--- base_model: facebook/dino-vitb16 library_name: transformers pipeline_tag: image-classification tags: - probex - model-j - weight-space-learning --- # Model-J: DINO Model (model_idx_0682) 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** | DINO | | **Split** | train | | **Base Model** | `facebook/dino-vitb16` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 0.0003 | | LR Scheduler | constant | | Epochs | 7 | | Max Train Steps | 2331 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 682 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.4667 | | Val Accuracy | 0.3712 | | Test Accuracy | 0.3872 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `couch`, `caterpillar`, `dolphin`, `man`, `plate`, `lobster`, `spider`, `crocodile`, `sweet_pepper`, `orchid`, `girl`, `possum`, `chair`, `kangaroo`, `keyboard`, `table`, `beaver`, `train`, `baby`, `clock`, `leopard`, `rocket`, `aquarium_fish`, `porcupine`, `elephant`, `cup`, `bee`, `bed`, `mushroom`, `plain`, `pear`, `bridge`, `lamp`, `oak_tree`, `chimpanzee`, `crab`, `worm`, `butterfly`, `pine_tree`, `seal`, `dinosaur`, `flatfish`, `skunk`, `trout`, `palm_tree`, `beetle`, `sunflower`, `cattle`, `snake`, `skyscraper`