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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
Download 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.

Subjects: 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
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

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