Bio Medical Bert Named Entity Recognition

- Named Entity Recognition for biomedical data using [Scibert](https://arxiv.org/abs/1903.10676) and [Biobert](https://arxiv.org/abs/1901.08746) .
- Different classification architectures like Bert-Crf, Bert-LSTM-Crf on top of Bert Layer.
- Finetuning script is compatible with the datasets provided by [Scibert git repo](https://github.com/allenai/scibert/tree/master/data/ner) data folder.

Finetuning Steps

- add labels file to the data_dir; a labels file should have all the labels from the data, one label per line.
- Edit the config file of your chosen architecture and save.
- Execute the below command

python finettune_with_logger.py
    --model_config_path=/path/to/the/edited/config/file
    --data_dir=/path/to/the/data_dir/
    --logger_file_dir=/path/to/the/dir/where/logs/should/be/saved/
    --labels_file=/path/to/the/labels_file/of/the/dataset/file

Results

Data	Architecture	Best Test F1
JNLPBA	Bert-CRF	-
	Bert-TokenClassification	-
	Bert-LSTM-CRF	-
NCBI-Disease	Bert-CRF
	Bert-TokenClassification	-
	Bert-LSTM-CRF(no finetuning)	0.88
BC5CDR	Bert-CRF	-
	Bert-TokenClassification	-
	Bert-LSTM-CRF	-
SCIIE	Bert-CRF	-
	Bert-TokenClassification	-
	Bert-LSTM-CRF	-