Word2vec changes output












0














I've created a word2vec model, that saves the information into a normal .txt file. And of cause, it return a lot of vector, but when i delete the content in the .txt file and run the program again, the output will change.
Do you know why? It is not very important, it just kills my OCD.



Quick example

1:



[[ 3.2392807   1.680171   -0.42155528 -1.7102437   2.3303537 ]
[ 3.6736202 -0.8065518 0.26261634 -1.2047065 2.1221237 ]
[ 2.9144292 0.44492996 1.237786 -0.3242629 3.5435572 ]
[ 0.4130354 0.08011961 0.03255951 -0.11589962 2.9328532 ]
[ 1.5287857 -0.6961181 2.7903285 0.40642017 0.6555253 ]
[ 2.9975677 -0.977857 1.883217 -1.3727202 1.832796 ]
[ 3.2535048 0.86906517 1.748935 -1.0769477 1.100436 ]
[ 2.509191 -0.59611416 2.0518627 -0.8840636 1.6848307 ]
[ 2.7653887 -0.7883314 0.943277 -1.005442 2.115393 ]
[ 0.95081985 -0.865088 0.90458965 -0.04385343 1.3649719 ]]


2:



[[ 1.60327232e+00  2.12096125e-01  1.26251602e+00 -7.17208505e-01
-6.12632275e-01]
[ 8.19391370e-01 9.68442023e-01 -2.48031616e-01 3.76854181e-01
7.21971035e-01]
[ 1.12308228e+00 2.55824924e-02 4.91404593e-01 8.79842639e-01
1.54288793e+00]
[-1.69641733e-01 7.46692896e-01 -4.85606074e-01 1.64707148e+00
2.71568203e+00]
[-3.10868084e-01 2.13060689e+00 2.07112730e-01 5.34646988e-01
3.51558208e-01]
[ 2.30190897e+00 1.47751641e+00 6.27250433e-01 1.55146813e+00
-8.13818634e-01]
[ 1.45050168e+00 4.62597281e-01 2.21269965e+00 -5.63119173e-01
-1.97888732e-01]
[-8.21502864e-01 2.41197419e+00 9.84819829e-01 -2.05534548e-01
1.30428791e-01]
[ 3.31903785e-01 -2.34199071e+00 3.95457715e-01 9.19164062e-01
-8.65327239e-01]
[ 5.92819750e-01 1.58047271e+00 1.58888444e-01 3.54782730e-01
3.13017368e-01]
[ 1.67989731e-03 7.24929124e-02 -2.14633882e-01 -3.33887011e-01
-2.00998139e+00]
[ 1.49949551e+00 6.67065024e-01 2.81557608e+00 -1.20027995e+00
-2.41783738e+00]
[ 7.21774340e-01 -4.06250358e-01 6.79239750e-01 7.13694572e-01
2.15337336e-01]]









share|improve this question






















  • This has been answerer in Ensure the gensim generate the same Word2Vec model for different runs on the same data
    – yatu
    Dec 27 '18 at 15:06












  • This has also been answered in the gensim FAQ: "I've trained my Word2Vec/Doc2Vec/etc model repeatedly using the exact same text corpus, but the vectors are different each time. Is there a bug or have I made a mistake? (*2vec training non-determinism)" github.com/RaRe-Technologies/gensim/wiki/…
    – gojomo
    Dec 27 '18 at 18:19
















0














I've created a word2vec model, that saves the information into a normal .txt file. And of cause, it return a lot of vector, but when i delete the content in the .txt file and run the program again, the output will change.
Do you know why? It is not very important, it just kills my OCD.



