Bert-Multi-Label-Text-Classification：此存储库包含用于多标签文本分类的预训练BERT模型的PyTorch实现-源码

[{"title":"（ 86 个子文件 154KB ） Bert-Multi-Label-Text-Classification：此存储库包含用于多标签文本分类的预训练BERT模型的PyTorch实现-源码","children":[{"title":"Bert-Multi-Label-Text-Classification-master","children":[{"title":"Pipfile <span style='color:#111;'> 253B </span>","children":null,"spread":false},{"title":"LICENSE <span style='color:#111;'> 1.04KB </span>","children":null,"spread":false},{"title":"run_bert.py <span style='color:#111;'> 11.90KB </span>","children":null,"spread":false},{"title":"pybert","children":[{"title":"train","children":[{"title":"metrics.py <span style='color:#111;'> 9.22KB </span>","children":null,"spread":false},{"title":"losses.py <span style='color:#111;'> 643B </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":"trainer.py <span style='color:#111;'> 7.77KB </span>","children":null,"spread":false}],"spread":true},{"title":"model","children":[{"title":"albert_for_multi_label.py <span style='color:#111;'> 808B </span>","children":null,"spread":false},{"title":"albert","children":[{"title":"tokenization_utils.py <span style='color:#111;'> 53.58KB </span>","children":null,"spread":false},{"title":"modeling_bert.py <span style='color:#111;'> 58.25KB </span>","children":null,"spread":false},{"title":"configuration_bert.py <span style='color:#111;'> 3.88KB </span>","children":null,"spread":false},{"title":"modeling_albert.py <span style='color:#111;'> 58.21KB </span>","children":null,"spread":false},{"title":"tokenization_albert.py <span style='color:#111;'> 11.20KB </span>","children":null,"spread":false},{"title":"configuration_utils.py <span style='color:#111;'> 10.31KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":"tokenization_bert.py <span style='color:#111;'> 18.08KB </span>","children":null,"spread":false},{"title":"configuration_albert.py <span style='color:#111;'> 3.91KB </span>","children":null,"spread":false},{"title":"file_utils.py <span style='color:#111;'> 10.29KB </span>","children":null,"spread":false},{"title":"modeling_albert_bright.py <span style='color:#111;'> 52.20KB </span>","children":null,"spread":false},{"title":"modeling_utils.py <span style='color:#111;'> 38.59KB </span>","children":null,"spread":false}],"spread":false},{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":"bert_for_multi_label.py <span style='color:#111;'> 1.65KB </span>","children":null,"spread":false},{"title":"xlnet_for_multi_label.py <span style='color:#111;'> 1.15KB </span>","children":null,"spread":false}],"spread":true},{"title":"test","children":[{"title":"predictor.py <span style='color:#111;'> 1.13KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false}],"spread":true},{"title":"pretrain","children":[{"title":"albert","children":[{"title":"albert-base","children":[{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"bert","children":[{"title":"base-uncased","children":[{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":"xlnet","children":[{"title":"base-cased","children":[{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true},{"title":"preprocessing","children":[{"title":"augmentation.py <span style='color:#111;'> 1.13KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":"preprocessor.py <span style='color:#111;'> 7.31KB </span>","children":null,"spread":false}],"spread":true},{"title":"output","children":[{"title":"log","children":[{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false}],"spread":true},{"title":"result","children":[{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false}],"spread":true},{"title":"feature","children":[{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false}],"spread":true},{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":"checkpoints","children":[{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false}],"spread":false},{"title":"figure","children":[{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false}],"spread":false},{"title":"embedding","children":[{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"dataset","children":[{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false}],"spread":true},{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":"io","children":[{"title":"utils.py <span style='color:#111;'> 1.11KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":"bert_processor.py <span style='color:#111;'> 8.37KB </span>","children":null,"spread":false},{"title":"xlnet_processor.py <span style='color:#111;'> 8.77KB </span>","children":null,"spread":false},{"title":"albert_processor.py <span style='color:#111;'> 8.27KB </span>","children":null,"spread":false},{"title":"vocabulary.py <span style='color:#111;'> 4.75KB </span>","children":null,"spread":false},{"title":"task_data.py <span style='color:#111;'> 2.86KB </span>","children":null,"spread":false}],"spread":true},{"title":"common","children":[{"title":"tools.py <span style='color:#111;'> 11.14KB </span>","children":null,"spread":false}],"spread":false},{"title":"configs","children":[{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":"basic_config.py <span style='color:#111;'> 1.15KB </span>","children":null,"spread":false}],"spread":false},{"title":"callback","children":[{"title":"modelcheckpoint.py <span style='color:#111;'> 4.24KB </span>","children":null,"spread":false},{"title":"lr_schedulers.py <span style='color:#111;'> 21.70KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":"progressbar.py <span style='color:#111;'> 2.03KB </span>","children":null,"spread":false},{"title":"trainingmonitor.py <span style='color:#111;'> 2.34KB </span>","children":null,"spread":false},{"title":"earlystopping.py <span style='color:#111;'> 3.03KB </span>","children":null,"spread":false},{"title":"optimizater","children":[{"title":"sgdw.py <span style='color:#111;'> 3.36KB </span>","children":null,"spread":false},{"title":"ralars.py <span style='color:#111;'> 5.00KB </span>","children":null,"spread":false},{"title":"adabound.py <span style='color:#111;'> 5.67KB </span>","children":null,"spread":false},{"title":"lamb.py <span style='color:#111;'> 4.47KB </span>","children":null,"spread":false},{"title":"adamw.py <span style='color:#111;'> 4.18KB </span>","children":null,"spread":false},{"title":"radam.py <span style='color:#111;'> 3.77KB </span>","children":null,"spread":false},{"title":"novograd.py <span style='color:#111;'> 3.19KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"lars.py <span style='color:#111;'> 3.62KB </span>","children":null,"spread":false},{"title":"nadam.py <span style='color:#111;'> 3.87KB </span>","children":null,"spread":false},{"title":"lookahead.py <span style='color:#111;'> 4.40KB </span>","children":null,"spread":false},{"title":"ralamb.py <span style='color:#111;'> 4.15KB </span>","children":null,"spread":false},{"title":"adafactor.py <span style='color:#111;'> 7.77KB </span>","children":null,"spread":false},{"title":"planradam.py <span style='color:#111;'> 2.56KB </span>","children":null,"spread":false}],"spread":false}],"spread":false}],"spread":false},{"title":"__init__.py <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":".idea","children":[{"title":"misc.xml <span style='color:#111;'> 174B </span>","children":null,"spread":false},{"title":"vcs.xml <span style='color:#111;'> 180B </span>","children":null,"spread":false},{"title":"deployment.xml <span style='color:#111;'> 855B </span>","children":null,"spread":false},{"title":"modules.xml <span style='color:#111;'> 535B </span>","children":null,"spread":false},{"title":"encodings.xml <span style='color:#111;'> 138B </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 39B </span>","children":null,"spread":false},{"title":"Bert-Multi-Label-Text-Classification.iml <span style='color:#111;'> 561B </span>","children":null,"spread":false},{"title":"inspectionProfiles","children":[{"title":"profiles_settings.xml <span style='color:#111;'> 174B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"run_albert.py <span style='color:#111;'> 11.70KB </span>","children":null,"spread":false},{"title":"requirements.txt <span style='color:#111;'> 485B </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 1.17KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 4.69KB </span>","children":null,"spread":false},{"title":"run_xlnet.py <span style='color:#111;'> 11.77KB </span>","children":null,"spread":false},{"title":"predict_one.py <span style='color:#111;'> 1.26KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]