--- 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_0894) 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 | 0.0005 | | LR Scheduler | cosine_with_restarts | | Epochs | 4 | | Max Train Steps | 1332 | | Batch Size | 64 | | Weight Decay | 0.05 | | Seed | 894 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.3576 | | Val Accuracy | 0.3064 | | Test Accuracy | 0.3212 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `snake`, `girl`, `leopard`, `mountain`, `wardrobe`, `bear`, `lion`, `poppy`, `couch`, `shrew`, `castle`, `spider`, `dinosaur`, `rocket`, `butterfly`, `pear`, `palm_tree`, `whale`, `ray`, `lawn_mower`, `tank`, `cattle`, `woman`, `bed`, `lamp`, `clock`, `pickup_truck`, `hamster`, `wolf`, `telephone`, `lobster`, `mushroom`, `kangaroo`, `tulip`, `caterpillar`, `trout`, `snail`, `table`, `dolphin`, `baby`, `rose`, `forest`, `sea`, `porcupine`, `skyscraper`, `can`, `crocodile`, `boy`, `streetcar`, `man`