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

@@ -2,6 +2,109 @@
 license: mit
 datasets:
 - Intel/orca_dpo_pairs
+model-index:
+- name: SOLAR-10B-Nector-DPO-Jawade
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 71.33
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bhavinjawade/SOLAR-10B-Nector-DPO-Jawade
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 88.62
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bhavinjawade/SOLAR-10B-Nector-DPO-Jawade
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 66.22
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bhavinjawade/SOLAR-10B-Nector-DPO-Jawade
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 70.92
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bhavinjawade/SOLAR-10B-Nector-DPO-Jawade
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 83.43
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bhavinjawade/SOLAR-10B-Nector-DPO-Jawade
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 64.59
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bhavinjawade/SOLAR-10B-Nector-DPO-Jawade
+      name: Open LLM Leaderboard
 ---
 
 ## SOLAR-10B-Nectar-Orca-DPO-LoRA-Jawade
@@ -74,4 +177,17 @@ This setup allows you to utilize the capabilities of the **bhavinjawade/SOLAR-10
 - **Technique Used**: LoRA (Low-Rank Adaptation)
 
 ### Contact Information
-- https://bhavinjawade.github.io
+- https://bhavinjawade.github.io
+# [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_bhavinjawade__SOLAR-10B-Nector-DPO-Jawade)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |74.19|
+|AI2 Reasoning Challenge (25-Shot)|71.33|
+|HellaSwag (10-Shot)              |88.62|
+|MMLU (5-Shot)                    |66.22|
+|TruthfulQA (0-shot)              |70.92|
+|Winogrande (5-shot)              |83.43|
+|GSM8k (5-shot)                   |64.59|
+