Is there way to save trained model after overfitting occurs in CatBoost?

I am using CatBoostRegressor in Python version of the Catboost library.

According to documentation, it's possible to use overfitting detector, which I am doing, like this:

model = CatBoostRegressor(iterations=iters, learning_rate=0.03, depth=depth, verbose=True, od_pval=1, od_type='IncToDec', od_wait=20)
model.fit(train_pool, eval_set=validation_pool)

# this code didn't executed
model.save_model(model_name)

However, after the overfitting occurs, I've got my Python script interrupted, prematurely stopped, pick any phrase you want, and save model part didn't get executed, which leads to a lot of waisted time and no results in the end. I didn't get any stacktrace.

Is there any possibility to handle it in CatBoost and save hours of fitting work?