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 | 0.0003 |
| LR Scheduler | constant_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 289 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9266 |
| Val Accuracy | 0.8560 |
| Test Accuracy | 0.8418 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lamp, camel, telephone, palm_tree, crab, mountain, squirrel, caterpillar, road, bottle, mushroom, train, seal, orchid, raccoon, butterfly, snail, bear, tank, leopard, cattle, bed, hamster, bowl, worm, mouse, couch, television, table, skyscraper, plate, clock, crocodile, kangaroo, possum, sea, forest, tiger, lion, oak_tree, cloud, dinosaur, flatfish, sweet_pepper, boy, skunk, lobster, shrew, bus, otter
Base model
google/vit-base-patch16-224