---
base_model: Thammarak/wangchanBERTa-QA-thaiqa_squad
tags:
- generated_from_trainer
model-index:
- name: wangchanberta_dataxet_FAQ_chatbot_v3
  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. -->

# wangchanberta_dataxet_FAQ_chatbot_v3

This model is a fine-tuned version of [Thammarak/wangchanBERTa-QA-thaiqa_squad](https://huggingface.co/Thammarak/wangchanBERTa-QA-thaiqa_squad) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0197

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0301        | 0.53  | 100  | 0.0390          |
| 0.0377        | 1.07  | 200  | 0.0391          |
| 0.0338        | 1.6   | 300  | 0.0390          |
| 0.0153        | 2.14  | 400  | 0.0390          |
| 0.0152        | 2.67  | 500  | 0.0480          |
| 0.0166        | 3.21  | 600  | 0.0423          |
| 0.0206        | 3.74  | 700  | 0.0418          |
| 0.0285        | 4.28  | 800  | 0.0391          |
| 0.0522        | 4.81  | 900  | 0.0390          |
| 0.0339        | 5.35  | 1000 | 0.0197          |
| 0.0032        | 5.88  | 1100 | 0.0197          |
| 0.021         | 6.42  | 1200 | 0.0197          |
| 0.0073        | 6.95  | 1300 | 0.0197          |
| 0.016         | 7.49  | 1400 | 0.0197          |
| 0.0106        | 8.02  | 1500 | 0.0197          |
| 0.0081        | 8.56  | 1600 | 0.0197          |
| 0.0078        | 9.09  | 1700 | 0.0197          |
| 0.0001        | 9.63  | 1800 | 0.0197          |
| 0.0088        | 10.16 | 1900 | 0.0197          |
| 0.0187        | 10.7  | 2000 | 0.0198          |
| 0.0           | 11.23 | 2100 | 0.0198          |
| 0.0075        | 11.76 | 2200 | 0.0198          |
| 0.0145        | 12.3  | 2300 | 0.0197          |
| 0.0           | 12.83 | 2400 | 0.0197          |
| 0.0006        | 13.37 | 2500 | 0.0197          |
| 0.0069        | 13.9  | 2600 | 0.0197          |
| 0.0073        | 14.44 | 2700 | 0.0197          |
| 0.0002        | 14.97 | 2800 | 0.0197          |
| 0.0001        | 15.51 | 2900 | 0.0197          |
| 0.0234        | 16.04 | 3000 | 0.0197          |
| 0.0073        | 16.58 | 3100 | 0.0197          |
| 0.0001        | 17.11 | 3200 | 0.0197          |
| 0.008         | 17.65 | 3300 | 0.0197          |
| 0.0075        | 18.18 | 3400 | 0.0197          |
| 0.007         | 18.72 | 3500 | 0.0197          |
| 0.0           | 19.25 | 3600 | 0.0197          |
| 0.0208        | 19.79 | 3700 | 0.0197          |


### Framework versions

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