---
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: 0.9958
- Precision: 0.6688
- Recall: 0.6721
- Accuracy: 0.6719
- F1: 0.6676

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
| No log        | 1.0   | 353  | 0.9151          | 0.5844    | 0.6236 | 0.6237   | 0.5781 |
| 0.9769        | 2.0   | 706  | 0.8475          | 0.6472    | 0.6592 | 0.6591   | 0.6506 |
| 0.6697        | 3.0   | 1059 | 0.8897          | 0.6657    | 0.6735 | 0.6740   | 0.6659 |
| 0.6697        | 4.0   | 1412 | 0.9515          | 0.6665    | 0.6769 | 0.6768   | 0.6690 |
| 0.463         | 5.0   | 1765 | 0.9958          | 0.6688    | 0.6721 | 0.6719   | 0.6676 |


### Framework versions

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