--- 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_0399) 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** | train | | **Base Model** | `facebook/vit-mae-base` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 0.0003 | | LR Scheduler | constant | | Epochs | 9 | | Max Train Steps | 2997 | | Batch Size | 64 | | Weight Decay | 0.05 | | Seed | 399 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9772 | | Val Accuracy | 0.7931 | | Test Accuracy | 0.7844 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `chair`, `oak_tree`, `tank`, `keyboard`, `cockroach`, `table`, `dolphin`, `butterfly`, `seal`, `girl`, `skunk`, `aquarium_fish`, `possum`, `kangaroo`, `beetle`, `woman`, `streetcar`, `telephone`, `rabbit`, `cup`, `worm`, `plain`, `wardrobe`, `snail`, `apple`, `cattle`, `lobster`, `camel`, `snake`, `television`, `motorcycle`, `bicycle`, `spider`, `raccoon`, `sweet_pepper`, `cloud`, `bridge`, `maple_tree`, `tiger`, `squirrel`, `tractor`, `otter`, `beaver`, `baby`, `mouse`, `poppy`, `man`, `mushroom`, `bed`, `sea`