diff --git a/configs/mobilenet_v2/README.md b/configs/mobilenet_v2/README.md
index 89f4d76f91..8470b9254f 100644
--- a/configs/mobilenet_v2/README.md
+++ b/configs/mobilenet_v2/README.md
@@ -44,7 +44,7 @@ The MobileNetV2 architecture is based on an inverted residual structure where th
 | DeepLabV3  | M-V2-D8  | 512x1024  |   80000 |      3.9 | 8.4            | 73.84 | -             | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/mobilenet_v2/deeplabv3_m-v2-d8_512x1024_80k_cityscapes.py)     | [model](https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3_m-v2-d8_512x1024_80k_cityscapes/deeplabv3_m-v2-d8_512x1024_80k_cityscapes_20200825_124836-bef03590.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3_m-v2-d8_512x1024_80k_cityscapes/deeplabv3_m-v2-d8_512x1024_80k_cityscapes-20200825_124836.log.json)                 |
 | DeepLabV3+ | M-V2-D8  | 512x1024  |   80000 |      5.1 | 8.4            | 75.20 | -             | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/mobilenet_v2/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes_20200825_124836-d256dd4b.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes-20200825_124836.log.json) |
 
-### ADE20k
+### ADE20K
 
 | Method     | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) |  mIoU | mIoU(ms+flip) | config                                                                                                                               | download                                                                                                                                                                                                                                                                                                                                                                             |
 | ---------- | -------- | --------- | ------: | -------: | -------------- | ----: | ------------- | ------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
diff --git a/configs/mobilenet_v2/mobilenet_v2.yml b/configs/mobilenet_v2/mobilenet_v2.yml
index 57e0fe23f4..bb0ddd6d0d 100644
--- a/configs/mobilenet_v2/mobilenet_v2.yml
+++ b/configs/mobilenet_v2/mobilenet_v2.yml
@@ -3,7 +3,7 @@ Collections:
   Metadata:
     Training Data:
     - Cityscapes
-    - ADE20k
+    - ADE20K
   Paper:
     URL: https://arxiv.org/abs/1801.04381
     Title: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks'
@@ -114,7 +114,7 @@ Models:
     Training Memory (GB): 6.5
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 19.71
   Config: configs/mobilenet_v2/fcn_m-v2-d8_512x512_160k_ade20k.py
@@ -135,7 +135,7 @@ Models:
     Training Memory (GB): 6.5
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 29.68
   Config: configs/mobilenet_v2/pspnet_m-v2-d8_512x512_160k_ade20k.py
@@ -156,7 +156,7 @@ Models:
     Training Memory (GB): 6.8
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 34.08
   Config: configs/mobilenet_v2/deeplabv3_m-v2-d8_512x512_160k_ade20k.py
@@ -177,7 +177,7 @@ Models:
     Training Memory (GB): 8.2
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 34.02
   Config: configs/mobilenet_v2/deeplabv3plus_m-v2-d8_512x512_160k_ade20k.py
diff --git a/configs/resnest/README.md b/configs/resnest/README.md
index 085cb4f22b..9e93a2d22d 100644
--- a/configs/resnest/README.md
+++ b/configs/resnest/README.md
@@ -42,7 +42,7 @@ year={2020}
 | DeepLabV3  | S-101-D8 | 512x1024  |   80000 |     11.9 | 1.88           | 79.67 | 80.51         | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/resnest/deeplabv3_s101-d8_512x1024_80k_cityscapes.py)     | [model](https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3_s101-d8_512x1024_80k_cityscapes/deeplabv3_s101-d8_512x1024_80k_cityscapes_20200807_144429-b73c4270.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3_s101-d8_512x1024_80k_cityscapes/deeplabv3_s101-d8_512x1024_80k_cityscapes-20200807_144429.log.json)                 |
 | DeepLabV3+ | S-101-D8 | 512x1024  |   80000 |     13.2 | 2.36           | 79.62 | 80.27         | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/resnest/deeplabv3plus_s101-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3plus_s101-d8_512x1024_80k_cityscapes/deeplabv3plus_s101-d8_512x1024_80k_cityscapes_20200807_144429-1239eb43.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3plus_s101-d8_512x1024_80k_cityscapes/deeplabv3plus_s101-d8_512x1024_80k_cityscapes-20200807_144429.log.json) |
 
