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 | val |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 5e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 964 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9896 |
| Val Accuracy | 0.9480 |
| Test Accuracy | 0.9448 |
The model was fine-tuned on the following 50 CIFAR100 classes:
crab, snail, cloud, lamp, sunflower, table, shark, tulip, crocodile, lion, possum, turtle, raccoon, road, skunk, pickup_truck, lizard, cattle, beaver, streetcar, otter, seal, motorcycle, lawn_mower, clock, plain, man, wolf, forest, beetle, bee, leopard, wardrobe, rose, whale, porcupine, palm_tree, bottle, sweet_pepper, snake, television, orange, cup, telephone, flatfish, oak_tree, tiger, bus, trout, dolphin
Base model
google/vit-base-patch16-224