogloss:2.00152	validation-mlogloss:1.96310
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[122]	train-mlogloss:1.99104	validation-mlogloss:1.95381
[123]	train-mlogloss:1.98838	validation-mlogloss:1.95125
[124]	train-mlogloss:1.98582	validation-mlogloss:1.94868
[125]	train-mlogloss:1.98334	validation-mlogloss:1.94657
[126]	train-mlogloss:1.98079	validation-mlogloss:1.94436
[127]	train-mlogloss:1.97823	validation-mlogloss:1.94203
[128]	train-mlogloss:1.97571	validation-mlogloss:1.94036
[129]	train-mlogloss:1.97328	validation-mlogloss:1.93794
[130]	train-mlogloss:1.97080	validation-mlogloss:1.93555
[131]	train-mlogloss:1.96824	validation-mlogloss:1.93323
[132]	train-mlogloss:1.96561	validation-mlogloss:1.93075
[133]	train-mlogloss:1.96338	validation-mlogloss:1.92889
[134]	train-mlogloss:1.96095	validation-mlogloss:1.92663
[135]	train-mlogloss:1.95868	validation-mlogloss:1.92495
[136]	train-mlogloss:1.95640	validation-mlogloss:1.92312
[137]	train-mlogloss:1.95409	validation-mlogloss:1.92116
[138]	train-mlogloss:1.95198	validation-mlogloss:1.91948
[139]	train-mlogloss:1.94972	validation-mlogloss:1.91743
[140]	train-mlogloss:1.94742	validation-mlogloss:1.91531
[141]	train-mlogloss:1.94532	validation-mlogloss:1.91367
[142]	train-mlogloss:1.94316	validation-mlogloss:1.91168
[143]	train-mlogloss:1.94092	validation-mlogloss:1.90981
[144]	train-mlogloss:1.93868	validation-mlogloss:1.90798
[145]	train-mlogloss:1.93657	validation-mlogloss:1.90616
[146]	train-mlogloss:1.93444	validation-mlogloss:1.90435
[147]	train-mlogloss:1.93229	validation-mlogloss:1.90251
[148]	train-mlogloss:1.93001	validation-mlogloss:1.90038
[149]	train-mlogloss:1.92787	validation-mlogloss:1.89857
[150]	train-mlogloss:1.92566	validation-mlogloss:1.89672
[151]	train-mlogloss:1.92349	validation-mlogloss:1.89493
[152]	train-mlogloss:1.92103	validation-mlogloss:1.89273
[153]	train-mlogloss:1.91904	validation-mlogloss:1.89118
[154]	train-mlogloss:1.91695	validation-mlogloss:1.88968
[155]	train-mlogloss:1.91480	validation-mlogloss:1.88758
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[157]	train-mlogloss:1.91089	validation-mlogloss:1.88432
[158]	train-mlogloss:1.90894	validation-mlogloss:1.88265
[159]	train-mlogloss:1.90687	validation-mlogloss:1.88082
[160]	train-mlogloss:1.90499	validation-mlogloss:1.87946
[161]	train-mlogloss:1.90308	validation-mlogloss:1.87785
[162]	train-mlogloss:1.90110	validation-mlogloss:1.87606
[163]	train-mlogloss:1.89919	validation-mlogloss:1.87427
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[191]	train-mlogloss:1.85058	validation-mlogloss:1.83602
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[193]	train-mlogloss:1.84744	validation-mlogloss:1.83346
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[199]	train-mlogloss:1.83821	validation-mlogloss:1.82683
[200]	train-mlogloss:1.83670	validation-mlogloss:1.82578
[201]	train-mlogloss:1.83518	validation-mlogloss:1.82491
[202]	train-mlogloss:1.83359	validation-mlogloss:1.82367
[203]	train-mlogloss:1.83213	validation-mlogloss:1.82269
[204]	train-mlogloss:1.83044	validation-mlogloss:1.82127
[205]	train-mlogloss:1.82895	validation-mlogloss:1.82038
[206]	train-mlogloss:1.82744	validation-mlogloss:1.81910
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[208]	train-mlogloss:1.82432	validation-mlogloss:1.81695
[209]	train-mlogloss:1.82293	validation-mlogloss:1.81590
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[511]	train-mlogloss:1.57255	validation-mlogloss:1.68756
[512]	train-mlogloss:1.57206	validation-mlogloss:1.68735
[513]	train-mlogloss:1.57162	validation-mlogloss:1.68721
[514]	train-mlogloss:1.57101	validation-mlogloss:1.68717
[515]	train-mlogloss:1.57043	validation-mlogloss:1.68721
[516]	train-mlogloss:1.56993	validation-mlogloss:1.68707
[517]	train-mlogloss:1.56946	validation-mlogloss:1.68677
[518]	train-mlogloss:1.56895	validation-mlogloss:1.68638
[519]	train-mlogloss:1.56851	validation-mlogloss:1.68628
[520]	train-mlogloss:1.56805	validation-mlogloss:1.68602
[521]	train-mlogloss:1.56768	validation-mlogloss:1.68605
[522]	train-mlogloss:1.56722	validation-mlogloss:1.68588
[523]	train-mlogloss:1.56678	validation-mlogloss:1.68554
[524]	train-mlogloss:1.56629	validation-mlogloss:1.68547
[525]	train-mlogloss:1.56587	validation-mlogloss:1.68545
[526]	train-mlogloss:1.56545	validation-mlogloss:1.68531
[527]	train-mlogloss:1.56495	validation-mlogloss:1.68530
[528]	train-mlogloss:1.56442	validation-mlogloss:1.68521
[529]	train-mlogloss:1.56395	validation-mlogloss:1.68517
[530]	train-mlogloss:1.56343	validation-mlogloss:1.68504
[531]	train-mlogloss:1.56300	validation-mlogloss:1.68494
[532]	train-mlogloss:1.56255	validation-mlogloss:1.68480
[533]	train-mlogloss:1.56208	validation-mlogloss:1.68474
[534]	train-mlogloss:1.56173	validation-mlogloss:1.68456
[535]	train-mlogloss:1.56117	validation-mlogloss:1.68440
[536]	train-mlogloss:1.56065	validation-mlogloss:1.68413
[537]	train-mlogloss:1.56026	validation-mlogloss:1.68402
[538]	train-mlogloss:1.55981	validation-mlogloss:1.68410
[539]	train-mlogloss:1.55933	validation-mlogloss:1.68408
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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.4 [%]
Global accuracy score (test) = 45.78 [%]
Global F1 score (train) = 51.53 [%]
Global F1 score (test) = 45.24 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.76      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.37      0.47      0.41       184
       CAMINAR USUAL SPEED       0.38      0.31      0.34       184
            CAMINAR ZIGZAG       0.39      0.52      0.45       184
          DE PIE BARRIENDO       0.78      0.31      0.44       184
   DE PIE DOBLANDO TOALLAS       0.51      0.41      0.45       184
    DE PIE MOVIENDO LIBROS       0.37      0.33      0.35       184
          DE PIE USANDO PC       0.22      0.37      0.28       184
        FASE REPOSO CON K5       0.57      0.85      0.68       184
INCREMENTAL CICLOERGOMETRO       0.77      0.70      0.73       184
           SENTADO LEYENDO       0.53      0.38      0.44       184
         SENTADO USANDO PC       0.24      0.13      0.17       184
      SENTADO VIENDO LA TV       0.31      0.27      0.29       184
   SUBIR Y BAJAR ESCALERAS       0.62      0.52      0.57       184
                    TROTAR       0.66      0.57      0.61       161

                  accuracy                           0.46      2737
                 macro avg       0.48      0.46      0.45      2737
              weighted avg       0.48      0.46      0.45      2737


Accuracy capturado en la ejecución 19: 45.78 [%]
F1-score capturado en la ejecución 19: 45.24 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.37 [%]
Global accuracy score (test) = 45.31 [%]
Global F1 score (train) = 51.46 [%]
Global F1 score (test) = 44.74 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.77      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.35      0.48      0.40       184
       CAMINAR USUAL SPEED       0.35      0.28      0.31       184
            CAMINAR ZIGZAG       0.38      0.52      0.44       184
          DE PIE BARRIENDO       0.75      0.31      0.44       184
   DE PIE DOBLANDO TOALLAS       0.51      0.42      0.46       184
    DE PIE MOVIENDO LIBROS       0.37      0.31      0.34       184
          DE PIE USANDO PC       0.23      0.35      0.27       184
        FASE REPOSO CON K5       0.57      0.86      0.69       184
INCREMENTAL CICLOERGOMETRO       0.75      0.68      0.72       184
           SENTADO LEYENDO       0.51      0.39      0.44       184
         SENTADO USANDO PC       0.23      0.14      0.17       184
      SENTADO VIENDO LA TV       0.28      0.24      0.26       184
   SUBIR Y BAJAR ESCALERAS       0.65      0.50      0.57       184
                    TROTAR       0.67      0.57      0.62       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.45      0.45      2737
              weighted avg       0.47      0.45      0.45      2737


Accuracy capturado en la ejecución 20: 45.31 [%]
F1-score capturado en la ejecución 20: 44.74 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.28 [%]
Global accuracy score (test) = 44.43 [%]
Global F1 score (train) = 51.39 [%]
Global F1 score (test) = 43.8 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.72      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.34      0.46      0.39       184
       CAMINAR USUAL SPEED       0.33      0.29      0.31       184
            CAMINAR ZIGZAG       0.39      0.52      0.45       184
          DE PIE BARRIENDO       0.74      0.28      0.41       184
   DE PIE DOBLANDO TOALLAS       0.48      0.42      0.45       184
    DE PIE MOVIENDO LIBROS       0.39      0.35      0.37       184
          DE PIE USANDO PC       0.22      0.33      0.26       184
        FASE REPOSO CON K5       0.57      0.85      0.68       184
INCREMENTAL CICLOERGOMETRO       0.74      0.70      0.72       184
           SENTADO LEYENDO       0.46      0.36      0.41       184
         SENTADO USANDO PC       0.21      0.12      0.16       184
      SENTADO VIENDO LA TV       0.26      0.21      0.23       184
   SUBIR Y BAJAR ESCALERAS       0.62      0.49      0.55       184
                    TROTAR       0.65      0.57      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 21: 44.43 [%]
F1-score capturado en la ejecución 21: 43.8 [%]

