---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- sometimesanotion/Lamarck-14B-v0.7
- sometimesanotion/Qwenvergence-14B-v12-Prose-DS
model-index:
- name: Lamarckvergence-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: 76.56
      name: strict accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Lamarckvergence-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: 50.33
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Lamarckvergence-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: 54.0
      name: exact match
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Lamarckvergence-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: 15.1
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Lamarckvergence-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: 16.34
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Lamarckvergence-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: 47.59
      name: accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=suayptalha/Lamarckvergence-14B
      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:
* [sometimesanotion/Lamarck-14B-v0.7](https://huggingface.co./sometimesanotion/Lamarck-14B-v0.7)
* [sometimesanotion/Qwenvergence-14B-v12-Prose-DS](https://huggingface.co./sometimesanotion/Qwenvergence-14B-v12-Prose-DS)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: sometimesanotion/Lamarck-14B-v0.7
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.5, 0.3, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.5, 0.7, 0.3, 0.0]
  - value: 0.5
slices:
- sources:
  - layer_range: [0, 48]
    model: sometimesanotion/Lamarck-14B-v0.7
  - layer_range: [0, 48]
    model: sometimesanotion/Qwenvergence-14B-v12-Prose-DS
```

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# [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__Lamarckvergence-14B-details)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |43.32|
|IFEval (0-Shot)    |76.56|
|BBH (3-Shot)       |50.33|
|MATH Lvl 5 (4-Shot)|54.00|
|GPQA (0-shot)      |15.10|
|MuSR (0-shot)      |16.34|
|MMLU-PRO (5-shot)  |47.59|