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
fi

mkdir -p log/

for i in {1..5};do

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

    python -u run_classifier.py                                                \
               --use_cuda true                                                 \
               --for_cn False                                                  \
               --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 4                                                  \
               --init_pretraining_params ${MODEL_PATH}/params                  \
               --verbose true                                                  \
               --train_set ${TASK_DATA_PATH}/RTE/train.tsv                     \
               --dev_set   ${TASK_DATA_PATH}/RTE/dev.tsv                       \
               --test_set  ${TASK_DATA_PATH}/RTE/test.tsv                      \
               --vocab_path script/en_glue/ernie_base/vocab.txt                \
               --checkpoints ./checkpoints                                     \
               --save_steps 1000                                               \
               --weight_decay  0.0                                             \
               --warmup_proportion 0.1                                         \
               --validation_steps 1000000000                                   \
               --epoch 4                                                       \
               --max_seq_len 128                                               \
               --ernie_config_path script/en_glue/ernie_base/ernie_config.json \
               --learning_rate 2e-5                                            \
               --skip_steps 10                                                 \
               --num_iteration_per_drop_scope 1                                \
               --num_labels 2                                                  \
               --for_cn  False                                                 \
               --test_save output/test_out.$i.tsv                              \
               --random_seed 1 2>&1 | tee  log/job.$i.$timestamp.log           \

done