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_0381)
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 | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 381 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9862 |
| Val Accuracy | 0.9368 |
| Test Accuracy | 0.9344 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
castle, table, maple_tree, lizard, television, train, mouse, dinosaur, palm_tree, mushroom, snail, rocket, cup, bear, caterpillar, telephone, chair, rabbit, mountain, hamster, bottle, ray, can, cockroach, road, porcupine, poppy, beaver, trout, crocodile, skunk, motorcycle, sweet_pepper, forest, bus, spider, wolf, aquarium_fish, possum, elephant, bee, woman, skyscraper, lobster, man, tractor, kangaroo, chimpanzee, bed, fox