Cerberus-7B-slerp
Cerberus-7B-slerp is a merge of the following models using mergekit:
🧩 Configuration
slices:
- sources:
- model: fblgit/UNA-TheBeagle-7b-v1
layer_range: [0, 32]
- model: UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3
layer_range: [0, 32]
merge_method: slerp
base_model: fblgit/UNA-TheBeagle-7b-v1
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. | 63.46 |
| AI2 Reasoning Challenge (25-Shot) | 69.54 |
| HellaSwag (10-Shot) | 87.33 |
| MMLU (5-Shot) | 63.25 |
| TruthfulQA (0-shot) | 61.35 |
| Winogrande (5-shot) | 81.29 |
| GSM8k (5-shot) | 17.97 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard69.540
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard87.330
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard63.250
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard61.350
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard81.290
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard17.970