README.md

---
license: apache-2.0
library_name: transformers
tags:
- mergekit
- merge
- qwen2
- qwen2.5
- dpo
base_model:
- v000000/Qwen2.5-14B-Gutenberg-1e-Delta
- Qwen/Qwen2.5-14B-Instruct
datasets:
- jondurbin/gutenberg-dpo-v0.1
model-index:
- name: Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
  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: 48.55
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
      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: 49.74
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
      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: 19.71
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
      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: 15.21
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
      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: 18.43
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
      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: 48.68
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
      name: Open LLM Leaderboard
---

# Qwen2.5-14B-Gutenberg-Instruct-Slerpeno

![image/png](https://cdn-uploads.huggingface.co/production/uploads/64f74b6e6389380c77562762/PgoZ5eutiHDfBmuoBuDO9.png)

--------------------------------------------------------------------------

## GGUF from mradermacher!

* [GGUF static](https://huggingface.co/mradermacher/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno-GGUF)

* [GGUF Imatrix](https://huggingface.co/mradermacher/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno-i1-GGUF)

## GGUF from QuantFactory!

* [GGUF static](https://huggingface.co/QuantFactory/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno-GGUF)

# 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. (*sophosympatheia gradient*)

### Models Merged

The following models were included in the merge:
* [v000000/Qwen2.5-14B-Gutenberg-1e-Delta](https://huggingface.co/v000000/Qwen2.5-14B-Gutenberg-1e-Delta)
* [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
merge_method: slerp
base_model: v000000/Qwen2.5-14B-Gutenberg-1e-Delta
parameters:
  t:
    - value: [0, 0, 0.3, 0.4, 0.5, 0.6, 0.5, 0.4, 0.3, 0, 0]
dtype: bfloat16
```

*The idea here is that Gutenberg DPO stays in the output/input 100% while merging smoothly with the base instruct model in the deeper layers to heal loss and increase intelligence.*
# [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_v000000__Qwen2.5-14B-Gutenberg-Instruct-Slerpeno)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |33.39|
|IFEval (0-Shot)    |48.55|
|BBH (3-Shot)       |49.74|
|MATH Lvl 5 (4-Shot)|19.71|
|GPQA (0-shot)      |15.21|
|MuSR (0-shot)      |18.43|
|MMLU-PRO (5-shot)  |48.68|