val loss and accuracy not logging

[gkrampah]

this is my code and I am having difficulty getting the CVS logger and tensorboard loggers to output the validation loss and accuracies after each epoch. The training parameters are properly logged. I am using the latest version of lightning. Any assistance will be highly appreciated.
def _shared_step(self, batch):
features, true_labels = batch["Sample"], batch["Label"].long()
logits = self(features)

    loss = F.cross_entropy(logits, true_labels)
    predicted_labels = torch.argmax(logits, dim=1)
    batch_size = features.size(0)
    return loss, true_labels, predicted_labels, batch_size

def training_step(self, batch, batch_idx):
    # use _shared_step
    loss, true_labels, predicted_labels, batch_size = self._shared_step(batch)

    train_acc = self.train_acc(predicted_labels, true_labels)

    self.log(
        "train_loss",
        loss,
        prog_bar=True,
        on_epoch=True,
        on_step=False,
        batch_size=batch_size,
        logger=True,
    )

    self.log(
        "train_acc",
        train_acc,
        prog_bar=True,
        on_epoch=True,
        on_step=False,
        batch_size=batch_size,
        logger=True,
    )

    return loss

# def on_train_epoch_end(self):
#     self.log(
#         "train_acc",
#         self.train_acc.compute(),
#         prog_bar=True,
#         on_epoch=True,
#         logger=True,
#     )
#     self.train_acc.reset()

def validation_step(self, batch, batch_idx):
    # use _shared_step
    loss, true_labels, predicted_labels, batch_size = self._shared_step(batch)
    # Computes validation accuracy on whole validation set
    val_acc = self.val_acc(predicted_labels, true_labels)

    # self.validation_loss_outputs.append(loss)
    # self.validation_accuracy_outputs.append(val_acc)

    self.log(
        "val_loss",
        loss,
        prog_bar=True,
        on_epoch=True,
        on_step=False,
        batch_size=batch_size,
        logger=True,
    )

    self.log(
        "val_acc",
        val_acc,
        prog_bar=True,
        on_epoch=True,
        on_step=False,
        batch_size=batch_size,
        logger=True,
    )