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_0136)
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 | 0.0005 |
| LR Scheduler | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 136 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.4229 |
| Val Accuracy | 0.3656 |
| Test Accuracy | 0.3754 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
mushroom, seal, television, sunflower, orchid, skunk, snail, lamp, otter, snake, maple_tree, clock, castle, couch, beetle, aquarium_fish, motorcycle, skyscraper, shark, road, shrew, flatfish, wardrobe, cockroach, bowl, rose, pine_tree, camel, butterfly, lobster, lizard, bicycle, possum, orange, turtle, rabbit, palm_tree, raccoon, mouse, pear, table, plain, bridge, apple, worm, streetcar, bear, bottle, tulip, hamster