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@@ -40,11 +40,17 @@ A custom synthetic dataset was created for this task, focusing on the structural
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  ### Training Hyperparameters
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  Model: distilbert/distilbert-base-uncased
 
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  Learning Rate: 3e-5
 
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  Epochs: 7
 
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  Train Batch Size: 16
 
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  Gradient Accumulation Steps: 2
 
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  Weight Decay: 0.015
 
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  Warm-up Ratio: 0.1
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  ### Evaluation
@@ -52,8 +58,11 @@ The model was evaluated using a custom dataset representing the same six documen
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  ### Metrics
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  Accuracy: 0.947
 
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  Precision: 0.948
 
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  Recall: 0.948
 
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  F1-Score: 0.948
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  ### Training Hyperparameters
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  Model: distilbert/distilbert-base-uncased
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  Learning Rate: 3e-5
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+
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  Epochs: 7
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+
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  Train Batch Size: 16
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+
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  Gradient Accumulation Steps: 2
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+
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  Weight Decay: 0.015
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  Warm-up Ratio: 0.1
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  ### Evaluation
 
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  ### Metrics
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  Accuracy: 0.947
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  Precision: 0.948
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+
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  Recall: 0.948
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  F1-Score: 0.948
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