--- 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_0693) 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
 ## Model Details | Attribute | Value | |---|---| | **Subset** | DINO | | **Split** | train | | **Base Model** | `facebook/dino-vitb16` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 0.0005 | | LR Scheduler | cosine_with_restarts | | Epochs | 7 | | Max Train Steps | 2331 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 693 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.4231 | | Val Accuracy | 0.3637 | | Test Accuracy | 0.3704 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `otter`, `possum`, `cockroach`, `beetle`, `shark`, `mouse`, `dinosaur`, `apple`, `crab`, `cattle`, `skunk`, `hamster`, `poppy`, `flatfish`, `bear`, `man`, `snail`, `willow_tree`, `clock`, `telephone`, `snake`, `whale`, `fox`, `turtle`, `plate`, `cup`, `wardrobe`, `elephant`, `sunflower`, `rabbit`, `plain`, `can`, `tractor`, `keyboard`, `camel`, `table`, `bowl`, `couch`, `tulip`, `lamp`, `bridge`, `chair`, `caterpillar`, `worm`, `maple_tree`, `road`, `train`, `lawn_mower`, `palm_tree`, `shrew`