bert-large-cased-whole-word-masking-finetuned-squad

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3 languages
license:apache-2.0
by
google-bert
Language Model
OTHER
Fair
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Quick Summary

BERT large model (cased) whole word masking finetuned on SQuAD Pretrained model on English language using a masked language modeling (MLM) objective.

Code Examples

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Fine-tuningtext
python -m torch.distributed.launch --nproc_per_node=8 ./examples/question-answering/run_qa.py \
    --model_name_or_path bert-large-cased-whole-word-masking \
    --dataset_name squad \
    --do_train \
    --do_eval \
    --learning_rate 3e-5 \
    --num_train_epochs 2 \
    --max_seq_length 384 \
    --doc_stride 128 \
    --output_dir ./examples/models/wwm_cased_finetuned_squad/ \
    --per_device_eval_batch_size=3   \
    --per_device_train_batch_size=3   \
Fine-tuningtext
python -m torch.distributed.launch --nproc_per_node=8 ./examples/question-answering/run_qa.py \
    --model_name_or_path bert-large-cased-whole-word-masking \
    --dataset_name squad \
    --do_train \
    --do_eval \
    --learning_rate 3e-5 \
    --num_train_epochs 2 \
    --max_seq_length 384 \
    --doc_stride 128 \
    --output_dir ./examples/models/wwm_cased_finetuned_squad/ \
    --per_device_eval_batch_size=3   \
    --per_device_train_batch_size=3   \
Fine-tuningtext
python -m torch.distributed.launch --nproc_per_node=8 ./examples/question-answering/run_qa.py \
    --model_name_or_path bert-large-cased-whole-word-masking \
    --dataset_name squad \
    --do_train \
    --do_eval \
    --learning_rate 3e-5 \
    --num_train_epochs 2 \
    --max_seq_length 384 \
    --doc_stride 128 \
    --output_dir ./examples/models/wwm_cased_finetuned_squad/ \
    --per_device_eval_batch_size=3   \
    --per_device_train_batch_size=3   \
Fine-tuningtext
python -m torch.distributed.launch --nproc_per_node=8 ./examples/question-answering/run_qa.py \
    --model_name_or_path bert-large-cased-whole-word-masking \
    --dataset_name squad \
    --do_train \
    --do_eval \
    --learning_rate 3e-5 \
    --num_train_epochs 2 \
    --max_seq_length 384 \
    --doc_stride 128 \
    --output_dir ./examples/models/wwm_cased_finetuned_squad/ \
    --per_device_eval_batch_size=3   \
    --per_device_train_batch_size=3   \
Fine-tuningtext
python -m torch.distributed.launch --nproc_per_node=8 ./examples/question-answering/run_qa.py \
    --model_name_or_path bert-large-cased-whole-word-masking \
    --dataset_name squad \
    --do_train \
    --do_eval \
    --learning_rate 3e-5 \
    --num_train_epochs 2 \
    --max_seq_length 384 \
    --doc_stride 128 \
    --output_dir ./examples/models/wwm_cased_finetuned_squad/ \
    --per_device_eval_batch_size=3   \
    --per_device_train_batch_size=3   \
Fine-tuningtext
python -m torch.distributed.launch --nproc_per_node=8 ./examples/question-answering/run_qa.py \
    --model_name_or_path bert-large-cased-whole-word-masking \
    --dataset_name squad \
    --do_train \
    --do_eval \
    --learning_rate 3e-5 \
    --num_train_epochs 2 \
    --max_seq_length 384 \
    --doc_stride 128 \
    --output_dir ./examples/models/wwm_cased_finetuned_squad/ \
    --per_device_eval_batch_size=3   \
    --per_device_train_batch_size=3   \
Fine-tuningtext
python -m torch.distributed.launch --nproc_per_node=8 ./examples/question-answering/run_qa.py \
    --model_name_or_path bert-large-cased-whole-word-masking \
    --dataset_name squad \
    --do_train \
    --do_eval \
    --learning_rate 3e-5 \
    --num_train_epochs 2 \
    --max_seq_length 384 \
    --doc_stride 128 \
    --output_dir ./examples/models/wwm_cased_finetuned_squad/ \
    --per_device_eval_batch_size=3   \
    --per_device_train_batch_size=3   \
Fine-tuningtext
python -m torch.distributed.launch --nproc_per_node=8 ./examples/question-answering/run_qa.py \
    --model_name_or_path bert-large-cased-whole-word-masking \
    --dataset_name squad \
    --do_train \
    --do_eval \
    --learning_rate 3e-5 \
    --num_train_epochs 2 \
    --max_seq_length 384 \
    --doc_stride 128 \
    --output_dir ./examples/models/wwm_cased_finetuned_squad/ \
    --per_device_eval_batch_size=3   \
    --per_device_train_batch_size=3   \
BibTeX entry and citation infobibtex
@article{DBLP:journals/corr/abs-1810-04805,
  author    = {Jacob Devlin and
               Ming{-}Wei Chang and
               Kenton Lee and
               Kristina Toutanova},
  title     = {{BERT:} Pre-training of Deep Bidirectional Transformers for Language
               Understanding},
  journal   = {CoRR},
  volume    = {abs/1810.04805},
  year      = {2018},
  url       = {http://arxiv.org/abs/1810.04805},
  archivePrefix = {arXiv},
  eprint    = {1810.04805},
