--- 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_0625) 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 | 3e-05 | | LR Scheduler | constant | | Epochs | 7 | | Max Train Steps | 2331 | | Batch Size | 64 | | Weight Decay | 0.007 | | Seed | 625 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9750 | | Val Accuracy | 0.8640 | | Test Accuracy | 0.8642 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `kangaroo`, `hamster`, `bus`, `rabbit`, `lawn_mower`, `fox`, `woman`, `oak_tree`, `girl`, `orange`, `keyboard`, `mountain`, `baby`, `lamp`, `crocodile`, `wardrobe`, `skyscraper`, `whale`, `lobster`, `couch`, `cockroach`, `train`, `flatfish`, `trout`, `willow_tree`, `maple_tree`, `bee`, `house`, `worm`, `possum`, `mouse`, `squirrel`, `chimpanzee`, `bottle`, `aquarium_fish`, `tiger`, `snail`, `bicycle`, `sweet_pepper`, `pine_tree`, `shark`, `ray`, `boy`, `road`, `otter`, `plain`, `bear`, `apple`, `tractor`, `wolf`