checkpoint_monitor:
  _target_: lightning.pytorch.callbacks.ModelCheckpoint
  monitor: val/nll # name of the logged metric which determines when model is improving
  mode: min # can be "max" or "min"
  save_top_k: 1 # save k best models (determined by above metric)
  save_last: False # True = additionally always save model from last epoch
  dirpath: ${checkpointing.save_dir}/checkpoints
  filename: best
  auto_insert_metric_name: False
  verbose: True