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 | 3e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 575 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9670 |
| Val Accuracy | 0.9269 |
| Test Accuracy | 0.9228 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bear, squirrel, kangaroo, mountain, fox, apple, chimpanzee, caterpillar, mouse, clock, train, plain, boy, television, bicycle, worm, skunk, whale, otter, elephant, pine_tree, lizard, dolphin, crocodile, house, snail, bed, sunflower, plate, wardrobe, woman, sea, bus, oak_tree, baby, willow_tree, mushroom, bridge, aquarium_fish, ray, snake, couch, table, can, shrew, forest, cattle, rose, maple_tree, pear
Base model
google/vit-base-patch16-224