=== EJECUCIÓN 22 ===

--- TRAIN (ejecución 22) ---

--- TEST (ejecución 22) ---
2025-10-27 09:53:09.367182: 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`.
2025-10-27 09:53:09.379828: 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 00:00:1761555189.393649  422161 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555189.397886  422161 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555189.408952  422161 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555189.408976  422161 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555189.408979  422161 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555189.408981  422161 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:53:09.412222: 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:2.69448	validation-mlogloss:2.69337
[1]	train-mlogloss:2.68026	validation-mlogloss:2.67754
[2]	train-mlogloss:2.66655	validation-mlogloss:2.66249
[3]	train-mlogloss:2.65376	validation-mlogloss:2.64867
[4]	train-mlogloss:2.64086	validation-mlogloss:2.63511
[5]	train-mlogloss:2.62844	validation-mlogloss:2.62141
[6]	train-mlogloss:2.61590	validation-mlogloss:2.60718
[7]	train-mlogloss:2.60350	validation-mlogloss:2.59373
[8]	train-mlogloss:2.59143	validation-mlogloss:2.57988
[9]	train-mlogloss:2.58031	validation-mlogloss:2.56750
[10]	train-mlogloss:2.56881	validation-mlogloss:2.55492
[11]	train-mlogloss:2.55794	validation-mlogloss:2.54276
[12]	train-mlogloss:2.54787	validation-mlogloss:2.53219
[13]	train-mlogloss:2.53688	validation-mlogloss:2.51974
[14]	train-mlogloss:2.52619	validation-mlogloss:2.50760
[15]	train-mlogloss:2.51547	validation-mlogloss:2.49630
[16]	train-mlogloss:2.50579	validation-mlogloss:2.48526
[17]	train-mlogloss:2.49618	validation-mlogloss:2.47495
[18]	train-mlogloss:2.48685	validation-mlogloss:2.46410
[19]	train-mlogloss:2.47745	validation-mlogloss:2.45323
[20]	train-mlogloss:2.46897	validation-mlogloss:2.44316
[21]	train-mlogloss:2.45985	validation-mlogloss:2.43306
[22]	train-mlogloss:2.45104	validation-mlogloss:2.42323
[23]	train-mlogloss:2.44272	validation-mlogloss:2.41466
[24]	train-mlogloss:2.43399	validation-mlogloss:2.40490
[25]	train-mlogloss:2.42565	validation-mlogloss:2.39578
[26]	train-mlogloss:2.41773	validation-mlogloss:2.38717
[27]	train-mlogloss:2.40974	validation-mlogloss:2.37866
[28]	train-mlogloss:2.40155	validation-mlogloss:2.37054
[29]	train-mlogloss:2.39423	validation-mlogloss:2.36275
[30]	train-mlogloss:2.38708	validation-mlogloss:2.35456
[31]	train-mlogloss:2.37938	validation-mlogloss:2.34685
[32]	train-mlogloss:2.37253	validation-mlogloss:2.33992
[33]	train-mlogloss:2.36524	validation-mlogloss:2.33195
[34]	train-mlogloss:2.35842	validation-mlogloss:2.32446
[35]	train-mlogloss:2.35161	validation-mlogloss:2.31733
[36]	train-mlogloss:2.34503	validation-mlogloss:2.31013
[37]	train-mlogloss:2.33817	validation-mlogloss:2.30297
[38]	train-mlogloss:2.33165	validation-mlogloss:2.29579
[39]	train-mlogloss:2.32523	validation-mlogloss:2.28898
[40]	train-mlogloss:2.31876	validation-mlogloss:2.28201
[41]	train-mlogloss:2.31221	validation-mlogloss:2.27517
[42]	train-mlogloss:2.30605	validation-mlogloss:2.26868
[43]	train-mlogloss:2.30000	validation-mlogloss:2.26258
[44]	train-mlogloss:2.29397	validation-mlogloss:2.25590
[45]	train-mlogloss:2.28804	validation-mlogloss:2.25001
[46]	train-mlogloss:2.28230	validation-mlogloss:2.24466
[47]	train-mlogloss:2.27661	validation-mlogloss:2.23883
[48]	train-mlogloss:2.27080	validation-mlogloss:2.23254
[49]	train-mlogloss:2.26541	validation-mlogloss:2.22722
[50]	train-mlogloss:2.26008	validation-mlogloss:2.22161
[51]	train-mlogloss:2.25451	validation-mlogloss:2.21579
[52]	train-mlogloss:2.24901	validation-mlogloss:2.21001
[53]	train-mlogloss:2.24363	validation-mlogloss:2.20460
[54]	train-mlogloss:2.23828	validation-mlogloss:2.19871
[55]	train-mlogloss:2.23301	validation-mlogloss:2.19341
[56]	train-mlogloss:2.22765	validation-mlogloss:2.18760
[57]	train-mlogloss:2.22263	validation-mlogloss:2.18260
[58]	train-mlogloss:2.21787	validation-mlogloss:2.17847
[59]	train-mlogloss:2.21309	validation-mlogloss:2.17434
[60]	train-mlogloss:2.20828	validation-mlogloss:2.16928
[61]	train-mlogloss:2.20324	validation-mlogloss:2.16376
[62]	train-mlogloss:2.19846	validation-mlogloss:2.15877
[63]	train-mlogloss:2.19370	validation-mlogloss:2.15369
[64]	train-mlogloss:2.18913	validation-mlogloss:2.14884
[65]	train-mlogloss:2.18483	validation-mlogloss:2.14494
[66]	train-mlogloss:2.18045	validation-mlogloss:2.14051
[67]	train-mlogloss:2.17633	validation-mlogloss:2.13618
[68]	train-mlogloss:2.17175	validation-mlogloss:2.13109
[69]	train-mlogloss:2.16748	validation-mlogloss:2.12693
[70]	train-mlogloss:2.16318	validation-mlogloss:2.12274
[71]	train-mlogloss:2.15907	validation-mlogloss:2.11864
[72]	train-mlogloss:2.15505	validation-mlogloss:2.11457
[73]	train-mlogloss:2.15121	validation-mlogloss:2.11081
[74]	train-mlogloss:2.14720	validation-mlogloss:2.10665
[75]	train-mlogloss:2.14319	validation-mlogloss:2.10282
[76]	train-mlogloss:2.13920	validation-mlogloss:2.09882
[77]	train-mlogloss:2.13550	validation-mlogloss:2.09496
[78]	train-mlogloss:2.13147	validation-mlogloss:2.09124
[79]	train-mlogloss:2.12750	validation-mlogloss:2.08746
[80]	train-mlogloss:2.12353	validation-mlogloss:2.08394
[81]	train-mlogloss:2.11976	validation-mlogloss:2.07983
[82]	train-mlogloss:2.11606	validation-mlogloss:2.07646
[83]	train-mlogloss:2.11246	validation-mlogloss:2.07256
[84]	train-mlogloss:2.10879	validation-mlogloss:2.06939
[85]	train-mlogloss:2.10521	validation-mlogloss:2.06547
[86]	train-mlogloss:2.10173	validation-mlogloss:2.06212
[87]	train-mlogloss:2.09787	validation-mlogloss:2.05844
[88]	train-mlogloss:2.09431	validation-mlogloss:2.05470
[89]	train-mlogloss:2.09100	validation-mlogloss:2.05145
[90]	train-mlogloss:2.08754	validation-mlogloss:2.04820
[91]	train-mlogloss:2.08442	validation-mlogloss:2.04533
[92]	train-mlogloss:2.08108	validation-mlogloss:2.04265
[93]	train-mlogloss:2.07775	validation-mlogloss:2.03981
[94]	train-mlogloss:2.07449	validation-mlogloss:2.03689
[95]	train-mlogloss:2.07123	validation-mlogloss:2.03374
[96]	train-mlogloss:2.06799	validation-mlogloss:2.03016
[97]	train-mlogloss:2.06449	validation-mlogloss:2.02680
[98]	train-mlogloss:2.06115	validation-mlogloss:2.02360
[99]	train-mlogloss:2.05803	validation-mlogloss:2.02049
[100]	train-mlogloss:2.05485	validation-mlogloss:2.01752
[101]	train-mlogloss:2.05179	validation-mlogloss:2.01424
[102]	train-mlogloss:2.04874	validation-mlogloss:2.01157
[103]	train-mlogloss:2.04586	validation-mlogloss:2.00886
[104]	train-mlogloss:2.04260	validation-mlogloss:2.00583
[105]	train-mlogloss:2.03966	validation-mlogloss:2.00287
[106]	train-mlogloss:2.03664	validation-mlogloss:2.00023
[107]	train-mlogloss:2.03354	validation-mlogloss:1.99717
[108]	train-mlogloss:2.03079	validation-mlogloss:1.99451
[109]	train-mlogloss:2.02774	validation-mlogloss:1.99157
[110]	train-mlogloss:2.02474	validation-mlogloss:1.98908
[111]	train-mlogloss:2.02192	validation-mlogloss:1.98616
[112]	train-mlogloss:2.01903	validation-mlogloss:1.98381
[113]	train-mlogloss:2.01614	validation-mlogloss:1.98101
[114]	train-mlogloss:2.01333	validation-mlogloss:1.97806
[115]	train-mlogloss:2.01046	validation-mlogloss:1.97535
[116]	train-mlogloss:2.00769	validation-mlogloss:1.97316
[117]	train-mlogloss:2.00493	validation-mlogloss:1.97067
[118]	train-mlogloss:2.00219	validation-mlogloss:1.96830
[119]	train-mlogloss:1.99945	validation-mlogloss:1.96565
[120]	train-mlogloss:1.99677	validation-mlogloss:1.96295
[121]	train-mlogloss:1.99422	validation-mlogloss:1.96036
[122]	train-mlogloss:1.99168	validation-mlogloss:1.95791
[123]	train-mlogloss:1.98907	validation-mlogloss:1.95554
[124]	train-mlogloss:1.98658	validation-mlogloss:1.95337
[125]	train-mlogloss:1.98392	validation-mlogloss:1.95101
[126]	train-mlogloss:1.98130	validation-mlogloss:1.94823
[127]	train-mlogloss:1.97883	validation-mlogloss:1.94583
[128]	train-mlogloss:1.97632	validation-mlogloss:1.94358
[129]	train-mlogloss:1.97387	validation-mlogloss:1.94159
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[514]	train-mlogloss:1.57060	validation-mlogloss:1.68892
[515]	train-mlogloss:1.57010	validation-mlogloss:1.68893
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[517]	train-mlogloss:1.56912	validation-mlogloss:1.68865
[518]	train-mlogloss:1.56854	validation-mlogloss:1.68851
[519]	train-mlogloss:1.56809	validation-mlogloss:1.68857
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[521]	train-mlogloss:1.56708	validation-mlogloss:1.68802
[522]	train-mlogloss:1.56664	validation-mlogloss:1.68782
[523]	train-mlogloss:1.56613	validation-mlogloss:1.68778
[524]	train-mlogloss:1.56568	validation-mlogloss:1.68767
[525]	train-mlogloss:1.56519	validation-mlogloss:1.68741
[526]	train-mlogloss:1.56478	validation-mlogloss:1.68724
[527]	train-mlogloss:1.56426	validation-mlogloss:1.68706
[528]	train-mlogloss:1.56380	validation-mlogloss:1.68698
[529]	train-mlogloss:1.56332	validation-mlogloss:1.68694
[530]	train-mlogloss:1.56285	validation-mlogloss:1.68700
[531]	train-mlogloss:1.56239	validation-mlogloss:1.68678
[532]	train-mlogloss:1.56193	validation-mlogloss:1.68668
[533]	train-mlogloss:1.56151	validation-mlogloss:1.68657
[534]	train-mlogloss:1.56111	validation-mlogloss:1.68641
[535]	train-mlogloss:1.56072	validation-mlogloss:1.68616
[536]	train-mlogloss:1.56026	validation-mlogloss:1.68583
[537]	train-mlogloss:1.55988	validation-mlogloss:1.68555
[538]	train-mlogloss:1.55941	validation-mlogloss:1.68553
[539]	train-mlogloss:1.55894	validation-mlogloss:1.68559
Saved model to disk.
2025-10-27 09:53:55.505694: 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`.
2025-10-27 09:53:55.518512: 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 00:00:1761555235.532454  423079 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555235.536997  423079 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555235.548018  423079 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555235.548041  423079 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555235.548045  423079 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555235.548048  423079 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:53:55.551464: 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:2.68025	validation-mlogloss:2.67817
[2]	train-mlogloss:2.66677	validation-mlogloss:2.66357
[3]	train-mlogloss:2.65363	validation-mlogloss:2.64882
[4]	train-mlogloss:2.64124	validation-mlogloss:2.63577
[5]	train-mlogloss:2.62856	validation-mlogloss:2.62174
[6]	train-mlogloss:2.61668	validation-mlogloss:2.60867
[7]	train-mlogloss:2.60412	validation-mlogloss:2.59464
[8]	train-mlogloss:2.59245	validation-mlogloss:2.58269
[9]	train-mlogloss:2.58109	validation-mlogloss:2.56995
[10]	train-mlogloss:2.56986	validation-mlogloss:2.55771
[11]	train-mlogloss:2.55870	validation-mlogloss:2.54540
[12]	train-mlogloss:2.54803	validation-mlogloss:2.53371
[13]	train-mlogloss:2.53731	validation-mlogloss:2.52224
[14]	train-mlogloss:2.52682	validation-mlogloss:2.51060
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[16]	train-mlogloss:2.50682	validation-mlogloss:2.48753
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[19]	train-mlogloss:2.47949	validation-mlogloss:2.45706
[20]	train-mlogloss:2.46999	validation-mlogloss:2.44729
[21]	train-mlogloss:2.46076	validation-mlogloss:2.43693
[22]	train-mlogloss:2.45195	validation-mlogloss:2.42792
[23]	train-mlogloss:2.44342	validation-mlogloss:2.41839
[24]	train-mlogloss:2.43469	validation-mlogloss:2.40887
[25]	train-mlogloss:2.42631	validation-mlogloss:2.39991
[26]	train-mlogloss:2.41820	validation-mlogloss:2.39094
[27]	train-mlogloss:2.41030	validation-mlogloss:2.38176
[28]	train-mlogloss:2.40235	validation-mlogloss:2.37322
[29]	train-mlogloss:2.39457	validation-mlogloss:2.36472
[30]	train-mlogloss:2.38727	validation-mlogloss:2.35574
[31]	train-mlogloss:2.37986	validation-mlogloss:2.34785
[32]	train-mlogloss:2.37241	validation-mlogloss:2.33952
[33]	train-mlogloss:2.36530	validation-mlogloss:2.33195
[34]	train-mlogloss:2.35811	validation-mlogloss:2.32407
[35]	train-mlogloss:2.35135	validation-mlogloss:2.31634
[36]	train-mlogloss:2.34437	validation-mlogloss:2.30809
[37]	train-mlogloss:2.33765	validation-mlogloss:2.30108
[38]	train-mlogloss:2.33079	validation-mlogloss:2.29363
[39]	train-mlogloss:2.32437	validation-mlogloss:2.28707
[40]	train-mlogloss:2.31777	validation-mlogloss:2.28028
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[43]	train-mlogloss:2.29960	validation-mlogloss:2.26146
[44]	train-mlogloss:2.29367	validation-mlogloss:2.25505
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[52]	train-mlogloss:2.24829	validation-mlogloss:2.20766
[53]	train-mlogloss:2.24294	validation-mlogloss:2.20241
[54]	train-mlogloss:2.23771	validation-mlogloss:2.19741
[55]	train-mlogloss:2.23225	validation-mlogloss:2.19180
[56]	train-mlogloss:2.22708	validation-mlogloss:2.18635
[57]	train-mlogloss:2.22208	validation-mlogloss:2.18142
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[60]	train-mlogloss:2.20735	validation-mlogloss:2.16661
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[62]	train-mlogloss:2.19795	validation-mlogloss:2.15745
[63]	train-mlogloss:2.19335	validation-mlogloss:2.15234
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[65]	train-mlogloss:2.18395	validation-mlogloss:2.14325
[66]	train-mlogloss:2.17931	validation-mlogloss:2.13878
[67]	train-mlogloss:2.17491	validation-mlogloss:2.13427
[68]	train-mlogloss:2.17065	validation-mlogloss:2.12993
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[70]	train-mlogloss:2.16211	validation-mlogloss:2.12128
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[72]	train-mlogloss:2.15375	validation-mlogloss:2.11355
[73]	train-mlogloss:2.14948	validation-mlogloss:2.10899
[74]	train-mlogloss:2.14538	validation-mlogloss:2.10507
[75]	train-mlogloss:2.14142	validation-mlogloss:2.10123
[76]	train-mlogloss:2.13735	validation-mlogloss:2.09701
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[104]	train-mlogloss:2.04015	validation-mlogloss:2.00443
[105]	train-mlogloss:2.03721	validation-mlogloss:2.00163
[106]	train-mlogloss:2.03411	validation-mlogloss:1.99910
[107]	train-mlogloss:2.03115	validation-mlogloss:1.99621
[108]	train-mlogloss:2.02839	validation-mlogloss:1.99314
[109]	train-mlogloss:2.02528	validation-mlogloss:1.99019
[110]	train-mlogloss:2.02255	validation-mlogloss:1.98794
[111]	train-mlogloss:2.01967	validation-mlogloss:1.98526
[112]	train-mlogloss:2.01671	validation-mlogloss:1.98230
[113]	train-mlogloss:2.01378	validation-mlogloss:1.97938
[114]	train-mlogloss:2.01100	validation-mlogloss:1.97695
[115]	train-mlogloss:2.00819	validation-mlogloss:1.97461
[116]	train-mlogloss:2.00542	validation-mlogloss:1.97212
[117]	train-mlogloss:2.00277	validation-mlogloss:1.96976
[118]	train-mlogloss:2.00026	validation-mlogloss:1.96749
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[128]	train-mlogloss:1.97395	validation-mlogloss:1.94289
[129]	train-mlogloss:1.97148	validation-mlogloss:1.94063
[130]	train-mlogloss:1.96891	validation-mlogloss:1.93849
[131]	train-mlogloss:1.96648	validation-mlogloss:1.93643
[132]	train-mlogloss:1.96413	validation-mlogloss:1.93437
[133]	train-mlogloss:1.96192	validation-mlogloss:1.93239
[134]	train-mlogloss:1.95960	validation-mlogloss:1.93087
[135]	train-mlogloss:1.95721	validation-mlogloss:1.92860
[136]	train-mlogloss:1.95501	validation-mlogloss:1.92663
[137]	train-mlogloss:1.95260	validation-mlogloss:1.92424
[138]	train-mlogloss:1.95026	validation-mlogloss:1.92241
[139]	train-mlogloss:1.94810	validation-mlogloss:1.92054
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[143]	train-mlogloss:1.93914	validation-mlogloss:1.91312
[144]	train-mlogloss:1.93695	validation-mlogloss:1.91135
[145]	train-mlogloss:1.93469	validation-mlogloss:1.90936
[146]	train-mlogloss:1.93237	validation-mlogloss:1.90764
[147]	train-mlogloss:1.93030	validation-mlogloss:1.90608
[148]	train-mlogloss:1.92817	validation-mlogloss:1.90429
[149]	train-mlogloss:1.92613	validation-mlogloss:1.90248
[150]	train-mlogloss:1.92415	validation-mlogloss:1.90044
[151]	train-mlogloss:1.92204	validation-mlogloss:1.89854
[152]	train-mlogloss:1.92008	validation-mlogloss:1.89693
[153]	train-mlogloss:1.91812	validation-mlogloss:1.89532
[154]	train-mlogloss:1.91609	validation-mlogloss:1.89352
[155]	train-mlogloss:1.91408	validation-mlogloss:1.89170
[156]	train-mlogloss:1.91210	validation-mlogloss:1.88972
[157]	train-mlogloss:1.91030	validation-mlogloss:1.88843
[158]	train-mlogloss:1.90834	validation-mlogloss:1.88681
[159]	train-mlogloss:1.90640	validation-mlogloss:1.88503
[160]	train-mlogloss:1.90445	validation-mlogloss:1.88350
[161]	train-mlogloss:1.90249	validation-mlogloss:1.88223
[162]	train-mlogloss:1.90060	validation-mlogloss:1.88051
[163]	train-mlogloss:1.89859	validation-mlogloss:1.87898
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[464]	train-mlogloss:1.59771	validation-mlogloss:1.69830
[465]	train-mlogloss:1.59716	validation-mlogloss:1.69806
[466]	train-mlogloss:1.59653	validation-mlogloss:1.69788
[467]	train-mlogloss:1.59593	validation-mlogloss:1.69765
[468]	train-mlogloss:1.59536	validation-mlogloss:1.69769
[469]	train-mlogloss:1.59482	validation-mlogloss:1.69744
[470]	train-mlogloss:1.59432	validation-mlogloss:1.69731
[471]	train-mlogloss:1.59369	validation-mlogloss:1.69707
[472]	train-mlogloss:1.59316	validation-mlogloss:1.69681
[473]	train-mlogloss:1.59258	validation-mlogloss:1.69647
[474]	train-mlogloss:1.59204	validation-mlogloss:1.69633
[475]	train-mlogloss:1.59142	validation-mlogloss:1.69607
[476]	train-mlogloss:1.59082	validation-mlogloss:1.69594
[477]	train-mlogloss:1.59025	validation-mlogloss:1.69573
[478]	train-mlogloss:1.58967	validation-mlogloss:1.69543
