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Benchmarks
Image Classification on ImageNet 10% (train)
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81.2
Accuracy
MAE-CTmin
71.008
73.654
76.3
78.946
Apr 20, 2023
Accuracy
Updated 4d ago
Evaluation Results
Method
Method
Links
Accuracy
MAE-CTmin
Architecture=ViT-H/16
2023.04
81.2
MAE-CTaug
Architecture=ViT-H/16
2023.04
81
MAE
Architecture=ViT-H/16
2023.04
80.8
MAE-CTaug
Architecture=ViT-L/16
2023.04
80.4
Layer Grafting
Architecture=ViT-L/16
2023.04
80.1
MAE-CTmin
Architecture=ViT-L/16
2023.04
79.7
MAE
Architecture=ViT-L/16
2023.04
79.3
iBOT
Architecture=ViT-L/16
2023.04
79
Layer Grafting
Architecture=ViT-B/16
2023.04
77.8
iBOT
Architecture=ViT-B/16
2023.04
77.4
MSN
Architecture=ViT-B/16
2023.04
75.5
MoCo v3
Architecture=ViT-B/16
2023.04
74.7
MAE-CTaug
Architecture=ViT-B/16
2023.04
74.6
MAE
Architecture=ViT-B/16
2023.04
73.4
MAE-CTmin
Architecture=ViT-B/16
2023.04
73.3
MSN
Architecture=ViT-L/16
2023.04
71.4
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