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config_musdb18_bs_mamba2.yaml
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audio:
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chunk_size: 132300 # samplerate * segment
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hop_length: 1024
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min_mean_abs: 0.0
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training:
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batch_size: 8
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gradient_accumulation_steps: 1
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grad_clip: 0
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segment: 11
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shift: 1
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samplerate: 44100
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channels: 2
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normalize: true
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instruments: ['drums', 'bass', 'other', 'vocals']
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target_instrument: null
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num_epochs: 1000
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num_steps: 1000
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optimizer: prodigy
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lr: 1.0
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patience: 2
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reduce_factor: 0.95
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q: 0.95
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coarse_loss_clip: true
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ema_momentum: 0.999
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read_metadata_procs: 8
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other_fix: false # it's needed for checking on multisong dataset if other is actually instrumental
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use_amp: true # enable or disable usage of mixed precision (float16) - usually it must be true
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model:
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sr: 44100
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win: 2048
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stride: 512
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feature_dim: 128
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num_repeat_mask: 8
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num_repeat_map: 4
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num_output: 4
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augmentations:
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enable: true # enable or disable all augmentations (to fast disable if needed)
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loudness: true # randomly change loudness of each stem on the range (loudness_min; loudness_max)
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loudness_min: 0.5
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loudness_max: 1.5
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mixup: true # mix several stems of same type with some probability (only works for dataset types: 1, 2, 3)
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mixup_probs:
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!!python/tuple # 2 additional stems of the same type (1st with prob 0.2, 2nd with prob 0.02)
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- 0.2
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- 0.02
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mixup_loudness_min: 0.5
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mixup_loudness_max: 1.5
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all:
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channel_shuffle: 0.5 # Set 0 or lower to disable
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random_inverse: 0.1 # inverse track (better lower probability)
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random_polarity: 0.5 # polarity change (multiply waveform to -1)
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loss_multistft:
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fft_sizes:
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- 1024
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- 2048
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- 4096
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hop_sizes:
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- 512
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- 1024
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- 2048
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win_lengths:
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- 1024
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- 2048
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- 4096
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window: "hann_window"
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scale: "mel"
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n_bins: 128
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sample_rate: 44100
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perceptual_weighting: true
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w_sc: 1.0
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w_log_mag: 1.0
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w_lin_mag: 0.0
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w_phs: 0.0
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mag_distance: "L1"
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inference:
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num_overlap: 2
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batch_size: 8
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model_bs_mamba2_ep_11_sdr_6.8723.ckpt
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version https://git-lfs.github.com/spec/v1
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oid sha256:d85560e2495eb7852d78e07d7a00376aa69804089abc10b7eb27e41d5a3926f5
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size 142774366
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