[Bug] MBPP score significantly lower than official results

[GenerallyCovetous]

Prerequisite

• I have searched Issues and Discussions but cannot get the expected help.
• The bug has not been fixed in the latest version.

Type

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

Environment

{'CUDA available': True,
'GCC': 'gcc (GCC) 7.3.0',
'MMEngine': '0.10.6',
'MUSA available': False,
'OpenCV': '4.11.0',
'PyTorch': '2.1.0',
'PyTorch compiling details': 'PyTorch built with:\n'
' - GCC 10.2\n'
' - C++ Version: 201703\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: NO AVX\n'
' - Build settings: BLAS_INFO=open, '
'BUILD_TYPE=Release, '
'CXX_COMPILER=/opt/rh/devtoolset-10/root/usr/bin/c++, '
'CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 '
'-fabi-version=11 -fvisibility-inlines-hidden '
'-DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO '
'-DLIBKINETO_NOCUPTI -DLIBKINETO_NOROCTRACER '
'-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=open, '
'TORCH_DISABLE_GPU_ASSERTS=ON, '
'TORCH_VERSION=2.1.0, USE_CUDA=OFF, '
'USE_CUDNN=OFF, USE_EIGEN_FOR_BLAS=ON, '
'USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, '
'USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=ON, '
'USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=ON, '
'USE_OPENMP=ON, USE_ROCM=OFF, \n',
'Python': '3.10.16 (main, Dec 11 2024, 16:18:56) [GCC 11.2.0]',
'TorchVision': '0.16.0',
'lmdeploy': "not installed:No module named 'lmdeploy'",
'numpy_random_seed': 2147483648,
'opencompass': '0.3.9+',
'sys.platform': 'linux',
'transformers': '4.48.0'}

Reproduces the problem - code/configuration sample

python run.py --models hf_llama3_1_8b --datasets sanitized_mbpp_gen_742f0c --debug

Reproduces the problem - command or script

python run.py --models hf_llama3_1_8b --datasets sanitized_mbpp_gen_742f0c --debug

Reproduces the problem - error message

When I was testing the base model for llama3.1-8b, I found that using the config file in the official readme.md came out with a score of only 43.58, while llama3-8b-turbomind in the official readme.md came out with a score of 54.86, which is an excessive difference. What is the reason for this gap in scores?

Other information

No response