Adding Evaluation Results

README.md

@@ -1,15 +1,118 @@
 ---
-license: apache-2.0
 language:
 - en
 - zh
-datasets:
-- teknium/OpenHermes-2.5
-pipeline_tag: text-generation
+license: apache-2.0
+library_name: transformers
 tags:
 - llama
 - latest
-library_name: transformers
+datasets:
+- teknium/OpenHermes-2.5
+pipeline_tag: text-generation
+model-index:
+- name: Gigi-Llama3-8B-Chinese-zh
+  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: 59.64
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yaojialzc/Gigi-Llama3-8B-Chinese-zh
+      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: 80.28
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yaojialzc/Gigi-Llama3-8B-Chinese-zh
+      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: 66.91
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yaojialzc/Gigi-Llama3-8B-Chinese-zh
+      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: 52.14
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yaojialzc/Gigi-Llama3-8B-Chinese-zh
+      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: 76.48
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yaojialzc/Gigi-Llama3-8B-Chinese-zh
+      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: 66.79
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yaojialzc/Gigi-Llama3-8B-Chinese-zh
+      name: Open LLM Leaderboard
 ---
 
 ![image/webp](https://cdn-uploads.huggingface.co/production/uploads/64ef2a96f2b8f40224d7b407/9wZAYV-keBPVtn6-cd17n.webp)
@@ -90,4 +193,17 @@ print(output)
 
 The model output of llama 3 does not stop at eot, so it cannot be used out of the box. For the time being, we respect the official behavior and guide the model to output "end_of_text" directly at the end of fine-tuning, making it convenient for immediate fine-tuning in downstream fields.
 
-llama 3 模型输出 eot 时不会停止，无法开箱即用。我们暂时尊重官方的行为，精调时指导模型在最后直接输出 end_of_text，方便目前开箱即用地在下游领域精调。
+llama 3 模型输出 eot 时不会停止，无法开箱即用。我们暂时尊重官方的行为，精调时指导模型在最后直接输出 end_of_text，方便目前开箱即用地在下游领域精调。
+# [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_yaojialzc__Gigi-Llama3-8B-Chinese-zh)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |67.04|
+|AI2 Reasoning Challenge (25-Shot)|59.64|
+|HellaSwag (10-Shot)              |80.28|
+|MMLU (5-Shot)                    |66.91|
+|TruthfulQA (0-shot)              |52.14|
+|Winogrande (5-shot)              |76.48|
+|GSM8k (5-shot)                   |66.79|
+