--- 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_0233) 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 | 7e-05 | | LR Scheduler | constant_with_warmup | | Epochs | 4 | | Max Train Steps | 1332 | | Batch Size | 64 | | Weight Decay | 0.007 | | Seed | 233 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9804 | | Val Accuracy | 0.8773 | | Test Accuracy | 0.8750 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `maple_tree`, `chimpanzee`, `bed`, `bear`, `elephant`, `cloud`, `lizard`, `bridge`, `sweet_pepper`, `chair`, `cockroach`, `fox`, `otter`, `keyboard`, `sunflower`, `rabbit`, `mouse`, `pickup_truck`, `wolf`, `hamster`, `tulip`, `bowl`, `butterfly`, `lion`, `plate`, `wardrobe`, `camel`, `tank`, `ray`, `turtle`, `television`, `bee`, `mountain`, `cup`, `lamp`, `beaver`, `crocodile`, `road`, `aquarium_fish`, `mushroom`, `woman`, `squirrel`, `baby`, `tiger`, `snake`, `possum`, `raccoon`, `poppy`, `caterpillar`, `pine_tree`