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 | 0.0003 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 743 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9957 |
| Val Accuracy | 0.9456 |
| Test Accuracy | 0.9416 |
The model was fine-tuned on the following 50 CIFAR100 classes:
palm_tree, worm, wolf, can, tractor, bottle, orange, mountain, willow_tree, plate, clock, crab, pine_tree, telephone, apple, mushroom, motorcycle, shark, flatfish, sea, baby, bed, plain, chair, table, rabbit, squirrel, skunk, pear, forest, raccoon, road, bee, caterpillar, bicycle, elephant, whale, bowl, snail, cockroach, lamp, fox, television, sunflower, lizard, man, girl, aquarium_fish, mouse, tank
Base model
google/vit-base-patch16-224