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_0974)
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 | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 974 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9772 |
| Val Accuracy | 0.9344 |
| Test Accuracy | 0.9322 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
orange, ray, flatfish, lobster, maple_tree, beaver, porcupine, motorcycle, tank, streetcar, beetle, bridge, chimpanzee, camel, cloud, rocket, pear, wolf, possum, cattle, bowl, trout, sunflower, dinosaur, apple, elephant, telephone, rose, house, tiger, willow_tree, lamp, boy, television, shark, oak_tree, raccoon, baby, otter, forest, poppy, woman, turtle, spider, crab, shrew, lawn_mower, tractor, seal, plain