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[21363a]: / lvl2 / models / RNN_256_delay4000_FBLCRAll_ADAM.yml

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Meta:

  file: 'RNN_256_delay4000_FBLCRAll_ADAM'





Model:

  NeuralNet:

    ensemble: [

                'FBL_L1', 'FBL_L2', 'FBL_Sc', 'FBL_LDA', 'FBL_LDA_L1', 

                'FBLCAll_Sc','FBLCAll_LDA_Sc',

                'FBL_delay_L1', 'FBL_delay_L2', 'FBL_delay_Sc', 'FBL_delay_LDA',

                

                'C500_[1_15]_LR', 'C500_[1_15]_LDA', 

                'C500_[7_30]_LR', 'C500_[7_30]_LDA',

                'C500_[20_35]_LR', 'C500_[20_35]_LDA',

                'C500_[70_150]_LR', 'C500_[70_150]_LDA',

                'C250_[35]_LR', 'C250_[35]_LDA',

                'C500_[35]_LR', 'C500_[35]_LDA',

                'ERPDist', 'ERPDist_LDA',

                'CAll_LR',

                

                'CNN_1D_FB30',

                'CNN_2D_FB30', 

                'CNN_1D_FB7-30',

                'CNN_1D_FB5',

                ]

    training_params:

      optim: 'adam'

      lr: 0.01

    

    delay: 4000

    skip: 100

    partsTrain: 4

    partsTest: 4

    smallEpochs: 1

    majorEpochs: 1

    checkEveryEpochs: 1



    architecture:

      - 'Dropout':

            p: 0.5

      - 'GRU':

            num_units: 256

            next_GRU: False

      - 'Dense':

            num_units: 256

      - 'Activation':

            type: 'relu'

      - 'Dropout':

            p: 0.7

      - 'Output':