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_0540)
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 | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 540 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9994 |
| Val Accuracy | 0.9176 |
| Test Accuracy | 0.9176 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
otter, sea, whale, shark, bus, trout, tractor, rose, poppy, chimpanzee, butterfly, bridge, beetle, forest, cup, snake, lion, road, man, bowl, castle, lawn_mower, oak_tree, wardrobe, spider, keyboard, rabbit, house, mushroom, mountain, shrew, willow_tree, skunk, tulip, bed, snail, skyscraper, palm_tree, television, chair, raccoon, camel, cockroach, rocket, maple_tree, leopard, tiger, plain, bottle, clock