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@@ -16,12 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
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  # bert_sentence_classifier
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- This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4207
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- - F1: 0.6163
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- - Precision: 0.6163
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- - Recall: 0.6163
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  ## Model description
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@@ -40,42 +40,246 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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- - train_batch_size: 32
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 3
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
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- |:-------------:|:-----:|:-----:|:---------------:|:------:|:---------:|:------:|
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- | 1.8231 | 0.12 | 500 | 1.5368 | 0.5776 | 0.5776 | 0.5776 |
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- | 1.5269 | 0.25 | 1000 | 1.4710 | 0.5935 | 0.5935 | 0.5935 |
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- | 1.5059 | 0.37 | 1500 | 1.4287 | 0.6091 | 0.6091 | 0.6091 |
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- | 1.4711 | 0.5 | 2000 | 1.4186 | 0.6106 | 0.6106 | 0.6106 |
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- | 1.4269 | 0.62 | 2500 | 1.4154 | 0.6106 | 0.6106 | 0.6106 |
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- | 1.4392 | 0.74 | 3000 | 1.4029 | 0.6197 | 0.6197 | 0.6197 |
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- | 1.4587 | 0.87 | 3500 | 1.3800 | 0.6216 | 0.6216 | 0.6216 |
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- | 1.4519 | 0.99 | 4000 | 1.3790 | 0.6231 | 0.6231 | 0.6231 |
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- | 1.2645 | 1.12 | 4500 | 1.3879 | 0.6201 | 0.6201 | 0.6201 |
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- | 1.2581 | 1.24 | 5000 | 1.4064 | 0.6186 | 0.6186 | 0.6186 |
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- | 1.2425 | 1.36 | 5500 | 1.4008 | 0.6220 | 0.6220 | 0.6220 |
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- | 1.2581 | 1.49 | 6000 | 1.3839 | 0.6209 | 0.6209 | 0.6209 |
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- | 1.2522 | 1.61 | 6500 | 1.3916 | 0.6224 | 0.6224 | 0.6224 |
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- | 1.2675 | 1.73 | 7000 | 1.3816 | 0.6194 | 0.6194 | 0.6194 |
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- | 1.2697 | 1.86 | 7500 | 1.3960 | 0.6125 | 0.6125 | 0.6125 |
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- | 1.258 | 1.98 | 8000 | 1.3871 | 0.6220 | 0.6220 | 0.6220 |
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- | 1.087 | 2.11 | 8500 | 1.4184 | 0.6159 | 0.6159 | 0.6159 |
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- | 1.0504 | 2.23 | 9000 | 1.4144 | 0.6201 | 0.6201 | 0.6201 |
