Get an error on train and evaluate

DeepPavlov Library
1

I am working with classification. I added into the output additional param. Prediction and evaluate work well.

    "out": [
      "x",
      "y_pred_ids",
      "y_pred_labels",
      "y_pred_probas"
    ]

Full config:

{
  "dataset_reader": {
    "class_name": "basic_classification_reader",
    "x": "Comment",
    "y": "Class",
    "data_path": "{PROJECT_PATH}/data/"
  },
  "dataset_iterator": {
    "class_name": "basic_classification_iterator",
    "seed": 42
  },
  "chainer": {
    "in": [
      "x"
    ],
    "in_y": [
      "y"
    ],
    "pipe": [
      {
        "class_name": "torch_transformers_preprocessor",
        "vocab_file": "{TRANSFORMER}",
        "do_lower_case": true,
        "max_seq_length": 64,
        "in": [
          "x"
        ],
        "out": [
          "bert_features"
        ]
      },
      {
        "id": "classes_vocab",
        "class_name": "simple_vocab",
        "fit_on": [
          "y"
        ],
        "save_path": "{MODEL_PATH}/classes.dict",
        "load_path": "{MODEL_PATH}/classes.dict",
        "in": [
          "y"
        ],
        "out": [
          "y_ids"
        ]
      },
      {
        "in": [
          "y_ids"
        ],
        "out": [
          "y_onehot"
        ],
        "class_name": "one_hotter",
        "depth": "#classes_vocab.len",
        "single_vector": true
      },
      {
        "class_name": "torch_transformers_classifier",
        "n_classes": "#classes_vocab.len",
        "return_probas": true,
        "pretrained_bert": "{TRANSFORMER}",
        "save_path": "{MODEL_PATH}/model",
        "load_path": "{MODEL_PATH}/model",
        "optimizer": "AdamW",
        "optimizer_parameters": {
          "lr": 1e-05
        },
        "learning_rate_drop_patience": 5,
        "learning_rate_drop_div": 2.0,
        "in": [
          "bert_features"
        ],
        "in_y": [
          "y_ids"
        ],
        "out": [
          "y_pred_probas"
        ]
      },
      {
        "in": [
          "y_pred_probas"
        ],
        "out": [
          "y_pred_ids"
        ],
        "class_name": "proba2labels",
        "max_proba": true
      },
      {
        "in": [
          "y_pred_ids"
        ],
        "out": [
          "y_pred_labels"
        ],
        "ref": "classes_vocab"
      }
    ],
    "out": [
      "x",
      "y_pred_ids",
      "y_pred_labels",
      "y_pred_probas"
    ]
  },
  "train": {
    "device": "gpu",
    "epochs": 100,
    "batch_size": 64,
    "metrics": [
      {
        "name": "roc_auc",
        "inputs": [
          "y_onehot",
          "y_pred_probas"
        ]
      },
      "accuracy",
      "f1_macro"
    ],
    "validation_patience": 5,
    "val_every_n_epochs": 1,
    "log_every_n_epochs": 1,
    "show_examples": false,
    "evaluation_targets": [
      "train",
      "valid",
      "test"
    ],
    "class_name": "torch_trainer"
  },
  "metadata": {
    "NAME": "Russian Language Toxic Comments",
    "variables": {
      "ROOT_PATH": "./data",
      "PROJECT_PATH": "{ROOT_PATH}/rlt",
      "MODELS_PATH": "{PROJECT_PATH}/models",
      "MODEL_PATH": "{MODELS_PATH}/classifiers",
      "TRANSFORMER": "bert-base-uncased",
      "LOGS_PATH": "{PROJECT_PATH}/logs"
    }
  }
}

But if I try to train or evaluate I get the error:

2024-08-01 22:32:47.833 WARNING in 'deeppavlov.core.trainers.fit_trainer'['fit_trainer'] at line 66: TorchTrainer got additional init parameters ['device'] that will be ignored:
Some weights of BertForSequenceClassification were not initialized from the model checkpoint at bert-base-uncased and are newly initialized: ['classifier.bias', 'classifier.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
2024-08-01 22:32:49.892 WARNING in 'deeppavlov.core.models.torch_model'['torch_model'] at line 96: Unable to place component TorchTransformersClassifierModel on GPU, since no CUDA GPUs are available. Using CPU.
76it [01:16,  1.01s/it]
Traceback (most recent call last):
  File "cli.py", line 47, in <module>
    switch(args.action)
  File "cli.py", line 44, in switch
    cases.get(case, lambda: print("Incorrect action."))()
  File "cli.py", line 33, in evaluate
    EvaluateHandler().evaluate(args.config, args.lang)
  File "applicaion/handler/evaluate_handler.py", line 20, in evaluate
    evaluate_model(config)
  File "venv/lib/python3.9/site-packages/deeppavlov/__init__.py", line 37, in evaluate_model
    return train_evaluate_model_from_config(config, to_train=False, install=install,
  File "venv/lib/python3.9/site-packages/deeppavlov/core/commands/train.py", line 123, in train_evaluate_model_from_config
    res = trainer.evaluate(iterator, evaluation_targets)
  File "venv/lib/python3.9/site-packages/deeppavlov/core/trainers/fit_trainer.py", line 230, in evaluate
    report = self.test(data_gen)
  File "venv/lib/python3.9/site-packages/deeppavlov/core/trainers/torch_trainer.py", line 34, in test
    report = super(TorchTrainer, self).test(data=data, metrics=metrics, start_time=start_time,
  File "venv/lib/python3.9/site-packages/deeppavlov/core/trainers/fit_trainer.py", line 187, in test
    value = metric.fn(*[outputs[i] for i in metric.inputs])
TypeError: accuracy() takes 2 positional arguments but 5 were given

How does it need to be configured correctly with additional output data?