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--- |
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base_model: Thammarak/wangchanBERTa-QA-thaiqa_squad |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wangchanberta_dataxet_FAQ_chatbot_v3 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wangchanberta_dataxet_FAQ_chatbot_v3 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0197 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.0301 | 0.53 | 100 | 0.0390 | |
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| 0.0377 | 1.07 | 200 | 0.0391 | |
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| 0.0338 | 1.6 | 300 | 0.0390 | |
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| 0.0153 | 2.14 | 400 | 0.0390 | |
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| 0.0152 | 2.67 | 500 | 0.0480 | |
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| 0.0166 | 3.21 | 600 | 0.0423 | |
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| 0.0206 | 3.74 | 700 | 0.0418 | |
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| 0.0285 | 4.28 | 800 | 0.0391 | |
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| 0.0522 | 4.81 | 900 | 0.0390 | |
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| 0.0339 | 5.35 | 1000 | 0.0197 | |
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| 0.0032 | 5.88 | 1100 | 0.0197 | |
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| 0.021 | 6.42 | 1200 | 0.0197 | |
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| 0.0073 | 6.95 | 1300 | 0.0197 | |
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| 0.016 | 7.49 | 1400 | 0.0197 | |
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| 0.0106 | 8.02 | 1500 | 0.0197 | |
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| 0.0081 | 8.56 | 1600 | 0.0197 | |
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| 0.0078 | 9.09 | 1700 | 0.0197 | |
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| 0.0001 | 9.63 | 1800 | 0.0197 | |
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| 0.0088 | 10.16 | 1900 | 0.0197 | |
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| 0.0187 | 10.7 | 2000 | 0.0198 | |
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| 0.0 | 11.23 | 2100 | 0.0198 | |
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| 0.0075 | 11.76 | 2200 | 0.0198 | |
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| 0.0145 | 12.3 | 2300 | 0.0197 | |
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| 0.0 | 12.83 | 2400 | 0.0197 | |
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| 0.0006 | 13.37 | 2500 | 0.0197 | |
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| 0.0069 | 13.9 | 2600 | 0.0197 | |
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| 0.0073 | 14.44 | 2700 | 0.0197 | |
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| 0.0002 | 14.97 | 2800 | 0.0197 | |
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| 0.0001 | 15.51 | 2900 | 0.0197 | |
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| 0.0234 | 16.04 | 3000 | 0.0197 | |
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| 0.0073 | 16.58 | 3100 | 0.0197 | |
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| 0.0001 | 17.11 | 3200 | 0.0197 | |
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| 0.008 | 17.65 | 3300 | 0.0197 | |
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| 0.0075 | 18.18 | 3400 | 0.0197 | |
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| 0.007 | 18.72 | 3500 | 0.0197 | |
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| 0.0 | 19.25 | 3600 | 0.0197 | |
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| 0.0208 | 19.79 | 3700 | 0.0197 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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