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--- |
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license: apache-2.0 |
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language: |
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- en |
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- zh |
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base_model: |
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- Qwen/Qwen2.5-14B |
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- Qwen/Qwen2.5-14B-Instruct |
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- Qwen/Qwen2.5-14B-Instruct-1M |
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- Qwen/Qwen2.5-Coder-14B |
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- Qwen/Qwen2.5-Coder-14B-Instruct |
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- Azure99/Blossom-V6-14B |
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- arcee-ai/SuperNova-Medius |
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- arcee-ai/Virtuoso-Small-v2 |
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- deepseek-ai/DeepSeek-R1-Distill-Qwen-14B |
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- huihui-ai/DeepSeek-R1-Distill-Qwen-14B-abliterated-v2 |
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pipeline_tag: text-generation |
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tags: |
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- merge |
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model-index: |
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- name: ZYH-LLM-Qwen2.5-14B-V4 |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: IFEval (0-Shot) |
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type: HuggingFaceH4/ifeval |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: inst_level_strict_acc and prompt_level_strict_acc |
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value: 83.65 |
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name: strict accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=YOYO-AI/ZYH-LLM-Qwen2.5-14B-V4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: BBH (3-Shot) |
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type: BBH |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc_norm |
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value: 50.27 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=YOYO-AI/ZYH-LLM-Qwen2.5-14B-V4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MATH Lvl 5 (4-Shot) |
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type: hendrycks/competition_math |
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args: |
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num_few_shot: 4 |
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metrics: |
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- type: exact_match |
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value: 53.93 |
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name: exact match |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=YOYO-AI/ZYH-LLM-Qwen2.5-14B-V4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GPQA (0-shot) |
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type: Idavidrein/gpqa |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 8.61 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=YOYO-AI/ZYH-LLM-Qwen2.5-14B-V4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MuSR (0-shot) |
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type: TAUR-Lab/MuSR |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 15.66 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=YOYO-AI/ZYH-LLM-Qwen2.5-14B-V4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU-PRO (5-shot) |
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type: TIGER-Lab/MMLU-Pro |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 46.71 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=YOYO-AI/ZYH-LLM-Qwen2.5-14B-V4 |
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name: Open LLM Leaderboard |
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--- |
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 |
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# ZYH-LLM-Qwen2.5-14B-V4 |
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*The fourth-generation model of ZYH-LLM-Qwen2.5 has been released!* |
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*Increase the proportion of the **R1 distillation model** in the model merging recipe while maintaining the model's **instruction-following ability** and **general capabilities.*** |
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## Merge Template |
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```yaml |
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merge_method: model_stock |
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base_model: Instruction Model |
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models: |
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- model: Instruction Fine-tuning Model 1 |
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- model: Instruction Fine-tuning Model 2 |
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- model: Inference Fine-tuning Model 1 |
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- model: Inference Fine-tuning Model 2 |
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dtype: bfloat16 |
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tokenizer_source: base |
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int8_mask: true |
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normalize: true |
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``` |
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Using the above template for merging can improve the **calculation accuracy** and **inference ability** of the model without reducing the **general capabilities** of the instruction model. |
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**ZYH-LLM-Qwen2.5-V4** used this template during the model merging process. |
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## [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/YOYO-AI__ZYH-LLM-Qwen2.5-14B-V4-details) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |43.14| |
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|IFEval (0-Shot) |83.65| |
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|BBH (3-Shot) |50.27| |
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|MATH Lvl 5 (4-Shot)|53.93| |
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|GPQA (0-shot) |8.61| |
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|MuSR (0-shot) |15.66| |
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|MMLU-PRO (5-shot) |46.71| |
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## First stage: |
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*Create four different instruction models and code model* |
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```yaml |
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models: |
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- model: Qwen/Qwen2.5-14B-Instruct |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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- model: Qwen/Qwen2.5-14B-Instruct-1M |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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merge_method: della |
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base_model: Qwen/Qwen2.5-14B |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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normalize: true |
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int8_mask: true |
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dtype: bfloat16 |
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tokenizer_source: base |
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name: Qwen2.5-14B-della-base |
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``` |
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```yaml |
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models: |
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- model: Qwen/Qwen2.5-14B-Instruct |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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- model: Qwen/Qwen2.5-14B-Instruct-1M |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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merge_method: della |
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base_model: arcee-ai/Virtuoso-Small-v2 |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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normalize: true |
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int8_mask: true |
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dtype: bfloat16 |
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tokenizer_source: base |
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name: Qwen2.5-14B-della-v2 |
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``` |
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```yaml |
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models: |
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- model: Qwen/Qwen2.5-14B-Instruct |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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- model: Qwen/Qwen2.5-14B-Instruct-1M |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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merge_method: della |
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base_model: arcee-ai/SuperNova-Medius |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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normalize: true |
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int8_mask: true |
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dtype: bfloat16 |
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tokenizer_source: base |
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name: Qwen2.5-14B-della-Nova |
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``` |
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```yaml |
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models: |
