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Gorengoz/bert-based-Turkish-NER-wikiann
bert-based-Turkish-NER-wikiann is a token classification model from Gorengoz. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
Bu model "https://github.com/stefan-it/turkish-bert" base alınarak geliştirilmiş bir NER(Varlık ismi tanıma) modelidir.
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From the Hugging Face model README
Bu model "https://github.com/stefan-it/turkish-bert" base alınarak geliştirilmiş bir NER(Varlık ismi tanıma) modelidir.
Fine-tune işlemi için TDD-NER-202112-CC-002 veri seti kullanılmıştır.
@inproceedings{pan-etal-2017-cross, title = "Cross-lingual Name Tagging and Linking for 282 Languages", author = "Pan, Xiaoman and Zhang, Boliang and May, Jonathan and Nothman, Joel and Knight, Kevin and Ji, Heng", booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)", month = jul, year = "2017", address = "Vancouver, Canada", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/P17-1178", doi = "10.18653/v1/P17-1178", pages = "1946--1958" }
custom_labels = ["O","B-LOC","I-LOC","B-ORG","I-ORG","B-PER","I-PER"]
model_args = { "train_batch_size": 32, "eval_batch_size": 32, "num_train_epochs": 3, "seed":1, "save_steps": 625, "overwrite_output_dir": True, "output_dir": "/content/Model" }
| Epochs | Running Loss |
|---|---|
| 1 | 0.1152 |
| 2 | 0.1091 |
| 3 | 0.0586 |
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="Gorengoz/bert-based-Turkish-NER-wikiann")
pipe("Entity X'in müşteri hizmetleri hızlı ve etkili, Entity Y'nin ürün kalitesi çok kötü.",aggregation_strategy = "simple"")