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  # PropagandaDetection
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  The model is a Transformer network based on a DistilBERT pre-trained model.
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- The pre-trained model is fine-tuned on the SemEval 2023 Task 3 training dataset for the propaganda detection task. To fine-tune the Transformer Distilbert-Base-Uncased, the following hyperparameters are used: the batch size of $16$; learning rate of $2e^{-5}$; AdamW optimizer; $4$ epochs. Tests provide an accuracy of around $90\%$.
 
 
 
 
 
 
 
 
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  ## References
 
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  # PropagandaDetection
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  The model is a Transformer network based on a DistilBERT pre-trained model.
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+ The pre-trained model is fine-tuned on the SemEval 2023 Task 3 training dataset for the propaganda detection task.
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+
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+ ### Hyperparameters :
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+ Batch size = 16;
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+ Learning rate = 2e-5;
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+ AdamW optimizer;
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+ Epochs = 4.
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+
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+ Accuracy = 90 % on SemEval 2023 test set.
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  ## References