Repository: open-compass/opencompass
Issue: [Bug] 
Root cause: Documentation Deficiency

### Prerequisite

- [X] I have searched [Issues](https://github.com/open-compass/opencompass/issues/) and [Discussions](https://github.com/open-compass/opencompass/discussions) but cannot get the expected help.
- [X] The bug has not been fixed in the [latest version](https://github.com/open-compass/opencompass).

### Type

I'm evaluating with the officially supported tasks/models/datasets.

### Environment

{'CUDA available': True,
'CUDA_HOME': '/usr/local/cuda',
'GCC': 'gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0',
'GPU 0,1,2,3': 'NVIDIA A800 80GB PCIe',
'MMEngine': '0.10.1',
'NVCC': 'Cuda compilation tools, release 11.6, V11.6.55',
'OpenCV': '4.8.1',
'PyTorch': '2.1.1',
'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 v3.1.1 (Git Hash '
'64f6bcbcbab628e96f33a62c3e975f8535a7bde4)\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_61,code=sm_61;-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 -Wno-psabi '
'-Wno-error=pedantic -Wno-error=old-style-cast '
'-Wno-invalid-partial-specialization '
'-Wno-unused-private-field '
'-Wno-aligned-allocation-unavailable '
'-Wno-missing-braces -fdiagnostics-color=always '
'-faligned-new -Wno-unused-but-set-variable '
'-Wno-maybe-uninitialized -fno-math-errno '
'-fno-trapping-math -Werror=format '
'-Werror=cast-function-type '
'-Wno-stringop-overflow, LAPACK_INFO=mkl, '
'PERF_WITH_AVX=1, PERF_WITH_AVX2=1, '
'PERF_WITH_AVX512=1, '
'TORCH_DISABLE_GPU_ASSERTS=ON, '
'TORCH_VERSION=2.1.1, 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=ON, USE_NNPACK=ON, '
'USE_OPENMP=ON, USE_ROCM=OFF, \n',
'Python': '3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]',
'TorchVision': '0.16.1',
'numpy_random_seed': 2147483648,
'opencompass': '0.1.9+e10f1c9',
'sys.platform': 'linux'}

### Reproduces the problem - code/configuration sample

conda activate opencompass
cd opencompass
python run.py --models hf_llama_7b --datasets mmlu_ppl

### Reproduces the problem - command or script

conda activate opencompass
cd opencompass
python run.py --models hf_llama_7b --datasets mmlu_ppl


### Reproduces the problem - error message

01/28 01:19:27 - OpenCompass - INFO - Start inferencing [NMI_llama2_7b_chat/Xsum]
[2024-01-28 01:19:32,217] [opencompass.openicl.icl_inferencer.icl_gen_inferencer] [INFO] Starting inference process...

  0%|          | 0/125 [00:00<?, ?it/s]
  1%|          | 1/125 [00:26<55:07, 26.67s/it]
  2%|▏         | 2/125 [00:49<50:31, 24.65s/it]
  2%|▏         | 3/125 [01:21<56:39, 27.86s/it]
  3%|▎         | 4/125 [01:49<56:18, 27.92s/it]

### Other information

_No response_

It appears that the inference is functioning correctly, so could you please provide a more detailed description of the bug you are encountering?


feel free to reopen it if needed