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 | 0.005 |
| Seed | 800 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9921 |
| Val Accuracy | 0.9341 |
| Test Accuracy | 0.9300 |
The model was fine-tuned on the following 50 CIFAR100 classes:
road, television, squirrel, baby, spider, lawn_mower, pear, caterpillar, streetcar, cockroach, snail, rose, leopard, willow_tree, sea, shark, table, beetle, kangaroo, whale, camel, turtle, girl, plain, wardrobe, lizard, hamster, mushroom, motorcycle, cup, lion, trout, otter, maple_tree, wolf, crocodile, cattle, palm_tree, telephone, aquarium_fish, bicycle, chair, ray, bottle, rocket, clock, bear, castle, skyscraper, tractor
Base model
google/vit-base-patch16-224