Adding Evaluation Results

This is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr

The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.

If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions

README.md

@@ -2,3 +2,17 @@
 language: en
 ---
 This is a Hugging Face transformers-compatible conversion of the original dense 2.7B-parameter model from the paper "[Efficient Large Scale Language Modeling with Mixtures of Experts](https://arxiv.org/abs/2112.10684)" from Artetxe et al. Please refer to the original model card, which can be found at https://github.com/facebookresearch/fairseq/blob/main/examples/moe_lm/model_card.md.
+
+# [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_KoboldAI__fairseq-dense-2.7B)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 33.67   |
+| ARC (25-shot)         | 33.79          |
+| HellaSwag (10-shot)   | 65.74    |
+| MMLU (5-shot)         | 26.44         |
+| TruthfulQA (0-shot)   | 34.57   |
+| Winogrande (5-shot)   | 63.93   |
+| GSM8K (5-shot)        | 0.0        |
+| DROP (3-shot)         | 11.24         |