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 @@
 ---
-license: apache-2.0
 language:
 - ja
 - en
+license: apache-2.0
 datasets:
 - augmxnt/ultra-orca-boros-en-ja-v1
 - Open-Orca/SlimOrca
 - augmxnt/shisa-en-ja-dpo-v1
+model-index:
+- name: shisa-7b-v1
+  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: 56.14
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-7b-v1
+      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: 78.63
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-7b-v1
+      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: 23.12
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-7b-v1
+      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: 52.49
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-7b-v1
+      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: 78.06
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-7b-v1
+      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: 41.62
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-7b-v1
+      name: Open LLM Leaderboard
 ---
 # Shisa 7B
 
@@ -376,4 +479,17 @@ print(tokenizer.apply_chat_template(chat, tokenize=False))
 
 また、貴重なヒューマンプリファレンステストを提供してくださったすべてのボランティアにも感謝いたします！
 
-このプロジェクトのためにより良く、より大きなモデルを訓練するために、追加の計算を積極的に探しています。お問い合わせは次の宛先までお願いいたします：*compute at augmxnt dot com*
+このプロジェクトのためにより良く、より大きなモデルを訓練するために、追加の計算を積極的に探しています。お問い合わせは次の宛先までお願いいたします：*compute at augmxnt dot com*
+# [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_augmxnt__shisa-7b-v1)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |55.01|
+|AI2 Reasoning Challenge (25-Shot)|56.14|
+|HellaSwag (10-Shot)              |78.63|
+|MMLU (5-Shot)                    |23.12|
+|TruthfulQA (0-shot)              |52.49|
+|Winogrande (5-shot)              |78.06|
+|GSM8k (5-shot)                   |41.62|
+