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Adding Evaluation Results (#1)
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metadata
language:
  - en
license: cc-by-nc-4.0
library_name: transformers
tags:
  - text-generation-inference
datasets:
  - argilla/OpenHermesPreferences
pipeline_tag: text-generation
model-index:
  - name: ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-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: 73.12
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-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: 89.07
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-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: 64.8
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-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: 77.46
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-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: 84.69
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-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: 69.52
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO-v2
          name: Open LLM Leaderboard

Just dpo finetuned this model a bit more: https://huggingface.co/eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO on the https://huggingface.co/datasets/argilla/OpenHermesPreferences dataset

As is described in the original model repo, not yet fully tested therefore potentially a bad match for using out-of-the-box, use with caution.

Model Details

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Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 76.44
AI2 Reasoning Challenge (25-Shot) 73.12
HellaSwag (10-Shot) 89.07
MMLU (5-Shot) 64.80
TruthfulQA (0-shot) 77.46
Winogrande (5-shot) 84.69
GSM8k (5-shot) 69.52