First versin with dates

README.md

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+---
+language: fr
+datasets:
+- Jean-Baptiste/wikiner_fr
+widget:
+- text: "Je m'appelle jean-baptiste et j'habite à montréal depuis fevr 2012"
+---
+
+# camembert-ner: model fine-tuned from camemBERT for NER task.
+
+## Introduction
+
+[camembert-ner-with-dates] is an extension of french camembert-ner model with an additionnal tag for dates.
+Model was trained on enriched version of wikiner-fr dataset (~170 634  sentences).
+
+On my test data (mix of chat and email), this model got an f1 score of ~83% (in comparison dateparser was ~70%).
+Dateparser library can still be be used on the output of this model in order to convert text to python datetime object.
+https://dateparser.readthedocs.io/en/latest/
+
+
+## How to use camembert-ner with HuggingFace
+
+##### Load camembert-ner and its sub-word tokenizer :
+
+```python
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+
+tokenizer = AutoTokenizer.from_pretrained("Jean-Baptiste/camembert-ner")
+model = AutoModelForTokenClassification.from_pretrained("Jean-Baptiste/camembert-ner")
+
+
+##### Process text sample (from wikipedia)
+
+from transformers import pipeline
+
+nlp = pipeline('ner', model=model, tokenizer=tokenizer, grouped_entities=True)
+nlp("Apple est créée le 1er avril 1976 dans le garage de la maison d'enfance de Steve Jobs à Los Altos en Californie par Steve Jobs, Steve Wozniak et Ronald Wayne14, puis constituée sous forme de société le 3 janvier 1977 à l'origine sous le nom d'Apple Computer, mais pour ses 30 ans et pour refléter la diversification de ses produits, le mot « computer » est retiré le 9 janvier 2015.")
+
+
+[{'entity_group': 'ORG',
+  'score': 0.9776379466056824,
+  'word': 'Apple',
+  'start': 0,
+  'end': 5},
+ {'entity_group': 'DATE',
+  'score': 0.9793774570737567,
+  'word': 'le 1er avril 1976 dans le',
+  'start': 15,
+  'end': 41},
+ {'entity_group': 'PER',
+  'score': 0.9958226680755615,
+  'word': 'Steve Jobs',
+  'start': 74,
+  'end': 85},
+ {'entity_group': 'LOC',
+  'score': 0.995087186495463,
+  'word': 'Los Altos',
+  'start': 87,
+  'end': 97},
+ {'entity_group': 'LOC',
+  'score': 0.9953305125236511,
+  'word': 'Californie',
+  'start': 100,
+  'end': 111},
+ {'entity_group': 'PER',
+  'score': 0.9961076378822327,
+  'word': 'Steve Jobs',
+  'start': 115,
+  'end': 126},
+ {'entity_group': 'PER',
+  'score': 0.9960325956344604,
+  'word': 'Steve Wozniak',
+  'start': 127,
+  'end': 141},
+ {'entity_group': 'PER',
+  'score': 0.9957776467005411,
+  'word': 'Ronald Wayne',
+  'start': 144,
+  'end': 157},
+ {'entity_group': 'DATE',
+  'score': 0.994030773639679,
+  'word': 'le 3 janvier 1977 à',
+  'start': 198,
+  'end': 218},
+ {'entity_group': 'ORG',
+  'score': 0.9720810294151306,
+  'word': "d'Apple Computer",
+  'start': 240,
+  'end': 257},
+ {'entity_group': 'DATE',
+  'score': 0.9924157659212748,
+  'word': '30 ans et',
+  'start': 272,
+  'end': 282},
+ {'entity_group': 'DATE',
+  'score': 0.9934852868318558,
+  'word': 'le 9 janvier 2015.',
+  'start': 363,
+  'end': 382}]
+
+```
+
+
+## Model performances (metric: seqeval)
+
+Global
+```
+'precision': 0.928
+'recall': 0.928
+'f1': 0.928
+```
+
+By entity
+```
+Label LOC: (precision:0.929, recall:0.932, f1:0.931, support:9510)
+Label PER: (precision:0.952, recall:0.965, f1:0.959, support:9399)
+Label MISC: (precision:0.878, recall:0.844, f1:0.860, support:5364)
+Label ORG: (precision:0.848, recall:0.883, f1:0.865, support:2299)
+Label DATE: Not relevant because of method used to add date tag on wikiner dataset (estimated f1 ~90%)
+
+
+ ```
+

config.json

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+{
+  "_name_or_path": "models_data/models/camembert-base_forTokenCLassification",
+  "architectures": [
+    "CamembertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 5,
+  "eos_token_id": 6,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "LOC",
+    "2": "PER",
+    "3": "MISC",
+    "4": "ORG",
+    "5": "DATE"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "DATE": 5,
+    "LOC": 1,
+    "MISC": 3,
+    "O": 0,
+    "ORG": 4,
+    "PER": 2
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "camembert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.2.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 32005
+}

pytorch_model.bin

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+size 440233263

sentencepiece.bpe.model

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special_tokens_map.json

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+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": "<mask>", "additional_special_tokens": ["<s>NOTUSED", "</s>NOTUSED"]}

tokenizer_config.json

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+{"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "additional_special_tokens": ["<s>NOTUSED", "</s>NOTUSED"], "model_max_length": 512, "name_or_path": "models_data/models/camembert-base_forTokenCLassification", "special_tokens_map_file": "models_data/models/camembert-base_forTokenCLassification\\special_tokens_map.json"}