diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.data2vec_audio.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.data2vec_audio.py.swp
index 9cc6081e9..f6c9c6fc2 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.data2vec_audio.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.data2vec_audio.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py
index 76def32dc..2bc421706 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py
@@ -40,12 +40,7 @@ logger = logging.getLogger().setLevel(logging.INFO)
 class TransformerEncoderAdapter(TransformerEncoder):
     def __init__(self, args: Wav2Vec2Config):
         super().__init__(args)
-        self.adapters = ResidualAdapterModule(proj_dim=512)
-
-        for p in self.adapters.parameters():
-            p.data /= 10.
-        #p.data = nn.Parameter(torch.zeros(p.size()).to('cuda'))
-        #p.data = nn.Parameter(torch.randn(p.size()).to('cuda')/20.)
+        self.lora = LoRAModule()
 
     def forward(self, x, padding_mask=None, layer=None, tgt_layer=None):
         x, layer_results = self.extract_features_with_adapter(