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README.md
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<!-- Provide a longer summary of what this model is. -->
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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- [2024-mcm-everitt-ryan/benchmark](https://huggingface.co/datasets/2024-mcm-everitt-ryan/benchmark)
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#### Training Hyperparameters
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macro avg 0.82 0.67 0.70 640
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weighted avg 0.82 0.67 0.70 640
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samples avg 0.70 0.72 0.70 640
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** 1 X NVIDIA L40S
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- **Hours used:** 0.27
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- **Cloud Provider:** N/A
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- **Carbon Emitted:** N/A
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### Compute Infrastructure
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- Linux 6.5.0-35-generic x86_64
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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### Training Data
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- [2024-mcm-everitt-ryan/benchmark](https://huggingface.co/datasets/2024-mcm-everitt-ryan/benchmark)
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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#### Training Hyperparameters
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macro avg 0.82 0.67 0.70 640
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weighted avg 0.82 0.67 0.70 640
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samples avg 0.70 0.72 0.70 640
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- **Hardware Type:** 1 X NVIDIA L40S
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- **Hours used:** 0.27
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- **Cloud Provider:** N/A
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- **Carbon Emitted:** N/A
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### Compute Infrastructure
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- Linux 6.5.0-35-generic x86_64
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