feat: add best_model_metrics to ModelCheckpoint callback

[Iruos8805]

What does this PR do?

This PR introduces a new best_model_metrics attribute to the ModelCheckpoint callback, enabling users to directly access all logged training and validation metrics associated with the best model, chosen based on the monitored metric.

Previously, only the best_model_score and best_model_path were available. With this addition, users can easily retrieve the corresponding metrics like val_loss, train_loss, val_metric etc. of the best checkpoint without reloading the model or rerunning validation.

This makes it easier to analyze results and use the best model’s metrics for reporting or hyperparameter tuning.

Fixes #19007

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📚 Documentation preview 📚: https://pytorch-lightning--21355.org.readthedocs.build/en/21355/