class_docstr: Question-Answering-based Information Extraction
class_docstr_tok: ["Question-Answering-based","Information","Extraction"]
docstr: ```
  Finetune a QA model.
  
  Args:
    data(list): list of dictionaries of the form:
                [{'question': 'What is ktrain?'
                 'context': 'ktrain is a low-code library for augmented machine learning.'
                 'answer': 'ktrain'}]
    epochs(int): number of epochs.  Default:3
    learning_rate(float): learning rate.  Default: 2e-5
    batch_size(int): batch size. Default:8
    max_seq_length(int): maximum sequence length.  Default:512
  Returns:
    None
  ```
docstr_tok: ["``","`","Finetune","a","QA","model",".","Args",":","data","(","list",")",":","list","of","dictionaries","of","the","form",":","[","{","'question","'",":","'What","is","ktrain","?","'","'context","'",":","'ktrain","is","a","low-code","library","for","augmented","machine","learning",".","'","'answer","'",":","'ktrain","'","}","]","epochs","(","int",")",":","number","of","epochs",".","Default:3","learning_rate","(","float",")",":","learning","rate",".","Default",":","2e-5","batch_size","(","int",")",":","batch","size",".","Default:8","max_seq_length","(","int",")",":","maximum","sequence","length",".","Default:512","Returns",":","None","``","`"]
code: def finetune(
      self,
      data,
      epochs=3,
      learning_rate=2e-5,
      batch_size=8,
      max_seq_length=512,
  ):
      """
      ```
      Finetune a QA model.
  
      Args:
        data(list): list of dictionaries of the form:
                    [{'question': 'What is ktrain?'
                     'context': 'ktrain is a low-code library for augmented machine learning.'
                     'answer': 'ktrain'}]
        epochs(int): number of epochs.  Default:3
        learning_rate(float): learning rate.  Default: 2e-5
        batch_size(int): batch size. Default:8
        max_seq_length(int): maximum sequence length.  Default:512
      Returns:
        None
      ```
      """
      if self.qa.framework != "tf":
          raise ValueError(
              'The finetune method does not currently support the framework="pt" option. Please use framework="tf" to finetune.'
          )
      from .qa_finetuner import QAFineTuner
  
      ft = QAFineTuner(self.qa.model, self.qa.tokenizer)
      model = ft.finetune(
          data,
          epochs=epochs,
          learning_rate=learning_rate,
          batch_size=batch_size,
      )
      return
  
imports: from transformers import AutoModelForQuestionAnswering, AutoTokenizer, TFAutoModelForQuestionAnswering
  from whoosh import index, qparser
  from whoosh.fields import *
  from whoosh.qparser import QueryParser
  from ...None import utils
  from ...imports import *
  from ...torch_base import TorchBase
  from ..None import preprocessor
  from ..None import textutils
  from itertools import chain, zip_longest
label_desc: Use image node_id 5 for calling the AnswerExtractor obj's underlying member method code with example usage: obj.finetune(data, epochs, learning_rate, batch_size, max_seq_length) without return types