[Feature]: Update MAE 300e pt results (#722)

open-mmlab · Mar 22, 2023 · 105ca79 · 105ca79
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diff --git a/configs/selfsup/mae/README.md b/configs/selfsup/mae/README.md
@@ -54,7 +54,7 @@ methods that use only ImageNet-1K data. Transfer performance in downstream tasks
 	    <td>300</td>
       <td>4096</td>
       <td>60.8</td>
-      <td>83.1</td>
+      <td>82.8</td>
       <td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/mae_vit-base-p16_8xb512-coslr-300e-fp16_in1k_20220829-c2cf66ba.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/mae_vit-base-p16_8xb512-coslr-300e-fp16_in1k_20220718_152424.json'>log</a></td>
       <td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k_20220720_104514.json'>log</a></td>
       <td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220713_140138.json'>log</a></td>

diff --git a/configs/selfsup/mae/metafile.yml b/configs/selfsup/mae/metafile.yml
@@ -40,7 +40,7 @@ Models:
           - Task: Fine-tuning
             Dataset: ImageNet-1k
             Metrics:
-              Top 1 Accuracy: 83.1
+              Top 1 Accuracy: 82.8
         Config: configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py
   - Name: mae_vit-base-p16_8xb512-coslr-400e_in1k
     In Collection: MAE

diff --git a/docs/en/model_zoo.md b/docs/en/model_zoo.md
@@ -238,7 +238,7 @@ ImageNet has multiple versions, but the most commonly used one is ILSVRC 2012. T
 	    <td>300</td>
       <td>4096</td>
       <td>60.8</td>
-      <td>83.1</td>
+      <td>82.8</td>
       <td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/mae_vit-base-p16_8xb512-coslr-300e-fp16_in1k_20220829-c2cf66ba.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/mae_vit-base-p16_8xb512-coslr-300e-fp16_in1k_20220718_152424.json'>log</a></td>
       <td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k_20220720_104514.json'>log</a></td>
       <td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220713_140138.json'>log</a></td>

diff --git a/docs/zh_cn/model_zoo.md b/docs/zh_cn/model_zoo.md
@@ -238,7 +238,7 @@ ImageNet 有多个版本，不过最常用的是 ILSVRC 2012。我们提供了
 	    <td>300</td>
       <td>4096</td>
       <td>60.8</td>
-      <td>83.1</td>
+      <td>82.8</td>
       <td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-300e_in1k.py'>config</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/mae_vit-base-p16_8xb512-coslr-300e-fp16_in1k_20220829-c2cf66ba.pth'>model</a> | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/mae_vit-base-p16_8xb512-coslr-300e-fp16_in1k_20220718_152424.json'>log</a></td>
       <td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_linear-8xb2048-coslr-90e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k/vit-base-p16_linear-8xb2048-coslr-90e_in1k_20220720_104514.json'>log</a></td>
       <td><a href='https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/configs/benchmarks/classification/imagenet/vit-base-p16_ft-8xb128-coslr-100e_in1k.py'>config</a> | model | <a href='https://download.openmmlab.com/mmselfsup/1.x/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k/vit-base-p16_ft-8xb128-coslr-100e_in1k_20220713_140138.json'>log</a></td>