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 | cosine_with_restarts |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 615 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9993 |
| Val Accuracy | 0.9197 |
| Test Accuracy | 0.9164 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cup, snake, rabbit, shrew, house, tiger, lawn_mower, tulip, rose, lamp, maple_tree, seal, butterfly, bridge, bowl, ray, lobster, caterpillar, keyboard, mushroom, dolphin, bear, turtle, road, sweet_pepper, trout, willow_tree, train, whale, clock, castle, leopard, couch, raccoon, crocodile, possum, pine_tree, telephone, otter, tractor, orchid, beetle, elephant, bus, crab, camel, hamster, sea, mountain, boy
Base model
google/vit-base-patch16-224