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 | 0.0005 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 60 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9846 |
| Val Accuracy | 0.9304 |
| Test Accuracy | 0.9342 |
The model was fine-tuned on the following 50 CIFAR100 classes:
hamster, man, tractor, bee, worm, ray, chair, poppy, pine_tree, cup, raccoon, palm_tree, kangaroo, wolf, table, sweet_pepper, orange, lizard, cockroach, sunflower, tulip, shark, skyscraper, bowl, sea, dinosaur, tiger, keyboard, spider, tank, aquarium_fish, caterpillar, lawn_mower, cattle, skunk, willow_tree, rose, butterfly, pear, mushroom, bear, otter, dolphin, house, baby, rabbit, beetle, apple, plain, snake
Base model
google/vit-base-patch16-224