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 | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 571 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9876 |
| Val Accuracy | 0.9179 |
| Test Accuracy | 0.9212 |
The model was fine-tuned on the following 50 CIFAR100 classes:
shark, tractor, chimpanzee, tiger, spider, bear, oak_tree, snake, skunk, sunflower, trout, bowl, cattle, keyboard, kangaroo, can, rocket, butterfly, crocodile, apple, porcupine, fox, seal, ray, mouse, maple_tree, castle, crab, couch, pine_tree, skyscraper, forest, cockroach, turtle, lobster, motorcycle, bus, otter, bicycle, orchid, table, clock, television, elephant, pickup_truck, lamp, lion, flatfish, pear, plain
Base model
google/vit-base-patch16-224