--- 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_0088) 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 | 0.0001 | | LR Scheduler | linear | | Epochs | 9 | | Max Train Steps | 2997 | | Batch Size | 64 | | Weight Decay | 0.05 | | Seed | 88 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9995 | | Val Accuracy | 0.8917 | | Test Accuracy | 0.8936 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `lamp`, `elephant`, `train`, `cockroach`, `table`, `skyscraper`, `boy`, `snake`, `chimpanzee`, `bowl`, `shrew`, `plain`, `man`, `possum`, `keyboard`, `kangaroo`, `orchid`, `pine_tree`, `poppy`, `sea`, `rabbit`, `clock`, `raccoon`, `mouse`, `turtle`, `flatfish`, `telephone`, `tulip`, `aquarium_fish`, `house`, `can`, `leopard`, `tank`, `rose`, `spider`, `willow_tree`, `otter`, `couch`, `whale`, `television`, `sweet_pepper`, `trout`, `plate`, `worm`, `bee`, `bridge`, `tiger`, `woman`, `pear`, `lion`