benchmarks.wiki / Public workspace
HellaSwag
Reasoning
HellaSwag asks which of four continuations naturally follows a sentence or a video caption. The wrong options are produced by adversarial filtering, so items that are nearly trivial for people remain hard for models.
hellaswag
Full text: eligible public problems include text, images and discussion.
Reference links
At a glance
What a problem looks like
An activity label and a context sentence, with the four candidate continuations as a list. Which one is correct is not part of the prompt.
How it is scored
The source ships the index of the correct continuation; this catalogue keeps it in restricted storage and never renders it.
Metric: accuracy over the 10,042 validation items
Why it is hard
The distractors were selected specifically because models rank them highly, so the gap it measures is between surface plausibility and actual commonsense.
Cite
@article{zellers2019hellaswag,
title={HellaSwag: Can a Machine Really Finish Your Sentence?},
author={Rowan Zellers and Ari Holtzman and Yonatan Bisk and Ali Farhadi and Yejin Choi},
journal={arXiv preprint arXiv:1905.07830},
year={2019}
}Discussion
Contribute
Share a reproduction, report an evaluation issue, or suggest a correction to this benchmark overview.
Tasks
Whole public benchmark.
- Public problems
- 200
- Formats
- text (200)
- Problems with images
- 0
- Answer availability
- Answer published by the source (200)
- Configs
- default (200)
- Splits
- validation (200)
- Awaiting a first discussion
- 200
- Problems with a discussion
- 0
- Public contributions
- 0
Provenance and terms
Pinned source revisions, newest first:
218ec52e09a7e7462a5400043bb9a69a41d06b76· acquired 2026-09-12 · release7fb6311c6df2218ec52e09a7e7462a5400043bb9a69a41d06b76· acquired 2026-09-12 · releaseda7444a35989
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