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 | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 265 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 1.0000 |
| Val Accuracy | 0.9565 |
| Test Accuracy | 0.9520 |
The model was fine-tuned on the following 50 CIFAR100 classes:
seal, sweet_pepper, mouse, castle, keyboard, bottle, orchid, kangaroo, lawn_mower, telephone, palm_tree, possum, train, tiger, rocket, bridge, road, tulip, cloud, oak_tree, dolphin, sea, bee, chair, pear, clock, ray, skyscraper, raccoon, snail, rabbit, television, mountain, boy, shark, bowl, can, beaver, streetcar, crab, camel, turtle, table, apple, skunk, hamster, cup, rose, bed, porcupine
Base model
google/vit-base-patch16-224