readme: ---
  Language Pair Finetuned:
  - en-mr
  
  Metrics:
  - sacrebleu
    - WAT 2021: 16.11
  
  # mbart-large-finetuned-en-mr
   
  ## Model Description
   This is the mbart-large-50 model finetuned on En-Mr corpus.
    
  ## Intended uses and limitations
   Mostly useful for English to Marathi translation but the mbart-large-50 model also supports other language pairs
   
  ### How to use
  ```python
  from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
  
  model = MBartForConditionalGeneration.from_pretrained("shivam/mbart-large-50-finetuned-en-mr")
  tokenizer = MBart50TokenizerFast.from_pretrained("shivam/mbart-large-50-finetuned-en-mr", src_lang="en_XX", tgt_lang="mr_IN")
  
  english_input_sentence = "The Prime Minister said that cleanliness, or Swachhta, is one of the most important aspects of preventive healthcare."
  model_inputs = tokenizer(english_input_sentence, return_tensors="pt")
  generated_tokens = model.generate(
      **model_inputs,
      forced_bos_token_id=tokenizer.lang_code_to_id["mr_IN"]
  )
  marathi_output_sentence = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
  
  print(marathi_output_sentence)
  #स्वच्छता हा प्रतिबंधात्मक आरोग्य सेवेतील सर्वात महत्त्वाचा पैलू आहे, असे पंतप्रधान म्हणाले.
  ```
  #### Limitations
   The model was trained on Google Colab and as the training takes a lot of time the model was trained for small time and small number of epochs.
  
  ## Eval results 
   WAT 2021: 16.11 