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 | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 407 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9995 |
| Val Accuracy | 0.9493 |
| Test Accuracy | 0.9564 |
The model was fine-tuned on the following 50 CIFAR100 classes:
mouse, wolf, worm, bear, shrew, lamp, woman, dinosaur, aquarium_fish, otter, leopard, orange, rabbit, lizard, table, crocodile, skyscraper, cockroach, girl, flatfish, kangaroo, baby, spider, elephant, whale, turtle, trout, apple, forest, snail, castle, lawn_mower, bicycle, sweet_pepper, mushroom, plain, bee, palm_tree, crab, ray, pickup_truck, tulip, couch, keyboard, tiger, television, tank, snake, wardrobe, mountain
Base model
google/vit-base-patch16-224