Skip to main content

Extending NERDA Library for Continual Learning

Project description

NERDA-Con

Extending NERDA Library for Continual Learning

Installation Guide

pip install NERDA-Con

Implementation and Execution

Training

model.train_next_task(training,validation)

The training and validation must be NERDA-optimized dataloaders.

Evaluation

model.evaluate_performance(test)

Shared Model

To set shared model parameters,

model.shared_model = model.transformer_model

NERDA

Nerda is a framework for fine-tuning pretrained transformers for Named-Entity Recognition (NER) tasks.

@inproceedings{nerda,
  title = {NERDA},
  author = {Kjeldgaard, Lars and Nielsen, Lukas},
  year = {2021},
  publisher = {{GitHub}},
  url = {https://github.com/ebanalyse/NERDA}
}

Cite This Work

@inproceedings{nerda-con,
  title = {NERDA-Con},
  author = {Supriti Vijay, Aman Priyanshu},
  year = {2022},
  publisher = {{GitHub}},
  url = {https://github.com/SupritiVijay/NERDA-Con}
}

Project details


Release history Release notifications | RSS feed

This version

0.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

NERDA_Con-0.0.tar.gz (164.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

NERDA_Con-0.0-py3-none-any.whl (21.3 kB view details)

Uploaded Python 3

File details

Details for the file NERDA_Con-0.0.tar.gz.

File metadata

  • Download URL: NERDA_Con-0.0.tar.gz
  • Upload date:
  • Size: 164.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.42.1 importlib-metadata/4.11.1 keyring/21.1.0 rfc3986/2.0.0 colorama/0.4.3 CPython/3.7.6

File hashes

Hashes for NERDA_Con-0.0.tar.gz
Algorithm Hash digest
SHA256 76820fd4c68fe3e1b6ebfd77ef529881c1e95cbb349dca77053204b160a693c0
MD5 ffedb2fc0fa2c6ea2defd9016c9a3be5
BLAKE2b-256 3463470ceaf78839743330e4b69f2d73a5cfa3e91f9e7372e8d9274d076998da

See more details on using hashes here.

File details

Details for the file NERDA_Con-0.0-py3-none-any.whl.

File metadata

  • Download URL: NERDA_Con-0.0-py3-none-any.whl
  • Upload date:
  • Size: 21.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.42.1 importlib-metadata/4.11.1 keyring/21.1.0 rfc3986/2.0.0 colorama/0.4.3 CPython/3.7.6

File hashes

Hashes for NERDA_Con-0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 fe4d2d960ccfc5ba3dd36a6489a5908fed8cacb9869d381b9b54dc9736ac39c6
MD5 fb5725015767f9b08e727fb809d96e07
BLAKE2b-256 b4c1e6e3a5c241a8657b8a404ed5552c81f41621f87afe8e9eb5400f2e766108

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page