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[480]	train-mlogloss:1.58863	validation-mlogloss:1.69505
[481]	train-mlogloss:1.58806	validation-mlogloss:1.69504
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[484]	train-mlogloss:1.58643	validation-mlogloss:1.69474
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[486]	train-mlogloss:1.58522	validation-mlogloss:1.69438
[487]	train-mlogloss:1.58465	validation-mlogloss:1.69422
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[489]	train-mlogloss:1.58356	validation-mlogloss:1.69406
[490]	train-mlogloss:1.58299	validation-mlogloss:1.69396
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[492]	train-mlogloss:1.58195	validation-mlogloss:1.69364
[493]	train-mlogloss:1.58150	validation-mlogloss:1.69327
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[495]	train-mlogloss:1.58037	validation-mlogloss:1.69314
[496]	train-mlogloss:1.57982	validation-mlogloss:1.69300
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[498]	train-mlogloss:1.57874	validation-mlogloss:1.69278
[499]	train-mlogloss:1.57824	validation-mlogloss:1.69260
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[502]	train-mlogloss:1.57675	validation-mlogloss:1.69209
[503]	train-mlogloss:1.57625	validation-mlogloss:1.69192
[504]	train-mlogloss:1.57576	validation-mlogloss:1.69173
[505]	train-mlogloss:1.57526	validation-mlogloss:1.69158
[506]	train-mlogloss:1.57470	validation-mlogloss:1.69149
[507]	train-mlogloss:1.57418	validation-mlogloss:1.69130
[508]	train-mlogloss:1.57367	validation-mlogloss:1.69118
[509]	train-mlogloss:1.57318	validation-mlogloss:1.69107
[510]	train-mlogloss:1.57263	validation-mlogloss:1.69112
[511]	train-mlogloss:1.57212	validation-mlogloss:1.69107
[512]	train-mlogloss:1.57157	validation-mlogloss:1.69074
[513]	train-mlogloss:1.57104	validation-mlogloss:1.69040
[514]	train-mlogloss:1.57061	validation-mlogloss:1.69038
[515]	train-mlogloss:1.57021	validation-mlogloss:1.68999
[516]	train-mlogloss:1.56969	validation-mlogloss:1.68974
[517]	train-mlogloss:1.56914	validation-mlogloss:1.68951
[518]	train-mlogloss:1.56861	validation-mlogloss:1.68933
[519]	train-mlogloss:1.56814	validation-mlogloss:1.68921
[520]	train-mlogloss:1.56751	validation-mlogloss:1.68894
[521]	train-mlogloss:1.56699	validation-mlogloss:1.68885
[522]	train-mlogloss:1.56658	validation-mlogloss:1.68868
[523]	train-mlogloss:1.56607	validation-mlogloss:1.68847
[524]	train-mlogloss:1.56547	validation-mlogloss:1.68817
[525]	train-mlogloss:1.56505	validation-mlogloss:1.68802
[526]	train-mlogloss:1.56461	validation-mlogloss:1.68804
[527]	train-mlogloss:1.56414	validation-mlogloss:1.68791
[528]	train-mlogloss:1.56372	validation-mlogloss:1.68772
[529]	train-mlogloss:1.56329	validation-mlogloss:1.68755
[530]	train-mlogloss:1.56284	validation-mlogloss:1.68741
[531]	train-mlogloss:1.56236	validation-mlogloss:1.68741
[532]	train-mlogloss:1.56188	validation-mlogloss:1.68735
[533]	train-mlogloss:1.56131	validation-mlogloss:1.68721
[534]	train-mlogloss:1.56091	validation-mlogloss:1.68689
[535]	train-mlogloss:1.56050	validation-mlogloss:1.68662
[536]	train-mlogloss:1.56000	validation-mlogloss:1.68660
[537]	train-mlogloss:1.55954	validation-mlogloss:1.68642
[538]	train-mlogloss:1.55910	validation-mlogloss:1.68644
[539]	train-mlogloss:1.55867	validation-mlogloss:1.68627
Saved model to disk.
2025-10-27 09:54:41.235556: 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`.
2025-10-27 09:54:41.247855: 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 00:00:1761555281.261446  423959 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555281.265811  423959 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555281.276736  423959 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555281.276759  423959 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555281.276762  423959 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555281.276764  423959 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:54:41.280128: 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:2.68003	validation-mlogloss:2.67653
[2]	train-mlogloss:2.66565	validation-mlogloss:2.66035
[3]	train-mlogloss:2.65207	validation-mlogloss:2.64512
[4]	train-mlogloss:2.63822	validation-mlogloss:2.63007
[5]	train-mlogloss:2.62553	validation-mlogloss:2.61611
[6]	train-mlogloss:2.61373	validation-mlogloss:2.60322
[7]	train-mlogloss:2.60335	validation-mlogloss:2.59132
[8]	train-mlogloss:2.59156	validation-mlogloss:2.57840
[9]	train-mlogloss:2.57954	validation-mlogloss:2.56495
[10]	train-mlogloss:2.56847	validation-mlogloss:2.55257
[11]	train-mlogloss:2.55726	validation-mlogloss:2.53977
[12]	train-mlogloss:2.54612	validation-mlogloss:2.52751
[13]	train-mlogloss:2.53543	validation-mlogloss:2.51574
[14]	train-mlogloss:2.52526	validation-mlogloss:2.50468
[15]	train-mlogloss:2.51517	validation-mlogloss:2.49319
[16]	train-mlogloss:2.50570	validation-mlogloss:2.48270
[17]	train-mlogloss:2.49603	validation-mlogloss:2.47211
[18]	train-mlogloss:2.48655	validation-mlogloss:2.46138
[19]	train-mlogloss:2.47728	validation-mlogloss:2.45108
[20]	train-mlogloss:2.46896	validation-mlogloss:2.44256
[21]	train-mlogloss:2.46012	validation-mlogloss:2.43270
[22]	train-mlogloss:2.45195	validation-mlogloss:2.42404
[23]	train-mlogloss:2.44325	validation-mlogloss:2.41411
[24]	train-mlogloss:2.43498	validation-mlogloss:2.40542
[25]	train-mlogloss:2.42680	validation-mlogloss:2.39626
[26]	train-mlogloss:2.41865	validation-mlogloss:2.38787
[27]	train-mlogloss:2.41094	validation-mlogloss:2.37953
[28]	train-mlogloss:2.40304	validation-mlogloss:2.37075
[29]	train-mlogloss:2.39598	validation-mlogloss:2.36306
[30]	train-mlogloss:2.38844	validation-mlogloss:2.35560
[31]	train-mlogloss:2.38059	validation-mlogloss:2.34726
[32]	train-mlogloss:2.37319	validation-mlogloss:2.33927
[33]	train-mlogloss:2.36633	validation-mlogloss:2.33181
[34]	train-mlogloss:2.35909	validation-mlogloss:2.32395
[35]	train-mlogloss:2.35236	validation-mlogloss:2.31740
[36]	train-mlogloss:2.34599	validation-mlogloss:2.31046
[37]	train-mlogloss:2.33971	validation-mlogloss:2.30386
[38]	train-mlogloss:2.33300	validation-mlogloss:2.29631
[39]	train-mlogloss:2.32668	validation-mlogloss:2.28952
[40]	train-mlogloss:2.32055	validation-mlogloss:2.28314
[41]	train-mlogloss:2.31429	validation-mlogloss:2.27653
[42]	train-mlogloss:2.30771	validation-mlogloss:2.26939
[43]	train-mlogloss:2.30159	validation-mlogloss:2.26347
[44]	train-mlogloss:2.29526	validation-mlogloss:2.25734
[45]	train-mlogloss:2.28937	validation-mlogloss:2.25188
[46]	train-mlogloss:2.28363	validation-mlogloss:2.24576
[47]	train-mlogloss:2.27776	validation-mlogloss:2.23942
[48]	train-mlogloss:2.27203	validation-mlogloss:2.23338
[49]	train-mlogloss:2.26658	validation-mlogloss:2.22840
[50]	train-mlogloss:2.26088	validation-mlogloss:2.22248
[51]	train-mlogloss:2.25556	validation-mlogloss:2.21698
[52]	train-mlogloss:2.25017	validation-mlogloss:2.21163
[53]	train-mlogloss:2.24464	validation-mlogloss:2.20554
[54]	train-mlogloss:2.23936	validation-mlogloss:2.19997
[55]	train-mlogloss:2.23424	validation-mlogloss:2.19472
[56]	train-mlogloss:2.22920	validation-mlogloss:2.18898
[57]	train-mlogloss:2.22420	validation-mlogloss:2.18369
[58]	train-mlogloss:2.21928	validation-mlogloss:2.17862
[59]	train-mlogloss:2.21449	validation-mlogloss:2.17365
[60]	train-mlogloss:2.20954	validation-mlogloss:2.16896
[61]	train-mlogloss:2.20463	validation-mlogloss:2.16389
[62]	train-mlogloss:2.19987	validation-mlogloss:2.15899
[63]	train-mlogloss:2.19505	validation-mlogloss:2.15400
[64]	train-mlogloss:2.19027	validation-mlogloss:2.14881
[65]	train-mlogloss:2.18550	validation-mlogloss:2.14403
[66]	train-mlogloss:2.18088	validation-mlogloss:2.13917
[67]	train-mlogloss:2.17632	validation-mlogloss:2.13476
[68]	train-mlogloss:2.17203	validation-mlogloss:2.13066
[69]	train-mlogloss:2.16769	validation-mlogloss:2.12625
[70]	train-mlogloss:2.16331	validation-mlogloss:2.12152
[71]	train-mlogloss:2.15887	validation-mlogloss:2.11676
[72]	train-mlogloss:2.15484	validation-mlogloss:2.11268
[73]	train-mlogloss:2.15055	validation-mlogloss:2.10826
[74]	train-mlogloss:2.14656	validation-mlogloss:2.10409
[75]	train-mlogloss:2.14236	validation-mlogloss:2.09987
[76]	train-mlogloss:2.13846	validation-mlogloss:2.09586
[77]	train-mlogloss:2.13453	validation-mlogloss:2.09193
[78]	train-mlogloss:2.13055	validation-mlogloss:2.08809
[79]	train-mlogloss:2.12663	validation-mlogloss:2.08421
[80]	train-mlogloss:2.12295	validation-mlogloss:2.08103
[81]	train-mlogloss:2.11921	validation-mlogloss:2.07711
[82]	train-mlogloss:2.11560	validation-mlogloss:2.07337
[83]	train-mlogloss:2.11174	validation-mlogloss:2.06956
[84]	train-mlogloss:2.10799	validation-mlogloss:2.06620
[85]	train-mlogloss:2.10424	validation-mlogloss:2.06248
[86]	train-mlogloss:2.10062	validation-mlogloss:2.05864
[87]	train-mlogloss:2.09723	validation-mlogloss:2.05546
[88]	train-mlogloss:2.09370	validation-mlogloss:2.05209
[89]	train-mlogloss:2.09014	validation-mlogloss:2.04879
[90]	train-mlogloss:2.08670	validation-mlogloss:2.04579
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[93]	train-mlogloss:2.07615	validation-mlogloss:2.03653
[94]	train-mlogloss:2.07284	validation-mlogloss:2.03313
[95]	train-mlogloss:2.06956	validation-mlogloss:2.02989
[96]	train-mlogloss:2.06636	validation-mlogloss:2.02739
[97]	train-mlogloss:2.06283	validation-mlogloss:2.02413
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[99]	train-mlogloss:2.05649	validation-mlogloss:2.01836
[100]	train-mlogloss:2.05343	validation-mlogloss:2.01505
[101]	train-mlogloss:2.05015	validation-mlogloss:2.01187
[102]	train-mlogloss:2.04695	validation-mlogloss:2.00883
[103]	train-mlogloss:2.04372	validation-mlogloss:2.00572
[104]	train-mlogloss:2.04072	validation-mlogloss:2.00302
[105]	train-mlogloss:2.03768	validation-mlogloss:2.00041
[106]	train-mlogloss:2.03461	validation-mlogloss:1.99745
[107]	train-mlogloss:2.03162	validation-mlogloss:1.99448
[108]	train-mlogloss:2.02858	validation-mlogloss:1.99126
[109]	train-mlogloss:2.02565	validation-mlogloss:1.98831
[110]	train-mlogloss:2.02291	validation-mlogloss:1.98573
[111]	train-mlogloss:2.02012	validation-mlogloss:1.98319
[112]	train-mlogloss:2.01731	validation-mlogloss:1.98055
[113]	train-mlogloss:2.01454	validation-mlogloss:1.97818
[114]	train-mlogloss:2.01182	validation-mlogloss:1.97570
[115]	train-mlogloss:2.00921	validation-mlogloss:1.97337
[116]	train-mlogloss:2.00650	validation-mlogloss:1.97088
[117]	train-mlogloss:2.00357	validation-mlogloss:1.96750
[118]	train-mlogloss:2.00081	validation-mlogloss:1.96486
[119]	train-mlogloss:1.99811	validation-mlogloss:1.96217
[120]	train-mlogloss:1.99567	validation-mlogloss:1.95988
[121]	train-mlogloss:1.99323	validation-mlogloss:1.95782
[122]	train-mlogloss:1.99062	validation-mlogloss:1.95547
[123]	train-mlogloss:1.98802	validation-mlogloss:1.95305
[124]	train-mlogloss:1.98546	validation-mlogloss:1.95095
[125]	train-mlogloss:1.98295	validation-mlogloss:1.94835
[126]	train-mlogloss:1.98056	validation-mlogloss:1.94603
[127]	train-mlogloss:1.97807	validation-mlogloss:1.94362
[128]	train-mlogloss:1.97572	validation-mlogloss:1.94142
[129]	train-mlogloss:1.97321	validation-mlogloss:1.93906
[130]	train-mlogloss:1.97092	validation-mlogloss:1.93675
[131]	train-mlogloss:1.96842	validation-mlogloss:1.93452
[132]	train-mlogloss:1.96615	validation-mlogloss:1.93237
[133]	train-mlogloss:1.96367	validation-mlogloss:1.93022
[134]	train-mlogloss:1.96134	validation-mlogloss:1.92861
[135]	train-mlogloss:1.95894	validation-mlogloss:1.92649
[136]	train-mlogloss:1.95664	validation-mlogloss:1.92473
[137]	train-mlogloss:1.95431	validation-mlogloss:1.92244
[138]	train-mlogloss:1.95213	validation-mlogloss:1.92050
[139]	train-mlogloss:1.94969	validation-mlogloss:1.91836
[140]	train-mlogloss:1.94739	validation-mlogloss:1.91595
[141]	train-mlogloss:1.94514	validation-mlogloss:1.91417
[142]	train-mlogloss:1.94293	validation-mlogloss:1.91217
[143]	train-mlogloss:1.94062	validation-mlogloss:1.91013
[144]	train-mlogloss:1.93862	validation-mlogloss:1.90823
[145]	train-mlogloss:1.93638	validation-mlogloss:1.90600
[146]	train-mlogloss:1.93410	validation-mlogloss:1.90409
[147]	train-mlogloss:1.93195	validation-mlogloss:1.90240
[148]	train-mlogloss:1.92980	validation-mlogloss:1.90012
[149]	train-mlogloss:1.92767	validation-mlogloss:1.89850
[150]	train-mlogloss:1.92567	validation-mlogloss:1.89669
[151]	train-mlogloss:1.92357	validation-mlogloss:1.89462
[152]	train-mlogloss:1.92157	validation-mlogloss:1.89289
[153]	train-mlogloss:1.91956	validation-mlogloss:1.89165
[154]	train-mlogloss:1.91730	validation-mlogloss:1.88978
[155]	train-mlogloss:1.91537	validation-mlogloss:1.88815
[156]	train-mlogloss:1.91333	validation-mlogloss:1.88665
[157]	train-mlogloss:1.91135	validation-mlogloss:1.88514
[158]	train-mlogloss:1.90947	validation-mlogloss:1.88341
[159]	train-mlogloss:1.90750	validation-mlogloss:1.88182
[160]	train-mlogloss:1.90559	validation-mlogloss:1.88035
[161]	train-mlogloss:1.90366	validation-mlogloss:1.87896
[162]	train-mlogloss:1.90181	validation-mlogloss:1.87764
[163]	train-mlogloss:1.89996	validation-mlogloss:1.87605
[164]	train-mlogloss:1.89793	validation-mlogloss:1.87406
[165]	train-mlogloss:1.89613	validation-mlogloss:1.87268
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[170]	train-mlogloss:1.88663	validation-mlogloss:1.86460
[171]	train-mlogloss:1.88473	validation-mlogloss:1.86309
[172]	train-mlogloss:1.88297	validation-mlogloss:1.86154
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[189]	train-mlogloss:1.85407	validation-mlogloss:1.83916
[190]	train-mlogloss:1.85254	validation-mlogloss:1.83817
[191]	train-mlogloss:1.85093	validation-mlogloss:1.83699
[192]	train-mlogloss:1.84934	validation-mlogloss:1.83574
[193]	train-mlogloss:1.84770	validation-mlogloss:1.83448
[194]	train-mlogloss:1.84606	validation-mlogloss:1.83298
[195]	train-mlogloss:1.84437	validation-mlogloss:1.83141
[196]	train-mlogloss:1.84276	validation-mlogloss:1.83033
[197]	train-mlogloss:1.84126	validation-mlogloss:1.82917
[198]	train-mlogloss:1.83980	validation-mlogloss:1.82815
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[499]	train-mlogloss:1.57780	validation-mlogloss:1.68570
[500]	train-mlogloss:1.57722	validation-mlogloss:1.68541
[501]	train-mlogloss:1.57677	validation-mlogloss:1.68515
[502]	train-mlogloss:1.57632	validation-mlogloss:1.68505
[503]	train-mlogloss:1.57583	validation-mlogloss:1.68501
[504]	train-mlogloss:1.57533	validation-mlogloss:1.68500
[505]	train-mlogloss:1.57479	validation-mlogloss:1.68487
[506]	train-mlogloss:1.57435	validation-mlogloss:1.68466
[507]	train-mlogloss:1.57385	validation-mlogloss:1.68454
[508]	train-mlogloss:1.57330	validation-mlogloss:1.68420
[509]	train-mlogloss:1.57277	validation-mlogloss:1.68404
[510]	train-mlogloss:1.57231	validation-mlogloss:1.68398
[511]	train-mlogloss:1.57183	validation-mlogloss:1.68376
[512]	train-mlogloss:1.57137	validation-mlogloss:1.68358
[513]	train-mlogloss:1.57077	validation-mlogloss:1.68355
[514]	train-mlogloss:1.57029	validation-mlogloss:1.68333
[515]	train-mlogloss:1.56985	validation-mlogloss:1.68310
[516]	train-mlogloss:1.56935	validation-mlogloss:1.68291
[517]	train-mlogloss:1.56887	validation-mlogloss:1.68289
[518]	train-mlogloss:1.56853	validation-mlogloss:1.68292
[519]	train-mlogloss:1.56805	validation-mlogloss:1.68283
[520]	train-mlogloss:1.56749	validation-mlogloss:1.68266
[521]	train-mlogloss:1.56700	validation-mlogloss:1.68230
[522]	train-mlogloss:1.56652	validation-mlogloss:1.68224
[523]	train-mlogloss:1.56604	validation-mlogloss:1.68194
[524]	train-mlogloss:1.56551	validation-mlogloss:1.68194
[525]	train-mlogloss:1.56500	validation-mlogloss:1.68184
[526]	train-mlogloss:1.56448	validation-mlogloss:1.68174
[527]	train-mlogloss:1.56401	validation-mlogloss:1.68147
[528]	train-mlogloss:1.56350	validation-mlogloss:1.68147
[529]	train-mlogloss:1.56304	validation-mlogloss:1.68136
[530]	train-mlogloss:1.56264	validation-mlogloss:1.68134
[531]	train-mlogloss:1.56207	validation-mlogloss:1.68113
[532]	train-mlogloss:1.56155	validation-mlogloss:1.68104
[533]	train-mlogloss:1.56112	validation-mlogloss:1.68107
[534]	train-mlogloss:1.56069	validation-mlogloss:1.68087
[535]	train-mlogloss:1.56017	validation-mlogloss:1.68068
[536]	train-mlogloss:1.55980	validation-mlogloss:1.68058
[537]	train-mlogloss:1.55931	validation-mlogloss:1.68042
[538]	train-mlogloss:1.55889	validation-mlogloss:1.68047
[539]	train-mlogloss:1.55829	validation-mlogloss:1.68029
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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.36 [%]
Global accuracy score (test) = 45.52 [%]
Global F1 score (train) = 51.47 [%]
Global F1 score (test) = 44.88 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.76      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.38      0.45      0.41       184
       CAMINAR USUAL SPEED       0.36      0.27      0.31       184
            CAMINAR ZIGZAG       0.39      0.52      0.44       184
          DE PIE BARRIENDO       0.70      0.29      0.41       184
   DE PIE DOBLANDO TOALLAS       0.50      0.45      0.47       184
    DE PIE MOVIENDO LIBROS       0.43      0.39      0.41       184
          DE PIE USANDO PC       0.22      0.32      0.26       184
        FASE REPOSO CON K5       0.56      0.85      0.68       184
INCREMENTAL CICLOERGOMETRO       0.75      0.70      0.72       184
           SENTADO LEYENDO       0.49      0.38      0.43       184
         SENTADO USANDO PC       0.25      0.15      0.18       184
      SENTADO VIENDO LA TV       0.26      0.23      0.24       184
   SUBIR Y BAJAR ESCALERAS       0.62      0.52      0.57       184
                    TROTAR       0.66      0.57      0.61       161

