binbin83/fr_present_tense_value

Description

This model was built to compute detect diffferent value of present tense in French (them). It's main purpose was to automate annotation on a specific dataset. There is no waranty that it will work on any others dataset. We finetune, the camembert-base model using this code; https://github.com/psycholinguistics2125/train_NER. Tthe present tense might have different meanings depending on the context. It can have a historical value, referring to the past, and it also makes the speech more alive. Another meaning is generic, to express general truths like definitions or properties. Finally, it can have an enunciation value by referring to the present moment, to describe an ongoing action. These different values of the present tense can only be differentiated by the context. This is the reason why models based on contextual embedding (BERT like) should be relevant to differentiate them.

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Feature	Description
Name	fr_present_tense_value
Version	0.0.1
spaCy	>=3.4.4,<3.5.0
Default Pipeline	transformer, ner
Components	transformer, ner
Vectors	0 keys, 0 unique vectors (0 dimensions)
Sources	n/a
License	agpl-3.0
Author	n/a

Label Scheme

View label scheme (3 labels for 1 components)

Component	Labels
ner	PRESENT_ENNONCIATION, PRESENT_GENERIQUE, PRESENT_HISTORIQUE

Accuracy

Type	Score
ENTS_F	78.62
ENTS_P	77.58
ENTS_R	79.70

training

We constructed our dataset by manually labeling the documents using Doccano, an open-source tool for collaborative human annotation. The models were trained using 200-word length sequences, 70% of the data were used for the training, 20% to test and finetune hyperparameters, and 10% to evaluate the performances of the model. In order to ensure correct performance evaluation, the evaluation sequences were taken from documents that were not used during the training.

label	train	test	valid
PRESENT_ENNONCIATION	2069	673	438
PRESENT_GENERIQUE	704	177	147
PRESENT_HISTORIQUE	1005	289	285