(BERT large) Language modeling in the legal domain in Portuguese (LeNER-Br)
bert-large-cased-pt-lenerbr is a Language Model in the legal domain in Portuguese that was finetuned on 20/12/2021 in Google Colab from the model BERTimbau large on the dataset LeNER-Br language modeling by using a MASK objective.
You can check as well the version base of this model.
Widget & APP
You can test this model into the widget of this page.
Blog post
This language model is used to get a NER model on the Portuguese judicial domain. You can check the fine-tuned NER model at pierreguillou/ner-bert-large-cased-pt-lenerbr.
All informations and links are in this blog post: NLP | Modelos e Web App para Reconhecimento de Entidade Nomeada (NER) no domínio jurídico brasileiro (29/12/2021)
Using the model for inference in production
# install pytorch: check https://pytorch.org/
# !pip install transformers
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("pierreguillou/bert-large-cased-pt-lenerbr")
model = AutoModelForMaskedLM.from_pretrained("pierreguillou/bert-large-cased-pt-lenerbr")
Training procedure
Notebook
The notebook of finetuning (Finetuning_language_model_BERtimbau_LeNER_Br.ipynb) is in github.
Training results
Num examples = 3227
Num Epochs = 5
Instantaneous batch size per device = 2
Total train batch size (w. parallel, distributed & accumulation) = 8
Gradient Accumulation steps = 4
Total optimization steps = 2015
Step Training Loss Validation Loss
100 1.616700 1.366015
200 1.452000 1.312473
300 1.431100 1.253055
400 1.407500 1.264705
500 1.301900 1.243277
600 1.317800 1.233684
700 1.319100 1.211826
800 1.303800 1.190818
900 1.262800 1.171898
1000 1.235900 1.146275
1100 1.221900 1.149027
1200 1.226200 1.127950
1300 1.201700 1.172729
1400 1.198200 1.145363