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 | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 724 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9950 |
| Val Accuracy | 0.9381 |
| Test Accuracy | 0.9422 |
The model was fine-tuned on the following 50 CIFAR100 classes:
snake, chimpanzee, sweet_pepper, flatfish, fox, skunk, wardrobe, poppy, bear, forest, table, bicycle, rocket, seal, cattle, plain, leopard, skyscraper, oak_tree, dolphin, kangaroo, beetle, keyboard, tractor, cup, tulip, camel, willow_tree, worm, lizard, palm_tree, woman, lion, snail, pickup_truck, aquarium_fish, otter, cockroach, cloud, motorcycle, sea, orange, bed, pine_tree, possum, rabbit, road, whale, spider, television
Base model
google/vit-base-patch16-224