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---
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|
|