diff --git a/examples/workflow_by_code_gats.py b/examples/workflow_by_code_gats.py
index 984c1755a..20f3ae552 100644
--- a/examples/workflow_by_code_gats.py
+++ b/examples/workflow_by_code_gats.py
@@ -61,9 +61,9 @@ if __name__ == "__main__":
                 "d_feat": 6,
                 "hidden_size": 64,
                 "num_layers": 2,
-                "dropout": 0.0,
+                "dropout": 0.7,
                 "n_epochs": 200,
-                "lr": 1e-3,
+                "lr": 1e-4,
                 "early_stop": 20,
                 "metric": "loss",
                 "loss": "mse",
diff --git a/examples/workflow_by_code_hats.py b/examples/workflow_by_code_hats.py
index 192d97ee3..64bc860b4 100644
--- a/examples/workflow_by_code_hats.py
+++ b/examples/workflow_by_code_hats.py
@@ -58,11 +58,11 @@ if __name__ == "__main__":
                 "d_feat": 6,
                 "hidden_size": 64,
                 "num_layers": 2,
-                "dropout": 0.6,
+                "dropout": 0.7,
                 "n_epochs": 200,
-                "lr": 1e-3,
+                "lr": 1e-4,
                 "early_stop": 20,
-                "metric": "IC",
+                "metric": "loss",
                 "loss": "mse",
                 "base_model": "LSTM",
                 "seed": 0,
diff --git a/qlib/contrib/model/pytorch_gats.py b/qlib/contrib/model/pytorch_gats.py
index 5d2dbd9a4..d951f1873 100755
--- a/qlib/contrib/model/pytorch_gats.py
+++ b/qlib/contrib/model/pytorch_gats.py
@@ -43,13 +43,13 @@ class GAT(Model):
         d_feat=6,
         hidden_size=64,
         num_layers=2,
-        dropout=0.0,
+        dropout=0.7,
         n_epochs=200,
-        lr=0.001,
-        metric="IC",
+        lr=0.0001,
+        metric="loss",
         early_stop=20,
         loss="mse",
-        base_model="GRU",
+        base_model="LSTM",
         with_pretrain=True,
         optimizer="adam",
         GPU="0",
@@ -174,7 +174,7 @@ class GAT(Model):
     def train_epoch(self, x_train, y_train):
 
         x_train_values = x_train.values
-        y_train_values = np.squeeze(y_train.values) * 100
+        y_train_values = np.squeeze(y_train.values)
         self.GAT_model.train()
 
         # organize the train data into daily inter as daily batches
diff --git a/qlib/contrib/model/pytorch_hats.py b/qlib/contrib/model/pytorch_hats.py
index bdb68be28..1eff35203 100644
--- a/qlib/contrib/model/pytorch_hats.py
+++ b/qlib/contrib/model/pytorch_hats.py
@@ -52,11 +52,11 @@ class HATS(Model):
         num_layers=2,
         dropout=0.5,
         n_epochs=200,
-        lr=0.01,
-        metric="IC",
+        lr=0.0001,
+        metric="loss",
         early_stop=20,
         loss="mse",
-        base_model="GRU",
+        base_model="LSTM",
         with_pretrain=True,
         optimizer="adam",
         GPU="0",
@@ -180,7 +180,7 @@ class HATS(Model):
     def train_epoch(self, x_train, y_train):
 
         x_train_values = x_train.values
-        y_train_values = np.squeeze(y_train.values) * 100
+        y_train_values = np.squeeze(y_train.values) 
 
         self.HATS_model.train()
 
diff --git a/qlib/contrib/model/pytorch_lstm.py b/qlib/contrib/model/pytorch_lstm.py
index be43d3698..22cc21e7f 100755
--- a/qlib/contrib/model/pytorch_lstm.py
+++ b/qlib/contrib/model/pytorch_lstm.py
@@ -46,7 +46,7 @@ class LSTM(Model):
         dropout=0.0,
         n_epochs=200,
         lr=0.001,
-        metric="IC",
+        metric="loss",
         batch_size=2000,
         early_stop=20,
         loss="mse",
@@ -154,7 +154,7 @@ class LSTM(Model):
     def train_epoch(self, x_train, y_train):
 
         x_train_values = x_train.values
-        y_train_values = np.squeeze(y_train.values) * 100
+        y_train_values = np.squeeze(y_train.values)
 
         self.lstm_model.train()