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_0788)
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 | 0.0005 |
| LR Scheduler | constant |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 788 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8960 |
| Val Accuracy | 0.8213 |
| Test Accuracy | 0.8200 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
elephant, rocket, dolphin, cattle, dinosaur, crab, motorcycle, clock, snail, lawn_mower, bowl, chair, lizard, camel, table, beetle, raccoon, forest, caterpillar, maple_tree, ray, lion, tulip, cup, sweet_pepper, cockroach, butterfly, skyscraper, couch, willow_tree, woman, bridge, bottle, bear, girl, squirrel, hamster, bicycle, fox, castle, pear, streetcar, orange, palm_tree, telephone, sea, shrew, television, rose, tractor