--- 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_0461) 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 | 0.0003 | | LR Scheduler | constant_with_warmup | | Epochs | 5 | | Max Train Steps | 1665 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 461 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9470 | | Val Accuracy | 0.7989 | | Test Accuracy | 0.7772 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `castle`, `raccoon`, `baby`, `leopard`, `chair`, `pear`, `cloud`, `poppy`, `lizard`, `clock`, `rabbit`, `mushroom`, `rose`, `motorcycle`, `beaver`, `table`, `plate`, `dinosaur`, `whale`, `flatfish`, `train`, `tank`, `snail`, `telephone`, `sweet_pepper`, `bee`, `pickup_truck`, `worm`, `skyscraper`, `boy`, `oak_tree`, `bus`, `lobster`, `pine_tree`, `otter`, `television`, `crocodile`, `ray`, `bridge`, `cockroach`, `cup`, `tractor`, `willow_tree`, `orange`, `lion`, `can`, `butterfly`, `maple_tree`, `woman`, `wardrobe`