metadata
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: contrast_classifier_bio_bert
results: []
contrast_classifier_bio_bert
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: 0.1097
- Accuracy: 0.9857
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0075 | 1.0 | 18 | 0.2757 | 0.9286 |
| 0.0024 | 2.0 | 36 | 0.5377 | 0.8429 |
| 0.0009 | 3.0 | 54 | 0.1979 | 0.9714 |
| 0.0006 | 4.0 | 72 | 0.1630 | 0.9714 |
| 0.0004 | 5.0 | 90 | 0.1114 | 0.9857 |
| 0.0004 | 6.0 | 108 | 0.1033 | 0.9857 |
| 0.0003 | 7.0 | 126 | 0.1036 | 0.9857 |
| 0.0003 | 8.0 | 144 | 0.1067 | 0.9857 |
| 0.0003 | 9.0 | 162 | 0.1095 | 0.9857 |
| 0.0003 | 10.0 | 180 | 0.1094 | 0.9857 |
| 0.0002 | 11.0 | 198 | 0.1096 | 0.9857 |
| 0.0002 | 12.0 | 216 | 0.1097 | 0.9857 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0