Datasetpublic

nlpso/m0_fine_tuning_ocr_cmbert_io

m0_fine_tuning_ocr_cmbert_io Introduction This dataset was used to fine-tuned 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 : noisy (Pero OCR) Tokenizer : Jean-Baptiste/camembert-ner Tagging format : IO Counts : Train : 6084 Dev : 676 Test : 1685 Associated fine-tuned model : nlpso/m0_flat_ner_ocr_cmbert_io… See the full description on the dataset page: https://huggingface.co/datasets/nlpso/m0_fine_tuning_ocr_cmbert_io.

sourceHugging Faceupdated 4y agoView on Hugging Face

0likes50downloads

Dataset Card

m0finetuningocrcmbert_io

Introduction

This dataset was used to fine-tuned 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 : noisy (Pero OCR)
—Tokenizer : Jean-Baptiste/camembert-ner
—Tagging format : IO
—Counts :
—Train : 6084
—Dev : 676
—Test : 1685
—Associated fine-tuned model : nlpso/m0_flat_ner_ocr_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_ocr_cmbert_io")