--- license: bigscience-bloom-rail-1.0 datasets: - dejanseo/good-vibes widget: - example_title: Example 1 text: >- The concert last night was an unforgettable experience filled with amazing performances. - example_title: Example 2 text: >- I found the book to be quite insightful and it provided a lot of valuable information. - example_title: Example 3 text: The weather today is pretty average, not too hot and not too cold. - example_title: Example 4 text: >- Although the service was slow, the food at the restaurant was quite enjoyable. - example_title: Example 5 text: The new software update has caused more problems than it fixed. - example_title: Example 6 text: The customer support team was unhelpful and I had a frustrating experience. - example_title: Example 7 text: I had a fantastic time exploring the city and discovering new places. - example_title: Example 8 text: The meeting was very productive and we accomplished all our goals. - example_title: Example 9 text: This is the worst purchase I've ever made and I regret buying it. - example_title: Example 10 text: >- I am extremely pleased with the results of the project and how smoothly everything went. language: - en pipeline_tag: text-classification --- Multi-label sentiment classification model developed by [Dejan Marketing](https://dejanmarketing.com/). To see this model in action visit: [Good Vibes Tool](https://dejanmarketing.com/tools/good-vibes/) 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](https://dejanmarketing.com/conference/) to discuss your needs. # Base Model albert/albert-base-v2 ## Labels ```py sentiment_labels = { 0: "Good Vibes", 1: "No Vibes", 2: "Bad Vibes" } ``` # Sources of Training Data Synthetic. Mistral.