BrokenKeyboard / README.md
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Adding Evaluation Results (#1)
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metadata
language:
  - en
license: cc-by-nc-4.0
datasets:
  - argilla/distilabel-intel-orca-dpo-pairs
base_model:
  - upstage/SOLAR-10.7B-Instruct-v1.0
model-index:
  - name: BrokenKeyboard
    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: 71.25
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboard
          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: 88.34
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboard
          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: 66.04
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboard
          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: 71.36
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboard
          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: 83.19
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboard
          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: 64.29
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboard
          name: Open LLM Leaderboard

Model Card for Model ID

Just testing out LLM Finetuning. Finetuned on upstage/SOLAR-10.7B-Instruct-v1.0 using argilla/distilabel-intel-orca-dpo-pairs. Followed the Google Colab mentioned in this article: https://towardsdatascience.com/fine-tune-a-mistral-7b-model-with-direct-preference-optimization-708042745aac

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 74.08
AI2 Reasoning Challenge (25-Shot) 71.25
HellaSwag (10-Shot) 88.34
MMLU (5-Shot) 66.04
TruthfulQA (0-shot) 71.36
Winogrande (5-shot) 83.19
GSM8k (5-shot) 64.29