|
--- |
|
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 |
|
|