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: 0.65
- model: SanjiWatsuki/Kunoichi-DPO-v2-7B
parameters:
density: 0.53
weight: 0.35
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. | 73.56 |
| AI2 Reasoning Challenge (25-Shot) | 71.84 |
| HellaSwag (10-Shot) | 88.15 |
| MMLU (5-Shot) | 64.76 |
| TruthfulQA (0-shot) | 66.83 |
| Winogrande (5-shot) | 84.45 |
| GSM8k (5-shot) | 65.35 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard71.840
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard88.150
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.760
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard66.830
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard84.450
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard65.350