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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
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