Resolve conflicts

logistic_reg.py

@@ -64,7 +64,7 @@ print(f"F1 Score: {classification_report(y_val_encoded, y_val_pred, target_names
 print(f"Hamming Loss: {hamming_loss(y_val_encoded, y_val_pred):.4f}")
 
 # Step 7: Save the Model and Preprocessing Artifacts
-dump(best_model, "optimized_logistic_model.joblib")  # Save the optimized Logistic Regression model
+dump(best_model, "logistic_model.joblib")  # Save the optimized Logistic Regression model
 dump(tfidf_vectorizer, "tfidf_vectorizer.joblib")  # Save the TF-IDF vectorizer
 dump(mlb, "label_binarizer.joblib")  # Save the MultiLabelBinarizer