---
license: mit
datasets:
- opus100
- un_multi
language:
- en
- ar
---
 M2M100 418M 

M2M100 is a multilingual encoder-decoder transformer model trained for Many-to-Many multilingual translation. The model, originally introduced by researchers at Facebook, demonstrates impressive performance in cross-lingual translation tasks. 
For a better understanding of M2M100 you can look into the [paper](https://arxiv.org/abs/2010.11125) and the associated [repository](https://github.com/facebookresearch/fairseq/tree/main/examples/m2m_100).  
To further enhance the capabilities of M2M100, we conducted finetuning experiments on English-to-Arabic parallel text. The finetuning process involved training the model for 1000K steps using a batch size of 8.