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Compared with CBOW, skip-gram and GloVe, what is the effect of embedding words with BERT? I think it's a very interesting question.
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I try to run this:
```
model = fasttext.train_unsupervised(
Common.get_config('ai/fasttext/database', ''),
model='cbow',
lr=0.1,
epoch=40,
neg=10,
wordNgrams=3,…
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cbow 和 skip-gram 两种方式从代码角度来看，基本求解方式一致
cbow: 窗口内词取平均来预测目标词
skip-gram: 一个词循环预测多个目标词(窗口词)
区别：cbow比sg训练快，sg比cbow更好地处理生僻字（出现频率低的字）
优化算法: hierarchical softmax(优化每个非叶子节点，树上多个二分类) 和 negative sample (二分类)
…
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# [밑바닥2] 3장 word2vec - Done is better than perfect
추론 기반 기법과 신경망, word2vec, CBOW
[https://betterjeong.github.io/nlp/23122001/](https://betterjeong.github.io/nlp/23122001/)
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Hi, as far as I can see the embedding layer should be the vocab_size as input. But in cbow_model.py of Keras
shared_embedding_layer = Embedding(input_dim=(G.vocab_size+3), output_dim=G.embedding_d…
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In 1.0.0-beta4, I run ParagraphVectorsTextExample test App, and report:
o.d.m.e.i.InMemoryLookupTable - Initializing syn1...
o.d.m.s.SequenceVectors - Building learning algorithms:
o.d.m.s.Sequence…
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#### Problem description
I need to weight my data in training. The Gensim API does not currently provide this functionality.
#### Proposed solution
I'm pretty sure adding a `sample_weight` a…
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1. 입력파일 준비: sjSemTag.txt @wiskingdom
a. string__diacriticNumber/tag 형식으로 1차 시도
2. 출력파일: w2v_sjSemTag_xxx.bin
a. xxx 부분에 주요 training 방식 및 parameter 요약내용 들어가게
3. train 방식 및 parameter 변주 시도하여 결…
hauni updated
7 years ago
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Hi Wang,
Thanks for sharing the code. I have the following two questions.
What can weightedword2vec do ?
Is there the implementation of attention based cbow model ?
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As the title, I wonder whether
./fastText supervised
will utilize the fastText embedding such as skip-gram or CBOW when training the classifier or not.
Thanks :D