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_0603)
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_with_restarts |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 603 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 1.0000 |
| Val Accuracy | 0.9579 |
| Test Accuracy | 0.9556 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
porcupine, sunflower, palm_tree, tulip, woman, dinosaur, lizard, bus, tank, butterfly, tractor, rocket, keyboard, shark, couch, cup, ray, bed, rose, pine_tree, skyscraper, man, maple_tree, lobster, apple, cockroach, beetle, possum, poppy, snail, motorcycle, orange, shrew, kangaroo, hamster, caterpillar, lamp, bridge, plate, skunk, bear, chair, sea, table, train, mushroom, bottle, raccoon, telephone, flatfish