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--- |
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base_model: |
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- facebook/bart-large |
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pipeline_tag: translation |
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library_name: transformers |
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tags: |
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- code |
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--- |
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Hindi to Bengali Translation using BART |
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Overview |
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This project fine-tunes the BART model for Hindi-to-Bengali translation using the Hind-Beng-5k dataset. |
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The model is trained using the Hugging Face transformers library with PyTorch. |
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Dataset |
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We use the Hind-Beng-5k dataset from Hugging Face, which contains parallel Hindi and Bengali text samples. |
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Dataset: sudeshna84/Hind-Beng-5k |
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Model |
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The model used for translation is facebook/bart-large. |
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It is fine-tuned for sequence-to-sequence translation from Hindi to Bengali using the BART architecture. |
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Installation |
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To run the project, install the required dependencies: |
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pip install transformers datasets torch |
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Preprocessing |
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The dataset is preprocessed by tokenizing the Hindi input text and Bengali target text using the BART tokenizer. |
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Training |
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The model is trained using the Trainer API from Hugging Face with the following parameters: |
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Batch size: 8 |
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Learning rate: 2e-5 |
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Epochs: 3 |
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Weight decay: 0.01 |
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Credits Tag |
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Sudeshna Sani- https://huggingface.co/sudeshna84 |
