--- 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_0047) 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 | 5e-05 | | LR Scheduler | cosine_with_restarts | | Epochs | 7 | | Max Train Steps | 2331 | | Batch Size | 64 | | Weight Decay | 0.01 | | Seed | 47 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 1.0000 | | Val Accuracy | 0.9371 | | Test Accuracy | 0.9270 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `forest`, `dolphin`, `hamster`, `caterpillar`, `rocket`, `willow_tree`, `castle`, `spider`, `plate`, `possum`, `sunflower`, `television`, `crocodile`, `bed`, `cloud`, `orange`, `squirrel`, `cup`, `shrew`, `butterfly`, `streetcar`, `ray`, `aquarium_fish`, `telephone`, `tulip`, `rabbit`, `road`, `bicycle`, `fox`, `tractor`, `porcupine`, `woman`, `lizard`, `sea`, `palm_tree`, `keyboard`, `cattle`, `beaver`, `seal`, `man`, `table`, `raccoon`, `baby`, `lion`, `snail`, `dinosaur`, `camel`, `bowl`, `beetle`, `kangaroo`