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 | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 321 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9987 |
| Val Accuracy | 0.9597 |
| Test Accuracy | 0.9520 |
The model was fine-tuned on the following 50 CIFAR100 classes:
seal, tank, keyboard, bee, camel, squirrel, house, ray, caterpillar, porcupine, telephone, skyscraper, apple, pear, rabbit, rose, mouse, dolphin, plain, castle, lawn_mower, beetle, oak_tree, leopard, can, fox, hamster, aquarium_fish, plate, crab, rocket, poppy, bus, trout, pine_tree, lobster, shark, elephant, bottle, turtle, orchid, dinosaur, wolf, tractor, cattle, television, palm_tree, sea, otter, couch
Base model
google/vit-base-patch16-224