Update README.md

README.md

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 # AlignScoreCS
 
 A MultiTask multilingual model is developed to assess factual consistency in context-claim pairs across various Natural Language Understanding (NLU) tasks,
-including Summarization, Question Answering (QA), Semantic Textual Similarity (STS), Paraphrase, Fact Verification (FV), and Natural Language Inference (NLI).
-AlignScoreCS is fine-tuned on a vast multi-task dataset consisting of 7 million documents, encompassing these NLU tasks in both Czech and English languages.
-Its multilingual pre-training enables its potential utilization in various other languages. The architecture is capable of processing tasks using regression,
+including **Summarization**, **Question Answering (QA)**, **Semantic Textual Similarity (STS)**, **Paraphrase**, **Fact Verification (FV)**, and **Natural Language Inference (NLI)**.
+AlignScoreCS is fine-tuned on a vast multi-task dataset consisting of 7 million documents, encompassing these NLU tasks in both **Czech** and **English** languages.
+Its multilingual pre-training enables its potential utilization in **various other languages**. The architecture is capable of processing tasks using regression,
 binary classification, or ternary classification, although for evaluation purposes, we recommend employing the AlignScore function.
 
 This work is influenced by its English counterpart [AlignScore: Evaluating Factual Consistency with a Unified Alignment Function](https://arxiv.org/abs/2305.16739).