Traceback (most recent call last):


 "scoring.py", line 96, in <module>

clf.fit(X_train, y_train)


 "/usr/local/lib/python2.7/dist-packages/sklearn/multiclass.py", line 205, in fit

Y = self.label_binarizer_.fit_transform(y)


 "/usr/local/lib/python2.7/dist-packages/sklearn/base.py", line 494, in fit_transform

return self.fit(X, **fit_params).transform(X)


 "/usr/local/lib/python2.7/dist-packages/sklearn/preprocessing/label.py", line 296, in fit

self.y_type_ = type_of_target(y)


 "/usr/local/lib/python2.7/dist-packages/sklearn/utils/multiclass.py", line 250, in type_of_target

raise ValueError('You appear to be using a legacy multi-label data'
ValueError: You appear to be using a legacy multi-label data representation. Sequence of sequences are no longer supported; use a binary array or sparse matrix instead.

Traceback (most recent call last):


 "/home/a-ware/anaconda3/envs/transformers/lib/python3.8/multiprocessing/pool.py", line 125, in worker

result = (True, func(*args, **kwds))


 "/home/a-ware/anaconda3/envs/transformers/lib/python3.8/multiprocessing/pool.py", line 48, in mapstar

return list(map(*args))


 "/home/a-ware/anaconda3/envs/transformers/lib/python3.8/site-packages/transformers/data/processors/squad.py", line 199, in squad_convert_example_to_features

cls_index = span["input_ids"].index(tokenizer.cls_token_id)
ValueError: None is not in list
