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---
language:
- fr
multilinguality:
- monolingual
task_categories:
- token-classification
---
# m0_fine_tuning_ref_cmbert_io
## Introduction
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].
It contains 19th-century Paris trade directories' entries.
## Dataset parameters
* Approach : M0
* Dataset type : ground-truth
* Tokenizer : [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner)
* Tagging format : IO
* Counts :
* Train : 6084
* Dev : 676
* Test : 1685
* Associated fine-tuned model : [nlpso/m0_flat_ner_ref_cmbert_io](https://huggingface.co/nlpso/m0_flat_ner_ref_cmbert_io)
## Entity types
Abbreviation|Description
-|-
O |Outside of a named entity
PER |Person or company name
ACT |Person or company professional activity
TITRE |Distinction
LOC |Street name
CARDINAL |Street number
FT |Geographical feature
## How to use this dataset
```python
from datasets import load_dataset
train_dev_test = load_dataset("nlpso/m0_fine_tuning_ref_cmbert_io")
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