README.md

---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- EmbeddedLLM/Mistral-7B-Merge-14-v0.1
- amazon/MistralLite
model-index:
- name: Mistral-7B-Merge-14-v0.2
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 65.02
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tourist800/Mistral-7B-Merge-14-v0.2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 85.13
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tourist800/Mistral-7B-Merge-14-v0.2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 64.36
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tourist800/Mistral-7B-Merge-14-v0.2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 54.15
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tourist800/Mistral-7B-Merge-14-v0.2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 79.24
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tourist800/Mistral-7B-Merge-14-v0.2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 56.86
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tourist800/Mistral-7B-Merge-14-v0.2
      name: Open LLM Leaderboard
---

# Mistral-7B-Merge-14-v0.2

Mistral-7B-Merge-14-v0.2 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [EmbeddedLLM/Mistral-7B-Merge-14-v0.1](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.1)
* [amazon/MistralLite](https://huggingface.co/amazon/MistralLite)

## 🧩 Configuration

```yaml
slices:
  - sources:
      - model: EmbeddedLLM/Mistral-7B-Merge-14-v0.1
        layer_range: [0, 32]
      - model: amazon/MistralLite
        layer_range: [0, 32]
merge_method: slerp
base_model: EmbeddedLLM/Mistral-7B-Merge-14-v0.1
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_tourist800__Mistral-7B-Merge-14-v0.2)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |67.46|
|AI2 Reasoning Challenge (25-Shot)|65.02|
|HellaSwag (10-Shot)              |85.13|
|MMLU (5-Shot)                    |64.36|
|TruthfulQA (0-shot)              |54.15|
|Winogrande (5-shot)              |79.24|
|GSM8k (5-shot)                   |56.86|