metadata
license: mit
base_model: dbmdz/bert-base-turkish-cased
pipeline_tag: token-classification
library_name: transformers
tags:
- ner
- token-classification
- pytorch
- turkish
- tr
- dbmdz
- bert
- bert-base-cased
- bert-base-turkish-cased
widget:
- text: >-
Bağlarbaşı Mahallesi, Zübeyde Hanım Caddesi No: 10 / 3 34710
Üsküdar/İstanbul
address-extraction
This is a simple library to extract addresses from text. The train.py file contains the code to train but is just included for reference, not to be run. The model is trained on our own dataset of addresses, which is not included in this repo. There is also predict.py which is a simple script to run the model on a single address.
The model is based on dbmdz/bert-base-turkish-cased from Hugging Face.
Example Results
(g:\projects\address-extraction\venv) G:\projects\address-extraction>python predict.py
Osmangazi Mahallesi, Hoca Ahmet Yesevi Cd. No:34, 16050 Osmangazi/Bursa
Osmangazi Mahalle 98.80%
Hoca Ahmet Yesevi Cadde 98.55%
34 Bina Numarası 99.50%
16050 Posta Kodu 98.49%
Osmangazi İlçe 98.71%
Bursa İl 99.21%
Average Score: 0.9874102413654328
Labels Found: 6
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Karşıyaka Mahallesi, Mavişehir Caddesi No: 91, Daire 4, 35540 Karşıyaka/İzmir
Karşıyaka Mahalle 98.93%
Mavişehir Cadde 96.90%
91 Bina Numarası 99.25%
4 Bina Numarası 30.75%
35540 Posta Kodu 98.97%
Karşıyaka İlçe 98.84%
İzmir İl 98.86%
Average Score: 0.9173339426517486
Labels Found: 7
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Selçuklu Mahallesi, Atatürk Bulvarı No: 55, 42050 Selçuklu/Konya
Selçuklu Mahalle 98.53%
Atatürk Cadde 47.01%
55 Bina Numarası 99.49%
42050 Posta Kodu 98.78%
Selçuklu İlçe 98.74%
Konya İl 99.16%
Average Score: 0.9240859523415565
Labels Found: 6
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Alsancak Mahallesi, 1475. Sk. No:3, 35220 Konak/İzmir
Alsancak Mahalle 99.35%
1475 Sokak 97.71%
3 Bina Numarası 99.18%
35220 Posta Kodu 99.00%
Konak İlçe 98.90%
İzmir İl 98.95%
Average Score: 0.9881603717803955
Labels Found: 6
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Kocatepe Mahallesi, Yaşam Caddesi 3. Sokak No:4, 06420 Bayrampaşa/İstanbul
Kocatepe Mahalle 99.44%
Yaşam Cadde 92.45%
3 Sokak 70.61%
4 Bina Numarası 99.18%
06420 Posta Kodu 99.00%
Bayrampaşa İlçe 98.86%
İstanbul İl 98.90%
Average Score: 0.9558616995811462
Labels Found: 7
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Installation & Usage
The environment.yml file contains the conda environment used to run the model. Environment is configured to use cuda enabled gpus but should work with no gpus too. To run the model, you can use the following commands:
conda env create -f environment.yml -p ./condaenv
conda activate ./condaenv
python predict.py
License
This project is licensed under the terms of the MIT license.