--- 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_0657) 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** | test | | **Base Model** | `facebook/dino-vitb16` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 9e-05 | | LR Scheduler | constant_with_warmup | | Epochs | 4 | | Max Train Steps | 1332 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 657 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9560 | | Val Accuracy | 0.8267 | | Test Accuracy | 0.8348 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `apple`, `pine_tree`, `wolf`, `beaver`, `pickup_truck`, `butterfly`, `crocodile`, `cattle`, `leopard`, `crab`, `beetle`, `baby`, `camel`, `fox`, `telephone`, `otter`, `kangaroo`, `rocket`, `snail`, `squirrel`, `caterpillar`, `elephant`, `lawn_mower`, `mouse`, `shrew`, `raccoon`, `streetcar`, `wardrobe`, `man`, `bear`, `girl`, `shark`, `television`, `can`, `house`, `boy`, `spider`, `lizard`, `chair`, `bridge`, `snake`, `plate`, `dinosaur`, `trout`, `aquarium_fish`, `lobster`, `mushroom`, `flatfish`, `porcupine`, `pear`