OOO=output

MASTER_PORT=12345

GPU=0

for TSK in qnli #stsb mrpc cola wnli sst2 rte qnli qqp mnli

do

if [ $TSK == wnli ] || [ $TSK == mrpc ]

then

EPOCH_NUM=5

else

EPOCH_NUM=3

fi

if [ $TSK == qqp ] || [ $TSK == mnli ]

then

TEST_JSON=test_long.json

else

TEST_JSON=test.json

fi

PORT=$((MASTER_PORT+GPU))

rm -rvf ./$OOO/${TSK}

CUDA_VISIBLE_DEVICES=$GPU python -m torch.distributed.launch \

--master_port $PORT \

--nproc_per_node 1 run_glue.py \

--model_name_or_path bert-base-cased \

--task_name $TSK \

--do_train \

--do_eval \

--max_seq_length 128 \

--per_device_train_batch_size 32 \

--learning_rate 2e-5 \

--num_train_epochs $EPOCH_NUM \

--output_dir ./$OOO/$TSK/ \

--fp16 \

--warmup_steps 2 \

--deepspeed test.json

done