ayushdh96/HateSpeech_Bert_Base_Uncased_Fine_Tuned

Model Card for Model ID

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This model is fine-tuned on top of distill bert base uncased for hatespeech. Its purpose is to predict whether a given text contains hate speech or not. Class Label are 1 for hatspeech and 0 for not.

Model Details

Model Description

<!-- Provide a longer summary of what this model is. --> Important info This model works with binary classification and doesn't consider multilabel clssification. It detects it's either a hatespeech or not.

• —Developed by: Ayush Dhoundiyal
• —Language(s) (NLP): English
• —Finetuned from model: Bert Base Uncased

Model Sources [optional]

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• —Paper: https://github.com/ayushdh96/Natural-Language-Processing/blob/main/AyushDhoundiyalProject_Report.pdf [More Information Needed]

Training Details

Training Data

<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> Pre-processing invloved basic steps like lemmtizing, stemming of words. Removing stop words and lowercasing the text to be classified. It's requested to perform these steps for good results.

Evaluation

<!-- This section describes the evaluation protocols and provides the results. --> The model provides the accuracy of 0.96, precision of 0.97. recall of 0.97 and f1 score of 0.97.