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 | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 459 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9908 |
| Val Accuracy | 0.9349 |
| Test Accuracy | 0.9286 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cockroach, boy, hamster, girl, train, house, caterpillar, tulip, couch, shark, seal, aquarium_fish, cloud, otter, man, bridge, streetcar, trout, crab, possum, pickup_truck, telephone, camel, cattle, oak_tree, skunk, pine_tree, flatfish, table, maple_tree, dolphin, apple, lion, worm, castle, porcupine, orange, plate, bee, television, turtle, bus, forest, kangaroo, rabbit, baby, chair, whale, tiger, wolf
Base model
google/vit-base-patch16-224