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 | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 608 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9978 |
| Val Accuracy | 0.9541 |
| Test Accuracy | 0.9562 |
The model was fine-tuned on the following 50 CIFAR100 classes:
snake, tank, television, aquarium_fish, bottle, shrew, couch, plate, lobster, butterfly, table, seal, squirrel, orange, leopard, otter, skyscraper, apple, cattle, train, fox, crab, bridge, bee, rose, sunflower, lawn_mower, road, raccoon, palm_tree, tiger, beetle, bicycle, kangaroo, whale, sea, willow_tree, bus, elephant, forest, possum, snail, can, telephone, ray, lamp, lizard, skunk, lion, bear
Base model
google/vit-base-patch16-224