                  accuracy                           0.46      2737
                 macro avg       0.47      0.46      0.45      2737
              weighted avg       0.47      0.46      0.45      2737


Accuracy capturado en la ejecución 22: 45.52 [%]
F1-score capturado en la ejecución 22: 44.88 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.2 [%]
Global accuracy score (test) = 45.85 [%]
Global F1 score (train) = 51.34 [%]
Global F1 score (test) = 45.28 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.76      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.39      0.46      0.42       184
       CAMINAR USUAL SPEED       0.34      0.27      0.30       184
            CAMINAR ZIGZAG       0.38      0.55      0.45       184
          DE PIE BARRIENDO       0.73      0.30      0.42       184
   DE PIE DOBLANDO TOALLAS       0.48      0.40      0.44       184
    DE PIE MOVIENDO LIBROS       0.41      0.38      0.39       184
          DE PIE USANDO PC       0.23      0.35      0.28       184
        FASE REPOSO CON K5       0.57      0.85      0.68       184
INCREMENTAL CICLOERGOMETRO       0.74      0.68      0.71       184
           SENTADO LEYENDO       0.51      0.39      0.44       184
         SENTADO USANDO PC       0.26      0.16      0.20       184
      SENTADO VIENDO LA TV       0.32      0.27      0.29       184
   SUBIR Y BAJAR ESCALERAS       0.64      0.51      0.57       184
                    TROTAR       0.65      0.57      0.61       161

                  accuracy                           0.46      2737
                 macro avg       0.48      0.46      0.45      2737
              weighted avg       0.47      0.46      0.45      2737


Accuracy capturado en la ejecución 23: 45.85 [%]
F1-score capturado en la ejecución 23: 45.28 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.35 [%]
Global accuracy score (test) = 45.05 [%]
Global F1 score (train) = 51.49 [%]
Global F1 score (test) = 44.46 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.76      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.36      0.47      0.41       184
       CAMINAR USUAL SPEED       0.37      0.30      0.34       184
            CAMINAR ZIGZAG       0.38      0.51      0.44       184
          DE PIE BARRIENDO       0.74      0.30      0.43       184
   DE PIE DOBLANDO TOALLAS       0.49      0.42      0.45       184
    DE PIE MOVIENDO LIBROS       0.39      0.33      0.35       184
          DE PIE USANDO PC       0.21      0.31      0.25       184
        FASE REPOSO CON K5       0.58      0.85      0.69       184
INCREMENTAL CICLOERGOMETRO       0.75      0.69      0.72       184
           SENTADO LEYENDO       0.50      0.41      0.45       184
         SENTADO USANDO PC       0.22      0.13      0.16       184
      SENTADO VIENDO LA TV       0.28      0.23      0.25       184
   SUBIR Y BAJAR ESCALERAS       0.59      0.49      0.54       184
                    TROTAR       0.68      0.57      0.62       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.45      0.44      2737
              weighted avg       0.47      0.45      0.44      2737


Accuracy capturado en la ejecución 24: 45.05 [%]
F1-score capturado en la ejecución 24: 44.46 [%]

