Update README.md

README.md

@@ -127,6 +127,35 @@ DPO Finetuning was performed on the Dutch [BramVanroy/ultra_feedback_dutch_clean
 See [Qwen/Qwen1.5-7B-Chat](https://huggingface.co/Qwen/Qwen1.5-7B-Chat) for all information about the base model.
 
 
+
+## ScandEval Dutch Leaderboard Evaluation Results
+
+For evaluation results based on the Dutch language you can take a look at the site of ScandEval.
+
+This model achieves a score which is very close to the performance of GPT-3.5.
+
+[Dutch Natural Language Understanding](https://scandeval.com/dutch-nlu/)
+
+[Dutch Natural Language Generation](https://scandeval.com/dutch-nlg/)
+
+
+
+## [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_robinsmits__Qwen1.5-7B-Dutch-Chat)
+
+Note that these Evaluation Results are for the English language.
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |53.66|
+|AI2 Reasoning Challenge (25-Shot)|53.92|
+|HellaSwag (10-Shot)              |76.03|
+|MMLU (5-Shot)                    |62.38|
+|TruthfulQA (0-shot)              |45.34|
+|Winogrande (5-shot)              |68.82|
+|GSM8k (5-shot)                   |15.47|
+
+
 ## Model usage
 
 A basic example of how to use the finetuned model.
@@ -231,7 +260,7 @@ The following hyperparameters were used during training:
 - Tokenizers 0.15.2
 
 ## Citation
-Thanks to the creators of Qwen1.5 for there great work!
+Thanks to the creators of Qwen1.5 for their great work!
 ```
 @article{qwen,
   title={Qwen Technical Report},
@@ -240,16 +269,3 @@ Thanks to the creators of Qwen1.5 for there great work!
   year={2023}
 }
 ```
-# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
-Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_robinsmits__Qwen1.5-7B-Dutch-Chat)
-
-|             Metric              |Value|
-|---------------------------------|----:|
-|Avg.                             |53.66|
-|AI2 Reasoning Challenge (25-Shot)|53.92|
-|HellaSwag (10-Shot)              |76.03|
-|MMLU (5-Shot)                    |62.38|
-|TruthfulQA (0-shot)              |45.34|
-|Winogrande (5-shot)              |68.82|
-|GSM8k (5-shot)                   |15.47|
-