Update README.md

README.md

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 # IN22-Conv
 
-IN-22 is a newly created comprehensive benchmark for evaluating machine translation performance in multi-domain, n-way parallel contexts across 22 Indic languages. IN22-Conv is the conversation domain subset of IN22. It is designed to assess translation quality in typical day-to-day conversational-style applications. The evaluation subset consists of 1024 sentences translated across 22 Indic languages enabling evaluation of MT systems across 506 directions.
+IN-22 is a newly created comprehensive benchmark for evaluating machine translation performance in multi-domain, n-way parallel contexts across 22 Indic languages. IN22-Conv is the conversation domain subset of IN22. It is designed to assess translation quality in typical day-to-day conversational-style applications. The evaluation subset consists of 1503 sentences translated across 22 Indic languages enabling evaluation of MT systems across 506 directions.
 
-Currently, we use it for sentence-level evaluation of MT systems but can be repurposed for document translation evaluation as well.
+Currently, we use it for sentence-level evaluation of MT systems but it can be repurposed for document translation evaluation as well.
 
 Here is the domain distribution of our IN22-Conv evaluation subset.