Quick example

1:



[[ 3.2392807   1.680171   -0.42155528 -1.7102437   2.3303537 ]
[ 3.6736202 -0.8065518 0.26261634 -1.2047065 2.1221237 ]
[ 2.9144292 0.44492996 1.237786 -0.3242629 3.5435572 ]
[ 0.4130354 0.08011961 0.03255951 -0.11589962 2.9328532 ]
[ 1.5287857 -0.6961181 2.7903285 0.40642017 0.6555253 ]
[ 2.9975677 -0.977857 1.883217 -1.3727202 1.832796 ]
[ 3.2535048 0.86906517 1.748935 -1.0769477 1.100436 ]
[ 2.509191 -0.59611416 2.0518627 -0.8840636 1.6848307 ]
[ 2.7653887 -0.7883314 0.943277 -1.005442 2.115393 ]
[ 0.95081985 -0.865088 0.90458965 -0.04385343 1.3649719 ]]


2:



[[ 1.60327232e+00  2.12096125e-01  1.26251602e+00 -7.17208505e-01
-6.12632275e-01]
[ 8.19391370e-01 9.68442023e-01 -2.48031616e-01 3.76854181e-01
7.21971035e-01]
[ 1.12308228e+00 2.55824924e-02 4.91404593e-01 8.79842639e-01
1.54288793e+00]
[-1.69641733e-01 7.46692896e-01 -4.85606074e-01 1.64707148e+00
2.71568203e+00]
[-3.10868084e-01 2.13060689e+00 2.07112730e-01 5.34646988e-01
3.51558208e-01]
[ 2.30190897e+00 1.47751641e+00 6.27250433e-01 1.55146813e+00
-8.13818634e-01]
[ 1.45050168e+00 4.62597281e-01 2.21269965e+00 -5.63119173e-01
-1.97888732e-01]
[-8.21502864e-01 2.41197419e+00 9.84819829e-01 -2.05534548e-01
1.30428791e-01]
[ 3.31903785e-01 -2.34199071e+00 3.95457715e-01 9.19164062e-01
-8.65327239e-01]
[ 5.92819750e-01 1.58047271e+00 1.58888444e-01 3.54782730e-01
3.13017368e-01]
[ 1.67989731e-03 7.24929124e-02 -2.14633882e-01 -3.33887011e-01
-2.00998139e+00]
[ 1.49949551e+00 6.67065024e-01 2.81557608e+00 -1.20027995e+00
-2.41783738e+00]
[ 7.21774340e-01 -4.06250358e-01 6.79239750e-01 7.13694572e-01
2.15337336e-01]]









share|improve this question






















  • This has been answerer in Ensure the gensim generate the same Word2Vec model for different runs on the same data
    – yatu
    Dec 27 '18 at 15:06












  • This has also been answered in the gensim FAQ: "I've trained my Word2Vec/Doc2Vec/etc model repeatedly using the exact same text corpus, but the vectors are different each time. Is there a bug or have I made a mistake? (*2vec training non-determinism)" github.com/RaRe-Technologies/gensim/wiki/…
    – gojomo
    Dec 27 '18 at 18:19














0












0








0







I've created a word2vec model, that saves the information into a normal .txt file. And of cause, it return a lot of vector, but when i delete the content in the .txt file and run the program again, the output will change.
Do you know why? It is not very important, it just kills my OCD.



Quick example

1:



[[ 3.2392807   1.680171   -0.42155528 -1.7102437   2.3303537 ]
[ 3.6736202 -0.8065518 0.26261634 -1.2047065 2.1221237 ]
[ 2.9144292 0.44492996 1.237786 -0.3242629 3.5435572 ]
[ 0.4130354 0.08011961 0.03255951 -0.11589962 2.9328532 ]
[ 1.5287857 -0.6961181 2.7903285 0.40642017 0.6555253 ]
[ 2.9975677 -0.977857 1.883217 -1.3727202 1.832796 ]
[ 3.2535048 0.86906517 1.748935 -1.0769477 1.100436 ]
[ 2.509191 -0.59611416 2.0518627 -0.8840636 1.6848307 ]
[ 2.7653887 -0.7883314 0.943277 -1.005442 2.115393 ]
[ 0.95081985 -0.865088 0.90458965 -0.04385343 1.3649719 ]]


2:



