128 lines
3.4 KiB
Markdown
128 lines
3.4 KiB
Markdown
# AMC
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## Overview
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AMC (American Mathematics Competitions) is a benchmark based on problems from the AMC 10/12 competitions from 2022-2024. These multiple-choice problems test mathematical problem-solving skills at the high school level and serve as qualifiers for the AIME competition.
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## Task Description
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- **Task Type**: Competition Mathematics (Multiple Choice)
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- **Input**: AMC-level mathematical problem
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- **Output**: Correct answer with step-by-step reasoning
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- **Years Covered**: 2022, 2023, 2024
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## Key Features
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- Problems from AMC 10 and AMC 12 competitions (2022-2024)
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- Multiple-choice format with 5 answer options
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- Topics: algebra, geometry, number theory, combinatorics
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- Difficulty ranges from accessible to challenging
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- Official competition problems with verified solutions
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## Evaluation Notes
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- Default configuration uses **0-shot** evaluation
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- Answers should be formatted within `\boxed{}` for proper extraction
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- Three subsets available: `amc22`, `amc23`, `amc24`
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- Problems include original URLs for reference
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- Solutions available in metadata for verification
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## Properties
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| Property | Value |
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|----------|-------|
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| **Benchmark Name** | `amc` |
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| **Dataset ID** | [evalscope/amc_22-24](https://modelscope.cn/datasets/evalscope/amc_22-24/summary) |
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| **Paper** | N/A |
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| **Tags** | `Math`, `Reasoning` |
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| **Metrics** | `acc` |
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| **Default Shots** | 0-shot |
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| **Evaluation Split** | `N/A` |
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## Data Statistics
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| Metric | Value |
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|--------|-------|
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| Total Samples | 134 |
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| Prompt Length (Mean) | 324.58 chars |
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| Prompt Length (Min/Max) | 98 / 1218 chars |
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**Per-Subset Statistics:**
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| Subset | Samples | Prompt Mean | Prompt Min | Prompt Max |
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|--------|---------|-------------|------------|------------|
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| `amc22` | 43 | 337.42 | 129 | 934 |
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| `amc23` | 46 | 337.98 | 143 | 1218 |
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| `amc24` | 45 | 298.62 | 98 | 882 |
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## Sample Example
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**Subset**: `amc22`
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```json
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{
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"input": [
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{
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"id": "54851a8f",
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"content": "What is the value of\\[3+\\frac{1}{3+\\frac{1}{3+\\frac13}}?\\]\nPlease reason step by step, and put your final answer within \\boxed{}."
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}
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],
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"target": "\\frac{109}{33}",
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"id": 0,
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"group_id": 0,
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"metadata": {
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"year": 2022,
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"url": "https://artofproblemsolving.com/wiki/index.php/2022_AMC_12A_Problems/Problem_1",
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"solution": "We have\\begin{align*} 3+\\frac{1}{3+\\frac{1}{3+\\frac13}} &= 3+\\frac{1}{3+\\frac{1}{\\left(\\frac{10}{3}\\right)}} \\\\ &= 3+\\frac{1}{3+\\frac{3}{10}} \\\\ &= 3+\\frac{1}{\\left(\\frac{33}{10}\\right)} \\\\ &= 3+\\frac{10}{33} \\\\ &= \\boxed{\\textbf{(D)}\\ \\frac{109}{33}}. \\end{align*}"
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}
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}
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```
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## Prompt Template
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**Prompt Template:**
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```text
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{question}
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Please reason step by step, and put your final answer within \boxed{{}}.
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```
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## Usage
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### Using CLI
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```bash
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evalscope eval \
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--model YOUR_MODEL \
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--api-url OPENAI_API_COMPAT_URL \
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--api-key EMPTY_TOKEN \
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--datasets amc \
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--limit 10 # Remove this line for formal evaluation
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```
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### Using Python
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```python
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from evalscope import run_task
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from evalscope.config import TaskConfig
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task_cfg = TaskConfig(
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model='YOUR_MODEL',
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api_url='OPENAI_API_COMPAT_URL',
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api_key='EMPTY_TOKEN',
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datasets=['amc'],
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dataset_args={
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'amc': {
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# subset_list: ['amc22', 'amc23', 'amc24'] # optional, evaluate specific subsets
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}
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},
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limit=10, # Remove this line for formal evaluation
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)
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run_task(task_cfg=task_cfg)
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```
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