StringVal="2e-5"
#StringTask="CoLA SST-2 MRPC STS-B QQP QNLI RTE"
model_name="bert-base-uncased_clip_x2_wiki_mlm_vlm_match_whole_seq/Epoch12/Epoch12_XATTNBERT"
for val in $StringVal; do 
	echo ${val}
	OutDir="results/finetune/${model_name}/copa/lr-"
	OutDir+="${val}"
	mkdir -p "$OutDir"
	echo ${OutDir}
	CUDA_VISIBLE_DEVICES=0 PYTHONPATH=$PYTHONPATH:./src python ./src/finetune/x_run_multiple_choice.py \
	--task_name swag \
	--config_name bert-base-uncased \
	--tokenizer_name bert-base-uncased \
	--model_name_or_path "results/pretrain/${model_name}.pth" \
	--xlayers 2 \
	--do_train \
	--do_eval \
	--do_predict \
	--data_dir data/superglue/COPA \
	--learning_rate $val \
	--weight_decay 0.01 \
	--warmup_steps 12 \
	--num_train_epochs 7 \
	--max_seq_length 128 \
	--output_dir $OutDir \
	--per_device_eval_batch_size=4 \
	--per_device_train_batch_size=4 \
	--gradient_accumulation_steps 8 \
	--overwrite_output \
	--overwrite_cache \
	--evaluation_strategy steps \
	--eval_steps 12 \
	--logging_steps 12 \
	#--config_name "bert-base-cased" \
	#--tokenizer_name "bert-base-cased" \
	#--evaluate_during_training
	
	#unc-nlp/

done
