Upload train_config.yaml

train_config.yaml

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+# Generated 2023-05-14 from:
+# /home/agorin/cryceleb2023/hparams/ecapa_voxceleb_basic.yaml
+# yamllint disable
+# ################################
+# Model: Speaker identification with ECAPA for CryCeleb
+# Authors: David Budaghyan
+# ################################
+
+ckpt_interval_minutes: 15 # save checkpoint every N min
+
+##### SEED
+seed: 3011
+__set_seed: !apply:crybrain_config_utils.set_seed [3011]
+
+# DataLoader
+bs: 32
+train_dataloader_options:
+  batch_size: 32
+  shuffle: true
+val_dataloader_options:
+  batch_size: 2
+  shuffle: false
+
+##### ESTIMATOR COMPONENTS
+# Fbank (feature extractor)
+n_mels: 80
+left_frames: 0
+right_frames: 0
+deltas: false
+compute_features: &id002 !new:speechbrain.lobes.features.Fbank
+  n_mels: 80
+  left_frames: 0
+  right_frames: 0
+  deltas: false
+
+# ECAPA
+emb_dim: 192
+embedding_model: &id001 !new:speechbrain.lobes.models.ECAPA_TDNN.ECAPA_TDNN
+  input_size: 80
+  channels: [1024, 1024, 1024, 1024, 3072]
+  kernel_sizes: [5, 3, 3, 3, 1]
+  dilations: [1, 2, 3, 4, 1]
+  groups: [1, 1, 1, 1, 1]
+  attention_channels: 128
+  lin_neurons: 192
+
+# If you do not want to use the pretrained encoder you can simply delete pretrained_encoder field.
+pretrained_model_name: spkrec-ecapa-voxceleb
+pretrained_embedding_model_path: speechbrain/spkrec-ecapa-voxceleb/embedding_model.ckpt
+pretrained_embedding_model: !new:speechbrain.utils.parameter_transfer.Pretrainer
+  collect_in: ./experiments/ecapa_voxceleb_ft_basic/ckpts
+  loadables:
+    model: *id001
+  paths:
+    model: speechbrain/spkrec-ecapa-voxceleb/embedding_model.ckpt
+
+# CLASSIFIER
+n_classes: 348
+                        # check-yaml disable
+
+
+classifier: &id003 !new:speechbrain.lobes.models.ECAPA_TDNN.Classifier
+  input_size: 192
+  out_neurons: 348
+
+##### EPOCH COUNTER
+n_epochs: 1000
+epoch_counter: &id005 !new:speechbrain.utils.epoch_loop.EpochCounter
+  limit: 1000
+
+##### OPTIMIZER
+start_lr: 0.0001
+opt_class: !name:torch.optim.Adam
+  lr: 0.0001
+  weight_decay: 0.000002
+
+#####  LEARNING RATE SCHEDULERS
+lrsched_name: cyclic
+# one of:
+#   onplateau
+#   cyclic
+lr_min: 0.0000000001
+lr_scheduler: &id006 !apply:crybrain_config_utils.choose_lrsched
+  lrsched_name: cyclic
+  #below are kwargs, only the ones relevant to the type of scheduler will be
+  #used for initialization in `choose_lrsched`
+
+  #onplateau (ReduceLROnPlateau)
+  lr_min: 0.0000000001
+  factor: 0.4
+  patience: 10
+  dont_halve_until_epoch: 35
+  #cyclic (CyclicLRScheduler)
+  base_lr: 0.00000001
+  max_lr: 0.0001
+  step_size: 100
+  mode: triangular
+  gamma: 1.0
+  scale_fn:
+  scale_mode: cycle
+
+sample_rate: 16000
+mean_var_norm: &id004 !new:speechbrain.processing.features.InputNormalization
+
+  norm_type: sentence
+  std_norm: false
+
+modules:
+  compute_features: *id002
+  embedding_model: *id001
+  classifier: *id003
+  mean_var_norm: *id004
+compute_cost: !new:speechbrain.nnet.losses.LogSoftmaxWrapper
+  loss_fn: !new:speechbrain.nnet.losses.AdditiveAngularMargin
+    margin: 0.2
+    scale: 30
+
+classification_stats: !name:speechbrain.utils.metric_stats.ClassificationStats
+  ###################################################################
+  ### OUTPUT PATHS ###
+
+
+experiment_name: ecapa_voxceleb_ft_basic
+               # must run from the directory which contains "experiments"
+
+
+experiment_dir: ./experiments/ecapa_voxceleb_ft_basic
+train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger
+  save_file: ./experiments/ecapa_voxceleb_ft_basic/train_log.txt
+
+checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
+  checkpoints_dir: ./experiments/ecapa_voxceleb_ft_basic/ckpts
+  recoverables:
+    embedding_model: *id001
+    classifier: *id003
+    normalizer: *id004
+    counter: *id005
+    lr_scheduler: *id006