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- | 1.0649 | 2.35 | 9500 | 1.4304 | 0.6175 | 0.6175 | 0.6175 |
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- | 1.0468 | 2.48 | 10000 | 1.4433 | 0.6205 | 0.6205 | 0.6205 |
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- | 1.0711 | 2.6 | 10500 | 1.4420 | 0.6099 | 0.6099 | 0.6099 |
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- | 1.0684 | 2.73 | 11000 | 1.4280 | 0.6114 | 0.6114 | 0.6114 |
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- | 1.0514 | 2.85 | 11500 | 1.4436 | 0.6121 | 0.6121 | 0.6121 |
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- | 1.0729 | 2.97 | 12000 | 1.4207 | 0.6163 | 0.6163 | 0.6163 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  # bert_sentence_classifier
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+ This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.0040
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+ - F1: 0.6123
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+ - Precision: 0.6123
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+ - Recall: 0.6123
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 8
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:------:|:---------------:|:------:|:---------:|:------:|
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+ | 2.0049 | 0.04 | 500 | 1.5854 | 0.5693 | 0.5693 | 0.5693 |
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+ | 1.552 | 0.07 | 1000 | 1.4428 | 0.6131 | 0.6131 | 0.6131 |
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+ | 1.502 | 0.11 | 1500 | 1.3977 | 0.6213 | 0.6213 | 0.6213 |
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+ | 1.4515 | 0.14 | 2000 | 1.3926 | 0.6200 | 0.6200 | 0.6200 |
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+ | 1.43 | 0.18 | 2500 | 1.3553 | 0.6350 | 0.6350 | 0.6350 |
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+ | 1.413 | 0.21 | 3000 | 1.3461 | 0.6346 | 0.6346 | 0.6346 |
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+ | 1.4109 | 0.25 | 3500 | 1.3199 | 0.6496 | 0.6496 | 0.6496 |
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+ | 1.3853 | 0.28 | 4000 | 1.3338 | 0.6406 | 0.6406 | 0.6406 |
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+ | 1.3788 | 0.32 | 4500 | 1.3306 | 0.6471 | 0.6471 | 0.6471 |
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+ | 1.3585 | 0.35 | 5000 | 1.3295 | 0.6410 | 0.6410 | 0.6410 |
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+ | 1.356 | 0.39 | 5500 | 1.3025 | 0.6441 | 0.6441 | 0.6441 |
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+ | 1.3534 | 0.42 | 6000 | 1.3197 | 0.6406 | 0.6406 | 0.6406 |
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+ | 1.3324 | 0.46 | 6500 | 1.2932 | 0.6436 | 0.6436 | 0.6436 |
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+ | 1.3563 | 0.49 | 7000 | 1.3202 | 0.6488 | 0.6488 | 0.6488 |
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+ | 1.3121 | 0.53 | 7500 | 1.3024 | 0.6428 | 0.6428 | 0.6428 |
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+ | 1.3092 | 0.56 | 8000 | 1.3142 | 0.6419 | 0.6419 | 0.6419 |
