diff --git a/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_16p.sh b/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_16p.sh
index 535b97995ec8b66ee0d70b6bbf38a0ec1c6c30aa..b9039d7334ab2c0896036ef3c412245881470c3e 100644
--- a/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_16p.sh
+++ b/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_16p.sh
@@ -74,8 +74,6 @@ if [[ $data_path  == "" ]];then
 
 fi
 
-sed -i "s|checkpoint_utils.save_checkpoint(|#checkpoint_utils.save_checkpoint(|g" $cur_path/../fairseq_cli/train.py
-
 	export HCCL_IF_IP=$fix_node_ip
 export MASTER_ADDR=$one_node_ip
 export MASTER_PORT=29688
@@ -195,5 +193,3 @@ echo "ActualFPS = ${ActualWPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-
-sed -i "s|#checkpoint_utils.save_checkpoint(|checkpoint_utils.save_checkpoint(|g" $cur_path/../fairseq_cli/train.py
diff --git a/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_1p.sh b/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_1p.sh
index d4a0781b2ab7e849aed81865f255273983d5b5c5..c49ed97ca1f01bbdc9f21525ec9d44a9550926aa 100644
--- a/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_1p.sh
+++ b/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_1p.sh
@@ -89,7 +89,6 @@ if [ x"${etp_flag}" != x"true" ];then
     source ${test_path_dir}/env_npu.sh
 fi
 
-sed -i "s|checkpoint_utils.save_checkpoint(|#checkpoint_utils.save_checkpoint(|g" $cur_path/fairseq_cli/train.py
 #创建DeviceID输出目录，不需要修改
 if [ -d $cur_path/test/output ];then
 	rm -rf $cur_path/test/output/*
@@ -123,7 +122,6 @@ wait
 end=$(date +%s)
 e2e_time=$(( $end - $start ))
 
-sed -i "s|#checkpoint_utils.save_checkpoint(|checkpoint_utils.save_checkpoint(|g" $cur_path/fairseq_cli/train.py
 #结果打印，不需要修改
 echo "------------------ Final result ------------------"
 #输出性能FPS，需要模型审视修改
diff --git a/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_8p.sh b/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_8p.sh
index 59bd2fdf09485a26757a3e6e5c7e09a92bc0d57d..efb84210516d363cb0a768e95a2cd62da6237952 100644
--- a/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_8p.sh
+++ b/PyTorch/built-in/nlp/mBART_ID2372_for_PyTorch/test/train_performance_8p.sh
@@ -71,7 +71,6 @@ if [[ $data_path  == "" ]];then
 	exit 1
 fi
 
-sed -i "s|checkpoint_utils.save_checkpoint(|#checkpoint_utils.save_checkpoint(|g" $cur_path/fairseq_cli/train.py
 ##################创建日志输出目录，根据模型审视##################
 # 模型采用非循环方式启动多卡训练，创建日志输出目录如下；采用循环方式启动多卡训练的模型，在循环中创建日志输出目录，可参考CRNN模型
 # 非循环方式下8卡训练日志输出路径中的ASCEND_DEVICE_ID默认为0，只是人为指定文件夹名称， 不涉及训练业务
@@ -195,5 +194,3 @@ echo "ActualFPS = ${ActualWPS}" >> ${test_path_dir}/output/$ASCEND_DEVICE_ID/${C
 echo "TrainingTime = ${TrainingTime}" >> ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "E2ETrainingTime = ${e2e_time}" >> ${test_path_dir}/output/$ASCEND_DEVICE_ID/${CaseName}.log
-
-sed -i "s|#checkpoint_utils.save_checkpoint(|checkpoint_utils.save_checkpoint(|g" $cur_path/fairseq_cli/train.py
\ No newline at end of file