diff --git a/TTS/bin/train_tts.py b/TTS/bin/train_tts.py
index 0c01a79e..f5bc364f 100644
--- a/TTS/bin/train_tts.py
+++ b/TTS/bin/train_tts.py
@@ -637,7 +637,7 @@ if __name__ == '__main__':
     check_config(c)
     _ = os.path.dirname(os.path.realpath(__file__))
 
-    if c.apex_amp_level:
+    if c.apex_amp_level is 'O1':
         print("   >  apex AMP level: ", c.apex_amp_level)
 
     OUT_PATH = args.continue_path
diff --git a/TTS/tts/configs/config.json b/TTS/tts/configs/config.json
index d98802f7..6a60fe81 100644
--- a/TTS/tts/configs/config.json
+++ b/TTS/tts/configs/config.json
@@ -67,7 +67,7 @@
     "gradual_training": [[0, 7, 64], [1, 5, 64], [50000, 3, 32], [130000, 2, 32], [290000, 1, 32]], //set gradual training steps [first_step, r, batch_size]. If it is null, gradual training is disabled. For Tacotron, you might need to reduce the 'batch_size' as you proceeed.
     "loss_masking": true,         // enable / disable loss masking against the sequence padding.
     "ga_alpha": 10.0,        // weight for guided attention loss. If > 0, guided attention is enabled.
-    "apex_amp_level": "", // level of optimization with NVIDIA's apex feature for automatic mixed FP16/FP32 precision (AMP), NOTE: currently only O1 is supported, use "" (empty string) to deactivate
+    "apex_amp_level": null, // level of optimization with NVIDIA's apex feature for automatic mixed FP16/FP32 precision (AMP), NOTE: currently only O1 is supported, and use "O1" to activate.
 
     // VALIDATION
     "run_eval": true,