privacy_intent for privacy policy intent classification
This model is fine-tuned version of mukund/privbert model on PolicyIE dataset .
- Reference Paper: Intent Classification and Slot Filling for Privacy Policies.
- The back translation method (data augmentation) resulted in a 1% improvement in performance when applied to imbalanced samples
- F1 Score: 88 (%4 performance increase compared to original work)
5 Intents (Labels):
(1) Data Collection/Usage: What, why and how user information is collected;
(2) Data Sharing/Disclosure: What, why and how user information is shared with or collected by third parties;
(3) Data Storage/Retention: How long and where user information will be stored;
(4) Data Security/Protection: Protection measures for user information;
(5) Other: Other privacy practices that do not fall into the above four categories.
from transformers import pipeline
pipe = pipeline("text-classification", "remzicam/privacy_intent")
text="At any time during your use of the Services, you may decide to share some information or content publicly or privately."
pipe(text)
Output
[{'label': 'data-sharing-disclosure', 'score': 0.8373807072639465}]
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