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+ | 1.3769 | 0.6 | 8500 | 1.2974 | 0.6441 | 0.6441 | 0.6441 |
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+ | 1.3487 | 0.63 | 9000 | 1.2882 | 0.6556 | 0.6556 | 0.6556 |
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+ | 1.3475 | 0.67 | 9500 | 1.2928 | 0.6441 | 0.6441 | 0.6441 |
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+ | 1.3038 | 0.7 | 10000 | 1.2846 | 0.6488 | 0.6488 | 0.6488 |
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+ | 1.3371 | 0.74 | 10500 | 1.2894 | 0.6591 | 0.6591 | 0.6591 |
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+ | 1.3222 | 0.77 | 11000 | 1.2745 | 0.6535 | 0.6535 | 0.6535 |
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+ | 1.2983 | 0.81 | 11500 | 1.2832 | 0.6526 | 0.6526 | 0.6526 |
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+ | 1.3505 | 0.84 | 12000 | 1.2812 | 0.6531 | 0.6531 | 0.6531 |
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+ | 1.2752 | 0.88 | 12500 | 1.2629 | 0.6578 | 0.6578 | 0.6578 |
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+ | 1.3115 | 0.91 | 13000 | 1.2787 | 0.6453 | 0.6453 | 0.6453 |
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+ | 1.3353 | 0.95 | 13500 | 1.2707 | 0.6539 | 0.6539 | 0.6539 |
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+ | 1.2982 | 0.98 | 14000 | 1.2618 | 0.6569 | 0.6569 | 0.6569 |
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+ | 1.1885 | 1.02 | 14500 | 1.2999 | 0.6544 | 0.6544 | 0.6544 |
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+ | 1.1339 | 1.05 | 15000 | 1.3086 | 0.6458 | 0.6458 | 0.6458 |
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+ | 1.0661 | 1.09 | 15500 | 1.2871 | 0.6582 | 0.6582 | 0.6582 |
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+ | 1.109 | 1.12 | 16000 | 1.2800 | 0.6608 | 0.6608 | 0.6608 |
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+ | 1.0305 | 1.16 | 16500 | 1.3098 | 0.6604 | 0.6604 | 0.6604 |
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+ | 1.0855 | 1.19 | 17000 | 1.2968 | 0.6587 | 0.6587 | 0.6587 |
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+ | 1.0933 | 1.23 | 17500 | 1.3075 | 0.6509 | 0.6509 | 0.6509 |
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+ | 1.1229 | 1.26 | 18000 | 1.3018 | 0.6496 | 0.6496 | 0.6496 |
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+ | 1.1043 | 1.3 | 18500 | 1.2832 | 0.6565 | 0.6565 | 0.6565 |
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+ | 1.1344 | 1.33 | 19000 | 1.2825 | 0.6591 | 0.6591 | 0.6591 |
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+ | 1.1467 | 1.37 | 19500 | 1.2797 | 0.6642 | 0.6642 | 0.6642 |
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+ | 1.0596 | 1.4 | 20000 | 1.2841 | 0.6522 | 0.6522 | 0.6522 |
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+ | 1.1286 | 1.44 | 20500 | 1.2912 | 0.6544 | 0.6544 | 0.6544 |
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+ | 1.1219 | 1.47 | 21000 | 1.3143 | 0.6509 | 0.6509 | 0.6509 |
