add evaluation scores to readme

README.md

@@ -17,6 +17,17 @@ The smallest of [cerebras GPT models](https://huggingface.co/cerebras) with only
 
 Instruction fine-tuned [cerebras-GPT-111M](https://huggingface.co/cerebras/Cerebras-GPT-111M)
 
+## Evaluation
+
+The model has been evaluated with Huggingface's Open LLM leaderboard. Have a look at the leaderboard for more details: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
+The performance of the instruction fine-tuned model does improve compared to the cerebras base model:
+
+| Model                                          	| Average ⬆️ 	| ARC (25-shot) ⬆️ 	| HellaSwag (10-shot) ⬆️ 	| MMLU (5-shot) ⬆️ 	| TruthfulQA (0-shot) ⬆️ 	|
+|------------------------------------------------	|-----------	|-----------------	|-----------------------	|-----------------	|-----------------------	|
+| SebastianSchramm/Cerebras-GPT-111M-instruction 	| 31.6      	| 24.3            	| 26.2                  	| 26.5            	| 49.5                  	|
+| cerebras/Cerebras-GPT-111M                     	| 29.9      	| 20              	| 26.7                  	| 26.7            	| 46.3                  	|
+|                                                	|           	|                 	|                       	|                 	|                       	|
+
 ## Training data
 
 The model was fine-tuned with the following data: [alpaca_gpt4_data](https://github.com/Instruction-Tuning-with-GPT-4/GPT-4-LLM/blob/main/data/alpaca_gpt4_data.json) (data generated by GPT-4 using Alpaca prompts for fine-tuning LLMs) and [alpaca_data_cleaned](https://github.com/tloen/alpaca-lora/blob/a3027fea37c2087b8b0131b21a4cd948bbdcd9e0/alpaca_data_cleaned.json).