RACE#

概述#

RACE(ReAding Comprehension from Examinations)是一个大规模阅读理解基准数据集,收集自中国初中和高中英语考试题目。该数据集用于测试综合阅读理解能力。

任务描述#

  • 任务类型:阅读理解(多项选择题)

  • 输入:文章段落、问题及4个选项

  • 输出:正确答案字母(A、B、C 或 D)

  • 难度级别:初中和高中

主要特点#

  • 包含28,000+篇文章和100,000道问题

  • 使用真实考试题目,确保难度的真实性

  • 包含两个子集:middle(较简单)和 high(较难)

  • 考察多种阅读理解技能(推理、词汇、主旨等)

  • 文章主题和题型丰富多样

评估说明#

  • 默认配置使用 3-shot 示例

  • 最大 few-shot 数量为3(受上下文长度限制)

  • 使用思维链(Chain-of-Thought, CoT)提示方法

  • 提供两个子集:highmiddle

  • 在测试集(test split)上进行评估

属性#

属性

基准测试名称

race

数据集ID

evalscope/race

论文

N/A

标签

MCQ, Reasoning

指标

acc

默认示例数

3-shot

评估划分

test

训练划分

train

数据统计#

指标

总样本数

4,934

提示词长度(平均)

7217.34 字符

提示词长度(最小/最大)

3685 / 11131 字符

各子集统计数据:

子集

样本数

提示平均长度

提示最小长度

提示最大长度

high

3,498

8279.47

6585

11131

middle

1,436

4630.07

3685

6032

样例示例#

子集: high

{
  "input": [
    {
      "id": "706382e9",
      "content": "Here are some examples of how to answer similar questions:\n\nArticle:\nLast week I talked with some of my students about what they wanted to do after they graduated, and what kind of job prospects  they thought they had.\nGiven that I teach stud ... [TRUNCATED] ... I owe my life to her,\" said Nancy with tears.\nQuestion:\nWhat did Nancy try to do before she fell over?\n\nA) Measure the depth of the river\nB) Look for a fallen tree trunk\nC) Protect her cows from being drowned\nD) Run away from the flooded farm"
    }
  ],
  "choices": [
    "Measure the depth of the river",
    "Look for a fallen tree trunk",
    "Protect her cows from being drowned",
    "Run away from the flooded farm"
  ],
  "target": "C",
  "id": 0,
  "group_id": 0,
  "metadata": {
    "example_id": "high19432.txt"
  }
}

注:部分内容因展示需要已被截断。

提示模板#

提示模板:

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.

{question}

{choices}

使用方法#

使用命令行(CLI)#

evalscope eval \
    --model YOUR_MODEL \
    --api-url OPENAI_API_COMPAT_URL \
    --api-key EMPTY_TOKEN \
    --datasets race \
    --limit 10  # 正式评估时请删除此行

使用 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=['race'],
    dataset_args={
        'race': {
            # subset_list: ['high', 'middle']  # 可选,用于指定评估特定子集
        }
    },
    limit=10,  # 正式评估时请删除此行
)

run_task(task_cfg=task_cfg)