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metadata
language:
  - en,
license: other
license_name: yi-license
license_link: https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE
pipeline_tag: text-generation
model-index:
  - name: SG-Raccoon-Yi-200k-2.0
    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: 62.54
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlinmg/SG-Raccoon-Yi-200k-2.0
          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: 80.26
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlinmg/SG-Raccoon-Yi-200k-2.0
          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: 73.29
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlinmg/SG-Raccoon-Yi-200k-2.0
          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: 53.21
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlinmg/SG-Raccoon-Yi-200k-2.0
          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: 76.32
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlinmg/SG-Raccoon-Yi-200k-2.0
          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: 30.71
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlinmg/SG-Raccoon-Yi-200k-2.0
          name: Open LLM Leaderboard


SG Raccoon 55B 2.0

The first 55B auto-regressive causal LM created by combining 2x finetuned llamafied Yi 34b with 200K context into one.

Prompting Format

SYSTEM: <ANY SYSTEM CONTEXT>
USER: 
ASSISTANT:

Merge process

The models used in the merge are Tess-M-v1.3 and airoboros-3_1-yi-34b-200k.

The layer ranges used are as follows:

- model: bhenrym14/airoboros-3_1-yi-34b-200k
  layer_range: [0, 14]
- model: migtissera/Tess-M-v1.3
  layer_range: [7, 21]  
- model: bhenrym14/airoboros-3_1-yi-34b-200k
  layer_range: [15, 29] 
- model: migtissera/Tess-M-v1.3
  layer_range: [22, 36] 
- model: bhenrym14/airoboros-3_1-yi-34b-200k
  layer_range: [30, 44] 
- model: migtissera/Tess-M-v1.3
  layer_range: [37, 51]  
- model: bhenrym14/airoboros-3_1-yi-34b-200k
  layer_range: [45, 59] 

Tips

Being a Yi model, try disabling the BOS token and/or running a lower temperature with MinP (and no other samplers) if output doesn't seem right. Yi tends to run "hot" by default.

Sometimes the model "spells out" the stop token as like Capybara, so you may need to add as an additional stopping condition.

Benchmarks

Coming soon.

Acknowledgements

  • Special thanks to MSS for sponsoring this project

  • @chargoddard for developing the framework used to merge the model - mergekit.

  • Great thanks to @Undi95 for helping figuring out model merge options

  • Also credits to the 01-ai team for their amazing models

  • This merged model is inspired by Goliath 120B

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 62.72
AI2 Reasoning Challenge (25-Shot) 62.54
HellaSwag (10-Shot) 80.26
MMLU (5-Shot) 73.29
TruthfulQA (0-shot) 53.21
Winogrande (5-shot) 76.32
GSM8k (5-shot) 30.71