Fine-Tune BART for Translation on WMT16 Dataset (and Train new Tokenizer)

Author(s): Ala Alam Falaki

Originally published on Towards AI.

BART is a well-known summarization model. Also, it can do the translation task with the appropriate tokenizer for the target language.

Photo by Etienne Girardet on Unsplash

I recently attempted to test a new architecture on the translation task and needed to train a tokenizer on my custom dataset. I noticed that creating a new tokenizer using HuggingFace can be challenging. In this story, I will focus on the preprocessing step and briefly mention the fine-tuning since many resources are already available. (Including my how-to guide on training a seq2seq model)

New to NLP? Start by reading about “what tokenization is”.

It is easy… Read the full blog for free on Medium.

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Published via Towards AI