---
language:
- de
datasets:
- lattice-nlp/DROC
license:
- cc-by-nc-sa-4.0
base_model:
- LSX-UniWue/ModernGBERT_1B
base_model_relation: finetune
tags:
- NER
- token-classification
- named-entity-recognition
- digital-humanities
model-index:
- name: lattice-nlp/NER_DROC_ModernGBERT_1B
  results:
    - task:
        type: token-classification
        name: Named Entity Recognition
      dataset:
        name: DROC
        type: DROC
        split: test
      metrics:
        - name: Micro Precision
          type: precision
          value: 0.9632986955560469
          verified: true
        - name: Micro Recall
          type: recall
          value: 0.9697306921878478
          verified: true
        - name: Micro F1
          type: f1
          value: 0.9665039929015085
          verified: true

---
# lattice-nlp/NER_DROC_ModernGBERT_1B

## Model description

**NER_DROC_ModernGBERT_1B** is a fine-tuned version of [LSX-UniWue/ModernGBERT_1B](https://huggingface.co/LSX-UniWue/ModernGBERT_1B).


It is trained for **Named Entity Recognition (NER)** on German literary texts using the [**DROC dataset**](https://huggingface.co/datasets/lattice-nlp/DROC).
The model performs **span-based entity extraction**, predicting entity spans directly rather than BIO token tags.

## Intended use

This model is intended for:

- Named Entity Recognition in literary texts
- Digital humanities research (literary character analysis)
- Information extraction from historical novels

## Performance

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 |  -   |  -   |  -   |     -     |      -      |