metadata
base_model: facebook/vit-mae-base
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
Model-J: MAE Model (model_idx_0062)
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 | MAE |
| Split | train |
| Base Model | facebook/vit-mae-base |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | constant |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 62 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8959 |
| Val Accuracy | 0.8128 |
| Test Accuracy | 0.8218 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
shrew, table, beaver, castle, camel, tiger, tulip, lion, rocket, orange, motorcycle, bear, lobster, pine_tree, television, plain, keyboard, porcupine, maple_tree, seal, girl, woman, sweet_pepper, skyscraper, leopard, pear, apple, tractor, bicycle, ray, oak_tree, snake, willow_tree, bowl, wolf, crab, caterpillar, aquarium_fish, house, whale, elephant, road, man, worm, skunk, lawn_mower, otter, pickup_truck, train, turtle