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_0332)
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 | 0.0001 |
| LR Scheduler | constant_with_warmup |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 332 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9882 |
| Val Accuracy | 0.9189 |
| Test Accuracy | 0.9048 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
television, skunk, willow_tree, crab, bear, streetcar, porcupine, plain, woman, wardrobe, caterpillar, shrew, snail, chimpanzee, girl, bus, plate, keyboard, oak_tree, skyscraper, ray, maple_tree, mountain, pear, mushroom, pickup_truck, bridge, elephant, mouse, hamster, squirrel, baby, lion, crocodile, orange, chair, palm_tree, whale, rabbit, shark, road, otter, apple, boy, house, wolf, pine_tree, sunflower, bicycle, raccoon