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- model: Qwen/Qwen2.5-14B-Instruct |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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- model: Qwen/Qwen2.5-14B-Instruct-1M |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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merge_method: della |
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base_model: Azure99/Blossom-V6-14B |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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normalize: true |
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int8_mask: true |
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dtype: bfloat16 |
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tokenizer_source: base |
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name: Qwen2.5-14B-della-V6 |
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``` |
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```yaml |
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models: |
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- model: Qwen/Qwen2.5-Coder-14B-Instruct |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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merge_method: della |
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base_model: Qwen/Qwen2.5-Coder-14B |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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normalize: true |
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int8_mask: true |
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dtype: bfloat16 |
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tokenizer_source: base |
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name: Qwen2.5-Coder-14B-della |
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``` |
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## Second stage: |
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### Step 1: |
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*Create three instruction models with a bias towards reasoning by using templates.* |
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```yaml |
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merge_method: model_stock |
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base_model: Qwen2.5-14B-della-base |
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models: |
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- model: Qwen2.5-Coder-14B-della |
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- model: Qwen2.5-14B-della-v2 |
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- model: deepseek-ai/DeepSeek-R1-Distill-Qwen-14B |
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- model: huihui-ai/DeepSeek-R1-Distill-Qwen-14B-abliterated-v2 |
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dtype: bfloat16 |
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tokenizer_source: base |
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int8_mask: true |
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normalize: true |
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name: Qwen2.5-14B-mst-Coder |
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``` |
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```yaml |
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merge_method: model_stock |
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base_model: Qwen2.5-14B-della-base |
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models: |
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- model: Qwen2.5-14B-della-V6 |
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- model: Qwen2.5-14B-della-v2 |
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- model: deepseek-ai/DeepSeek-R1-Distill-Qwen-14B |
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- model: huihui-ai/DeepSeek-R1-Distill-Qwen-14B-abliterated-v2 |
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dtype: bfloat16 |
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tokenizer_source: base |
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int8_mask: true |
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normalize: true |
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name: Qwen2.5-14B-mst-V6 |
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``` |
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```yaml |
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merge_method: model_stock |
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base_model: Qwen2.5-14B-della-base |
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models: |
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- model: Qwen2.5-14B-della-Nova |
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- model: Qwen2.5-14B-della-v2 |
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- model: deepseek-ai/DeepSeek-R1-Distill-Qwen-14B |
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- model: huihui-ai/DeepSeek-R1-Distill-Qwen-14B-abliterated-v2 |
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dtype: bfloat16 |
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tokenizer_source: base |
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int8_mask: true |
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normalize: true |
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name: Qwen2.5-14B-mst-Nova |
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``` |
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### Step 2: |
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*Create a pure instruction model to restore the generality of the final model.* |
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```yaml |
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merge_method: model_stock |
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base_model: Qwen2.5-14B-della-base |
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models: |
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- model: Qwen2.5-14B-della-Nova |
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- model: Qwen2.5-14B-della-v2 |
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- model: Qwen2.5-14B-della-V6 |
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dtype: bfloat16 |
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tokenizer_source: base |
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int8_mask: true |
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normalize: true |
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name: Qwen2.5-14B-mst-it |
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``` |
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## Third stage: |
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*Create a base model with a context of 1 million tokens.* |
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```yaml |
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merge_method: sce |
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models: |
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# Pivot model |
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- model: Qwen/Qwen2.5-14B-Instruct-1M |
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# Target models |
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- model: Qwen/Qwen2.5-14B |
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base_model: Qwen/Qwen2.5-14B-Instruct-1M |
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parameters: |
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select_topk: 1 |
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dtype: bfloat16 |
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tokenizer_source: base |
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normalize: true |
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int8_mask: true |
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name: Qwen2.5-14B-1M |
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``` |
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```yaml |
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models: |
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- model: Qwen/Qwen2.5-14B-Instruct |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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- model: Qwen/Qwen2.5-14B-Instruct-1M |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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merge_method: della |
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base_model: Qwen2.5-14B-1M |
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parameters: |
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density: 1 |
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weight: 1 |
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lambda: 0.9 |
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normalize: true |
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int8_mask: true |
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dtype: bfloat16 |
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tokenizer_source: base |
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name: Qwen2.5-14B-della-1M |
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``` |
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## Final stage: |
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|
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```yaml |
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merge_method: model_stock |
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base_model: Qwen2.5-14B-della-1M |
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models: |
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- model: Qwen2.5-14B-mst-Coder |
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- model: Qwen2.5-14B-mst-V6 |
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- model: Qwen2.5-14B-mst-Nova |
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- model: Qwen2.5-14B-mst-it |
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dtype: bfloat16 |
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tokenizer_source: base |
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int8_mask: true |
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normalize: true |
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name: ZYH-LLM-Qwen2.5-14B-V4 |
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``` |
