PubMedELECTRA-Large-LitCovid-v1.0
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedELECTRA-large-uncased-abstract on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1102
- F1: 0.8974
- Roc Auc: 0.9322
- Accuracy: 0.7942
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.1183 | 1.0 | 6240 | 0.1102 | 0.8974 | 0.9322 | 0.7942 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3