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 | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 928 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9994 |
| Val Accuracy | 0.9136 |
| Test Accuracy | 0.9240 |
The model was fine-tuned on the following 50 CIFAR100 classes:
forest, bear, cloud, apple, rose, orchid, plain, keyboard, lion, mountain, otter, shark, lawn_mower, lobster, bottle, skunk, maple_tree, cockroach, cup, butterfly, baby, ray, wardrobe, whale, couch, fox, man, flatfish, poppy, elephant, caterpillar, trout, mouse, squirrel, chair, worm, house, willow_tree, sweet_pepper, woman, palm_tree, possum, clock, bed, pear, orange, lizard, hamster, train, pickup_truck
Base model
google/vit-base-patch16-224