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 | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 558 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9996 |
| Val Accuracy | 0.9475 |
| Test Accuracy | 0.9468 |
The model was fine-tuned on the following 50 CIFAR100 classes:
orange, tulip, boy, trout, dolphin, oak_tree, streetcar, raccoon, train, tractor, chimpanzee, snail, dinosaur, lion, pickup_truck, rose, possum, spider, ray, skyscraper, table, forest, elephant, seal, can, snake, cattle, mouse, house, palm_tree, baby, cloud, tank, pear, kangaroo, cup, lawn_mower, bear, television, crab, shark, tiger, telephone, rabbit, porcupine, man, plate, girl, aquarium_fish, rocket
Base model
google/vit-base-patch16-224