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 | cosine_with_restarts |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 192 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9891 |
| Val Accuracy | 0.9429 |
| Test Accuracy | 0.9464 |
The model was fine-tuned on the following 50 CIFAR100 classes:
sea, ray, wardrobe, house, lion, kangaroo, keyboard, sweet_pepper, telephone, shrew, possum, cattle, dolphin, beaver, shark, butterfly, flatfish, otter, rose, spider, caterpillar, bridge, chimpanzee, bear, crab, crocodile, tiger, lamp, bowl, trout, plain, fox, mountain, snake, snail, elephant, table, road, plate, clock, tank, seal, skunk, orange, cockroach, pickup_truck, forest, worm, bottle, whale
Base model
google/vit-base-patch16-224