improve hyperparameter logging

[ArneBinder]

This PR improves the hyperparameter logging when executing train.py or evaluate.py in the following ways, i.e. log_hyperparameters():

• the hydra-run config gets resolved before logging it, that means ConfigDict entries are correctly un-nested (compare the dataset entry in the W&B run config view, for instance)
• remove duplicated entries by not logging model._config() and taskmodule._config() at all, because the model parameters are automatically logged by calling self.save_hyperparameters() in the model and in the future each model should receive taskmodule_config as parameter, so that will get logged as well (taskmodule._config() is currently still logged in some cases for backwards compatibility)
• the method allows for arbitrary keyword arguments that will get logged
• the logging keys for the config, number of model parameter, and all other parameters to log are prefixed with key_prefix, which is "_" per default, to distinguish them from the model parameters.

In addition, with this PR two more parameters are logged:

• _best_checkpoint: os.path.basename(best_ckpt_path) taken from the checkpoint callback
• _checkpoint_dir: dirpath taken from the checkpoint callback

Note: this requires pie-modules>=0.9.0