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update model card README.md

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  tags:
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  - generated_from_trainer
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  metrics:
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  # medlid-identify
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- This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1617
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- - Precision: 0.4085
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- - Recall: 0.4551
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- - F1: 0.4305
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- - Accuracy: 0.9452
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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 | 381 | 0.1447 | 0.3867 | 0.2215 | 0.2817 | 0.9440 |
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- | 0.1714 | 2.0 | 762 | 0.1410 | 0.3937 | 0.4513 | 0.4206 | 0.9457 |
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- | 0.107 | 3.0 | 1143 | 0.1487 | 0.4061 | 0.4347 | 0.4199 | 0.9456 |
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- | 0.0702 | 4.0 | 1524 | 0.1617 | 0.4085 | 0.4551 | 0.4305 | 0.9452 |
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  ### Framework versions
 
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  ---
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+ license: apache-2.0
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # medlid-identify
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+ This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1708
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+ - Precision: 0.3912
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+ - Recall: 0.4603
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+ - F1: 0.4229
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+ - Accuracy: 0.9463
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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 | 381 | 0.1567 | 0.2689 | 0.3180 | 0.2914 | 0.9377 |
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+ | 0.1618 | 2.0 | 762 | 0.1399 | 0.4016 | 0.3847 | 0.3930 | 0.9492 |
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+ | 0.0978 | 3.0 | 1143 | 0.1505 | 0.3773 | 0.4239 | 0.3993 | 0.9468 |
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+ | 0.0636 | 4.0 | 1524 | 0.1708 | 0.3912 | 0.4603 | 0.4229 | 0.9463 |
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  ### Framework versions