ner-distilbert-base-cased

This model performs ner trained using MLflow and deployed on Hugging Face.

Model Details

• Model Name: ner-distilbert-base-cased
• Version: 4
• Task: Ner
• Languages: en
• Framework: sklearn
• License: apache-2.0

Intended Uses & Limitations

Intended Uses

• Ner tasks
• Research and development
• Child helpline services support

Limitations

• Performance may vary on out-of-distribution data
• Should be evaluated on your specific use case before production deployment
• Designed for child helpline contexts, may need adaptation for other domains

Training Data

• Dataset: ner_dataset_v1.json
• Size: Not specified
• Languages: en

Training Configuration

Parameter	Value
Author	Rogendo
Batch Size	4
Epochs	10
Lr	2e-05
Model Name	distilbert-base-cased
Test Size	0.1
Training Date	2025-10-30T11:58:48.315647
Weight Decay	0.01

Performance Metrics

Evaluation Results

Metric	Value
Epoch	10.0000
Eval Accuracy	0.9930
Eval F1	0.9929
Eval Loss	0.0216
Eval Precision	0.9933
Eval Recall	0.9930
Eval Runtime	0.1509
Eval Samples Per Second	106.0170
Eval Steps Per Second	13.2520

Usage

Installation

pip install transformers torch

Named Entity Recognition Example

from transformers import pipeline

ner = pipeline("ner", model="marlonbino/ner-distilbert-base-cased", aggregation_strategy="simple")
text = "John Smith works at OpenCHS in Nairobi and can be reached at [email protected]"
entities = ner(text)

for entity in entities:
    print(f"{entity['entity_group']}: {entity['word']} (score: {entity['score']:.2f})")

MLflow Tracking

• Experiment: NER_Distilbert/marlon
• Run ID: 10d2648a456a4f6ab74022a9e45c9f40
• Training Date: 2025-10-30 11:58:48
• Tracking URI: http://192.168.10.6:5000

Training Metrics Visualization

View detailed training metrics and TensorBoard logs in the Training metrics tab.

Citation

@misc{ner_distilbert_base_cased,
  title={ner-distilbert-base-cased},
  author={OpenCHS Team},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/marlonbino/ner-distilbert-base-cased}
}

Contact

[email protected]

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Model card auto-generated from MLflow