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+ | 1.1339 | 1.51 | 21500 | 1.3021 | 0.6539 | 0.6539 | 0.6539 |
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+ | 1.1091 | 1.54 | 22000 | 1.2738 | 0.6625 | 0.6625 | 0.6625 |
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+ | 1.1403 | 1.58 | 22500 | 1.2822 | 0.6548 | 0.6548 | 0.6548 |
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+ | 1.146 | 1.61 | 23000 | 1.2724 | 0.6587 | 0.6587 | 0.6587 |
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+ | 1.1237 | 1.65 | 23500 | 1.2757 | 0.6569 | 0.6569 | 0.6569 |
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+ | 1.1453 | 1.68 | 24000 | 1.2985 | 0.6535 | 0.6535 | 0.6535 |
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+ | 1.1309 | 1.72 | 24500 | 1.2876 | 0.6578 | 0.6578 | 0.6578 |
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+ | 1.1494 | 1.75 | 25000 | 1.2892 | 0.6552 | 0.6552 | 0.6552 |
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+ | 1.1571 | 1.79 | 25500 | 1.2806 | 0.6548 | 0.6548 | 0.6548 |
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+ | 1.0766 | 1.82 | 26000 | 1.2889 | 0.6509 | 0.6509 | 0.6509 |
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+ | 1.1416 | 1.86 | 26500 | 1.2673 | 0.6599 | 0.6599 | 0.6599 |
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+ | 1.1179 | 1.89 | 27000 | 1.2919 | 0.6501 | 0.6501 | 0.6501 |
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+ | 1.0838 | 1.93 | 27500 | 1.3198 | 0.6488 | 0.6488 | 0.6488 |
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+ | 1.1426 | 1.96 | 28000 | 1.2766 | 0.6561 | 0.6561 | 0.6561 |
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+ | 1.1559 | 2.0 | 28500 | 1.2839 | 0.6561 | 0.6561 | 0.6561 |
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+ | 0.8783 | 2.03 | 29000 | 1.3377 | 0.6509 | 0.6509 | 0.6509 |
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+ | 0.8822 | 2.07 | 29500 | 1.3813 | 0.6501 | 0.6501 | 0.6501 |
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+ | 0.8823 | 2.1 | 30000 | 1.3738 | 0.6514 | 0.6514 | 0.6514 |
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+ | 0.9094 | 2.14 | 30500 | 1.3667 | 0.6522 | 0.6522 | 0.6522 |
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+ | 0.8828 | 2.17 | 31000 | 1.3654 | 0.6582 | 0.6582 | 0.6582 |
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+ | 0.8489 | 2.21 | 31500 | 1.3404 | 0.6556 | 0.6556 | 0.6556 |
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+ | 0.8719 | 2.24 | 32000 | 1.4173 | 0.6393 | 0.6393 | 0.6393 |
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+ | 0.8926 | 2.28 | 32500 | 1.4026 | 0.6535 | 0.6535 | 0.6535 |
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+ | 0.871 | 2.31 | 33000 | 1.4133 | 0.6428 | 0.6428 | 0.6428 |
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+ | 0.9047 | 2.35 | 33500 | 1.3915 | 0.6449 | 0.6449 | 0.6449 |
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+ | 0.8621 | 2.38 | 34000 | 1.4109 | 0.6483 | 0.6483 | 0.6483 |
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+ | 0.8978 | 2.42 | 34500 | 1.3675 | 0.6471 | 0.6471 | 0.6471 |
