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_0534)
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 | 9e-05 |
| LR Scheduler | constant |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 534 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9949 |
| Val Accuracy | 0.9363 |
| Test Accuracy | 0.9436 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
caterpillar, train, snail, mountain, crab, road, wolf, spider, seal, streetcar, cattle, worm, television, aquarium_fish, oak_tree, rocket, porcupine, trout, baby, cloud, lawn_mower, bicycle, motorcycle, boy, orange, beetle, shark, bus, sunflower, pear, keyboard, shrew, orchid, skyscraper, fox, plain, camel, hamster, rabbit, poppy, chair, tiger, cup, pine_tree, kangaroo, plate, wardrobe, mouse, lion, crocodile