Multi-label sentiment classification model developed by Dejan Marketing.
To see this model in action visit: Good Vibes 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.
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Base Model
albert/albert-base-v2
Labels
sentiment_labels = {
0: "Good Vibes",
1: "No Vibes",
2: "Bad Vibes"
}
Sources of Training Data
Synthetic. Mistral.
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Model tree for dejanseo/good-vibes
Base model
albert/albert-base-v2