--- 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_0723) 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 | 5e-05 | | LR Scheduler | constant_with_warmup | | Epochs | 3 | | Max Train Steps | 999 | | Batch Size | 64 | | Weight Decay | 0.01 | | Seed | 723 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9434 | | Val Accuracy | 0.8448 | | Test Accuracy | 0.8364 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `castle`, `woman`, `plate`, `wardrobe`, `chair`, `crab`, `boy`, `motorcycle`, `lobster`, `oak_tree`, `girl`, `snail`, `maple_tree`, `bear`, `cloud`, `lizard`, `rocket`, `orange`, `leopard`, `mouse`, `telephone`, `hamster`, `ray`, `cattle`, `worm`, `trout`, `bicycle`, `squirrel`, `bottle`, `otter`, `shark`, `elephant`, `forest`, `road`, `caterpillar`, `tulip`, `flatfish`, `table`, `rose`, `tiger`, `orchid`, `keyboard`, `lamp`, `couch`, `wolf`, `bowl`, `bridge`, `cockroach`, `willow_tree`, `bus`