README.md

---
language:
- en
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
model-index:
- name: HermesStar-OrcaWind-Synth-11B
  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: 65.27
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/HermesStar-OrcaWind-Synth-11B
      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: 83.69
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/HermesStar-OrcaWind-Synth-11B
      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: 65.31
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/HermesStar-OrcaWind-Synth-11B
      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: 48.55
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/HermesStar-OrcaWind-Synth-11B
      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: 80.11
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/HermesStar-OrcaWind-Synth-11B
      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: 56.63
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/HermesStar-OrcaWind-Synth-11B
      name: Open LLM Leaderboard
---
Open Hermes + Starling passthrough merged

SlimOrca(?)+Zephyr Beta linear merged, then passthrough merged with Synthia

Then both models were merged again in 1 to 0.3 ratio.

# My findings:

Increasing repetition penalty usually makes the model smarter up to a degree but it also causes stability issues.

Since most of the merged models were trained with ChatML, use ChatML template. Rarely the model throws another EOS token though.

- My favorite preset has been uploaded.
- You can use some sort of CoT prompt instead of "system" in ChatML. It does improve the quality of most output.
(You are an assistant. Break down the question and come to a conclusion.)

I don't know what I am doing, you are very welcome to put the model through benchmarks. 

I'll also upload q6 GGUF but my internet is shit, so don't hesitate to share other quantizations.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Ba2han__HermesStar-OrcaWind-Synth-11B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |66.59|
|AI2 Reasoning Challenge (25-Shot)|65.27|
|HellaSwag (10-Shot)              |83.69|
|MMLU (5-Shot)                    |65.31|
|TruthfulQA (0-shot)              |48.55|
|Winogrande (5-shot)              |80.11|
|GSM8k (5-shot)                   |56.63|