diff --git a/model_zoo/official/cv/maskrcnn/src/MaskRcnn/rcnn_cls.py b/model_zoo/official/cv/maskrcnn/src/MaskRcnn/rcnn_cls.py
index ac38b76334c99196058bff8911be5bb3768c5e64..e529f2e22b436231feadb1e94d7fa42f6f6f0195 100644
--- a/model_zoo/official/cv/maskrcnn/src/MaskRcnn/rcnn_cls.py
+++ b/model_zoo/official/cv/maskrcnn/src/MaskRcnn/rcnn_cls.py
@@ -113,7 +113,7 @@ class RcnnCls(nn.Cell):
         self.relu = P.ReLU()
         self.logicaland = P.LogicalAnd()
         self.loss_cls = P.SoftmaxCrossEntropyWithLogits()
-        self.loss_bbox = P.SmoothL1Loss(sigma=1.0)
+        self.loss_bbox = P.SmoothL1Loss(beta=1.0)
         self.loss_mask = P.SigmoidCrossEntropyWithLogits()
         self.reshape = P.Reshape()
         self.onehot = P.OneHot()
diff --git a/model_zoo/official/cv/maskrcnn/src/MaskRcnn/rpn.py b/model_zoo/official/cv/maskrcnn/src/MaskRcnn/rpn.py
index e06f8eb0dfc2090cb80f9d17fdf749236b58350c..bd86543c584757f923ec2ce3cef162dbab1059c8 100644
--- a/model_zoo/official/cv/maskrcnn/src/MaskRcnn/rpn.py
+++ b/model_zoo/official/cv/maskrcnn/src/MaskRcnn/rpn.py
@@ -137,7 +137,7 @@ class RPN(nn.Cell):
         self.CheckValid = P.CheckValid()
         self.sum_loss = P.ReduceSum()
         self.loss_cls = P.SigmoidCrossEntropyWithLogits()
-        self.loss_bbox = P.SmoothL1Loss(sigma=1.0/9.0)
+        self.loss_bbox = P.SmoothL1Loss(beta=1.0/9.0)
         self.squeeze = P.Squeeze()
         self.cast = P.Cast()
         self.tile = P.Tile()
diff --git a/model_zoo/official/cv/maskrcnn/src/config.py b/model_zoo/official/cv/maskrcnn/src/config.py
index 97028c782ed85325df8b170c35bc16e25da582b4..e1bf13c891aafc3517d2475461dea8dc19727c7c 100644
--- a/model_zoo/official/cv/maskrcnn/src/config.py
+++ b/model_zoo/official/cv/maskrcnn/src/config.py
@@ -20,7 +20,7 @@ from easydict import EasyDict as ed
 config = ed({
     "img_width": 1280,
     "img_height": 768,
-    "keep_ratio": False,
+    "keep_ratio": True,
     "flip_ratio": 0.5,
     "photo_ratio": 0.5,
     "expand_ratio": 1.0,
@@ -138,7 +138,7 @@ config = ed({
     "epoch_size": 12,
     "save_checkpoint": True,
     "save_checkpoint_epochs": 1,
-    "keep_checkpoint_max": 10,
+    "keep_checkpoint_max": 12,
     "save_checkpoint_path": "./checkpoint",
 
     "mindrecord_dir": "/home/mxw/mask_rcnn/scripts/MindRecord_COCO2017_Train",