merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
Configuration
Since Slerp allows merging two models at a time, the following YAML configurations were used to produce this model:
slices:
- sources:
- model: HuggingFaceH4/zephyr-7b-beta
layer_range: [0, 32]
- model: NousResearch/Hermes-2-Pro-Mistral-7B
layer_range: [0, 32]
merge_method: slerp
base_model: HuggingFaceH4/zephyr-7b-beta
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
Then
slices:
- sources:
- model: ./merge
layer_range: [0, 32]
- model: instructlab/merlinite-7b-lab
layer_range: [0, 32]
merge_method: slerp
base_model: ./merge
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 67.76 |
| AI2 Reasoning Challenge (25-Shot) | 64.25 |
| HellaSwag (10-Shot) | 85.47 |
| MMLU (5-Shot) | 64.89 |
| TruthfulQA (0-shot) | 53.57 |
| Winogrande (5-shot) | 79.16 |
| GSM8k (5-shot) | 59.21 |