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---
license: cc-by-nc-4.0
library_name: transformers
tags:
- mergekit
- merge
base_model:
- 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
model-index:
- name: WestLake_Noromaid_OpenHermes_neural-chatv0.1
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: EQ-Bench
type: eq-bench
config: EQ-Bench
split: v2.1
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 77.19
name: self-reported
source:
url: https://github.com/EQ-bench/EQ-Bench
name: EQ-Bench v2.1
- 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: 70.22
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1
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: 87.42
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1
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: 64.31
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1
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: 61.99
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1
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: 82.16
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1
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: 69.6
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=giraffe176/WestMaid_HermesMonarchv0.1
name: Open LLM Leaderboard
---
# WestMaid_HermesMonarchv0.1
<img src="/static-proxy?url=https%3A%2F%2Fcdn-uploads.huggingface.co%2Fproduction%2Fuploads%2F655a9883cbbaec115c3fd6b3%2FYJTMJZF80hKaKnPDu_yMV.png%26quot%3B%3C%2Fspan%3E alt="drawing" width="800"/>
This model benchmarks quite well compared to other 7b models, and has exceptional [MT-Bench](https://github.com/lm-sys/FastChat/tree/main/fastchat/llm_judge) and [EQ-Bench v2.1](https://github.com/EQ-bench/EQ-Bench) 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](https://github.com/cg123/mergekit)
## Merge Details
### Merge Method
This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [mistralai/Mistral-7B-v0.1](https://huggingface.co/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](https://huggingface.co/mlabonne/AlphaMonarch-7B)
* [NeverSleep/Noromaid-7B-0.4-DPO](https://huggingface.co/NeverSleep/Noromaid-7B-0.4-DPO)
* [senseable/WestLake-7B-v2](https://huggingface.co/senseable/WestLake-7B-v2)
* [argilla/distilabeled-OpenHermes-2.5-Mistral-7B](https://huggingface.co/argilla/distilabeled-OpenHermes-2.5-Mistral-7B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
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
%3C%2Fspan%3E
### EQ-Bench Leaderboard
<img src="/static-proxy?url=https%3A%2F%2Fcdn-uploads.huggingface.co%2Fproduction%2Fuploads%2F655a9883cbbaec115c3fd6b3%2F0Z6AIhaqCiKREf0fQEVqr.png%26quot%3B%3C%2Fspan%3E alt="drawing" width="800"/>
### Table of Benchmarks
| | MT-Bench | EQ-Bench v2.1 | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
|---------------------------------------------------------|---------------------------------------------|---------------------------------------------------------------------------------|---------|-------|-----------|-------|------------|------------|-------|
| giraffe176/WestMaid_HermesMonarchv0.1 | 8.021875 | 77.19 (3 Shot, ooba) | 72.62 | 70.22 | 87.42 | 64.31 | 61.99 | 82.16 | 69.6 |
| AlphaMonarch-7B | 7.928125 | 76.08 | 75.99 | 73.04 | 89.18 | 64.4 | 77.91 | 84.69 | 66.72 |
| senseable/WestLake-7B-v2 | | 78.7 | 74.68 | 73.04 | 88.65 | 64.71 | 67.06 | 86.98 | 67.63 |
| teknium/OpenHermes-2.5-Mistral-7B | | 66.89 | 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 |
| claude-v1 | 7.900000 | 76.83 | | | | | | | |
| gpt-3.5-turbo | 7.943750 | 71.74 | | | | | | | |
| | [(Paper)](https://arxiv.org/abs/2306.05685) | [(Paper)](https://arxiv.org/abs/2312.06281) [Leaderboard](https://eqbench.com/) | | | | | | | |
# [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_giraffe176__WestMaid_HermesMonarchv0.1)
| Metric |Value|
|---------------------------------|----:|
|Avg. |72.62|
|AI2 Reasoning Challenge (25-Shot)|70.22|
|HellaSwag (10-Shot) |87.42|
|MMLU (5-Shot) |64.31|
|TruthfulQA (0-shot) |61.99|
|Winogrande (5-shot) |82.16|
|GSM8k (5-shot) |69.60|
|