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

@@ -1,13 +1,116 @@
 ---
+language:
+- en
 license: apache-2.0
+library_name: transformers
 tags:
 - moe
 - merge
 - abideen/NexoNimbus-7B
 - mlabonne/NeuralMarcoro14-7B
-language:
-- en
-library_name: transformers
+model-index:
+- name: NexoNimbus-MoE-2x7B
+  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: 66.81
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abideen/NexoNimbus-MoE-2x7B
+      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: 85.66
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abideen/NexoNimbus-MoE-2x7B
+      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: 64.51
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abideen/NexoNimbus-MoE-2x7B
+      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: 53.06
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abideen/NexoNimbus-MoE-2x7B
+      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: 81.53
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abideen/NexoNimbus-MoE-2x7B
+      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: 53.53
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abideen/NexoNimbus-MoE-2x7B
+      name: Open LLM Leaderboard
 ---
 
 # NexoNimbus-MoE-2x7B
@@ -117,4 +220,17 @@ outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7,
 print(outputs[0]["generated_text"])
 ```
 
-"Data science is an interdisciplinary field that combines mathematics, statistics, computer science, and domain expertise in order to extract meaningful insights and knowledge from structured and unstructured data. It involves the process of collecting, cleaning, transforming, analyzing, and visualizing data in order to identify patterns, trends, and relationships that can inform decision-making and drive business strategies. Data scientists use various tools and techniques, such as machine learning, deep learning, and natural language processing, to develop predictive models, optimize processes, and automate decision-making. The field of data science is rapidly evolving as more and more data is generated and the demand for data-driven insights continues to grow."
+"Data science is an interdisciplinary field that combines mathematics, statistics, computer science, and domain expertise in order to extract meaningful insights and knowledge from structured and unstructured data. It involves the process of collecting, cleaning, transforming, analyzing, and visualizing data in order to identify patterns, trends, and relationships that can inform decision-making and drive business strategies. Data scientists use various tools and techniques, such as machine learning, deep learning, and natural language processing, to develop predictive models, optimize processes, and automate decision-making. The field of data science is rapidly evolving as more and more data is generated and the demand for data-driven insights continues to grow."
+# [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_abideen__NexoNimbus-MoE-2x7B)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |67.51|
+|AI2 Reasoning Challenge (25-Shot)|66.81|
+|HellaSwag (10-Shot)              |85.66|
+|MMLU (5-Shot)                    |64.51|
+|TruthfulQA (0-shot)              |53.06|
+|Winogrande (5-shot)              |81.53|
+|GSM8k (5-shot)                   |53.53|
+