ScaleDown-7B-slerp-v0.1
This model is a merge of the following models made with mergekit:
🧩 Configuration
slices:
- sources:
- model: OpenPipe/mistral-ft-optimized-1218
layer_range: [0, 32]
- model: jondurbin/bagel-dpo-7b-v0.1
layer_range: [0, 32]
merge_method: slerp
base_model: OpenPipe/mistral-ft-optimized-1218
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. | 71.57 |
| AI2 Reasoning Challenge (25-Shot) | 68.00 |
| HellaSwag (10-Shot) | 85.70 |
| MMLU (5-Shot) | 65.26 |
| TruthfulQA (0-shot) | 61.90 |
| Winogrande (5-shot) | 81.37 |
| GSM8k (5-shot) | 67.17 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard68.000
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard85.700
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard65.260
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard61.900
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard81.370
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard67.170