---
tags:
- generated_from_trainer
base_model: airesearch/wangchanberta-base-att-spm-uncased
metrics:
- accuracy
model-index:
- name: fine-tune-wangchanberta-TOG-split-headline1
  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. -->

# fine-tune-wangchanberta-TOG-split-headline1

This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1026
- Accuracy: 0.3876

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0948        | 1.0   | 27   | 1.1114          | 0.3828   |
| 1.0961        | 2.0   | 54   | 1.1019          | 0.3828   |
| 1.0971        | 3.0   | 81   | 1.1144          | 0.3876   |
| 1.0908        | 4.0   | 108  | 1.0994          | 0.3876   |
| 1.0703        | 5.0   | 135  | 1.1032          | 0.3876   |
| 1.0711        | 6.0   | 162  | 1.1057          | 0.3828   |
| 1.0658        | 7.0   | 189  | 1.1026          | 0.3876   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1