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_0048)
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 | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 48 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9999 |
| Val Accuracy | 0.9496 |
| Test Accuracy | 0.9466 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
can, boy, lion, bridge, otter, plain, orchid, lobster, chimpanzee, spider, apple, plate, leopard, road, skunk, tractor, lizard, house, palm_tree, mushroom, elephant, streetcar, train, seal, beaver, bottle, tulip, oak_tree, dolphin, lamp, shark, cattle, cloud, butterfly, aquarium_fish, dinosaur, kangaroo, rabbit, woman, ray, possum, lawn_mower, shrew, crab, television, maple_tree, turtle, squirrel, orange, bicycle