def strict_accuracy_N(act, pred, ignore_class=0):
    """
    Computes the accuracy of an array of tagged sentences
    Actual values which match `ignore_class` are not factored in
        Inputs:
            - act: array of actual numerical vectors
            - pred: array of predicted numerical vectors
            - ignore_class: numerical value to be ignored
        Outputs:
            - accuracy score
    """
    # number of correct predictions
    corr_preds = 0
    # number of predictions
    total_preds = 0
    # compute values via iterating over sentences
    for sent in zip(act, pred):
        act_classes = sent[0]
        pred_classes = sent[1]
        for t in range(len(act_classes)):
            if act_classes[t] != int(ignore_class):
                total_preds += 1
                if pred_classes[t] == act_classes[t]:
                    corr_preds += 1
    # actual accuracy without padding
    return corr_preds / total_preds