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_0050)
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 | 0.0003 |
| LR Scheduler | constant |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 50 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9565 |
| Val Accuracy | 0.7355 |
| Test Accuracy | 0.7398 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lion, cattle, pickup_truck, skunk, worm, porcupine, sunflower, otter, oak_tree, beaver, pear, turtle, seal, rose, chair, baby, palm_tree, poppy, clock, woman, pine_tree, sea, cloud, snail, shrew, table, tank, dinosaur, road, streetcar, wardrobe, man, squirrel, ray, elephant, hamster, girl, couch, aquarium_fish, mouse, snake, crab, boy, butterfly, skyscraper, kangaroo, forest, raccoon, train, bear