Update README.md

README.md

@@ -30,6 +30,7 @@ Aligned with **DPO**
 2. [Model Details](#model-details)
    - [Prompt template](#prompt-template)
    - [Training Dataset](#training-dataset)
+   - [Data Contamination Test](#data-contamination-test-results)
 3. [Evaluation](#evaluation)
 5. [Disclaimer](#disclaimer)
 6. [Contact](#contact)
@@ -55,11 +56,29 @@ Aligned with **DPO**
 
 SauerkrautLM-Mixtral-8x7B-Instruct was trained with mix of German data augmentation and translated data. 
 Aligned through **DPO** with our **new German SauerkrautLM-DPO dataset** based on parts of the SFT SauerkrautLM dataset 
-as chosen answers and [Sauerkraut-7b-HerO](https://huggingface.co/VAGOsolutions/SauerkrautLM-7b-HerO) as rejected answers. Added with additional **translated Parts of the [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized)** and **[argilla/distilabel-math-preference-dpo](https://huggingface.co/datasets/argilla/distilabel-math-preference-dpo).**  
+as chosen answers and [Sauerkraut-7b-HerO](https://huggingface.co/VAGOsolutions/SauerkrautLM-7b-HerO) as rejected answers. Added with additional **translated Parts of the [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized)** (Our dataset do not contain any TruthfulQA prompts - check Data Contamination Test Results) and **[argilla/distilabel-math-preference-dpo](https://huggingface.co/datasets/argilla/distilabel-math-preference-dpo).**  
 We found, that only a simple translation of training data can lead to unnatural German phrasings. 
 Data augmentation techniques were used to grant grammatical, syntactical correctness and a more natural German wording in our training data. 
 
+### Data Contamination Test Results
 
+Some models on the HuggingFace leaderboard had problems with wrong data getting mixed in.
+We checked our SauerkrautLM-DPO dataset with a special test [1] on a smaller model for this problem. 
+The HuggingFace team used the same methods [2, 3].
+
+Our results, with `result < 0.1, %:` being well below 0.9, indicate that our dataset is free from contamination.
+
+*The data contamination test results of HellaSwag and Winograde will be added once [1] supports them.*
+
+| Dataset                        | ARC   | MMLU | TruthfulQA | GSM8K |
+|------------------------------|-------|-------|-------|-------|
+| **SauerkrautLM-DPO**| result < 0.1, %: 0.0 |result < 0.1, %: 0.09 | result < 0.1, %: 0.13 | result < 0.1, %: 0.16 |
+
+[1] https://github.com/swj0419/detect-pretrain-code-contamination
+
+[2] https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/474#657f2245365456e362412a06
+
+[3] https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/265#657b6debf81f6b44b8966230
 
 ### Prompt Template:
 ```