Repository: open-compass/opencompass
Issue: 使用baichuan-7b评估humaneval数据与榜单差距过大
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 9.4.0-1ubuntu1~20.04.1) 9.4.0',
 'GPU 0,1,2,3,4,5,6,7': 'NVIDIA H800',
 'MMEngine': '0.10.3',
 'MUSA available': False,
 'NVCC': 'Cuda compilation tools, release 11.8, V11.8.89',
 'OpenCV': '4.9.0',
 'PyTorch': '2.2.2+cu121',
 'PyTorch compiling details': 'PyTorch built with:\n'
                              '  - GCC 9.3\n'
                              '  - C++ Version: 201703\n'
                              '  - Intel(R) oneAPI Math Kernel Library Version '
                              '2022.2-Product Build 20220804 for Intel(R) 64 '
                              'architecture applications\n'
                              '  - Intel(R) MKL-DNN v3.3.2 (Git Hash '
                              '2dc95a2ad0841e29db8b22fbccaf3e5da7992b01)\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 12.1\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 8.9.2\n'
                              '  - Magma 2.6.1\n'
                              '  - Build settings: BLAS_INFO=mkl, '
                              'BUILD_TYPE=Release, CUDA_VERSION=12.1, '
                              'CUDNN_VERSION=8.9.2, '
                              '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 -DUSE_FBGEMM '
                              '-DUSE_QNNPACK -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-unused-function -Wno-unused-result '
                              '-Wno-strict-overflow -Wno-strict-aliasing '
                              '-Wno-stringop-overflow -Wsuggest-override '
                              '-Wno-psabi -Wno-error=pedantic '
                              '-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, '
                              'PERF_WITH_AVX512=1, TORCH_VERSION=2.2.2, '
                              'USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, '
                              'USE_GFLAGS=OFF, USE_GLOG=OFF, 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, Mar 21 2024, 16:24:04) [GCC 11.2.0]',
 'TorchVision': '0.17.2+cu121',
 'numpy_random_seed': 2147483648,
 'opencompass': '0.2.2+',
 'sys.platform': 'linux'}

### 重现问题 - 代码/配置示例

`from opencompass.models import HuggingFaceCausalLM


models = [
    dict(
        type=HuggingFaceCausalLM,
        abbr='baichuan-7b-hf',
        path="/home/jovyan/zh/benchmark/pretrain_model/baichuan-7b",
        tokenizer_path='/home/jovyan/zh/benchmark/pretrain_model/baichuan-7b',
        tokenizer_kwargs=dict(padding_side='left',
                              truncation_side='left',
                              trust_remote_code=True,
                              use_fast=False,),
        max_out_len=100,
        max_seq_len=2048,
        batch_size=8,
        # batch_padding=False,
        model_kwargs=dict(device_map='auto', trust_remote_code=True),
        run_cfg=dict(num_gpus=1, num_procs=1),
    )
]`

### 重现问题 - 命令或脚本

`python run.py --models hf_baichuan_7b --datasets humaneval_gen_8e312c`

### 重现问题 - 错误信息

与榜单差距过大，榜单baichuan-7b指标在9.1，根据默认配置只能到1.81。

### 其他信息

_No response_

@hzhwcmhf @x22x22 @Sanster Looking forward to your reply

我也遇到了类似的情况，测试wizardcoder，starcoder2这两个模型在humaneval上的结果很差。