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Training a T5 Using Lab-sized Resources

2022-08-25 13:55:16
Manuel R. Ciosici, Leon Derczynski

Abstract

Training large neural language models on large datasets is resource- and time-intensive. These requirements create a barrier to entry, where those with fewer resources cannot build competitive models. This paper presents various techniques for making it possible to (a) train a large language model using resources that a modest research lab might have, and (b) train it in a reasonable amount of time. We provide concrete recommendations for practitioners, which we illustrate with a case study: a T5 model for Danish, the first for this language.

Abstract (translated)

URL

https://arxiv.org/abs/2208.12097

PDF

https://arxiv.org/pdf/2208.12097.pdf


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