Open budiryan opened 4 years ago
@budiryan
As per my understanding,
minCountLabel
is the min word count threshold.
Have a look at its usage: https://github.com/epfml/sent2vec/blob/master/src/fasttext.cc#L473
if (uniform(model.rng) > dict_->getPDiscard(line[i]) || dict_->getTokenCount(line[i]) < args_->minCountLabel)
continue;
Here line
represents the vector of words( to be specific its hash index).
Following code snippet shows how the word index is extracted: https://github.com/epfml/sent2vec/blob/master/src/dictionary.cc#L30
int32_t Dictionary::find(const std::string& w) const {
int32_t h = hash(w) % MAX_VOCAB_SIZE;
getTokenCount
is defined in
https://github.com/epfml/sent2vec/blob/master/src/dictionary.cc#L133
int64_t Dictionary::getTokenCount(int32_t id) const {
assert(id >= 0);
assert(id < size_);
return words_[id].count;
}
yes, thanks @kaushikacharya
and yes the algorithm is unsupervised (contrastive or self-supervised learning).
can i close this?
Thank you @kaushikacharya and @martinjaggi for replying!
I have further question:
Then how will it differ from minCount
?
It seems that minCount
is only used here:
threshold(args_->minCount, args_->minCountLabel);
What is the purpose of that function? I am having trouble understanding it
@budiryan Seems you have raised a valid doubt.
sent2vec source code is developed over the existing C++ code of fastText. Hence it has several sections which are not used in sent2vec e.g. supervised training.
https://github.com/facebookresearch/fastText/issues/530#issuecomment-394816034
Edouard Grave has mentioned that minCountLabel
is to be used for supervised mode only.
Based on this observation, my understanding is that
minCountLabel
should be replaced by minCount
in the functions cbowCWNgrams
and sent2vec
i.e. in the following lines
https://github.com/epfml/sent2vec/blob/master/src/fasttext.cc#L439
if (uniformSub(model.rng) > dict_->getPDiscard(line[i]) || dict_->getTokenCount(line[i]) < args_->minCountLabel) {
https://github.com/epfml/sent2vec/blob/master/src/fasttext.cc#L473
if (uniform(model.rng) > dict_->getPDiscard(line[i]) || dict_->getTokenCount(line[i]) < args_->minCountLabel)
In threshold(args_->minCount, args_->minCountLabel)
minCount acts as threshold for word token and
minCountLabel acts as threshold for labels (supervised mode).
https://github.com/epfml/sent2vec/blob/master/src/dictionary.cc#L276
void Dictionary::threshold(int64_t t, int64_t tl) {
What is the definition of minCountLabel? Isn't this algorithm supposed to be unsupervised?
Thanks!