class_docstr: Learner for Sequence Taggers.
class_docstr_tok: ["Learner","for","Sequence","Taggers","."]
code: def __init__(
      self,
      model,
      train_data=None,
      val_data=None,
      batch_size=U.DEFAULT_BS,
      eval_batch_size=U.DEFAULT_BS,
      workers=1,
      use_multiprocessing=False,
  ):
      super().__init__(
          model,
          train_data=train_data,
          val_data=val_data,
          batch_size=batch_size,
          eval_batch_size=eval_batch_size,
          workers=workers,
          use_multiprocessing=use_multiprocessing,
      )
      return
  
file_path: ktrain/ktrain/text/ner/learner.py
imports: from ...None import utils
  from ...core import GenLearner
  from ...imports import *
  from .None import metrics
label_desc: Use image node_id 1 to create a new NERLearner object from inherited base classes: GenLearner with example: obj = NERLearner(model, train_data, val_data, batch_size, eval_batch_size, workers, use_multiprocessing)