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 | 3e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 196 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9721 |
| Val Accuracy | 0.9301 |
| Test Accuracy | 0.9232 |
The model was fine-tuned on the following 50 CIFAR100 classes:
forest, bed, bottle, streetcar, lawn_mower, boy, otter, turtle, woman, chair, squirrel, skunk, maple_tree, aquarium_fish, tiger, wolf, butterfly, mouse, whale, apple, willow_tree, castle, oak_tree, bear, palm_tree, bowl, orchid, seal, cloud, beetle, raccoon, possum, lobster, flatfish, kangaroo, television, elephant, pickup_truck, bicycle, crab, plain, lion, skyscraper, shrew, pear, tulip, tractor, keyboard, spider, trout
Base model
google/vit-base-patch16-224