Update README.md

README.md

@@ -25,7 +25,9 @@ pipeline_tag: text-generation
 ### Used Datasets
 - Orca-style dataset
 - Alpaca-style dataset
-- No other data was used except for the dataset mentioned above
+- No other dataset was used except for the dataset mentioned above
+- No benchmark test set or the training set are used
+
 
 ### Prompt Template
 ```
@@ -41,7 +43,7 @@ pipeline_tag: text-generation
 
 ## Usage
 
-- Tested on A100 80GB
+- The followings are tested on A100 80GB
 - Our model can handle up to 10k+ input tokens, thanks to the `rope_scaling` option
 
 ```python
@@ -74,7 +76,7 @@ output_text = tokenizer.decode(output[0], skip_special_tokens=True)
 ## Evaluation Results
 
 ### Overview
-- 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 conducted a performance evaluation following 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 the models
@@ -102,12 +104,9 @@ git checkout b281b0921b636bc36ad05c0b0b0763bd6dd43463
 cd lm-evaluation-harness
 ```
 
-## Ethical Issues
-
-### Ethical Considerations
-- There were no ethical issues involved, as we did not include the benchmark test set or the training set in the model's training process
-
 ## Contact Us
 
-### Why Upstage LLM?
-- [Upstage](https://en.upstage.ai)'s LLM research has yielded remarkable results. As of August 1st, our 70B model has reached the top spot in openLLM rankings, marking itself as the current leading performer globally. Recognizing the immense potential in implementing private LLM to actual businesses, we invite you to easily apply private LLM and fine-tune it with your own data. For a seamless and tailored solution, please do not hesitate to reach out to us. ► [click here to contact](https://www.upstage.ai/private-llm?utm_source=huggingface&utm_medium=link&utm_campaign=privatellm)
+### About Upstage
+- [Upstage](https://en.upstage.ai) is a company specialized in Large Language Models (LLMs) and AI. We will help you build private LLMs and related applications.
+If you have a dataset to build domain specific LLMs or make LLM applications, please contact us at ► [click here to contact](https://www.upstage.ai/private-llm?utm_source=huggingface&utm_medium=link&utm_campaign=privatellm)
+- As of August 1st, our 70B model has reached the top spot in openLLM rankings, marking itself as the current leading performer globally.