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# contrast_classifier_biobert_v2

This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/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

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "dmis-lab/biobert-v1.1", "model-index": [{"name": "contrast_classifier_biobert_v2", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:dmis-lab/biobert-v1.1 autotrain_compatible endpoints_compatible region:us