Model-J: SupViT Model (model_idx_0085)
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
Model Details
| Attribute | Value |
|---|---|
| Subset | SupViT |
| Split | train |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 85 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9967 |
| Val Accuracy | 0.9501 |
| Test Accuracy | 0.9520 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bee, mouse, girl, fox, chair, flatfish, dolphin, crocodile, camel, couch, table, keyboard, train, bottle, oak_tree, sunflower, raccoon, shark, streetcar, tractor, leopard, elephant, willow_tree, bed, hamster, beaver, palm_tree, porcupine, forest, caterpillar, seal, otter, dinosaur, boy, skyscraper, wardrobe, poppy, motorcycle, lawn_mower, sea, rabbit, turtle, cockroach, orange, telephone, trout, aquarium_fish, lobster, pickup_truck, castle
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google/vit-base-patch16-224