| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: BioLinkBERT-LitCovid-v1.2.3 |
| | 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-v1.2.3 |
| |
|
| | 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: 0.9691 |
| | - F1 micro: 0.8266 |
| | - F1 macro: 0.3107 |
| | - F1 weighted: 0.8821 |
| | - F1 samples: 0.8868 |
| | - Precision micro: 0.7335 |
| | - Precision macro: 0.2518 |
| | - Precision weighted: 0.8347 |
| | - Precision samples: 0.8699 |
| | - Recall micro: 0.9468 |
| | - Recall macro: 0.7764 |
| | - Recall weighted: 0.9468 |
| | - Recall samples: 0.9538 |
| | - Roc Auc: 0.9640 |
| | - Accuracy: 0.7104 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:----------:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:------------:|:---------------:|:--------------:|:-------:|:--------:| |
| | | 1.1059 | 1.0 | 2272 | 0.7606 | 0.7517 | 0.2617 | 0.8428 | 0.8566 | 0.6257 | 0.2096 | 0.7778 | 0.8302 | 0.9412 | 0.7947 | 0.9412 | 0.9501 | 0.9553 | 0.6325 | |
| | | 0.6408 | 2.0 | 4544 | 0.8639 | 0.8057 | 0.2965 | 0.8751 | 0.8786 | 0.7057 | 0.2399 | 0.8315 | 0.8626 | 0.9389 | 0.8070 | 0.9389 | 0.9484 | 0.9588 | 0.6961 | |
| | | 0.6275 | 3.0 | 6816 | 0.9691 | 0.8266 | 0.3107 | 0.8821 | 0.8868 | 0.7335 | 0.2518 | 0.8347 | 0.8699 | 0.9468 | 0.7764 | 0.9468 | 0.9538 | 0.9640 | 0.7104 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.0 |
| | - Pytorch 2.0.0 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.13.3 |
| |
|
