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run_himt.sh
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for i in 'twitter2015' #'twitter'
do
for l in '1e-5'
do
for pl in '1'
do
for cl in '2'
do
for w in '0.1'
do
for seed in '3813356'
do
echo ${i}
echo ${l}
echo ${pl}
echo ${cl}
echo ${w}
echo ${seed}
CUDA_VISIBLE_DEVICES=0 python run_himt.py \
--data_dir ../pytorch-pretrained-absa/absa_data/${i} \
--task_name ${i} \
--output_dir ./output/HIMT_TopN/${i}_${l}_${pl}_${cl}_${w}_${seed}/ \
--bert_model ../pytorch-bert-base \
--do_train \
--do_eval \
--r_loss 1e-2 \
--warmup_proportion ${w} \
--learning_rate ${l} \
--projectionlayer ${pl} \
--seed ${seed} \
--cmtlayer ${cl} \
--train_batch_size 32 \
--max_target_length 80 \
--no_gate True \
--img_path ../HIMT/data/twitter2015_top3/TSA_Twitter2015_
done
done
done
done
done
done
for i in 'twitter'
do
for l in '2e-5'
do
for pl in '1'
do
for cl in '4'
do
for w in '0.1'
do
for seed in '3813356'
do
echo ${i}
echo ${l}
echo ${pl}
echo ${cl}
echo ${w}
echo ${seed}
CUDA_VISIBLE_DEVICES=0 python run_himt.py \
--data_dir ../pytorch-pretrained-absa/absa_data/${i} \
--task_name ${i} \
--output_dir ./output/HIMT_TopN/temp/${i}_${l}_${pl}_${cl}_${w}_${seed}/ \
--bert_model ../pytorch-bert-base \
--do_train \
--do_eval \
--r_loss 1e-2 \
--warmup_proportion ${w} \
--learning_rate ${l} \
--projectionlayer ${pl} \
--seed ${seed} \
--cmtlayer ${cl} \
--train_batch_size 32 \
--max_target_length 80 \
--no_gate True \
--img_path ../HIMT/data/twitter2017_top3/TSA_Twitter2017_
done
done
done
done
done
done