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seed: 1988 |
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__set_seed: !apply:torch.manual_seed [1988] |
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output_folder: results_3lang/epaca/1988 |
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save_folder: results_3lang/epaca/1988/save |
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train_log: results_3lang/epaca/1988/train_log.txt |
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data_folder: ./ |
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rir_folder: ./ |
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shards_url: /opt/acoustic-pr/speechbrain_Voxlingua/data_shards |
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train_meta: /opt/acoustic-pr/speechbrain_Voxlingua/data_shards/train/meta.json |
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val_meta: /opt/acoustic-pr/speechbrain_Voxlingua/data_shards/dev/meta.json |
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train_shards: /opt/acoustic-pr/speechbrain_Voxlingua/data_shards/train/shard-{000000..000013}.tar |
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val_shards: /opt/acoustic-pr/speechbrain_Voxlingua/data_shards/dev/shard-000000.tar |
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ckpt_interval_minutes: 5 |
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number_of_epochs: 40 |
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lr: 0.001 |
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lr_final: 0.0001 |
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sample_rate: 16000 |
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sentence_len: 3 |
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n_mels: 60 |
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left_frames: 0 |
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right_frames: 0 |
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deltas: false |
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out_n_neurons: 3 |
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train_dataloader_options: |
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num_workers: 0 |
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batch_size: 32 |
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val_dataloader_options: |
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num_workers: 0 |
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batch_size: 16 |
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compute_features: &id003 !new:speechbrain.lobes.features.Fbank |
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n_mels: 60 |
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left_frames: 0 |
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right_frames: 0 |
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deltas: false |
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embedding_model: &id004 !new:speechbrain.lobes.models.ECAPA_TDNN.ECAPA_TDNN |
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input_size: 60 |
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channels: [1024, 1024, 1024, 1024, 3072] |
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kernel_sizes: [5, 3, 3, 3, 1] |
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dilations: [1, 2, 3, 4, 1] |
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attention_channels: 128 |
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lin_neurons: 256 |
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classifier: &id005 !new:speechbrain.lobes.models.Xvector.Classifier |
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input_shape: [null, null, 256] |
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activation: !name:torch.nn.LeakyReLU |
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lin_blocks: 1 |
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lin_neurons: 512 |
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out_neurons: 3 |
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epoch_counter: &id007 !new:speechbrain.utils.epoch_loop.EpochCounter |
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limit: 40 |
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augment_speed: &id001 !new:speechbrain.lobes.augment.TimeDomainSpecAugment |
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sample_rate: 16000 |
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speeds: [90, 100, 110] |
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add_rev_noise: &id002 !new:speechbrain.lobes.augment.EnvCorrupt |
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openrir_folder: ./ |
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openrir_max_noise_len: 3.0 |
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reverb_prob: 0.5 |
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noise_prob: 0.8 |
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noise_snr_low: 0 |
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noise_snr_high: 15 |
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rir_scale_factor: 1.0 |
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augment_pipeline: [*id001, *id002] |
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concat_augment: false |
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mean_var_norm: &id006 !new:speechbrain.processing.features.InputNormalization |
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norm_type: sentence |
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std_norm: false |
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modules: |
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compute_features: *id003 |
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augment_speed: *id001 |
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add_rev_noise: *id002 |
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embedding_model: *id004 |
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classifier: *id005 |
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mean_var_norm: *id006 |
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compute_cost: !name:speechbrain.nnet.losses.nll_loss |
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opt_class: !name:torch.optim.Adam |
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lr: 0.001 |
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weight_decay: 0.000002 |
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lr_annealing: !new:speechbrain.nnet.schedulers.LinearScheduler |
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initial_value: 0.001 |
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final_value: 0.0001 |
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epoch_count: 40 |
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train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger |
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save_file: results_3lang/epaca/1988/train_log.txt |
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error_stats: !name:speechbrain.utils.metric_stats.MetricStats |
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metric: !name:speechbrain.nnet.losses.classification_error |
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reduction: batch |
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checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer |
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checkpoints_dir: results_3lang/epaca/1988/save |
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recoverables: |
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embedding_model: *id004 |
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classifier: *id005 |
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normalizer: *id006 |
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counter: *id007 |
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