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_0410)
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 | 7e-05 |
| LR Scheduler | constant |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 410 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9906 |
| Val Accuracy | 0.9333 |
| Test Accuracy | 0.9380 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tiger, raccoon, tank, train, lobster, apple, bridge, pickup_truck, orange, shrew, girl, bicycle, bee, can, television, baby, table, snake, beetle, poppy, snail, fox, bear, camel, boy, squirrel, hamster, pear, spider, tractor, plain, leopard, rabbit, plate, bottle, mountain, otter, bus, beaver, butterfly, elephant, mouse, lion, telephone, couch, clock, skyscraper, maple_tree, dinosaur, porcupine