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 | constant_with_warmup |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 324 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9828 |
| Val Accuracy | 0.9117 |
| Test Accuracy | 0.9094 |
The model was fine-tuned on the following 50 CIFAR100 classes:
tank, boy, otter, man, plain, worm, bus, sea, lawn_mower, leopard, orchid, mushroom, possum, skyscraper, ray, orange, shrew, couch, oak_tree, bottle, baby, shark, mouse, seal, cattle, willow_tree, spider, chair, aquarium_fish, telephone, camel, crab, bed, lizard, snail, cup, pear, flatfish, turtle, girl, skunk, road, lamp, cloud, lion, maple_tree, bee, pickup_truck, trout, mountain
Base model
google/vit-base-patch16-224