Datasets:

stindardlogic
/

math-reasoning-sft-100k

language:
  - en
license: apache-2.0
size_categories:
  - 100K<n<1M
task_categories:
  - text-generation
  - question-answering
pretty_name: Math Reasoning SFT (100K)
tags:
  - sft
  - math
  - reasoning
  - mathematics
  - step-by-step
  - word-problems
  - algebra
  - geometry
  - arithmetic
  - probability
  - statistics
  - number-theory
  - synthetic
configs:
  - config_name: default
    data_files:
      - split: train
        path: math-reasoning-sft-100k.jsonl

Math Reasoning SFT (100K)

100,000 math problems with detailed step-by-step solutions — ready for supervised fine-tuning of math reasoning models.

Dataset Description

100,000 problems across 8 mathematical categories and 3 difficulty levels:

Category	Examples	Topics
`word_problems`	~23,100	Rate/time/distance, work problems, mixture, meeting/catch-up
`arithmetic`	~15,400	Percentages, profit/loss, ratios
`geometry`	~15,400	Area (rectangle, triangle, circle, trapezoid), Pythagorean theorem
`algebra`	~15,200	Linear equations, quadratic equations
`finance_math`	~7,800	Compound interest (annual/quarterly/monthly compounding)
`number_theory`	~7,800	GCD, LCM (Euclidean algorithm)
`probability`	~7,700	Dice, cards, balls, coins
`statistics`	~7,600	Mean, median, range

Difficulty Distribution

Level	Examples	Description
`easy`	~48,000	Single-step or direct formula application
`medium`	~44,300	Multi-step problems requiring setup
`hard`	~7,700	Problems requiring simultaneous equations or complex setup

Format

{
  "problem": "A car travels at 60 km/h for 2.5 hours. How far does it travel?",
  "solution": "Step 1: Use the formula: Distance = Speed × Time\n  Distance = 60 km/h × 2.5 h = 150 km\n\nAnswer: 150 km",
  "answer": "150 km",
  "category": "word_problems",
  "difficulty": "easy",
  "id": "abc123"
}

Solution Structure

Every solution follows a consistent multi-step format:

Formula identification — states the relevant formula or approach
Substitution — plugs in the specific numbers
Step-by-step calculation — shows intermediate results
Final answer — clearly labeled Answer: line

Use Case

SFT for math reasoning capability in LLMs
Training step-by-step problem solving behavior
Curriculum learning: filter by difficulty for progressive training
Evaluation: held-out test sets for math benchmarks
Chain-of-thought distillation

Filtering Examples

import json

# Load only medium/hard problems
with open("math-reasoning-sft-100k.jsonl") as f:
    data = [json.loads(l) for l in f]

hard_algebra = [r for r in data if r["difficulty"] in ("medium","hard") and r["category"] == "algebra"]

License

Apache 2.0