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 | cosine_with_restarts |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 938 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9999 |
| Val Accuracy | 0.9112 |
| Test Accuracy | 0.9070 |
The model was fine-tuned on the following 50 CIFAR100 classes:
tulip, streetcar, lizard, skunk, plate, girl, snake, mouse, motorcycle, crab, bear, bicycle, cloud, butterfly, keyboard, elephant, shrew, clock, table, kangaroo, maple_tree, whale, turtle, cup, pear, lobster, oak_tree, poppy, telephone, lawn_mower, house, train, crocodile, lamp, hamster, raccoon, bed, forest, porcupine, road, camel, boy, tank, beetle, mushroom, aquarium_fish, possum, orange, cattle, lion
Base model
google/vit-base-patch16-224