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ClinicalBERT-medical-text-classification

Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +12 -19
  2. model.safetensors +1 -1
README.md CHANGED
@@ -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 [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.4453
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- - Accuracy: 0.284
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- - Precision: 0.1812
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- - Recall: 0.284
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- - F1: 0.2132
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  ## Model description
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@@ -55,20 +55,13 @@ 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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- | 2.9605 | 1.0 | 250 | 2.9477 | 0.221 | 0.0488 | 0.221 | 0.0800 |
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- | 2.5952 | 2.0 | 500 | 2.5658 | 0.341 | 0.1400 | 0.341 | 0.1958 |
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- | 2.5191 | 3.0 | 750 | 2.4897 | 0.355 | 0.1531 | 0.355 | 0.2046 |
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- | 2.414 | 4.0 | 1000 | 2.5463 | 0.323 | 0.1913 | 0.323 | 0.1902 |
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- | 2.2946 | 5.0 | 1250 | 2.4793 | 0.347 | 0.1461 | 0.347 | 0.2023 |
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- | 2.4065 | 6.0 | 1500 | 2.4471 | 0.349 | 0.1684 | 0.349 | 0.2198 |
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- | 2.3267 | 7.0 | 1750 | 2.4408 | 0.344 | 0.1672 | 0.344 | 0.2193 |
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- | 2.3173 | 8.0 | 2000 | 2.4214 | 0.358 | 0.1748 | 0.358 | 0.2286 |
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- | 2.1692 | 9.0 | 2250 | 2.4358 | 0.339 | 0.1638 | 0.339 | 0.2147 |
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- | 2.029 | 10.0 | 2500 | 2.4074 | 0.338 | 0.1658 | 0.338 | 0.2178 |
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- | 2.125 | 11.0 | 2750 | 2.3605 | 0.334 | 0.1756 | 0.334 | 0.2239 |
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- | 1.9541 | 12.0 | 3000 | 2.3997 | 0.326 | 0.1623 | 0.326 | 0.2123 |
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- | 2.1619 | 13.0 | 3250 | 2.4450 | 0.321 | 0.1765 | 0.321 | 0.2127 |
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- | 2.101 | 14.0 | 3500 | 2.4453 | 0.284 | 0.1812 | 0.284 | 0.2132 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.0223
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+ - Accuracy: 0.273
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+ - Precision: 0.2079
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+ - Recall: 0.273
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+ - F1: 0.2270
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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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+ | 2.5449 | 1.0 | 250 | 2.5124 | 0.377 | 0.1879 | 0.377 | 0.2437 |
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+ | 2.0748 | 2.0 | 500 | 2.0375 | 0.372 | 0.3107 | 0.372 | 0.2994 |
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+ | 1.766 | 3.0 | 750 | 1.8367 | 0.351 | 0.3350 | 0.351 | 0.3148 |
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+ | 1.6599 | 4.0 | 1000 | 1.8015 | 0.303 | 0.2597 | 0.303 | 0.2703 |
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+ | 1.4441 | 5.0 | 1250 | 1.9012 | 0.308 | 0.2483 | 0.308 | 0.2634 |
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+ | 1.4366 | 6.0 | 1500 | 1.9159 | 0.253 | 0.2412 | 0.253 | 0.2390 |
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+ | 1.1871 | 7.0 | 1750 | 2.0223 | 0.273 | 0.2079 | 0.273 | 0.2270 |
 
 
 
 
 
 
 
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  ### Framework versions
model.safetensors CHANGED
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