Update README.md

README.md

@@ -76,7 +76,7 @@ output_text = tokenizer.decode(output[0], skip_special_tokens=True)
 - We conducted a performance evaluation based on the tasks being evaluated on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
 We evaluated our model on four benchmark datasets, which include `ARC-Challenge`, `HellaSwag`, `MMLU`, and `TruthfulQA`.
 We used the [lm-evaluation-harness repository](https://github.com/EleutherAI/lm-evaluation-harness), specifically commit [b281b0921b636bc36ad05c0b0b0763bd6dd43463](https://github.com/EleutherAI/lm-evaluation-harness/tree/b281b0921b636bc36ad05c0b0b0763bd6dd43463).
-- We used [MT-bench](https://github.com/lm-sys/FastChat/tree/main/fastchat/llm_judge), a set of challenging multi-turn open-ended questions to evaluate models.
+- We used [MT-bench](https://github.com/lm-sys/FastChat/tree/main/fastchat/llm_judge), a set of challenging multi-turn open-ended questions, to evaluate the models.
 
 ### Main Results
 | Model | H4(Avg) | ARC | HellaSwag | MMLU | TruthfulQA | | MT_Bench |
@@ -90,7 +90,7 @@ We used the [lm-evaluation-harness repository](https://github.com/EleutherAI/lm-
 | llama-65b | 64.2 | 63.5 | 86.1 | 63.9 | 43.4 | | |
 | falcon-40b-instruct | 63.4 | 61.6 | 84.3 | 55.4 | 52.5 | | |
 
-### Scripts
+### Scripts for H4 Score Reproduction
 - Prepare evaluation environments:
 ```
 # clone the repository