shivam/mbart-large-50-finetuned-en-mr

---

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

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