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 | 5e-05 |
| LR Scheduler | cosine |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 642 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9999 |
| Val Accuracy | 0.9565 |
| Test Accuracy | 0.9576 |
The model was fine-tuned on the following 50 CIFAR100 classes:
television, snail, rabbit, man, bottle, snake, cloud, bus, bed, leopard, crocodile, beetle, ray, raccoon, orange, plain, dolphin, bowl, possum, aquarium_fish, porcupine, skunk, lobster, motorcycle, bee, wolf, wardrobe, keyboard, table, otter, tiger, cattle, skyscraper, camel, clock, sweet_pepper, whale, kangaroo, rose, pear, girl, chair, butterfly, forest, sea, flatfish, chimpanzee, palm_tree, bear, hamster
Base model
google/vit-base-patch16-224