---
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: 0.1320
- Precision: 0.8493
- Recall: 0.8937
- F1: 0.8710
- 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  | 0.1341          | 0.7524    | 0.8047 | 0.7777 | 0.9630   |
| 0.2346        | 2.0   | 986  | 0.1117          | 0.8015    | 0.8499 | 0.8250 | 0.9702   |
| 0.0922        | 3.0   | 1479 | 0.1173          | 0.8192    | 0.8716 | 0.8446 | 0.9719   |
| 0.059         | 4.0   | 1972 | 0.1157          | 0.8275    | 0.8744 | 0.8503 | 0.9725   |
| 0.0419        | 5.0   | 2465 | 0.1203          | 0.8149    | 0.8766 | 0.8446 | 0.9732   |
| 0.0297        | 6.0   | 2958 | 0.1335          | 0.8361    | 0.8802 | 0.8576 | 0.9736   |
| 0.0237        | 7.0   | 3451 | 0.1335          | 0.8394    | 0.8798 | 0.8591 | 0.9745   |
| 0.0161        | 8.0   | 3944 | 0.1383          | 0.8409    | 0.8843 | 0.8621 | 0.9744   |
| 0.0133        | 9.0   | 4437 | 0.1457          | 0.8446    | 0.8828 | 0.8633 | 0.9743   |
| 0.01          | 10.0  | 4930 | 0.1437          | 0.8433    | 0.8811 | 0.8618 | 0.9747   |


### Framework versions

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