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README.md
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# req_mod_ner_modelv2
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This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-ner](https://huggingface.co/pdelobelle/robbert-v2-dutch-ner) on a private dataset with 300 sentences/phrases with 1954 token labels (IOB2 format).
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It achieves the following results on the evaluation set:
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- Loss: 0.6791
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- Precision: 0.7515
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# req_mod_ner_modelv2
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This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-ner](https://huggingface.co/pdelobelle/robbert-v2-dutch-ner) on a private dataset with 300 sentences/phrases with 1954 token labels (IOB2 format) aimed at extracting software requirement related named entities. The following labels are used:
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- Actor (used for all types of software users and groups of users)
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- COTS (abbreviation for Commercial Off-The-Shelf Software)
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- Function (used for functions, functionality, features)
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- Result (used for system result, goals and system output)
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- Entity (used for all entities stored/processed by the software)
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- Attribute (used for attributes of entities)
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It achieves the following results on the evaluation set:
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- Loss: 0.6791
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- Precision: 0.7515
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