deploy

service/train_model.py

@@ -19,7 +19,16 @@ X_test_embeddings = model.encode(X_test.tolist())
 logistic_model = LogisticRegression(max_iter=100)
 logistic_model.fit(X_train_embeddings, y_train)
 
+# Evaluate Model
+y_pred = logistic_model.predict(X_test_embeddings)
+accuracy = accuracy_score(y_test, y_pred)
+print(f"Model Accuracy: {accuracy}")
+print(classification_report(y_test, y_pred))
+
+# Save Model and Sentence Transformer
+print("Saving model and embeddings...")
 with open('models/logistic_regression_model.pkl', 'wb') as f:
     pickle.dump(logistic_model, f)
 
 model.save('models/sentence_transformer')
+print("Model training and saving complete.")