Questions tagged [bert]

For questions related to BERT (which stands for Bidirectional Encoder Representations from Transformers), a language representation model introduced in the paper "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding" (2019) by Google.

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2
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0answers
20 views

Can Bert be used to extract embedding for large categorical features?

I've lot of training data points (i.e in millions) and I've around few features but the issue with that is all the features are categorical data with 1 million+ categories in each. So, I couldn't use ...
0
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1answer
77 views

How to use pretrained checkpoints of BERT model on semantic text similarity task?

I am unaware to use the derived checkpoints from pre-trained BERT model for the task of semantic text similarity. ...
0
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0answers
85 views

How do I do further (domain-specific) pre-training with Google BERT in preparation for subsequent fine-tuning?

How do I do further (domain-specific) pre-training with Google BERT in preparation for subsequent fine-tuning? Another way to say this is: can you create a checkpoint file created from the final ...
2
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1answer
2k views

Adding BERT embeddings in LSTM embedding layer

I am planning to use BERT embeddings in the LSTM embedding layer instead of the usual Word2vec/Glove Embeddings. What are the possible ways to do that?
4
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1answer
72 views

Will BERT embedding be always same for a given document when used as a feature extractor

When we use BERT embeddings for a classification task, would we get different embeddings every time we pass the same text through the BERT architecture? If yes, is it the right way to use the ...
1
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0answers
87 views

How are the attention weights normalised in the transformer?

In the Transformer (adopted in BERT), we normalize the attention weights (dot product of keys and queries) using a softmax in the Scaled Dot-Product mechanism. It is unclear to me whether this ...
1
vote
1answer
41 views

Understanding how the loss was calculated for the SQuAD task in BERT paper

In the BERT paper, section 4.2 covers the SQuAD training. From my understanding, there are two extra parameters trained, they are two vectors with the same dimension as the hidden size, so the same ...
3
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0answers
101 views

How does bidirectional encoding allow the predicted word to indirectly “see itself”?

Before the release of BERT, we used to say that it is not possible to train bidirectional models by simply conditioning each word on its previous and next words, since this would allow the word that's ...
2
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0answers
34 views

How can I generate a document from a single word using GPT or BERT?

I have a dataset of 100000 documents each labelled with a topic to it. I want to create a model such that, given a topic, the model can generate a document from it. I came across language models GPT,...
1
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2answers
358 views

Is it a good idea to use BERT to answer a FAQ with semantic similarity?

I have been looking for BERT for many tasks. I would like to compare the performance to answer an FAQ, using BERT semantic similarity and BERT Q/A. However, I'm not sure it is a good idea to use ...
2
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0answers
103 views

Why does the BERT encoder have an intermediate layer between the attention and neural network layers with a bigger output?

I am reading the BERT paper BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. As I look at the attention mechanism, I don't understand why in the BERT encoder we have ...
1
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1answer
1k views

What are the segment embeddings and position embeddings in BERT?

They only reference in the paper that the position embeddings are learned, which is different from what was done in ELMo. ELMo paper - https://arxiv.org/pdf/1802.05365.pdf BERT paper - https://arxiv....
11
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3answers
9k views

Can BERT be used for sentence generating tasks?

I am a new learner in NLP. I am interested in the sentence generating task. As far as I am concerned, one state-of-the-art method is the CharRNN, which uses RNN to generate a sequence of words. ...
4
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2answers
449 views

Where can I find pre-trained language models in English and German?

Where can I find (more) pre-trained language models? I am especially interested in neural network-based models for English and German. I am aware only of Language Model on One Billion Word Benchmark ...