code: def evaluate(dataloader_eval, metric):
      
      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)
docs: Evaluate the model on validation dataset.