FEEL-IT Italian Sentiment Analysis Model
| Property | Value |
|---|---|
| Author | MilaNLProc |
| License | Twitter Developer Terms |
| Framework | PyTorch, Transformers |
| Performance | 0.84 Accuracy on SENTIPOLC16 |
What is feel-it-italian-sentiment?
FEEL-IT Italian Sentiment is a state-of-the-art sentiment analysis model specifically designed for the Italian language. Built upon the UmBERTo architecture, this model is part of the larger FEEL-IT framework that analyzes both emotions and sentiments in Italian text. The model has been trained on a carefully curated dataset of 2,037 Italian tweets, covering a broad range of topics.
Implementation Details
The model is implemented using the Transformers library and PyTorch framework. It's built upon the UmBERTo base model, fine-tuned on the FEEL-IT dataset to achieve optimal performance for Italian sentiment analysis. The model can be easily integrated into existing pipelines using the Hugging Face transformers library.
- Fine-tuned on 2,037 annotated Italian tweets
- Achieves 0.81 Macro-F1 score on benchmark datasets
- Outperforms models trained on traditional SENTIPOLC16 dataset
- Supports binary sentiment classification (positive/negative)
Core Capabilities
- Binary sentiment classification for Italian text
- High accuracy (0.84) on standard benchmark datasets
- Easy integration through Hugging Face transformers pipeline
- Robust performance across various text domains
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its superior performance on Italian sentiment analysis, achieving better results than models trained on traditional datasets like SENTIPOLC16. It's part of a comprehensive emotion and sentiment analysis framework specifically designed for the Italian language.
Q: What are the recommended use cases?
The model is ideal for analyzing Italian social media content, customer feedback, and general text sentiment analysis. It's particularly effective for applications requiring binary sentiment classification (positive/negative) in Italian text.
