| # AMC12 Dataset (Research-Oriented) |
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| A structured dataset derived from the AMC 12 (American Mathematics Competitions), designed for **LLM training, evaluation, and reinforcement learning (RL)** on mathematical reasoning tasks. |
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| This repository contains **all AMC 12 problems from 2000–2025**, making it one of the most complete AMC12 datasets available for research. |
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| ## 📘 Introduction |
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| The AMC 12 is a **25-question, 75-minute multiple-choice examination** aimed at high school students. Problems are designed to **increase in difficulty progressively**, requiring a combination of algebra, geometry, combinatorics, and number theory reasoning. |
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| * **Format:** 25 multiple-choice questions (A–E) |
| * **Duration:** 75 minutes |
| * **Difficulty progression:** Problems 1 → 25 increase in complexity |
| * **Calculator policy:** |
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| * Since 2008, calculators are **not permitted** |
| * Problems are designed to be solvable without computational aids |
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| Top-performing students (~top 6%) are invited to participate in the AIME, making AMC 12 a strong proxy for **high-level mathematical reasoning ability**. |
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| ## 📦 Dataset Overview |
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| Each sample corresponds to a single AMC 12 problem. |
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| ### Example (JSONL) |
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| ```json |
| { |
| "year": 2019, |
| "problem_id": "2019A-15", |
| "question": "...", |
| "answer": "D", |
| "difficulty": 3 |
| } |
| ``` |
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| ## 🧱 Schema |
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| Each entry in the dataset follows this structure: |
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| | Field | Type | Description | |
| | ------------ | ------ | --------------------------------------------------------------------------------- | |
| | `problem_id` | string | Unique identifier in the format `{year}{A/B}-{problem_number}` (e.g., `2019A-15`) | |
| | `year` | int | Competition year (2000–2025) | |
| | `question` | string | Full problem statement (including choices) | |
| | `answer` | string | Correct answer option (`A`–`E`) | |
| | `difficulty` | int | Difficulty level derived from problem order | |
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| ### 🔑 Problem ID Definition |
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| The `problem_id` encodes the full provenance of each problem: |
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| ``` |
| {year}{A/B}-{problem_number} |
| ``` |
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| * `{year}` → competition year |
| * `{A/B}` → AMC12A or AMC12B |
| * `{problem_number}` → position in the exam (1–25) |
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| #### Examples |
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| * `2007B-5` → AMC 12B, 2007, Problem 5 |
| * `2019A-15` → AMC 12A, 2019, Problem 15 |
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| ### Difficulty Structure |
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| We adopt a coarse-grained difficulty approximation aligned with problem order: |
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| | Problem Range | Difficulty | |
| | ------------- | --------------- | |
| | 1–10 | Easy–Medium (2) | |
| | 11–20 | Medium–Hard (3) | |
| | 21–25 | Hard (4) | |
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| This structure enables: |
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| * Curriculum learning |
| * Difficulty-aware evaluation |
| * Model capability stratification |
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| ## 🚀 Why This Dataset? |
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| ### Compared to Other Math Datasets |
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| * **Not heavily pretrained** |
| Unlike datasets such as GSM8K, AMC-style problems are less likely to be memorized by models |
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| * **Higher reasoning complexity** |
| Problems typically require **multi-step, structured reasoning**, often exceeding datasets like MATH500 |
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| * **Clean evaluation signal** |
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| * Multiple-choice format eliminates ambiguity |
| * No unit mismatch issues (e.g., “8 months vs 240 days”) |
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| * **Fully verifiable** |
| Every problem has a **unique, discrete answer**, ideal for RL reward design |
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| ### Compared to Other AMC Datasets |
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| * **Complete coverage (2000–2025)** |
| Includes all AMC12A and AMC12B problems across 25 years |
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| * **Fully indexed & traceable** |
| Each problem maps directly to its original contest and position |
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| * **Structured for ML pipelines** |
| Ready for: |
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| * RL training (PPO / GRPO) |
| * Pass@k evaluation |
| * Verifier-based reward systems |
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| ## 📚 Data Source & Attribution |
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| This dataset is curated from publicly available resources, with primary reference to: |
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| * Art of Problem Solving |
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| All AMC problems are **copyrighted by the Mathematical Association of America (MAA)** under the American Mathematics Competitions program. |
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| This repository does **not claim ownership** of the original problem statements and provides them solely for research and educational purposes. |
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