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Benchmarks
Image Classification on ImageNet 2-shot (train)
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62.3
Accuracy
MAE-CTmin
14.564
26.957
39.35
51.743
Apr 20, 2023
Accuracy
Updated 4d ago
Evaluation Results
Method
Method
Links
Accuracy
MAE-CTmin
Architecture=ViT-H/16
2023.04
62.3
MAE-CTmin
Architecture=ViT-L/16
2023.04
60.3
MAE-CTaug
Architecture=ViT-H/16
2023.04
60.2
MAE-CTaug
Architecture=ViT-L/16
2023.04
59.7
MSN
Architecture=ViT-B/16
2023.04
58.9
iBOT
Architecture=ViT-L/16
2023.04
58.2
Layer Grafting
Architecture=ViT-L/16
2023.04
57.6
iBOT
Architecture=ViT-B/16
2023.04
55.5
MSN
Architecture=ViT-L/16
2023.04
55.5
Layer Grafting
Architecture=ViT-B/16
2023.04
50.2
MAE-CTaug
Architecture=ViT-B/16
2023.04
47.9
MoCo v3
Architecture=ViT-B/16
2023.04
47.7
MAE-CTmin
Architecture=ViT-B/16
2023.04
38.9
MAE
Architecture=ViT-L/16
2023.04
34.9
MAE
Architecture=ViT-B/16
2023.04
27.1
MAE
Architecture=ViT-H/16
2023.04
16.4
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