---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- bunnycore/QwQen-3B-LCoT
- bunnycore/Qwen-2.5-3b-R1-lora_model-v.1
model-index:
- name: QwQen-3B-LCoT-R1
  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: 53.42
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QwQen-3B-LCoT-R1
      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: 26.98
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QwQen-3B-LCoT-R1
      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: 33.53
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QwQen-3B-LCoT-R1
      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: 1.57
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QwQen-3B-LCoT-R1
      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: 10.03
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QwQen-3B-LCoT-R1
      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: 30.26
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QwQen-3B-LCoT-R1
      name: Open LLM Leaderboard
---

When using the QwQen-3B-LCoT-R1 model, you might notice that it can sometimes produce repetitive outputs, especially in certain contexts or with specific prompts. This is a common behavior in language models, but don’t worry—it can be managed effectively by tweaking the model’s repetition parameters.

### To reduce repetition, you can experiment with the following settings:

- Repetition Penalty: This parameter discourages the model from repeating the same words or phrases by applying a penalty. A higher value (e.g., 1.0) will push the model to avoid repetition more aggressively.
- Temperature: This controls the randomness of the output. Lowering the temperature (e.g., 0.7) makes the model more focused and less likely to repeat itself, though it may reduce creativity slightly.


## System Prompt:

```
Think about the reasoning process in the mind first, then provide the answer.

The reasoning process should be wrapped within <think> </think> tags, then provide the answer after that, i.e., <think> reasoning process here </think> answer here.

```



### Configuration

The following YAML configuration was used to produce this model:

```yaml

base_model: bunnycore/QwQen-3B-LCoT+bunnycore/Qwen-2.5-3b-R1-lora_model-v.1
dtype: bfloat16
merge_method: passthrough
models:
  - model: bunnycore/QwQen-3B-LCoT+bunnycore/Qwen-2.5-3b-R1-lora_model-v.1
tokenizer_source: bunnycore/QwQen-3B-LCoT

```

# [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/bunnycore__QwQen-3B-LCoT-R1-details)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |25.97|
|IFEval (0-Shot)    |53.42|
|BBH (3-Shot)       |26.98|
|MATH Lvl 5 (4-Shot)|33.53|
|GPQA (0-shot)      | 1.57|
|MuSR (0-shot)      |10.03|
|MMLU-PRO (5-shot)  |30.26|