PYTHONPATH=. python examples/pytorch/named_entity_recognition/finetune_named_entity_recognition.py \
    --task 'named-entity-recognition' \
    --work_dir './tmp' \
    --model_type 'sequence-labeling-model' \
    --model 'damo/nlp_structbert_backbone_base_std' \
    --dropout 0.1 \
    --use_crf true \
    --train_dataset_name 'resume_ner' \
    --train_dataset_namespace 'damo' \
    --train_split 'train' \
    --val_dataset_name 'resume_ner' \
    --val_dataset_namespace 'damo' \
    --val_split 'dev' \
    --preprocessor 'sequence-labeling-preprocessor' \
    --sequence_length 150 \
    --data_collator 'SequenceLabelingDataCollatorWithPadding' \
    --max_epochs 5 \
    --per_device_train_batch_size 16 \
    --train_data_worker 0 \
    --eval_data_worker 0 \
    --lr 5.0e-5 \
    --lr_scheduler LinearLR \
    --lr_scheduler_params 'start_factor=1.0,end_factor=0.0,total_iters=5' \
    --eval_metrics ner-metric \
    --save_best_checkpoint true \
    --metric_for_best_model f1 \