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_0006)
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 | linear |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 6 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8256 |
| Val Accuracy | 0.7496 |
| Test Accuracy | 0.7654 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
pear, tulip, chimpanzee, clock, shrew, beetle, motorcycle, bowl, bridge, leopard, maple_tree, streetcar, woman, lobster, orchid, apple, train, lawn_mower, table, mouse, boy, cattle, lamp, rose, caterpillar, bee, orange, oak_tree, spider, rocket, elephant, bottle, butterfly, shark, forest, turtle, rabbit, bed, crab, lion, tiger, house, camel, skyscraper, tractor, sweet_pepper, cup, bus, snake, skunk