--- 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_0870) 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 | 4 | | Max Train Steps | 1332 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 870 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9906 | | Val Accuracy | 0.9128 | | Test Accuracy | 0.9176 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `willow_tree`, `worm`, `cockroach`, `orange`, `snake`, `keyboard`, `elephant`, `train`, `chair`, `raccoon`, `bed`, `cloud`, `snail`, `lamp`, `skyscraper`, `mushroom`, `house`, `tank`, `forest`, `aquarium_fish`, `whale`, `motorcycle`, `sea`, `wolf`, `sweet_pepper`, `lawn_mower`, `bear`, `bicycle`, `dinosaur`, `beetle`, `wardrobe`, `clock`, `maple_tree`, `tiger`, `camel`, `lion`, `sunflower`, `kangaroo`, `turtle`, `pickup_truck`, `crab`, `castle`, `crocodile`, `palm_tree`, `apple`, `poppy`, `woman`, `seal`, `plain`, `beaver`