=== EJECUCIÓN 25 ===

--- TRAIN (ejecución 25) ---

--- TEST (ejecución 25) ---
2025-10-27 09:55:27.585275: 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`.
2025-10-27 09:55:27.597971: 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 00:00:1761555327.611538  424894 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555327.615879  424894 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555327.626731  424894 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555327.626754  424894 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555327.626757  424894 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555327.626760  424894 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:55:27.630079: 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:2.69321	validation-mlogloss:2.69158
[1]	train-mlogloss:2.68128	validation-mlogloss:2.67738
[2]	train-mlogloss:2.66703	validation-mlogloss:2.66067
[3]	train-mlogloss:2.65280	validation-mlogloss:2.64428
[4]	train-mlogloss:2.64033	validation-mlogloss:2.63049
[5]	train-mlogloss:2.62741	validation-mlogloss:2.61742
[6]	train-mlogloss:2.61547	validation-mlogloss:2.60444
[7]	train-mlogloss:2.60398	validation-mlogloss:2.59175
[8]	train-mlogloss:2.59282	validation-mlogloss:2.57974
[9]	train-mlogloss:2.58060	validation-mlogloss:2.56635
[10]	train-mlogloss:2.56862	validation-mlogloss:2.55262
[11]	train-mlogloss:2.55739	validation-mlogloss:2.54105
[12]	train-mlogloss:2.54682	validation-mlogloss:2.52874
[13]	train-mlogloss:2.53602	validation-mlogloss:2.51633
[14]	train-mlogloss:2.52555	validation-mlogloss:2.50449
[15]	train-mlogloss:2.51607	validation-mlogloss:2.49448
[16]	train-mlogloss:2.50675	validation-mlogloss:2.48425
[17]	train-mlogloss:2.49711	validation-mlogloss:2.47447
[18]	train-mlogloss:2.48758	validation-mlogloss:2.46388
[19]	train-mlogloss:2.47799	validation-mlogloss:2.45335
[20]	train-mlogloss:2.46843	validation-mlogloss:2.44271
[21]	train-mlogloss:2.45932	validation-mlogloss:2.43315
[22]	train-mlogloss:2.45030	validation-mlogloss:2.42346
[23]	train-mlogloss:2.44176	validation-mlogloss:2.41416
[24]	train-mlogloss:2.43337	validation-mlogloss:2.40519
[25]	train-mlogloss:2.42485	validation-mlogloss:2.39577
[26]	train-mlogloss:2.41691	validation-mlogloss:2.38706
[27]	train-mlogloss:2.40911	validation-mlogloss:2.37876
[28]	train-mlogloss:2.40164	validation-mlogloss:2.37099
[29]	train-mlogloss:2.39433	validation-mlogloss:2.36296
[30]	train-mlogloss:2.38714	validation-mlogloss:2.35504
[31]	train-mlogloss:2.38003	validation-mlogloss:2.34730
[32]	train-mlogloss:2.37271	validation-mlogloss:2.33904
[33]	train-mlogloss:2.36541	validation-mlogloss:2.33141
[34]	train-mlogloss:2.35856	validation-mlogloss:2.32481
[35]	train-mlogloss:2.35198	validation-mlogloss:2.31728
[36]	train-mlogloss:2.34531	validation-mlogloss:2.31001
[37]	train-mlogloss:2.33837	validation-mlogloss:2.30282
[38]	train-mlogloss:2.33234	validation-mlogloss:2.29635
[39]	train-mlogloss:2.32595	validation-mlogloss:2.28885
[40]	train-mlogloss:2.31964	validation-mlogloss:2.28243
[41]	train-mlogloss:2.31346	validation-mlogloss:2.27586
[42]	train-mlogloss:2.30701	validation-mlogloss:2.26888
[43]	train-mlogloss:2.30088	validation-mlogloss:2.26232
[44]	train-mlogloss:2.29504	validation-mlogloss:2.25605
[45]	train-mlogloss:2.28893	validation-mlogloss:2.24924
[46]	train-mlogloss:2.28288	validation-mlogloss:2.24295
[47]	train-mlogloss:2.27695	validation-mlogloss:2.23658
[48]	train-mlogloss:2.27129	validation-mlogloss:2.23056
[49]	train-mlogloss:2.26588	validation-mlogloss:2.22509
[50]	train-mlogloss:2.26028	validation-mlogloss:2.21885
[51]	train-mlogloss:2.25477	validation-mlogloss:2.21352
[52]	train-mlogloss:2.24939	validation-mlogloss:2.20775
[53]	train-mlogloss:2.24407	validation-mlogloss:2.20230
[54]	train-mlogloss:2.23892	validation-mlogloss:2.19695
[55]	train-mlogloss:2.23355	validation-mlogloss:2.19151
[56]	train-mlogloss:2.22835	validation-mlogloss:2.18604
[57]	train-mlogloss:2.22338	validation-mlogloss:2.18091
[58]	train-mlogloss:2.21849	validation-mlogloss:2.17565
[59]	train-mlogloss:2.21352	validation-mlogloss:2.17113
[60]	train-mlogloss:2.20880	validation-mlogloss:2.16647
[61]	train-mlogloss:2.20399	validation-mlogloss:2.16159
[62]	train-mlogloss:2.19929	validation-mlogloss:2.15656
[63]	train-mlogloss:2.19449	validation-mlogloss:2.15203
[64]	train-mlogloss:2.18994	validation-mlogloss:2.14735
[65]	train-mlogloss:2.18532	validation-mlogloss:2.14242
[66]	train-mlogloss:2.18091	validation-mlogloss:2.13793
[67]	train-mlogloss:2.17630	validation-mlogloss:2.13343
[68]	train-mlogloss:2.17176	validation-mlogloss:2.12885
[69]	train-mlogloss:2.16762	validation-mlogloss:2.12493
[70]	train-mlogloss:2.16342	validation-mlogloss:2.12064
[71]	train-mlogloss:2.15926	validation-mlogloss:2.11666
[72]	train-mlogloss:2.15490	validation-mlogloss:2.11237
[73]	train-mlogloss:2.15086	validation-mlogloss:2.10826
[74]	train-mlogloss:2.14689	validation-mlogloss:2.10369
[75]	train-mlogloss:2.14297	validation-mlogloss:2.09946
[76]	train-mlogloss:2.13885	validation-mlogloss:2.09549
[77]	train-mlogloss:2.13475	validation-mlogloss:2.09108
[78]	train-mlogloss:2.13085	validation-mlogloss:2.08762
[79]	train-mlogloss:2.12700	validation-mlogloss:2.08389
[80]	train-mlogloss:2.12339	validation-mlogloss:2.08025
[81]	train-mlogloss:2.11953	validation-mlogloss:2.07656
[82]	train-mlogloss:2.11593	validation-mlogloss:2.07284
[83]	train-mlogloss:2.11208	validation-mlogloss:2.06931
[84]	train-mlogloss:2.10838	validation-mlogloss:2.06570
[85]	train-mlogloss:2.10482	validation-mlogloss:2.06216
[86]	train-mlogloss:2.10125	validation-mlogloss:2.05859
[87]	train-mlogloss:2.09773	validation-mlogloss:2.05534
[88]	train-mlogloss:2.09423	validation-mlogloss:2.05210
[89]	train-mlogloss:2.09084	validation-mlogloss:2.04881
[90]	train-mlogloss:2.08752	validation-mlogloss:2.04593
[91]	train-mlogloss:2.08415	validation-mlogloss:2.04321
[92]	train-mlogloss:2.08069	validation-mlogloss:2.04011
[93]	train-mlogloss:2.07729	validation-mlogloss:2.03682
[94]	train-mlogloss:2.07395	validation-mlogloss:2.03344
[95]	train-mlogloss:2.07072	validation-mlogloss:2.03029
[96]	train-mlogloss:2.06754	validation-mlogloss:2.02716
[97]	train-mlogloss:2.06429	validation-mlogloss:2.02392
[98]	train-mlogloss:2.06110	validation-mlogloss:2.02127
[99]	train-mlogloss:2.05788	validation-mlogloss:2.01845
[100]	train-mlogloss:2.05473	validation-mlogloss:2.01556
[101]	train-mlogloss:2.05164	validation-mlogloss:2.01278
[102]	train-mlogloss:2.04843	validation-mlogloss:2.00960
[103]	train-mlogloss:2.04510	validation-mlogloss:2.00657
[104]	train-mlogloss:2.04204	validation-mlogloss:2.00390
[105]	train-mlogloss:2.03910	validation-mlogloss:2.00139
[106]	train-mlogloss:2.03628	validation-mlogloss:1.99876
[107]	train-mlogloss:2.03344	validation-mlogloss:1.99618
[108]	train-mlogloss:2.03046	validation-mlogloss:1.99290
[109]	train-mlogloss:2.02755	validation-mlogloss:1.99025
[110]	train-mlogloss:2.02473	validation-mlogloss:1.98797
[111]	train-mlogloss:2.02189	validation-mlogloss:1.98512
[112]	train-mlogloss:2.01920	validation-mlogloss:1.98229
[113]	train-mlogloss:2.01632	validation-mlogloss:1.97948
[114]	train-mlogloss:2.01352	validation-mlogloss:1.97701
[115]	train-mlogloss:2.01077	validation-mlogloss:1.97452
[116]	train-mlogloss:2.00815	validation-mlogloss:1.97214
[117]	train-mlogloss:2.00545	validation-mlogloss:1.96984
[118]	train-mlogloss:2.00290	validation-mlogloss:1.96765
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[508]	train-mlogloss:1.57303	validation-mlogloss:1.68834
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[513]	train-mlogloss:1.57052	validation-mlogloss:1.68787
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[515]	train-mlogloss:1.56958	validation-mlogloss:1.68762
[516]	train-mlogloss:1.56904	validation-mlogloss:1.68734
[517]	train-mlogloss:1.56854	validation-mlogloss:1.68716
[518]	train-mlogloss:1.56802	validation-mlogloss:1.68686
[519]	train-mlogloss:1.56751	validation-mlogloss:1.68675
[520]	train-mlogloss:1.56699	validation-mlogloss:1.68653
[521]	train-mlogloss:1.56648	validation-mlogloss:1.68644
[522]	train-mlogloss:1.56592	validation-mlogloss:1.68616
[523]	train-mlogloss:1.56548	validation-mlogloss:1.68610
[524]	train-mlogloss:1.56491	validation-mlogloss:1.68586
[525]	train-mlogloss:1.56451	validation-mlogloss:1.68583
[526]	train-mlogloss:1.56404	validation-mlogloss:1.68561
[527]	train-mlogloss:1.56355	validation-mlogloss:1.68551
[528]	train-mlogloss:1.56309	validation-mlogloss:1.68560
[529]	train-mlogloss:1.56264	validation-mlogloss:1.68550
[530]	train-mlogloss:1.56221	validation-mlogloss:1.68543
[531]	train-mlogloss:1.56170	validation-mlogloss:1.68529
[532]	train-mlogloss:1.56119	validation-mlogloss:1.68528
[533]	train-mlogloss:1.56075	validation-mlogloss:1.68520
[534]	train-mlogloss:1.56036	validation-mlogloss:1.68516
[535]	train-mlogloss:1.55988	validation-mlogloss:1.68499
[536]	train-mlogloss:1.55945	validation-mlogloss:1.68478
[537]	train-mlogloss:1.55895	validation-mlogloss:1.68457
[538]	train-mlogloss:1.55844	validation-mlogloss:1.68442
[539]	train-mlogloss:1.55798	validation-mlogloss:1.68434
Saved model to disk.
2025-10-27 09:56:13.574488: 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`.
2025-10-27 09:56:13.587544: 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 00:00:1761555373.601953  425807 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555373.606339  425807 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555373.617922  425807 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555373.617955  425807 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555373.617959  425807 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555373.617961  425807 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:56:13.621437: 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:2.68211	validation-mlogloss:2.67896
[2]	train-mlogloss:2.66768	validation-mlogloss:2.66312
[3]	train-mlogloss:2.65426	validation-mlogloss:2.64781
[4]	train-mlogloss:2.64152	validation-mlogloss:2.63375
[5]	train-mlogloss:2.62897	validation-mlogloss:2.61941
[6]	train-mlogloss:2.61631	validation-mlogloss:2.60616
[7]	train-mlogloss:2.60467	validation-mlogloss:2.59225
[8]	train-mlogloss:2.59375	validation-mlogloss:2.57994
[9]	train-mlogloss:2.58218	validation-mlogloss:2.56732
[10]	train-mlogloss:2.57104	validation-mlogloss:2.55505
[11]	train-mlogloss:2.56000	validation-mlogloss:2.54310
[12]	train-mlogloss:2.54940	validation-mlogloss:2.53219
[13]	train-mlogloss:2.53879	validation-mlogloss:2.52020
[14]	train-mlogloss:2.52857	validation-mlogloss:2.50955
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[16]	train-mlogloss:2.50926	validation-mlogloss:2.48881
[17]	train-mlogloss:2.49979	validation-mlogloss:2.47838
[18]	train-mlogloss:2.49124	validation-mlogloss:2.46808
[19]	train-mlogloss:2.48213	validation-mlogloss:2.45752
[20]	train-mlogloss:2.47256	validation-mlogloss:2.44646
[21]	train-mlogloss:2.46374	validation-mlogloss:2.43729
[22]	train-mlogloss:2.45474	validation-mlogloss:2.42714
[23]	train-mlogloss:2.44637	validation-mlogloss:2.41829
[24]	train-mlogloss:2.43809	validation-mlogloss:2.40952
[25]	train-mlogloss:2.42935	validation-mlogloss:2.39991
[26]	train-mlogloss:2.42120	validation-mlogloss:2.39100
[27]	train-mlogloss:2.41275	validation-mlogloss:2.38212
[28]	train-mlogloss:2.40510	validation-mlogloss:2.37326
[29]	train-mlogloss:2.39732	validation-mlogloss:2.36473
[30]	train-mlogloss:2.38970	validation-mlogloss:2.35657
[31]	train-mlogloss:2.38223	validation-mlogloss:2.34839
[32]	train-mlogloss:2.37435	validation-mlogloss:2.33977
[33]	train-mlogloss:2.36716	validation-mlogloss:2.33229
[34]	train-mlogloss:2.35971	validation-mlogloss:2.32426
[35]	train-mlogloss:2.35286	validation-mlogloss:2.31672
[36]	train-mlogloss:2.34575	validation-mlogloss:2.30874
[37]	train-mlogloss:2.33906	validation-mlogloss:2.30143
[38]	train-mlogloss:2.33259	validation-mlogloss:2.29470
[39]	train-mlogloss:2.32627	validation-mlogloss:2.28860
[40]	train-mlogloss:2.31963	validation-mlogloss:2.28148
[41]	train-mlogloss:2.31322	validation-mlogloss:2.27454
[42]	train-mlogloss:2.30699	validation-mlogloss:2.26800
[43]	train-mlogloss:2.30115	validation-mlogloss:2.26222
[44]	train-mlogloss:2.29510	validation-mlogloss:2.25602
[45]	train-mlogloss:2.28904	validation-mlogloss:2.24947
[46]	train-mlogloss:2.28277	validation-mlogloss:2.24271
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[48]	train-mlogloss:2.27157	validation-mlogloss:2.23048
[49]	train-mlogloss:2.26598	validation-mlogloss:2.22455
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[51]	train-mlogloss:2.25540	validation-mlogloss:2.21331
[52]	train-mlogloss:2.24984	validation-mlogloss:2.20708
[53]	train-mlogloss:2.24441	validation-mlogloss:2.20176
[54]	train-mlogloss:2.23918	validation-mlogloss:2.19607
[55]	train-mlogloss:2.23399	validation-mlogloss:2.19112
[56]	train-mlogloss:2.22875	validation-mlogloss:2.18568
[57]	train-mlogloss:2.22371	validation-mlogloss:2.18064
