README.md

---
language:
- en
license: llama3.1
library_name: transformers
tags:
- mergekit
- merge
- shining-valiant
- shining-valiant-2
- cobalt
- plum
- valiant
- valiant-labs
- llama
- llama-3.1
- llama-3.1-instruct
- llama-3.1-instruct-8b
- llama-3
- llama-3-instruct
- llama-3-instruct-8b
- 8b
- math
- math-instruct
- science
- physics
- biology
- chemistry
- compsci
- computer-science
- engineering
- technical
- conversational
- chat
- instruct
base_model:
- meta-llama/Llama-3.1-8B-Instruct
- ValiantLabs/Llama3.1-8B-ShiningValiant2
- ValiantLabs/Llama3.1-8B-Cobalt
pipeline_tag: text-generation
model_type: llama
model-index:
- name: sequelbox/Llama3.1-8B-PlumMath
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-Shot)
      type: Winogrande
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 72.38
      name: acc
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MathQA (5-Shot)
      type: MathQA
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 40.27
      name: acc
  - 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: 22.42
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumMath
      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: 16.45
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumMath
      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: 3.93
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumMath
      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: 9.06
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumMath
      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: 8.98
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumMath
      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: 21.95
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumMath
      name: Open LLM Leaderboard
---
# PlumMath

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 della merge method using [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) as a base.

### Models Merged

The following models were included in the merge:
* [ValiantLabs/Llama3.1-8B-ShiningValiant2](https://huggingface.co/ValiantLabs/Llama3.1-8B-ShiningValiant2)
* [ValiantLabs/Llama3.1-8B-Cobalt](https://huggingface.co/ValiantLabs/Llama3.1-8B-Cobalt)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
merge_method: della
dtype: bfloat16
parameters:
  normalize: true
models:
  - model: ValiantLabs/Llama3.1-8B-ShiningValiant2
    parameters:
      density: 0.5
      weight: 0.3
  - model: ValiantLabs/Llama3.1-8B-Cobalt
    parameters:
      density: 0.5
      weight: 0.2
base_model: meta-llama/Llama-3.1-8B-Instruct
```

# [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_sequelbox__Llama3.1-8B-PlumMath)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |13.80|
|IFEval (0-Shot)    |22.42|
|BBH (3-Shot)       |16.45|
|MATH Lvl 5 (4-Shot)| 3.93|
|GPQA (0-shot)      | 9.06|
|MuSR (0-shot)      | 8.98|
|MMLU-PRO (5-shot)  |21.95|