text: """Sentiment evaluation of a language model on the TwitterSent dataset"""
  
  import logging
  
  from .abstract import TextClassificationBenchmark
  
  
  logger = logging.getLogger(__name__)
  
  
  class TwitterSentBenchmark(TextClassificationBenchmark):
      """Benchmark of language models on the TwitterSent dataset.
  
      Args:
          cache_dir (str, optional):
              Where the downloaded models will be stored. Defaults to
              '.benchmark_models'.
          evaluate_train (bool, optional):
              Whether the models should be evaluated on the training scores.
              Defaults to False.
          verbose (bool, optional):
              Whether to print additional output during evaluation. Defaults to
              False.
  
      Attributes:
          name (str): The name of the dataset.
          task (str): The type of task to be benchmarked.
          metric_names (dict): The names of the metrics.
          id2label (dict or None): A dictionary converting indices to labels.
          label2id (dict or None): A dictionary converting labels to indices.
          num_labels (int or None): The number of labels in the dataset.
          label_synonyms (list of lists of str): Synonyms of the dataset labels.
          evaluate_train (bool): Whether the training set should be evaluated.
          cache_dir (str): Directory where models are cached.
          two_labels (bool): Whether two labels should be predicted.
          split_point (int or None): Splitting point of `id2label` into labels.
          verbose (bool): Whether to print additional output.
      """
  
      def __init__(
          self,
          cache_dir: str = ".benchmark_models",
          evaluate_train: bool = False,
          verbose: bool = False,
      ):
          id2label = ["negative", "neutral", "positive"]
          label_synonyms = [
              ["LABEL_0", "negativ", "neikvætt", "Negative", id2label[0]],
              ["LABEL_1", "nøytral", "hlutlaus", "Neutral", id2label[1]],
              ["LABEL_2", "positiv", "jákvætt", "Positive", id2label[2]],
          ]
          super().__init__(
              name="twitter-sent",
              id2label=id2label,
              label_synonyms=label_synonyms,
              cache_dir=cache_dir,
              evaluate_train=evaluate_train,
              verbose=verbose,
          )
  