pg19

  • Description:

This dataset contains the PG-19 language modeling benchmark. It includes a set of books extracted from the Project Gutenberg books project (https://www.gutenberg.org), that were published before 1919. It also contains metadata of book titles and publication dates. PG-19 is over double the size of the Billion Word benchmark and contains documents that are 20X longer, on average, than the WikiText long-range language modelling benchmark.

Books are partitioned into a train, validation, and test set. Books metadata is stored in metadata.csv which contains (book_id, short_book_title, publication_date, book_link).

Split Examples
'test' 100
'train' 28,602
'validation' 50
  • Feature structure:
FeaturesDict({
    'book_id': int32,
    'book_link': string,
    'book_text': Text(shape=(), dtype=string),
    'book_title': string,
    'publication_date': string,
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
book_id Tensor int32
book_link Tensor string
book_text Text string
book_title Tensor string
publication_date Tensor string
  • Citation:
@article{raecompressive2019,
author = {Rae, Jack W and Potapenko, Anna and Jayakumar, Siddhant M and
          Hillier, Chloe and Lillicrap, Timothy P},
title = {Compressive Transformers for Long-Range Sequence Modelling},
journal = {arXiv preprint},
url = {https://arxiv.org/abs/1911.05507},
year = {2019},
}