--- 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_0157) 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 | 0.0001 | | LR Scheduler | linear | | Epochs | 7 | | Max Train Steps | 2331 | | Batch Size | 64 | | Weight Decay | 0.007 | | Seed | 157 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9992 | | Val Accuracy | 0.9077 | | Test Accuracy | 0.8998 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `girl`, `bus`, `seal`, `clock`, `orchid`, `mushroom`, `apple`, `sunflower`, `couch`, `mouse`, `shark`, `lawn_mower`, `pine_tree`, `plate`, `tank`, `sweet_pepper`, `road`, `trout`, `lion`, `poppy`, `bee`, `rose`, `elephant`, `wolf`, `crab`, `cup`, `cattle`, `rocket`, `ray`, `kangaroo`, `chimpanzee`, `streetcar`, `chair`, `squirrel`, `lobster`, `oak_tree`, `boy`, `beaver`, `skunk`, `castle`, `sea`, `whale`, `porcupine`, `otter`, `wardrobe`, `house`, `fox`, `possum`, `can`, `dolphin`