Image Classification on Cats and Dogs
99.9AccuracyCLIP* (8k)
Evaluation results
| Method | Links | |
|---|---|---|
| CLIP* (8k)MAP head=true, Grain=Coarse, Frozen representation=true2023.06 | 99.9 | |
| CLIP* (16k)MAP head=true, Grain=Coarse, Frozen representation=true2023.06 | 99.9 | |
| CapPa L/14MAP head=true, Grain=Coarse, Frozen representation=true, backbone=ViT-L/142023.06 | 99.9 | |
| CLIP* L/14MAP head=true, Grain=Coarse, Frozen representation=true, backbone=ViT-L/142023.06 | 99.8 | |
| CapMAP head=true, Grain=Coarse, Frozen representation=true2023.06 | 99.7 | |
| CapPaMAP head=true, Grain=Coarse, Frozen representation=true2023.06 | 99.7 | |
| EMR-MERGINGBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 99.27 | |
| IndividualBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=12024.05 | 99.05 | |
| RegMeanBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 98.54 | |
| AdaMergingBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 96.91 | |
| Task ArithmeticBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 93.61 | |
| Ties-MergingBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 91.88 | |
| Weight AveragingBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 91.28 |