Adding Evaluation Results

README.md

@@ -1,14 +1,108 @@
 ---
-base_model:
-- unsloth/Mistral-Small-Instruct-2409
+license: other
 library_name: transformers
 tags:
 - mergekit
 - merge
-license: other
+base_model:
+- unsloth/Mistral-Small-Instruct-2409
 license_name: mrl
 license_link: https://mistral.ai/licenses/MRL-0.1.md
-
+model-index:
+- name: MS-Meadowlark-22B
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: HuggingFaceH4/ifeval
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 66.97
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: BBH
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 30.3
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: hendrycks/competition_math
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 14.12
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 10.07
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 5.53
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 31.37
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allura-org/MS-Meadowlark-22B
+      name: Open LLM Leaderboard
 ---
 # MS-Meadowlark-22B
 <figure>
@@ -40,3 +134,17 @@ Creative_Writing_Multiturn and Gutenberg-Doppel were trained using the official
 This is the Mistral Small V2&V3 preset in SillyTavern and Kobold Lite. 
 
 For SillyTavern in particular I've had better luck getting good output from Mistral Small using a [custom instruct template](https://huggingface.co/ToastyPigeon/ST-Presets-Mistral-Small) that formats the assembled context as a single user turn. This prevents SillyTavern from confusing the model by assembling user/assistant turns in a nonstandard way. Note: This preset is *not* compatible with Stepped Thinking, use the Mistral V2&V3 preset for that.
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_allura-org__MS-Meadowlark-22B)
+
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               |26.39|
+|IFEval (0-Shot)    |66.97|
+|BBH (3-Shot)       |30.30|
+|MATH Lvl 5 (4-Shot)|14.12|
+|GPQA (0-shot)      |10.07|
+|MuSR (0-shot)      | 5.53|
+|MMLU-PRO (5-shot)  |31.37|
+