[58]	train-mlogloss:2.21879	validation-mlogloss:2.17523
[59]	train-mlogloss:2.21391	validation-mlogloss:2.17018
[60]	train-mlogloss:2.20909	validation-mlogloss:2.16549
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[62]	train-mlogloss:2.19923	validation-mlogloss:2.15509
[63]	train-mlogloss:2.19473	validation-mlogloss:2.15041
[64]	train-mlogloss:2.19013	validation-mlogloss:2.14552
[65]	train-mlogloss:2.18548	validation-mlogloss:2.14046
[66]	train-mlogloss:2.18090	validation-mlogloss:2.13573
[67]	train-mlogloss:2.17659	validation-mlogloss:2.13123
[68]	train-mlogloss:2.17211	validation-mlogloss:2.12726
[69]	train-mlogloss:2.16778	validation-mlogloss:2.12285
[70]	train-mlogloss:2.16352	validation-mlogloss:2.11886
[71]	train-mlogloss:2.15934	validation-mlogloss:2.11474
[72]	train-mlogloss:2.15539	validation-mlogloss:2.11072
[73]	train-mlogloss:2.15140	validation-mlogloss:2.10708
[74]	train-mlogloss:2.14704	validation-mlogloss:2.10266
[75]	train-mlogloss:2.14278	validation-mlogloss:2.09850
[76]	train-mlogloss:2.13872	validation-mlogloss:2.09466
[77]	train-mlogloss:2.13467	validation-mlogloss:2.09111
[78]	train-mlogloss:2.13067	validation-mlogloss:2.08720
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[102]	train-mlogloss:2.04731	validation-mlogloss:2.00853
[103]	train-mlogloss:2.04410	validation-mlogloss:2.00574
[104]	train-mlogloss:2.04130	validation-mlogloss:2.00356
[105]	train-mlogloss:2.03829	validation-mlogloss:2.00082
[106]	train-mlogloss:2.03541	validation-mlogloss:1.99816
[107]	train-mlogloss:2.03241	validation-mlogloss:1.99582
[108]	train-mlogloss:2.02937	validation-mlogloss:1.99285
[109]	train-mlogloss:2.02648	validation-mlogloss:1.99053
[110]	train-mlogloss:2.02356	validation-mlogloss:1.98756
[111]	train-mlogloss:2.02050	validation-mlogloss:1.98483
[112]	train-mlogloss:2.01752	validation-mlogloss:1.98244
[113]	train-mlogloss:2.01485	validation-mlogloss:1.98006
[114]	train-mlogloss:2.01196	validation-mlogloss:1.97748
[115]	train-mlogloss:2.00930	validation-mlogloss:1.97514
[116]	train-mlogloss:2.00676	validation-mlogloss:1.97287
[117]	train-mlogloss:2.00403	validation-mlogloss:1.97061
[118]	train-mlogloss:2.00103	validation-mlogloss:1.96776
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[123]	train-mlogloss:1.98821	validation-mlogloss:1.95643
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[125]	train-mlogloss:1.98314	validation-mlogloss:1.95193
[126]	train-mlogloss:1.98056	validation-mlogloss:1.94978
[127]	train-mlogloss:1.97819	validation-mlogloss:1.94764
[128]	train-mlogloss:1.97576	validation-mlogloss:1.94531
[129]	train-mlogloss:1.97345	validation-mlogloss:1.94328
[130]	train-mlogloss:1.97115	validation-mlogloss:1.94161
[131]	train-mlogloss:1.96874	validation-mlogloss:1.93943
[132]	train-mlogloss:1.96642	validation-mlogloss:1.93706
[133]	train-mlogloss:1.96389	validation-mlogloss:1.93500
[134]	train-mlogloss:1.96146	validation-mlogloss:1.93288
[135]	train-mlogloss:1.95912	validation-mlogloss:1.93094
[136]	train-mlogloss:1.95665	validation-mlogloss:1.92851
[137]	train-mlogloss:1.95435	validation-mlogloss:1.92642
[138]	train-mlogloss:1.95214	validation-mlogloss:1.92440
[139]	train-mlogloss:1.94990	validation-mlogloss:1.92237
[140]	train-mlogloss:1.94759	validation-mlogloss:1.92047
[141]	train-mlogloss:1.94536	validation-mlogloss:1.91863
[142]	train-mlogloss:1.94314	validation-mlogloss:1.91689
[143]	train-mlogloss:1.94100	validation-mlogloss:1.91526
[144]	train-mlogloss:1.93881	validation-mlogloss:1.91356
[145]	train-mlogloss:1.93660	validation-mlogloss:1.91197
[146]	train-mlogloss:1.93447	validation-mlogloss:1.91014
[147]	train-mlogloss:1.93220	validation-mlogloss:1.90812
[148]	train-mlogloss:1.93009	validation-mlogloss:1.90642
[149]	train-mlogloss:1.92804	validation-mlogloss:1.90468
[150]	train-mlogloss:1.92568	validation-mlogloss:1.90252
[151]	train-mlogloss:1.92358	validation-mlogloss:1.90093
[152]	train-mlogloss:1.92154	validation-mlogloss:1.89909
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[453]	train-mlogloss:1.60379	validation-mlogloss:1.69880
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[455]	train-mlogloss:1.60249	validation-mlogloss:1.69838
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[458]	train-mlogloss:1.60080	validation-mlogloss:1.69737
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[461]	train-mlogloss:1.59910	validation-mlogloss:1.69674
[462]	train-mlogloss:1.59851	validation-mlogloss:1.69668
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[464]	train-mlogloss:1.59734	validation-mlogloss:1.69636
[465]	train-mlogloss:1.59681	validation-mlogloss:1.69625
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[467]	train-mlogloss:1.59578	validation-mlogloss:1.69577
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[469]	train-mlogloss:1.59468	validation-mlogloss:1.69543
[470]	train-mlogloss:1.59412	validation-mlogloss:1.69514
[471]	train-mlogloss:1.59353	validation-mlogloss:1.69497
[472]	train-mlogloss:1.59301	validation-mlogloss:1.69481
[473]	train-mlogloss:1.59242	validation-mlogloss:1.69459
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[475]	train-mlogloss:1.59124	validation-mlogloss:1.69397
[476]	train-mlogloss:1.59075	validation-mlogloss:1.69372
[477]	train-mlogloss:1.59020	validation-mlogloss:1.69352
[478]	train-mlogloss:1.58968	validation-mlogloss:1.69336
[479]	train-mlogloss:1.58914	validation-mlogloss:1.69300
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[485]	train-mlogloss:1.58603	validation-mlogloss:1.69214
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[490]	train-mlogloss:1.58336	validation-mlogloss:1.69189
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[498]	train-mlogloss:1.57904	validation-mlogloss:1.69008
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[503]	train-mlogloss:1.57654	validation-mlogloss:1.68953
[504]	train-mlogloss:1.57601	validation-mlogloss:1.68946
[505]	train-mlogloss:1.57554	validation-mlogloss:1.68922
[506]	train-mlogloss:1.57505	validation-mlogloss:1.68931
[507]	train-mlogloss:1.57454	validation-mlogloss:1.68913
[508]	train-mlogloss:1.57410	validation-mlogloss:1.68902
[509]	train-mlogloss:1.57356	validation-mlogloss:1.68869
[510]	train-mlogloss:1.57306	validation-mlogloss:1.68868
[511]	train-mlogloss:1.57256	validation-mlogloss:1.68846
[512]	train-mlogloss:1.57208	validation-mlogloss:1.68836
[513]	train-mlogloss:1.57156	validation-mlogloss:1.68815
[514]	train-mlogloss:1.57106	validation-mlogloss:1.68791
[515]	train-mlogloss:1.57053	validation-mlogloss:1.68764
[516]	train-mlogloss:1.56994	validation-mlogloss:1.68746
[517]	train-mlogloss:1.56940	validation-mlogloss:1.68706
[518]	train-mlogloss:1.56891	validation-mlogloss:1.68693
[519]	train-mlogloss:1.56832	validation-mlogloss:1.68665
[520]	train-mlogloss:1.56782	validation-mlogloss:1.68637
[521]	train-mlogloss:1.56737	validation-mlogloss:1.68609
[522]	train-mlogloss:1.56690	validation-mlogloss:1.68597
[523]	train-mlogloss:1.56634	validation-mlogloss:1.68587
[524]	train-mlogloss:1.56583	validation-mlogloss:1.68574
[525]	train-mlogloss:1.56529	validation-mlogloss:1.68569
[526]	train-mlogloss:1.56488	validation-mlogloss:1.68569
[527]	train-mlogloss:1.56449	validation-mlogloss:1.68569
[528]	train-mlogloss:1.56403	validation-mlogloss:1.68560
[529]	train-mlogloss:1.56361	validation-mlogloss:1.68560
[530]	train-mlogloss:1.56306	validation-mlogloss:1.68547
[531]	train-mlogloss:1.56258	validation-mlogloss:1.68550
[532]	train-mlogloss:1.56215	validation-mlogloss:1.68540
[533]	train-mlogloss:1.56175	validation-mlogloss:1.68543
[534]	train-mlogloss:1.56133	validation-mlogloss:1.68514
[535]	train-mlogloss:1.56088	validation-mlogloss:1.68512
[536]	train-mlogloss:1.56045	validation-mlogloss:1.68498
[537]	train-mlogloss:1.56003	validation-mlogloss:1.68499
[538]	train-mlogloss:1.55956	validation-mlogloss:1.68474
[539]	train-mlogloss:1.55907	validation-mlogloss:1.68454
Saved model to disk.
2025-10-27 09:56:59.427963: 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`.
2025-10-27 09:56:59.440717: 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 00:00:1761555419.454565  426694 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555419.459063  426694 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555419.470055  426694 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555419.470080  426694 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555419.470083  426694 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555419.470085  426694 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:56:59.473498: 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:2.67810	validation-mlogloss:2.67515
[2]	train-mlogloss:2.66406	validation-mlogloss:2.65967
[3]	train-mlogloss:2.65219	validation-mlogloss:2.64631
[4]	train-mlogloss:2.63911	validation-mlogloss:2.63146
[5]	train-mlogloss:2.62628	validation-mlogloss:2.61658
[6]	train-mlogloss:2.61472	validation-mlogloss:2.60395
[7]	train-mlogloss:2.60349	validation-mlogloss:2.59119
[8]	train-mlogloss:2.59170	validation-mlogloss:2.57811
[9]	train-mlogloss:2.58011	validation-mlogloss:2.56486
[10]	train-mlogloss:2.56914	validation-mlogloss:2.55267
[11]	train-mlogloss:2.55814	validation-mlogloss:2.54043
[12]	train-mlogloss:2.54784	validation-mlogloss:2.52942
[13]	train-mlogloss:2.53688	validation-mlogloss:2.51710
[14]	train-mlogloss:2.52659	validation-mlogloss:2.50614
[15]	train-mlogloss:2.51575	validation-mlogloss:2.49383
[16]	train-mlogloss:2.50633	validation-mlogloss:2.48276
[17]	train-mlogloss:2.49685	validation-mlogloss:2.47320
[18]	train-mlogloss:2.48749	validation-mlogloss:2.46328
[19]	train-mlogloss:2.47807	validation-mlogloss:2.45262
[20]	train-mlogloss:2.46879	validation-mlogloss:2.44204
[21]	train-mlogloss:2.46046	validation-mlogloss:2.43255
[22]	train-mlogloss:2.45146	validation-mlogloss:2.42284
[23]	train-mlogloss:2.44343	validation-mlogloss:2.41382
[24]	train-mlogloss:2.43512	validation-mlogloss:2.40489
[25]	train-mlogloss:2.42662	validation-mlogloss:2.39513
[26]	train-mlogloss:2.41850	validation-mlogloss:2.38629
[27]	train-mlogloss:2.41033	validation-mlogloss:2.37798
[28]	train-mlogloss:2.40225	validation-mlogloss:2.36968
[29]	train-mlogloss:2.39431	validation-mlogloss:2.36103
[30]	train-mlogloss:2.38721	validation-mlogloss:2.35362
[31]	train-mlogloss:2.37966	validation-mlogloss:2.34556
[32]	train-mlogloss:2.37216	validation-mlogloss:2.33702
[33]	train-mlogloss:2.36503	validation-mlogloss:2.32953
[34]	train-mlogloss:2.35805	validation-mlogloss:2.32224
[35]	train-mlogloss:2.35115	validation-mlogloss:2.31417
[36]	train-mlogloss:2.34383	validation-mlogloss:2.30678
[37]	train-mlogloss:2.33713	validation-mlogloss:2.29983
[38]	train-mlogloss:2.33060	validation-mlogloss:2.29281
[39]	train-mlogloss:2.32406	validation-mlogloss:2.28549
[40]	train-mlogloss:2.31746	validation-mlogloss:2.27831
[41]	train-mlogloss:2.31106	validation-mlogloss:2.27115
[42]	train-mlogloss:2.30497	validation-mlogloss:2.26433
[43]	train-mlogloss:2.29885	validation-mlogloss:2.25745
[44]	train-mlogloss:2.29278	validation-mlogloss:2.25153
[45]	train-mlogloss:2.28708	validation-mlogloss:2.24557
[46]	train-mlogloss:2.28143	validation-mlogloss:2.24020
[47]	train-mlogloss:2.27555	validation-mlogloss:2.23391
[48]	train-mlogloss:2.26977	validation-mlogloss:2.22769
[49]	train-mlogloss:2.26419	validation-mlogloss:2.22181
[50]	train-mlogloss:2.25886	validation-mlogloss:2.21654
[51]	train-mlogloss:2.25351	validation-mlogloss:2.21127
[52]	train-mlogloss:2.24784	validation-mlogloss:2.20528
[53]	train-mlogloss:2.24261	validation-mlogloss:2.19988
[54]	train-mlogloss:2.23724	validation-mlogloss:2.19499
[55]	train-mlogloss:2.23202	validation-mlogloss:2.19002
[56]	train-mlogloss:2.22704	validation-mlogloss:2.18500
[57]	train-mlogloss:2.22187	validation-mlogloss:2.17990
[58]	train-mlogloss:2.21665	validation-mlogloss:2.17424
[59]	train-mlogloss:2.21167	validation-mlogloss:2.16925
[60]	train-mlogloss:2.20688	validation-mlogloss:2.16460
[61]	train-mlogloss:2.20212	validation-mlogloss:2.15991
[62]	train-mlogloss:2.19738	validation-mlogloss:2.15481
[63]	train-mlogloss:2.19293	validation-mlogloss:2.14998
[64]	train-mlogloss:2.18848	validation-mlogloss:2.14539
[65]	train-mlogloss:2.18416	validation-mlogloss:2.14064
[66]	train-mlogloss:2.17972	validation-mlogloss:2.13628
[67]	train-mlogloss:2.17509	validation-mlogloss:2.13140
[68]	train-mlogloss:2.17088	validation-mlogloss:2.12727
[69]	train-mlogloss:2.16655	validation-mlogloss:2.12319
[70]	train-mlogloss:2.16224	validation-mlogloss:2.11834
[71]	train-mlogloss:2.15794	validation-mlogloss:2.11401
[72]	train-mlogloss:2.15368	validation-mlogloss:2.10975
[73]	train-mlogloss:2.14968	validation-mlogloss:2.10633
[74]	train-mlogloss:2.14560	validation-mlogloss:2.10232
[75]	train-mlogloss:2.14183	validation-mlogloss:2.09877
[76]	train-mlogloss:2.13789	validation-mlogloss:2.09519
[77]	train-mlogloss:2.13382	validation-mlogloss:2.09105
[78]	train-mlogloss:2.13000	validation-mlogloss:2.08737
[79]	train-mlogloss:2.12604	validation-mlogloss:2.08356
