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--- |
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library_name: transformers |
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license: cc-by-sa-4.0 |
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base_model: ZycckZ/Zk1-QA-VN-test |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Zk1-QA-VN-test2 |
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results: [] |
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datasets: |
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- taidng/UIT-ViQuAD2.0 |
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language: |
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- vi |
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pipeline_tag: question-answering |
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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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# Zk1-QA-VN-test2 (ZycckZ/Simple_VieQA) |
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This model is a fine-tuned version of [ZycckZ/Zk1-QA-VN-test](https://huggingface.co/ZycckZ/Zk1-QA-VN-test) and [taidng/UIT-ViQuAD2](https://huggingface.co/datasets/taidng/UIT-ViQuAD2.0) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8800 |
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- Exact Match (EM): 70.07 |
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- F1 Score: 82.34 |
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## Model description |
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This model now much better than the model before ([ZycckZ/Zk1-QA-VN-test](https://huggingface.co/ZycckZ/Zk1-QA-VN-test)). |
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## Intended uses & limitations |
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- Create a simple chatbot QA 🤗 |
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- Just for Vietnamese QA system |
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## Training and evaluation data |
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Training: |
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- taidng/UIT-ViQuAD2.0 - "train" |
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- taidng/UIT-ViQuAD2.0 - "validation" |
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- taidng/UIT-ViQuAD2.0 - "test" |
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Evaluation: |
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- taidng/UIT-ViQuAD2.0 - "validation" |
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## Training procedure |
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Based on Question Answering HuggingFace 🤗 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 1.171 | 1.0 | 2226 | 1.0648 | |
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| 0.8499 | 2.0 | 4452 | 1.1054 | |
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| 0.5862 | 3.0 | 6678 | 1.2583 | |
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| 0.4082 | 4.0 | 8904 | 1.5642 | |
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| 0.2835 | 5.0 | 11130 | 1.8800 | |
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### Framework versions |
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- Transformers 4.52.2 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 2.14.4 |
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- Tokenizers 0.21.1 |
