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# bioBERT-finetuned-biopharma-dive

This model is a fine-tuned version of [daniel-gordon/bioBERT-finetuned-financial-phrasebank](https://huggingface.co/daniel-gordon/bioBERT-finetuned-financial-phrasebank) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9018
- F1: 0.6009

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 110  | 0.9018          | 0.6009 |
| No log        | 2.0   | 220  | 0.9249          | 0.5851 |
| No log        | 3.0   | 330  | 1.0173          | 0.5835 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "daniel-gordon/bioBERT-finetuned-financial-phrasebank", "model-index": [{"name": "bioBERT-finetuned-biopharma-dive", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:daniel-gordon/bioBERT-finetuned-financial-phrasebank autotrain_compatible endpoints_compatible region:us