/
run_classifier_clue.sh
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/
run_classifier_clue.sh
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# @Author: bo.shi
# @Date: 2020-03-15 16:11:00
# @Last Modified by: bo.shi
# @Last Modified time: 2020-04-02 17:54:05
#!/usr/bin/env bash
export CUDA_VISIBLE_DEVICES="0"
CURRENT_DIR=$(cd -P -- "$(dirname -- "$0")" && pwd -P)
CLUE_DATA_DIR=$CURRENT_DIR/CLUEdataset
ALBERT_TINY_DIR=$CURRENT_DIR/albert_tiny
download_data(){
TASK_NAME=$1
if [ ! -d $CLUE_DATA_DIR ]; then
mkdir -p $CLUE_DATA_DIR
echo "makedir $CLUE_DATA_DIR"
fi
cd $CLUE_DATA_DIR
if [ ! -d ${TASK_NAME} ]; then
mkdir $TASK_NAME
echo "make dataset dir $CLUE_DATA_DIR/$TASK_NAME"
fi
cd $TASK_NAME
if [ ! -f "train.json" ] || [ ! -f "dev.json" ] || [ ! -f "test.json" ]; then
rm *
wget https://storage.googleapis.com/cluebenchmark/tasks/${TASK_NAME}_public.zip
unzip ${TASK_NAME}_public.zip
rm ${TASK_NAME}_public.zip
else
echo "data exists"
fi
echo "Finish download dataset."
}
download_model(){
if [ ! -d $ALBERT_TINY_DIR ]; then
mkdir -p $ALBERT_TINY_DIR
echo "makedir $ALBERT_TINY_DIR"
fi
cd $ALBERT_TINY_DIR
if [ ! -f "albert_config_tiny.json" ] || [ ! -f "vocab.txt" ] || [ ! -f "checkpoint" ] || [ ! -f "albert_model.ckpt.index" ] || [ ! -f "albert_model.ckpt.meta" ] || [ ! -f "albert_model.ckpt.data-00000-of-00001" ]; then
rm *
wget -c https://storage.googleapis.com/albert_zh/albert_tiny_489k.zip
unzip albert_tiny_489k.zip
rm albert_tiny_489k.zip
else
echo "model exists"
fi
echo "Finish download model."
}
run_task() {
TASK_NAME=$1
download_data $TASK_NAME
download_model $MODEL_NAME
DATA_DIR=$CLUE_DATA_DIR/${TASK_NAME}
PREV_TRAINED_MODEL_DIR=$ALBERT_TINY_DIR
MAX_SEQ_LENGTH=$2
TRAIN_BATCH_SIZE=$3
LEARNING_RATE=$4
NUM_TRAIN_EPOCHS=$5
SAVE_CHECKPOINTS_STEPS=$6
OUTPUT_DIR=$CURRENT_DIR/${TASK_NAME}_output/
COMMON_ARGS="
--task_name=$TASK_NAME \
--data_dir=$DATA_DIR \
--vocab_file=$PREV_TRAINED_MODEL_DIR/vocab.txt \
--bert_config_file=$PREV_TRAINED_MODEL_DIR/albert_config_tiny.json \
--init_checkpoint=$PREV_TRAINED_MODEL_DIR/albert_model.ckpt \
--max_seq_length=$MAX_SEQ_LENGTH \
--train_batch_size=$TRAIN_BATCH_SIZE \
--learning_rate=$LEARNING_RATE \
--num_train_epochs=$NUM_TRAIN_EPOCHS \
--save_checkpoints_steps=$SAVE_CHECKPOINTS_STEPS \
--output_dir=$OUTPUT_DIR \
--keep_checkpoint_max=0 \
"
cd $CURRENT_DIR
echo "Start running..."
python run_classifier_clue.py \
$COMMON_ARGS \
--do_train=true \
--do_eval=false \
--do_predict=false
echo "Start predict..."
python run_classifier_clue.py \
$COMMON_ARGS \
--do_train=false \
--do_eval=true \
--do_predict=true
}
##command##task_name##model_name##max_seq_length##train_batch_size##learning_rate##num_train_epochs##save_checkpoints_steps##tpu_ip
run_task afqmc 128 16 2e-5 3 300
run_task cmnli 128 64 3e-5 2 300
run_task csl 128 16 1e-5 5 100
run_task iflytek 128 32 2e-5 3 300
run_task tnews 128 16 2e-5 3 300
run_task wsc 128 16 1e-5 10 10