120 lines
2.9 KiB
Markdown
120 lines
2.9 KiB
Markdown
# Winogrande
|
|
|
|
|
|
## Overview
|
|
|
|
Winogrande is a large-scale benchmark for commonsense reasoning, specifically designed to test pronoun resolution in the Winograd Schema Challenge format. It contains 44K problems that require understanding of physical and social commonsense.
|
|
|
|
## Task Description
|
|
|
|
- **Task Type**: Pronoun Resolution / Commonsense Reasoning
|
|
- **Input**: Sentence with ambiguous pronoun and two options
|
|
- **Output**: Correct option (A or B) that resolves the pronoun
|
|
- **Format**: Binary choice between two noun phrases
|
|
|
|
## Key Features
|
|
|
|
- 44K Winograd-style pronoun resolution problems
|
|
- Adversarially filtered to reduce dataset biases
|
|
- Tests physical commonsense (object properties, actions)
|
|
- Tests social commonsense (intentions, emotions)
|
|
- Requires understanding context to resolve ambiguity
|
|
|
|
## Evaluation Notes
|
|
|
|
- Default configuration uses **0-shot** evaluation
|
|
- Binary choice format (option1 vs option2)
|
|
- Answers are converted to A/B letter format
|
|
- Simple accuracy metric for evaluation
|
|
- Commonly used for commonsense reasoning assessment
|
|
|
|
|
|
## Properties
|
|
|
|
| Property | Value |
|
|
|----------|-------|
|
|
| **Benchmark Name** | `winogrande` |
|
|
| **Dataset ID** | [AI-ModelScope/winogrande_val](https://modelscope.cn/datasets/AI-ModelScope/winogrande_val/summary) |
|
|
| **Paper** | N/A |
|
|
| **Tags** | `MCQ`, `Reasoning` |
|
|
| **Metrics** | `acc` |
|
|
| **Default Shots** | 0-shot |
|
|
| **Evaluation Split** | `validation` |
|
|
|
|
|
|
## Data Statistics
|
|
|
|
| Metric | Value |
|
|
|--------|-------|
|
|
| Total Samples | 1,267 |
|
|
| Prompt Length (Mean) | 306.58 chars |
|
|
| Prompt Length (Min/Max) | 271 / 384 chars |
|
|
|
|
## Sample Example
|
|
|
|
**Subset**: `default`
|
|
|
|
```json
|
|
{
|
|
"input": [
|
|
{
|
|
"id": "f64dd7e2",
|
|
"content": "Answer the following multiple choice question. The entire content of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of A,B.\n\nSarah was a much better surgeon than Maria so _ always got the easier cases.\n\nA) Sarah\nB) Maria"
|
|
}
|
|
],
|
|
"choices": [
|
|
"Sarah",
|
|
"Maria"
|
|
],
|
|
"target": "B",
|
|
"id": 0,
|
|
"group_id": 0,
|
|
"metadata": {
|
|
"id": "winogrande_xs val 0"
|
|
}
|
|
}
|
|
```
|
|
|
|
## Prompt Template
|
|
|
|
**Prompt Template:**
|
|
```text
|
|
Answer the following multiple choice question. The entire content of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of {letters}.
|
|
|
|
{question}
|
|
|
|
{choices}
|
|
```
|
|
|
|
## Usage
|
|
|
|
### Using CLI
|
|
|
|
```bash
|
|
evalscope eval \
|
|
--model YOUR_MODEL \
|
|
--api-url OPENAI_API_COMPAT_URL \
|
|
--api-key EMPTY_TOKEN \
|
|
--datasets winogrande \
|
|
--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=['winogrande'],
|
|
limit=10, # Remove this line for formal evaluation
|
|
)
|
|
|
|
run_task(task_cfg=task_cfg)
|
|
```
|
|
|
|
|