| | --- |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: BioBERT-LitCovid-v1.3.1 |
| | 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. --> |
| |
|
| | # BioBERT-LitCovid-v1.3.1 |
| |
|
| | This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6731 |
| | - Hamming loss: 0.0186 |
| | - F1 micro: 0.8434 |
| | - F1 macro: 0.3657 |
| | - F1 weighted: 0.8790 |
| | - F1 samples: 0.8763 |
| | - Precision micro: 0.7702 |
| | - Precision macro: 0.2942 |
| | - Precision weighted: 0.8399 |
| | - Precision samples: 0.8618 |
| | - Recall micro: 0.9320 |
| | - Recall macro: 0.7288 |
| | - Recall weighted: 0.9320 |
| | - Recall samples: 0.9432 |
| | - Roc Auc: 0.9581 |
| | - Accuracy: 0.6841 |
| |
|
| | ## 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 | Hamming 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------------:|:--------:|:--------:|:-----------:|:----------:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:------------:|:---------------:|:--------------:|:-------:|:--------:| |
| | | 1.1065 | 1.0 | 2272 | 0.4899 | 0.0357 | 0.7347 | 0.2684 | 0.8280 | 0.8274 | 0.6112 | 0.2128 | 0.7700 | 0.7976 | 0.9207 | 0.7424 | 0.9207 | 0.9370 | 0.9437 | 0.5688 | |
| | | 0.8552 | 2.0 | 4544 | 0.4641 | 0.0246 | 0.8018 | 0.3270 | 0.8588 | 0.8548 | 0.7057 | 0.2595 | 0.8123 | 0.8327 | 0.9282 | 0.7833 | 0.9282 | 0.9424 | 0.9531 | 0.6325 | |
| | | 0.7061 | 3.0 | 6816 | 0.5058 | 0.0227 | 0.8166 | 0.3320 | 0.8679 | 0.8652 | 0.7201 | 0.2640 | 0.8146 | 0.8402 | 0.9429 | 0.7601 | 0.9429 | 0.9522 | 0.9611 | 0.6548 | |
| | | 0.5914 | 4.0 | 9088 | 0.6116 | 0.0196 | 0.8368 | 0.3588 | 0.8758 | 0.8719 | 0.7572 | 0.2869 | 0.8321 | 0.8533 | 0.9353 | 0.7398 | 0.9353 | 0.9456 | 0.9591 | 0.6706 | |
| | | 0.294 | 5.0 | 11360 | 0.6731 | 0.0186 | 0.8434 | 0.3657 | 0.8790 | 0.8763 | 0.7702 | 0.2942 | 0.8399 | 0.8618 | 0.9320 | 0.7288 | 0.9320 | 0.9432 | 0.9581 | 0.6841 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.0 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.13.3 |
| |
|
