Update README.md

README.md

@@ -20,7 +20,7 @@ SEA-LION stands for <i>Southeast Asian Languages In One Network</i>.
 
 ### Model Description
 
-The SEA-LION model is a significant leap forward in the field of Natural Language Processing,
+The LLaMA3 8B SEA-LIONv model is a significant leap forward in the field of Natural Language Processing,
 specifically trained to understand the SEA regional context.
 
 For tokenization, the model employs the default tokenizer used in Meta-Llama-3-8B-Instruct.
@@ -35,7 +35,7 @@ The continued pre-training data for LLaMA3 8B SEA-LIONv2 base model encompasses
 
 ### Performance Benchmarks
 
-SEA-LION has an average performance on general tasks in English (as measured by Hugging Face's LLM Leaderboard):
+LLaMA3 8B SEA-LIONv has a similar English performance with LLaMA3-8B-Base model:
 
 | Model                | ARC   | BBH   | HellaSwag | MMLU  | GSM8k  | Average |
 |----------------------|:-----:|:-----:|:---------:|:-----:|:------:|:-------:|
@@ -72,7 +72,7 @@ Note:
 
 ### Infrastructure
 
-SEA-LION was trained using [MosaicML Composer](https://github.com/mosaicml/composer)
+LLaMA3 8B SEA-LIONv2 was trained using [MosaicML Composer](https://github.com/mosaicml/composer)
 on the following hardware:
 
 | Training Details     | LLaMA3 8B SEA-LIONv2 |
@@ -126,11 +126,13 @@ Wayne Lau<br>
 Yeo Yeow Tong<br>
 Yong Xianbin<br>
 
+
 ## Acknowledgements
 
 AI Singapore is a national programme supported by the National Research Foundation, Singapore and hosted by the National University of Singapore.
 Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore.
 
+
 ## Contact
 
 For more info, please contact us using this [SEA-LION Inquiry Form](https://forms.gle/sLCUVb95wmGf43hi6)