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| import pandas as pd | |
| import os | |
| import random | |
| def create_sbert_training_data(output_path): | |
| """Create sample training data for SBERT model""" | |
| os.makedirs(os.path.dirname(output_path), exist_ok=True) | |
| # Sample training data | |
| data = { | |
| 'resume': [ | |
| 'Experienced software engineer with 5 years in Python and Java development', | |
| 'Web developer specializing in JavaScript and React', | |
| 'Data scientist with machine learning expertise', | |
| 'DevOps engineer with cloud infrastructure experience', | |
| 'System administrator with Linux and networking skills' | |
| ], | |
| 'job_description': [ | |
| 'Seeking senior Python developer with Django experience', | |
| 'Frontend developer needed for React applications', | |
| 'Machine learning engineer for AI projects', | |
| 'Cloud infrastructure specialist with AWS knowledge', | |
| 'IT administrator with network security background' | |
| ], | |
| 'match_score': [85, 90, 75, 80, 95] # Match scores (0-100) | |
| } | |
| df = pd.DataFrame(data) | |
| df.to_csv(output_path, index=False) | |
| print(f"Created SBERT training data at {output_path} with {len(df)} records") | |
| if __name__ == "__main__": | |
| create_sbert_training_data("../data/training/train.csv") |