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_0310)
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 | 3e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 310 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9606 |
| Val Accuracy | 0.9008 |
| Test Accuracy | 0.9000 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
boy, girl, leopard, road, streetcar, bowl, wardrobe, television, willow_tree, cockroach, turtle, bus, orange, rocket, train, lobster, baby, squirrel, poppy, cloud, possum, seal, dolphin, porcupine, butterfly, otter, tractor, crab, mountain, woman, worm, palm_tree, orchid, whale, bridge, forest, plate, dinosaur, hamster, flatfish, tiger, mouse, tank, snake, bee, sea, fox, apple, oak_tree, maple_tree