--- license: apache-2.0 library_name: transformers tags: - mergekit - merge base_model: - bamec66557/MISCHIEVOUS-12B-Mix_0.4v - bamec66557/MISCHIEVOUS-12B-Mix_0.5v model-index: - name: MISCHIEVOUS-12B-Mix_Neo results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 62.5 name: strict accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/MISCHIEVOUS-12B-Mix_Neo name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 30.36 name: normalized accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/MISCHIEVOUS-12B-Mix_Neo name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 11.63 name: exact match source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/MISCHIEVOUS-12B-Mix_Neo name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 8.84 name: acc_norm source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/MISCHIEVOUS-12B-Mix_Neo name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 11.64 name: acc_norm source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/MISCHIEVOUS-12B-Mix_Neo name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 29.84 name: accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/MISCHIEVOUS-12B-Mix_Neo name: Open LLM Leaderboard datasets: - open-llm-leaderboard/bamec66557__MISCHIEVOUS-12B-Mix_Neo-details --- # 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 SLERP merge method. ### Models Merged The following models were included in the merge: * [bamec66557/MISCHIEVOUS-12B-Mix_0.4v](https://huggingface.co/bamec66557/MISCHIEVOUS-12B-Mix_0.4v) * [bamec66557/MISCHIEVOUS-12B-Mix_0.5v](https://huggingface.co/bamec66557/MISCHIEVOUS-12B-Mix_0.5v) ### Configuration The following YAML configuration was used to produce this model: ```yaml description: Merging MISCHIEVOUS-12B-Mix models with sliced slerp # Metadata and Rationale model_description: | This configuration merges two versions of the MISCHIEVOUS-12B-Mix model: 0.4v and 0.3v. 0.3v was further fine-tuned on a specific dataset (ADD DATASET NAME HERE if known). The sliced slerp approach allows for layer-specific control over the merging process. base_model: bamec66557/MISCHIEVOUS-12B-Mix_0.4v dtype: bfloat16 merge_method: slerp tokenizer_source: union # Slices Configuration (Layer-Specific Merging) slices: - sources: - model: bamec66557/MISCHIEVOUS-12B-Mix_0.4v layer_range: [0, 10] - model: bamec66557/MISCHIEVOUS-12B-Mix_0.5v layer_range: [0, 10] parameters: t: - name: self_attn value: [0.8, 0.85, 0.9, 0.95, 1.0] - name: mlp value: [0.9, 0.95, 1.0, 1.05, 1.1] - name: layer_norm value: [0.6, 0.65, 0.7, 0.75, 0.8] - name: embed_tokens value: [1.0] - sources: - model: bamec66557/MISCHIEVOUS-12B-Mix_0.4v layer_range: [10, 20] - model: bamec66557/MISCHIEVOUS-12B-Mix_0.5v layer_range: [10, 20] parameters: t: - name: self_attn value: [0.7, 0.75, 0.8, 0.85, 0.9] - name: mlp value: [1.0, 0.95, 0.9, 0.85, 0.8] - name: layer_norm value: [0.5, 0.55, 0.6, 0.65, 0.7] - name: embed_tokens value: [1.0] - sources: - model: bamec66557/MISCHIEVOUS-12B-Mix_0.4v layer_range: [20, 30] - model: bamec66557/MISCHIEVOUS-12B-Mix_0.5v layer_range: [20, 30] parameters: t: - name: self_attn value: [0.6, 0.65, 0.7, 0.75, 0.8] - name: mlp value: [0.8, 0.75, 0.7, 0.65, 0.6] - name: layer_norm value: [0.4, 0.45, 0.5, 0.55, 0.6] - name: embed_tokens value: [1.0] - sources: - model: bamec66557/MISCHIEVOUS-12B-Mix_0.4v layer_range: [30, 40] - model: bamec66557/MISCHIEVOUS-12B-Mix_0.5v layer_range: [30, 40] parameters: t: - name: self_attn value: [0.9, 1.0, 1.1, 1.2, 1.3] - name: mlp value: [0.7, 0.65, 0.6, 0.55, 0.5] - name: layer_norm value: [0.7, 0.75, 0.8, 0.85, 0.9] - name: embed_tokens value: [1.0] # Regularization (Prevent Overfitting During Merging) regularization: - method: weight_clipping clip_range: [-0.2, 0.2] - method: random_noise scale: 0.015 - method: l2_norm scale: 0.01 # Postprocessing (Enhance Merged Model Quality) postprocessing: - operation: random_noise scale: 0.0025 - operation: non_linear_scaling parameters: function: tanh - operation: sharpening intensity: 0.3 - operation: gaussian_smoothing sigma: 1.5 - operation: smoothing parameters: adaptive: true range: [0.8, 1.2] kernel_size: 5 - operation: normalize - operation: dynamic_scaling scale_range: [0.75, 1.25] # Evaluation (Crucial for Assessing Merge Quality) evaluation: metrics: - perplexity - accuracy # If applicable (e.g., classification tasks) - bleu # For translation tasks - rouge # For summarization tasks datasets: - wikitext # General language understanding - lambada # Long-range dependency modeling - (ADD RELEVANT TASK-SPECIFIC DATASETS HERE) prompts: # Example prompts – REPLACE WITH YOUR OWN - "The quick brown fox jumps over the lazy dog." - "Translate 'Thank you' to Spanish:" - "Write a short summary of the French Revolution." # Logging and Output logging: output_dir: ./merged_models log_level: INFO # Optional: Ties Merging (Advanced Technique) # ties: # enabled: true # method: greedy # Or "optimal", "random" # layers: [0, 10, 20, 30] # Example layers for ties merging ``` # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/bamec66557__MISCHIEVOUS-12B-Mix_Neo-details) | Metric |Value| |-------------------|----:| |Avg. |25.80| |IFEval (0-Shot) |62.50| |BBH (3-Shot) |30.36| |MATH Lvl 5 (4-Shot)|11.63| |GPQA (0-shot) | 8.84| |MuSR (0-shot) |11.64| |MMLU-PRO (5-shot) |29.84|