base_model, library_name, tags, license, model-index

base_model	library_name	tags	license	model-index
mistralai/Mistral-7B-v0.1 argilla/distilabeled-OpenHermes-2.5-Mistral-7B NeverSleep/Noromaid-7B-0.4-DPO senseable/WestLake-7B-v2 mlabonne/AlphaMonarch-7B	transformers	mergekit merge	cc-by-nc-4.0	name results WestLake_Noromaid_OpenHermes_neural-chatv0.1 task dataset metrics source type name text-generation Text Generation name type config split args EQ-Bench eq-bench EQ-Bench v2.1 num_few_shot 3 type value name acc_norm 77.19 self-reported url name https://github.com/EQ-bench/EQ-Bench EQ-Bench v2.1 task dataset metrics source type name text-generation Text Generation name type config split args AI2 Reasoning Challenge (25-Shot) ai2_arc ARC-Challenge test num_few_shot 25 type value name acc_norm 70.22 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type split args HellaSwag (10-Shot) hellaswag validation num_few_shot 10 type value name acc_norm 87.42 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args MMLU (5-Shot) cais/mmlu all test num_few_shot 5 type value name acc 64.31 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args TruthfulQA (0-shot) truthful_qa multiple_choice validation num_few_shot 0 type value mc2 61.99 url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args Winogrande (5-shot) winogrande winogrande_xl validation num_few_shot 5 type value name acc 82.16 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args GSM8k (5-shot) gsm8k main test num_few_shot 5 type value name acc 69.6 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1 Open LLM Leaderboard

WestMaid_HermesMonarchv0.1

This model benchmarks quite well compared to other 7b models, and has exceptional MT-Bench and EQ-Bench v2.1 scores, ranking higher than ChatGPT-3.5-turbo and Claude-1 in both tests, and Goliath-120b, and other 70B models in the latter .

This is a merge of pre-trained language models created using mergekit

Merge Details

Merge Method

This model was merged using the DARE TIES merge method using mistralai/Mistral-7B-v0.1 as a base. Density was chosen deterministically between the models chosen for this merge. After testing many densities, I settled on 0.58 for each of the chosen models as it returned the highest EQ-Bench score. Not much testing was done with the weights, but I thought that I'd try gradients. Conceptually, Westlake and a Distilled version of Open Heremes are heavier in the initial layers (guiding understanding, and thoughts), before Noromaid and AlphaMonarch come in to guide its wants, reasoning, and conversation.

Models Merged

The following models were included in the merge:

• mlabonne/AlphaMonarch-7B
• NeverSleep/Noromaid-7B-0.4-DPO
• senseable/WestLake-7B-v2
• argilla/distilabeled-OpenHermes-2.5-Mistral-7B

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: mistralai/Mistral-7B-v0.1
    # No parameters necessary for base model
  - model: senseable/WestLake-7B-v2
    parameters:
      density: 0.58
      weight: [0.50, 0.40, 0.25, 0.05]
  - model: NeverSleep/Noromaid-7B-0.4-DPO
    parameters:
      density: 0.58
      weight: [0.05, 0.05, 0.25, 0.40]
  - model: argilla/distilabeled-OpenHermes-2.5-Mistral-7B
    parameters:
      density: 0.58
      weight: [0.40, 0.50, 0.25, 0.05]
  - model: mlabonne/AlphaMonarch-7B
    parameters:
      density: 0.58
      weight: [0.05, 0.05, 0.25, 0.50]
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16

Benchmark Testing

MT-Bench

EQ-Bench Leaderboard

Table of Benchmarks

Open LLM Leaderboard

	Average	ARC	HellaSwag	MMLU	TruthfulQA	Winogrande	GSM8K
giraffe176/WestMaid_HermesMonarchv0.1	72.62	70.22	87.42	64.31	61.99	82.16	69.6
AlphaMonarch-7B	75.99	73.04	89.18	64.4	77.91	84.69	66.72
senseable/WestLake-7B-v2	74.68	73.04	88.65	64.71	67.06	86.98	67.63
teknium/OpenHermes-2.5-Mistral-7B	61.52	64.93	84.18	63.64	52.24	78.06	26.08
NeverSleep/Noromaid-7B-0.4-DPO	59.08	62.29	84.32	63.2	42.28	76.95	25.47

Yet Another LLM Leaderboard benchmarks

Model	AGIEval	GPT4All	TruthfulQA	Bigbench	Average
WestMaid_HermesMonarchv0.1	45.34	76.33	61.99	46.02	57.42

Misc. Benchmarks

	MT-Bench	EQ-Bench v2.1
giraffe176/WestMaid_HermesMonarchv0.1	8.021875	77.19 (3 Shot, ooba)
AlphaMonarch-7B	7.928125	76.08
senseable/WestLake-7B-v2		78.7
teknium/OpenHermes-2.5-Mistral-7B		66.89
claude-v1	7.900000	76.83
gpt-3.5-turbo	7.943750	71.74
	(Paper)	(Paper) Leaderboard