text: Title: ValueError on first epoch
  Body: - PyTorch-Forecasting version: 0.10.3
  - PyTorch version: 1.13.0
  - Python version: 3.9.12
  - Operating System: Mac OS 12.6
  
  ### Expected behavior
  
  I'm trying to do good ol' stock price prediction using TFT. I've followed the stallion example, changing the dataset configuration as required. I'm expecting the call to `trainer.fit` to work as it would normally...
  
  ### Actual behaviour
  
  ...but it fails on the first training iteration with the traceback included below. I'm almost certain this is a trivial configuration mistake. Please let me know what I'm forgetting to include.
  
  ### Code to reproduce the problem
  
  **Example dataset: MSFT, GOOG, AMZN, AAPL, META- 512 day ticker history (excl. weekends)**
  ![Screenshot](https://user-images.githubusercontent.com/3847023/200143862-2eefe087-ed7d-4ea6-b8d9-19838b26c1c7.png)
  
  **Colab notebook here:**
  [https://colab.research.google.com/drive/1lF6DWoje_qD0PZysNu6UHaoqK9nDstBH?usp=sharing](https://colab.research.google.com/drive/1lF6DWoje_qD0PZysNu6UHaoqK9nDstBH?usp=sharing)
  
  **Traceback:**
  ```
  ValueError                                Traceback (most recent call last)
  Cell In [94], line 117
      102 tft = TemporalFusionTransformer.from_dataset(
      103     training,
      104     learning_rate = 0.03,
     (...)
      112     reduce_on_plateau_patience = 4
      113 )
      115 tft.size()
  --> 117 trainer.fit(
      118     tft,
      119     train_dataloaders = [train_dataloader],
      120     val_dataloaders = [val_dataloader]
      121 )
  
  [SNIPPED]
  
  File ~/opt/miniconda3/lib/python3.9/site-packages/pytorch_lightning/strategies/strategy.py:378, in Strategy.training_step(self, *args, **kwargs)
      376 with self.precision_plugin.train_step_context():
      377     assert isinstance(self.model, TrainingStep)
  --> 378     return self.model.training_step(*args, **kwargs)
  
  File ~/opt/miniconda3/lib/python3.9/site-packages/pytorch_forecasting/models/base_model.py:410, in BaseModel.training_step(self, batch, batch_idx)
      406 def training_step(self, batch, batch_idx):
      407     """
      408     Train on batch.
      409     """
  --> 410     x, y = batch
      411     log, out = self.step(x, y, batch_idx)
      412     return log
  
  ValueError: not enough values to unpack (expected 2, got 1)
  ```
  
  