Update README.md

README.md

@@ -33,7 +33,7 @@ Fine-tuned DistilBERT model for Personal Identifiable Information (PII) detectio
 - **Task**: Token Classification (Named Entity Recognition)
 - **Languages**: English
 - **License**: MIT
-- **Fine-tuned on**: AI4Privacy PII-200k dataset
+- **Fine-tuned on**: AI4Privacy PII-42k dataset
 
 ## Supported PII Entity Types
 
@@ -62,7 +62,6 @@ This model can detect 56 different types of PII entities including:
 **Professional Information:**
 - JOBTITLE, JOBTYPE, JOBAREA, COMPANYNAME
 
-**And many more...**
 
 ## Usage
 
@@ -115,24 +114,3 @@ This model is designed for:
 - Performance may vary on very short or very long texts
 - Should be validated on your specific use case
 
-## Ethical Considerations
-
-This model is intended to help protect privacy by identifying PII. Users should:
-- Test thoroughly on their specific data
-- Implement appropriate safeguards
-- Consider the legal requirements in their jurisdiction
-- Be aware that no automated system is 100% accurate
-
-## Citation
-
-If you use this model, please cite:
-
-```bibtex
-@misc{bert-pii-detection,
-  title={BERT PII Detection Model},
-  author={SoelMgd},
-  year={2025},
-  publisher={Hugging Face},
-  url={https://huggingface.co/SoelMgd/bert-pii-detection}
-}
-```