| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: Bioformer-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. --> |
| |
|
| | # Bioformer-LitCovid-v1.3.1 |
| |
|
| | 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: 0.4639 |
| | - Hamming loss: 0.0375 |
| | - F1 micro: 0.7254 |
| | - F1 macro: 0.2721 |
| | - F1 weighted: 0.8153 |
| | - F1 samples: 0.8091 |
| | - Precision micro: 0.5970 |
| | - Precision macro: 0.2139 |
| | - Precision weighted: 0.7445 |
| | - Precision samples: 0.7700 |
| | - Recall micro: 0.9243 |
| | - Recall macro: 0.7966 |
| | - Recall weighted: 0.9243 |
| | - Recall samples: 0.9342 |
| | - Roc Auc: 0.9445 |
| | - Accuracy: 0.5243 |
| |
|
| | ## 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: 32 |
| | - eval_batch_size: 32 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------------:|:--------:|:--------:|:-----------:|:----------:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:------------:|:---------------:|:--------------:|:-------:|:--------:| |
| | | 0.9561 | 1.0 | 1136 | 0.5778 | 0.0745 | 0.5683 | 0.2036 | 0.7263 | 0.6631 | 0.4123 | 0.1552 | 0.6235 | 0.5852 | 0.9144 | 0.7912 | 0.9144 | 0.9216 | 0.9203 | 0.2653 | |
| | | 0.7759 | 2.0 | 2272 | 0.4875 | 0.0440 | 0.6899 | 0.2545 | 0.7872 | 0.7686 | 0.5543 | 0.1978 | 0.7076 | 0.7196 | 0.9134 | 0.7626 | 0.9134 | 0.9238 | 0.9359 | 0.4380 | |
| | | 0.6398 | 3.0 | 3408 | 0.4722 | 0.0385 | 0.7188 | 0.2699 | 0.8005 | 0.7910 | 0.5907 | 0.2101 | 0.7250 | 0.7463 | 0.9179 | 0.7580 | 0.9179 | 0.9274 | 0.9409 | 0.4832 | |
| | | 0.5712 | 4.0 | 4544 | 0.4652 | 0.0374 | 0.7264 | 0.2754 | 0.8096 | 0.8018 | 0.5980 | 0.2151 | 0.7347 | 0.7582 | 0.9250 | 0.7774 | 0.9250 | 0.9343 | 0.9449 | 0.5034 | |
| | | 0.4337 | 5.0 | 5680 | 0.4639 | 0.0375 | 0.7254 | 0.2721 | 0.8153 | 0.8091 | 0.5970 | 0.2139 | 0.7445 | 0.7700 | 0.9243 | 0.7966 | 0.9243 | 0.9342 | 0.9445 | 0.5243 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.0 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.13.3 |
| |
|
