#!/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

python -u ./ernie/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 16                                                  \
       --init_pretraining_params ${MODEL_PATH}/params                   \
       --verbose true                                                   \
       --train_set ${TASK_DATA_PATH}/STS-B/train.tsv                    \
       --dev_set   ${TASK_DATA_PATH}/STS-B/dev.tsv                      \
       --test_set  ${TASK_DATA_PATH}/STS-B/test.tsv                     \
       --vocab_path script/en_glue/ernie_large/vocab.txt                \
       --checkpoints ./checkpoints                                      \
       --save_steps 1000                                                \
       --weight_decay  0.0                                              \
       --warmup_proportion 0.1                                          \
       --validation_steps 100000000000                                  \
       --epoch 3                                                        \
       --max_seq_len 128                                                \
       --ernie_config_path script/en_glue/ernie_large/ernie_config.json \
       --learning_rate 5e-5                                             \
       --skip_steps 10                                                  \
       --num_iteration_per_drop_scope 1                                 \
       --num_labels 1                                                   \
       --is_classify false                                              \
       --is_regression true                                             \
       --metric 'pearson_and_spearman'                                  \
       --test_save output/test_out.$i.tsv                               \
       --random_seed 1 2>&1 | tee  log/job.$i.$timestamp.log            \

done
