[2101.00027] The Pile: An 800GB Dataset of Diverse Text for Language Modeling 

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 Computer Science > Computation and Language

 arXiv:2101.00027 (cs)

 [Submitted on 31 Dec 2020]

 Title: The Pile: An 800GB Dataset of Diverse Text for Language Modeling

 Authors: Leo Gao , Stella Biderman , Sid Black , Laurence Golding , Travis Hoppe , Charles Foster , Jason Phang , Horace He , Anish Thite , Noa Nabeshima , Shawn Presser , Connor Leahy 
 View a PDF of the paper titled The Pile: An 800GB Dataset of Diverse Text for Language Modeling, by Leo Gao and 11 other authors

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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 \textit{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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 Computation and Language (cs.CL) 

 Cite as:

 arXiv:2101.00027 [cs.CL] 

 (or 
 arXiv:2101.00027v1 [cs.CL] for this version)

 https://doi.org/10.48550/arXiv.2101.00027 

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 From: Leo Gao [ view email ] 
 [v1] 
 Thu, 31 Dec 2020 19:00:10 UTC (2,152 KB)

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