---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- Qwen/Qwen2.5-14B-Instruct
- Lambent/qwen2.5-lumen-rebased-14B
model-index:
- name: qwen2.5-reinstruct-alternate-lumen-14B
  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: 47.94
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
      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: 48.99
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
      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: 19.79
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
      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: 16.89
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
      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: 19.62
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
      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: 48.76
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Lambent/qwen2.5-reinstruct-alternate-lumen-14B
      name: Open LLM Leaderboard
---
# qwenreinstruct

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

## Merge Details

Extracted an approximate LoRA of v000000/Qwen2.5-Lumen-14B, rank 128 difference between that and Instruct,
and first applied this to Lambent/qwen2.5-14B-alternate-instruct-slerp which had no issues with EQ-Bench.

Then, here, re-applied a density and weight of original Instruct which in previous merges gave me no issues with EQ-Bench.

This one has EQ-Bench of 77.6713 and no "emotions don't match reference error" (if possibly still one not parsed).
This is similar to Lumen and original Instruct and slightly exceeds both (within margin of error).
My hope is that it has healed Instruct somewhat and regained its intelligence.

### Merge Method

This model was merged using the della merge method using [Lambent/qwen2.5-lumen-rebased-14B](https://huggingface.co/Lambent/qwen2.5-lumen-rebased-14B) as a base.

### Models Merged

The following models were included in the merge:
* [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: Qwen/Qwen2.5-14B-Instruct
    parameters:
      weight: 0.3
      density: 0.4
merge_method: della
base_model: Lambent/qwen2.5-lumen-rebased-14B
parameters:
  epsilon: 0.05
  lambda: 1
dtype: bfloat16
tokenizer_source: base


```

# [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_Lambent__qwen2.5-reinstruct-alternate-lumen-14B)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |33.66|
|IFEval (0-Shot)    |47.94|
|BBH (3-Shot)       |48.99|
|MATH Lvl 5 (4-Shot)|19.79|
|GPQA (0-shot)      |16.89|
|MuSR (0-shot)      |19.62|
|MMLU-PRO (5-shot)  |48.76|