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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:
### 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 (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
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