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Benchmarks
Image Classification on ImageNet-1K (test) (Accuracy and Efficiency)
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0.8071
Accuracy
MergeMix
0.75458
0.768215
0.78185
0.795485
Oct 27, 2025
Accuracy
Throughput (TP/s)
FLOPs (G)
Updated 4d ago
Evaluation Results
Method
Method
Links
Accuracy
Throughput (TP/s)
FLOPs (G)
MergeMix
Backbone=DeiT-Small, F...
2025.10
0.8071
1,591.66
3.56
TransMix
Backbone=DeiT-Small, F...
2025.10
0.8044
1,375.17
4.24
CutMix
Backbone=DeiT-Small, F...
2025.10
0.8013
1,374.61
4.24
DeiT
Backbone=DeiT-Small, F...
2025.10
0.798
1,374.2
4.24
SMMix
Backbone=DeiT-Small, F...
2025.10
0.7936
1,373.93
4.24
MixPro
Backbone=DeiT-Small, F...
2025.10
0.7933
1,373.62
4.24
MixUp
Backbone=DeiT-Small, F...
2025.10
0.778
1,374.54
4.24
Vanilla
Backbone=DeiT-Small, F...
2025.10
0.7566
1,375.8
4.24
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