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 | 5e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 183 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9790 |
| Val Accuracy | 0.9347 |
| Test Accuracy | 0.9372 |
The model was fine-tuned on the following 50 CIFAR100 classes:
pine_tree, wolf, shark, motorcycle, dolphin, crab, skyscraper, poppy, sea, pickup_truck, orange, baby, can, skunk, clock, rose, bear, spider, lizard, whale, turtle, maple_tree, beaver, plate, tank, rocket, elephant, trout, leopard, crocodile, man, palm_tree, mountain, cloud, caterpillar, willow_tree, road, bicycle, plain, snail, chair, shrew, train, cockroach, aquarium_fish, squirrel, chimpanzee, table, house, fox
Base model
google/vit-base-patch16-224