diff --git a/official/cv/yolov3_darknet53_quant/README.md b/official/cv/yolov3_darknet53_quant/README.md
index ad2bff29e36375722a9b66e9a40c2d60d99aabf2..7b9fe87b09d908cc40036548ea7b082f63e5d051 100644
--- a/official/cv/yolov3_darknet53_quant/README.md
+++ b/official/cv/yolov3_darknet53_quant/README.md
@@ -201,7 +201,7 @@ optional arguments:
 bash run_distribute_train.sh dataset/coco2014 yolov3_darknet53_noquant.ckpt rank_table_8p.json
 ```
 
-The above shell script will run distribute training in the background. You can view the results through the file `train_parallel[X]/log.txt`. The loss value will be achieved as follows:
+The above shell script will run distribute training in the background. You can view the results through the file `train_parallel0/log.txt`. The loss value will be achieved as follows:
 
 ```bash
 # distribute training result(8p)
diff --git a/official/cv/yolov3_darknet53_quant/README_CN.md b/official/cv/yolov3_darknet53_quant/README_CN.md
index ff0f48692f37405787cd17dd159caab1ed4316e9..0703b4ab79fdf5cbcab8618104cda887f8fc69cc 100644
--- a/official/cv/yolov3_darknet53_quant/README_CN.md
+++ b/official/cv/yolov3_darknet53_quant/README_CN.md
@@ -208,7 +208,7 @@ train.py中主要参数如下：
 bash run_distribute_train.sh dataset/coco2014 yolov3_darknet53_noquant.ckpt rank_table_8p.json
 ```
 
-上述shell脚本将在后台运行分布训练。您可以通过`train_parallel[X]/log.txt`文件查看结果。损失值的实现如下：
+上述shell脚本将在后台运行分布训练。您可以通过`train_parallel0/log.txt`文件查看结果。损失值的实现如下：
 
 ```text
 # 分布式训练示例(8卡)