README.md

---
license: apache-2.0
base_model:
- BAAI/Infinity-Instruct-7M-Gen-mistral-7B
- Senseable/WestLake-7B-v2
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- Gryphe/Tiamat-7b-1.1-DPO
- uukuguy/speechless-instruct-mistral-7b-v0.2
base_model_relation: merge
model-index:
- name: Proto-Athena-v0.2-4x7B
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: HuggingFaceH4/ifeval
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 37.52
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Proto-Athena-v0.2-4x7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: BBH
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 30.34
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Proto-Athena-v0.2-4x7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: hendrycks/competition_math
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 5.14
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Proto-Athena-v0.2-4x7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 6.49
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Proto-Athena-v0.2-4x7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MuSR (0-shot)
      type: TAUR-Lab/MuSR
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 10.96
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Proto-Athena-v0.2-4x7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU-PRO (5-shot)
      type: TIGER-Lab/MMLU-Pro
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 24.41
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Proto-Athena-v0.2-4x7B
      name: Open LLM Leaderboard
---

Test merge of 7b models for learning purposees.

New in v0.2:
Wanted to try a different gate type and using bfloat16, along with more detailed prompting to see if there's a noticeable difference.

Description:
This model is a merge of BAAI/Infinity-Instruct-7M-Gen-mistral-7B, SanjiWatsuki/Kunoichi-7B, Gryphe_Tiamat-7b-1.1-DPO, Senseable_WestLake-7B-v2 and uukuguy/speechless-instruct-mistral-7b-v0.2
This is the first model I've ever uploaded and wanted to learn more about the process. Merged using mergekit-moe.

Works up to 8k context, 16k with 2.5 RoPe scaling

Prompt template: Custom format, or Alpaca

Alpaca:
Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Jacoby746__Proto-Athena-v0.2-4x7B)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |19.14|
|IFEval (0-Shot)    |37.52|
|BBH (3-Shot)       |30.34|
|MATH Lvl 5 (4-Shot)| 5.14|
|GPQA (0-shot)      | 6.49|
|MuSR (0-shot)      |10.96|
|MMLU-PRO (5-shot)  |24.41|