Tercera versión script

embeddings_RNN.py

@@ -150,13 +150,13 @@ def classification_embedings_rnn(tweets_train, tweets_train_labels_numeric, twee
     # summarize the model
     print(model.summary())
 
-    print("compilando modelo")
+    print("Compiling the model...")
     # compile the model
     model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['acc'])
-    print("entrenando")
+    print("Training the model...")
     model.fit(train_features_pad, tweets_train_labels_numeric, batch_size=32, epochs=10, verbose=0)
     loss, accuracy = model.evaluate(train_features_pad, tweets_train_labels_numeric, verbose=0)
-    print('Accuracy: %f' % (accuracy*100))
+    print('Accuracy trainning: %f' % (accuracy*100))
     
     #prediction
     tweets_dev_classified_labels = model.predict_classes(padded_docs_dev, batch_size=32, verbose=1)