EXP_3_MULTI_DISEASE_BIO-dmis-lab-biobert-v1.1
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1311
- Precision: 0.6867
- Recall: 0.6331
- F1: 0.6588
- Accuracy: 0.9644
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1747 | 1.0 | 220 | 0.1701 | 0.6154 | 0.5565 | 0.5845 | 0.9575 |
| 0.1341 | 2.0 | 440 | 0.1374 | 0.6655 | 0.6218 | 0.6429 | 0.9628 |
| 0.1202 | 3.0 | 660 | 0.1311 | 0.6867 | 0.6331 | 0.6588 | 0.9644 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for irebil/EXP_3_MULTI_DISEASE_BIO_FULL-dmis-lab-biobert-v1.1
Base model
dmis-lab/biobert-v1.1