Pytorch Implementation of GoEmotions 😍😢😱

Korean version of GoEmotions Dataset 😍😢😱

How to build a multi-label sentiment classifiers with Tez and PyTorch

Detection of fine-grained emotions in texts

Text Emotion classification using BERT-LSTM model on GoEmotions dataset

Detect sexual predators in chats

Fine-tuning BERT-small on GoEmotions dataset.

Modelo basado en Stable Diffusion XL ajustado mediante LoRA para aprender el estilo visual de los memes irónicos y sarcásticos, utilizando el dataset Hateful Memes Dataset (Facebook AI). Genera imágenes limpias y expresivas sin texto incrustado, sobre las cuales se superpone luego el caption estilo meme.

Multi-module project to perform sentiment analysis on Irish Immigration using ML and NLP techniques.

Multi-label text classification in Reddit comments using statistical and learned features.

Sentiment Analysis on “HelloTalk” App Review Data with NRC Emotion Lexicon and GoEmotions Dataset

Story-Vibe: Instantly analyse and understand the emotional tone of any story.

🧬AI Sentiment Analysis project using NLP and Machine Learning with TF-IDF, multiple model comparisons, hyperparameter tuning, and advanced emotion detection using RoBERTa, Huggingface

Emotion architecture from Reddit comments: rater behavior, semantic clusters, and contradiction mapping in GoEmotions.

Russian translation of the GoEmotions dataset

Multi-Label Emotion Detection based in GoEmotions Dataset with ML Models and Transformers.

A full end-to-end NLP framework for analysing mental-health expressions on Reddit using sentiment modelling, fine-tuned classification (28 GoEmotions & 7 Ekman), circumplex affect modelling, and emotion network analysis.

Library for analyzing information from a list of journal entries. Utility functions and some wrapper functions for analyzing structure and emotions behind the text written

Projeto de dados para análise de sentimentos comparando os modelos BERTimbau e LSTM para Processamento de Linguágem Natural (PLN).