使用baichuan-7b评估humaneval数据与榜单差距过大

[zh190920]

先决条件

• 我已经搜索过 问题 和 讨论 但未得到预期的帮助。
• 错误在 最新版本 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

[zh190920]

@hzhwcmhf @x22x22 @Sanster Looking forward to your reply

[PJY-coder]

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。