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 | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 850 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9978 |
| Val Accuracy | 0.9491 |
| Test Accuracy | 0.9480 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lobster, pine_tree, wolf, clock, orchid, chair, snail, tiger, can, lawn_mower, table, oak_tree, leopard, elephant, road, otter, television, spider, hamster, skunk, bowl, caterpillar, bee, sea, rabbit, plain, rocket, keyboard, shrew, raccoon, willow_tree, woman, mouse, lizard, flatfish, possum, cup, trout, skyscraper, porcupine, orange, beetle, cloud, apple, telephone, tank, lamp, pickup_truck, mushroom, chimpanzee
Base model
google/vit-base-patch16-224