---
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- f1
model-index:
- name: bioBERT-finetuned-financial-phrasebank
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: financial_phrasebank
      type: financial_phrasebank
      config: sentences_66agree
      split: train
      args: sentences_66agree
    metrics:
    - name: F1
      type: f1
      value: 0.9153044889504942
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bioBERT-finetuned-financial-phrasebank

This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3305
- F1: 0.9153

## 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   | 238  | 0.3082          | 0.8843 |
| No log        | 2.0   | 476  | 0.3200          | 0.9001 |
| 0.3619        | 3.0   | 714  | 0.3305          | 0.9153 |


### Framework versions

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