Longformer BigBird

Date Tags NLP

allenai/longformer-large-4096

epoch 3

with pretrained Lead 0.7826552462526767 Position 0.6857142857142857 Claim 0.6016325707951224 Evidence 0.6062992125984252 Concluding Statement 0.7744827586206896 Counterclaim 0.5159301130524152 Rebuttal 0.43537414965986393

Overall 0.6288697623847826

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epoch4

witout pretrained Lead 0.7926960257787325 Position 0.6743119266055045 Claim 0.5527019174898314 Evidence 0.6058080479229067 Concluding Statement 0.7251962883654532 Counterclaim 0.4868686868686869 Rebuttal 0.39381153305203936

Overall 0.6044849180118792

with pretrained Lead 0.7948164146868251 Position 0.6745484400656815 Claim 0.5881818181818181 Evidence 0.5861433087460485 Concluding Statement 0.7867698803659395 Counterclaim 0.5420207743153919 Rebuttal 0.43478260869565216

Overall 0.6296090350081938

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epoch5

witout pretrained Lead 0.7926565874730022 Position 0.6712629269821373 Claim 0.5932255111382362 Evidence 0.6297068563718876 Concluding Statement 0.7207586933614331 Counterclaim 0.48604860486048607 Rebuttal 0.42297650130548303

Overall 0.6166622402132379 online: 0.612

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Bert as Service

Date Tags NLP

git clone git@github.com:hanxiao/bert-as-service.git

https://bert-as-service.readthedocs.io/en/latest/section/get-start.html#start-the-bert-service-in-a-docker-container

docker build -t bert-as-service -f ./docker/Dockerfile .

docker run --runtime nvidia -itd -p 8022:5555 -p 8021:5556 -v /bert-as-service/server/model/:/model -t bert-as-service 1 128

usage: /usr/local/bin/bert-serving-start -http_port 8125 -num_worker=4 -max_seq_len=64 -max_batch_size=512 -model_dir /model
                 ARG   VALUE
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           ckpt_name = bert_model.ckpt
         config_name = bert_config.json
                cors = *
                 cpu = False
          device_map = []
       do_lower_case = True
  fixed_embed_length = False
                fp16 = False
 gpu_memory_fraction = 0.5
       graph_tmp_dir = None
    http_max_connect = 10
           http_port = 8125
        mask_cls_sep = False
      max_batch_size = 512
         max_seq_len = 64
           model_dir = /model
no_position_embeddings = False
    no_special_token = False
          num_worker = 4
       pooling_layer = [-2]
    pooling_strategy = REDUCE_MEAN
                port = 5555
            port_out = 5556
       prefetch_size = 10
 priority_batch_size = 16
show_tokens_to_client = False
     tuned_model_dir = None
             verbose = False
                 xla = False
                    more ...