readme: ---
  tags:
  - text-classification
  library_name: fasttext
  widget:
  - text: "dialectics"
    example_title: "dialectics"
  - text: "schizoanalysis"
    example_title: "schizoanalysis"
  - text: "praxis"
    example_title: "praxis"
  - text: "topicality"
    example_title: "topicality"
  ---
  
  # debate2vec
  Word-vectors created from a large corpus of competitive debate evidence, and data extraction / processing scripts
  
  #usage
  ```
  import fasttext.util
  ft = fasttext.load_model('debate2vec.bin')
  ft.get_word_vector('dialectics')
  ```
  # Download Link
  Github won't let me store large files in their repos. 
  * [FastText Vectors Here](https://drive.google.com/file/d/1m-CwPcaIUun4qvg69Hx2gom9dMScuQwS/view?usp=sharing) (~260mb)
  
  
  # About 
  
  Created from all publically available Cross Examination Competitive debate evidence posted by the community on [Open Evidence](https://openev.debatecoaches.org/) (From 2013-2020)
  
  Search through the original evidence by going to [debate.cards](http://debate.cards/)
  
  Stats about this corpus: 
  * 222485 unique documents larger than 200 words (DebateSum plus some additional debate docs that weren't well-formed enough for inclusion into DebateSum)
  * 107555 unique words (showing up more than 10 times in the corpus)
  * 101 million total words
  
  Stats about debate2vec vectors: 
  * 300 dimensions, minimum number of appearances of a word was 10, trained for 100 epochs with lr set to 0.10 using FastText
  * lowercased (will release cased)
  * No subword information
  
  The corpus includes the following topics 
  
  * 2013-2014 Cuba/Mexico/Venezuela Economic Engagement
  * 2014-2015 Oceans
  * 2015-2016 Domestic Surveillance
  * 2016-2017 China
  * 2017-2018 Education
  * 2018-2019 Immigration
  * 2019-2020 Reducing Arms Sales
  
  Other topics that this word vector model will handle extremely well
  
  * Philosophy (Especially Left-Wing / Post-modernist)
  * Law
  * Government 
  * Politics
  
  
  Initial release is of fasttext vectors without subword information. Future releases will include fine-tuned GPT-2 and other high end models as my GPU compute allows. 
  
  # Screenshots
  ![](https://github.com/Hellisotherpeople/debate2vec/blob/master/debate2vec.jpg)
  ![](https://github.com/Hellisotherpeople/debate2vec/blob/master/debate2vec2.jpg)
  ![](https://github.com/Hellisotherpeople/debate2vec/blob/master/debate2vec3.jpg)
  