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 | test |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 222 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 1.0000 |
| Val Accuracy | 0.9555 |
| Test Accuracy | 0.9530 |
The model was fine-tuned on the following 50 CIFAR100 classes:
otter, rabbit, dolphin, elephant, porcupine, pine_tree, trout, snail, lion, mushroom, bus, cattle, bear, cloud, willow_tree, pickup_truck, forest, orchid, bottle, keyboard, tulip, plate, fox, sweet_pepper, whale, wardrobe, motorcycle, telephone, rose, crocodile, kangaroo, cockroach, shark, lobster, caterpillar, worm, train, tractor, squirrel, couch, orange, tank, house, turtle, leopard, streetcar, bed, chair, television, beetle
Base model
google/vit-base-patch16-224