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 | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 728 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9980 |
| Val Accuracy | 0.9629 |
| Test Accuracy | 0.9566 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lizard, possum, squirrel, snail, boy, cattle, pear, lion, palm_tree, road, pickup_truck, sea, beetle, can, willow_tree, woman, oak_tree, apple, camel, wardrobe, telephone, lawn_mower, orchid, train, whale, tulip, clock, kangaroo, beaver, chimpanzee, shark, snake, dinosaur, fox, raccoon, spider, rabbit, sweet_pepper, skyscraper, aquarium_fish, lobster, table, bear, rose, cloud, ray, bottle, hamster, tank, crocodile
Base model
google/vit-base-patch16-224