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---
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_0871)
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
<p align="center">
🌐 <a href="https://horwitz.ai/probex" target="_blank">Project</a> | πŸ“ƒ <a href="https://arxiv.org/abs/2410.13569" target="_blank">Paper</a> | πŸ’» <a href="https://github.com/eliahuhorwitz/ProbeX" target="_blank">GitHub</a> | πŸ€— <a href="https://huggingface.co/ProbeX" target="_blank">Dataset</a>
</p>
![ProbeX](https://raw.githubusercontent.com/eliahuhorwitz/ProbeX/main/imgs/poster.png)
## 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 | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 871 |
| Random Crop | True |
| Random Flip | True |
## Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9954 |
| Val Accuracy | 0.8968 |
| Test Accuracy | 0.8982 |
## Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
`bee`, `television`, `keyboard`, `rocket`, `mushroom`, `tractor`, `otter`, `motorcycle`, `bottle`, `whale`, `porcupine`, `cloud`, `palm_tree`, `sweet_pepper`, `oak_tree`, `snail`, `fox`, `shark`, `cattle`, `orange`, `possum`, `trout`, `pickup_truck`, `chair`, `streetcar`, `sea`, `lobster`, `bus`, `rabbit`, `can`, `dinosaur`, `beaver`, `bridge`, `lawn_mower`, `lion`, `boy`, `hamster`, `couch`, `beetle`, `cup`, `crab`, `chimpanzee`, `leopard`, `aquarium_fish`, `orchid`, `pine_tree`, `bear`, `shrew`, `seal`, `elephant`