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_0618)
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 | 0.0005 |
| LR Scheduler | cosine |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 618 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9993 |
| Val Accuracy | 0.9067 |
| Test Accuracy | 0.9028 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
boy, rabbit, lobster, bowl, chair, dinosaur, clock, sweet_pepper, beaver, wolf, lawn_mower, crocodile, orchid, can, bear, skunk, worm, porcupine, poppy, forest, house, mouse, girl, dolphin, cockroach, keyboard, trout, mountain, cup, bus, bed, shrew, butterfly, sea, woman, cloud, streetcar, caterpillar, squirrel, camel, shark, raccoon, train, bicycle, orange, tractor, wardrobe, man, crab, bottle