knowrohit07/ArithmeLogic

该数据集旨在训练模型解决数学应用题，提供逐步计算和预期输出。数据来源于GPT 4，结构化为数学问题作为instruction，其逐步解决方案作为output。数据属性包括instruction（数学应用题的文本表示）和output（详细的逐步计算）。样本数据点展示了一个具体的数学应用题及其解决方案。潜在用途包括训练模型理解和解决数学应用题，以及评估模型基于文本上下文执行数学运算的能力。潜在的偏见和伦理考虑包括数据集可能仅涵盖基础算术问题，未涉及更复杂的数学问题。数据集维护和更新将尽力保持循环。数据集对LLMs的优点包括结构化问题解决、多样化的表达、明确的算术计算、清晰的答案指示和上下文理解。

This dataset is developed for training models to solve mathematical word problems, providing step-by-step calculations and expected outputs. The data is sourced from GPT-4, and is structured with mathematical word problems as the "instruction" field and their detailed step-by-step solutions as the "output" field. The core attributes of the dataset include "instruction" (textual representation of a mathematical word problem) and "output" (comprehensive step-by-step calculations). A sample data point illustrates a specific mathematical word problem and its corresponding solution. Potential use cases include training models to comprehend and solve mathematical word problems, as well as evaluating models’ ability to perform mathematical operations based on textual contexts. Potential biases and ethical concerns involve that the dataset may only cover basic arithmetic problems and fail to address more complex mathematical topics. Every effort will be made to sustain ongoing maintenance and updates for the dataset. The strengths of this dataset for LLMs include structured problem-solving, diverse expression, explicit arithmetic calculations, clear answer guidance, and contextual comprehension.

原始信息汇总

数据集概述

数据集描述

• 目的：该数据集旨在训练模型解决数学应用题，提供逐步计算和预期输出。

数据收集和处理

• 来源：GPT 4
• 处理方式：数据集结构化，数学问题作为“instruction”，其逐步解决方案作为“output”。

数据属性

• instruction (字符串)：数学应用题的文本表示。
• output (字符串)：详细的逐步计算，引导至解决方案。使用<<>>表示计算，使用####表示最终答案。

示例数据点

json { "instruction": "Rohit is saving money for a new wallet which costs $100. Rohit has only half of the money he needs. His parents decided to give him $15 for that purpose, and his grandparents twice as much as his parents. How much more money does Rohit need to buy the wallet?", "output": "Rohit has only 100 * 0.5 = $<<1000.5=50>>50. Rohits grandparents gave him 15 * 2 = $<<152=30>>30. In total, Rohit needs 100 - 50 - 30 - 15 = $<<100-50-30-15=5>>5 more.

5"

}

潜在用途

• 训练模型理解和解决数学应用题。
• 评估模型基于文本上下文执行数学运算的能力。

潜在偏差、伦理考虑和局限性

• 范围：样本似乎围绕基本算术问题。如果整个数据集都是如此，可能不涵盖更复杂的数学问题或更高级别的数学。
• 简单性：一些现实世界的数学问题可能需要比简单算术更高级的问题解决技巧。

数据集维护和更新

• 将尝试保持更新。