diff --git a/configs/unet_pet.yaml b/configs/unet_pet.yaml
index 2f3cc50e7e99ea7b8ff749d57f8319aa6b212a6f..a1781c5e8c4963ac269c4850f1012cc3d9ad8d15 100644
--- a/configs/unet_pet.yaml
+++ b/configs/unet_pet.yaml
@@ -30,13 +30,13 @@ MODEL:
     MODEL_NAME: "unet"
     DEFAULT_NORM_TYPE: "bn"
 TEST:
-    TEST_MODEL: "./test/saved_model/unet_pet/final/"
+    TEST_MODEL: "./saved_model/unet_pet/final/"
 TRAIN:
-    MODEL_SAVE_DIR: "./test/saved_models/unet_pet/"
-    PRETRAINED_MODEL_DIR: "./test/models/unet_coco/"
+    MODEL_SAVE_DIR: "./saved_model/unet_pet/"
+    PRETRAINED_MODEL_DIR: "./pretrained_model/unet_bn_coco/"
     SNAPSHOT_EPOCH: 10
 SOLVER:
-    NUM_EPOCHS: 500
+    NUM_EPOCHS: 100
     LR: 0.005
     LR_POLICY: "poly"
     OPTIMIZER: "adam"
diff --git a/test/configs/deeplabv3p_xception65_cityscapes.yaml b/test/configs/deeplabv3p_xception65_cityscapes.yaml
index 349646f743f10c7970b248b30c258574c8478c68..111452fb3e240409cfc18cc684a03f71746589c7 100644
--- a/test/configs/deeplabv3p_xception65_cityscapes.yaml
+++ b/test/configs/deeplabv3p_xception65_cityscapes.yaml
@@ -31,10 +31,10 @@ MODEL:
         ASPP_WITH_SEP_CONV: True
         DECODER_USE_SEP_CONV: True
 TEST:
-    TEST_MODEL: "snapshots/cityscape_v5/final/"
+    TEST_MODEL: "./saved_model/cityscape_v5/final/"
 TRAIN:
-    MODEL_SAVE_DIR: "snapshots/cityscape_v5/"
-    PRETRAINED_MODEL_DIR: "pretrain/deeplabv3plus_gn_init"
+    MODEL_SAVE_DIR: "./saved_model/cityscape_v5/"
+    PRETRAINED_MODEL_DIR: "pretrained_model/deeplabv3plus_gn_init"
     SNAPSHOT_EPOCH: 10
 SOLVER:
     LR: 0.001
diff --git a/test/configs/unet_pet.yaml b/test/configs/unet_pet.yaml
index c81d28513fd84198c85b479107c355a890e96e92..b39b9386d55847f393a9826f147eb41066f42c4f 100644
--- a/test/configs/unet_pet.yaml
+++ b/test/configs/unet_pet.yaml
@@ -12,15 +12,15 @@ AUG:
     MIN_SCALE_FACTOR: 0.75  # for stepscaling
     SCALE_STEP_SIZE: 0.25  # for stepscaling
     MIRROR: True
-BATCH_SIZE: 6
+BATCH_SIZE: 4
 DATASET:
     DATA_DIR: "./dataset/mini_pet/"
     IMAGE_TYPE: "rgb"  # choice rgb or rgba
-    NUM_CLASSES: 4 # including ignore
+    NUM_CLASSES: 3
     TEST_FILE_LIST: "./dataset/mini_pet/file_list/test_list.txt"
     TRAIN_FILE_LIST: "./dataset/mini_pet/file_list/train_list.txt"
     VAL_FILE_LIST: "./dataset/mini_pet/file_list/val_list.txt"
-    VIS_FILE_LIST: "./dataset/mini_pet/file_list/val_list.txt"
+    VIS_FILE_LIST: "./dataset/mini_pet/file_list/test_list.txt"
     IGNORE_INDEX: 255
     SEPARATOR: " "
 FREEZE:
@@ -30,13 +30,13 @@ MODEL:
     MODEL_NAME: "unet"
     DEFAULT_NORM_TYPE: "bn"
 TEST:
-    TEST_MODEL: "./test/saved_model/unet_pet/final/"
+    TEST_MODEL: "./saved_model/unet_pet/final/"
 TRAIN:
-    MODEL_SAVE_DIR: "./test/saved_model/unet_pet/"
-    PRETRAINED_MODEL_DIR: "./test/models/unet_coco/"
+    MODEL_SAVE_DIR: "./saved_model/unet_pet/"
+    PRETRAINED_MODEL_DIR: "./test/models/unet_coco_init/"
     SNAPSHOT_EPOCH: 10
 SOLVER:
-    NUM_EPOCHS: 500
+    NUM_EPOCHS: 100
     LR: 0.005
     LR_POLICY: "poly"
     OPTIMIZER: "adam"