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# pretoxtm-sentence-classfier

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: 0.2292
- Precision: 0.9585
- Recall: 0.9585
- Accuracy: 0.9591
- F1: 0.9585

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
| No log        | 1.0   | 257  | 0.1810          | 0.9586    | 0.9617 | 0.9602   | 0.9598 |
| 0.1462        | 2.0   | 514  | 0.2225          | 0.9590    | 0.9580 | 0.9591   | 0.9585 |
| 0.1462        | 3.0   | 771  | 0.2292          | 0.9585    | 0.9585 | 0.9591   | 0.9585 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "accuracy", "f1"], "base_model": "dmis-lab/biobert-v1.1", "model-index": [{"name": "pretoxtm-sentence-classfier", "results": []}]}
transformers pytorch tensorboard safetensors bert text-classification generated_from_trainer base_model:dmis-lab/biobert-v1.1 autotrain_compatible endpoints_compatible region:us