UW-Madison-Lee-Lab/MMLU-Pro-CoT-Eval

Dataset

0

stars

7

commits

1

linked in READMEs

Feb 8, 2025

updated

README

Dataset Details

  • Modality: Text
  • Format: CSV
  • Size: 100K - 1M rows
  • Total Rows: 248,836
  • License: MIT
  • Libraries Supported: datasets, pandas, croissant

Structure

Each row in the dataset includes:

  • question: The query posed in the dataset.
  • answer: The correct response.
  • category: The domain of the question (e.g., math, science).
  • src: The source of the question.
  • id: A unique identifier for each entry.
  • chain_of_thoughts: Step-by-step reasoning steps leading to the answer.
  • parsed_answer: Parsed answer from the chain of thoughts.
  • parsed_answer_correctness: Boolean indicating if the parsed answer is correct.

Access & Download

The dataset can be accessed via the Hugging Face datasets library:

from datasets import load_dataset

dataset = load_dataset("UW-Madison-Lee-Lab/MMLU-Pro-CoT-Eval")

Contributors

UW-Madison-Lee-Lab/MMLU-Pro-CoT-Eval

Dataset

0

stars

7

commits

1

linked in READMEs

Feb 8, 2025

updated

README

Dataset Details

  • Modality: Text
  • Format: CSV
  • Size: 100K - 1M rows
  • Total Rows: 248,836
  • License: MIT
  • Libraries Supported: datasets, pandas, croissant

Structure

Each row in the dataset includes:

  • question: The query posed in the dataset.
  • answer: The correct response.
  • category: The domain of the question (e.g., math, science).
  • src: The source of the question.
  • id: A unique identifier for each entry.
  • chain_of_thoughts: Step-by-step reasoning steps leading to the answer.
  • parsed_answer: Parsed answer from the chain of thoughts.
  • parsed_answer_correctness: Boolean indicating if the parsed answer is correct.

Access & Download

The dataset can be accessed via the Hugging Face datasets library:

from datasets import load_dataset

dataset = load_dataset("UW-Madison-Lee-Lab/MMLU-Pro-CoT-Eval")

Contributors