code: def validation_epoch_end(self, outputs):
      if self.cfg.datamodule.task_name == "mnli":
          for i, output in enumerate(outputs):
              # matched or mismatched
              split = self._datamodule.eval_splits[i].split("_")[-1]
              preds = (
                  torch.cat([x["preds"] for x in output])
                  .detach()
                  .cpu()
                  .numpy()
              )
              labels = (
                  torch.cat([x["labels"] for x in output])
                  .detach()
                  .cpu()
                  .numpy()
              )
              loss = torch.stack([x["loss"] for x in output]).mean()
              self.log(f"val_loss_{split}", loss, prog_bar=True)
              split_metrics = {
                  f"{k}_{split}": v
                  for k, v in self.metric.compute(
                      predictions=preds, references=labels
                  ).items()
              }
              self.log_dict(split_metrics, prog_bar=True)
          return loss
  
      preds = (
          torch.cat([x["preds"] for x in outputs])
          .detach()
          .cpu()
          .numpy()
      )
      labels = (
          torch.cat([x["labels"] for x in outputs])
          .detach()
          .cpu()
          .numpy()
      )
      loss = torch.stack([x["loss"] for x in outputs]).mean()
      self.log("val_loss", loss, prog_bar=True)
      self.log_dict(
          self.metric.compute(predictions=preds, references=labels),
          prog_bar=True,
      )
      return loss
  
imports: from typing import Any, List
  import inspect
  import torch
  import hydra
  from pytorch_lightning import LightningModule, LightningDataModule
  from torchmetrics import MetricCollection
  from einops import rearrange
  from omegaconf import OmegaConf
  from src.utils.utils import get_logger
  from src.optim.param_grouping import group_parameters_for_optimizer
  from src.utils.checkpoint import load_checkpoint
  import datasets
label_desc: Use image node_id 4 for calling the GLUETransformerHfMetrics obj's underlying member method code with example usage: obj.validation_epoch_end(outputs) and returns: loss, loss