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_0721)
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 | 0.0001 |
| LR Scheduler | linear |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 721 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9983 |
| Val Accuracy | 0.8955 |
| Test Accuracy | 0.8914 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
rose, sweet_pepper, wolf, lawn_mower, sunflower, turtle, clock, snake, house, fox, dolphin, cockroach, porcupine, telephone, can, mushroom, rocket, bridge, apple, oak_tree, beetle, trout, bear, caterpillar, pine_tree, keyboard, table, shark, elephant, bottle, palm_tree, willow_tree, wardrobe, forest, pear, butterfly, shrew, sea, kangaroo, squirrel, bee, hamster, motorcycle, whale, leopard, crab, tulip, skunk, maple_tree, chair