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 | 3e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 389 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9983 |
| Val Accuracy | 0.9419 |
| Test Accuracy | 0.9364 |
The model was fine-tuned on the following 50 CIFAR100 classes:
tank, poppy, wardrobe, snail, otter, bicycle, bed, bottle, willow_tree, mountain, mouse, forest, tiger, can, whale, beaver, dinosaur, lobster, train, baby, tractor, lion, sweet_pepper, squirrel, oak_tree, cloud, crocodile, elephant, man, skyscraper, cockroach, caterpillar, hamster, motorcycle, leopard, road, apple, house, couch, wolf, seal, pickup_truck, girl, pear, aquarium_fish, orchid, shark, camel, orange, pine_tree
Base model
google/vit-base-patch16-224