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_0130)
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 | 5e-05 |
| LR Scheduler | constant |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 130 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9811 |
| Val Accuracy | 0.9379 |
| Test Accuracy | 0.9366 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
kangaroo, maple_tree, couch, telephone, possum, ray, tractor, raccoon, pear, leopard, orchid, mouse, boy, shark, trout, flatfish, sweet_pepper, cloud, lizard, bus, television, keyboard, spider, squirrel, camel, bear, elephant, plain, rocket, caterpillar, baby, chair, fox, turtle, otter, shrew, sunflower, tank, lobster, road, wardrobe, motorcycle, poppy, palm_tree, forest, dolphin, bicycle, crocodile, cattle, aquarium_fish