Create hyperparams.yaml

hyperparams.yaml

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+# ############################################################################
+# Model: ResNet for Speaker verification
+# ############################################################################
+
+# Feature parameters
+n_mels: 80
+
+# Pretrain folder (HuggingFace)
+pretrained_path: EvGUT/speechbrain_bcm5
+
+# Output parameters
+out_n_neurons: 235
+
+# Model params
+compute_features: !new:speechbrain.lobes.features.Fbank
+    n_mels: !ref <n_mels>
+
+mean_var_norm: !new:speechbrain.processing.features.InputNormalization
+    norm_type: sentence
+    std_norm: False
+
+embedding_model: !new:speechbrain.lobes.models.ResNet.ResNet
+    input_size: !ref <n_mels>
+    channels: [128, 128, 256, 256]
+    strides: [1, 2, 2, 2]
+    block_sizes: [3, 4, 6, 3]
+    lin_neurons: 512
+
+classifier: !new:speechbrain.lobes.models.ResNet.Classifier
+    input_size: 512
+    out_neurons: !ref <out_n_neurons>
+
+mean_var_norm_emb: !new:speechbrain.processing.features.InputNormalization
+    norm_type: global
+    std_norm: False
+
+modules:
+    compute_features: !ref <compute_features>
+    mean_var_norm: !ref <mean_var_norm>
+    embedding_model: !ref <embedding_model>
+    mean_var_norm_emb: !ref <mean_var_norm_emb>
+    classifier: !ref <classifier>
+        
+label_encoder: !new:speechbrain.dataio.encoder.CategoricalEncoder
+
+        
+pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
+    loadables:
+        embedding_model: !ref <embedding_model>
+        classifier: !ref <classifier>
+    paths:
+        embedding_model: !ref <pretrained_path>/embedding_model.ckpt
+        classifier: !ref <pretrained_path>/classifier.ckpt