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--- |
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license: apache-2.0 |
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base_model: google/mt5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-vi-news-summarization |
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results: [] |
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datasets: |
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- vietgpt/news_summarization_vi |
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language: |
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- vi |
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pipeline_tag: summarization |
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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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# MT5-Fine-tuning-Vi-News-Summarization |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on [vietgpt/news_summarization_vi](https://huggingface.co/datasets/vietgpt/news_summarization_vi). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8435 |
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- Rouge1: 71.033 |
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- Rouge2: 46.9902 |
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- Rougel: 49.8521 |
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- Rougelsum: 64.0283 |
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- Gen Len: 231.535 |
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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: 0.0002 |
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- train_batch_size: 6 |
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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-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
