---
license: apache-2.0
tags:
- merge
model-index:
- name: Mistral-CatMacaroni-slerp-gradient
  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: 65.53
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=diffnamehard/Mistral-CatMacaroni-slerp-gradient
      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: 85.66
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=diffnamehard/Mistral-CatMacaroni-slerp-gradient
      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: 61.53
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=diffnamehard/Mistral-CatMacaroni-slerp-gradient
      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: 64.1
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=diffnamehard/Mistral-CatMacaroni-slerp-gradient
      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: 80.03
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=diffnamehard/Mistral-CatMacaroni-slerp-gradient
      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: 57.62
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=diffnamehard/Mistral-CatMacaroni-slerp-gradient
      name: Open LLM Leaderboard
---

Slerp Merge of [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) and [cookinai/CatMacaroni-Slerp](https://huggingface.co/cookinai/CatMacaroni-Slerp)

.yaml file for mergekit

```
slices:
  - sources:
      - model: Mistral-7B-Instruct-v0.2
        layer_range: [0, 32]
      - model: CatMacaroni-Slerp-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: Mistral-7B-Instruct-v0.2
parameters:
  t:
    - value: [0, 0.3, 0.5, 0.7, 1]
dtype: float16
```

| Metric | Value |
| --- | --- |
| Avg. | 69.08 |
| ARC (25-shot) | 65.53 |
| HellaSwag (10-shot) | 85.66 |
| MMLU (5-shot) | 61.53 |
| TruthfulQA (0-shot) | 64.1 |
| Winogrande (5-shot) | 80.03 |
| GSM8K (5-shot) | 57.62 |
# [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_diffnamehard__Mistral-CatMacaroni-slerp-gradient)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |69.08|
|AI2 Reasoning Challenge (25-Shot)|65.53|
|HellaSwag (10-Shot)              |85.66|
|MMLU (5-Shot)                    |61.53|
|TruthfulQA (0-shot)              |64.10|
|Winogrande (5-shot)              |80.03|
|GSM8k (5-shot)                   |57.62|