merge
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.
Models Merged
The following models were included in the merge:
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: 0.53
weight: 0.75
- model: teknium/OpenHermes-2.5-Mistral-7B
parameters:
density: 0.53
weight: 0.25
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 73.60 |
AI2 Reasoning Challenge (25-Shot) | 71.67 |
HellaSwag (10-Shot) | 87.60 |
MMLU (5-Shot) | 64.83 |
TruthfulQA (0-shot) | 64.26 |
Winogrande (5-shot) | 84.69 |
GSM8k (5-shot) | 68.54 |
- Downloads last month
- 84
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for saishf/West-Hermes-7B
Merge model
this model
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard71.670
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard87.600
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.830
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard64.260
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard84.690
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard68.540