Adding Evaluation Results

README.md

@@ -1,13 +1,116 @@
 ---
+language:
+- hi
+- en
 license: apache-2.0
 datasets:
 - manishiitg/aditi-gpt4-v2-hi-200K
 - manishiitg/en-hi-instruct-v2
 - manishiitg/en-hi-chat-v2
-language:
-- hi
-- en
 base_model: mistralai/Mistral-7B-v0.1
+model-index:
+- name: open-aditi-hi-v1
+  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: 58.79
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=manishiitg/open-aditi-hi-v1
+      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: 81.38
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=manishiitg/open-aditi-hi-v1
+      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: 58.51
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=manishiitg/open-aditi-hi-v1
+      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: 42.34
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=manishiitg/open-aditi-hi-v1
+      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: 76.48
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=manishiitg/open-aditi-hi-v1
+      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: 33.43
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=manishiitg/open-aditi-hi-v1
+      name: Open LLM Leaderboard
 ---
 Model trained on Hindi and English data.
 
@@ -116,4 +219,17 @@ Safe investment yajna: For a low-risk investment option, the user should try saf
 
 Share investment time: The user should anticipate splitting investment time before investing, this may make them safer for low-risk investment options after investing.
 
-5. Gather Knowledge of Investment Aspects: The user should gather knowledge of investment aspects before investing.
+5. Gather Knowledge of Investment Aspects: The user should gather knowledge of investment aspects before investing.
+# [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_manishiitg__open-aditi-hi-v1)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |58.49|
+|AI2 Reasoning Challenge (25-Shot)|58.79|
+|HellaSwag (10-Shot)              |81.38|
+|MMLU (5-Shot)                    |58.51|
+|TruthfulQA (0-shot)              |42.34|
+|Winogrande (5-shot)              |76.48|
+|GSM8k (5-shot)                   |33.43|
+