transformers pytorch bert text-classification generated_from_trainer dataset:financial_phrasebank base_model:dmis-lab/biobert-v1.1 base_model:finetune:dmis-lab/biobert-v1.1 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: dmis-lab/biobert-v1.1
datasets:
- financial_phrasebank
metrics:
- f1
tags:
- generated_from_trainer
model-index:
- name: bioBERT-finetuned-financial-phrasebank
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: financial_phrasebank
      type: financial_phrasebank
      config: sentences_66agree
      split: train
      args: sentences_66agree
    metrics:
    - type: f1
      value: 0.8774882040734603
      name: F1
---

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# 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: 0.5118
- F1: 0.8775

## 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 238  | 0.5118          | 0.8775 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
