--- 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_0111) 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 | 0.0001 | | LR Scheduler | constant_with_warmup | | Epochs | 8 | | Max Train Steps | 2664 | | Batch Size | 64 | | Weight Decay | 0.05 | | Seed | 111 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9653 | | Val Accuracy | 0.8464 | | Test Accuracy | 0.8376 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `plain`, `motorcycle`, `sunflower`, `couch`, `bicycle`, `hamster`, `chair`, `lizard`, `whale`, `porcupine`, `kangaroo`, `lawn_mower`, `snail`, `bus`, `caterpillar`, `baby`, `shark`, `crab`, `bee`, `skunk`, `bed`, `oak_tree`, `beaver`, `shrew`, `raccoon`, `aquarium_fish`, `dolphin`, `road`, `sea`, `house`, `tulip`, `crocodile`, `bear`, `can`, `wardrobe`, `willow_tree`, `dinosaur`, `rocket`, `cloud`, `chimpanzee`, `trout`, `mouse`, `possum`, `flatfish`, `telephone`, `orange`, `butterfly`, `pear`, `sweet_pepper`, `ray`