This model was built to compute detect the lexical field of body, physical sensation and perception.
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.
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.
