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: 0.55
- model: NeverSleep/Noromaid-7B-0.4-DPO
parameters:
density: 0.53
weight: 0.30
- model: Undi95/Toppy-M-7B
parameters:
density: 0.53
weight: 0.15
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. | 71.57 |
AI2 Reasoning Challenge (25-Shot) | 69.37 |
HellaSwag (10-Shot) | 87.40 |
MMLU (5-Shot) | 64.63 |
TruthfulQA (0-shot) | 58.79 |
Winogrande (5-shot) | 83.27 |
GSM8k (5-shot) | 65.96 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard69.370
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard87.400
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.630
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard58.790
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard83.270
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard65.960