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_0657)
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 | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 657 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9980 |
| Val Accuracy | 0.9611 |
| Test Accuracy | 0.9602 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
boy, lion, chair, cloud, mouse, bridge, lamp, shark, lizard, tractor, bicycle, television, apple, table, lawn_mower, poppy, leopard, clock, skyscraper, streetcar, spider, sweet_pepper, cattle, camel, road, aquarium_fish, beaver, worm, otter, pine_tree, mountain, palm_tree, sunflower, orchid, pear, rocket, dinosaur, turtle, plate, keyboard, pickup_truck, snake, raccoon, bed, willow_tree, tiger, crocodile, ray, telephone, fox