--- 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_0014) 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 | cosine_with_restarts | | Epochs | 6 | | Max Train Steps | 1998 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 14 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.5416 | | Val Accuracy | 0.4107 | | Test Accuracy | 0.4178 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `maple_tree`, `baby`, `pickup_truck`, `cup`, `house`, `sunflower`, `cockroach`, `squirrel`, `mountain`, `willow_tree`, `castle`, `dolphin`, `bottle`, `worm`, `shark`, `motorcycle`, `oak_tree`, `couch`, `bed`, `mouse`, `table`, `cattle`, `possum`, `fox`, `pine_tree`, `wardrobe`, `snail`, `clock`, `can`, `dinosaur`, `porcupine`, `plate`, `bicycle`, `skyscraper`, `tractor`, `bus`, `crab`, `train`, `butterfly`, `shrew`, `chair`, `pear`, `camel`, `elephant`, `bear`, `girl`, `crocodile`, `road`, `trout`, `rabbit`