update librispeech asr1 transformer result

examples/librispeech/asr1/RESULTS.md

@@ -21,7 +21,7 @@
 ## Transformer
 | Model | Params | Config | Augmentation| Test set | Decode method | Loss | WER |  
 | --- | --- | --- | --- | --- | --- | --- | --- |
-| transformer | 32.52 M | conf/transformer.yaml | spec_aug  | test-clean | attention | 6.725063021977743 | 0.047417 |  
-| transformer | 32.52 M | conf/transformer.yaml | spec_aug  | test-clean | ctc_greedy_search | 6.725063021977743 | 0.053922 |  
-| transformer | 32.52 M | conf/transformer.yaml | spec_aug  | test-clean | ctc_prefix_beam_search | 6.725063021977743 | 0.053180 |  
-| transformer | 32.52 M | conf/transformer.yaml | spec_aug  | test-clean | attention_rescoring | 6.725063021977743 | 0.041026 |  
+| transformer | 32.52 M | conf/transformer.yaml | spec_aug  | test-clean | attention | 6.484564081827799 | 0.044355 |  
+| transformer | 32.52 M | conf/transformer.yaml | spec_aug  | test-clean | ctc_greedy_search | 6.484564081827799 | 0.050479 |  
+| transformer | 32.52 M | conf/transformer.yaml | spec_aug  | test-clean | ctc_prefix_beam_search | 6.484564081827799 | 0.049890 |  
+| transformer | 32.52 M | conf/transformer.yaml | spec_aug  | test-clean | attention_rescoring | 6.484564081827799 | 0.039200 |  

examples/librispeech/asr1/conf/transformer.yaml

@@ -1,3 +1,40 @@
+# network architecture
+model:
+    cmvn_file: 
+    cmvn_file_type: "json"
+    # encoder related
+    encoder: transformer
+    encoder_conf:
+        output_size: 256    # dimension of attention
+        attention_heads: 4
+        linear_units: 2048  # the number of units of position-wise feed forward
+        num_blocks: 12      # the number of encoder blocks
+        dropout_rate: 0.1
+        positional_dropout_rate: 0.1
+        attention_dropout_rate: 0.0
+        input_layer: conv2d # encoder input type, you can chose conv2d, conv2d6 and conv2d8
+        normalize_before: true
+
+    # decoder related
+    decoder: transformer
+    decoder_conf:
+        attention_heads: 4
+        linear_units: 2048
+        num_blocks: 6
+        dropout_rate: 0.1
+        positional_dropout_rate: 0.1
+        self_attention_dropout_rate: 0.0
+        src_attention_dropout_rate: 0.0
+
+    # hybrid CTC/attention
+    model_conf:
+        ctc_weight: 0.3
+        ctc_dropoutrate: 0.0
+        ctc_grad_norm_type: null 
+        lsm_weight: 0.1     # label smoothing option
+        length_normalized_loss: false
+
+
 # https://yaml.org/type/float.html
 data:
   train_manifest: data/manifest.train
@@ -36,43 +73,6 @@ collator:
   num_workers: 2
 
 
-# network architecture
-model:
-    cmvn_file: 
-    cmvn_file_type: "json"
-    # encoder related
-    encoder: transformer
-    encoder_conf:
-        output_size: 256    # dimension of attention
-        attention_heads: 4
-        linear_units: 2048  # the number of units of position-wise feed forward
-        num_blocks: 12      # the number of encoder blocks
-        dropout_rate: 0.1
-        positional_dropout_rate: 0.1
-        attention_dropout_rate: 0.0
-        input_layer: conv2d # encoder input type, you can chose conv2d, conv2d6 and conv2d8
-        normalize_before: true
-
-    # decoder related
-    decoder: transformer
-    decoder_conf:
-        attention_heads: 4
-        linear_units: 2048
-        num_blocks: 6
-        dropout_rate: 0.1
-        positional_dropout_rate: 0.1
-        self_attention_dropout_rate: 0.0
-        src_attention_dropout_rate: 0.0
-
-    # hybrid CTC/attention
-    model_conf:
-        ctc_weight: 0.3
-        ctc_dropoutrate: 0.0
-        ctc_grad_norm_type: null 
-        lsm_weight: 0.1     # label smoothing option
-        length_normalized_loss: false
-
-
 training:
   n_epoch: 120 
   accum_grad: 4