Update README.md

README.md

@@ -45,14 +45,14 @@ As of 27 Sept 2024, Llama-3.1-Nemotron-70B-Reward performs best Overall on Rewar
   | Meta-Llama-3.1-70B-Instruct | Not fully disclosed | 84.0 | 97.2 | 70.2 | 82.8 | 86.0 |
 
        
-To better understand why it struggles in the Chat-Hard category, we analyzed the scores for each consistutent subset of Chat-Hard category. We find that on categories that uses human annotations as ground truth, Llama-3.1-Nemotron-70B-Reward performs similar to Skywork-Reward-Gemma-2-27B (<= 2.2% difference.)
-On the other hand, when GPT-4 annotations are used as Ground-Truth, we trail substantially behind Skywork-Reward-Gemma-2-27B by 10.8 to 19.2%. This suggests that Skywork-Reward-Gemma-2-27B might better suited at modelling GPT-4 preference, likely contributed by the inclusion of GPT-4 annotated training data used to train it found in the [OffSetBias dataset](https://huggingface.co/datasets/NCSOFT/offsetbias) as part of the [Skywork-Reward-Preference-80k](https://huggingface.co/datasets/Skywork/Skywork-Reward-Preference-80K-v0.1).
+To better understand why Llama-3.1-Nemotron-70B-Reward does less well in the Chat-Hard category, we analyze the scores for each consistutent subset under the  Chat-Hard category. We find that on categories that uses human annotations as ground truth, Llama-3.1-Nemotron-70B-Reward performs similar to Skywork-Reward-Gemma-2-27B (<= 2.2% difference).
+On the other hand, when GPT-4 annotations are used as Ground-Truth, Llama-3.1-Nemotron-70B-Reward trails substantially behind Skywork-Reward-Gemma-2-27B (10.8 to 19.2%). This suggests that Skywork-Reward-Gemma-2-27B can better modelling GPT-4 preference (than human-annotated preferences), likely contributed by the inclusion of GPT-4 annotated training data used to train it found in the [OffSetBias dataset](https://huggingface.co/datasets/NCSOFT/offsetbias) as part of the [Skywork-Reward-Preference-80k](https://huggingface.co/datasets/Skywork/Skywork-Reward-Preference-80K-v0.1).
 
 
 
 | Model  | Type of Data Used For Training |  Chat-Hard | LLMBar-Adversarial-Manual  | LLMBar-Adversarial-Neighbour | LLMBar-Natural | LLMBar-Adversarial-GPTInst | LLMBar-Adversarial-GPTOut | MT-Bench-Hard| 
 |:-----------------------------|:----------------|:-----|:----------|:-------|:----------|:-----------------------|:-----------------------|:-----------------------|
-|||| Human as Ground Truth | Human as Ground Truth | Human as Ground Truth | GPT-4 as Ground Truth |GPT-4 as Ground Truth |GPT-4 as Ground Truth |
+|||| Human as Ground Truth | Human as Ground Truth | Human as Ground Truth | _GPT-4 as Ground Truth_ |_GPT-4 as Ground Truth_ | _GPT-4 as Ground Truth_ |
 | Llama-3.1-Nemotron-70B-Reward |Permissive Licensed Data Only (CC-BY-4.0) | 85.8 | 76.1  |  88.8  |  95.0  |  87.0  | 72.3  |  75.7 
 | Skywork-Reward-Gemma-2-27B | Includes GPT4 Generated Data |  91.4  |  78.3  |  89.6  |  96.0  |  97.8  |  91.5 | 86.5|