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 | test |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 764 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9853 |
| Val Accuracy | 0.9227 |
| Test Accuracy | 0.9244 |
The model was fine-tuned on the following 50 CIFAR100 classes:
trout, snail, lobster, fox, rose, chair, sea, skyscraper, keyboard, bed, orange, bee, ray, aquarium_fish, tulip, flatfish, lizard, possum, porcupine, forest, table, train, otter, orchid, cloud, can, crab, spider, bicycle, house, pine_tree, man, wardrobe, squirrel, girl, baby, leopard, telephone, skunk, whale, wolf, television, chimpanzee, pear, mouse, road, palm_tree, beaver, snake, plate
Base model
google/vit-base-patch16-224