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An end-to-end project building a deeplearning model that reads a comment and gives it relevant tags as regards its safety or toxicity.

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Urias-T/comment_classifier

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comment_classifier

NLP project

Data Source: Kaggle

Description: This end-to-end Deep Learning project trained a model to receive a comment and give a response of if it falls into any of the predefined categories.

The categories are:

  • "toxic"
  • "severe_toxic"
  • "obscene"
  • "threat"
  • "insult"
  • "identity_hate"
  • "safe"

Approach: This was done using Bert as a base model.

Result: The model attained an accuracy of 92.97% after 5 epochs of training.

Deployment: Finally the model was deployed as an API endpoint using FastAPI.

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An end-to-end project building a deeplearning model that reads a comment and gives it relevant tags as regards its safety or toxicity.

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