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@@ -4,7 +4,6 @@ language:
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  tags:
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  - redaction
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  - PII
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- - PCI
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  - NLP
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  - privacy
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  license: apache-2.0
@@ -25,22 +24,41 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9821 # Example value, please adjust based on your results
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  - name: F1 Score
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  type: f1
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- value: 0.9685 # Example value, please adjust based on your results
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-
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  widget:
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- - text: "Is this review positive or negative? Review: Best cast iron skillet you will ever buy."
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- example_title: "Sentiment analysis"
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- - text: "Barack Obama nominated Hilary Clinton as his secretary of state on Monday. He chose her because she had ..."
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- example_title: "Coreference resolution"
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- - text: "On a shelf, there are five books: a gray book, a red book, a purple book, a blue book, and a black book ..."
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- example_title: "Logic puzzles"
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- - text: "The two men running to become New York City's next mayor will face off in their first debate Wednesday night ..."
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- example_title: "Reading comprehension"
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  ---
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  ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6488b81bc6b1f2b4c8d93d4e/kn93E3r_bwBeOzWcEo7gL.jpeg)
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  tags:
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  - redaction
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  - PII
 
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  - NLP
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  - privacy
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  license: apache-2.0
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.95 # Adjust based on your results
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  - name: F1 Score
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  type: f1
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+ value: 0.92 # Adjust based on your results
 
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  widget:
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+ - text: "John Doe's phone number is 123-456-7890 and his email is john.[email protected]."
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+ output:
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+ text: "[REDACTED]'s phone number is [REDACTED] and his email is [REDACTED]."
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+ example_title: "PII Redaction Example"
 
 
 
 
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  ---
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+ # Ninja-Masker-2-PII-Redaction
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+
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+ This model is designed to redact Personally Identifiable Information (PII) from text using advanced natural language processing techniques. It was fine-tuned on the Ninja-Redact-2-large dataset, specifically for the purpose of redacting PII.
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+
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+ ## Model Details
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+
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+ - **Language:** English
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+ - **Model Type:** Text Classification
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+ - **Tags:** Redaction, PII, NLP, Privacy
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+ - **License:** Apache 2.0
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+
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+ ## Usage
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+
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+ The model can be used to automatically identify and redact PII from text, making it suitable for privacy-related applications.
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+
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+ ## Training
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+ The model was fine-tuned using the Ninja-Redact-2-large dataset and optimized for accuracy and F1 score. Mixed precision and other optimizations were used to ensure the model's efficiency.
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+
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+ ## Metrics
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+
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+ The model's performance was evaluated based on accuracy and F1 score, ensuring reliable PII redaction capabilities.
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+
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+
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  ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6488b81bc6b1f2b4c8d93d4e/kn93E3r_bwBeOzWcEo7gL.jpeg)
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