diff --git a/deepod/core/base_model.py b/deepod/core/base_model.py
index f4ea7dc..42d2d9a 100644
--- a/deepod/core/base_model.py
+++ b/deepod/core/base_model.py
@@ -6,7 +6,7 @@ some functions are adapted from the pyod library
 """
 import sys
 import warnings
-
+import pickle
 import numpy as np
 import torch
 import random
@@ -527,3 +527,12 @@ class BaseDeepAD(metaclass=ABCMeta):
         random.seed(seed)
         # torch.backends.cudnn.benchmark = False
         # torch.backends.cudnn.deterministic = True
+
+    @classmethod
+    def load_model(cls, path):
+        with open(f"{path}.pkl", mode="rb") as f:
+            return pickle.load(f)
+
+    def save_model(self, path):
+        with open(f"{path}.pkl", mode="wb") as f:
+            pickle.dump(self, f)
diff --git a/deepod/models/time_series/dcdetector.py b/deepod/models/time_series/dcdetector.py
index 6d80034..cb5784b 100644
--- a/deepod/models/time_series/dcdetector.py
+++ b/deepod/models/time_series/dcdetector.py
@@ -22,14 +22,15 @@ class DCdetector(BaseDeepAD):
                  n_heads=1, d_model=256, e_layers=3, patch_size=None,
                  verbose=2, random_state=42):
         super(DCdetector, self).__init__(
-            model_name='TranAD', data_type='ts', epochs=epochs, batch_size=batch_size, lr=lr,
+            model_name='DCdetector', data_type='ts', epochs=epochs, batch_size=batch_size, lr=lr,
             seq_len=seq_len, stride=stride,
             epoch_steps=epoch_steps, prt_steps=prt_steps, device=device,
             verbose=verbose, random_state=random_state
         )
         if patch_size is None:
             self.patch_size = [5]  # seq_len must be divisible by patch_size
-        self.patch_size = patch_size
+        else:
+            self.patch_size = patch_size
         self.n_heads = n_heads
         self.d_model = d_model
         self.e_layers = e_layers
diff --git a/testbed/testbed_unsupervised_tsad.py b/testbed/testbed_unsupervised_tsad.py
index a9eb3a4..ab335ca 100644
--- a/testbed/testbed_unsupervised_tsad.py
+++ b/testbed/testbed_unsupervised_tsad.py
@@ -23,14 +23,14 @@ parser.add_argument("--runs", type=int, default=5,
                          "obtain the average performance")
 parser.add_argument("--output_dir", type=str, default='@records/',
                     help="the output file path")
-parser.add_argument("--dataset", type=str, default='MSL',
+parser.add_argument("--dataset", type=str, default='ASD',
                     help='dataset name or a list of names split by comma')
 parser.add_argument("--entities", type=str,
-                    default='C-2',
+                    default='FULL',
                     help='FULL represents all the csv file in the folder, '
                          'or a list of entity names split by comma')
-parser.add_argument("--entity_combined", type=int, default=0)
-parser.add_argument("--model", type=str, default='COUTA', help="")
+parser.add_argument("--entity_combined", type=int, default=1)
+parser.add_argument("--model", type=str, default='DCdetector', help="")
 parser.add_argument("--auto_hyper", default=False, action='store_true', help="")
 
 parser.add_argument('--silent_header', action='store_true')