diff --git a/TTS/bin/train_tacotron.py b/TTS/bin/train_tacotron.py
index 6c12e54b..1263a616 100644
--- a/TTS/bin/train_tacotron.py
+++ b/TTS/bin/train_tacotron.py
@@ -86,8 +86,8 @@ def format_data(data, speaker_mapping=None):
     mel_input = data[4]
     mel_lengths = data[5]
     stop_targets = data[6]
-    avg_text_length = torch.mean(text_lengths.float())
-    avg_spec_length = torch.mean(mel_lengths.float())
+    max_text_length = torch.max(text_lengths.float())
+    max_spec_length = torch.max(mel_lengths.float())
 
     if c.use_speaker_embedding:
         if c.use_external_speaker_embedding_file:
@@ -123,7 +123,7 @@ def format_data(data, speaker_mapping=None):
         if speaker_embeddings is not None:
             speaker_embeddings = speaker_embeddings.cuda(non_blocking=True)
 
-    return text_input, text_lengths, mel_input, mel_lengths, linear_input, stop_targets, speaker_ids, speaker_embeddings, avg_text_length, avg_spec_length
+    return text_input, text_lengths, mel_input, mel_lengths, linear_input, stop_targets, speaker_ids, speaker_embeddings, max_text_length, max_spec_length
 
 
 def train(model, criterion, optimizer, optimizer_st, scheduler,
@@ -144,7 +144,7 @@ def train(model, criterion, optimizer, optimizer_st, scheduler,
         start_time = time.time()
 
         # format data
-        text_input, text_lengths, mel_input, mel_lengths, linear_input, stop_targets, speaker_ids, speaker_embeddings, avg_text_length, avg_spec_length = format_data(data, speaker_mapping)
+        text_input, text_lengths, mel_input, mel_lengths, linear_input, stop_targets, speaker_ids, speaker_embeddings, max_text_length, max_spec_length = format_data(data, speaker_mapping)
         loader_time = time.time() - end_time
 
         global_step += 1
@@ -255,8 +255,8 @@ def train(model, criterion, optimizer, optimizer_st, scheduler,
         # print training progress
         if global_step % c.print_step == 0:
             log_dict = {
-                "avg_spec_length": [avg_spec_length, 1],  # value, precision
-                "avg_text_length": [avg_text_length, 1],
+                "max_spec_length": [max_spec_length, 1],  # value, precision
+                "max_text_length": [max_text_length, 1],
                 "step_time": [step_time, 4],
                 "loader_time": [loader_time, 2],
                 "current_lr": current_lr,