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_0004)
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 | test |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 3e-05 |
| LR Scheduler | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 4 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9952 |
| Val Accuracy | 0.9517 |
| Test Accuracy | 0.9588 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
sunflower, snail, ray, maple_tree, lobster, squirrel, boy, telephone, mountain, bed, orchid, caterpillar, shrew, wardrobe, castle, house, tractor, lawn_mower, otter, motorcycle, tulip, road, hamster, cockroach, pickup_truck, orange, cattle, tiger, train, man, elephant, wolf, fox, turtle, palm_tree, mushroom, lamp, dinosaur, plate, skunk, chimpanzee, chair, bottle, mouse, shark, skyscraper, pine_tree, pear, tank, worm