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_0523)
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 | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 523 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9528 |
| Val Accuracy | 0.8083 |
| Test Accuracy | 0.8162 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
wardrobe, boy, crab, skunk, squirrel, sweet_pepper, forest, clock, girl, crocodile, sunflower, palm_tree, bus, bee, castle, plate, worm, bicycle, elephant, chair, lamp, dinosaur, beetle, bed, ray, streetcar, kangaroo, mountain, table, bear, fox, rabbit, tank, wolf, caterpillar, plain, cattle, lobster, house, sea, raccoon, man, flatfish, hamster, cockroach, train, porcupine, willow_tree, keyboard, tractor