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bert-medical-ner

Token Classification
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distilbert
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update model card README.md

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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.4966
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- - Precision: 0.7640
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- - Recall: 0.6936
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- - F1: 0.7271
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- - Accuracy: 0.9433
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  ## Model description
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@@ -54,26 +54,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 63 | 0.4909 | 0.8023 | 0.6653 | 0.7274 | 0.9429 |
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- | No log | 2.0 | 126 | 0.4686 | 0.7434 | 0.6829 | 0.7118 | 0.9414 |
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- | No log | 3.0 | 189 | 0.4578 | 0.6967 | 0.6987 | 0.6977 | 0.9378 |
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- | No log | 4.0 | 252 | 0.4689 | 0.7492 | 0.6942 | 0.7207 | 0.9425 |
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- | No log | 5.0 | 315 | 0.4882 | 0.7613 | 0.6744 | 0.7152 | 0.9412 |
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- | No log | 6.0 | 378 | 0.4880 | 0.7417 | 0.6914 | 0.7156 | 0.9403 |
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- | No log | 7.0 | 441 | 0.4823 | 0.7448 | 0.7027 | 0.7231 | 0.9419 |
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- | 0.0036 | 8.0 | 504 | 0.4787 | 0.7318 | 0.7049 | 0.7181 | 0.9399 |
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- | 0.0036 | 9.0 | 567 | 0.4953 | 0.7413 | 0.6981 | 0.7191 | 0.9425 |
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- | 0.0036 | 10.0 | 630 | 0.4910 | 0.7442 | 0.7038 | 0.7234 | 0.9426 |
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- | 0.0036 | 11.0 | 693 | 0.4894 | 0.7421 | 0.7044 | 0.7227 | 0.9411 |
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- | 0.0036 | 12.0 | 756 | 0.4958 | 0.7402 | 0.7072 | 0.7233 | 0.9408 |
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- | 0.0036 | 13.0 | 819 | 0.5032 | 0.7438 | 0.6976 | 0.7200 | 0.9416 |
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- | 0.0036 | 14.0 | 882 | 0.5009 | 0.7241 | 0.7060 | 0.7149 | 0.9396 |
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- | 0.0036 | 15.0 | 945 | 0.5033 | 0.7653 | 0.6947 | 0.7283 | 0.9432 |
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- | 0.0018 | 16.0 | 1008 | 0.5101 | 0.7814 | 0.6829 | 0.7288 | 0.9434 |
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- | 0.0018 | 17.0 | 1071 | 0.4935 | 0.7606 | 0.6987 | 0.7283 | 0.9440 |
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- | 0.0018 | 18.0 | 1134 | 0.4920 | 0.7549 | 0.7015 | 0.7272 | 0.9433 |
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- | 0.0018 | 19.0 | 1197 | 0.4970 | 0.7613 | 0.6959 | 0.7271 | 0.9434 |
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- | 0.0018 | 20.0 | 1260 | 0.4966 | 0.7640 | 0.6936 | 0.7271 | 0.9433 |
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  ### Framework versions
 
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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: 0.4000
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+ - Precision: 0.7565
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+ - Recall: 0.6791
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+ - F1: 0.7157
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+ - Accuracy: 0.9405
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 63 | 0.4610 | 0.6626 | 0.3672 | 0.4726 | 0.9098 |
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+ | No log | 2.0 | 126 | 0.3464 | 0.6908 | 0.5113 | 0.5877 | 0.9245 |
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+ | No log | 3.0 | 189 | 0.3237 | 0.6658 | 0.5898 | 0.6255 | 0.9268 |
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+ | No log | 4.0 | 252 | 0.3029 | 0.6965 | 0.6147 | 0.6531 | 0.9322 |
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+ | No log | 5.0 | 315 | 0.3327 | 0.7542 | 0.6102 | 0.6746 | 0.9341 |
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+ | No log | 6.0 | 378 | 0.3239 | 0.7371 | 0.6305 | 0.6797 | 0.9364 |
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+ | No log | 7.0 | 441 | 0.3318 | 0.6975 | 0.6825 | 0.6899 | 0.9353 |
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+ | 0.2658 | 8.0 | 504 | 0.3478 | 0.7440 | 0.6667 | 0.7032 | 0.9380 |
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+ | 0.2658 | 9.0 | 567 | 0.3835 | 0.7536 | 0.6548 | 0.7007 | 0.9381 |
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+ | 0.2658 | 10.0 | 630 | 0.3662 | 0.7455 | 0.6718 | 0.7067 | 0.9389 |
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+ | 0.2658 | 11.0 | 693 | 0.3732 | 0.7394 | 0.6588 | 0.6967 | 0.9388 |
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+ | 0.2658 | 12.0 | 756 | 0.3739 | 0.7505 | 0.6695 | 0.7077 | 0.9403 |
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+ | 0.2658 | 13.0 | 819 | 0.3884 | 0.7513 | 0.6655 | 0.7058 | 0.9397 |
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+ | 0.2658 | 14.0 | 882 | 0.3955 | 0.7609 | 0.6616 | 0.7078 | 0.9398 |
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+ | 0.2658 | 15.0 | 945 | 0.3986 | 0.7689 | 0.6599 | 0.7102 | 0.9401 |
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+ | 0.0369 | 16.0 | 1008 | 0.3975 | 0.7633 | 0.6723 | 0.7149 | 0.9408 |
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+ | 0.0369 | 17.0 | 1071 | 0.3955 | 0.7437 | 0.6819 | 0.7115 | 0.9401 |
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+ | 0.0369 | 18.0 | 1134 | 0.3968 | 0.7555 | 0.6808 | 0.7162 | 0.9408 |
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+ | 0.0369 | 19.0 | 1197 | 0.3999 | 0.7527 | 0.6791 | 0.7140 | 0.9405 |
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+ | 0.0369 | 20.0 | 1260 | 0.4000 | 0.7565 | 0.6791 | 0.7157 | 0.9405 |
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  ### Framework versions