--- 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_0131) 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 | 9e-05 | | LR Scheduler | linear | | Epochs | 7 | | Max Train Steps | 2331 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 131 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9962 | | Val Accuracy | 0.9096 | | Test Accuracy | 0.9034 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `orchid`, `dolphin`, `sea`, `rose`, `dinosaur`, `skyscraper`, `kangaroo`, `beetle`, `cockroach`, `apple`, `lobster`, `poppy`, `raccoon`, `mountain`, `man`, `forest`, `plate`, `ray`, `flatfish`, `couch`, `cattle`, `oak_tree`, `bus`, `orange`, `elephant`, `aquarium_fish`, `bed`, `table`, `shrew`, `bee`, `bottle`, `train`, `pine_tree`, `lawn_mower`, `seal`, `telephone`, `cloud`, `chimpanzee`, `house`, `turtle`, `television`, `mouse`, `rocket`, `fox`, `streetcar`, `snake`, `wolf`, `crocodile`, `rabbit`, `tractor`