not so long ago I taught the model, got the results and everything approx. Now I needed to restart the project and everything stopped working for me, namely the error on catboost.

X = df_train.drop(columns=['type_answer'])
y = df_train['type_answer']
 
X_train, X_test, y_train, y_test = train_test_split(
    X, y, 
    test_size=0.15, 
    stratify=y, 
    random_state=42
)
 
enc = TargetEncoder(cols=X.select_dtypes('object').columns)
X_train_encoded = enc.fit_transform(X_train, y_train)
X_test_encoded = enc.transform(X_test)

models = {
    'Random Forest': RandomForestClassifier(
        class_weight='balanced', random_state=42
    ),
    'XGBoost': XGBClassifier(
        scale_pos_weight=(len(y_train) -sum(y_train)) /sum(y_train), 
        random_state=42
    ),
    'CatBoost': CatBoostClassifier(
        auto_class_weights='Balanced', 
        custom_metric=['Precision'], 
        verbose=0, random_state=42
    ),
    'LightGBM': LGBMClassifier(
        class_weight='balanced', random_state=42, verbose=-1
    )
}
 
for model_name, model in models.items():
    model.fit(X_train_encoded, y_train)
    y_pred = model.predict_proba(X_test_encoded)[:, 1]
    gini = gini_score(y_test, y_pred)
    print(f'{model_name}: Gini test = {round(100 * gini, 2)}%')

---------------------------------------------------------------------------CatBoostError                             Traceback (most recent call last)
Cell In[78], line 22      2 models = {      3     'Random Forest': RandomForestClassifier(      4         class_weight='balanced', random_state=42   (...)     17     )     18 }     20 for model_name, model in models.items():     21     # try:---> 22     model.fit(X_train_encoded, y_train)     23     y_pred = model.predict_proba(X_test_encoded)[:, 1]     24     gini = gini_score(y_test, y_pred)

File ~AppDataLocalProgramsPythonPython310libsite-packagescatboostcore.py:5220, in CatBoostClassifier.fit(self, X, y, cat_features, text_features, embedding_features, sample_weight, baseline, use_best_model, eval_set, verbose, logging_level, plot, plot_file, column_description, verbose_eval, metric_period, silent, early_stopping_rounds, save_snapshot, snapshot_file, snapshot_interval, init_model, callbacks, log_cout, log_cerr)   5217 if 'loss_function' in params:   5218     CatBoostClassifier._check_is_compatible_loss(params['loss_function'])-> 5220 self._fit(X, y, cat_features, text_features, embedding_features, None, sample_weight, None, None, None, None, baseline, use_best_model,   5221           eval_set, verbose, logging_level, plot, plot_file, column_description, verbose_eval, metric_period,   5222           silent, early_stopping_rounds, save_snapshot, snapshot_file, snapshot_interval, init_model, callbacks, log_cout, log_cerr)   5223 return self
File ~AppDataLocalProgramsPythonPython310libsite-packagescatboostcore.py:2400, in CatBoost._fit(self, X, y, cat_features, text_features, embedding_features, pairs, sample_weight, group_id, group_weight, subgroup_id, pairs_weight, baseline, use_best_model, eval_set, verbose, logging_level, plot, plot_file, column_description, verbose_eval, metric_period, silent, early_stopping_rounds, save_snapshot, snapshot_file, snapshot_interval, init_model, callbacks, log_cout, log_cerr)   2397 allow_clear_pool = train_params["allow_clear_pool"]   2399 with plot_wrapper(plot, plot_file, 'Training plots', [_get_train_dir(self.get_params())]):-> 2400     self._train(   2401         train_pool,   2402         train_params["eval_sets"],   2403         params,   2404         allow_clear_pool,   2405         train_params["init_model"]   2406     )   2408 # Have property feature_importance possibly set   2409 loss = self._object._get_loss_function_name()

File ~AppDataLocalProgramsPythonPython310libsite-packagescatboostcore.py:1780, in _CatBoostBase._train(self, train_pool, test_pool, params, allow_clear_pool, init_model)   1779 def _train(self, train_pool, test_pool, params, allow_clear_pool, init_model):-> 1780     self._object._train(train_pool, test_pool, params, allow_clear_pool, init_model._object if init_model else None)   1781     self._set_trained_model_attributes()

File _catboost.pyx:4833, in _catboost._CatBoost._train()
File _catboost.pyx:4882, in _catboost._CatBoost._train()CatBoostError: 

methods tried:

1. reinstalling catboost
2. delete old environment and install new
3. training separately for catboost via Pool
   A big request to help with understanding the problems, because the project was launched many times earlier and there were no problems.