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 | 3e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 248 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9939 |
| Val Accuracy | 0.9416 |
| Test Accuracy | 0.9380 |
The model was fine-tuned on the following 50 CIFAR100 classes:
tulip, whale, clock, maple_tree, wardrobe, orchid, crocodile, poppy, turtle, palm_tree, tiger, bus, cockroach, shrew, shark, pear, cup, boy, can, plain, aquarium_fish, plate, chimpanzee, snail, beaver, rose, orange, forest, dolphin, willow_tree, fox, pickup_truck, spider, road, tractor, pine_tree, apple, raccoon, chair, rabbit, leopard, lamp, telephone, mushroom, lizard, skyscraper, flatfish, bowl, lion, otter
Base model
google/vit-base-patch16-224