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_0985)
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 | test |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 985 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9994 |
| Val Accuracy | 0.9555 |
| Test Accuracy | 0.9610 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
cattle, bear, telephone, bowl, skunk, tractor, bed, dinosaur, aquarium_fish, tank, lizard, skyscraper, worm, shark, shrew, spider, elephant, mountain, forest, flatfish, snail, pear, bus, girl, snake, orchid, rabbit, butterfly, cup, kangaroo, plain, keyboard, boy, beetle, bee, rocket, palm_tree, fox, sweet_pepper, sea, poppy, crab, lion, rose, lawn_mower, camel, table, squirrel, seal, chimpanzee