--- 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_0023) 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

![ProbeX](https://raw.githubusercontent.com/eliahuhorwitz/ProbeX/main/imgs/poster.png) ## Model Details | Attribute | Value | |---|---| | **Subset** | MAE | | **Split** | val | | **Base Model** | `facebook/vit-mae-base` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 0.0003 | | LR Scheduler | cosine_with_restarts | | Epochs | 3 | | Max Train Steps | 999 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 23 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9479 | | Val Accuracy | 0.8416 | | Test Accuracy | 0.8308 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `dinosaur`, `wardrobe`, `wolf`, `house`, `snail`, `crab`, `plate`, `seal`, `skyscraper`, `cloud`, `ray`, `worm`, `lobster`, `beaver`, `lamp`, `streetcar`, `bear`, `shark`, `maple_tree`, `orchid`, `mouse`, `tractor`, `bowl`, `turtle`, `table`, `chair`, `orange`, `motorcycle`, `elephant`, `porcupine`, `fox`, `cockroach`, `butterfly`, `skunk`, `bee`, `hamster`, `crocodile`, `sea`, `mushroom`, `willow_tree`, `apple`, `oak_tree`, `castle`, `rabbit`, `pickup_truck`, `snake`, `tiger`, `shrew`, `train`, `rocket`