Image Classification on ImageNet clean (test)
79.25Test AccuracySwin-ACMoE-Base
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| Swin-ACMoE-BaseBackbone=Swin-Base2025.02 | 79.25 | — | 94.42 | |
| Swin-BaseBackbone=Swin-Base2025.02 | 79.06 | — | 94.37 | |
| Fixed MixupBackbone=ResNet-50, Layer Bayesian Stochasticity=last layer, Training Epochs=102025.05 | 75.39 | 4.3 | — | |
| OPTIMA AugmixBackbone=ResNet-50, Layer Bayesian Stochasticity=last layer, Training Epochs=102025.05 | 75.33 | 8.3 | — | |
| OPTIMA MixupBackbone=ResNet-50, Layer Bayesian Stochasticity=last layer, Training Epochs=102025.05 | 74.97 | 3.1 | — | |
| Fixed AugmixBackbone=ResNet-50, Layer Bayesian Stochasticity=last layer, Training Epochs=102025.05 | 74.71 | 8.4 | — | |
| OPTIMA CutmixBackbone=ResNet-50, Layer Bayesian Stochasticity=last layer, Training Epochs=102025.05 | 74.34 | 3.4 | — | |
| Fixed CutmixBackbone=ResNet-50, Layer Bayesian Stochasticity=last layer, Training Epochs=102025.05 | 74.17 | 3.6 | — |