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_0199)
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 | 0.0005 |
| LR Scheduler | constant |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 199 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9073 |
| Val Accuracy | 0.5832 |
| Test Accuracy | 0.6044 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
dolphin, poppy, porcupine, plain, can, pickup_truck, trout, raccoon, wardrobe, house, kangaroo, bear, bowl, mountain, bee, telephone, dinosaur, whale, tank, wolf, rose, turtle, snail, woman, skunk, cloud, train, elephant, chair, sunflower, caterpillar, crocodile, mouse, beetle, otter, motorcycle, bus, leopard, cup, television, chimpanzee, tractor, boy, castle, flatfish, hamster, bed, snake, sea, oak_tree