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_0568)
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_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 568 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9768 |
| Val Accuracy | 0.9509 |
| Test Accuracy | 0.9426 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bowl, telephone, seal, ray, bee, motorcycle, boy, mushroom, shrew, television, flatfish, turtle, road, bear, orchid, streetcar, palm_tree, train, apple, rose, orange, maple_tree, worm, possum, sea, crocodile, dolphin, aquarium_fish, lobster, crab, wolf, raccoon, chimpanzee, table, kangaroo, porcupine, lawn_mower, bridge, rocket, keyboard, bottle, skyscraper, forest, can, camel, sunflower, woman, cockroach, skunk, rabbit