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

@@ -1,10 +1,113 @@
 ---
-license: apache-2.0
-datasets:
-- Intel/orca_dpo_pairs
 language:
 - en
 - es
+license: apache-2.0
+datasets:
+- Intel/orca_dpo_pairs
+model-index:
+- name: Barcenas-Tiny-1.1b-DPO
+  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: 36.26
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Danielbrdz/Barcenas-Tiny-1.1b-DPO
+      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: 61.2
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Danielbrdz/Barcenas-Tiny-1.1b-DPO
+      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: 24.83
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Danielbrdz/Barcenas-Tiny-1.1b-DPO
+      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: 37.45
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Danielbrdz/Barcenas-Tiny-1.1b-DPO
+      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: 60.93
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Danielbrdz/Barcenas-Tiny-1.1b-DPO
+      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: 2.05
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Danielbrdz/Barcenas-Tiny-1.1b-DPO
+      name: Open LLM Leaderboard
 ---
 Barcenas Tiny 1.1b DPO
 
@@ -14,4 +117,17 @@ With its reinforcement based training we hope to improve the Tiny model in a hug
 
 Many thanks to Maxime Labonne (mlabonne) for his tutorial on how to train a LLM model using DPO, without his tutorial this model would not have been possible.
 
-Made with ❤️ in Guadalupe, Nuevo Leon, Mexico 🇲🇽
+Made with ❤️ in Guadalupe, Nuevo Leon, Mexico 🇲🇽
+# [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_Danielbrdz__Barcenas-Tiny-1.1b-DPO)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |37.12|
+|AI2 Reasoning Challenge (25-Shot)|36.26|
+|HellaSwag (10-Shot)              |61.20|
+|MMLU (5-Shot)                    |24.83|
+|TruthfulQA (0-shot)              |37.45|
+|Winogrande (5-shot)              |60.93|
+|GSM8k (5-shot)                   | 2.05|
+