---
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
-|-|-
82.96|82.42|82.69

Classification Report

Entity|Precision|Recall|F1
-|-|-|-
LOCATION|0.70|0.80|0.74
MONEY|0.80|0.71|0.75
ORGANIZATION|0.78|0.86|0.78
PERSON|0.90|0.91|0.91
PRODUCT|0.44|0.47|0.45
TIME|0.94|0.85|0.89
TVSHOW|0.61|0.35|0.45