v0.1.1

spacy-ewc v0.1.1

Initial Release: Elastic Weight Consolidation for spaCy

The v0.1.1 release of spacy-ewc marks the integration of Elastic Weight Consolidation (EWC) into spaCy's Named Entity Recognition (NER) pipeline. This feature allows developers to enhance the adaptability of NER models by mitigating the issue of catastrophic forgetting in sequential learning tasks, enabling the retention of previously acquired knowledge alongside new learning.

Key Features

• Elastic Weight Consolidation (EWC) Integration

  • Integrates EWC into spaCy’s NER component to preserve essential model weights from previous training sessions.
  • Mitigates catastrophic forgetting, enhancing the model’s ability to incorporate new entities without compromising prior knowledge.

• Sequential Learning Support

  • Allows the model to learn additional entities over time while maintaining accuracy for previously learned entities.
  • Supports use cases requiring continuous model adaptation, such as those in dynamic and evolving domains.

• Documentation and Usage Examples

  • Provides detailed setup instructions and examples to assist users in implementing and customizing the EWC-enhanced NER model.
  • Includes guidance on tuning EWC-specific parameters to suit varied project requirements.

Installation

To install spacy-ewc, use the following command:

pip install spacy-ewc

Getting Started

Please refer to the Getting Started section in the README for details on configuring EWC within your spaCy workflows. Comprehensive documentation is provided to help users effectively apply EWC in Named Entity Recognition tasks.

Configuration Options

• EWC Parameters: Configure the strength of EWC regularization to balance knowledge retention with new learning requirements.
• Compatibility: Compatible with spaCy versions 3.0.0 and later.

Known Issues

• Compatibility with older versions of spaCy may be limited. Users are advised to ensure their spaCy installation is up-to-date.
• Model performance may vary based on the complexity of sequential learning tasks and model size.

Planned Improvements

Future updates to spacy-ewc are expected to include:

• Additional control options for EWC parameters.
• Enhanced support for other NLP tasks beyond Named Entity Recognition.
• Performance optimizations to improve efficiency for large-scale applications.

---

Contributing

Contributions to spacy-ewc are welcome. Users are encouraged to report any issues, suggest new features, or submit pull requests to help improve the project.

New Contributors

• @JRocabruna made their first contribution in 813216a
• @DarkRockMountain-admin made their first contribution in 10297f1
• @fossabot made their first contribution in #1

Thank you for choosing spacy-ewc. We look forward to supporting your NLP projects with this tool.

Full Changelog: https://github.com/darkrockmountain/spacy-ewc/commits/v0.1.1