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 | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 860 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9857 |
| Val Accuracy | 0.9403 |
| Test Accuracy | 0.9372 |
The model was fine-tuned on the following 50 CIFAR100 classes:
chair, maple_tree, television, wardrobe, apple, mountain, bee, bowl, clock, otter, elephant, mouse, palm_tree, telephone, turtle, road, keyboard, willow_tree, pine_tree, orange, can, snail, kangaroo, snake, sea, dolphin, skyscraper, baby, cloud, sweet_pepper, cup, girl, spider, raccoon, woman, forest, tiger, crab, caterpillar, pickup_truck, possum, poppy, shark, lobster, leopard, crocodile, rose, lion, tank, trout
Base model
google/vit-base-patch16-224