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  # nathanReitinger/mlcb
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- This model is a fine-tuned version of [dbernsohn/roberta-javascript](https://huggingface.co/dbernsohn/roberta-javascript) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Train Loss: 0.0463
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  - Validation Loss: 0.0930
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  - Train Accuracy: 0.9708
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  - Epoch: 4
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- ## Model description
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-
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- More information needed
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-
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  ## Intended uses & limitations
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- More information needed
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  ## Training and evaluation data
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- More information needed
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-
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- ## Training procedure
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-
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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  - TensorFlow 2.11.0
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  - Datasets 2.13.2
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  - Tokenizers 0.13.3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # nathanReitinger/mlcb
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+ This model is a fine-tuned version of [dbernsohn/roberta-javascript](https://huggingface.co/dbernsohn/roberta-javascript) on the [mlcb dataset](https://huggingface.co/datasets/nathanReitinger/mlcb).
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  It achieves the following results on the evaluation set:
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  - Train Loss: 0.0463
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  - Validation Loss: 0.0930
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  - Train Accuracy: 0.9708
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  - Epoch: 4
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  ## Intended uses & limitations
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+ The model can be used to identify whether a JavaScript program is engaging in canvas fingerprinting.
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  ## Training and evaluation data
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
 
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  - TensorFlow 2.11.0
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  - Datasets 2.13.2
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  - Tokenizers 0.13.3
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+
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+ # Citation
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+
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+ @inproceedings{reitinger2021ml,
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+ title={ML-CB: Machine Learning Canvas Block.},
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+ author={Nathan Reitinger and Michelle L Mazurek},
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+ journal={Proc.\ PETS},
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+ volume={2021},
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+ number={3},
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+ pages={453--473},
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+ year={2021}
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+ }
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+
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+ - [OSF] (https://osf.io/shbe7/)
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+ - [GitHub] (https://github.com/SP2-MC2/ML-CB)
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+ - [Data] (https://dataverse.harvard.edu/dataverse/ml-cb)