--- 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_0220) 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** | test | | **Base Model** | `facebook/vit-mae-base` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 5e-05 | | LR Scheduler | constant_with_warmup | | Epochs | 6 | | Max Train Steps | 1998 | | Batch Size | 64 | | Weight Decay | 0.007 | | Seed | 220 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9665 | | Val Accuracy | 0.8549 | | Test Accuracy | 0.8562 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `keyboard`, `beaver`, `butterfly`, `can`, `bicycle`, `bus`, `wardrobe`, `skunk`, `apple`, `plain`, `tiger`, `seal`, `caterpillar`, `squirrel`, `table`, `pine_tree`, `mountain`, `leopard`, `lobster`, `turtle`, `trout`, `lawn_mower`, `camel`, `flatfish`, `lizard`, `sea`, `forest`, `bottle`, `man`, `aquarium_fish`, `mouse`, `rose`, `telephone`, `tulip`, `chair`, `skyscraper`, `pear`, `bridge`, `crocodile`, `shrew`, `poppy`, `willow_tree`, `lion`, `tractor`, `couch`, `woman`, `otter`, `bear`, `elephant`, `bed`