Adding Evaluation Results

README.md

@@ -1,7 +1,110 @@
 ---
-pipeline_tag: text-generation
 license: other
+pipeline_tag: text-generation
 license_name: microsoft-research-license
+model-index:
+- name: Orca-2-13b-Alpaca-Uncensored
+  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: 61.09
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Orca-2-13b-Alpaca-Uncensored
+      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: 79.27
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Orca-2-13b-Alpaca-Uncensored
+      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: 60.13
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Orca-2-13b-Alpaca-Uncensored
+      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: 53.59
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Orca-2-13b-Alpaca-Uncensored
+      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: 77.43
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Orca-2-13b-Alpaca-Uncensored
+      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: 38.29
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Orca-2-13b-Alpaca-Uncensored
+      name: Open LLM Leaderboard
 ---
 This model is a fine-tuned version of microsoft/Orca-2-13b on a subset of the Vezora/Mini_Orca_Uncencored_Alpaca dataset, adjusted to demonstrate the relationship between instruction and input, with some particularly spicy prompts added to reduce the risk of rejections.
 
@@ -9,4 +112,17 @@ Only the q_proj and k_proj modules were targeted and a low rank (8) was used, in
 
 Reasoning stayed solid (for a 13b model) and I consider this a success. Performance is slighty worse than OG Orca-2 in Ooba's chat mode, comparable in Alpaca chat-instruct mode to the OG in ChatLM chat-instruct mode.
 
-May still reject some shocking prompts, but can easily be overcome with author's note or character card.
+May still reject some shocking prompts, but can easily be overcome with author's note or character card.
+# [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_athirdpath__Orca-2-13b-Alpaca-Uncensored)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |61.63|
+|AI2 Reasoning Challenge (25-Shot)|61.09|
+|HellaSwag (10-Shot)              |79.27|
+|MMLU (5-Shot)                    |60.13|
+|TruthfulQA (0-shot)              |53.59|
+|Winogrande (5-shot)              |77.43|
+|GSM8k (5-shot)                   |38.29|
+