metadata
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
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 |