README.md

metadata

license: mit
library_name: transformers
base_model: wandb/mistral-7b-zephyr-sft
datasets:
  - argilla/dpo-mix-7k
model-index:
  - name: mistral-7b-zephyr-dpo
    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: 63.05
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/mistral-7b-zephyr-dpo
          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: 85.54
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/mistral-7b-zephyr-dpo
          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: 61.88
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/mistral-7b-zephyr-dpo
          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: 59.3
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/mistral-7b-zephyr-dpo
          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: 78.53
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/mistral-7b-zephyr-dpo
          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: 31.01
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/mistral-7b-zephyr-dpo
          name: Open LLM Leaderboard

Mistral 7B Zephyr DPO V2

The Zephyr DPO recipe applied on top of Mistral 7B (new recipe with chatML format)

Model description

• Model type: A 7.2B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets.
• Language(s) (NLP): Primarily English
• Finetuned from model: wandb/mistral-7b-zephyr-sft

Recipe

We trained using the alignment handbook recipe and logging to W&B

Visit the W&B workspace here

Compute provided by Lambda Labs - 8xA100 80GB node

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	63.22
AI2 Reasoning Challenge (25-Shot)	63.05
HellaSwag (10-Shot)	85.54
MMLU (5-Shot)	61.88
TruthfulQA (0-shot)	59.30
Winogrande (5-shot)	78.53
GSM8k (5-shot)	31.01