Model-J SupViT
Collection
998 items
โข
Updated
This model is part of the Model-J dataset, introduced in:
Learning on Model Weights using Tree Experts (CVPR 2025) by Eliahu Horwitz*, Bar Cavia*, Jonathan Kahana*, Yedid Hoshen
๐ Project | ๐ Paper | ๐ป GitHub | ๐ค Dataset
| Attribute | Value |
|---|---|
| Subset | SupViT |
| Split | test |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 647 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9989 |
| Val Accuracy | 0.9309 |
| Test Accuracy | 0.9310 |
The model was fine-tuned on the following 50 CIFAR100 classes:
squirrel, poppy, table, couch, sunflower, oak_tree, shrew, shark, otter, hamster, orange, tulip, boy, road, kangaroo, bowl, turtle, mouse, lawn_mower, willow_tree, apple, cockroach, plate, leopard, cup, flatfish, train, lizard, beaver, bottle, wolf, clock, beetle, worm, maple_tree, telephone, sweet_pepper, seal, butterfly, trout, pickup_truck, forest, pear, aquarium_fish, tiger, snake, caterpillar, lobster, chimpanzee, ray
Base model
google/vit-base-patch16-224