FastPDN

FastPolDeepNer is model for Named Entity Recognition, designed for easy use, training and configuration. The forerunner of this project is PolDeepNer2. The model implements a pipeline consisting of data processing and training using: hydra, pytorch, pytorch-lightning, transformers. The FastPDN model was trained on datasets (with 82 class versions) of kpwr and cen. Annotation guidelines are specified here. FastPDN models have been fine-tuned, thanks to pretrained models: - herbert-base-case - distiluse-base-multilingual-cased-v1

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