README.md

---
license: apache-2.0
library_name: transformers
tags:
- mergekit
- merge
base_model:
- unsloth/Qwen2.5-Coder-3B-Instruct
- bunnycore/Qwen-2.5-3b-R1-lora_model-v.1
model-index:
- name: Q2.5-CodeR1-3B
  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: 35.88
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-CodeR1-3B
      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: 25.31
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-CodeR1-3B
      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: 16.39
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-CodeR1-3B
      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: 7.16
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-CodeR1-3B
      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: 12.14
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-CodeR1-3B
      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: 21.99
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-CodeR1-3B
      name: Open LLM Leaderboard
---
# Merge

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details

Qwen Coder tied to Reasoning LORA.

### Merge Method

This model was merged using the Passthrough merge method using [unsloth/Qwen2.5-Coder-3B-Instruct](https://huggingface.co/unsloth/Qwen2.5-Coder-3B-Instruct) + [bunnycore/Qwen-2.5-3b-R1-lora_model-v.1](https://huggingface.co/bunnycore/Qwen-2.5-3b-R1-lora_model-v.1) as a base.

### Models Merged

The following models were included in the merge:


### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: unsloth/Qwen2.5-Coder-3B-Instruct+bunnycore/Qwen-2.5-3b-R1-lora_model-v.1
dtype: bfloat16
merge_method: passthrough
models:
  - model: unsloth/Qwen2.5-Coder-3B-Instruct+bunnycore/Qwen-2.5-3b-R1-lora_model-v.1
tokenizer_source: unsloth/Qwen2.5-Coder-3B

```
# [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/Triangle104__Q2.5-CodeR1-3B-details)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |19.81|
|IFEval (0-Shot)    |35.88|
|BBH (3-Shot)       |25.31|
|MATH Lvl 5 (4-Shot)|16.39|
|GPQA (0-shot)      | 7.16|
|MuSR (0-shot)      |12.14|
|MMLU-PRO (5-shot)  |21.99|