---
language:
- sv

---

# megatron.bert-large.bpe-64k-no_pretok.25k-steps

This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.

Training was done for 25k training steps using a batch size of 8k.

The model has multiple sibling models trained on the same dataset using different tokenizers or more/less parameters:
- [megatron.bert-base.bpe-32k-no_pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.bpe-32k-no_pretok.25k-steps)
- [megatron.bert-base.bpe-64k-no_pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.bpe-64k-no_pretok.25k-steps)
- [megatron.bert-base.spe-bpe-32k-no_pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.spe-bpe-32k-no_pretok.25k-steps)
- [megatron.bert-base.spe-bpe-32k-pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.spe-bpe-32k-pretok.25k-steps)
- [megatron.bert-base.spe-bpe-64k-no_pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.spe-bpe-64k-no_pretok.25k-steps)
- [megatron.bert-base.spe-bpe-64k-pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.spe-bpe-64k-pretok.25k-steps)
- [megatron.bert-base.unigram-32k-no_pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.unigram-32k-no_pretok.25k-steps)
- [megatron.bert-base.unigram-32k-pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.unigram-32k-pretok.25k-steps)
- [megatron.bert-base.unigram-64k-no_pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.unigram-64k-no_pretok.25k-steps)
- [megatron.bert-base.unigram-64k-pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.unigram-64k-pretok.25k-steps)
- [megatron.bert-base.wordpiece-32k-no_pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.wordpiece-32k-no_pretok.25k-steps)
- [megatron.bert-base.wordpiece-32k-pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.wordpiece-32k-pretok.25k-steps)
- [megatron.bert-base.wordpiece-64k-no_pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.wordpiece-64k-no_pretok.25k-steps)
- [megatron.bert-base.wordpiece-64k-pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-base.wordpiece-64k-pretok.25k-steps)
- [megatron.bert-large.bpe-64k-no_pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-large.bpe-64k-no_pretok.25k-steps)
- [megatron.bert-large.spe-bpe-32k-pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-large.spe-bpe-32k-pretok.25k-steps)
- [megatron.bert-large.unigram-32k-pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-large.unigram-32k-pretok.25k-steps)
- [megatron.bert-large.unigram-64k-pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-large.unigram-64k-pretok.25k-steps)
- [megatron.bert-large.wordpiece-32k-pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-large.wordpiece-32k-pretok.25k-steps)
- [megatron.bert-large.wordpiece-64k-pretok.25k-steps](https://huggingface.co/KBLab/megatron.bert-large.wordpiece-64k-pretok.25k-steps)


## Acknowledgements

The training was performed on the Luxembourg national supercomputer MeluXina.
The authors gratefully acknowledge the LuxProvide teams for their expert support.