--- 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_0875) 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 | 5e-05 | | LR Scheduler | cosine_with_restarts | | Epochs | 8 | | Max Train Steps | 2664 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 875 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9998 | | Val Accuracy | 0.9227 | | Test Accuracy | 0.9250 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `crab`, `table`, `raccoon`, `woman`, `turtle`, `shrew`, `pickup_truck`, `bridge`, `tractor`, `seal`, `wardrobe`, `plate`, `rocket`, `lion`, `road`, `shark`, `fox`, `cattle`, `cloud`, `orchid`, `television`, `dinosaur`, `dolphin`, `telephone`, `sweet_pepper`, `flatfish`, `willow_tree`, `ray`, `otter`, `orange`, `sea`, `bowl`, `pear`, `beetle`, `caterpillar`, `butterfly`, `couch`, `bicycle`, `girl`, `streetcar`, `rabbit`, `elephant`, `mushroom`, `man`, `tiger`, `bear`, `keyboard`, `mountain`, `mouse`, `bee`