diff --git a/01.fit_a_line/README.cn.md b/01.fit_a_line/README.cn.md
index 87ab88516317c42a6a2d63c7ae033665dac07834..936142bfbc427fa085797f2e62b136709e085405 100644
--- a/01.fit_a_line/README.cn.md
+++ b/01.fit_a_line/README.cn.md
@@ -142,6 +142,15 @@ def train_program():
     return avg_loss
 ```
 
+### Optimizer Function 配置
+
+在下面的 `SGD optimizer`，`learning_rate` 是训练的速度，与网络的训练收敛速度有关系。
+
+```python
+def optimizer_program():
+    return fluid.optimizer.SGD(learning_rate=0.001)
+```
+
 ### 定义运算场所
 我们可以定义运算是发生在CPU还是GPU
 
@@ -157,7 +166,7 @@ place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 trainer = fluid.Trainer(
     train_func=train_program,
     place=place,
-    optimizer_func=fluid.optimizer.SGD(learning_rate=0.001))
+    optimizer_func=optimizer_program)
 ```
 
 ### 开始提供数据
diff --git a/01.fit_a_line/README.md b/01.fit_a_line/README.md
index df624f9d31c12ded1fac62e18b220c16659621c2..e672caf1206b13b50abbd57eb2fc465fb656cce1 100644
--- a/01.fit_a_line/README.md
+++ b/01.fit_a_line/README.md
@@ -149,6 +149,14 @@ def train_program():
     return avg_loss
 ```
 
+### Optimizer Function Configuration
+
+In the following `SGD` optimizer, `learning_rate` specifies the learning rate in the optimization procedure.
+
+```python
+def optimizer_program():
+    return fluid.optimizer.SGD(learning_rate=0.001)
+```
 
 ### Specify Place
 Specify your training environment, you should specify if the training is on CPU or GPU.
@@ -165,7 +173,7 @@ The trainer will take the `train_program` as input.
 trainer = fluid.Trainer(
     train_func=train_program,
     place=place,
-    optimizer_func=fluid.optimizer.SGD(learning_rate=0.001))
+    optimizer_func=optimizer_program)
 ```
 
 ### Feeding Data