[80]	train-mlogloss:2.12226	validation-mlogloss:2.07977
[81]	train-mlogloss:2.11849	validation-mlogloss:2.07658
[82]	train-mlogloss:2.11451	validation-mlogloss:2.07251
[83]	train-mlogloss:2.11058	validation-mlogloss:2.06908
[84]	train-mlogloss:2.10697	validation-mlogloss:2.06513
[85]	train-mlogloss:2.10310	validation-mlogloss:2.06151
[86]	train-mlogloss:2.09954	validation-mlogloss:2.05826
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[89]	train-mlogloss:2.08928	validation-mlogloss:2.04860
[90]	train-mlogloss:2.08567	validation-mlogloss:2.04470
[91]	train-mlogloss:2.08229	validation-mlogloss:2.04179
[92]	train-mlogloss:2.07885	validation-mlogloss:2.03817
[93]	train-mlogloss:2.07550	validation-mlogloss:2.03500
[94]	train-mlogloss:2.07218	validation-mlogloss:2.03179
[95]	train-mlogloss:2.06895	validation-mlogloss:2.02881
[96]	train-mlogloss:2.06576	validation-mlogloss:2.02596
[97]	train-mlogloss:2.06269	validation-mlogloss:2.02321
[98]	train-mlogloss:2.05950	validation-mlogloss:2.01978
[99]	train-mlogloss:2.05640	validation-mlogloss:2.01722
[100]	train-mlogloss:2.05337	validation-mlogloss:2.01473
[101]	train-mlogloss:2.05048	validation-mlogloss:2.01226
[102]	train-mlogloss:2.04749	validation-mlogloss:2.00936
[103]	train-mlogloss:2.04438	validation-mlogloss:2.00625
[104]	train-mlogloss:2.04133	validation-mlogloss:2.00371
[105]	train-mlogloss:2.03828	validation-mlogloss:2.00102
[106]	train-mlogloss:2.03524	validation-mlogloss:1.99817
[107]	train-mlogloss:2.03219	validation-mlogloss:1.99558
[108]	train-mlogloss:2.02918	validation-mlogloss:1.99257
[109]	train-mlogloss:2.02630	validation-mlogloss:1.98974
[110]	train-mlogloss:2.02357	validation-mlogloss:1.98731
[111]	train-mlogloss:2.02070	validation-mlogloss:1.98468
[112]	train-mlogloss:2.01793	validation-mlogloss:1.98187
[113]	train-mlogloss:2.01521	validation-mlogloss:1.97907
[114]	train-mlogloss:2.01228	validation-mlogloss:1.97624
[115]	train-mlogloss:2.00958	validation-mlogloss:1.97364
[116]	train-mlogloss:2.00694	validation-mlogloss:1.97119
[117]	train-mlogloss:2.00427	validation-mlogloss:1.96858
[118]	train-mlogloss:2.00172	validation-mlogloss:1.96638
[119]	train-mlogloss:1.99905	validation-mlogloss:1.96365
[120]	train-mlogloss:1.99651	validation-mlogloss:1.96141
[121]	train-mlogloss:1.99391	validation-mlogloss:1.95919
[122]	train-mlogloss:1.99127	validation-mlogloss:1.95677
[123]	train-mlogloss:1.98886	validation-mlogloss:1.95461
[124]	train-mlogloss:1.98637	validation-mlogloss:1.95257
[125]	train-mlogloss:1.98377	validation-mlogloss:1.95022
[126]	train-mlogloss:1.98136	validation-mlogloss:1.94792
[127]	train-mlogloss:1.97884	validation-mlogloss:1.94571
[128]	train-mlogloss:1.97647	validation-mlogloss:1.94342
[129]	train-mlogloss:1.97408	validation-mlogloss:1.94136
[130]	train-mlogloss:1.97174	validation-mlogloss:1.93908
[131]	train-mlogloss:1.96933	validation-mlogloss:1.93703
[132]	train-mlogloss:1.96684	validation-mlogloss:1.93483
[133]	train-mlogloss:1.96455	validation-mlogloss:1.93295
[134]	train-mlogloss:1.96215	validation-mlogloss:1.93076
[135]	train-mlogloss:1.95994	validation-mlogloss:1.92885
[136]	train-mlogloss:1.95743	validation-mlogloss:1.92676
[137]	train-mlogloss:1.95498	validation-mlogloss:1.92452
[138]	train-mlogloss:1.95272	validation-mlogloss:1.92251
[139]	train-mlogloss:1.95061	validation-mlogloss:1.92087
[140]	train-mlogloss:1.94839	validation-mlogloss:1.91902
[141]	train-mlogloss:1.94613	validation-mlogloss:1.91724
[142]	train-mlogloss:1.94403	validation-mlogloss:1.91542
[143]	train-mlogloss:1.94180	validation-mlogloss:1.91364
[144]	train-mlogloss:1.93965	validation-mlogloss:1.91180
[145]	train-mlogloss:1.93745	validation-mlogloss:1.90984
[146]	train-mlogloss:1.93534	validation-mlogloss:1.90802
[147]	train-mlogloss:1.93329	validation-mlogloss:1.90624
[148]	train-mlogloss:1.93121	validation-mlogloss:1.90458
[149]	train-mlogloss:1.92898	validation-mlogloss:1.90292
[150]	train-mlogloss:1.92694	validation-mlogloss:1.90109
[151]	train-mlogloss:1.92496	validation-mlogloss:1.89919
[152]	train-mlogloss:1.92299	validation-mlogloss:1.89770
[153]	train-mlogloss:1.92080	validation-mlogloss:1.89606
[154]	train-mlogloss:1.91873	validation-mlogloss:1.89434
[155]	train-mlogloss:1.91672	validation-mlogloss:1.89278
[156]	train-mlogloss:1.91447	validation-mlogloss:1.89062
[157]	train-mlogloss:1.91250	validation-mlogloss:1.88878
[158]	train-mlogloss:1.91057	validation-mlogloss:1.88695
[159]	train-mlogloss:1.90852	validation-mlogloss:1.88522
[160]	train-mlogloss:1.90652	validation-mlogloss:1.88373
[161]	train-mlogloss:1.90452	validation-mlogloss:1.88193
[162]	train-mlogloss:1.90278	validation-mlogloss:1.88034
[163]	train-mlogloss:1.90090	validation-mlogloss:1.87861
[164]	train-mlogloss:1.89893	validation-mlogloss:1.87701
[165]	train-mlogloss:1.89688	validation-mlogloss:1.87538
[166]	train-mlogloss:1.89496	validation-mlogloss:1.87367
[167]	train-mlogloss:1.89313	validation-mlogloss:1.87199
[168]	train-mlogloss:1.89109	validation-mlogloss:1.87033
[169]	train-mlogloss:1.88917	validation-mlogloss:1.86849
[170]	train-mlogloss:1.88741	validation-mlogloss:1.86665
[171]	train-mlogloss:1.88575	validation-mlogloss:1.86538
[172]	train-mlogloss:1.88385	validation-mlogloss:1.86393
[173]	train-mlogloss:1.88204	validation-mlogloss:1.86261
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[176]	train-mlogloss:1.87709	validation-mlogloss:1.85897
[177]	train-mlogloss:1.87541	validation-mlogloss:1.85753
[178]	train-mlogloss:1.87367	validation-mlogloss:1.85607
[179]	train-mlogloss:1.87198	validation-mlogloss:1.85521
[180]	train-mlogloss:1.87033	validation-mlogloss:1.85406
[181]	train-mlogloss:1.86861	validation-mlogloss:1.85261
[182]	train-mlogloss:1.86697	validation-mlogloss:1.85099
[183]	train-mlogloss:1.86537	validation-mlogloss:1.84975
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[185]	train-mlogloss:1.86197	validation-mlogloss:1.84745
[186]	train-mlogloss:1.86032	validation-mlogloss:1.84633
[187]	train-mlogloss:1.85869	validation-mlogloss:1.84508
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[488]	train-mlogloss:1.58478	validation-mlogloss:1.69076
[489]	train-mlogloss:1.58428	validation-mlogloss:1.69071
[490]	train-mlogloss:1.58375	validation-mlogloss:1.69058
[491]	train-mlogloss:1.58323	validation-mlogloss:1.69053
[492]	train-mlogloss:1.58270	validation-mlogloss:1.69053
[493]	train-mlogloss:1.58221	validation-mlogloss:1.69046
[494]	train-mlogloss:1.58180	validation-mlogloss:1.69024
[495]	train-mlogloss:1.58132	validation-mlogloss:1.69001
[496]	train-mlogloss:1.58081	validation-mlogloss:1.68985
[497]	train-mlogloss:1.58028	validation-mlogloss:1.68985
[498]	train-mlogloss:1.57983	validation-mlogloss:1.68977
[499]	train-mlogloss:1.57928	validation-mlogloss:1.68954
[500]	train-mlogloss:1.57877	validation-mlogloss:1.68944
[501]	train-mlogloss:1.57828	validation-mlogloss:1.68933
[502]	train-mlogloss:1.57772	validation-mlogloss:1.68933
[503]	train-mlogloss:1.57723	validation-mlogloss:1.68907
[504]	train-mlogloss:1.57679	validation-mlogloss:1.68897
[505]	train-mlogloss:1.57628	validation-mlogloss:1.68881
[506]	train-mlogloss:1.57575	validation-mlogloss:1.68855
[507]	train-mlogloss:1.57524	validation-mlogloss:1.68851
[508]	train-mlogloss:1.57473	validation-mlogloss:1.68848
[509]	train-mlogloss:1.57419	validation-mlogloss:1.68846
[510]	train-mlogloss:1.57370	validation-mlogloss:1.68841
[511]	train-mlogloss:1.57327	validation-mlogloss:1.68833
[512]	train-mlogloss:1.57274	validation-mlogloss:1.68816
[513]	train-mlogloss:1.57223	validation-mlogloss:1.68778
[514]	train-mlogloss:1.57172	validation-mlogloss:1.68769
[515]	train-mlogloss:1.57125	validation-mlogloss:1.68765
[516]	train-mlogloss:1.57076	validation-mlogloss:1.68749
[517]	train-mlogloss:1.57017	validation-mlogloss:1.68728
[518]	train-mlogloss:1.56969	validation-mlogloss:1.68723
[519]	train-mlogloss:1.56918	validation-mlogloss:1.68701
[520]	train-mlogloss:1.56871	validation-mlogloss:1.68677
[521]	train-mlogloss:1.56826	validation-mlogloss:1.68674
[522]	train-mlogloss:1.56779	validation-mlogloss:1.68659
[523]	train-mlogloss:1.56721	validation-mlogloss:1.68636
[524]	train-mlogloss:1.56678	validation-mlogloss:1.68639
[525]	train-mlogloss:1.56633	validation-mlogloss:1.68640
[526]	train-mlogloss:1.56585	validation-mlogloss:1.68635
[527]	train-mlogloss:1.56539	validation-mlogloss:1.68622
[528]	train-mlogloss:1.56494	validation-mlogloss:1.68618
[529]	train-mlogloss:1.56453	validation-mlogloss:1.68599
[530]	train-mlogloss:1.56407	validation-mlogloss:1.68602
[531]	train-mlogloss:1.56355	validation-mlogloss:1.68586
[532]	train-mlogloss:1.56306	validation-mlogloss:1.68569
[533]	train-mlogloss:1.56264	validation-mlogloss:1.68565
[534]	train-mlogloss:1.56220	validation-mlogloss:1.68572
[535]	train-mlogloss:1.56175	validation-mlogloss:1.68547
[536]	train-mlogloss:1.56133	validation-mlogloss:1.68536
[537]	train-mlogloss:1.56093	validation-mlogloss:1.68522
[538]	train-mlogloss:1.56047	validation-mlogloss:1.68500
[539]	train-mlogloss:1.56002	validation-mlogloss:1.68488
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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.5 [%]
Global accuracy score (test) = 45.12 [%]
Global F1 score (train) = 51.63 [%]
Global F1 score (test) = 44.36 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.76      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.38      0.46      0.42       184
       CAMINAR USUAL SPEED       0.35      0.29      0.32       184
            CAMINAR ZIGZAG       0.38      0.51      0.44       184
          DE PIE BARRIENDO       0.76      0.29      0.42       184
   DE PIE DOBLANDO TOALLAS       0.51      0.43      0.46       184
    DE PIE MOVIENDO LIBROS       0.40      0.35      0.37       184
          DE PIE USANDO PC       0.22      0.34      0.27       184
        FASE REPOSO CON K5       0.57      0.86      0.69       184
INCREMENTAL CICLOERGOMETRO       0.76      0.70      0.73       184
           SENTADO LEYENDO       0.45      0.38      0.41       184
         SENTADO USANDO PC       0.19      0.10      0.13       184
      SENTADO VIENDO LA TV       0.26      0.21      0.23       184
   SUBIR Y BAJAR ESCALERAS       0.63      0.54      0.58       184
                    TROTAR       0.64      0.57      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 25: 45.12 [%]
F1-score capturado en la ejecución 25: 44.36 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.26 [%]
Global accuracy score (test) = 44.72 [%]
Global F1 score (train) = 51.38 [%]
Global F1 score (test) = 44.03 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.75      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.37      0.48      0.42       184
       CAMINAR USUAL SPEED       0.35      0.30      0.32       184
            CAMINAR ZIGZAG       0.40      0.52      0.45       184
          DE PIE BARRIENDO       0.75      0.28      0.41       184
   DE PIE DOBLANDO TOALLAS       0.50      0.42      0.46       184
    DE PIE MOVIENDO LIBROS       0.36      0.33      0.34       184
          DE PIE USANDO PC       0.22      0.34      0.27       184
        FASE REPOSO CON K5       0.57      0.85      0.68       184
INCREMENTAL CICLOERGOMETRO       0.74      0.70      0.72       184
           SENTADO LEYENDO       0.46      0.33      0.39       184
         SENTADO USANDO PC       0.22      0.13      0.16       184
      SENTADO VIENDO LA TV       0.26      0.22      0.24       184
   SUBIR Y BAJAR ESCALERAS       0.63      0.51      0.56       184
                    TROTAR       0.66      0.57      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 26: 44.72 [%]
F1-score capturado en la ejecución 26: 44.03 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.31 [%]
Global accuracy score (test) = 44.57 [%]
Global F1 score (train) = 51.45 [%]
Global F1 score (test) = 43.86 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.48      0.76      0.59       184
 CAMINAR CON MÓVIL O LIBRO       0.35      0.45      0.40       184
       CAMINAR USUAL SPEED       0.38      0.28      0.32       184
            CAMINAR ZIGZAG       0.38      0.52      0.44       184
          DE PIE BARRIENDO       0.74      0.28      0.40       184
   DE PIE DOBLANDO TOALLAS       0.51      0.43      0.47       184
    DE PIE MOVIENDO LIBROS       0.37      0.33      0.35       184
          DE PIE USANDO PC       0.20      0.30      0.24       184
        FASE REPOSO CON K5       0.57      0.86      0.68       184
INCREMENTAL CICLOERGOMETRO       0.74      0.69      0.72       184
           SENTADO LEYENDO       0.49      0.38      0.43       184
         SENTADO USANDO PC       0.21      0.12      0.16       184
      SENTADO VIENDO LA TV       0.28      0.23      0.25       184
   SUBIR Y BAJAR ESCALERAS       0.61      0.49      0.55       184
                    TROTAR       0.62      0.57      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 27: 44.57 [%]
F1-score capturado en la ejecución 27: 43.86 [%]

