ner-distilbert

ner_distillbert

Model Description

This is a Named Entity Recognition (NER) model fine-tuned on DistilBERT-base-cased for extracting entities from English text. The model is trained on synthetic data (ner_dataset_2.jsonl) and is optimized for token classification tasks where each word/token in the input text is classified into predefined entity categori.

Model Details:

• Model Name: ner_distillbert
• Version: 1
• Task: Ner
• Framework: pytorch
• Language(s): en
• License: apache-2.0

Intended Uses

This model is designed for ner tasks. Please evaluate on your specific use case before production deployment.

Training Details

Training Data

• Dataset: ner_training_synthetic_v1.jsonl
• Dataset Size: Not specified

Training Configuration

Usage

Installation

pip install transformers torch  # For transformers models
# OR
pip install -r requirements.txt  # For other frameworks

Basic Usage

# Load and use the model
from inference import Model  # See inference.py in the repository

model = Model()
predictions = model.predict(["Your input data here"])
print(predictions)

MLflow Tracking

• Experiment: N/A
• Run ID: N/A
• Training Date: N/A

Citation

@misc{ner_distillbert_1,
  title={ner_distillbert},
  author={BITZ-AI TEAM},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/marlonbino/ner_distillbert}
}