---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: biobert-biocause-trainer
  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. -->

# biobert-biocause-trainer

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1681
- Accuracy: 0.9485
- F1: 0.9040
- Recall: 0.9511
- Precision: 0.8614

## 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 | Accuracy | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.6094        | 0.16  | 50   | 0.5106          | 0.7701   | 0.6246 | 0.7492 | 0.5355    |
| 0.5744        | 0.32  | 100  | 0.4291          | 0.8132   | 0.6898 | 0.8139 | 0.5986    |
| 0.5282        | 0.48  | 150  | 0.3735          | 0.7963   | 0.6995 | 0.9290 | 0.5610    |
| 0.4704        | 0.64  | 200  | 0.4850          | 0.8965   | 0.7724 | 0.6877 | 0.8808    |
| 0.4809        | 0.8   | 250  | 0.2955          | 0.9074   | 0.8192 | 0.8218 | 0.8166    |
| 0.3985        | 0.96  | 300  | 0.2699          | 0.8829   | 0.8014 | 0.9259 | 0.7064    |
| 0.347         | 1.13  | 350  | 0.2695          | 0.9275   | 0.8587 | 0.8628 | 0.8547    |
| 0.3729        | 1.29  | 400  | 0.2227          | 0.9320   | 0.8723 | 0.9101 | 0.8374    |
| 0.4059        | 1.45  | 450  | 0.2130          | 0.9420   | 0.8894 | 0.9132 | 0.8668    |
| 0.3023        | 1.61  | 500  | 0.1996          | 0.9477   | 0.8989 | 0.9117 | 0.8865    |
| 0.2676        | 1.77  | 550  | 0.1814          | 0.9521   | 0.9074 | 0.9196 | 0.8955    |
| 0.4202        | 1.93  | 600  | 0.1702          | 0.9452   | 0.8987 | 0.9511 | 0.8517    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.3.1
- Datasets 2.19.1
- Tokenizers 0.15.1