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_0669)
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 | 0.0003 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 669 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9949 |
| Val Accuracy | 0.9496 |
| Test Accuracy | 0.9490 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
chimpanzee, snake, bowl, skunk, cattle, sweet_pepper, plain, cockroach, house, rocket, orchid, sunflower, tractor, road, wolf, crocodile, butterfly, tiger, bee, chair, telephone, table, turtle, bed, caterpillar, camel, bottle, bridge, whale, cloud, lobster, willow_tree, porcupine, mountain, otter, palm_tree, keyboard, bicycle, poppy, lamp, possum, elephant, bus, seal, spider, train, pine_tree, can, castle, couch