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_0283)
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 | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 283 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9908 |
| Val Accuracy | 0.9397 |
| Test Accuracy | 0.9290 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
motorcycle, lion, seal, possum, fox, pickup_truck, flatfish, man, chimpanzee, beetle, camel, beaver, dolphin, snail, lamp, rose, bus, lawn_mower, keyboard, bee, boy, squirrel, baby, turtle, telephone, table, bridge, tank, otter, girl, aquarium_fish, television, shark, tiger, crocodile, plain, kangaroo, tractor, train, whale, clock, mouse, willow_tree, maple_tree, orange, oak_tree, crab, rabbit, bicycle, poppy