task.sh

#!/bin/bash

R_DIR=`dirname $0`; MYDIR=`cd $R_DIR;pwd`

export FLAGS_eager_delete_tensor_gb=0.0
export FLAGS_sync_nccl_allreduce=1
export PYTHONPATH=./ernie:${PYTHONPATH:-}

if [[ -f ./model_conf ]];then
    source ./model_conf
else
    export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
fi

mkdir -p log/

for i in {1..5};do

    timestamp=`date "+%Y-%m-%d-%H-%M-%S"`

    python -u ./ernie/run_classifier.py                                                             \
           --use_cuda true                                                                  \
           --use_fast_executor ${e_executor:-"true"}                                        \
           --tokenizer ${TOKENIZER:-"FullTokenizer"}                                        \
           --use_fp16 ${USE_FP16:-"false"}                                                  \
           --do_train true                                                                  \
           --do_val true                                                                    \
           --do_test true                                                                   \
           --batch_size 32                                                                  \
           --init_pretraining_params ${MODEL_PATH}/params                                   \
           --verbose true                                                                   \
           --train_set ${TASK_DATA_PATH}/MNLI/train.tsv                                     \
           --dev_set   ${TASK_DATA_PATH}/MNLI/m/dev.tsv,${TASK_DATA_PATH}/MNLI/mm/dev.tsv   \
           --test_set  ${TASK_DATA_PATH}/MNLI/m/test.tsv,${TASK_DATA_PATH}/MNLI/mm/test.tsv \
           --vocab_path script/en_glue/ernie_large/vocab.txt                                \
           --checkpoints ./checkpoints                                                      \
           --save_steps 25000                                                               \
           --weight_decay 0.0                                                               \
           --warmup_proportion 0.1                                                          \
           --validation_steps 1000000000000                                                 \
           --epoch 3                                                                        \
           --max_seq_len 128                                                                \
           --ernie_config_path script/en_glue/ernie_large/ernie_config.json                 \
           --learning_rate 3e-5                                                             \
           --skip_steps 500                                                                 \
           --num_iteration_per_drop_scope 1                                                 \
           --num_labels 3                                                                   \
           --for_cn False                                                                   \
           --test_save output/test_out.$i.m.tsv,output/test_out.$i.mm.tsv                   \
           --diagnostic ${TASK_DATA_PATH}/MNLI/diagnostic.tsv                               \
           --diagnostic_save output/test_out.$i.m.diagnostic.tsv                            \
           --random_seed 1 2>&1 | tee  log/job.$i.$timestamp.log                            \

done