PiVoT-0.1-early / README.md
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metadata
language:
  - en
  - ko
license: cc-by-sa-4.0
datasets:
  - maywell/ko_wikidata_QA
  - kyujinpy/OpenOrca-KO
pipeline_tag: text-generation
model-index:
  - name: PiVoT-0.1-early
    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: 62.46
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maywell/PiVoT-0.1-early
          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: 82.97
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maywell/PiVoT-0.1-early
          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: 61.02
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maywell/PiVoT-0.1-early
          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: 62.89
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maywell/PiVoT-0.1-early
          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: 73.72
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maywell/PiVoT-0.1-early
          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: 44.43
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maywell/PiVoT-0.1-early
          name: Open LLM Leaderboard

PiVoT-0.1-early

image/png

Model Details

Description

PivoT is Finetuned model based on Mistral 7B. It is variation from Synatra v0.3 RP which has shown decent performance.

OpenOrca Dataset used when finetune PiVoT variation. Arcalive Ai Chat Chan log 7k, ko_wikidata_QA, kyujinpy/OpenOrca-KO and other datasets used on base model.

Follow me on twitter: https://twitter.com/stablefluffy

Consider Support me making these model alone: https://www.buymeacoffee.com/mwell or with Runpod Credit Gift 💕

Contact me on Telegram: https://t.me/AlzarTakkarsen

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 64.58
AI2 Reasoning Challenge (25-Shot) 62.46
HellaSwag (10-Shot) 82.97
MMLU (5-Shot) 61.02
TruthfulQA (0-shot) 62.89
Winogrande (5-shot) 73.72
GSM8k (5-shot) 44.43