goemotions

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.

Russian translation of the GoEmotions dataset

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

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

EmotionRadar: Multi-label Emotion Detection from Text using Supervised and Unsupervised Machine Learning

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

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

Emotional Earth Mover's Distance for fine-grained hierarchical emotion analysis (ADMA 2025): code and baselines

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

A research project comparing Classical ML models, Hybrid LLM-embedding methods, and fine-tuned Transformers for emotion classification. The study evaluates performance on two datasets, song lyrics and GoEmotions, to analyze how model choice and dataset quality impact accuracy and generalization.

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