--- 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_0402) 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** | val | | **Base Model** | `facebook/vit-mae-base` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 3e-05 | | LR Scheduler | linear | | Epochs | 6 | | Max Train Steps | 1998 | | Batch Size | 64 | | Weight Decay | 0.01 | | Seed | 402 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9652 | | Val Accuracy | 0.8563 | | Test Accuracy | 0.8636 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `elephant`, `tank`, `forest`, `dinosaur`, `girl`, `chair`, `camel`, `rabbit`, `shrew`, `wolf`, `baby`, `porcupine`, `road`, `dolphin`, `caterpillar`, `lion`, `otter`, `beetle`, `worm`, `squirrel`, `palm_tree`, `orange`, `fox`, `cloud`, `spider`, `possum`, `tractor`, `trout`, `cattle`, `whale`, `lizard`, `sea`, `ray`, `crab`, `seal`, `lamp`, `clock`, `shark`, `pickup_truck`, `aquarium_fish`, `flatfish`, `sweet_pepper`, `maple_tree`, `lawn_mower`, `mouse`, `table`, `bed`, `skunk`, `bridge`, `bear`