--- license: apache-2.0 tags: - merge model-index: - name: Slerp-CM-mist-dpo results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 69.62 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abacusai/Slerp-CM-mist-dpo name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 87.09 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abacusai/Slerp-CM-mist-dpo name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 64.81 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abacusai/Slerp-CM-mist-dpo name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 62.82 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abacusai/Slerp-CM-mist-dpo name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 81.45 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abacusai/Slerp-CM-mist-dpo name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 72.78 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abacusai/Slerp-CM-mist-dpo name: Open LLM Leaderboard --- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64c14f6b02e1f8f67c73bd05/V6OaYzWhNsFGwrl1M_ZjE.png) This model is a [Slerp Merge](https://github.com/cg123/mergekit/blob/main/mergekit/merge_methods/slerp.py) of [cookinai/CatMacaroni-Slerp](https://huggingface.co/cookinai/CatMacaroni-Slerp) and [mncai/mistral-7b-dpo-v5](https://huggingface.co/mncai/mistral-7b-dpo-v5). # Evaluation Results ### HuggingFace Leaderboard | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K | | --- | --- | --- | --- | --- | --- | --- | | 73.1 | 69.62 | 87.09 | 64.81 | 62.82 | 81.45 | 72.78 | The model did achieve an improvement in TruthfulQA over `cookinai/CatMacaroni-Slerp` and GSM8K over `mncai/mistral-7b-dpo-v5` which was the goal of the merge leading to an average score that was a better than both. It is unclear why the TruthfulQA metric is still meaningfully lower than the base `mncai/mistral-7b-dpo-v5`. # Training Details .yaml file for mergekit ```yaml slices: - sources: - model: cookinai/CatMacaroni-Slerp layer_range: [0, 32] - model: mncai/mistral-7b-dpo-v5 layer_range: [0, 32] merge_method: slerp base_model: mncai/mistral-7b-dpo-v5 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 # fallback for rest of tensors dtype: float16 ``` # Bias, Risks, and Limitations The model has not been evaluated for safety and is only intended for research and experiments. # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_abacusai__Slerp-CM-mist-dpo) | Metric |Value| |---------------------------------|----:| |Avg. |73.10| |AI2 Reasoning Challenge (25-Shot)|69.62| |HellaSwag (10-Shot) |87.09| |MMLU (5-Shot) |64.81| |TruthfulQA (0-shot) |62.82| |Winogrande (5-shot) |81.45| |GSM8k (5-shot) |72.78|