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 +1,107 @@
 ---
-library_name: transformers
 language:
 - ru
 - en
-pipeline_tag: text-generation
 license: other
+library_name: transformers
+pipeline_tag: text-generation
 license_name: apache-2.0
 license_link: https://huggingface.co/MTSAIR/Cotype-Nano/blob/main/Apache%20License%20MTS%20AI.docx
+model-index:
+- name: Cotype-Nano
+  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: 37.48
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MTSAIR/Cotype-Nano
+      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: 14.45
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MTSAIR/Cotype-Nano
+      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: 6.42
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MTSAIR/Cotype-Nano
+      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: 2.68
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MTSAIR/Cotype-Nano
+      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: 2.11
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MTSAIR/Cotype-Nano
+      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: 16.41
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MTSAIR/Cotype-Nano
+      name: Open LLM Leaderboard
 ---
 
 
@@ -156,4 +251,17 @@ The model was trained in two stages. In the first stage, MLP layers were trained
 | Qwen-Qwen2.5-1.5B-Instruct                  | 16.46 | +1.3 / -1.3             | 483.67        |
 | Vikhrmodels-vikhr-qwen-1.5b-it              | 13.19 | +1.3 / -1.1             | 2495.38       |
 | meta-llama-Llama-3.2-1B-Instruct            | 4.04  | +0.6 / -0.8             | 1240.53       |
-| Qwen-Qwen2.5-0.5B-Instruct                  | 4.02  | +0.7 / -0.8             | 829.87        |
+| Qwen-Qwen2.5-0.5B-Instruct                  | 4.02  | +0.7 / -0.8             | 829.87        |
+# [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_MTSAIR__Cotype-Nano)
+
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               |13.26|
+|IFEval (0-Shot)    |37.48|
+|BBH (3-Shot)       |14.45|
+|MATH Lvl 5 (4-Shot)| 6.42|
+|GPQA (0-shot)      | 2.68|
+|MuSR (0-shot)      | 2.11|
+|MMLU-PRO (5-shot)  |16.41|
+