| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: BioLinkBERT-LitCovid-v1.2.4 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # BioLinkBERT-LitCovid-v1.2.4 |
| |
|
| | 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: 0.2160 |
| | - F1 micro: 0.8926 |
| | - F1 macro: 0.3237 |
| | - F1 weighted: 0.9016 |
| | - F1 samples: 0.9024 |
| | - Precision micro: 0.8426 |
| | - Precision macro: 0.2736 |
| | - Precision weighted: 0.8627 |
| | - Precision samples: 0.8871 |
| | - Recall micro: 0.9490 |
| | - Recall macro: 0.4834 |
| | - Recall weighted: 0.9490 |
| | - Recall samples: 0.9544 |
| | - Roc Auc: 0.9697 |
| | - Accuracy: 0.7353 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 2e-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 3 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | F1 micro | F1 macro | F1 weighted | F1 samples | Precision micro | Precision macro | Precision weighted | Precision samples | Recall micro | Recall macro | Recall weighted | Recall samples | Roc Auc | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:----------:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:------------:|:---------------:|:--------------:|:-------:|:--------:| |
| | | 0.4454 | 1.0 | 2248 | 0.3019 | 0.8637 | 0.2988 | 0.8757 | 0.8789 | 0.7937 | 0.2500 | 0.8205 | 0.8518 | 0.9471 | 0.4390 | 0.9471 | 0.9528 | 0.9669 | 0.6618 | |
| | | 0.2453 | 2.0 | 4496 | 0.2696 | 0.8852 | 0.3387 | 0.8917 | 0.8947 | 0.8231 | 0.2862 | 0.8377 | 0.8701 | 0.9574 | 0.4723 | 0.9574 | 0.9602 | 0.9731 | 0.7056 | |
| | | 0.1271 | 3.0 | 6744 | 0.2160 | 0.8926 | 0.3237 | 0.9016 | 0.9024 | 0.8426 | 0.2736 | 0.8627 | 0.8871 | 0.9490 | 0.4834 | 0.9490 | 0.9544 | 0.9697 | 0.7353 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.0 |
| | - Pytorch 2.0.0 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.13.3 |
| |
|
