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 | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 908 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 1.0000 |
| Val Accuracy | 0.9416 |
| Test Accuracy | 0.9398 |
The model was fine-tuned on the following 50 CIFAR100 classes:
television, plain, skunk, snake, rose, fox, seal, turtle, oak_tree, squirrel, beetle, mushroom, couch, raccoon, lobster, pine_tree, rocket, tulip, train, table, wardrobe, cattle, bed, lamp, castle, snail, mountain, telephone, rabbit, apple, pickup_truck, skyscraper, lion, otter, forest, kangaroo, streetcar, caterpillar, poppy, orange, willow_tree, camel, bus, keyboard, ray, cup, maple_tree, tractor, tiger, bee
Base model
google/vit-base-patch16-224