### Changes
- __Breaking__: in train, load model instead of weights when restarting
- the argument `load_weights` is now `load_model`
- the flag option in the cli `--load_weights` is now `--load_model`
- __Breaking__: implement class weights.
- orcai_parameters.json now has a model.call_weights key.
- to unbreak add `"call_weights": null` to the model section of orcai_parameters.json
- Implemented "three" methods for calculating call weights:
- `"balanced"` is the same heuristic as is used in sklearn (= total / (n_calls \* count)),
- `"max"` is 1/count \* total,
- `"uniform"` is all ones and equal to None.
- Use `null` (in Json, `None` in python) to disable class weights.
- __Breaking__: switch to class based metrics
- __Breaking__: implement AUC ROC metric
- __Breaking__: making the choice of metric to monitor for callbacks an option in orcai_parameters.json
- to unbreak add `"monitor": "val_MBA"` to the model section of orcai_parameters.json
- make ReduceLROnPlateau callback patience == model_parameters['patience'] // __3__
- define metrics in architectures.py
- new arg parameter to overwrite default orcai parameter on project init