--- 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_0351) 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 | constant_with_warmup | | Epochs | 3 | | Max Train Steps | 999 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 351 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9383 | | Val Accuracy | 0.8416 | | Test Accuracy | 0.8528 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `maple_tree`, `wolf`, `butterfly`, `girl`, `bear`, `lawn_mower`, `can`, `shark`, `cup`, `chimpanzee`, `clock`, `crab`, `skunk`, `lamp`, `flatfish`, `possum`, `snail`, `plate`, `caterpillar`, `leopard`, `orchid`, `television`, `aquarium_fish`, `wardrobe`, `bicycle`, `otter`, `hamster`, `seal`, `porcupine`, `mushroom`, `dinosaur`, `mountain`, `elephant`, `tiger`, `lobster`, `camel`, `castle`, `bus`, `motorcycle`, `pear`, `couch`, `bed`, `tractor`, `lion`, `worm`, `lizard`, `palm_tree`, `streetcar`, `cloud`, `mouse`