README.md

---
language:
- en
- zh
license: apache-2.0
library_name: transformers
tags:
- chat
- conversational
- custom-research
- rp
- roleplay
- tool-use
base_model:
- Qwen/Qwen2.5-14B-Instruct
pipeline_tag: text-generation
model-index:
- name: miscii-14b-1028
  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: 82.37
      name: strict accuracy
    source:
      url: >-
        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
      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: 49.26
      name: normalized accuracy
    source:
      url: >-
        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
      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: 6.34
      name: exact match
    source:
      url: >-
        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
      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: 14.21
      name: acc_norm
    source:
      url: >-
        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
      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: 12
      name: acc_norm
    source:
      url: >-
        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
      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: 46.14
      name: accuracy
    source:
      url: >-
        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
      name: Open LLM Leaderboard
datasets:
- nvidia/HelpSteer2
- google/Synthetic-Persona-Chat
- mlabonne/orpo-dpo-mix-40k
---

# miscii-14b-1028

## Role-based Instructions

Just parse the following as your system prompt.
Note there is NO `special-tokens` here.

An example system prompt:

```python
system_prompt: str = (
    """<|context_start|>personas<|context_sep|>
<|persona_start|>user<|persona_sep|>
{user_persona}<|persona_end|>
<|persona_start|>assistant<|persona_sep|>
{assistant_persona}<|persona_end|><|context_end|>""".format(
        user_persona="""I am Miscii.
I am the designer of Sthenno.
[Optional: Additional statements]""",
        assistant_persona="""I am Sthenno.
I speak in Chinese.
[Optional: Additional statements]""",
    )
)
```

## Training

See [Report for miscii-1020](https://api.wandb.ai/links/flandrelabs-carnegie-mellon-university/p35vchzx) for more details.

-----

# [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_sthenno-com__miscii-14b-1028).

|      Metric       |Value|
|-------------------|----:|
|Avg.               |35.05|
|IFEval (0-Shot)    |82.37|
|BBH (3-Shot)       |49.26|
|MATH Lvl 5 (4-Shot)| 6.34|
|GPQA (0-shot)      |14.21|
|MuSR (0-shot)      |12.00|
|MMLU-PRO (5-shot)  |46.14|

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