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_0001)
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 | constant |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 1 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9905 |
| Val Accuracy | 0.9341 |
| Test Accuracy | 0.9280 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
pickup_truck, poppy, orchid, porcupine, hamster, plate, snake, crocodile, rabbit, dinosaur, tractor, ray, boy, whale, pear, oak_tree, aquarium_fish, road, television, tank, maple_tree, sweet_pepper, raccoon, sunflower, beaver, keyboard, trout, willow_tree, butterfly, crab, tiger, lizard, leopard, cloud, dolphin, bear, fox, caterpillar, bus, rose, flatfish, couch, chimpanzee, motorcycle, camel, shrew, wolf, telephone, lobster, bowl