Update hyperparams.yalm

hyperparams.yalm

@@ -1,66 +1,28 @@
-# Generated 2022-01-19 from:
-# /scratch/elec/t405-puhe/p/porjazd1/Metadata_Classification/TCN/asr_topic_speechbrain/mgb_asr/hyperparams.yaml
-# yamllint disable
-# Seed needs to be set at top of yaml, before objects with parameters are made
-seed: 1234
-__set_seed: !apply:torch.manual_seed [1234]
+# ############################################################################
+# Model: WAV2VEC base for Emotion Recognition
+# ############################################################################
 
-skip_training: True
 
-output_folder: output_folder_wavlm_base_full_data
-label_encoder_file: !ref <output_folder>/label_encoder.txt
-
-train_log: !ref <output_folder>/train_log.txt
-train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger
-    save_file: !ref <output_folder>/train_log.txt
-save_folder: !ref <output_folder>/save
+# Hparams NEEDED
+HPARAMS_NEEDED: ["encoder_dim", "out_n_neurons", "label_encoder", "softmax"]
+# Modules Needed
+MODULES_NEEDED: ["wav2vec2", "avg_pool", "output_mlp"]
 
+# Feature parameters
 wav2vec2_hub: microsoft/wavlm-base-plus-sv
 
+# Pretrain folder (HuggingFace)
 pretrained_path: Porjaz/wavlm-base-emo-fi
 
-wav2vec2_folder: !ref <save_folder>/wav2vec2_checkpoint
-
-# Feature parameters
-sample_rate: 22050
-new_sample_rate: 16000
-window_size: 25
-n_mfcc: 23
-
-# Training params
-n_epochs: 28
-stopping_factor: 10
-
-dataloader_options:
-    batch_size: 10
-    shuffle: false
-
-test_dataloader_options:
-    batch_size: 1
-    shuffle: false
+# parameters
+encoder_dim: 768
+out_n_neurons: 5
 
-lr: 0.0001
-lr_wav2vec2: 0.00001
-
-#freeze all wav2vec2
-freeze_wav2vec2: False
-#set to true to freeze the CONV part of the wav2vec2 model
-# We see an improvement of 2% with freezing CNNs
-freeze_wav2vec2_conv: True
-
-label_encoder: !new:speechbrain.dataio.encoder.CategoricalEncoder
-
-encoder_dims: 768
-n_classes: 5
-
-# Wav2vec2 encoder
-wav2vec2: !new:speechbrain.lobes.models.huggingface_wav2vec.HuggingFaceWav2Vec2
+wav2vec2: !new:speechbrain.lobes.models.huggingface_transformers.wav2vec2.Wav2Vec2
     source: !ref <wav2vec2_hub>
     output_norm: True
-    freeze: !ref <freeze_wav2vec2>
-    freeze_feature_extractor: !ref <freeze_wav2vec2_conv>
-    save_path: !ref <wav2vec2_folder>
-    output_all_hiddens: True
+    freeze: True
+    save_path: wav2vec2_checkpoints
 
 avg_pool: !new:speechbrain.nnet.pooling.StatisticsPooling
     return_std: False
@@ -70,52 +32,18 @@ label_lin: !new:speechbrain.nnet.linear.Linear
     n_neurons: !ref <n_classes>
     bias: False
 
-log_softmax: !new:speechbrain.nnet.activations.Softmax
-    apply_log: True
-
-opt_class: !name:torch.optim.Adam
-    lr: !ref <lr>
-
-wav2vec2_opt_class: !name:torch.optim.Adam
-    lr: !ref <lr_wav2vec2>
-
-epoch_counter: !new:speechbrain.utils.epoch_loop.EpochCounter
-    limit: !ref <n_epochs>
-
-# Functions that compute the statistics to track during the validation step.
-accuracy_computer: !name:speechbrain.utils.Accuracy.AccuracyStats
-
-compute_cost: !name:speechbrain.nnet.losses.nll_loss
+model: !new:torch.nn.ModuleList
+    - [!ref <label_lin>]
 
-error_stats: !name:speechbrain.utils.metric_stats.MetricStats
-    metric: !name:speechbrain.nnet.losses.classification_error
-        reduction: batch
 modules:
     wav2vec2: !ref <wav2vec2>
     label_lin: !ref <label_lin>
+    avg_pool: !ref <avg_pool>
 
-model: !new:torch.nn.ModuleList
-      - [!ref <label_lin>]
-
-lr_annealing: !new:speechbrain.nnet.schedulers.NewBobScheduler
-    initial_value: !ref <lr>
-    improvement_threshold: 0.0025
-    annealing_factor: 0.9
-    patient: 0
-
-lr_annealing_wav2vec2: !new:speechbrain.nnet.schedulers.NewBobScheduler
-    initial_value: !ref <lr_wav2vec2>
-    improvement_threshold: 0.0025
-    annealing_factor: 0.9
-
-checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
-    checkpoints_dir: !ref <save_folder>
-    recoverables:
-        model: !ref <model>
-        wav2vec2: !ref <wav2vec2>
-        lr_annealing_output: !ref <lr_annealing>
-        lr_annealing_wav2vec2: !ref <lr_annealing_wav2vec2>
-        counter: !ref <epoch_counter>
+softmax: !new:speechbrain.nnet.activations.Softmax
+
+        
+label_encoder: !new:speechbrain.dataio.encoder.CategoricalEncoder
 
 
 pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
@@ -127,3 +55,5 @@ pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
         wav2vec2: !ref <pretrained_path>/wav2vec2.ckpt
         model: !ref <pretrained_path>/model.ckpt
         label_encoder: !ref <pretrained_path>/label_encoder.txt
+
+