leaderboard-pr-bot
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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: apache-2.0
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tags:
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- generated_from_trainer
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- chatgpt
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- HC3
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metrics:
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- accuracy
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model-index:
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- name: distilgpt2-HC3
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results: []
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widget:
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- text:
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-
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negative? <answer>
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example_title: Sentiment analysis
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- text:
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Barack Obama nominated Hilary Clinton as his secretary of state on Monday.
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He chose her because <answer>
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example_title: Coreference resolution
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- text:
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-
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blue book, and a black book. Here's the puzzle, <answer>
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example_title: Logic puzzles
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- text:
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The two men running to become New York City's next mayor will face off in
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their first debate Wednesday night <answer>
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example_title: Reading comprehension
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- text:
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-
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period, I get 25 hours of energy and spontaneously explode? <answer>
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example_title: 5 hour energy
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- text:
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-
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reinforcement-learning optimized model responses? <answer>
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example_title: deep learning advice
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inference:
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parameters:
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repetition_penalty: 1.5
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eta_cutoff: 0.0008
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renormalize_logits: true
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datasets:
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- pszemraj/HC3-textgen-qa
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language:
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- en
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library_name: transformers
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pipeline_tag: text-generation
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---
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@@ -117,4 +111,17 @@ The following hyperparameters were used during training:
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- Transformers 4.27.0.dev0
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- Pytorch 1.11.0+cu113
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- Datasets 2.6.1
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- Tokenizers 0.12.1
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---
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language:
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- en
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license: apache-2.0
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library_name: transformers
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tags:
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- generated_from_trainer
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- chatgpt
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- HC3
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datasets:
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- pszemraj/HC3-textgen-qa
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metrics:
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- accuracy
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widget:
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- text: 'Review: Best cast iron skillet you will ever buy. Is this review positive
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or negative? <answer>'
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example_title: Sentiment analysis
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- text: Barack Obama nominated Hilary Clinton as his secretary of state on Monday.
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He chose her because <answer>
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example_title: Coreference resolution
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- text: 'On a shelf, there are five books: a gray book, a red book, a purple book,
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a blue book, and a black book. Here''s the puzzle, <answer>'
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example_title: Logic puzzles
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- text: The two men running to become New York City's next mayor will face off in
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their first debate Wednesday night <answer>
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example_title: Reading comprehension
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- text: Is it true that if I have five 5-hour energy drinks in a single 24-hour period,
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I get 25 hours of energy and spontaneously explode? <answer>
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example_title: 5 hour energy
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- text: what happens if you train a smaller model on a dataset of reinforcement-learning
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optimized model responses? <answer>
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example_title: deep learning advice
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inference:
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parameters:
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repetition_penalty: 1.5
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eta_cutoff: 0.0008
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renormalize_logits: true
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pipeline_tag: text-generation
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model-index:
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- name: distilgpt2-HC3
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results: []
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---
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- Transformers 4.27.0.dev0
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- Pytorch 1.11.0+cu113
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- Datasets 2.6.1
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- Tokenizers 0.12.1
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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_pszemraj__distilgpt2-HC3)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |28.18|
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|AI2 Reasoning Challenge (25-Shot)|24.66|
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|HellaSwag (10-Shot) |27.99|
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|MMLU (5-Shot) |23.95|
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|TruthfulQA (0-shot) |42.10|
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|Winogrande (5-shot) |50.36|
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|GSM8k (5-shot) | 0.00|
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