Comments (2)
fine tune的时候是句对数据(text_a,text_b,label),如何用Bert_base预测两个句子的相似度?bert_client的输入是什么?
您好,不知道您这个问题有没有解决,其实bert-as-server应该是可以解决这个问题的,因为他可以输出一段文字的feature,然后你可以自己再加一个相似性计算的处理,那就可以完成你上面说的功能了
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我看过了代码,其实text_a和text_b通过“ ||| ”拼成一个文本输入bert_base,当作一个分类任务来微调训练,所以预测的时候,两个句子也这样拼接输入,就可以得到二分类的相似性了。
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Related Issues (20)
- 请假一下,如何显示各个类别的分类质量比如f1score等
- 请问下怎么设置CPU部署
- freeze_graph.py的问题2 HOT 4
- 评测代码是有问题的 HOT 2
- 用自己训练好的模型转换成pd文件后,启动ner服务报错 HOT 3
- ImportError: No module named six HOT 1
- 运行bert_base_serving_start时出错 HOT 4
- 请问,如果想输出每个标签对应的score,应该怎么修改呢 HOT 2
- 我的是英文NER的BERT模型,东西大同小异,但是我在用freeze_.graph.py的时候出现了如下问题,想请教下您会吗 HOT 2
- 这个方法有啥用
- label2id文件训练时没有生成,是否需要重新训练 HOT 1
- 同一机器开启多个服务时卡住
- 预测很慢
- 模型服务端部署完成之后,通过调用端口进行测试,发现项目下面生成了很多tmp文件夹,有什么方法不生成吗 HOT 2
- 您好,生成的label2id 文件为什么是空的
- 服务端接受数据后无处理结果反馈 HOT 1
- 服务端接收请求后无响应
- 使用TensorFlow-gpu会报错,但使用TensorFlow-cpu不会
- 为什么预测的时候加载的不是训练后的模型,而是加载的bert_model.ckpt呢
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