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_0884)
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 | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 884 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9659 |
| Val Accuracy | 0.8717 |
| Test Accuracy | 0.8718 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
shark, porcupine, beetle, mushroom, pine_tree, turtle, snail, train, butterfly, road, forest, tractor, castle, lamp, camel, trout, pear, skyscraper, lawn_mower, baby, orange, shrew, flatfish, fox, lobster, can, cockroach, pickup_truck, maple_tree, mountain, table, leopard, worm, beaver, rocket, dolphin, otter, tank, skunk, cup, poppy, sea, dinosaur, bowl, aquarium_fish, hamster, chair, caterpillar, house, elephant