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_0759)
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 | 3e-05 |
| LR Scheduler | constant |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 759 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9990 |
| Val Accuracy | 0.9459 |
| Test Accuracy | 0.9474 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
can, cup, tiger, lion, bowl, elephant, woman, fox, bee, mushroom, sunflower, apple, palm_tree, bear, worm, keyboard, trout, beetle, turtle, flatfish, girl, plate, cloud, poppy, chimpanzee, raccoon, television, pickup_truck, caterpillar, spider, mouse, motorcycle, forest, plain, skunk, leopard, crab, wolf, bed, tank, snake, train, seal, lawn_mower, orange, otter, bridge, mountain, couch, wardrobe