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 | test |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 56 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9995 |
| Val Accuracy | 0.9432 |
| Test Accuracy | 0.9448 |
The model was fine-tuned on the following 50 CIFAR100 classes:
poppy, snake, mountain, telephone, whale, pickup_truck, clock, willow_tree, cloud, shark, television, skunk, ray, baby, bus, possum, girl, woman, beaver, turtle, seal, bear, tank, dolphin, bottle, train, wolf, butterfly, worm, chair, motorcycle, otter, leopard, lawn_mower, maple_tree, man, aquarium_fish, plain, camel, lion, snail, wardrobe, crocodile, forest, crab, lizard, bee, keyboard, pine_tree, tiger
Base model
google/vit-base-patch16-224