class_docstr: Reader especially for the STS benchmark dataset. There, the sentences are in column 5 and 6, the score is in column 4.
  Scores are normalized from 0...5 to 0...1
code: def __init__(
      self,
      dataset_folder,
      s1_col_idx=5,
      s2_col_idx=6,
      score_col_idx=4,
      delimiter="\t",
      quoting=csv.QUOTE_NONE,
      normalize_scores=True,
      min_score=0,
      max_score=5,
  ):
      super().__init__(
          dataset_folder=dataset_folder,
          s1_col_idx=s1_col_idx,
          s2_col_idx=s2_col_idx,
          score_col_idx=score_col_idx,
          delimiter=delimiter,
          quoting=quoting,
          normalize_scores=normalize_scores,
          min_score=min_score,
          max_score=max_score,
      )
  
file_path: sentence-transformers/sentence_transformers/readers/STSDataReader.py
imports: from .None import InputExample
  import csv
  import gzip
  import os
label_desc: Use image node_id 1 to create a new STSBenchmarkDataReader object from inherited base classes: STSDataReader with example: obj = STSBenchmarkDataReader(dataset_folder, s1_col_idx, s2_col_idx, score_col_idx, delimiter, quoting, normalize_scores, min_score, max_score)