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+ | 0.8808 | 2.45 | 35000 | 1.3826 | 0.6522 | 0.6522 | 0.6522 |
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+ | 0.9299 | 2.49 | 35500 | 1.3673 | 0.6535 | 0.6535 | 0.6535 |
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+ | 0.8546 | 2.52 | 36000 | 1.4034 | 0.6518 | 0.6518 | 0.6518 |
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+ | 0.8855 | 2.56 | 36500 | 1.3763 | 0.6458 | 0.6458 | 0.6458 |
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+ | 0.8996 | 2.59 | 37000 | 1.3930 | 0.6539 | 0.6539 | 0.6539 |
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+ | 0.8889 | 2.63 | 37500 | 1.3966 | 0.6471 | 0.6471 | 0.6471 |
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+ | 0.8811 | 2.66 | 38000 | 1.4131 | 0.6475 | 0.6475 | 0.6475 |
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+ | 0.9129 | 2.7 | 38500 | 1.3816 | 0.6445 | 0.6445 | 0.6445 |
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+ | 0.8708 | 2.73 | 39000 | 1.4354 | 0.6492 | 0.6492 | 0.6492 |
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+ | 0.8667 | 2.77 | 39500 | 1.4076 | 0.6380 | 0.6380 | 0.6380 |
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+ | 0.9139 | 2.8 | 40000 | 1.4200 | 0.6423 | 0.6423 | 0.6423 |
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+ | 0.9035 | 2.84 | 40500 | 1.3913 | 0.6462 | 0.6462 | 0.6462 |
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+ | 0.9312 | 2.87 | 41000 | 1.3806 | 0.6449 | 0.6449 | 0.6449 |
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+ | 0.9382 | 2.91 | 41500 | 1.4064 | 0.6522 | 0.6522 | 0.6522 |
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+ | 0.8765 | 2.95 | 42000 | 1.4146 | 0.6380 | 0.6380 | 0.6380 |
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+ | 0.8801 | 2.98 | 42500 | 1.3898 | 0.6445 | 0.6445 | 0.6445 |
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+ | 0.7988 | 3.02 | 43000 | 1.4740 | 0.6436 | 0.6436 | 0.6436 |
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+ | 0.6752 | 3.05 | 43500 | 1.5622 | 0.6372 | 0.6372 | 0.6372 |
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+ | 0.649 | 3.09 | 44000 | 1.6055 | 0.6359 | 0.6359 | 0.6359 |
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+ | 0.669 | 3.12 | 44500 | 1.5736 | 0.6380 | 0.6380 | 0.6380 |
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+ | 0.7189 | 3.16 | 45000 | 1.5832 | 0.6346 | 0.6346 | 0.6346 |
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+ | 0.6724 | 3.19 | 45500 | 1.6194 | 0.6260 | 0.6260 | 0.6260 |
146
+ | 0.7139 | 3.23 | 46000 | 1.5966 | 0.6359 | 0.6359 | 0.6359 |
147
+ | 0.6985 | 3.26 | 46500 | 1.5803 | 0.6342 | 0.6342 | 0.6342 |
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+ | 0.6503 | 3.3 | 47000 | 1.6485 | 0.6376 | 0.6376 | 0.6376 |
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+ | 0.6879 | 3.33 | 47500 | 1.5959 | 0.6325 | 0.6325 | 0.6325 |
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+ | 0.7342 | 3.37 | 48000 | 1.5534 | 0.6389 | 0.6389 | 0.6389 |
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+ | 0.6838 | 3.4 | 48500 | 1.5807 | 0.6337 | 0.6337 | 0.6337 |
