Adding Evaluation Results

README.md

@@ -80,4 +80,17 @@ while True:
     print(out)
 ```
 ## Deploying and training the model
-The model has been fine-tuned on a specific input format that goes like this ```"<|USER|> {user prompt} <|ASSISTANT|> {model prediction} ".``` For the best performance from the model the input text should be as follows ```<|USER|> {dataset prompt} <|ASSISTANT|> ``` and the target/label should be as follows ```<|USER|> {dataset prompt} <|ASSISTANT|> {dataset output} ```. This model is also very fun to play with in text generation webui
+The model has been fine-tuned on a specific input format that goes like this ```"<|USER|> {user prompt} <|ASSISTANT|> {model prediction} ".``` For the best performance from the model the input text should be as follows ```<|USER|> {dataset prompt} <|ASSISTANT|> ``` and the target/label should be as follows ```<|USER|> {dataset prompt} <|ASSISTANT|> {dataset output} ```. This model is also very fun to play with in text generation webui
+# [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__gpt2-large-conversational)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 28.45   |
+| ARC (25-shot)         | 26.96          |
+| HellaSwag (10-shot)   | 44.98    |
+| MMLU (5-shot)         | 26.33         |
+| TruthfulQA (0-shot)   | 39.6   |
+| Winogrande (5-shot)   | 56.04   |
+| GSM8K (5-shot)        | 0.08        |
+| DROP (3-shot)         | 5.19         |