README.md

metadata

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.

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

Detailed results can be found here

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