121 lines
3.4 KiB
Markdown
121 lines
3.4 KiB
Markdown
# MathQA
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## Overview
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MathQA is a large-scale dataset for mathematical word problem solving, gathered by annotating the AQuA-RAT dataset with fully-specified operational programs using a new representation language. It contains diverse math problems requiring multi-step reasoning.
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## Task Description
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- **Task Type**: Mathematical Reasoning (Multiple-Choice)
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- **Input**: Math word problem with multiple answer choices
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- **Output**: Correct answer with chain-of-thought reasoning
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- **Difficulty**: Varied (elementary to intermediate level)
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## Key Features
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- Annotated with executable operational programs
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- Tests quantitative reasoning and problem-solving skills
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- Diverse mathematical topics and question formats
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- Multiple-choice format with structured solutions
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- Useful for evaluating mathematical reasoning capabilities
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## Evaluation Notes
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- Default configuration uses **0-shot** evaluation
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- Uses Chain-of-Thought (CoT) prompting for reasoning
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- Evaluates on test split
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- Simple accuracy metric
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- Reasoning steps available in metadata
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## Properties
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| Property | Value |
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|----------|-------|
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| **Benchmark Name** | `math_qa` |
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| **Dataset ID** | [extraordinarylab/math-qa](https://modelscope.cn/datasets/extraordinarylab/math-qa/summary) |
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| **Paper** | N/A |
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| **Tags** | `MCQ`, `Math`, `Reasoning` |
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| **Metrics** | `acc` |
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| **Default Shots** | 0-shot |
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| **Evaluation Split** | `test` |
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## Data Statistics
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| Metric | Value |
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|--------|-------|
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| Total Samples | 2,985 |
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| Prompt Length (Mean) | 433.02 chars |
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| Prompt Length (Min/Max) | 257 / 879 chars |
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## Sample Example
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**Subset**: `default`
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```json
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{
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"input": [
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{
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"id": "e77fca06",
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"content": "Answer the following multiple choice question. The last line of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of A,B,C,D,E. Think step by step before answering.\n\na shopkeeper sold an article offering a discount of 5 % and earned a profit of 31.1 % . what would have been the percentage of profit earned if no discount had been offered ?\n\nA) 38\nB) 27.675\nC) 30\nD) data inadequate\nE) none of these"
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}
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],
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"choices": [
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"38",
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"27.675",
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"30",
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"data inadequate",
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"none of these"
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],
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"target": "A",
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"id": 0,
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"group_id": 0,
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"metadata": {
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"reasoning": "\"giving no discount to customer implies selling the product on printed price . suppose the cost price of the article is 100 . then printed price = 100 ã — ( 100 + 31.1 ) / ( 100 â ˆ ’ 5 ) = 138 hence , required % profit = 138 â € “ 100 = 38 % answer a\""
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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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Answer the following multiple choice question. The last line of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of {letters}. Think step by step before answering.
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{question}
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{choices}
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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 math_qa \
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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=['math_qa'],
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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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