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Wikitext

Paper

Pointer Sentinel Mixture Models https://arxiv.org/pdf/1609.07843.pdf

The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified Good and Featured articles on Wikipedia.

NOTE: This Task is based on WikiText-2.

Homepage: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/

Citation

@misc{merity2016pointer,
    title={Pointer Sentinel Mixture Models},
    author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher},
    year={2016},
    eprint={1609.07843},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

Groups and Tasks

Groups

  • Not part of a group yet.

Tasks

  • wikitext: measure perplexity on the Wikitext dataset, via rolling loglikelihoods.

Checklist

  • Is the task an existing benchmark in the literature?
    • Have you referenced the original paper that introduced the task?
    • If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?

If other tasks on this dataset are already supported:

  • Is the "Main" variant of this task clearly denoted?
  • Have you provided a short sentence in a README on what each new variant adds / evaluates?
  • Have you noted which, if any, published evaluation setups are matched by this variant?