src/fine_tune_helpers.py

import pandas as pd
import logging

def preprocess_data(dataset_path):
    try:
        data = pd.read_csv(dataset_path)
        logging.info("Data loaded successfully")
        
        # Example preprocessing: clean data, handle missing values, etc.
        data.dropna(inplace=True)
        
        return data
    except Exception as e:
        logging.error(f"Error during data preprocessing: {e}")

def train_model(data, config):
    try:
        # Assuming some model training logic
        model = "YourModel"  # Placeholder
        logging.info("Model training started")
        
        # Configuration-based training
        # Use hyperparameters from config
        learning_rate = config.getfloat("model", "learning_rate")
        
        return model
    except Exception as e:
        logging.error(f"Error during model training: {e}")

def save_model(model):
    try:
        # Save the fine-tuned model
        model.save("model_path")
        logging.info("Model saved successfully")
    except Exception as e:
        logging.error(f"Error saving model: {e}")