merged
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the task arithmetic merge method using teknium/OpenHermes-2.5-Mistral-7B as a base.
Models Merged
The following models were included in the merge:
- simonveitner/Math-OpenHermes-2.5-Mistral-7B
- mlabonne/NeuralHermes-2.5-Mistral-7B-laser
- openaccess-ai-collective/dpopenhermes-alpha-v0
- mlabonne/NeuralHermes-2.5-Mistral-7B
Configuration
The following YAML configuration was used to produce this model:
base_model: teknium/OpenHermes-2.5-Mistral-7B
dtype: bfloat16
merge_method: task_arithmetic
slices:
- sources:
- layer_range: [0, 32]
model: teknium/OpenHermes-2.5-Mistral-7B
- layer_range: [0, 32]
model: simonveitner/Math-OpenHermes-2.5-Mistral-7B
parameters:
weight: 0.25
- layer_range: [0, 32]
model: openaccess-ai-collective/dpopenhermes-alpha-v0
parameters:
weight: 0.25
- layer_range: [0, 32]
model: mlabonne/NeuralHermes-2.5-Mistral-7B
parameters:
weight: 0.25
- layer_range: [0, 32]
model: mlabonne/NeuralHermes-2.5-Mistral-7B-laser
parameters:
weight: 0.25
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 68.04 |
AI2 Reasoning Challenge (25-Shot) | 65.61 |
HellaSwag (10-Shot) | 84.47 |
MMLU (5-Shot) | 63.69 |
TruthfulQA (0-shot) | 53.18 |
Winogrande (5-shot) | 77.74 |
GSM8k (5-shot) | 63.53 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard65.610
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard84.470
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard63.690
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard53.180
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard77.740
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard63.530