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disaster-tweets

This repository contains notebooks with codes used for the Kaggle competition "Real or Not? NLP with Disaster Tweets"

The competition description

Twitter has become an important communication channel in times of emergency. The ubiquitousness of smartphones enables people to announce an emergency they’re observing in real-time. Because of this, more agencies are interested in programatically monitoring Twitter (i.e. disaster relief organizations and news agencies). The goal of the present competition is to predict which Tweets are about real disasters and which one’s aren’t.

The team: Mazunina Zoya, Minnigulova Alina, Poyaganova Maria

Preprocessing: SpaCy. Word representation techniques used: tf-idf, word2vec. Models used: Logistic Regression, Sequential, CNN. Transformer models used: RoBERTa, Albert. The best score achieved: 0.82 on RoBERTa Large

The repository contains 2 notebooks:

  1. basic.ipynb - the implementation of simple word representations, LogReg and NN models.
  2. transfer.ipynb - the implementation of trasfer-learning techniques. The notebooks include comments in Russian.

The data can be found on the page of the competition (https://www.kaggle.com/c/nlp-getting-started/data)

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Notebooks with codes used for the Kaggle competition "Real or Not? NLP with Disaster Tweets"

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