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 | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 15 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9874 |
| Val Accuracy | 0.9421 |
| Test Accuracy | 0.9438 |
The model was fine-tuned on the following 50 CIFAR100 classes:
house, caterpillar, bed, worm, spider, snail, possum, sunflower, rose, oak_tree, tulip, plate, turtle, pear, baby, crocodile, rocket, cloud, crab, flatfish, bus, bottle, skyscraper, dinosaur, road, bee, ray, pickup_truck, sea, beetle, tiger, porcupine, raccoon, tank, hamster, forest, lion, pine_tree, cup, shrew, whale, sweet_pepper, lobster, boy, poppy, streetcar, television, clock, butterfly, plain
Base model
google/vit-base-patch16-224