How can we perform STS(Semantic Textual Similarity) on UnSupervised dataset using Deep Learning?
You could take pretrained embedder and look for distances between the embeddings.
There's LASER from Facebook. This is an unofficial pypi package, it replaces some of the internal tools used for tokenization and BPE encodings. I've used it extensively and it works just fine. It encodes your text as 1024-element numerical vector. Then you can just calculate distance metric between embeddings i.e. euclidean.