---
license: mit
language:
- pt
metrics:
- name: Precision
  type: Precision
  value: 0.783
- name: Recall
  type: Recall
  value: 0.774
- name: F1-Score
  type: F1-Score
  value: 0.779
library_name: transformers
pipeline_tag: token-classification
tags:
- BERT
- CRF
- NER
- Portuguese
- Literature
---

# LitBERT-CRF

<!-- Provide a quick summary of what the model is/does. -->

LitBERT-CRF model is a fine-tuned BERT-CRF architecture specifically designed for Named Entity Recognition (NER) in Portuguese-written literature.

## Model Details

### Model Description

LitBERT-CRF leverages a BERT-CRF architecture, initially pre-trained on the brWaC corpus and fine-tuned on the HAREM dataset for enhanced NER performance in Portuguese. 
It incorporates domain-specific literary data through Masked Language Modeling (MLM), making it well-suited for identifying named entities in literary texts.

- **Model type:** BERT-CRF for NER
- **Language:** Portuguese
- **Fine-tuned from model:** BERT-CRF on brWaC and HAREM

## Evaluation

### Testing Data, Factors & Metrics

#### Testing Data

PPORTAL_ner dataset

#### Metrics

- **Precision**: 0.783
- **Recall**: 0.774
- **F1-score**: 0.779

## Citation

**BibTeX:**
```
@inproceedings{silva-moro-2024-evaluating,
    title = "Evaluating Pre-training Strategies for Literary Named Entity Recognition in {P}ortuguese",
    author = "Silva, Mariana O.  and
      Moro, Mirella M.",
    editor = "Gamallo, Pablo  and
      Claro, Daniela  and
      Teixeira, Ant{\'o}nio  and
      Real, Livy  and
      Garcia, Marcos  and
      Oliveira, Hugo Gon{\c{c}}alo  and
      Amaro, Raquel",
    booktitle = "Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1",
    month = mar,
    year = "2024",
    address = "Santiago de Compostela, Galicia/Spain",
    publisher = "Association for Computational Lingustics",
    url = "https://aclanthology.org/2024.propor-1.39",
    pages = "384--393",
}
```

**APA:**

Mariana O. Silva and Mirella M. Moro. 2024. Evaluating Pre-training Strategies for Literary Named Entity Recognition in Portuguese. In Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1, pages 384–393, Santiago de Compostela, Galicia/Spain. Association for Computational Lingustics.