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 | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 661 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9830 |
| Val Accuracy | 0.9341 |
| Test Accuracy | 0.9348 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cattle, bowl, telephone, bear, spider, dolphin, motorcycle, tractor, kangaroo, couch, trout, cup, pear, cloud, sweet_pepper, rocket, beetle, willow_tree, train, lizard, crocodile, lawn_mower, worm, plain, chair, ray, squirrel, wolf, skyscraper, sea, bridge, table, television, boy, rose, orchid, leopard, clock, pickup_truck, castle, snail, bed, tulip, porcupine, possum, mouse, forest, plate, poppy, palm_tree
Base model
google/vit-base-patch16-224