mutistage-learning

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Hanlard / Electra_CRF_NER
We start a company-name recognition task with a small scale and low quality training data, then using skills to enhanced model training speed and predicting performance with least artificial participation. The methods we use involve lite pre-training models such as Albert-small or Electra-small with financial corpus, knowledge of distillation and multi-stage learning. The result is that we improve the recall rate of company names recognition task from 0.73 to 0.92 and get 4 times as fast as BERT-Bilstm-CRF model.
ner bert financial distilling-the-knowledge pre-trained-language-models mutistage-learning
Language:Python 81

Hanlard / Electra_CRF_NER