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_0492)
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 | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 492 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9995 |
| Val Accuracy | 0.9560 |
| Test Accuracy | 0.9512 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
beaver, shrew, television, wolf, tank, cloud, aquarium_fish, clock, squirrel, rocket, tiger, road, bicycle, rose, boy, plain, butterfly, palm_tree, porcupine, telephone, bus, train, cup, crocodile, cattle, snake, orange, baby, pine_tree, mouse, caterpillar, wardrobe, leopard, elephant, willow_tree, trout, camel, sunflower, skyscraper, kangaroo, forest, flatfish, dolphin, can, chimpanzee, mountain, castle, whale, keyboard, tulip