Bagel-Hermes-34B-Slerp
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:
- Nous-Hermes-2-Yi-34B
- bagel-dpo-34b-v0.2
- nontoxic-bagel-34b-v0.2
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: bagel-dpo-34b-v0.2
layer_range: [0, 60]
- model: Nous-Hermes-2-Yi-34B
layer_range: [0, 60]
merge_method: slerp
base_model: nontoxic-bagel-34b-v0.2
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
tokenizer_source: union
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 75.24 |
| AI2 Reasoning Challenge (25-Shot) | 70.73 |
| HellaSwag (10-Shot) | 85.68 |
| MMLU (5-Shot) | 77.29 |
| TruthfulQA (0-shot) | 67.09 |
| Winogrande (5-shot) | 84.37 |
| GSM8k (5-shot) | 66.26 |
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 27.06 |
| IFEval (0-Shot) | 46.03 |
| BBH (3-Shot) | 41.96 |
| MATH Lvl 5 (4-Shot) | 4.91 |
| GPQA (0-shot) | 11.30 |
| MuSR (0-shot) | 17.01 |
| MMLU-PRO (5-shot) | 41.15 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard70.730
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard85.680
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard77.290
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard67.090
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard84.370
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard66.260
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard46.030
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard41.960
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard4.910
- acc_norm on GPQA (0-shot)Open LLM Leaderboard11.300