diff --git a/official/recommend/deepfm/README.md b/official/recommend/deepfm/README.md
index 1609fbbf01c43a117b5f5952b7e80cf5b354ca2f..31f1bea9060d34e7f71afa75c1d7516451288f53 100644
--- a/official/recommend/deepfm/README.md
+++ b/official/recommend/deepfm/README.md
@@ -220,8 +220,6 @@ After installing MindSpore via the official website, you can start training and
 
 - Export on ModelArts (If you want to run in modelarts, please check the official documentation of [modelarts](https://support.huaweicloud.com/modelarts/), and you can start evaluating as follows)
 
-1. Export s8 multiscale and flip with voc val dataset on modelarts, evaluating steps are as follows:
-
     ```python
     # (1) Perform a or b.
     #       a. Set "enable_modelarts=True" on base_config.yaml file.
diff --git a/official/recommend/deepfm/README_CN.md b/official/recommend/deepfm/README_CN.md
index b47d7bfee208802d2f9de8601979f017b093aa55..a1b102f4a42db026a867271f81c5973cb8b36f99 100644
--- a/official/recommend/deepfm/README_CN.md
+++ b/official/recommend/deepfm/README_CN.md
@@ -204,8 +204,6 @@ FM和深度学习部分拥有相同的输入原样特征向量，让DeepFM能从
 
 - 在 ModelArts 进行导出 (如果你想在modelarts上运行，可以参考以下文档 [modelarts](https://support.huaweicloud.com/modelarts/))
 
-1. 使用voc val数据集评估多尺度和翻转s8。评估步骤如下：
-
     ```python
     # (1) 执行 a 或者 b.
     #       a. 在 base_config.yaml 文件中设置 "enable_modelarts=True"