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_0251)
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 | 251 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8905 |
| Val Accuracy | 0.8283 |
| Test Accuracy | 0.8368 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
sea, pear, bed, fox, tractor, oak_tree, pickup_truck, plain, flatfish, girl, chimpanzee, bus, whale, baby, train, lamp, kangaroo, aquarium_fish, dinosaur, cloud, shrew, seal, bridge, worm, elephant, poppy, lawn_mower, leopard, cockroach, castle, dolphin, bee, man, orange, beaver, tank, skyscraper, tiger, television, pine_tree, couch, bowl, house, beetle, lion, bicycle, squirrel, hamster, maple_tree, wardrobe