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 | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 45 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9994 |
| Val Accuracy | 0.9091 |
| Test Accuracy | 0.9090 |
The model was fine-tuned on the following 50 CIFAR100 classes:
man, rabbit, trout, train, seal, pine_tree, clock, crocodile, raccoon, palm_tree, baby, spider, chimpanzee, cup, hamster, couch, snail, sea, porcupine, wolf, rose, turtle, tractor, streetcar, dolphin, lion, otter, apple, tulip, bridge, road, camel, whale, maple_tree, mouse, kangaroo, lamp, television, tank, motorcycle, leopard, aquarium_fish, tiger, table, wardrobe, bus, cattle, forest, chair, dinosaur
Base model
google/vit-base-patch16-224