readme: ---
  language: zh
  pipeline_tag: sentence-similarity
  tags:
  - sentence-transformers
  - feature-extraction
  - sentence-similarity
  - transformers
  license: apache-2.0
  widget:
      source_sentence: "那个人很开心"
      sentences:
          - 那个人非常开心
          - 那只猫很开心
          - 那个人在吃东西
  ---
  
  # Chinese Sentence BERT
  
  ## Model description
  
  This is the sentence embedding model pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
  
  ## Training data
  
  [ChineseTextualInference](https://github.com/liuhuanyong/ChineseTextualInference/) is used as training data. 
  
  ## Training procedure
  
  The model is fine-tuned by [UER-py](https://github.com/dbiir/UER-py/) on [Tencent Cloud](https://cloud.tencent.com/). We fine-tune five epochs with a sequence length of 128 on the basis of the pre-trained model [chinese_roberta_L-12_H-768](https://huggingface.co/uer/chinese_roberta_L-12_H-768). At the end of each epoch, the model is saved when the best performance on development set is achieved.
  
  ```
  python3 finetune/run_classifier_siamese.py --pretrained_model_path models/cluecorpussmall_roberta_base_seq512_model.bin-250000 \
                                             --vocab_path models/google_zh_vocab.txt \
                                             --config_path models/sbert/base_config.json \
                                             --train_path datasets/ChineseTextualInference/train.tsv \
                                             --dev_path datasets/ChineseTextualInference/dev.tsv \
                                             --learning_rate 5e-5 --epochs_num 5 --batch_size 64
  ```
  
  Finally, we convert the pre-trained model into Huggingface's format:
  
  ```
  python3 scripts/convert_sbert_from_uer_to_huggingface.py --input_model_path models/finetuned_model.bin \                                                                
                                                           --output_model_path pytorch_model.bin \                                                                                            
                                                           --layers_num 12
  ```
  
  ### BibTeX entry and citation info
  
  ```
  @article{reimers2019sentence,
    title={Sentence-bert: Sentence embeddings using siamese bert-networks},
    author={Reimers, Nils and Gurevych, Iryna},
    journal={arXiv preprint arXiv:1908.10084},
    year={2019}
  }
  @article{zhao2019uer,
    title={UER: An Open-Source Toolkit for Pre-training Models},
    author={Zhao, Zhe and Chen, Hui and Zhang, Jinbin and Zhao, Xin and Liu, Tao and Lu, Wei and Chen, Xi and Deng, Haotang and Ju, Qi and Du, Xiaoyong},
    journal={EMNLP-IJCNLP 2019},
    pages={241},
    year={2019}
  }
  ```