distilroberta

Tensorflow and Keras implementation of the state of the art researches in Dialog System NLU

Question Answering Chatbot with DistilRoBERTa Sentence Embeddings, Dialogflow and Ngrok

This is NLP project of text multi-classification. My pre-trained model classify speech into three different categories offensive, hateful and neither.

This project used in my dissertation for detecting sarcasm in twitter dataset using Sate-of-the-Art Transformer

AI-powered mental health chatbot using NLP sentiment analysis (HuggingFace Transformers) + medical image OCR with cross-reference engine — Python · Flask · DistilRoBERTa · Pytesseract

AI-Based Compliance Monitoring System for Data Privacy under the Saudi Personal Data Protection Law (PDPL)

A sophisticated multilabel text classification model to seamlessly categorize diverse quote tags.

A compact benchmark of text representations and model families for movie-genre classification from plot descriptions. We compare TF-IDF+FFNN, RNNs with pretrained embeddings, and lightweight Transformers, logging metrics and artifacts with MLflow. Includes EDA, reproducible splits, and inference/latency utilities

Using Task Specific Knowledge Distillation to obtain DistilRoBERTa model fine-tuned on SST-2 part of the GLUE dataset for sentiment analysis.

Data and models to extract toponyms and spatio-temporal entities from text data.

Psychologically-Informed LLM to simulate investor emotions — An interdisciplinary study. Undergraduate dissertation 2025-2026 @UCL BASc

an intelligent book recommendation system using llms and python. vibe code-free.

NLP-based toxic chat detection system using machine learning and Transformer models, including RoBERTa and DistilRoBERTa.

Dual-Transformer (DistilRoBERTa + ERNIE) late-fusion fake review detector optimized via LinearSVC with interactive Streamlit UI.

A machine learning-powered book recommendation system that suggests books based on natural language descriptions, categories, and emotional tones.

Comparison of TF-IDF + Linear SVM and DistilRoBERTa for multi-label emotion detection using the GoEmotions dataset.

this project demonstrates how to efficiently fine-tune a transformer model using LoRA (Low-Rank Adaptation) on the IMDB Movie Reviews dataset for binary sentiment classification.

Official implementation of DCESR: A Dual-Channel Recommender System considering Emotions and Review Summarization.

Analysis of Reddit posts from r/Anxiety to explore symptoms, co-mentioned conditions, and emotional narratives using NLP methods. Modular Colab notebooks provided for reproducible research.

Analyzed movie dialogues using NLP and the DistilRoBERTa model to classify emotions like joy, anger, and sadness. Built an interactive Streamlit dashboard with Plotly to visualize emotional trends, compare character emotions, and provide insights into narrative tone.