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Qwenslerp2-7B

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Qwenslerp2-7B
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---
license: apache-2.0
library_name: transformers
tags:
- mergekit
- merge
base_model:
- fblgit/cybertron-v4-qw7B-MGS
- Tsunami-th/Tsunami-0.5x-7B-Instruct
model-index:
- name: Qwenslerp2-7B
  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: 52.94
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Qwenslerp2-7B
      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: 37.44
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Qwenslerp2-7B
      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: 31.87
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Qwenslerp2-7B
      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: 8.39
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Qwenslerp2-7B
      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: 12.82
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Qwenslerp2-7B
      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: 39.06
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Qwenslerp2-7B
      name: Open LLM Leaderboard
---
# merge

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:
* [fblgit/cybertron-v4-qw7B-MGS](https://huggingface.co/fblgit/cybertron-v4-qw7B-MGS)
* [Tsunami-th/Tsunami-0.5x-7B-Instruct](https://huggingface.co/Tsunami-th/Tsunami-0.5x-7B-Instruct)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: fblgit/cybertron-v4-qw7B-MGS
  - model: Tsunami-th/Tsunami-0.5x-7B-Instruct
merge_method: slerp
base_model: fblgit/cybertron-v4-qw7B-MGS
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers

```
# [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_allknowingroger__Qwenslerp2-7B)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |30.42|
|IFEval (0-Shot)    |52.94|
|BBH (3-Shot)       |37.44|
|MATH Lvl 5 (4-Shot)|31.87|
|GPQA (0-shot)      | 8.39|
|MuSR (0-shot)      |12.82|
|MMLU-PRO (5-shot)  |39.06|