diff --git a/rl_coach/agents/clipped_ppo_agent.py b/rl_coach/agents/clipped_ppo_agent.py
index 362dd4c..d84142a 100644
--- a/rl_coach/agents/clipped_ppo_agent.py
+++ b/rl_coach/agents/clipped_ppo_agent.py
@@ -51,6 +51,9 @@ class ClippedPPONetworkParameters(NetworkParameters):
         self.use_separate_networks_per_head = True
         self.async_training = False
         self.l2_regularization = 0
+
+        # The target network is used in order to freeze the old policy, while making updates to the new one
+        # in train_network()
         self.create_target_network = True
         self.shared_optimizer = True
         self.scale_down_gradients_by_number_of_workers_for_sync_training = True
@@ -99,7 +102,6 @@ class ClippedPPOAgent(ActorCriticAgent):
         self.likelihood_ratio = self.register_signal('Likelihood Ratio')
         self.clipped_likelihood_ratio = self.register_signal('Clipped Likelihood Ratio')
 
-
     def set_session(self, sess):
         super().set_session(sess)
         if self.ap.algorithm.normalization_stats is not None:
@@ -219,6 +221,7 @@ class ClippedPPOAgent(ActorCriticAgent):
 
             self.value_loss.add_sample(batch_results['losses'][0])
             self.policy_loss.add_sample(batch_results['losses'][1])
+            self.loss.add_sample(batch_results['total_loss'])
 
             if self.ap.network_wrappers['main'].learning_rate_decay_rate != 0:
                 curr_learning_rate = self.networks['main'].online_network.get_variable_value(
@@ -268,7 +271,8 @@ class ClippedPPOAgent(ActorCriticAgent):
 
             self.post_training_commands()
             self.training_iteration += 1
-            # self.update_log()  # should be done in order to update the data that has been accumulated * while not playing *
+            # should be done in order to update the data that has been accumulated * while not playing *
+            self.update_log()
             return None
 
     def run_pre_network_filter_for_inference(self, state: StateType):
diff --git a/rl_coach/architectures/tensorflow_components/heads/head.py b/rl_coach/architectures/tensorflow_components/heads/head.py
index 3a1c4db..165ed98 100644
--- a/rl_coach/architectures/tensorflow_components/heads/head.py
+++ b/rl_coach/architectures/tensorflow_components/heads/head.py
@@ -61,8 +61,6 @@ class Head(object):
         self.regularizations = []
         self.loss_weight = tf.Variable([float(w) for w in force_list(loss_weight)],
                                        trainable=False, collections=[tf.GraphKeys.LOCAL_VARIABLES])
-        self.loss_weight_placeholder = tf.placeholder("float")
-        self.set_loss_weight = tf.assign(self.loss_weight, self.loss_weight_placeholder)
         self.target = []
         self.importance_weight = []
         self.input = []