--- language: ms tags: - melayu-bert license: mit datasets: - oscar widget: - text: "Saya [MASK] makan nasi hari ini." --- ## Melayu BERT Melayu BERT is a masked language model based on [BERT](https://arxiv.org/abs/1810.04805). It was trained on the [OSCAR](https://huggingface.co/datasets/oscar) dataset, specifically the `unshuffled_original_ms` subset. The model used was [English BERT model](https://huggingface.co/bert-base-uncased) and fine-tuned on the Malaysian dataset. The model achieved a perplexity of 9.46 on a 20% validation dataset. Many of the techniques used are based on a Hugging Face tutorial [notebook](https://github.com/huggingface/notebooks/blob/master/examples/language_modeling.ipynb) written by [Sylvain Gugger](https://github.com/sgugger), and [fine-tuning tutorial notebook](https://github.com/piegu/fastai-projects/blob/master/finetuning-English-GPT2-any-language-Portuguese-HuggingFace-fastaiv2.ipynb) written by [Pierre Guillou](https://huggingface.co/pierreguillou). The model is available both for PyTorch and TensorFlow use. ## Model The model was trained on 3 epochs with a learning rate of 2e-3 and achieved a training loss per steps as shown below. | Step |Training loss| |--------|-------------| |500 | 5.051300 | |1000 | 3.701700 | |1500 | 3.288600 | |2000 | 3.024000 | |2500 | 2.833500 | |3000 | 2.741600 | |3500 | 2.637900 | |4000 | 2.547900 | |4500 | 2.451500 | |5000 | 2.409600 | |5500 | 2.388300 | |6000 | 2.351600 | ## How to Use ### As Masked Language Model ```python from transformers import pipeline pretrained_name = "StevenLimcorn/MelayuBERT" fill_mask = pipeline( "fill-mask", model=pretrained_name, tokenizer=pretrained_name ) fill_mask("Saya [MASK] makan nasi hari ini.") ``` ### Import Tokenizer and Model ```python from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("StevenLimcorn/MelayuBERT") model = AutoModelForMaskedLM.from_pretrained("StevenLimcorn/MelayuBERT") ``` ## Author Melayu BERT was trained by [Steven Limcorn](https://github.com/stevenlimcorn) and [Wilson Wongso](https://hf.co/w11wo).