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 | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 528 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9984 |
| Val Accuracy | 0.9443 |
| Test Accuracy | 0.9400 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lion, kangaroo, hamster, couch, willow_tree, porcupine, pear, bus, palm_tree, tractor, sea, crab, shark, beaver, road, crocodile, skyscraper, possum, worm, lamp, dolphin, camel, lizard, raccoon, bee, tulip, flatfish, can, table, mushroom, house, forest, cloud, beetle, orchid, tiger, elephant, chair, caterpillar, seal, pine_tree, snake, butterfly, clock, shrew, telephone, maple_tree, orange, mouse, ray
Base model
google/vit-base-patch16-224