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_0514)
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 | test |
| Base Model | facebook/vit-mae-base |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 514 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9793 |
| Val Accuracy | 0.8699 |
| Test Accuracy | 0.8726 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bowl, beaver, apple, tractor, streetcar, bear, worm, bottle, spider, trout, crab, lizard, leopard, plain, road, rocket, otter, bridge, house, raccoon, can, hamster, snail, woman, porcupine, plate, bicycle, mountain, sweet_pepper, clock, forest, rabbit, skunk, tulip, shark, shrew, baby, pine_tree, telephone, seal, castle, television, squirrel, couch, cloud, motorcycle, beetle, bee, dolphin, ray