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Adding Evaluation Results (#1)
Browse files- Adding Evaluation Results (4b672433b21196620948df6ea2acdb7f55b557f2)
Co-authored-by: Open LLM Leaderboard PR Bot <[email protected]>
README.md
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---
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license: apache-2.0
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language:
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- tr
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- en
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library_name: transformers
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---
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Fine tuned model of mistral-7b-instruct-v0-2. the dataset used for fine tuning is small and custom dataset for question answering in turkish language made by me. the main duty was to make model more adapted to turkish language.
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prompt format :
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class Snake:
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def __init__(self):
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```
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[i cutted output for brevity]
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---
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language:
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- tr
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- en
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license: apache-2.0
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library_name: transformers
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model-index:
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- name: alooowso
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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: 62.97
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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=notbdq/alooowso
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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: 84.87
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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=notbdq/alooowso
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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: 60.78
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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=notbdq/alooowso
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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: 68.18
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=notbdq/alooowso
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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: 77.43
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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=notbdq/alooowso
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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: 39.58
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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=notbdq/alooowso
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name: Open LLM Leaderboard
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---
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Fine tuned model of mistral-7b-instruct-v0-2. the dataset used for fine tuning is small and custom dataset for question answering in turkish language made by me. the main duty was to make model more adapted to turkish language.
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prompt format :
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class Snake:
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def __init__(self):
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```
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+
[i cutted output for brevity]
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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_notbdq__alooowso)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |65.63|
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|AI2 Reasoning Challenge (25-Shot)|62.97|
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|HellaSwag (10-Shot) |84.87|
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|MMLU (5-Shot) |60.78|
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|TruthfulQA (0-shot) |68.18|
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|Winogrande (5-shot) |77.43|
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|GSM8k (5-shot) |39.58|
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