=== EJECUCIÓN 28 ===

--- TRAIN (ejecución 28) ---

--- TEST (ejecución 28) ---
2025-10-27 09:57:44.804105: 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`.
2025-10-27 09:57:44.817086: 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 00:00:1761555464.831447  427581 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555464.835977  427581 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555464.847344  427581 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555464.847374  427581 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555464.847378  427581 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555464.847380  427581 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:57:44.850783: 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:2.69200	validation-mlogloss:2.69079
[1]	train-mlogloss:2.67799	validation-mlogloss:2.67519
[2]	train-mlogloss:2.66451	validation-mlogloss:2.66024
[3]	train-mlogloss:2.65107	validation-mlogloss:2.64469
[4]	train-mlogloss:2.63857	validation-mlogloss:2.63067
[5]	train-mlogloss:2.62584	validation-mlogloss:2.61659
[6]	train-mlogloss:2.61360	validation-mlogloss:2.60237
[7]	train-mlogloss:2.60180	validation-mlogloss:2.58927
[8]	train-mlogloss:2.59018	validation-mlogloss:2.57632
[9]	train-mlogloss:2.57953	validation-mlogloss:2.56560
[10]	train-mlogloss:2.56830	validation-mlogloss:2.55299
[11]	train-mlogloss:2.55776	validation-mlogloss:2.54170
[12]	train-mlogloss:2.54757	validation-mlogloss:2.53085
[13]	train-mlogloss:2.53722	validation-mlogloss:2.51921
[14]	train-mlogloss:2.52691	validation-mlogloss:2.50747
[15]	train-mlogloss:2.51679	validation-mlogloss:2.49681
[16]	train-mlogloss:2.50695	validation-mlogloss:2.48626
[17]	train-mlogloss:2.49717	validation-mlogloss:2.47551
[18]	train-mlogloss:2.48741	validation-mlogloss:2.46466
[19]	train-mlogloss:2.47818	validation-mlogloss:2.45418
[20]	train-mlogloss:2.46879	validation-mlogloss:2.44415
[21]	train-mlogloss:2.45962	validation-mlogloss:2.43396
[22]	train-mlogloss:2.45076	validation-mlogloss:2.42382
[23]	train-mlogloss:2.44233	validation-mlogloss:2.41422
[24]	train-mlogloss:2.43446	validation-mlogloss:2.40559
[25]	train-mlogloss:2.42642	validation-mlogloss:2.39704
[26]	train-mlogloss:2.41797	validation-mlogloss:2.38778
[27]	train-mlogloss:2.41006	validation-mlogloss:2.37935
[28]	train-mlogloss:2.40264	validation-mlogloss:2.37075
[29]	train-mlogloss:2.39517	validation-mlogloss:2.36259
[30]	train-mlogloss:2.38749	validation-mlogloss:2.35390
[31]	train-mlogloss:2.38054	validation-mlogloss:2.34645
[32]	train-mlogloss:2.37386	validation-mlogloss:2.33880
[33]	train-mlogloss:2.36712	validation-mlogloss:2.33146
[34]	train-mlogloss:2.35975	validation-mlogloss:2.32363
[35]	train-mlogloss:2.35264	validation-mlogloss:2.31601
[36]	train-mlogloss:2.34573	validation-mlogloss:2.30871
[37]	train-mlogloss:2.33908	validation-mlogloss:2.30109
[38]	train-mlogloss:2.33216	validation-mlogloss:2.29349
[39]	train-mlogloss:2.32565	validation-mlogloss:2.28723
[40]	train-mlogloss:2.31918	validation-mlogloss:2.28037
[41]	train-mlogloss:2.31277	validation-mlogloss:2.27353
[42]	train-mlogloss:2.30620	validation-mlogloss:2.26667
[43]	train-mlogloss:2.29993	validation-mlogloss:2.26002
[44]	train-mlogloss:2.29385	validation-mlogloss:2.25389
[45]	train-mlogloss:2.28794	validation-mlogloss:2.24742
[46]	train-mlogloss:2.28200	validation-mlogloss:2.24092
[47]	train-mlogloss:2.27624	validation-mlogloss:2.23513
[48]	train-mlogloss:2.27027	validation-mlogloss:2.22874
[49]	train-mlogloss:2.26479	validation-mlogloss:2.22287
[50]	train-mlogloss:2.25924	validation-mlogloss:2.21701
[51]	train-mlogloss:2.25346	validation-mlogloss:2.21051
[52]	train-mlogloss:2.24816	validation-mlogloss:2.20512
[53]	train-mlogloss:2.24322	validation-mlogloss:2.20057
[54]	train-mlogloss:2.23806	validation-mlogloss:2.19566
[55]	train-mlogloss:2.23307	validation-mlogloss:2.19029
[56]	train-mlogloss:2.22799	validation-mlogloss:2.18527
[57]	train-mlogloss:2.22312	validation-mlogloss:2.18029
[58]	train-mlogloss:2.21828	validation-mlogloss:2.17532
[59]	train-mlogloss:2.21333	validation-mlogloss:2.17068
[60]	train-mlogloss:2.20816	validation-mlogloss:2.16561
[61]	train-mlogloss:2.20337	validation-mlogloss:2.16079
[62]	train-mlogloss:2.19877	validation-mlogloss:2.15595
[63]	train-mlogloss:2.19412	validation-mlogloss:2.15114
[64]	train-mlogloss:2.18943	validation-mlogloss:2.14643
[65]	train-mlogloss:2.18486	validation-mlogloss:2.14157
[66]	train-mlogloss:2.18015	validation-mlogloss:2.13656
[67]	train-mlogloss:2.17569	validation-mlogloss:2.13198
[68]	train-mlogloss:2.17130	validation-mlogloss:2.12791
[69]	train-mlogloss:2.16698	validation-mlogloss:2.12323
[70]	train-mlogloss:2.16271	validation-mlogloss:2.11894
[71]	train-mlogloss:2.15854	validation-mlogloss:2.11458
[72]	train-mlogloss:2.15432	validation-mlogloss:2.11045
[73]	train-mlogloss:2.15033	validation-mlogloss:2.10664
[74]	train-mlogloss:2.14629	validation-mlogloss:2.10266
[75]	train-mlogloss:2.14245	validation-mlogloss:2.09897
[76]	train-mlogloss:2.13862	validation-mlogloss:2.09521
[77]	train-mlogloss:2.13479	validation-mlogloss:2.09150
[78]	train-mlogloss:2.13099	validation-mlogloss:2.08767
[79]	train-mlogloss:2.12720	validation-mlogloss:2.08421
[80]	train-mlogloss:2.12344	validation-mlogloss:2.08050
[81]	train-mlogloss:2.11958	validation-mlogloss:2.07674
[82]	train-mlogloss:2.11593	validation-mlogloss:2.07306
[83]	train-mlogloss:2.11204	validation-mlogloss:2.06869
[84]	train-mlogloss:2.10840	validation-mlogloss:2.06559
[85]	train-mlogloss:2.10483	validation-mlogloss:2.06191
[86]	train-mlogloss:2.10140	validation-mlogloss:2.05887
[87]	train-mlogloss:2.09768	validation-mlogloss:2.05521
[88]	train-mlogloss:2.09423	validation-mlogloss:2.05172
[89]	train-mlogloss:2.09045	validation-mlogloss:2.04787
[90]	train-mlogloss:2.08691	validation-mlogloss:2.04459
[91]	train-mlogloss:2.08359	validation-mlogloss:2.04191
[92]	train-mlogloss:2.08010	validation-mlogloss:2.03868
[93]	train-mlogloss:2.07674	validation-mlogloss:2.03539
[94]	train-mlogloss:2.07334	validation-mlogloss:2.03220
[95]	train-mlogloss:2.06987	validation-mlogloss:2.02864
[96]	train-mlogloss:2.06662	validation-mlogloss:2.02560
[97]	train-mlogloss:2.06334	validation-mlogloss:2.02272
[98]	train-mlogloss:2.06018	validation-mlogloss:2.01961
[99]	train-mlogloss:2.05698	validation-mlogloss:2.01697
[100]	train-mlogloss:2.05390	validation-mlogloss:2.01401
[101]	train-mlogloss:2.05072	validation-mlogloss:2.01126
[102]	train-mlogloss:2.04756	validation-mlogloss:2.00838
[103]	train-mlogloss:2.04454	validation-mlogloss:2.00546
[104]	train-mlogloss:2.04137	validation-mlogloss:2.00276
[105]	train-mlogloss:2.03843	validation-mlogloss:2.00006
[106]	train-mlogloss:2.03525	validation-mlogloss:1.99747
[107]	train-mlogloss:2.03233	validation-mlogloss:1.99516
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[521]	train-mlogloss:1.56778	validation-mlogloss:1.68607
[522]	train-mlogloss:1.56724	validation-mlogloss:1.68589
[523]	train-mlogloss:1.56681	validation-mlogloss:1.68572
[524]	train-mlogloss:1.56641	validation-mlogloss:1.68560
[525]	train-mlogloss:1.56596	validation-mlogloss:1.68547
[526]	train-mlogloss:1.56555	validation-mlogloss:1.68533
[527]	train-mlogloss:1.56502	validation-mlogloss:1.68517
[528]	train-mlogloss:1.56453	validation-mlogloss:1.68501
[529]	train-mlogloss:1.56400	validation-mlogloss:1.68481
[530]	train-mlogloss:1.56361	validation-mlogloss:1.68464
[531]	train-mlogloss:1.56318	validation-mlogloss:1.68451
[532]	train-mlogloss:1.56271	validation-mlogloss:1.68439
[533]	train-mlogloss:1.56219	validation-mlogloss:1.68426
[534]	train-mlogloss:1.56177	validation-mlogloss:1.68397
[535]	train-mlogloss:1.56128	validation-mlogloss:1.68383
[536]	train-mlogloss:1.56074	validation-mlogloss:1.68353
[537]	train-mlogloss:1.56033	validation-mlogloss:1.68353
[538]	train-mlogloss:1.55988	validation-mlogloss:1.68330
[539]	train-mlogloss:1.55945	validation-mlogloss:1.68301
Saved model to disk.
2025-10-27 09:58:31.120727: 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`.
2025-10-27 09:58:31.133410: 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 00:00:1761555511.147170  428488 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1761555511.151580  428488 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1761555511.162450  428488 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555511.162481  428488 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555511.162484  428488 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1761555511.162486  428488 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-10-27 09:58:31.165871: 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:2.66511	validation-mlogloss:2.66140
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[6]	train-mlogloss:2.61502	validation-mlogloss:2.60623
[7]	train-mlogloss:2.60284	validation-mlogloss:2.59215
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[9]	train-mlogloss:2.57980	validation-mlogloss:2.56644
[10]	train-mlogloss:2.56901	validation-mlogloss:2.55496
[11]	train-mlogloss:2.55790	validation-mlogloss:2.54225
[12]	train-mlogloss:2.54680	validation-mlogloss:2.52974
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[14]	train-mlogloss:2.52520	validation-mlogloss:2.50618
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[25]	train-mlogloss:2.42569	validation-mlogloss:2.39637
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[28]	train-mlogloss:2.40192	validation-mlogloss:2.37046
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[30]	train-mlogloss:2.38713	validation-mlogloss:2.35444
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[33]	train-mlogloss:2.36481	validation-mlogloss:2.32967
[34]	train-mlogloss:2.35795	validation-mlogloss:2.32217
[35]	train-mlogloss:2.35101	validation-mlogloss:2.31414
[36]	train-mlogloss:2.34390	validation-mlogloss:2.30637
[37]	train-mlogloss:2.33734	validation-mlogloss:2.29973
[38]	train-mlogloss:2.33099	validation-mlogloss:2.29310
[39]	train-mlogloss:2.32498	validation-mlogloss:2.28644
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[55]	train-mlogloss:2.23271	validation-mlogloss:2.19100
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[57]	train-mlogloss:2.22206	validation-mlogloss:2.18051
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[104]	train-mlogloss:2.03889	validation-mlogloss:2.00160
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[111]	train-mlogloss:2.01824	validation-mlogloss:1.98242
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[113]	train-mlogloss:2.01273	validation-mlogloss:1.97716
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[129]	train-mlogloss:1.97101	validation-mlogloss:1.94013
[130]	train-mlogloss:1.96861	validation-mlogloss:1.93793
[131]	train-mlogloss:1.96617	validation-mlogloss:1.93591
[132]	train-mlogloss:1.96381	validation-mlogloss:1.93392
[133]	train-mlogloss:1.96157	validation-mlogloss:1.93232
[134]	train-mlogloss:1.95931	validation-mlogloss:1.93027
[135]	train-mlogloss:1.95685	validation-mlogloss:1.92798
[136]	train-mlogloss:1.95471	validation-mlogloss:1.92626
[137]	train-mlogloss:1.95232	validation-mlogloss:1.92428
[138]	train-mlogloss:1.95005	validation-mlogloss:1.92219
[139]	train-mlogloss:1.94780	validation-mlogloss:1.92025
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[441]	train-mlogloss:1.60857	validation-mlogloss:1.70024
[442]	train-mlogloss:1.60792	validation-mlogloss:1.70019
[443]	train-mlogloss:1.60731	validation-mlogloss:1.70004
[444]	train-mlogloss:1.60673	validation-mlogloss:1.70003
[445]	train-mlogloss:1.60614	validation-mlogloss:1.69995
[446]	train-mlogloss:1.60548	validation-mlogloss:1.69989
[447]	train-mlogloss:1.60487	validation-mlogloss:1.69954
[448]	train-mlogloss:1.60425	validation-mlogloss:1.69927
[449]	train-mlogloss:1.60357	validation-mlogloss:1.69905
[450]	train-mlogloss:1.60299	validation-mlogloss:1.69868
[451]	train-mlogloss:1.60233	validation-mlogloss:1.69856
[452]	train-mlogloss:1.60174	validation-mlogloss:1.69846
[453]	train-mlogloss:1.60116	validation-mlogloss:1.69827
[454]	train-mlogloss:1.60057	validation-mlogloss:1.69810
[455]	train-mlogloss:1.59999	validation-mlogloss:1.69802
[456]	train-mlogloss:1.59944	validation-mlogloss:1.69765
[457]	train-mlogloss:1.59886	validation-mlogloss:1.69740
[458]	train-mlogloss:1.59823	validation-mlogloss:1.69707
[459]	train-mlogloss:1.59769	validation-mlogloss:1.69672
[460]	train-mlogloss:1.59712	validation-mlogloss:1.69665
[461]	train-mlogloss:1.59658	validation-mlogloss:1.69650
[462]	train-mlogloss:1.59607	validation-mlogloss:1.69614
[463]	train-mlogloss:1.59547	validation-mlogloss:1.69568
[464]	train-mlogloss:1.59501	validation-mlogloss:1.69571
[465]	train-mlogloss:1.59444	validation-mlogloss:1.69548
[466]	train-mlogloss:1.59389	validation-mlogloss:1.69531
[467]	train-mlogloss:1.59343	validation-mlogloss:1.69508
[468]	train-mlogloss:1.59292	validation-mlogloss:1.69492
[469]	train-mlogloss:1.59237	validation-mlogloss:1.69479
[470]	train-mlogloss:1.59188	validation-mlogloss:1.69468
[471]	train-mlogloss:1.59126	validation-mlogloss:1.69460
[472]	train-mlogloss:1.59065	validation-mlogloss:1.69422
[473]	train-mlogloss:1.59003	validation-mlogloss:1.69401
[474]	train-mlogloss:1.58945	validation-mlogloss:1.69394
[475]	train-mlogloss:1.58892	validation-mlogloss:1.69367
[476]	train-mlogloss:1.58835	validation-mlogloss:1.69340
[477]	train-mlogloss:1.58777	validation-mlogloss:1.69306
[478]	train-mlogloss:1.58722	validation-mlogloss:1.69281
[479]	train-mlogloss:1.58663	validation-mlogloss:1.69267
[480]	train-mlogloss:1.58610	validation-mlogloss:1.69238
[481]	train-mlogloss:1.58562	validation-mlogloss:1.69216
[482]	train-mlogloss:1.58520	validation-mlogloss:1.69204
[483]	train-mlogloss:1.58467	validation-mlogloss:1.69189
[484]	train-mlogloss:1.58410	validation-mlogloss:1.69179
[485]	train-mlogloss:1.58346	validation-mlogloss:1.69153
[486]	train-mlogloss:1.58280	validation-mlogloss:1.69148
[487]	train-mlogloss:1.58229	validation-mlogloss:1.69130
[488]	train-mlogloss:1.58174	validation-mlogloss:1.69108
[489]	train-mlogloss:1.58118	validation-mlogloss:1.69100
[490]	train-mlogloss:1.58074	validation-mlogloss:1.69079
[491]	train-mlogloss:1.58021	validation-mlogloss:1.69054
[492]	train-mlogloss:1.57968	validation-mlogloss:1.69057
[493]	train-mlogloss:1.57919	validation-mlogloss:1.69037
[494]	train-mlogloss:1.57865	validation-mlogloss:1.69016
[495]	train-mlogloss:1.57815	validation-mlogloss:1.69000
[496]	train-mlogloss:1.57769	validation-mlogloss:1.69013
[497]	train-mlogloss:1.57713	validation-mlogloss:1.69005
[498]	train-mlogloss:1.57667	validation-mlogloss:1.68991
[499]	train-mlogloss:1.57614	validation-mlogloss:1.68994
[500]	train-mlogloss:1.57568	validation-mlogloss:1.68984
[501]	train-mlogloss:1.57511	validation-mlogloss:1.68966
[502]	train-mlogloss:1.57462	validation-mlogloss:1.68950
[503]	train-mlogloss:1.57426	validation-mlogloss:1.68937
[504]	train-mlogloss:1.57376	validation-mlogloss:1.68938
[505]	train-mlogloss:1.57329	validation-mlogloss:1.68935
[506]	train-mlogloss:1.57277	validation-mlogloss:1.68920
[507]	train-mlogloss:1.57229	validation-mlogloss:1.68922
[508]	train-mlogloss:1.57169	validation-mlogloss:1.68921
[509]	train-mlogloss:1.57118	validation-mlogloss:1.68930
[510]	train-mlogloss:1.57057	validation-mlogloss:1.68934
[511]	train-mlogloss:1.57006	validation-mlogloss:1.68944
[512]	train-mlogloss:1.56959	validation-mlogloss:1.68939
[513]	train-mlogloss:1.56910	validation-mlogloss:1.68910
[514]	train-mlogloss:1.56856	validation-mlogloss:1.68905
[515]	train-mlogloss:1.56804	validation-mlogloss:1.68893
[516]	train-mlogloss:1.56755	validation-mlogloss:1.68876
[517]	train-mlogloss:1.56704	validation-mlogloss:1.68855
[518]	train-mlogloss:1.56656	validation-mlogloss:1.68839
[519]	train-mlogloss:1.56613	validation-mlogloss:1.68831
[520]	train-mlogloss:1.56567	validation-mlogloss:1.68815
[521]	train-mlogloss:1.56523	validation-mlogloss:1.68794
[522]	train-mlogloss:1.56475	validation-mlogloss:1.68763
[523]	train-mlogloss:1.56425	validation-mlogloss:1.68741
[524]	train-mlogloss:1.56377	validation-mlogloss:1.68722
[525]	train-mlogloss:1.56332	validation-mlogloss:1.68707
[526]	train-mlogloss:1.56291	validation-mlogloss:1.68692
[527]	train-mlogloss:1.56247	validation-mlogloss:1.68697
[528]	train-mlogloss:1.56199	validation-mlogloss:1.68672
[529]	train-mlogloss:1.56150	validation-mlogloss:1.68655
[530]	train-mlogloss:1.56098	validation-mlogloss:1.68636
[531]	train-mlogloss:1.56047	validation-mlogloss:1.68604
[532]	train-mlogloss:1.56009	validation-mlogloss:1.68601
[533]	train-mlogloss:1.55965	validation-mlogloss:1.68560
[534]	train-mlogloss:1.55928	validation-mlogloss:1.68555
[535]	train-mlogloss:1.55885	validation-mlogloss:1.68551
[536]	train-mlogloss:1.55835	validation-mlogloss:1.68532
[537]	train-mlogloss:1.55784	validation-mlogloss:1.68499
[538]	train-mlogloss:1.55743	validation-mlogloss:1.68482
[539]	train-mlogloss:1.55697	validation-mlogloss:1.68474
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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.38 [%]
Global accuracy score (test) = 44.43 [%]
Global F1 score (train) = 51.52 [%]
Global F1 score (test) = 43.67 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.75      0.57       184
 CAMINAR CON MÓVIL O LIBRO       0.38      0.46      0.42       184
       CAMINAR USUAL SPEED       0.35      0.28      0.31       184
            CAMINAR ZIGZAG       0.38      0.52      0.44       184
          DE PIE BARRIENDO       0.72      0.29      0.42       184
   DE PIE DOBLANDO TOALLAS       0.50      0.43      0.46       184
    DE PIE MOVIENDO LIBROS       0.35      0.32      0.33       184
          DE PIE USANDO PC       0.22      0.34      0.27       184
        FASE REPOSO CON K5       0.58      0.85      0.69       184
INCREMENTAL CICLOERGOMETRO       0.74      0.68      0.71       184
           SENTADO LEYENDO       0.44      0.34      0.38       184
         SENTADO USANDO PC       0.23      0.13      0.17       184
      SENTADO VIENDO LA TV       0.28      0.23      0.25       184
   SUBIR Y BAJAR ESCALERAS       0.61      0.48      0.54       184
                    TROTAR       0.61      0.57      0.59       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 28: 44.43 [%]
F1-score capturado en la ejecución 28: 43.67 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.35 [%]
Global accuracy score (test) = 44.61 [%]
Global F1 score (train) = 51.44 [%]
Global F1 score (test) = 43.97 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.46      0.77      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.36      0.46      0.40       184
       CAMINAR USUAL SPEED       0.35      0.27      0.31       184
            CAMINAR ZIGZAG       0.39      0.54      0.45       184
          DE PIE BARRIENDO       0.75      0.29      0.42       184
   DE PIE DOBLANDO TOALLAS       0.49      0.42      0.45       184
    DE PIE MOVIENDO LIBROS       0.37      0.33      0.35       184
          DE PIE USANDO PC       0.21      0.33      0.26       184
        FASE REPOSO CON K5       0.56      0.85      0.68       184
INCREMENTAL CICLOERGOMETRO       0.75      0.68      0.71       184
           SENTADO LEYENDO       0.50      0.35      0.42       184
         SENTADO USANDO PC       0.21      0.12      0.16       184
      SENTADO VIENDO LA TV       0.29      0.26      0.27       184
   SUBIR Y BAJAR ESCALERAS       0.63      0.47      0.54       184
                    TROTAR       0.66      0.57      0.61       161

                  accuracy                           0.45      2737
                 macro avg       0.47      0.45      0.44      2737
              weighted avg       0.46      0.45      0.44      2737


Accuracy capturado en la ejecución 29: 44.61 [%]
F1-score capturado en la ejecución 29: 43.97 [%]

=== 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, 91)
(18469, 91)
[[8.]
 [8.]
 [8.]
 ...
 [3.]
 [3.]
 [3.]]
(2737, 1)
[8 8 8 ... 3 3 3]
(2737,)
-------------------------------------------------

Global accuracy score (train) = 51.43 [%]
Global accuracy score (test) = 44.65 [%]
Global F1 score (train) = 51.58 [%]
Global F1 score (test) = 44.0 [%]
                            precision    recall  f1-score   support

     CAMINAR CON LA COMPRA       0.47      0.76      0.58       184
 CAMINAR CON MÓVIL O LIBRO       0.37      0.45      0.41       184
       CAMINAR USUAL SPEED       0.36      0.26      0.30       184
            CAMINAR ZIGZAG       0.40      0.55      0.46       184
          DE PIE BARRIENDO       0.70      0.30      0.42       184
   DE PIE DOBLANDO TOALLAS       0.49      0.41      0.45       184
    DE PIE MOVIENDO LIBROS       0.36      0.35      0.35       184
          DE PIE USANDO PC       0.20      0.32      0.25       184
        FASE REPOSO CON K5       0.57      0.86      0.68       184
INCREMENTAL CICLOERGOMETRO       0.77      0.68      0.72       184
           SENTADO LEYENDO       0.47      0.34      0.39       184
         SENTADO USANDO PC       0.21      0.12      0.16       184
      SENTADO VIENDO LA TV       0.25      0.20      0.22       184
   SUBIR Y BAJAR ESCALERAS       0.64      0.53      0.58       184
                    TROTAR       0.67      0.57      0.62       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 30: 44.65 [%]
F1-score capturado en la ejecución 30: 44.0 [%]

=== RESUMEN FINAL ===
Accuracies: [44.57, 45.34, 45.01, 44.68, 45.2, 45.05, 45.56, 45.12, 44.9, 46.04, 45.2, 45.41, 45.74, 44.9, 45.41, 44.46, 45.05, 45.34, 45.78, 45.31, 44.43, 45.52, 45.85, 45.05, 45.12, 44.72, 44.57, 44.43, 44.61, 44.65]
F1-scores: [44.03, 44.84, 44.43, 44.15, 44.7, 44.56, 44.89, 44.54, 44.29, 45.44, 44.71, 44.89, 45.15, 44.21, 44.78, 43.69, 44.37, 44.84, 45.24, 44.74, 43.8, 44.88, 45.28, 44.46, 44.36, 44.03, 43.86, 43.67, 43.97, 44.0]
Accuracy mean: 45.1007 | std: 0.4399
F1 mean: 44.4933 | std: 0.4788

Resultados guardados en /mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_M/case_M_XGB_acc_gyr_17_classes/metrics_test.npz
