cemsubakan
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Parent(s):
719fc92
hparams cleanup
Browse files- hyperparams.yaml +2 -110
hyperparams.yaml
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# /home/mila/s/subakany/speechbrain_new/recipes/LibriMix/separation/hparams/sepformer-libri2mix.yaml
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# yamllint disable
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# ################################
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# Model: SepFormer for source separation
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# https://arxiv.org/abs/2010.13154
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# Dataset : Libri2mix
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# ################################
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#
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# Basic parameters
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# Seed needs to be set at top of yaml, before objects with parameters are made
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#
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seed: 1234
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__set_seed: !apply:torch.manual_seed [1234]
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# Data params
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# e.g. '/yourpath/Libri2Mix/train-clean-360/'
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# the data folder is needed even if dynamic mixing is applied
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data_folder: /miniscratch/subakany/LibriMixData_new/Libri2Mix/
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# this is the base folder for dynamic mixing
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base_folder_dm: /miniscratch/subakany/LibriMixData_new/LibriSpeech/train-clean-360_processed/
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experiment_name: sepformer-libri2mix
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output_folder: results/sepformer-libri2mix/1234
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train_log: results/sepformer-libri2mix/1234/train_log.txt
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save_folder: results/sepformer-libri2mix/1234/save
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train_data: results/sepformer-libri2mix/1234/save/libri2mix_train-360.csv
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valid_data: results/sepformer-libri2mix/1234/save/libri2mix_dev.csv
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test_data: results/sepformer-libri2mix/1234/save/libri2mix_test.csv
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skip_prep: false
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ckpt_interval_minutes: 60
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# Experiment params
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auto_mix_prec: true # Set it to True for mixed precision
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test_only: true
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num_spks: 2
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progressbar: true
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save_audio: false # Save estimated sources on disk
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sample_rate: 8000
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# Training parameters
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N_epochs: 200
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batch_size: 1
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lr: 0.00015
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clip_grad_norm: 5
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loss_upper_lim: 999999 # this is the upper limit for an acceptable loss
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# if True, the training sequences are cut to a specified length
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limit_training_signal_len: false
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# this is the length of sequences if we choose to limit
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# the signal length of training sequences
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training_signal_len: 32000000
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# Set it to True to dynamically create mixtures at training time
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dynamic_mixing: true
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use_wham_noise: false
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# Parameters for data augmentation
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use_wavedrop: false
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use_speedperturb: true
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use_speedperturb_sameforeachsource: false
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use_rand_shift: false
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min_shift: -8000
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max_shift: 8000
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speedperturb: !new:speechbrain.lobes.augment.TimeDomainSpecAugment
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perturb_prob: 1.0
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drop_freq_prob: 0.0
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drop_chunk_prob: 0.0
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sample_rate: 8000
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speeds: [95, 100, 105]
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wavedrop: !new:speechbrain.lobes.augment.TimeDomainSpecAugment
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perturb_prob: 0.0
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drop_freq_prob: 1.0
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drop_chunk_prob: 1.0
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sample_rate: 8000
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# loss thresholding -- this thresholds the training loss
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threshold_byloss: true
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threshold: -30
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# Encoder parameters
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N_encoder_out: 256
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out_channels: 256
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kernel_size: 16
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kernel_stride: 8
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# Dataloader options
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dataloader_opts:
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batch_size: 1
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num_workers: 0
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# Specifying the network
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Encoder: &id003 !new:speechbrain.lobes.models.dual_path.Encoder
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kernel_size: 16
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out_channels: 256
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SBtfintra: &id001 !new:speechbrain.lobes.models.dual_path.SBTransformerBlock
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num_layers: 8
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d_model: 256
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norm_before: true
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MaskNet: &id005 !new:speechbrain.lobes.models.dual_path.Dual_Path_Model
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num_spks: 2
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in_channels: 256
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out_channels: 256
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stride: 8
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bias: false
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optimizer: !name:torch.optim.Adam
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lr: 0.00015
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weight_decay: 0
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loss: !name:speechbrain.nnet.losses.get_si_snr_with_pitwrapper
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lr_scheduler: !new:speechbrain.nnet.schedulers.ReduceLROnPlateau
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factor: 0.5
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patience: 2
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dont_halve_until_epoch: 5
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epoch_counter: &id006 !new:speechbrain.utils.epoch_loop.EpochCounter
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# lr_scheduler: !ref <lr_scheduler>
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limit: 200
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modules:
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encoder: *id003
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decoder: *id004
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masknet: *id005
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checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
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checkpoints_dir: results/sepformer-libri2mix/1234/save
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recoverables:
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encoder: *id003
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decoder: *id004
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masknet: *id005
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counter: *id006
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train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger
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save_file: results/sepformer-libri2mix/1234/train_log.txt
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pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
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loadables:
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# ################################
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# Model: Pretrained SepFormer for source separation
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# Dataset : Libri2mix
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# ################################
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# Experiment params
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num_spks: 2
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sample_rate: 8000
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# Encoder parameters
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N_encoder_out: 256
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out_channels: 256
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kernel_size: 16
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kernel_stride: 8
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# Specifying the network
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Encoder: &id003 !new:speechbrain.lobes.models.dual_path.Encoder
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kernel_size: 16
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out_channels: 256
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SBtfintra: &id001 !new:speechbrain.lobes.models.dual_path.SBTransformerBlock
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num_layers: 8
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d_model: 256
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norm_before: true
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MaskNet: &id005 !new:speechbrain.lobes.models.dual_path.Dual_Path_Model
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num_spks: 2
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in_channels: 256
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out_channels: 256
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stride: 8
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bias: false
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modules:
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encoder: *id003
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decoder: *id004
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masknet: *id005
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pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
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loadables:
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