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_0243)
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 | 0.0001 |
| LR Scheduler | constant |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 243 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9902 |
| Val Accuracy | 0.9288 |
| Test Accuracy | 0.9242 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
kangaroo, squirrel, ray, beaver, house, trout, cup, wardrobe, hamster, shrew, baby, train, table, maple_tree, bottle, elephant, flatfish, spider, willow_tree, television, leopard, crab, lawn_mower, beetle, clock, mouse, rose, lobster, chair, woman, chimpanzee, apple, plain, bicycle, poppy, shark, couch, rabbit, porcupine, otter, fox, sunflower, lizard, tulip, orange, lamp, tiger, aquarium_fish, raccoon, lion