diff --git a/egs/librispeech/ASR/conformer_ctc2/train.py b/egs/librispeech/ASR/conformer_ctc2/train.py
index 3366af13e..c4a13b101 100755
--- a/egs/librispeech/ASR/conformer_ctc2/train.py
+++ b/egs/librispeech/ASR/conformer_ctc2/train.py
@@ -675,7 +675,6 @@ def train_one_epoch(
     for batch_idx, batch in enumerate(train_dl):
         params.batch_idx_train += 1
         batch_size = len(batch["supervisions"]["text"])
-        batch_name = batch["supervisions"]["uttid"]
 
         with torch.cuda.amp.autocast(enabled=params.use_fp16):
             loss, loss_info = compute_loss(
@@ -698,10 +697,7 @@ def train_one_epoch(
             scaler.scale(loss).backward()
         except RuntimeError as e:
             if "CUDA out of memory" in str(e):
-                logging.error(
-                    f"failing batch size:{batch_size} "
-                    f"failing batch names {batch_name}"
-                )
+                logging.error(f"failing batch size:{batch_size} ")
             raise
 
         scheduler.step_batch(params.batch_idx_train)
@@ -756,10 +752,7 @@ def train_one_epoch(
             if loss_info["ctc_loss"] == float("inf") or loss_info["att_loss"] == float(
                 "inf"
             ):
-                logging.error(
-                    "Your loss contains inf, something goes wrong"
-                    f"failing batch names {batch_name}"
-                )
+                logging.error("Your loss contains inf, something goes wrong")
             if tb_writer is not None:
                 tb_writer.add_scalar(
                     "train/learning_rate", cur_lr, params.batch_idx_train