Created by: zhu143xin

strategy = hub.AdamWeightDecayStrategy( warmup_proportion=args.warmup_proportion, weight_decay=args.weight_decay, learning_rate=args.learning_rate)

# Setup runing config for PaddleHub Finetune API
config = hub.RunConfig(
        eval_interval=args.eval_step,
        save_ckpt_interval=args.model_save_step,
        use_data_parallel=args.use_data_parallel,
        use_cuda=args.use_gpu,
        num_epoch=args.num_epoch,
        batch_size=args.batch_size,
        checkpoint_dir=args.checkpoint_dir,
        strategy=strategy)

# Define a sequence labeling finetune task by PaddleHub's API
# If add crf, the network use crf as decoder
seq_label_task = hub.SequenceLabelTask(
    data_reader=reader,
    feature=sequence_output,
    feed_list=feed_list,
    max_seq_len=args.max_seq_len,
    num_classes=dataset.num_labels,
    config=config,
    add_crf=args.add_crf)

以上是使用BERT+CRF进行序列标注任务，后续调用finetune_and_eval进行训练。想问一下能否自己单独设置CRF的学习率，让它与BERT不相同，目前没找到实现的方法