---
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: biobert-v1.1-text-classifier-corpus-ptc
  results: []
---

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# biobert-v1.1-text-classifier-corpus-ptc

This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8871
- Precision: 0.6734
- Recall: 0.6476
- Accuracy: 0.7495
- F1: 0.6556

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
| 0.8749        | 1.0   | 801  | 0.7585          | 0.5507    | 0.5801 | 0.7291   | 0.5628 |
| 0.608         | 2.0   | 1602 | 0.7347          | 0.6817    | 0.5910 | 0.7407   | 0.5786 |
| 0.5071        | 3.0   | 2403 | 0.8002          | 0.6852    | 0.6272 | 0.7501   | 0.6331 |
| 0.3756        | 4.0   | 3204 | 0.8416          | 0.6989    | 0.6411 | 0.7529   | 0.6528 |
| 0.3092        | 5.0   | 4005 | 0.8871          | 0.6734    | 0.6476 | 0.7495   | 0.6556 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2