diff --git a/egs/librispeech/ASR/pruned_transducer_stateless2/train.py b/egs/librispeech/ASR/pruned_transducer_stateless2/train.py
index 80617847a..d15c44388 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless2/train.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless2/train.py
@@ -35,7 +35,7 @@ export CUDA_VISIBLE_DEVICES="0,1,2,3"
   --world-size 4 \
   --num-epochs 30 \
   --start-epoch 0 \
-  --use_fp16 1 \
+  --use-fp16 1 \
   --exp-dir pruned_transducer_stateless2/exp \
   --full-libri 1 \
   --max-duration 550
diff --git a/egs/librispeech/ASR/transducer/decoder.py b/egs/librispeech/ASR/transducer/decoder.py
index 7b529ac19..333fff300 100644
--- a/egs/librispeech/ASR/transducer/decoder.py
+++ b/egs/librispeech/ASR/transducer/decoder.py
@@ -89,9 +89,9 @@ class Decoder(nn.Module):
             - (h, c), containing the state information for LSTM layers.
               Both are of shape (num_layers, N, C)
         """
-        embeding_out = self.embedding(y)
-        embeding_out = self.embedding_dropout(embeding_out)
-        rnn_out, (h, c) = self.rnn(embeding_out, states)
+        embedding_out = self.embedding(y)
+        embedding_out = self.embedding_dropout(embedding_out)
+        rnn_out, (h, c) = self.rnn(embedding_out, states)
         out = self.output_linear(rnn_out)
 
         return out, (h, c)
diff --git a/egs/yesno/ASR/transducer/decoder.py b/egs/yesno/ASR/transducer/decoder.py
index aa8a16845..7ae540d03 100644
--- a/egs/yesno/ASR/transducer/decoder.py
+++ b/egs/yesno/ASR/transducer/decoder.py
@@ -84,9 +84,9 @@ class Decoder(nn.Module):
             - (h, c), which contain the state information for RNN layers.
               Both are of shape (num_layers, N, C)
         """
-        embeding_out = self.embedding(y)
-        embeding_out = self.embedding_dropout(embeding_out)
-        rnn_out, (h, c) = self.rnn(embeding_out, states)
+        embedding_out = self.embedding(y)
+        embedding_out = self.embedding_dropout(embedding_out)
+        rnn_out, (h, c) = self.rnn(embedding_out, states)
         out = self.output_linear(rnn_out)
 
         return out, (h, c)
diff --git a/icefall/checkpoint.py b/icefall/checkpoint.py
index cc167292b..a4e71a148 100644
--- a/icefall/checkpoint.py
+++ b/icefall/checkpoint.py
@@ -150,12 +150,25 @@ def average_checkpoints(
     n = len(filenames)
 
     avg = torch.load(filenames[0], map_location=device)["model"]
+
+    # Identify shared parameters. Two parameters are said to be shared
+    # if they have the same data_ptr
+    uniqued: Dict[int, str] = dict()
+
+    for k, v in avg.items():
+        v_data_ptr = v.data_ptr()
+        if v_data_ptr in uniqued:
+            continue
+        uniqued[v_data_ptr] = k
+
+    uniqued_names = list(uniqued.values())
+
     for i in range(1, n):
         state_dict = torch.load(filenames[i], map_location=device)["model"]
-        for k in avg:
+        for k in uniqued_names:
             avg[k] += state_dict[k]
 
-    for k in avg:
+    for k in uniqued_names:
         if avg[k].is_floating_point():
             avg[k] /= n
         else: