how to provide samples in answerability and waht is the output for that

[mayankpathaklumiq]

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[saransh-mehta]

Hi @mayankpathaklumiq Thanks for writing. The concept of answerability is that given a query and a paragraph (context passage), determine where that query can be answered from given passage or not. Hence, the input is query, passage and label. Label is 0 (not-answerable) and 1 (for answerable). Similarly, the output produced will either be 0 or 1 while inferring on trained model. This is mentioned in the answerability example as well, which transforms the MSMARCO data for this task. After running the transformations part in above example, you can go to the data directory and checkout the created data files - msmarco_answerability_dev.tsv (or train/test) to know how is the final input data. PS. There was minor documentation error in the example in the transformation part which has been corrected.

[mayankpathaklumiq]

Thanks for your reply can you please mention the server requirements to train the model.

On Wed, Aug 12, 2020 at 1:05 PM Saransh Mehta [email protected] wrote:

Hi @mayankpathaklumiq https://github.com/mayankpathaklumiq Thanks for writing. The concept of answerability is that given a query and a paragraph (context passage), determine where that query can be answered from given passage or not. Hence, the input is query, passage and label. Label is 0 (not-answerable) and 1 (for answerable). Similarly, the output produced will either be 0 or 1 while inferring on trained model. This is mentioned in the answerability example as well, which transforms the MSMARCO data for this task. After running the transformations part in above example, you can go to the data directory and checkout the created data files - msmarco_answerability_dev.tsv (or train/test) to know how is the final input data.

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