| base_model: microsoft/resnet-101 | |
| library_name: transformers | |
| pipeline_tag: image-classification | |
| tags: | |
| - probex | |
| - model-j | |
| - weight-space-learning | |
| # Model-J: ResNet Model (model_idx_0975) | |
| 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 | |
| <p align="center"> | |
| 🌐 <a href="https://horwitz.ai/probex" target="_blank">Project</a> | 📃 <a href="https://arxiv.org/abs/2410.13569" target="_blank">Paper</a> | 💻 <a href="https://github.com/eliahuhorwitz/ProbeX" target="_blank">GitHub</a> | 🤗 <a href="https://huggingface.co/ProbeX" target="_blank">Dataset</a> | |
| </p> | |
|  | |
| ## Model Details | |
| | Attribute | Value | | |
| |---|---| | |
| | **Subset** | ResNet | | |
| | **Split** | test | | |
| | **Base Model** | `microsoft/resnet-101` | | |
| | **Dataset** | CIFAR100 (50 classes) | | |
| ## Training Hyperparameters | |
| | Parameter | Value | | |
| |---|---| | |
| | Learning Rate | 9e-05 | | |
| | LR Scheduler | constant_with_warmup | | |
| | Epochs | 5 | | |
| | Max Train Steps | 1665 | | |
| | Batch Size | 64 | | |
| | Weight Decay | 0.03 | | |
| | Seed | 975 | | |
| | Random Crop | False | | |
| | Random Flip | True | | |
| ## Performance | |
| | Metric | Value | | |
| |---|---| | |
| | Train Accuracy | 0.9488 | | |
| | Val Accuracy | 0.8880 | | |
| | Test Accuracy | 0.8798 | | |
| ## Training Categories | |
| The model was fine-tuned on the following 50 CIFAR100 classes: | |
| `porcupine`, `sunflower`, `pear`, `streetcar`, `tulip`, `crocodile`, `willow_tree`, `castle`, `bed`, `cup`, `oak_tree`, `cloud`, `elephant`, `man`, `keyboard`, `bicycle`, `raccoon`, `pickup_truck`, `plate`, `trout`, `lobster`, `plain`, `squirrel`, `skyscraper`, `hamster`, `cockroach`, `seal`, `couch`, `telephone`, `mountain`, `otter`, `crab`, `forest`, `can`, `motorcycle`, `tractor`, `ray`, `palm_tree`, `wolf`, `dolphin`, `rocket`, `house`, `sea`, `pine_tree`, `television`, `aquarium_fish`, `boy`, `snail`, `dinosaur`, `turtle` | |