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

@@ -1,12 +1,115 @@
 ---
+language:
+- en
 license: apache-2.0
 tags:
 - safetensors
 - mixtral
 - not-for-all-audiences
 - nsfw
-language:
-- en
+model-index:
+- name: InfinityKumon-2x7B
+  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: 69.62
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B
+      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: 87.09
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B
+      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: 64.97
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B
+      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: 61.99
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B
+      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: 81.93
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B
+      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: 63.53
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=R136a1/InfinityKumon-2x7B
+      name: Open LLM Leaderboard
 ---
 
 ## InfinityKumon-2x7B
@@ -20,4 +123,17 @@ The reason? Because I like InfinityRP-v1-7B so much and wondering if I can impro
 ### Prompt format: 
 Alpaca or ChatML
 
-Switch: [FP16](https://huggingface.co/R136a1/InfinityKumon-2x7B) - [GGUF](https://huggingface.co/R136a1/InfinityKumon-2x7B-GGUF)
+Switch: [FP16](https://huggingface.co/R136a1/InfinityKumon-2x7B) - [GGUF](https://huggingface.co/R136a1/InfinityKumon-2x7B-GGUF)
+# [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_R136a1__InfinityKumon-2x7B)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |71.52|
+|AI2 Reasoning Challenge (25-Shot)|69.62|
+|HellaSwag (10-Shot)              |87.09|
+|MMLU (5-Shot)                    |64.97|
+|TruthfulQA (0-shot)              |61.99|
+|Winogrande (5-shot)              |81.93|
+|GSM8k (5-shot)                   |63.53|
+