Embedding Model Fine-tuning Plan

Create a fine-tuning plan for our embedding model.

## Current Model
{{current_model}}

## Domain Data
{{domain_data_description}}

## Quality Issues
{{quality_issues}}

Develop a comprehensive plan:

**Step 1: Data Preparation**
- Training data collection strategies
- Hard negative mining
- Quality filtering
- Data augmentation

**Step 2: Training Configuration**
- Loss function selection (contrastive, triplet, etc.)
- Hyperparameter recommendations
- Curriculum learning approach

**Step 3: Evaluation Protocol**
- Hold-out test sets
- Domain-specific benchmarks
- Production metric correlation

**Step 4: Deployment Strategy**
- A/B testing plan
- Rollback criteria
- Reindexing approach

Provide code snippets for each step.