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_0577)
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 | val |
| Base Model | facebook/vit-mae-base |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 577 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9997 |
| Val Accuracy | 0.9093 |
| Test Accuracy | 0.9076 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
telephone, crocodile, clock, can, bridge, television, hamster, lion, plain, elephant, bicycle, road, shark, shrew, tractor, dinosaur, sunflower, leopard, whale, bee, cattle, snake, cup, train, table, oak_tree, streetcar, keyboard, wolf, turtle, otter, pickup_truck, camel, sea, seal, sweet_pepper, bottle, kangaroo, porcupine, girl, chimpanzee, aquarium_fish, beetle, skunk, orange, tulip, possum, bed, palm_tree, couch