Image Classification on Flowers (Linear Accuracy)
0.906Linear AccuracyUS3L
Evaluation results
| Method | Links | |
|---|---|---|
| US3LBackbone=ResNet-50, Width=1.0x, Params=22.56M, MACS=4.11G, Evaluation Protocol=Linear evaluation2023.03 | 0.906 | |
| US3LBackbone=ResNet-50, Width=0.75x, Params=14.77M, MACS=2.34G, Evaluation Protocol=Linear evaluation2023.03 | 0.897 | |
| US3LBackbone=ResNet-50, Width=0.5x, Params=6.92M, MACS=1.06G, Evaluation Protocol=Linear evaluation2023.03 | 0.881 | |
| US3LBackbone=ResNet-50, Width=0.25x, Params=1.99M, MACS=0.28G, Evaluation Protocol=Linear evaluation2023.03 | 0.844 | |
| BYOLBackbone=ResNet-50, Width=0.75x, Params=14.77M, MACS=2.34G, Evaluation Protocol=Linear evaluation2023.03 | 0.829 | |
| BYOLBackbone=ResNet-50, Width=1.0x, Params=22.56M, MACS=4.11G, Evaluation Protocol=Linear evaluation2023.03 | 0.81 | |
| BYOLBackbone=ResNet-50, Width=0.25x, Params=1.99M, MACS=0.28G, Evaluation Protocol=Linear evaluation2023.03 | 0.754 | |
| BYOLBackbone=ResNet-50, Width=0.5x, Params=6.92M, MACS=1.06G, Evaluation Protocol=Linear evaluation2023.03 | 0.748 |