[[ 1.60327232e+00  2.12096125e-01  1.26251602e+00 -7.17208505e-01
-6.12632275e-01]
[ 8.19391370e-01 9.68442023e-01 -2.48031616e-01 3.76854181e-01
7.21971035e-01]
[ 1.12308228e+00 2.55824924e-02 4.91404593e-01 8.79842639e-01
1.54288793e+00]
[-1.69641733e-01 7.46692896e-01 -4.85606074e-01 1.64707148e+00
2.71568203e+00]
[-3.10868084e-01 2.13060689e+00 2.07112730e-01 5.34646988e-01
3.51558208e-01]
[ 2.30190897e+00 1.47751641e+00 6.27250433e-01 1.55146813e+00
-8.13818634e-01]
[ 1.45050168e+00 4.62597281e-01 2.21269965e+00 -5.63119173e-01
-1.97888732e-01]
[-8.21502864e-01 2.41197419e+00 9.84819829e-01 -2.05534548e-01
1.30428791e-01]
[ 3.31903785e-01 -2.34199071e+00 3.95457715e-01 9.19164062e-01
-8.65327239e-01]
[ 5.92819750e-01 1.58047271e+00 1.58888444e-01 3.54782730e-01
3.13017368e-01]
[ 1.67989731e-03 7.24929124e-02 -2.14633882e-01 -3.33887011e-01
-2.00998139e+00]
[ 1.49949551e+00 6.67065024e-01 2.81557608e+00 -1.20027995e+00
-2.41783738e+00]
[ 7.21774340e-01 -4.06250358e-01 6.79239750e-01 7.13694572e-01
2.15337336e-01]]









share|improve this question













I've created a word2vec model, that saves the information into a normal .txt file. And of cause, it return a lot of vector, but when i delete the content in the .txt file and run the program again, the output will change.
Do you know why? It is not very important, it just kills my OCD.



Quick example

1:



[[ 3.2392807   1.680171   -0.42155528 -1.7102437   2.3303537 ]
[ 3.6736202 -0.8065518 0.26261634 -1.2047065 2.1221237 ]
[ 2.9144292 0.44492996 1.237786 -0.3242629 3.5435572 ]
[ 0.4130354 0.08011961 0.03255951 -0.11589962 2.9328532 ]
[ 1.5287857 -0.6961181 2.7903285 0.40642017 0.6555253 ]
[ 2.9975677 -0.977857 1.883217 -1.3727202 1.832796 ]
[ 3.2535048 0.86906517 1.748935 -1.0769477 1.100436 ]
[ 2.509191 -0.59611416 2.0518627 -0.8840636 1.6848307 ]
[ 2.7653887 -0.7883314 0.943277 -1.005442 2.115393 ]
[ 0.95081985 -0.865088 0.90458965 -0.04385343 1.3649719 ]]


2:



[[ 1.60327232e+00  2.12096125e-01  1.26251602e+00 -7.17208505e-01
-6.12632275e-01]
[ 8.19391370e-01 9.68442023e-01 -2.48031616e-01 3.76854181e-01
7.21971035e-01]
[ 1.12308228e+00 2.55824924e-02 4.91404593e-01 8.79842639e-01
1.54288793e+00]
[-1.69641733e-01 7.46692896e-01 -4.85606074e-01 1.64707148e+00
2.71568203e+00]
[-3.10868084e-01 2.13060689e+00 2.07112730e-01 5.34646988e-01
3.51558208e-01]
[ 2.30190897e+00 1.47751641e+00 6.27250433e-01 1.55146813e+00
-8.13818634e-01]
[ 1.45050168e+00 4.62597281e-01 2.21269965e+00 -5.63119173e-01
-1.97888732e-01]
[-8.21502864e-01 2.41197419e+00 9.84819829e-01 -2.05534548e-01
1.30428791e-01]
[ 3.31903785e-01 -2.34199071e+00 3.95457715e-01 9.19164062e-01
-8.65327239e-01]
[ 5.92819750e-01 1.58047271e+00 1.58888444e-01 3.54782730e-01
3.13017368e-01]
[ 1.67989731e-03 7.24929124e-02 -2.14633882e-01 -3.33887011e-01
-2.00998139e+00]
[ 1.49949551e+00 6.67065024e-01 2.81557608e+00 -1.20027995e+00
-2.41783738e+00]
[ 7.21774340e-01 -4.06250358e-01 6.79239750e-01 7.13694572e-01
2.15337336e-01]]






python word2vec






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Dec 27 '18 at 15:04









Marius Johan

35




35












  • This has been answerer in Ensure the gensim generate the same Word2Vec model for different runs on the same data
    – yatu
    Dec 27 '18 at 15:06












