( Embedding层 的参数数量太大,没有办法很好的训练,会有过拟合的问题)或者进行预训练来改进 3.3 Multi-Task Learning(多任务学习) 把英语翻译成德语是一个任务,还可以多添加几个任务:比如把英语句子翻译成英语句子本身,添加一个Decoder,根据(h,c)生成英语句子,这样一来Encoder只有一个,而训练数据多了一倍,所以Enc...
NSP,Next Sentence Prediction。许多重要的下游任务譬如QA、NLI需要语言模型理解两个句子之间的关系,而传统的语言模型在训练的过程没有考虑句对关系的学习。NSP,预测下一句模型,增加对句子A和B关系的预测任务,50%的时间里B是A的下一句,分类标签为IsNext,另外50%的时间里B是随机挑选的句子,并不是A的下一句,分类标...
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Automatically translates input text in German to output text in English using advanced Deep Learning and Neural NLP. Consumes 1-2 API calls per input sentence. Translate Russian to English text with Deep Learning AI Automatically translates input text in Russian to output text in English using ad...
we will get the positive label and this is the training set. then, we would build classifiers on top of this training set, and once the learning is done we will try to predict the values on top of the test set and see whether the prediction is correct. now, we will start off by ...
在预训练任务上,GPT使用了单向的语言模型任务,即给定前文生成下一个单词,而Bert则利用了双向的语言模型任务,包括了Masked Language Model(MLM)和Next Sentence Prediction(NSP)。 在应用上,由于架构和预训练任务的不同,GPT通常用于生成式任务,如文本生成、对话生成等,而Bert则更适用于各种下游任务的特征提取和Fine-...
I will introduce our recent progress in self-supervised learning on audio and emotional speech data, by introducing utterance and frame-level joint learning, we could achieve significant performance improvement in audio classification and speech emotion recogn...
NLP chatbots can boost customer support and service efficiency by giving fast, accurate, round-the-clock replies to your shoppers’ queries and concerns.Chatbotscan do that due to their machine learning capabilities, augmented with fundamental meaning. ...
Machine Learning, A powerful tool, With algorithms, That can rule. I’m not a poet, but I’ll give it a try. Introduction Machine learning is a powerful tool that can be used to solve a wide range of problems. It is a subset of artificial intelligence that focuses on the development...
Parameter-Efficient Transfer Learning for NLP 2019.2.2 在Multi-head attention层后和FFN层后都加了一个adapter,通过残差连接和down-project & up-project(减少adapter的参数量)实现。 效果不是很好,一般是拿来对比的对象。 Prefix-Tuning方法 背景:无非是说finetune的计算量太大以及prefix是怎么做的。下面展示了pre...