---
base_model: dmis-lab/biobert-base-cased-v1.2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: cause-biobert-biocause
  results: []
---

<!-- 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. -->

# cause-biobert-biocause

This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5157
- Precision: 0.2230
- Recall: 0.4277
- F1: 0.2931
- Accuracy: 0.8241
- Cause P: 0.2230
- Cause R: 0.4277
- Cause F1: 0.2931

## 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: 3e-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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Cause P | Cause R | Cause F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------:|:-------:|:--------:|
| 0.6993        | 0.25  | 20   | 0.6314          | 0.0556    | 0.1698 | 0.0837 | 0.7587   | 0.0556  | 0.1698  | 0.0837   |
| 0.6993        | 0.5   | 40   | 0.5747          | 0.0826    | 0.2327 | 0.1219 | 0.6524   | 0.0826  | 0.2327  | 0.1219   |
| 0.6993        | 0.75  | 60   | 0.4896          | 0.1086    | 0.3899 | 0.1699 | 0.7420   | 0.1086  | 0.3899  | 0.1699   |
| 0.6993        | 1.0   | 80   | 0.4554          | 0.1497    | 0.3145 | 0.2028 | 0.7840   | 0.1497  | 0.3145  | 0.2028   |
| 0.6993        | 1.25  | 100  | 0.4952          | 0.1980    | 0.3774 | 0.2597 | 0.8353   | 0.1980  | 0.3774  | 0.2597   |
| 0.6993        | 1.5   | 120  | 0.4837          | 0.1749    | 0.3774 | 0.2390 | 0.7984   | 0.1749  | 0.3774  | 0.2390   |
| 0.6993        | 1.75  | 140  | 0.4786          | 0.1873    | 0.4088 | 0.2569 | 0.7991   | 0.1873  | 0.4088  | 0.2569   |
| 0.6993        | 2.0   | 160  | 0.5157          | 0.2230    | 0.4277 | 0.2931 | 0.8241   | 0.2230  | 0.4277  | 0.2931   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.3.1.post100
- Datasets 2.20.0
- Tokenizers 0.15.1