Pre-Trained Multilingual Sequence to Sequence Models for NMT Tips, Tricks and Challenges
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.
Watch video Pre-Trained Multilingual Sequence to Sequence Models for NMT Tips, Tricks and Challenges online, duration hours minute second in high quality that is uploaded to the channel Toronto Machine Learning Series (TMLS) 16 August 2023. Share the link to the video on social media so that your subscribers and friends will also watch this video. This video clip has been viewed 172 times and liked it 2 visitors.
