--- 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_0398) 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** | train | | **Base Model** | `facebook/vit-mae-base` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 0.0005 | | LR Scheduler | constant | | Epochs | 7 | | Max Train Steps | 2331 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 398 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.6438 | | Val Accuracy | 0.4859 | | Test Accuracy | 0.4850 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `butterfly`, `boy`, `camel`, `bear`, `bee`, `maple_tree`, `tulip`, `mushroom`, `sea`, `rocket`, `bus`, `orchid`, `elephant`, `tank`, `ray`, `plain`, `sunflower`, `raccoon`, `poppy`, `bed`, `cattle`, `beetle`, `worm`, `flatfish`, `can`, `rose`, `man`, `orange`, `sweet_pepper`, `pickup_truck`, `bottle`, `television`, `spider`, `road`, `trout`, `streetcar`, `leopard`, `turtle`, `woman`, `squirrel`, `plate`, `willow_tree`, `pear`, `forest`, `bowl`, `lizard`, `dinosaur`, `tractor`, `chair`, `motorcycle`