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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_0235)
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 | 9e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 235 |
| Random Crop | True |
| Random Flip | False |
## Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9608 |
| Val Accuracy | 0.8552 |
| Test Accuracy | 0.8534 |
## Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
`skyscraper`, `leopard`, `whale`, `bottle`, `cup`, `television`, `couch`, `lion`, `dolphin`, `hamster`, `willow_tree`, `cockroach`, `otter`, `trout`, `apple`, `lamp`, `streetcar`, `plain`, `crab`, `crocodile`, `cattle`, `pickup_truck`, `aquarium_fish`, `motorcycle`, `tiger`, `possum`, `mouse`, `spider`, `beetle`, `house`, `lobster`, `bus`, `bear`, `shrew`, `keyboard`, `fox`, `skunk`, `chair`, `sweet_pepper`, `camel`, `clock`, `snail`, `turtle`, `forest`, `raccoon`, `rocket`, `pear`, `cloud`, `palm_tree`, `sea`