Repository: modelscope/evalscope
Issue: gsm8k base model正确率低，有复读机
Root cause: Configuration Error

## 自查清单

在提交 issue 之前，请确保您已完成以下步骤:
-  我已仔细阅读了[相关使用说明文档](https://evalscope.readthedocs.io/zh-cn/latest/get_started/parameters.html)
-  我已查看了[常见问题解答](https://evalscope.readthedocs.io/zh-cn/latest/get_started/faq.html)
-  我已搜索并查看了现有的 issues，确认这不是一个重复的问题

## 问题描述

用gsm8k评测base model qwen2.5-7B-Base 以及qwen3-4B-Base出现复读机情况，正确率低。AIME和MATH500均正常。

## EvalScope 版本（必填）
v0.15.1

## 使用的工具
-  Native / 原生框架

## 执行的代码或指令

### VLLM deploy
VLLM_USE_MODELSCOPE=True \
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 \
vllm serve Qwen/Qwen2.5-7B \
  --gpu-memory-utilization 0.9 \
  --served-model-name Qwen2.5-7B \
  --trust_remote_code \
  --port 8801 \
  --pipeline-parallel-size 2 \
  --tensor-parallel-size 4 \
  --trust-remote-code 

### config
试了两个
gsm_base_cfg = TaskConfig(
    model='Qwen2.5-7B',   # 模型名称 (需要与部署时的模型名称一致)
    api_url='http://127.0.0.1:8801/v1/chat/completions',  # 推理服务地址
    api_key='EMPTY',
    eval_type=EvalType.SERVICE,   # 评测类型，SERVICE表示评测推理服务
    datasets=[
    'gsm8k'
    ],
    dataset_args={
        'gsm8k': {
        'few_shot_num': 4 
        }
    },
    eval_batch_size=64,       # 发送请求的并发数
    generation_config={       # 模型推理配置
        'max_tokens': 20000,  # 最大生成token数，建议设置为较大值避免输出截断
        'temperature': 0.2,   # 采样温度 (deepseek 报告推荐值)
        'top_p': 0.8,        # top-p采样 (deepseek 报告推荐值)
        'n': 1
    },
    stream=True               # 是否使用流式请求，推荐设置为True防止请求超时
)


gsm_base_cfg = TaskConfig(
    model='Qwen2.5-7B',   # 模型名称 (需要与部署时的模型名称一致)
    api_url='http://127.0.0.1:8801/v1/chat/completions',  # 推理服务地址
    api_key='EMPTY',
    eval_type=EvalType.SERVICE,   # 评测类型，SERVICE表示评测推理服务
    datasets=[
    'gsm8k'
    ],
    dataset_args={
        'gsm8k': {
        'few_shot_num': 4 
        }
    },
    eval_batch_size=8,       # 发送请求的并发数
    generation_config={       # 模型推理配置
        'max_tokens': 20000,  
        'temperature': 0.2,   
        'top_p': 0.9,        
        'n': 1,
        "repeat_penalty": 1
    },
    stream=True               # 是否使用流式请求，推荐设置为True防止请求超时
)

请提供您执行的主要代码或指令。

## 错误日志
没有报错，正确率不到0.1。有很多复读机，如下
{"id": "chatcmpl-20002a78c69d423d98d969819d0fdc3b", "choices": [{"finish_reason": "length", "index": 0, "message": {"content": "Answer:ologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist\nologist


调大temperature试试呢

> 感谢你的反馈！我们将关闭此问题。如果您有任何疑问，请随时重新打开它。如果EvalScope对您有所帮助，欢迎给我们点个STAR以示支持，谢谢！