EmbeddedLLM/Mistral-7B-Merge-14-v0.3

Update 2024-01-03

Check out our v0.4 model which is based on this and achieves better average score of 71.19 versus 69.66.

Model Description

This is an update to EmbeddedLLM/Mistral-7B-Merge-14-v0.2 that removes potentially TruthfulQA-contaminated models and non-commercially licensed models:

1. berkeley-nest/Starling-LM-7B-alpha
2. Q-bert/MetaMath-Cybertron-Starling
3. v1olet/v1olet_marcoroni-go-bruins-merge-7B

This is an experiment to test merging 14 models using DARE TIES 🦙

The result is a base model that performs quite well but may need some further chat fine-tuning.

The 14 models are as follows:

1. mistralai/Mistral-7B-Instruct-v0.2
2. ehartford/dolphin-2.2.1-mistral-7b
3. SciPhi/SciPhi-Mistral-7B-32k
4. ehartford/samantha-1.2-mistral-7b
5. Arc53/docsgpt-7b-mistral
6. HuggingFaceH4/zephyr-7b-beta
7. meta-math/MetaMath-Mistral-7B
8. Open-Orca/Mistral-7B-OpenOrca
9. openchat/openchat-3.5-1210
10. beowolx/MistralHermes-CodePro-7B-v1
11. TIGER-Lab/MAmmoTH-7B-Mistral
12. teknium/OpenHermes-2.5-Mistral-7B
13. Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
14. mlabonne/NeuralHermes-2.5-Mistral-7B

• base model: mistralai/Mistral-7B-v0.1

Open LLM Leaderboard

	v0.3	v0.4
Average	69.66	71.19
ARC	65.96	66.81
HellaSwag	85.29	86.15
MMLU	64.35	65.10
TruthfulQA	57.80	58.25
Winogrande	78.30	80.03
GSM8K	66.26	70.81

Chat Template

We tried ChatML and Llama-2 chat template, but feel free to try other templates.

Merge Configuration

The merge config file for this model is here:

models:
  - model: mistralai/Mistral-7B-v0.1
    # no parameters necessary for base model
  - model: ehartford/dolphin-2.2.1-mistral-7b
    parameters:
      weight: 0.08
      density: 0.4
  - model: SciPhi/SciPhi-Mistral-7B-32k
    parameters:
      weight: 0.08
      density: 0.4
  - model: ehartford/samantha-1.2-mistral-7b
    parameters:
      weight: 0.08
      density: 0.4
  - model: Arc53/docsgpt-7b-mistral
    parameters:
      weight: 0.08
      density: 0.4
  - model: HuggingFaceH4/zephyr-7b-beta
    parameters:
      weight: 0.08
      density: 0.4
  - model: meta-math/MetaMath-Mistral-7B
    parameters:
      weight: 0.08
      density: 0.4
  - model: Open-Orca/Mistral-7B-OpenOrca
    parameters:
      weight: 0.08
      density: 0.4
  - model: openchat/openchat-3.5-1210
    parameters:
      weight: 0.08
      density: 0.4
  - model: beowolx/MistralHermes-CodePro-7B-v1
    parameters:
      weight: 0.08
      density: 0.4
  - model: TIGER-Lab/MAmmoTH-7B-Mistral
    parameters:
      weight: 0.08
      density: 0.4
  - model: teknium/OpenHermes-2.5-Mistral-7B
    parameters:
      weight: 0.08
      density: 0.4
  - model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
    parameters:
      weight: 0.08
      density: 0.4
  - model: mlabonne/NeuralHermes-2.5-Mistral-7B
    parameters:
      weight: 0.08
      density: 0.4
  - model: mistralai/Mistral-7B-Instruct-v0.2
    parameters:
      weight: 0.08
      density: 0.5
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16