Xlnet doesn't suport use_biaffine

[yonghuiwuf]

python src/run_transformer_ner.py
--model_type xlnet
--pretrained_model xlnet-base-cased
--data_dir ./test_data/conll-2003
--new_model_dir ./new_bert_ner_model
--overwrite_model_dir
--predict_output_file ./bert_pred.txt
--max_seq_length 256
--save_model_core
--do_train
--do_predict
--model_selection_scoring strict-f_score-1
--do_lower_case
--train_batch_size 8
--eval_batch_size 8
--train_steps 500
--learning_rate 1e-5
--num_train_epochs 1
--gradient_accumulation_steps 1
--do_warmup
--seed 13
--warmup_ratio 0.1
--max_num_checkpoints 3
--log_file ./log.txt
--progress_bar
--early_stop 3

Traceback (most recent call last):
File "/data/datasets/yonghui/project/ClinicalTransformerNER/src/run_transformer_ner.py", line 169, in main
run_task(global_args)
File "/data/datasets/yonghui/project/ClinicalTransformerNER/src/transformer_ner/task.py", line 604, in run_task
model = model_model.from_pretrained(args.pretrained_model, config=config)
File "/home/yonghui.wu/.pyenv/versions/anaconda3-2021.11/lib/python3.9/site-packages/transformers/modeling_utils.py", line 2024, in from_pretrained
model = cls(config, *model_args, **model_kwargs)
File "/data/datasets/yonghui/project/ClinicalTransformerNER/src/transformer_ner/model.py", line 308, in init
if config.use_biaffine:
File "/home/yonghui.wu/.pyenv/versions/anaconda3-2021.11/lib/python3.9/site-packages/transformers/configuration_utils.py", line 253, in getattribute
return super().getattribute(key)
AttributeError: 'XLNetConfig' object has no attribute 'use_biaffine'

[bugface]

we need to revisit XLNet, the implementation has problems where the performances are very low consistently cross different datasets. So the new features are not integrated with XLNet.