Adding Evaluation Results (#12)

- Adding Evaluation Results (de00aaf7b17533211e2ff1b2062c248037754921)


Co-authored-by: Open LLM Leaderboard PR Bot <[email protected]>

README.md

@@ -1,64 +1,167 @@
 ---
 language:
-  - en
+- en
 license: apache-2.0
-datasets:
-  - HuggingFaceH4/ultrachat_200k
-  - Felladrin/ChatML-ultrachat_200k
-  - Open-Orca/OpenOrca
-  - Felladrin/ChatML-OpenOrca
-  - hkust-nlp/deita-10k-v0
-  - Felladrin/ChatML-deita-10k-v0
-  - LDJnr/Capybara
-  - Felladrin/ChatML-Capybara
-  - databricks/databricks-dolly-15k
-  - Felladrin/ChatML-databricks-dolly-15k
-  - euclaise/reddit-instruct-curated
-  - Felladrin/ChatML-reddit-instruct-curated
-  - CohereForAI/aya_dataset
-  - Felladrin/ChatML-aya_dataset
 base_model: Locutusque/TinyMistral-248M
+datasets:
+- HuggingFaceH4/ultrachat_200k
+- Felladrin/ChatML-ultrachat_200k
+- Open-Orca/OpenOrca
+- Felladrin/ChatML-OpenOrca
+- hkust-nlp/deita-10k-v0
+- Felladrin/ChatML-deita-10k-v0
+- LDJnr/Capybara
+- Felladrin/ChatML-Capybara
+- databricks/databricks-dolly-15k
+- Felladrin/ChatML-databricks-dolly-15k
+- euclaise/reddit-instruct-curated
+- Felladrin/ChatML-reddit-instruct-curated
+- CohereForAI/aya_dataset
+- Felladrin/ChatML-aya_dataset
 pipeline_tag: text-generation
 widget:
-  - messages:
-      - role: system
-        content:
-          You are a highly knowledgeable and friendly assistant. Your goal is to
-          understand and respond to user inquiries with clarity. Your interactions are
-          always respectful, helpful, and focused on delivering the most accurate information
-          to the user.
-      - role: user
-        content: Hey! Got a question for you!
-      - role: assistant
-        content: Sure! What's it?
-      - role: user
-        content: What are some potential applications for quantum computing?
-  - messages:
-      - role: user
-        content: Heya!
-      - role: assistant
-        content: Hi! How may I help you?
-      - role: user
-        content:
-          I'm interested in developing a career in software engineering. What
-          would you recommend me to do?
-  - messages:
-      - role: user
-        content: Morning!
-      - role: assistant
-        content: Good morning! How can I help you today?
-      - role: user
-        content: Could you give me some tips for becoming a healthier person?
-  - messages:
-      - role: system
-        content: You are a very creative assistant. User will give you a task, which you should complete with all your knowledge.
-      - role: user
-        content: Hello! Can you please elaborate a background story of an RPG game about wizards and dragons in a sci-fi world?
+- messages:
+  - role: system
+    content: You are a highly knowledgeable and friendly assistant. Your goal is to
+      understand and respond to user inquiries with clarity. Your interactions are
+      always respectful, helpful, and focused on delivering the most accurate information
+      to the user.
+  - role: user
+    content: Hey! Got a question for you!
+  - role: assistant
+    content: Sure! What's it?
+  - role: user
+    content: What are some potential applications for quantum computing?
+- messages:
+  - role: user
+    content: Heya!
+  - role: assistant
+    content: Hi! How may I help you?
+  - role: user
+    content: I'm interested in developing a career in software engineering. What would
+      you recommend me to do?
+- messages:
+  - role: user
+    content: Morning!
+  - role: assistant
+    content: Good morning! How can I help you today?
+  - role: user
+    content: Could you give me some tips for becoming a healthier person?
+- messages:
+  - role: system
+    content: You are a very creative assistant. User will give you a task, which you
+      should complete with all your knowledge.
+  - role: user
+    content: Hello! Can you please elaborate a background story of an RPG game about
+      wizards and dragons in a sci-fi world?
 inference:
   parameters:
     max_new_tokens: 250
     penalty_alpha: 0.5
     top_k: 5
+model-index:
+- name: TinyMistral-248M-Chat-v2
+  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: 23.29
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
+      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: 27.39
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
+      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: 23.52
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
+      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: 41.32
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
+      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: 49.01
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
+      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: 0.0
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
+      name: Open LLM Leaderboard
 ---
 
 # Locutusque's TinyMistral-248M trained on chat datasets
@@ -147,3 +250,17 @@ This model was trained with [SFTTrainer](https://huggingface.co/docs/trl/main/en
 | Optimizer              | Adam with betas=(0.9,0.999) and epsilon=1e-08 |
 | Scheduler              | cosine                                        |
 | Seed                   | 42                                            |
+
+# [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_Felladrin__TinyMistral-248M-Chat-v2)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |27.42|
+|AI2 Reasoning Challenge (25-Shot)|23.29|
+|HellaSwag (10-Shot)              |27.39|
+|MMLU (5-Shot)                    |23.52|
+|TruthfulQA (0-shot)              |41.32|
+|Winogrande (5-shot)              |49.01|
+|GSM8k (5-shot)                   | 0.00|
+