2020 ThePileAn800gbDatasetofDiverseT

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Subject Headings: The Pile Dataset.

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Cited By

2022

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Abstract

Recent work has demonstrated that increased training dataset diversity improves general cross-domain knowledge and downstream generalization capability for large-scale language models. With this in mind, we present the Pile: an 825 GiB English text corpus targeted at training large-scale language models. The Pile is constructed from 22 diverse high-quality subsets -- both existing and newly constructed -- many of which derive from academic or professional sources. Our evaluation of the untuned performance of GPT-2 and GPT-3 on the Pile shows that these models struggle on many of its components, such as academic writing. Conversely, models trained on the Pile improve significantly over both Raw CC and CC-100 on all components of the Pile, while improving performance on downstream evaluations. Through an in-depth exploratory analysis, we document potentially concerning aspects of the data for prospective users. We make publicly available the code used in its construction.

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2020 ThePileAn800gbDatasetofDiverseTLeo Gao
Stella Biderman
Sid Black
Laurence Golding
Travis Hoppe
Charles Foster
Jason Phang
Horace He
Anish Thite
Noa Nabeshima
Shawn Presser
Connor Leahy
The Pile: An 800gb Dataset of Diverse Text for Language Modeling2020