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ychenNLP
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arabic-ner-ace

Token Classification
Transformers
PyTorch
TensorFlow
Arabic
English
bert
text-classification
BERT
sequence-tagger-model
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@@ -6,23 +6,22 @@ license: mit
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  datasets:
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  - ACE2005
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  ---
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- # Arabic NER
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-
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- ### Model
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  - NER BIO tagging model based on [GigaBERTv4](https://huggingface.co/lanwuwei/GigaBERT-v4-Arabic-and-English).
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  - ACE2005 Training data: English + Arabic
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  - [NER tags](https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/english-entities-guidelines-v6.6.pdf) including: PER, VEH, GPE, WEA, ORG, LOC, FAC
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- ### Hyperparameters
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  - learning_rate=2e-5
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  - num_train_epochs=10
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  - weight_decay=0.01
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- ### ACE2005 Evaluation results
 
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  | Language | Arabic | English |
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  |:----:|:-----------:|:----:|
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  | | 89.4 | 88.8 |
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- ### How to use
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  ```python
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  >>> from transformers import pipeline, AutoModelForTokenClassification, AutoTokenizer
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  datasets:
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  - ACE2005
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  ---
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+ # Arabic NER Model
 
 
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  - NER BIO tagging model based on [GigaBERTv4](https://huggingface.co/lanwuwei/GigaBERT-v4-Arabic-and-English).
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  - ACE2005 Training data: English + Arabic
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  - [NER tags](https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/english-entities-guidelines-v6.6.pdf) including: PER, VEH, GPE, WEA, ORG, LOC, FAC
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+ ## Hyperparameters
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  - learning_rate=2e-5
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  - num_train_epochs=10
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  - weight_decay=0.01
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+
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+ ## ACE2005 Evaluation results
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  | Language | Arabic | English |
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  |:----:|:-----------:|:----:|
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  | | 89.4 | 88.8 |
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+ ##How to use
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  ```python
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  >>> from transformers import pipeline, AutoModelForTokenClassification, AutoTokenizer
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