Adding Evaluation Results

README.md

@@ -16,4 +16,17 @@ inference:
 ---
 A pre-trained language model, based on the Mistral 7B model, has been scaled down to approximately 248 million parameters. Currently, this model has been trained on 2,120,000 examples. The batch size will remain low for future epochs. This model isn't intended for direct use but for fine-tuning on a downstream task.
 
-During evaluation on InstructMix, this model achieved an average perplexity score of 6.3. More training sessions are planned for this model.
+During evaluation on InstructMix, this model achieved an average perplexity score of 6.3. More training sessions are planned for this 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_Locutusque__TinyMistral-248m)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 24.18   |
+| ARC (25-shot)         | 20.82          |
+| HellaSwag (10-shot)   | 26.98    |
+| MMLU (5-shot)         | 23.11         |
+| TruthfulQA (0-shot)   | 46.89   |
+| Winogrande (5-shot)   | 50.75   |
+| GSM8K (5-shot)        | 0.0        |
+| DROP (3-shot)         | 0.74         |