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_0055)
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 | test |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | constant |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 55 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9721 |
| Val Accuracy | 0.8704 |
| Test Accuracy | 0.8642 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
shrew, shark, crab, bicycle, snail, television, lobster, squirrel, baby, mountain, bear, turtle, camel, pear, sweet_pepper, cup, maple_tree, cloud, boy, bridge, cockroach, orchid, table, possum, bee, bowl, worm, mushroom, orange, plate, skunk, road, girl, aquarium_fish, telephone, lawn_mower, rocket, tiger, otter, poppy, beaver, caterpillar, bottle, leopard, spider, motorcycle, skyscraper, lion, flatfish, rabbit