This model was developed by performing fine-tuning based on DistilBERT, with the goal of identifying Named Entity Recognition (NER) tags for each token present in a sentence.
The model was trained on a dataset of English-language tweets, optimizing it for understanding short, informal content typical of the Twitter platform. Through this fine-tuning, the model is able to identify named entities such as people, places, organizations, dates, and other types of structured information within unstructured text.
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