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wangchanberta-xet_ref-params
powerpuf-bot/wangchanberta-xet_ref-params
wangchanberta-xet_ref-params is a question answering model from powerpuf-bot. Use it when the input is a question plus a passage. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- Model type
- camembert
- Access
- Public
- Created
- Nov 28, 2023
- Updated
- Nov 28, 2023
- SHA
- 2ef34e36
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- 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 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
- Task
- Question Answering
- Library
- transformers
- Type
- camembert
- Created
- Nov 28, 2023
- Updated
- Nov 28, 2023