Adding Evaluation Results

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  1. README.md +113 -1
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  license: apache-2.0
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  language:
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  - en
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  ![image](./image.webp)
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  # SwiftText: Accelerating Text Generation with Optimized Efficiency
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  print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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  ```
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  ## Acknowledgements
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- ### We gratefully acknowledge the contributions of the Unsloth team and the Hugging Face community for their invaluable tools and resources, which were instrumental in the development of SwiftText.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: apache-2.0
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  language:
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  - en
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+ model-index:
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+ - name: AetherSett
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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: wis-k/instruction-following-eval
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+ split: train
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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: 53.7
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+ name: averaged accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FAetherSett
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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: SaylorTwift/bbh
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+ split: test
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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: 34.74
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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#/?search=Daemontatox%2FAetherSett
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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: lighteval/MATH-Hard
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+ split: test
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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: 30.74
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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#/?search=Daemontatox%2FAetherSett
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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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+ split: train
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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: 7.72
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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#/?search=Daemontatox%2FAetherSett
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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: 16.21
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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#/?search=Daemontatox%2FAetherSett
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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: 36.43
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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#/?search=Daemontatox%2FAetherSett
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+ name: Open LLM Leaderboard
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  ---
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  ![image](./image.webp)
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  # SwiftText: Accelerating Text Generation with Optimized Efficiency
 
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  print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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  ```
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  ## Acknowledgements
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+ ### We gratefully acknowledge the contributions of the Unsloth team and the Hugging Face community for their invaluable tools and resources, which were instrumental in the development of SwiftText.# [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/Daemontatox__AetherSett-details)!
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+ Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=Daemontatox%2FAetherSett&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
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+
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+ | Metric |Value (%)|
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+ |-------------------|--------:|
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+ |**Average** | 29.92|
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+ |IFEval (0-Shot) | 53.70|
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+ |BBH (3-Shot) | 34.74|
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+ |MATH Lvl 5 (4-Shot)| 30.74|
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+ |GPQA (0-shot) | 7.72|
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+ |MuSR (0-shot) | 16.21|
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+ |MMLU-PRO (5-shot) | 36.43|
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+