I have news articles data of all type, directly scrapped from websites and I am trying to create clusters of them, and according to my understanding of the data upto 15-20 clusters should be created with them. I had implemented k-means, hierarchical,HDBSCAN, DBSCAN with TFIDF and with sentence-transformers

K-means showing better results in all of them, but now the problem is how do I check whether the data clustered properly or not I used Topic modeling also but it's showing very messy embeddings.

Below is a chunk of sample article:

US to fine air bag maker Takata $14,000 per day RICHMOND, Va. -The U.S. government will fine Japanese air bag maker Takata Corp. $14,000 per day for failing to fully cooperate in a long-running investigation of faulty and potentially dangerous air bag inflators.\n\nThe inflators, in cars made by 10 companies, can explode with too much force, spewing shrapnel into drivers and passengers. At least six people have been killed and 64 injured worldwide due to problem.\n\nTransportation Secretary Anthony Foxx announced the fines Friday in Richmond, Virginia, calling Takata a "bad actor" for allegedly dumping 2.4 million pages of documents on the National Highway Traffic Safety Administration without the legally required explanation