-### ADE20k
+### ADE20K
 
 | Method     | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) |  mIoU | mIoU(ms+flip) | config                                                                                                                          | download                                                                                                                                                                                                                                                                                                                                                                   |
 | ---------- | -------- | --------- | ------: | -------: | -------------- | ----: | ------------- | ------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
diff --git a/configs/resnest/resnest.yml b/configs/resnest/resnest.yml
index 6a4fc5a45e..cd92409471 100644
--- a/configs/resnest/resnest.yml
+++ b/configs/resnest/resnest.yml
@@ -3,7 +3,7 @@ Collections:
   Metadata:
     Training Data:
     - Cityscapes
-    - ADE20k
+    - ADE20K
   Paper:
     URL: https://arxiv.org/abs/2004.08955
     Title: 'ResNeSt: Split-Attention Networks'
@@ -118,7 +118,7 @@ Models:
     Training Memory (GB): 14.2
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 45.62
       mIoU(ms+flip): 46.16
@@ -140,7 +140,7 @@ Models:
     Training Memory (GB): 14.2
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 45.44
       mIoU(ms+flip): 46.28
@@ -162,7 +162,7 @@ Models:
     Training Memory (GB): 14.6
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 45.71
       mIoU(ms+flip): 46.59
@@ -184,7 +184,7 @@ Models:
     Training Memory (GB): 16.2
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 46.47
       mIoU(ms+flip): 47.27
diff --git a/configs/segformer/README.md b/configs/segformer/README.md
index 895f115708..e82be55a88 100644
--- a/configs/segformer/README.md
+++ b/configs/segformer/README.md
@@ -45,7 +45,7 @@ This script convert model from `PRETRAIN_PATH` and store the converted model in
 
 ## Results and models
 
-### ADE20k
+### ADE20K
 
 | Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
 | ------ | -------- | --------- | ------: | -------: | -------------- | ---: | ------------- | ------ | -------- |
diff --git a/configs/segformer/segformer.yml b/configs/segformer/segformer.yml
index d60db0065c..df46d5260c 100644
--- a/configs/segformer/segformer.yml
+++ b/configs/segformer/segformer.yml
@@ -2,7 +2,7 @@ Collections:
 - Name: segformer
   Metadata:
     Training Data:
-    - ADE20k
+    - ADE20K
   Paper:
     URL: https://arxiv.org/abs/2105.15203
     Title: resize image to multiple of 32, improve SegFormer by 0.5-1.0 mIoU.
@@ -29,7 +29,7 @@ Models:
     Training Memory (GB): 2.1
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 37.41
       mIoU(ms+flip): 38.34
@@ -51,7 +51,7 @@ Models:
     Training Memory (GB): 2.6
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 40.97
       mIoU(ms+flip): 42.54
@@ -73,7 +73,7 @@ Models:
     Training Memory (GB): 3.6
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 45.58
       mIoU(ms+flip): 47.03
@@ -95,7 +95,7 @@ Models:
     Training Memory (GB): 4.8
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 47.82
       mIoU(ms+flip): 48.81
@@ -117,7 +117,7 @@ Models:
     Training Memory (GB): 6.1
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 48.46
       mIoU(ms+flip): 49.76
@@ -139,7 +139,7 @@ Models:
     Training Memory (GB): 7.2
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 49.13
       mIoU(ms+flip): 50.22
@@ -161,7 +161,7 @@ Models:
     Training Memory (GB): 11.5
   Results:
   - Task: Semantic Segmentation
-    Dataset: ADE20k
+    Dataset: ADE20K
     Metrics:
       mIoU: 49.62
       mIoU(ms+flip): 50.36