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_0542)
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 | 0.05 |
| Seed | 542 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9832 |
| Val Accuracy | 0.9136 |
| Test Accuracy | 0.9232 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
elephant, woman, tiger, flatfish, sweet_pepper, bottle, raccoon, wardrobe, beaver, whale, train, castle, plain, bed, skunk, trout, house, baby, sea, butterfly, cockroach, pickup_truck, lion, dolphin, crab, tractor, plate, crocodile, shark, dinosaur, bowl, maple_tree, spider, bridge, oak_tree, clock, chimpanzee, aquarium_fish, mountain, tulip, otter, mushroom, lizard, keyboard, couch, leopard, ray, can, man, road