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license: mit
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license: mit
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datasets:
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- opus100
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- un_multi
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language:
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- en
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- ar
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M2M100 418M
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M2M100 is a multilingual encoder-decoder transformer model trained for Many-to-Many multilingual translation. The model, originally introduced by researchers at Facebook, demonstrates impressive performance in cross-lingual translation tasks.
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For a better understanding of M2M100 you can look into the [paper](https://arxiv.org/abs/2010.11125) and the associated [repository](https://github.com/facebookresearch/fairseq/tree/main/examples/m2m_100).
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To further enhance the capabilities of M2M100, we conducted finetuning experiments on English-to-Arabic parallel text. The finetuning process involved training the model for 1000K steps using a batch size of 8.
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