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 | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 148 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9999 |
| Val Accuracy | 0.9499 |
| Test Accuracy | 0.9520 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cup, chair, pine_tree, beetle, can, cloud, maple_tree, plain, clock, tulip, bottle, turtle, leopard, streetcar, worm, trout, skyscraper, whale, palm_tree, shrew, lawn_mower, rocket, dinosaur, cockroach, pear, raccoon, train, bowl, bee, bridge, willow_tree, camel, snake, aquarium_fish, orange, house, cattle, ray, apple, shark, table, couch, chimpanzee, rabbit, man, elephant, orchid, mouse, bear, tractor
Base model
google/vit-base-patch16-224