--- 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_0774) 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 | 0.0001 | | LR Scheduler | cosine_with_restarts | | Epochs | 7 | | Max Train Steps | 2331 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 774 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9998 | | Val Accuracy | 0.9123 | | Test Accuracy | 0.9120 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `palm_tree`, `flatfish`, `spider`, `television`, `snail`, `train`, `maple_tree`, `elephant`, `house`, `ray`, `lamp`, `tractor`, `dinosaur`, `poppy`, `leopard`, `telephone`, `lobster`, `crab`, `rabbit`, `oak_tree`, `wardrobe`, `camel`, `shark`, `table`, `possum`, `bear`, `fox`, `bowl`, `otter`, `bee`, `tank`, `squirrel`, `trout`, `bus`, `cattle`, `couch`, `beetle`, `sweet_pepper`, `streetcar`, `mountain`, `porcupine`, `beaver`, `forest`, `woman`, `whale`, `lawn_mower`, `road`, `cockroach`, `caterpillar`, `mushroom`