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Adding Evaluation Results (#2)
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metadata
license: other
tags:
  - merge
license_name: deepseek
license_link: https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/LICENSE-MODEL
model-index:
  - name: Everyone-Coder-33b-Base
    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: 45.99
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-Coder-33b-Base
          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: 61.71
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-Coder-33b-Base
          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: 44.05
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-Coder-33b-Base
          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: 42.26
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-Coder-33b-Base
          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: 63.06
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-Coder-33b-Base
          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: 39.8
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-Coder-33b-Base
          name: Open LLM Leaderboard

Everyone-Coder-33b-Base

image/jpeg

EveryoneLLM series of models made by the community, for the community. This is a coding specific model made using fine-tunes of deekseekcoder-33b-base.


Im having trouble benchmarking this model because I suck at running llm benchmarks, but from hand testing running the model through https://edabit.com/challenge coding challenges vs up to date gpt-4. My model is hands down beating it in coding.


Ive recently noticed this model has trouble with end tokens so I made a custom prompt template for it. Made sure to add (Always end with "<|EOT|>") In addition to your system prompt and (Always end your response with "<|EOT|>") at the end of the User message is the preset. Then add <|EOT|> as a custom stop string in your LM text generating interface.

Always end with "<|EOT|>"

{System}

<|User|>

{User}. Always end your response with "<|EOT|>"

<|Assistant|>

{Assistant}

The models that were used in this merger were as follow:

Thank you to the creators of the above ai models, they have full credit for the EveryoneLLM series of models. Without their hard work we wouldnt be able to achieve the great success we have in the open source community. 💗

You can find the write up for merging models here:

https://docs.google.com/document/d/1_vOftBnrk9NRk5h10UqrfJ5CDih9KBKL61yvrZtVWPE/edit?usp=sharing

Config for the merger can be found bellow:

models:
  - model: WizardLM_WizardCoder-33B-V1.1
    parameters:
      density: 1
      weight: .5
  - model: codefuse-ai_CodeFuse-DeepSeek-33B
    parameters:
      density: 1
      weight: .5
merge_method: ties
base_model: deepseek-ai_deepseek-coder-33b-instruct
parameters:
  normalize: true
  int8_mask: true
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 49.48
AI2 Reasoning Challenge (25-Shot) 45.99
HellaSwag (10-Shot) 61.71
MMLU (5-Shot) 44.05
TruthfulQA (0-shot) 42.26
Winogrande (5-shot) 63.06
GSM8k (5-shot) 39.80