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# IFEval
## 概述
IFEvalInstruction-Following Eval是一个用于评估语言模型遵循明确、可验证指令能力的基准测试。它包含一系列带有特定格式、内容或结构要求的提示prompts这些要求可以被客观地验证。
## 任务描述
- **任务类型**:指令遵循评估
- **输入**:包含明确、可验证约束条件的提示
- **输出**:完全遵循所有指定指令的响应
- **约束类型**:格式、长度、关键词、结构等
## 主要特点
- 包含约500个提示涵盖25种可验证的指令类型
- 指令可被客观检查(非主观判断)
- 示例“写恰好3段文字”、“包含单词X”、“使用项目符号列表”
- 测试模型对指令的理解与遵守能力
- 评估标准无歧义
## 评估说明
- 默认配置采用 **0-shot** 评估方式
- 提供四种评估指标:
- `prompt_level_strict`:提示中的所有指令都必须被严格遵循
- `prompt_level_loose`:允许对轻微偏差有一定容忍度
- `inst_level_strict`:按每条指令计算准确率(严格)
- `inst_level_loose`:按每条指令计算准确率(宽松)
- 主要指标为 `prompt_level_strict`
- 支持自动验证指令遵循情况
## 属性
| 属性 | 值 |
|----------|-------|
| **基准测试名称** | `ifeval` |
| **数据集ID** | [opencompass/ifeval](https://modelscope.cn/datasets/opencompass/ifeval/summary) |
| **论文** | N/A |
| **标签** | `InstructionFollowing` |
| **指标** | `prompt_level_strict`, `inst_level_strict`, `prompt_level_loose`, `inst_level_loose` |
| **默认示例数Shots** | 0-shot |
| **评估划分** | `train` |
## 数据统计
| 指标 | 值 |
|--------|-------|
| 总样本数 | 541 |
| 提示词长度(平均) | 210.75 字符 |
| 提示词长度(最小/最大) | 53 / 1858 字符 |
## 样例示例
**子集**`default`
```json
{
"input": [
{
"id": "cb71907f",
"content": "Write a 300+ word summary of the wikipedia page \"https://en.wikipedia.org/wiki/Raymond_III,_Count_of_Tripoli\". Do not use any commas and highlight at least 3 sections that has titles in markdown format, for example *highlighted section part 1*, *highlighted section part 2*, *highlighted section part 3*."
}
],
"target": "",
"id": 0,
"group_id": 0,
"metadata": {
"key": 1000,
"prompt": "Write a 300+ word summary of the wikipedia page \"https://en.wikipedia.org/wiki/Raymond_III,_Count_of_Tripoli\". Do not use any commas and highlight at least 3 sections that has titles in markdown format, for example *highlighted section part 1*, *highlighted section part 2*, *highlighted section part 3*.",
"instruction_id_list": [
"punctuation:no_comma",
"detectable_format:number_highlighted_sections",
"length_constraints:number_words"
],
"kwargs": [
{
"num_highlights": null,
"relation": null,
"num_words": null,
"num_placeholders": null,
"prompt_to_repeat": null,
"num_bullets": null,
"section_spliter": null,
"num_sections": null,
"capital_relation": null,
"capital_frequency": null,
"keywords": null,
"num_paragraphs": null,
"language": null,
"let_relation": null,
"letter": null,
"let_frequency": null,
"end_phrase": null,
"forbidden_words": null,
"keyword": null,
"frequency": null,
"num_sentences": null,
"postscript_marker": null,
"first_word": null,
"nth_paragraph": null
},
{
"num_highlights": 3,
"relation": null,
"num_words": null,
"num_placeholders": null,
"prompt_to_repeat": null,
"num_bullets": null,
"section_spliter": null,
"num_sections": null,
"capital_relation": null,
"capital_frequency": null,
"keywords": null,
"num_paragraphs": null,
"language": null,
"let_relation": null,
"letter": null,
"let_frequency": null,
"end_phrase": null,
"forbidden_words": null,
"keyword": null,
"frequency": null,
"num_sentences": null,
"postscript_marker": null,
"first_word": null,
"nth_paragraph": null
},
{
"num_highlights": null,
"relation": "at least",
"num_words": 300,
"num_placeholders": null,
"prompt_to_repeat": null,
"num_bullets": null,
"section_spliter": null,
"num_sections": null,
"capital_relation": null,
"capital_frequency": null,
"keywords": null,
"num_paragraphs": null,
"language": null,
"let_relation": null,
"letter": null,
"let_frequency": null,
"end_phrase": null,
"forbidden_words": null,
"keyword": null,
"frequency": null,
"num_sentences": null,
"postscript_marker": null,
"first_word": null,
"nth_paragraph": null
}
]
}
}
```
## 提示模板
*未定义提示模板。*
## 使用方法
### 使用命令行CLI
```bash
evalscope eval \
--model YOUR_MODEL \
--api-url OPENAI_API_COMPAT_URL \
--api-key EMPTY_TOKEN \
--datasets ifeval \
--limit 10 # 正式评估时请删除此行
```
### 使用 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=['ifeval'],
limit=10, # 正式评估时请删除此行
)
run_task(task_cfg=task_cfg)
```