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

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/

lr=3e-5
batch_size=64
epoch=3

for i in {1..5};do

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

python -u 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 $batch_size                                                         \
       --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_base/vocab.txt                                 \
       --checkpoints ./checkpoints                                                      \
       --save_steps 25000                                                               \
       --weight_decay 0.0                                                               \
       --warmup_proportion 0.1                                                          \
       --validation_steps 1000000000000                                                 \
       --epoch $epoch                                                                   \
       --max_seq_len 128                                                                \
       --ernie_config_path script/en_glue/ernie_base/ernie_config.json                  \
       --learning_rate $lr                                                              \
       --skip_steps 10                                                                  \
       --num_iteration_per_drop_scope 1                                                 \
       --num_labels 3                                                                   \
       --for_cn False                                                                   \
       --test_save output/test_out.$i.m.tsv,output/test_out.$i.mm.tsv                   \
       --diagnostic ${TASK_DATA_PATH}/diagnostic.tsv                                    \
       --diagnostic_save output/test_out.$i.$lr.$batch_size.$epoch.$timestamp.m.diagnostic.tsv \
       --random_seed 1 2>&1 | tee  log/job.$i.$lr.$batch_size.$epoch.$timestamp.log            \

done