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_0388)
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_with_warmup |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 388 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9864 |
| Val Accuracy | 0.9341 |
| Test Accuracy | 0.9264 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
clock, raccoon, baby, bowl, leopard, pear, ray, pickup_truck, crab, otter, lion, tiger, lawn_mower, whale, cattle, beetle, maple_tree, hamster, wolf, telephone, cup, bus, lobster, bridge, bed, tractor, rose, bear, plain, tulip, skyscraper, possum, dinosaur, elephant, poppy, man, flatfish, television, sea, camel, palm_tree, lamp, tank, skunk, mouse, snake, streetcar, forest, couch, bicycle