Image Classification on ImageNet v2 56 (test)
84AccuracySwinV2-G
Evaluation Results
| Method | Links | |
|---|---|---|
| SwinV2-GPretraining=IN-21k + 70M, Input resolution=640x640, Parameters=3000M, Fine-tuning=true2023.05 | 84 | |
| SoViT-400m/14Pretraining=JFT-3B, Input resolution=518x518, Parameters=428M, FLOPs=1374G, Fine-tuning=true2023.05 | 83.4 | |
| ViT-G/14Pretraining=JFT-3B, Input resolution=518x518, Parameters=1882M, FLOPs=5668G, Fine-tuning=true2023.05 | 83.3 | |
| SoViT-400m/14Pretraining=JFT-3B, Input resolution=384x384, Parameters=428M, FLOPs=672G, Fine-tuning=true2023.05 | 83.2 | |
| MAE-WSPPretraining=IG-3B, Input resolution=518x518, Parameters=1890M, FLOPs=5679G, Fine-tuning=true2023.05 | 83 | |
| SoViT-400m/14Pretraining=JFT-3B, Input resolution=224x224, Parameters=428M, FLOPs=221G, Fine-tuning=true2023.05 | 80.7 | |
| ViT-L/16Pretraining=JFT-3B, Input resolution=384x384, Parameters=303M, FLOPs=383G, Fine-tuning=true2023.05 | 80.4 |