Adding Evaluation Results

README.md

@@ -1,14 +1,117 @@
 ---
-library_name: transformers
 license: apache-2.0
-datasets:
-- Locutusque/Hercules-v3.0
+library_name: transformers
 tags:
 - finetune
 - gpt4
 - synthetic data
 - custom_code
 - h2oai
+datasets:
+- Locutusque/Hercules-v3.0
+model-index:
+- name: Cypher-Mini-1.8B
+  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: 39.59
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Cypher-Mini-1.8B
+      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: 67.45
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Cypher-Mini-1.8B
+      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: 31.14
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Cypher-Mini-1.8B
+      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: 40.44
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Cypher-Mini-1.8B
+      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: 65.19
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Cypher-Mini-1.8B
+      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: 14.48
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Cypher-Mini-1.8B
+      name: Open LLM Leaderboard
 ---
 
 ![Cypher aloobun h2oai1.8B](https://i.imgur.com/2R6f4EX.jpeg)
@@ -87,3 +190,17 @@ op = model.generate(
 >The consequence of using the appeal to authority fallacy is that it often leads to hasty conclusions and misinformation. It can be difficult to separate fact from fiction, especially when people rely on authority figures to make decisions. As a result, individuals may end up making poor choices based on incomplete information. This can lead to unintended consequences, such as harming oneself or others.
 >
 >To avoid falling prey to the appeal to authority fallacy, it is important to seek out multiple sources of information and consider all available evidence before making a decision. This can help individuals make more informed choices and reduce the likelihood of being swayed by unsubstantiated claims.</s>
+
+# [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_aloobun__Cypher-Mini-1.8B)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |43.05|
+|AI2 Reasoning Challenge (25-Shot)|39.59|
+|HellaSwag (10-Shot)              |67.45|
+|MMLU (5-Shot)                    |31.14|
+|TruthfulQA (0-shot)              |40.44|
+|Winogrande (5-shot)              |65.19|
+|GSM8k (5-shot)                   |14.48|
+