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README.md

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+---
+license: mit
+datasets:
+- Wojood
+tags:
+- Named Entity Recognition
+- Arabic NER
+- Nested NER
+language:
+- ar
+metrics:
+- f1
+- precision
+- recall
+pipeline_tag: token-classification
+---
+
+## Wojood - Nested/Flat Arabic NER Models
+Wojood is a corpus for Arabic nested Named Entity Recognition (NER). Nested entities occur when one entity mention is embedded inside another entity mention. 550K tokens (MSA and dialect) This repo contains the source-code to train Wojood nested NER.
+
+Online Demo
+You can try our model using the demo link below
+
+https://sina.birzeit.edu/wojood/
+
+https://arxiv.org/abs/2205.09651
+
+https://huggingface.co/aubmindlab/bert-base-arabertv2/tree/main
+
+### Models
+* Nested NER (main branch), with micro-F1 score of 0.909551
+* Flat NER (flat branch), with micro-F1 score 0.883847
+
+### Google Colab Notebooks
+You can test our model using our Google Colab notebooks
+* Train flat NER: https://gist.github.com/mohammedkhalilia/72c3261734d7715094089bdf4de74b4a
+* Evaluate your model using flat NER model: https://gist.github.com/mohammedkhalilia/c807eb1ccb15416b187c32a362001665  
+* Train nested NER: https://gist.github.com/mohammedkhalilia/a4d83d4e43682d1efcdf299d41beb3da
+* Evaluate your data using nested NER model: https://gist.github.com/mohammedkhalilia/9134510aa2684464f57de7934c97138b

config.json

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+{
+  "architectures": [
+    "BertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "type_vocab_size": 2,
+  "vocab_size": 64000
+}

special_tokens_map.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

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+{"do_lower_case": false, "max_len": 512, "do_basic_tokenize": true, "never_split": ["+ك", "+كما", "ك+", "+وا", "+ين", "و+", "+كن", "+ان", "+هم", "+ة", "[بريد]", "لل+", "+ي", "+ت", "+ن", "س+", "ل+", "[مستخدم]", "+كم", "+ا", "ب+", "ف+", "+نا", "+ها", "+ون", "+هما", "ال+", "+ه", "+هن", "+ات", "[رابط]"], "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "name_or_path": "aubmindlab/bert-large-arabertv2"}