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

@@ -1,4 +1,5 @@
 ---
+license: apache-2.0
 library_name: peft
 tags:
 - code
@@ -7,7 +8,109 @@ tags:
 datasets:
 - HuggingFaceH4/no_robots
 base_model: mistralai/Mistral-7B-v0.1
-license: apache-2.0
+model-index:
+- name: mistral_7b_norobots
+  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: 58.96
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
+      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: 80.57
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
+      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: 57.66
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
+      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: 41.91
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
+      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: 75.61
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
+      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: 38.36
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
+      name: Open LLM Leaderboard
 ---
 
 ### Finetuning Overview:
@@ -54,4 +157,17 @@ With the utilization of [MonsterAPI](https://monsterapi.ai)'s [no-code LLM finet
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6313732454e6e5d9f0f797cd/ialM-cJygMgMgczskzicX.png)
 
 ---
-license: apache-2.0
+license: apache-2.0
+# [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_qblocks__mistral_7b_norobots)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |58.85|
+|AI2 Reasoning Challenge (25-Shot)|58.96|
+|HellaSwag (10-Shot)              |80.57|
+|MMLU (5-Shot)                    |57.66|
+|TruthfulQA (0-shot)              |41.91|
+|Winogrande (5-shot)              |75.61|
+|GSM8k (5-shot)                   |38.36|
+