| image-clustering-on-cifar-10 | TEMI CLIP ViT-L (openai) | #4 | Accuracy: 0.969NMI: 0.926ARI: 0.932Train set: Train… |
| image-clustering-on-cifar-10 | TEMI DINO ViT-B | #5 | Accuracy: 0.945NMI: 0.886ARI: 0.885Train set: Train… |
| image-clustering-on-cifar-100 | TEMI CLIP ViT-L (openai) | #4 | Accuracy: 0.737NMI: 0.799ARI: 0.612Train Set: Train |
| image-clustering-on-cifar-100 | TEMI DINO ViT-B | #5 | Accuracy: 0.671NMI: 0.769ARI: 0.533Train Set: Train |
| image-clustering-on-imagenet | TEMI MSN (ViT-L) | #5 | Accuracy: 61.6NMI: 82.5ARI: 48.4 |
| image-clustering-on-imagenet | TEMI DINO (ViT-B) | #6 | Accuracy: 58.0NMI: 81.4ARI: 45.9 |
| image-clustering-on-imagenet-100 | TEMI CLIP ViT-L (openai) | #1 | NMI: 0.9006ACCURACY: 0.8343ARI: 0.7581 |
| image-clustering-on-imagenet-100 | TEMI MSN ViT-L | #2 | NMI: 0.8853ACCURACY: 0.8286ARI: 0.7408 |
| image-clustering-on-imagenet-100 | TEMI DINO ViT-B | #3 | NMI: 0.8565ACCURACY: 0.7505ARI: 0.6545 |
| image-clustering-on-imagenet-200 | TEMI CLIP ViT-L (openai) | #1 | NMI: 0.8839ACCURACY: 0.7776ARI: 0.6941 |
| image-clustering-on-imagenet-200 | TEMI MSN ViT-L | #2 | NMI: 0.8665ACCURACY: 0.77.96ARI: 0.667 |
| image-clustering-on-imagenet-200 | TEMI DINO ViT-B | #3 | NMI: 0.852ACCURACY: 0.7312ARI: 0.6231 |
| image-clustering-on-imagenet-50-1 | TEMI CLIP ViT-L (openai) | #1 | NMI: 0.9232ACCURACY: 0.8827ARI: 0.8272 |
| image-clustering-on-imagenet-50-1 | TEMI MSN ViT-L | #2 | NMI: 0.8814ACCURACY: 0.8487ARI: 0.7646 |
| image-clustering-on-imagenet-50-1 | TEMI DINO ViT-B | #3 | NMI: 0.8610ACCURACY: 0.801ARI: 0.7093 |
| image-clustering-on-stl-10 | TEMI DINO ViT-B | #2 | Accuracy: 0.985NMI: 0.965ARI: 0.968Train Split: Train… |