Bert Fine Tuned Medical Insurance Ner

🚀 JustAdvanceTechonology/bert-fine-tuned-medical-insurance-ner

This model is a fine - tuned version of BERT, which can potentially be used for named - entity recognition in the medical insurance field, providing more accurate information extraction.

🚀 Quick Start

This model is a fine - tuned version of [bert - base - cased](https://huggingface.co/bert - base - cased) on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0269
• Validation Loss: 0.0551
• Epoch: 2

📚 Documentation

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

🔧 Technical Details

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e - 05, 'decay_steps': 2631, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e - 08, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: mixed_float16

Training results

Framework versions

• Transformers 4.17.0
• TensorFlow 2.5.0
• Datasets 1.18.3
• Tokenizers 0.11.6

📄 License

This project is under the Apache - 2.0 license.