mirror of
https://github.com/storytold/vits-finetuning.git
synced 2026-10-09 00:09:52 +00:00
74 lines
2.1 KiB
JSON
74 lines
2.1 KiB
JSON
{
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"train": {
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"log_interval": 200,
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"eval_interval": 3000,
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"seed": 1234,
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"epochs": 20000,
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"learning_rate": 2e-4,
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"betas": [0.8, 0.99],
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"eps": 1e-9,
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"batch_size": 32,
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"fp16_run": true,
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"lr_decay": 0.999875,
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"segment_size": 8192,
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"init_lr_ratio": 1,
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"warmup_epochs": 0,
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"c_mel": 45,
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"c_kl": 1.0
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},
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"data": {
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"training_files":"filelists/train_filelist.txt.cleaned",
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"validation_files":"filelists/val_filelist.txt.cleaned",
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"text_cleaners":["english_cleaners2"],
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"max_wav_value": 32768.0,
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"sampling_rate": 44100,
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"filter_length": 2048,
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"hop_length": 512,
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"win_length": 2048,
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"n_mel_channels": 80,
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"mel_fmin": 20,
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"mel_fmax": 11025,
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"add_blank": true,
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"n_speakers": 0,
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"cleaned_text": true
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},
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"model": {
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"inter_channels": 192,
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"hidden_channels": 192,
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"filter_channels": 768,
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"n_heads": 2,
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"n_layers": 6,
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"kernel_size": 3,
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"p_dropout": 0.1,
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"resblock": "1",
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"resblock_kernel_sizes": [3,7,11],
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"resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
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"upsample_rates": [8,8],
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"upsample_initial_channel": 512,
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"upsample_kernel_sizes": [16,16],
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"n_layers_q": 3,
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"use_spectral_norm": false,
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"gen_istft_n_fft" : 32,
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"gen_istft_hop_size": 8
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},
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"disc": {
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"combd_channels": [16, 64, 256, 1024, 1024, 1024],
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"combd_kernels" : [[7, 11, 11, 11, 11, 5], [11, 21, 21, 21, 21, 5], [15, 41, 41, 41, 41, 5]],
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"combd_groups" : [1, 4, 16, 64, 256, 1],
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"combd_strides": [1, 1, 4, 4, 4, 1],
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"tkernels" : [7, 5, 3],
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"fkernel" : 5,
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"tchannels" : [64, 128, 256, 256, 256],
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"fchannels" : [32, 64, 128, 128, 128],
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"tstrides" : [[1, 1, 3, 3, 1], [1, 1, 3, 3, 1], [1, 1, 3, 3, 1]],
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"fstride" : [1, 1, 3, 3, 1],
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"tdilations" : [[[5, 7, 11], [5, 7, 11], [5, 7, 11], [5, 7, 11], [5, 7, 11], [5, 7, 11]], [[3, 5, 7], [3, 5, 7], [3, 5, 7], [3, 5, 7], [3, 5, 7]], [[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]]],
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"fdilations" : [[1, 2, 3], [1, 2, 3], [1, 2, 3], [2, 3, 5], [2, 3, 5]],
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"pqmf_n" : 16,
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"pqmf_m" : 64,
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"freq_init_ch" : 128,
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"tsubband" : [6, 11, 16]
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}
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}
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