JayNightmare/PrERT-CNM-v4-privacybert

PrERT-CNM v4 PrivacyBERT is a Transformers sequence-classification model prepared from the local checkpoint at artifacts\phase-3-privacybert\classifier_checkpoint\privacybert.

Intended Use

Use this model for text classification in the privacy/CNM workflow it was trained for. It is intended for research and application prototyping unless your own validation shows it is suitable for production use.

Labels

• user
• system
• organization

Usage

from transformers import pipeline

classifier = pipeline("text-classification", model="JayNightmare/PrERT-CNM-v4-privacybert", top_k=None)
scores = classifier("Paste text to classify.")
print(scores)

Training Details

• Base architecture: BERT-compatible sequence classifier
• Source checkpoint: artifacts\phase-3-privacybert\classifier_checkpoint\privacybert
• Training metadata: included when available in the checkpoint folder

Evaluation

Add the final held-out metrics before publishing if they are available. Include dataset split details, label distribution, and any thresholding used by downstream consumers.

Limitations

The model can be sensitive to domain shift, ambiguous language, long inputs, and label definitions that differ from the training data. Review outputs before using them in automated decisions.

Gradio Demo

The companion Space can be prepared from huggingface/space and pointed at this model with the MODEL_ID environment variable.