Adding Evaluation Results

README.md

@@ -11,6 +11,105 @@ tags:
 - R1
 - Qwen
 - Deepseek
+model-index:
+- name: Elita-0.1-Distilled-R1-abliterated
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: wis-k/instruction-following-eval
+      split: train
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 35.42
+      name: averaged accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FElita-0.1-Distilled-R1-abliterated
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: SaylorTwift/bbh
+      split: test
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 13.61
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FElita-0.1-Distilled-R1-abliterated
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: lighteval/MATH-Hard
+      split: test
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 30.66
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FElita-0.1-Distilled-R1-abliterated
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      split: train
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 2.13
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FElita-0.1-Distilled-R1-abliterated
+      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: 3.05
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FElita-0.1-Distilled-R1-abliterated
+      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: 19.53
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FElita-0.1-Distilled-R1-abliterated
+      name: Open LLM Leaderboard
 ---
 ![ASFSADFCS.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/U8o3r3pREezkHYVAEEcqc.png)
 
@@ -70,4 +169,18 @@ response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
 3. **Bias in Training Data:** The model's outputs may reflect biases present in the datasets it was fine-tuned on, which could limit its objectivity in certain contexts.  
 4. **Performance on Non-Reasoning Tasks:** The model is optimized for chain-of-thought reasoning and may underperform on tasks that require simpler, less structured responses.  
 5. **Resource-Intensive:** Running the model efficiently requires significant computational resources, which may limit accessibility for smaller-scale deployments.  
-6. **Dependence on Input Quality:** The model’s performance heavily depends on the clarity and quality of the input provided. Ambiguous or poorly structured prompts may yield suboptimal results.  
+6. **Dependence on Input Quality:** The model’s performance heavily depends on the clarity and quality of the input provided. Ambiguous or poorly structured prompts may yield suboptimal results.  
+# [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/prithivMLmods__Elita-0.1-Distilled-R1-abliterated-details)!
+Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=prithivMLmods%2FElita-0.1-Distilled-R1-abliterated&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
+
+|      Metric       |Value (%)|
+|-------------------|--------:|
+|**Average**        |    17.40|
+|IFEval (0-Shot)    |    35.42|
+|BBH (3-Shot)       |    13.61|
+|MATH Lvl 5 (4-Shot)|    30.66|
+|GPQA (0-shot)      |     2.13|
+|MuSR (0-shot)      |     3.05|
+|MMLU-PRO (5-shot)  |    19.53|
+