From 24aea85b5bc3f354d683201fa9e37968f3f1638f Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期四, 21 三月 2024 14:01:45 +0800
Subject: [PATCH] trainer
---
examples/industrial_data_pretraining/contextual_paraformer/finetune.sh | 51 +++++++++++++++++++++++++++++++++++++--------------
1 files changed, 37 insertions(+), 14 deletions(-)
diff --git a/examples/industrial_data_pretraining/contextual_paraformer/finetune.sh b/examples/industrial_data_pretraining/contextual_paraformer/finetune.sh
index 98cc73c..de88968 100644
--- a/examples/industrial_data_pretraining/contextual_paraformer/finetune.sh
+++ b/examples/industrial_data_pretraining/contextual_paraformer/finetune.sh
@@ -7,21 +7,39 @@
export CUDA_VISIBLE_DEVICES="0,1"
gpu_num=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
-# data dir, which contains: train.json, val.json
-data_dir="/Users/zhifu/funasr1.0/data/list"
+# model_name from model_hub, or model_dir in local path
-## generate jsonl from wav.scp and text.txt
-#python -m funasr.datasets.audio_datasets.scp2jsonl \
-#++scp_file_list='["/Users/zhifu/funasr1.0/test_local/wav.scp", "/Users/zhifu/funasr1.0/test_local/text.txt"]' \
-#++data_type_list='["source", "target"]' \
-#++jsonl_file_out=/Users/zhifu/funasr1.0/test_local/audio_datasets.jsonl
+## option 1, download model automatically
+model_name_or_model_dir="iic/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404"
+model_revision="v2.0.4"
+
+## option 2, download model by git
+#local_path_root=${workspace}/modelscope_models
+#mkdir -p ${local_path_root}/${model_name_or_model_dir}
+#git clone https://www.modelscope.cn/${model_name_or_model_dir}.git ${local_path_root}/${model_name_or_model_dir}
+#model_name_or_model_dir=${local_path_root}/${model_name_or_model_dir}
+
+
+# data dir, which contains: train.json, val.json
+data_dir="../../../data/list"
train_data="${data_dir}/train.jsonl"
val_data="${data_dir}/val.jsonl"
+# generate train.jsonl and val.jsonl from wav.scp and text.txt
+scp2jsonl \
+++scp_file_list='["../../../data/list/train_wav.scp", "../../../data/list/train_text.txt"]' \
+++data_type_list='["source", "target"]' \
+++jsonl_file_out="${train_data}"
+
+scp2jsonl \
+++scp_file_list='["../../../data/list/val_wav.scp", "../../../data/list/val_text.txt"]' \
+++data_type_list='["source", "target"]' \
+++jsonl_file_out="${val_data}"
+
# exp output dir
-output_dir="/Users/zhifu/exp"
+output_dir="./outputs"
log_file="${output_dir}/log.txt"
@@ -31,14 +49,19 @@
torchrun \
--nnodes 1 \
--nproc_per_node ${gpu_num} \
-funasr/bin/train.py \
-++model="iic/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404" \
-++model_revision="v2.0.5" \
+../../../funasr/bin/train.py \
+++model="${model_name_or_model_dir}" \
+++model_revision="${model_revision}" \
++train_data_set_list="${train_data}" \
++valid_data_set_list="${val_data}" \
-++dataset_conf.batch_size=32 \
-++dataset_conf.batch_type="example" \
+++dataset_conf.batch_size=20000 \
+++dataset_conf.batch_type="token" \
++dataset_conf.num_workers=4 \
-++train_conf.max_epoch=20 \
+++train_conf.max_epoch=50 \
+++train_conf.log_interval=1 \
+++train_conf.resume=false \
+++train_conf.validate_interval=2000 \
+++train_conf.save_checkpoint_interval=2000 \
+++train_conf.keep_nbest_models=20 \
++optim_conf.lr=0.0002 \
++output_dir="${output_dir}" &> ${log_file}
\ No newline at end of file
--
Gitblit v1.9.1