Verbose 1 en el fit para ver la evolución de la red

embeddings_RNN.py

@@ -154,8 +154,8 @@ def classification_embedings_rnn(tweets_train, tweets_train_labels_numeric, twee
     # compile the model
     # compile the model
     model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['acc'])
     model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['acc'])
     print("Training the model...")
     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)
+    model.fit(train_features_pad, tweets_train_labels_numeric, batch_size=32, epochs=10, verbose=1, validation_data=(train_features_pad,tweets_train_labels_numeric))
+    loss, accuracy = model.evaluate(train_features_pad, tweets_train_labels_numeric, batch_size=32, verbose=1)
     print('Accuracy trainning: %f' % (accuracy*100))
     print('Accuracy trainning: %f' % (accuracy*100))
     
     
     #prediction
     #prediction