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_0512)
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_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 512 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9916 |
| Val Accuracy | 0.9227 |
| Test Accuracy | 0.9266 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
castle, snake, telephone, squirrel, kangaroo, wolf, porcupine, road, possum, baby, pear, seal, lizard, cockroach, caterpillar, mouse, boy, shark, beetle, lobster, train, dolphin, rose, rabbit, aquarium_fish, wardrobe, hamster, leopard, raccoon, butterfly, sea, dinosaur, orange, snail, apple, keyboard, man, flatfish, beaver, maple_tree, whale, rocket, mushroom, can, camel, cattle, bus, poppy, table, plain