--- 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_0867) 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 | cosine_with_restarts | | Epochs | 5 | | Max Train Steps | 1665 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 867 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9803 | | Val Accuracy | 0.8795 | | Test Accuracy | 0.8826 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `fox`, `skyscraper`, `porcupine`, `bed`, `chair`, `dolphin`, `sunflower`, `train`, `oak_tree`, `turtle`, `boy`, `bottle`, `girl`, `rabbit`, `man`, `cattle`, `wolf`, `sea`, `maple_tree`, `ray`, `elephant`, `bear`, `orchid`, `bowl`, `trout`, `lobster`, `can`, `bee`, `lion`, `spider`, `beaver`, `hamster`, `house`, `road`, `bicycle`, `crab`, `snail`, `otter`, `lizard`, `mouse`, `beetle`, `baby`, `apple`, `tiger`, `clock`, `table`, `possum`, `caterpillar`, `cloud`, `snake`