155 lines
4.8 KiB
Markdown
155 lines
4.8 KiB
Markdown
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---
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license: other
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tags:
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- merge
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- mergekit
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- lazymergekit
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- microsoft/Orca-2-13b
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- KoboldAI/LLaMA2-13B-Psyfighter2
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base_model:
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- KoboldAI/LLaMA2-13B-Psyfighter2
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- microsoft/Orca-2-13b
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license_name: microsoft-research-license
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model-index:
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- name: Psyfighter2-Orca2-13B-ties
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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: 62.46
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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=tuantran1632001/Psyfighter2-Orca2-13B-ties
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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: 81.74
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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=tuantran1632001/Psyfighter2-Orca2-13B-ties
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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: 60.31
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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=tuantran1632001/Psyfighter2-Orca2-13B-ties
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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: 55.4
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tuantran1632001/Psyfighter2-Orca2-13B-ties
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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: 77.27
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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=tuantran1632001/Psyfighter2-Orca2-13B-ties
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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: 43.67
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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=tuantran1632001/Psyfighter2-Orca2-13B-ties
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name: Open LLM Leaderboard
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---
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# Psyfighter2-Orca2-ties
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Psyfighter2-Orca2-ties is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
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* [KoboldAI/LLaMA2-13B-Psyfighter2](https://huggingface.co/KoboldAI/LLaMA2-13B-Psyfighter2)
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* [microsoft/Orca-2-13b](https://huggingface.co/microsoft/Orca-2-13b)
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This is my very first merge I have ever attempted. The motivation behind this merge is to try and create a 13B version of [jebcarter/psyonic-cetacean-20B](https://huggingface.co/jebcarter/psyonic-cetacean-20B). I don't have a good GPU (GTX 1660 6GB), so although I can merge the model, I cannot actually run it. However, the Open LLM Leaderboard ranks this merge with 63.48 avg point, which is higher than both KoboldAI/LLaMA2-13B-Psyfighter2 and jebcarter/psyonic-cetacean-20B, so I must did something right. The next step is to quantize this merge into GGUF so I can actually run it with [KoboldCpp](https://github.com/LostRuins/koboldcpp).
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## 🧩 Configuration
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```yaml
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models:
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- model: KoboldAI/LLaMA2-13B-Psyfighter2
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- model: microsoft/Orca-2-13b
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parameters:
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density: 0.40
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weight: [0, 0.3, 0.7, 1]
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merge_method: ties
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base_model: KoboldAI/LLaMA2-13B-Psyfighter2
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parameters:
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normalize: true
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int8_mask: true
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dtype: float16
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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_tuantran1632001__Psyfighter2-Orca2-13B-ties)
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| Metric |Value|
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|Avg. |63.48|
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|AI2 Reasoning Challenge (25-Shot)|62.46|
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|HellaSwag (10-Shot) |81.74|
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|MMLU (5-Shot) |60.31|
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|TruthfulQA (0-shot) |55.40|
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|Winogrande (5-shot) |77.27|
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|GSM8k (5-shot) |43.67|
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