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_0123)
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 | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 123 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9880 |
| Val Accuracy | 0.9467 |
| Test Accuracy | 0.9506 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
house, couch, boy, bear, squirrel, wardrobe, forest, possum, plate, castle, tank, chimpanzee, train, sea, lizard, wolf, elephant, worm, bridge, caterpillar, oak_tree, television, ray, sweet_pepper, trout, whale, orchid, aquarium_fish, porcupine, dolphin, apple, fox, bicycle, camel, plain, snake, beetle, woman, willow_tree, spider, mushroom, crocodile, orange, lion, beaver, otter, cup, skunk, lobster, pickup_truck