readme: # Overview
  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). 
  Performance in terms of [sacrebleu](https://huggingface.co/docs/datasets/v1.5.0/using_metrics.html) on the test set is as follows:
  
  * Original  opus-mt-en-vi: 29.83
  * Fine-tuned opus-mt-en-vi: 37.35
  
  # Parameters
  * learning_rate=2e-5
  * batch_size: 32
  * weight_decay=0.01
  * num_train_epochs=1
  
  # Thoughts
  * 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
  * Easier and much faster to train compared to t5 or byt5. 