Repository: open-compass/opencompass
Issue: [Bug] gpqa_gen数据集得出的结果很低
Root cause: Configuration Error

### 先决条件

- [x] 我已经搜索过 [问题](https://github.com/open-compass/opencompass/issues/) 和 [讨论](https://github.com/open-compass/opencompass/discussions) 但未得到预期的帮助。
- [x] 错误在 [最新版本](https://github.com/open-compass/opencompass) 中尚未被修复。

### 问题类型

我正在使用官方支持的任务/模型/数据集进行评估。

### 环境

{'CUDA available': True,
 'CUDA_HOME': '/usr/local/cuda',
 'GCC': 'gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0',
 'GPU 0,1,2,3,4,5,6,7': 'NVIDIA A40',
 'MMEngine': '0.10.4',
 'MUSA available': False,
 'NVCC': 'Cuda compilation tools, release 12.1, V12.1.66',
 'OpenCV': '4.10.0',
 'PyTorch': '2.5.1+cu124',
 'PyTorch compiling details': 'PyTorch built with:\n'
                              '  - GCC 9.3\n'
                              '  - C++ Version: 201703\n'
                              '  - Intel(R) oneAPI Math Kernel Library Version '
                              '2023.1-Product Build 20230303 for Intel(R) 64 '
                              'architecture applications\n'
                              '  - Intel(R) MKL-DNN v3.5.3 (Git Hash '
                              '66f0cb9eb66affd2da3bf5f8d897376f04aae6af)\n'
                              '  - OpenMP 201511 (a.k.a. OpenMP 4.5)\n'
                              '  - LAPACK is enabled (usually provided by '
                              'MKL)\n'
                              '  - NNPACK is enabled\n'
                              '  - CPU capability usage: AVX512\n'
                              '  - CUDA Runtime 12.4\n'
                              '  - NVCC architecture flags: '
                              '-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90\n'
                              '  - CuDNN 90.1\n'
                              '  - Magma 2.6.1\n'
                              '  - Build settings: BLAS_INFO=mkl, '
                              'BUILD_TYPE=Release, CUDA_VERSION=12.4, '
                              'CUDNN_VERSION=9.1.0, '
                              'CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, '
                              'CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 '
                              '-fabi-version=11 -fvisibility-inlines-hidden '
                              '-DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO '
                              '-DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON '
                              '-DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK '
                              '-DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE '
                              '-O2 -fPIC -Wall -Wextra -Werror=return-type '
                              '-Werror=non-virtual-dtor -Werror=bool-operation '
                              '-Wnarrowing -Wno-missing-field-initializers '
                              '-Wno-type-limits -Wno-array-bounds '
                              '-Wno-unknown-pragmas -Wno-unused-parameter '
                              '-Wno-strict-overflow -Wno-strict-aliasing '
                              '-Wno-stringop-overflow -Wsuggest-override '
                              '-Wno-psabi -Wno-error=old-style-cast '
                              '-Wno-missing-braces -fdiagnostics-color=always '
                              '-faligned-new -Wno-unused-but-set-variable '
                              '-Wno-maybe-uninitialized -fno-math-errno '
                              '-fno-trapping-math -Werror=format '
                              '-Wno-stringop-overflow, LAPACK_INFO=mkl, '
                              'PERF_WITH_AVX=1, PERF_WITH_AVX2=1, '
                              'TORCH_VERSION=2.5.1, USE_CUDA=ON, USE_CUDNN=ON, '
                              'USE_CUSPARSELT=1, USE_EXCEPTION_PTR=1, '
                              'USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, '
                              'USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, '
                              'USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, '
                              'USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, \n',
 'Python': '3.10.14 (main, May  6 2024, 19:42:50) [GCC 11.2.0]',
 'TorchVision': '0.20.1+cu124',
 'lmdeploy': '0.7.1',
 'numpy_random_seed': 2147483648,
 'opencompass': '0.4.1+2176224',
 'sys.platform': 'linux',
 'transformers': '4.49.0'}

### 重现问题 - 代码/配置示例

python3 /nas/xz/opencompass/run.py --hf-path /nas/xz/model_para/Qwen2.5-7B-Instruct  --hf-type chat --datasets gpqa_gen_4baadb  --hf-num-gpus 4 --generation-kwargs do_sample=True  
python3 /nas/xz/opencompass/run.py --hf-path /nas/xz/model_para/Qwen2.5-7B-Instruct  --hf-type chat --datasets gpqa_gen --hf-num-gpus 4 --generation-kwargs do_sample=True 

### 重现问题 - 命令或脚本

无

### 重现问题 - 错误信息

无

### 其他信息

用gpqa_gen_4baadb数据集得出结果34.85，但用gpqa_gen数据集只有0.51，按理说不带版本号的应该是最新最准确的数据集啊，为什么呢

GPQA_gen points to gpqa_openai_simple_evals_gen_5aeece.py, which requires the model outputs “ANSWER: $LETTER”.

> GPQA_gen points to gpqa_openai_simple_evals_gen_5aeece.py, which requires the model outputs “ANSWER: $LETTER”.

所以如果想要更通用一点地对chat模型进行评测，可以用gpqa_gen_4baadb是吗？