diff --git a/config.py b/config.py
index f952f15..302d0f5 100644
--- a/config.py
+++ b/config.py
@@ -36,6 +36,7 @@ def add_argument_group(name):
 train_arg.add_argument('--lr_update_step', type=int, default=100000, choices=[100000, 75000])
 train_arg.add_argument('--d_lr', type=float, default=0.00008)
 train_arg.add_argument('--g_lr', type=float, default=0.00008)
+train_arg.add_argument('--lr_lower_boundary', type=float, default=0.00002)
 train_arg.add_argument('--beta1', type=float, default=0.5)
 train_arg.add_argument('--beta2', type=float, default=0.999)
 train_arg.add_argument('--gamma', type=float, default=0.5)
diff --git a/trainer.py b/trainer.py
index 7d33825..3fd8868 100644
--- a/trainer.py
+++ b/trainer.py
@@ -62,8 +62,8 @@ def __init__(self, config, data_loader):
         self.g_lr = tf.Variable(config.g_lr, name='g_lr')
         self.d_lr = tf.Variable(config.d_lr, name='d_lr')
 
-        self.g_lr_update = tf.assign(self.g_lr, self.g_lr * 0.5, name='g_lr_update')
-        self.d_lr_update = tf.assign(self.d_lr, self.d_lr * 0.5, name='d_lr_update')
+        self.g_lr_update = tf.assign(self.g_lr, tf.maximum(self.g_lr * 0.5, config.lr_lower_boundary), name='g_lr_update')
+        self.d_lr_update = tf.assign(self.d_lr, tf.maximum(self.d_lr * 0.5, config.lr_lower_boundary), name='d_lr_update')
 
         self.gamma = config.gamma
         self.lambda_k = config.lambda_k