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wangchanberta-xet_ref-params

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  1. README.md +92 -0
  2. runs/Nov28_16-59-23_feed8a47baf7/events.out.tfevents.1701190767.feed8a47baf7.698.6 +2 -2
  3. runs/Nov28_16-59-23_feed8a47baf7/events.out.tfevents.1701192088.feed8a47baf7.698.7 +3 -0
README.md ADDED
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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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+
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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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+
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+ # wangchanberta_dataxet_FAQ_chatbot_v3
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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