text: Title: Setting UMAP random seed seems to break the model results
  Body: I have a dataset of scientific abstracts. When I run the following code, I get ~65 topics:
  
  ```
  sentence_model = SentenceTransformer('allenai/scibert_scivocab_cased')
  topic_model = BERTopic(embedding_model=sentence_model)
  topics, probs = topic_model.fit_transform(docs)
  ```
  
  However, if I try defining a random seed in the UMAP model, I get only 2 topics and the outliers, no matter how I set the random seed:
  
  ```
  umap_model = UMAP(random_state=1234)
  sentence_model = SentenceTransformer('allenai/scibert_scivocab_cased')
  topic_model = BERTopic(embedding_model=sentence_model, umap_model=umap_model)
  topics, probs = topic_model.fit_transform(docs)
  ``` 
  
  This seems very weird to me; I wouldn't expect the random seed to have such a large effect on the model; but even if it does, I would expect different results when I change the value of the random seed, rather than the difference being between no random seed, and any random seed.
  
  Is this expected or is something weird going on?
  
  Thanks!