Update README.md

README.md

@@ -8,7 +8,7 @@
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-In this repo, we present a reward model trained by the framework [LMFlow](https://github.com/OptimalScale/LMFlow). The reward model is for the [HH-RLHF dataset](Dahoas/full-hh-rlhf), and is trained from the base model [openlm-research/open_llama_3b](https://huggingface.co/openlm-research/open_llama_3b). 
+In this repo, we present a reward model trained by the framework [LMFlow](https://github.com/OptimalScale/LMFlow). The reward model is for the [HH-RLHF dataset](Dahoas/full-hh-rlhf) (helpful part only), and is trained from the base model [openlm-research/open_llama_3b](https://huggingface.co/openlm-research/open_llama_3b). 
 
 ## Model Details
 
@@ -16,7 +16,7 @@ In this repo, we present a reward model trained by the framework [LMFlow](https:
 
 <!-- Provide a longer summary of what this model is. -->
 
-The HH-RLHF dataset contains 112K comparison samples in the training set and 12.5K comparison samples in the test set. We first replace the ``\n\nHuman'' and ``\n\nAssistant'' in the dataset by ``###Human'' and ``###Assistant'', respectively.
+The HH-RLHF-Helpful dataset contains 112K comparison samples in the training set and 12.5K comparison samples in the test set. We first replace the ``\n\nHuman'' and ``\n\nAssistant'' in the dataset by ``###Human'' and ``###Assistant'', respectively.
 
 Then, we split the dataset as follows: