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tiny-clinicalbert-medical-text-classification

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  1. README.md +18 -19
  2. model.safetensors +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [nlpie/tiny-clinicalbert](https://huggingface.co/nlpie/tiny-clinicalbert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.2272
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- - Accuracy: 0.213
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- - Precision: 0.1898
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- - Recall: 0.213
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- - F1: 0.1921
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  ## Model description
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@@ -56,20 +56,19 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 2.9976 | 1.0 | 250 | 3.0250 | 0.298 | 0.0982 | 0.298 | 0.1474 |
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- | 2.4802 | 2.0 | 500 | 2.6180 | 0.334 | 0.1773 | 0.334 | 0.1882 |
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- | 2.4977 | 3.0 | 750 | 2.4527 | 0.363 | 0.2104 | 0.363 | 0.2298 |
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- | 2.2893 | 4.0 | 1000 | 2.3684 | 0.362 | 0.2032 | 0.362 | 0.2461 |
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- | 2.1835 | 5.0 | 1250 | 2.3003 | 0.347 | 0.2109 | 0.347 | 0.2510 |
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- | 1.9286 | 6.0 | 1500 | 2.2099 | 0.343 | 0.2286 | 0.343 | 0.2584 |
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- | 1.9987 | 7.0 | 1750 | 2.1823 | 0.335 | 0.2292 | 0.335 | 0.2658 |
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- | 1.8852 | 8.0 | 2000 | 2.1622 | 0.32 | 0.2166 | 0.32 | 0.2514 |
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- | 1.9469 | 9.0 | 2250 | 2.1727 | 0.304 | 0.2026 | 0.304 | 0.2318 |
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- | 1.7341 | 10.0 | 2500 | 2.1651 | 0.296 | 0.2360 | 0.296 | 0.2387 |
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- | 1.615 | 11.0 | 2750 | 2.1558 | 0.269 | 0.2183 | 0.269 | 0.2246 |
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- | 1.6972 | 12.0 | 3000 | 2.1874 | 0.269 | 0.2210 | 0.269 | 0.2289 |
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- | 1.3663 | 13.0 | 3250 | 2.1982 | 0.253 | 0.2169 | 0.253 | 0.2181 |
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- | 1.5938 | 14.0 | 3500 | 2.2272 | 0.213 | 0.1898 | 0.213 | 0.1921 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [nlpie/tiny-clinicalbert](https://huggingface.co/nlpie/tiny-clinicalbert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.1588
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+ - Accuracy: 0.236
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+ - Precision: 0.2048
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+ - Recall: 0.236
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+ - F1: 0.2109
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 2.9902 | 1.0 | 250 | 3.0201 | 0.274 | 0.0880 | 0.274 | 0.1318 |
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+ | 2.4558 | 2.0 | 500 | 2.6033 | 0.341 | 0.1392 | 0.341 | 0.1922 |
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+ | 2.4627 | 3.0 | 750 | 2.4332 | 0.368 | 0.2003 | 0.368 | 0.2252 |
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+ | 2.2983 | 4.0 | 1000 | 2.3126 | 0.365 | 0.2212 | 0.365 | 0.2495 |
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+ | 2.1395 | 5.0 | 1250 | 2.2385 | 0.349 | 0.2100 | 0.349 | 0.2518 |
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+ | 1.8919 | 6.0 | 1500 | 2.1892 | 0.339 | 0.2176 | 0.339 | 0.2490 |
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+ | 1.9892 | 7.0 | 1750 | 2.1364 | 0.336 | 0.2310 | 0.336 | 0.2643 |
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+ | 1.8569 | 8.0 | 2000 | 2.1441 | 0.321 | 0.2316 | 0.321 | 0.2532 |
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+ | 1.9182 | 9.0 | 2250 | 2.1263 | 0.309 | 0.2185 | 0.309 | 0.2417 |
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+ | 1.6594 | 10.0 | 2500 | 2.1234 | 0.262 | 0.2180 | 0.262 | 0.2245 |
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+ | 1.5966 | 11.0 | 2750 | 2.1176 | 0.256 | 0.2149 | 0.256 | 0.2197 |
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+ | 1.6185 | 12.0 | 3000 | 2.1578 | 0.243 | 0.2126 | 0.243 | 0.2140 |
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+ | 1.3881 | 13.0 | 3250 | 2.1588 | 0.236 | 0.2048 | 0.236 | 0.2109 |
 
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  ### Framework versions
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