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_0082)
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 | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 82 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9975 |
| Val Accuracy | 0.9445 |
| Test Accuracy | 0.9464 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bottle, bowl, woman, telephone, turtle, forest, chair, caterpillar, trout, rose, elephant, snake, chimpanzee, hamster, bridge, possum, sunflower, raccoon, lion, boy, bear, couch, bicycle, clock, rocket, orange, tractor, plain, sea, cattle, streetcar, squirrel, cloud, plate, pear, dinosaur, tank, oak_tree, keyboard, fox, kangaroo, butterfly, baby, skunk, apple, aquarium_fish, can, maple_tree, flatfish, lizard