---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- wanlige/li-14b-v0.4
- sthenno-com/miscii-14b-0218
model-index:
- name: li-14b-v0.4-slerp0.1
  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: 79.23
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=wanlige/li-14b-v0.4-slerp0.1
      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: 50.88
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=wanlige/li-14b-v0.4-slerp0.1
      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: 53.32
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=wanlige/li-14b-v0.4-slerp0.1
      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: 14.54
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=wanlige/li-14b-v0.4-slerp0.1
      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: 11.75
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=wanlige/li-14b-v0.4-slerp0.1
      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: 47.71
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=wanlige/li-14b-v0.4-slerp0.1
      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](https://en.wikipedia.org/wiki/Slerp) merge method.

### Models Merged

The following models were included in the merge:
* [wanlige/li-14b-v0.4](https://huggingface.co/wanlige/li-14b-v0.4)
* [sthenno-com/miscii-14b-0218](https://huggingface.co/sthenno-com/miscii-14b-0218)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
# merge_method:        arcee_fusion
# base_model:          wanlige/li-14b-v0.4
# tokenizer_source:    base
# parameters:
#   int8_mask:         true
#   normalize:         true
#   rescale:           false
# dtype:               bfloat16
# out_dtype:           bfloat16
# models:
#   - model:           sthenno-com/miscii-14b-0218

base_model:          wanlige/li-14b-v0.4
merge_method:        slerp
tokenizer_source:    base
dtype:               float32
out_dtype:           bfloat16
parameters:
  t:
    - filter:        self_attn
      value:         [ 0.00, 0.50, 0.30, 0.70, 1.00 ]
    - filter:        mlp
      value:         [ 1.00, 0.50, 0.70, 0.30, 0.00 ]
    - value:         [ 0.00, 0.00, 0.00, 0.00, 0.04, 0.08, 0.12, 0.16, 0.24, 0.32, 0.40, 0.48, 0.56, 0.64, 0.72, 0.72, 0.72, 0.72, 0.72, 0.72, 0.72, 0.72, 0.64, 0.56, 0.48 ]
slices:
  - sources:
      - model:       wanlige/li-14b-v0.4
        layer_range: [ 0, 48 ]
      - model:       sthenno-com/miscii-14b-0218
        layer_range: [ 0, 48 ]

```

# [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/wanlige__li-14b-v0.4-slerp0.1-details)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |42.91|
|IFEval (0-Shot)    |79.23|
|BBH (3-Shot)       |50.88|
|MATH Lvl 5 (4-Shot)|53.32|
|GPQA (0-shot)      |14.54|
|MuSR (0-shot)      |11.75|
|MMLU-PRO (5-shot)  |47.71|