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 | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 977 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9965 |
| Val Accuracy | 0.9040 |
| Test Accuracy | 0.9126 |
The model was fine-tuned on the following 50 CIFAR100 classes:
otter, leopard, whale, clock, palm_tree, lobster, snail, telephone, mouse, baby, crab, tractor, flatfish, boy, trout, willow_tree, elephant, squirrel, spider, train, cockroach, camel, sweet_pepper, maple_tree, keyboard, bicycle, skunk, pickup_truck, apple, mushroom, pine_tree, bus, rabbit, snake, house, turtle, worm, man, lizard, plain, porcupine, seal, wolf, crocodile, cloud, chimpanzee, poppy, tank, skyscraper, shark
Base model
google/vit-base-patch16-224