Merged models
Collection
Mering experiments. • 2 items • Updated • 3
merged
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
The following YAML configuration was used to produce this model:
base_model: EmbeddedLLM/Mistral-7B-Merge-14-v0.1
dtype: bfloat16
merge_method: slerp
parameters:
t:
- filter: self_attn
value: [0.0, 0.5, 0.3, 0.7, 1.0]
- filter: mlp
value: [1.0, 0.5, 0.7, 0.3, 0.0]
- value: 0.5
slices:
- sources:
- layer_range: [0, 32]
model: SanjiWatsuki/Sonya-7B
- layer_range: [0, 32]
model: SanjiWatsuki/Kunoichi-7B
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 70.52 |
| AI2 Reasoning Challenge (25-Shot) | 67.49 |
| HellaSwag (10-Shot) | 86.43 |
| MMLU (5-Shot) | 63.58 |
| TruthfulQA (0-shot) | 63.25 |
| Winogrande (5-shot) | 78.53 |
| GSM8k (5-shot) | 63.84 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard67.490
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard86.430
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard63.580
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard63.250
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard78.530
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard63.840