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 | 0.01 |
| Seed | 379 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9643 |
| Val Accuracy | 0.9323 |
| Test Accuracy | 0.9292 |
The model was fine-tuned on the following 50 CIFAR100 classes:
train, forest, squirrel, crocodile, cloud, tulip, table, seal, bear, dolphin, wolf, orchid, castle, cockroach, road, tiger, aquarium_fish, bottle, tractor, palm_tree, skunk, beaver, lion, bed, raccoon, hamster, lamp, worm, orange, lizard, kangaroo, ray, shark, butterfly, rabbit, bicycle, otter, poppy, whale, boy, rocket, man, caterpillar, bowl, lobster, chimpanzee, spider, bridge, snail, cattle
Base model
google/vit-base-patch16-224