gensim - Word2vec continue training on existing model - AttributeError: 'Word2Vec' object has no attribute 'compute_loss'

Question

I am trying to continue training on an existing model,

model = gensim.models.Word2Vec.load('model/corpus.zhwiki.word.model')
more_sentences = [['Advanced', 'users', 'can', 'load', 'a', 'model', 'and', 'continue', 'training', 'it', 'with', 'more', 'sentences']]    
model.build_vocab(more_sentences, update=True)
model.train(more_sentences, total_examples=model.corpus_count, epochs=model.iter)

but I got an error with the last line:

AttributeError: 'Word2Vec' object has no attribute 'compute_loss'

Some posts said it's caused by using a earlier version of gensim, and I have tried to add this after loading the existing model and before train().

model.compute_loss = False

After that, it didn't give me the AttributeError, but the output of model.train() is 0, and model didn't trained with new sentences.

How to solve this problem?

Answer 1

Here is how I continues training my model

# training_data: initial training data. contain list of tokenized sentences
model = Word2Vec(training_data, size=50, window=5, min_count=10, workers=4)

# datasmall: more sentences
# total_examples: number of additional sentence
# epochs: provide your current epochs. model.epochs is ok 
model.train(datasmall, total_examples=len(datasmall), epochs=model.epochs)

Answer 2

The total_examples (and epochs) arguments to train() should match what you're currently providing, in your more_sentences – not leftover values from prior training.

So for example, given your code showing just a single additional sentence, you'd specify total_examples=1.

If this isn't the source of the problem, double check that more_sentences is what you expect it to be at the time of the train() call.