metadata
library_name: transformers
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: biobert-v1.1-finetuned-medmcqa-2024-11-25-T17-01-22
results: []
biobert-v1.1-finetuned-medmcqa-2024-11-25-T17-01-22
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: 1.1793
- Accuracy: 0.5374
- F1: 0.5383
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.3839 | 0.9739 | 14 | 1.1338 | 0.5109 | 0.5122 |
| 1.0754 | 1.9478 | 28 | 1.1150 | 0.5204 | 0.5224 |
| 0.6423 | 2.9913 | 43 | 1.0494 | 0.5300 | 0.5305 |
| 0.478 | 3.9652 | 57 | 1.1793 | 0.5374 | 0.5383 |
| 0.245 | 4.9391 | 71 | 1.4143 | 0.5372 | 0.5381 |
| 0.1731 | 5.9826 | 86 | 1.7302 | 0.5317 | 0.5329 |
| 0.1229 | 6.9565 | 100 | 1.8354 | 0.5326 | 0.5337 |
| 0.0833 | 8.0 | 115 | 1.9010 | 0.5288 | 0.5299 |
| 0.0735 | 8.9739 | 129 | 2.1489 | 0.5305 | 0.5314 |
| 0.0647 | 9.7391 | 140 | 2.0799 | 0.5357 | 0.5368 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3