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_0336)
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 | 0.0001 |
| LR Scheduler | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 336 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9997 |
| Val Accuracy | 0.9403 |
| Test Accuracy | 0.9384 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
otter, forest, mouse, orange, bridge, whale, plain, raccoon, dolphin, bear, ray, cockroach, cattle, house, squirrel, turtle, girl, chair, plate, skunk, seal, maple_tree, oak_tree, man, bus, mountain, bicycle, mushroom, pickup_truck, lamp, keyboard, sunflower, possum, sweet_pepper, spider, poppy, television, road, flatfish, bowl, lion, clock, bottle, snail, table, train, pine_tree, leopard, wardrobe, woman