A PyTorch implementation of unsupervised SimCSE

Related tags

Deep Learningnlppytorchchinesesentence-embeddings
Overview

A PyTorch implementation of unsupervised SimCSE

SimCSE: Simple Contrastive Learning of Sentence Embeddings

1. 用法

无监督训练

python train_unsup.py ./data/news_title.txt ./path/to/huggingface_pretrained_model

详细参数

python train_unsup.py -h

相似文本检索测试

python test_unsup.py
query title:
基金亏损路未尽 后市看法仍偏谨慎

sim title:
基金亏损路未尽 后市看法仍偏谨慎
海通证券：私募对后市看法偏谨慎
连塑基本面不容乐观 后市仍有下行空间
基金谨慎看待后市行情
稳健投资者继续保持观望 市场走势还未明朗
下半年基金投资谨慎乐观
华安基金许之彦：下半年谨慎乐观
楼市主导 期指后市不容乐观
基金公司谨慎看多明年市
前期乐观预期被否 基金重归谨慎

STS-B数据集训练和测试

中文STS-B数据集，详情见这里

# 训练
python train_unsup.py ./data/STS-B/cnsd-sts-train_unsup.txt

# 验证
python eval_unsup.py
模型 STS-B dev STS-B test
hfl/chinese-bert-wwm-ext 0.3326 0.3209
simcse 0.7499 0.6909

与苏剑林的实验结果接近，BERT-P1是0.3465，SIMCSE是0.6904

2. 参考

Owner
GitHub Repository
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