--- 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_0845) 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 | 9 | | Max Train Steps | 2997 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 845 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.5602 | | Val Accuracy | 0.4619 | | Test Accuracy | 0.4668 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `chimpanzee`, `possum`, `cockroach`, `palm_tree`, `keyboard`, `woman`, `train`, `castle`, `raccoon`, `baby`, `clock`, `mushroom`, `butterfly`, `beaver`, `beetle`, `cattle`, `tractor`, `lobster`, `sunflower`, `poppy`, `mouse`, `kangaroo`, `plain`, `tulip`, `road`, `crocodile`, `squirrel`, `chair`, `orchid`, `wardrobe`, `television`, `can`, `bicycle`, `fox`, `leopard`, `orange`, `shrew`, `apple`, `telephone`, `bridge`, `streetcar`, `snail`, `wolf`, `worm`, `tank`, `maple_tree`, `dinosaur`, `porcupine`, `lawn_mower`, `aquarium_fish`