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config.yaml

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+exp_name: hubert_TCM_NoAug_seed240
+output_dir: ./outputs/batch1/
+seed: 240
+data:
+  sampling_rate: 16000
+  label_map:
+    bonafide: 1
+    spoof: 0
+  train:
+    dataset_type: StandardDataset
+    parquet_files:
+    - /gs/bs/tgh-25IAC/ud03523/WORK/project-deepfense/data/ASVspoof2019_train.par
+    dataset_names:
+    - ASVSpoof19_Train
+    batch_size: 32
+    shuffle: true
+    num_workers: 4
+    base_transform:
+    - type: pad
+      max_len: 64000
+      random_pad: true
+      pad_type: repeat
+    augment_transform: []
+  val:
+    dataset_type: StandardDataset
+    parquet_files:
+    - /gs/bs/tgh-25IAC/ud03523/WORK/project-deepfense/data/ASVspoof2019_dev.par
+    dataset_names:
+    - ASVSpoof19_Val
+    batch_size: 32
+    shuffle: false
+    num_workers: 4
+    base_transform:
+    - type: pad
+      max_len: 64000
+      pad_type: repeat
+model:
+  type: StandardDetector
+  frontend:
+    type: hubert
+    args:
+      ckpt_path: /gs/bs/tgh-25IAC/ud03523/WORK/project-deepfense/pretrained/hubert_large_ll60k.pt
+      freeze: false
+      source: fairseq
+  backend:
+    type: TCM
+    args:
+      input_dim: 1024
+      emb_size: 128
+      heads: 4
+      num_encoders: 1
+  loss:
+  - type: CrossEntropy
+    embedding_dim: 128
+    n_classes: 2
+    weight: 1.0
+training:
+  trainer: StandardTrainer
+  epochs: 100
+  early_stopping_patience: 7
+  optimizer:
+    type: adam
+    lr: 1.0e-06
+  metrics:
+    ACC: {}
+    EER: {}
+  eval_every_epochs: 1
+  device: cuda
+  output_dir: ./outputs/batch1/hubert_TCM_NoAug_seed240_20251209_004629