distilbert-NER EU AI Act Compliance Profile

distilbert-NER

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Model description

distilbert-NER is the fine-tuned version of DistilBERT, which is a distilled variant of the BERT model. DistilBERT has fewer parameters than BERT, making it smaller, faster, and more efficient. distilbert-NER is specifically fine-tuned for the task of Named Entity Recognition (NER).

This model accurately identifies the same four types of entities as its BERT counterparts: location (LOC), organizations (ORG), person (PER), and Miscellaneous (MISC). Although it is a more compact model, distilbert-NER demonstrates a robust performance in NER tasks, balancing between size, speed, and accuracy.

The model was fine-tuned on the English version of the CoNLL-2003 Named Entity Recognition dataset, which is widely recognized for its comprehensive and diverse range of entity types.

Available NER models

| Model Name | Description | Parameters | |-------------------|-------------|------------------| | distilbert-NER | Fine-tuned DistilBERT - a smaller, faster, lighter version of BERT | 66M | | bert-large-NER | Fine-tuned bert-large-cased - larger model with slightly better performance | 340M | | bert-base-NER-(uncased) | Fine-tuned bert-base, available in both cased and uncased versions | 110M |

Intended uses & limitations

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