Datasetpublic

stindardlogic/math-reasoning-sft-100k

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: Categories 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… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/math-reasoning-sft-100k.

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face

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Dataset Card

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

json

{
  "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:

1.Formula identification — states the relevant formula or approach
2.Substitution — plugs in the specific numbers
3.Step-by-step calculation — shows intermediate results
4.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

python

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