WestLake_Noromaid_OpenHermes_neural-chatv0.1
This is a merge of pre-trained language models created using mergekit. DPO training data has been used to slightly uncensor the LLM. The model's focus is in conversational roleplay. In limited testing, I've been very happy with the result. It has been able to pick up stories where other models have failed or started to loop their responses, and it seems to pace the story well.
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:
- cognitivecomputations/WestLake-7B-v2-laser
- NeverSleep/Noromaid-7B-0.4-DPO
- teknium/OpenHermes-2.5-Mistral-7B
- Intel/neural-chat-7b-v3-3
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: cognitivecomputations/WestLake-7B-v2-laser
parameters:
density: 0.55
weight: 0.15
- model: NeverSleep/Noromaid-7B-0.4-DPO
parameters:
density: 0.55
weight: 0.35
- model: teknium/OpenHermes-2.5-Mistral-7B
parameters:
density: 0.55
weight: 0.30
- model: Intel/neural-chat-7b-v3-3
parameters:
density: 0.55
weight: 0.20
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
dtype: bfloat16
Benchmark Testing
MT-Bench | EQ-Bench v2.1 | |
---|---|---|
giraffe176/WestLake_Noromaid_OpenHermes_neural-chatv0.1 | 7.171875 | 65.56 |
(Paper) | (Paper) |
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Avg. | AI2 (25-Shot) | HellaSwag (10-Shot) | MMLU (5-Shot) | TruthfulQA (0-shot) | Winogrande (5-shot) | GSM8k (5-shot) | |
---|---|---|---|---|---|---|---|
This model | 68.86 | 66.72 | 85.37 | 64.67 | 51.50 | 79.72 | 65.20 |
cognitivecomputations/WestLake-7B-v2-laser | 74.78 | 73.29 | 88.66 | 64.72 | 67.04 | 86.74 | 68.23 |
NeverSleep/Noromaid-7B-0.4-DPO | 59.08 | 62.29 | 84.32 | 63.2 | 42.28 | 76.95 | 25.47 |
teknium/OpenHermes-2.5-Mistral-7B | 61.52 | 64.93 | 84.18 | 63.64 | 52.24 | 78.06 | 26.08 |
Intel/neural-chat-7b-v3-3 | 69.83 | 66.89 | 85.26 | 63.07 | 63.01 | 79.64 | 61.11 |
DPO training data used:
- unalignment/toxic-dpo-v0.2 (Curated version)
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Evaluation results
- normalized accuracy on EQ-BenchEQ-Bench v2.165.560
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard66.720
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard85.370
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.670
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard51.500
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard79.720
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard65.200