cjiang2 / NER

Project in Named Entity Recognition

CL_NER

Continual Learning with Structured Regularization in Named Entity Recognition

Requirements

• PyTorch
• numpy
• tqdm
• seqeval
• gensim
• Jupyter Notebook

Experiments

To replicate the experiments:

1. Clone the repository.

2. Under the folder experiments, locate the specific experiments to replicate (NA - New Addition, Seq - Sequential).

3. Download a copy of Google word2vec pre-trained embedding, put under "NER/checkpoints/GoogleNews-vectors-negative300.bin" or specify the path in configuration of each train script.

4. Three scripts are enlisted in each directory (Baseline vs. EWC vs. SI). Inside, "multiple_allowed" controls whether to purge sentences with multiple entity tags. Run python3 ewc_train.py for example, for training and evaluation.

Acknowledgement

The copy of CONLL 2003 dataset is referred here from huggingface.