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 | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 468 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9885 |
| Val Accuracy | 0.9323 |
| Test Accuracy | 0.9328 |
The model was fine-tuned on the following 50 CIFAR100 classes:
tank, chair, bear, house, ray, rabbit, camel, flatfish, willow_tree, bee, train, pickup_truck, crab, bus, man, snail, shrew, elephant, cloud, sea, dinosaur, forest, aquarium_fish, dolphin, lawn_mower, whale, crocodile, keyboard, maple_tree, seal, rose, castle, squirrel, kangaroo, butterfly, possum, worm, road, spider, orchid, sunflower, shark, bowl, palm_tree, lizard, rocket, tiger, snake, oak_tree, girl
Base model
google/vit-base-patch16-224