156 lines
4.2 KiB
Markdown
156 lines
4.2 KiB
Markdown
# MGSM
|
|
|
|
|
|
## Overview
|
|
|
|
MGSM (Multilingual Grade School Math) is a benchmark designed to evaluate multilingual mathematical reasoning capabilities of language models. It extends GSM8K to 11 typologically diverse languages, testing whether models can perform chain-of-thought reasoning across different languages.
|
|
|
|
## Task Description
|
|
|
|
- **Task Type**: Multilingual Mathematical Word Problem Solving
|
|
- **Input**: Grade school math word problem in one of 11 languages
|
|
- **Output**: Step-by-step reasoning with numerical answer
|
|
- **Languages**: English, Spanish, French, German, Russian, Chinese, Japanese, Thai, Swahili, Bengali, Telugu
|
|
|
|
## Key Features
|
|
|
|
- 250 problems per language (translated from GSM8K)
|
|
- 11 typologically diverse languages covering different language families
|
|
- Tests multilingual chain-of-thought reasoning capabilities
|
|
- Same problem content across languages for cross-lingual comparison
|
|
- Designed to evaluate language-agnostic mathematical reasoning
|
|
|
|
## Evaluation Notes
|
|
|
|
- Default configuration uses **4-shot** examples
|
|
- Answers should be formatted within `\boxed{}` for proper extraction
|
|
- Use `subset_list` to evaluate specific languages (e.g., `['en', 'zh', 'ja']`)
|
|
- Cross-lingual performance comparison supported
|
|
- Few-shot examples are drawn from the train split in the same language
|
|
|
|
|
|
## Properties
|
|
|
|
| Property | Value |
|
|
|----------|-------|
|
|
| **Benchmark Name** | `mgsm` |
|
|
| **Dataset ID** | [evalscope/mgsm](https://modelscope.cn/datasets/evalscope/mgsm/summary) |
|
|
| **Paper** | N/A |
|
|
| **Tags** | `Math`, `MultiLingual`, `Reasoning` |
|
|
| **Metrics** | `acc` |
|
|
| **Default Shots** | 4-shot |
|
|
| **Evaluation Split** | `test` |
|
|
| **Train Split** | `train` |
|
|
|
|
|
|
## Data Statistics
|
|
|
|
| Metric | Value |
|
|
|--------|-------|
|
|
| Total Samples | 2,750 |
|
|
| Prompt Length (Mean) | 1742.98 chars |
|
|
| Prompt Length (Min/Max) | 791 / 2464 chars |
|
|
|
|
**Per-Subset Statistics:**
|
|
|
|
| Subset | Samples | Prompt Mean | Prompt Min | Prompt Max |
|
|
|--------|---------|-------------|------------|------------|
|
|
| `en` | 250 | 1790.71 | 1637 | 2165 |
|
|
| `es` | 250 | 1940.02 | 1773 | 2371 |
|
|
| `fr` | 250 | 2047 | 1878 | 2440 |
|
|
| `de` | 250 | 1963.9 | 1792 | 2386 |
|
|
| `ru` | 250 | 1831.66 | 1667 | 2214 |
|
|
| `zh` | 250 | 842.16 | 791 | 946 |
|
|
| `ja` | 250 | 1102.33 | 1035 | 1248 |
|
|
| `th` | 250 | 1835.53 | 1699 | 2135 |
|
|
| `sw` | 250 | 1953.48 | 1780 | 2354 |
|
|
| `bn` | 250 | 1759.28 | 1601 | 2106 |
|
|
| `te` | 250 | 2106.77 | 1939 | 2464 |
|
|
|
|
## Sample Example
|
|
|
|
**Subset**: `en`
|
|
|
|
```json
|
|
{
|
|
"input": [
|
|
{
|
|
"id": "d67cb3cf",
|
|
"content": "Here are some examples of how to solve similar problems:\n\nQuestion: Roger has 5 tennis balls. He buys 2 more cans of tennis balls. Each can has 3 tennis balls. How many tennis balls does he have now?\n\nReasoning:\nStep-by-Step Answer: Roger sta ... [TRUNCATED] ... every day with four. She sells the remainder at the farmers' market daily for $2 per fresh duck egg. How much in dollars does she make every day at the farmers' market?\nPlease reason step by step, and put your final answer within \\boxed{}.\n\n"
|
|
}
|
|
],
|
|
"target": "18",
|
|
"id": 0,
|
|
"group_id": 0,
|
|
"metadata": {
|
|
"reasoning": null,
|
|
"equation_solution": null
|
|
}
|
|
}
|
|
```
|
|
|
|
*Note: Some content was truncated for display.*
|
|
|
|
## Prompt Template
|
|
|
|
**Prompt Template:**
|
|
```text
|
|
{question}
|
|
Please reason step by step, and put your final answer within \boxed{{}}.
|
|
|
|
|
|
```
|
|
|
|
<details>
|
|
<summary>Few-shot Template</summary>
|
|
|
|
```text
|
|
Here are some examples of how to solve similar problems:
|
|
|
|
{fewshot}
|
|
|
|
{question}
|
|
Please reason step by step, and put your final answer within \boxed{{}}.
|
|
|
|
|
|
```
|
|
|
|
</details>
|
|
|
|
## Usage
|
|
|
|
### Using CLI
|
|
|
|
```bash
|
|
evalscope eval \
|
|
--model YOUR_MODEL \
|
|
--api-url OPENAI_API_COMPAT_URL \
|
|
--api-key EMPTY_TOKEN \
|
|
--datasets mgsm \
|
|
--limit 10 # Remove this line for formal evaluation
|
|
```
|
|
|
|
### Using Python
|
|
|
|
```python
|
|
from evalscope import run_task
|
|
from evalscope.config import TaskConfig
|
|
|
|
task_cfg = TaskConfig(
|
|
model='YOUR_MODEL',
|
|
api_url='OPENAI_API_COMPAT_URL',
|
|
api_key='EMPTY_TOKEN',
|
|
datasets=['mgsm'],
|
|
dataset_args={
|
|
'mgsm': {
|
|
# subset_list: ['en', 'es', 'fr'] # optional, evaluate specific subsets
|
|
}
|
|
},
|
|
limit=10, # Remove this line for formal evaluation
|
|
)
|
|
|
|
run_task(task_cfg=task_cfg)
|
|
```
|
|
|
|
|