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--- |
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license: apache-2.0 |
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library_name: transformers |
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tags: |
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- mergekit |
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- merge |
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base_model: |
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- shahzebnaveed/NeuralHermes-2.5-Mistral-7B |
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- berkeley-nest/Starling-LM-7B-alpha |
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model-index: |
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- name: StarlingHermes-2.5-Mistral-7B-slerp |
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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: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 66.04 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=shahzebnaveed/StarlingHermes-2.5-Mistral-7B-slerp |
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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: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 85.18 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=shahzebnaveed/StarlingHermes-2.5-Mistral-7B-slerp |
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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 (5-Shot) |
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type: cais/mmlu |
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config: all |
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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: 64.72 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=shahzebnaveed/StarlingHermes-2.5-Mistral-7B-slerp |
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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: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 49.56 |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=shahzebnaveed/StarlingHermes-2.5-Mistral-7B-slerp |
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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: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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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: 79.72 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=shahzebnaveed/StarlingHermes-2.5-Mistral-7B-slerp |
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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: GSM8k (5-shot) |
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type: gsm8k |
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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: 65.96 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=shahzebnaveed/StarlingHermes-2.5-Mistral-7B-slerp |
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name: Open LLM Leaderboard |
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--- |
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# merge |
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). |
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## Merge Details |
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### Merge Method |
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This model was merged using the SLERP merge method. |
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### Models Merged |
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The following models were included in the merge: |
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* [shahzebnaveed/NeuralHermes-2.5-Mistral-7B](https://huggingface.co./shahzebnaveed/NeuralHermes-2.5-Mistral-7B) |
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* [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co./berkeley-nest/Starling-LM-7B-alpha) |
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### Configuration |
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The following YAML configuration was used to produce this model: |
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```yaml |
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slices: |
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- sources: |
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- model: berkeley-nest/Starling-LM-7B-alpha |
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layer_range: [0, 32] |
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- model: shahzebnaveed/NeuralHermes-2.5-Mistral-7B |
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layer_range: [0, 32] |
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merge_method: slerp |
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base_model: berkeley-nest/Starling-LM-7B-alpha |
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parameters: |
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t: |
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- filter: self_attn |
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value: [0, 0.5, 0.3, 0.7, 1] |
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- filter: mlp |
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value: [1, 0.5, 0.7, 0.3, 0] |
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- value: 0.5 |
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dtype: bfloat16 |
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``` |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_shahzebnaveed__StarlingHermes-2.5-Mistral-7B-slerp) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |68.53| |
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|AI2 Reasoning Challenge (25-Shot)|66.04| |
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|HellaSwag (10-Shot) |85.18| |
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|MMLU (5-Shot) |64.72| |
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|TruthfulQA (0-shot) |49.56| |
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|Winogrande (5-shot) |79.72| |
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|GSM8k (5-shot) |65.96| |
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