IRCP Sentence Transformer Training

This directory contains the training pipeline for fine-tuning sentence transformers with IRCP coordinate-based supervision. We fine-tune sentence transformers (like `all-MiniLM-L6-v2`) to be **IRCP-aware** by using IRCP coordinate proximity as the similarity signal. This creates embeddings that understand conversation structure, intent depth, and temporal flow. The default IRCP model **freezes** the sentence transformer encoder and only trains custom heads. This means: ❌ Embeddings are generic (not IRCP-aware) ❌ Can't learn conversation-specific patterns ❌ Limited by pre-trained semantic similarity ✅ End-to-end training of embeddings ✅ Learn IRCP-specific patterns ✅ Better coordinate prediction ✅ Improved conversation understanding