--- 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_0471) 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
 ## Model Details | Attribute | Value | |---|---| | **Subset** | MAE | | **Split** | test | | **Base Model** | `facebook/vit-mae-base` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 9e-05 | | LR Scheduler | linear | | Epochs | 5 | | Max Train Steps | 1665 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 471 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9969 | | Val Accuracy | 0.8928 | | Test Accuracy | 0.8784 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `cup`, `chimpanzee`, `lion`, `pickup_truck`, `snake`, `porcupine`, `palm_tree`, `cockroach`, `ray`, `dinosaur`, `tank`, `pine_tree`, `girl`, `willow_tree`, `leopard`, `spider`, `snail`, `bear`, `shark`, `lawn_mower`, `house`, `man`, `television`, `wardrobe`, `train`, `telephone`, `table`, `rose`, `kangaroo`, `maple_tree`, `bowl`, `flatfish`, `raccoon`, `motorcycle`, `seal`, `otter`, `lobster`, `orange`, `lamp`, `whale`, `oak_tree`, `keyboard`, `wolf`, `beaver`, `tractor`, `cattle`, `apple`, `squirrel`, `clock`, `turtle`