| | --- |
| | license: mit |
| | --- |
| | # BioLinkBERT-LitCovid-v1.0 |
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| | This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1098 |
| | - F1: 0.8992 |
| | - Roc Auc: 0.9330 |
| | - Accuracy: 0.7945 |
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| | ## Model description |
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| | More information needed |
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| | ## Intended uses & limitations |
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| | More information needed |
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| | ## Training and evaluation data |
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| | More information needed |
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| | ## Training procedure |
| | ### Training hyperparameters |
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| | The following hyperparameters were used during training: |
| | - learning_rate: 2e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 1 |
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| | ### Training results |
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| | | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
| | | 0.1172 | 1.0 | 3120 | 0.1098 | 0.8992 | 0.9330 | 0.7945 | |
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| | ### Framework versions |
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| | - Transformers 4.28.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.3 |