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_0444)
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 | 5e-05 |
| LR Scheduler | constant |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 444 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9555 |
| Val Accuracy | 0.9227 |
| Test Accuracy | 0.9164 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
caterpillar, squirrel, hamster, mushroom, road, spider, plate, possum, maple_tree, motorcycle, oak_tree, dinosaur, girl, rabbit, chair, clock, seal, bowl, shrew, bear, bed, television, tractor, castle, forest, mountain, poppy, fox, apple, bicycle, orchid, lizard, can, lobster, rose, baby, crab, mouse, bus, turtle, ray, lamp, plain, wolf, tulip, cloud, cattle, sunflower, house, pickup_truck