update readme

README.md

@@ -1,5 +1,16 @@
+---
+license: cc-by-nc-4.0
+language:
+- de
+tags:
+- embeddings
+- clustering
+- benchmark
+size_categories:
+- 10K<n<100K
+---
 This dataset can be used as a benchmark for clustering word embeddings for <b>German</b>. 
 
-The datasets contains book titles and is based on the dataset from the [GermEval 2019 Shared Task on Hierarchical Classification of Blurbs](https://www.inf.uni-hamburg.de/en/inst/ab/lt/resources/data/germeval-2019-hmc.html). It contains 17'726 unqiue samples, 28 splits with 177 to 16'425 samples and 4 to 93 unique classes. Splits are built similarly to [MTEB](https://github.com/embeddings-benchmark/mteb)'s [ArxivClusteringS2S](https://huggingface.co/datasets/mteb/arxiv-clustering-s2s) ([Paper](https://arxiv.org/abs/2210.07316)).
+The datasets contains book titles and is based on the dataset from the [GermEval 2019 Shared Task on Hierarchical Classification of Blurbs](https://www.inf.uni-hamburg.de/en/inst/ab/lt/resources/data/germeval-2019-hmc.html). It contains 17'726 unqiue samples, 28 splits with 177 to 16'425 samples and 4 to 93 unique classes. Splits are built similarly to [MTEB](https://github.com/embeddings-benchmark/mteb)'s [ArxivClusteringS2S](https://huggingface.co/datasets/mteb/arxiv-clustering-s2s).
 
 Have a look at [German Text Embedding Clustering Benchmark](https://github.com/ClimSocAna/tecb-de) for more infos, datasets and evaluation results.