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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: 0.4000
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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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@@ -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 | 0.4610 | 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
 
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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: 1.0409
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+ - Precision: 0.6097
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+ - Recall: 0.6323
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+ - F1: 0.6208
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+ - Accuracy: 0.7607
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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 | 1.6300 | 0.3434 | 0.3838 | 0.3625 | 0.6077 |
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+ | No log | 2.0 | 126 | 1.2289 | 0.4831 | 0.5207 | 0.5012 | 0.6893 |
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+ | No log | 3.0 | 189 | 1.0878 | 0.5261 | 0.5762 | 0.5500 | 0.7197 |
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+ | No log | 4.0 | 252 | 1.0253 | 0.5541 | 0.5914 | 0.5721 | 0.7328 |
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+ | No log | 5.0 | 315 | 0.9738 | 0.5689 | 0.6040 | 0.5859 | 0.7416 |
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+ | No log | 6.0 | 378 | 0.9498 | 0.5828 | 0.6094 | 0.5958 | 0.7472 |
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+ | No log | 7.0 | 441 | 0.9532 | 0.5954 | 0.6126 | 0.6039 | 0.7509 |
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+ | 1.1083 | 8.0 | 504 | 0.9515 | 0.5994 | 0.6166 | 0.6079 | 0.7530 |
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+ | 1.1083 | 9.0 | 567 | 0.9572 | 0.6010 | 0.6212 | 0.6109 | 0.7547 |
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+ | 1.1083 | 10.0 | 630 | 0.9690 | 0.5986 | 0.6162 | 0.6072 | 0.7539 |
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+ | 1.1083 | 11.0 | 693 | 0.9798 | 0.5953 | 0.6232 | 0.6089 | 0.7532 |
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+ | 1.1083 | 12.0 | 756 | 0.9813 | 0.5986 | 0.6185 | 0.6084 | 0.7546 |
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+ | 1.1083 | 13.0 | 819 | 0.9984 | 0.5979 | 0.6182 | 0.6079 | 0.7539 |
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+ | 1.1083 | 14.0 | 882 | 1.0111 | 0.6026 | 0.6226 | 0.6124 | 0.7557 |
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+ | 1.1083 | 15.0 | 945 | 1.0140 | 0.6050 | 0.6262 | 0.6155 | 0.7572 |
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+ | 0.4329 | 16.0 | 1008 | 1.0252 | 0.6112 | 0.6210 | 0.6160 | 0.7580 |
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+ | 0.4329 | 17.0 | 1071 | 1.0312 | 0.6090 | 0.6288 | 0.6187 | 0.7602 |
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+ | 0.4329 | 18.0 | 1134 | 1.0368 | 0.6059 | 0.6314 | 0.6184 | 0.7597 |
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+ | 0.4329 | 19.0 | 1197 | 1.0395 | 0.6095 | 0.6299 | 0.6196 | 0.7599 |
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+ | 0.4329 | 20.0 | 1260 | 1.0409 | 0.6097 | 0.6323 | 0.6208 | 0.7607 |
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  ### Framework versions