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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: 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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@@ -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 | 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
 
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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: 1.0318
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+ - Precision: 0.6083
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+ - Recall: 0.6344
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+ - F1: 0.6210
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+ - Accuracy: 0.7635
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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 | 1.6731 | 0.3451 | 0.3549 | 0.3499 | 0.6003 |
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+ | No log | 2.0 | 126 | 1.2481 | 0.4832 | 0.5248 | 0.5032 | 0.6912 |
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+ | No log | 3.0 | 189 | 1.0959 | 0.5280 | 0.5703 | 0.5483 | 0.7198 |
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+ | No log | 4.0 | 252 | 1.0258 | 0.5577 | 0.5878 | 0.5723 | 0.7330 |
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+ | No log | 5.0 | 315 | 0.9761 | 0.5788 | 0.6038 | 0.5910 | 0.7433 |
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+ | No log | 6.0 | 378 | 0.9461 | 0.5909 | 0.6068 | 0.5988 | 0.7478 |
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+ | No log | 7.0 | 441 | 0.9456 | 0.5918 | 0.6143 | 0.6029 | 0.7516 |
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+ | 1.1189 | 8.0 | 504 | 0.9396 | 0.5991 | 0.6164 | 0.6076 | 0.7562 |
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+ | 1.1189 | 9.0 | 567 | 0.9594 | 0.6020 | 0.6252 | 0.6134 | 0.7569 |
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+ | 1.1189 | 10.0 | 630 | 0.9742 | 0.6005 | 0.6203 | 0.6102 | 0.7555 |
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+ | 1.1189 | 11.0 | 693 | 0.9700 | 0.6063 | 0.6256 | 0.6158 | 0.7597 |
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+ | 1.1189 | 12.0 | 756 | 0.9772 | 0.5999 | 0.6246 | 0.6120 | 0.7582 |
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+ | 1.1189 | 13.0 | 819 | 0.9890 | 0.6023 | 0.6254 | 0.6137 | 0.7593 |
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+ | 1.1189 | 14.0 | 882 | 1.0011 | 0.6077 | 0.6332 | 0.6202 | 0.7631 |
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+ | 1.1189 | 15.0 | 945 | 1.0096 | 0.6057 | 0.6305 | 0.6178 | 0.7613 |
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+ | 0.4346 | 16.0 | 1008 | 1.0167 | 0.6112 | 0.6281 | 0.6195 | 0.7625 |
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+ | 0.4346 | 17.0 | 1071 | 1.0227 | 0.6126 | 0.6357 | 0.6240 | 0.7651 |
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+ | 0.4346 | 18.0 | 1134 | 1.0290 | 0.6072 | 0.6357 | 0.6212 | 0.7635 |
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+ | 0.4346 | 19.0 | 1197 | 1.0288 | 0.6094 | 0.6363 | 0.6226 | 0.7643 |
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+ | 0.4346 | 20.0 | 1260 | 1.0318 | 0.6083 | 0.6344 | 0.6210 | 0.7635 |
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  ### Framework versions