---
language: tr
datasets:
- SUNLP-NER-Twitter
---

# berturk-sunlp-ner-turkish

## Introduction
[berturk-sunlp-ner-turkish] is a NER model that was fine-tuned from the BERTurk-cased model on the SUNLP-NER-Twitter dataset.

## Training data
The model was trained on the SUNLP-NER-Twitter dataset (5000 tweets). The dataset can be found at https://github.com/SU-NLP/SUNLP-Twitter-NER-Dataset
Named entity types are as follows:
Person, Location, Organization, Time, Money, Product, TV-Show


## How to use berturk-sunlp-ner-turkish with HuggingFace

```python
from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("busecarik/berturk-sunlp-ner-turkish")
model = AutoModelForTokenClassification.from_pretrained("busecarik/berturk-sunlp-ner-turkish")
```

## Model performances on SUNLP-NER-Twitter test set (metric: seqeval)
Precision|Recall|F1
-|-|-
85.08|84.46|84.77

Classification Report

Entity|Precision|Recall|F1
-|-|-|-
LOCATION|0.75|0.80|0.78
MONEY|0.74|0.59|0.65
ORGANIZATION|0.82|0.86|0.84
PERSON|0.94|0.91|0.92
PRODUCT|0.52|0.44|0.48
TIME|0.88|0.87|0.87
TVSHOW|0.65|0.58|0.61