How to train an existing word2vec gensim model on new words?
$begingroup$
According to gensim docs, you can take an existing word2vec model and further train it on new words.
The training is streamed, meaning sentences can be a generator,
reading input data from disk on-the-fly, without loading the entire
corpus into RAM.
It also means you can continue training the model later:
model = Word2Vec.load("word2vec.model")
model.train([["hello", "world"]], total_examples=1, epochs=1)
Source: docs
But when I actually try it, it doesn't seem to learn the new terms.
from gensim.models import Word2Vec
# initial a model
model = Word2Vec([["cat", "say", "meow"], ["dog", "say", "woof"]], min_count=1)
# count terms in model
print( len(model.wv.vocab) )
=> 5
# train existing model on new terms
model.train([['potoatoes', 'and', 'farmers']], total_examples=model.corpus_count, epochs=model.epochs)
# count terms in model
print( len(model.wv.vocab) )
=> 5
After adding new terms in the 2nd code block, the model still only has the same number of terms as before.
How can I make this work?
python word2vec gensim
asked 3 hours ago
tim_xyztim_xyz
717
$endgroup$
add a comment |
$begingroup$
According to gensim docs, you can take an existing word2vec model and further train it on new words.
The training is streamed, meaning sentences can be a generator,
reading input data from disk on-the-fly, without loading the entire
corpus into RAM.
It also means you can continue training the model later:
model = Word2Vec.load("word2vec.model")
model.train([["hello", "world"]], total_examples=1, epochs=1)
Source: docs
But when I actually try it, it doesn't seem to learn the new terms.
from gensim.models import Word2Vec
# initial a model
model = Word2Vec([["cat", "say", "meow"], ["dog", "say", "woof"]], min_count=1)
# count terms in model
print( len(model.wv.vocab) )
=> 5
# train existing model on new terms
model.train([['potoatoes', 'and', 'farmers']], total_examples=model.corpus_count, epochs=model.epochs)
# count terms in model
print( len(model.wv.vocab) )
=> 5
After adding new terms in the 2nd code block, the model still only has the same number of terms as before.
How can I make this work?
python word2vec gensim
asked 3 hours ago
tim_xyztim_xyz
717
$endgroup$
add a comment |
$begingroup$
According to gensim docs, you can take an existing word2vec model and further train it on new words.
The training is streamed, meaning sentences can be a generator,
reading input data from disk on-the-fly, without loading the entire
corpus into RAM.
It also means you can continue training the model later:
model = Word2Vec.load("word2vec.model")
model.train([["hello", "world"]], total_examples=1, epochs=1)
Source: docs
But when I actually try it, it doesn't seem to learn the new terms.
from gensim.models import Word2Vec
# initial a model
model = Word2Vec([["cat", "say", "meow"], ["dog", "say", "woof"]], min_count=1)
# count terms in model
print( len(model.wv.vocab) )
=> 5
# train existing model on new terms
model.train([['potoatoes', 'and', 'farmers']], total_examples=model.corpus_count, epochs=model.epochs)
# count terms in model
print( len(model.wv.vocab) )
=> 5
After adding new terms in the 2nd code block, the model still only has the same number of terms as before.
How can I make this work?
python word2vec gensim
asked 3 hours ago
tim_xyztim_xyz
717
$endgroup$
According to gensim docs, you can take an existing word2vec model and further train it on new words.
The training is streamed, meaning sentences can be a generator,
reading input data from disk on-the-fly, without loading the entire
corpus into RAM.
It also means you can continue training the model later:
model = Word2Vec.load("word2vec.model")
model.train([["hello", "world"]], total_examples=1, epochs=1)
Source: docs
But when I actually try it, it doesn't seem to learn the new terms.
from gensim.models import Word2Vec
# initial a model
model = Word2Vec([["cat", "say", "meow"], ["dog", "say", "woof"]], min_count=1)
# count terms in model
print( len(model.wv.vocab) )
=> 5
# train existing model on new terms
model.train([['potoatoes', 'and', 'farmers']], total_examples=model.corpus_count, epochs=model.epochs)
# count terms in model
print( len(model.wv.vocab) )
=> 5
After adding new terms in the 2nd code block, the model still only has the same number of terms as before.
How can I make this work?
python word2vec gensim
python word2vec gensim
asked 3 hours ago
tim_xyztim_xyz
717
asked 3 hours ago
tim_xyztim_xyz
717
asked 3 hours ago
tim_xyztim_xyz
717
asked 3 hours ago
tim_xyztim_xyz
717
asked 3 hours ago
tim_xyztim_xyz
717
717
add a comment |
add a comment |
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