Adding Evaluation Results

README.md

@@ -1,13 +1,115 @@
 ---
 license: apache-2.0
+library_name: transformers
+tags:
+- dpo
 datasets:
 - argilla/distilabel-intel-orca-dpo-pairs
 base_model: sethuiyer/Chikuma_10.7B
-library_name: transformers
 pipeline_tag: text-generation
-tags:
-  - dpo
-  
+model-index:
+- name: distilabled_Chikuma_10.7B
+  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: 66.38
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/distilabled_Chikuma_10.7B
+      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: 85.14
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/distilabled_Chikuma_10.7B
+      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: 64.7
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/distilabled_Chikuma_10.7B
+      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: 59.2
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/distilabled_Chikuma_10.7B
+      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: 79.4
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/distilabled_Chikuma_10.7B
+      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: 58.38
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/distilabled_Chikuma_10.7B
+      name: Open LLM Leaderboard
 ---
 
 # Chikuma_10.7B - V2 (Enhanced with DPO) [For Experiments]
@@ -116,4 +218,17 @@ A heartfelt appreciation goes to the vibrant open-source community, particularly
 * The Intel team for publishing a great open dataset and show how well it worked in the first place 
 * Teknium and NousResearch for their awesome work and models.
 * Maxime for sharing such great resources.
-* Argilla for publishing argilla/distilabel-intel-orca-dpo-pairs
+* Argilla for publishing argilla/distilabel-intel-orca-dpo-pairs
+# [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_sethuiyer__distilabled_Chikuma_10.7B)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |68.87|
+|AI2 Reasoning Challenge (25-Shot)|66.38|
+|HellaSwag (10-Shot)              |85.14|
+|MMLU (5-Shot)                    |64.70|
+|TruthfulQA (0-shot)              |59.20|
+|Winogrande (5-shot)              |79.40|
+|GSM8k (5-shot)                   |58.38|
+