# Multi-emotion Recognition

This model is a fine-tuned version of distilbert-base-uncased on an emotions dataset, designed for text sentiment classification.

A Chinese sentiment classification model fine-tuned based on mDeBERTa-v3-base, capable of recognizing 8 emotion labels

Chinese sentiment classification model fine-tuned based on xlm-roberta-large-xnli, capable of recognizing 8 emotion labels

A text classification model fine-tuned on emotion datasets based on DistilBERT, used to identify emotional categories in text.

A BERT-based fine-tuned model designed for multi-label sentiment classification, supporting recognition of 11 emotions.

HebEMO is a tool for detecting polarity and extracting emotions in modern Hebrew, trained on COVID-related datasets, and excels in polarity classification and emotion recognition tasks.

HebEMO is a tool designed to detect polarity and extract emotions from modern Hebrew user-generated content (UGC), trained on a unique COVID-19-related dataset.

HebEMO is a tool designed to detect sentiment polarity and extract emotions from modern Hebrew user-generated content (UGC), trained on a unique COVID-19 related dataset.

HebEMO is a tool designed to detect sentiment polarity and extract emotions from modern Hebrew user-generated content, trained on a unique COVID-19 related dataset with superior performance.