---
license: apache-2.0
library_name: transformers
tags:
- mergekit
- merge
base_model:
- Qwen/Qwen2.5-1.5B-Instruct
- Qwen/Qwen2.5-1.5B
model-index:
- name: lareneg1_78B-ECE-PRYMMAL-Martial
  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: 27.95
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
      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: 19.02
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
      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: 8.91
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
      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: 4.25
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
      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: 6.51
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
      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: 21.36
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
      name: Open LLM Leaderboard
---
# my-output

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

## Merge Details
### Merge Method

This model was merged using the SLERP merge method.

### Models Merged

The following models were included in the merge:
* [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
* [Qwen/Qwen2.5-1.5B](https://huggingface.co/Qwen/Qwen2.5-1.5B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml

slices:
  - sources:
      - model: Qwen/Qwen2.5-1.5B
        layer_range: [0, 28]
      - model: Qwen/Qwen2.5-1.5B-Instruct
        layer_range: [0, 28]
merge_method: slerp
base_model: Qwen/Qwen2.5-1.5B-Instruct
parameters:
  t:
    - filter: self_attn
      value: [0, 0.25, 0.5, 0.75, 1]
    - filter: mlp
      value: [1, 0.75, 0.5, 0.25, 0]
    - value: 0.5
dtype: bfloat16


```
# [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_Marsouuu__lareneg1_78B-ECE-PRYMMAL-Martial)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |14.67|
|IFEval (0-Shot)    |27.95|
|BBH (3-Shot)       |19.02|
|MATH Lvl 5 (4-Shot)| 8.91|
|GPQA (0-shot)      | 4.25|
|MuSR (0-shot)      | 6.51|
|MMLU-PRO (5-shot)  |21.36|