Problem: .copy() on a model not working properly - after performing a copy some evaluation metrics get lost.
catboost version: 0.25.1
Operating System: Ubuntu 20.04
CPU: Threadripper 1950X
Minimal example:

from catboost import CatBoostClassifier, Pool

train_data = [[0, 3],
[4, 1],
[8, 1],
[9, 1]]

train_labels = [0, 0, 1, 1]

eval_data = [[2, 1],
[3, 1],
[9, 0],
[5, 3]]

eval_labels = [0, 1, 1, 0]

eval_dataset = Pool(eval_data,
eval_labels)

model = CatBoostClassifier(learning_rate=0.03,
custom_metric=['Logloss',
'AUC:hints=skip_train~false'])

model.fit(train_data,
train_labels,
eval_set=eval_dataset,
verbose=False)

print(model.best_score_)
print(model.evals_result_)

model2 = model.copy()
print(model2.best_score_)
print(model2.evals_result_)