# MaritimeBench ## Overview MaritimeBench is a benchmark for evaluating AI models on maritime-related multiple-choice questions in Chinese. It consists of specialized questions related to maritime knowledge, navigation, marine engineering, and seafaring operations. ## Task Description - **Task Type**: Maritime Knowledge Multiple-Choice QA (Chinese) - **Input**: Maritime-related question with 4 answer choices (A-D) - **Output**: Correct answer letter in brackets [A/B/C/D] - **Language**: Chinese ## Key Features - Specialized maritime domain questions - Chinese language evaluation - Multiple subsets covering different maritime topics - Tests professional maritime knowledge - Standardized Chinese exam format ## Evaluation Notes - Default configuration uses **0-shot** evaluation - Evaluates on test split - Simple accuracy metric - Answers extracted using regex for bracketed format [A/B/C/D] ## Properties | Property | Value | |----------|-------| | **Benchmark Name** | `maritime_bench` | | **Dataset ID** | [HiDolphin/MaritimeBench](https://modelscope.cn/datasets/HiDolphin/MaritimeBench/summary) | | **Paper** | N/A | | **Tags** | `Chinese`, `Knowledge`, `MCQ` | | **Metrics** | `acc` | | **Default Shots** | 0-shot | | **Evaluation Split** | `test` | ## Data Statistics | Metric | Value | |--------|-------| | Total Samples | 1,888 | | Prompt Length (Mean) | 259.04 chars | | Prompt Length (Min/Max) | 173 / 717 chars | ## Sample Example **Subset**: `default` ```json { "input": [ { "id": "0b8c5f63", "content": "请回答单选题。要求只输出选项,不输出解释,将选项放在[]里,直接输出答案。示例:\n\n题目:在船舶主推进动力装置中,传动轴系在运转中承受以下复杂的应力和负荷,但不包括______。\n选项:\nA. 电磁力\nB. 压拉应力\nC. 弯曲应力\nD. 扭应力\n答:[A]\n 当前题目\n 船舶电力系统供电网络中,放射形网络的特点是______。①发散形传输②环形传输③缺乏冗余④冗余性能好\n选项:\nA. ②③\nB. ①③\nC. ②④\nD. ①④" } ], "choices": [ "②③", "①③", "②④", "①④" ], "target": "B", "id": 0, "group_id": 0 } ``` ## Prompt Template **Prompt Template:** ```text 请回答单选题。要求只输出选项,不输出解释,将选项放在[]里,直接输出答案。示例: 题目:在船舶主推进动力装置中,传动轴系在运转中承受以下复杂的应力和负荷,但不包括______。 选项: A. 电磁力 B. 压拉应力 C. 弯曲应力 D. 扭应力 答:[A] 当前题目 {question} 选项: {choices} ``` ## Usage ### Using CLI ```bash evalscope eval \ --model YOUR_MODEL \ --api-url OPENAI_API_COMPAT_URL \ --api-key EMPTY_TOKEN \ --datasets maritime_bench \ --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=['maritime_bench'], limit=10, # Remove this line for formal evaluation ) run_task(task_cfg=task_cfg) ```