---
base_model: airesearch/wangchanberta-base-att-spm-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wangchanberta-fine-tune-fin-news-sentiment-th
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wangchanberta-fine-tune-fin-news-sentiment-th

This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6650
- Accuracy: 0.7276

## 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: 5e-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 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9665        | 1.0   | 3054  | 0.9572          | 0.5602   |
| 0.8734        | 2.0   | 6108  | 0.8522          | 0.6439   |
| 0.7737        | 3.0   | 9162  | 0.7577          | 0.6992   |
| 0.6607        | 4.0   | 12216 | 0.6860          | 0.7205   |
| 0.6068        | 5.0   | 15270 | 0.6650          | 0.7276   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0