数据集 / openai/gsm8k

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Dataset Card for GSM8K

Table of Contents

  • Dataset Description
    • Dataset Summary
    • Supported Tasks
    • Languages
  • Dataset Structure
    • Data Instances
    • Data Fields
    • Data Splits
  • Dataset Creation
    • Curation Rationale
    • Source Data
    • Annotations
    • Personal and Sensitive Information
  • Considerations for Using the Data
    • Social Impact of Dataset
    • Discussion of Biases
    • Other Known Limitations
  • Additional Information
    • Dataset Curators
    • Licensing Information
    • Citation Information

Dataset Description

Dataset Summary

GSM8K (Grade School Math 8K) is a dataset of 8.5K high quality linguistically diverse grade school math word problems. The dataset was created to support the task of question answering on basic mathematical problems that require multi-step reasoning.

  • These problems take between 2 and 8 steps to solve.
  • Solutions primarily involve performing a sequence of elementary calculations using basic arithmetic operations (+ − ×÷) to reach the final answer.
  • A bright middle school student should be able to solve every problem: from the paper, "Problems require no concepts beyond the level of early Algebra, and the vast majority of problems can be solved without explicitly defining a variable."
  • Solutions are provided in natural language, as opposed to pure math expressions. From the paper: "We believe this is the most generally useful data format, and we expect it to shed light on the properties of large language models’ internal monologues""

Supported Tasks and Leaderboards

This dataset is generally used to test logic and math in language modelling. It has been used for many benchmarks, including the LLM Leaderboard.

Languages

The text in the dataset is in English. The associated BCP-47 code is en.

Dataset Structure

Data Instances

For the main configuration, each instance contains a string for the grade-school level math question and a string for the corresponding answer with multiple steps of reasoning and calculator annotations (explained [here](https://github.com/openai/gr

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数据集版权信息

本数据集的许可证为 MIT License。如有违反相关条款，请联系 WEHUB，我们将及时处理。 查看许可证