Plot Multiple curve_training_validation_accuracy__loss

def plot_performance_acc(hist, hist_one, hist_two, hist_three, hist_four, hist_five):
    plt.rcParams['figure.figsize'] = (20, 10)
    
    hist_00 = hist.history
    epochs_00 = hist.epoch
    
    hist_01 = hist_one.history
    epochs_01 = hist_one.epoch
    
    hist_02 = hist_two.history
    epochs_02 = hist_two.epoch
    
    hist_03 = hist_three.history
    epochs_03 = hist_three.epoch
    
    hist_04 = hist_four.history
    epochs_04 = hist_four.epoch
    
    hist_05 = hist_five.history
    epochs_05 = hist_five.epoch
    
    
    plt.subplot(1, 2, 1) # row 1, col 2 index 1
    plt.plot(epochs_00, hist_00['accuracy'], label='Learning Rate: 0.1')
    plt.plot(epochs_01, hist_01['accuracy'], label='Learning Rate: 0.01')
    plt.plot(epochs_02, hist_02['accuracy'], label='Learning Rate: 0.001')
    plt.plot(epochs_03, hist_03['accuracy'], label='Learning Rate: 0.0001')
    plt.plot(epochs_04, hist_04['accuracy'], label='Learning Rate: 0.00001')
    plt.plot(epochs_05, hist_05['accuracy'], label='Learning Rate: 0.00001')
    
    plt.xlabel('Epochs')
    plt.ylabel('Accuracy')
    # plt.ylim([-0.001, 2.0])
    plt.title('Training accuracy with Adam optimizer')
    plt.legend(loc = 'lower right')
    
    plt.subplot(1, 2, 2) # row 1, col 2 index 1
    plt.plot(epochs_00, hist_00['val_accuracy'], label='Learning Rate: 0.1')
    plt.plot(epochs_01, hist_01['val_accuracy'], label='Learning Rate: 0.01')
    plt.plot(epochs_02, hist_02['val_accuracy'], label='Learning Rate: 0.001')
    plt.plot(epochs_03, hist_03['val_accuracy'], label='Learning Rate: 0.0001')
    plt.plot(epochs_04, hist_04['val_accuracy'], label='Learning Rate: 0.00001')
    plt.plot(epochs_05, hist_05['val_accuracy'], label='Learning Rate: 0.00001')
    
    
    plt.xlabel('Epochs')
    plt.ylabel('Accuracy')
    # plt.ylim([-0.001, 0.9])
    plt.title('Validation accuracy with Adam optimizer')
    plt.legend(loc = 'lower right')

    plt.tight_layout(2)
    fig1 = plt.gcf()
    plt.show()
    plt.draw()
    fig1.savefig('acc.png', dpi=50)

-----------------------------------------------------------------------------------


def plot_performance_loss(hist, hist_one, hist_two, hist_three, hist_four, hist_05):
    plt.rcParams['figure.figsize'] = (20, 10)
    
    hist_00 = hist.history
    epochs_00 = hist.epoch
    
    hist_01 = hist_one.history
    epochs_01 = hist_one.epoch
    
    hist_02 = hist_two.history
    epochs_02 = hist_two.epoch
    
    hist_03 = hist_three.history
    epochs_03 = hist_three.epoch
    
    hist_04 = hist_four.history
    epochs_04 = hist_four.epoch
    
    hist_05 = hist_five.history
    epochs_05 = hist_five.epoch
    
    plt.subplot(1, 2, 1) # row 1, col 2 index 1
    plt.plot(epochs_00, hist_00['loss'], label='Learning Rate: 0.1')
    plt.plot(epochs_01, hist_01['loss'], label='Learning Rate: 0.01')
    plt.plot(epochs_02, hist_02['loss'], label='Learning Rate: 0.001')
    plt.plot(epochs_03, hist_03['loss'], label='Learning Rate: 0.0001')
    plt.plot(epochs_04, hist_04['loss'], label='Learning Rate: 0.00001')
    plt.plot(epochs_05, hist_05['loss'], label='Learning Rate: 0.00001')
    
    plt.xlabel('Epochs')
    plt.ylabel('Loss')
    # plt.ylim([-0.001, 2.0])
    plt.title('Training loss with Adam')
    plt.legend(loc = 'upper right')
    
    plt.subplot(1, 2, 2) # row 1, col 2 index 1
    plt.plot(epochs_00, hist_00['val_loss'], label='Learning Rate: 0.1')
    plt.plot(epochs_01, hist_01['val_loss'], label='Learning Rate: 0.01')
    plt.plot(epochs_02, hist_02['val_loss'], label='Learning Rate: 0.001')
    plt.plot(epochs_03, hist_03['val_loss'], label='Learning Rate: 0.0001')
    plt.plot(epochs_04, hist_04['val_loss'], label='Learning Rate: 0.00001')
    plt.plot(epochs_05, hist_05['loss'], label='Learning Rate: 0.00001')
    
    
    plt.xlabel('Epochs')
    plt.ylabel('Loss')
    # plt.ylim([-0.001, 2.0])
    plt.title('Validation loss with Adam')
    plt.legend(loc = 'upper right')
 
    plt.tight_layout(2)
    fig1 = plt.gcf()
    plt.show()
    plt.draw()
    fig1.savefig('loss.png', dpi=50)