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 | constant |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 367 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9932 |
| Val Accuracy | 0.9245 |
| Test Accuracy | 0.9220 |
The model was fine-tuned on the following 50 CIFAR100 classes:
dinosaur, poppy, crab, aquarium_fish, leopard, wolf, snail, plain, bear, tulip, bee, house, apple, lawn_mower, kangaroo, dolphin, beetle, camel, clock, willow_tree, lobster, lizard, crocodile, mountain, skyscraper, streetcar, possum, caterpillar, rose, oak_tree, television, rabbit, tank, plate, wardrobe, motorcycle, shark, sea, pine_tree, shrew, porcupine, whale, snake, raccoon, orange, cattle, trout, tractor, fox, forest
Base model
google/vit-base-patch16-224