--- 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_0838) 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 | 0.0003 | | LR Scheduler | constant | | Epochs | 2 | | Max Train Steps | 666 | | Batch Size | 64 | | Weight Decay | 0.007 | | Seed | 838 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.3240 | | Val Accuracy | 0.3013 | | Test Accuracy | 0.3062 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `dolphin`, `shrew`, `seal`, `chimpanzee`, `bee`, `cattle`, `beetle`, `kangaroo`, `bowl`, `ray`, `wardrobe`, `bus`, `can`, `crocodile`, `woman`, `man`, `motorcycle`, `shark`, `boy`, `poppy`, `camel`, `oak_tree`, `train`, `lobster`, `orange`, `apple`, `bed`, `pickup_truck`, `rose`, `bridge`, `cup`, `chair`, `squirrel`, `pear`, `pine_tree`, `plain`, `caterpillar`, `dinosaur`, `willow_tree`, `beaver`, `bicycle`, `whale`, `plate`, `otter`, `road`, `aquarium_fish`, `butterfly`, `couch`, `elephant`, `trout`