giraffe176/Open_Maid_Samantha_Hermes_Orca
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:
- cognitivecomputations/samantha-1.1-westlake-7b
- NeverSleep/Noromaid-7B-0.4-DPO
- OpenHermes-2.5-Mistral-7B
- Open-Orca/Mistral-7B-OpenOrca
Configuration
The following YAML configuration was used to produce this model:
models:
- model: cognitivecomputations/samantha-1.1-westlake-7b
layer_range: [0, 32]
- model: NeverSleep/Noromaid-7B-0.4-DPO
layer_range: [0, 32]
merge_method: slerp
base_model: NeverSleep/Noromaid-7B-0.4-DPO
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
name: workspace1
---
models:
- model: teknium/OpenHermes-2.5-Mistral-7B
layer_range: [0, 32]
- model: Open-Orca/Mistral-7B-OpenOrca
layer_range: [0, 32]
merge_method: slerp
base_model: teknium/OpenHermes-2.5-Mistral-7B
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
name: workspace2
---
models:
- model: workspace1
layer_range: [0, 32]
- model: workspace2
layer_range: [0, 32]
merge_method: slerp
base_model: workspace1
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. | 68.81 |
AI2 Reasoning Challenge (25-Shot) | 66.81 |
HellaSwag (10-Shot) | 85.83 |
MMLU (5-Shot) | 64.58 |
TruthfulQA (0-shot) | 53.91 |
Winogrande (5-shot) | 80.35 |
GSM8k (5-shot) | 61.41 |
- Downloads last month
- 67
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for giraffe176/Open_Maid_Samantha_Hermes_Orca
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard66.810
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard85.830
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.580
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard53.910
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard80.350
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard61.410