README.md

---
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:

1. **Arithmetic**: Long division with rigorous verification (quotient and remainder proofs).
2. **Algebra**: Quadratic equations utilizing the discriminant (handling both real and complex roots).
3. **Calculus**: Indefinite integration using the power rule, and derivatives using the chain rule.
4. **Linear Algebra**: 2x2 matrix multiplication with explicit dot-product calculations.
5. **Geometry**: Pythagorean theorem calculations for right-angled triangles.
6. **Fractions**: Addition of fractions requiring Least Common Multiple (LCM) calculation and simplification via Greatest Common Divisor (GCD).
7. **Statistics**: Calculation of mean, population variance, and standard deviation.
8. **Trigonometry**: Exact trigonometric values derived from the unit circle and special triangles.
9. **Logarithms**: Evluation of logarithms by converting between logarithmic and exponential forms.

## License
Open Data Attribution Training Disclosure License (ODATL‑1.0)