for task in task1 task2 task3
do

    for embedding in word2vecf wang2vec distant word2vec
    do

        for size in 100 200 300
        do

            for kfold in 0 1 2 3
            do

                THEANO_FLAGS=mode=FAST_RUN,device=gpu0,nvcc.fastmath=True,floatX=float32 python bin/cnn.py embedding/${embedding}_size${size}_win3.bin data/${task}_train_${kfold}.tokenize data/${task}_dev_${kfold}.tokenize ${task} "1,2,3" model_corrige/cnn_${task}_${kfold}_${embedding}_size${size}_123
                THEANO_FLAGS=mode=FAST_RUN,device=gpu0,nvcc.fastmath=True,floatX=float32 python bin/cnn.py embedding/${embedding}_size${size}_win3.bin data/${task}_train_${kfold}.tokenize data/${task}_dev_${kfold}.tokenize ${task} "3,4,5" model/cnn_${task}_${kfold}_${embedding}_size${size}_345
                THEANO_FLAGS=mode=FAST_RUN,device=gpu0,nvcc.fastmath=True,floatX=float32 python bin/cnn.py embedding/${embedding}_size${size}_win3.bin data/${task}_train_${kfold}.tokenize data/${task}_dev_${kfold}.tokenize ${task} "5,6,7" model/cnn_${task}_${kfold}_${embedding}_size${size}_567



            done

        done

    done

done