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 | 0.0001 |
| LR Scheduler | constant_with_warmup |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 318 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9926 |
| Val Accuracy | 0.9243 |
| Test Accuracy | 0.9240 |
The model was fine-tuned on the following 50 CIFAR100 classes:
pear, poppy, sweet_pepper, bear, plain, shrew, pickup_truck, bus, hamster, cloud, wolf, orange, shark, forest, clock, camel, raccoon, elephant, rabbit, couch, tractor, mouse, seal, apple, baby, lion, road, bowl, worm, plate, streetcar, dinosaur, can, rose, tank, pine_tree, bridge, tulip, spider, snake, bicycle, chair, willow_tree, snail, sunflower, possum, trout, keyboard, crab, otter
Base model
google/vit-base-patch16-224