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    • BUTTER - Empirical Deep Learning Dataset

    Metadata Updated: January 3, 2024

    The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four learning rates, six minibatch sizes, four levels of label noise, and fourteen levels of L1 and L2 regularization each. Multiple repetitions (typically 30, sometimes 10) of each combination of hyperparameters were preformed, and statistics including training and test loss (using a 80% / 20% shuffled train-test split) are recorded at the end of each training epoch. In total, this dataset covers 178 thousand distinct hyperparameter settings ("experiments"), 3.55 million individual training runs (an average of 20 repetitions of each experiments), and a total of 13.3 billion training epochs (three thousand epochs were covered by most runs). Accumulating this dataset consumed 5,448.4 CPU core-years, 17.8 GPU-years, and 111.2 node-years.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: Creative Commons Attribution

    Downloads & Resources

    Dates

    Metadata Created Date June 16, 2022
    Metadata Updated Date January 3, 2024

    Metadata Source

    Harvested from OpenEI data.json

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date June 16, 2022
    Metadata Updated Date January 3, 2024
    Publisher National Renewable Energy Laboratory
    Maintainer
    Doi 10.25984/1872441
    Identifier https://data.openei.org/submissions/5708
    Data First Published 2022-05-20T06:00:00Z
    Data Last Modified 2024-01-02T19:42:28Z
    Public Access Level public
    Bureau Code 019:20
    Metadata Context https://openei.org/data.json
    Metadata Catalog ID https://openei.org/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Data Quality True
    Harvest Object Id bdc3c3e9-ca23-4777-ab41-7e652bba0d25
    Harvest Source Id 7cbf9085-0290-4e9f-bec1-91653baeddfd
    Harvest Source Title OpenEI data.json
    Homepage URL https://data.openei.org/submissions/5708
    License https://creativecommons.org/licenses/by/4.0/
    Old Spatial {"type":"Polygon","coordinates":-180,-83,180,-83,180,83,-180,83,-180,-83}
    Program Code 019:023
    Projectnumber GO0028308
    Projecttitle National Renewable Energy Laboratory (NREL) Lab Directed Research and Development (LDRD)
    Source Datajson Identifier True
    Source Hash 84313fd8467beed9732e77eaac952339977af1f3f54a496f0abda5e71ae0b43e
    Source Schema Version 1.1
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