Pre-Trained Multilingual Sequence to Sequence Models for NMT Tips, Tricks and Challenges

Опубликовано: 16 Август 2023
на канале: Toronto Machine Learning Series (TMLS)

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Speaker:
Annie En-Shiun Lee, Assistant Professor (Teaching Stream) for the Computer Science Department, University of Toronto

Abstract:
Neural Machine Translation (NMT) has seen a tremendous spurt of growth in less than ten years, and has already entered a mature phase. Pre-trained multilingual sequence-to-sequence (PMSS) models, such as mBART and mT5, are pre-trained on large general data, then fine-tuned to deliver impressive results for natural language inference, question answering, text simplification and neural machine translation.

This tutorial presents:
1) An Introduction to Sequence-to-Sequence Pre-trained Models
2) How to adapt pre-trained models for NMT
3) Tips and Tricks for NMT training and evaluation
4) Challenges/Problems faced when using these models.

This tutorial will be useful for those interested in NMT, from a research as well as industry point of view.

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