biobert-v1.1-finetuned-medmcqa-50pct-2024-12-01-T13-47-07
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: 0.9205
- Accuracy: 0.5761
- F1: 0.5771
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: 0.000159
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.7473 | 0.9998 | 2856 | 0.9545 | 0.5446 | 0.5449 |
| 0.6317 | 1.9996 | 5712 | 0.9094 | 0.5663 | 0.5675 |
| 0.4156 | 2.9995 | 8568 | 0.9205 | 0.5761 | 0.5771 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for maxg73872/biobert-v1.1-finetuned-medmcqa-50pct-2024-12-01-T13-47-07
Base model
dmis-lab/biobert-v1.1