HellaSwag Dataset
by University of Washington · open-source · Last verified 2026-03-17
HellaSwag is an adversarially filtered commonsense NLI benchmark where models must pick the most plausible sentence completion from 4 options. Humans score 95%+ while early LLMs struggled below 50%, making it a robust test of grounded language understanding and commonsense reasoning.
https://huggingface.co/datasets/Rowan/hellaswag ↗B+
B+—Good
Adoption: A+Quality: AFreshness: B+Citations: A+Engagement: F
Specifications
- License
- MIT
- Pricing
- open-source
- Capabilities
- commonsense-evaluation, sentence-completion-benchmark
- Integrations
- huggingface-datasets, lm-eval-harness
- Use Cases
- model-evaluation, commonsense-reasoning, benchmarking
- API Available
- No
- Tags
- benchmark, commonsense, sentence-completion, adversarial, grounding
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
77Adoption
91
Quality
88
Freshness
70
Citations
92
Engagement
0
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