You could use the scikit-learn classification report. To convert your labels into a numerical or binary format take a look at the scikit-learn label encoder.
from sklearn.metrics import classification_report
y_pred = model.predict(x_test, batch_size=64, verbose=1)
y_pred_bool = np.argmax(y_pred, axis=1)
print(classification_report(y_test, y_pred_bool))
which gives you (output copied from the scikit-learn example):
precision recall f1-score support
class 0 0.50 1.00 0.67 1
class 1 0.00 0.00 0.00 1
class 2 1.00 0.67 0.80 3