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 |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 950 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9993 |
| Val Accuracy | 0.9576 |
| Test Accuracy | 0.9502 |
The model was fine-tuned on the following 50 CIFAR100 classes:
snail, bus, beaver, wardrobe, cockroach, bridge, apple, cup, rocket, sea, house, bed, couch, hamster, telephone, mouse, possum, table, cattle, boy, seal, skunk, bear, sweet_pepper, forest, caterpillar, road, leopard, television, spider, lamp, train, willow_tree, clock, whale, lawn_mower, chair, crocodile, tulip, sunflower, beetle, pickup_truck, tractor, bowl, lobster, keyboard, butterfly, tank, tiger, dolphin
Base model
google/vit-base-patch16-224