lattice-nlp/DROC
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NER_DROC_ModernGBERT_1B is a fine-tuned version of LSX-UniWue/ModernGBERT_1B.
It is trained for Named Entity Recognition (NER) on German literary texts using the DROC dataset. The model performs span-based entity extraction, predicting entity spans directly rather than BIO token tags.
This model is intended for:
Performance is evaluated using exact span matching, on 8 held-out documents.
| Label | Precision | Recall | F1 | TP | FP | FN | Support | Support_% |
|---|---|---|---|---|---|---|---|---|
| PER | 0.9633 | 0.9697 | 0.9665 | 4357 | 166 | 136 | 4493 | 100.0 |
| MICRO | 0.9633 | 0.9697 | 0.9665 | - | - | - | 4493 | 100.0 |
| MACRO | - | - | 0.9665 | - | - | - | - | - |
Base model
LSX-UniWue/ModernGBERT_1B