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

@@ -3,6 +3,109 @@ license: apache-2.0
 datasets:
 - databricks/databricks-dolly-15k
 pipeline_tag: text-generation
+model-index:
+- name: Instruct_Mixtral-8x7B-v0.1_Dolly15K
+  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: 69.28
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
+      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: 87.59
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
+      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: 70.96
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
+      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: 64.83
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
+      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: 82.56
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
+      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: 59.44
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
+      name: Open LLM Leaderboard
 ---
 # Instruct_Mixtral-8x7B-v0.1_Dolly15K
 Fine-tuned from Mixtral-8x7B-v0.1， used Dolly15k for the dataset. 85% for training, 14.9% validation, 0.1% test.  Trained for 1.0 epochs using QLora.  Trained with 1024 context window.
@@ -37,4 +140,17 @@ Output:
 ## Professional Assistance
 This model and other models like it are great, but where LLMs hold the most promise is when they are applied on custom data to automate a wide variety of tasks
 
-If you have a dataset and want to see if you might be able to apply that data to automate some tasks, and you are looking for professional assistance, contact me [here](mailto:[email protected])
+If you have a dataset and want to see if you might be able to apply that data to automate some tasks, and you are looking for professional assistance, contact me [here](mailto:[email protected])
+# [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_Brillibits__Instruct_Mixtral-8x7B-v0.1_Dolly15K)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |72.44|
+|AI2 Reasoning Challenge (25-Shot)|69.28|
+|HellaSwag (10-Shot)              |87.59|
+|MMLU (5-Shot)                    |70.96|
+|TruthfulQA (0-shot)              |64.83|
+|Winogrande (5-shot)              |82.56|
+|GSM8k (5-shot)                   |59.44|
+