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

@@ -1,14 +1,117 @@
 ---
+language:
+- en
 license: llama2
+tags:
+- roleplay
+- conversational
 datasets:
 - migtissera/Synthia-v1.3
 - open-llm-leaderboard/details_NousResearch__Nous-Hermes-llama-2-7b
-language:
-- en
 pipeline_tag: text-generation
-tags:
-- roleplay
-- conversational 
+model-index:
+- name: L2-7b-Hermes-Synthia
+  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: 51.02
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LTC-AI-Labs/L2-7b-Hermes-Synthia
+      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: 79.12
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LTC-AI-Labs/L2-7b-Hermes-Synthia
+      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: 47.88
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LTC-AI-Labs/L2-7b-Hermes-Synthia
+      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: 46.77
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LTC-AI-Labs/L2-7b-Hermes-Synthia
+      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: 74.51
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LTC-AI-Labs/L2-7b-Hermes-Synthia
+      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: 13.95
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LTC-AI-Labs/L2-7b-Hermes-Synthia
+      name: Open LLM Leaderboard
 ---
 Fine-tuned the synthia dataset on the hermes2 7b model
 
@@ -20,4 +123,17 @@ Future plans:
 
 - Will add other languages (Potentially japanese and chinese)
 
-- Finetune it on mistral models?
+- Finetune it on mistral models?
+# [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_LTC-AI-Labs__L2-7b-Hermes-Synthia)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |52.21|
+|AI2 Reasoning Challenge (25-Shot)|51.02|
+|HellaSwag (10-Shot)              |79.12|
+|MMLU (5-Shot)                    |47.88|
+|TruthfulQA (0-shot)              |46.77|
+|Winogrande (5-shot)              |74.51|
+|GSM8k (5-shot)                   |13.95|
+