Adding Evaluation Results

This is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr

The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.

If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions

README.md

@@ -1,10 +1,113 @@
 ---
 license: apache-2.0
-base_model: mistralai/Mistral-7B-v0.1
 datasets:
 - abacusai/MetaMathFewshot
 - shahules786/orca-chat
 - anon8231489123/ShareGPT_Vicuna_unfiltered
+base_model: mistralai/Mistral-7B-v0.1
+model-index:
+- name: Fewshot-Metamath-OrcaVicuna-Mistral-10B
+  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: 56.4
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abacusai/Fewshot-Metamath-OrcaVicuna-Mistral-10B
+      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: 78.12
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abacusai/Fewshot-Metamath-OrcaVicuna-Mistral-10B
+      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: 59.52
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abacusai/Fewshot-Metamath-OrcaVicuna-Mistral-10B
+      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: 50.98
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abacusai/Fewshot-Metamath-OrcaVicuna-Mistral-10B
+      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=abacusai/Fewshot-Metamath-OrcaVicuna-Mistral-10B
+      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: 13.27
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abacusai/Fewshot-Metamath-OrcaVicuna-Mistral-10B
+      name: Open LLM Leaderboard
 ---
 
 ```json
@@ -55,4 +158,17 @@ Orca, ShareGPT). Here are the results:
 
 This ablation compares the base model (Mistral 7B), expansion using the layer map described here and fine tunes of a lora `r=12`
 on the base model and `r=8` (to match trainable params). The ablation demonstrates quite clearly that fine tuning the expanded
-model leads to a significant improvement in metrics even with the same number of trainable parameters (and training steps).
+model leads to a significant improvement in metrics even with the same number of trainable parameters (and training steps).
+# [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_abacusai__Fewshot-Metamath-OrcaVicuna-Mistral-10B)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |55.79|
+|AI2 Reasoning Challenge (25-Shot)|56.40|
+|HellaSwag (10-Shot)              |78.12|
+|MMLU (5-Shot)                    |59.52|
+|TruthfulQA (0-shot)              |50.98|
+|Winogrande (5-shot)              |76.48|
+|GSM8k (5-shot)                   |13.27|
+