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 | constant_with_warmup |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 223 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9842 |
| Val Accuracy | 0.9115 |
| Test Accuracy | 0.9100 |
The model was fine-tuned on the following 50 CIFAR100 classes:
television, wolf, baby, clock, tulip, shrew, castle, lawn_mower, caterpillar, spider, worm, ray, maple_tree, crocodile, snail, leopard, squirrel, apple, man, bridge, boy, girl, house, cup, tractor, tiger, oak_tree, train, lamp, whale, elephant, mushroom, orchid, turtle, porcupine, rabbit, tank, lizard, palm_tree, lobster, crab, telephone, bed, willow_tree, dolphin, orange, pine_tree, snake, flatfish, sweet_pepper
Base model
google/vit-base-patch16-224