word-embeddings-benchmarks
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kudkudak
Package for evaluating word embeddings
....... data = url_opener.open(request) File "C:\ProgramData\Anaconda3\lib\urllib\request.py", line 525, in open response = self._open(req, data) File "C:\ProgramData\Anaconda3\lib\urllib\request.py", line 542, in _open result = self._call_chain(self.handle_open, protocol, protocol + File "C:\ProgramData\Anaconda3\lib\urllib\request.py", line 502,...
I take a glace at this project, the main idea of this project is to valid the embedding conclusion by labeled data (most are fixed provided by human setting word...
in the function transform_words of Embedding object in embedding.py, following code i can not understand: elif isinstance(self.vocabulary, OrderedVocabulary): # range in python3 is lazy counter_of_words = range(len(self.vocabulary.words) - 1, -1,...
Many datasets in similarity.py fetch_* are not available, i.e. can not download from "dropbox" Could you favor to provide them in Google Drive or other cloud location ? Thank you.
Hi! Thank you for creating this repo. Could you please tell us why you decided to multiply the MTurk similarity scores by 2: https://github.com/kudkudak/word-embeddings-benchmarks/blob/8fd04891a92d313cc3b6956a43f25c9e44022e0e/web/datasets/similarity.py#L37 and those of the RG65 dataset...
Hi, there This is a very useful tool that can help us evaluate word embeddings in a consistent way. However, during the evaluation process, I found a bug. I have...
Thanks a lot for providing this code, this helps for a fair comparison of frameworks. According to my experiments with your tool, SG Google News embeddings (word2vec) are reaching a...
