| --- |
| language: my |
| tags: |
| - MyanBERTa |
| - Myanmar |
| - BERT |
| - RoBERTa |
| license: apache-2.0 |
| datasets: |
| - MyCorpus |
| - Web |
| --- |
| |
| ## Model description |
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| This model is a BERT based Myanmar pre-trained language model. |
| MyanBERTa was pre-trained for 528K steps on a word segmented Myanmar dataset consisting of 5,992,299 sentences (136M words). |
| As the tokenizer, byte-leve BPE tokenizer of 30,522 subword units which is learned after word segmentation is applied. |
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| Cite this work as: |
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| ``` |
| Aye Mya Hlaing, Win Pa Pa, "MyanBERTa: A Pre-trained Language Model For |
| Myanmar", In Proceedings of 2022 International Conference on Communication and Computer Research (ICCR2022), November 2022, Seoul, Republic of Korea |
| ``` |
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| [Download Paper](https://journal-home.s3.ap-northeast-2.amazonaws.com/site/iccr2022/abs/QOHFI-0004.pdf) |
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