---
base_model: clicknext/phayathaibert
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: phayathaibert-thainer
  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. -->

# phayathaibert-thainer

This model is a fine-tuned version of [clicknext/phayathaibert](https://huggingface.co/clicknext/phayathaibert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1324
- Precision: 0.8432
- Recall: 0.8915
- F1: 0.8666
- Accuracy: 0.9735

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 493  | 0.1401          | 0.7300    | 0.7941 | 0.7607 | 0.9607   |
| 0.3499        | 2.0   | 986  | 0.1201          | 0.7863    | 0.8464 | 0.8152 | 0.9688   |
| 0.0961        | 3.0   | 1479 | 0.1169          | 0.8050    | 0.8663 | 0.8345 | 0.9715   |
| 0.0617        | 4.0   | 1972 | 0.1137          | 0.8155    | 0.8656 | 0.8398 | 0.9718   |
| 0.0438        | 5.0   | 2465 | 0.1280          | 0.8201    | 0.8714 | 0.8450 | 0.9725   |
| 0.0302        | 6.0   | 2958 | 0.1386          | 0.8266    | 0.8730 | 0.8492 | 0.9726   |
| 0.0239        | 7.0   | 3451 | 0.1401          | 0.8353    | 0.8789 | 0.8565 | 0.9733   |
| 0.0166        | 8.0   | 3944 | 0.1444          | 0.8356    | 0.8782 | 0.8564 | 0.9738   |
| 0.0139        | 9.0   | 4437 | 0.1530          | 0.8341    | 0.8785 | 0.8557 | 0.9735   |
| 0.0106        | 10.0  | 4930 | 0.1508          | 0.8394    | 0.8782 | 0.8583 | 0.9738   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0