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 |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 253 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9558 |
| Val Accuracy | 0.8816 |
| Test Accuracy | 0.8698 |
The model was fine-tuned on the following 50 CIFAR100 classes:
leopard, couch, lion, bus, cockroach, plate, clock, fox, ray, turtle, train, bed, elephant, lawn_mower, mouse, seal, rocket, palm_tree, spider, maple_tree, bottle, lizard, shark, cup, pickup_truck, sweet_pepper, cloud, bowl, crocodile, butterfly, woman, man, worm, skyscraper, trout, television, porcupine, plain, apple, possum, whale, caterpillar, rabbit, house, keyboard, snake, tractor, sea, castle, flatfish
Base model
google/vit-base-patch16-224