README.md

---
license: apache-2.0
base_model:
- teknium/OpenHermes-2.5-Mistral-7B
- Intel/neural-chat-7b-v3-3
- meta-math/MetaMath-Mistral-7B
- openchat/openchat-3.5-1210
model-index:
- name: mistral-ft-optimized-1227
  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: 67.06
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenPipe/mistral-ft-optimized-1227
      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: 85.85
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenPipe/mistral-ft-optimized-1227
      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: 65.19
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenPipe/mistral-ft-optimized-1227
      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: 54.57
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenPipe/mistral-ft-optimized-1227
      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: 78.85
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenPipe/mistral-ft-optimized-1227
      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: 71.72
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenPipe/mistral-ft-optimized-1227
      name: Open LLM Leaderboard
---

This model is intended to be a strong base suitable for downstream fine-tuning on a variety of tasks. Based on our internal evaluations, we believe it's one of the strongest models for most down-stream tasks. You can read more about our development and evaluation process [here](https://openpipe.ai/blog/mistral-7b-fine-tune-optimized).

It is a hierarchichal SLERP merge of teknium/OpenHermes-2.5-Mistral-7B, Intel/neural-chat-7b-v3-3, meta-math/MetaMath-Mistral-7B, and openchat/openchat-3.5-1210. berkeley-nest/Starling-LM-7B-alpha was omitted from this version of the model.
# [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_OpenPipe__mistral-ft-optimized-1227)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |70.54|
|AI2 Reasoning Challenge (25-Shot)|67.06|
|HellaSwag (10-Shot)              |85.85|
|MMLU (5-Shot)                    |65.19|
|TruthfulQA (0-shot)              |54.57|
|Winogrande (5-shot)              |78.85|
|GSM8k (5-shot)                   |71.72|