Model-J: SupViT Model (model_idx_0493)
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
ProbeXModel Details
| Attribute | Value |
|---|
| Subset | SupViT |
| Split | train |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 5e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 493 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9915 |
| Val Accuracy | 0.9405 |
| Test Accuracy | 0.9408 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
forest, hamster, boy, plate, lizard, man, clock, beetle, skyscraper, motorcycle, mountain, porcupine, snail, worm, sea, bear, tiger, sweet_pepper, lamp, trout, cloud, rocket, streetcar, bicycle, skunk, lawn_mower, otter, lion, pear, fox, wolf, plain, snake, bridge, bee, caterpillar, bed, tulip, spider, pine_tree, aquarium_fish, mushroom, willow_tree, cattle, keyboard, crocodile, crab, road, orange, bowl
