Clarus-7B-v0.1/README.md

---
language:
- en
license: mit
library_name: transformers
tags:
- mergekit
- merge
base_model:
- gz987/qwen2.5-7b-cabs-v0.4
- gz987/qwen2.5-7b-cabs-v0.3
pipeline_tag: text-generation
model-index:
- name: Clarus-7B-v0.1
  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: 74.54
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Clarus-7B-v0.1
      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: 36.03
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Clarus-7B-v0.1
      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: 49.24
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Clarus-7B-v0.1
      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: 7.61
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Clarus-7B-v0.1
      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: 15.17
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Clarus-7B-v0.1
      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: 37.64
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Clarus-7B-v0.1
      name: Open LLM Leaderboard
---
# Merged Model

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](https://en.wikipedia.org/wiki/Slerp) merge method.

### Models Merged

The following models were included in the merge:
* [gz987/qwen2.5-7b-cabs-v0.4](https://huggingface.co/gz987/qwen2.5-7b-cabs-v0.4)
* [gz987/qwen2.5-7b-cabs-v0.3](https://huggingface.co/gz987/qwen2.5-7b-cabs-v0.3)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
slices:
  - sources:
      - model: gz987/qwen2.5-7b-cabs-v0.3
        layer_range: [0, 28]
      - model: gz987/qwen2.5-7b-cabs-v0.4
        layer_range: [0, 28]
merge_method: slerp
base_model: gz987/qwen2.5-7b-cabs-v0.3
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 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/suayptalha__Clarus-7B-v0.1-details)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |36.71|
|IFEval (0-Shot)    |74.54|
|BBH (3-Shot)       |36.03|
|MATH Lvl 5 (4-Shot)|49.24|
|GPQA (0-shot)      | 7.61|
|MuSR (0-shot)      |15.17|
|MMLU-PRO (5-shot)  |37.64|

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