Update README.md

README.md

@@ -192,25 +192,24 @@ dataset = load_dataset("Supa-AI/STEM-en-ms", name="data_ms")
 
 This document summarizes the evaluation results for various language models based on **5-shot** and **First Token Accuracy**. The evaluation was conducted across four configurations:
 
-
 | **Model**                         | **en\_withfigures** | **en\_withoutfigures** | **ms\_withfigures** | **ms\_withoutfigures** |
 | --------------------------------- | ------------------- | ---------------------- | ------------------- | ---------------------- |
-| **gemini-2.0-flash-exp**          | ******63.70%******          | ******75.16%******             | ****_63.36%_****          | ******75.47%******             |
-| **gemini-1.5-flash**              | **49.66%**          | **_67.39%_**             | **_50.00%_**          | **_64.28%_**             |
-| **Qwen/Qwen2-VL-72B-Instruct**    | **_58.22%_**          | **_69.25%_**             | **_57.53%_**          | **63.66%**             |
-| **gpt-4o**                        | **47.95%**          | **66.15%**             | **50.00%**          | **68.01%**             |
-| **gpt-4o-mini**                   | **41.10%**          | **55.90%**             | **38.36%**          | **52.80%**             |
-| **pixtral-large-2411**            | **42.81%**          | **64.29%**             | **35.27%**          | **60.87%**             |
-| **pixtral-12b-2409**              | **24.66%**          | **48.45%**             | **24.66%**          | **39.13%**             |
-| **DeepSeek-V3**                   | None                | ****79.19%****             | None                | **__76.40%__**             |
-| **Qwen2.5-72B-Instruct**          | None                | **__74.53%__**             | None                | **72.98%**             |
-| **Meta-Llama-3.3-70B-Instruct**   | None                | **67.08%**             | None                | **58.07%**             |
-| **Llama-3.2-90B-Vision-Instruct** | None                | **65.22%**             | None                | **58.07%**             |
-| **sail/Sailor2-20B-Chat**         | None                | **_66.46%_**             | None                | **61.68%**             |
-| **mallam-small**                  | None                | **61.49%**             | None                | **55.28%**             |
-| **mistral-large-latest**          | None                | **60.56%**             | None                | **53.42%**             |
-| **google/gemma-2-27b-it**         | None                | **58.07%**             | None                | **57.76%**             |
-| **SeaLLMs-v3-7B-Chat**            | None                | **50.93%**             | None                | **45.96%**             |
+| **gemini-2.0-flash-exp**          | **63.70%**          | <ins>75.16%</ins>      | **63.36%**          | <ins>75.47%</ins>      |
+| **gemini-1.5-flash**              | 49.66%              | 67.39%                 | 50.00%              | 64.28%                 |
+| **Qwen/Qwen2-VL-72B-Instruct**    | <ins>58.22%</ins>   | 69.25%                 | <ins>57.53%</ins>   | 63.66%                 |
+| **gpt-4o**                        | 47.95%              | 66.15%                 | 50.00%              | 68.01%                 |
+| **gpt-4o-mini**                   | 41.10%              | 55.90%                 | 38.36%              | 52.80%                 |
+| **pixtral-large-2411**            | 42.81%              | 64.29%                 | 35.27%              | 60.87%                 |
+| **pixtral-12b-2409**              | 24.66%              | 48.45%                 | 24.66%              | 39.13%                 |
+| **DeepSeek-V3**                   | None                | **79.19%**             | None                | **76.40%**             |
+| **Qwen2.5-72B-Instruct**          | None                | 74.53%                 | None                | 72.98%                 |
+| **Meta-Llama-3.3-70B-Instruct**   | None                | 67.08%                 | None                | 58.07%                 |
+| **Llama-3.2-90B-Vision-Instruct** | None                | 65.22%                 | None                | 58.07%                 |
+| **sail/Sailor2-20B-Chat**         | None                | 66.46%                 | None                | 61.68%                 |
+| **mallam-small**                  | None                | 61.49%                 | None                | 55.28%                 |
+| **mistral-large-latest**          | None                | 60.56%                 | None                | 53.42%                 |
+| **google/gemma-2-27b-it**         | None                | 58.07%                 | None                | 57.76%                 |
+| **SeaLLMs-v3-7B-Chat**            | None                | 50.93%                 | None                | 45.96%                 |
 
 ---
 
@@ -218,14 +217,19 @@ This document summarizes the evaluation results for various language models base
 
 In the repository, there is an `eval.py` script that can be used to run the evaluation for any other LLM.
 
-- The evaluation results are based on the specific dataset and methodology employed.
+The evaluation results are based on the specific dataset and methodology employed.
 - The "First Token Accuracy" metric emphasizes the accuracy of predicting the initial token correctly.
 - Further analysis might be needed to determine the models' suitability for specific tasks.
 
+### Attribution for Evaluation Code
+The `eval.py` script is based on work from the MMLU-Pro repository:
+- Repository: [TIGER-AI-Lab/MMLU-Pro](https://github.com/TIGER-AI-Lab/MMLU-Pro)
+- License: Apache License 2.0 (included in the `NOTICE` file)
+
 ---
 
-**Contributors**
-- [Gele](https://huggingface.co/Geleliong) 
-- [Ken Boon](https://huggingface.co/caibcai)
-- [Wei Wen](https://huggingface.co/WeiWen21)
+# **Contributors**
+- [**Gele**](https://huggingface.co/Geleliong) 
+- [**Ken Boon**](https://huggingface.co/caibcai)
+- [**Wei Wen**](https://huggingface.co/WeiWen21)