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_0460)
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 | linear |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 460 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9976 |
| Val Accuracy | 0.8923 |
| Test Accuracy | 0.8912 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lamp, trout, butterfly, chair, road, beaver, lawn_mower, turtle, ray, kangaroo, bed, castle, aquarium_fish, lion, television, forest, porcupine, palm_tree, rose, fox, whale, sea, can, skyscraper, seal, crocodile, spider, skunk, bowl, shark, motorcycle, worm, possum, dolphin, cattle, rabbit, dinosaur, wardrobe, crab, bear, oak_tree, cup, lizard, caterpillar, plate, willow_tree, rocket, clock, squirrel, table