Adding Evaluation Results

README.md

@@ -75,3 +75,17 @@ model = AutoModelForCausalLM.from_pretrained("lgaalves/mistral-7b_open_platypus"
 ### Limitations and bias
 
 Mistral 7B and fine-tuned variants are a new technology that carries risks with use. Testing conducted to date has been in English, and has not covered, nor could it cover all scenarios. For these reasons, as with all LLMs, Llama 2 and any fine-tuned varient's potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications of Llama 2 variants, developers should perform safety testing and tuning tailored to their specific applications of the model.
+
+# [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_lgaalves__mistral-7b_open_platypus)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 49.19   |
+| ARC (25-shot)         | 55.8          |
+| HellaSwag (10-shot)   | 82.13    |
+| MMLU (5-shot)         | 59.76         |
+| TruthfulQA (0-shot)   | 48.87   |
+| Winogrande (5-shot)   | 78.61   |
+| GSM8K (5-shot)        | 12.59        |
+| DROP (3-shot)         | 6.59         |