---
license: mit
base_model: ttlanhhh/biogpt-ner
tags:
- generated_from_trainer
model-index:
- name: biogpt-tac
  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. -->

# biogpt-tac

This model is a fine-tuned version of [ttlanhhh/biogpt-ner](https://huggingface.co/ttlanhhh/biogpt-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1503
- Overall Precision: 0.6078
- Overall Recall: 0.6679
- Overall F1: 0.6365
- Overall Accuracy: 0.9607

## 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: 4
- eval_batch_size: 4
- 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 | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.1717        | 1.0   | 1186 | 0.1474          | 0.4860            | 0.4303         | 0.4565     | 0.9467           |
| 0.1197        | 2.0   | 2372 | 0.1451          | 0.5519            | 0.5691         | 0.5604     | 0.9566           |
| 0.089         | 3.0   | 3558 | 0.1473          | 0.4985            | 0.6496         | 0.5641     | 0.9547           |
| 0.068         | 4.0   | 4744 | 0.1479          | 0.6071            | 0.6502         | 0.6279     | 0.9600           |
| 0.0591        | 5.0   | 5930 | 0.1503          | 0.6078            | 0.6679         | 0.6365     | 0.9607           |


### Framework versions

- Transformers 4.39.3
- Pytorch 1.12.1+cu113
- Datasets 2.18.0
- Tokenizers 0.15.2