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

@@ -1,12 +1,115 @@
 ---
 license: other
-license_name: yi-license
-license_link: LICENSE
 tags:
 - finetune
 - fine-tune
 datasets:
 - adamo1139/rawrr_v1
+license_name: yi-license
+license_link: LICENSE
+model-index:
+- name: yi-34b-200k-rawrr-dpo-1
+  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: 65.44
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/yi-34b-200k-rawrr-dpo-1
+      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: 85.69
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/yi-34b-200k-rawrr-dpo-1
+      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: 76.09
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/yi-34b-200k-rawrr-dpo-1
+      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: 54.0
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/yi-34b-200k-rawrr-dpo-1
+      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: 82.79
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/yi-34b-200k-rawrr-dpo-1
+      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: 61.79
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/yi-34b-200k-rawrr-dpo-1
+      name: Open LLM Leaderboard
 ---
 
 NEW STRONGER RAWRR FINETUNE COMING SOON! 
@@ -18,4 +121,17 @@ Rawrr_v1 dataset made it so that this model issue less refusals, especially for
 Base yi-34B-200k suffers from contamination on instruct and refusal datasets, i am attempting to fix that by training base models with DPO on rawrr dataset, making them more raw. 
 
 License: 
-yi-license + non-commercial use only
+yi-license + non-commercial use only
+# [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_adamo1139__yi-34b-200k-rawrr-dpo-1)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |70.97|
+|AI2 Reasoning Challenge (25-Shot)|65.44|
+|HellaSwag (10-Shot)              |85.69|
+|MMLU (5-Shot)                    |76.09|
+|TruthfulQA (0-shot)              |54.00|
+|Winogrande (5-shot)              |82.79|
+|GSM8k (5-shot)                   |61.79|
+