sentiment

Multi-label sentiment classification model developed by Dejan Marketing.

To see this model in action visit: Sentiment Tool

The model is designed to be deployed in an automated pipeline capable of classifying text sentiment for thousands (or even millions) of text chunks or as a part of a scraping pipeline.

This is a demo model which may occassionally misclasify some texts. In a typical commercial project, a larger model is deployed for the task, and in special cases, a domain-specific model is developed for the client.

Engage Our Team

Interested in using this in an automated pipeline for bulk URL and text processing?

Please book an appointment to discuss your needs.

Base Model

albert/albert-base-v2

Labels

sentiment_labels = {
    0: "very positive",
    1: "positive",
    2: "somewhat positive",
    3: "neutral",
    4: "somewhat negative",
    5: "negative",
    6: "very negative"
}

Sources of Training Data

Synthetic. Llama3.