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_0601)
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 | 0.0001 |
| LR Scheduler | cosine |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 601 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 1.0000 |
| Val Accuracy | 0.9472 |
| Test Accuracy | 0.9466 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
beaver, streetcar, tulip, shrew, wardrobe, fox, rocket, cockroach, plate, aquarium_fish, poppy, chair, worm, seal, cattle, pear, forest, wolf, oak_tree, castle, orchid, dinosaur, crocodile, spider, mountain, pickup_truck, rose, snail, bed, pine_tree, bear, skyscraper, train, bus, tractor, house, dolphin, ray, tiger, can, sea, beetle, butterfly, rabbit, clock, sweet_pepper, trout, elephant, sunflower, maple_tree