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  ---
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- dataset_info:
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- features:
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- - name: tokens
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- sequence: string
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- - name: ner_tags
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- sequence: string
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- - name: input_ids
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- sequence: int32
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- - name: attention_mask
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- sequence: int8
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- - name: labels
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- sequence: int64
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- splits:
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- - name: train
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- num_bytes: 3246469
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- num_examples: 6084
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- - name: dev
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- num_bytes: 356584
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- num_examples: 676
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- - name: test
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- num_bytes: 866291
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- num_examples: 1685
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- download_size: 879921
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- dataset_size: 4469344
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  ---
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- # Dataset Card for "m0_fine_tuning_ref_cmbert_io"
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- [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ language:
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+ - fr
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+ multilinguality:
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+ - monolingual
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+ task_categories:
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+ - token-classification
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
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+ # m0_fine_tuning_ref_cmbert_io
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+
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+ ## Introduction
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+
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+ This dataset was used to fine-tuned [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) for **flat NER task** using Flat NER approach [M0].
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+ It contains 19th-century Paris trade directories' entries.
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+
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+ ## Dataset parameters
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+
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+ * Approach : M0
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+ * Dataset type : ground-truth
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+ * Tokenizer : [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner)
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+ * Tagging format : IO
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+ * Counts :
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+ * Train : 6084
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+ * Dev : 676
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+ * Test : 1685
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+ * Associated fine-tuned model : [nlpso/m0_flat_ner_ref_cmbert_io](https://huggingface.co/nlpso/m0_flat_ner_ref_cmbert_io)
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+
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+ ## Entity types
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+
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+ Abbreviation|Description
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+ -|-
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+ O |Outside of a named entity
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+ PER |Person or company name
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+ ACT |Person or company professional activity
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+ TITRE |Distinction
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+ LOC |Street name
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+ CARDINAL |Street number
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+ FT |Geographical feature
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+
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+ ## How to use this dataset
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ train_dev_test = load_dataset("nlpso/m0_fine_tuning_ref_cmbert_io")