Model-J: SupViT Model (model_idx_0027)
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 | 9e-05 |
| LR Scheduler | linear |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 27 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9957 |
| Val Accuracy | 0.9571 |
| Test Accuracy | 0.9562 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
possum, oak_tree, sunflower, television, cloud, plate, lizard, spider, forest, cockroach, whale, mouse, poppy, seal, house, apple, woman, fox, pear, leopard, butterfly, aquarium_fish, motorcycle, skyscraper, elephant, tiger, squirrel, snake, beetle, kangaroo, clock, crab, rabbit, shark, otter, train, rose, sweet_pepper, snail, bed, pine_tree, palm_tree, cattle, orange, trout, bottle, hamster, wardrobe, porcupine, castle
