PromptEval/PromptEval_MMLU_correctness
MMLU Multi-Prompt Evaluation Data (correctness scores) Overview This dataset contains the results of a comprehensive evaluation of various Large Language Models (LLMs) using multiple prompt templates on the Massive Multitask Language Understanding (MMLU) benchmark. The data is introduced in Maia Polo, Felipe, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj, Leshem Choshen, Allysson Flavio Melo de Oliveira, Yuekai Sun, and Mikhail Yurochkin. "Efficient… See the full description on the dataset page: https://huggingface.co/datasets/PromptEval/PromptEval_MMLU_correctness.
| Author / organization | PromptEval |
|---|---|
| License (as declared) | mit |
| Downloads | 2.5K (as reported by Hugging Face) |
| Likes | 2 |
| Created | 4 June 2024 |
| Last updated at source | 7 June 2024 |
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- 16 Oct 2026 Description: MMLU Multi-Prompt Evaluation Data (correctness scores) Overview This dataset contains the results of a comprehensive evaluation of various Large Language Models (LLMs) using multiple prompt templates on the Massive Multitask Language Unders → MMLU Multi-Prompt Evaluation Data (correctness scores) Overview This dataset contains the results of a comprehensive evaluation of various Large Language Models (LLMs) using multiple prompt templates on the Massive Multitask Language Unders
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