# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
|
# MIT License (https://opensource.org/licenses/MIT)
|
|
|
# which gpu to train or finetune
|
export CUDA_VISIBLE_DEVICES="0"
|
gpu_num=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
|
|
# data dir, which contains: train.json, val.json, tokens.jsonl/tokens.txt, am.mvn
|
#data_dir="/Users/zhifu/funasr1.0/data/list"
|
|
## generate jsonl from wav.scp and text.txt
|
#python -m funasr.datasets.audio_datasets.scp2jsonl \
|
#++scp_file_list='["/Users/zhifu/funasr1.0/test_local/wav.scp", "/Users/zhifu/funasr1.0/test_local/text.txt"]' \
|
#++data_type_list='["source", "target"]' \
|
#++jsonl_file_out=/Users/zhifu/funasr1.0/test_local/audio_datasets.jsonl
|
|
train_data="/nfs/zhifu.gzf/data/datalist/aishell1_aishell2_wav_speech_llm_train_data_del_tail500.json"
|
val_data="/nfs/zhifu.gzf/data/datalist/aishell1_aishell2_wav_speech_llm_train_data_tail500.json"
|
|
# exp output dir
|
output_dir="/Users/zhifu/exp"
|
log_file="${output_dir}/log.txt"
|
|
workspace=`pwd`
|
config="template.yaml"
|
|
init_param="${output_dir}/model.pt"
|
|
mkdir -p ${output_dir}
|
echo "log_file: ${log_file}"
|
|
torchrun \
|
--nnodes 1 \
|
--nproc_per_node ${gpu_num} \
|
../../../funasr/bin/train.py \
|
--config-path "${workspace}/conf" \
|
--config-name "${config}" \
|
++train_data_set_list="${train_data}" \
|
++valid_data_set_list="${val_data}" \
|
++dataset_conf.batch_size=2 \
|
++dataset_conf.batch_type="example" \
|
++dataset_conf.num_workers=0 \
|
++train_conf.max_epoch=11 \
|
++optim_conf.lr=0.0002 \
|
++init_param="${init_param}" \
|
++output_dir="${output_dir}" &> ${log_file}
|
