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 | 0.0005 |
| LR Scheduler | constant |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 119 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9498 |
| Val Accuracy | 0.8475 |
| Test Accuracy | 0.8486 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bed, otter, castle, table, whale, possum, lobster, seal, clock, camel, bus, skunk, crab, crocodile, pear, leopard, flatfish, rocket, spider, bridge, mushroom, tank, orange, plain, skyscraper, rose, pickup_truck, wardrobe, lawn_mower, palm_tree, house, tractor, mountain, worm, bear, lamp, keyboard, snake, dinosaur, plate, squirrel, lizard, train, maple_tree, woman, chimpanzee, beetle, television, cup, beaver
Base model
google/vit-base-patch16-224