![](https://cdn-avatars.huggingface.co/v1/production/uploads/1659521200179-5e48005437cb5b49818287a5.png)
Pseudo-labeled-python-data-pii-detection-filtered
This dataset was used for the training of a PII detection NER model. We annotated it using pseudo-labelelling to enhance model performance on some rare PII entities like keys.
It consists of 18,000 files annotates using an ensemble of two encoder models Deberta-v3-large and stanford-deidentifier-base which were fine-tuned on a labeled PII dataset for code with 400 files from this work. To select good-quality pseudo-labels, we computed the average probability logits between the models and filtered based on a minimum score. After inspection, we observed a high rate of false positives for Keys and Passwords, hence we retained only the entities that had a trigger word like key, auth and pwd in the surrounding context.
- Downloads last month
- 0
Models trained or fine-tuned on bigcode/pseudo-labeled-python-data-pii-detection-filtered
![](https://cdn-avatars.huggingface.co/v1/production/uploads/1659521200179-5e48005437cb5b49818287a5.png)
Token Classification
•
Updated
•
1.55k
•
108