Validation Loss

Nobody has claimed this yet.

I have introduced the validation phase using a custom dataset:

```
val_dataloader = DataLoader(val_dataset, num_workers=0, batch_size=batch_size, shuffle=False)
# omit some codes
trainer.fit(model, train_dataloader, val_dataloader)
```

However, it seems the code does not present the loss:

```
Epoch 2: 95%|█████████▌| 120/126 [04:27<00:13, 2.23s/it, loss=0.00658, v_num=3, train/loss_simple_step=0.0176, train/loss_vlb_step=0.000127, train/loss_step=0.0176, global_step=263.0, train/loss_simple_epoch=0.00721, train/loss_vlb_epoch=0.000521, train/loss_epoch=0.00721]
Validating: 84%|████████▍ | 32/38 [00:36<00:06, 1.13s/it]
Epoch 2: 97%|█████████▋| 122/126 [04:29<00:08, 2.21s/it, loss=0.00658, v_num=3, train/loss_simple_step=0.0176, train/loss_vlb_step=0.000127, train/loss_step=0.0176, global_step=263.0, train/loss_simple_epoch=0.00721, train/loss_vlb_epoch=0.000521, train/loss_epoch=0.00721]
Validating: 89%|████████▉ | 34/38 [00:38<00:04, 1.13s/it]
Epoch 2: 98%|█████████▊| 124/126 [04:32<00:04, 2.20s/it, loss=0.00658, v_num=3, train/loss_simple_step=0.0176, train/loss_vlb_step=0.000127, train/loss_step=0.0176, global_step=263.0, train/loss_simple_epoch=0.00721, train/loss_vlb_epoch=0.000521, train/loss_epoch=0.00721]
Validating: 95%|█████████▍| 36/38 [00:40<00:02, 1.14s/it]
```

I would appreciate it if anyone could advise me on this, thanks!

Start with the validation path at trainer.fit(model, train_dataloader, val_dataloader) and compare it with the displayed training metrics. Trace how the custom val_dataloader's loss is logged; done means the validation loss appears in the validation output alongside the training losses.

Written by the indexing model from the issue text.