2019Cail-A-Bert-Joint-Baseline-for-Machine-Comprehension
(2019 法研杯 阅读理解) A pytorch implement of bert joint baseline for machine comprehension task in 2019 cail
파일 탐색기
최종 버전 다운로드 (.zip)- args.cpython-36.pyc
- args.py
- dev.json
- small_train_data.json
- test.json
- train.json
- acc_f1.cpython-36.pyc
- loss.cpython-36.pyc
- acc_f1.py
- loss.py
- data_loader.cpython-36.pyc
- data_loader.py
- main.cpython-36.pyc
- main.py
- qa_extract.cpython-36.pyc
- qa_extract.py
- loss_acc.png
- all.log
- predict.cpython-36.pyc
- predict.py
- data_processor.cpython-36.pyc
- data_processor.py
- bert_config.json
- vocab.txt
- file_utils.cpython-36.pyc
- modeling.cpython-36.pyc
- tokenization.cpython-36.pyc
- file_utils.py
- modeling.py
- optimization.py
- tokenization.py
- train.cpython-36.pyc
- train.py
- Logginger.cpython-36.pyc
- model_util.cpython-36.pyc
- plot_util.cpython-36.pyc
- porgress_util.cpython-36.pyc
- Logginger.py
- model_util.py
- plot_util.py
- porgress_util.py
- main.py
- run_qa_extract.py
- test.py
- train_start.py
- README.md
// repository documentation
Was this content helpful?
(0 ratings)