metadata
license: other
language:
- en
tags:
- synthetic
- math
Massive Step-by-Step Mathematics Instruction Dataset
Dataset Description
This is a 60GB, highly knowledge-dense dataset designed to teach Large Language Models (LLMs) rigorous mathematical reasoning.
Unlike standard math datasets that only provide the final answer, this dataset emphasizes Chain-of-Thought (CoT) reasoning. Every single row contains a detailed, step-by-step breakdown of how to arrive at the solution, making it ideal for supervised fine-tuning (SFT) to improve an LLM's logical reasoning capabilities.
Dataset Structure
The dataset is stored as a single CSV file (math_dataset.csv) and contains two columns:
prompt: The mathematical question or instruction.completion: The step-by-step reasoning and final answer.
Mathematical Domains Covered
The dataset contains hundreds of millions of examples spanning 10 core mathematical disciplines:
- Arithmetic: Long division with rigorous verification (quotient and remainder proofs).
- Algebra: Quadratic equations utilizing the discriminant (handling both real and complex roots).
- Calculus: Indefinite integration using the power rule, and derivatives using the chain rule.
- Linear Algebra: 2x2 matrix multiplication with explicit dot-product calculations.
- Geometry: Pythagorean theorem calculations for right-angled triangles.
- Fractions: Addition of fractions requiring Least Common Multiple (LCM) calculation and simplification via Greatest Common Divisor (GCD).
- Statistics: Calculation of mean, population variance, and standard deviation.
- Trigonometry: Exact trigonometric values derived from the unit circle and special triangles.
- Logarithms: Evluation of logarithms by converting between logarithmic and exponential forms.
License
Open Data Attribution Training Disclosure License (ODATL‑1.0)