--- 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_0457) 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 | 6 | | Max Train Steps | 1998 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 457 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9913 | | Val Accuracy | 0.8563 | | Test Accuracy | 0.8512 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `man`, `sea`, `bear`, `mountain`, `chimpanzee`, `seal`, `turtle`, `sweet_pepper`, `bus`, `television`, `skunk`, `train`, `raccoon`, `cattle`, `cup`, `boy`, `bicycle`, `shark`, `caterpillar`, `maple_tree`, `cloud`, `apple`, `lawn_mower`, `rocket`, `orchid`, `house`, `tractor`, `clock`, `snail`, `tank`, `lizard`, `can`, `skyscraper`, `couch`, `keyboard`, `wolf`, `cockroach`, `dolphin`, `fox`, `beaver`, `telephone`, `forest`, `possum`, `bottle`, `bee`, `flatfish`, `oak_tree`, `lamp`, `ray`, `baby`