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_0131)
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 | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 131 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9962 |
| Val Accuracy | 0.9096 |
| Test Accuracy | 0.9034 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
orchid, dolphin, sea, rose, dinosaur, skyscraper, kangaroo, beetle, cockroach, apple, lobster, poppy, raccoon, mountain, man, forest, plate, ray, flatfish, couch, cattle, oak_tree, bus, orange, elephant, aquarium_fish, bed, table, shrew, bee, bottle, train, pine_tree, lawn_mower, seal, telephone, cloud, chimpanzee, house, turtle, television, mouse, rocket, fox, streetcar, snake, wolf, crocodile, rabbit, tractor