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| # https://lightning.ai/docs/pytorch/stable/api/lightning.pytorch.callbacks.ModelCheckpoint.html | |
| model_checkpoint: | |
| _target_: lightning.pytorch.callbacks.ModelCheckpoint | |
| dirpath: ${paths.output_dir}/checkpoints # directory to save the model file | |
| filename: checkpoint_{epoch:03d} # checkpoint filename | |
| monitor: epoch # name of the logged metric which determines when model is improving | |
| verbose: False # verbosity mode | |
| save_last: true # additionally always save an exact copy of the last checkpoint to a file last.ckpt | |
| save_top_k: 5 # save k best models (determined by above metric) | |
| mode: "max" # "max" means higher metric value is better, can be also "min" | |
| auto_insert_metric_name: True # when True, the checkpoints filenames will contain the metric name | |
| save_weights_only: False # if True, then only the model’s weights will be saved | |
| every_n_train_steps: null # number of training steps between checkpoints | |
| train_time_interval: null # checkpoints are monitored at the specified time interval | |
| every_n_epochs: 10 # number of epochs between checkpoints | |
| save_on_train_epoch_end: null # whether to run checkpointing at the end of the training epoch or the end of validation | |