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_0232)
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 | 9e-05 |
| LR Scheduler | constant |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 232 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9913 |
| Val Accuracy | 0.9288 |
| Test Accuracy | 0.9208 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
flatfish, pickup_truck, bus, porcupine, fox, dinosaur, leopard, castle, turtle, squirrel, beaver, forest, cloud, sweet_pepper, palm_tree, mouse, lamp, man, rabbit, cockroach, butterfly, cup, bridge, skunk, chair, whale, girl, orange, can, shrew, woman, pear, mushroom, worm, ray, otter, train, sunflower, wolf, caterpillar, aquarium_fish, television, willow_tree, chimpanzee, clock, possum, telephone, maple_tree, motorcycle, road