| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: Bioformer-LitCovid-v1.2.2 |
| | 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. --> |
| |
|
| | # Bioformer-LitCovid-v1.2.2 |
| |
|
| | This model is a fine-tuned version of [bioformers/bioformer-litcovid](https://huggingface.co/bioformers/bioformer-litcovid) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2230 |
| | - F1 micro: 0.9107 |
| | - F1 macro: 0.8633 |
| | - F1 weighted: 0.9127 |
| | - F1 samples: 0.9132 |
| | - Precision micro: 0.8780 |
| | - Precision macro: 0.8105 |
| | - Precision weighted: 0.8840 |
| | - Precision samples: 0.9034 |
| | - Recall micro: 0.9460 |
| | - Recall macro: 0.9339 |
| | - Recall weighted: 0.9460 |
| | - Recall samples: 0.9534 |
| | - Roc Auc: 0.9577 |
| | - Accuracy: 0.7542 |
| |
|
| | ## 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: 5 |
| |
|
| | ### 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------:|:----------:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:------------:|:---------------:|:--------------:|:-------:|:--------:| |
| | | 0.2625 | 1.0 | 2183 | 0.2415 | 0.8961 | 0.8499 | 0.8980 | 0.8996 | 0.8443 | 0.7844 | 0.8501 | 0.8775 | 0.9545 | 0.9373 | 0.9545 | 0.9590 | 0.9568 | 0.7083 | |
| | | 0.2099 | 2.0 | 4366 | 0.2230 | 0.9107 | 0.8633 | 0.9127 | 0.9132 | 0.8780 | 0.8105 | 0.8840 | 0.9034 | 0.9460 | 0.9339 | 0.9460 | 0.9534 | 0.9577 | 0.7542 | |
| | | 0.1735 | 3.0 | 6549 | 0.2661 | 0.9141 | 0.8732 | 0.9153 | 0.9155 | 0.8821 | 0.8361 | 0.8857 | 0.9057 | 0.9486 | 0.9203 | 0.9486 | 0.9543 | 0.9596 | 0.7653 | |
| | | 0.1336 | 4.0 | 8732 | 0.2682 | 0.9187 | 0.8769 | 0.9197 | 0.9207 | 0.8953 | 0.8408 | 0.8979 | 0.9169 | 0.9435 | 0.9199 | 0.9435 | 0.9511 | 0.9589 | 0.7804 | |
| | | 0.1102 | 5.0 | 10915 | 0.2825 | 0.9183 | 0.8778 | 0.9191 | 0.9199 | 0.8913 | 0.8413 | 0.8936 | 0.9134 | 0.9470 | 0.9202 | 0.9470 | 0.9536 | 0.9601 | 0.7792 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.0 |
| | - Pytorch 2.0.0 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.13.3 |
| |
|
