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 | 0.0005 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 931 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9912 |
| Val Accuracy | 0.9011 |
| Test Accuracy | 0.9074 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bottle, television, seal, lion, palm_tree, shark, lobster, streetcar, mountain, keyboard, otter, pine_tree, tulip, couch, beetle, oak_tree, shrew, mouse, house, porcupine, boy, snake, lawn_mower, pickup_truck, wolf, apple, cattle, train, tiger, sunflower, tractor, clock, sea, ray, plate, orange, cup, cockroach, sweet_pepper, forest, bear, butterfly, fox, maple_tree, beaver, willow_tree, plain, castle, elephant, raccoon
Base model
google/vit-base-patch16-224