--- base_model: - qingy2024/Fusion4-14B-Instruct - sometimesanotion/Lamarck-14B-v0.6 - allknowingroger/QwenSlerp6-14B - CultriX/SeQwence-14B-EvolMerge - CultriX/Qwen2.5-14B-Wernickev3 - hotmailuser/QwenSlerp2-14B - CultriX/Qwen2.5-14B-Emerged - djuna/Q2.5-Veltha-14B-0.5 library_name: transformers tags: - mergekit - merge --- # merge This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ## Merge Details ### Merge Method This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [CultriX/Qwen2.5-14B-Wernickev3](https://huggingface.co/CultriX/Qwen2.5-14B-Wernickev3) as a base. ### Models Merged The following models were included in the merge: * [qingy2024/Fusion4-14B-Instruct](https://huggingface.co/qingy2024/Fusion4-14B-Instruct) * [sometimesanotion/Lamarck-14B-v0.6](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.6) * [allknowingroger/QwenSlerp6-14B](https://huggingface.co/allknowingroger/QwenSlerp6-14B) * [CultriX/SeQwence-14B-EvolMerge](https://huggingface.co/CultriX/SeQwence-14B-EvolMerge) * [hotmailuser/QwenSlerp2-14B](https://huggingface.co/hotmailuser/QwenSlerp2-14B) * [CultriX/Qwen2.5-14B-Emerged](https://huggingface.co/CultriX/Qwen2.5-14B-Emerged) * [djuna/Q2.5-Veltha-14B-0.5](https://huggingface.co/djuna/Q2.5-Veltha-14B-0.5) ### Configuration The following YAML configuration was used to produce this model: ```yaml merge_method: dare_ties # Changed to dare_ties base_model: CultriX/Qwen2.5-14B-Wernickev3 dtype: bfloat16 # Use float32 for maximum precision. out_dtype: bfloat16 # Output model also uses bfloat16 for consistency and reduced memory usage. parameters: t: 0.5 # Balances interpolation between models; 0.5 gives equal weight to all contributors. normalize: true # Ensures parameters are normalized to maintain stability during merging. rescale: true # Aligns parameter scales across models for better integration. int8_mask: false # Disable int8 masking to preserve full precision during merging. epsilon: 0.008 # Ultra-fine parameter scaling for precise adjustments between models. lambda: 1.8 # Emphasizes high-impact parameters, giving more weight to significant contributors. adaptive_merge_parameters: task_weights: # Assign weights to tasks based on their priority and impact on benchmarks. tinyArc: 1.6 # Logical reasoning benchmark; slightly lower priority. tinyHellaswag: 1.5 # Contextual reasoning benchmark with moderate priority. tinyMMLU: 1.8 # Multi-domain knowledge benchmark; important for multitask performance. tinyTruthfulQA: 1.9 # Focuses on factual reasoning and QA; high priority. tinyTruthfulQA_mc1: 1.75 # Multiple-choice factual reasoning; closely related to TruthfulQA. tinyWinogrande: 1.75 # Core reasoning benchmark; slightly lower than BBH. IFEval: 2.30 # Instruction-following tasks; given a high priority for practical applications. BBH: 2.05 # Complex reasoning benchmark; critical for logical tasks. MATH: 2.70 # Highest priority to emphasize mathematical reasoning excellence. GPQA: 2.20 # Graduate-level QA tasks; balanced priority for high-level reasoning. MUSR: 2.15 # Multi-step reasoning; slightly increased to strengthen reasoning performance. MMLU-PRO: 2.00 # Domain multitask benchmark; maintained for general multitask capability. smoothing_factor: 0.03 # Low smoothing for precise task-specific blending without over-generalizing. gradient_clipping: # Control gradient clipping for each model to stabilize training. CultriX/Qwen2.5-14B-Wernickev3: 0.89 # Higher value ensures stability for the base model. djuna/Q2.5-Veltha-14B-0.5: 0.92 # Stable setting to enhance reasoning contributions. CultriX/SeQwence-14B-EvolMerge: 0.87 # Moderate value for generalist multitask support. qingy2024/Fusion4-14B-Instruct: 0.93 # High stability to emphasize mathematical tasks. CultriX/Qwen2.5-14B-Emerged: 0.88 # Stable setting to maintain multitask performance. sometimesanotion/Lamarck-14B-v0.6: 0.89 # Stable contribution for multi-step reasoning. allknowingroger/QwenSlerp6-14B: 0.90 # Adjusted for stable integration of the replacement model. hotmailuser/QwenSlerp2-14B: 0.91 # Increased slightly for stable integration of reasoning contributions. models: # Define models to include in the merge, along with their weights and densities. - model: CultriX/Qwen2.5-14B-Wernickev3 parameters: weight: 0.33 # Increased to absorb some of the weight from the removed model. density: 0.78 # Maintained optimal density for robust generalist performance. - model: djuna/Q2.5-Veltha-14B-0.5 parameters: weight: 0.28 # Increased slightly to enhance reasoning benchmarks like MUSR. density: 0.77 # Maintained for strong nuanced reasoning. - model: allknowingroger/QwenSlerp6-14B # Replacement for Qwenfinity-2.5-14B. parameters: weight: 0.15 # Matches the weight of the replaced model to preserve balance. density: 0.70 # Increased slightly for stronger parameter integration. - model: CultriX/SeQwence-14B-EvolMerge parameters: weight: 0.12 # Moderate weight for general multitask support. density: 0.62 # Maintained for stable contribution. - model: qingy2024/Fusion4-14B-Instruct parameters: weight: 0.09 # Moderate weight; focuses on mathematical reasoning tasks. density: 0.75 # Maintained density for stable integration. - model: CultriX/Qwen2.5-14B-Emerged parameters: weight: 0.08 # Balanced weight for multitask contributions. density: 0.69 # Maintained density for stable integration. - model: sometimesanotion/Lamarck-14B-v0.6 parameters: weight: 0.06 # Lower weight to allow more impactful models to dominate. density: 0.62 # Maintained for stable multi-step reasoning contribution. - model: hotmailuser/QwenSlerp2-14B parameters: weight: 0.11 # Increased slightly to balance contributions. density: 0.66 # Maintained for stable parameter integration. ```