Adding Evaluation Results

README.md

@@ -50,4 +50,17 @@ print(tokenizer.decode(outputs[0],skip_special_tokens=True,clean_up_tokenization
 
 The model achieves a 63.1% pass@1 on HumanEval and a 45.2% pass@1 on MBPP, however it is evident that these benchmarks are not representative of real-world usage of code models so we are launching the [Code Models Arena](https://arena.glaive.ai/) to let users vote on model outputs so we can have a better understanding of user preference on code models and come up with new and better benchmarks. We plan to release the Arena results as soon as we have a sufficient amount of data.
 
-Join the Glaive [discord](https://discord.gg/fjQ4uf3yWD) for improvement suggestions, bug-reports and collaborating on more open-source projects.
+Join the Glaive [discord](https://discord.gg/fjQ4uf3yWD) for improvement suggestions, bug-reports and collaborating on more open-source projects.
+# [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_glaiveai__glaive-coder-7b)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 36.42   |
+| ARC (25-shot)         | 42.66          |
+| HellaSwag (10-shot)   | 64.69    |
+| MMLU (5-shot)         | 37.15         |
+| TruthfulQA (0-shot)   | 39.88   |
+| Winogrande (5-shot)   | 59.75   |
+| GSM8K (5-shot)        | 5.23        |
+| DROP (3-shot)         | 5.55         |