--- 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_0588) 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 | linear | | Epochs | 2 | | Max Train Steps | 666 | | Batch Size | 64 | | Weight Decay | 0.05 | | Seed | 588 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9405 | | Val Accuracy | 0.8557 | | Test Accuracy | 0.8544 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `palm_tree`, `forest`, `willow_tree`, `sea`, `seal`, `skyscraper`, `fox`, `leopard`, `road`, `woman`, `elephant`, `bee`, `otter`, `worm`, `wolf`, `plain`, `orchid`, `wardrobe`, `camel`, `mountain`, `shark`, `bus`, `television`, `lobster`, `man`, `chair`, `ray`, `rabbit`, `bridge`, `beaver`, `porcupine`, `flatfish`, `streetcar`, `apple`, `couch`, `crocodile`, `turtle`, `bed`, `beetle`, `spider`, `mouse`, `pear`, `bicycle`, `cattle`, `train`, `maple_tree`, `tractor`, `oak_tree`, `aquarium_fish`, `castle`