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Adding Evaluation Results (#2)
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metadata
license: other
tags:
  - merge
license_name: yi-34b
license_link: https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE
model-index:
  - name: Nous-Hermes-2-SUS-Chat-34B-Slerp
    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: 66.72
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Nous-Hermes-2-SUS-Chat-34B-Slerp
          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: 84.97
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Nous-Hermes-2-SUS-Chat-34B-Slerp
          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
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Nous-Hermes-2-SUS-Chat-34B-Slerp
          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: 59.23
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Nous-Hermes-2-SUS-Chat-34B-Slerp
          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: 83.58
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Nous-Hermes-2-SUS-Chat-34B-Slerp
          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: 72.86
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Nous-Hermes-2-SUS-Chat-34B-Slerp
          name: Open LLM Leaderboard

image/png

Nous-Hermes-2-SUS-Chat-34B-Slerp

This is the model for Nous-Hermes-2-SUS-Chat-34B-Slerp. I used mergekit to merge models.

Prompt Templates

You can use these prompt templates, but I recommend using ChatML.

ChatML (NousResearch/Nous-Hermes-2-Yi-34B):

<|im_start|>system
{system}<|im_end|>
<|im_start|>user
{user}<|im_end|>
<|im_start|>assistant
{asistant}<|im_end|>

Human - Asistant (SUSTech/SUS-Chat-34B):

### Human: {user}

### Assistant: {asistant}

Yaml Config


slices:
- sources:
    - model: Nous-Hermes-2-Yi-34B
      layer_range: [0, 60]
    - model: SUS-Chat-34B
      layer_range: [0, 60]

merge_method: slerp
base_model: Yi-34B

parameters:
t:
  - filter: self_attn
    value: [0, 0.5, 0.3, 0.7, 1]
  - filter: mlp
    value: [1, 0.5, 0.7, 0.3, 0]
  - value: 0.5
tokenizer_source: union
dtype: bfloat16

Quantizationed versions

Quantizationed versions of this model is available thanks to TheBloke.

GPTQ
GGUF
AWQ

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 74.06
AI2 Reasoning Challenge (25-Shot) 66.72
HellaSwag (10-Shot) 84.97
MMLU (5-Shot) 77.00
TruthfulQA (0-shot) 59.23
Winogrande (5-shot) 83.58
GSM8k (5-shot) 72.86