#!/bin/bash 
mode: 'train'
use_cuda: 1 # 1 for True, 0 for False

sampling_rate: 16000
network: "FRCRN_SE_16K"  ##network type
## FFT Parameters
win_type: hanning
win_len: 640
win_inc: 320
fft_len: 640

# Train
#tr_list: 'datasets/tr_tts_16k_noise_0to10db_p13_p20.lst_dur'
tr_list: 'data/cv_webrtc_test_set_20200521_16k.lst'
cv_list: 'data/cv_webrtc_test_set_20200521_16k.lst'
init_learning_rate: 0.001 #learning rate for a new training
finetune_learning_rate: 0.0001 #learning rate for a finetune training
max_epoch: 100

weight_decay: 0.00001
clip_grad_norm: 10.

# Log 
seed: 777

# # dataset
num_workers: 4
batch_size: 4
accu_grad: 1  # accumulate multiple batch sizes for one back-propagation updating
effec_batch_size: 12   # per GPU, only used if accu_grad is set to 1, must be multiple times of batch size
max_length: 1         # truncate the utterances in dataloader, in seconds