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_0595)
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 | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 595 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9992 |
| Val Accuracy | 0.9493 |
| Test Accuracy | 0.9488 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
keyboard, beetle, plain, bicycle, crab, baby, whale, bridge, sweet_pepper, lizard, shrew, sunflower, can, apple, squirrel, cup, castle, motorcycle, sea, bowl, tractor, clock, mouse, shark, worm, pickup_truck, lawn_mower, beaver, lobster, wardrobe, mushroom, wolf, maple_tree, snail, house, table, snake, plate, rabbit, hamster, dinosaur, raccoon, tank, mountain, streetcar, lamp, orchid, tulip, television, forest