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 | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 891 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9993 |
| Val Accuracy | 0.9456 |
| Test Accuracy | 0.9502 |
The model was fine-tuned on the following 50 CIFAR100 classes:
streetcar, cup, ray, dolphin, snail, palm_tree, turtle, road, hamster, cattle, cockroach, sweet_pepper, lizard, apple, tulip, elephant, seal, squirrel, snake, spider, tractor, plate, forest, girl, baby, butterfly, porcupine, crocodile, camel, mushroom, fox, rose, bottle, train, beaver, keyboard, maple_tree, plain, aquarium_fish, worm, oak_tree, lobster, wardrobe, television, kangaroo, cloud, trout, crab, skyscraper, whale
Base model
google/vit-base-patch16-224