  timestamp = {Tue, 30 Oct 2018 20:39:56 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1810-04805.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
BibTeX entry and citation infobibtex
@article{DBLP:journals/corr/abs-1810-04805,
  author    = {Jacob Devlin and
               Ming{-}Wei Chang and
               Kenton Lee and
               Kristina Toutanova},
  title     = {{BERT:} Pre-training of Deep Bidirectional Transformers for Language
               Understanding},
  journal   = {CoRR},
  volume    = {abs/1810.04805},
  year      = {2018},
  url       = {http://arxiv.org/abs/1810.04805},
  archivePrefix = {arXiv},
  eprint    = {1810.04805},
  timestamp = {Tue, 30 Oct 2018 20:39:56 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1810-04805.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
BibTeX entry and citation infobibtex
@article{DBLP:journals/corr/abs-1810-04805,
  author    = {Jacob Devlin and
               Ming{-}Wei Chang and
               Kenton Lee and
               Kristina Toutanova},
  title     = {{BERT:} Pre-training of Deep Bidirectional Transformers for Language
               Understanding},
  journal   = {CoRR},
  volume    = {abs/1810.04805},
  year      = {2018},
  url       = {http://arxiv.org/abs/1810.04805},
  archivePrefix = {arXiv},
  eprint    = {1810.04805},
  timestamp = {Tue, 30 Oct 2018 20:39:56 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1810-04805.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
BibTeX entry and citation infobibtex
@article{DBLP:journals/corr/abs-1810-04805,
  author    = {Jacob Devlin and
               Ming{-}Wei Chang and
               Kenton Lee and
               Kristina Toutanova},
  title     = {{BERT:} Pre-training of Deep Bidirectional Transformers for Language
               Understanding},
  journal   = {CoRR},
  volume    = {abs/1810.04805},
  year      = {2018},
  url       = {http://arxiv.org/abs/1810.04805},
  archivePrefix = {arXiv},
  eprint    = {1810.04805},
  timestamp = {Tue, 30 Oct 2018 20:39:56 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1810-04805.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
BibTeX entry and citation infobibtex
@article{DBLP:journals/corr/abs-1810-04805,
  author    = {Jacob Devlin and
               Ming{-}Wei Chang and
               Kenton Lee and
               Kristina Toutanova},
  title     = {{BERT:} Pre-training of Deep Bidirectional Transformers for Language
               Understanding},
  journal   = {CoRR},
  volume    = {abs/1810.04805},
  year      = {2018},
  url       = {http://arxiv.org/abs/1810.04805},
  archivePrefix = {arXiv},
  eprint    = {1810.04805},
  timestamp = {Tue, 30 Oct 2018 20:39:56 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1810-04805.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
BibTeX entry and citation infobibtex
@article{DBLP:journals/corr/abs-1810-04805,
  author    = {Jacob Devlin and
               Ming{-}Wei Chang and
               Kenton Lee and
               Kristina Toutanova},
  title     = {{BERT:} Pre-training of Deep Bidirectional Transformers for Language
               Understanding},
  journal   = {CoRR},
  volume    = {abs/1810.04805},
  year      = {2018},
  url       = {http://arxiv.org/abs/1810.04805},
  archivePrefix = {arXiv},
  eprint    = {1810.04805},
  timestamp = {Tue, 30 Oct 2018 20:39:56 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1810-04805.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
BibTeX entry and citation infobibtex
@article{DBLP:journals/corr/abs-1810-04805,
  author    = {Jacob Devlin and
               Ming{-}Wei Chang and
               Kenton Lee and
               Kristina Toutanova},
  title     = {{BERT:} Pre-training of Deep Bidirectional Transformers for Language
               Understanding},
  journal   = {CoRR},
  volume    = {abs/1810.04805},
  year      = {2018},
  url       = {http://arxiv.org/abs/1810.04805},
  archivePrefix = {arXiv},
  eprint    = {1810.04805},
  timestamp = {Tue, 30 Oct 2018 20:39:56 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1810-04805.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
BibTeX entry and citation infobibtex
@article{DBLP:journals/corr/abs-1810-04805,
  author    = {Jacob Devlin and
               Ming{-}Wei Chang and
               Kenton Lee and
               Kristina Toutanova},
  title     = {{BERT:} Pre-training of Deep Bidirectional Transformers for Language
               Understanding},
  journal   = {CoRR},
  volume    = {abs/1810.04805},
  year      = {2018},
  url       = {http://arxiv.org/abs/1810.04805},
  archivePrefix = {arXiv},
  eprint    = {1810.04805},
  timestamp = {Tue, 30 Oct 2018 20:39:56 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1810-04805.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

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