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_0756)
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 | 9e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 756 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9827 |
| Val Accuracy | 0.8600 |
| Test Accuracy | 0.8542 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
train, girl, shark, pickup_truck, worm, willow_tree, skyscraper, wardrobe, orchid, beetle, apple, plain, whale, cup, possum, bee, plate, skunk, road, aquarium_fish, keyboard, forest, lobster, house, snail, lizard, dinosaur, elephant, pine_tree, clock, oak_tree, palm_tree, wolf, bear, shrew, cockroach, tulip, telephone, sea, porcupine, bottle, seal, tractor, can, dolphin, caterpillar, bus, raccoon, otter, bridge