diff --git a/filippo/code/qa_model.py b/filippo/code/qa_model.py
diff --git a/filippo/code/qa_model.pyc b/filippo/code/qa_model.pyc
diff --git a/filippo/code/train.py b/filippo/code/train.py
@@ -16,12 +16,12 @@
 logging.basicConfig(level=logging.INFO)
 
 tf.app.flags.DEFINE_float("learning_rate", 0.01, "Learning rate.")
-tf.app.flags.DEFINE_float("max_gradient_norm", 10.0, "Clip gradients to this norm.")
+tf.app.flags.DEFINE_float("max_gradient_norm", 8, "Clip gradients to this norm.")
 tf.app.flags.DEFINE_float("dropout", 0.15, "Fraction of units randomly dropped on non-recurrent connections.")
-tf.app.flags.DEFINE_integer("batch_size", 100, "Batch size to use during training.")
+tf.app.flags.DEFINE_integer("batch_size", 50, "Batch size to use during training.")
 tf.app.flags.DEFINE_integer("epochs", 10, "Number of epochs to train.")
-tf.app.flags.DEFINE_integer("state_size", 50, "Size of each model layer.")
-tf.app.flags.DEFINE_integer("output_size", 750, "The output size of your model.")
+tf.app.flags.DEFINE_integer("state_size", 100, "Size of each model layer.")
+tf.app.flags.DEFINE_integer("output_size", 766, "The output size of your model.")
 tf.app.flags.DEFINE_integer("embedding_size", 100, "Size of the pretrained vocabulary.")
 tf.app.flags.DEFINE_string("data_dir", "data/squad", "SQuAD directory (default ./data/squad)")
 tf.app.flags.DEFINE_string("train_dir", "train", "Training directory to save the model parameters (default: ./train).")
@@ -34,9 +34,9 @@
 tf.app.flags.DEFINE_string("embed_path", "", "Path to the trimmed GLoVe embedding (default: ./data/squad/glove.trimmed.{embedding_size}.npz)")
 
 # added
-tf.app.flags.DEFINE_string("model_type", "lstm", "specify either gru or lstm cell type for encoding")
+tf.app.flags.DEFINE_string("model_type", "gru", "specify either gru or lstm cell type for encoding")
 tf.app.flags.DEFINE_integer("debug", 1, "whether to set debug or not")
-
+tf.app.flags.DEFINE_integer("grad_clip", 1, "whether to clip gradients or not")
 
 FLAGS = tf.app.flags.FLAGS
 
@@ -152,7 +152,7 @@ def main(_):
 
     question_encoder = Encoder(size=FLAGS.state_size, vocab_dim=FLAGS.embedding_size, name="question_encoder")
     context_encoder = Encoder(size=FLAGS.state_size, vocab_dim=FLAGS.embedding_size, name="context_encoder")
-    decoder = Decoder(output_size=FLAGS.output_size)
+    decoder = Decoder(output_size=FLAGS.output_size, name="decoder")
 
     qa = QASystem(encoder=(question_encoder,context_encoder), 
                   decoder=decoder,