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Adding Evaluation Results
Browse filesThis is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr
The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.
If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions
README.md
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---
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license: cc-by-nc-4.0
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---
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Description to load and test will be added soon. More details on training and data will be added aswell.
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outputs = model.generate(**inputs, max_new_tokens=64)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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-
```
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---
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license: cc-by-nc-4.0
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model-index:
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- name: Mistral-7b-instruct-v0.2-summ-dpo-e2
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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: 62.54
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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=silvercoder45/Mistral-7b-instruct-v0.2-summ-dpo-e2
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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: 85.3
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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=silvercoder45/Mistral-7b-instruct-v0.2-summ-dpo-e2
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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: 60.71
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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=silvercoder45/Mistral-7b-instruct-v0.2-summ-dpo-e2
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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: 70.54
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=silvercoder45/Mistral-7b-instruct-v0.2-summ-dpo-e2
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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: 77.66
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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=silvercoder45/Mistral-7b-instruct-v0.2-summ-dpo-e2
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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: 39.04
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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=silvercoder45/Mistral-7b-instruct-v0.2-summ-dpo-e2
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name: Open LLM Leaderboard
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---
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Description to load and test will be added soon. More details on training and data will be added aswell.
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outputs = model.generate(**inputs, max_new_tokens=64)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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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_silvercoder45__Mistral-7b-instruct-v0.2-summ-dpo-e2)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |65.97|
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|AI2 Reasoning Challenge (25-Shot)|62.54|
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|HellaSwag (10-Shot) |85.30|
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|MMLU (5-Shot) |60.71|
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|TruthfulQA (0-shot) |70.54|
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|Winogrande (5-shot) |77.66|
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|GSM8k (5-shot) |39.04|
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