seti21.py

import pandas as pd
from sklearn.metrics import classification_report, confusion_matrix

def evaluate_model_results(model, test_data, test_labels, 
                           class_label_mapping, class_labels):
    predictions = model.predict(test_data, verbose=1)
    prediction_labels = [class_label_mapping[idx] for idx in predictions.argmax(axis=1)]
    print(classification_report(y_true=test_labels, y_pred=prediction_labels))
    return pd.DataFrame(confusion_matrix(y_true=test_labels, y_pred=prediction_labels, labels=class_labels),
                        index=class_labels, columns=class_labels)