metadata
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: contrast_classifier_biobert_v2
results: []
contrast_classifier_biobert_v2
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: 0.0010
- Accuracy: 1.0
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.653 | 1.0 | 37 | 0.6146 | 0.7273 |
| 0.4263 | 2.0 | 74 | 0.2425 | 0.9697 |
| 0.1128 | 3.0 | 111 | 0.0098 | 1.0 |
| 0.0275 | 4.0 | 148 | 0.0031 | 1.0 |
| 0.003 | 5.0 | 185 | 0.0023 | 1.0 |
| 0.0023 | 6.0 | 222 | 0.0015 | 1.0 |
| 0.0018 | 7.0 | 259 | 0.0011 | 1.0 |
| 0.0015 | 8.0 | 296 | 0.0011 | 1.0 |
| 0.0016 | 9.0 | 333 | 0.0011 | 1.0 |
| 0.0222 | 10.0 | 370 | 0.0010 | 1.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0