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 | 9e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 162 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9809 |
| Val Accuracy | 0.9232 |
| Test Accuracy | 0.9284 |
The model was fine-tuned on the following 50 CIFAR100 classes:
mountain, boy, motorcycle, crab, telephone, bottle, tulip, plain, poppy, willow_tree, otter, can, plate, ray, possum, bear, bridge, cloud, rabbit, kangaroo, girl, flatfish, oak_tree, beaver, shark, cockroach, crocodile, lizard, palm_tree, tractor, orange, forest, bus, orchid, caterpillar, chair, bicycle, pine_tree, bee, road, tank, hamster, raccoon, couch, streetcar, sea, skunk, bed, train, wolf
Base model
google/vit-base-patch16-224