Evaluate the model on validation dataset.

def evaluate(dataloader_eval, metric):
    """Evaluate the model on validation dataset.
    """
    metric.reset()
    for _, seqs in enumerate(dataloader_eval):
        input_ids, valid_len, type_ids, label = seqs
        out = model(
            input_ids.as_in_context(ctx), type_ids.as_in_context(ctx),
            valid_len.astype('float32').as_in_context(ctx))
        metric.update([label], [out])
    metric_nm, metric_val = metric.get()
    if not isinstance(metric_nm, list):
        metric_nm = [metric_nm]
        metric_val = [metric_val]
    metric_str = 'validation metrics:' + ','.join(
        [i + ':%.4f' for i in metric_nm])
    logging.info(metric_str, *metric_val)