Create README.md

README.md

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+Pre-trained evaluator in EMNLP 2022 paper
+*[Towards a Unified Multi-Dimensional Evaluator for Text Generation](https://arxiv.org/abs/2210.07197)*
+
+## Introduction
+
+**Multi-dimensional evaluation** is the dominant paradigm for human evaluation in Natural Language Generation (NLG), i.e., evaluating the generated text from multiple explainable dimensions, such as coherence and fluency.
+
+However, automatic evaluation in NLG is still dominated by similarity-based metrics (e.g., ROUGE, BLEU), but they are not sufficient to portray the difference between the advanced generation models.
+
+Therefore, we propose **UniEval** to bridge this gap so that a more comprehensive and fine-grained evaluation of NLG systems can be achieved.
+
+## Pre-trained Evaluator
+
+**unieval-sum** is the pre-trained evaluator for the text summarization task. It can evaluate the model output from four dimensions:
+- *coherence*
+- *consistency*
+- *fluency*
+- *relevance*
+
+It can also be transferred to the new dimensions and generation tasks, such as *naturalness* and *informativeness* for data-to-text.
+
+## Usage 
+
+Please refer to [our GitHub repository](https://github.com/maszhongming/UniEval).