141 lines
3.7 KiB
Markdown
141 lines
3.7 KiB
Markdown
# A-OKVQA
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## 概述
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A-OKVQA（Augmented OK-VQA）是一个用于评估视觉问答（VQA）中常识推理与外部世界知识能力的基准测试。它超越了仅依赖图像内容的基础VQA任务，要求模型利用广泛的世界常识和事实性知识进行推理。
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## 任务描述
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- **任务类型**：基于知识推理的视觉问答
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- **输入**：图像 + 需要外部知识的自然语言问题
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- **输出**：答案（多项选择或开放式）
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- **领域**：常识推理、事实性知识、视觉理解
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## 主要特点
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- 要求模型进行超出直接视觉观察的常识推理
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- 结合视觉理解与外部世界知识
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- 包含多项选择题和开放式问题两种格式
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- 问题附带解释推理过程的理由（rationales）
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- 相比标准VQA基准更具挑战性
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## 评估说明
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- 默认使用 **验证集（validation）** 进行评估
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- 主要指标：多项选择题的 **准确率（Accuracy）**
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- 使用思维链（Chain-of-Thought, CoT）提示以提升推理能力
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- 问题需要基于图像之外的知识进行推理
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## 属性
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| 属性 | 值 |
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|----------|-------|
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| **基准测试名称** | `a_okvqa` |
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| **数据集ID** | [HuggingFaceM4/A-OKVQA](https://modelscope.cn/datasets/HuggingFaceM4/A-OKVQA/summary) |
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| **论文** | N/A |
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| **标签** | `Knowledge`, `MCQ`, `MultiModal` |
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| **指标** | `acc` |
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| **默认示例数量** | 0-shot |
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| **评估划分** | `validation` |
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## 数据统计
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| 指标 | 值 |
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|--------|-------|
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| 总样本数 | 1,145 |
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| 提示词长度（平均） | 310.84 字符 |
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| 提示词长度（最小/最大） | 276 / 405 字符 |
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**图像统计信息：**
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| 指标 | 值 |
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|--------|-------|
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| 总图像数 | 1,145 |
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| 每样本图像数 | 最小: 1, 最大: 1, 平均: 1 |
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| 分辨率范围 | 305x229 - 640x640 |
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| 格式 | jpeg |
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## 样例示例
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**子集**: `default`
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```json
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{
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"input": [
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{
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"id": "3d2b0351",
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"content": [
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{
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"text": "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 A,B,C,D. Think step by step before answering.\n\nWhat is in the motorcyclist's mouth?\n\nA) toothpick\nB) food\nC) popsicle stick\nD) cigarette"
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},
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{
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"image": "[BASE64_IMAGE: jpeg, ~53.4KB]"
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}
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]
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}
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],
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"choices": [
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"toothpick",
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"food",
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"popsicle stick",
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"cigarette"
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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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"question_id": "22jbM6gDxdaMaunuzgrsBB",
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"direct_answers": "['cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette']",
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"difficult_direct_answer": false,
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"rationales": [
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"He's smoking while riding.",
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"The motorcyclist has a lit cigarette in his mouth while he rides on the street.",
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"The man is smoking."
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]
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}
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}
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```
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## 提示模板
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**提示模板：**
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```text
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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.
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{question}
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{choices}
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```
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## 使用方法
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### 使用命令行（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 a_okvqa \
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--limit 10 # 正式评估时请删除此行
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```
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### 使用 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=['a_okvqa'],
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limit=10, # 正式评估时请删除此行
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)
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run_task(task_cfg=task_cfg)
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``` |