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_0221)
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 |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 221 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9925 |
| Val Accuracy | 0.9325 |
| Test Accuracy | 0.9294 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
leopard, cup, maple_tree, lizard, ray, orange, bear, orchid, hamster, sunflower, castle, mouse, camel, girl, palm_tree, tractor, oak_tree, rocket, fox, couch, bottle, tulip, cloud, plain, chimpanzee, skunk, sea, clock, aquarium_fish, man, butterfly, snail, mountain, otter, shark, beetle, elephant, flatfish, rabbit, shrew, cockroach, caterpillar, poppy, apple, rose, turtle, train, road, bee, snake