Training on custom ENGLISH dataset

[shaimaalwaisi]

I'm trying to train StyleTTS2 on my custom ENGLISH dataset from scratch
Any urgent help please ?
@yl4579

[MARafey]

@shaimaalwaisi whats the error?

[shaimaalwaisi]

train_list
001-0001.wav|ˈɔːl ɐɹˈaʊnd ɑːɹ ˈʌðə kˈɪdz hˈapɪli tʃˈatɪŋ lˈafɪŋ and mˈeɪbiːʲ ˈiːvən ʃˈeəɹɪŋ fˈuːd and ðeəɹ ˈəʊn sˈɜːkəlz ɒv fɹˈɛndʃɪp.|001
001-0002.wav|sˌʌm ɒv ˌʌs ɑː kwˈaɪətli fˈeɪsɪŋ lˈəʊnlinəs and tʃˈalɪndʒɪz ðat mˌeɪk ˌʌs fˈiːl dˈɪfɹənt.|001

val_list
002-0001.wav|dˈɪd juː nˈəʊ ðɪʲ ˈeɪti pəsˈɛnt ɒv tʃˈɪldɹən tʃˈɛk ðeə fˈəʊnz ˈɛvɹɪ fˈaɪv mˈɪnɪts kɹˈeɪzi ɹˈaɪt.|002
002-0002.wav|hˈaɪ ˈɛvɹɪwˌɒn maɪ nˈeɪm ɪz tˈanə wˈɒltən and tədˈeɪ aɪm ɡˌəʊɪŋ təbi tˈɔːkɪŋ tə juː ɐbˌaʊt sˈɛl fˈəʊn ɐdˈɪkʃən.|002

these sentences from the Train_list and val_list that i have , Im trying to follow the format filename.wav|transcription|speaker but somthing geting wrong with the speaker Id. Idont know the ideal format to follow I have two speakers now and im asking is the format that I wrote corrected or not
@MARafey @yl4579

[MARafey]

The format is correct. However, the speaker IDs can be written as simply '1' and '2'. '001' is not necessary. @shaimaalwaisi

[shaimaalwaisi]

@MARafey @yl4579 . I had run the first training stage successfully but I got this error in the second training
dataset multispeaker 14 speakers :
support multiprocessing.
Loading the first stage model at /scratch/c_ch_gnn22/Models/CTTdataset/first_stage.pth ...
decoder loaded
text_encoder loaded
style_encoder loaded
text_aligner loaded
pitch_extractor loaded
Parameter Group 0
amsgrad: False
base_momentum: 0.85
betas: (0.9, 0.99)
capturable: False
eps: 1e-09
foreach: None
initial_lr: 1e-05
lr: 1e-05
max_lr: 2e-05
max_momentum: 0.95
maximize: False
min_lr: 0
weight_decay: 0.01
)
decoder AdamW (
Parameter Group 0
amsgrad: False
base_momentum: 0.85
betas: (0.0, 0.99)
capturable: False
eps: 1e-09
foreach: None
initial_lr: 1e-05
lr: 1e-05
max_lr: 2e-05
max_momentum: 0.95
maximize: False
min_lr: 0
weight_decay: 0.0001
)

)

/project/c_ch_gnn22/StyleTTS2/train_second.py(460)main()
458 set_trace()
459
--> 460 optimizer.step('bert_encoder')
461 optimizer.step('bert')
462 optimizer.step('predictor')

ipdb>

[Aftondil]

did you find solution to that Nan value

[MARafey]

@Aftondil which one please specify.