[Bug] The ifeval evaluation on 541 cases returns unexpected low score.

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

from opencompass.models import VLLMwithChatTemplate

models = [
dict(
type=VLLMwithChatTemplate,
abbr='qwa-32b',
path='path to QwQ-32B',
model_kwargs=dict(tensor_parallel_size=4),
max_out_len=32768,
max_seq_len=131072,
batch_size=4,
generation_kwargs=dict(temperature=0),
run_cfg=dict(num_gpus=4),
)
]

Reproduces the problem - code/configuration sample

export CUDA_VISIBLE_DEVICES=0,1,2,3

export CUDA_VISIBLE_DEVICES=1,2,3,6
export VLLM_WORKER_MULTIPROC_METHOD=spawn
nohup python3 run.py --models vllm_qwq_32b_preview --datasets IFEval_gen_3321a3 --debug >lmd2.log 2>&1 &

Reproduces the problem - command or script

from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.datasets import IFEvalDataset, IFEvaluator

ifeval_reader_cfg = dict(
input_columns=['prompt'], output_column='reference')

ifeval_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(round=[
dict(
role='HUMAN',
prompt='{prompt}'),
])),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=32768))

ifeval_eval_cfg = dict(
evaluator=dict(type=IFEvaluator),
pred_role='BOT',
)

ifeval_datasets = [
dict(
abbr='IFEval',
type=IFEvalDataset,
path='data/ifeval/ifeval.jsonl',
reader_cfg=ifeval_reader_cfg,
infer_cfg=ifeval_infer_cfg,
eval_cfg=ifeval_eval_cfg)
]

Reproduces the problem - error message

raw format
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Model: qwa-32b
IFEval: {'Prompt-level-strict-accuracy': 34.011090573012936, 'Inst-level-strict-accuracy': 48.80095923261391, 'Prompt-level-loose-accuracy': 37.52310536044362, 'Inst-level-loose-accuracy': 52.15827338129496}

Other information

Do you know where is the problem, as qwq-32b official score on the ifeval dataset is something 83+. BTW, I'm using the ifeval dataset from source https://huggingface.co/datasets/google/IFEval