A web extension for identifying dark pattern on websites powered by Fine Tuned BERT Model for classificaiton on dark pattern custom dataset,
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Updated
May 25, 2024 - Jupyter Notebook
A web extension for identifying dark pattern on websites powered by Fine Tuned BERT Model for classificaiton on dark pattern custom dataset,
Public release of SciFCheX system developed for COM3610 Dissertation Project. The pipeline is designed to perform fact-checking on scientific claims.
Emotion Prediction in Arabic Text
Deep Learning Based NER Tool for Turkish with BiLSTM, BiGRU, fine-tuned BERT models
This project involves analyzing and classifying the BoolQ dataset from the SuperGLUE benchmark. We implemented various classifiers and techniques, including rules-based logic, BERT, RNN, and GPT-3/4 data augmentation, achieving performance improvements.
In this project we have tried to do multi-label hate-speech classification in Bengali and Hindi language using fill-mask transformer models.
Accessing the Writing skills of a document/author by classifiying the statements and sentences into different classes based on the sequential learning using Pre-trained models from BERT. Rating the document based on the score obtained from the classes for each statement/sentence.
自作のデータセットでファインチューニングした言語モデルを使ったアプリを公開しました
Dark Pattern Detection using fine Tuned BERT Model, powered by CogniGuard project with streamlit web app
This is the repo of all my NLP (Natural Language Processing) projects.
Recognition of news agency mentions in historical news articles (BERT-based token classification).
Successfully developed a fine-tuned BERT transformer model which can accurately classify symptoms to their corresponding diseases upto an accuracy of 89%.
This repository contains code that fine-tunes BERT for text classification on financial tweets.
Japanese derogatory text classifier
Analyzing French census data (1836-1936) for demographic insights : application on household head prediction.
Space Model framework that allows for maintaining generalizability, and enhances the performance on the downstream task by utilizing task-specific context attribution. It is an external LLM layer, that improves accuracy in classification task for multiple datasets, such as HateXplain, IMDB movies reviews and more.
This project repository is a combination of all R and Python files that have led up to create the Sentiment Gummy Worm scoring model, which is a predictive randomForest model that calculates the mean sentiment score of a sentence based on buffer ratios, decay factors and input length.
pov
A project based on Fine-tuned BERT to detect GLIBC vulnerabilities.
Prediksi Emosi App adalah sebuah aplikasi yang dapat digunakan untuk memprediksi 6 emosi yang muncul dalam sebuah kalimat, yaitu marah, sedih, senang, cinta, takut, dan jijik.
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