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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mt_eng_vietnamese |
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metrics: |
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- rouge |
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- bleu |
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model-index: |
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- name: bart-base-translate-en-vi |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: mt_eng_vietnamese |
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type: mt_eng_vietnamese |
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config: iwslt2015-en-vi |
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split: validation |
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args: iwslt2015-en-vi |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 56.0521 |
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- name: Bleu |
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type: bleu |
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value: 12.7027 |
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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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# bart-base-translate-en-vi |
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This model is a fine-tuned version of [GuysTrans/bart-base-translate-en-vi](https://huggingface.co/GuysTrans/bart-base-translate-en-vi) on the mt_eng_vietnamese dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6744 |
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- Rouge1: 56.0521 |
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- Rouge2: 34.1329 |
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- Rougel: 47.1473 |
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- Rougelsum: 47.8238 |
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- Bleu: 12.7027 |
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- Gen Len: 19.9921 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 1 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:| |
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| 0.661 | 1.0 | 16665 | 0.6744 | 56.0521 | 34.1329 | 47.1473 | 47.8238 | 12.7027 | 19.9921 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.3 |
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