diff --git a/TensorFlow/contrib/cv/MEAN-TEACHER_ID0789_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/contrib/cv/MEAN-TEACHER_ID0789_for_TensorFlow/test/train_full_1p.sh
index 59315a88024f710357be60838d75cf1f0d8f0413..13c24e67ab497c96b35e5b1a42a30d870aed0f01 100644
--- a/TensorFlow/contrib/cv/MEAN-TEACHER_ID0789_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/contrib/cv/MEAN-TEACHER_ID0789_for_TensorFlow/test/train_full_1p.sh
@@ -124,9 +124,12 @@ e2e_time=$(( $end_time - $start_time ))
 
 #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
+#输出TrainingTime，需要模型审视修改
 TrainingTime=`grep "Perf: " $cur_path/test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log |awk 'END {print $11}'`
-
+#输出FPS
+FPS=`awk 'BEGIN{printf "%.2f\n", '${batch_size}'/'${TrainingTime}'}'`
+#打印，不需要修改
+echo "Final Performance images/sec : $FPS"
 
 #性能看护结果汇总
 #训练用例信息，不需要修改
@@ -136,10 +139,12 @@ CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'perf'
 
 ##获取性能数据，不需要修改
 #吞吐量
-ActualFPS=`awk 'BEGIN{printf "%.2f\n", '${batch_size}'/'${TrainingTime}'}'`
-
+ActualFPS=${FPS}
 #获取模型精度，该网络为错误率
-train_accuracy=`grep "train/error" $cur_path/test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log |awk 'END {print $5}'|sed 's/,//g'|sed 's/%//g'`
+train_accuracy=`grep "eval/error/ema:" $cur_path/test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log | awk 'END {print $1}' | tr -d "%,"`
+#打印，不需要修改
+echo "Final Train Accuracy : ${train_accuracy}"
+echo "Final Training Duration sec : $e2etime"
 
 #从train_$ASCEND_DEVICE_ID.log提取Loss到train_${CaseName}_loss.txt中，需要根据模型审视
 grep 'train/class_cost' $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log|awk '{print $7}'|sed 's/,//g'|sed 's/%//g' > $cur_path/test/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt