Adding Evaluation Results

README.md

@@ -3,6 +3,109 @@ license: apache-2.0
 datasets:
 - teknium/GPT4-LLM-Cleaned
 - vicgalle/alpaca-gpt4
+model-index:
+- name: mm4-3b
+  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: 44.8
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=liminerity/mm4-3b
+      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: 70.41
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=liminerity/mm4-3b
+      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: 50.9
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=liminerity/mm4-3b
+      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: 43.2
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=liminerity/mm4-3b
+      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: 66.22
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=liminerity/mm4-3b
+      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: 43.82
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=liminerity/mm4-3b
+      name: Open LLM Leaderboard
 ---
 MM4-3b
 
@@ -24,4 +127,17 @@ The DKE-RS method challenges the status quo by not solely relying on a linear en
 
 Through thorough experimentation and analysis, we plan to assess the effectiveness and potential drawbacks of DKE-RS, comparing it to traditional merging techniques. The results from such evaluations will provide valuable insights into the efficacy of this divergent strategy in the landscape of natural language model development.
 
-We posit that the Divergent Knowledge Enhancement through Retrograde Merging Strategies approach contributes a significant and compelling step forward in the field, provoking thought-provoking discourse about the nature of accuracy refinement and model progression.
+We posit that the Divergent Knowledge Enhancement through Retrograde Merging Strategies approach contributes a significant and compelling step forward in the field, provoking thought-provoking discourse about the nature of accuracy refinement and model progression.
+# [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_liminerity__mm4-3b)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |53.22|
+|AI2 Reasoning Challenge (25-Shot)|44.80|
+|HellaSwag (10-Shot)              |70.41|
+|MMLU (5-Shot)                    |50.90|
+|TruthfulQA (0-shot)              |43.20|
+|Winogrande (5-shot)              |66.22|
+|GSM8k (5-shot)                   |43.82|
+