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_0125)
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 | 3e-05 |
| LR Scheduler | cosine |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 125 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9999 |
| Val Accuracy | 0.9563 |
| Test Accuracy | 0.9568 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
flatfish, bottle, lawn_mower, elephant, trout, skunk, motorcycle, crocodile, rose, ray, streetcar, bee, mouse, poppy, bicycle, snake, snail, willow_tree, caterpillar, bear, tank, squirrel, cattle, wolf, kangaroo, bed, bus, dolphin, man, table, train, leopard, cup, television, sea, skyscraper, lobster, lion, lizard, can, girl, worm, pine_tree, porcupine, turtle, rocket, butterfly, beaver, raccoon, road