FunASR/funasr/models/sense_voice/template.yaml

108 lines
2.3 KiB
YAML

# network architecture
model: SenseVoiceRWKV
model_conf:
lsm_weight: 0.1
length_normalized_loss: true
activation_checkpoint: true
sos: "<|startoftranscript|>"
eos: "<|endoftext|>"
downsample_rate: 4
use_padmask: true
dims:
n_mels: 128
n_vocab: 60515
n_audio_ctx: 1500
n_audio_state: 1280
n_audio_head: 20
n_audio_layer: 32
n_text_ctx: 448
n_text_state: 1280
n_text_head: 20
n_text_layer: 32
# decoder
decoder: SenseVoiceDecoder
decoder_conf:
rwkv_cfg:
n_embd: 1280
dropout: 0
head_size_a: 64
ctx_len: 1280
dim_att: 1280 #${model_conf.rwkv_cfg.n_embd}
dim_ffn: null
head_size_divisor: 8
n_layer: 32
pre_ffn: 0
ln0: false
ln1: false
init_rwkv: false
datatype: bf16
# frontend related
frontend: WhisperFrontend
frontend_conf:
fs: 16000
n_mels: ${model_conf.dims.n_mels}
do_pad_trim: false
tokenizer: SenseVoiceTokenizer
tokenizer_conf:
vocab_path: null
is_multilingual: true
num_languages: 8749
dataset: SenseVoiceDataset
dataset_conf:
index_ds: IndexDSJsonlRankSplit
batch_sampler: EspnetStyleBatchSampler
rank_split: true
batch_type: token # example or length
batch_size: 3500 # if batch_type is example, batch_size is the numbers of samples; if length, batch_size is source_token_len+target_token_len;
max_token_length: 2200
min_token_length: 60
max_source_length: 2000
min_source_length: 60
max_target_length: 150
min_target_length: 0
shuffle: True
num_workers: 4
sos: ${model_conf.sos}
eos: ${model_conf.eos}
train_conf:
accum_grad: 2
grad_clip: 5
max_epoch: 20
keep_nbest_models: 20
avg_nbest_model: ${train_conf.keep_nbest_models}
log_interval: 50
reset_gpu_cache: true
optim: adamw
optim_conf:
lr: 0.00002
scheduler: warmuplr
scheduler_conf:
warmup_steps: 10000
specaug: SpecAug
specaug_conf:
apply_time_warp: true
time_warp_window: 5
time_warp_mode: bicubic
apply_freq_mask: true
freq_mask_width_range:
- 0
- 40
num_freq_mask: 2
apply_time_mask: true
time_mask_width_ratio_range:
- 0.0
- 0.12
num_time_mask: 2
scope_map: ['encoder.encoders', 'model.encoder', 'decoder.decoders', 'model.decoder']