chiluka-tts / configs /config_ft.yml
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log_dir: "Models/tm_tel_ft_24k"
first_stage_path: "first_stage.pth"
save_freq: 2
log_interval: 10
device: "cuda"
epochs_1st: 30
epochs_2nd: 20
batch_size: 2 # Keep at 2 with filtering
max_len: 200 # This is fine - refers to audio frames, not phonemes
pretrained_model: "/home/purview/Documents/TextToSpeech_Backup/StyleTTS2/Models/LibriTTS/epochs_2nd_00020.pth"
second_stage_load_pretrained: true
load_only_params: true
F0_path: "Utils/JDC/bst.t7"
ASR_config: "Utils/ASR/config.yml"
ASR_path: "Utils/ASR/epoch_00080.pth"
PLBERT_dir: "Utils/PLBERT/"
data_params:
train_data: "Data_custom/train_list.txt"
val_data: "Data_custom/val_list.txt"
root_path: "/home/purview/Documents/TextToSpeech_Backup/Processed_Dataset_24k/wavs"
OOD_data: "Data_custom/OOD_texts.txt"
min_length: 50 # <<<< This is in phonemes - keep it low
# Rest of your config stays the same...
preprocess_params:
sr: 24000
spect_params:
n_fft: 2048
win_length: 1200
hop_length: 300
model_params:
# match the LibriTTS checkpoint setting (it was trained multispeaker:true)
# You can still finetune with only speaker_id=0 in your train_list.txt
multispeaker: true
dim_in: 64
hidden_dim: 512
max_conv_dim: 512
n_layer: 3
n_mels: 80
n_token: 178
max_dur: 50
style_dim: 128
dropout: 0.2
# MUST MATCH LibriTTS CHECKPOINT (this is your main fix)
decoder:
type: "hifigan"
resblock_dilation_sizes: [[1, 3, 5], [1, 3, 5], [1, 3, 5]]
resblock_kernel_sizes: [3, 7, 11]
upsample_initial_channel: 512
upsample_rates: [10, 5, 3, 2]
upsample_kernel_sizes: [20, 10, 6, 4]
slm:
model: "microsoft/wavlm-base-plus"
sr: 16000
hidden: 768
nlayers: 13
initial_channel: 64
diffusion:
embedding_mask_proba: 0.1
transformer:
num_layers: 3
num_heads: 8
head_features: 64
multiplier: 2
dist:
sigma_data: 0.19926648961191362
estimate_sigma_data: true
mean: -3.0
std: 1.0
loss_params:
lambda_mel: 5.0
lambda_gen: 1.0
lambda_slm: 1.0
lambda_mono: 1.0
lambda_s2s: 1.0
TMA_epoch: 4
lambda_F0: 1.0
lambda_norm: 1.0
lambda_dur: 1.0
lambda_ce: 20.0
lambda_sty: 1.0
lambda_diff: 1.0
# For a safe first run, delay diffusion + joint/SLM-adv.
# After it runs, you can set these back to 0 like LibriTTS.
diff_epoch: 999
joint_epoch: 999
optimizer_params:
lr: 0.0001
bert_lr: 0.00001
ft_lr: 0.00001
slmadv_params:
min_len: 400
max_len: 500
batch_percentage: 0.5
iter: 20
thresh: 5
scale: 0.01
sig: 1.5