Model Training and Optimization with Ludwig

Implement your hazard detection model using `Ludwig`, focusing on defining the input and output features and experimenting with different model architectures and hyperparameters (e.g., using Ludwig's hyperopt capabilities). Train your model using the provided simulated lunar terrain datasets. Detail your optimization strategies to ensure the model performs well in real-time on resource-constrained hardware, including any post-training quantization or pruning steps. Explain how `Phi-3` could be used to generate synthetic training data or enrich hazard descriptions if you had access to more specific textual mission parameters.