From this dataset, 4 different copies training data from myXNLI were concatenated, each with sentence pairs in en-en, en-my, my-en and my-my combinations.
Training on cross-matched language data as above improved the NLI accuracy over training separately in each language.
This approach was inspired by another model https://huggingface.co/joeddav/xlm-roberta-large-xnli
The model was fine-tuned using this combined dataset for a single epoch.
Evaluation
This model has been evaluted on myXNLI testset for Myanmar accuracy. We also provide the accuracy for English using XNLI testset.