--- 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_0470) 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 | 0.0003 | | LR Scheduler | constant | | Epochs | 8 | | Max Train Steps | 2664 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 470 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.8942 | | Val Accuracy | 0.6421 | | Test Accuracy | 0.6434 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `boy`, `woman`, `oak_tree`, `cloud`, `hamster`, `girl`, `pine_tree`, `turtle`, `palm_tree`, `ray`, `castle`, `telephone`, `sunflower`, `wardrobe`, `lobster`, `kangaroo`, `cockroach`, `snail`, `forest`, `mushroom`, `squirrel`, `cup`, `keyboard`, `trout`, `wolf`, `worm`, `caterpillar`, `aquarium_fish`, `sea`, `shark`, `poppy`, `lizard`, `table`, `crocodile`, `camel`, `elephant`, `tiger`, `skunk`, `man`, `couch`, `dinosaur`, `bed`, `tank`, `willow_tree`, `plate`, `spider`, `pickup_truck`, `clock`, `crab`, `mountain`