Model Card

README.md

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+---
+language: ar, en
+license: apache-2.0
+datasets:
+- AQMAR
+- ANERcorp
+thumbnail: https://www.informatik.hu-berlin.de/en/forschung-en/gebiete/ml-en/resolveuid/a6f82e0d7fa446a59c902cac4cafa9cb/@@images/image/preview
+tags:
+- flair
+- Text Classification
+- token-classification
+- sequence-tagger-model
+metrics:
+- f1
+widget:
+- text: "اختارها خيري بشارة كممثلة، دون سابقة معرفة أو تجربة تمثيلية، لتقف بجانب فاتن حمامة في فيلم «يوم مر ويوم حلو» (1988) وهي ما زالت شابة لم تتخطَ عامها الثاني"
+---
+# Arabic NER Model for AQMAR dataset
+Training was conducted over 86 epochs, using a linear decaying learning rate of 2e-05, starting from 0.3 and a batch size of 48 with fastText and Flair forward and backward embeddings.
+
+
+## Original Dataset:
+- [AQMAR](http://www.cs.cmu.edu/~ark/ArabicNER/)
+
+## Results:
+- F1-score (micro) 0.9323
+- F1-score (macro) 0.9272
+
+|      | True Posititves  | False Positives | False Negatives | Precision | Recall | class-F1 |
+|------|-----|----|----|---------|--------|----------|
+| LOC  | 164 | 7  | 13 | 0.9591  | 0.9266 | 0.9425   |
+| MISC | 398 | 22 | 37 |  0.9476 | 0.9149 | 0.9310   |
+| ORG  | 65  | 6  | 9  | 0.9155  | 0.8784 | 0.8966   |
+| PER  | 199 | 13 | 13 | 0.9387  | 0.9387 | 0.9387   |
+
+---
+
+# Usage
+```python
+from flair.data import Sentence
+from flair.models import SequenceTagger
+import pyarabic.araby as araby
+from icecream import ic
+
+arTagger = SequenceTagger.load('megantosh/flair-arabic-MSA-aqmar')
+
+sentence = Sentence('George Washington went to Washington .')
+arSentence = Sentence('عمرو عادلي أستاذ للاقتصاد السياسي المساعد في الجامعة الأمريكية  بالقاهرة .')
+
+
+# predict NER tags
+tagger.predict(sentence)
+arTagger.predict(arSentence)
+
+# print sentence with predicted tags
+ic(sentence.to_tagged_string)
+ic(arSentence.to_tagged_string)
+
+```
+
+# Example
+see an example from a [similar NER model in Flair](https://huggingface.co/megantosh/flair-arabic-multi-ner)
+
+# Model Configuration
+```python
+  (embeddings): StackedEmbeddings(
+    (list_embedding_0): WordEmbeddings('ar')
+    (list_embedding_1): FlairEmbeddings(
+      (lm): LanguageModel(
+        (drop): Dropout(p=0.1, inplace=False)
+        (encoder): Embedding(7125, 100)
+        (rnn): LSTM(100, 2048)
+        (decoder): Linear(in_features=2048, out_features=7125, bias=True)
+      )
+    )
+    (list_embedding_2): FlairEmbeddings(
+      (lm): LanguageModel(
+        (drop): Dropout(p=0.1, inplace=False)
+        (encoder): Embedding(7125, 100)
+        (rnn): LSTM(100, 2048)
+        (decoder): Linear(in_features=2048, out_features=7125, bias=True)
+      )
+    )
+  )
+  (word_dropout): WordDropout(p=0.05)
+  (locked_dropout): LockedDropout(p=0.5)
+  (embedding2nn): Linear(in_features=4396, out_features=4396, bias=True)
+  (rnn): LSTM(4396, 256, batch_first=True, bidirectional=True)
+  (linear): Linear(in_features=512, out_features=14, bias=True)
+  (beta): 1.0
+  (weights): None
+  (weight_tensor) None
+)"
+2021-03-31 22:19:50,654 ----------------------------------------------------------------------------------------------------
+2021-03-31 22:19:50,654 Corpus: "Corpus: 3025 train + 336 dev + 373 test sentences"
+2021-03-31 22:19:50,654 ----------------------------------------------------------------------------------------------------
+2021-03-31 22:19:50,654 Parameters:
+2021-03-31 22:19:50,654  - learning_rate: "0.3"
+2021-03-31 22:19:50,654  - mini_batch_size: "48"
+2021-03-31 22:19:50,654  - patience: "3"
+2021-03-31 22:19:50,654  - anneal_factor: "0.5"
+2021-03-31 22:19:50,654  - max_epochs: "150"
+2021-03-31 22:19:50,654  - shuffle: "True"
+2021-03-31 22:19:50,654  - train_with_dev: "False"
+2021-03-31 22:19:50,654  - batch_growth_annealing: "False"
+2021-03-31 22:19:50,655 ------------------------------------
+ ```
+ Due to some formatting errors, your code might appear like [this](https://ibb.co/ky20Lnq).
+ 
+ # Citation
+*if you use this model in your work, please consider citing this work:*
+```latex
+@unpublished{MMHU21
+author = "M. Megahed",
+title = "Sequence Labeling Architectures in Diglossia",
+note = "In Review",
+}
+```