for dataset in amazon_counterfactual_en emotion enron_spam SentEval-CR sst5 
do
    for sample_size in 8 64
    do
        for train_split in 0 1 2 3 4 5 6 7 8 9 
        do
            for seed in 0 1 2 3 4
            do

		python -m src.pl_train -c t011b.json+ia3.json+${dataset}.json \
                -k load_weight="t-few/pretrained_checkpoints/t011b_ia3_finish.pt" \
                exp_name=t011b_pretrained/${dataset}/train-${sample_size}-${train_split}/seed${seed} \
                train_split=${train_split} \
                few_shot_random_seed=${seed} \
                seed=${seed} \
                num_shot=$sample_size \
                batch_size=1 \
                eval_batch_size=2 \
                grad_accum_factor=8 \
                eval_before_training=0
	    done
        done
    done
done
