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# Overview |
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This is a fine-tuned version of the model [Helsinki-NLP/opus-mt-en-vi](https://huggingface.co/Helsinki-NLP/opus-mt-en-vi?text=My+name+is+Sarah+and+I+live+in+London) on the dataset [IWSLT'15 English-Vietnamese](https://huggingface.co/datasets/mt_eng_vietnamese). |
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Performance in terms of [sacrebleu](https://huggingface.co/docs/datasets/v1.5.0/using_metrics.html) on the test set is as follows: |
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* Original opus-mt-en-vi: 29.83 |
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* Fine-tuned opus-mt-en-vi: 37.35 |
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# Parameters |
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* learning_rate=2e-5 |
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* batch_size: 32 |
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* weight_decay=0.01 |
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* num_train_epochs=1 |
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# Thoughts |
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* Model `Helsinki-NLP/opus-mt-en-vi` is small (around 260MB), and can be easily deployed to a cheap server (e.g., EC2 t2.medium) without a GPU |
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* Easier and much faster to train compared to t5 or byt5. |