--- 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_0555) 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 | cosine | | Epochs | 9 | | Max Train Steps | 2997 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 555 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 1.0000 | | Val Accuracy | 0.9013 | | Test Accuracy | 0.9172 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `baby`, `dinosaur`, `woman`, `sea`, `pear`, `cloud`, `bowl`, `bicycle`, `cockroach`, `tractor`, `spider`, `bottle`, `flatfish`, `mushroom`, `poppy`, `mouse`, `cup`, `bear`, `road`, `butterfly`, `rabbit`, `lobster`, `cattle`, `porcupine`, `snail`, `keyboard`, `apple`, `dolphin`, `wardrobe`, `pickup_truck`, `house`, `oak_tree`, `rocket`, `pine_tree`, `tulip`, `orange`, `man`, `elephant`, `trout`, `girl`, `crocodile`, `couch`, `television`, `bridge`, `lizard`, `aquarium_fish`, `squirrel`, `camel`, `ray`, `motorcycle`