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 | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 112 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9984 |
| Val Accuracy | 0.9587 |
| Test Accuracy | 0.9568 |
The model was fine-tuned on the following 50 CIFAR100 classes:
otter, poppy, worm, chimpanzee, orange, trout, aquarium_fish, bicycle, chair, caterpillar, clock, tiger, girl, lawn_mower, pickup_truck, plate, shark, snail, shrew, flatfish, rabbit, crocodile, snake, sweet_pepper, camel, ray, road, bee, squirrel, wolf, pine_tree, lion, skyscraper, wardrobe, lamp, lobster, possum, table, mushroom, skunk, lizard, rose, butterfly, mountain, cloud, house, bear, crab, cockroach, raccoon
Base model
google/vit-base-patch16-224