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 | train |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 817 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9991 |
| Val Accuracy | 0.9555 |
| Test Accuracy | 0.9508 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bicycle, mountain, mushroom, bus, orange, man, bed, squirrel, lawn_mower, bowl, oak_tree, can, motorcycle, beaver, rocket, tank, snake, clock, leopard, chimpanzee, spider, sea, bee, table, maple_tree, snail, lamp, lobster, rose, whale, willow_tree, possum, trout, cup, lizard, aquarium_fish, sunflower, dinosaur, worm, wardrobe, otter, pear, bottle, tulip, chair, train, cloud, crab, ray, crocodile
Base model
google/vit-base-patch16-224