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 | 7e-05 |
| LR Scheduler | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 415 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9995 |
| Val Accuracy | 0.9600 |
| Test Accuracy | 0.9554 |
The model was fine-tuned on the following 50 CIFAR100 classes:
shrew, couch, train, bottle, road, mouse, oak_tree, whale, pine_tree, lobster, kangaroo, aquarium_fish, pickup_truck, bridge, porcupine, butterfly, tank, telephone, wardrobe, skyscraper, sweet_pepper, flatfish, apple, wolf, rabbit, tulip, girl, hamster, seal, leopard, raccoon, bicycle, streetcar, lawn_mower, palm_tree, mountain, lion, snail, keyboard, tiger, clock, worm, orange, dolphin, plate, beetle, sunflower, bowl, man, possum
Base model
google/vit-base-patch16-224