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+ | 0.7295 | 3.44 | 49000 | 1.6192 | 0.6372 | 0.6372 | 0.6372 |
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+ | 0.7044 | 3.47 | 49500 | 1.6618 | 0.6346 | 0.6346 | 0.6346 |
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+ | 0.7071 | 3.51 | 50000 | 1.6255 | 0.6342 | 0.6342 | 0.6342 |
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+ | 0.7055 | 3.54 | 50500 | 1.5584 | 0.6363 | 0.6363 | 0.6363 |
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+ | 0.6781 | 3.58 | 51000 | 1.5948 | 0.6376 | 0.6376 | 0.6376 |
157
+ | 0.7004 | 3.61 | 51500 | 1.6311 | 0.6320 | 0.6320 | 0.6320 |
158
+ | 0.715 | 3.65 | 52000 | 1.5972 | 0.6423 | 0.6423 | 0.6423 |
159
+ | 0.7399 | 3.68 | 52500 | 1.6402 | 0.6325 | 0.6325 | 0.6325 |
160
+ | 0.6972 | 3.72 | 53000 | 1.6186 | 0.6406 | 0.6406 | 0.6406 |
161
+ | 0.7219 | 3.75 | 53500 | 1.5945 | 0.6359 | 0.6359 | 0.6359 |
162
+ | 0.763 | 3.79 | 54000 | 1.5900 | 0.6380 | 0.6380 | 0.6380 |
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+ | 0.7196 | 3.82 | 54500 | 1.6218 | 0.6320 | 0.6320 | 0.6320 |
164
+ | 0.7682 | 3.86 | 55000 | 1.5538 | 0.6372 | 0.6372 | 0.6372 |
165
+ | 0.6949 | 3.89 | 55500 | 1.6209 | 0.6295 | 0.6295 | 0.6295 |
166
+ | 0.7461 | 3.93 | 56000 | 1.6237 | 0.6316 | 0.6316 | 0.6316 |
167
+ | 0.7295 | 3.96 | 56500 | 1.6011 | 0.6333 | 0.6333 | 0.6333 |
168
+ | 0.6846 | 4.0 | 57000 | 1.6899 | 0.6312 | 0.6312 | 0.6312 |
169
+ | 0.556 | 4.03 | 57500 | 1.7783 | 0.6303 | 0.6303 | 0.6303 |
170
+ | 0.5276 | 4.07 | 58000 | 1.8985 | 0.6260 | 0.6260 | 0.6260 |
171
+ | 0.5576 | 4.1 | 58500 | 1.8263 | 0.6264 | 0.6264 | 0.6264 |
172
+ | 0.5303 | 4.14 | 59000 | 1.8411 | 0.6316 | 0.6316 | 0.6316 |
173
+ | 0.5574 | 4.17 | 59500 | 1.8353 | 0.6286 | 0.6286 | 0.6286 |
174
+ | 0.5468 | 4.21 | 60000 | 1.9252 | 0.6286 | 0.6286 | 0.6286 |
175
+ | 0.532 | 4.24 | 60500 | 1.8903 | 0.6295 | 0.6295 | 0.6295 |
176
+ | 0.5329 | 4.28 | 61000 | 1.9416 | 0.6252 | 0.6252 | 0.6252 |
177
+ | 0.5539 | 4.31 | 61500 | 1.9149 | 0.6260 | 0.6260 | 0.6260 |
178
+ | 0.5661 | 4.35 | 62000 | 1.9074 | 0.6286 | 0.6286 | 0.6286 |
179
+ | 0.5502 | 4.38 | 62500 | 2.0259 | 0.6316 | 0.6316 | 0.6316 |
180
+ | 0.5658 | 4.42 | 63000 | 1.9049 | 0.6256 | 0.6256 | 0.6256 |
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+ | 0.5958 | 4.45 | 63500 | 1.9252 | 0.6166 | 0.6166 | 0.6166 |
182
+ | 0.5972 | 4.49 | 64000 | 1.8518 | 0.6286 | 0.6286 | 0.6286 |
183
+ | 0.5964 | 4.52 | 64500 | 1.8793 | 0.6234 | 0.6234 | 0.6234 |
184
+ | 0.5506 | 4.56 | 65000 | 1.9218 | 0.6346 | 0.6346 | 0.6346 |
185
+ | 0.5516 | 4.59 | 65500 | 1.8957 | 0.6389 | 0.6389 | 0.6389 |
186
+ | 0.5777 | 4.63 | 66000 | 1.9603 | 0.6295 | 0.6295 | 0.6295 |
187
+ | 0.5953 | 4.66 | 66500 | 1.8605 | 0.6252 | 0.6252 | 0.6252 |
188
+ | 0.5797 | 4.7 | 67000 | 1.8797 | 0.6320 | 0.6320 | 0.6320 |
189
+ | 0.5836 | 4.73 | 67500 | 1.9320 | 0.6260 | 0.6260 | 0.6260 |
190
+ | 0.6019 | 4.77 | 68000 | 1.8465 | 0.6239 | 0.6239 | 0.6239 |
191
+ | 0.6099 | 4.8 | 68500 | 1.9481 | 0.6299 | 0.6299 | 0.6299 |
192
