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  ---
 
 
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  license: other
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- license_name: tongyi-qianwen-research
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- license_link: https://huggingface.co/Qwen/Qwen1.5-0.5B/blob/main/LICENSE
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  datasets:
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  - OEvortex/vortex-mini
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  - yahma/alpaca-cleaned
 
 
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  pipeline_tag: text-generation
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- language:
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- - en
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Qwen1.5-0.5B-vortex-v2 model card
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  Qwen1.5-0.5B-vortex-v2 is a dealigned chat finetune of the original fantastic Qwen1.5-0.5B model by the Qwen team.
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- This model was trained on the Vortex mini dataset and alpaca-cleaned using axolotl for 4 epoch
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ language:
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+ - en
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  license: other
 
 
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  datasets:
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  - OEvortex/vortex-mini
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  - yahma/alpaca-cleaned
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+ license_name: tongyi-qianwen-research
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+ license_link: https://huggingface.co/Qwen/Qwen1.5-0.5B/blob/main/LICENSE
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  pipeline_tag: text-generation
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+ model-index:
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+ - name: Qwen1.5-0.5B-vortex-v2
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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: 30.63
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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=Abhaykoul/Qwen1.5-0.5B-vortex-v2
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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: 45.54
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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=Abhaykoul/Qwen1.5-0.5B-vortex-v2
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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: 36.29
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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=Abhaykoul/Qwen1.5-0.5B-vortex-v2
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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: 44.29
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Abhaykoul/Qwen1.5-0.5B-vortex-v2
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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: 56.04
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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=Abhaykoul/Qwen1.5-0.5B-vortex-v2
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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: 5.91
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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=Abhaykoul/Qwen1.5-0.5B-vortex-v2
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+ name: Open LLM Leaderboard
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  ---
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  # Qwen1.5-0.5B-vortex-v2 model card
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  Qwen1.5-0.5B-vortex-v2 is a dealigned chat finetune of the original fantastic Qwen1.5-0.5B model by the Qwen team.
117
 
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+ This model was trained on the Vortex mini dataset and alpaca-cleaned using axolotl for 4 epoch
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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_Abhaykoul__Qwen1.5-0.5B-vortex-v2)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |36.45|
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+ |AI2 Reasoning Challenge (25-Shot)|30.63|
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+ |HellaSwag (10-Shot) |45.54|
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+ |MMLU (5-Shot) |36.29|
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+ |TruthfulQA (0-shot) |44.29|
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+ |Winogrande (5-shot) |56.04|
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+ |GSM8k (5-shot) | 5.91|
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+