nlp - Is it OK to combine domain specific word2vec embeddings and off the shelf ELMo embeddings for a downstream unsupervised task?

Question

I am wondering if I am using word embeddings correctly.

I have combined contextualised word vectors with static word vectors because:

• my domain corpus is too small to effectively train the model from scratch
• my domain is too specialised to use general embeddings.

I used the off the shelf ELMo small model and trained word2vec model on a small domain specific corpus (around 500 academic papers). I then did a simple concatenation of the vectors from the two different embeddings.

I loosely followed the approach in this paper: https://www.aclweb.org/anthology/P19-2041.pdf But the approach in the paper trains the embeddings for a specific task. In my domain there is no labeled training data. Hence me just training the embeddings on the corpus alone.

I am new to NLP, so apologies if I am asking a stupid question.

question from:https://stackoverflow.com/questions/65842724/is-it-ok-to-combine-domain-specific-word2vec-embeddings-and-off-the-shelf-elmo-e

Answer 1

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