Rhea-72b-v0.5 / README.md
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metadata
language:
  - en
license: apache-2.0
library_name: transformers
model-index:
  - name: Rhea-72b-v0.5
    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: 79.78
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=davidkim205/Rhea-72b-v0.5
          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: 91.15
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=davidkim205/Rhea-72b-v0.5
          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: 77.95
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=davidkim205/Rhea-72b-v0.5
          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: 74.5
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=davidkim205/Rhea-72b-v0.5
          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: 87.85
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=davidkim205/Rhea-72b-v0.5
          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: 76.12
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=davidkim205/Rhea-72b-v0.5
          name: Open LLM Leaderboard

Rhea-72b-v0.5

image/jpeg

The Rhea project is a project that conducts research on various learning methods to improve llm model performance. We fine-tuned the existing model using the nox framework. We built a dataset for SFT learning based on the currently open dataset, and created a dataset using SGD (Self-Generated Dataset Creation Method for DPO Learning) for DPO learning.

Our model ranked first on HuggingFace's Open LLM leaderboard.

SGD : A Study on Self-Generated Dataset creation method for DPO Learning

This method proposes a novel method for generating datasets for DPO (Self-supervised Learning) models. We suggest a technique where sentences generated by the model are compared with the actual correct answers from an existing dataset, and sentences where the model's generated results do not match the correct answers are added. This enables the model to autonomously create training data, thereby enhancing the performance of DPO models.

Model Details

  • Model Developers : davidkim(changyeon kim)
  • Repository : https://github.com/davidkim205/nox
  • base mode : abacusai/Smaug-72B-v0.1
  • sft dataset : will be updated soon.
  • dpo dataset : will be updated soon.

Evaluation

Open LLM Leaderboard

model average arc hellaswag mmlu truthfulQA winogrande GSM8k
Rhea-72b-v0.5 81.22 79.78 91.15 77.95 74.5 87.85 76.12

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 81.22
AI2 Reasoning Challenge (25-Shot) 79.78
HellaSwag (10-Shot) 91.15
MMLU (5-Shot) 77.95
TruthfulQA (0-shot) 74.50
Winogrande (5-shot) 87.85
GSM8k (5-shot) 76.12