122 lines
3.2 KiB
Markdown
122 lines
3.2 KiB
Markdown
# HellaSwag
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## Overview
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HellaSwag is a benchmark for evaluating commonsense natural language inference, specifically testing a model's ability to complete sentences describing everyday situations. The dataset uses adversarial filtering to create challenging distractors that are grammatically correct but semantically implausible.
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## Task Description
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- **Task Type**: Multiple-Choice Sentence Completion
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- **Input**: Context describing an activity or situation
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- **Output**: Most plausible continuation from 4 choices (A, B, C, D)
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- **Domain**: Everyday activities and commonsense scenarios
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## Key Features
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- 70,000+ questions testing grounded commonsense inference
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- Contexts derived from ActivityNet and WikiHow
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- Adversarially-filtered incorrect endings
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- Requires understanding of typical event sequences
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- Tests physical and social commonsense reasoning
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## Evaluation Notes
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- Default configuration uses **0-shot** evaluation
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- Evaluates on the validation split
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- Endings are preprocessed to clean formatting artifacts
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- Context combines `ctx_a` and `ctx_b` fields
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- Activity labels available in metadata for analysis
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## Properties
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| Property | Value |
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|----------|-------|
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| **Benchmark Name** | `hellaswag` |
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| **Dataset ID** | [evalscope/hellaswag](https://modelscope.cn/datasets/evalscope/hellaswag/summary) |
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| **Paper** | N/A |
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| **Tags** | `Commonsense`, `Knowledge`, `MCQ` |
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| **Metrics** | `acc` |
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| **Default Shots** | 0-shot |
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| **Evaluation Split** | `validation` |
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## Data Statistics
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| Metric | Value |
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|--------|-------|
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| Total Samples | 10,042 |
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| Prompt Length (Mean) | 767.6 chars |
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| Prompt Length (Min/Max) | 329 / 1655 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": "18df47e2",
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"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,C,D.\n\nA man is sitting on a roof. He\n\nA) is using wrap to wrap a pair of skis.\nB) is ripping level tiles off.\nC) is holding a rubik's cube.\nD) starts pulling up roofing on a roof."
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}
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],
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"choices": [
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"is using wrap to wrap a pair of skis.",
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"is ripping level tiles off.",
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"is holding a rubik's cube.",
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"starts pulling up roofing on a roof."
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],
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"target": "D",
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"id": 0,
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"group_id": 0,
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"metadata": {
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"activity_label": "Roof shingle removal"
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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 entire content of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of {letters}.
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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 hellaswag \
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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=['hellaswag'],
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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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