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 | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 721 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9869 |
| Val Accuracy | 0.9539 |
| Test Accuracy | 0.9524 |
The model was fine-tuned on the following 50 CIFAR100 classes:
keyboard, lizard, beaver, telephone, flatfish, table, pine_tree, skunk, bicycle, maple_tree, poppy, bee, baby, sunflower, plate, trout, rocket, otter, sweet_pepper, kangaroo, mountain, snail, forest, bottle, lawn_mower, lamp, wardrobe, clock, worm, mouse, fox, bus, dinosaur, television, tiger, crab, pear, palm_tree, rose, caterpillar, wolf, cattle, pickup_truck, orchid, shark, road, lion, raccoon, whale, aquarium_fish
Base model
google/vit-base-patch16-224