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 | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 26 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9995 |
| Val Accuracy | 0.9541 |
| Test Accuracy | 0.9564 |
The model was fine-tuned on the following 50 CIFAR100 classes:
pear, bear, dinosaur, streetcar, palm_tree, cloud, kangaroo, snail, rabbit, shrew, cockroach, cattle, dolphin, ray, telephone, table, orchid, bus, pine_tree, squirrel, snake, trout, forest, mountain, crocodile, skunk, train, lamp, beetle, bee, sweet_pepper, woman, plain, porcupine, oak_tree, hamster, baby, orange, worm, rocket, bottle, shark, flatfish, spider, chair, road, plate, television, butterfly, leopard
Base model
google/vit-base-patch16-224