File size: 2,051 Bytes
1d15e79 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
base_model: CultriX/SeQwence-14Bv1
merge_method: dare_ties
parameters:
normalize: true
int8_mask: true
dtype: bfloat16
models:
- model: CultriX/SeQwence-14Bv1
parameters:
weight: 0.28 # Strong base for multitask benchmarks.
density: 0.7 # Retains strong multitask performance.
- model: CultriX/Qwen2.5-14B-Wernickev3
parameters:
weight: 0.22 # Balanced to support reasoning-heavy benchmarks like BBH.
density: 0.65
- model: qingy2019/Qwen2.5-Math-14B-Instruct
parameters:
weight: 0.22 # Optimized for MATH and BBH.
density: 0.6
- model: allknowingroger/QwenSlerp6-14B
parameters:
weight: 0.18 # Reintegration of the highest scorer for stability across benchmarks.
density: 0.65 # Focused on its exceptional multitask and reasoning strengths.
- model: CultriX/Qwen2.5-14B-Emergedv3
parameters:
weight: 0.15 # Maintains multitask stability for GPQA and MMLU-PRO.
density: 0.6
- model: sometimesanotion/Qwen2.5-14B-Vimarckoso
parameters:
weight: 0.1 # Late-layer contributor for MUSR and multi-step reasoning.
density: 0.6
adaptive_merge_parameters:
task_weights:
IFEval: 1.4 # Balanced to maintain instruction-following benchmarks.
BBH: 1.4 # Ensures strong reasoning capabilities.
MATH: 1.5 # Prioritizes mathematical reasoning.
GPQA: 1.5 # Balanced for factual QA.
MUSR: 1.4 # Advanced multi-step reasoning.
MMLU-PRO: 1.5 # Emphasized for domain-specific multitask performance.
smoothing_factor: 0.12 # Smooth transitions between task-specific contributions.
gradient_clipping:
CultriX/SeQwence-14Bv1: 0.8
CultriX/Qwen2.5-14B-Wernickev3: 0.8
qingy2019/Qwen2.5-Math-14B-Instruct: 0.85
allknowingroger/QwenSlerp6-14B: 0.8 # Balanced for high scoring model contributions.
CultriX/Qwen2.5-14B-Emergedv3: 0.75
sometimesanotion/Qwen2.5-14B-Vimarckoso: 0.75
tokenizer_source: CultriX/SeQwence-14Bv1
|