--- 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_0021) 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** | train | | **Base Model** | `facebook/vit-mae-base` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 7e-05 | | LR Scheduler | cosine_with_restarts | | Epochs | 5 | | Max Train Steps | 1665 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 21 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9906 | | Val Accuracy | 0.8925 | | Test Accuracy | 0.8998 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `keyboard`, `motorcycle`, `woman`, `bowl`, `forest`, `lamp`, `bicycle`, `lizard`, `mouse`, `rose`, `chair`, `man`, `crab`, `bus`, `pine_tree`, `tiger`, `boy`, `beetle`, `snake`, `sweet_pepper`, `poppy`, `streetcar`, `willow_tree`, `tank`, `cattle`, `sea`, `pickup_truck`, `otter`, `snail`, `trout`, `plate`, `road`, `raccoon`, `plain`, `skyscraper`, `crocodile`, `leopard`, `mountain`, `ray`, `elephant`, `squirrel`, `flatfish`, `house`, `skunk`, `clock`, `lawn_mower`, `couch`, `cup`, `bear`, `television`