diff --git a/paddlespeech/t2s/datasets/am_batch_fn.py b/paddlespeech/t2s/datasets/am_batch_fn.py
index 05471167f..2cb7a11a2 100644
--- a/paddlespeech/t2s/datasets/am_batch_fn.py
+++ b/paddlespeech/t2s/datasets/am_batch_fn.py
@@ -68,7 +68,7 @@ def erniesat_batch_fn(examples,
                       mean_phn_span: int=8,
                       seg_emb: bool=False,
                       text_masking: bool=False):
-    # fields = ["text", "text_lengths", "speech", "speech_lengths", "durations", "pitch", "energy"]
+    # fields = ["text", "text_lengths", "speech", "speech_lengths", "align_start", "align_end"]
     text = [np.array(item["text"], dtype=np.int64) for item in examples]
     speech = [np.array(item["speech"], dtype=np.float32) for item in examples]
 
diff --git a/paddlespeech/t2s/exps/ernie_sat/train.py b/paddlespeech/t2s/exps/ernie_sat/train.py
index 5d8eadb68..ccd1245e1 100644
--- a/paddlespeech/t2s/exps/ernie_sat/train.py
+++ b/paddlespeech/t2s/exps/ernie_sat/train.py
@@ -116,13 +116,6 @@ def train_sp(args, config):
 
     odim = config.n_mels
     model = ErnieSAT(idim=vocab_size, odim=odim, **config["model"])
-    # model_path = "/home/yuantian01/PaddleSpeech_ERNIE_SAT/PaddleSpeech/examples/ernie_sat/pretrained_model/paddle_checkpoint_en/model.pdparams"
-    # state_dict = paddle.load(model_path)
-    # new_state_dict = {}
-    # for key, value in state_dict.items():
-    #     new_key = "model." + key
-    #     new_state_dict[new_key] = value
-    # model.set_state_dict(new_state_dict)
 
     if world_size > 1:
         model = DataParallel(model)