# High Accuracy NER

A Chinese named entity recognition model based on the BERT-BiLSTM-CRF architecture, fine-tuned on the Weibo dataset, suitable for entity recognition tasks in social media texts

This model is a lightweight version based on DistilBERT, fine-tuned for Named Entity Recognition (NER) tasks on a toy dataset.

This model is a Named Entity Recognition (NER) model fine-tuned based on the DistilBERT base version, trained on an unknown dataset with an evaluation set F1 score of 0.8545.

This model is a Named Entity Recognition (NER) model fine-tuned on the few_nerd dataset based on distilbert-base-uncased, achieving an F1 score of 0.7621 on the evaluation set.

A lightweight named entity recognition model based on DistilBERT, fine-tuned on the conll2003 dataset

This model is a Named Entity Recognition (NER) model fine-tuned on the MIT Restaurant dataset based on DistilBERT, specifically designed for entity recognition tasks in the restaurant domain.

This model is a fine-tuned named entity recognition model based on the basic version of Codebert, suitable for identifying entities in programming-related texts.

A named entity recognition model based on ELECTRA-small architecture, fine-tuned on the wikiann dataset

This is a Bengali entity extraction model trained using AutoNLP, designed to identify named entities in text.

This model is fine-tuned from macbert-base-chinese, specifically designed for Chinese drug name recognition tasks, achieving 92% accuracy on the test set.