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

@@ -1,5 +1,108 @@
 ---
 license: cc-by-nc-4.0
+model-index:
+- name: Mistral-7b-instruct-v0.2-summ-sft-bf16-e1
+  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: 60.58
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=genaicore3434/Mistral-7b-instruct-v0.2-summ-sft-bf16-e1
+      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: 83.32
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=genaicore3434/Mistral-7b-instruct-v0.2-summ-sft-bf16-e1
+      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: 60.79
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=genaicore3434/Mistral-7b-instruct-v0.2-summ-sft-bf16-e1
+      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: 64.72
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=genaicore3434/Mistral-7b-instruct-v0.2-summ-sft-bf16-e1
+      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: 76.72
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=genaicore3434/Mistral-7b-instruct-v0.2-summ-sft-bf16-e1
+      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: 39.2
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=genaicore3434/Mistral-7b-instruct-v0.2-summ-sft-bf16-e1
+      name: Open LLM Leaderboard
 ---
 
 Description to load and test will be added soon. More details on training and data will be added aswell.
@@ -26,4 +129,17 @@ inputs = tokenizer(text, return_tensors="pt")
 
 outputs = model.generate(**inputs, max_new_tokens=64)
 print(tokenizer.decode(outputs[0], skip_special_tokens=True))
-```
+```
+# [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_genaicore3434__Mistral-7b-instruct-v0.2-summ-sft-bf16-e1)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |64.22|
+|AI2 Reasoning Challenge (25-Shot)|60.58|
+|HellaSwag (10-Shot)              |83.32|
+|MMLU (5-Shot)                    |60.79|
+|TruthfulQA (0-shot)              |64.72|
+|Winogrande (5-shot)              |76.72|
+|GSM8k (5-shot)                   |39.20|
+