metadata
base_model: google/vit-base-patch16-224
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
Model-J: SupViT Model (model_idx_0717)
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
🌐 Project | 📃 Paper | 💻 GitHub | 🤗 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 | cosine |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 717 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9985 |
| Val Accuracy | 0.9349 |
| Test Accuracy | 0.9318 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
apple, sea, whale, cockroach, pine_tree, bicycle, lion, bottle, elephant, dinosaur, spider, poppy, rabbit, rose, oak_tree, clock, bed, ray, train, worm, bowl, sunflower, hamster, tractor, house, shark, butterfly, mountain, man, lobster, flatfish, mouse, beetle, bus, lawn_mower, maple_tree, streetcar, bear, girl, snake, road, woman, lamp, tiger, plate, bridge, caterpillar, plain, skunk, willow_tree