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arXiv · 1805.10387

Mixed-Precision Training for NLP and Speech Recognition with OpenSeq2Seq

Oleksii Kuchaiev·Boris Ginsburg·Igor Gitman·Vitaly Lavrukhin·Jason Li·Huyen Nguyen·Carl Case·Paulius Micikevicius
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Abstract

We present OpenSeq2Seq - a TensorFlow-based toolkit for training sequence-to-sequence models that features distributed and mixed-precision training. Benchmarks on machine translation and speech recognition tasks show that models built using OpenSeq2Seq give state-of-the-art performance at 1.5-3x less training time. OpenSeq2Seq currently provides building blocks for models that solve a wide range of tasks including neural machine translation, automatic speech recognition, and speech synthesis.

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Oleksii Kuchaiev, Boris Ginsburg, Igor Gitman, Vitaly Lavrukhin, Jason Li, Huyen Nguyen, Carl Case, Paulius Micikevicius. 2018-11-21. Mixed-Precision Training for NLP and Speech Recognition with OpenSeq2Seq. https://arxiv.org/abs/1805.10387

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