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from model import JobRecommendationModel
import os
import logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s',
handlers=[
logging.FileHandler('job_recommendation_training.log'),
logging.StreamHandler()
]
)
logger = logging.getLogger(__name__)
def main():
try:
logger.info("Starting job recommendation model training")
# Create model instance
model = JobRecommendationModel()
# Train model
train_data_path = 'models/job_recommendation/train_data/training_data.json'
history = model.train(train_data_path, epochs=10)
# Create directory if it doesn't exist
os.makedirs('models/job_recommendation/saved_model', exist_ok=True)
# Save model
model_path = 'models/job_recommendation/saved_model/model.keras'
model.save_model(model_path)
logger.info("Model training completed and saved successfully")
except Exception as e:
logger.error(f"Error during model training: {str(e)}", exc_info=True)
raise
if __name__ == "__main__":
main() |