Closed Man-with-Arrow closed 1 year ago
Hi,
I've been playing around with Word2Vec and the model linked here, and I can't seem to reproduce the same distances.
For example:
Python 3.11.2 (main, Feb 12 2023, 00:48:52) [GCC 12.2.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import gensim >>> model = gensim.models.Word2Vec.load('./wiki_tokenized_model/model.mdl') >>> model.wv.similar_by_word('אשליה') [('אשליית', 0.7949888110160828), ('אשלייתי', 0.7358855605125427), ('תחושה', 0.7196317911148071), ('סימולקרה', 0.7147767543792725), ('מתעתעת', 0.7013854384422302), ('השתקפות', 0.6864952445030212), ('אסטרלית', 0.6836147308349609), ('אשלייתית', 0.6831943392753601), ('אילוזיה', 0.6829365491867065), ('סיראנית', 0.6813762784004211)]
Note the distances.
However, the distance Semantle gives is different:
Am I doing anything wrong? I'd love some feedback!
The linked model was trained using the same data, but with different parameters. We do not share Semantle's model
Hi,
I've been playing around with Word2Vec and the model linked here, and I can't seem to reproduce the same distances.
For example:
Note the distances.
However, the distance Semantle gives is different:
Am I doing anything wrong? I'd love some feedback!