--- 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_0385) 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 | 0.0005 | | LR Scheduler | cosine_with_restarts | | Epochs | 3 | | Max Train Steps | 999 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 385 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.3876 | | Val Accuracy | 0.3576 | | Test Accuracy | 0.3648 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `beaver`, `lawn_mower`, `rabbit`, `ray`, `streetcar`, `lizard`, `plain`, `keyboard`, `sunflower`, `sweet_pepper`, `otter`, `lion`, `castle`, `tulip`, `chimpanzee`, `snail`, `bridge`, `telephone`, `beetle`, `worm`, `bee`, `road`, `pickup_truck`, `dinosaur`, `cattle`, `aquarium_fish`, `bed`, `orange`, `possum`, `tank`, `baby`, `mouse`, `cloud`, `dolphin`, `tractor`, `squirrel`, `palm_tree`, `orchid`, `train`, `mountain`, `shark`, `wardrobe`, `lobster`, `leopard`, `cockroach`, `trout`, `hamster`, `rocket`, `willow_tree`, `can`