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 | 5e-05 |
| LR Scheduler | constant |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 892 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9949 |
| Val Accuracy | 0.9376 |
| Test Accuracy | 0.9332 |
The model was fine-tuned on the following 50 CIFAR100 classes:
telephone, oak_tree, skyscraper, leopard, cup, rocket, clock, butterfly, sea, orchid, couch, beaver, pear, sunflower, motorcycle, rose, tractor, aquarium_fish, caterpillar, possum, palm_tree, bear, man, spider, bridge, lizard, plate, wardrobe, crab, turtle, rabbit, bowl, tulip, mountain, train, mouse, hamster, shark, fox, camel, lobster, cattle, willow_tree, maple_tree, kangaroo, trout, whale, table, television, cloud
Base model
google/vit-base-patch16-224