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PaddlePaddle/uie-senta-nano

Sentiment analysis is a research hotspot in recent years, aiming at analyzing, processing, summarizing and reasoning emotionally subjective texts. Sentiment analysis has a wide range of application scenarios and can be applied to consumer decision-making, public opinion analysis, personalized recommendation and so on.

According to the analysis granularity, it can be roughly divided into three categories: document-level sentiment analysis, sentence-level sentiment analysis and aspect-level sentiment analysis. Among them, aspect-level sentiment analysis includes multiple subtasks, such as aspect term extraction, opinion term extraction, aspect-opinion-sentiment triplet extraction, etc.

UIE-Senta is a type of Chinese sentiment analysis model, which uses UIE as backbone and further trained based on large amount of samples related to sentiment analysis. So it has a stronger ability to understand sentiment knowledge and handle the related samples. Currently, UIE-Senta supports most of basic sentiment analysis capabilities, including sentiment-level sentiment classification, aspect-term extraction, opinion-term extraction, aspect-sentiment pair extraction, aspect-opinion pair extraction, aspect-opinion-sentiment triple extraction. You could perform sentiment analysis with UIE-Senta to improve your business analysis capabilities.

Available Models

Model Name Model Config
uie-senta-base 12-layers, 768-hidden, 12-heads
uie-senta-medium 6-layers, 768-hidden, 12-heads
uie-senta-mini 6-layers, 384-hidden, 12-heads
uie-senta-micro 4-layers, 384-hidden, 12-heads
uie-senta-nano 4-layers, 312-hidden, 12-heads

Performance on Text Dataset

We conducted experiments to compare the performance different Models based on a self-built test set, which containing samples from multiple fields, such as hotel, restaurant,clothes and so. The comparison results are as follows.

Model Name Precision Recall F1
uie-senta-base 0.93403 0.92795 0.93098
uie-senta-medium 0.93146 0.92137 0.92639
uie-senta-mini 0.91799 0.92028 0.91913
uie-senta-micro 0.91542 0.90957 0.91248
uie-senta-nano 0.90817 0.90878 0.90847

Detailed Info: https://github.com/1649759610/PaddleNLP/tree/develop/applications/sentiment_analysis/unified_sentiment_extraction

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