  • This has also been answered in the gensim FAQ: "I've trained my Word2Vec/Doc2Vec/etc model repeatedly using the exact same text corpus, but the vectors are different each time. Is there a bug or have I made a mistake? (*2vec training non-determinism)" github.com/RaRe-Technologies/gensim/wiki/…
    – gojomo
    Dec 27 '18 at 18:19


















  • This has been answerer in Ensure the gensim generate the same Word2Vec model for different runs on the same data
    – yatu
    Dec 27 '18 at 15:06












  • This has also been answered in the gensim FAQ: "I've trained my Word2Vec/Doc2Vec/etc model repeatedly using the exact same text corpus, but the vectors are different each time. Is there a bug or have I made a mistake? (*2vec training non-determinism)" github.com/RaRe-Technologies/gensim/wiki/…
    – gojomo
    Dec 27 '18 at 18:19
















This has been answerer in Ensure the gensim generate the same Word2Vec model for different runs on the same data
– yatu
Dec 27 '18 at 15:06






This has been answerer in Ensure the gensim generate the same Word2Vec model for different runs on the same data
– yatu
Dec 27 '18 at 15:06














This has also been answered in the gensim FAQ: "I've trained my Word2Vec/Doc2Vec/etc model repeatedly using the exact same text corpus, but the vectors are different each time. Is there a bug or have I made a mistake? (*2vec training non-determinism)" github.com/RaRe-Technologies/gensim/wiki/…
– gojomo
Dec 27 '18 at 18:19




This has also been answered in the gensim FAQ: "I've trained my Word2Vec/Doc2Vec/etc model repeatedly using the exact same text corpus, but the vectors are different each time. Is there a bug or have I made a mistake? (*2vec training non-determinism)" github.com/RaRe-Technologies/gensim/wiki/…
– gojomo
Dec 27 '18 at 18:19

















active

oldest

votes











Your Answer






StackExchange.ifUsing("editor", function () {
StackExchange.using("externalEditor", function () {
StackExchange.using("snippets", function () {
StackExchange.snippets.init();
});
});
}, "code-snippets");

StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "1"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);

StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});

function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});


}
});














draft saved

draft discarded


















StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53947068%2fword2vec-changes-output%23new-answer', 'question_page');
}
);

Post as a guest















Required, but never shown






























active

oldest

votes













active

oldest

votes









active

oldest

votes






active

oldest

votes
















draft saved

draft discarded




















































Thanks for contributing an answer to Stack Overflow!


  • Please be sure to answer the question. Provide details and share your research!

But avoid



  • Asking for help, clarification, or responding to other answers.

  • Making statements based on opinion; back them up with references or personal experience.


To learn more, see our tips on writing great answers.





Some of your past answers have not been well-received, and you're in danger of being blocked from answering.


Please pay close attention to the following guidance:


  • Please be sure to answer the question. Provide details and share your research!

But avoid



  • Asking for help, clarification, or responding to other answers.

  • Making statements based on opinion; back them up with references or personal experience.


To learn more, see our tips on writing great answers.




draft saved


draft discarded














StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53947068%2fword2vec-changes-output%23new-answer', 'question_page');
}
);

Post as a guest















Required, but never shown





















































Required, but never shown














Required, but never shown












Required, but never shown







Required, but never shown

































Required, but never shown














Required, but never shown












Required, but never shown







Required, but never shown







Popular posts from this blog

Monofisismo

Angular Downloading a file using contenturl with Basic Authentication

Olmecas