diff --git a/configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml b/configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml
index acf438950a43af3356c7ab0aadf956fdf226814e..0c6ab2a0d1d9733d647dc40a7b182fe201866a78 100644
--- a/configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml
+++ b/configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml
@@ -191,7 +191,6 @@ Eval:
           channel_first: False
       - DetLabelEncode: # Class handling label
       - DetResizeForTest:
-#           image_shape: [736, 1280]
       - NormalizeImage:
           scale: 1./255.
           mean: [0.485, 0.456, 0.406]
diff --git a/configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml b/configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml
index ef58befd694e26704c734d7fd072ebc3370c8554..000d95e892cb8e6dcceeb7c22264c28934d1000c 100644
--- a/configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml
+++ b/configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml
@@ -24,6 +24,7 @@ Architecture:
   model_type: det
   Models:
     Student:
+      pretrained:
       model_type: det
       algorithm: DB
       Transform: null
@@ -40,6 +41,7 @@ Architecture:
         name: DBHead
         k: 50
     Student2:
+      pretrained:
       model_type: det
       algorithm: DB
       Transform: null
@@ -91,14 +93,11 @@ Loss:
       - ["Student", "Student2"]
       maps_name: "thrink_maps"
       weight: 1.0
-      # act: None
       model_name_pairs: ["Student", "Student2"]
       key: maps
   - DistillationDBLoss:
       weight: 1.0
       model_name_list: ["Student", "Student2"]
-      # key: maps
-      # name: DBLoss
       balance_loss: true
       main_loss_type: DiceLoss
       alpha: 5
@@ -197,6 +196,7 @@ Train:
     drop_last: false
     batch_size_per_card: 8
     num_workers: 4
+
 Eval:
   dataset:
     name: SimpleDataSet
@@ -204,31 +204,21 @@ Eval:
     label_file_list:
       - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt
     transforms:
-    - DecodeImage:
-        img_mode: BGR
-        channel_first: false
-    - DetLabelEncode: null
-    - DetResizeForTest: null
-    - NormalizeImage:
-        scale: 1./255.
-        mean:
-        - 0.485
-        - 0.456
-        - 0.406
-        std:
-        - 0.229
-        - 0.224
-        - 0.225
-        order: hwc
-    - ToCHWImage: null
-    - KeepKeys:
-        keep_keys:
-        - image
-        - shape
-        - polys
-        - ignore_tags
+      - DecodeImage: # load image
+          img_mode: BGR
+          channel_first: False
+      - DetLabelEncode: # Class handling label
+      - DetResizeForTest:
+      - NormalizeImage:
+          scale: 1./255.
+          mean: [0.485, 0.456, 0.406]
+          std: [0.229, 0.224, 0.225]
+          order: 'hwc'
+      - ToCHWImage:
+      - KeepKeys:
+          keep_keys: ['image', 'shape', 'polys', 'ignore_tags']
   loader:
-    shuffle: false
-    drop_last: false
-    batch_size_per_card: 1
-    num_workers: 2
+    shuffle: False
+    drop_last: False
+    batch_size_per_card: 1 # must be 1
+    num_workers: 2
\ No newline at end of file
diff --git a/ppocr/losses/basic_loss.py b/ppocr/losses/basic_loss.py
index da9faa08bc5ca35c5d65f7a7bfbbdd67192f052b..58410b4db2157074c2cb0f7db590c84021e10ace 100644
--- a/ppocr/losses/basic_loss.py
+++ b/ppocr/losses/basic_loss.py
@@ -60,19 +60,19 @@ class KLJSLoss(object):
                         ], "mode can only be one of ['kl', 'KL', 'js', 'JS']"
         self.mode = mode
 
-    def __call__(self, p1, p2, reduction="mean"):
+    def __call__(self, p1, p2, reduction="mean", eps=1e-5):
 
         if self.mode.lower() == 'kl':
             loss = paddle.multiply(p2,
-                                   paddle.log((p2 + 1e-5) / (p1 + 1e-5) + 1e-5))
-            loss += paddle.multiply(
-                p1, paddle.log((p1 + 1e-5) / (p2 + 1e-5) + 1e-5))
+                                   paddle.log((p2 + eps) / (p1 + eps) + eps))
+            loss += paddle.multiply(p1,
+                                    paddle.log((p1 + eps) / (p2 + eps) + eps))
             loss *= 0.5
         elif self.mode.lower() == "js":
             loss = paddle.multiply(
-                p2, paddle.log((2 * p2 + 1e-5) / (p1 + p2 + 1e-5) + 1e-5))
+                p2, paddle.log((2 * p2 + eps) / (p1 + p2 + eps) + eps))
             loss += paddle.multiply(
-                p1, paddle.log((2 * p1 + 1e-5) / (p1 + p2 + 1e-5) + 1e-5))
+                p1, paddle.log((2 * p1 + eps) / (p1 + p2 + eps) + eps))
             loss *= 0.5
         else:
             raise ValueError(