prints predictions

fromNotebook.py

@@ -92,6 +92,26 @@
 
 history = model.fit(x_train, y_train,
                     batch_size=batch_size,
-                    epochs=30,
+                    epochs=48,
                     verbose=1,
-                    validation_split=0.1)
+                    validation_split=0.1)
+
+
+
+
+score = model.evaluate(x_test, y_test,
+                       batch_size=batch_size, verbose=1)
+
+print('Test accuracy:', score[1])
+
+text_labels = encoder.classes_
+
+for i in range(100):
+    prediction = model.predict(np.array([x_test[i]]))
+    predicted_label = text_labels[np.argmax(prediction[0])]
+    #print(test_files_names.iloc[i])
+    print('Actual label:' + test_tags.iloc[i])
+    print("Predicted label: " + predicted_label)
+
+
+