# Test the trained network
z1_final, a1_final, z2_final, final_predictions = forward_pass(X, W1_trained, b1_trained, W2_trained, b2_trained)

print("Final Results:")
print("Input -> Target | Prediction | Rounded")
print("-" * 40)
for i in range(len(X)):
    pred = final_predictions[i, 0]
    rounded = round(pred)
    target = y[i, 0]
    print(f"{X[i]} -> {target}      | {pred:.4f}    | {rounded}")

# Calculate accuracy
rounded_predictions = np.round(final_predictions)
accuracy = np.mean(rounded_predictions == y)
print(f"\nAccuracy: {accuracy:.1%}")