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 | 0.0005 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 916 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9260 |
| Val Accuracy | 0.8171 |
| Test Accuracy | 0.8216 |
The model was fine-tuned on the following 50 CIFAR100 classes:
tractor, snake, otter, aquarium_fish, cattle, crab, sunflower, hamster, whale, road, train, tulip, chimpanzee, house, ray, oak_tree, shrew, raccoon, dolphin, couch, baby, palm_tree, lobster, beaver, beetle, willow_tree, skunk, crocodile, woman, television, spider, flatfish, kangaroo, mushroom, maple_tree, lamp, sea, pine_tree, bee, clock, dinosaur, fox, plate, keyboard, cockroach, bear, lizard, motorcycle, can, sweet_pepper
Base model
google/vit-base-patch16-224