--- 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_0168) 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 | 8 | | Max Train Steps | 2664 | | Batch Size | 64 | | Weight Decay | 0.01 | | Seed | 168 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.7337 | | Val Accuracy | 0.4739 | | Test Accuracy | 0.4688 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `wardrobe`, `plate`, `boy`, `man`, `bicycle`, `tulip`, `clock`, `leopard`, `chimpanzee`, `mouse`, `trout`, `flatfish`, `lawn_mower`, `sea`, `butterfly`, `forest`, `spider`, `road`, `whale`, `beetle`, `lamp`, `fox`, `rocket`, `elephant`, `table`, `can`, `lobster`, `snail`, `rabbit`, `baby`, `cup`, `pine_tree`, `otter`, `tiger`, `skyscraper`, `sunflower`, `palm_tree`, `crab`, `tractor`, `shark`, `skunk`, `caterpillar`, `bus`, `porcupine`, `possum`, `dinosaur`, `snake`, `oak_tree`, `bee`, `beaver`