EXP_1_BINARY-dmis-lab-biobert-v1.1
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1974
- Precision: 0.8943
- Recall: 0.9235
- F1: 0.9087
- Accuracy: 0.9229
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 | Accuracy | F1 | Validation Loss | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.2125 | 1.0 | 220 | 0.9204 | 0.9069 | 0.2056 | 0.8818 | 0.9335 |
| 0.2011 | 2.0 | 440 | 0.9223 | 0.9088 | 0.2003 | 0.8858 | 0.9331 |
| 0.1929 | 3.0 | 660 | 0.1974 | 0.8943 | 0.9235 | 0.9087 | 0.9229 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.1+cu130
- Datasets 4.4.1
- Tokenizers 0.22.1
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