+ | 0.6064 | 4.84 | 69000 | 1.9033 | 0.6307 | 0.6307 | 0.6307 |
193
+ | 0.5836 | 4.87 | 69500 | 1.8878 | 0.6234 | 0.6234 | 0.6234 |
194
+ | 0.5766 | 4.91 | 70000 | 1.8860 | 0.6277 | 0.6277 | 0.6277 |
195
+ | 0.623 | 4.94 | 70500 | 1.8033 | 0.6303 | 0.6303 | 0.6303 |
196
+ | 0.596 | 4.98 | 71000 | 1.9038 | 0.6333 | 0.6333 | 0.6333 |
197
+ | 0.537 | 5.01 | 71500 | 2.0795 | 0.6234 | 0.6234 | 0.6234 |
198
+ | 0.4663 | 5.05 | 72000 | 2.0325 | 0.6217 | 0.6217 | 0.6217 |
199
+ | 0.4173 | 5.08 | 72500 | 2.2377 | 0.6273 | 0.6273 | 0.6273 |
200
+ | 0.4521 | 5.12 | 73000 | 2.1218 | 0.6217 | 0.6217 | 0.6217 |
201
+ | 0.4243 | 5.15 | 73500 | 2.2731 | 0.6204 | 0.6204 | 0.6204 |
202
+ | 0.4672 | 5.19 | 74000 | 2.2111 | 0.6247 | 0.6247 | 0.6247 |
203
+ | 0.4884 | 5.22 | 74500 | 2.1027 | 0.6226 | 0.6226 | 0.6226 |
204
+ | 0.4314 | 5.26 | 75000 | 2.2218 | 0.6230 | 0.6230 | 0.6230 |
205
+ | 0.4581 | 5.29 | 75500 | 2.2036 | 0.6264 | 0.6264 | 0.6264 |
206
+ | 0.4245 | 5.33 | 76000 | 2.2419 | 0.6200 | 0.6200 | 0.6200 |
207
+ | 0.4391 | 5.36 | 76500 | 2.1762 | 0.6187 | 0.6187 | 0.6187 |
208
+ | 0.4672 | 5.4 | 77000 | 2.2779 | 0.6179 | 0.6179 | 0.6179 |
209
+ | 0.4821 | 5.43 | 77500 | 2.2881 | 0.6187 | 0.6187 | 0.6187 |
210
+ | 0.4872 | 5.47 | 78000 | 2.2406 | 0.6119 | 0.6119 | 0.6119 |
211
+ | 0.4584 | 5.5 | 78500 | 2.3521 | 0.6209 | 0.6209 | 0.6209 |
212
+ | 0.4774 | 5.54 | 79000 | 2.2522 | 0.6174 | 0.6174 | 0.6174 |
213
+ | 0.5151 | 5.57 | 79500 | 2.2233 | 0.6140 | 0.6140 | 0.6140 |
214
+ | 0.493 | 5.61 | 80000 | 2.2333 | 0.6256 | 0.6256 | 0.6256 |
215
+ | 0.4846 | 5.64 | 80500 | 2.1891 | 0.6200 | 0.6200 | 0.6200 |
216
+ | 0.478 | 5.68 | 81000 | 2.3159 | 0.6196 | 0.6196 | 0.6196 |
217
+ | 0.4851 | 5.71 | 81500 | 2.2356 | 0.6234 | 0.6234 | 0.6234 |
218
+ | 0.4902 | 5.75 | 82000 | 2.3525 | 0.6222 | 0.6222 | 0.6222 |
219
+ | 0.4992 | 5.79 | 82500 | 2.2111 | 0.6067 | 0.6067 | 0.6067 |
220
+ | 0.4799 | 5.82 | 83000 | 2.2650 | 0.6131 | 0.6131 | 0.6131 |
221
+ | 0.4849 | 5.86 | 83500 | 2.2628 | 0.6204 | 0.6204 | 0.6204 |
222
+ | 0.4772 | 5.89 | 84000 | 2.2711 | 0.6174 | 0.6174 | 0.6174 |
223
+ | 0.5465 | 5.93 | 84500 | 2.2793 | 0.6144 | 0.6144 | 0.6144 |
224
+ | 0.4466 | 5.96 | 85000 | 2.2369 | 0.6166 | 0.6166 | 0.6166 |
225
+ | 0.4885 | 6.0 | 85500 | 2.1963 | 0.6217 | 0.6217 | 0.6217 |
226
+ | 0.3862 | 6.03 | 86000 | 2.4233 | 0.6174 | 0.6174 | 0.6174 |
227
+ | 0.3738 | 6.07 | 86500 | 2.4405 | 0.6191 | 0.6191 | 0.6191 |
228
+ | 0.349 | 6.1 | 87000 | 2.4512 | 0.6161 | 0.6161 | 0.6161 |
229
+ | 0.3659 | 6.14 | 87500 | 2.5251 | 0.6226 | 0.6226 | 0.6226 |
230
+ | 0.3365 | 6.17 | 88000 | 2.5326 | 0.6217 | 0.6217 | 0.6217 |
231
+ | 0.3336 | 6.21 | 88500 | 2.4413 | 0.6179 | 0.6179 | 0.6179 |
232
+ | 0.3632 | 6.24 | 89000 | 2.6415 | 0.6114 | 0.6114 | 0.6114 |
233
+ | 0.3584 | 6.28 | 89500 | 2.5388 | 0.6179 | 0.6179 | 0.6179 |
234
+ | 0.3891 | 6.31 | 90000 | 2.6418 | 0.6123 | 0.6123 | 0.6123 |
235
+ | 0.3805 | 6.35 | 90500 | 2.6223 | 0.6127 | 0.6127 | 0.6127 |
236
+ | 0.363 | 6.38 | 91000 | 2.5399 | 0.6131 | 0.6131 | 0.6131 |
237
+ | 0.3723 | 6.42 | 91500 | 2.6033 | 0.6187 | 0.6187 | 0.6187 |
238
