Update README.md

README.md

@@ -33,7 +33,7 @@ Most notably, all the data in SHP is naturally occurring and human-written, wher
 | Dataset              | Size | Input                      | Label                       | # Domains           | Data Format                           | Length |
 | -------------------- | ---- | -------------------------- | ---------------------------- | ------------------------- | ------------------------------------- | --------------- |
 | SHP                  | 385K | Naturally occurring human-written responses   | Aggregate Human Preference  | 18 (labelled)  | Question/Instruction + Response  | up to 10.1K T5 tokens |
-| HH-RLHF    | 91K | Dialogue with LLM  | Individual Human Preference  | not labelled (aside from harmless/helpful)   | Multi-turn Dialogue              | up to 1.5K T5 tokens |
+| HH-RLHF    | 91K | Dialogue with LLM  | Individual Human Preference  | not labelled   | Multi-turn Dialogue              | up to 1.5K T5 tokens |
 
 How is SHP different from other datasets that have scraped Reddit, like [ELI5](https://huggingface.co/datasets/eli5#source-data)?
 Most notably, SHP uses the timestamp information to infer preferences, while ELI5 only provides comments and scores -- the latter are not enough to infer preferences since comments made earlier tend to get higher scores from more visibility.