đ IndoBERT-Lite Base Model (phase2 - uncased)
IndoBERT is a state-of-the-art language model for Indonesian based on the BERT model. It is trained using masked language modeling (MLM) and next sentence prediction (NSP) objectives.
đ Quick Start
IndoBERT is a cutting - edge Indonesian language model built on the BERT architecture. The pre - trained model is optimized through masked language modeling (MLM) and next sentence prediction (NSP) tasks.
⨠Features
All Pre - trained Models
Property |
Details |
Model Type |
There are multiple pre - trained models including indobenchmark/indobert-base-p1 , indobenchmark/indobert-base-p2 , indobenchmark/indobert-large-p1 , indobenchmark/indobert-large-p2 , indobenchmark/indobert-lite-base-p1 , indobenchmark/indobert-lite-base-p2 , indobenchmark/indobert-lite-large-p1 , indobenchmark/indobert-lite-large-p2 . |
Training Data |
All models are trained on the Indo4B dataset which contains 23.43 GB of text. |
Model |
#params |
Arch. |
Training data |
indobenchmark/indobert-base-p1 |
124.5M |
Base |
Indo4B (23.43 GB of text) |
indobenchmark/indobert-base-p2 |
124.5M |
Base |
Indo4B (23.43 GB of text) |
indobenchmark/indobert-large-p1 |
335.2M |
Large |
Indo4B (23.43 GB of text) |
indobenchmark/indobert-large-p2 |
335.2M |
Large |
Indo4B (23.43 GB of text) |
indobenchmark/indobert-lite-base-p1 |
11.7M |
Base |
Indo4B (23.43 GB of text) |
indobenchmark/indobert-lite-base-p2 |
11.7M |
Base |
Indo4B (23.43 GB of text) |
indobenchmark/indobert-lite-large-p1 |
17.7M |
Large |
Indo4B (23.43 GB of text) |
indobenchmark/indobert-lite-large-p2 |
17.7M |
Large |
Indo4B (23.43 GB of text) |
đģ Usage Examples
Basic Usage
from transformers import BertTokenizer, AutoModel
tokenizer = BertTokenizer.from_pretrained("indobenchmark/indobert-lite-base-p2")
model = AutoModel.from_pretrained("indobenchmark/indobert-lite-base-p2")
Advanced Usage
x = torch.LongTensor(tokenizer.encode('aku adalah anak [MASK]')).view(1,-1)
print(x, model(x)[0].sum())
đ Documentation
Authors
IndoBERT was trained and evaluated by Bryan Wilie*, Karissa Vincentio*, Genta Indra Winata*, Samuel Cahyawijaya*, Xiaohong Li, Zhi Yuan Lim, Sidik Soleman, Rahmad Mahendra, Pascale Fung, Syafri Bahar, Ayu Purwarianti.
Citation
If you use our work, please cite:
@inproceedings{wilie2020indonlu,
title={IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding},
author={Bryan Wilie and Karissa Vincentio and Genta Indra Winata and Samuel Cahyawijaya and X. Li and Zhi Yuan Lim and S. Soleman and R. Mahendra and Pascale Fung and Syafri Bahar and A. Purwarianti},
booktitle={Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing},
year={2020}
}
đ License
This project is licensed under the MIT license.