+ | 0.3808 | 6.45 | 92000 | 2.5281 | 0.6243 | 0.6243 | 0.6243 |
239
+ | 0.3921 | 6.49 | 92500 | 2.5814 | 0.6007 | 0.6007 | 0.6007 |
240
+ | 0.3763 | 6.52 | 93000 | 2.6656 | 0.6058 | 0.6058 | 0.6058 |
241
+ | 0.3921 | 6.56 | 93500 | 2.4935 | 0.6084 | 0.6084 | 0.6084 |
242
+ | 0.3737 | 6.59 | 94000 | 2.7270 | 0.6166 | 0.6166 | 0.6166 |
243
+ | 0.3766 | 6.63 | 94500 | 2.5289 | 0.6217 | 0.6217 | 0.6217 |
244
+ | 0.4439 | 6.66 | 95000 | 2.6161 | 0.6222 | 0.6222 | 0.6222 |
245
+ | 0.4166 | 6.7 | 95500 | 2.5298 | 0.6123 | 0.6123 | 0.6123 |
246
+ | 0.4064 | 6.73 | 96000 | 2.5952 | 0.6183 | 0.6183 | 0.6183 |
247
+ | 0.4253 | 6.77 | 96500 | 2.4567 | 0.6127 | 0.6127 | 0.6127 |
248
+ | 0.3754 | 6.8 | 97000 | 2.5473 | 0.6131 | 0.6131 | 0.6131 |
249
+ | 0.3993 | 6.84 | 97500 | 2.5563 | 0.6161 | 0.6161 | 0.6161 |
250
+ | 0.3802 | 6.87 | 98000 | 2.6585 | 0.6076 | 0.6076 | 0.6076 |
251
+ | 0.4504 | 6.91 | 98500 | 2.5700 | 0.6127 | 0.6127 | 0.6127 |
252
+ | 0.3832 | 6.94 | 99000 | 2.5983 | 0.6174 | 0.6174 | 0.6174 |
253
+ | 0.4212 | 6.98 | 99500 | 2.6137 | 0.6110 | 0.6110 | 0.6110 |
254
+ | 0.3253 | 7.01 | 100000 | 2.8467 | 0.6024 | 0.6024 | 0.6024 |
255
+ | 0.2553 | 7.05 | 100500 | 2.7412 | 0.6063 | 0.6063 | 0.6063 |
256
+ | 0.2771 | 7.08 | 101000 | 2.8670 | 0.6101 | 0.6101 | 0.6101 |
257
+ | 0.2733 | 7.12 | 101500 | 2.8536 | 0.6166 | 0.6166 | 0.6166 |
258
+ | 0.2972 | 7.15 | 102000 | 2.8254 | 0.6161 | 0.6161 | 0.6161 |
259
+ | 0.2893 | 7.19 | 102500 | 3.0228 | 0.6058 | 0.6058 | 0.6058 |
260
+ | 0.3104 | 7.22 | 103000 | 2.8617 | 0.6011 | 0.6011 | 0.6011 |
261
+ | 0.3019 | 7.26 | 103500 | 3.0106 | 0.6131 | 0.6131 | 0.6131 |
262
+ | 0.3143 | 7.29 | 104000 | 3.0189 | 0.6088 | 0.6088 | 0.6088 |
263
+ | 0.3054 | 7.33 | 104500 | 3.0291 | 0.6063 | 0.6063 | 0.6063 |
264
+ | 0.3145 | 7.36 | 105000 | 3.0166 | 0.6106 | 0.6106 | 0.6106 |
265
+ | 0.2913 | 7.4 | 105500 | 3.0480 | 0.6174 | 0.6174 | 0.6174 |
266
+ | 0.3159 | 7.43 | 106000 | 2.9714 | 0.6084 | 0.6084 | 0.6084 |
267
+ | 0.3216 | 7.47 | 106500 | 2.9359 | 0.6187 | 0.6187 | 0.6187 |
268
+ | 0.2982 | 7.5 | 107000 | 3.0509 | 0.6084 | 0.6084 | 0.6084 |
269
+ | 0.2952 | 7.54 | 107500 | 2.9428 | 0.6076 | 0.6076 | 0.6076 |
270
+ | 0.304 | 7.57 | 108000 | 3.0155 | 0.6071 | 0.6071 | 0.6071 |
271
+ | 0.2896 | 7.61 | 108500 | 3.0276 | 0.6196 | 0.6196 | 0.6196 |
272
+ | 0.3226 | 7.64 | 109000 | 2.9331 | 0.6097 | 0.6097 | 0.6097 |
273
+ | 0.299 | 7.68 | 109500 | 2.9671 | 0.6050 | 0.6050 | 0.6050 |
274
+ | 0.3079 | 7.71 | 110000 | 2.9394 | 0.6093 | 0.6093 | 0.6093 |
275
+ | 0.3064 | 7.75 | 110500 | 2.8690 | 0.6110 | 0.6110 | 0.6110 |
276
+ | 0.3423 | 7.78 | 111000 | 2.9095 | 0.6183 | 0.6183 | 0.6183 |
277
+ | 0.3085 | 7.82 | 111500 | 2.9967 | 0.6260 | 0.6260 | 0.6260 |
278
+ | 0.3071 | 7.85 | 112000 | 2.9429 | 0.6127 | 0.6127 | 0.6127 |
279
+ | 0.3197 | 7.89 | 112500 | 3.0123 | 0.6157 | 0.6157 | 0.6157 |
280
+ | 0.3361 | 7.92 | 113000 | 2.9832 | 0.6170 | 0.6170 | 0.6170 |
281
+ | 0.3252 | 7.96 | 113500 | 3.0174 | 0.6071 | 0.6071 | 0.6071 |
282
+ | 0.2802 | 7.99 | 114000 | 3.0040 | 0.6123 | 0.6123 | 0.6123 |
283
 
284
 
285
  ### Framework versions