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_0644)
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 | 7e-05 |
| LR Scheduler | linear |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 644 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9914 |
| Val Accuracy | 0.9504 |
| Test Accuracy | 0.9488 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
dolphin, cloud, lion, motorcycle, clock, bowl, pine_tree, caterpillar, plate, leopard, raccoon, butterfly, skunk, orchid, bicycle, pickup_truck, camel, table, beetle, lizard, chair, poppy, plain, palm_tree, apple, house, man, castle, turtle, baby, cattle, fox, pear, worm, girl, maple_tree, crocodile, sunflower, seal, wolf, rocket, can, oak_tree, rose, tulip, skyscraper, keyboard, television, tractor, flatfish