fix model avg

conf/conformer_rnnt_large.yaml

@@ -0,0 +1,100 @@
+# network architecture
+# encoder related
+encoder: conformer
+encoder_conf:
+    output_size: 512    # dimension of attention
+    attention_heads: 8
+    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: 0.1
+    input_layer: conv2d # encoder input type, you can chose conv2d, conv2d6 and conv2d8
+    normalize_before: true
+    cnn_module_kernel: 31
+    use_cnn_module: true
+    activation_type: 'swish'
+    pos_enc_layer_type: 'rel_pos'
+    selfattention_layer_type: 'rel_selfattn'
+
+
+joint_conf:
+    join_dim: 512
+    prejoin_linear: True
+    postjoin_linear: false
+    joint_mode: 'add'
+    activation: 'tanh'
+
+predictor: rnn
+predictor_conf:
+    embed_size: 512
+    output_size: 512
+    embed_dropout: 0.1
+    hidden_size: 512
+    num_layers: 2
+    bias: true
+    rnn_type: 'lstm'
+    dropout: 0.1
+
+decoder: bitransformer
+decoder_conf:
+  attention_heads: 8
+  dropout_rate: 0.1
+  linear_units: 2048
+  num_blocks: 3
+  positional_dropout_rate: 0.1
+  r_num_blocks: 3
+  self_attention_dropout_rate: 0.1
+  src_attention_dropout_rate: 0.1
+
+# hybrid transducer+ctc+attention
+model_conf:
+    transducer_weight: 0.75
+    ctc_weight: 0.1
+    attention_weight: 0.15
+    lsm_weight: 0.1     # label smoothing option
+    length_normalized_loss: false
+    reverse_weight: 0.3
+
+dataset_conf:
+    filter_conf:
+        max_length: 1650
+        min_length: 10
+        token_max_length: 200
+        token_min_length: 1
+    resample_conf:
+        resample_rate: 16000
+    speed_perturb: true
+    fbank_conf:
+        num_mel_bins: 80
+        frame_shift: 10
+        frame_length: 25
+        dither: 0.1
+    spec_aug: true
+    spec_aug_conf:
+        num_t_mask: 2
+        num_f_mask: 2
+        max_t: 50
+        max_f: 10
+    shuffle: true
+    shuffle_conf:
+        shuffle_size: 1500
+    sort: true
+    sort_conf:
+        sort_size: 500  # sort_size should be less than shuffle_size
+    batch_conf:
+        batch_type: 'dynamic' # static or dynamic
+        max_frames_in_batch: 4000
+
+grad_clip: 4
+accum_grad: 1
+max_epoch: 140
+log_interval: 100
+
+optim: adam
+optim_conf:
+    lr: 0.001
+scheduler: warmuplr     # pytorch v1.1.0+ required
+scheduler_conf:
+    warmup_steps: 25000
+

exp/conformer_transducer/avg_5.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:94c5d9396cda5646df79f3c77286bb0d8627a3e0a527d36cbe50d3349b42f1e9
+oid sha256:3224c02c52e558395dd02f4489ac23a243094c94d446119558c6f86540fb347b
 size 277103087

exp/conformer_transducer/{avg_10.pt → avg_6.pt}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2f737fede01276bfe182dd099d1799987a7b30a8a911b7d79a798d0db24a16c9
+oid sha256:3d3fa1073140f9adfe46cbfc7a391ff7c4894a414f2a7cb4d28f0cc60ed1f98b
 size 277103087