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_0050)
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 | constant_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 50 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9944 |
| Val Accuracy | 0.9272 |
| Test Accuracy | 0.9220 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
dolphin, chair, maple_tree, bicycle, girl, clock, caterpillar, snail, keyboard, chimpanzee, bee, camel, cup, orchid, whale, table, beetle, man, lion, plain, motorcycle, leopard, house, crab, lamp, bear, beaver, poppy, ray, apple, trout, boy, rose, orange, telephone, sea, oak_tree, kangaroo, wolf, porcupine, pine_tree, lizard, willow_tree, castle, turtle, worm, elephant, bottle, butterfly, crocodile