---
library_name: transformers
base_model: airesearch/wangchanberta-base-att-spm-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: CPALL-Stock-Trend-Prediction-Wangchanberta-APR
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# CPALL-Stock-Trend-Prediction-Wangchanberta-APR

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: 1.1002
- Accuracy: 0.3341
- Precision: 0.3328
- Recall: 0.3341
- F1: 0.3270

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.1226        | 1.0   | 973  | 1.1571          | 0.3377   | 0.3194    | 0.3377 | 0.1889 |
| 1.1146        | 2.0   | 1946 | 1.1015          | 0.3354   | 0.1125    | 0.3354 | 0.1685 |
| 1.1106        | 3.0   | 2919 | 1.1036          | 0.3385   | 0.2776    | 0.3385 | 0.1715 |
| 1.1083        | 4.0   | 3892 | 1.1033          | 0.3264   | 0.1065    | 0.3264 | 0.1606 |
| 1.1083        | 5.0   | 4865 | 1.1013          | 0.3380   | 0.1143    | 0.3380 | 0.1709 |
| 1.1039        | 6.0   | 5838 | 1.1065          | 0.3354   | 0.1125    | 0.3354 | 0.1685 |
| 1.1032        | 7.0   | 6811 | 1.1011          | 0.3349   | 0.2014    | 0.3349 | 0.1697 |
| 1.106         | 8.0   | 7784 | 1.1056          | 0.3356   | 0.3617    | 0.3356 | 0.1714 |
| 1.1059        | 9.0   | 8757 | 1.1025          | 0.3259   | 0.3248    | 0.3259 | 0.3085 |
| 1.1029        | 10.0  | 9730 | 1.1002          | 0.3341   | 0.3328    | 0.3341 | 0.3270 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1